Ibm Quotes

I have my own theory about why decline happens at companies like IBM or Microsoft. The company does a great job, innovates and becomes a monopoly or close to it in some field, and then the quality of the product becomes less important. The company starts valuing the great salesmen, because they’re the ones who can move the needle on revenues, not the product engineers and designers. So the salespeople end up running the company.

When deep space exploration ramps up, it'll be the corporations that name everything, the IBM Stellar Sphere, the Microsoft Galaxy, Planet Starbucks.

(Thomas J. Watson Sr. of IBM followed the same rule: “I’m no genius,” he said. “I’m smart in spots—but I stay around those spots.”)

IBM experimented with adding Urban Dictionary data to its artificial intelligence system Watson, only to scrub it all out again when the computer started swearing at them.

NOTHING APPLIES, I print with the magnetized IBM pencil. What does apply, they ask later, as if the word "nothing" were ambiguous, open to interpretation, a questionable fragment of an Icelandic rune.

A while back, I came across a line attributed to IBM founder Thomas Watson. If you want to achieve excellence, he said, you can get there today. As of this second, quit doing less-than-excellent work.

I came to see, in my time at IBM, that culture isn’t just one aspect of the game—it is the game.

Goods in any storehouse are useless until somebody takes them out and puts them to the use they were meant for. That applies to what man stores away in his brain, too. —THOMAS J. WATSON, FORMER PRESIDENT OF IBM

And Thomas Watson, chairman of IBM, said in 1943, “I think there is a world market for maybe five computers.

Watson, Sr., was running IBM, he decided they would never have more than four layers from the chairman of the board to the lowest level in the company. That may have been one of the greatest single reasons why IBM was successful.

In the past, pure scientists took a snobbish view of business. They saw the pursuit of money as intellectually uninteresting, suited only to shopkeepers. And to do research for industry, even at the prestigious Bell or IBM labs, was only for those who couldn't get a university appointment. Thus the attitude of pure scientists was fundamentally critical toward the work of applied scientists, and to industry in general. Their long-standing antagonism kept university scientists free of contaminating industry ties, and whenever debate arose about technological matters, disinterested scientists were available to discuss the issues at the highest levels.

These guys are fakes. All they've got on their minds is impressing the new girls with the big words they're so proud of, while sticking their hanse up their skirts. And when they graduate,they cut their hair short and march off to work for Mitsubishi or IBM or Fuji Bank. They marry pretty wives who've never read Marx and have kids they give fancy names to that are enough to make you puke. Smash what educational-industrial complex? Don't make me laugh!

recent IBM poll of fifteen hundred CEOs identified creativity as the number-one “leadership competency” of the future.

mandelbrot changed the way ibm's engineers thought about the cause of noise. bursts of errors had always sent the engineers looking for a man sticking a screwdriver somewhere.

The year before, 279,000 Apple IIs were sold, compared to 240,000 IBM PCs and its clones.

One reason alone is enough for today, and that reason lies in the national misconception of what constitutes education. All of your lives you have been trained to believe that your mental equipment consisted of learning how to memorize a multitude of facts. This is what I call parroting a man. To my mind, this inadequate concept of education is the crime of the age.

The two directions of thinking are the outward direction toward your material equipment which gives you your resources, and the inward direction toward your mental equipment, which gives you your resourcefulness.

A promising junior executive of IBM was involved in a risky venture for the company and managed to lose over $10 million in the gamble. It was a disaster. When Watson called the nervous executive into his office, the young man blurted out, 'I guess you want my resignation?' Watson said, 'You can't be serious. We've just spent $10 million educating you!

We cannot change situations in life, but we can change our attitude towards them

Скудность мысли порождает легионы единомышленников.

I have my own theory about why decline happens at companies like IBM or Microsoft.

The colonel dwelt in a vortex of specialists who were still specializing in trying to determine what was troubling him. They hurled lights in his eyes to see if he could see, rammed needles into nerves to hear if he could feel. There was a urologist for his urine, a lymphologist for his lymph, an endocrinologist for his endocrines, a psychologist for his psyche, a dermatologist for his derma; there was a pathologist for his pathos, a cystologist for his cysts, and a bald and pendantic cetologist from the zoology department at Harvard who had been shanghaied ruthlessly into the Medical Corps by a faulty anode in an I.B.M. machine and spent his sessions with the dying colonel trying to discuss Moby Dick with him.

IBM and other mainframe companies spent more money selling their products and serving their customers than they did in actually building their machines. They sold their computers to people who were actually going to use them, not to middlemen, and this market required good manners. Microcomputer companies sold equipment as if it were corn, in large quantities; they spent most of their money making things and competed not by being polite but by being aggressive.

Jack quit his advertising job and devoted himself to the life of the pen. Or rather, to the life of the Remington, soon to be replaced with an IBM Selectric, with the bouncing ball that let you change the typeface. Now that was cool!

At IBM, a corporation that embodied the ideal of the company man, the sales force gathered each morning to belt out the company anthem, “Ever Onward,” and to harmonize on the “Selling IBM” song, set to the tune of “Singin’ in the Rain.

The I.B.M. machine has no ethic of its own; what it does is enable one or two people to do the computing work that formerly required many more people. If people often use it stupidly, it's their stupidity, not the machine's, and a return to the abacus would not exorcise the failing. People can be treated as drudges just as effectively without modern machines.

