IBM insists its revamped AI strategy – a scaled-down, less world-changing goal – works. The job of resurrecting growth was entrusted to Arvind Krishna, a computer scientist who became chief executive last year after leading the recent overhaul of IBM’s cloud and AI business.
But the great visions of the past are gone. Today, Watson is not just an acronym for technological prowess, but a sobering example of the pitfalls of technological hype and AI hubris
It turns out that the march of artificial intelligence through the mainstream economy will be a gradual evolution rather than a catastrophic revolution.
A new wave of riding
Time and again in its 110-year history, IBM has introduced new technologies and sold them to corporations. The company dominated the mainframe market so much that it became the target of federal antitrust proceedings. PC sales really took off after IBM launched in 1981 and the small machines were recommended as indispensable tools in corporate offices. In the 1990s, IBM helped its traditional corporate customers adapt to the Internet.
IBM executives came to see AI as the next wave.
Mr. Ferrucci presented the idea of Watson recognizing and analyzing words for the first time to his bosses in the research laboratories of IBM in 2006. Another research goal was the further development of techniques for automated answering of questions.
After overcoming initial skepticism, Mr. Ferrucci assembled a team of scientists – eventually more than two dozen – to work from the company’s laboratory in Yorktown Heights, NY, about 20 miles north of IBM’s Armonk headquarters.
The Watson they built was a room-sized supercomputer with thousands of processors running millions of lines of code. His storage disks were filled with digitized reference works, Wikipedia entries, and electronic books. Computer intelligence is a brute force issue, and the massive machine required 85,000 watts of power. The human brain, on the other hand, works with the equivalent of 20 watts.