MIT associate professor Josh Tenenbaum and his former student, Charles Kemp, have developed a computer algorithm that can select the best type of structure to fit a set of data. Such structures, shown here, include linear order, rings and clusters. (Credit: Image courtesy of Charles Kemp)

ScienceDaily (Aug. 28, 2008) — Humans have a natural tendency to find order in sets of information, a skill that has proven difficult to replicate in computers. Faced with a large set of data, computers don’t know where to begin — unless they’re programmed to look for a specific structure, such as a hierarchy, linear order, or a set of clusters.

Now, in an advance that may impact the field of artificial intelligence, a new model developed at MIT can help computers recognize patterns the same way that humans do. The model, reported earlier this month in the Proceedings of the National Academy of Science, can analyze a set of data and figure out which type of organizational structure best fits it.

“Instead of looking for a particular kind of structure, we came up with a broader algorithm that is able to look for all of these structures and weigh them against each other,” said Josh Tenenbaum, an associate professor of brain and cognitive sciences at MIT and senior author of the paper. more>>>

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This entry was posted on Thursday, August 28th, 2008 at 10:02 pm and is filed under Advanced Computing. You can follow any responses to this entry through the RSS 2.0 feed. Both comments and pings are currently closed.