Software systems could one day analyze everything from blurry war-zone footage to the subtle sarcasm in a written paragraph, thanks to two unassuming scientists who are inspired by biology to make revolutionary strides in intelligent computing.
Yann LeCun and Rob Fergus, both computer science professors at New York University, are the brains behind “Deep Learning,” a program sponsored by Darpa, the Pentagon’s blue-sky research agency. The idea, ultimately, is to develop code that can teach itself to spot objects in a picture, actions in a video, or voices in a crowd. LeCun and Fergus have $2 million and four years to make it happen.
Existing software programs rely heavily on human assistance to identify objects. A user extracts key feature sets, like edge statistics (how many edges an object has, and where they are) and then feeds the data into a running algorithm, which uses the feature sets to recognize the visual input.
“People spend huge amounts of time building these feature sets, figuring out which are better or more accurate, and then refining them,” LeCun told Danger Room. “The question we’re asking is whether we can create computers that automatically learn feature sets from data. The brain can do it, so why not machines?”
The computer systems will be inspired by biology, but not modeled after it. That’s because researchers still aren’t entirely sure how animals are able to turn inputs — an object, a movement, a sound — into usable information. Ten years ago, a study at MIT helped answer the question. Researchers rewired ferret brains, so that the optical nerve fed into the auditory cortex, and vice versa. But the ferrets still saw and heard normally, leading the team to conclude that brain function depends on the signal — not the area.
Brains also display plenty of abstraction when it comes to identifying specific inputs: LeCun was inspired to create his algorithmic layering approach, called “a convolutional network,” by the 1960s research of David Hubel and Torstein Weisel. The two used cats to demonstrate how the brain’s visual cortex relies on abstractions to create complex representations of a given visual input.
In other words, LeCun said, “There’s some sort of learning algorithm within the brain. We just don’t know what it is.”...
