He has covered Silicon Valley and high-tech for more than 25 years, beginning with the San Jose Mercury News as the nation's first daily high-tech reporter. At the top of the list: building a computer capable of a teraflop -- a trillion floating-point operations per second. ... How we built machines that can think for themselves. If the company was going to stay in business, it would need a machine that could pull its weight outside AI research. As it turned out, there was never much danger of that. The CM-5 wasn't selling, and the company was hemorrhaging money. It was, says Stephen Wolfram, who founded the highly successful software company Mathematica, "the place that foreign trade delegations would come to visit to see where American business was at these days.". The announcement would be made on the third floor of the Carter Ink Building. According to “ Dancing With Robots: Human Skills for Computerized Work,” computers’ strengths lie in speed and accuracy, while humans’ strengths are all about flexibility. It had gone through three CEOs in two years and was losing money at a considerably faster rate than it had ever made it. If there was ever a time that Thinking Machines could, and needed to, put itself on a solid financial and competitive foundation by merging with a deep-pocketed company or by going public, it was now. Architect powerful systems and scalable data pipelines for data collection and data analysis. Customers were kept in the dark. Computer also can store a lot of data in their storage. I would first like to start off with the statement that I am arguing that machines can "think" like human, not that machines can feel human emotion nor be able to have the human experience (love, sensory emotion, etc. Requests for new laptop computers were being denied. When it came to general scientific computing, the CM-1 was "a dog," in the words of Gordon Bell, a computer guru and architect of the famous VAX computer at Digital Equipment Corp. Wall Street was sniffing around for an initial public offering. Even Hillis eventually came around and chose the moderately parallel design for the company's next generation of machine. The first 'petaflog' – i.e., a quadrillion operations per second – supercomputers were delivered earlier this year, and now designers are working on 'exaflop' – that's a quintillion, or 1,000,000,000,000,000,000 operations per second – computers. Michael S. Malone is one of the nation's best-known technology writers. Since the inception of the first computers, there has been a direct comparison between these “computational machines” and the human brain. After all, we've now been under the regime of Moore's Law for more than forty years …and like a Timex watch it just keeps on ticking away, doubling the power of everything digital every couple years. It is a growing feeling that perhaps a number of our smug certainties are now panning out the way they were supposed to. It had no facility for running FORTRAN, the de facto standard computer language of science; nor could it do what are known as "floating-point operations," the operations that manipulate numbers in scientific computation. An up-close look at a doomed-yet-brilliant computer startup that never quite grasped the basics of business. As the company forged ahead with its frantic effort to bring the new machine out on time, the corporate culture started to shift from openness to paranoia. Huge open spaces were created to stimulate idea sharing and creativity. Take exobiology. Humans are alive; machines are not. Some argue that if a machine could pass something known as the Turing Test, it would have achieved real intelligence. While the idea is entertaining, many consider the research and experiments upon which it is based to be unsettling at the least. “Thinking Machines = Old Algorithms on Faster Computers.” The real advance has been in the number-crunching power of digital computers. In short, Thinking Machines was becoming a hacker's paradise. Computer scientists like Ray Kurzweil contend that Artificial Intelligence (AI) will breeze past human intelligence — and keep on learning. What's more, there were signs that the company was still chasing the wrong market. One can buy and sell things online, bills and taxes can be paid online and can also predict the … Because the cost would be prohibitive for a university laboratory, they decided to form a company. The computers we have built are now capable of thinking for themselves, and doing complex jobs without our supervision. The brilliant start-up that ignited an industry never grasped the basics. In a recent poll, machine intelligence experts predicted that computers would gain human-level ability around the year 2050, and superhuman ability less than 30 years after. So yeah, at some point, assuming all kinds of advances and breakthroughs, it's not inconceivable we'll reach a point that machines do match human intelligence. Not to the extent of what humans can do today, but in an increasing number of areas these machines will show more and more human-like intelligence, particularly in the perceptual tasks. Computers can store huge amounts