Dr. Noah D. Goodman

The ScienceDaily article Grand Unified Theory of AI: New Approach Unites Two Prevailing but Often Opposed Strains in Artificial-Intelligence Research said

In the 1950s and ’60s, artificial-intelligence researchers saw themselves as trying to uncover the rules of thought. But those rules turned out to be way more complicated than anyone had imagined. Since then, artificial-intelligence (AI) research has come to rely, instead, on probabilities — statistical patterns that computers can learn from large sets of training data.
 
The probabilistic approach has been responsible for most of the recent progress in artificial intelligence, such as voice recognition systems, or the system that recommends movies to Netflix subscribers. But Noah Goodman, an MIT research scientist whose department is Brain and Cognitive Sciences but whose lab is Computer Science and Artificial Intelligence, thinks that AI gave up too much when it gave up rules. By combining the old rule-based systems with insights from the new probabilistic systems, Goodman has found a way to model thought that could have broad implications for both AI and cognitive science.

Noah D. Goodman, Ph.D. is Research Scientist in the Computational Cognitive Science Group at MIT.
 
His research interests include:

• Concepts, categorization, and intuitive theories.
• Computational models of cognition, integrating logic and probability.
• Probabilistic programming languages: foundations, implementation, and application.
• Cognitive development.
• Language acquisition.
• Natural language semantics.
• Causal learning and reasoning.
• Social cognition.

Noah coauthored The Infinite Latent Events Model, Fragment Grammars: Exploring Computation and Reuse in Language, Learning a Theory of Causality, Cause and Intent: Social Reasoning in Causal Learning, How Tall Is Tall? Compositionality, Statistics, and Gradable Adjectives, One and Done? Optimal Decisions From Very Few Samples, Informative Communication inWord Production andWord Learning, and Using Speakers’ Referential Intentions to Model Early Cross-Situational Word Learning. Read the full list of his publications!
 
Noah earned his B.A. in Mathematics (Cum Laude) at the University of Arizona in 1997, his B.S. in Physics (Cum Laude) at the University of Arizona in 1997, and his Ph.D. in Mathematics at the University of Texas at Austin in 2003.
 
Read Interview of Noah Goodman of the Cognitive Science Group at MIT by Sander Olson.