view additional pages

Perfect Numbers

Six is such a number: it is the sum of all numbers that divide it except itself. In 2,000 years 12 perfect numbers were found; now a computer has discovered five more

by Constance Reid

THE GREEKS, greatly intrigued by the fact that the number 6 is the sum of all its divisors except itself (1+2 + 3), called it a “perfect” number. They wondered how many other such numbers there were. It was easy enough to ascertain by trial that the second perfect number was 28 (1+2 + 4 + 7+14). The great Euclid was able to prove that in all cases where a number can be factored into the form 2^n-l(2^n—1) and 2^n—1 is a prime number, the number must be the sum of all its divisors except itself. Thus in the case of 6, n is 2 and 2^n—1=3, a prime number; in the case of 28, n is 3 and 2^n—1 = 7, again a prime number. With Euclid’s formula it was no difficult matter to compute that the third and fourth perfect numbers were 496 (n=5) and 8,128 (n = 7). But beyond that the computation became laborious, and in any event it was not proved that this rule included all the perfect numbers. Euclid left for future mathematicians a challenging question: How many perfect numbers are there?

In more than 2,000 years mathematicians were able to turn up only 12 numbers that met the strict requirements for numerical perfection. Within the past year, however, the University of California mathematician R. M. Robinson has, with the aid of a modern computer, discovered five more. The discovery did not attract the attention of the press. Perfect numbers are not useful in the construction of atomic bombs. In fact, they are not useful at all. They are merely interesting, and their story is an interesting one.

For many centuries philosophers were more concerned with the ethical or religious significance of perfect numbers than with their mathematics. The Romans attached the number 6 to Venus, because it is the product of the two sexes—the odd (masculine) number 3 and the even (feminine) number 2. The ancient Hebrews explained that God chose to create the world in six days rather than in one because 6 is the more perfect number. The eighth-century English theologian Alcuin pointed out that the second origin of the human race, from the eight human beings on Noah’s Ark, was less perfect than the first, 8 being an imperfect number. In the 12th century Rabbi Josef Ankin recommended the study of perfect numbers in a program for the “healing of souls.”

THE mathematicians, meanwhile, had been making slow progress. The first four perfect numbers—6, 28, 496 and 8,128—had been known as early as the first century. Not until 14 centuries later was the fifth discovered. It was 33,550,336 (n=13). Then in 1644 the French mathematician Marin Mersenne, a colleague of Descartes, announced six more at one clip, and thereby linked his name forever with perfect numbers. The numbers were now so large that they were necessarily described only by the prime number 2^n—1, or, more briefly, by the exponent, n, in Euclid’s formula. The values of n for the 11 perfect numbers, including Mersenne’s six new ones, were 2, 3, 5, 7, 13, 17. 19, 31, 67, 127 and 257. In other words, the largest prime in the series was the enormous number 2^257— 1.

It was obvious to other mathematicians that Mersenne could not have tested for primality all the numbers he had announced. But neither could they. At that time the only method of testing was to try every possible divisor of each number. By this laborious method mathematicians did test Mersenne’s first eight numbers and found them prime.

It was the great Swiss mathematician Leonhard Euler who tested the eighth number (2^31 —1). Euler also proved that all even perfect numbers must be of the form expressed by Euclid’s theorem. No odd perfect number has ever been found, but it has never been proved that such a number cannot exist.

For more than 100 years the perfect number formed from the prime 2^31 — 1 remained the largest proved. Then in 1876 the French mathematician Eduard Lucas worked out a method by which a possible prime could be tested without trying all potential divisors. At the same time he announced that he had tested 2^127—1 by his method and found it prime.

According to Lucas, the number 2^n—1 is prime if, and only if, it divides the (n— 1) term of a certain series. In this series the first number is 4 and each succeeding number is the square of the preceding one minus 2; in other words 4, 14, 194, 37,634, and so on. For example, to test the prime number 7 (2^3—1), one divides 7 into 14; the n—1 term in this case being the second number in the series, since n is 3. Since 7 divides evenly into 14, it is prime by Lucas’ test.

Obviously even Lucas’ short-cut method becomes rather unwieldy when, as in the case of 2^127—1, one must divide 170,141,183,460,469,231,731,687,303,-715,884,105,727 into the 126th term of Lucas’ series. For such numbers, mathematicians use a short-cut of the shortcut: instead of squaring each term of the series, they square only the remainder after they have divided the number being tested into it.

Even with the help of Lucas’ method mathematicians were not able to finish testing all of the possible Mersenne numbers until a few years ago. Their tally showed that Mersenne’s list of perfect numbers was incorrect. He was right on nine numbers (those for which n is 2, 3, 5, 7, 13, 17, 19, 31 and 127), but he was wrong on two he had listed (those with the exponents 67 and 257), and he had missed three numbers in the series (with exponents 61, 89 and 107). Thus the list stood at 12, with 2^126(2^127 —1) the largest known perfect number.

THEN on January 30 last year Robinson fed the problem to the National Bureau of Standards’ Western Automatic Computer, known briefly as SWAC. This is a high-speed machine: it can do an addition of 36 binary digits in 64 millionths of a second. Robinson’s job was to break down the Lucas method into a program of the 13 kinds of commands to which the SWAC responds. The job was complicated by the fact that, while the machine is built to handle numbers up to only 36 binary digits, the numbers he was working with ran to 2,300 such digits. It was, he found, very much like explaining to a human being how to multiply 100-digit numbers on a desk calculator built to handle 10. To tell SWAC how to test a possible prime by the Lucas method, 184 separate commands were necessary. The same program of commands, however, could be used for testing any number of the Mersenne type from 2^3—1 to 2^2297—1.

The program of commands, coded and punched on paper tape, was placed in the machine’s “memory.” All that was then necessary to test the primality of any Mersenne number was to insert the exponent of the new number as it was to be tested. The machine could do the rest, even to typing out the result of the test—continuous zeros if the number was a prime.

The first number to be tested was 2^257—1, the largest of the 11 numbers announced by Mersenne. Twenty years before it had been found not prime by D. H. Lehmer, who worked two hours a day for a year with a desk calculator to do the test. It happened that this evening Lehmer himself, now the director of research at the Bureau of Standards’ Institute for Numerical Analysis on the U.C.L.A. campus, was in the room. He saw the machine do in 48 seconds what had taken him an arduous 700 and some hours. But the machine got exactly the same result.

SWAC then continued on a list of larger possible primes. Mersenne had said that all eternity would not suffice to test whether a given number of 15 or 20 digits was prime. But within a few hours SWAC tested 42 numbers, the smallest of which had more than 80 digits. One by one it determined that they were not prime. Finally at 10 p.m. a string of zeros came up: the machine had found a new perfect number. Its prime was 2^521—1. Just before midnight, 13 more numbers later, another prime came up: 2^607—1. In the decimal system this is a number of 183 digits.

The machine continued testing numbers when opportunity afforded during the next few months. Last June the number 2^1270— 1 was found to be prime. In October, concluding the program, it established as prime the numbers 2^2203 —1 and 2^2281l—1. The latter is the largest prime number, of any form, now known.

The perfect numbers of which these primes are components are, of course, much larger—so large that in comparison with them conventionally “astronomical” numbers seem microscopic. Yet, by a proof as old as Euclid, mathematicians know that these numbers are the sum of all their divisors except themselves—just as surely as they know that 6=1 + 2 + 3.

They still do not know, however, how many perfect numbers there are.

view additional pages

COMPUTERS: THEIR BUILT-IN LIMITATIONS

ARTICLE BY MAX GUNTHER “OH, MY GOD” croaked a network-TV director in New York. He seemed to be strangling in his turtle-neck shirt. It was the evening of Election Day, 1966, and the director’s world was caving in. Here he was, on the air with the desperately important Election Night coverage, competing with the two enemy networks to see whose magnificently transistorized, fearfully fast electronic computer could predict the poll results soonest and best. Live coverage: tense-voiced, sweating announcers, papers flapping around, aura of unbearable suspense. The whole country watching. And what happens? The damned computer quits.

Oh, my God. The computer rooms disintegrated in panic. Engineers leaped with trembling screwdrivers at the machine’s intestines. The director stared fish-eyed at a mathematician. A key-punch girl yattered terrified questions at a programmer. Young Madison Avenue types rushed in and out, uttering shrill cries. And the computer just sat there.

The story of this ghastly evening has circulated quietly in the computer business ever since. You hear it in out-of-the-way bars and dim corners of cocktail parties, told in hoarse, quavering tones. It has never reached the public at large, for two reasons. One reason is obvious: Those concerned have sat on it. The second reason is less obvious and much more interesting.

When the initial panic subsided, the director freed some of his jammed synapses and lurched into action. He rounded up mathematicians, programmers, political experts, research girls and others. And he rounded up some hand-operated adding machines. “All right,” he said, “we’ll simplify the calculations and do die whole thing by hand. This may be my last night on TV; but, by God, I’ll go on the air with something!”

And so they perspired through the long, jangling night. The network’s election predictions appeared on the screen just like its competitors’. The director and his aides gulped coffee, clutched burning stomachs and smoked appalling numbers of cigarettes. They kept waiting for an ax to fall. Somebody was bound to notice something wrong sooner or later, they thought. The hand-cranked predictions couldn’t conceivably be as good as the computerized punditry of the competition. Maybe the hand-cranked answers would be totally wrong! Maybe the network would become the laughingstock of the nation! Maybe. . . . Oh, my God!

Well. As history now tells us, the entire poll-predicting razzmatazz was the laughingstock of the nation that November. None of the three networks was wronger than the other two. When the half-gutted director and his fellow conspirators skulked out of bed the next morning and focused smoldering eyes on their newspapers, they at last recognized the obscure little facts that had saved their professional lives: An electronic computer, no matter how big or how expensive or how gorgeously bejeweled with flashing lights or how thoroughly crammed with unpronounceable components, is no smarter than the men who use it. Its answers can never be better than the data and formulas that are programed into it. It has no magical insights of its own. Given inadequate data and inexact formulas, it will produce the same wrong answers as a man with an aching head and an adding machine. It will produce them in a more scientific-looking manner, that’s all.

Over the past ten years, it has been fashionable to call these great buzzing, clattering machines “brains.” Science-fiction writers and Japanese moviemakers have had a lovely time with the idea. Superintelligent machines take over the world! Squish people with deadly squish rays! Hypnotize nubile girls with horrible mind rays, baby! It’s all nonsense, of course. A computer is a machine like any other machine. It produces numbers on order. That’s all it can do.

Yet computers have been crowned with a halo of exaggerated glamor, and the TV election-predicting circus is a classic example. The Columbia Broadcasting System got into this peculiar business back in 1952, using a Remington Rand Univac. The Univac did well. In 1956, for instance, with 1/27 of the popular vote in at 9:15 p.m., it predicted that Dwight Eisenhower would win with 56 percent of the votes. His actual share turned out to be 57.4 percent, and everybody said, “My, my, what a clever machine!” The Univac certainly was a nicely wrought piece of engineering, one of the two or three fastest and most reliable then existing. But the credit for insight belonged to the political experts and mathematicians who told the Univac what to do. It was they, not the machine, who estimated that if Swamp-water County went Democratic by X percent, the odds were Y over Z that the rest of the state would go Democratic by X-plus-N percent. The Univac only did the routine arithmetic.

Which escaped attention. By the 1960s, the U. S. public had the idea that some kind of arcane, unknowable, hyper-human magic was soldered into computers—that a computerized answer was categorically better than a hand-cranked answer. As the TV networks and hundreds of other businesses realized, computers could be used to impress people. A poll prediction looked much more accurate on computer print-out paper than in human handwriting. But, as became clear at least to a few in 1966, it’s the input that counts. Honeywell programing expert Malcolm Smith says: “You feed guesswork into a computer, you get beautiful neat guesswork back out. The machine contains no Automatic Guess Rectifier or Factualizing Whatchamacallit.”

The fact is, computers are monumentally dense—”so literal,” says Smith, “so inflexible, so flat-footed dumb that it sometimes makes you want to burst into tears.” Smith knows, for he spends his life trying to make the great dimwits cogitate. To most people, however, computers are metallic magic, wonderful, tireless, emotionless, infallible brains that will finally solve mankind’s every problem. Electronic data processing (EDP) is the great fad of the 1960s and perhaps the costliest fad in history. Companies big and small, universities, Government agencies are tumbling over one another in a gigantic scramble for the benefits of EDP. They believe EDP represents, at last, instant solutions to problems they’ve wrestled with for decades: problems of information flow, bookkeeping, inventory control. And they’re hounded by dreams of status. To have a computer is “in.” Even if you’re a scruffy little company that nobody ever heard of, you must have a computer. Businessmen meeting at conventions like to drop phrases such as “My EDP manager told me” and “Our programing boys think,” and watch the crestfallen looks of uncomputerized listeners.

It’s a great business to be in. Computer makers shipped some 8000 machines in 1965 and 13,700 (3.75 billion dollars’ worth) in 1966. There are over 30,000 computers at work in the country today and there will be (depending on whose guess you listen to) as many as 100,000 by 1975. It’s a boom business in which young salesmen can buy Cadillacs and Porsches, while their college classmates in other professions are still eating canned beans in one-and-a-half-room flats. The salesmen don’t need any unusual qualifications to strike it rich: just a two- or three-year apprenticeship, a sincere hard handshake, a radiating awareness of belonging to an elite group and a good memory for a polysyllabic vocabulary. (You don’t sell machines; you sell “systems” or “systems concepts,” or “integrated functional solid-state logic systems concepts.” They seem to cost more that way.) The salesmen are all business. They sell machines on a severely pragmatic level, maybe exaggerating their products’ worth sometimes but, in general, avoiding any unbusinesslike talk about “superbrains.” Computer manufacturers as a whole, in fact, avoid such talk. To their credit, they have struggled from the beginning to keep things in perspective, have publicly winced when imaginative journalists compared computers with that odd gray mushy stuff inside the human skull. “Don’t call them brains! Please, please don’t call them brains!” shouted IBM scientist Dr. Arthur Samuel at a reporter once. “But listen,” said the reporter, “don’t they——”

“No, they don’t!” howled Samuel. “Whatever you’re going to say they do, they don’t!” (Samuel, now at Stanford University, had won unwanted fame for programing an IBM machine to play checkers.) “Computers are just extremely fast idiots,” says logician-mathematician Richard Bloch, a former Honeywell vice-president now working with Philadelphia’s Auerbach Corporation. Bloch, a lean, dark, ferociously energetic man who smokes cigars incessantly, first tangled with the machines in the early 1940s, when he helped run Harvard University’s historic Mark 1. “On second thought, ‘idiots’ is the wrong word. It suggests some innate thinking capacity gone wrong. Computers have no thinking capacity at all. They’re just big shiny machines. When will people learn that machines don’t think?”

Maybe never, though men like Bloch never tire of saying so. “A computer can multiply umpteen umpteen-digit numbers a second,” says Bloch, “but this is only blind manipulation of numbers, not thinking. To think about a problem, you’ve got to understand it. A computer never understands a problem.”

Arthur Samuel, for instance, tells about an early checkers-playing experiment. A British computer was given a simple set of rules in arithmetical form. Among other things, it was told that a king is worth three points, an uncrowned piece one point. It played an ordinary undistinguished game until its human opponent maneuvered a piece within one move of being crowned. Then the machine seemed to go mad.

Somewhere in its buzzing electrical innards, a chain of “reasoning” something like this took place: “Oh, my goodness! If my opponent gets his piece into the king’s row, he’ll gain a three-point king where he had only a one-point man before. In effect, this means I’ll lose two points. What’ll I do? (buzz, buzz . . .) Ah! I’ll sacrifice one of my uncrowned pieces. The rules say he must take my piece if I offer it, and this will force him to use his move and prevent him from getting his man crowned. I’ll have lost only one point instead of two!”

So the cunning computer sacrificed a man. The human player took it. The situation was now exactly the same as it had been before, so the computer slyly sacrificed another man. And so on. Piece by piece, the unthinking machine wiped itself out.

The computer had proved itself able to manipulate some of the arithmetical and logical formulas of checkers. But it had failed in one supremely important way. It simply didn’t understand the game. It didn’t grasp what no human novice ever needs to be told: that the basic object of a game is to win.

The trouble with computers is that they seem to be thinking. While cars, lawn mowers and other machines perform easily understood physical tasks, computers seem to be working with abstract thoughts. They aren’t, of course: they are only switching electric currents along preordained paths. But they produce answers to questions, and this gives them a weird brainlike quality.

People expect too much of them, as a result, and this seriously worries some scientists. The late Norbert Wiener, coiner of the term “cybernetics.” was particularly worried about the increasing use of computers in military decision making. Referring to machines that can manipulate the logical patterns of a game without understanding it. lie once wrote that computers could win some future nuclear war “on points … at the cost of every interest we have at heart.” He conjured up a nightmarish vision of a giant computer printing out “war won: assignment completed . . .” and then shutting itself down, never to be used again, because there were no men left on earth to use it.

Secretary of Defense Robert S. McNamara lias hinted at similar worries in the years-long argument about our famous (but so far nonexistent) Nike-X missile-defense system. Neither full-Hedged hawk nor dove, McNamara favors a leisurely and limited building of Nike bases. He wants the U. S. to have some defense against a possible Russian or Chinese ballistic-missile attack, but he fears that an all-out missile-building program will involve us in a ghastly game of nuclear leapfrog with the Soviets—the two sides alternately jumping ahead of each other in countermeasures and countercountermeasures until the radioactive end. One trouble with missile and antimissile systems, as McNamara once expressed it to a group of reporters, is that “the bigger and more complex such systems get, the more remote grows man’s control of them.” In a nuclear-missile war, so many things would happen so fast, so much data would have to be interpreted in so limited a time that human brains could not possibly handle the job. The only answer for both the U. S. and Russia in a missile arms race would be increasing reliance on automatic control—in other words, on computers.

The last war might, in fact, be a war between computers. It would be a coldly efficient war, no doubt. A logical war: Score 70,000,000 deaths for my side, 60 megadeaths for your side; I’m ahead: your move. pal. How could we convey to the machines our totally illogical feelings about life and death? A country is made of people and money, and the people may properly be asked to give their lives for their country, yet a single human life is worth more than all the money in the world. Only the human brain is flexible enough to assimilate contradictions such as this without blowing a fuse.

A large modern computer can literally perform more arithmetic in an hour than can a football stadium full of human mathematicians in a lifetime, and it makes sense to enlist this lightning-fast electronic help in national defense. “But,” said Norbert Wiener shortly before he died in 1964, “let us always keep human minds in the decision loop somewhere, if only at the last ‘yes’ or ‘no.’ ”

The U.S. Ballistic Missile Early Warning System (BMEWS) is an example of the kind of setup that worried Wiener. Its radar eyes scan sky and space. Objects spotted up there are analyzed automatically to determine whether they are or aren’t enemy missiles. The calculations performed by computers— distance of the objects, direction, checkoff against known craft—take place in fractions of a second, far faster than human thought. It all works beautifully most of the time, and this has led some enthusiasts to suggest going one step further in automation. “If BMEWS can spot enemy missiles by itself,” they say, “why not hook up one more wire and have BMEWS launch our missiles?” But U. S. military chiefs have so far agreed with Norbert Wiener. There is a subtlety in the human brain that no computer seems likely ever to duplicate.

A few years ago, an officer was monitoring a BMEWS computer station in the Arctic. It was night. The rest of the staff was in bed. Suddenly, the computer exploded into action. Lights flashed, a printer chattered, tape reels whirled. The officer gaped, horrified. The machine was signaling a massive missile attack.

There are self-checking devices and “redundant” networks in the BMEWS, as in any other large computer system, and the officer had no logical reason to suspect a mechanical breakdown. There could be little doubt that the computer was actually reporting what its far-flung radar eyes saw. The officer’s orders were clear: In an event like this, he must send a message that would mobilize military installations all over the United States. Global war was only minutes away.

The officer hesitated. Questioned later, he couldn’t explain why. He could only say, “It didn’t feel right.” And he gambled time to wake other staff members. One of them dashed outdoors to look at the cold, clear, starlit Arctic sky, ran back indoors, examined the computer’s print-out, conferred with the others. Standing there in that antiseptic room full of shiny electronic equipment, the small knot of men made what may have been the most important decision in all the history of the world to date. They decided to wait.

They waited 30 awful seconds. The missile attack came no closer.

The officer’s feeling had been correct. This was no missile attack. Unaccountably, through a freakish tangle of circumstances that should never have happened and could not have been predicted and was not fully unraveled until weeks later, the computer and its eyes had locked onto something quite without menace: earth’s friendly companion and goddess of love, the moon, peacefully coming up over the horizon. If computers alone had handled the affair, the earth might now be a smoldering radioactive cinder. Because of a man and his slow, strange human brain and its unfathomable intuition, we are all still here.

When a computer makes a mistake, it’s likely to be a big one. In a situation where a man would stop and say. “Hey, something’s wrong!” the machine blindly rushes ahead because it lacks the man’s general awareness of what is and isn’t reasonable in that particular situation; such as the time when a New York bank computer, supposed to issue a man a dividend check for $162.40, blandly mailed him one for $1,624,000; or the time when a computer working for a publishing company shipped a Massachusetts reader six huge cartons neatly packed with several hundred copies of the same book: or the time when an IBM machine was constructing a mathematical “model” of a new Air Force bomber that would fly automatically a few dozen feet off the ground. Halfway through the figuring, it became apparent that the computer was solemnly guiding its imaginary aircraft along a course some five feet below the ground. (”Goddamn it,” roared General Curtis LeMay at one of the scientists, “I asked for an airplane, not a plow!”) Or the time when—– Well, everybody makes mistakes. In general, society is most worried about mistakes made by war computers in the BMEWS style, for the potential result of a mistake in this field is the end of the world. Fearful imaginings such as hail-Safe have expressed this fear, and most U. S. military planners share the fear and are cautious in their approach to computers. But no such colossal danger haunts computer users in science and business; and in these two fields, the great dumb machines have been pushed willy-nilly into all kinds of applications —some more sensible than others. A New York management-consultant firm, McKinsey and Company, exhaustively studied computer installations in 27 big manufacturing companies four years ago and found that only nine were getting enough benefits to make the machines pay.

“Sometimes computers are used for prestige purposes, sometimes as a means of avoiding human responsibility,” says computer consultant John Diebold. Diebold, at 41, is a millionaire and an internationally sought-after expert on “automation” (a term he coined in the early 1950s). “Scientists and executives have discovered that it’s impressive to walk into a meeting with a ream of computer print-out under your arm. The print-out may be utter nonsense, but it looks good, looks exact, gives you that secure, infallible feeling. Later, if the decision you were supposed to make or the theory you were propounding turns out to be wrong, you simply blame the computer or the man who programed it for you.”

Professor David Johnson of the University of Washington is another well-known computer consultant who worries about what he calls “the mindless machines.” He is amused by the fact that his engineering students seek status by using IBM cards as bookmarks—just as, 20 years from now. they will seek it by buying IBM machines for their companies. He praises computers for their ability to manipulate and organize huge masses of data at huge speeds. But, “What the computer does,” he says, “is to allow us to believe in the myth of objectivity.” The computer “acts without excessive hesitation, as if it is sure, as if it knows. …” A man who isn’t sure can often make people think he is, simply by coming up with a bundle of factual-looking print-out. He hides his own bad brainwork, says Professor Johnson, by “sprinkling it with eau de computer.”

Worse, Professor Johnson says, the growing availability of computers tends to make some researchers in scientific institutions avoid problems that don’t lend themselves to machine handling: Problems involving human values, problems of morality and aesthetics, subtle problems that can’t be translated into arithmetic and punched itito those neat little snip-cornered cards—all these get left out of the calculations. The tendency is to wrench reality around and hammer it into a nice square shape so the inflexible machines can swallow it. Professor Johnson glumly cites the case of a computer-headed robot recently developed by a major agricultural-research center to pick tomatoes. It clanks along briskly, picking the juicy red fruits faster than a whole gang of human workers. The only trouble is, its blind, clumsy fingers break the tomatoes’ skins. The agricultural scientists are now trying to solve the problem. By making the robot more gentle? No, by developing thicker-skinned tomatoes.

“It simply isn’t accurate to call these machines ‘clever,’ ” says Robert Cheek, a chief of the Westinghouse Tele-Computer Center near Pittsburgh. This is one of the biggest computer installations in the world, designed to handle Westinghouse’s huge load of corporate clerical and accounting work, and it generates science-fictionish visions of an office of the (if the cliche may be pardoned) future. It’s an entire modernistic building housing almost nothing but computing equipment. Clerks and secretaries who once populated it have been crowded out, and now it smells like the inside of a new car. Bob Cheek, a slight, mild man, looks small and lonely as he paces among the square whining monsters; and it is tempting to imagine that the machines have subjugated him as their slave. Actually, he is little more awed by this great aggregation of computing power than by an electric toaster. “Artificial intelligence?” he will say in response to the question he has heard too often. And lie will look at his machines, think of the man-hours required to make them work, take off his glasses, rub his weary eyes and chuckle sourly.

Logician Richard Bloch is an example of high human intelligence. He learned chess at the age of three and is now, among other things, a Life Master bridge player and a blackjack shark. He once tried to teach a Honeywell computer to play bridge. “The experiment gave me new respect for the human brain,” lie recalls wryly. “The brain can act on insufficient, disorganized data. A bridge novice can start to play—badly but not stupidly—after an hour or so of mediocre instruction, in a half drunken foursome. His brain makes generalization! on its own. reaches conclusions nobody ever told it to reach. It can absorb badly thought-out, unspecific instructions such as, ‘If your hand looks pretty good, bid such and such.’ What does ‘pretty good’ mean? The brain can feel it out. Now, you take a computer——-”

Bloch pauses to chew moodily on his cigar. “A computer won’t move unless you tell it every single step it must take, in excruciating detail. It took me more than a hundred pages of densely packed programing before I could even get the damned machine to make the first bid. Then I gave up.”

The fact is, human thinking is so marvelous and mysterious a process that there is really not much serious hope of imitating it electronically—at least, not in this century. Nobody even knows how the brain works. Back in the late 1950s. during the first great soaring gush of enthusiasm over computers, journalists and some scientists were saying confidently that the brain works much like a very small, very complex digital computer— by means of X trillion tiny on-or-off switches. It remained only for IBM, Honeywell and Rem Rand to devise a monstrous mile-high machine with that many switches (and somehow figure out a way to supply its enormous power needs and somehow cool it so it wouldn’t melt itself), and we’d have a full-fledged brain. But this was only another case of wrenching reality around to fit machinery. There is no reliable evidence that the brain works like an EDP machine. In fact, evidence is now growing that the basic components of human thought may be fantastically complicated molecules of RNA (ribonucleic acid), which seem to store and process information by means of a little-understood four-letter “code.”

The human brain is uncanny. It programs itself. It asks itself questions and then tells itself how to answer them. It steps outside itself and looks back inside. It wonders what “thinking” is.

No computer ever wondered about anything. “It’s the speed of computers that gives the false impression that they’re thinking,” says Reed Roberts, an automation expert who works for a New York management-consultant firm, Robert Sibson Associates. “Once a man has told a machine how to process a set of data, the machine will do the job faster than the man’s brain could; so fast, in fact, that you’re tempted to suspect the machine has worked out short cuts on its own. It hasn’t. It has done the job in precisely the way it was told, showing no originality whatever.”

For instance, you can program a machine to add the digits of each number from 1 to 10,000 and name every number whose digits add up to 9 or a multiple of 9. The machine will print out a list instantly—9, 18, 27—acting as though it has gone beyond its instructions and cleverly figured out a short cut. This is the way a man would tackle the problem. Instead of routinely adding the digits of every number from 1 to 10,000, he’d look for a formula. His brain would generalize: “Every time you multiply a number by 9, the result is a number whose digits add up to 9 or a multiple of 9. Therefore, I can do my assignment quickly just by listing the multiples of 9 and ignoring all other numbers.” Is this what the computer did? No. With blinding speed but monumental stupidity, it laboriously tried every number, from 1 to 10,000, one by one.

In this example lies one of the main differences between thought and EDP. The human brain collects specific bits of data and makes generalizations out of them, organizes them into patterns. EDP works the other way around. A human programmer starts the machine out by giving it generalizations—problem-solving methods or “algorithms”—and the machine blindly applies these to specific data.

It is by no means easy to program a computer, and one of the great problems of the 1960s is a severe shortage of people who know how to do it. There are now some 150,000 professional programmers in the country, and computer owners are pitifully crying for at least 75,000 more. One estimate is that 500,000, all told, will be needed by the early 1970s.

The shortage is understandable. Computer programing is self-inflicted torture. The problem is to make a mindless machine behave rationally. Before you can tell the machine how to solve a problem, you must first figure out how your own brain solves it—every step, every detail. You watch your brain as it effortlessly snakes its way along some line of reasoning that loops back through itself, and then you try to draw a diagram showing how your brain did it, and you discover that your brain couldn’t possibly have done it—yet you know it did. And there sits the computer. If you can’t explain to yourself, how are you ever going to explain to it} Aptitude tests for would-be programmers contain questions that begin, “If John is three years older than Mary would have been if she were three and a half times as old as John was when. . . .” This is the kind of human thought that must precede the switching on of a computer. The machine can’t add two plus two unless there are clever, patient human brains to guide it. And even then it can’t: All it can do is add one and one and one and one and come up with the answer—instantaneously, of course. No computer can multiply; all it can do is add, by ones, too fast for human conception. Nor can any computer divide; it can only subtract, again by ones. Feed it problems in square roots, cube roots, prime numbers, complex mathematical computations with mile-long formulas—it can solve them all with incredible rapidity. How? Essentially, by adding or subtracting one, as required, as often as required, to come up at once with an accurate answer it might take a team of mathematicians a thousand years to obtain—and another thousand to check for accuracy. It never invents its own mathematical short cuts. If it uses short cuts, they must be invented and programed into it by human thinkers.

A computer’s only mental process is the ability to distinguish between is and isn’t—the presence or absence of an electric current, the this way or that way of a magnetic field. In terms of human thought, this kind of distinction can be conceived as one and zero, yes and no. The machine can be made to perform binary arithmetic, which has a radix (base) of 2 instead of our familiar 10 and which is expressed with only two digits, 1 and 0. By stringing together yeses and noes in appropriate patterns, the machine can also be made to manipulate logical concepts such as “and,” “or,” “except when,” “only when,” and so on.

But it won’t manipulate anything unless a man tells it how. Honeywell, whose aggressive EDP division has recently risen to become the nation’s second-biggest computer maker, conducts a monthly programing seminar in a Boston suburb for top executives of its customer companies to help them understand what their EDP boys are gibbering about. The executives learn how to draw a “flow chart,” agonizingly breaking down a problem-solving method into its smallest steps. They translate this flow chart into a set of instructions in a special, rigid, stilted English, (open input omast INVCRD. OPEN OUTPUT NMAST INVLST.) They watch a girl type out this semi-English version on a key-punch machine, which codes words and numbers in the form of holes punched into cards. These cards are fed into the computer, and another translation takes place. A canned “compiler” program (usually fed into the machine from a magnetic-tape unit) acts as an interpreter, translates the semi-English into logical statements in binary arithmetic. The computer finally does what the novice programmers have told it to do—if they’ve told it in the right way. The machine understands absolutely no deviations from its rigid language. Leave out so much as a comma, and it will either stop dead or go haywire. (At Cape Kennedy recently, a computer-guided rocket headed for Brazil instead of outer space because a programmer had left out a hyphen.) Finally, the executives head back to Boston’s Logan International Airport, soothe their tired brains with ethyl alcohol with an olive or a twist, and morosely agree that nobody is so intractably, so maddeningly dense as a computer.

But they are glad to have learned. They’ve made a start toward finding out what goes on inside those strange square machines in the plant basement; and with that knowledge, they’ll have a defense against a Machiavellian new kind of holdup that their Honeywell instructors have warned them about. It has happened more and more often and recently happened in one of the country’s biggest publishing houses. Almost all the company’s clerical work was computerized: inventory, billing, bookkeeping, payroll. With the corporate neurons thus inextricably tangled into the computer, the chief programmer went to the president and smilingly demanded that his salary be doubled. The president fired him on the spot—and shortly afterward realized the full enormity of what he had done. Nobody in the company, nobody in the whole world except the chief programmer knew what went on in the computer or how to make it do its work. The programs were too complex—and the computer, having no intelligence, could offer no explanations. As the horrified president now discovered, it was not true (as he had boasted) that a marvelous machine was running his company’s paperwork. The cleverness hadn’t been in the machine but in the brain of a man. With the man gone, the machine was just a pile of cold metal. The company nearly foundered in the ensuing year while struggling to unravel the mess.

Computers are that way: They absorb credit for human cleverness. Often a computerized operation will seem to go much more smoothly than it did in the old eyeshade-and-ledger days and the feeling will grow that the machine itself smoothed things out. What has really happened, however, is that the availability of the computer has forced human programmers to think logically about the operation and make it straightforward enough for the machine to handle. Professor David Johnson recalls a time when a company called him in to program an accounting operation for a computer. In previous years, this operation had taken two men ten months to perform by hand and brain. Johnson drew his flow charts, saw ways of simplifying, finally came up with an operation so organized that one man could do it in two days with a desk calculator. The company promptly abandoned its dreams of EDP—but if it had used a computer as planned, the machine rather than the programmer would doubtless have been showered with praise for the new simplicity.

