Watson won jeopardy by being an expert system with hand coded knowledge (their NLP parser was written in Prolog) and sophisticated QA text search. It wasn't a pure unsupervised/semi supervised deep learning model so it didn't generalize well to other domains like medicine despite it being hyped as a ML trailblazer.
Watson (the quiz winner) was in 2011 before the deep learning revolution (which kicked off in 2014 with AlexNet for image recognition). It was probably the pinnacle of old-style natural language processing.
The success of that led to a set of basically unrelated tools being released under the IBM Watson brand which were mostly failures.
Watson as a system was designed specifically to play Jeopardy. After the win it got a lot of global hype behind it and IBM's marketing and sales teams went into overdrive positioning it as some next generation intelligent AI that could help with generic business processes, analytics, medical diagnosis, legal briefs, customer service and every other business area under the sun. Instead, companies that bought into it got the same army of IBM offshore consultants to custom build half-assed solutions for them like before.
"Watson" is ultimately a marketing name for a sub-par IT consulting service, nothing more.
Some other comments here are good but I'll point out that what most people don't understand is that "Watson" is the name of a marketing umbrella, not a technology. Essentially, almost anything at IBM that had AI/ML smell to it got tossed into the "Watson" market bucket. This allowed IBM to push a huge set of technologies that they could then customize and build services around, for a large fee of course.
The problem is that most of the AI/ML technologies IBM used were stock, off the shelf, often not even state of the art. You could literally go to a github page or use scikit_learn out of the box to get equivalent or better performing models without being tied to IBM's proprietary, consultant heavy, solutions.
The marketing of Watson, tied to the Jeopardy performance, made people think it was the first coming of AGI -- a kind of Skynet moment. It was really just a cobbled together basket of unintegrated, nothing special, industry bog standard AI/ML stuff.
KRAKRISMOTT|3 years ago
nl|3 years ago
Watson (the quiz winner) was in 2011 before the deep learning revolution (which kicked off in 2014 with AlexNet for image recognition). It was probably the pinnacle of old-style natural language processing.
The success of that led to a set of basically unrelated tools being released under the IBM Watson brand which were mostly failures.
paxys|3 years ago
"Watson" is ultimately a marketing name for a sub-par IT consulting service, nothing more.
bane|3 years ago
The problem is that most of the AI/ML technologies IBM used were stock, off the shelf, often not even state of the art. You could literally go to a github page or use scikit_learn out of the box to get equivalent or better performing models without being tied to IBM's proprietary, consultant heavy, solutions.
The marketing of Watson, tied to the Jeopardy performance, made people think it was the first coming of AGI -- a kind of Skynet moment. It was really just a cobbled together basket of unintegrated, nothing special, industry bog standard AI/ML stuff.
aintgonnatakeit|3 years ago