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IBM AI Medicine

Watson Goes To Medical School 100

First time accepted submitter Kwyj1b0 writes "I.B.M's Watson is headed to the Cleavland Clinic Lerner College of Medicine of Case Western Reserve University for training. Clinicians and students will answer and correct Watson's questions, in an attempt to crowdsource its education. From the article: '“Hopefully, we can contribute to the training of this technology,” said Dr. James K. Stoller, chairman of the Education Institute at Cleveland Clinic. The goal, he added, was for Watson to become a “very smart assistant.” Part of Watson’s training will be to feed it test questions from the United States Medical Licensing Exam, which every human student must pass to become a practicing physician. The benefit for Watson should be to have a difficult but measurable set of questions on which to measure the progress of its machine-learning technology.'"
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Watson Goes To Medical School

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  • I recently worked at IBM and this is one of the things they really love to showcase - I think primarily because it's really cool, but also has really useful end results - exactly the kind of thing you want to be working on.
  • by Unnngh! ( 731758 ) on Wednesday October 31, 2012 @10:24PM (#41837821)
    You are wrong, broadly speaking. This is the whole point of machine learning: given a very complicated task that it would take a human a tremendous amount of effort to program correctly, you can instead get the machine to figure out how to perform the task itself, rather than explicitly programming it to do one thing. Some types of learning are supervised, particularly classifiers: I tell the computer which items belong to which class, and given a new, previously unseen item, the computer attempts to determine its class based on the training. Others are unsupervised: set the robot free in the environment with some goal function and let it learn through trial-and-error how to optimize its behavior toward the goal. Watson is a combination of first-order logic (prolog and a huge kb) and a variety of such learning algorithms. Some of this is stuff that was considered an industry failure in the 80s but, paired with modern machine learning techniques, is quite powerful. Indeed we may be seeing the first instances of computers that have some form of this "intelligence" of which you speak, though I think we are still a long way from "strong AI".

If graphics hackers are so smart, why can't they get the bugs out of fresh paint?