Computers have been given credit for many things they haven’t done. Even more, they’ve been given credit for things they were going to do in the future. The loudest crescendo of computer prognostications occurred in the late 1950s. Future-gazers went wild with enthusiasm. Soon, they said, computers would translate languages, write superb music, run libraries of information, become chess champions. Ah, those fantastic machines! Unfortunately, the whole history of computers—going all the way back to the pioneering Charles Babbage in the 19th Century—has been a series of manic-depressive cycles: early wild enthusiasm, followed by unexpected difficulties, followed by puzzled disappointment and silence.

Music? An amiable professor at the University of Illinois, Lejaren Hiller, Jr., has programed a machine to write music. One of the machine’s compositions is the Illiac Suite. Says Hiller: “Critics have found it—er—interesting.”

Chess? A computer in Russia is now engaged in a long-distance match with one at Stanford University in California. The match began awkwardly, with both machines making what for humans would be odd mistakes. Everybody concerned now seems somewhat embarrassed. Stanford’s Professor of Computer Science John McCarthy, when asked recently how the game was going, said: “I have decided to put off any further interviews until the match is over.”

Translate languages? There’s something about human speech that computers just don’t seem to get. It isn’t rigid or formal enough; it’s too subtle, too idiomatic. An IBM computer once translated “out of sight, out of mind” from English to Russian and back to English. The phrase returned to English as “blind, insane.”

Libraries of information? “We don’t know a good enough way to make a computer look up facts,” says Honeywell programing researcher Roger Bender. He leans forward abruptly and jabs a finger at you. “Who wrote Ivanhoe?” he asks. You say, “Walter Scott.” Bender says, “How did you know? Did you laboriously sort through books in your memory until you came to Ivanhoe} No. And how did you even know it was a book? You made the connections instantly, and we don’t know how.”

Superbrains? Dr. Hubert L. Dreyfus, professor of philosophy at the Massachusetts Institute of Technology, recently published a paper called “Alchemy and Artificial Intelligence.” In it, he expresses amusement at the prognosticators’ claim that today’s computers are “first steps” toward an ultimate smarter-than-human brain. The claim, he says, makes him think of a man climbing a tree, shouting, “Hey, look at me, I’m taking the first steps toward reaching the moon!” In fact, says Professor Dreyfus, computers don’t and can’t approximate human intelligence. They aren’t even in the same league.

Honeywell’s Roger Bender agree. “We once had a situation where we wanted a machine to take a long list of numbers and find the highest number,” he recalls. “Now, wouldn’t that seem to you like an easy problem? Kids in first grade do it. Nobody has to tell them how. You just hand them a list and they look at the numbers and pick the highest. Of all the simple-minded—— Well, it just shows what you have to go through with computers.”

In this case, a programmer tried to figure out how he himself would tackle such a problem. He told the machine; “Start with the first number and go down the list until you come to a number that’s higher. Store that number in memory. Continue until you find a still higher number,” and so on. The last number stored would obviously (obviously to a man, that is) be the highest number on the list.

The machine imbibed its instructions, hummed for a while and stopped. It produced no answer.

“It was baffling,” says Bender. “Nobody knew what the trouble was, until someone happened to glance down the list by eye. Then the problem became apparent. By great bad luck, it turned out, the highest number on the list was the first number. The computer simply couldn’t figure out what to do about it.”

Consultant John Diebold says: “Computers are enormously useful as long as you can predict in advance what the problems are going to be. But when something unexpected happens, the only computer in the world that’s going to do you any good is the funny little one beneath your scalp.”

RCA 301 computer now steps up to big system workpower!

Core memory doubled to 40,000 characters! Magnetic tape capability increased to twelve or more 66,000 character/second tape units! System rentals remain low, and you can still begin on a small scale!

Already widely accepted by business and government, the RCA 301 has been so stepped up in workpower that the running time for many jobs has been cut in half. Now it can also tackle much larger and more complex jobs, and can be greatly extended in capacity as your work load grows. With the advanced 301 you have a wider choice of system configuration—and therefore, a better match to your job—than with any other system in its price range. And when you buy 301, you are buying top productivity per rental dollar for your overall needs.

Be sure you evaluate this advanced RCA 301 for your data processing needs. Or if you already have an RCA 301 system, add the new memory and high performance tape units as you require them. No reprogramming is necessary.

These new 301 advances are the latest in RCA’s continuing program of bringing you higher levels of EDP efficiency through the application of the world’s newest electronic techniques.

RCA 301 rental prices begin under $3000 per month, and delivery can be made in less than a year. Contact your local RCA EDP representative, or write: RCA Electronic Data Processing, Camden 8, New Jersey.

NEW RCA 301 SPECIFICATIONS:
Random Access: Data Record File, 27 million char. capacity
Data Disc File, 176 million char. capacity
Core Memory: 10,000-20,000-40,000 characters
Tape Units: 10,000-33,000-66,000 char./second
Printers: Up to two, 750-1000 lines/minute
Card Readers: Up to two, 600 cards/minute Card
Punch: 100 or 200 cards/minute
Paper Tape: Read, 100 or 1000 char./second Punch, 100 char./second

RCA
The Most Trusted Name in Electronics
RADIO CORPORATION OF AMERICA

Related posts

• Expand your knowledge – Subscribe to Byte (Dec, 1961)
• ANELEX (Dec, 1961)
• “Radio Shack’s TRS-80 Computer Is the Smartest Way to Write” (Dec, 1961)
• FOR THE MATHEMATICIAN who’s ahead of his time (Dec, 1961)
• Engineering hours turn into minutes when you speed up your data analysis (Dec, 1961)
• What’s New in Mnemonics? (Dec, 1961)

view additional pages

THINKING MACHINES ARE GETTING SMARTER

By Robert Strother

AT THE Vanguard Computing Center – in Washington, D. C, I watched a young woman present a machine with an extremely complex problem in ballistics involving hundreds of variables. At once lights on a control panel twinkled and winked as the computer checked to see that all equipment was operating properly. Then it set briskly to work. Magnetic tapes spun in their shiny glass-and-steel vacuum cabinets, the high-speed printer muttered. Suddenly the machine stopped and the electric typewriter wrote: “Last entry improperly stated!”

A little embarrassed, the young operator corrected her error, and the machine started again. Four minutes later it gave an answer that had required several million individual calculations.

“This is a wonderful machine” the girl said, “but it makes you shiver sometimes, especially when you give it a wrong figure. Once in a while we give it an incorrect figure on purpose—just to see it sneer at us.”

The machine was an IBM electronic computer—one of the new “giant brains” which differ from previous computing and tabulating machines in that they function with the speed of light— 186,000 miles per second. They can read, write and calculate simultaneously; they have tenacious “memories” and they can learn by experience. In the last half dozen years these electronic computers have come into wide use to perform miracles that touch the lives of all of us. Most commercial and scientific computer systems are huge affairs that fill a good-sized room which must be air-conditioned and dust-free. The largest digital computers cost from $500,000 to $4,000,000 each and yet they are being produced on an assembly-line basis by several companies. An idea of the complexity of the manufacturing job is given by a single statistic: there are 500,000 electrical connections in a giant computer.

Some machines are sold outright, some are rented, and some are available on a job basis, like a washing machine in a laundry center. Several computing service centers where problems are solved for a fee have been established by the leading U. S. producers in principal cities here and in Europe. Some of the more spectacular uses for computers are in national defense. A ballistic missile in flight, for example, must be in exactly the right position at precisely the right speed when the thrust is cut: An error of one foot per second in speed can cause a one-mile miss at the point of impact.

As it climbs a missile sends radio signals to a computer on the ground, informing it about variations in wind, fuel consumption, center of gravity, temperature, rotation of the earth and a score of other items. The computer figures the effect of these factors and instantly flashes instructions to keep the missile on course. When the great “bird” hits the right speed and is properly trimmed, the computer cuts the motor and the missile coasts at 14,000 miles an hour to its target. No human being could possibly work with the speed and accuracy required by this complex operation.

One of these machines has almost every one of us at its electronic fingertips: Computers at the Social Security Administration in Baltimore keep track of 160 million names and 1,750 billion dollars in wages. Formerly a change in a person’s name, or a transposed serial number, caused trouble. Now the computers know some 25 common sources of trouble—and search for them in order of probable occurrence. Correspondence in this, the world’s largest bookkeeping job, has been greatly reduced and the same staff can handle three times as many accounts.

One of the routine marvels computers are performing nowadays for business is the operation of the Boston home office of the John Hancock Mutual Life Insurance Company, where a Remington-Rand Univac II under the direction of five operators keeps all the records on two million policy accounts. The computer selects the accounts on which premiums are coming due, and calculates the amounts owed by matching data from magnetic tapes with premium and interest tables in its memory. It wraps up the job by printing out premium notices, ready for mailing, at the rate of 100 per minute.

Once a week it makes out the home office payroll, figuring income tax, bond purchase, health insurance and other deductions as it writes 7,500 checks an hour.

On the anniversary of each policy, the computer calculates cash values, dividends, loan interest due, or interest payable on accumulated dividends, and prints out a statement.

The present computers grew out of the early tabulating, calculating and teletype machines. Combined into one complete system, and speeded up by electronics, the most advanced of them can solve any problem that can be expressed in writing. Here, briefly, is how they work. An operator types information and instructions on a special typewriter that converts letters and numerals into a code of dots on a magnetic tape. The computer then “reads” these signals and sends them to its central “brain” or “memory”—which consists of thousands of pinhead-size iron doughnuts or cores, each linked electrically to all others.

This “memory” temporarily stores partial answers to a long problem until the computer’s ingenious circuits call them out at the right moment to complete the answers. It also permanently stores for repeated use such standard data as logarithm tables or withholding-tax figures. The actual calculating is then done on orders from an instruction tape that tells the computer precisely what to do with the stored information.

An involved problem may require thousands of steps, but computers make light work of it by performing 40,000 arithmetical operations per second. Electrons flash through the bewildering maze of up to 500,000 circuits and deliver the correct answers to a high-speed printer which types it out at speeds up to 900 lines a minute. The printers are versatile, too: they will express the answer in figures, plain language, or a diagram. And to top it all, the computer automatically checks the accuracy of its own answers. In rare cases of error—dust specks are the usual villains—the machine stops and refigures.

One of the most popular exhibits at the World’s Fair in Brussels is a computer that answers questions in any one of ten languages. The questions are about major historical events in any year from 4 B.C. to the present. A visitor calls out, in German for instance, the years 1480 and 1766. The operator enters these years and the language on the keyboard. In less than a second the machine’s electric typewriter begins printing, in German: “1480—Leonardo da Vinci invented the parachute. 1766—Mozart composed his first opera at the age of 11.”

When a concordance of the Revised Standard Version of the Bible was needed last year a computer was given the task: to identify and list by location and context the Bible’s 800,000 words. The 2,000-page Concordance that resulted contains 350,000 cross references. To prepare the previous Concordance took 30 years. After a few months of preparatory coding, the computer did the job in a few hours.

A computer demonstrated detective talents while indexing the Dead Sea Scrolls. The Concordance technique was used but in many cases the computer had to guess at letters or entire words missing from the crumbling old documents. It did this by analyzing the words preceding and follow- ing each gap. Then it scanned the thousands of index words to find the one that most nearly fitted the context. To test the accuracy of the method, portions of known text were blocked out and the partial sentences given the machine. It replaced correctly as many as five consecutive words.

The giant brain has also been set to work translating the current flood of scientific papers produced in a score of languages. First, every word in a sizable English dictionary is listed on tape under a code number. The Russian, French or German equivalents for each word are given the same number. Then, to translate from Russian to English, for example, a tape with the Russian code numbers is fed into the machine, which matches the numbers and prints out the English. In an early experiment, the computer was asked to translate the English saying “Out of sight, out of mind,” into Russian. The result was startling: “Invisible and insane.” Newer computers are much more sophisticated, and while human editing to rearrange awkward word sequences is still needed, the computer can make hundreds of rough translations in a day.

Computers make business forecasts, prepare weather predictions, run refineries. They hunt up legal precedents, help in the diagnosing of diseases, and compose harmonic but uninspired music. They even help design better computers.

“Computers can be programmed to do almost any mental work a man can spell out,” says Dr. Alan Perlis, one of the mathematician-philosophers who have played key roles in extending the scope of computers. “Each generation of human pupils must be taught afresh, but once you’ve taught any single computer to perform a process, you’ve taught them all, and forever. After a method for solving a certain problem is successfully worked out, it becomes part of the huge library of machine methods now available to users everywhere.”

Manufacturers have been working to give computers larger and faster memories and greater flexibility; they also have sought to realize the goal expressed a decade ago by the late John von Neumann, a trail-blazer in computer development. “Computers must be able to modify their behavior on the basis of their experience,” he said. One of the scientists tackling this problem is Dr. A. L. Samuel, who has taught an electronic computer to play checkers. This has a serious purpose: to train the machine to learn by experience.

The first step was to number the 32 checkerboard squares and the 12 men on each side. Then into the computer’s brain went a few thousand plays, selected from books written by experts—a half-dozen promising moves for every situation. A few instructions were added, and it was ready. The computer politely gives its human opponent the choice of colors, then prints out “Ml 12 16″—indicating the machine’s first move is piece 12 into square 16. Its human opponent replies by punching out the numbers of his play on a card which he gives to the computer.

The machine now runs over all plays open to it. It “mentally” makes a move, calculates what would be the best response for its opponent, figures its next probable move in that case, then the probable reply to that. It carries this procedure forward six steps before printing out the play it has selected. It does all this in 15 seconds and then waits—humming quietly —for its opponent’s next move.

The checker-playing computer keeps every move of every game stored in its “memory,” and it displays uncanny powers: it will sacrifice a piece to gain a future advantage; and it marks the plays that have led to losing games. When it next encounters the same situation, it selects a different move from its repertoire. The result is that it shows improvement in almost every game, and now easily defeats anyone except a real expert. To watch it print: “EXPECT TO WIN IN FIVE MOVES” gives some observers an uneasy feeling.

Computer men, thrilled by the powers of the genie they have created, like to speculate on the tremendous promise it holds for human advancement. “Computers open up scientific possibilities that were unthinkable before,” says Ralph J. Cordiner, Chairman of the Board of General Electric Co. “They will make possible entirely new products and industries. These computer-derived technologies will be a major source of new employment in the coming decades.”

Such leaders as Dr. Simon Ramo of Ramo-Wooldridge believe that the computer, by making vast new areas of knowledge manageable, and by directing operations too fast or too complex and requiring too much speed for a man to handle, will prove to be the most valuable of all the developments of these fast-moving times. No man can foretell what the future holds, but there is no doubt that many of our questions about it will be answered with the speed of light. •

YOUR business will benefit with NCR Data Processing!

Regardless of the type or size of your business, you will benefit from the efficiencies of National Data Processing. From one or more of NCR’s original entry products—accounting machines, cash registers, listing, window posting and receipting systems—you can get just the input media of your need and choice. This may be punched paper tape or punched cards.

This input media is processed quickly, accurately and economically by an NCR computer specifically designed to furnish complete record information tailored to your specific needs. NCR offers a full range of Data Processing Systems: small, medium, and large-scale computers, plus a network of processing centers.

For more complete information on how NCR Data Processing can benefit your business, call your local National Branch Office or WRITE TO US TODAY!

NCR GOES ALL THE WAY FROM ORIGINAL ENTRIES TO FINAL REPORTS.

THE NATIONAL CASH REGISTER COMPANY, Dayton 9, Ohio 1039 OFFICES IN 121 COUNTRIES • 77 YEARS OF HELPING BUSINESS SAVE MONEY

view additional pages

COMPUTERS: THEIR SCOPE TODAY

ARTICLE BY ERNEST HAVEMANN

AT THE Massachusetts Institute of Technology there sits a giant computer, its lights constantly blinking and its dials endlessly churning out new numbers, on which some unknown technician has fastened one of the buttons now so popular among the hippie set. The button reads:

I AM A HUMAN BEING.
DO NOT FOLD, SPINDLE OR MUTILATE

Newcomers to the laboratory spot the button, move in for a closer look and nod—yet seldom smile. To most people who deal with computers, the button seems not funny, not ridiculous, not cynical but oddly appropriate.

True, the computer has introduced us to an age in which a great many human traits, activities, hopes and fears have been depersonalized into cards designed to be run through a machine, like so many playing cards through a baccarat shoe or slabs of steel through an assembly line. We pay our bills and resubscribe to our magazines on coldly formal rectangles that must not be folded or spindled. We sometimes take our college tests on them. The friendly neighborhood bank knows us only as a number, printed in the strange devices of magnetic ink. We are also no more than a number to machines in some unknown location, never seen by us, that determine our credit standing, calculate the Social Security benefits we may someday receive and decide how honest we have been on our income-tax returns. To other machines, busy charting population growth, divorce statistics, economic trends, future demands for houses and automobiles and the number of hospital beds that will be needed for the victims of heart attacks, we are not even a number—just a couple of anonymous magnetic beeps stored somewhere inside an electronic circuit whose mysteries we would never be able to unravel. The rows of lights wink like drunken fireflies; the wheels spin out their figures; human history gets made and recorded almost without the touch of a human hand.

Still, there is something about the computer that can inspire affection. You can talk to a machine now. Well, not exactly talk; you have to type out your end of the dialog, and the machine types in turn. But this new kind of pen-palship has its own kind of warmth. The machine is at least as solicitous as an airline stewardess and far more polite than a New York bus driver. It says, “You’re quite welcome”; “Come again”; “I didn’t understand you”; “Feel free”; “Very good.” To a school child trying to learn arithmetic, it says, “Hello, I’ve been waiting for you”; “Please type your name”; “Goodbye, O fearless drill tester.” Dr. Joseph Weizenbaum of MIT tells the story of the time he let his secretary start a typewritten conversation with his machine. After a few sentences back and forth, the dialog began to seem so personal and private that she asked Dr. Weizenbaum to please leave the room.

But there is an even deeper bond between the men who use the computers and the machines they use. Some men lavish affection on their automobiles, those metal creatures that have augmented the mobility of the human leg muscles. Some men are sentimentally attached to their power tools, those potent extensions of the human arm. The computer scientists often take this same fond attitude toward their marvelously intricate, cunningly designed, mechanically beautiful extensions of the human brain. Many of them, indeed, believe that the computers came along just in time to save civilization from collapsing under the weight of its own complexity and are therefore not only the friends but the saviors of man. “The trouble with a world like ours,” says Professor Robert Fano of MIT, “is that we will soon need more experts to run it than there are people. Only the computer seems likely to keep us going.” This is a sentiment shared by many thoughtful observers of civilization who, without any direct experience with computers, have developed a grateful respect for them. Professor Jacques Barzun of Columbia University, a noted humanist who might be expected to resent the machines, has said, “I think computers are perhaps the salvation of the welfare state —particularly the overpopulated welfare state in which we’re all going to live.”

There is a persistent legend, of course, that computers are not very smart—no smarter, say, than an adding machine. Faster, yes. Smarter, no. This is partly the result of propaganda. The companies that make these fantastic new machines are all too painfully aware of what happened when the first wide-scale application of labor-saving machinery was begun in the factories of about a century and a half ago: A group of determined Englishmen called the Luddites, believing that the machines would throw everybody out of work, set about systematically destroying them. If machines that threatened to make human muscles obsolete could arouse that much mass resentment, the computer manufacturers figure, then machines that threaten to supersede the human brain may arouse a good deal more. Computer makers consistently put the knock on their own products, which they like to call, in the words of one of them, “a tool and nothing more.” They shudder to hear the machines compared with the human brain. They even avoid die word “memory”; they say that the machine has not a memory but a “storage capacity.”

It is also true that, until recently, die machines were not asked to behave in any very intelligent fashion. When they were first introduced, they were terribly expensive to own or rent and to operate. They were put to work only on jobs where they could pay their own way— and these were mostly clerical and accounting jobs of the simplest kind, where the machines did nothing spectacular but did it in enormous quantity and at superhuman speed. A good example is keeping track of magazine subscriptions and printing the mailing labels.

Even today, most of the computers in the world are performing routine tasks. It is only when you go to the universities and the experimental laboratories of the manufacturers that you catch a glimpse of the true possibilities—and see machines that can do well on human intelligence tests, can converse intelligently, can learn and can even teach. Yes, even teach. One of the most exciting prospects for the future is that all of us, however lacking in engineering skill, will someday be able to operate a computer as easily as we now operate our automobiles, because the computer itself will show us how. It is only a matter of time, you discover in the laboratories, before all of us will have our homes hooked up to what the scientists are calling “information public utilities” and will have brain power piped in just as we now have electric power. What the world will then be like staggers the imagination. But more of this later.

As of this moment—the autumn of 1967—die most important fact about computers is that they already are essential to civilization as we in America now know it. They are only 20 years old; they have been used mostly in obvious and unimaginative ways; their real potential has only been scratched—yet life would not be the same without them. You cannot have a nation as big, prosperous, active and mobile as the United States, with 200,000,000 people in constant interaction, without the computer. The complexities of keeping the communications lines open, getting the goods delivered, keeping the accounts and paying the bills represent too big a job for the unaided human brain and hands.

The telephone system is a good example. If every call still had to be handled by an operator sticking plugs into a switchboard, today’s volume of telephone conversations, local and long distance, would be an intolerable strain on the economy; it would take the services of every woman now alive in the U. S. Instead, the job is done by computers. To those who doubt that the average man will ever be using a computer, indeed, the telephone system provides a clear answer. Every one of us already has a computer console in his own home—the telephone dial or touch buttons—and we use it every day to tap the amazing resources of the computer. By dialing or touching ten numbers, we manage with the computer’s help to ring a telephone all the way across die continent, any time we feel like it.

If you are running a modern railroad with tens of thousands of freight cars, how do you know where any one of those cars is at any given moment? You don’t—or didn’t until recently. One reason the railroad industry has fallen on lean days is that the average freight car has been used on an average of only a little more than an hour a day and has stood idle the rest of the time, waiting for somebody to discover where it was, put something in it and send it on its way. Now the New York Central uses a computer to keep an account of every one of its cars, and the Association of American Railroads is about to install a computer that will keep track of all 1,800,000 cars in the nation.

If you are running an airline with several hundred flights a day and a thousand or more ticket counters, how do you keep track of reservations? You don’t —without a computer. Here American Airlines pioneered, with its $30,000,000 system called SABRE, which serves all of its offices, from Boston to San Diego. SABRE tells the ticket clerk immediately if space is available on any particular flight at any time within the next year; it then reserves seats under die customer’s name, remembers how to get in touch with him and, when the time comes, makes sure there are enough drinks and food aboard to keep him happy. It even corrects the kind of human error mat used to foul up the airlines’ plans almost beyond redemption. John Smythe, on a trip of many stops from coast to coast, stops by a ticket counter to change the date of his next flight. The clerk, as so often happens, gets the name a little bit wrong; he asks the computer about John Smith. Without hesitation, the machine says, in its own language, “Hold on, buddy. I’ve got John Smythe, John Schmidt, John Schmid and John Smithfield—but no John Smith. Which one did you mean?” Other airlines have quickly followed suit: Delta, as a side line, now uses its computer’s excess capacity to sell tickets to the Atlanta Braves’ baseball games.

Suppose you are an airplane manufacturer and have spent several billion dollars to develop a new supersonic plane that will further improve air travel by carrying several hundred passengers from New York to Los Angeles in a single hour. To the pilot, the plane is a totally new experience^ for the cockpit from which he scans the landing field is several stories above the landing gear. And there’s the rub—for even the best pilot in the world, trying to land this monster for the first time, will almost surely crack it up. Do yon take the chance? Of course not. You use a computer to simulate the airplane’s controls, its performance and the landing field and thus teach the pilot how to land safely and gracefully without ever taking to the air.

These are the obvious ways in which the system—and individual units of the system, such as the supersonic plane— has grown far too complex lor human control. There is another way that, though hidden, is in fact even more important. What has made our modern scientific era possible is an information explosion; our whole society is based on a rapidly expanding new knowledge of physics, chemistry, medicine and engineering. Information pours out of the research laboratories too last lor any human brain to absorb. Around the world, 100,000 separate and different technical journals are published in (30-odd languages. The total amount of scientific data published each year runs to 250,000,000 pages. In the rush, there is even a good deal of information that never gets published at all. In the laboratories of a pharmaceutical company, for example, a new thug discovered by some ingenious researcher today may, in fact, be being “discovered” for the second or even the third time. It’s original discovery may very well lie buried in the unread workbook of some earlier researcher who, knowing of no use for the drug at the time, did not pass his knowledge along.

Thus, the information explosion that produced the computer now needs the computer to keep up with it. A computer prints the weekly publication called Chemical Titles, listing the topics covered by new articles in 690 leading chemical journals. Another computer prints the monthly Index Medicus, which lists alphabetically, under subject matter, the new articles in some 2400 medical journals. Each issue of Index Medicus runs about GOO pages and nearly 2,000,000 words; without the computer it could never be printed in time to keep up with new developments. Drug companies are starting to store the workbooks of their researchers in a computer’s infallible memory, to avoid the waste of new research that merely duplicates the old.

The biggest single user of computers today is the U. S. Government, which would otherwise be crushed under an impossible load of paperwork. Computers not only scan tax returns and keep Social Security records but also calculate census data, direct prospective employees to their Civil Service examinations and make out pay checks for something like 2,000,000 Federal workers and more than 500,000 others who are retired and living on pensions. The Air Force uses one of the most intricate of all computer systems to control its world-wide inventory of equipment and supplies, which is worth well over ten billion dollars at any given moment. It uses another complex system to keep track of every single airplane in the skies above the U.S. and Canada, second by second, around the clock. The space program— the control and tracking of 20,000-mph satellites and spaceships—would be impossible without computers.

The second biggest user is, of course, American business; and there are experts who will argue that it has been the computer in industry, rather than the new economics or sheer luck, that has permitted our nation to remain so prosperous over so long a period. This is because one of the uses to which the computer has been put by business as well as by the Air Force is the control of inventory, at which it has been exceptionally effective. Industries that get a constant flow of computerized information about their supplies and sales can get by with a much smaller inventory than in the past; they do not get stuck with large and immovable supplies of goods and then have to cut back on production until the supplies have been whittled down. A decade or so ago, the inventories of the manufacturers of durable goods used to fluctuate by an average of four billion dollars a year, causing corresponding changes in production and employment. Now, the average fluctuation is cut in half and the peaks and valleys of production have been evened out. No one would argue that the computer has made recessions impossible—but it has certainly reduced the danger from one of the frequent causes of recessions in the past. Other business applications of the computer are legion. Schlitz uses it to make predictions of the sales of beer and to help decide where and when to build new breweries. International Harvester uses it to make simulated runs of new trucks and to predict their life span. Ford has a computer controlling a production run that will operate nonstop for three years and at the end of that time will have turned out a 9000-mile strip of windshield glass; this computer gets a constant flow of information on how the process is going from 700 sensing devices and makes the necessary readjustments at 80 control points. Mobil Oil has a computer-controlled refining unit that automatically analyzes market prices and then turns out whatever combination of products will be most profitable. Pills-bury has a machine that provides its executives, at eight o’clock in the morning, with a complete analysis of the company’s sales and inventory position as of closing time the previous day. Executives at Woodward R: Lothrop, a Washington department store, get a similar early-morning report on the previous day’s sales in each department of nine separate stores, along with a running account of this year’s trend compared with last year’s at this date. Clothing manufacturers feed a new dress design into the machine and let the computer draw up the many individual patterns needed to produce it in all sizes from 6 to 46.

The stock exchanges have computers that talk. If you want to know what is happening today to U. S. Steel or Syntex, you simply call the computer on your touch-tone phone, touch three more buttons to give the code number of your stock, then listen. Stored in the computer are sound tracks such as those on a movie film. The computer picks out the correct combination of voice sounds to give you the quotation on the last sale, the current bid and offered price and, in fact, the figure at which the stock opened and its high and low for the day. Several times a day and immediately after the close of the markets, the Associated Press uses its own computers to rush the stock tables to newspapers around the nation.

In medicine, the computer already has many uses. A computerized dummy of a human being, with a heart that beats and throat muscles that twitch, is used to train anesthesiologists at the University of Southern California; the dummy, which sometimes has heart failure or vomiting attacks, enables the trainees to learn in a few days what used to take several months to master. At Mount Sinai Hospital in New York City, a computer is used for rapid analysis of electrocardiograms made at the patient’s bedside. In fact, electrocardiogram signals have been sent from France to the U. S. via satellite, have been expertly analyzed by a computer and the results have then been sent back to France, all within 30 seconds. In many medical centers, computers make and report on blood tests much faster than the tests can be made by human technicians. In Mayo Clinic, a * computer keeps constant track of the blood pressure, body temperature, heart rate and breathing rate of patients undergoing neurosurgery and flashes its findings onto a television screen in the operating room. At Presbyterian Medical Center in San Francisco, a computer keeps watch over patients recovering from open-heart surgery and flashes an immediate alarm if complications develop. In Brooklyn, nine hospitals are hooked into a computer system that keeps a second-by-second census of the beds available or occupied in their children’s wards; a child brought to a hospital that is already filled can be sent without delay to the nearest place where space is available. At Sara Mayo Hospital in New Orleans, a computer plans menus that provide a balanced diet and the proper calorie count at lowest possible prices; the computer takes full account of the preferences and dislikes expressed by patients in the past and also the need for variety in the color and consistency of the foods served at each meal.

The miscellaneous uses of the computer would require a catalog of their own. It has been used by modern versions of the old-fashioned lonely-hearts clubs in an attempt to help college men and women, and older people as well, find dates who share their interests and tastes. (Computerized dating may be just a fad and no better than older methods of matching cards showing personality traits—but conceivably, if applied to thousands of people on a city-wide scale, it could be a standard part of romance in the future.) It is used in printing plants to set type, on airplanes and ships as a sort of supernavigator, in engineering to solve previously insoluble problems and to draw up working blueprints, at the race track to calculate the pariimituel odds and pay-offs. It is being used to analyze and to plan ways of combating air pollution and water pollution and, experimentally, to relieve big-city traffic jams and to improve weather forecasting. It provides pathways through the vast confusion of the nation’s laws, for the benefit of lawyers and legislators and, in fact, augments the grasping power of the long arm of the law. In Chicago, it is used to enforce payment of 2.500.000 parking tickets issued each year. The Federal Bureau of Investigation has set up a nationwide computer system that will eventually enable any local policeman, when he sees a suspicious automobile, to phone his headquarters and learn almost immediately, while still keeping the automobile in view, whether it has been stolen or is wanted in connection with some crime. The computer is even used to design and help manufacture better computers—an indication that it may someday, like living creatures, be capable of reproduction.

If the nation’s computers went dead this very moment, all of us would know it at once—and to our sorrow. Our telephones would go silent. Our self-service elevators would stop. It would be impossible to make an airplane reservation. A great many industrial plants would shut down. The nation’s banks would stagger under an avalanche of checks impossible to sort by hand. Yet most of the current uses of the computer—however marvelous, however essential to the day-by-day operation of a civilization as complicated as ours—are somewhat remote from your and my personal experience. Most Americans have never seen a computer, except possibly on television on election night. Except for our contacts with telephones and elevators, most of us have never operated one or even dreamed of using one in any intensive way. As a matter of fact, there are very few executives in Government or business, those two great customers of the computer industry, who have ever had any direct personal contact with a machine. Most executives do not understand computers or know how to use them; they deal with the machines through a group of rather mysterious middlemen called programmers, who use a new kind of language, full of code words and mathematical symbols, to tell the machines what to do.

Thus, the computer age, in many ways, has so far been a disappointment. The computer was supposed to revolutionize our lives; it was supposed to put marvels of new technology at our finger tips: there were even some dark but fascinating hints that it might out-think us and take us over. But where are all these fabulous new machines and what are they doing for us} “Computers,” admits one of their manufacturers, “have been flagrantly misrepresented. They haven’t been useful to people at all—except to the few people who run them.” But that day is ending. “In the past,” says this manufacturer, “computers have been like railroads, great for the businessman who wants to ship a heavy load of freight across the country, no good at all to the individual who wants to get from his home to his office. Now we’re moving into a new stage, where the computer will be like a passenger automobile, available to take anybody wherever he wants to go, whenever he wants to go there.”

There are many scientists now at work trying to adapt the machines to handle the complications, not of civilization as a whole but of life for the individual man; these scientists are thinking not of the mass problems of society but of the personal problems that you and I encounter every day of our lives in this intricate, difficult, baffling and often exasperating world. This is the special goal, for example, of Dr. Fano and the MAC Project (for Machine Aided Cognition) that he directs at MIT. Says Dr. Fano, “We’re all faced with daily problems that are rapidly getting much too complex to solve. We don’t have enough time, information or experience to keep up with the growing difficulties that surround us when we try to budget our incomes, pay our bills, balance our checkbooks, make out our tax returns, save and invest for our old age, decide whether to buy or rent a house, evaluate a new job offer, contemplate a move to California, keep track of family anniversaries, draw up a will or even plan a sensible work schedule for tomorrow. Somehow we have to break through this ceiling of complexity.”

The kind of computer use that Dr. Fano and his colleagues have in mind is typified by an experimental program already under way in California, where high school students get a highly expert form of guidance from a machine. In planning his next year’s program, the student goes to the machine and learns what courses are available. The machine asks him if he is planning to go to college and, if so, what kind of college; it then advises him what kind of courses to take to meet that college’s entrance requirements as well as his high school’s requirements for graduation. It tells him how well students with his kind of record have done at that kind of college —how many of them have managed to be A students or how many have flunked out—and may suggest that he is aiming his sights either too high or too low. It refers all special problems to the school’s guidance counselor, while freeing him from the routine questions.