Apple Computers is a famous example: it was founded by (mostly Republi­can) computer engineers who broke from IBM in Silicon Valley in the 198os, forming little democratic circles of twenty to forty people with their laptops in each other's garages.

A billion hours ago, modern Homo sapiens emerged. A billion minutes ago, Christianity began. A billion seconds ago, the IBM personal computer was released. A billion Google searches ago… was this morning. —HAL VARIAN, GOOGLE’S CHIEF ECONOMIST, DECEMBER 20, 2013

… as I associated with more and more different types, I realized that to make it, you had to get along with almost everybody. If you dislike the people you work with, you’d better not show it. I learned that to be a good leader, I had to strike a delicate balance.

By contrast Hobie lived and wafted like some great sea mammal in his own mild atmosphere, the dark brown of tea stains and tobacco, where every clock in the house said something different and time didn’t actually correspond to the standard measure but instead meandered along at its own sedate tick-tock, obeying the pace of his antique-crowded backwater, far from the factory-built, epoxy-glued version of the world. Though he enjoyed going out to the movies, there was no television; he read old novels with marbled end papers; he didn’t own a cell phone; his computer, a prehistoric IBM, was the size of a suitcase and useless.

Some research suggests that collecting vast amounts of data simply can’t predict rare events like terrorism. A 2006 paper by Jeff Jonas, an IBM research scientist, and Jim Harper, the director of information policy at the Cato Institute, concluded that terrorism events aren’t common enough to lend themselves to large-scale computer data mining.

Человек эпической низости.

Drugs are in every walk of life - doctors, lawyers, preachers, the guy who works for IBM, teenagers on the street, teenagers in school.

En lugares como IBM, que se especializa en mejoras cotidianas realizadas por equipos de ingenieros, esta es la forma preferida de entender cómo se produce realmente la innovación.

Once IBM gains control of a market sector, they almost always stop innovation.

IBM veteran and computer science professor Frederick Brooks argued that adding manpower to complex software projects actually delayed progress.

Within IBM at that time, growing a beard without getting fired was an indisputable mark of technical genius. In

Big Thinkers like IBM’s Watson are programmed and named to sound like men.

Hyperledger.org is a corporate open source Potemkin village of the sort IBM has long favoured: the illusion of an open project, with no “there” there.

In other words, I realized that for IBM to become a great company it would have to act like a great company long before it ever became one.

el famoso ordenador de la película 2001: Una odisea en el espacio, que, según una leyenda urbana, lo habían llamado “HAL” porque eran las letras que precedían en el alfabeto a “IBM”.

The fashionable term now is “Big Data.” IBM estimates that we are generating 2.5 quintillion bytes of data each day, more than 90 percent of which was created in the last two years.36

I became a door-to-door IBM salesman in 1963, a job I had for six years. But most everyone thought it was a bad idea. Door-to-door salesmen were lower than used-car salesmen or attorneys.

– Наши дети становятся американцами. Они не читают по-русски. Это ужасно. Они не читают Достоевского. Как они смогут жить без Достоевского? На что художник Бахчанян заметил: – Пушкин жил, и ничего.

A billion hours ago, modern Homo sapiens emerged. A billion minutes ago, Christianity began. A billion seconds ago, the IBM personal computer was released. A billion Google searches ago… was this morning.

These guys are a bunch of phonies. All they’ve got on their minds is impressing the new girls with the big words they’re so proud of and sticking their hands up their skirts. And when they’re seniors, they cut their hair short and go trooping to work for Mitsubishi or IBM or Fuji Bank. They marry pretty wives who’ve never read Marx and have kids they give fancy new names to that are enough to make you puke.

As an IBM document describing the Watson technology points out: “We have noses that run, and feet that smell. How can a slim chance and a fat chance be the same, but a wise man and a wise guy are opposites?

The commercialization of molecular biology is the most stunning ethical event in the history of science, and it has happened with astonishing speed. For four hundred years since Galileo, science has always proceeded as a free and open inquiry into the workings of nature. Scientists have always ignored national boundaries, holding themselves above the transitory concerns of politics and even wars. Scientists have always rebelled against secrecy in research, and have even frowned on the idea of patenting their discoveries, seeing themselves as working to the benefit of all mankind. And for many generations, the discoveries of scientists did indeed have a peculiarly selfless quality... Suddenly it seemed as if everyone wanted to become rich. New companies were announced almost weekly, and scientists flocked to exploit genetic research... It is necessary to emphasize how significant this shift in attitude actually was. In the past, pure scientists took a snobbish view of business. They saw the pursuit of money as intellectually uninteresting, suited only to shopkeepers. And to do research for industry, even at the prestigious Bell or IBM labs, was only for those who couldn't get a university appointment. Thus the attitude of pure scientists was fundamentally critical toward the work of applied scientists, and to industry in general. Their long-standing antagonism kept university scientists free of contaminating industry ties, and whenever debate arose about technological matters, disinterested scientists were available to discuss the issues at the highest levels. But that is no longer true. There are very few molecular biologists and very few research institutions without commercial affiliations. The old days are gone. Genetic research continues, at a more furious pace than ever. But it is done in secret, and in haste, and for profit.

It is 1958,” he began. “IBM passes up a chance to buy a young fledgling company that has invented a new technology called xerography. Two years later, Xerox was born, and IBM has been kicking themselves ever since.

