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David Ferrucci on Singularity 1 on 1: Pursue the Big Challenges

This Monday I interviewed Dr. David Ferrucci on Singularity 1 on 1.

David is the IBM team leader behind Watson – the computer that succeeded in dethroning humanity’s greatest ever jeopardy champion – Ken Jennings.

I met both Dr. Ferrucci and Ken Jennings during last year’s Singularity Summit where both of them spoke about Watson and the opportunities and challenges associated with it. It was then and there that I hatched my plan to get David (and Ken) on Singularity 1 on 1.

I have to say that I learned a lot from and enjoyed talking to David very much. My favorite quote that I will take away from him is this:

“Pursue the big challenges and do the big things that inspire people and make them scratch their heads.”

During our conversation with Dr. Ferrucci we also discuss topics such as: his original interest in biology and medicine and the story of how he got (accidentally) involved in computer science and programming; why Watson is not mere speech recognition software (or statistical database) but natural language processing and (a lot) more; the inside story behind the idea of creating Watson; the motivation and challenges behind the project; overcoming resistance and the danger and fear of failure; the definition of AI; the importance of Watson in the general scheme of things; Watson’s future and David Ferrucci’s plans; the technological singularity; whole brain simulation and/or emulation; the importance of pursuing the big challenges.

(As always you can listen to or download the audio file above or scroll down and watch the adapted video interview in full.)


Building Watson – A Brief Overview of the DeepQA Project

David Ferrucci of IBM discusses the DeepQA Project; the technology and architecture behind IBM’s newest technological innovation, the question answering and natural language processing system, Watson.


Who is David Ferrucci?

Dr. David Ferrucci is an IBM Fellow and the Principal Investigator (PI) for the Watson/Jeopardy! project. He has been at IBM’s T.J. Watson’s Research Center since 1995 where he heads up the Semantic Analysis and Integration department. Dr. Ferrucci focuses on technologies for automatically discovering valuable knowledge in natural language content and using it to enable better decision making.

As part of his research he led the team that developed UIMA. UIMA is a software framework and open standard widely used by industry and academia for collaboratively integrating, deploying and scaling advanced text and multi-modal (e.g., speech, video) analytics. As chief software architect for UIMA, Dr. Ferrucci led its design and chaired the UIMA standards committee at OASIS. The UIMA software framework is deployed in IBM products and has been contributed to Apache open-source to facilitate broader adoption and development.

In 2007, Dr. Ferrucci took on the Jeopardy! Challenge – tasked to create a computer system that can rival human champions at the game of Jeopardy!. As the PI for the exploratory research project dubbed DeepQA, he focused on advancing automatic, open-domain question answering using massively parallel evidence based hypothesis generation and evaluation. By building on UIMA, on key university collaborations and by taking bold research, engineering and management steps, he led his team to integrate and advance many search, NLP and semantic technologies to deliver results that have out-performed all expectations and have demonstrated world-class performance at a task previously thought insurmountable with the current state-of-the-art. Watson, the computer system built by Ferrucci and his team beat the highest ranked Jeopardy! champions of all time on national television on February 14th 2011. He is now leading his team to demonstrate how DeepQA can make dramatic advances for intelligent decision support in areas including medicine and health care.

Dr. Ferrucci has been the Principal Investigator (PI) on several government-funded research programs on automatic question answering, intelligent systems and saleable text analytics. His team at IBM consists of 32 researchers and software engineers specializing in the areas of Natural Language Processing (NLP), Software Architecture, Information Retrieval, Machine Learning and Knowledge Representation and Reasoning (KR&R).

Dr. Ferrucci graduated from Manhattan College with a BS in Biology and from Rensselaer Polytechnic Institute in 1994 with a PhD in Computer Science specializing in knowledge representation and reasoning. He is published in the areas of AI, KR&R, NLP and automatic question-answering.

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  • A great
    explanation of the motivation, logistics, and algorithms behind Watson. I
    believe Watson’s biggest contribution was in long-term strong AI PR, and that
    contribution was non-trivial. 😉

    I like
    Ferrucci’s attitude toward “failure.” I also believe failure is just
    another step toward success, and failure often teaches more than success does.
    “Is it possible? If it isn’t, why? If it is, I want to be the one that did
    it.” Take a closer look at the accomplishments of someone who always
    succeeds, and you will likely see a history padded with mundane, uninteresting,
    and common tasks.

    interview solidified my conflicting predictions on the potential behavior of
    strong AI. On one hand, I believe strong AI may have “motives” (using
    the most general definition of the term “motive”) similar to the
    humans who catalyzed the strong AI, because the humans will, intentionally or unintentionally,
    build those motives into the AI system. On the other hand, I believe strong AI
    may not have motives (as we understand “motives”) or may have motives
    that are too exotic for us to understand, because, after all, the motives will
    be *of strong AI.*

    quite useful is Ferrucci’s explanation of the limitations of the Turing Test.
    As useful as the Turing Test may be, it is just one tool of many on the journey
    to strong AI recognition, and not the pinnacle definition of strong AI

    ending point about the potential horrors of constructing a human-like brain
    unconnected to everything else in a normal human environment is important.
    Creating a conscious, sentient, human-like brain- with a corresponding
    human-like mind- outside of a human body / environment would likely be an
    experiment in abuse.

  • Thank you very much Cynthia, 

    as always you make not only fantastic comments yourself but you also have a keen eye for the interviewee’s best quote gems.  

  • Dan Vasii

    Neither Watson, nor DeepBlue, are not artificial intelligence. They are just “smart’ databases; Watson has a special input ability in order to treat certain verbal informations as commands for query. It is a great advancement to AI, but it isn’t AI. AI is a system that will extract informations from an environment and incorporate into itself, changing for better its ability to respond to that environment. Watson and DeepBlue do not do this. 

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