A similar sort of program, Dr. Fano has pointed out, could be devised for helping people make out their income-tax returns; it would be superior to any conceivable book on taxes. One trouble with the tax laws is that they have to Ik written to cover every possible situation; they must therefore be extremely complicated. The trouble with the books that try to explain the laws is that they can do so only by citing examples—which often turn out to be slightly different from our own problems, in ways whose importance or unimportance we find hard to judge. A computer could be programed to listen to any kind of tax problem, even the most unusual, and work out the logical applications of the law to that particular case. Dr. Fano has even suggested that the income-tax laws of the future might be programed directly into the machine instead of printed on paper.

One computer scientist, partly for fun but partly in earnest, has been thinking about a computer program that would give advice on restaurants in New York or other big cities; it would ask the user questions such as, “Do you like Chinese food?”; “Do you prefer a small place or a large one?”; “Do you want music?”; “How much do you want to spend?”; “Does the restaurant have to be near some particular theater?” From what it learned about the user’s tastes and budget, it would then give him a list of places he might like. Afterward, by finding out how well he actually enjoyed the meal, the machine would learn even more about him and be able to supply even better advice the next time. The same program could be enlarged to suggest ways of spending an evening or a weekend. (”People who live in cities have a fantastic array of choices of how to spend their time,” says this scientist, “but at the moment, they don’t take much advantage of the choices. They need help.”) It could even be made into a sort of super travel bureau, with a full array of up-to-the-minute information such as no travel bureau now possesses. Conceivably, you could call up the computer and say, “I’ve got from four o’clock Friday afternoon to nine o’clock Tuesday morning; where shall I go?” The machine would ask some questions, such as, “Would you be willing to spend as much as $300?” and “Do you like to fish?” and would then come up with a suggestion: “I can give you a suite in the Americana Hotel in Miami Beach for $75; you can have a seat on Eastern’s Flight 123 at six p.m. Friday and return on Flight 321 arriving Monday midnight; Captain Harry Brown and his fishing boat will be waiting for you at seven o’clock Saturday morning.”

The possibilities are almost endless. It is perfectly feasible to program a computer to help the baffled householder; he could be instructed how to repair a leaky faucet or get squirrels out of his chimney. Dr. Spock’s wisdom about babies could be put into a computer, in much more detail, to help meet individual crises, than is possible within the covers of a book. Excellent medical and legal advice could be dispensed by a computer, if the medical and legal professions permitted. It is even possible that people will someday take to the computer the kind of problems they now take to psychiatrists, psychologists and marriage counselors. A computer program has already been developed, in fact, that actually sounds quite a bit like some types of psychotherapists; it has had the following typewritten conversation with a make-believe woman “patient”: patient: Men are all alike. machine: In what way? patient: They’re always bugging us about something or other. machine: Can you think of a specific example?

patient: Well, my boyfriend made me come here.

machine: Your boyfriend made you come here?

patient: He noticed that I’m depressed much of the time. machine: I’m sorry to hear you are depressed. . . .

And so on, through what sounds very much like a 50-minute session with a therapist.

Another use of the machine that is prominent in the thinking of computer scientists is in shopping. The Sears, Roebuck type of printed catalog, expensive to publish and distribute, will probably vanish. Instead, the shopper will call up the computer at Sears, Roebuck or his favorite department store, ask what is available, see pictures of it on a television screen, ask questions and get more intelligent and complete answers than he is likely to get in person from most of today’s salesclerks. He will probably pay for his purchase with computerized money, by direct transfer from his own bank account to the account of the store, without writing or mailing a check. This kind of financial transaction is already taking place successfully in an experimental program set up by the Bank of Delaware and a chain of shoe stores; when a customer buys a pair of shoes, the clerk uses a touch-tone telephone to call the bank’s computer, enters the customer’s identification number and presses buttons showing the amount of the sale. The method is bound to spread, because the volume of checks written in the nation, about 70.000,000 a day, is rapidly getting out of hand, despite the computerized sorting of checks. It costs the banks more than three billion dollars a year just to move the checks through the clearing system and eventually back to the people who made them out.

The physical barriers to setting up an intellectual public utility are not very serious. As a matter of fact, there already is such a system, designed to help scientists, in operation under the MAC Project. It has 160 “outlets” in the form of teletypewriters scattered around the MIT campus and in the homes of professors; these typewriters are connected to two separate computers, each of which can serve 30 users simultaneously under a time-sharing program developed by the MAC scientists and the computer manufacturers. The MIT faculty and students use the system constantly, particularly to help with the complicated mathematical calculations involved in advanced research. One engineering professor says that he has not used his slide rule, once the badge of his profession, in three years.

The same kind of time-sharing computer system could rather easily be set up to serve an entire community; each home would have its own console, preferably including not only a teletypewriter but also a viewing screen of some kind, connected to a computer center just as every home is now connected to electric power and telephone centers. The machine might even communicate to the user by speaking, although it probably would not understand human speech. (It is much more difficult to build a machine that listens than one that speaks, and opinion among scientists as to how soon, if ever, a listening machine will be available is sharply divided.) Although the physical problems are easy to solve, there are other problems more sticky. One of them is that most of us would hardly care to spend two years learning how to program a computer for our own special uses; the experts will have to find ways of making computers easier for the average man to use. In the words of Dr. Fano, “The user should be able to talk to the machine as easily as a businessman now talks to an assistant who knows the business well. In fact, that is what the machine should be— a skillful and knowledgeable assistant.” But progress in this direction is being made all the time. Computer scientists like to point out that, when the automobile was introduced, a man had to be an expert mechanic to own and drive one. Now, they say, the computer is rapidly getting to the stage where anyone can learn to operate it, as the automobile did long ago.

What will the intellectual public utility of the future bring into our homes? Dr. Fano foresees a day when the computer will have a giant mass memory containing all the knowledge of its particular community—all the knowledge now found in the books and journals of the very best library, plus everybody’s daily work reports, financial records, tax returns, medical histories and what have you. Storing as much information in a computer as can be put on a page with single-spaced typewriting now costs as little as ten cents a month in some systems; eventually, it will probably be cheaper to store everything in a computer than in a book or a filing cabinet. When that day comes, the computer will put all the accumulated knowledge and skills of the world to our own personal service. A man will be able to produce the solutions to problems in calculus without ever studying calculus, to design a new house without ever taking an architecture course.

Far from depersonalizing life, the computer of the future will probably create a great deal more individual variety. Indeed, it has already won some battles against mass conformity. It makes possible the manufacture of more different models of automobiles with more available options; and in Los Angeles, it enables a customer to walk into any of 75 Dodge showrooms and immediately select exactly what he wants from a pooled and computer-controlled inventory of 6500 cars. Computerized teaching machines have provided considerably more individualized instruction for elementary school pupils, geared to their own backgrounds and ability to progress, than is otherwise possible in a large class. The computer has even brought back at least a faint echo of that delightful bygone day when the village librarian knew every patron so well that she could suggest new books that she knew would interest him. At the big technical libraries of IBM, profiles of staff members have been fed into a machine that automatically sends them abstracts of new books and articles they might want to see. In the future, the computer will very likely print out a morning newsletter or even an entire newspaper designed specifically to meet the needs of the man reading it. It could tailor-make individualized magazines and television programs and permit a man to design his own special kind of furniture or even a new automobile. On an even more important level, it may free us from the restrictions of what has been called the creeping bureaucracy of our recent past—for many of today’s rules, regulations, inspections and permits are designed simply to prevent a densely populated society from falling into chaos. In a society where information circulated freely and almost instantaneously, many of the restrictions would probably be unnecessary.

Which brings us to the question: Just how brainy, in actual fact, are these machines? Can they learn? Can they think? Can they create? Will they ever reach the stage assumed in a joke popular among computer scientists, in which one machine asks another, “Do you believe in man?”

The answer to most of these questions is that, at the moment, nobody really knows. The phrase used by the scientists in this connection is “artificial intelligence”; some think the machine has it, others that it does not.

Certainly the machine can learn. The machine that counsels the California high school students asks questions, learns from the answers what each student is like, then gives him not just general advice but guidance intelligently molded to his special needs. The University of Virginia has developed a computer system that learns to solve problems by trial and error. Part of the MAC Project is a language program called ELIZA because, like Eliza Doolittle in Pygmalion and My Fair Lady, it can be taught to use language increasingly well. Indeed, once ELIZA has been taught English phrases, it can also learn the German equivalents; the operator need merely tell it, “When I say Ich sage, I mean I say”—and the machine remembers this.

As anyone who has ever taken a psych-I course knows, however, the human brain solves problems in strange and marvelous ways. All of us possess a large memory bank of facts, mathematical rules and knowledge about relationships. In our thinking, we sometimes manipulate this knowledge through the rules of logic; we know that since all mammals nurse their young and since a whale is a mammal, whales must nurse their young. At other times, we manipulate it through our own individual kind of something like free association. To a minister, the word “angel” may set off a train of thought such as angel-heaven-God-Holy Ghost-Virgin Mary-Sermon on the Mount. To an athlete, the associations might go angel-fly-fly ball-baseball-Willie Mays. If the machine is ever to be truly creative, it must learn to think in this random, freewheeling, rather haphazard but richly productive kind of way. Can it? Maybe, maybe not. Nobody has yet tried to make the machine think in this fashion.

There have been only about 20 experiments in artificial intelligence, most of them conducted by graduate students working on Ph.D.s. The students have tried what seemed most promising, random thinking not included. They have, however, produced some truly amazing results. One MIT student taught a computer to solve algebra problems stated not in mathematical terms, which is easy for the machine, but in plain ordinary English—such as, “Mary is twice as old as Ann was when Mary was as old as Ann is now. If Mary is 24 years old, how old is Ann?” (Unless you can figure out quickly that Ann is 18, something that few people can do, the computer is a lot better at this kind of problem than you are.) Another student taught a machine to solve the kind of problems in geometrical analogies often included in intelligence tests, such as: The machine can do as well on this part of an intelligence test—even with geometric figures it has never seen before— as the average ten-year-old. And now another student at MIT, this time just an undergraduate, has taught a machine to solve the verbal analogies of intelligence tests, such as dog is to bark as saw is to blade, wood, cut, whine or tool?

There is a popular saying, of course, that the machine can do only what it is programed to do—and a human being must do the programing. This is reassuring to human pride and has become the cliche response to every new accomplishment by the machine. But the scientists who believe in artificial intelligence point out that the human brain must also be programed; our thinking processes are the end result of all the information and instruction ever received by our input devices, notably our eyes and ears, from birth. Moreover, programing a computer is by no means so exact a science as has been advertised. It had to be very precise at first. Now, in the words of MIT’s Professor Marvin Minsky, “Programmers don’t have to know exactly what they are doing; they can be very sloppy, as a matter of fact.” They do not always understand how or why their programs work. And, as the programs get revised and enlarged through dialog between man and machine, they become increasingly versatile. Says Professor Minsky, “People claim that programs are all right for special purposes but aren’t flexible. Well, a typewriter or a violin isn’t flexible, either— until you learn to use it.” In the computers of the information public utilities of the future, which will be conversing with all kinds of people, learning all kinds of new facts and getting instructions to perform many different tasks, the user may be able to present a brand-new kind of problem and get it solved simply by telling the machine, “Which of the problems you’ve solved in the past is most like this one? Try that method.” And quite possibly, Professor Minsky believes, the machine may reach the solution through a method that would never have occurred to the man himself. No one individual will know everything that is in the machine and what may therefore come out. Very little special training will be needed to operate the machine, but probably some users will have better luck with the computer than others. “Some people will be just naturally good at it,” says Professor Minsky, “the way some people are good at skiing.”

Eventually, Professor Minsky believes, the machines will be programed for self-improvement; they will get better and better of their own accord; then they will unquestionably display the traits we refer to as intelligence, intuition and consciousness, and the world will never again be the same. Will they be man’s equal or even his superior? Dr. George Feeney of General Electric says, “I think we’ll get to the point where that question won’t really matter. The humanists, if optimists, will say that the machine is an extension of man—and the realists, if pessimists, will say that man is an extension of the machine.”

view additional pages

COMPUTERS THAT ARE REALLY PORTABLE

By Philip L. Harrison & Margaret A. Taylor

IN 1946, the first American electronic digital computer, ENIAC (for Electronic Numerical Integrator and Calculator), was unveiled. It ran on 18,000 vacuum tubes, 70,000 resistors, 6,000 switches and 10,000 capacitors. It weighed more than 30 tons, occupied 1,500 square feet of floor space and consumed 140,000 watts of electricity. Commercial versions of this machine ran to the tune of $5 million.

Today your neighborhood computer store can sell you a computer more capable for less than the price of a compact car. It’ll use less electricity than a 150-watt bulb and won’t even clutter your desk top.

And there’s more. Today you can buy an honest-to-goodness science-fiction dream machine: a computer that you can hold in your hand and carry around in your pocket, which compares as favorably to most current micros as those desk tops do to the ancient ENIAC.

There is a point of confusion that has to be cleared up first: Just what is the difference between a pocket computer and some of the more sophisticated hand-held programmable calculators?

From a practical standpoint, it all depends on the type of information (data, if you will) that you manipulate. For many problems, numbers and mathematical formulas are all that are involved. And if number crunching is your game, either product may be suitable. (Astronauts, in fact, have often used programmable calculators to determine the data to be entered into on-board spacecraft computers.) Pocket or hand-held computers, however, not only allow you to crunch numbers (and in greater quantity), but to save them. You’ll also be able to save and manipulate letters and, in some cases, graphic symbols. This opens up problem solving to other-than-strictly-mathematical areas. In fact, it opens up the whole field of information storage and retrieval for virtually any purpose, from nuclear physics to household recipes.

Among the machines currently making their way to the marketplace, the two that most amply fit the criterion of pocketable are the Radio Shack TRS-80 Pocket Computer (manufactured by Sharp and also sold as the Sharp PC-1211) and the Quasar/Panasonic HHC (developed jointly by Matsushita of Japan and Friends Amis of San Francisco—those wonderful people in Silicon Valley who originally brought you the Atari video games and the Craig/Quasar/Panasonic language translator).

These computers are versatile tools that can put cheap but powerful and useful computing capability into the hands of everyone. And, while patience is a virtue in learning to operate these hand-held marvels, you don’t have to be an Einstein to figure out how they work or a mathematician/engineer to make practical use of them.

Lightest in weight (a mere 6 ounces) and least expensive (at $229.95), the Radio Shack/Sharp pocketable is the first to have come out in mass distribution.

The computer is just under 7 inches long, less than 3 inches wide and about 3A inch thick. It has a standard typewriter-format alphabetic keyboard with seven additional special-function keys. Twenty numerical and other notation keys are arranged for calculator-type convenience.

The Radio Shack/Sharp computer has a 24-character dot-matrix liquid-crystal display that can be automatically scrolled if a line is longer than 24 characters. Its workings include UK bytes of ROM (read-only memory) and just under 1.5K bytes of user-available BASIC programmable RAM (random-access memory).

Four mercury batteries (nonrechargeable) give a life of 300 hours. Additionally, a small amount of power remains on at all times— even when the unit itself is switched off—to protect the memory (and whatever data you have put into it).

When the display indicates (via gradually fading characters) that it’s battery-replacement time, just pop out the old and stick in the new; a built-in capacitor retains the electrical charge for about a minute, allowing the batteries to be replaced without losing anything in memory.

Among other important features to note are a built-in edit and debug mode. For the computer novice, the edit mode allows you to easily correct or change your programs. The debug mode executes a program one line at a time, which is very valuable in determining where program problems exist since it enables you to follow the computer’s actions step by step.

The computer also boasts a reservable memory system that allows you to store frequently used commands in any of 18 keys for one-touch recall along with a definable key system that lets you easily execute up to 18 frequently used programs. Within certain limits, this allows you to customize the computer.

Optional accessories (or peripherals, in tech talk) include a dot-matrix printer and a cassette interface for program and data storage. A nice touch is that this cassette-stored data can be accessed by your BASIC programs, which allows large amounts of data to be read or saved quickly.

Eleven ready-to-run cassette programs are available, including some that cover areas such as civil engineering, business, real estate, aviation and personal finance, along with a selection of games.

The Quasar/Panasonic pocket computer is the latest that technology has to offer and consequently the highest-priced pocketable (starting at $525).

A bit bigger than its TRS-80/PC-1211 brother (about 9 inches long, 33/4 inches wide and about VA inches thick) and 8 ounces heavier, the HHC comes standard with 16K bytes of ROM and either 2K or 4K (at an additional $70) of RAM, of which about 700 bytes are not user-available.

In the 2K version, this would appear to make the HHC less powerful than the TRS-80/PC-1211, but there is more. Unlike the other machine, this hand-held wonder is expandable. Three slots in the back each hold optional 16K ROM capsules, allowing a total on-board capability of 64K bytes of application programs or data. External programmable RAM banks are available in 4K modules, each expandable to 8K, and up to six such modules can be attached to the HHC at any one time, for a total of 48K.

That’s a respectable amount of computing power even for a desktop micro. Of course, adding those external modules onto the HHC eliminates its hand-holdability, but the unit is still quite portable.

In fact, Quasar sells an attache case to go along with the HHC and its accessories which include, besides a dot-matrix printer and a cassette interface, an acoustical modem, color-TV adapter and an RS-232C interface.

The result is a hand-held computer that can tie into any of the popular telephone-line data banks (like The Source, CompuServe or Dow Jones) or carry on a discussion with your company’s big mainframe from anywhere in the world (even a public phone booth) or can interface— through the RS-232C—-with any of hundreds of other peripherals manufactured by scores of companies.

Power for all of this is handled through the HHC itself, which utilizes 12-hour rechargeable Ni-Cads that are good for up to 600 hours, depending on accessory control and programming applications. Only the color-TV adapter (which produces displays in eight colors) requires AC power.

Like the TRS-80/PC-1211, the HHC is on even when you’ve shut it off. This means that what you’ve placed in memory remains there until you decide to change it, even if you accidentally hit the Off key. The unit also has an automatic shutdown after about ten minutes of inactivity.

Among the HHC’s other advantages is a built-in real-time clock that allows you to use the unit as an electronic secretary to remind you of appointments and important future dates. It does this, regardless of what mode you’re in, with a musical tone. You may continue with whatever you were doing or acknowledge the tone and check the secretary files.

Additionally, all 65 keys on the keyboard can be redefined, virtually customizing the computer for any individual need.

About the only complaint of substance concerns the HHC’s editing and debug features. For starters, there are two different editing procedures, depending on whether it is a text (the kind you would put into the secretary) or a program file.

The program files are listed in two menus but can only be changed from one (the BASIC menu).

The text file editor is easy to use, but the BASIC file editor is complicated by the software’s inability to move backward through a program. On a regular computer, this would be no particular problem, but keep in mind that the HHC’s 24-character display—like the TRS-80/PC-1211— shows only one line at a time. And unless you personally have a real good memory, you’re out of luck.

This problem, however, can be greatly alleviated through the use of the TV hookup, since the HHC then displays 16 lines at a time.

Also, data entered into a text file is not accessible by the BASIC language. As such, your programs can’t obtain any information you’ve put in this file. More-sophisticated users can, however, access these text files by using a language called SNAP, which also is available with the HHC.

Since there seems to be no end in sight to computer miniaturization, a fond dream of science-fiction writers is rapidly becoming a reality. By the year 2000, there seems to be little doubt that you’ll be able to hold in the palm of your hand a computer as capable as the most powerful machines now on the planet.

Couple this with such technical abilities as modern satellite communications and it’s quite possible that the sum total knowledge of the human race could eventually be at the tip of your fingers.

view additional pages

THE OVSHINSKY INVENTION

By Norman Carlisle

Is it greater than the transistor, or is this self-taught engineer a fraud as the big companies claim?

Everyone knew that glass was an insulator, not a conductor of electricity. Everybody, that is, except a controversial independent inventor named Stanford Ovshinsky. To the consternation of orthodox scientists he’s found a way to turn glass into a conductor—a discovery that may rival that of the transistor effect.

At least that’s what Ovshinksy and a number of fellow scientists and engineers claim, thereby starting a red-hot hassle among scientists.

Ovshinsky’s defenders maintain that in the “Ovshinsky effect” he’s hit on something completely original. Something big enough, they maintain, to create a second transistor revolution that will lead to the dreamed-of flat screen TV that will hang on your wall and a computer small enough to wear like a wristwatch.

Scoffers—among them many researchers for the nation’s big labs—say he’s claiming something they knew about all along. And that, anyway, it won’t work—at least not like he says it will.

“Sure they say that,” say Ovshinsky supporters. “It’s just sour grapes.”

Their chagrin in not having hit on the discovery first, if that’s what it is, is understandable if Ovshinsky’s claims work out as he vows they will. For what he has developed is a kind of device that will permit smaller, faster, simpler, and more reliable electronic circuitry than that made possible by that electronic marvel, the transistor. And what’s more, it’ll do it for far less than even the ever-decreasing cost of transistors, which use relatively expensive materials.

Ovshinsky’s transistor-like devices can be made of low-cost, easily-produced substances —like glass, for instance—which can be used to make “print on” conducting devices. A thin film of his semi-conducting material deposited on wire, metal blanks, or plastic sheet will create the equivalent of a transistor, opening up many design possibilities.

One thing that makes fellow scientists raise their eyebrows over Ovshinsky’s accomplishment is the fact that he doesn’t have a degree to his name. Following his graduation from high school, he had a few months of training at a trade school in Akron, Ohio, and then went to work in a factory as a machinist. In his early twenties he brashly announced that he knew a better way to make a drive for a particularly complicated machine.

Engineers laughed at this green kid, but they didn’t laugh long. He came up with a design involving electrical, hydraulic, and pneumatic servo-mechanisms that actually worked.

Before he was thirty, Ovshinsky was president of a big machine tool company. His machine became standard in the industry during the Korean war when it proved that it could turn out shell cases ten times faster than any other.

For all his success, Ovshinsky felt restless and confined inventing for other companies, even ones he had an interest in. He kicked over the traces to tackle the Big One, the idea that glass and related materials might be used in transistor-like devices. The problem facing him looked insurmountable. In the crystalline substances from which transistors are made, such as germanium and silicon, current is easily controlled because these materials are structured in neat lattices through which current can be made to flow predictably.

Materials like glass would never have anything like the transistor effect, most scientists were sure, because they are disorderly in structure, jumbled into helter-skelter arrangements. Surely, in such materials, electrons would be so isolated from each other that they could not join up to move in a steady stream, as required in transistors.

Ovshinsky had a bold idea about that. Maybe those disordered materials had a property nobody had really checked out. Perhaps there was some way to bring “short range order” into them. Suppose you shot an electric current of just the right voltage into them. Might it not change the material, per- mitting the electrons to join up and flow as a current?

After thousands of mathematical calculations and lab experiments, Ovshinsky emerged with the announcement that he had established the existence of the “Ovshinsky effect.” In layman’s terms it boils down to this: when you apply a certain voltage to a material of a given chemical composition, this material will be affected by this current and turned into a conductor.

The result is embodied in “Ovonic Switches,” for which the inventor has been granted patents. They are now being turned out by Ovshinsky’s company, Energy Conversion Devices, Inc., in Troy, Mich.

One type is the Ovonic Threshold Switch. It switches from blocking a current to conducting it in 150 trillionths of a second. The switch keeps conducting as long as the current through it exceeds a certain voltage. When the current drops below this voltage, the switch again blocks current rather than conducting it.

A second Ovshinsky invention is the Ovonic Memory Switch. It operates like the Threshold Switch, but it remains in the conducting condition even when the current is turned off. A pulse of electricity is required to convert it back to the blocking state. Ovshinsky sees it as being the “perfect” memory unit for computers. One of its main advantages is the fact that it’s blackout proof; it isn’t affected when the current goes off. Therefore a computer using Ovonic switches wouldn’t lose its memory in power failures, as many did in the big Northeastern U.S. blackout of ‘65. (Continued on next page) All Ovshinsky switches have a property transistors lack. A transistor sends current in one direction only and therefore operates on D.C. or requires special adaption to operate on A.C. Ovonic switches operate on A.C., which makes them ideal for home use, Ovshinsky asserts. The inventor pictures small, cheap computer control units that will do the thinking for all kinds of household appliances—like, say, robot vacuum cleaners and lawnmowers.

Is Ovshinsky’s invention as big as many claim it is? Will Ovonic switches create, as Ovshinsky believes they will, a second transistor revolution? Will the scientific critics who say it really isn’t all that great be proved wrong?

Ovshinsky isn’t worried about the answers. His switches are being tried out in military hardware and a number of consumer products. Ovshinsky shrugs off the skeptics who doubt that they’ll really work.

“We’re going to prove that,” he says, with the confident smile that befits a man who’s sure he has invented something bigger than the transistor. •

IF

• you’re weary of matching one assembler instruction per one machine language instruction.

• you’re spending half of your machine time translating compiler programs into machine language programs of questionable efficiency.

• you’re using up time and money with hunt-and-peck machine language debugging and reprogramming.

• you’re tired of seeking, teaching or even becoming a bilingual programmer—fluent in both problem and machine languages.

• you’re fed up with programming methods that are cumbersome, time-consuming and costly.

Then, you’ll be interested in Burroughs B 5000, a new kind of information processing system which is the result of a total departure from traditional computer design concepts. A system in which software dictates equipment designs and specifications to bridge the communication gap between man and machine.

As a problem oriented system, its software capabilities accept ALGOL and COBOL statements directly because its logic matches the logic of problem-language programming. Instead of an instruction-address-instruction-address sequence, there’s a continuous flow of instructions with table references when addresses are required. Addresses are independent of instructions.

The system language is designed to implement the problem language for extremely rapid translations allowing program translation each run. Object programs, as efficient as those written in machine language, can be created far faster than with the most advanced conventional computers.

The need for the programmer to know both problem and machine languages is eliminated. Now for the first time, the programmer is free to concentrate on the processing problem itself. Free of the gymnastics he used to employ to make his problem acceptable to the machine, he merely states the problem and the Burroughs B 5000 provides an efficient, rapid solution.

Burroughs Corporation, Detroit 32, Michigan Burroughs Corporation

Also be sure to check out the other great computer article from this issue: “The Chip”

view additional pages

HIGH TECH, HIGH RISK, AND HIGH LIFE IN Silicon Valley

By MOIRA JOHNSTON

Photographs by CHARLES O’REAR

SILICON VALLEY appears on no map, but this former California prune patch, an hour’s drive south of San Francisco, is the heartland of an electronics revolution that may prove as far-reaching as the industrial revolution of the 19th century.

It is a place where fast fortunes are made, corporate head-hunting is profitable sport, and seven-day workweeks send cutting-edge technology tumbling over itself in its competitive rush to the marketplace.

Not surprisingly, flying—fast, challenging, and risky—is a sport that appeals powerfully to Silicon Valley men such as Bob Noyce, who snatches every chance to fly his twin-engine Turbo Commander to Aspen to ski, to his Intel plant in Phoenix, or just to wheel in the sky around Silicon Valley.

At age 54, he is one of the grand old men of an industry so young that its pioneers are scarcely in their 50s, yet so powerful that it is fast becoming known as the oil business of the eighties. Noyce had a key role in inventing the integrated circuit, the tiny computer chip that is the brains and basic building block of virtually all of today’s electronic equipment, providing the quantum leap that created much of the wealth that spreads below his wings in a golden tide of purring Mercedes-Benzes and half-million-dollar homes in the hills. From the air the valley itself, with its grid of roads and rectangular buildings, has taken on the look of an integrated circuit.

Fifty years ago it was a landscape of orchards supplying half of the world’s dried prunes. Even through the sixties, it bloomed with plums, pears, apricots, and cherries, one of the nation’s most bountiful agricultural regions. Today only 13,000 acres of orchards survive out of an original 100,000. By the late 1960s, as industry surpassed agriculture as Santa Clara County’s economic base, buildings of the valley’s many semiconductor companies were beginning to fill the region from Palo Alto to San Jose, named in 1980 as the nation’s fastest growing city.

Yet this dynamic growth happens behind a deceptively sedate facade. Driving through Silicon Valley, I am flanked by a monotone sprawl of low rectangular buildings, on which corporate nameplates display fusions of high-technology words that give few clues as to what goes on inside: Siltec, Avantek, Intersil, Signetics, Intel, Synertek. Inside, an intense concentration of brains, innovation, and enterprising zeal creates products that have captured one-fifth of the estimated 16-billion-dollar worldwide semiconductor market. And, despite recession, more of the aggressive little start-up companies that are the valley’s backbone are constantly being born.

Befriending the computer, and putting it to work and play in daily life a decade before most of us found the courage to touch a keyboard, Silicon Valley and its families may well be a glimpse of a computer-and-communications culture that is the prototype of the future.

The freewheeling egalitarianism that has replaced the rural pace is nowhere more visible than at Intel, one of the valley’s most innovative semiconductor companies. Leisure-time pilot Bob Noyce, a physicist, and Gordon Moore, a chemist, run Intel from modest cubicles separated from a surrounding sea of cubicles only by head-high movable partitions. Here, at the highest executive level, sport shirts and accessibility have replaced corporate pinstripes and wood-paneled boardrooms. Noyce says of his Spartan habitat, “It makes you feel as if you’re in touch with what’s going on.”

The “Intel culture,” as they call it, fanned with messianic zeal by co-founder Andy Grove, has produced the microprocessor, an all-purpose “computer on a chip” that can be adapted to infinite uses, the chip that opened the era of personal computers.

This innovative spirit not only is the life-blood of Silicon Valley but also may be the key to its survival in an increasingly intense trade war with Japan, the competitor it perceives as a mortal threat in the international marketplace. Maintaining Silicon Valley’s creative lead as chips grow so complex that computers increasingly help design them is one of Noyce’s principal challenges. With a certain wistfulness for the days of the individual breakthrough, he says, “Now it’s a team effort. In 1970 Federico Faggin designed the 4004 microprocessor chip by himself at Intel in nine months; our 32-bit microprocessor took 100 man-years!”

But the individual can still star as an entrepreneur. Competitive energy vibrated from Sandy Kurtzig as she told me, “I have taken a bet that ASK Computer Systems will be doing 100 million dollars in annual sales in four years. We will.” Sharing a quiet brunch after tennis with her husband, Arie, a research manager at Hewlett-Packard, and their two young sons, this lively brunette in slacks and sweater is president of ASK, which she founded with $2,000 in the back bedroom of her apartment in 1972. Since ASK went public last year, the worth of the company’s stock has soared to more than 75 million dollars.

Sandy, 35, entered the industry with a mathematics-and-chemistry degree as well as a master’s in aeronautical engineering. Aware of the nation’s productivity crisis, she shrewdly saw that “the technology of the chip had far outstripped our capacity to put all that potential to work.” Sandy targeted software, the programs that tell computers what to do. She developed software systems for minicomputers and sold them as easy-to-use packages to accomplish tasks such as inventory control and accounting in manufacturers’ factories and offices. Her strategies have been so successful that, while chip stocks plunged in 1981, ASK’s rose to make the firm perhaps the nation’s fastest growing public software company.

Yet Sandy, like most of Silicon Valley’s successes, does not wallow in hedonistic excess. True, she recently purchased a baronial Tudor-style home, but says, “We didn’t buy the house to show off. It was mainly to be on the flats where the kids could ride their bicycles.”

But in a valley characterized by venture capitalist Don Valentine as “a pocket of entrepreneuring that attracts a breed of buccaneer capitalists and high-risk takers—an area barely big enough to contain the egos,” there are some Silicon Valley winners who revel in flamboyant display.

“Money is life’s report card,” says a laughing Jerry Sanders, a street-wise kid from Chicago who parlayed an engineering degree and intuitive salesmanship to the presidency of Advanced Micro Devices (AMD) and to a reputation as the valley’s highest flying businessman. Exuding brio and self-confidence, he measures his success in a string of homes, hand-tailored suits, a Rolls-Royce, and a Bentley. In good years he makes grand gestures to employees: a $350,000 Christmas party in San Francisco’s Civic Auditorium; in a lean year he served hot dogs and sauerkraut with panache that won cheers.

But for Sanders, as for Silicon Valley, work is the thing. The valley was born in 1955. Dr. William Shockley, Nobel Prize-winning co-inventor of the transistor at Bell Telephone Laboratories, sent out a call to a dozen handpicked young Ph.D.’s in physics and chemistry to join him in a warehouse in Mountain View, at Shockley Semiconductor Laboratory.

Noyce and Moore answered the call. There they would exploit the properties of silicon, a semiconductor of electricity whose conductivity could be modified by the addition of minute amounts of chemicals, allowing on-off electric signals—the very basis of computers—to occur at mind-boggling speeds. As transistors replaced vacuum tubes, the computing power of an unwieldy roomful of metal boxes ultimately could be contained in a hand-held calculator.

Ironically, Shockley’s pioneering laboratory failed. “His ideas were too far ahead of the still primitive silicon technology, and he never produced a manufacturable product. What he did was to spawn Silicon Valley,” says Shockley alumnus Harry Sello. Believing they had something—a better transistor—Noyce, Moore, and six others got financial backing from Fairchild Camera and Instrument to develop it. Since the founding of Fairchild Semiconductor in 195 7, the valley’s first viable semiconductor company, no fewer than two dozen companies have spun off from it, including the present leading triumvirate: Intel, Advanced Micro Devices, and National Semiconductor, all started by former Fairchild men.

