It is a growing feeling that perhaps a number of our smug certainties are now panning out the way they were supposed to. Unfortunately, few AI labs could afford a $5-million computer, and, as Resnikov had predicted, hardly anyone else was interested. Supercomputer, any of a class of extremely powerful computers. The firm filed for bankruptcy in 1994; its hardware and parallel computing software divisions were acquired in time by Sun Microsystems . IBM was doing the same. special software is used in these computers to calculate the huge bills within seconds. ... Why machines don't think like humans. ", Nonetheless, thanks to DARPA, Thinking Machines went into the black for the first time. 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." 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 that machine a single processor completes instructions one at a time, in sequence. She was also running her own nonprofit consulting firm, specializing in third-world resource planning. 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. 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. The agency responded by offering the company a multiyear $4.5-million contract. Puppies can do that because their brains -- like those of all animals, including humans -- are "massively parallel" computers. Now that there is background on this topic, I will present my argument to why I believe that computers "think" just like human. The two were determined to build a connection machine as a tool with which to develop software programs for artificial intelligence. 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.". Hillis claimed it had the highest "theoretical" peak performance of any supercomputer ever, if you added enough processors to it. But at Thinking Machines the idea got stuck in endless discussions. 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. Malone has also hosted three public television interview series, and most recently co-produced the celebrated PBS miniseries on social entrepreneurs, "The New Heroes." His articles and editorials have appeared in such publications as The Wall Street Journal, The Economist and Fortune, and for two years he was a columnist for The New York Times. 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. And since Moore's Law is exponential, that power curve is also getting more and more vertical – which means that each one of those performance jumps is now huge and getting even bigger. The standard explanation is that Thinking Machines was a great company victimized by the sudden cutbacks in science funding brought about by the end of the cold war. Even Hillis eventually came around and chose the moderately parallel design for the company's next generation of machine. Thinking Machines didn't need to make good business decisions because it had the Defense Advanced Research Projects Agency. At the top of the list: building a computer capable of a teraflop -- a trillion floating-point operations per second. Every day, though you don't read it in the general press, scientists at Intel, HP, IBM or some university comes up with a new way to make an electronic switch – organic, quantum, out of just a couple atoms, etc. The new company's managers immediately got into a disagreement over the market for supercomputers. Already, as the Network World article itself noted, computers are exhibiting characteristics far beyond anything in human imagination. Unfortunately, according to Resnikov, the decision to tailor the CM-1 to the AI "nonmarket" cost Thinking Machines three years in the real-world marketplace. 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. As it turned out, there was never much danger of that. They can efficiently perform input, process, output and storage operations, and they can store massive amounts of data. 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. 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. 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. Hillis and Handler called their new company Thinking Machines because, says Hillis, "we wanted a dream we weren't going to outgrow." Since the inception of the first computers, there has been a direct comparison between these “computational machines” and the human brain. Ultimately, humans are mere biological machines, and conversely, a thinking, dreaming computer could be considered a silicon life-form. This two-symbol system is the foundational principle that all of digital computing is based upon. 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. Humans are more powerful than computers at tasks that … More than ever, Thinking Machines was depending on its DARPA edge to move its products. Huge open spaces were created to stimulate idea sharing and creativity. 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. It had gone through three CEOs in two years and was losing money at a considerably faster rate than it had ever made it. Why Wouldn't Computers Start Thinking? For the first time the company had to sell its machines on their merits in an open market. But thanks to the support of DARPA, which continued to broker deals, Thinking Machines didn't have to seriously contemplate building a machine that had a natural market. Despite the model's simplicity, given any computer algorithm, a Turing machine capable of simulating that algorithm's logic can be constructed.. Modern computers have become incredibly powerful, Nick Bostrom became famous for his thoughts on superintelligent artificial machines and even simulations of human brains seem to be in reach. Hillis is what good scientists call a very bright guy -- creative, imaginative, but not quite a genius. But Handler nixed all deal making. Handler had participated in the start-up of the Genetics Institute, a Harvard-based genetic-engineering firm. Continue Reading. He is also an inveterate tinkerer, whose work has always been more fascinating than practical. The CM-5 wasn't selling, and the company was hemorrhaging money. Such computers have been used primarily for scientific and engineering work requiring exceedingly high-speed computers. That has come from the steady Moore’s-law doubling of circuit density every two years or so. Some argue that if a machine could pass something known as the Turing Test, it would have achieved real intelligence. (Lotus Development Corp., which was virtually across the street from Thinking Machines, was paying $8 a square foot.) So large companies were beginning to check out parallel computers. The truth is very different. 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. 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. 