Every time a seismic shift takes place in our economy, there are people who feel the vibrations long before the rest of us do, vibrations so strong they demand action—action that can seem rash, even stupid. Ferry owner Cornelius Vanderbilt jumped ship when he saw the railroads coming. Thomas Watson Jr., overwhelmed by his sense that computers would be everywhere even when they were nowhere, bet his father’s office-machine company on it: IBM. Jeffrey Preston Bezos had that same experience when he first peered into the maze of connected computers called the World Wide Web and realized that the future of retailing was glowing back at him.

My big dream back then was to buy an IBM Selectric. I still have that dream. I really ought to buy a word-processor. Half the cabbies at Rocky own computers. They tell me they can write failed novels ten times faster on a PC.

If you look at economics textbooks, you will learn that homo economicus can think like Albert Einstein, store as much memory as IBM’s Big Blue, and exercise the willpower of Mahatma Gandhi. Really. But the folks that we know are not like that. Real people have trouble with long division if they don’t have a calculator, sometimes forget their spouse’s birthday, and have a hangover on New Year’s Day. They are not homo economicus; they are homo sapiens.

At that time in IBM you had to wear a white shirt, dark pants and a black tie with your badge stapled to your shoulder or something,” said Steve Bristow, an engineer. “At Atari the work people did counted more than how they looked.

Even thirty years later, reflecting back on the competition, Jobs cast it as a holy crusade: “IBM was essentially Microsoft at its worst. They were not a force for innovation; they were a force for evil. They were like ATT or Microsoft or Google is.” Unfortunately

Behind every text footnote is a file folder with all the hardcopy documentation needed to document every sentence in this book at a moment’s notice. Moreover, I assembled a team of hair-splitting, nitpicking, adversarial researchers and archivists to review each and every sentence, collectively ensuring that each fact and fragment of a fact was backed up with the necessary black and white documents.

(When the company was finally broken up in the 1980s to satisfy antitrust regulators, it was worth more than the combined worth of General Electric, General Motors, Ford, IBM, Xerox, and Coca-Cola, and employed a million people.) Bell moved to Washington, D.C., became

Throughout his career, Jobs liked to see himself as an enlightened rebel pitted against evil empires, a Jedi warrior or Buddhist samurai fighting the forces of darkness. IBM was his perfect foil. He cleverly cast the upcoming battle not as a mere business competition,

I realized much later in life that the reason this decision between MIT and IBM was so agonizing was because it wasn't really about choosing a career; it was about deciding who I was, which part of myself I wanted to be, and that's the hardest decision any of us has to make.

We needed a man to repair the machines, to keep them going and everything. And the army was always going to send this fellow they had, but he was always delayed. Now, we always were in a hurry. Everything we did, we tried to do as quickly as possible. In this particular case, we worked out all the numerical steps that the machines were supposed to do—multiply this, and then do this, and subtract that. Then we worked out the program, but we didn’t have any machine to test it on. So we set up this room with girls in it. Each one had a Marchant: one was the multiplier, another was the adder. This one cubed—all she did was cube a number on an index card and send it to the next girl. We went through our cycle this way until we got all the bugs out. It turned out that the speed at which we were able to do it was a hell of a lot faster than the other way, where every single person did all the steps. We got speed with this system that was the predicted speed for the IBM machine. The only difference is that the IBM machines didn’t get tired and could work three shifts. But the girls got tired after a while.

After IBM’s chess program Deep Blue beat Garry Kasparov in 1997, humans did not stop playing chess. Rather, thanks to AI trainers, human chess masters became better than ever, and at least for a while human-AI teams known as “centaurs” outperformed both humans and computers in chess.

...Sonra da, dördüncü yıla geldiklerinde, Mitsubishi'de IBM'de veya Fuji Bankası'nda işe alınmak için saçlarını kestiriyorlardı, sonra da Marx'ı hiç okumamış güzel bir genç kadınla evleniyorlar ve çocuklarına olmadık, gülünç adlar veriyorlardı. ...Öylesine gülünç ki, insanın ağlayası geliyor.

certain group of people in the United States tried an experiment. They tried the experiment of making a fortune without working, of making a fortune through the stock exchange. They extended the experiment until it exploded and all went down to earth.  “Aspects of World Trade” Thomas J. Watson Sr. July 31, 1930

In my Confessions, I told how I started by making a list of the clients I most wanted – General Foods, Lever Brothers, Bristol Myers, Campbell Soup Company and Shell. It took time, but in due course I got them all, plus American Express, Sears Roebuck, IBM, Morgan Guaranty, Merrill Lynch and a few others, including

Using Hollerith’s tabulators, the 1890 census was completed in one year rather than eight. It was the first major use of electrical circuits to process information, and the company that Hollerith founded became in 1924, after a series of mergers and acquisitions, the International Business Machines Corporation, or IBM.

But Mandelbrot continued to feel oppressed by France’s purist mathematical establishment. “I saw no compatibility between a university position in France and my still-burning wild ambition,” he writes. So, spurred by the return to power in 1958 of Charles de Gaulle (for whom Mandelbrot seems to have had a special loathing), he accepted the offer of a summer job at IBM in Yorktown Heights, north of New York City. There he found his scientific home. As a large and somewhat bureaucratic corporation, IBM would hardly seem a suitable playground for a self-styled maverick. The late 1950s, though, were the beginning of a golden age of pure research at IBM. “We can easily afford a few great scientists doing their own thing,” the director of research told Mandelbrot on his arrival. Best of all, he could use IBM’s computers to make geometric pictures. Programming back then was a laborious business that involved transporting punch cards from one facility to another in the backs of station wagons.