The start-ups and spin-offs could never have flourished without infrastructure, the valley’s vital support system that has built up south of Stanford University. Born before Silicon Valley, it began in 1939 with Hewlett-Packard, granddaddy of the area’s electronics firms. Today it is an incestuous network of suppliers, customers, venture capitalists, brains, research institutes, computer and software companies, schools, and headhunters, the executive recruiters who move men around the valley at a dizzying rate in a tradition of musical jobs that is a key to the valley’s contagious vitality.

With the convergence of infrastructure, innovative minds, and venture capital in the sixties, dramatic improvements in integrated circuitry (which basically masses many transistors on a single chip) brought prices plummeting. Noyce and Moore sold their first transistors to IBM for $150 apiece; today the price would be a fraction of a penny.

Toward a More “Personal” Computer

Steve Jobs is pleased with the falling prices. He hopes that his computer will become the Volkswagen of the industry, the computer every family can own. The 27-year-old co-founder of Apple Computer, whose typewriter-size instrument is pioneering the incorporation of the computer into daily life, bristles a little, too, as he reminds, “We’d rather call the Apple a personal than a home computer.” Although 1981 and 1982 have been the “years of the personal computer,” with giants like IBM jumping into the market and about two million now in use in the United States, predictions that computers would be the nerve centers of our homes by the early 1980s have proved premature.

“It’s no more difficult than learning to cook, but people are afraid they can’t handle it,” says Jobs’s Silicon Valley neighbor Dan Fylstra, whose VisiCorp software packages are simple enough for use in the home. The machines are just not yet “user friendly” enough. Though research labs all over the valley are struggling to solve the elusive problem of speech recognition, we are a long way from marketing a computer that can respond to ordinary conversation—the ultimate friendliness.

So Jobs and his growing host of competitors have directed their sales efforts to office uses. But the Apple has inspired a dedicated cult of hard-core enthusiasts who trade new uses for the computer in the columns of Apple magazines; one engineer has programmed his Apple to activate a small motor that rocks the crib when his colicky baby cries or wriggles. And Jobs has become a potent role model for a new breed of bright kids who are writing and selling software programs and, with their arcane computer skills, gaining the prestige formerly tasted only by the high-school football team.

Over herb tea in a vegetarian restaurant, Jobs explained to me, “For us, computers have always been around. That’s what separates us guys from you guys. You were born B.C.—Before Computers. And it’s because of this place. I was born here. When I was 14,1 was asking famous computer engineers here questions. Apple came out of the microprocessor, created in this valley just five miles from here.”

Jobs’s passion has paid off handsomely. With Steve Wozniak he built his first Apple in 1976 in his parents’ Los Altos garage because they couldn’t afford to buy a computer; now he owns Apple Computer stock worth 100 million dollars. While the chip companies suffered this spring, Apple’s revenues soared 81 percent over last year’s. Apple now occupies 22 buildings in Silicon Valley and plants in Texas, Singapore, and Ireland, which is bidding to become Europe’s Silicon Valley.

Although Jobs drives the requisite Mercedes, success seems not to have spoiled the first folk hero of the computer age. In plaid shirt and jeans, he still prefers, as a friend said, “to drive his motorcycle to my place, sit around and drink wine, and talk about what we’re going to do when we grow up.”

The excitement of Apple’s presence in Cupertino has touched the district school system. Here children are introduced to computers as early as the first grade.

Bobby Goodson, the school district’s computer specialist, believes computer literacy is going to be the next great crisis in education. “If kids don’t understand computers, how can they handle the future?” she asked, as she restrained a class of seven-year-olds eager to get their hands on a computer for the first time.

A little girl with pigtails hunches over the keyboard, fiercely concentrating on following Mrs. Goodson’s instructions. “Type in ‘10 PRINT “BARBARA.” ‘ Now type ‘RUN.’” Her name pops up on the screen. Bouncing with delight, she rushes ahead to execute the next instruction. Barbara fills the screen and begins repeating in relentless rows. Barbara looks up, awed by her own power. She has entered the computer age with the ease of skipping rope.

“The broad integration into society, though, is going to be a 10- or 15-year process,” says Jobs. “But I believe we are already making a little ding in the universe.”

Not All Share the Good Life The social impact and the profits, Jobs notes, scarcely touch the lives of the 120,000 people who work on Silicon Valley’s assembly lines. Most of those who live in ethnically mixed east San Jose—black, Hispanic, and about 18,000 Vietnamese and other Asian refugees—cannot afford to own a home.

But the opportunity that lures entrepreneurs gives some workers, too, a crack at the California dream. Secure in a comfortable home in Cupertino with her husband —Thanh, a computer engineer—Tien Nguyen, a gentle beauty with lush black hair pulled into a topknot, relives her escape from Vietnam in 1975.

“We left with nothing. I had just the slacks and blouse I had on. My father feared that when the Communists came, they would kill the whole family. The police put us—my parents, my three sisters, my younger brother—on a barge in the Saigon River with no shelter, no food, no drink. A tugboat pulled us to the open sea to an American ship we shared with 20,000 people. We slept on deck. My older sister, Dao, almost died of flu.”

Brought to Silicon Valley by the pastor of a suburban church, Tien and Dao had assembly jobs within ten days. They found the route to upward mobility, the valley’s electronics schools, and soon moved up to better jobs at Tandem Computer.

“We delivered papers after work and put our father through electronics school, and he has a job now with a valley electronics company,” Tien says with pride.

The sisters have been upgraded again to office jobs at Tandem. But their smiles and chic clothes screen a deep homesickness. “But I feel strong,” Tien says. “In my country I would stay home and cook. Over there I couldn’t interface with all these people”— the local buzz word that reveals how well she has, well, interfaced.

Even Light Industry Brings Pollution But the job growth that gives the Nguyen family a chance to prosper is compromising the sweetness of success. Straining from a small aircraft to see through the opaque veil of pink-brown smog that obscured the low mountains that flank Silicon Valley, county planner Eric Carruthers cracked to me, “On a clear day you can still see it’s a valley.”

Most of the smog is belched from automobiles. Below us, as rush hour began, rivers of red lights ran south, as Silicon Valley disgorged a quarter of a million people to housing tracts 10 and 20 miles away. “Jobs have grown faster than housing,” Carruthers said. In 30 years San Jose has grown from 95,000 to nearly 660,000.

To deal with such growth, Santa Clara County has embraced a new program for systematic regional planning that it hopes will replace wanton expansion. And the need is urgent. The county recoiled this past winter when it was revealed that hazardous chemicals from 11 of the valley’s major electronics firms had leaked from buried tanks and, in one instance, contaminated public water.

Voicing the shock shared by cities that had assumed the electronics industry was nonpolluting, San Jose’s mayor, Janet Gray Hayes, said, “I remember thinking about smokestacks in other industries. I didn’t expect this problem in my own backyard.”

The county has proposed to have the cities use their powers to limit new jobs as a means of curtailing housing expansion. As mayor of Sunnyvale, Dianne McKenna joined her city council in declaring a four-month moratorium on new industrial building, during which limits were voted on waste water and the number of employees per building for new plants.

Campaigning against the runaway growth that threatens the quality of life that once inspired the nickname Valley of Heart’s Delight, Pulitzer Prize-winning novelist and 37-year Santa Clara County resident Wallace Stegner cautions, “It happens slyly. You see an orchard go next to you, but there are still a lot of orchards. Then it becomes catastrophic.”

“The problems are the growing pains of any community that grew fast after World War II, plus the breakneck speed of change in Silicon Valley companies,” says Bob Kirkwood, Hewlett-Packard’s manager of government affairs. “The start-ups of the 1960s are just beginning to have the luxury of lifting their heads to look around.”

As they do, some have gained a special view of the universe. Cherry Lorenzini, whose husband Bob’s company, Siltec, produces the silicon wafers from which chips are made, says: “I can point out a satellite to my kids in the night sky and say, ‘You know, there might be some of our silicon up there.’ ” Proud of her role, she says, “For a man to reach his moon, he needs a support team. Bob designed his first crystal-growing furnace on our dining-room table. We were the little guys going in and eating up the competing companies. His dream was to take Siltec from scratch to SO million dollars; now the goal is ISO million. But for the men in this industry, it’s total dedication,” she adds. “I merged my dreams with his, but many women can’t accept their limited roles in their husbands’ lives.”

There are other problems. “It’s a tremendously striving, intellectually oriented population. They tend to be workaholics who can fall prey to alcoholism, divorce, and depression,” says Dr. Rudolph Grziwok, director of the county’s Fairoaks Mental Health Center in Sunnyvale. “Burn out” has become a common valley syndrome, for not all can maintain the winner profile.

In this environment, relationships can suffer. Driving home in his Mercedes-Benz from his weekly dance class, one of the valley’s brightest engineers said: “Stars are rewarded. There are stock options—you’re riding in one! And my house is another. But you’ve just seen my social life. The projects are incredibly interesting, but they’re on your mind seven days a week. Relationships get screwed up. Somebody who was very important to me met somebody who didn’t work every weekend, and that was it.”

Pressure Spawns Drug Abuse

For those on the assembly line, the stress shows in drug abuse. Marijane Esparza, an instructor at a San Jose drug rehabilitation center, described the vicious cycle that gripped her for several years as a board stuffer, soldering chips to the circuit boards that are inserted into computers.

“You start on drugs because the job’s so boring, hour after hour, and you don’t even know what the board is for. You take ‘crank’ [amethamphetamine] and you feel a flash of energy—zzt, zzt, zzt—and do you work!

You do twice as many boards! Then, the technician standing behind you says, ‘Hurry up, you did 100 boards last night.’” The pressure to maintain the drug-induced productivity rate, she and others fear, encourages the use of drugs.

Theft, an estimated third of it to support the drug habit, has been growing by leaps and bounds, according to Patrick Moore of the organized-crime section of the county sheriff’s office. Greed has created an illicit market for the chips, as well as for the tapes and masks from which they can also be copied (page 458). A stolen chip design can save a corporation or nation ambitious for advanced technology millions of dollars and man-years in research and development.

“Integrated circuits are small, extremely valuable products,” says Moore. “Someone can walk out with a fortune in his fist.”

The largest haul yet occurred over the 1981 Thanksgiving weekend—3.5 million dollars in chips from Monolithic Memories. “Truckloads!” said an astonished Doug Southard, Santa Clara County’s deputy district attorney, as he prepared his case against two men arrested. The spectacular recovery of the chips in South Lake Tahoe this past spring confirmed Southard’s suspicions of a connection with the 1980 theft of 11,000 memory chips from Synertek. “It’s organized crime—with a small ‘o.’ Not Mafia, but well-organized rings. The common thread is drugs and violence,” he says.

International Duel Heats Up Other thefts being investigated are increasingly casting the specter of international industrial espionage over Silicon Valley.

“The Japanese are coming awfully close to copying our chips,” said Roger Borovoy, Intel’s chief counsel. “They can buy them off the shelf and make detailed photographs of them without breaking any law. But if we get our hands on a copied chip, we’ll sue!”

It was computer software, not chips, however, that made headlines this year, when the FBI in San Jose and San Francisco arrested nine people, most of them employees of Japan’s Hitachi and Mitsubishi industrial giants. The nine and a dozen other Hitachi and Mitsubishi employees in Japan were charged with attempting to buy stolen data concerning IBM’s new superfast 3081 computer from undercover FBI agents.

The power of the Japanese electronics industry had already been reflected in the tear-soaked balance sheets of Silicon Valley. In 1981, before Silicon Valley had one on the market, the Japanese cornered 70 percent of the world market for the 64K random-access memory (RAM) chip—most of the other 30 percent going to non-valley competitors Texas Instruments and Motorola. The 64K RAM—four times as powerful as the 16K RAM it supplanted—can handle 65,536 bits of information (1,024 per K). Minuscule though it is, the 64K chip, and the early Japanese domination of its sales, will be remembered in Silicon Valley as the technological equivalent of Pearl Harbor.

A conjunction of events—the 64K RAM, the international recession, corporate price wars—sent the valley’s semiconductor profits plunging.

Frustrated but irrepressible, the valley responded with the esprit and determination of wartime.

Lobbying in Washington, Silicon Valley leaders bemoaned the lack in the United States of a national industrial policy similar to that of Japan, which throws its resources behind specific areas, such as chips.

AMD’s Jerry Sanders fumed, “I just don’t want to pretend I’m in a fair fight. I’m not. The Japanese pay 7 percent for capital; I pay 18 percent on a good day. They get hundreds of millions of dollars of free R and D [research and development] paid for by their government. Then their products arrive here in a flood.”

As the trade war escalated into a critical test of the two cultures, Silicon Valley became a metaphor for the American way. “We’ll outcompete the Japanese in the marketplace,” asserted Harry Sello. “After all, we Yankees invented competition. Against the Japanese companies, we offer superiority in infrastructure, software, and, above all, innovation.”

Carrying that confidence into the enemy camp, Intel aggressively launched an advanced new memory chip in Tokyo, breaching the Japanese market, and, this spring, fired its 64K RAM into the fray, announcing, “They’ve won the first skirmish, but we’ll win the war.”

The Valley’s Pulse Beats On But Silicon Valley’s power was being assaulted by other forces. The need for capital to sustain growth is forcing many of the smaller companies to sell out to major corporations, a move an industry financial specialist, Sal Accardo in New York City, believes may strip the valley of its “flair, drive, and creativity.”

And by fouling its own nest with pollution, congestion, and soaring housing and labor costs, Silicon Valley is forcing industry out. Charles Sporck, president of National Semiconductor, flies regularly to Malaysia and Arizona to visit his assembly plants. Apple’s Jobs flies to a June board meeting in Ireland.

Yet Apple and Intel are still headquartered here. Giants like IBM and Hewlett-Packard are committing themselves to expanded research facilities in Silicon Valley. And profit-driven investors are pouring capital into a buoyant new wave of chip, computer, and software companies, the definitive act of economic faith that, in the words of Sal Accardo: “Silicon Valley will continue to be the cerebrum, a magnet for creative minds.”

Related posts

• Byte review of the original Macintosh (Oct, 1982)
• Apple’s Enhanced Computer, the Apple IIe (Oct, 1982)
• The Lisa Computer System – Apple designs a new kind of machine (Oct, 1982)
• A behind-the-scenes look at the development of Apple’s Lisa (Oct, 1982)
• New Personal Computers — now the big guns have arrived (Oct, 1982)
• Apple Ad: What kind of man owns his own computer? (Oct, 1982)

view additional pages

How the Computer gets the answer

Photographed by HENRY GROSKINSKY
Text by ROBERT CAMPBELL

Step by step, an easy exercise reveals the workings of man’s most complex machine Two plus One—not exactly a problem to set the mind racing or to blow a computer’s fuse. Yet it is enough to send electric pulses flying through the computer’s intricate web of wires. Although we are barely in the third decade of the computer age, computers already touch the life of everyone in the U.S. Each year—each day—our involvement with these machines rises toward unimaginable levels. It is a commonplace that if it weren’t for computers we couldn’t fly to the moon, or even keep an accurate record of the national debt. On the question of how it does what it does, however, the computer has always remained essentially mysterious—unfathomable to all but a small handful of initiates. An officer of one major computer concern guessed recently that not more than 2% of his employes really know how it works.

On the following pages Life presents a computer primer which, with the help of models, shows clearly what goes on inside a computer as it tackles one simple problem in addition. In just the same distinctively straightforward fashion, the computer would approach any problem, no matter how complex. On the pages following the problem, a new-style computer is opened up for inspection, with a close-in view of some of its sophisticated and surprisingly beautiful components.

Despite all recent improvements, a computer still cannot “think.” It can, in fact, do only three rather simple things, but it can do them superlatively well: 1) it can retrieve almost instantly any stored piece of information—the cost of the item you charged at the department store this morning, a number needed to calculate a rocket’s trajectory; 2) it can compare two numbers and perform any mathematical operation with them—add, subtract, multiply or divide; 3) it can perform any combination of these functions in a specified sequence—a program—without additional human intervention. The paradoxical essence of a computer is its simplicity: it takes but a single step at a time. When it completes one tiny operation, it goes on to the next and then to the next, all at bewildering speed, until finally it gets the answer—in this case 2+1=3.

‘On-off’ language feeds in the data and instructions

The modern digital computer, whether it is used for routine bookkeeping or for complex scientific calculations, is composed of half a dozen basic elements. The same elements form the components of the ingenious photo models shown here and on the following pages. Like its big electronic brother, the model is constructed to handle a variety of calculations. In the case at hand it will tackle the problem of adding 1 and 2. As the model proceeds toward the answer, it will reveal how a big digital machine moves step by step toward its own solutions.

The first requirement of any computer is an Input—a means of feeding into the machine the information, data and instructions it will need to solve a problem. This can be done in a variety of ways, including magnetic tape, an electric typewriter hooked into the computer, or the familiar punched “do-not-fold-mutilate-or-spindle” card shown in the photo model, on which information is contained in coded holes punched in the card. The Input must be translated into language the machine can understand. This process and the language involved will be explained further on, but the step is symbolized here by the glowing disks labeled “Encoder.”

Information that is put into the computer must be stored someplace until the machine is ready to make use of it. This is the function of a computer’s Memory section—represented here by the vertical boxes.

Then, when the computer begins to work on the problem, an Arithmetic unit—which actually does the calculation—comes into play. So also does a Control system to govern the machine’s sequence of operations. (Both these elements appear on the next page.) After the problem has been solved and the answer stored (suggested here by the Answer box), the computer must then reverse its opening procedure. It must retranslate its machine language and display the answer in a form the person who presented the problem can understand.

The first problem, obviously, is language. How does an electronic instrument handle and manipulate numbers?

The answer is suggested by the nature of all electrical devices: a light bulb is either on or off, a switch is either open or closed, a magnet has a field in one direction or the opposite. For the purpose of understanding computer language, one can think of the “on” condition as being equal to 1 and the “off” state as 0. So the computer, which is made up of literally millions of electronic components, has two numbers it can work with. These numbers, 1 and 0, form all the elements needed in the binary system of notation.

In our more familiar decimal system, the right-hand column of a figure counts numbers up to 10; the column to the left of that registers the number of 10s; the column next to the left registers hundreds—then thousands, millions and so on. In binary notation, the columns starting at the right register powers of 2 instead of 10. Take the binary number 10110, with the successive powers of 2 noted above each column: 16 8 4 2 1 10 110 Adding together the powers of 2 turned “on” in this binary number —16, 4 and 2—we arrive at its decimal equivalent—22. The first eight decimal numbers, translated into the binary system look like this: 1=1 5= 101 2= 10 6= 110 3= 11 7= 111 4 = 100 8=1000 In a real computer (which would encounter the decimal number 6 as a series of pulses —”on-on-off”) binary coded information is stored electronically in memory units of enormous sophistication.

Instead of electric pulses, however, our model uses colored disks, with red disks representing 1 (or “on”) and the blues 0 (or “off”). Our Memory unit is a series of simple boxes—but the principle is exactly the same. The boxes in the model have room for “words” of exactly five binary digits—or “bits”—but this is, in fact, large enough for the model to add together any two numbers whose total is not larger than 31. The binary number system can provide more than pure numerical data for the machine. Depending on an agreed-upon code, the combinations of bits can stand for letters of the alphabet, symbols, punctuation marks and so forth. Instructions to the machine are also given in abbreviated binary form. A relatively brief “word” can tell the computer to take two numbers stored in its memory, add them together, subtract a third number from the total and store the result.

The photo model follows this arrangement exactly as it proceeds with the task of loading in the data and instructions it will need to solve the problem of adding 1 and 2. The data, in this case the two numbers we wish to add together, goes in first. The Encoder translates the two numbers into binary notation, using red disks for 1 and blue disks for 0. Thus the number 1 is stored in Box 5 of Memory as a five-bit “word” consisting of a red disk followed by four blue ones. Into Box 6 goes the number 2—a blue disk, a red one and then three blue disks as indicated by the data key. Each piece of information that enters a computer is allocated a specific place in the Memory bank, so that the human operator of the machine can later direct the computer to go back and get it.

With the data stored away in the model’s Memory, the machine needs instructions as to what should be done with it. These instructions are entered in the Memory boxes numbered 1 to 4. Each five-bit instruction consists of a three-bit Box Address number telling where to find the needed data, and a two-bit Operations Code which specifies what should happen to the data. In the Address section of Box 1 are a red, blue and red disk, the model’s binary code for the number 5. In the Operations section are two red disks that, as indicated by the key, mean “add.” In the language of professional computer people, Box 1 now contains the cryptic directive: “Add 5.” What the instruction really means is: “Take the contents of Box 5 and carry it to the Arithmetic unit for addition.” Box 2 holds a similar instruction regarding Box 6. Boxes 3 and 4 contain instructions on where the computer should store the answer once it has been obtained, and how the answer should be displayed. These two operations will be explained on the next page.

The instructions as to how to proceed are long and very detailed, for this model and all real computers are excessively simple-minded. They must be guided every step of the way. But they are also indefatigable and will follow the instructions endlessly, until the problem is solved.

Like the family dishwasher, our model is now loaded with everything it needs to cope with the problem—both data and the instructions it needs. When the button is pushed no further human intervention will be necessary.

A model train tracks the route to a solution

The model train on these pages shows how a real computer carries out its task. The tracks, turntables and cranes of the railroad system are remarkably similar in function to the wiring and elaborate electronic switching circuits of a modern digital computer. Furthermore, the train will accomplish the task of adding 1 and 2 in almost precisely the same way that a computer would add any two numbers: taking steps one at a time in an ordered sequence.

The boxes containing the computer’s Instructions, Data and, eventually, the Answer are here separated to show the actual process more clearly. The remaining major elements of the computer have been added: 1) the Control section at center makes certain that instructions are carried out in proper sequence; 2) the Arithmetic unit at lower right will ultimately combine the two numbers in our problem.

Starting at the Instructions area, the train picks up its first load, consisting of five colored disks from Box 1. These disks constitute an order: “Take the contents of Box 5 and deliver it to the Arithmetic unit for addition.” The three disks—red, blue, red—already on the train make up the Box Address for Box 5. The two red disks just about to land on the train make up the Operations Code for addition.

Thus loaded, the train proceeds toward the Control section. At the lower turntable the two red disks of the operational order are unloaded and the order “add” is read and remembered. The train moves to the upper turntable, where the Box Address is taken off. Guided by this address, the upper turntable sends the train out on Track 5 to its destination, Box 5. Here it picks up the box’s contents, which are part of the data for the problem, in this case the number 1.

With this cargo, the train circles back to the Operations Codes turntable where, remembering the “add” order already deposited there, the turntable sends it out on the track labeled “Add” to the Arithmetic unit. There five disks signifying the number 1 are lifted off and put in the Accumulator, the component of the Arithmetic unit that performs arithmetical operations. The disks arrived on the Add track, so they will be added.

Since the instruction has been carried out, the train now loops up and around and returns to the Instructions area. There it receives the orders for its second trip from Box 2. These instructions tell it to take the contents of Box 6 to the Accumulator for addition. As on its first trip, the train goes to Control where the two disks meaning “add” are first unloaded at Operations; then at the Box Addresses turntable the Box Address disks are taken off, and the turntable sends the train off on Track 6 to Box 6. Here it picks up the number 2— a blue, a red and three blue disks—and, as before, proceeds to the Operations turntable, where the instruction “add” is in force. The turntable sends the train down the Add track again, and the number 2 is loaded into the Accumulator where the number 1 was previously stored.

The Accumulator, which keeps a running tally of whatever is put into it, instantly adds the new number to the old and produces a total. In a real computer, this trick is accomplished with logic circuits. Because they are electronic and thus always either “on” (1) or “off” (0), the circuits can follow absolutely the simple rules of binary addition. Incoming pulses are combined, through the logic circuits, to produce a new condition according to this scheme: 0+0 = 0, 0+1=1,1 +0=1,1+1=10. Thus, in our problem: 00001= 1 00010 = 2 00011=3 The logic circuits can carry numbers along from one column to the next, just as in decimal addition. This would have been necessary if our problem had been 00011=3 00001 =± 00100 = 4 In the Accumulator of our railroad computer, a result has been reached by this method and is held in temporary storage.

Having completed two trips, the train is now back at Box 3, where it receives the order: “Take the number now in the Accumulator and store it in Box 7.” The two-disk signal for “store” is put down at the Operations Codes turntable and the Box Address is deposited at the Box Addresses turntable. The train then proceeds via Track 7 all the way to the Operations Codes turntable, which directs it out along the Store track to the Accumulator. Here it receives what the Accumulator has accumulated, namely two red disks followed by three blue ones. The train continues down the track to the crane beside the Answer box. Here the answer is unloaded and stored in Box 7. From there the train circles back for its final instruction, provided by Box 4. This instruction reads: “Take what is in Box 7 and carry it to the Printer.” Following a now familiar pattern, the train goes to Box 7, picks up its contents and moves to the Operations turntable and out along the Print track to the Printer where another crane waits to unload its cargo.

The real thing: tapes, cores, logic units

Once our train has carried the answer to the Printer, its job is done. It remains only for the Printer to convert the final binary number into a form that the operator can read. Using a device like the Encoder (.pages 62, 63), it swiftly does just that—and prints out the number 3 (left).

How the railroad’s boxes, turntables, track loops and other equipment look in a real computer is shown at right. This is one of the newest and most versatile machines, Model 40 in IBM’s System/360 line. It is opened up to reveal its electronic components. It would have performed each of the steps in our problem in five millionths of a second.

At the upper right is the control panel, which enables the operator to alter the program, interrupt the computer if need be or request progress reports on his problem. The typewriter console at top left can print out such reports and also provide additional access to the computer. Actually, Model 40 can take on the problems of 63 separate operators, provided each has his own device for communicating with the machine. These devices can be in the next county, the next state—or another country, for that matter.

Unlike our model railroad, which had a single group of boxes in its Memory section, Model 40 has two areas where massive amounts of information can be stored. One chassis, shown at lower right, holds permanent instructions. A second, appearing above and to the left, contains data and instructions for any specific program being run.

The permanent instructions handle operational procedures likely to come up no matter what the problem: addition, subtraction, finding the square root of a number, and so on. When one of these instructions is encountered in a program, the machine switches automatically to it to determine how to proceed. These instructions are encoded on wire-laced plastic tapes laid one on top of the other in a cartridge (bottom right). The wiring runs down each tape in vertical columns, and locations along the network are either “on” or “off.” When one of these tapes is called on, the “ons” and “offs” are read in sequence, and an instruction is produced.

For the storage of data and program instructions, a different system is used, comparable to the memory boxes of our model train. Its basic device is the magnetic core, a ring of ferrite 3/100ths of an inch in diameter (right).

Cores can be magnetized in either a clockwise or a counterclockwise direction—again the equivalent of the “on-off” or 1 – 0 binary notation. The cores are strung on frames by pairs of wires that intersect each core at right angles, giving the completed frame (or core plane) the appearance of an ambitious exercise in bead-stringing. Each of the 33,280 cores in a plane has its own “address,” determined by the two wires that intersect it like coordinates on a map. Nine core planes are stacked one on top of the other to form a core array.

There is in the first core plane, therefore, one core that is identified by a particular set of coordinates. There is another core at the same two coordinates in the second plane and one in each plane through the ninth. A reading of the stack’s nine similarly identified cores forms a nine-bit unit of information.

When information is being put into the stack, the direction of the current flow in any pair of intersecting wires sets which way that particular core is magnetized. A third strand, called a sensing wire, is woven through every core in a plane. These wires report on the magnetic state of cores when information is being taken out of the stack. The whole operation is incredibly fast: the sensing wires announce the “off-on” state of cores at the rate of 6,400 every thousandth of a second.

At the lower left is the computer’s Arithmetic unit, consisting of thousands of transistors, resistors and diodes which can perform additions at a rate of 100,000 a second. Because the Arithmetic unit can also be programmed to make certain choices and comparisons —comparing the size of two numbers and selecting the next step on that basis—it is also known as the logic unit. Behind it is the Control section of the machine— the track and turntables of our model—with panels of wiring and switching apparatus that connect all the units of Model 40 together.

A new generation of parts to save billions of a second

Components invariably betray a computer’s age, and the ones shown here are brand-new. The first machines used great banks of vacuum tubes—the kind found in radios—which took up a large amount of room, consumed enormous amounts of power and were not, by modern standards, very efficient at all. In the second generation, tubes were replaced by transistors, which were so much better in every respect that computer designers began to think about a new problem—speed. For a pulse to travel over eight inches of wire takes one nanosecond—a mere one-billionth of a second, but an interval large enough to create difficulties. More compact circuits, like the one at the left, with transistors cut down in size, shaved the distance that pulses had to travel. This process of shrinking circuitry, called microminiaturization, marks the computer’s entry into a third generation—and units on the next page represent a step further still.

The eerie interface of man and machine

Can a computing machine be taught to “think” in the broadest sense, as the human brain can think and learn? Efforts have been made in this direction, based on accumulating knowledge of how the human brain works. The brain is, in effect, a whole hierarchy of computers with much of its basic input provided by ranks of lesser computers down the line. The information gathered by the retina of the eye, for instance, is not simply shunted along to the brain. Instead, the retina acts like a tiny, highly sophisticated computer, analyzing the visual data and passing on only the significant results. In the brain itself further analysis takes place as information moves from one level to another and is processed in computerlike fashion all along the way until a unified perception results.

In a computer, electric pulses travel to specific places along specific conduits to produce their own version of a unified perception in the form of an answer. Not so in the brain. One brain cell, or neuron, may pulse another, as the electronic switches in a computer pulse each other, but the similarity ends there. Each neuron has inputs from a number of other nerve cells, so that in one way or another all the 10 billion or so neurons in the brain are interconnected directly or indirectly. The system provides whole arrays of incredibly complex feedback loops in which some cells qualify the operations of others, stimulating them to respond to certain incoming signals and inhibiting their responses to others.

Theoretically it would be possible, as one computer scientist has noted, to hook together hierarchies of computers to simulate the complex layers of the brain. The gear necessary to give this supercomputer even 1/20th of a human brain’s capacity would fill several barns. And the fact is that no one would really know how to hook together such an array. Scientists have a general idea about how the brain functions, but a wiring diagram, or anything like it, is almost totally lacking and seems likely to remain elusive for a long time to come. Even if a wiring diagram came to hand, the problem of writing a program for such a contraption would present an equally enormous obstacle. Reflecting on the difficulties, a veteran programmer said, “It takes us 15 to 20 years to program our children. And they can really learn —sometimes. But with the kind of machine you’re talking about, you would have to feed in millions of separate little things every day to equal what a child takes in. And after three years of this kind of business, it still might not have learned to reason or work out its own programs. You ask it to add 2 and 2, and maybe it says 5.”

Since “thinking” is apparently not a prospect—at least not until the brain is better understood or a major new breakthrough revolutionizes computer technology again—computers will remain painfully literal-minded. One important word in the lexicon of computer programmers is GIGO, which simply means: “Garbage In, Garbage Out”—that is, if the wrong information is put into the machine, the results will also be wrong. The computer has no sense that it is being fed garbage, and anyone who gets about much on the computer circuit is bound to hear some rich examples of GIGOism.

At Cape Kennedy some time ago a rocket rose majestically from its launch pad and headed toward Venus. But following liftoff it began to wobble uncontrollably and had to be destroyed after only 293 seconds of flight. What had happened to $18.5 million worth of hardware was that a programmer omitted a minor item from the long list of explicit instructions to the computer that was “flying” the bird.

The missed item was a hyphen, and its omission led the computer into the same sort of misunderstanding that leaving the hyphen out of a phrase involving “fifty-five gallon drums” might have on a human.

When Astronauts L. Gordon Cooper and Charles Conrad splashed down 103,miles off target on Aug. 29, 1965, it was no fault of theirs or of their computer. The flight, including reentry, was computer-guided. In determining the exact time for fir- ing retro rockets, the programmer had assumed that the earth revolved exactly once every 24 hours, whereas in fact—as we know from having to squeeze in a whole extra day every fourth year—it makes a shade more than one revolution in that time. But if you’re orbiting the earth many times and someone fires the retros exactly at 1:51 p.m., after figuring on a day of precisely 24 hours, you can wind up out of touch with the earth by a significant number of earthy miles— which is just what happened to Astronauts Cooper and Conrad.

The very simple-mindedness of the computer plays a significant part in its highly symbiotic relationship with humans. It is everything we are not. Human beings, by and large, are imaginative, intuitive, sensitive to values and occasionally capricious. A computer is none of these things. It can pay undivided attention to details that would drive a mortal right out of his mind. It can be told something and won’t forget it until told to do so. It never gets huffy. It will work on the most boring problem forever without getting overheated. It will not laugh outright at human error and will work prodigiously at any problem put to it, no matter how trivial.

People who work with computers—especially those being exposed to a machine for the first time—can become quite entranced with these qualities, finding in the computer a kind of alter ego. “Sometimes programmers just won’t go home, take a bath or anything,” reports a computer man who has got over it himself. “They’re like a kid falling in love with a hot rod. They’ll sit there working with their newfound ‘friend’ 20 hours a day, just watching the lights and drinking coffee. After a while they get to looking pale and unhealthy. They sit there fascinated and just forget to eat.”

