[Editors] MIT: Model helps computers sort data more like humans

[Teresa Herbert]

FOR IMMEDIATE RELEASE
Contact: Teresa Herbert, MIT News Office
T. 617-258-5403, E. therbert at mit.edu

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MIT model helps computers sort data more like humans
--Advance could impact artificial intelligence field
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CAMBRIDGE, Mass. -- Humans have a natural tendency to find order in  
sets of information, a skill that has proven difficult to replicate in  
computers. Faced with a large set of data, computers don’t know where  
to begin — unless they’re programmed to look for a specific structure,  
such as a hierarchy, linear order, or a set of clusters.

Now, in an advance that may impact the field of artificial  
intelligence, a new model developed at MIT can help computers  
recognize patterns the same way that humans do. The model, reported  
earlier this month in the Proceedings of the National Academy of  
Science, can analyze a set of data and figure out which type of  
organizational structure best fits it.

“Instead of looking for a particular kind of structure, we came up  
with a broader algorithm that is able to look for all of these  
structures and weigh them against each other,” said Josh Tenenbaum, an  
associate professor of brain and cognitive sciences at MIT and senior  
author of the paper.

The model could help scientists in many fields analyze large amounts  
of data, and could also shed light on how the human brain discovers  
patterns.

The computer algorithm was developed by recent MIT PhD recipient  
Charles Kemp, now an assistant professor of psychology at Carnegie  
Mellon University, along with Tenenbaum.

The model considers a range of possible data structures, such as  
trees, linear orders, rings, dominance hierarchies, clusters, etc. It  
finds the best-fitting structure of each type for a given data set and  
then picks the type of structure that best represents the data.

Humans perform the same feat in everyday life, often unconsciously.  
Several scientific milestones have resulted from the human skill of  
finding patterns in data — for example, the development of the  
periodic table of the chemical elements or the organization of  
biological species into a tree-structured system of classification.

Children exhibit this data organization skill at a young age, when  
they learn that social networks can be organized into cliques, and  
that words can fit into overlapping categories (for example, dog,  
mammal, animal).

“We think of children as taking in data, forming theories, and testing  
those theories with experiments. They’re like little scientists,”  
Tenenbaum said. “Until now there’s been no good computational model  
for how children can, like scientists, grasp the underlying global  
structure of a set of data.”

The research was funded by the James S. McDonnell Foundation Causal  
Learning Research Collaborative, the Air Force Office of Scientific  
Research, and the NTT Communication Sciences Laboratory.

By Anne Trafton, MIT News Office
# # #

Teresa Herbert
Media Specialist
Massachusetts Institute of Technology
News Office, Room 11-400
Cambridge, MA 02139-4307

Phone: 617-258-5403
Fax: 617-258-8762

therbert at mit.edu




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