You were never to say you weren't "fine, thank you — and yourself?" You were supposed to be Heidi. You were supposed to lug goat milk up the hills and not think twice. Heidi did not complain. Heidi did not do things like stand in front of the new IBM photocopier saying, "If this fucking Xerox machine breaks on me one more time, I'm going to slit my wrists.

He also telephoned the Real Time Computer Complex on the ground floor of the Operations Wing to ask that an additional big I.B.M. computer be brought onto the line.

Хармс говорил: — Телефон у меня простой — 32–08. Запоминается легко. Тридцать два зуба и восемь пальцев.

All great masters in any line think positive thoughts, which they put into action with intensive desire tested and tempered by balanced judgement.   All

I believe the principles of structural revolution are the same,” Lou Gerstner pointed out in the middle of his positive transformation of IBM. “First, it takes personal commitment on the part of the CEO. This is not a job you can delegate. Second, it takes a willingness to confront and expel the people and the organizations that are throwing up roadblocks to the changes you consider critical.

You “burn” your way into the mind by narrowing the focus to a single word or concept. It’s the ultimate marketing sacrifice. Federal Express was able to put the word overnight into the minds of its prospects because it sacrificed its product line and focused on overnight package delivery only. In a way, the law of leadership—it’s better to be first than to be better—enables the first brand or company to own a word in the mind of the prospect. But the word the leader owns is so simple that it’s invisible. The leader owns the word that stands for the category. For example, IBM owns computer. This is another way of saying that the brand becomes a generic name for the category. “We need an IBM machine.” Is there any doubt that a computer is being requested? You can also test the validity of a leadership claim by a word association test. If the given words are computer, copier, chocolate bar, and cola, the four most associated words are IBM, Xerox, Hershey’s, and Coke. An astute leader will go one step further to solidify its position. Heinz owns the word ketchup. But Heinz went on to isolate the most important ketchup attribute. “Slowest ketchup in the West” is how the company

Historically, noted James Manyika, one of the authors of the McKinsey report, companies kept their eyes on competitors “who looked like them, were in their sector and in their geography.” Not anymore. Google started as a search engine and is now also becoming a car company and a home energy management system. Apple is a computer manufacturer that is now the biggest music seller and is also going into the car business, but in the meantime, with Apple Pay, it’s also becoming a bank. Amazon, a retailer, came out of nowhere to steal a march on both IBM and HP in cloud computing. Ten years ago neither company would have listed Amazon as a competitor. But Amazon needed more cloud computing power to run its own business and then decided that cloud computing was a business! And now Amazon is also a Hollywood studio.

The 1970s were the decade of megabytes. In the summer of 1970, IBM introduced two new computer models with more memory than ever before: the Model 155, with 768,000 bytes of memory, and the larger Model 165, with a full megabyte, in a large cabinet. One of these room-filling mainframes could be purchased for $4,674,160. By 1982 Prime Computer was marketing a megabyte of memory on a single circuit board, for $36,000.

Deep Blue, IBM’s chess-playing computer, was a sole entity, and not a team of self-improving ASIs, but the feeling of going up against it is instructive. Two grandmasters said the same thing: “It’s like a wall coming at you.” IBM’s Jeopardy! champion, Watson, was a team of AIs—to answer every question it performed this AI force multiplier trick, conducting searches in parallel before assigning a probability to each answer.

Under Armour. "Ahora estamos en el punto donde está ocurriendo un cambio y los consumidores están demandando más de esta información. Esta asociación con IBM nos permitirá aportar valor al consumidor de manera inédita, ya que integramos la tecnología de aprendizaje de máquinas de IBM Watson con los robustos datos de la comunidad Connected Fitness de Under Armour, la comunidad digital más grande del mundo de más de 160 millones de miembros". [4]

Think different” isn’t just a slogan. It’s a credo, one that made Apple the most profitable company in human history. People accused Steve Jobs of creating a “reality distortion field,” but he understood that reality is already distorted. Apple would never win by trying to build a better mainframe computer. That would have been playing by IBM’s rules. Instead, Apple created a personal computer because that was what it wanted the future to look like.

On May 3, 1997, a chess match began between Deep Blue, a chess computer built by IBM, and Garry Kasparov, the world chess champion and possibly the best human player in history. Newsweek billed the match as “The Brain’s Last Stand.” On May 11, with the match tied at 2½–2½, Deep Blue defeated Kasparov in the final game. The media went berserk. The market capitalization of IBM increased by $18 billion overnight. AI had, by all accounts, achieved a massive breakthrough.

When it came time to renegotiate the price, Hoff made a critical recommendation to Noyce, one that helped create a huge market for general-purpose chips and assured that Intel would remain a driver of the digital age. It was a deal point that Bill Gates and Microsoft would emulate with IBM a decade later. In return for giving Busicom a good price, Noyce insisted that Intel retain the rights to the new chip and be allowed to license it to other companies for purposes other than making a calculator.