This affectionate relationship between man and machine takes its most acute form in major computer centers, where many people learning programming and using computers come together to work with one or a cluster of the big machines. Inevitably, the idea is to think up something new for the computer to do. Here both students and instructors devise rather fanciful programs that pit the machine’s quick, literal and retentive mind against the inventiveness of humans. The results of such interaction can be quite impressive.

In one such center a game was devised with the program title of HR-3. When the operator typed in “HR-3,” five rows of tiny lights, extending across the display console of the computer, were activated. In any given row a light would go on, then out, and the light to its right would be illuminated—and so on in all five rows from one side of the panel to the other. How fast the flashing lights moved across any row was determined by a program called a “random number generator,” which has many uses in higher mathematics but was here employed to bump the lights along in random fashion. The group would bet on which row of lights would reach to the end of the console first. The winner bought morning coffee. What they had, with the aid of several million dollars’ worth of computer, was a completely honest race, which accounts for the title of the program, “Horse Race 3.”

A more complex program, which many centers worked out, involved teaching a computer to play blackjack. Anyone with access to the machine could type in the code word for the program, and the computer would type back: WELCOME TO THE GAME OF BLACKJACK.

I AM GOING TO DEAL.

WHAT IS YOUR BET?

As the game progressed, the computer also kept a running tally of wins and losses, and would report this to any individual player even if he dialed a month later. A computer never forgets.

Such gambits are generally ill-regarded by the managers and bosses of computer centers— even if the purpose is training, computer time is still extremely expensive. It is said that a general in charge of one computer discovered the continuing blackjack game and ordered it erased from the computer’s memory. This was obediently done. But the general didn’t think to have the original program classified and burned, so it was surreptitiously put back in the machine—under a new heading in the program index. It may be there today, half forgotten among programs of great national import. Which brings up the fascinating (and quite real) possibility that someday an operator who wants the latest computerized estimate of China’s nuclear capability—access Code BJ-20—will type into the machine instead BJ-21. And from the unforgetful machine will come the reply:
WELCOME TO THE GAME OF BLACKJACK.
I AM GOING TO DEAL.. .

view additional pages

Behold the Computer Revolution

By PETER T. WHITE National Geographic Staff
Illustrations by National Geographic Photographers BRUCE DALE and EMORY KRISTOF

MY WIFE IS MAD AT COMPUTERS. “Those awful machines,” she calls them. “How they mess up our credit card accounts! Imagine sending a bill for $232.24 every month for four months after you’ve paid it!”

But I’m not mad. That mixup was settled after five months; and we never did feel as computer-harassed as some Americans, notably the Kansan repeatedly reminded that his department store bill was “overdue in the amount of $00.00.” At last he too managed to pacify the computer— with a check for $00.00.

In a way though, my wife is right. After a year of looking closely at computers—at what they are doing all over the country, what they are likely to do before long, and what their effects are expected to be upon us all and upon our descendants—I must say that these machines are indeed awful, in just about every sense the dictionaries assign to that word: inspiring dread, appalling, objectionable; solemnly impressive; commanding reverential fear or profound respect; sublimely majestic.

In the end I found my own ways of thinking fundamentally changed. It began with my first inkling of how significantly computers are embedded in our everyday life.

I take my salary check to the bank. The check is imprinted with sharp-cornered numbers in magnetic ink that can be read by computers. A computer credits my account, and sorts all the checks received at my bank, for forwarding to the banks on which they are drawn. Another computer will charge my employer’s account in his bank.

In this way our commercial banks handled 20 billion checks in 1969. As the Bank of America, the Nation’s biggest, puts it, “Had we not started to use computers years ago, we soon would have had to hire every adult in California to help with our bookkeeping.”

Machine Keeps Track of New Numbers I pick up my telephone and dial a number.

An operator’s voice cuts in and says, “May I have the number you are calling, please?”

I say, “555-7170.”‘ “Thank you,” says the operator. Now another voice tells me: “The number you have called, 555-7170, has been changed. The new number is 555-7535….”

That second voice came from a computer. While I was saying 555-7170, the operator punched those numbers on a keyboard. She thanked me, pressed a key marked “Start,” and the computer took over.

It reached into its memory, or storage unit, to match the old number with the new number. Then it fed the new number into an audio-response unit, which contains a vocabulary of prerecorded phrases and numbers from zero to nine, to assemble a message custom-made for me. That was the second voice I heard. The operator was through with me in seven seconds. She would have taken at least three times as long if she had had to do the whole job by herself.

Similarly, before the automatic dialing of long-distance calls, an operator had to write down the time and charges for each call. Now more and more computers keep track of that and send the bills, and the telephone companies get along with about 170,000 long distance operators. To handle today’s volume of long-distance calls in the old way would require nearly 750,000 operators—equivalent to all the unmarried women in their thirties now in the country’s labor force.

At this point I paused to look into the nature of the computer itself.

Like all machines, it transforms things, as a lathe shapes a chunk of metal into a useful part, or a typewriter turns the touch of my fingers into words on paper.

The computer transforms information. This sounds simple, but it is in fact the basis of all its awesome power. How so? Because the information going in—in the form of numbers, letters, symbols, and even pictures —can be made to represent a tremendous variety of things. And the numbers, letters, and symbols coming out can be made to produce, often without human help, a tremendous variety of action, as we shall see.

One more thing to remember: The computer transforms information by electronic means. To enable the machine to do this, the information, or data, going in must first of all be put into a form the machine can come to grips with. For most computers in use today, the data is rendered into the so-called binary code, in which any number, or letter of the alphabet, can be expressed in terms of just two digits, 0 and 1. (For example, the binary equivalents of the decimal numbers one through ten are: 1, 10, 11, 100, 101, 110, 111, 1000, 1001, and 1010.) Inside the machine, those binary digits— 0 and 1—are represented by switches that may be either off (for 0) or on (for 1). The machine, in effect, consists of hundreds of thousands of tiny switches. They are grouped into five units: Input. Storage, or memory. Control. Processing. Output.

The input unit senses, or “reads,” data in binary code from various sources, such as: • Punched cards, each with hundreds of spots in which a hole may be punched. A hole may represent 1, no hole may represent 0.

• Magnetic tape, with more than a thousand spots per inch —a spot magnetized in one direction represents 0; a spot magnetized in the other direction represents 1.

• A keyboard. When a key is pressed, the letter or number it represents is automatically encoded into electronic impulses corresponding to 0’s and 1’s.

• A radar antenna, or a TV camera. The data they gather is also turned into electronic impulses, representing binary 0’s and 1’s.

Output Appears in Varied Forms Once sets of binary electronic impulses have been put into the machine, they are ready to be manipulated by the almost indescribably complex interactions of the memory, control, and processing units—that is, to be added together, or to be subtracted from others, or to be sorted or compared with each other; in short, to be processed. Then the output unit delivers the results, which can be made to appear in a variety of ways: In binary code on punched cards or magnetic tape. Or decoded into decimal numbers and letters of the alphabet, and printed by an electric typewriter or other machine— such as the one turning out the mailing labels for 6,900,000 copies of this magazine. Or displayed on a cathode-ray tube similar to that of a TV set. Or put into words through an audio-response unit, such as the one I heard after dialing that telephone number that had been changed.

And because it’s all done by what is basically the switching around of electronic impulses, the work of this most astonishing machine man ever built is known by the modest phrase “electronic data processing.”

For a modest but far-reaching example, I drive to a Jr. Hot Shoppe in northwest Washington to get a Royalburger. The girl at the checkout register punches a key marked RBG and out pops my check: 55 cents. Her punching automatically sends a series of electronic impulses to a computer memory.

Next morning, over a telephone line, a computer four miles away pulls in all the data stored the previous day, and the electronic data processing begins.

The computer adds the number of Royal-burger patties sold the day before in all the Jr. Hot Shoppes. It subtracts that number from the number of patties in the supply center. It compares the result with the number of patties estimated to be needed today, and prints an order for the right number of patties to be brought to the center. The computer also prints a list of how many patties are to be trucked to each Shoppe.

“How many buns, too,” adds a senior official of Jr. Hot Shoppes. “It’s quick, it’s economical.”

And it’s characteristic of much data processing done by the biggest organizations nowadays. Thus do the automobile manufacturers keep from running out of parts. So do Boeing Aircraft and the U. S. Air Force.

Crime Data Converges at the FBI Now I stand in a quiet room in the heart of Washington. An electric typewriter, unattended, clicks softly and rapidly, and stops. This is the FBI’s National Crime Information Center—essentially a computer linked to police in all 50 states.

An FBI inspector says, “Watch the typewriter. If you see the word ‘hit,’ it means somebody has found something that somebody else is looking for.” I see a timely cross section of crime and apprehension.

11:38 a.m. New Jersey State Police report a hit on a Vespa motor scooter with Arizona plates. It had been stolen in New York___ 11:56 Man wanted in Baltimore for unlawful flight. Computer acknowledges, adds that this man already is wanted in Virginia for breaking and entering….

12:01 Inquiry from Utah, giving engine number of blue ‘67 Chevy pickup truck. It’s another hit. The truck was stolen in Texas….

The inspector explains that criminals have become disconcertingly mobile. “But as they rush across the country, a lot of them get caught in the middle, in Kansas, Nebraska, Texas. Say a trooper in North Platte, Nebraska, stops a man for making a left turn without signaling. Intuition tells him something’s wrong; the man may be wanted, so he radios the information on the driver’s license to his dispatcher, who types it on a keyboard, which is connected to our computer here, and the trooper gets his answer within 90 seconds, before he has to let the man go.

“Or if he chases a car on the highway, he can check out the license plate while traveling only three miles. Could save his life, if he is told the man is armed and dangerous.”

The anticrime computer’s job is a matter of electronic matching. The Vespa hit at 11:38 was typed in thus: B505/AZ/67/MC. That stood for license plate b 505, Arizona, ‘67 motorcycle or motor scooter. Had there been nothing to match in the computer’s storage, the machine would have typed back: no record. But the match was made, which triggered the outpouring of the stored information.

“We also put in stolen securities,” the inspector said, “and boats, aircraft, snowmobiles. About two million records. By the way, Mr. White, what is your date of birth?”

I said May 11, 1925.

He typed dcfbiwa. nam/white, peter. DOB/051125.

The machine typed no record, and the inspector bade me goodbye.

Computer Solves a Builder’s Nightmare I drove to the Potomac shore, to the Watergate complex—hotel, shops, offices, and apartments—four vast and unconventionally curvy buildings: a monument to computerization.

The reason is that so little is square about these buildings. All those curves, so harmonious to the eye, are far from symmetrical; an architect’s dream but a construction man’s nightmare. The project manager supervising the erection of two additional high-rise buildings says a computer is saving his sanity.

“Each concrete floor reaches out to a slightly different edge. Those glass walls are really hundreds of separate windows, set in hundreds of steel frames, each of slightly different breadth! To get the necessary specifications takes hundreds of thousands of calculations. Even if we could get enough engineers to do it, they’d each make little errors, and the pieces wouldn’t fit properly.

“So—one computer figured it all. It sends specifications to the manufacturers for each window and frame. Each arrives labeled as to precise location. Excuse me.”

He turns to a teletypewriter that spits out blocks of numbers.

“A lady who bought an apartment on the eleventh floor wants a wood-burning fire place,” he says. “Now the computer tells us how we can put in a chimney for her without messing up the apartments higher up.”

To learn how one operates computers, I entered a special school in Washington. The teacher said, “We don’t just feed data into the machine; we must also put in instructions. First we analyze the problem. Then we write a solution as a logical flow of consecutive steps.”

And so we drew up a flow chart, a sequence of concise instructions; in this case, the purpose was to turn out a factory payroll.

IF HOURS WORKED GREATER THAN 40, GO TO OVERTIME.

IF SOCIAL SECURITY AMOUNT IS LESS THAN SOCIAL SECURITY LIMIT, GO TO DEDUCTION.

IF BONDS EQUAL $18.75, GO TO BOND—BUY.

And a lot more instructions. Finally: WRITE CHECK FOR NET PAY. And STOP RUN.

All these instructions would be encoded into series of electronic impulses and fed into the computer—to set a lot of the switches inside it, so to speak. Incredible, how much switching our instructions would unleash. To do the data processing necessary for the printing of each paycheck, circuits by the tens of thousands would be switched on and off, all within a single second!

And how marvelous that we didn’t have to worry much about the inside of the machine: the mass of wiring linking masses of minuscule parts. But of course we weren’t studying to become engineers. We were learning to write recipes for data processing; or, as the jargon has it, to write computer programs. I was becoming a programmer.

The teacher said, “Any well-defined procedure can be programmed.” But how can one define the ever-changing factors in an industrial process well enough so that a computer can run an oil refinery? Or a steel plant?

The teacher said, “A properly programmed computer can control and modify its own operation.” Many measuring devices keep watch on the process to be controlled. Their output is turned into electronic impulses. These are continuously fed back into the computer, which in turn sends out impulses of its own to continuously adjust the machinery necessary to refine crude oil into gasoline.

Or to mix the ingredients for steel in a furnace, and then flatten fat ingots into sheets thin enough to sheathe cars and refrigerators (pages 604-5). Or to launch one of NASA’s rockets into space. That process—requiring so many things to happen so fast and so accurately—could never be managed without computers.

Before such a rocket can be launched, hundreds of programs must be written, containing hundreds of thousands of steps. That requires hundreds of programmers, and a lot of programmers can make a lot of mistakes. Errors, or bugs, are eliminated as programs are run for testing, or debugging. Just the same, an undetected bug disabled the $18,500,000 Mariner I, so that instead of flying to Venus it had to be destroyed barely five minutes after take-off from Florida.

Alas, how tricky it could be just to program a girl to cross a road! I had learned that from a film which, to illustrate the pitfalls of programming, shows her holding a walkie-talkie and doing only what she is told to do.

Take a step forward. Have you reached the curb? No.

Take a step forward. Have you reached the curb? Yes.

Stop. Look to the left. Is there a vehicle within 60 yards? Yes.

Is there a vehicle within 60 yards? Yes.

Is there a vehicle within 60 yards? Yes.

What went wrong? The girl was stuck because the programmer forgot that vehicles can be parked. He should have asked: Is there a moving vehicle within 60 yards?

The reply would have been No, and the next instruction could have been Cross the road.

Something like this had happened in that department store’s billing operation in Kansas, the one that produced bills for $00.00, remember? Something was missing from the flow chart for that program, a step saying “Test for zero. If yes, send no bill.”

Now that I knew how demanding it can be to work with computers, and how frustrating, I could see why extra-bright programmers can earn $20,000 a year at age 25. Why they sometimes chew their nails and pencils around the clock, and snap at their wives when they finally get home. And why one night a programmer fired two bullets into a computer. Unemployment checks were late that week in the vicinity of Spokane, Washington.

Machines Keep Track of Fashion Trends To celebrate my escape from programming, my wife and I sent a lot of electronic impulses flying. We headed for a suburban Washington department store, and she chose a dress. The salesgirl tore off a portion of the price ticket that had a mass of holes in it (page 613).

That night many such stubs would go through a reading machine; it would transform the data on the stubs into holes in punch cards, ready for the computer.

Next morning the dress buyer would have a report from all the store’s branches, showing just what dress styles were selling best, so she could reorder fast.

I stopped at the store’s theater ticket counter. Any seats for the musical 1776 in New York tomorrow? The girl punched a keyboard, and the answer flashed right back on a little screen like that on a TV set: N101 and 102, fourteenth row, center. I said all right. The girl punched another key and our tickets were printed out then and there.

The morning after the show, I kissed my wife goodbye, picked up the phone, and asked an airline for a seat to Dallas. I couldn’t see the reservations girl, but I knew what she was doing: punching keys, looking at a little TV screen, then punching in my flight number, date, destination, and name.

And something in addition. Did I want steak or lobster for my dinner? Steak! I was off to see H. Ross Perot, the celebrated computer tycoon, in Texas (page 598).

Mr. Perot had responded to a widespread need. Many a businessman eager to benefit from computers had learned the hard way that one can’t simply buy the machines, plug them in, and expect them to do just what the salesman promised. A procedure might take only an hour to run, but the necessary programming might have taken a year.

Even little changes in a program consume much time and nervous energy. And a switch from one computer system to a newer one? Programmers quitting in a huff! Accounts mixed up by the thousands! Chaos! No wonder many corporations find it best to let somebody else do their data processing for them.

$1,000 Check Turns Into Millions Many men have discerned this need and scores have invested to profit by it, but none with the touch of Mr. Perot.

On his coffee table I saw a $1,000 check framed in silver. “With that I started Electronic Data Systems,” he said, “in 1962, when I was 32″ Eventually his company issued shares to be sold to the public. These soon rose in value, to such an extent that the shares he had kept for himself were now worth several hundred million dollars.

The brightly lit hall where I watched his computers at work looked like any other computer center: False floors, to accommodate thick cables connecting those massive steel cabinets, in pale blue and pale gray. Reels of magnetic tape, spurting and stopping, quietly, behind plates of glass. Machinery printing out 1,100 lines a minute. For an insurance company, a bank, a brokerage house.

Mr. Perot said, “My secret is to hire men who are smarter than I am.” Ten of his employees had become millionaires too.

Next to dazzle me with computer doings was a pigtailed first-grader named Shelia, in McComb, Mississippi (pages 594-5). I watched her at the keyboard of a Teletype machine as she hunted and pecked with slender fingers.

The machine typed: 6 — 5 =__ Shelia pecked in:X Machine: 4 + 3 =__ Shelia made it: 7 Then came the thing that impressed me so.

Machine: 5 + 2 = C + 3 C = _ Shelia, quickly: 4 I have since been assured that this is not an uncommon accomplishment for first-graders —that’s the sort of math they are taught nowadays. But not many as yet are drilled daily by computers, as were all the pupils in the seven elementary schools of the McComb school district. It was an experiment then, piped in over telephone lines from Stanford University in California. Today the McComb schools have a mini-computer of their own.

The machine summed up. 16 problems WITH 94 PERCENT CORRECT IN l68 SECONDS. GOOD-BYE, SHELIA. PLEASE TEAR OFF ON THE DOTTED LINE.

“The machine doesn’t allow the mind to wander,” said the district superintendent. “Some teachers were opposed. They thought it was just play. But our test results show significant improvements in the children’s mathematical abilities. So what if it’s fun?”

I noticed that among Shelia’s classmates none got quite the same problems. A little boy named Ralph was given only the simplest additions. To 22 + 33 =__he replied 6. The machine typed, no, try again.

Ralph thought and thought.

TIME IS UP, ANSWER IS 55.

Ralph said, “It’s a good thing; it tells you when you’re wrong.”

The machine does a lot more than that. As soon as a pupil types in his first name and identity number, it finds his file and provides a drill custom-made on the basis of his previous performances, geared to his own pace of learning. Teachers get daily summaries, reporting on each pupil’s progress, and periodic printouts of grades, saving paper work. If special counseling seems advisable, the child’s file is instantly available for review. The teachers still teach. The machine provides drill.

Oh, oh, no more drills today. All the machines are out of order. A day later, they type out an explanation: storms have been raging IN CALIFORNIA . . . POWER FAILURES . . .

WEAKENED CIRCUITS WITHIN COMPONENTS THAT MAKE UP A COMPUTER … IT TAKES LONG HOURS AND CONSTANT PROBING TO TRACK DOWN AND REPAIR THEM ONE BY ONE____ Those are the ills computers are heir to. There are more. Excessive humidity can make them go haywire. So can the vibration from heavy traffic. And particles of tobacco ash can mix up the impulses stored on magnetic tape and produce errors.

Exasperated Student Gets a Warning As I traveled on, I was impressed by the variety of sophisticated programming done for the benefit of students nowadays. I sampled the computer-assisted instruction available to all the midshipmen at the U. S. Naval Academy—physics, electrical engineering, economics. And I took a geography lesson myself at Dartmouth College.

Please keep in mind that there is no human being at the other end of the line, just a well-programmed computer.

HI, I AM CALLED MISS TELETYPE—WHAT WOULD YOU LIKE ME TO CALL YOU?

PETER.

HELLO, PETER! TOGETHER WE WILL LEARN THE LOGIC OF LOCATING A SET OF CLIMATE DATA ON THE GLOBE____ I was given climatological definitions, plus information about average monthly temperature ranges and average rainfall for a real but unidentified place—interspersed with questions I was to answer in my own words.

Step by step I located the place in the Northern Hemisphere, in the upper mid-latitudes. I did fairly well but not for long.

BE SERIOUS, PETER.

I confess that I became unduly exasperated. I typed in an intemperate word. Miss Teletype reacted immediately.

GOODNESS—SHAME ON YOU!!! WATCH YOUR LANGUAGE OR I’LL CUSS BACK AT YOU.

I was ashamed. I buckled down.

VERY GOOD. EXCELLENT, PETER.

PERFECT—THAT WASN’T HARD, WAS IT! SO LONG FOR NOW, PLEASE GIVE ME A CALL AGAIN—SOON.

I paid my respects to the professor who had programmed Miss Teletype. “It’s not all that hard,” he said. “You know—you present things logically, you try to anticipate what might happen.”

An even more graphic lesson awaited me at the Massachusetts Institute of Technology.

The associate dean of engineering took me to a desk equipped with a TV screen, a keyboard, and a so-called light pen all connected to the same computer.

“Take the pen and draw on the screen,” he said. “Lines of light will appear on the screen, in the path of the pen. Please draw a child’s set of building blocks. When you are satisfied, press this key—your drawing will be stored in the computer’s memory.”

I was creating a model, so to speak, of a set of blocks. It was in the form of information stored in the computer, representing algebraic formulas based upon lines and curves. No need to worry about the mathematics, though; the computer’s program took care of that.

“Now watch,” said the dean. “I can command your blocks to become larger or smaller. I can change their shapes. And rotate them, to view them in different perspectives. I can arrange them as I like; I can erase them.” He did all that, moving the light pen, pressing keys. I had never seen a fancier toy.

Computer Models Help Decision Makers “In the same way,” said the dean, “we can create a model of something we really want to build. A school building perhaps, or a traffic interchange. Then we type in information on the physical site, on design requirements, and human considerations, on many factors affecting our project. The computer calculates these, and we can modify the model accordingly—add parts, delete parts, change some.

“We look at various stages of modification. We measure the effects and the costs. We are simulating things that might happen—to find the best choice, to make the best decision.”

In other words, figuring out a lot of things a lot faster than many men could with pencils?

“I think your analogy is unfair to the computer,” said the professor. “We have a brand-new capability here, to do things we couldn’t do before, to explore so many possibilities. To let the truly creative man use his mind freely. An incomparable tool of exploration.”

Modeling! Simulation! Much aircraft designing is done that way nowadays (page 615). An engineer with a light pen draws a cross section of a wing. Then, in effect, he turns his computer into a wind tunnel, subjecting the wing to simulated stresses.

He changes the shape and dimensions of the wing, and when the results look good to him, he presses a key. Thereupon a computer-controlled plotting machine will draw a blueprint of what he designed. Then the computer could produce a tape, to control a machine to build that wing for a prototype.

Modeling and simulation get astronauts to the moon.* In training, they see the effects of their piloting simulated as they practice in a mockup.

For months the spacecraft’s flight is mathematically simulated in computers; during the actual flight the model is corrected once every second. This freshly calculated navigational guidance can be beamed up, as needed, from NASA’s central computers.

Never was space flight simulated more triumphantly than during the anxious hours of the Apollo 13 mission. While Astronauts James Lovell, Fred Haise, and John Swigert hurtled through space in their damaged craft, other astronauts huddled inside the computerized command-module and lunar-module simulators in Houston, doggedly trying out procedures for returning Apollo 13 to earth under circumstances never before encountered and never really foreseen in complete detail. Finally the procedures thus checked and double-checked were radioed up to the real Apollo 13, and applied successfully.

I found less hectic varieties of simulation far and wide. Scientists in Connecticut observe the spread of blight in a mathematically simulated field of tomatoes. From an analysis of rock data, a geologist at the University of Michigan simulates erosion, to show in successive computer-printed profiles how the Colorado River cut the Grand Canyon.

Scores of major companies use simulation. If car production drops, what’s the effect on the steel industry? How high can copper prices rise before it is wise to switch to aluminum wire for winding transformers?

And how was the duck shooting last year? How is duck breeding coming along in Canada? From such information the U. S. Fish and Wildlife Service creates a model to simulate duck populations for the coming season, to decide how many hunting days to permit.

It would take all the pages the Geographic publishes in a year just to list all of today’s computer applications.

Science Projects Stored for Reference Back in Washington, I visited the Smithsonian Institution’s computerized Science Information Exchange. Researchers send in brief summaries of their projects, to be stored on magnetic tape. Any scientist can order computer print-outs describing research underway in his field, so that he won’t start to do what somebody else is already doing.

The director said he had about 100,000 active projects on tape, lots of them employing electronic data processing. “I suspect that using computers in research is becoming as common as using the microscope.”

Computers monitor experiments. They analyze, tabulate, and sift findings, thus fostering the discovery of newly appreciated relationships and proving new theses. Not only in the physical sciences but also in biology, in archeology (see the article beginning on page 634), and in the humanities as well. Through analysis of the recurrence of certain words, a computer furnished convincing evidence that 11 Federalist Papers widely thought to have been written by Hamilton were by Madison.

By now I longed for a rest from computers. But I couldn’t avoid the newspapers, with their daily diet of computer-related items:

• Computers in hospitals analyze electrocardiograms and brain waves; they monitor patients’ progress by continuously measuring heart and respiratory functions, temperature, and blood pressure.

• Computers in state and municipal employment agencies match job applicants with job listings that are truly up to date, so that a man won’t go after a position that was filled two days before.

• Computers control traffic lights at city intersections, changing the signals in tune with the over-all traffic situation that very-moment, as scanned by many sensors.

I also read that computer-made music is booming (pages 628-9). So is business in computer-written horoscopes. For $20, one gets reams of advice and predictions—every bit as reliable, it seems, as any other horoscope. Computerized dating services flourish too. People love them, even though a computer once matched brother and sister.

And crime? Two bright young men from North Carolina are in jail now, but for a time they were riding high with an anti-poverty agency in New York City. They made a computer turn out thousands of checks to nonexistent youths working at fictitious jobs. Then they had a lot of those checks cashed, collecting several hundred thousand dollars.

High Hopes for the “Beep-boom” System I took to the road again, to discover what electronic data processing is doing to warfare.

The general who heads the U. S. Army’s Computer Systems Command gives me a glimpse of the automated battlefield of the future, where far-off detection devices, or sensors, feed data to tactical headquarters by radio.* “Some sensors go ‘beep.’ The computer evaluates what set them off, say enemy tanks of a certain size. It picks out the right artillery pieces, orders the right fuses, aims, fires! No time wasted. We call it ‘beep-boom.’”

This new system will soon be tested on maneuvers, and the general worries lest I jump to misleading conclusions.

“Remember, the decisions are still up to the commanders,” he says. “A computer program has value judgments built into it—it says when certain conditions are met, go this way. But a commander can punch different criteria into the program. And he stays always in command because we put him either on-line, as we say, meaning the chain of action passes through him, or we put him off-line, meaning he acts as a monitor. If the commands coming out of the computer look good to him, he lets them be carried out. If not, he overrides them, with a button.”

How can electronic data processing assist a commander under attack? During a Navy demonstration at the Fleet Anti-Air Warfare Training Center in San Diego, I watch the weapons coordinator on an aircraft carrier make up his mind as enemy planes close in from different directions, faster than the speed of sound. Which of the enemy planes presents the greatest threat?

The coordinator sits at a console of the Navy Tactical Data System, which is fed by various sensors—the radars of friendly ships and planes. He presses a button and tiny pointed symbols jump onto a display screen: the hostile planes. Round symbols show friendly ones.

With his palm, he rolls a black rubber gadget protruding from the console like half a tennis ball. As he rolls it, a bright blip moves correspondingly on the screen; he rolls until the blip coincides with the closest hostile plane, presses another button, and the system “hooks on” to that plane.

He presses a third button. Rows of white digits appear in his read-out panel, giving information about that plane. Its present course. Altitude. Speed. Time to target, if it keeps going this way. A green digit flashes a computer-calculated “threat number”… 2 … 3 … 6___The highest would be 7.

He checks on other enemy planes before making recommendations to the skipper. Other buttons will unleash the defense, the Phantom jets, the Terrier missiles….

In the future, should a real battle be in the offing, the admiral in another ship may be able to press buttons to cut in with commands of his own. So may the Chief of Naval Operations in Washington. So may the President of the United States, wherever he may be.

That’s the idea of the World Wide Military Command and Control System. When completed, it will be the biggest computer network ever built. I saw something like that already in operation—inside Cheyenne Mountain, near Colorado Springs, Colorado. This is NORAD, the North American Air Defense Command, a most awesome electronic data processing complex, employing 15 computers and 34 generals.

President Himself Can Go “On-Line”

Information constantly feeds in from radars around the globe. Masses of intelligence and weather data are stored and constantly updated. The job, says a U. S. Air Force general in NORAD’s Combat Operations Center, is to process all this data rapidly; to display the gist concisely; and, if necessary, to trigger nuclear weapons for air defense. Subject to decision from the President, of course. If necessary, the President would be right on-line.

“The only nation in the world that can launch an all-out nuclear strike on us is the Soviet Union,” says the general. “And so our biggest radars look more than 3,000 miles over the horizon and into the Eurasian land-mass, from England, Greenland, and Alaska. They pick up a rocket launch. Is it a test? Or a space shot? Or an attack on the North American Continent?

“Within a minute the computers calculate the trajectory and display the answer. If it should be an attack, they predict the impact area. We’d get 15 to 25 minutes’ warning. A target in the north would get less warning than one in the south.”

The general goes home and a U. S. Army colonel takes over the operations console. “There are thousands of commercial planes in the air all the time, and we don’t want to see those,” the colonel says. “But if one isn’t in a position where his flight plan says he should be, the computers pick him up. That’s an ‘Unknown.’ A red light goes on, and if we can’t identify him fast, we send up fighters to take a look.

Radar Watches Soviet Planes “Of course,” adds the colonel, “we routinely keep an eye on a few ‘Specials’ we’re interested in.” He lights a cigar and reclines in his swivel chair. Sixty-three buttons glow to the left of him, eighty to his right (page 626). He presses one.

On his screen appears an outline of eastern North America and part of the Atlantic. Near Newfoundland glow two dots with tiny tails. He presses again. Letters and numbers appear alongside the screen. “NN370, the Russian Aeroflot flight from Murmansk to Gander to Havana. NN245 is going the other way, Havana—Gander—Moscow.” Another button brings up a little triangle off Cape Hatteras: VE01, a Russian fishing trawler.

The colonel presses the button marked “World,” and another button. I see the path of a Soviet Cosmos satellite. A blip marks the spot where it was a second ago. The colonel says, “We track every man-made thing in earth orbit.”

It was an uneventful night. Cosmos 221 over New York. Cosmos 236 over Anchorage, Alaska. The airborne command post of the Strategic Air Command near Kansas City.

Then a red light went on. An Unknown popped up over California, going east.

It turned out to be United Airlines Flight 14, a DC-8 scheduled from Los Angeles to Kennedy Airport, New York, with 50 passengers and a crew of 7. It had been hijacked and was heading for Havana.

I headed back to MIT, whose researchers developed so much of today’s computer gadgetry. What’s in the future, for nonmilitary men like me?

magazine will have a lot of news yours doesn’t have—about stamp collecting and fishing, if that’s what he cares about. For the computer that won’t be much of a problem.

“You could have a rug made to your own design with a fault woven into it, for individuality, but made by machine on a production line with thousands of other rugs. A computer program can do that.

“Or a suit can be cut for you along with thousands of other suits, but to your measurements, fed in from a plastic card. You’ll keep the card, for other suits later on. You can see the beginnings of what I mean, right now, in the automobile industry___”

Sure enough, at the Oldsmobile assembly plant in Lansing, Michigan, not one car coming down the line looks like the next. Sedan, convertible, hardtop, topless chassis for a hearse; Aspen Green, Sherwood Green, Burnished Gold, Galleon Gold, Azure Blue, Twilight Blue, Reef Turquoise—all mixed up, all ordered individually. Big engine, bigger engine, biggest; two-way power-adjustable seat, six-way power-adjustable seat; eight types of steering wheels…. The computer arranges for the right parts to reach the right assembly-line station at just the right moment.

How many 1970 Oldsmobiles could conceivably be made here, without any being exactly like the other? The programmer winces; not every option can go into every model. He takes eight hours to prepare a program, and 18 seconds of computer time. The answer is 61,758,733,548,151,070,414.

What else lies ahead? A lot of computerized paying of bills. Say you keep an account in the bank and make a purchase in a shoe store. The clerk takes your bank credit card, inserts it into an attachment on his Touch-Tone telephone, and punches in the amount. The bank automatically deducts that from your account, and credits it to the account of the store.

Gas and electric meters will be linked to telephone lines, so that computers read the meters from afar and send out the bills. They could also be connected to banks; customers would then find utility charges on their monthly bank statements.

Your credit card will be truly theft-proof: it’ll be your thumb. Computers will soon be programmed to recognize fingerprints rapidly. Eventually, when a state trooper stops a suspect, he may ask the man to put his thumb on a little screen in the patrol car—for instant scanning by the FBI computer in Washington.

Perhaps someday the desk worker fed up with traffic jams in the city will do his job at a computer input-output station at home: If he wants to see documents from company files, he punches his keyboard and they appear on his display screen. If he needs a copy, he presses a button and there it is, on paper.

