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ABHIMANYU PALLAVI SUDHIR




RESEARCH

PhD student @ University of Warwick

 * CV: relevant, extended, html (autogenerated by Pandoc)
 * Blogs: The Winding Number, Copypasta
 * Profiles: LessWrong, Stack Exchange, Twitter
 * Also profiles: LinkedIn, GScholar, ORCID

My goal is to design an AI agent whose internal structure is that of a market
(because markets and intelligent agents do basically the same things; markets :
intelligence :: capitalism : learning). My research will prevent the
now-seemingly-inevitable destruction of the world and lead us to a glorious
utopia, for three broad reasons:

 * (Alignment is Industrial Organization) Markets serve the consumers, they
   don’t develop nefarious goals of their own, at least when you have a decent
   antitrust system, or spies. In fact this also addresses the question of how
   to handle conflicting interests between the humans we’d like to align the AI
   to.
 * (Eliciting Latent Knowledge = Interpretability) We could maybe get agents to
   bet on questions on their own latent space, or get agents to somehow bet on
   each others’ latent spaces in a useful manner.
 * (Coherent Extrapolated Volition) I like transhumanism as much as the next
   android, but there was a Jimmy Neutron episode wherein one of the characters’
   heads grew 500x its size and he became evil. It’s not obvious how to factor
   someone as Intelligence X Utility_function, because any “utility function”
   you might have is going to be some rationalization/as-if fit to the person’s
   actions, which are limited by his bounded rationality. But markets solve the
   question of bounded rationality; “more algorithmic information” just means
   “more traders”.

So far all I’ve done is devise prediction markets for First-Order Logic (and
also hyperarithmetical) sentences – preprint: arxiv.org/abs/2402.14021. Some
side-quests that have emerged as a corollary of all this – contact if you’re
interested in collaborating, because I don’t have the time to do them all:

 * Building practical markets: I can prove that a very theoretical implication
   of my framework works; designing real markets for this will require some
   work.
 * Implications for mathematical logic: What if you let mathematical theories
   bet on markets? If they make a lot of money, we should trust them. Maybe this
   gives us a nice way to think about proof-theoretic ordinals etc. IDK.
 * Rewriting probability theory: I think the probability theory axioms are wrong
   and should be rewritten in a way to make long-term prices on my market a
   probability distribution. In particular, a sigma-algebra should only be
   required to be closed under countable union of a computable enumeration of
   its elements.
 * Bridges to neural networks: As it stands, program markets are absurdly
   impractical. Now I think I can solve this with latent spaces, but maybe we
   can somehow transfer our ideas to neural networks, or interpret neural
   networks as markets.

The first one will help you get rich; the second and third will satiate your
deepest intellectual curiosities; the last one will prevent the world from being
destroyed.