As a part of their effort to turn Watson into a practical tool, IBM researchers confronted one of the primary tenets of the big data revolution: the idea that prediction based on correlation is sufficient, and that a deep understanding of causation is usually both unachievable and unnecessary. A new feature they named “WatsonPaths” goes beyond simply providing an answer and lets researchers see the specific sources Watson consulted, the logic it used in its evaluation, and the inferences it made on

It wasn’t until I got to the law firm that things started hitting me. First, the people around me seemed pretty unhappy. You can go to any corporate law firm and see dozens of people whose satisfaction with their jobs is below average. The work was entirely uninspiring. We were for the most part grease on a wheel, helping shepherd transactions along; it was detail-intensive and often quite dull. Only years later did I realize what our economic purpose was: if a transaction was large enough, you had to pay a team of people to pore over documents into the wee hours to make sure nothing went wrong. I had zero attachment to my clients—not unusual, given that I was the last rung down on the ladder, and most of the time I only had a faint idea of who my clients were. Someone above me at the firm would give me a task, and I’d do it. I also kind of thought that being a corporate lawyer would help me with the ladies. Not so much, just so you know. It was true that I was getting paid a lot for a twenty-four-year-old with almost no experience. I made more than my father, who has a PhD in physics and had generated dozens of patents for IBM over the years. It seemed kind of ridiculous to me; what the heck had I done to deserve that kind of money? As you can tell, not a whole lot. That didn’t keep my colleagues from pitching a fit if the lawyers across the street were making one dollar more than we were. Most worrisome of all, my brain started to rewire itself after only the first few months. I was adapting. I started spotting issues in offering memoranda. My ten-thousand-yard unblinking document review stare got better and better. Holy cow, I thought—if I don’t leave soon, I’m going to become good at this and wind up doing it for a long time. My experience is a tiny data point in a much bigger problem.

Одна знакомая поехала на дачу к Вознесенским. Было это в середине зимы. Жена Вознесенского, Зоя, встретила ее очень радушно. Хозяин не появился. – Где же Андрей? – Сидин в чулане. В дубленке на голое тело. – С чего это вдруг? – Из чулана вид хороший на дорогу. А к нам должны приехать западные журналисты. Андрюша и решил: как появится машина – дубленку в сторону! Выбежит на задний двор и будет обсыпаться снегом. Журналисты увидят – русский медведь купается в снегу. Колоритно и впечатляюще! Андрюша их заметит, смутится. Затем, прикрывая срам, убежит. А статьи в западных газетах будут начинаться так: «Гениального русского поэта мы застали купающимся в снегу…

There were movies to go see at the Gem, which has long since been torn down; science fiction movies like Gog with Richard Egan and westerns with Audie Murphy (Teddy saw every movie Audie Murphy made at least three times; he believed Murphy was almost a god) and war movies with John Wayne. There were games and endless bolted meals, lawns to mow, places to run to, walls to pitch pennies against, people to clap you on the back. And now I sit here trying to look through an IBM keyboard and see that time, trying to recall the best and the worst of that green and brown summer, and I can almost feel the skinny, scabbed boy still buried in this advancing body and hear those sounds. But

IBM is what it is today for three special reasons. The first reason is that, at the very beginning, I had a very clear picture of what the company would look like when it was finally done. You might say I had a model in my mind of what it would look like when the dream—my vision—was in place. The second reason was that once I had that picture, I then asked myself how a company which looked like that would have to act. I then created a picture of how IBM would act when it was finally done. The third reason IBM has been so successful was that once I had a picture of how IBM would look when the dream was in place and how such a company would have to act, I then realized that, unless we began to act that way from the very beginning, we would never get there. In other words, I realized that for IBM to become a great company it would have to act like a great company long before it ever became one. From the very outset, IBM was fashioned after the template of my vision. And each and every day we attempted to model the company after that template. At the end of each day, we asked ourselves how well we did, discovered the disparity between where we were and where we had committed ourselves to be, and, at the start of the following day, set out to make up for the difference. Every day at IBM was a day devoted to business development, not doing business. We didn’t do business at IBM, we built one

I think we're all just doing our best to survive the inevitable pain and suffering that walks alongside us through life. Long ago, it was wild animals and deadly poxes and harsh terrain. I learned about it playing The Oregon Trail on an old IBM in my computer class in the fourth grade. The nature of the trail has changed, but we keep trekking along. We trek through the death of a sibling, a child, a parent, a partner, a spouse; the failed marriage, the crippling debt, the necessary abortion, the paralyzing infertility, the permanent disability, the job you can't seem to land; the assault, the robbery, the break-in, the accident, the flood, the fire; the sickness, the anxiety, the depression, the loneliness, the betrayal, the disappointment, and the heartbreak. There are these moments in life where you change instantly. In one moment, you're the way you were, and in the next, you're someone else. Like becoming a parent: you're adding, of course, instead of subtracting, as it is when someone dies, and the tone of the occasion is obviously different, but the principal is the same. Birth is an inciting incident, a point of no return, that changes one's circumstances forever. The second that beautiful baby onto whom you have projected all your hopes and dreams comes out of your body, you will never again do anything for yourself. It changes you suddenly and entirely. Birth and death are the same in that way.

received a message on LinkedIn from an IBM executive who wrote, “Pat, I’ve been at IBM for a while and I have been following your content for a few years. I make good money, but I really want to be an entrepreneur. However, I have a wife and three kids and I’m kind of worried about them. What should I do?” We emailed back and forth for a while, and I asked him questions about who he wanted to be. He began to see that intrapreneurship looked like the ideal choice for him. This is when you’re part of a company and create a new business unit, lead a new initiative, or work out incentives that reward you for driving growth and innovation. In some cases, it might just mean being so indispensable that a company has to pay you equity to retain you.

