Remember IBM’s Watson? He’s Still Here.

The celeb computer is branching out from game shows to medical and financial analysis


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Watson uses a cognitive system that is similar to how humans reason and process information. It uses context when it can, and then taps into its own ever-increasing knowledge base to process deep natural language. (At one point, Watson was even fed the Urban Dictionary, a compendium of street slang, but it was quickly removed.) 

The key is that after Watson sifts through huge amounts of data, it can then engage in complex decision-making. It uses what researchers call “Deep QA,” which is very different from search-engine technology. With a search engine, you type in key words or phrases and get links to documents or websites where those words appear. It is then up to you to sort through the results—likely tens of thousands—and find what’s relevant. Watson does that for you. It doesn’t return documents, it returns answers to your questions in a ranked list, with the computer’s confidence level attached to each answer. “What Watson would do is analyze your question and try to figure out what you are actually asking for. It would understand the context of what you’re asking,” explains Jennifer Chu-Carroll, one of the core IBM researchers who developed Watson. 

This is far more than a parlor trick. IBM estimates that 90 percent of all the data in the world was produced in the last two years alone, and that 80 percent of all the information in the world is unstructured. By unstructured, they mean that the untagged material appears in all sorts of forms—as literature, as articles in academic journals, as PowerPoint presentations, as physician notes dictated into charts, as blogs, as Tweets, as emails, as banter in chat rooms, and more. 

“Watson is the first commercially available cognitive computing offering—a system capable of continually learning and refining itself through human/computer interaction,” says Steve Gold, vice president of Watson Solutions at IBM. “Part of why cognitive systems are so necessary is because of the rise of Big Data. As organizations work to make fact-based decisions based on data, they need advanced systems that are able to crunch massive amounts of structured and unstructured data and deliver insights within seconds.” 

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