Shahab Bakhtiari
@shahabbakht.bsky.social did:plc:dpgtuy5vtitbaayhzhe4mctb
|| assistant prof at University of Montreal || leading the systems neuroscience and AI lab (SNAIL: https://www.snailab.ca/) 🐌 || associate academic member of Mila (Quebec AI Institute) || #NeuroAI || vision and learning in brains and machines
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Zusammenfassung
Shahab Bakhtiari (@shahabbakht.bsky.social) ist seit 5 August 2023 auf Bluesky. Das Konto hat 6.584 Follower, folgt 1.184 Konten und hat 1.567 Posts veröffentlicht.
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- Brad Wyble@bwyble.bsky.social
AI has not made theory any cheaper. AI has made it easier to develop code and tools that allow us to test things, somewhat lowering the bar for testing some kinds of theories.
Post anzeigen 👀An important one for representational “stability-flexibility“ and drift debaters, including PV INs regulating drift, separable from task. Yet another noteworthy finding from Wenbo Tang in Oliva and @antferrui.bsky.social labs 🧪 🧠📈 www.nature.com/articles/s41...
Post anzeigenNew theory about value computations in PFC from the awesome @jowarrn.bsky.social and @jcrwhittington.bsky.social V excited that we can start thinking about sequence/schema tasks and value tasks in the same language. (This time with working videos:)
Post anzeigenIs meta-RL in PFC just a big RNN or can we figure out its mechanism? Here we show that RNNs learn a particular, but general, method for meta-RL. They place options in 'ranked’ subspaces (slots), and dynamically re-rank them. Value doesn’t pick the action; it reorders the slots 🧵 (Reposted w/ vids)
Post anzeigenHow do children learn the meanings of their first words? One idea is cross-situational learning: tracking which words go with which things across many situations. In a new preprint, we test this idea at scale on video from children's own perspective 🧵 arxiv.org/abs/2610.31842
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