Based on excerpts from the new book Cognitive Computing: A Brief Guide for Game Changers
But a few resolute researchers carried on. According to Hinton and Yann LeCun (NYU professor and Director of Facebook’s new AI Lab), it was rough going. Even as late as 2004 — more than 20 years after Hinton and LeCun first developed the “back-propagation” algorithms that seeded their work on neural networks — the rest of the academic world was largely uninterested.
By the middle aughts, they had the computing power they needed to realize many of their earlier ideas. As they came together for regular workshops, their research accelerated. They built more powerful deep learning algorithms that operated on much larger datasets. By the middle of the decade, they were winning global AI competitions. And by the beginning of the current decade, the giants of the Web began to notice.
Deep learning is now mainstream. “We ceased to be the lunatic fringe,” Hinton says. “We’re now the lunatic core.” Perhaps a key turning point was in 2004 when Hinton founded the Neural Computation and Adaptive Perception (NCAP) program (a consortium of computer scientists, psychologists, neuroscientists, physicists, biologists and electrical engineers) through funding provided by the Canadian Institute for Advanced Research (CIFAR).i
Back in the 1980s, the AI market turned out to be something of a graveyard for overblown technology hopes. Computerworld’s Lamont Wood reported, “For decades the field of artificial intelligence (AI) experienced two seasons: recurring springs, in which hype-fueled expectations were high; and subsequent winters, after the promises of spring could not be met and disappointed investors turned away. But now real progress is being made, and it’s being made in the absence of hype. In fact, some of the chief practitioners won’t even talk about what they are doing.
But wait! 2011 ushered in a sizzling renaissance for A.I.
How did we get here? What’s really new in A.I.?
Next: Deep Learning