DARPA aims to breach the human-computer natural language barrier

Ambitious DARPA program looks to turn computers into good natural language blabbermouths

Will it be possible to actually communicate with a computer and have it understand context, gestures and even its human counterparts facial expressions? Such notions are usually reserved for the screenplays of science fiction novels and movies.

A new Defense Advanced Research Projects Agency (DARPA) program however wants to take such ideas out of the science fiction realm and make them reality in the next few years.

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This week the advanced research agency announced the Communicating with Computers (CwC) program that aims to develop technology to turn computers into good communicators.

CWC aims to accelerate progress toward two-way communication between people and computers in which the machine is more than merely a receiver of commands and in which a full range of natural modes is tapped, including potentially language, gesture and facial or other expressions, DARPA stated.

Humans almost never hear a sentence without some context, but machines almost never hear a sentence in context. Communication relies on the power of context, so machines must be able to use context.

"Human communication feels so natural that we don't notice how much mental work it requires," said Paul Cohen, DARPA program manager. "But try to communicate while you're doing something else –the high accident rate among people who text while driving says it all– and you'll quickly realize how demanding it is."

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According to DARPA, to further the goal of developing systems that communicate more like people do, the CwC program will set chores in which humans and machines must communicate to do a job. One task will involve collaborative story-telling, in which a human and a machine will take turns contributing sentences until they have written a short story.

“Another CwC task will be to build computer-based models of the complicated molecular processes that cause cells to become cancerous. Computers are starting to do this already in DARPA's Big Mechanism program, but they don't work collaboratively with human biologists—a shortcoming, because while machines read more quickly and widely than humans, they do not read as deeply, and while machines can generate vast numbers of molecular models, humans are better judges of the biological plausibility of those proposed models,” DARPA says.

DARPA's Big Mechanism program looks to let computers gather the massive amounts of exiting data about a particular topic, say cancer research, keep it up-to-date and develop new conclusions or research directions. Today's researchers read deeply but struggle to keep up with relentless streams of relevant publications. To stay current, a researcher must specialize, becoming expert in a small part of something much bigger.

The vision for the Big Mechanism program is fundamentally different:  Every publication would immediately become part of a public, computer-maintained, causal model of a complicated system-a big mechanism-and every aspect of a big mechanism would be tied to the data that supports it or contradicts it.  To the extent that we can automate the construction of Big Mechanisms, we can change how science is done, DARPA said.

“Because humans and machines have different abilities, collaborations between them might be very productive. But today we view computers as tools to be activated by a few clicks or keywords, in large part because we are separated by a language barrier,” Cohen said. “The goal of CwC is to bridge that barrier, and in the process encourage the development of new problem-solving technologies."

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