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The questions studied in Artificial Intelligence Group (AI)
are of enormous practical and scientific importance and have proven to
be quite difficult for conventional programming techniques. Human brains
evolved to excel at tasks such as vision, motor control, speech, and language
understanding, and are much better at these than
artificial systems. The ICSI AI Group effort is
exploring how computational models and techniques based
on natural intelligence can prove useful in applications tasks. The
ICSI project differs from most others in its emphasis on structured
networks, strong methods that exploit scientific knowledge, and extensive
interaction with other computer science techniques and theory.
In particular, the Artificial Intelligence group
continues its long term study of language, learning, and connectionist
neural modeling. The scientific goal of this effort is to understand how
people learn and use language. The applied goal is to develop systems
that support human centered computing through natural language and other
intelligent systems.
Natural language processing is a core activity of the AI
Group. There are three main efforts that comprise this work: FrameNet, a
project to build a machine-readable lexicon with detailed semantic
descriptions of a substantial portion of the English vocabulary; NTL,
the Neural Theory of Language, which uses computational models and
simulations of language and learning to answer basic questions about the
production and use of natural language; and SHRUTI, a project on
representation and inference that deals with rapid parallel inferencing
of the kind humans display when performing common-sense reasoning or
recalling association.
Professor Srini Narayanan, Adjunct Professor of
Cognitive Science at UC Berkeley, is the AI Group leader.
Browse AI Group Publications
Read about specific projects of the AI Group.
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