If he wants to confer with colleagues, he presses buttons, and they appear on the screen too. To dictate a letter, he punches up his secretary, at her office desk or at her terminal in her home. She’ll type it on her keyboard— and the text will emerge in the downtown office, to go into the files and into the mail. Or she’ll send electronic impulses directly to the company addressed—into their computer.

How soon could computer use from home be upon us? Among 85 leading technical experts asked, the majority say within a decade. But it’s not only a question of technology. It is also a question of economic practicality, and I trust no predictions on that.

On the other hand, computer technology may yet outstrip the experts’ expectations. Computer performance, in terms of capacity and operating speed, continues to grow by a factor of ten every two and a half to three years. Had the speed of manned flight increased at such a rate, an astronaut could have orbited the earth nine years after Orville Wright wobbled aloft at Kitty Hawk.

The fact is that the first “electronic digital computer, with a variable program stored in its memory”—to use a proper definition—was not in operation until 1950. At present some 70,000 are in use in the United States and another 20,000 abroad, chiefly in Europe and Japan. Technologically, 99 percent of these computers are obsolescent, and even engineers are awed by what is already being tested.

For data storage, not magnetic tape but holograms, or laser pictures.* For processing, not wires for electronic impulses to travel in, but laser beams. Not a million processing steps per second, but a billion per second.

Such advances permit vastly increased amounts of data storage. Such speeds will enable a computer to serve hundreds or thousands of users and still respond as rapidly as it now serves 30. Those machines might cost a lot more, but their output, unit by unit, will become cheaper. Many new applications will be economically feasible.

And so I may yet have a chance to sit home and punch my push-button telephone to ask a computer for the best car route to the beach on Labor Day, and see the directions spelled out on my TV screen. Or see my wife pushing those buttons to order bargains from the department stores, with the charges automatically deducted from my bank balance— without mistakes! But to extend such services to millions of households might put such stress on the telephone network that it would have to be rebuilt, a matter of a decade at least.

Biggest Computer Grows in Pennsylvania Architect of what may become the most powerful computer yet is Dr. Daniel L. Slot-nick of the University of Illinois in Urbana. Here was brought forth one of the classic computers, the first illiac, in 1952. Dr. Slot-nick’s baby is the illiac iv, being built in Paoli, Pennsylvania (page 631). Would it really equal the capacity of all other computers in the world combined?

“That would be one hellish calculation,” said Dr. Slotnick, “but it’s probably not far from right.”

Marvelous, 256 processing elements, a billion operations per second. Who needs all this computer power? The U. S. Atomic Energy Commission, for one. It seeks the biggest and most advanced computers, to design nuclear weapons and to make calculations for peaceful atomic uses. Could Dr. Slotnick cite a homelier application? He said: “Weather forecasts, one to two weeks ahead, accurate beyond anything now possible. Ideally we’d have readings taken at some 8,000 points around the globe, at 10 levels above each point, and 4 different measurements at each level. Altogether, more than 300,000 measurements, illiac iv could digest all that, fast.” Bigger, faster, increasingly interesting. But as I toured the laboratories, what intrigued me most was the programming done to develop so-called artificial intelligence.

Robots Can “Learn” by Experience At the Stanford Research Institute in Menlo Park, California, I watched a computerized robot moving about and making decisions on its own, “learning” as it went (page 608). Such machinery, I was told, might precede men in exploring the bottom of the sea, or the planets —their microphone ears hearing things in frequencies humans cannot hear, their television eyes seeing things in the infrared portion of the spectrum….

How does a machine learn? By trial and error.

I had found that out at MIT too—from a 25-year-old Missourian, Richard Greenblatt. He had written a chess-playing program for a computer employed by MIT’s artificial-intelligence team.

“In any given situation, some moves look more promising than others,” he said. He drew me a “decision tree,” showing various branches, or possible moves.

Having made a losing move, he explained, the program will clip off that branch. And so it will sooner or later wind up with the optimum path. “Now I don’t feed in moves any more,” he said, “I feed in principles. The learning process is already built in. While it’s playing, I don’t feed in anything, of course.”

In 1967 this had become the first computer to win a tournament game. Now its official rating was close to the median for tournament players in the United States.

Could I play?

“Sure,” said Richard. “We had a professor here the other day who said computers can’t think. It beat him.”

It beat me too, with its tenth move. Could I take my last move back, and play on?

We went to twenty moves, to thirty. More and more young men gathered around. Forty moves, fifty. I got out of a trap rather elegantly, I thought. I looked around and was surprised. Why was everybody rooting against me?

Queen from Queen’s Bishop 8 to King’s Rook 8! The machine had nailed me with its fifty-ninth move. There was a great sigh of relief. Richard said, “You lasted longer than most people who come in here.”

His program can be adjusted to look two moves ahead, or four, or six. It cannot possibly look ahead to the outcome of all possible moves—that would be a number with more than a hundred digits. No computer envisioned today would be capable of such a thing.

But the thought of things that computers may do before long gave me pause. Says Dr. Herbert Grosch, a senior researcher in the Center for Computer Sciences and Technology at the National Bureau of Standards: “Many machines now can derive totally unexpected information through procedures the builder cannot fully predict. An advanced machine, programmed to evaluate its own performance by given criteria, may determine that some criteria are worthless and others more important than indicated in the initial programming. The human programmer has no way of knowing about these shifts in criteria values. He only knows that he gave the machine the capacity to make them.”

Computers May Act on Moral Values Even today’s computer technology—primitive in view of what is likely to come—permits the design of machines that adapt to a changing environment, repair themselves, and make new parts as needed. Moreover, serious men with impressive credentials in data processing do not think it at all unlikely that someday computers, supplied with feelings and even moral values, will make decisions based on those feelings and values, as well as on what their sensors perceive.

Right now there is growing concern that computer technology can damage individuals, and curtail the personal liberties of all.

U. S. Senator William Proxmire of Wisconsin warns that as credit-bureau files on some 120 million Americans are computerized, and linked into nationwide data banks, questionable information and data-processing errors are traveling faster and farther than ever.

“You could lose your credit, your insurance, even your job, because of such an error in a credit-bureau file. You say, ‘Not a chance in my case.’ Don’t be so sure; it has happened.”

The National Academy of Sciences, mindful of computerized data banks being set up at every level of government, is sponsoring a nationwide study of the problems thus posed for individual privacy and due process of law.

How does a citizen know what information about him is going into a data bank? He doesn’t know. Some is highly personal. Say you want to buy a house and apply to the Federal Housing Administration for a federally guaranteed loan. Your file will contain a credit-bureau investigator’s report of whether your marriage is in trouble—because, says FHA, divorce is a leading cause for defaulting on housing loans, and what’s wrong with weeding out the worst of the poor risks?

What if in the future FHA should exchange tapes with other agencies, as has been suggested? Then somebody else’s idea of your domestic life might be all over the place. How could you correct inaccurate information about you once it was in the government data banks? As things stand now, you couldn’t. An error in a personnel file, put in from some extraneous tape, could cost a civil servant a promotion. Or keep a man from getting a job. Chances are he would never know why.

Machines Hold Power for Evil and Good Directing the Academy of Science’s study is Alan F. Westin, Professor of Public Law and Government at Columbia University. He says: “Man has progressed over the centuries from the status of a subject of a ruler to that of a citizen in a constitutional state. We must be careful to avert a situation in which the press of government for systematic information and the powerful technology of computers reverse this historical process in the second half of the 20th century, making us ’subjects’ again.” He adds, “Perhaps the greatest legal device to facilitate the movement from subject to citizen in England was the writ of habeas corpus—the command issued by the courts to the Crown to produce the body of the person being held, and to justify his imprisonment.

“Perhaps what we need now is a kind of writ of ‘habeas data’—commanding government and powerful private organizations to produce the data they have collected and are using to make judgments about an individual, and to justify their using it.”

What if computer-equipped authority, insufficiently restrained, should turn hyper-inquisitive someday? If every purchase one makes, down to the last 10-cent newspaper, is recorded by a computer, showing where it was made and at what time; if millions of telephone conversations can not only be recorded daily but instantly scanned to pick out key words considered alarming by the surveillance officers…. The implications surpass the horrors of George Orwell’s 1984.

Dr. Jerome B. Wiesner, Provost of MIT, has said that the computer’s potential for good, and the danger inherent in its misuse, exceed our ability to imagine. Wouldn’t that be the worst it could do—to become an instrument of tyranny, propelling mankind into a new Dark Age?

Flying north over the snowy fields of New England, I thought of the best it might do. It might induce men to take a fresh look at the world. Let’s call this the systems view, and let me explain how it was explained to me.

To make a useful computer model of a complicated process at work, one must first gather a mass of facts about that process. About the life cycle of the lobster. About the growth and decay of the cities. About the dynamics of the American economy, for the model now being built for the governors of the Federal Reserve System.

The finished model should help one decide what to do if one wants more lobsters, or healthier cities, or a healthier economy. But the greatest value of the model lies not in such specific guidance, but in the insight one gains in making the model, in what one learns while going after the factors that make up a complicated, ever-changing process.

In short, the common way of thinking in terms of simple cause and effect—the Newtonian, mechanistic view—is replaced by new awareness: of many causes, constantly producing varied effects, in what really are highly complicated and dynamic systems.

My little boy gets into trouble in kindergarten. There’s rioting in Chicago, a coup d’etat in Cambodia. I used to have pretty- simple explanations for these occurrences. But no more.

It looks as if computers will become so common, so taken for granted, that we no longer will talk much about computers but rather about computing, in the sense that we no longer talk as much about automobiles as we talk about driving somewhere. When that day arrives, when we see the world in terms of systems, we may discover that an intellectual revolution has come, comparable to those wrought by Galileo and Darwin.

I landed at Hanover in New Hampshire, drove once more to Dartmouth, and found that this revolution may be closer at hand than I had thought.

Dr. John G. Kemeny (page 598), the mathematician who earlier this year became Dartmouth’s thirteenth president, has a computer terminal in his office, near a bust of Einstein, whose assistant he was. He told me: “Nine out of ten of our undergraduates sit down at a computer terminal as naturally as they would go to the library to look up something in a book. Our freshmen start writing programs after two one-hour lectures. We don’t teach them about computers, we teach habits of inquiry.”

Snoopy Emerges From a Computer That evening on campus, in the Kiewit Computation Center (left), ten of the sixteen terminals were occupied.

One sophomore had a girl with him. He was running a program printing out a picture made up of teletypewriter characters, a picture of the dog Snoopy.

“It snows your date,” said a freshman. He was modeling a course for an Apollo flight.

Another worked on a Physics I problem, to see what would happen if another moon entered earth’s orbit and crashed with the one already there. No, he didn’t know much math, he was planning to major in English. But here he was, crashing moons around.

Said a professor, “Once the kids get their hands on the thing like that, they’re no longer in awe of it. And they learn how enormously they can increase their powers.”

Tens of thousands of kids, perhaps hundreds of thousands, will get their hands on the thing within one generation. I’ll be awfully curious to see what they’ll do with it.

Cartridge Tape System Is Fast, Compact

Product Preview

Employing a new cartridge-loading technique, IBM Hypertape eliminates the need for threading and, when used in the IBM 7090 computer system, it has the ability to “read” and “write” information at twice the speed of the conventional magnetic tape system. Hypertape currently can be used as an auxiliary storage system, increasing the computer’s capability to utilize internal computing power.

Units making up this new system are the IBM 7340 Hypertape drive and the 7640 Hypertape control, which can be linked to IBM’s 7074, 7080 or 7090 computers.

Equipped with Hypertape units, the IBM 7074 and 7080 computers can read and write numbers at speeds up to 340,000 a second, or letters at the rate of 170,000 a second, or a typical combination of numbers and letters up to 250,000 a second. The IBM 7090 can perform all three functions at the 170,000 character-per-second rate. At its top speed, Hypertape could enter all 137 million U. S. Social Security numbers into a computer in an hour.

As many as 20 of the 7340 Hypertape drives may be attached to any of the three computer systems through one 7640 control unit.

Among the features of the new magnetic tape system are cartridge loading, which eliminates the need to handle the magnetic tape itself; a new method of data recording and error detection and correction; and an advanced mechanism that moves the tape without touching its recording surface—resulting in less tape wear and greater preservation of data.

In loading, the operator inserts the cartridge into a slot at the front of the unit and presses a button. The machine then automatically opens the cartridge, engages the tape and begins processing. Unloading can take place at any point during processing, since the cartridge can be sealed and removed without rewinding.

A method of detecting and correcting errors in the Hypertape system is provided by IBM Phase Encoding, a signal pattern recorded continuously on tape. Two of 10 channels which run the length of the tape are reserved for checking.

A single roller drive exerts as little as one pound of vacuum tension pull on the tape. The 1-in. wide tape can hold up to 2 million characters per reel. Circle No. 115

view additional pages

The Brain Builders

“At last I came under a huge archway and beheld the Grand Lunar exalted on his throne in a blaze of incandescent blue . . . The quintessential brain looked very much like an opaque, featureless bladder with dim, undulating ghosts of convolutions writhing visibly within . . . Tiers of attendants were busy spraying that great brain with a cooling spray, and patting and sustaining it . . .”

—H. G. Wells,
The First Men in the Moon

Last week, in a pastel blue and grey room on the fifth floor of a St. Louis office building, the newest Wellsian brain in the earthly world was enthroned. This quintessential brain looked like nothing more than a collection of filing cases, stretching in a 60-ft. semicircle about the room. From within the grey metal cases came a faint humming sound; along the light-studded metallic face were scores of twinkling orange sparks, rippling like waves of thought. As in the Grand Lunar’s palace, a blaze of light flooded over the pale walls and pillars of rosy pink. Air conditioning filtered out the dust, kept the temperature at an even 75°. Along one end of the chamber was a gleaming plate-glass observation window, through which mere humans—attendants and sightseers —could watch and marvel.

The brain was the newest electronic calculator, developed by International Business Machines Corp. and installed in Monsanto Chemical Co.’s St. Louis headquarters. To IBM, it was the “Model 702 Electronic Data Processing Machine.” To Monsanto and awed visitors, it was simply “the giant brain.” Seated at its control console, a man has at his command the computing ability of 25,000 trained mathematicians.

New Horizons. On each of its reels of magnetic tape, the brain can remember enough information to fill a 1,836-page Manhattan telephone book—any figure, word, chemical or mathematical symbol— and work the information at the rate of 7,200 unerringly logical operations per second. In its vast computing units (2,500 electronic tubes, three miles of wire) it can multiply a pair of 127-digit numbers and arrive at a 254-digit answer in one-third of a second. In a second it can add 4,000 five-digit figures or do 160 equally complicated long divisions. And at the end, it can produce its answers in any of four ways—flash them on a TV-like screen, punch them on cards, print them on paper, or store them away on rolls of magnetic tape at the rate of 15,000 characters every second.

To Monsanto, the great brain will mean unprecedented speed, accuracy and economy in every phase of its manifold chemical business. In just twelve machine-hours the brain will do 1,200 cost reports that normally take 1,800 man-hours; in barely two hours it will complete a financial statement that takes a staff of accountants 320 hours. For Monsanto’s chemists it will open up new horizons by rapidly working out complex equations to help discover new products, improve old ones, find out which of dozens of technically “correct” answers to problems are the best.

“THINK.” IBM’s new brain is a logical extension of the company’s famed slogan, “think.” In the age of giant electronic brains, IBM’s President Thomas J. Watson Jr. is applying to machines the slogan which his father, IBM’s Board Chairman Thomas J. Watson Sr., applied only to men. President Watson hopes to mechanize hundreds of processes which require the drab, repetitive “thought” of everyday business. Thus liberated from grinding routine, man can put his own brain to work on problems requiring a function beyond the capabilities of the machine: creative thought. Says Watson: “Our job is to make automatic a lot of things now done by slow and laborious human drudgery. A hundred years ago there was an industrial revolution in which seven to ten horsepower was put behind each pair of industrial hands in America. Today we’re beginning to put horsepower behind office hands, electric energy in the place of brain power.”

IBM is not the only company with the idea of automating U.S. offices. In the fast-growing business equipment industry, such big firms as National Cash Register, Burroughs Corp. and Remington Rand are busy making everything from adding machines to the new electronic computers. But IBM is the biggest of all with 25% of the two billion dollar industry.

IBM, with orders for 14 of its Model 702 electronic computers (renting at $20,-000 a month), has already delivered 19 giant computers of an earlier model—the 701. Almost no job under the industrial sun is too tough for IBM’s electronic brains if the problem can be reduced to a formula. The Atomic Energy Commission has three 701 computers, uses them to figure out incredibly complex problems on its nuclear production line. The Navy has a 701 keeping track of inventories and shipments, calculating when to reorder thousands of different items and how much to buy. IBM has just delivered a new NORC computer (Time, Dec. 13) to the Navy; it cost $2,500,000 to build, can do one billion calculations daily.

Even bigger electronic brains are being readied for the Air Force’s supersecret “Project Lincoln.” These computers will one day direct the defense of North America by calculating the course, speed and altitude of approaching enemy planes, then firing guided missiles to intercept them. A 701 has gone to work for the Weather Bureau, and will attempt to make weather forecasting an exact science. Weathermen will feed into it hundreds of reports on rainfall, temperature, humidity, expect that the brain will be able to predict accurate weather for any place in the U.S. 48 hours in advance.

On the West Coast, almost every aircraft company has at least one big IBM computer. At Lockheed, for example, a brain is given all the characteristics of a plane, e.g., weight, wing stress, etc., then “flown” at imaginary speeds, put into dives, etc. Swiftly and accurately, the brain tells what would happen in real flight. In its spare time, the brain solves production problems by coordinating thousands of workers with thousands of parts flowing into plane assembly lines.

The Automatic Factory. Businessmen already envision a day when the brains will be used not only for paper-work problems, but to operate factories, to run auto production lines or any plant where a process can be reduced to a pre-set, repetitive system. Swiftly and obediently, the big robot will start and stop production lines, supervise all the machines, correct faulty workmanship, inspect the finished product, package it and ship it out to U.S. consumers.

The mere vision of such total automation for industry has touched off a siren of alarm among U.S. labor unions; they fear that the already swift spread toward automation will throw thousands of workers out of jobs. Before a congressional committee investigating the stock market last week (see Wall Street) , General Motors President Harlow H. Curtice took special care to debunk the bugaboo. Said he: “Automation is the making of tools to produce more efficiently . . . It’s progress.”

In such progress, some workers may indeed be displaced by machines. But for every job lost, a dozen more interesting, better-paying jobs will open up in the making and servicing of machines. Says Tom Watson Sr.: “Automation will develop as all other forms of power. Primitive man had only his hands, then animal power, then wind power—windmills and sailing ships—then came steam and electric power, and gasoline and oil power, and now, atomic power. Not one of these powers ever canceled out the powers we already had. In every development we made, the original power—manpower—¦ became more valuable than ever. Never in history has man gotten higher rates of pay for his work than he is getting today.” The Perennial Fallacy. Nowhere is the fallacy of unemployment from automation more evident than in offices. There, automation has made its greatest strides, helped along by dozens of whirring, clicking machines. Yet the number of office workers has actually risen from 5.100,000 to 8,100,000 in the last ten years. Only the new machines have made it possible for U.S. businessmen to keep up with the increasing Hood of paper work. There are automatic time clocks, electric typewriters, card punchers, sorters, analyzers, tabulating machines and accounting machines. They do everything from keeping records to servicing bank accounts and writing checks. The U.S. Government alone uses 23,150 tabulating machines (more than 90% made by IBM).

To fill new needs, IBM has just brought out a “Cardatype” machine, which can do a complete accounting job, has electric typewriters type out the finished accounts from punched cards, all automatically. They can do and type as many as five separate accounts simultaneously. IBM also has a new super-time-clock system, in which one master clock regulates all lights, air conditioning, heating, doors and vaults in a plant. For example, a few minutes before 9 o’clock each morning, the machine can open the doors, flick on lights, turn on heat or the air conditioner; at closing time it shuts up shop without human help.

The Big Shift. IBM’s success in office automation was built on machines of cogs and gears; its swift tabulating machine was basically only a mechanical improvement on the first one built by Blaise Pascal in 1640, which in turn was an improvement on the ancient Chinese abacus. But in the last few years there has been a profound change in the business. The mechanical cogs and gears have given way to electronic circuits, cathode-ray tubes and transistors. For IBM the change could not have come at a better time. Tom Watson Sr., who had improved his machines close to their mechanical limits, was ready to step up from president to chairman. His son, who took over the president’s chair in 1952, was quick to see the new electronic age adawning. Almost singlehanded. he fought his ideas through, persuaded everyone that IBM had to learn to make electronic circuits do the work of old-fashioned cogs and wheels.

As it was. Remington Rand hit the electronic computer market first, with its $1,125,000 UNIVAC in 1951, cleaned up the early contracts. Today Remington Rand has 26 big UNIVACs in various models around the U.S., orders for eleven more. But spurred by President Watson, IBM now has orders for 129 giant electronic calculators; 109 of the orders are for the new 704 and 705, which are bigger and faster than the current Model 702. The big computers will cost IBM more than $1,000,000 each to build, but they will bring the company a whopping income of nearly $50 million each year in rental fees from U.S. industry.

Cash & Collars. IBM was created by Thomas John Watson Sr., who built it into the 37th ranking U.S. manufacturing corporation, and in so doing, carved out an American business legend for himself. Watson, who believes that “nobody really gets started until he’s 40,” worked for Dayton’s National Cash Register Co. until 1914. Then at 41. he suddenly pulled up stakes. Going East to Manhattan, he went to work for the Computing-Tabula-ing-Recording-Co.. which in 1911 had begun making new kinds of time clocks, butcher’s scales and accounting machines.

With his kindly, canny Scots face and fluent speech, Watson was his own best salesman. Carefully he designed new machines to fit each customer’s needs, and within a year he was president of C-T-R. Two years later, the company paid out its first $3 dividend and Watson was on his way. He conjured up so many new ideas that he still holds in his own name more than a dozen patents for machines. Wherever he went, he drove his staff to do more, learn more—above all, to THINK more.

By 1924 C-T-R had three plants in the, U.S., had expanded abroad with branches in France, Great Britain, Canada and Germany, “developing Europe,” as Watson called it. He changed the company’s name to International Business Machines, expanded still more. His high, stiff collars, his aversion to smoking and drinking, his vast store of aphorisms became trademarks of IBM to the outside world. Inside his company, he operated like a benign patriarch. IBM’s workers were among the best paid in industry, had other benefits that few companies had. At company banquets, Watson liked to lead his employees in singing company songs such as his Hail to IBM* anthem. Every executive, both big and little, became a polished speech-maker, and all dressed like Watson. He wanted them to look neat.

Through the ’20s and ’30s, no fewer than 45 new business machines appeared under the new IBM label. While other companies cut payrolls through the Depression, Watson refused to lay off men. IBM stored away what it could not sell, against better days. In 1933 Watson bought up Electromatic Typewriters, Inc., a Rochester (N.Y.) firm which had the first completely electric typewriter, and put the first such mass-produced machine into U.S. business offices.

Today the IBM empire spreads to every corner of the world, selling or renting business machines at the rate of $461 million in 1954. In the U.S. alone, IBM employs 34,000 workers; at six plants (Endicott, Poughkeepsie and Kingston, N.Y.; Washington, D.C.; Green-castle, Ind.; San Jose, Calif.) it makes 5,960 different models of business machines which it sells or rents through * Sample Lines: With hearts and hands to you devoted, And inspiration ever new; . . . We will toast a name that lives forever, Hail to the IBM.

188 U.S. offices. Overseas, IBM’s World Trade Corp., run by 35-year-old Arthur Watson, Tom Jr.’s younger brother, employs 16,500 more workers in 17 smaller plants, 227 offices in 79 nations.

IBM has never had a union; it never needed one. Besides high wages ($2.25 an hour for production employees, $10,000 and up for salesmen), IBM puts large chunks of its payroll (24% in 1954) into employee benefits such as free country clubs, bowling alleys, 52 extracurricular activities with 656 instructors, teaching everything from psychology to home repairs. And for IBM’s stockholders, Watson has not missed a dividend in 39 years. A man who bought 100 shares of IBM stock in 1914 would have paid out $2,750 for his original stock, spent another $3,614 to take advantage of all options. Today he would own 3,893 shares worth $1,492,965.

At Work at Five. Tom Watson was not content just to build an empire; he also carefully trained Tom Jr. to take it over. The training started as soon as Junior was old enough to toddle. At the age of five, he went on his first inspection tour of an IBM plant; four years later he went to Europe with his father on the first tour of the new overseas division. IBM executives were frequent guests at the big, rambling Watson mansion in Short Hills, N.J. and at the 1,000-acre farm 30 miles away in the rolling Jersey hills near Oldwick. Tom Jr. got to know them all. and through them, IBM.

When he was twelve, he even made a speech before IBM’s 100% Club of star salesmen. It was a “very good, short speech,” his father happily recalls. For Tom Jr., his father set strict standards and never relaxed them. When Tom, an ardent boy scout, failed to make his Eagle badge, his father refused to send him on a gala seven-week trip to Europe, which he was financing for other Short Hills scouts.

Young Tom Watson was no ball of fire in his studies in school. He went to private schools in Short Hills, barely managed to scrape through Hun School in Princeton. After graduation from Brown University, he joined IBM. Starting at the bottom as a salesman in Manhattan’s financial district, young Tom soon proved that he was his father’s son. In an area where previous IBM salesmen had never made 100% of quota, he hit 231% and hung up a record. Says his father: “That was the only right way. He had to make his own records. Otherwise, people might feel that he had some special help, which he did not have.”

Churchill & the Desk. When World War II came, Salesman Tom Watson Jr. enlisted and spent the next 5j>- years as a transport pilot in the Army Air Forces. Right after Pearl Harbor he married Olive Field Cawley, then started shuttling between Russia and the Middle East on staff missions. In his B-24 he once flew escort for Britain’s Prime Minister Churchill on a long flight from Moscow to Teheran. When he got out in 1946, he was a lieutenant colonel with 2,000 hours of flight time, the Air Medal, and senior pilot’s wings.

IBM’s executives hardly recognized him when he got back. Tom Watson Jr. had grown up in the Army. His first job was as assistant to Charles Kirk, IBM’s vice president in charge of sales. “He had a large desk,” says Tom Watson Jr., “and I simply had a chair pulled up at the edge of the desk, alongside him, and saw 90% of what he did.” When Kirk was away, Tom Watson Jr. had to make the decisions. He made them so well that when Kirk died suddenly in the summer of 1947, Tom Jr. took over the job, moved up to executive vice president in 1949.

Three years later, his father called him into his 17th floor office at IBM’s Manhattan World Headquarters, told him that he was IBM’s new president. Says Tom: “It was the most moving experience of my life. I was completely disarmed.”

Today, after three years as president, there is little doubt who is running the company, though his father is still active in IBM and outside as well,* likes to be * Among his r68 activities: trustee of Columbia University and Lafayette College, International Commissioner of the Boy Scouts, member of the Carnegie Fund, National Foundation for Infantile Paralysis, Y.M.C.A., a director of three other corporations.

informed of everything, and takes part in most high policy decisions. Tom Watson Jr. makes no bones about the fact that his father was able to put him in the president’s chair largely because of his position in the company and the fact that the Watson family holds 6% of IBM’s 4,098,-471 shares. But Tom Watson Jr. is proving that the choice was a good one.

Phones & Time Clocks. Tall and rangy (6 ft. 3 in., 190 lbs.), prematurely grey at 41, Tom Watson Jr. is much like his father at IBM. He does not smoke, except for a few weeks at Christmastime, never drinks. He used to do both, but when he took over the president’s chair, he gave them up in deference to his father. He usually wears the traditional IBM uniform —dark suit, quiet tie, white shirt with stiff, detachable paper collar—punches a time clock along with the lowliest employee. But he is a more relaxed executive than his father. He likes to be called Tom, delegates responsibility. Nine times out of ten, he answers his own phone in his office atop IBM’s Manhattan World Headquarters. He gives orders in a quiet, assured voice, never expects to be told that they have been accomplished. Much of the time he is off on inspection trips in a company plane (often doing the piloting himself), and, like all IBM executives, is a good public speaker.

He lives in a big colonial brick house in Greenwich, Conn., with his pretty wife and their five children—Tom III, 11, Jeannette, 9, Olive, 7, Lucinda, 5, Susan, 2— and tries to lead the happy, solid life of a normal, 9^0-5 commuter. He is as hard-muscled as a 25-year-old, loves to ski and sail. Whenever he can, he sails his 47-ft. racing yawl Palawan on Long Island Sound, has taken it on two Newport-to-Bermuda races.

In measuring his success, IBM’s new president must stack himself up against his father’s impressive record. Since 1929, IBM sales have jumped an average of 14% each year. On his personal score card, Tom Watson Jr. has done even better, with an average gain of 19% for his three years. It is estimated that IBM’s gross this year will hit $500 million, and profits will climb to $56 million.

To the Justice Department, International Business Machines is already too big, too successful. It has had a suit pending against the company since 1952, charging it with a 90% monopoly of the tabulating-machine industry; the Government charges that IBM restrains trade through its 1,500 patents and by the fact that it leases its accounting machines instead of selling them. Nevertheless, President Tom Watson Jr. intends to keep on expanding at top speed. By i960 he confidently expects IBM’s sales to climb over the magic $1 billion figure.

The Roads Ahead. In the coming age of automation, unlimited areas for electronic machines will open up for IBM. For office work alone, Tom Watson Jr. sees a vast new field in swift baby computers for small companies. He envisions them in airline and train stations to handle the repetitive job of reservations, in offices to write business letters by drawing on pre-written paragraphs stored away in the brain’s memory units.

Beyond office paper work, the entire horizon of factory automation is beginning to open up for electronics. While U.S. industry has always had automatic machines, a whole new family of “feedback” controls is growing up which not only run the machines, but also correct their mistakes, order the machines to rework defective parts until they are perfect. Such feedback controls are the forerunner of real automation. Linked together, they will make automated production lines. A form of the new automation is already at work making telephone relays for Western Electric, acetylene gas and carbide for the National Carbide division of Air Reduction Co., aircraft engines at Curtiss-Wright. Other firms, such as American Smelting & Refining. General Mills, Dunlop Tire & Rubber, have turned to automatic controls to produce everything from bronze castings to printed circuits and foam-rubber mattresses. In the oil industry, automation has advanced to the point where a handful of technicians can run an entire $40 million plant by remote control from a panel of instruments. In some of the newer refineries now under construction, there will even be controls to watch the instruments, run the cracking processes from start to finish without human help. Among the new developments: Detroit’s $250,000 “transfer” machines operated by Ford, Oldsmobile, Chevrolet and Packard, which can turn out a complete engine block on an automated line 100 yds. long and carry it through 500 separate processes. Whenever any part of the machine makes a mistake, a special sensing device halts all work until the mistake is corrected.

A West Coast aircraft company’s $1,128,000 contour milling machine, which will soon be built to work any known metal into as many as 18 shapes automatically, correct itself with a feedback control keyed to magnetic tape. The Army’s ordnance plant at Parsons, Kans., which turns out 2,400 shell fuses each hour on a production line run by automatic controls. As each part flows onto the assembly line, special controls check the part to see that it is positioned perfectly, then send it on for automatic assembly of the parts into shell fuses.

The Golden Age. Total automation is a long step away. But the prospects for mankind are truly dazzling. Automation of industry will mean new reaches of leisure, new wealth, new dignity for the laboring man. The coalpit worker, the steel puddler. and those who do many maintenance jobs on an assembly line can surrender to self-controlled electronic machines the hazards and dullness of backbreaking menial work. Thus liberated, the world’s laboring man can find a new pleasure and culture in life.

Actually, automation is not a threat against jobs, but a real necessity for an expanding economy. Despite the progress towards office automation, businessmen must move even faster to keep up with the mountain of paper work growing out of the increasing complexity of production and industry. To date, only 5% of office work is done by automatic machines. There is no reason in IBM’s mind why businessmen could not mechanize more than 35% of their office work. This would not only speed it up but save billions of dollars.

In the same way, industry must speed up automation in factories. By 1965, if the standard of living is to keep on rising, the U.S. will require at least a 50% increase in gross national product. By then, the U.S. population will hit 190 million, but since much of it will consist of school-age children and oldsters, there will actually be relatively fewer effective workers in the labor force. To keep up with production requirements, U.S. industry must rely on more automation. Can the breach be filled? IBM and its team of Watsons have no doubt it will be. Says Tom Watson Sr.: “In the next 40 years we will accomplish so much more than in the past 40 that people will wonder why we didn’t do more in the first 40.”

Related posts

• AUTOMATION (Mar, 1955)
• FOR THE MATHEMATICIAN who’s ahead of his time (Mar, 1955)
• IBM 1001 DATA TRANSMISSION SYSTEM (Mar, 1955)
• 5 NEW IBM PRODUCTS (Mar, 1955)
• IBM Ad: Parade with a purpose (Mar, 1955)
• FOR THE MATHEMATICIAN who’s ahead of his time (Mar, 1955)

view additional pages

Three new home computers that teach themselves – and teach you how to use them

They’re smart, they come ready to work, and one of them even talks to you

By BILL HAWKINS
PHOTOS BY ORLANDO GUERRA

Only two years ago, home computers were for the hobbyist: a jumble of wires, transistors, and circuit boards that came in a kit. And once the kit was assembled, there was complicated programming to master. Things have really changed since then.