Meanwhile, people are busy using fractals to explain any system that has defied other, more reductionist approaches. Since they were successfully applied by IBM's Benoit Mandlebrot to the problem of seemingly random, intermittent interference on the phone lines, fractals have been used to identify underlying patterns in weather systems, computer files, and bacteria cultures. Sometimes fractal enthusiasts go a bit too far, however, using these nonlinear equations to mine for patterns in systems where none exist. Applied to the stock market to consumer behavior, fractals may tell less about those systems than about the people searching for patterns within them. There is a dual nature to fractals: They orient us while at the same time challenging our sense of scale and appropriateness. They offer us access to the underlying patterns of complex systems while at the same time tempting us to look for patterns where none exist. This makes them a terrific icon for the sort of pattern recognition associated with present shock—a syndrome we'll call factalnoia. Like the robots on Mystery Science Theater 3000, we engage by relating one thing to another, even when the relationship is forced or imagined. The tsunami makes sense once it is connected to chemtrails, which make sense when they are connected to HAARP. It's not just conspiracy theorists drawing fractalnoid connections between things. In a world without time, any and all sense making must occur on the fly. Simultaneity often seems like all we have. That's why anyone contending with present shock will have a propensity to make connections between things happening in the same moment—as if there had to be an underlying logic.

Inspired by the punched railway tickets of the time, an inventor by the name of Herman Hollerith devised a system of punched manila cards to store information, and a machine, which he called the Hollerith Machine, to count and sort them. Hollerith was awarded a patent in 1889, and the government adopted the Hollerith Machine for the 1890 census. No one had ever seen anything like it. Wrote one awestruck observer, “The apparatus works as unerringly as the mills of the Gods, but beats them hollow as to speed.” Another, however, reasoned that the invention was of limited use: “As no one will ever use it but governments, the inventor will not likely get very rich.” This prediction, which Hollerith clipped and saved, would not prove entirely correct. Hollerith’s firm merged with several others in 1911 to become the Computing-Tabulating-Recording Company. A few years later it was renamed—to International Business Machines, or IBM.

As additional precautions, Kranz requested that a two-hundred-foot radio antenna (called a deep-space dish) in Australia be added to the global network tracking and communicating with the spacecraft, and that additional computers at the Goddard Space Flight Center in Maryland be what he called "cranked up" -- made ready for use. He also telephoned the Real Time Computer Complex on the ground floor of the Operations Wing to ask that an additional I.B.M. computer be brought onto the line.

I am so sorry to hear of Asher's passing. I will miss his scientific insight and advice, but even more his humor and stubborn integrity. I remember when one of his colleagues complained about Asher's always rejecting his manuscript when they were sent to him to referee. Asher said in effect, 'You should thank me. I am only trying to protect your reputation.' He often pretended to consult me, a fellow atheist, on matters of religious protocol. {Charles H. Bennett's letter written to the family of Israeli physicist, Asher Peres}

COBOL er i dag uten tvil verdens mest brukte høynivå programmeringsspråk. Det har vært i kontinuerlig bruk siden den første kompilatoren så dagens lys i 1960. En rekke versjoner av COBOL er blitt standardisert og internasjonalisert, først i 1968, senere i 1974 og i 1985. Som standardisert språk har COBOL klart vist sin verdi. Men på tross av dette har ettervirkningene fra utviklingen vært forholdsvis beskjedne, bortsett fra det IBM-utviklede generelle programmeringsspråket PL/1 som ble lansert i begynnelsen av 1970-årene. Kanskje en av grunnene til en manglende bred videreføring av COBOLs gode prinsipper og strukturer er at få har sett det mulig å gå videre. En annen grunn er kanskje at mesteparten av COBOL-brukerne er nettopp brukere og ikke teknologer. Den store masse av brukerne er enten ikke i stand til eller interessert i å utvikle et nytt programmeringsspråk, så lenge de har ett som virker bra, og som dessuten har vist seg å være utrolig pålitelig. COBOL har derfor vært uten virkelig konkurranse i over førti år. Selv i dag skrives det flere applikasjonsprogrammer i COBOL enn i hvilket som helst annet høynivå programmeringsspråk, FORTRAN inklusivt.

Then, in the end, the leader makes the call. It’s conflict and debate leading to an executive decision. No major decision we’ve studied was ever taken at a point of unanimous agreement. There was always some disagreement in the air. Our research showed that before a major decision, you would see significant debate. But after the decision, people would unify behind that decision to make it successful. Again, and I can’t stress this too much, it all begins with having the right people—those who can debate in search of the best answers but who can then set aside their disagreements and work together for the success of the enterprise.

One of those was Gary Bradski, an expert in machine vision at Intel Labs in Santa Clara. The company was the world’s largest chipmaker and had developed a manufacturing strategy called “copy exact,” a way of developing next-generation manufacturing techniques to make ever-smaller chips. Intel would develop a new technology at a prototype facility and then export that process to wherever it planned to produce the denser chips in volume. It was a system that required discipline, and Bradski was a bit of a “Wild Duck”—a term that IBM originally used to describe employees who refused to fly in formation—compared to typical engineers in Intel’s regimented semiconductor manufacturing culture. A refugee from the high-flying finance world of “quants” on the East Coast, Bradski arrived at Intel in 1996 and was forced to spend a year doing boring grunt work, like developing an image-processing software library for factory automation applications. After paying his dues, he was moved to the chipmaker’s research laboratory and started researching interesting projects. Bradski had grown up in Palo Alto before leaving to study physics and artificial intelligence at Berkeley and Boston University. He returned because he had been bitten by the Silicon Valley entrepreneurial bug.

