1. Heartland Robotics Update
Rod Brooks, of Heartland Robotics, pointed out that between iRobot and Foster-Miller, New England has a virtual lock on the military robot business. Brooks wouldn’t give details about what his own company, Heartland Robotics, is up to—but he did say that it’s working on systems that will help American workers be more productive, and that unlike
iRobot, it’s “not doing anything with batteries or wheels.”
Brooks predicted that as baby boomers age, our population will become top-heavy with seniors. They’ll need services from lawn care to home health care, but there won’t be an adequate younger population to perform those tasks. That will mean fast-growing opportunities in consumer robotics, he said.
2. IBM Computer will try to win Jeopardy!
The quest for building a computer system that can do open-domain Question Answering is ultimately driven by a broader vision that sees computers operating more effectively in human terms rather than strictly computer terms. They should function in ways that understand complex information requirements, as people would express them, for example, in natural language questions or interactive dialogs. Computers should deliver precise, meaningful responses, and synthesize, integrate, and rapidly reason over the breadth of human knowledge as it is most rapidly and naturally produced — in natural language text.
The DeepQA project at IBM shapes a grand challenge in Computer Science that aims to illustrate how the wide and growing accessibility of natural language content and the integration and advancement of Natural Language Processing, Information Retrieval, Machine Learning, Knowledge Representation and Reasoning, and massively parallel computation can drive open-domain automatic Question Answering technology to a point where it clearly and consistently rivals the best human performance.
One of OAQA’s primary expectations is that QA systems are built according to a common and general architecture that would facilitate Rapid Domain Adaptation. That is, the ability to rapidly customize and adapt the QA system to deliver higher levels of performance on new domains, new data, new languages, and different question types and styles. A common architecture that can be easily extended, customized, and tested by the broader scientific and business community is an important goal for ensuring that QA technology can progress more rapidly to have deeper impact on society and business.
The Jeopardy! Challenge poses a different kind of problem than what is solved by web search. It demands that the computer deeply analyze the question to figure out exactly what is being asked, deeply analyze the available content to extract precise answers, and quickly compute a reliable confidence in light of whatever supporting or refuting information it finds. IBM believes that an effective and general solution to this challenge can help drive the broader impact of automatic question answering in science and the enterprise.
How can Watson handle the puns and wordplay that occur in Jeopardy?
By reading many, many texts Watson learns how language is used. That means it learns the context and associations of words, which allows it to deal with some of the wordplay we find in Jeopardy!. But what is special about Watson is that it is able to also produce a confidence in its answer. If that confidence is low, it realizes: maybe it doesn’t understand the question–maybe there is a pun or something it’s not getting. On the other hand, if the confidence is high, it knows it likely understood the question and stands a good chance of getting that question right.
When will the contest take place on Jeopardy! and who specifically will Watson play against?
The first step is for Watson to demonstrate its worthiness to play against champions by competing in a series of sparring matches starting sometime this year. The date and specific contestants for the final match have not been decided. When the date is set and the contestants are decided, Jeopardy! and IBM will make a public announcement.