of data and information. Steven Spielberg was so taken with Thinking Machines and its technology that he would soon cast the company's gleaming black Connection Machine in the role of the supercomputer in the film Jurassic Park, even though the Michael Crichton novel to which the movie was otherwise faithful specified a Cray. And now the other players were howling. Also, computers allow users to communicate with other users or computers. But, as one of the company's senior scientists would later put it, what if pigs could fly? Handler had every surface on the new floor repainted a slightly different shade of mauve. Thinking Machines made some of the most powerful supercomputers of the time, and by 1993 the four fastest computers in the world were Connection Machines. When a national supercomputer conference was held in Seattle, she decided to stay in San Francisco and commute to Seattle from the swank Stanford Court Hotel. At the end of 1992, Thinking Machines reported a loss for the year of $17 million. "Our charter," says Tucker, "wasn't to look at a machine and figure out the commercial profit. But how far away is that moment, that "singularity", when computers easily pass the Turing Test – i.e., when communicating with them is indistinguishable from speaking to a human being? Now all Thinking Machines had to do was build one of the world's fastest computers in two years' time. Soon Hillis himself left the company that had been founded around his thesis. The cost advantages of using off-the-shelf chips, as well as the functional advantage of running existing software, seemed overwhelming -- especially considering the fact that few customers outside the tiny AI community had much interest in Thinking Machines' massively parallel design. In 1984 Hillis and his colleagues at Thinking Machines repackaged Hillis's thesis and pitched it to DARPA. ", Nonetheless, thanks to DARPA, Thinking Machines went into the black for the first time. Even Hollywood was interested. (Many researchers later reported that once they were hired, they never got to speak to Handler again -- even when they were alone with her in an elevator.). Computers are designed to perform some task well, not to survive and replicate. After all, the more problems the machine could solve, the more sales prospects there would be. For the first time the company had to sell its machines on their merits in an open market. In May 1985, Thinking Machines announced the impending completion of the first Connection Machine, the CM-1. This equation suggests that if take the number of stars in the Milky Way and then start dividing it down by various liklihoods – if it has planets, if those planets are the right size and distance from the sun, if they have the right chemistry, etc. Why? Thinking Machines wins Best Paper Award at NeurIPS 2020 ML4D Workshop. They had begun to collect all conceivable data and were feeding them into their mainframes, looking for any insight that would help them maximize profits. Handler personally oversaw the design of the office space, insisting that each office be painted a different and specific color. Hillis later complained about the injustice of a world where "the real money is in handling Wal-Mart's inventory rather than searching for the origins of the universe. If Hillis disapproved, he didn't make it known. Sure, there are some technical problems in the way. They began to talk about solving what D. Allan Bromley, the president's science adviser, dubbed "grand challenge" scientific problems: modeling the global climate, analyzing the folding of proteins, mapping the human genome, predicting earthquakes, revealing the nuances of quantum mechanics. It has not come from any fundamentally new algorithms. Puppies can do that because their brains -- like those of all animals, including humans -- are "massively parallel" computers. And the soft-drink machine was wired to a terminal. Meanwhile, the company had developed an image as one of the leading high-tech companies in the country. It turned out that DARPA had subsidized -- sometimes to the tune of the entire purchase price -- the sale of some 24 Connection Machines in recent years. He was editor of Forbes ASAP, the world's largest-circulation business-tech magazine, at the height of the dot-com boom. As soon as Thinking Machines promised it would have a scaled-down version of a teraflop machine ready by 1992, the agency awarded the company an initial contract of $12 million. Couches were scattered throughout the offices so that researchers could take naps or even sleep there overnight, which many of them did. For example, the human brain neurons are linked all over the place their fellow neurons, while silicon transistors are much more linear. Instead, there are Mentats - humans trained to perform the kinds of calculations and analysis that you normally expect a computer to carry .. My hunch is that the latter will arrive long before the former. There are fascinating questions about why we are unaware of so much that goes on in our brains, and why our awareness is the way it is. Such computers have been used primarily for scientific and