Back in early 2011, I wrote a number of posts here about IBM’s Watson system, which scored a convincing victory over human champions in the long-running TV game show, Jeopardy!. Since then, IBM with its partners has launched efforts to employ Watson in a variety of other fields, including marketing, financial services and medical diagnosis, in which Watson’s ability to assimilate a large body of information from natural language sources can be put to good use.
Now, according to a post on the Gigaom blog, Watson will, in a sense, return to its roots in computer science research. IBM has supplied a Watson system to the Rensselaer Polytechnic Institute [RPI] in Troy, NY. According to Professor James Hendler, author of the post, and head of the Computer Science department at RPI, one focus of the work with Watson will be expanding the scope of information sources the system can use.
One of our first goals is to explore how Watson can be used in the big data context. As an example, in the research group I run, we have collected information about more than one million datasets that have been released by governments around the world. We’re going to see what it takes to get Watson to answer questions such as “What datasets are available that talk about crop failures in the Horn of Africa?”.
Some of the research work with Watson will also be aimed at gaining more understanding of the process of cognition, and the interplay of a large memory and sophisticated processing.
By exploring how Watson’s memory functions as part of a more complex problem solver, we may learn more about how our own minds work. To this end, my colleague Selmer Bringsjord, head of the Cognitive Science Department, and his students, will explore how adding a reasoning component to Watson’s memory-based question-answering could let it do more powerful things.
The Watson system is being provided to RPI as part of a Shared University Research Award granted by IBM Research. It will have approximately the same capacity as the system used for Jeopardy!, and will be able to support ~20 simultaneous users. It will be fascinating to see what comes out of this research.
The original IBM press release is here; it includes a brief video from Prof. Hendler.