The Rise and Fall of Thinking Machines, Bankruptcy Article | Inc.com

A close up look at a doomed-yet-brilliant start-up computer company that never quite grasped the basics of business.

The brilliant start-up that ignited an industry never grasped the basics

Some day we will build a thinking machine. It will be a truly intelligent machine. One that can see and hear and speak. A machine that will be proud of us.

-- From a Thinking Machines brochure

In 1990, seven years after its founding, Thinking Machines was the market leader in parallel supercomputers, with sales of about $65 million. 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." Several giants in the computer industry were seeking a merger or a partnership with the company. Wall Street was sniffing around for an initial public offering. Even Hollywood was interested. 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.

In August of last year Thinking Machines filed for Chapter 11. It had gone through three CEOs in two years and was losing money at a considerably faster rate than it had ever made it.

What caused this high-flying company to come crashing to earth? 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.

The truth is very different. This is the story of how Thinking Machines got the jump on a hot new market -- and then screwed up, big time.

Until W. Daniel Hillis came along, computers more or less had been designed along the lines of ENIAC. In that machine a single processor completes instructions one at a time, in sequence. "Sequential" computers are good at adding long strings of numbers and at other feats of arithmetic. But they're seriously deficient at the kinds of pattern-recognition tasks that a two-week-old puppy can master effortlessly -- identifying faces or figuring out where it is in a room. Puppies can do that because their brains -- like those of all animals, including humans -- are "massively parallel" computers. 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.

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. Hillis called the device a "connection machine": it had 64,000 simple processors, all of them completing a single instruction at the same time. To get more speed, more processors would be added. Eventually, so the theory went, with enough processors (perhaps billions) and the right software, a massively parallel computer might start acting vaguely human. Whether it would take pride in its creators would remain to be seen.

Hillis is what good scientists call a very bright guy -- creative, imaginative, but not quite a genius. He is also an inveterate tinkerer, whose work has always been more fascinating than practical. On the fifth floor of Boston's Computer Museum, for instance, is a minimalist computer constructed of fishing line and 10,000 Tinkertoy parts. Hillis built it to play and win at tic-tac-toe, which it invariably does. 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.

At the AI Lab, Hillis had become a disciple of legendary AI guru Marvin Minsky. The two were determined to build a connection machine as a tool with which to develop software programs for artificial intelligence. Because the cost would be prohibitive for a university laboratory, they decided to form a company. They went looking for help and found Sheryl Handler.

Handler had participated in the start-up of the Genetics Institute, a Harvard-based genetic-engineering firm. 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. She was also running her own nonprofit consulting firm, specializing in third-world resource planning. She had a taste for classical music and a fine appreciation for style. 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."

Handler also had a talent for cultivating friendships with brilliant and famous people. One of her Genetics Institute colleagues later called her a "professional schmoozer." She quickly proved her usefulness by connecting the people who would build the Connection Machine with CBS founder William Paley. 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. Still, he managed to impress the television moguls, who with others eventually agreed to kick in a total of $16 million to the venture.

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. Hillis and Handler called their new company Thinking Machines because, says Hillis, "we wanted a dream we weren't going to outgrow." As it turned out, there was never much danger of that.