a harbinger of a third wave of computing, one that blurred the line between augmented human intelligence and artificial intelligence. “The first generation of computers were machines that counted and tabulated,” Rometty says, harking back to IBM’s roots in Herman Hollerith’s punch-card tabulators used for the 1890 census. “The second generation involved programmable machines that used the von Neumann architecture. You had to tell them what to do.” Beginning with Ada Lovelace, people wrote algorithms that instructed these computers, step by step, how to perform tasks. “Because of the proliferation of data,” Rometty adds, “there is no choice but to have a third generation, which are systems that are not programmed, they learn.”27 But even as this occurs, the process could remain one of partnership and symbiosis with humans rather than one designed to relegate humans to the dustbin of history. Larry Norton, a breast cancer specialist at New York’s Memorial Sloan-Kettering Cancer Center, was part of the team that worked with Watson. “Computer science is going to evolve rapidly, and medicine will evolve with it,” he said. “This is coevolution. We’ll help each other.”28 This belief that machines and humans will get smarter together is a process that Doug Engelbart called “bootstrapping” and “coevolution.”29 It raises an interesting prospect: perhaps no matter how fast computers progress, artificial intelligence may never outstrip the intelligence of the human-machine partnership. Let us assume, for example, that a machine someday exhibits all of the mental capabilities of a human: giving the outward appearance of recognizing patterns, perceiving emotions, appreciating beauty, creating art, having desires, forming moral values, and pursuing goals. Such a machine might be able to pass a Turing Test. It might even pass what we could call the Ada Test, which is that it could appear to “originate” its own thoughts that go beyond what we humans program it to do. There would, however, be still another hurdle before we could say that artificial intelligence has triumphed over augmented intelligence. We can call it the Licklider Test. It would go beyond asking whether a machine could replicate all the components of human intelligence to ask whether the machine accomplishes these tasks better when whirring away completely on its own or when working in conjunction with humans. In other words, is it possible that humans and machines working in partnership will be indefinitely more powerful than an artificial intelligence machine working alone?

By that time, Bezos and his executives had devoured and raptly discussed another book that would significantly affect the company’s strategy: The Innovator’s Dilemma, by Harvard professor Clayton Christensen. Christensen wrote that great companies fail not because they want to avoid disruptive change but because they are reluctant to embrace promising new markets that might undermine their traditional businesses and that do not appear to satisfy their short-term growth requirements. Sears, for example, failed to move from department stores to discount retailing; IBM couldn’t shift from mainframe to minicomputers. The companies that solved the innovator’s dilemma, Christensen wrote, succeeded when they “set up autonomous organizations charged with building new and independent businesses around the disruptive technology.”9 Drawing lessons directly from the book, Bezos unshackled Kessel from Amazon’s traditional media organization. “Your job is to kill your own business,” he told him. “I want you to proceed as if your goal is to put everyone selling physical books out of a job.” Bezos underscored the urgency of the effort. He believed that if Amazon didn’t lead the world into the age of digital reading, then Apple or Google would. When Kessel asked Bezos what his deadline was on developing the company’s first piece of hardware, an electronic reading

What’s the best thing you’ve done in your work and career? In business decision-making, certainly one of your highlights was licensing your computer operating system to IBM for almost no money, provided you could retain the right to license the system to other computer manufacturers as well. IBM was happy to agree because, after all, nobody would possibly want to compete with the most powerful company in the world, right? With that one decision, your system and your company became dominant throughout the world, and you, Bill Gates, were on your way to a net worth of more than $60 billion. Or maybe you’d like to look at your greatest career achievement from a different angle. Instead of focusing on the decision that helped you make so much money, maybe you’d like to look at the decision to give so much of it away. After all, no other person in history has become a philanthropist on the scale of Bill Gates. Nations in Africa and Asia are receiving billions of dollars in medical and educational support. This may not be as well publicized as your big house on Lake Washington with its digitalized works of art, but it’s certainly something to be proud of. Determining your greatest career achievement is a personal decision. It can be something obvious or something subtle. But it should make you proud of yourself when you think of it. So take a moment, then make your choice.

In a 1997 showdown billed as the final battle for supremacy between natural and artificial intelligence, IBM supercomputer Deep Blue defeated Garry Kasparov. Deep Blue evaluated two hundred million positions per second. That is a tiny fraction of possible chess positions—the number of possible game sequences is more than atoms in the observable universe—but plenty enough to beat the best human. According to Kasparov, “Today the free chess app on your mobile phone is stronger than me.” He is not being rhetorical. “Anything we can do, and we know how to do it, machines will do it better,” he said at a recent lecture. “If we can codify it, and pass it to computers, they will do it better.” Still, losing to Deep Blue gave him an idea. In playing computers, he recognized what artificial intelligence scholars call Moravec’s paradox: machines and humans frequently have opposite strengths and weaknesses. There is a saying that “chess is 99 percent tactics.” Tactics are short combinations of moves that players use to get an immediate advantage on the board. When players study all those patterns, they are mastering tactics. Bigger-picture planning in chess—how to manage the little battles to win the war—is called strategy. As Susan Polgar has written, “you can get a lot further by being very good in tactics”—that is, knowing a lot of patterns—“and have only a basic understanding of strategy.