Recently I’ve been trying three of the newest home units from APF, Atari, and Texas Instruments (first reported on in PS, Nov. ‘79). They’re no more complicated to hook up than a video game. The programming can be learned in just a few evenings. External pieces, such as a printer for making permanent records, are as easy to plug in as a toaster. Best of all, the computers can teach themselves.

Basically, these new computers resemble each other. But with prices spread from $600 to well over $1000, there are important differences. Some of that is in what you get now. In other cases, your money goes for what you can add later. I found strengths and weaknesses in each machine.

Before getting into the specifics of these systems, it’s important first to know the basics of what these machines offer.

Minimum gear The brain of a computer is a tiny integrated circuit chip (microprocessor). But for that brain to do actual work, it needs more.

It needs a keyboard for entering information into the computer. To get info back out again so you can see it, the system requires a display. This can be its own (dedicated) video monitor or, as it is in most cases, a standard TV set.

And somewhere between putting data in and getting it out, the computer must have a memory—more integrated circuit chips that can hold bits of information for the system to use.

Conventional memories retain information only until you switch off the power. To save programs or raw data for future retrieval, these home computers include a cassette-tape storage system—usually a standard cassette recorder that’s either attached or built into the computer box.

Now the system has the hardware necessary to enter, retrieve, and save data. But computers are stupid. The final ingredient they need is intelligence—programming—to teach them what to do when asked to print out 2+2, for example.

Using their built-in language-called BASIC—these computers convert your English commands, from the keyboard, into binary numbers the microprocessor can use. Thus all you need to do is learn a few key words used by BASIC to make the system work.

Besides these minimum necessities the new computers offer color graphics—the ability to draw “computerized” color pictures on the screen—and sound effects for creating your owe electronic music.

Another plus is flexibility—extremely important to the future of any computer—both in hardware and software. If you want to add a printer later, for example, you not only need a place to attach it to the computer (hardware port), but the computer must also know how to use it (software control). In that respect, these systems become quite clever.

Each contains a monitor program.

When you first switch on the computer, the monitor takes over to give the microprocessor instructions—how to read the keyboard, how to put info on the TV screen, etc. But the monitor also “looks” at what’s attached to the computer. It runs a short test and, if you’ve connected a printer, for instance, it knows that all commands dealing with the printer are operable.

The same holds true when adding a disk system—a high-speed recording device. Data are saved on a record-like disk that’s actually a round, flat piece of magnetic recording tape. Normally, disks are very difficult to “bring up” in a computer system. But, because of these advanced monitors, it’s simply a matter of plugging in the new disk drive when you’re ready to use one. Now let’s take a closer look at the three computers.

APF The APF Imagination Machine is actually made of two separate components. The first is APFs MP-1000 programmable video game ($130 bought separately), which contains the microprocessor, memory, and video circuits (RF out to color TV). As a stand-alone unit, it can use APF’s game cartridges, but will not accept your custom programming. Place it atop the separate keyboard ($500) and connect them together (see photos), however, and the result is a full-scale computer that accepts your commands.

The keyboard box also contains a built-in stereo cassette deck and speaker. As one track of the cassette is played into the computer to give it machine instructions, the other track can contain conventional audio: human instructions (you record with a separate mike) or programming notes to yourself.

The keyboard is of good quality with conventional key placement—important for text-oriented programs and touch-typists. Also, standard BASIC commands such as PRINT or RUN needn’t be typed out each time you need them. Pressing a special control key, along with another key marked with the word you need, automatically spells the word on the screen—a clever, time-saving idea.

The Imagination Machine has the lowest price in this group, and the add-on approach is also economical if you want to start with just the video game. But it does have one drawback. APF has treated each part as totally separate: There are two on/off switches, two power supplies to plug in, two reset buttons, and too much confusion until you get used to it.

Atari Although the Atari 800 will play games with you, it is one of the most serious home computers I’ve seen. A printer, tape deck, and up to four disk drives simply plug in the side. The top swings up and off (see photos), giving you access to all its memory—including the monitor program saved in a permanent (ROM) memory module. (You may not have any reason to change it now, but it gives you added flexibility if Atari comes up with a better one later.) Normal programming memory (RAM) can be added, expanding the system up to 48,000 bytes (48K)— more than enough for most home applications.

Keyboard quality is excellent and special keys, such as INSERT and BACK SPACE, make text creation and editing a breeze with the right software.

Besides the conventional RF connection for attaching the system to a regular TV set, there is also a video jack for connecting it to a video monitor which, theoretically, should give you an even sharper picture.

It’s a good system, but expensive. Besides the cost of the basic system, add in the price of a new color TV.

Texas Instruments If you like bells and whistles, the TI-99/4 should please you. It accepts all the conventional add-ons, such as disk drives, a printer, and a cassette tape recorder, through a side connection. But there is one add-on unique to TI: a speaking module. With it, the computer talks through the speaker in the video monitor ($150 for the module plus $45 for the software necessary to use it).

The module comes with about 300 words (expandable to about 900), and any one or strings of them can be called in your program at any time. The module I tried was just a prototype, but the intelligibility of the voice was incredible. You haven’t lived until your home computer says “hello” and asks you to “please enter a number.” Add together the speech, graphics, and musical capability of this machine, and it could almost become another family member.

Cost of the system ($1150) isn’t bad, considering that it includes the color-TV monitor. There was one disappointment, however. I found the keyboard more difficult to use than the others. It is not standard, so a touch-typist may have a few problems with it.

wanted: sales engineers to sell electronic computers

WELL ESTABLISHED MANUFACTURER IN GROWTH INDUSTRY NOW FORMING TECHNICAL SALES GROUP. The ElectroData Corporation, a subsidiary of Consolidated Engineering Corporation, one of America’s leading makers of electronic analytical instruments, needs qualified sales personnel to establish commercial applications and close sales for electronic data-processing systems. ElectroData Corporation was formerly the Electronic Computer Division of Consolidated Engineering Corporation, one of the leading designers and marketers of high quality instrumentation for science and industry, whose mass-spectrometers and recording oscillographs are the recognized standard of quality throughout the world. ElectroData Corporation will benefit from Consolidated’s 17 years of experience in technical application knowledge and management skill.

DIVERSIFIED MARKET… here is your chance to get into a new industry with unlimited growth possibilities. Electronic data-processing systems establish new horizons for scientific research, engineering computation, process control, production, accounting and statistical control, distribution and marketing.

BASIC QUALIFICATIONS: A.B. degree with satisfactory credits in physics, electrical engineering, physical chemistry and mathematics or a combination of these. Two years applicable sales experience. Age, to 40. Pleasing personality, reliable habits and desire to travel are essential. Duties involve technical consultation, sales promotion by mail and personal contact. Must qualify for secret clearance. Base headquarters will be in the Rose Bowl city, Pasadena, with regional operating headquarters in seven locations throughout the nation. Write to attention of personnel manager.

ElectroData CORPORATION 717 North Lake Avenue Pasadena, California • RYan 1-8335

ONE OF THE GREAT MISCALCULATIONS IN IBM HISTORY

In the early 1950’s, we took a hard look at the future for business computer systems.

Our best estimate, at the time, was a potential of 50 new customers.

But in a relatively short time, we’d built and installed 75 systems. And by the time the dust had settled, we’d sold 1500 of them.

It’s hard to believe that a forecast could have been so wide of the mark.

But then, as now, this industry continues to surprise nearly everyone.

Who would have dreamed, back in the ’50s, that in less than 30 years this would be an industry that has installed more than 500,000 computer systems in the U .S. alone.

Who could have guessed that a business started by a few dozen scientists, inventors, and engineer would become a multibillion dollar industry employing more than three-quarters of a million people here in the United States.

For the past 30 years computer technology has been exploding, and even today demand continues to exceed the most optimistic forecasts.

There is one forecast, however, we feel confident in making.

As long as we can keep driving the cost of using a computer down, this looks like an industry with nowhere to go but up.

IBM

BIZMAC at Bat—”Brain” Predicts 1957 Averages

Early in March, when the Army Ordnance Command’s BIZMAC computer was demonstrated publicly for the first time, the operators used it to predict batting averages for the 1957 season. Twelve of the leading major league baseball players were “analyzed” by the computer, which based its predictions on the players’ averages for the past five years.

Leading the field was Mickey Mantle (.342); followed by Richie Ashburn (.328), Ted Williams (.322),HarveyKuehn (.319), Minnie Minoso (.317), Carl Furillo (.314), Ray Boone (.313), Nellie Fox (.309), Stan Musial (.305), Ted Kluszewski (.304), Duke Snider (.302) and Yogi Berra (.297). This is a reminder—just to show that computers can be wrong.

In the photo at left is a portion of the BIZMAC control. The “real” use of the computer is to keep track of U. S.
Army truck and tank supplies scattered over the world.

view additional pages

Public Key Cryptography

An introduction to a powerful cryptographic system for use on microcomputers.

John Smith
21505 Evalyn Ave.
Torrance, CA 90503

Cryptography, the art of concealing the meaning of messages, has been practiced for at least 3000 years. In the past few centuries, it has become an indispensable tool in the military affairs, diplomacy, and commerce of most major nations. During that time there have been many innovations, and cryptography has changed and grown to accommodate the increasingly complex needs of its users. Present techniques are very sophisticated and provide excellent message protection. Current developments in computer technology and information theory, however, are on the verge of revolutionizing cryptography. New kinds of cryptographic systems are emerging that have incredible properties, which appear to eliminate completely some problems that have plagued cryptography users for centuries. One of these new systems is public key cryptography.

In public key systems, as in most forms of cryptography, a piece of information called a key is used to transform a message into cryptic form. In conventional cryptography this key must be kept secret, for it can also be used to decrypt the message. In public key cryptography, however, a message remains secure even if its encryption key is publicly revealed. This unique feature gives public key systems great advantages over conventional systems.

This article deals with the theory and application of public key cryptography. It reviews the methods and problems of traditional cryptography and describes the remarkable concept and advantages of public keys. It also describes a real public key cryptosystem, showing examples of the encryption and decryption operations; and it attempts to clarify the concept of trap-door one-way functions, upon which public key systems are based.

Computers are essential for implementing many modern cryptosystems, including the one described here. Several BASIC-language programs (TRS-80) are included to illustrate algorithms used in this system. These can be used to experiment with the encryption, decryption, and derivation of small keys.

Conventional Cryptosystems.

A cryptosystem must have two methods for transforming messages: a method of encryption, which renders messages unintelligible; and a method of decryption, for restoring them to their original forms. For simplicity, normal message text shall be called plaintext, and the encrypted form, ciphertext. Ciphertext messages may also be called cryptograms, or may just be called messages when it is clear that the encrypted form is meant.

To appreciate the significance of a public key system, we need to know some of the methods and problems of conventional cryptosystems. In a conventional system (see figure 1), a plaintext message is converted to a cryptogram by an encryptor and sent over a communication channel. While in transit, the cryptogram may be intercepted by someone other than the intended recipient. If it is encrypted well, it will be meaningless to the interceptor. At the receiving end, the cryptogram is converted back into plaintext by a decryptor. The encryptor and decryptor may be procedures executed by people or computers or may be specially constructed devices. In any case, they are both supplied with keys from a key source.

Cryptographic keys are analogous to the house and car keys we carry in our daily lives and serve a similar purpose. In many modern systems, each key is a string of digits. For example, keys defined by the Data Encryption Standard of the National Bureau of Standards consist of 64 binary digits, 56 of which are significant. To encrypt a message, a key and the message are somehow inserted into an encryptor, and the cryptogram that emerges is a jumble of characters that depends on both the message and the key. To decrypt the message, the correct key and the cryptogram are inserted into a decryptor, and the plaintext message emerges. In conventional systems, the correct key for decrypting a message is the same one used to encrypt it. Obviously, the keys used must be closely guarded secrets.

In a good system the number of possible keys should be very large, and decryption of any cryptogram should be possible with only very few of the keys, often with only one. These conditions make it impractical to try decrypting a message with one key after another until the one that reveals plaintext is found. The Data Encryption Standard provides more than 7 X 1016 keys (a 7 followed by 16 zeros), and there is some controversy over whether this number is sufficient!

The keys to be used are obtained from a key source, which selects them, perhaps randomly, from the large set of all usable keys. The key source may be located near the encryptor, near the decryptor, or elsewhere. But each key to be used must be made available to both the encryptor and the decryptor. Therein lies the most serious problem of conventional cryptosystems: some safe method must exist for distributing secret keys to the encryptor and the decryptor.

This problem is illustrated with a simple example: let’s say you want to communicate privately with a friend named Mary. Many communication channels are available to you, none of which may be completely private: telephone, mail, and computer networks, for examples. You could send encrypted messages, but Mary could not read them without the keys. And you dare not send secret keys over these public channels. One of you must visit the other, so that you could agree on a key to use for future correspondence. But if your communication need was for only one private message exchange, it could be transacted during the visit, rendering the conventional cryptosystem unnecessary. Or if your communication need were immediate, a personal visit could cause an unacceptable delay. And if you need to communicate with several people, all the necessary visits could entail considerable expense.

Most conventional cryptosystems, including the Data Encryption Standard system, have this problem. Public key cryptosystems, however, can avoid this problem entirely.

Public Key Systems.

The concept of public keys may be one of the most significant cryptographic ideas of all time. A public key system has two kinds of keys: encryption keys and decryption keys. It may seem that having two kinds would make the key distribution problem worse, or at least no better. These keys, however, have remarkable, almost magical, properties:

• for each encryption key there is a decryption key, which is not the same as the encryption key
• it is feasible to compute a pair of keys, consisting of an encryption key and a corresponding decryption key
• it is not feasible to compute the decryption key from knowledge of the encryption key

Because of these properties, Mary and you can use a public key system to communicate privately without transmitting any secret keys. To set it up, you generate a pair of keys, and send the encryption key to Mary by any convenient means. It need not be kept secret. It can only encrypt messages—not decrypt them. Revealing it discloses nothing useful about the decryption key. Mary can use it to encrypt messages and send them to you. No one but you, however, can decrypt the messages (not even Mary!), as long as you do not reveal the decryption key. Figure 2 illustrates the flow of information in this situation, with Mary on the left and you on the right. To allow you to send private messages to her, Mary must similarly create a pair of keys, and send her encryption key to you. You can also go a step further. Since your encryption key need not be kept secret, you can make it public, for example, by placing it in a computer network public file. Once you have done so, anyone who wants to send you a private message can look up your public key and use it to encrypt a message. Since you need not transmit the decryption key, and since it cannot be computed from your public key, the message is secure. Only you can decrypt it. Other people can place their encryption keys in the same public file, which would thus become a directory of public keys. Any two people with directory entries could then communicate privately, even if they had no previous contact. It would be necessary, however, to protect the keys in such a file so that no one could change someone else’s encryption key, for example, by substituting another encryption key. Fortunately, there is a way to protect the keys themselves with a public key cryptosystem, but that is another topic.

The RSA Cryptosystem.

Now that the general concepts of public key cryptography have been examined, the next problem is how to design an actual working system. Indeed, when Whitfield Diffie and Martin Hellman conceived the basic properties of this cryptosystem in 1976, no one knew how to make a system that could employ them. The situation was similar to that of space travel in 1950. It was conceivable, but no one had accomplished it. In 1977, three researchers at the Massachusetts Institute of Technology, Ron Rivest, Adi Shamir, and Len Adleman, published an elegant method for creating and using public keys.

In the Rivest-Shamir-Adleman (or RSA) cryptosystem, the keys are 200-digit numbers. The encryption key is the product of two secret prime numbers, having approximately 100 digits each, selected by the person creating the keys. The corresponding decryption key is computed from the same two prime numbers, using a nonsecret formula.

Anyone who knows the secret prime numbers can compute the decryption key, but the primes are hidden because only their product, the encryption key, is revealed. Of course, the primes may be discovered by factoring the key, but factoring such a number is about as easy as traveling to Alpha Centauri, especially if the person who constructs the number has done it in a way that discourages factoring. Rivest, Shamir, and Adleman estimated that a fast computer would require 3.8 billion years (nearly the estimated age of the earth) to factor a 200-digit key. Estimates of the time required to factor keys of several other lengths are shown in table 1.

Before encryption, a message is converted into a string of numbers. This step is common in cryptosystems, as it is in computers and communication systems. Next, the message is subdivided into blocks, much as computer text files are subdivided into records or sectors. Each block contains the same number of digits, and is treated as one large number during encryption. To encrypt the message, an arithmetic operation involving the encryption key is performed on each block, resulting in a cryptogram containing as many blocks as the original message. The arithmetic operation, described below, is the same for all blocks. To decrypt, the inverse arithmetic operation, which requires the decryption key, is performed on each block of the cryptogram. The result is the original message in its numerical form.

As you can imagine, it would be cumbersome to illustrate these operations with 200-digit numbers, so the detailed descriptions below use small keys and messages; otherwise, the operations shown are the same as those used in a full-size RSA system. Also, the encryption method described here is actually a subset of the original RSA method. This modification, which is due to Donald Knuth (see reference 3), uses the basic RSA technique, while lessening somewhat the number of computations involved. (For more detailed information, the reader should refer to the original Rivest-Shamir-Adleman paper, shown as reference 5.)

How to Encrypt.

While the encryption and decryption operations are normally performed by a computer program, I will describe them as if you were performing them by hand. Normally, the only manual operation required is entering the message to be encrypted.

Suppose you wish to encrypt the message

MARY HAD A LITTLE LAMB.

Once entered into a computer, the message will be in numerical form, frequently in ASCII (American Standard Code for Information Interchange). In ASCII, this message is

77 65 82 89 32 72 65 68 32

65 32 76 73 84 84 76 69 32 76 65 77 66 46

This is not yet encrypted, of course. It is merely written as a computer might represent it (all the numbers in this article are decimal). Group the message into blocks with six digits each:

776582 893272 656832 653276 738484 766932 766577 664600

Each block except the last consists of three consecutive characters from the ASCII representation above. The last block consists of the last two characters plus two zeros added at the right to make the final block as long as the rest. Digits added for this purpose may have any value.

Suppose that the encryption key, usually called n, is 94815109. This is the product of two prime numbers. To encrypt the message, treat each block as a number, and cube it modulo n (see the text box “Arithmetic with a Modulus”). For example, to encrypt the first block of the message:

(776582 X 776582 X 776582) mod 94815109 = 71611947

Performing the cubing operation on all eight blocks produces the cryptogram

71611947 48484364 03944704 03741778 61544362 35331577 88278091 50439554

Arithmetic modulo n is a fundamental part of the RSA system. It is also used in decryption and creating keys. Most of us have used arithmetic modulo n, although perhaps we didn’t call it that. For instance, arithmetic modulo 12 is frequently used in calculations related to keeping time. The text box “Arithmetic with a Modulus” reviews the mechanics.

Almost any method may be used to convert the text to numbers. It would have worked just as well to use A = l, B=2, . . . Z = 26, but the ASCII code is already in wide use, and it includes numbers for spaces and punctuation. The block length should be almost equal to the key length, because making it long minimizes the number of blocks per message. When considered as a number, however, no block should be as large as the key. For the above key, no block should be larger than 94815108. Making the block length slightly less than the key length ensures that this requirement is met. Of course, with full-length keys, there will be about 100 characters per block.

Listing 1 is a BASIC program that uses the above key to encrypt a line of text. Two lines of the program (670 and 680) perform the encryption. The rest deal with input, formatting, and printing. If desired, the encryption key in line 220 may be changed; use a key with seven or eight digits, or reduce the number of characters per block (line 210).

The programs in listings 1 through 4 were written for the TRS-80 BASIC interpreter, which is capable of 16-digit precision. They may be adapted for use with other interpreters, and I have tried to structure and annotate them well enough to make them easy to modify.

How to Decrypt.

Since the RSA system is a public key system, the decryption key, usually called d, differs from the public encryption key. For the above encryption key, d is 63196467. Knowing the value of d, you can decrypt the message by raising each cryptogram block to the power d, modulo n. That is, if a cryptogram block is C, you must compute (C) mod n. For example, to decrypt the first block of the above cryptogram:

(71611947^63196467) mod 94815109 = 776582

converts this block back to the first three ASCII codes of the original message. Each of the remaining blocks is decrypted in the same way. Fortunately, raising a number to a large power does not require performing a comparable number of multiplications. One efficient algorithm is a variation of the “Russian Peasant Method” of multiplication (see reference 4). It computes M = (C^d) mod n, as follows:

1. Let M = 1.

2. If d is odd, let M = (MXC) mod n.

3. Let C = (CXC) mod n.

4. Let d = integer part of d/2.

5. If d is not zero, repeat from step 2; otherwise, terminate with M as the answer.

To raise a number to the power 63196467, this algorithm executes its loop (steps 2 through 5) 26 times. It is employed as a subroutine in the BASIC-language decryption program of listing 2. Line 200 contains the keys, which may be changed, if desired. Lines 340 through 380 execute the algorithm.

How to Derive Keys.

Earlier, I said that it is feasible to derive a pair of keys, n and d, for encryption and decryption, but not feasible to calculate d from n. That seems incredible, but experts believe it is true when n and d are constructed in the following way.

The encryption key, n, is the product of two large prime numbers, p and q:

n = pq (1)

The decryption key, d, is calculated from p and q by

d = [ 2(p-l)(q-l) + 1 ]/3 (2)

Although n is made public, p and q remain secret. If n is sufficiently large, say 200 digits, it is practically impossible for anyone to factor it and discover the values of p and q; and without knowing p and q, it is equally difficult to compute d.

For the encryption and decryption examples given earlier, the keys were constructed as follows:

prime number, p = 7151 prime number, q = 13259 encryption key, n = 7151X13259

= 94815109 decryption key, d = (2X7150X 13258 + l)/3

= 63196467

Because p and q may have 100 or more digits in an operational RSA system, their selection requires computer assistance. The following three restrictions apply to how they should be chosen. First, neither p — 1 nor q — 1 must be divisible by 3, or the decryption operation will not work correctly. Second, p — 1 and q — 1 should both contain at least one large prime factor. Third, the ratio p/q should not approximate a simple fraction, e.g., 2/3, 3/4, etc., etc. These last two restrictions help ensure that n will be difficult to factor. Donald Knuth, in the second edition of his book (see reference 3), gives a detailed procedure for selecting p and q, which ensures that these restrictions are met. While the procedure described is for constructing 250-digit keys, it is applicable to other key lengths.

Enough keys are available for everyone. The number of 250-digit keys constructible with Knuth’s procedure is much greater than 10^200. For comparison, the number of atoms in the known universe is about 10^80.

To create a different pair of seven-or eight-digit keys, find primes p and q such that neither p — 1 nor q— 1 is divisible by 3, and the product n=pq is a seven- or eight-digit number. Then calculate d from formula (2). Divisibility by 3 is easily checked by casting out 3s, and the BASIC programs described below are helpful in finding prime numbers.

How to Find Large Prime Numbers.

To find a large prime number, select a random odd number of the required size and determine whether it is prime. If it is not, increase it (or decrease it) by 2 and try again, repeating until finding a prime. It is not necessary, however, to attempt to factor a number to determine whether it is prime.

To test whether a number n is prime, select any number greater than 1 and smaller than n, say x, and calculate

y = (x^n-1) mod n

If y is not equal to 1, n is not prime. But if y = 1, n may be prime, and further testing is required. Repeat the test using another value of x. If this test is performed with many different values of x, and if y = 1 for all the test cases, n is probably prime. Listing 3 is a BASIC program that uses 10 values of x to test a number for primality. If the program says the number is not prime, it is not prime. But if the program says the number is probably prime, there is a small chance that it is not.

What is the probability that this program will make an error? I don’t know, but it illustrates a class of programs, some of which are very good. Knuth (reference 3, page 375) presents one that is slightly more complicated, for which the odds against an error are a million to one when 10 values of x are used for testing, and are a million million to one when 20 values are used. For serious work I would use the more complicated program, but the one presented here illustrates the process of testing without factoring—and it doesn’t seem bad. It has not made an error in several hundred trials.

Listing 4 is a BASIC program that searches for a prime number using the same test method as the previous program. The program will begin with the number you enter and search downward until it finds a probable prime, which it will identify. If you enter 99999999, it will find the largest eight-digit prime. This program helps to find primes for constructing small keys like the ones above.

One-Way Functions and Trap-Doors.

Public key cryptosystems derive their unusual properties from mathematical functions called trap-door one-way functions, which are useful because they can act as ordinary functions or as one-way functions.

One-way functions are like oneway streets. The ordinary cube function, B = A3, resembles a one-way function in that it is easier to calculate B, given A, than it is to calculate A, given B. The latter calculation, the cube-root function, is called the inverse of the cube function. The inverse of an automobile would convert smog to gasoline. A mathematical function is said to be one-way if it is much more difficult to compute the inverse than to compute the function itself. To qualify as a one-way function, the inverse must be very difficult to compute, even by machine.

A function that could be computed in a few seconds, for which computing an inverse required thousands of years, would fit the definition.

To create a public key cryptosystem, a trap-door one-way function is used. It is easy to compute an inverse of a trap-door one-way function, but it can be very difficult to determine how. Computing an inverse can take millions of years because finding out how to do it can take that long. If the method is known, computing an inverse may take only a few seconds. This is a completely different situation than that created by a one-way function, for which there is no easy way to compute an inverse. When a trap-door one-way function is being constructed, the person constructing it has access to information, called trap-door information, that reveals how to compute inverses. Once the function is constructed, the trap-door information is hidden so well that it can take millions of years to find.

The Knuth modification of the RSA system encryption function, cubing a number modulo n, is a trapdoor one-way function. Its inverse function is the cube root modulo n. In arithmetic modulo n, “cube root” is defined as in ordinary arithmetic: if B is the cube of A, then A is the cube root of B. Notice that this definition does not say how to compute cube roots (in either kind of arithmetic). If you know how to compute cube roots modulo n, you know how to decrypt messages. In modulo n arithmetic, the cube root of B is computed by raising B to some power d, modulo n. But knowing this doesn’t help unless you know the value of d. And d can be computed by formula (2) if n has two factors (p and q), and p — 1 and q — 1 are not divisible by 3. If you construct the modulus, n, you know p and q, and can therefore calculate the value of d. Knowing d, you can compute cube roots; in other words, decrypt cryptograms. The values of p and q are hidden from other people by the difficulty of factoring n. They are deprived of the value of d, and therefore cannot compute cube roots. Hence, they cannot decrypt cryptograms created by cubing modulo n. In the RSA system, the value of d is the trap-door information that reveals how to compute inverses (cube roots). You might think of p and q as comprising a trap-door through which the value of d is obtained. Factoring n is analogous to finding the trap-door, but it is very difficult to do.

Other trap-door one-way functions undoubtedly exist, and these could be the foundations for other public key cryptosystems. For each of these systems, the same principles would apply. The creator of the system parameters would have access to certain trap-door information, which would reveal how to compute inverses. For everyone else, the trapdoor would be hidden, and for them the encryption function would be, in effect, a one-way function.

Is the RSA System Unbreakable?.

Successfully analyzing a cryptosystem, and being able to read its cryptograms without authorization, is called breaking the system. Theoretically, the RSA system can be broken by a determined analyst. Factoring the encryption key, or modulus, would do the trick, for then the decryption key could be easily calculated from formula (2), after which any message could easily be decrypted. However, factoring a key of the recommended length and construction does not seem feasible. Knuth gives a procedure for constructing a 250-digit key and considers it inconceivable at this time that such a key could be factored. Experts acknowledge that a breakthrough in the art of factoring large numbers would render the RSA system worthless but consider such a breakthrough extremely unlikely. Apparently, factoring large numbers is not a new problem, but one that expert mathematicians have attacked for centuries, and it is known to be very difficult.

Another way to break the system is to determine the value of d without factoring n. Although you can approach this problem in several ways, experts believe that none of them are likely to be fruitful.

Yet another method of breaking the system is to learn how to compute cube roots modulo n without knowing the value of d. Less seems to be known about the difficulty of doing this than is known about the difficulty of factoring n. At this time, no one knows how to compute such cube roots in a reasonable time without knowing d.

Any new cryptosystem should be viewed with suspicion. The accepted method of demonstrating the adequacy of a new system is to subject it to prolonged, concerted attack by people with experience in breaking other systems. If the new system proves resistant to such an attack, it may tentatively be considered secure. The process of validation is continuing, but a fairly large number of preliminary studies done so far indicate that the system is quite secure.

Digital Signatures.

Very closely related to public key cryptography is the concept of digital signatures. One problem with corresponding electronically, such as via a computer network, is that messages can be easily forged—you usually cannot be certain that the sender of a received message is actually the person claimed in the message. A public key cryptosystem, however, can be used to provide positive identification of any sender who has a public key on record. If, for example, Mary has filed a public key in some public access file, she can digitally sign a message to you by decrypting it with her private key before transmitting it. After receiving the message, you (or anyone else) can read the message by encrypting it with Mary’s public encryption key. The process is essentially the reverse of the cryptosystem: the message is first decrypted and then encrypted, and anyone can reveal the message, but only Mary with her secret decryption key can create it.

In addition, messages using digital signatures can be subsequently encrypted with another key. After Mary decrypts her message to you with her secret decryption key, she can then encrypt it with your public encryption key. The result is a message that only Mary could have created, and only you can read!

Messages with digital signatures have other interesting and useful properties and may be used to advantage with other (non-PKC) cryptosystems. These properties and applications might easily justify an article on digital signatures alone.

Summary.

This article has described the principles of public key cryptosystems. One example has been given, the Rivest-Shamir-Adleman system. We have seen how keys are constructed and used, and have at our disposal four BASIC programs for further experimentation. These programs may also be useful as models for assembly-language programs that could manipulate larger numbers and run faster. We have seen that the RSA cryptosystem provides public keys in more than astronomical quantities and that it is believed to be unbreakable.

Several questions come to mind: Is a personal computer powerful enough to run a full-size RSA system? How long would a small computer take to construct a 200-digit key? Or even a 100-digit key? How long would it take to decrypt a medium-length message?

Regardless of the answers to these questions, the prospects are good for using public key systems with small computers. New computer models appear almost monthly, and their performance is improving rapidly. The theoretical work that gave birth to the RSA system is also proceeding at a rapid pace, and we can expect new and different public key systems to result from that work. Some of these may be suitable, perhaps even optimized, for small machines, and the prospects are exciting.

view additional pages

Navy Brain Answers with Pictures

By George H. Waltz, Jr.
PS PHOTOS BY HUBERT LUCKETT

COMPLEX problems can now be reduced to three-dimensional, easy-to-understand answers by “Typhoon,” the latest thing in electronic brains. Built by the RCA Laboratories for the Navy Bureau of Aeronautics, the new computer is showing naval experts just how theoretical guided missiles will react in actual flight.

Up until the completion of the new $1,400,000 calculator a few months ago, the men whose job it is to create new and better guided missiles had to spend thousands of hours at complicated computations and many months at building full-size $100,000 test models. And when they were finished, there was no guarantee that the new missile would perform as expected.

Now, they can simply dial the design characteristics of any proposed guided-missile system into Typhoon and actually see in drawings and in three-dimensional models just how the missile will function. What’s even more valuable, the design characteris tics can be altered by twisting dials until the computer shows that the theoretical missile will track airplanes and score hits. And all this before a penny has been spent on costly missile construction.

Typhoon Tackles a Problem Most electronic brains buzz out answers that are mere figures. Not Typhoon. It actually demonstrates its answers in terms that even the layman can understand. When I first saw Typhoon operate recently at the RCA Laboratories in Princeton, N. J., the brain was set up to check the accuracy of a proposed radar-guided, rocket-propelled missile with a take-off speed of 720 m.p.h, against a bomber flying 360 m.p.h, at an altitude of 25,000 feet. Previously, 100 dials had been adjusted and some 6,000 plug-in connections had been made to feed the complicated problem into the brain.

When A. W. Vance, who developed the project, touched a red master switch on the long control console, the big brain went to work. As pilot lights flashed and relays clicked, two pens on each of two plotting boards—one board for the plan view, the other for elevation—began tracing out the flight paths of both the target airplane and the missile.

At the same time, two plastic balls suspended in a glass-walled booth and glowing under the illumination from ultraviolet lights, duplicated the movements of plane and missile in three dimensions. Nearby, a small-scale missile model, 12 inches long, 3/2 inches in diameter, and complete with operating control fins, went through all the motions, gyrations, and spins that the actual missile—if there were one—would go through on a flight to the target. In 60 seconds, the entire flight, which ended in a direct hit, had been simulated and recorded.

In one minute, the new computer, largest of its kind ever built, had made 250 additions, 67 multiplications, 30 integrations, and had solved 20 aerodynamic equations. All were carried on simultaneously with continuously varying factors—a chore that would have taken two mathematicians at least five years. Besides that, the brain had provided the answer in visual, understandable form as well as on records.

How would this same guided missile perform if the plane tried to avoid the missile by diving, zooming, and turning? To find out, evasive tactics were dialed into the portion of the brain that did the thinking for the plane. As I watched the two balls and the pens on the plotting boards, the theoretical “dog fight” came to life. I could see the zigzagging target plane being hunted by the guided projectile. I witnessed the actual hit.