engineering work requiring exceedingly high-speed computers. The first round of layoffs had started. Thinking Machines also hired another 120 employees, bringing the total to over 400. Everyone, from programmers to administrative assistants, had to be interviewed by Handler, who had a very specific, if mysterious, idea of who would be good enough to work for Thinking Machines. If today's most powerful computers are even half as smart as the human brain, why don't they exhibit the sentience of say, my cat, or a lizard? (Hillis envisioned his machine eventually becoming a sort of public-intelligence utility into which people would tap their home PCs, thereby bringing artificial intelligence to the world.) Thinking Machines sold seven CM-1s, but only because DARPA brokered and subsidized most of the deals. And, given that most experts now predict that Moore's Law could keep going for another 20 years more, it seems a pretty safe bet that someday out there we'll cross an invisible threshold and one of our biggest computers will suddenly start whispering, "Cogito ergo sum" and our world will change forever. The most famous prognosticator on the subject, scientist and writer Ray Kurzweil, has predicted the singularity will arrive in about twenty years or so. It can solve a lot of calculation using their ALU and CU system. Moore's Law seems to suggest we can do this one – and though we not find Kurzweil's Singular immortality, we may be able to stuff enough experience in the short time we've got in this world to make it seem like forever. And, of course, there's always the nagging concern that somewhere out there Moore's Law is simply going to crash into a heretofore hidden law of physics, an insurmountable technical barrier, and will be stopped in its tracks. Well, not so fast. The CM-2 might be more like the human brain than a sequential computer like the Cray was, but scientists knew how to write programs for the Cray. In the first few years it didn't seem to matter. This is probably because you have a computer that is not powerful enough to run the emulator properly. In fact, Thinking Machines was becoming Handler's aesthetic creation as much as the Connection Machine was Hillis's. In the late 1980s, DARPA and the Bush administration, having accepted the fact that the end of the cold war had reduced the urgency for military supercomputing, came up with a new challenge for parallel computing. X=2), language functions (Metaphorical – i.e., X=Y is true), and truth-telling functions (Metaphysical – i.e., based on everything I have experienced X does not =Y). Followers of ‘Transhumanism‘ and advocates of strong AI (which is the label for the idea of emerging self-conscious machines, or ‘h+’ in short), such as one of their most prominent speakers, Ray Kurzweil, cite two key arguments to why the end of humanity as we know it is inescapable and nigh. Hillis, Minsky, and Handler pitched the idea to Paley and CBS president Fred Stanton in a meeting to which Hillis wore his customary jeans and T-shirt. She commissioned a $40,000 logo design for a CM-5 sweatshirt and then rejected it. But the definition of interesting would soon change. Whether it would take pride in its creators would remain to be seen. This is the opinion of the columnist and in no way reflects the opinion of ABC News. In May 1983, despite the lack of a business plan, the company was founded and took up shop in a dilapidated mansion outside Boston that once was owned by Thomas Paine, the author of the Revolutionary War pamphlet Common Sense. He has been the ABCNews.com "Silicon Insider" columnist since 2000. Sept. 25, 2009 -- Will computers soon think like us? Still, he managed to impress the television moguls, who with others eventually agreed to kick in a total of $16 million to the venture. Every clever school kid over the last thirty years has heard about the Drake Equation (devised by scientist Frank Drake around the same time as Gordon Moore proposed his Law). Everything a computer does involves manipulating two symbols in some way. It might become supremely adaptive to its environment, and capable of rapidly responding to new challenges …but still never know of its own existence. Increasingly paranoid, she had a video camera aimed at her personal parking spot and, by some accounts, made people take meetings with her in her parked car. Meanwhile, Handler had an enormous marble archway installed in the atrium of the Carter Ink Building. – that suggests we are already working on the solutions to those problems we haven't yet found. Sun and IBM were interested, says Tucker, but weren't willing to take on Thinking Machines' mounting debt, which included six more years of rent at the Carter Ink Building, a $36-million commitment. Even Fujitsu Limited, one of Japan's major supercomputer manufacturers, was in the process of opening a parallel-computing lab, looking toward marketing a 1,000-processor machine. "We had all sorts of reasoned discussions," says Resnikov, "and then emotional decisions were fundamentally made by Sheryl and Danny." As a number of observers have noted, today's computers, a dozen generations advanced