IBM is what it is today for three special reasons. The first reason is that, at the very beginning, I had a very clear picture of what the company would look like when it was finally done. You might say I had a model in my mind of what it would look like when the dream—my vision—was in place. The second reason was that once I had that picture, I then asked myself how a company which looked like that would have to act. I then created a picture of how IBM would act when it was finally done. The third reason IBM has been so successful was that once I had a picture of how IBM would look when the dream was in place and how such a company would have to act, I then realized that, unless we began to act that way from the very beginning, we would never get there. In other words, I realized that for IBM to become a great company it would have to act like a great company long before it ever became one. From the very outset, IBM was fashioned after the template of my vision. And each and every day we attempted to model the company after that template. At the end of each day, we asked ourselves how well we did, discovered the disparity between where we were and where we had committed ourselves to be, and, at the start of the following day, set out to make up for the difference. Every day at IBM was a day devoted to business development, not doing business. We didn’t do business at IBM, we built one Now,

I once heard a story about Tom Watson, the founder of IBM. Asked to what he attributed the phenomenal success of IBM, he is said to have answered: IBM is what it is today for three special reasons. The first reason is that, at the very beginning, I had a very clear picture of what the company would look like when it was finally done. You might say I had a model in my mind of what it would look like when the dream—my vision—was in place. The second reason was that once I had that picture, I then asked myself how a company which looked like that would have to act. I then created a picture of how IBM would act when it was finally done. The third reason IBM has been so successful was that once I had a picture of how IBM would look when the dream was in place and how such a company would have to act, I then realized that, unless we began to act that way from the very beginning, we would never get there. In other words, I realized that for IBM to become a great company it would have to act like a great company long before it ever became one. From the very outset, IBM was fashioned after the template of my vision. And each and every day we attempted to model the company after that template. At the end of each day, we asked ourselves how well we did, discovered the disparity between where we were and where we had committed ourselves to be, and, at the start of the following day, set out to make up for the difference. Every day at IBM was a day devoted to business development, not doing business. We didn’t do business at IBM, we built one Now,

Да речем, че съм обикновен човек, въпреки че това не е съвсем точно: няма обикновени хора. Но историята не ми е отредила някаква особена роля, нито пък, успокоявам се, е имало условия за такова нещо. Никога не съм драпал за ня- какво изключително място в живота. Това може би е после- дица от вродената ми срамежливост и стеснителност, а мо- же би и работа на домашното ми възпитание (израсъл съм в скромно чиновническо семейство) , при това никога не съм командвал други, нито пък това ме е привличало. Но затова пък други са ме командвали! По време на двайсетгодишната си служба смених над сто шефове, секретари, началници, помощници и директори. Те бяха какви ли не. Търпеливо чаках да се уморят малките тирани от властването и да из- чезнат от моя живот. Само каква наивност! Понякога и до- чаквах това (умираха или биваха свалени от длъжност), но, уви, наследяваха ги тозчас някакви млади, подобни на тях, бодри и отпочинали – жадни за власт и могъщество. Колко- то и да е незначително – господството няма край! Сякаш ми биваше по-добре с онези, предишните. Първо, биваха зна- чително по-възрастни от мене, освен това, много от тях с времето бяха затлъстели, натежали, уморили се от властва- не, станали някак си тромави и дори добродушни, защото се бяха уверили, че не желая да им отнемам поста. Трябваше, значи, да чакам и техните наследници да се наядат, да под- редят апартаменти и къщи, да изженят децата и най-накрая да мирясат... Но аз имам само един живот! А той далеч не е толкова дълъг, че да изтрае, докато се изредят всички онези, които са жадни за власт. Би било наивно да се вярва, че вла- стта – тази прастара подправка на историята – ще изчезне в някоя канцелария само затова, че са измислени електричес- ките пишещи машини, та кореспонденцията на шефовете вече не се преписва с подострено гъше перо от Гоголевия колежки секретар от четиринайсети чиновнически клас, а това вече извършва електронна машина IBM.

The collapse, for example, of IBM’s legendary 80-year-old hardware business in the 1990s sounds like a classic P-type story. New technology (personal computers) displaces old (mainframes) and wipes out incumbent (IBM). But it wasn’t. IBM, unlike all its mainframe competitors, mastered the new technology. Within three years of launching its first PC, in 1981, IBM achieved $5 billion in sales and the #1 position, with everyone else either far behind or out of the business entirely (Apple, Tandy, Commodore, DEC, Honeywell, Sperry, etc.). For decades, IBM dominated computers like Pan Am dominated international travel. Its $13 billion in sales in 1981 was more than its next seven competitors combined (the computer industry was referred to as “IBM and the Seven Dwarfs”). IBM jumped on the new PC like Trippe jumped on the new jet engines. IBM owned the computer world, so it outsourced two of the PC components, software and microprocessors, to two tiny companies: Microsoft and Intel. Microsoft had all of 32 employees. Intel desperately needed a cash infusion to survive. IBM soon discovered, however, that individual buyers care more about exchanging files with friends than the brand of their box. And to exchange files easily, what matters is the software and the microprocessor inside that box, not the logo of the company that assembled the box. IBM missed an S-type shift—a change in what customers care about. PC clones using Intel chips and Microsoft software drained IBM’s market share. In 1993, IBM lost $8.1 billion, its largest-ever loss. That year it let go over 100,000 employees, the largest layoff in corporate history. Ten years later, IBM sold what was left of its PC business to Lenovo. Today, the combined market value of Microsoft and Intel, the two tiny vendors IBM hired, is close to $1.5 trillion, more than ten times the value of IBM. IBM correctly anticipated a P-type loonshot and won the battle. But it missed a critical S-type loonshot, a software standard, and lost the war.