Dr. David Ferrucci discusses Watson Deep QA project at TiEcon Keynote

At TiEcon 2011 keynote session (www.tiecon.org), Dr. David Ferrucci discussed the phenomenal challenges of building Watson, an artificial intelligence computer system that competed with human subjects in the quiz show Jeopardy and consistently outperformed the human competitors.  Compared to the Deep Blue, the chess-playing computer, developed in 1997, the Watson Deep QA project was infinitely more challenging.  Chess is finite, mathematically well defined with limited number of moves.  Computer can be really good at mathematically challenges and can find information very quickly.  Jeopardy however is a significantly more complex challenge.  Not only Watson had to navigate through frequently convoluted human speech which is infinitely complex, contextual, idiomatic and full of puns and expressions that alter the meaning of the words, but additionally Watson had to demonstrate the level of confidence it had in the answer it came up with and it had to do all that in a matter of seconds.  Watson got better at the game and finally came up with answers at the average speed of 3 seconds.  Watson had access to over 200 million pages of structured and unstructured content consuming several terabytes of storage.  While Watson outperformed its human opponents most of the time, it had trouble responding to several categories.  Ferruci shared several examples where Watson was completely off the mark and that gave impressive evidence of how infinitely complex human speech is, where meaning of the same words is often determined or altered based on the order of the words, the sentence structure, placement of commas and exclamation marks.

English: Watson demoed by IBM employees.

English: Watson demoed by IBM employees. (Photo credit: Wikipedia)

At TiEcon, this was a breakthrough keynote, considering that most keynotes focus on the business aspect.  Ferrucci’s presentation was technical and fascinating and kept the audience riveted, soaking up the impressive information.

Ferrucci discussed the implications of this project in several other domains, with the members of the press.  It is possible that Watson-based technology, or services built upon it, might appear and might have implications in a wide range of industries.  Application in disease and healthcare diagnosis for instance, can be an invaluable tool to aid the doctors rarely have enough time with each patient to consider all possible data.  Also unlike many previous projects, Watson shows considerable similarity of thinking with the human mind.  For instance, Watson is programmed for uncertainty.  If is often not completely confident then Watson gives answers with varying levels of confidence, making it easier to determine how much weight to give to the answer given.  Truly fascinating project.

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  1. #1 by kumar on May 15, 2011 - 5:26 am

    There was a terrific article @newyorker http://goo.gl/Z8BAJ . It is 15 pages so let me quote a great example for context based understanding ,
    “The mouse on the desk is broken,” your mind calls forth a different image than if you hear, “The mouse on the desk is eating cheese.” Your brain registers the word “mouse,” waits for its context, and only then goes back to visualize it. But language leaves time for second thoughts. The flash-lag effect seems instantaneous. It’s as if the word “mouse” were changed to “track pad” before you even heard it.

    We @trolion trying to decipher the (semantic) web to make sense of social media and enhance automated customer support. Like @garyvee says data is not going to be the king but context will be. Hoping to attend TieCon next year, and also hoping that robots be grown organically (like we do) than try to build genetic algorithms to understand us!

    p.s: it is unfair for Watson to have questions as “text” while human contestants have to wait for verbal input.

    • #2 by Darshana V. Nadkarni, Ph.D. on May 15, 2011 - 10:56 pm

      Thank you for a wonderful response Kumar. What you are attempting to do seems fascinating and loved your comment “data is not going to be the king but context will be” – that is where the next disruptive AI technology might appear.

  2. #3 by kumar on May 16, 2011 - 2:00 am

    I am not entirely sanguine about the future of AI,
    Hard AI doesn’t get you 6 figure jobs at Apple/Goog/FB. But, any progress is better than no progress.

    BTW you have a fascinating blog. I liked your take on “Tiger Moms”. Here is another interesting take at NY Magazine yesterday,
    It is quite long but makes an interesting summer read. My favorite was ” A conspicuous person standing apart from the crowd and yet devoid of any individuality”. Talk about diversity is a double edged sword! Also, are Indians “Asians” in all these narratives? That discussion may be is for some other time. Now let me get back to the task of saving the world @TroLion!

    • #4 by Darshana V. Nadkarni, Ph.D. on May 16, 2011 - 2:08 am

      Thanks Kumar. I don’t know much about AI but seems fascinating. Thanks for sharing the NY article. Interesting. Thanks for your comments and good luck in saving the world — right there with Bill & Melinda Gates!!

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