NYT-1201: STATE OF THE ART A Thermostat That's Clever, Not ...

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he 1940s, the biological metaphor has been irresis tible. The first computers — room-size behemoths — were referred to as “giant brains” or “electronic brains,” in headlines and everyday speech. As com puters improved and became capable of some tasks f amiliar to humans, like playing chess, the term us ed was “artificial intelligence.” DNA, it is said, is the original software. For the most part, the biological metaphor has lon g been just that — a simplifying analogy rather th an a blueprint for how to do computing. Engineerin g, not biology, guided the pursuit of artificial i ntelligence. As Frederick Jelinek, a pioneer in sp eech recognition, put it, “airplanes don’t flap th eir wings.” Yet the principles of biology are gaining ground a s a tool in computing. The shift in thinking resul ts from advances in neuroscience and computer scie nce, and from the prod of necessity. The physical limits of conventional computer desig ns are within sight — not today or tomorrow, but s oon enough. Nanoscale circuits cannot shrink much further. Today’s chips are power hogs, running hot , which curbs how much of a chip’s circuitry can b e used. These limits loom as demand is acceleratin g for computing capacity to make sense of a surge of new digital data from sensors, online commerce, social networks, video streams and corporate and government databases. To meet the challenge, without gobbling the world’ s energy supply, a different approach will be need ed. And biology, scientists say, promises to contr ibute more than metaphors. “Every time we look at this, biology provides a clue as to how we should pursue the frontiers of computing,” said John E. K elly, the director of research at I.B.M. Dr. Kelly points to Watson, the question-answering
computer that can play “Jeopardy!” and beat two h uman champions earlier this year. I.B.M.’s clever machine consumes 85,000 watts of electricity, whil e the human brain runs on just 20 watts. “Evolutio n figured this out,” Dr. Kelly said. Several biologically inspired paths are being expl ored by computer scientists in universities and co rporate laboratories worldwide. But researchers fr om I.B.M. and four universities — Cornell, Columbi a, the University of Wisconsin, and the University of California, Merced — are engaged in a project that seems particularly intriguing. The project, a collaboration of computer scientist s and neuroscientists begun three years ago, has b een encouraging enough that in August it won a $21 million round of government financing from the De fense Advanced Research Projects Agency, bringing the total to $41 million in three rounds. In recen t months, the team has developed prototype “neuros ynaptic” microprocessors, or chips that operate mo re like neurons and synapses than like conventiona l semiconductors. But since 2008, the project itself has evolved, be coming more focused, if not scaled back. Its exper ience suggests what designs, concepts and techniqu es might be usefully borrowed from biology to push the boundaries of computing, and what cannot be a pplied, or even understood. At the outset, Dharmendra S. Modha, the I.B.M. com puter scientist leading the project, described the research grandly as “the quest to engineer the mi nd by reverse-engineering the brain.” The project embarked on supercomputer simulations intended to equal the complexity of animal brains — a cat and then a monkey. In science blogs and online forums, some neuroscientists sharply criticized I.B.M. fo r what they regarded as exaggerated claims of what the project could achieve.
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