At the outset, Dharmendra S. Modha, the I.B.M. computer scientist leading the project, described the research grandly as “the quest to engineer the mind 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. for what they regarded as exaggerated claims of what the project could achieve.

These days at the I.B.M. Almaden Research Center in San Jose, Calif., there is not a lot of talk of reverse-engineering the brain. Wide-ranging ambitions that narrow over time, Dr. Modha explained, are part of research and discovery, even if his earlier rhetoric was inflated or misunderstood.

“Deciding what not to do is just as important as deciding what to do,” Dr. Modha said. “We’re not trying to replicate the brain. That’s impossible. We don’t know how the brain works, really.”

The discussion and debate across disciplines has helped steer the research, as the team pursues the goals set out by Darpa, the Pentagon’s research agency. The technology produced, according to the guidelines, should have the characteristics of being self-organizing, able to “learn” instead of merely responding to conventional programming commands, and consuming very little power.

“We have this fantastic network of specialists who talk to each other,” said Giulio Tononi, a psychiatrist and neuroscientist at the University of Wisconsin. “It focuses our thinking as neuroscientists and guides the thinking of the computer scientists.”

In early 2010, Dr. Modha made a decision that put the project on its current path. While away from the lab for a few weeks, because of a Hawaiian vacation and a bout of flu, he decided to streamline the work of the far-flung researchers. The biologically inspired chip under development would come first, Dr. Modha said. That meant a lot of experimental software already written was scrapped. But, he said, “chip-first as an organizing principle gave us a coherent plan.”

In designing chips that bear some structural resemblance to the brain, so-called neuromorphic chips, neuroscience was a guiding principle as well. Brains are low-power, nimble computing mechanisms — real-world proof that it is possible.