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IBM Pitched Its Watson Supercomputer as a Revolution in Cancer Care. It's Nowhere Close (statnews.com)
IBM began selling Watson to recommend the best cancer treatments to doctors around the world three years ago. But is it really doing its job? Not so much. An investigation by Stat found that the supercomputer isn't living up to the lofty expectations IBM created for it. It is still struggling with the basic step of learning about different forms of cancer. Only a few dozen hospitals have adopted the system, which is a long way from IBM's goal of establishing dominance in a multibillion-dollar market. And at foreign hospitals, physicians complained its advice is biased toward American patients and methods of care. From the report: The interviews suggest that IBM, in its rush to bolster flagging revenue, unleashed a product without fully assessing the challenges of deploying it in hospitals globally. While it has emphatically marketed Watson for cancer care, IBM hasn't published any scientific papers demonstrating how the technology affects physicians and patients. As a result, its flaws are getting exposed on the front lines of care by doctors and researchers who say that the system, while promising in some respects, remains undeveloped. [...] Perhaps the most stunning overreach is in the company's claim that Watson for Oncology, through artificial intelligence, can sift through reams of data to generate new insights and identify, as an IBM sales rep put it, "even new approaches" to cancer care. STAT found that the system doesn't create new knowledge and is artificially intelligent only in the most rudimentary sense of the term.
Except Mayo is not a 'world leading cancer treatment center'. It's one of literally thousands of places with excellent oncology teams.
Who look at the exact same data as Watson.
And come up with pretty much exactly the same result. Sans Watson.
The clueless doc at General Hospital doesn't even figure into this. If a patient has a complex / rare / difficult cancer they get referred to a regional cancer center. A lot of cancer treatments are pretty straightforward due to the large number of trials that have been done over the years. The databases have existed for decades and obviously are getting better and more complete over time. The real killer, so to speak, for Watson is that it could never really beat the industry standard 'tumor board' composed of various meat space biologic computers. Perhaps one day. When AI is actually a bit more than a marketing term.
Faster! Faster! Faster would be better!
First of all, Jeopardy Watson has almost nothing to do with the Watson product IBM is selling. That system was largely NLP based and the team disbanded afterwards. From what I can tell, the only thing still alive from that project is Apache UIMA. Watson isn't even a single product. It's a collection of about a dozen disjoint products with the word "Watson" in front of their name.
The current iteration of "Watson" is not interesting at all. Their machine learning portion is just SPSS. Their next-gen machine learning is just Apache Spark. Their UI to setup hardware and submit spark jobs is very unreliable. When you get an error, it's generally a "An error has occurred" or something just as useless.
Jeopardy Watson was interesting, but the big players are doing much more interesting things these days. Google and Microsoft have very good public machine learning and AI platforms. Amazon's is OK, nothing special. If you want to work at a lower level, Stanford maintains a set of libraries with implementations of their cutting edge algorithms. Especially their NLP group. Theirs are actually user-friendly compared to many other research level projects.