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. While the idea is entertaining, many consider the research and experiments upon which it is based to be unsettling at the least. These futuristic ideas raise fundamental questions about humanity and our relation to intelligent machines. What got me thinking about this was the comment this week, covered throughout the mainstream media, by Intel Chief Technology Officer Justin Rattner: "There will be a surprising amount of machines that do exhibit human-like capabilities. As a result, there still wasn't much of a market for Connection Machines. But that's hardware/software solution that seems pretty solvable. The first round of layoffs had started. Computers are powerful for a variety of reasons. Thinking Machines sold seven CM-1s, but only because DARPA brokered and subsidized most of the deals. And now the other players were howling. Finally, Handler and Hillis won out. Humans are alive; machines are not. At that point, he says, we will be able to map all of the charges in all of the neurons of our brains, and then port them over to computers … and thus give ourselves not only enhanced cognitive powers, but also a kind of immortality. She quickly proved her usefulness by connecting the people who would build the Connection Machine with CBS founder William Paley. Architect powerful systems and scalable data pipelines for data collection and data analysis. But could machines ever truly experience the whole range of human feelings and emotions, or are there technical limitations ? Yet competition was looming. In April 1986, Thinking Machines announced the arrival of the CM-2, a machine the scientific community actually could use. Once again, the company was off to a late start. But it sometimes took mainframes hours, even days, to churn out the answer to a single question. According to “ Dancing With Robots: Human Skills for Computerized Work,” computers’ strengths lie in speed and accuracy, while humans’ strengths are all about flexibility. 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. Resnikov lasted another two years before he quit. 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. Unfortunately, the old dream died hard: the decision came only after 18 months of internal bickering. Researchers who wanted a drink simply typed in their choice. For example, the human brain neurons are linked all over the place their fellow neurons, while silicon transistors are much more linear. Fishman was a longtime friend of Handler, but when he realized that no outsider would fund the sinking company while Handler remained at its helm, he engineered her ouster. One of the common phrases that has stuck around for decades, and which encourages the idea of a brain vs. computer argument, is “brains are analogue, computers are digital”. 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? I have some ideas. Watch our latest big-idea animation to find out how computers solve problems using a novel thinking process. Thinking Machines announced the CM-5 in October 1991. – that suggests we are already working on the solutions to those problems we haven't yet found. Hillis called the device a "connection machine": it had 64,000 simple processors, all of them completing a single instruction at the same time. If the company was going to stay in business, it would need a machine that could pull its weight outside AI research. Would that wake them up? Whether it would take pride in its creators would remain to be seen. Turn on desktop notifications for breaking stories about interest. 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. Hillis built it to play and win at tic-tac-toe, which it invariably does. Handler promptly signed a 10-year lease with the Carter Ink Building for a whopping $6 million a year -- about $37 a square foot. 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. 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. In August of last year Thinking Machines filed for Chapter 11. It will be a truly intelligent machine. For a year, while the argument went on, the company did nothing. 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. Because the cost would be prohibitive for a university laboratory, they decided to form a company. A machine that will be proud of us. As late as 1989, says Fishman, Thinking Machines was still three years ahead of the rest of the world in parallel-processing technology. So, should we then assume that we are on the brink of the age of truly thinking, even conscious, machines? Couches were scattered throughout the offices so that researchers could take naps or even sleep there overnight, which many of them did. Fishman focused the company on the business market and began looking for a partner. Those are 'sands on all of the world's beaches' kinds of numbers; or, more impressively, every heartbeat of every human being that has ever lived on Earth. 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. The board discussed dumping Handler, but she managed to get her biggest enemies there kicked off. Of course, you can make a lot of convincing arguments about why we haven't found anyone out there. Some day we will build a thinking machine. While a graduate student at MIT's Artificial Intelligence (AI) Lab, Hillis, whom everyone knows as Danny, had conceived of a computer architecture for his thesis that would mimic that massively parallel process in silicon. Everything a computer does involves manipulating two symbols in some way. Even if this scenario seems a bit ghastly to you (as it does to me), the logic behind it seems pretty sound. In the meantime, several computer companies were exploring a new technology -- a compromise between the comfort of sequential computing and the performance of massively parallel 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? In light of all that, Rattner's comments, far from being radical, actually seem pretty conservative. In 1984 Hillis and his colleagues at Thinking Machines repackaged Hillis's thesis and pitched it to DARPA. In the first few years it didn't seem to matter. It has not come from any fundamentally new algorithms. Malone is the author or co-author of a dozen books, notably the best-selling "Virtual Corporation." ). In fact, Thinking Machines was becoming Handler's aesthetic creation as much as the Connection Machine was Hillis's. 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. The brilliant start-up that ignited an industry never grasped the basics. 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. Not only was the company profitable; it also, in the words of one IBM computer scientist, had cornered the market "on sex appeal in high-performance computing." Soon Hillis himself left the company that had been founded around his thesis. After all, the more problems the machine could solve, the more sales prospects there would be. When it was done, she wasn't satisfied. What's more, there were signs that the company was still chasing the wrong market. At the AI Lab, Hillis had become a disciple of legendary AI guru Marvin Minsky. And the soft-drink machine was wired to a terminal. Meanwhile, competitors like Intel, Kendall Square Research (KSR), MasPar Computer, and nCube were starting to ship faster supercomputers. A plush cafeteria was put in, complete with a gourmet chef. 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. So she had her researchers and scientists paint it again. This makes it seem like computers are superior, but in truth, the human brain is far more advanced and efficient… More problems the machine operates on an infinite memory tape divided into discrete `` cells '' CEO quickly... 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