The AI Industry: Lessons Learned in the First 20 Years

Students in Computer and Information Sciences often wonder about the
realistic prospects for Artificial Intelligence. On the one hand, it appears
that the AI industry had its boom and bust cycle in the 1980's. Overall, the
hype for AI exceeded expectations considerably, and disappointed many
investors and technologists. However, history shows that in cases of
disruptive technological innovation, forecasts are usually too optimistic in
the short run, and too conservative in the long run. Is that the case with
AI? This talk will briefly review the history of the AI industry, and
identify 7 lessons learned from that experience. We will then examine the
question of where AI is now with respect to current technology and business
opportunities. Finally, we will address the significance of accelerating
technological progress, and the doubling times for knowledge and computer
hardware. How can we avoid the mistakes of the past, and still take
advantage of unprecedented new opportunities for technical development and
wealth generation? An interactive question and answer session will follow
this talk.

Summary Bio:
Teknowledge was one of the first AI companies in the world, and has the
distinction of having survived despite AI becoming unfashionable in some
eyes. (He writes: "We have been profitable for the past 29 quarters and
have about 75 employees, plus about 50 contractors".)

Neil began his career at Xerox Palo Alto Research Center, and the Center
for the Biology of Natural Systems. He holds an MSc from the University of
Texas, under a USPHS scholarship with NASA.

After joining Teknowledge in 1984, he rose to Vice President of the
Knowledge Systems Division, becoming President in 1993. He was appointed
Chairman and CEO in 1999.

He has consulted for: GM, Ford, P&G, Boeing, Applied Materials, NPR, NIH,
NASA, EPA, DOE, NIST, and the Defense Advanced Research Projects Agency.