A Cheek on New Theories With Typhoon, any guided missile problem can be run through over and over again. New theories can be tried and checked. The design of a missile can be varied for each run until the desired results are obtained. Thus, by avoiding the high cost of actual trial-and-error launching tests, the new brain can inform scientists how a missile will act under any set of conditions. It can help them to remove all the possible bugs long before the design leaves the drawing board.

Most electronic brains are either analogue computers (comparable to a slide rule) or digital computers (similar to an adding machine). Typhoon, however, is a combination of both and, by blending the two techniques in more complex forms, it achieves a flexibility and accuracy unattainable by either system alone. It is exact to better than one part in 25,000.

Typhoon’s nerve center consists of some 4,000 electron tubes, 600 supersensitive relays, several miles of intricate wiring, and thousands of condensers, resistors, and other components. Basically, it consists of five major sections—one for the missile, one for the system for guiding the missile, one for the target plane, one for calculating the results, and one for recording those results. It takes a staff of nine engineers and mathematicians plus six technical assistants to operate and maintain the computer. Also, since it seems that an electronic brain can get a cold in the head and not operate efficiently, the room in which the computer is housed is kept at a constant temperature of 75° F. and at a relative humidity of not more than 50 percent.

When solving a problem, the various varying factors enter the brain as voltages. These are then fed in the proper order to the components set up to add, subtract, multiply, and divide in the right sequence to provide a constantly changing answer. As a result, at any moment during a solution such things as the missile’s speed, yaw, pitch, roll, and fuel supply can be read from a bank of recorders. It is possible, for example, to determine the exact positions of each of the missile’s control fins at any instant.

Although the new computer, after it is installed in the Naval Research Laboratories at Johnsville, Pa., will be used principally to solve guided-missile problems., its abilities are by no means limited to that one function. Fed the characteristics of a new supersonic airplane design, the brain can tell you if the plane will fly as expected, and if not, why not. It can be used to pretest the hull designs for new surface ships and submarines or the streamlined shapes of bullets, bombs, and torpedoes.

Bigger Brain May Plot Defense And, unless its designers and users miss their guess, it will serve as a model for an even larger master calculator that will solve all the riddles connected with the successful defense of our cities and our coastlines against any possible enemy attack. The super-electronic brain they contemplate would be capable of duplicating all the possibilities of a combined land, sea, and air attack and illustrate in three dimensions the best possible methods of sure-fire defense!

ENGINEERS… RCA IS NOW CREATING TOMORROW’S MOST ADVANCED, COMPREHENSIVE ELECTRONIC DATA PROCESSING SYSTEMS!

Past-moving computer advances at RCA call for many more computer engineers. If you have a BS or advanced degree and at least 2 years’ design and development experience … this is your opportunity to team up with RCA scientists whose far-reaching new systems concepts utilize the latest digital techniques to broaden the scope of the electronic data processing field.

SPECIALIZE IN YOUR AREA OF INTEREST:
Transistor Circuits, Magnetic Core Memories, Rapid Access File, Switching Systems, Printed Wiring Design, Diagnostic Program Routings, Magnetic Circuits, Magnetic Tope Storage, High Speed Printing, High Speed Data Translation, Automatic Programming, System Analysis and Synthesis

Modern employe benefits . . .

Relocation assistance available.

BEGIN YOUR PROGRESS NOW WITH RCA—

Send complete resume of education and experience to:
Mr. John R. Weld Employment Manager
Dept. B-1F
Radio Corporation of America
Camden 2, N. J.

RADIO CORPORATION of AMERICA
ENGINEERING PRODUCTS DIVISION, CAMDEN, N.J.

Safety Computer Forecasts Atomic Fall-out Pattern

How “safe” is it to test an atom bomb ? Will wind-blown radioactive dust or charged rain clouds endanger life or crops in inhabited regions?

The National Bureau of Standards recently developed a “portable” analog computer to assist in predicting radioactive fall-out from a nuclear explosion. The fall-out pattern appears instantly on oscilloscope (left of photo) after weather data and the size and type of bomb are “told to” the computer by setting dials. As computers go, “portable” means that it will fit into a truck.

Wind-carried fall-out even from “small” atomic tests has traveled as far as Paris and Tokyo when caught in the “jet stream” of the upper atmosphere.

view additional pages

Apple Announces the Lisa 2

by Gregg Williams

When several of us at BYTE saw the Macintosh, we were seriously concerned about the fate of the Lisa in the face of the Macintosh, a machine that is one-third its price and clearly superior in some areas. Apple has answered these concerns by announcing two versions of the Lisa 2, along with the Macintosh, at its annual stockholders’ meeting on January 24.

New Features

The Lisa 2 will use the same modified Sony 3-1/2-inch floppy-disk drives as the Macintosh. It will be sold with a new, faster operating system, one 3V2-inch floppy disk, and 512K bytes of memory (the single drive takes the place of the two 5-1/4-inch drives in the Lisa 1). The Lisa 2 includes a mouse, detached keyboard, built-in 12-inch video display, and can be expanded to 1 megabyte (the memory capacity of the Lisa 1); it will cost “under $4000,” according to Apple (the exact price had not been decided when this was written). The Lisa 2/10 will add an internal 10-megabyte Winchester hard disk and will sell for “under $5500.” All the Lisa application programs will be available separately for $200 to $400 each. Apple planned to have the Lisa 2 available by January 24.

Software

Aside from the availability of a larger hard disk, the most welcome feature of the Lisa 2 family is that it will be able to run all Macintosh software as supplied on 3-1/2-inch disks. When the Lisa 2 boots a Macintosh program, the system will look and behave like a Macintosh, except that it will automatically take advantage of all the extra memory in the Lisa 2. Since literally hundreds of companies are developing Macintosh software, the Lisa 2’s ability to run it greatly increases its software base and, therefore, its usefulness.

Both the Lisa 2 and the 2/10 come without an operating system. Lisa 2 owners will need to buy the Macintosh operating system (unpriced at the time this was written); Lisa 2/10 owners can buy that operating system or the multitasking Lisa operating system (for about $300). With the Lisa operating system only, you will be able to have multiple windows, each of which can contain a separate application.

Apple is planning two new releases of Lisa software as well. The first release, available in late January, has optimized various parts of the operating system to make Lisa programs run faster and use the 10-megabyte hard disk. This software release will be free for anyone who bought the Lisa before September 12,1983 (when the price was reduced and the software was unbundled), and available at a nominal fee for buyers of unbundled Lisa software.

The second release of Lisa software will come sometime during the second quarter of 1984. This software will increase the integration among Lisa products (for the first time, you will be able to move graphics from Lisa Draw to a text document in Lisa Write, data from Lisa Calc to Lisa List, and data from Lisa Terminal to Lisa Calc, for example). It will also include enhancements in many of the Lisa application programs. For example, Lisa Write will include a spelling checker and the ability to process form letters, Lisa Graph will allow data to be graphed in new ways, all programs will support a $5000 laser printer and a 70-megabyte hard disk to be introduced by Apple, and Lisa Draw and Lisa Graph will support color printing. The second release of Lisa software will be available to owners of previous versions for a nominal fee.

Upgrading

Lisa 1 owners have two upgrading paths. Apple will let them upgrade to a Lisa 2 for free or to a Lisa 2/10 for $2500 (both upgrades involve replacing parts in the Lisa 1, not swapping the Lisa 1 for a new Lisa 2). In both cases, Lisa 1 owners will keep their 5-megabyte Profiles, thus allowing them to transfer all their information to the new system (by copying all such data from 5%-inch floppy disks to the Profile before converting to the Lisa 2).

Conclusions

With the announcement of the Lisa 2 and 2/10, Apple has made the Lisa computer both more competitive and part of an innovative, powerful, but still affordable family of computers. The reduced price and Macintosh software compatibility of the Lisa 2 make it far more attractive to potential buyers than the Lisa 1 was. The features added to the Lisa application programs make them even more useful than they currently are. Finally, Apple’s upgrading policy is commendable because it does not leave behind the Lisa 1 owners who supported the machine in its early days.

ANELEX

Anelex High Speed Line Printers are standard equipment in the data processing systems of almost every major computer manufacturer here and abroad.

Further information available upon request

ANelex Corporation

157 Causeway Street, Boston 14, Massachusetts

Related posts

• Expand your knowledge – Subscribe to Byte (Dec, 1961)
• RCA 301 computer now steps up to big system workpower! (Dec, 1961)
• “Radio Shack’s TRS-80 Computer Is the Smartest Way to Write” (Dec, 1961)
• FOR THE MATHEMATICIAN who’s ahead of his time (Dec, 1961)
• Engineering hours turn into minutes when you speed up your data analysis (Dec, 1961)
• What’s New in Mnemonics? (Dec, 1961)

“Radio Shack’s TRS-80 Computer Is the Smartest Way to Write”

Our word processing system changed Isaac Asimov’s mind about writing-and he’s a renowned science and science fiction author! But you don’t have to be an author to use a TRS-80. If you prepare memos, letters and reports-do what Isaac did. It will change your mind, too.

“I may never use a typewriter again!” Isaac likes the time he saves using SuperSCRIPSIT™ (26-1590, $199), our newest word processing program. “For example, I can assign frequently-used words and phrases to a user-defined key. So whenever I press that

key, the word or phrase is displayed instantly!”

“SuperSCRIPSIT gives me the advanced features I need, including true proportional spacing for even right and left margins, and automatic pagination.” For professional-looking letters, SuperSCRIPSIT supports underline, bold face, super and subscripts, and multiple column printing.

“A professional computer, too.”

Add VisiCalc® (26-1569, $199) for fast and accurate planning and forecasting. Or choose from a variety of other personal, management or entertainment programs, too.

“Surprisingly affordable!” This system includes the TRS-80 Model III computer with a built-in disk drive (26-1065), and the new DMP-200 dot-matrix printer (26-1254) that prints your documents correction-free at 520 words per minute and features a word processing mode for superb-looking correspondence. It has a graphics and data processing mode, too! With cable (26-1401), it all comes to just $2687! Try it out today at a Radio Shack Computer Center, store or participating dealer near

you-and be sure to ask to see our other TRS-80S, too.

Radio Shack
The biggest name in little computers

A DIVISION OF TANDY CORPORATION

Related posts

• Expand your knowledge – Subscribe to Byte (Jan, 1983)
• RCA 301 computer now steps up to big system workpower! (Jan, 1983)
• ANELEX (Jan, 1983)
• FOR THE MATHEMATICIAN who’s ahead of his time (Jan, 1983)
• Engineering hours turn into minutes when you speed up your data analysis (Jan, 1983)
• What’s New in Mnemonics? (Jan, 1983)

view additional pages

GENIAC

An interesting kit builds circuits that solve problems and play games.

“Electric brains” that work in much the same manner as giant computers can now be built quickly and cheaply by the novice using the new Geniac Construction Kit.

One of the most remarkable kits ever introduced to the public, the Geniac kit provides material and instructions for building 125 separate circuits for operating as many “brain machines.” Among the devices that may be built are logic machines for comparing and reasoning; cryptographic machines for coding and decoding; games such as tic-tac-toe and nim; arithmetic machines for both decimal and binary computations; puzzles such as “the space ship airlock,” “the fox, hen, corn, and hired man;” and miscellaneous devices such as a burglar alarm, an automatic oil furnace circuit, etc.

In addition to a complete assortment of all necessary parts is a carefully prepared instruction manual which explains in detail how to wire each circuit. The 63-page manual also furnishes basic information on the application of symbolic logic to circuits, which is the basis of the Geniac kit.

The kit is completely safe for anyone to use. No soldering is required, and every circuit operates on one common flashlight battery.

By the use of ingeniously designed parts, such as a new type multiple switch and special circuit jumpers, the kit provides circuits that “act out” or “prove” the truth of verbal statements about certain situations. One of the most popular of these circuits is the machine for the two jealous wives. In this problem, a “brain machine” must be devised that will inform either or both wives of unfaithfulness on the part of their husbands.

Mathematical basis for the Geniac circuits is the application of “Boolean algebra” to circuit design. George Boole, a nineteenth century British mathematician, evolved a system of logic in which symbols represent specific possibilities of things happening one way or another, such as A and B, or, A or B, etc. Certain types of information, when stated verbally, can be analyzed and reduced to simple statements. These statements, or “elements,” are, in turn, expressed in symbols. The symbolic statement or “formula” then represents the verbal statement. From the symbols, it can be determined what circuit components are needed and how, to a large extent, they must be arranged in order to provide a circuit that “acts out” the original statement. The gigantic computers that solve complex problems in the twinkling of an eye are based, in part, on these principles.

A good illustration of how this system works is the problem of the hall light, one of the circuits included in the kit. The problem, stated in normal language, is this: a man wants to turn off or turn on a hall light either from downstairs or from upstairs. A circuit must be devised so that if either switch is turned the light will go off if it was on, and will go on if it was off.

This is a practical problem and involves a kind of wiring that may be familiar to many readers. It implies a switching arrangement in which either of two switches may be “off” or “on” in any position, depending on the relative position of the other switch.

The circuit solution to this problem evolves logically from stating the problem in Boolean symbols. U represents the upstairs switch in one position, and D represents the downstairs switch in the same relative position. U-D represents the two switches in series and in positions that permit the flow of current to light the bulb. U’ and D’ represent both switches in their respective opposite positions. Thus, U’-D’ also represents a flow of current. U’-D and U-D’ both represent the switches in such relative positions as to break the circuit and permit no current to light the bulb.

Stating this in Boolean symbols: U-D v U’-D’. The “v” stands for an expression similar to “and/or” and implies a state of parallelism between the two expressions it connects. Thus, the formula tells us that two series switches are needed in parallel with each other. Since each switch must perform one of two possible functions (the “either-or” element), each switch must be a double-throw switch. The diagram and schematic shown here illustrate this reasoning process.

In every application of Boolean logic to a verbal statement, the circuit must prove the truth of the statement. In this case, the final circuit fulfills the requirements of the man with the upstairs and downstairs halls. In other circuits which can be built with the kit, a similar proof is achieved.

For instance, the kit may be used to construct an electronic version of tic-tac-toe. Now, anyone who has played this game knows that if you make the first move, regardless of what your opponent does, you must either win or draw, provided you make the best possible move following each of your opponent’s moves. In other words, the player who goes second cannot win unless the first player commits an error. The Geniac circuit for this situation is a complex one, but once constructed, proves infallible. In a word, you can’t beat the machine!

The underlying principles of the Geniac kit have been in development and research for a number of years. One of the best known pioneers in this country in the application of algebraic analysis to the problems of telephone circuitry is Dr. Claude Shannon of Bell Telephone Laboratories, whose “magnetic mouse” was described in Popular Electronics.

In addition to its value as a source of amusement and education, the kit exhibits certain technological features that may have widespread implications in other areas. The switches themselves are designed for simplicity and economy. Where the equivalent of several banks is needed, which ordinarily requires a multi-deck or multi-wafer switch built up vertically, the Geniac method uses a single wafer. Contacts on this wafer provide the equivalent—laterally—of what conventionally ganged switches do. This single wafer unit is an exclusive Geniac development.

Geniacs are manufactured by Oliver Garfield Co., Inc., 108 East 16th St., N. Y. 3, N. Y. and are available for $19.95 postpaid.

---

BUILD 125 COMPUTERS AT HOME WITH GENIAC
ONLY $19.95

With the 1958 model GENIAC®, the original electric brain construction kit including seven books and pamphlets, over 400 parts and component rack, and parts tray, and all materials for experimental computer lab plus DESIGN-O-Mat®.

A COMPLETE COURSE IN COMPUTER FUNDAMENTALS The GENIAC Kit by itself Is the equivalent of a complete course in computer fundamentals. In use by thousands of colleges, schools and industrial training labs and private individuals. Includes everything necessary for building an astonishing variety of computers that reason, calculate, solve codes and puzzles, forecast the weather, compose music, etc. Included in every set are seven books described below, which introduce you step-by-step to the wonder and variety of computer fundamentals and the special problems involved in designing and building your own experimental computers—the way so many of our customers have.

ANYONE CAN BUILD IT!

You can build any one of these 125 exciting electric brain machines in just a few hours by following the clear cut step by step directions given in these thrilling books. No soldering required … no wiring beyond your skill. But GENIAC is a genuine electric brain machine-not a toy. The only logic and reasoning machine kit in the world that not only adds and subtracts but presents the basic ideas of cybernetics, boolean algebra, symbolic logic automation etc. So simple to construct that a twelve year old can build what will fascinate a PhD. In use by thousands of schools, colleges, etc. and with the special low circuitry you can build machines that compose music, forecast the weather, which have just recently been added.

TEXT PREPARED BY MIT SPECIALIST Dr. Claude Shannon, known to the readers of Popular Electronics for his invention of the electronic mouse, that runs a maze, learning as it goes, formerly a research mathematician for Bell Telephone Laboratories is now a research associate at MIT. His books include publications on Communication theory and the recent volume “Automat Studies” on the theory of robot construction. He has prepared a paper entitled “A Symbolic Analysis of Relay and Switching Circuits” which is available to purchasers of the GENIAC. Covering the basic theory necessary for advanced circuit design it vastly extends the range of our kit.

The complete re-designing of the 1958 kit and the manual as well as the special book DESIGN-O-MAT® was created by Oliver Garfield, author of “Minds and Machines,” editor of the “Gifted Child Magazine” and the “Review of Technical Publications.”

KIT IS COMPLETE The 1958 GENIAC comes complete with seven books and manuals and over 400 components.

I) A sixty-four page book “Simple Electric Brains and How to Make Them.”

2} Beginners Manual—which outlines for people with no previous experience how to create electric circuits.

S) “A Symbolic Analysis of Relay and Switching Circuits” By Dr. Claude Shannon provides the basis for new and exciting experimental work by the kit owner who has finished book No. 1.

4) DESIGN-0-MAT; introduces the user to over 50 new circuits that he can build with GENIAC and outlines the practical principle of circuit design.

5) GENIAC STUDY GUIDE equivalent to a complete course in computer fundamentals, this guides the user to more advanced literature.

6) A Machine to Compose Music shows in an actual circuit what other GENIAC owners have been able to do on their own In designing new devices.

7) A Machine to Forecast the Weather—again a new adventure in scientific thinking created by one of our users who was trained on his GKN1AC Kit.

Plus all the components necessary for the building of over 125 machines and as many others as you can design yourself.

OVER 20,000 SOLD We are proud to announce that over 20.000 GEN I ACS are in use by satisfied’ customers-—schools, colleges, industrial firms and private individuals—a tribute to the skill and design work which makes it America’s leading scientific kit. People like yourself with a desire to inform themselves’ about the computer held know that GENIAC is the only method for learning that includes both materials and texts and is devoted exclusive to the problems faced in computer study.

Your are safe in joining this group because you are fully protected by our guarantee, and have a complete question and answer service available at no cost beyond that of the kit itself. You share in the experience of 20,000 kit users which contributes to the success of the 1958 GENIAC—with DESIGN-O-Mat® the exclusive product of Oliver Garfield Co., Inc., a Geniac is truly the most complete and unique kit of its kind in the world.

COMMENTS BY CUSTOMERS We know the best recommendation for GENIAC is what it has done for the people who bought it. The comments from our customers we like best are the ones that come in dally attached to new circuits that have been created by the owners of GENIACS. Recently one man wrote: “GENIAC has opened a new world of thinking to me.” Another who designed the “Machine that Forecasts the Weather” commented: “Several months ago I purchased your GENIAC Kit and found it an excellent piece of equipment. I learned a lot about computer* from the enclosed books and pamphlet* and I am now designing a small relay computer which will include arithmetical and logical units . . . another of my pet projects in cybernetics is a weather forecaster. I find that your GENIAC Kit may be used in their construction. 1 enclose the circuits and their explanation.” Eugene Darling, Maiden.

view additional pages

Science Newsfront

Last-minute news and notes to keep you up-to-date

By ARTHUR FISHER

NASA fights auto pollution

The big guns of aerospace technology are being enlisted in the battle against the major source of air pollution in this country—automobile exhaust. The mission: to reduce the one-quarter to one-half ton of carbon monoxide and hydrocarbons each car spews into the atmosphere in a year, as a result of incomplete fuel combustion. The battle plan: Develop a thermal reactor that would replace the standard exhaust manifold and serve as an afterburner. But such a reactor must withstand temperatures occasionally exceeding 2,000 degrees F, thermal shock from cold starts, and jarring vibrations—all problems routinely encountered in space exploration. That’s why the National Air Pollution Control Administration has asked NASA’s Lewis Research Center to help develop new materials and designs for thermal reactors. Engineers at Lewis are using a V8 engine hitched to a number of experimental reactors. They have learned that the temperature inside must reach a minimum of 1,400 degrees F to clean up exhaust products. Next will come studies to develop iron-chromium-aluminum alloys as reactor materials, and eventually a ceramic core that can withstand shock.

Shaking up the Lunar Rover

Vibration testing of Boeing’s Lunar Roving Vehicle is under way. Seen here on a large electromechanical vibrator, a test version of the moon explorer will be buffeted and jiggled to simulate the stresses of a Saturn V launch and actual operation on the lunar surface. The first of four Lunar Rovers is scheduled to be carried on a forthcoming Apollo mission. It will be nestled in a cargo bay at the bottom of the coming Apollo Lunar Module.

Shock waves break records

The fastest and most powerful shock waves ever produced by man have been generated at the Columbia University School of Engineering and Applied Science, as part of continuing research into ways to control hydrogen fusion. The waves flashed down a special, 10-foot-long metal tube at six million miles an hour—some 3,000 times faster than the speed of sound, and 10 times faster than any shock waves previously created. The tube was filled with deuterium—a hydrogen isotope. The waves, driven by a two-million-ampere jolt of electricity, heated the deuterium gas to more than 10 million degrees, enough to release neutrons and fuse its atoms into helium nuclei, actually the very essence of the fusion process.

Ink jets copy photos

A new technique developed at Sweden’s Lund Institute of Technology can make a nonphotographic high-quality copy of a picture on ordinary paper in just 40 seconds. It relies on writing with a thin jet of ink forced at high pressure through a nozzle. The jet draws a line on the moving recording paper. When 500 volts is applied to the nozzle, the jet instantly changes to a spray, and the line is interrupted (the spray droplets can be masked from the paper by a diaphragm). Thus the intensity of the line can be modulated by the voltage. The reproducing device actually scans the original optically and converts its information into electric signals, which then regulate the copying procedure to suit.

New wide-range laser

A new laser at Bell Laboratories, dubbed the “exciplex” for “excited-state complex,” can emit light in a range of colors from near ultraviolet to yellow-almost half the visible spectrum. The frequency desired can be selected by “tuning” the organic dye material that actually lases. Although other tunable dye lasers exist, this one has a tuning range four times greater than any previous single dye type—a very important advance for researchers who are investigating the interaction of light with matter and need to tailor the frequency of laser beams to specific requirements.

The rectangular chip you see almost lost on the face of a penny is a fullblown, infrared, continuous laser—the first of its kind. Made from a crystal of semiconductor materials, it can operate from a dry-cell battery at room temperatures, and needs no cooling. Thus a whole unit with power supply might take up no more room than a pocket flashlight. Scientists at Bell Laboratories, where the mini-laser was developed, say it will run for years and will cost mere dollars to produce. This laser, or one like it, will probably see duty in the not-too-distant future in communications systems. A single laser beam can carry many thousands of electronic signals, including phone, radio, and TV communications.

Salting the oceans with gold

The U.S. Government is dumping gold into the oceans. No, it’s not a gigantic boondoggle, but a joint effort of the AEC and the Army Corps of Engineers to study the effects of ocean currents on coastline erosion and sediment flow. The researchers dump sand tagged with minute amounts of radioactive isotopes of gold in coastal waters a short distance offshore. Then underwater radiation detectors can trace its movement out to sea up to 1,500 feet and parallel to the coastline more than 8,000 feet. Only a quart of the glittery sand is needed to investigate an area of more than 500,000 square feet of water-borne sediments. The dispersal can be monitored for a week before dilution and the radioactive decay make the gold undetectable.

Fort to get honorable discharge The Departments of Defense and Health, Education and Welfare are reported to be planning to convert the super-secret Ft. Detrick, Md., facility into a civil lab—possibly for critical medical and environmental research. Ft. Detrick has been a center for research in chemical and biological warfare.

Related posts

• A True Light Amplifier – The First Laser (Nov, 1970)
• Cutting wood with a beam of light (Nov, 1970)
• The coming record revolution: digital discs (Nov, 1970)
• Early Laser Pointer (Nov, 1970)
• How Lasers Are Going to Work for You (Nov, 1970)
• First Continuous Laser (Nov, 1970)

view additional pages

AUTOMATION

Robot Machines Are Cutting Costs, Boosting Profits and Making Jobs, Bringing More Leisure to Everyone.

THOUGH its history is brief, automation already has its own folklore. One of its most widely told legends concerns C.I.O. President Walter P. Reuther and a Ford executive who were touring Ford’s automated engine plant in Cleveland. As they strode past huge self-operating tools that bored cylinder holes, positioned connecting rods and bolted down manifolds, the Ford executive wisecracked: “You know, not one of these machines pays dues to the U.A.W.” Retorted Reuther: “And not one of them buys new Ford cars, either.”

In 1950, when automation was just getting under way, Norbert Wiener, M.I.T. mathematics professor and pioneer in the development of automated machines, forecast that automation would reduce wage earners to “slave labor,” and bring on an economic crash that would make “the Depression of the ’30s seem a pleasant joke.” Now Wiener has changed his mind: man is becoming automation’s master, not its slave. He cheerfully concedes that automation is “increasing man’s leisure, enriching his spiritual life.”

Coined only eight years ago by Ford Executive Vice President Delmar S. Harder, “automation” first described the automatic transfer of auto parts from one metalworking machine to the next. But its meaning has broadened as fast as its application. A few purists still claim that it should be applied only to completely automatic machines that feed back into themselves reports of how they are doing, and correct themselves if necessary. But most businessmen lump under automation all automatic machines and processes, including the giant tools that follow directions punched on a tape, huge computers that make thousands of intricate mathematical calculations in a fraction of a second, gauges that check fractions of a hairbreadth with a tiny beam of light.

The growth of automation is impressive. Of the $720 million spent by the oil-processing industry in 1955 for capital improvements, 15% went for automation. Manufacturers of automatic controls last week estimated that they have installed automated equipment in 100,000 U.S. manufacturing plants during the last few years, “yet hardly scratched the surface.” After the broadest survey yet on automation’s markets, the American Society of Tool Engineers reported that automation will account for 18% of metalworkers’ equipment orders this year. In the aircraft industry one-fifth of all money spent for equipment this year will go for pushbutton machines; one-third of the automakers’ 1956-57 equipment orders will be invested in automation. Among the items on U.S. industry’s automation shopping list: 25,000 welding machines, 55,000 grinders and finishers. 200,000 machine tools.

Automation has been force-fed by the boom. With wages constantly going up and skilled labor hard to find, many a businessman has turned to bigger and better machines to keep costs down and production up. Moreover, automation is most profitable in a time of full production: so much money is invested in the automated tool that a plant manager must keep it at work. In Jenkintown, Pa., for example, the Standard Pressed Steel Co. installed a $140,000 automated furnace in its bolt factory. The furnace could be operated by one man instead of five; it boosted bolt production 133% to 2,100 lbs. hourly. But unless it kept running continuously, it was not profitable.

Barreled Benefits. The nation’s most automated industries are chemicals and oils. If it were not for automation, the U.S. motorist would pay a much higher price for gasoline than he does. While the oil industry’s average wage jumped from $1.87 hourly in 1949 to $2.47 hourly last year, automation boosted production so fast that the labor cost per barrel of finished products dropped from 28.3^ to 23.7^. Refinery workers also benefited. For example, as production at Texas’ McMurrey Refining Co. increased from $7,500,000 of high-quality motor fuels a year to $22 million, weekly paychecks rose from an average of $82 to $114. and the total payroll increased. Said President Marvin H. McMurrey: “We have never had any trouble with our union people over automation, and I think the reason is that they realize there wouldn’t be as many jobs available as there are now if we weren’t fully automated. If we went back to old hand production methods, we simply couldn’t compete, and there wouldn’t be any jobs for anyone.”

For some industries it is not cost but quality of production that brings in automation. The airfoils of supersonic aircraft and guided missiles demand such close tolerance that the human hand is often incapable of milling and finishing to exact specifications. To end one time-wasting source of human error, North American Aviation installed an automated “skin mill” to mill i^-in. aluminum slabs into F-100 wing panels with one one-thousandth-in. tolerances, found that the robot millers could make a pair of perfect wings in 23 hours v. 20 hours for a skilled machinist with a possibility of error. North American’s new skin mill has worked out so well that the Air Force has ordered 48 more for U.S. aircraft plants, will install some automated giants that can mill wing panels up to 12 ft. wide and 45 ft. long.

Fast Answers. With the marvels of the automated factory has come the automated office, manned by electronic brains that set up orders, encode instructions to lesser machines, post accounts, send out bills, write letters and clank out p:ofit and loss statements. One of the newest of the great brains is the $5,500,-000 RCA-built Bizmac, now being installed in Detroit by the Army Ordnance Tank-Automotive Command to keep track of tank and auto parts all over the world. Operators who sit at Bizmac’s console can store away on magnetic tape records of 155,000 types of spare parts, lists of vehicles that use them, detailed inventories in major depots from Japan to West Germany. If, for example, the Army needs to check world supplies of tank crankshafts, Bizmac will compile records no more than 48 hours old, bring forth the reply in three minutes, feed it out at a speed of 600 printed lines a minute. To print up a new catalogue of spare parts, Bizmac’s operator needs only to press the proper buttons, and Bizmac’s 25 electric tapewriters will clack out pages ready for offset photography. Able as it is, Bizmac is only the prototype of even better computers that will be capable of running entire factories. Tomorrow’s great brain will start up machinery, feed in raw materials, switch from one product to the next as orders come in, convey parts to assembly lines, put them together, inspect, box, band and load finished products into freight cars and trucks.

Though automation has made a striking impact on U.S. industry, the great brain and the robot machine will never make the human mind and hand obsolete. In some companies automation is not practical. One manufacturer decided to convert all the clerical work to automatic processing by means of punch card order blanks that could be fed into machines. But many of his customers ignored his punch card blanks, and the system broke down. He found that some orders were taking five days to fill by automation, so he went back to pencil and typewriters.

For reasons of labor relations many an industrialist pooh-poohs reports that automation will eliminate jobs. But unless automation eliminates jobs, it is neither profitable nor practical. Detroit Machine Maker Charles F. Hautau claims that he can cut a man off the payroll for every $5,000 a manufacturer invests in Hautau’s automation machinery. However, for every skill eliminated, others will be created and upgraded.

Oilmen are already complaining about the shortage of control panel operators for automated refineries; these technicians must be part engineer, physicist, chemist and mechanic. General Electric is training 28,000 employees for automation’s better jobs, expects the company’s average pay to rise 50% to $8,000 in ten years. Though automation will displace some workers, in the long run the U.S. economic problem will not be unemployment but how to stretch the U.S. labor force enough to keep up with a population growth of 3% yearly and a standard of living that grows much faster. With every new production climb will come new demands for shorter hours, more leisure time. Once automation hits its full stride, the 30-hour week and the three-day weekend will not be far behind.

Related posts

• A Hundred Miles of Cookies Every Day (Mar, 1956)
• MODERN WONDERS of an Ancient Art Part II (Mar, 1956)
• The Brain Builders (Mar, 1956)
• Auto Made from Beans (Mar, 1956)
• Toys Keep Pace With Children’s Tastes (Mar, 1956)
• FOR THE MATHEMATICIAN who’s ahead of his time (Mar, 1956)

FOR THE MATHEMATICIAN who’s ahead of his time

IBM is looking for a special kind of mathematician, and will pay especially well for his abilities.

This man is a pioneer, an educator—with a major or graduate degree in Mathematics, Physics, or Engineering with Applied Mathematics equivalent.

You may be the man.

If you can qualify, you’ll work as a special representative of IBM’s Applied Science Division, as a top-level consultant to scientists, business executives and government officials on the application of Electronic Data Processing Machines. It is an exciting position, crammed with interest, and responsibility.

Employment assignment can probably be made in almost any major U. S. city you choose. Excellent working conditions and employee-benefit program.

For applicants with the same basic qualifications, opportunities are available to teach in this exciting, new field.

Your reply will, of course, be held in the strictest confidence. Write, giving full details of education and experience, to:

Dr. C. R. DeCarlo
DIRECTOR, APPLIED SCIENCE DIVISION

INTERNATIONAL BUSINESS MACHINES CORP.
590 Madison Avenue, New York 22, N. Y.

IBM Producer of electronic data processing machines, electric typewriters, and electronic time equipment.

Related posts

• Expand your knowledge – Subscribe to Byte (Mar, 1956)
• RCA 301 computer now steps up to big system workpower! (Mar, 1956)
• The Brain Builders (Mar, 1956)
• ANELEX (Mar, 1956)
• “Radio Shack’s TRS-80 Computer Is the Smartest Way to Write” (Mar, 1956)
• AUTOMATION (Mar, 1956)

Tiny new memory cell
Too small to be seen in detail with an ordinary microscope, this mite of a memory cell developed by Bell Telephone Laboratories appears here courtesy of the scanning electron microscope. (Some of the dust particles in this photo are the size of a wavelength of light.) The cells are a new kind of silicon semiconductor memory called “charge transfer diode memory,” and are destined for future telephone switching systems, where they will permit computer-memory access speeds in billionths rather than millionths of a second.