[ExI] ExtroBritannia: Machine super intelligence

estropico estropico at gmail.com
Sun Oct 18 16:55:46 UTC 2009

Dr Shane Legg leads a state-of-the-art review of models of how super
intelligent machines might work.

2pm-4pm, Saturday 31st October

Room 416, 4th floor (via main lift), Birkbeck College, Torrington
Square, London WC1E 7HX

About the talk:

What ever happened to the ambitious aims of artificial intelligence,
specifically, its original goal of creating an "intelligent machine"?
Are we any closer to this than we were 20 or 30 years ago? Indeed,
have we made any progress on figuring out what intelligence is, let
alone knowing how to build one? After all, if we had a clearer idea of
where we want to get to, we might be able to come up with some better
ideas on how to get there!

Clearly, artificial intelligence could do with a better theoretical
foundation. This talk will outline work on creating such a foundation:

*) What is intelligence?
*) How can we formalise machine intelligence?
*) Solomonoff Induction: a universal prediction system.
*) AIXI: Hutter's universal artificial intelligence.
*) MC-AIXI: a computable approximation of AIXI.
*) Can the brain tell us anything useful for building an AI?
*) Is building a super intelligent machine a good idea?

About the speaker:

Dr Shane Legg is a post doctoral research associate at the Gatsby
Computational Neuroscience Unit, University College London. He
received a PhD in 2008 from the Department of Informatics, University
of Lugano, Switzerland. His PhD supervisor was Prof. Marcus Hutter,
the originator of the AIXI model of optimal machine intelligence. Upon
the completion of his PhD he won the $10,000 Canadian Singularity
Institute for Artificial Intelligence Prize and was also awarded a
post doctoral research grant by the Swiss National Science Foundation.

Shane is a native of New Zealand. After training in mathematics he
began a career as a software engineer, mostly for American companies
specialising in artificial intelligence. In 2003 he returned to
academia to complete a PhD. His research has been published in top
academic journals (e.g. IEEE TEC), and featured in mainstream
publications (e.g. New Scientist). All of Shane's publications,
including his doctoral thesis "Machine super intelligence", are
available on his website: vetta.org.


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