Users are excited about the new paper modeling economics of recursive self-improvement in AI because they find its visual approach helpful for understanding feedback loops and appreciate the launch and supporters.
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@testingham @ElasticityInst Very cool will give it a deep read Have you considered 'upgrading' the dag to some kind of Markov chain model which could capture stochastic processes? I assume you did and would love to hear comments
@testingham @ElasticityInst the visual approach to formalizing feedback loops actually makes the abstract stuff way easier to digest
@testingham @ElasticityInst Congrats on the launch, Tom!
@Afinetheorem @ElasticityInst Thanks Kevin!
It uses elasticity measures to map AI capability feedback loops.
@testingham @ElasticityInst the visual approach to formalizing feedback loops actually makes the abstract stuff way easier to digest
marvellous work, one couldn’t hope for a better treatment. I think Tom should get a “Such microeconomic effects are self-evidently already occurring” bumper sticker. https://twitter.com/testingham/status/2076723049609801995
Useful formalisation of recursive improvement feedback loops https://twitter.com/testingham/status/2076723055062405129
@__nmca__ Ha thank you Nat!
Users are excited about the new paper modeling economics of recursive self-improvement in AI because they find its visual approach helpful for understanding feedback loops and appreciate the launch and supporters.
Based on 7 visible X reactions from 7 accounts; directional sample.
Ask a question below.
Published answers will appear here.
Useful formalisation of recursive improvement feedback loops https://twitter.com/testingham/status/2076723055062405129