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.”)

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.

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.

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

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.

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

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.

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

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!

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

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.

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

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!

Скудность мысли порождает легионы единомышленников.

Another key strategic concept deriving from competitor analysis is creating a situation of mixed motives or conflicting goals for competitors. This strategy involves finding moves for which retaliation, though effective, would hurt the competitor’s broader position. For example, as IBM responds to the threat of the minicomputer with its own minicomputer, it may hasten the decline in growth of its large computers and accelerate the changeover to minicomputers. Placing competitors in a situation of conflicting goals can be a very effective strategic approach for attacking established firms that have been successful in their markets. Small firms and newly entered firms often have very little legacy in the existing strategies in the industry and can reap great rewards from finding strategies that penalize competitors for their stake in these existing strategies.

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.

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

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.

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

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.

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.

Человек эпической низости.

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.

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.

… 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.

It was an IBM machine, archaic now but gaudy then. The university owned it, in effect, and it lay inside a room that none but the machine’s professional caretakers could enter during the day. But Alsing found out that a student could just walk into that room at night and play with the computer. Alsing didn’t drink much and he never took any other drugs. “I was a midnight programmer,” he confessed.

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.

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.

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.

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.

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.

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

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

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.

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.

Finding a situation that catches the key competitor or competitors with conflicting goals is at the heart of many company success stories. The slow Swiss reaction to the Timex watch provides an example. Timex sold its watches through drugstores, rather than through the traditional jewelry store outlets for watches, and emphasized very low cost, the need for no repair, and the fact that a watch was not a status item but a functional part of the wardrobe. The strong sales of the Timex watch eventually threatened the financial and growth goals of the Swiss, but it also raised an important dilemma for them were they to retaliate against it directly. The Swiss had a big stake in the jewelry store as a channel and a large investment in the Swiss image of the watch as a piece of fine precision jewelry. Aggressive retaliation against Timex would have helped legitimize the Timex concept, threatened the needed cooperation of jewelers in selling Swiss watches, and blurred the Swiss product image. Thus the Swiss retaliation to Timex never really came. There are many other examples of this principle at work. Volkswagen’s and American Motor’s early strategies of producing a stripped-down basic transportation vehicle with few style changes created a similar dilemma for the Big Three auto producers. They had a strategy built on trade-up and frequent model changes. Bic’s recent introduction of the disposable razor has put Gillette in a difficult position: if it reacts it may cut into the sales of another product in its broad line of razors, a dilemma Bic does not face.4 Finally, IBM has been reluctant to jump into minicomputers because the move will jeopardize its sales of larger mainframe computers.

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.… Bezos’ vision of the online retailing universe was so complete, his Amazon.com site so elegant and appealing, that it became from Day One the point of reference for anyone who had anything to sell online. And that, it turns out, is everyone.

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.

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.

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…

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.

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?