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Deep question answering: Watson vs. Aristotle

At the SemTech conference last week, a few companies asked me how to respond to IBM’s Watson given my involvement with rapid knowledge acquisition for deep question answering at Vulcan.  My answer varies with whether there is any subject matter focus, but essentially involves extending their approach with deeper knowledge and more emphasis on logical in additional to textual entailment.

Today, in a discussion on the LinkedIn NLP group, there was some interest in finding more technical details about Watson.  A year ago, IBM published the most technical details to date about Watson in the IBM Journal of Research and Development.  Most of those journal articles are available for free on the web.  For convenience, here are my bookmarks to them.


  1. Peter Lin says:

    Thanks for blogging on the difference. Quite interesting.

  2. […] in response to continued discussion in the Natural Language Processing group on LinkedIn under the topic “This is Watson”, […]

  3. […] these sentences are too complex to be precisely understood, although evidentiary approaches, such as demonstrated in Watson, suggest that most can be understood with sufficient precision to answer many questions.  As the […]