2011
IBM's Watson AI system won the quiz show Jeopardy in 2011.
“Watson, the company's famous A I supercomputer, won Jeopardy in 2011, but since then, as far as most of us are concerned, it's been mostly ads during football games and not a lot else.”
Nilay Patel · IBM CEO Arvind Krishna says there is no AI bubble after all, 0:02:41
2011
IBM built Watson in 2011 to show that AI could handle natural-language questions, including winning the game show Jeopardy.
“In 2011, we wanted to prove that A I can do and solve problems that were unimaginable.”
Arvind Krishna · IBM CEO: Transforming a Tech Giant, AI Bets and Quantum Computing, 0:20:01
Undated
Krishna says IBM's Watson effort failed partly because it targeted healthcare, the hardest industry, with monolithic applications.
“we unfortunately picked the vertical that is the hardest health. That was the mistake.”
Arvind Krishna · IBM CEO: Transforming a Tech Giant, AI Bets and Quantum Computing, 0:20:33
Undated
Arvind Krishna says IBM's Watson winning Jeopardy woke the world up to AI and spurred other companies to invest heavily.
“I think when we, uh, won Jeopardy with Watson, I think it woke the world up.”
Arvind Krishna · IBM’s $10 billion bet on what comes after AI, 0:06:09
Undated
Krishna says one Watson mistake was entering healthcare, where IBM had few salespeople who dealt with doctors or the FDA.
“Mistake number three, how many IBMers sell to doctors, and how many of those IBMers deal with the FDA?”
Arvind Krishna · IBM’s $10 billion bet on what comes after AI, 0:06:59
Undated
Arvind Krishna said IBM's Watson winning Jeopardy woke the world up to AI's capabilities.
“when we uh won Jeopardy with Watson, I think it woke the world up because I think for the first time in a long time, AI started doing something people thought it could not do.”
Arvind Krishna · Masters of Scale: IBM’s $10 billion bet on what comes after AI, 0:06:48
Undated
Arvind Krishna said IBM's Watson mistakes included building monolithic applications and choosing healthcare, a hard domain.
“we wanted to make a monolithic application. Mistake number one, mistake number two, we picked a domain, which is perhaps the hardest of them all, which is health.”
Arvind Krishna · Masters of Scale: IBM’s $10 billion bet on what comes after AI, 0:07:38