[ExI] Watson on NOVA

Amara D. Angelica amara at kurzweilai.net
Mon Feb 14 06:35:15 UTC 2011

Kelly, thanks. These are excellent questions, which I'll include in a
follow-up interview. We just posted three IBM videos that discuss customer
service, finance, and healthcare applications; and two more on other Watson
design issues, including one related to building the system: 




-----Original Message-----
From: Kelly Anderson [mailto:kellycoinguy at gmail.com] 
Sent: Sunday, February 13, 2011 9:57 PM
To: amara at kurzweilai.net; ExI chat list
Subject: Re: [ExI] Watson on NOVA


On Sun, Feb 13, 2011 at 2:14 AM, Amara D. Angelica <amara at kurzweilai.net>

> Kelly, I had similar questions, so I interviewed an IBM Watson research

> manager. Please see if this helps:


> m-research-manager. I would be interested in any critiques of this, or

> questions for a follow-up interview.


"open, pluggable architecture of analytics" sounds like it has an

engine, and can add heuristics. If that's the case, then this is a

pretty powerful core technology, but it requires that it be "built and

tuned to play Jeopardy!" So if I were going to ask follow up

questions, I would ask some along these lines...


On the NOVA show it talked about adding gender information... is this

one of the pluggable pieces you are referring to?


When you say "open" do you mean open source? Or open for purchasers of

the system to augment?


Is this going to be available in a cloud configuration anytime soon?


Tell us more about "building" and "tuning"... It appears from the NOVA

show that it took 4 years to build and tune the system for Jeopardy,

how much effort would it take to build and tune a system for medical

diagnosis? Or build a technical support database for say Microsoft



It seems that the natural language processing of the questions and

categories is very extensive and uses a kind of search tree technology

reminiscent of AI search trees used in games such as chess. Is that



Tell us more about the index that is build a priori of the raw data

that the answers are sought from. Is it indexed, or is there just a

brute force algorithm based on keyword searches and then further

statistical processing of the results of the keyword search. In other

words, what's done prior to the question being asked on the index side

of the equation?


(I'm sure you could make that question shorter... :-)


You talk about Watson "learning", is the learning on the side of

understanding the question, finding the answer or both? Are you using

neural networks, statistical approaches, or some new approach for



If developers wanted to build and tune their own solutions on this

architecture, how soon do you think it will be available? Is there a

business unit working on this yet?


Are there going to be any papers published by the Watson team?


What aspect of Watson is the most novel? Or is Watson just putting

together the best of what was already out there in a really good way?


I'm sure I could come up with more questions... but those would be

among the ones I would ask first I think. I really liked your article.

It was particularly interesting to listen to them think about what

IBM's business model for such things might be.




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