Challenging the Limits of Learning

TAU measures the human mind against the yardstick of a machine

Although we’re convinced that baby is brilliant when she mutters her first words, cognitive scientists have been conducting a decades-long debate about whether or not human beings actually “learn” language.

Most theoretical linguists, including the noted researcher Noam Chomsky, argue that people have little more than a “language organ” — an inherent capacity for language that’s activated during early childhood. On the other hand, researchers like Dr. Roni Katzir of Tel Aviv University‘s Department of Linguistics insist that what humans can actually learn is still an open question — and he has built a computer program to try and find an answer.

“I have built a computer program that learns basic grammar using only the bare minimum of cognitive machinery — the bare minimum that children might have — to test the hypothesis that language can indeed be learned,” says Dr. Katzir, a graduate of the Massachusetts Institute of Technology (where he took classes taught by Chomsky) and a former faculty member at Cornell University. His early results suggest that the process of language acquisition might be much more active than the majority of linguists have assumed up until now.

Dr. Katzir’s work was recently presented at a Cornell University workshop, where researchers from fields in linguistics, psychology, and computer science gathered to discuss learning processes.

A math model in mind

Able to learn basic grammar, the computer program relies on no preconceived assumptions about language or how it might be learned. Still in its early stages of development, the program helps Dr. Katzir explore the limits of learning — what kinds of information can a complex cognitive system like the human mind acquire and then store at the unconscious level? Do people “learn” language, and if so, can a computer be made to learn the same way?

Using a type of machine learning known as “unsupervised learning,” Dr. Katzir has programmed his computer to “learn” simple grammar on its own. The program sees raw data and conducts a random search to find the best way to characterize what it sees.

The computer looks for the simplest description of the data using a criterion known as Minimum Description Length. “The process of human learning is similar to the way computers compress files: it searches for recognizable patterns in the data. Let’s say, for instance, that you want to describe a string of 1,000 letters. You can be very naïve and list all the letters in order, or you can start to notice patterns — maybe every other character is a vowel — and use that information to give a more compact description. Once you understand something better, you can describe it more efficiently,” he says.

Artificial intelligence for answering machines

His early results point to the conclusion that the computer, modeling the human mind, is indeed able to “learn” — that language acquisition need not be limited to choosing from a finite series of possibilities.

While it’s primarily theoretical, Dr. Katzir’s research may have applications in technologies such as voice dialogue systems: a computer that, on its own, can better understand what callers are looking for. A more advanced version of Dr. Katzir’s program might learn natural language grammar and be able to process data received in a realistic setting, reflecting the manner in which humans actually talk.

The results of the research might also be applied to study how we learn to “read” visual images, and may be able to teach a robot how to reconstruct a three-dimensional space from a two-dimensional image and describe what it sees. Dr. Katzir plans to pursue this line of research with engineering colleagues at Tel Aviv University and abroad.

“Many linguists today assume that there are severe limits on what is learnable,” Dr. Katzir says. “I take a much more optimistic view about those limitations and the capacity of humans to learn.”

Reference Link
http://www.aftau.org/site/News2?page=NewsArticle&id=13753

Courtesy
American Friends of Tel Aviv University

Bihar could serve as a role model: NYT

PATNA, India: Bihar is changing and it is now being acknowledged by the international media. An article published in New York Times (NYT) has termed Bihar as a state which could serve as a model.

Recalling that for decades Bihar was “something between a punch line and cautionary tale, the exact opposite of the high tech, rapidly growing, rising global power India has sought to become,” the article said that previously “criminals could count on police protection, not prosecution. Highway men ruled the shredded roads and kidnapping was one of the most profitable businesses”.

“The name captured everything that was wrong with the old India — a combustible mix of crime, corruption and caste politics in a state crucible that stifled economic growth,” it said.

However, after the turnaround when it notched an 11 per cent average growth rate for the last five years, the news was greeted as a sign that even India’s most intractable corners of backwardness and misery were being transformed, the article says.

Bihar’s turnaround illustrates how a handful of seemingly small changes can yields big results in India’s most impoverished and badly governed regions. It stressed that state governments are responsible for everything from schools to hospitals to policing to maintaining most roads. “Bihar is a textbook case of how leadership determines development,” it says.

The article has uncharitable things to say about Lalu Prasad who ran the state for 15 years `from beneath a banyan tree’.

“Under Mr Prasad’s watch, criminal syndicates kidnapped, extorted and robbed with impunity, protected by political leaders or in some cases led by politicians,” it says, adding Lalu’s government did little to improve the daily lives of Biharis. It talks about dismal road conditions, schools crumbling as teachers did not turn up for work and health centres left unstaffed.

Reference Link
http://timesofindia.indiatimes.com/city/patna/Bihar-could-serve-as-a-role-model-NYT/articleshow/5786048.cms

Courtesy
Bennett, Coleman & Co. Ltd.