Select your localized edition:

Close ×

More Ways to Connect

Discover one of our 28 local entrepreneurial communities »

Be the first to know as we launch in new countries and markets around the globe.

Interested in bringing MIT Technology Review to your local market?

MIT Technology ReviewMIT Technology Review - logo


Unsupported browser: Your browser does not meet modern web standards. See how it scores »

{ action.text }

Emilio Bizzi, one of the founding members of MIT’s McGovern Institute of Brain Research, agreed that researchers should focus on important elements of human intellect, such as the ability to generalize learning experiences, or fluidly plan movements to avoid obstacles to achieve a specific goal such as grasping a pair of glasses. “I am optimistic that in the next few years, we will make a lot of progress, and the reason is that there are many laboratories scattered in various parts of the world that are pursuing humanoid robotics.”

The two linguists on the panel, Noam Chomsky and Barbara Partee, both made seminal contributions to our understanding of language by considering it as a computational, rather than purely cultural, phenomenon. Both also felt that understanding human language was the key to creating genuinely thinking machines. “Really knowing semantics is a prerequisite for anything to be called intelligence,” said Partee.

Chomsky derided researchers in machine learning who use purely statistical methods to produce behavior that mimics something in the world, but who don’t try to understand the meaning of that behavior. Chomsky compared such researchers to scientists who might study the dance made by a bee returning to the hive, and who could produce a statistically based simulation of such a dance without attempting to understand why the bee behaved that way. “That’s a notion of [scientific] success that’s very novel. I don’t know of anything like it in the history of science,” said Chomsky.

Sydney Brenner, who deciphered the three-letter DNA code with Francis Crick and teased out the complete neural structure of the c. elegans worm on a cellular level, agreed that researchers in both artificial intelligence and neuroscience might be getting overwhelmed with surface details rather than seeking the bigger questions underneath. Looking at attempts to replicate his mapping of the c. elegans neural “wiring diagram” with more complex organisms, Brenner worried that neuro- and cognitive scientists were being “overzealous” in these attempts. He said they should refocus on higher level problems instead. He used the analogy of someone taking a picture with a smart phone: no one today would bother to give a transistor-level description of such an action: it’s much more useful to discuss the process in terms of higher level subsystems and software.

34 comments. Share your thoughts »

Credit: Technology Review

Tagged: Computing, MIT, neuroscience, AI, artificial intelligence

Reprints and Permissions | Send feedback to the editor

From the Archives


Introducing MIT Technology Review Insider.

Already a Magazine subscriber?

You're automatically an Insider. It's easy to activate or upgrade your account.

Activate Your Account

Become an Insider

It's the new way to subscribe. Get even more of the tech news, research, and discoveries you crave.

Sign Up

Learn More

Find out why MIT Technology Review Insider is for you and explore your options.

Show Me