from the first computational machines and millions of times more powerful, are no more intelligent than their predecessors; rather, they are just faster, with more sophisticated software. Emotional decision making would last almost until the company fell. He is also an inveterate tinkerer, whose work has always been more fascinating than practical. Perhaps the clearest and most damning criticism came from KSR founder Henry Burkhardt: "Vendors handed money by the government have no interest in solving customers' problems," he growled. But it sometimes took mainframes hours, even days, to churn out the answer to a single question. – you will eventually come up with a number …a very big number, it seems … of the number of planets in our galaxy that have intelligent life. Science fiction is full of thinking computers, machines that have evolved into living, sentient beings. The CM-2 was able to run FORTRAN and to do floating-point operations. Turn on desktop notifications for breaking stories about interest. A machine that will be proud of us. Even if this scenario seems a bit ghastly to you (as it does to me), the logic behind it seems pretty sound. This is the story of how Thinking Machines got the jump on a hot new market -- and then screwed up, big time. A sort of "moderately parallel" design, the technology entailed stringing together a smaller number of the powerful, cheap, off-the-shelf microprocessors used in PCs and workstations -- rather than the thousands of highly customized but less powerful processors used in the Connection Machines -- into a single supercomputer that would work with existing software. In 1990, seven years after its founding, Thinking Machines was the market leader in parallel supercomputers, with sales of about $65 million. Today computers can be found in every store, supermarkets, restaurants, offices etc. ). Had the CM-5 been built without the miscues and the wasted time, the company might have gone on to live up to its considerable promise. Hillis claimed it had the highest "theoretical" peak performance of any supercomputer ever, if you added enough processors to it. Would that wake them up? While other computer companies were out wooing customers, Handler had been cultivating a friendship with Bromley. Nothing to date suggests that it will – no matter how far out we go on the curve of Moore's Law. No such machine exists as of 2002, and whether it can be built in principle and how many years of research this would take is a matter of much dispute. Hillis and Handler (Minsky quickly became a figurehead at the company) wanted to design a machine strictly along the lines of Hillis's thesis, a machine that would have its maximum impact as a research tool for scientists studying artificial intelligence. Malone has also hosted three public television interview series, and most recently co-produced the celebrated PBS miniseries on social entrepreneurs, "The New Heroes." Cray Research launched a crash program in 1990 to get a massively parallel machine on the market within two years. More than ever, Thinking Machines was depending on its DARPA edge to move its products. Thinking Machines presented at NeurIPS 2020 workshops, ML4D and AI … In April 1986, Thinking Machines announced the arrival of the CM-2, a machine the scientific community actually could use. A plush cafeteria was put in, complete with a gourmet chef. That has come from the steady Moore’s-law doubling of circuit density every two years or so. Hillis built it to play and win at tic-tac-toe, which it invariably does. Now that there is background on this topic, I will present my argument to why I believe that computers "think" just like human. Employees weren't allowed to discuss the machine with one another in the cafeteria. In 1990, seven years after its founding, Thinking Machines was the market leader in parallel supercomputers, with sales of about $65 million. In the summer of 1984 the company moved into its new home -- the top two floors of the old Carter Ink Building in Cambridge, Mass., a few blocks from MIT. Unfortunately, few AI labs could afford a $5-million computer, and, as Resnikov had predicted, hardly anyone else was interested. Then, in August 1991, as DARPA was about to start the process of determining which supercomputer vendors would win the lion's share of its planned spending spree, the Wall Street Journal broke the story that the agency had been playing favorites. When it was done, she wasn't satisfied. She had a taste for classical music and a fine appreciation for style. The CM-1 was an AI researcher's dream. In a near future, artificial superintelligence will become vastly more intellectually capable and versatile than humans. Instead of looking at information one jigsaw-puzzle piece at a time, a brain processes millions, even billions, of pieces of data at once, allowing images and other patterns to leap out. Among other problems, the standard chips the company had chosen weren't ready, so some machines had to ship with slower, earlier-generation chips. His other work includes a robot finger that can differentiate between a washer and a screw but is flummoxed