Both ANNs and brains are (1) highly distributed and parallel (2) make small changes (3) efficient. Ideas like generalization hold for all systems with these three properties. In that sense, @tyrell_turing is obviously right. Maybe @GaryMarcus uses narrow def of abstraction.https://twitter.com/GaryMarcus/status/1200088188934451200 …
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Timos Moraitis, PhD Retweeted Gary Marcus
@tyrell_turing is right, ANNs are an abstraction. Of something. Which might be too simplistic/misdirected, so@GaryMarcus is right too. Both probably agree on these. The meaningful Q is: "What do ANNs miss?" Our next paper aims to give a partial answer.https://twitter.com/GaryMarcus/status/1200088188934451200 …Timos Moraitis, PhD added,
Gary Marcus @GaryMarcusastonished that anyone knowledgeable could claim that neural nets are (obviously) an “abstraction of neural processing” when we don’t yet know how brains work. if you don’t know how Y works you can’t really speak with certainty about whether X is an abstraction of Y. Period. https://twitter.com/tyrell_turing/status/1200072223299657728 …1 reply 1 retweet 5 likes -
Replying to @timos_m @KordingLab and
Exactly. Saying “it’s an abstraction” isn’t helpful as it’s just redundant information *at best*. Proper Q is how useful - useful here being faithful to biology - is it, for making concrete progress towards synthetic intelligence.
1 reply 0 retweets 2 likes
just for the record, i was just following @tyrell_turing's terminology. agree that one key question is about usefulness, other is about epistemology: how can we really know at this point when we really don't yet understand the brain.
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