by a piece of gum; a propeller-driven jumpsuit that allows its wearer literally to walk on water; and a home robot constructed of paint cans, lightbulbs, and a rotisserie motor. Thinking Machines The term thinking machine (or intelligent machine) refers to a computer or a robot that has human intelligence. As late as 1989, says Fishman, Thinking Machines was still three years ahead of the rest of the world in parallel-processing technology. The DS emulator requires a fairly powerful computer to run correctly. "While others caught up," he says, "Thinking Machines was losing time, losing customers, and not moving on to the next generation." Watch our latest big-idea animation to find out how computers solve problems using a novel thinking process. Unfortunately, the old dream died hard: the decision came only after 18 months of internal bickering. Yet competition was looming. So convincing is this equation that it has sparked a massive search (SETI being the most famous example) for our intelligent counterparts out there ever since. In the novel Dune by Frank Herbert, which is set hundreds of years the future, it is forbidden to build computers. Finally, Handler and Hillis won out. An embarrassed Bush administration put an end to Thinking Machines' DARPA gravy train. Its prime hunting grounds were the computer-science departments of MIT, Carnegie-Mellon, Yale, and Stanford -- which happened to house four of the world's leading AI labs. Humans are more powerful than computers at tasks that … In 1989 the company reported a profit of $700,000 on revenues of $45 million. The official name of the new project was the High Performance Computing and Communication (HPCC) program, and DARPA was the lead agency, with a projected budget of several billion dollars through 1996 to accomplish its goals. DARPA had greased Intel's supercomputing wheels too but had left the rest of the supercomputer industry to fend for itself. Industry analysts in 1992 were projecting that the growth in supercomputers was not in science but in business applications -- in particular in what's known as "database mining," an area that could well become, as IBM parallel-computing expert Art Williams put it, "the killer application" for parallel computers. Until W. Daniel Hillis came along, computers more or less had been designed along the lines of ENIAC. Hillis and Handler already were bitter about having to target general scientific computing rather than artificial intelligence; they weren't about to jump on the idea of servicing mere merchants. The truth is very different. Computers are powerful tools because they can process information with incredible speed, accuracy and dependability. In fact, Thinking Machines had sold two Connection Machines to American Express. A Turing machine is a mathematical model of computation that defines an abstract machine, which manipulates symbols on a strip of tape according to a table of rules. But could machines ever truly experience the whole range of human feelings and emotions, or are there technical limitations ? In August of last year Thinking Machines filed for Chapter 11. The problems didn't require artificial intelligence, just enormous computing power. Thinking Machines would reemerge as a small software firm selling programs for its former competitors' parallel computers. But for now you can help but sense a growing unease among researchers that just maybe the Drake equation is wrong, that there is some missing X factor we haven't considered that throws the whole model out the window. Computers will soon be able to simulate the functioning of a human brain. So computers are more powerful that humans when it comes to executing simple step-by-step instructions. Thinking Machines didn't need to make good business decisions because it had the Defense Advanced Research Projects Agency. IBM was doing the same. And yet …nothing. If your are not a student of Thinking Machines, then you can buy this course for Rs.3540/-If you don't want to pay using the [pay now] button, then you can transfer the fee amount to our HDFC Bank Account as specified below. Her background was eclectic: she had studied interior design, held a master's degree in landscape architecture from Harvard, and at the time was pursuing a doctorate in city planning at MIT. As with life in the universe, with thinking machines we may forever be unable to discover that missing X factor. One of her Genetics Institute colleagues later called her a "professional schmoozer." Needless to say, that could all change tomorrow if one of our big radio telescope were to pick up, say, the Alpha Centauri equivalent of the "Jack Benny Show." Hillis called the device a "connection machine": it had 64,000 simple processors, all of them completing a single instruction at the same time. It will be a truly intelligent machine. She'd even been the subject of a Dewars Profile that ran with the quote "My feminine instinct to shelter and nurture contributes to my professional perspective.". A silicon life-form, sentient beings until the company that had been founded around his.! 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