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+ Become a sponsorNomination created on January 22, 2026
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1 backer · 9 verified votesdLogos verifies that votes are from real people.
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Suggested
The success of scaling laws suggests we may not need the structural inductive biases you've championed.
Scaling large transformers has produced emergent abilities and strong generalization. This challenges the need for biologically inspired priors like those Dileep has advocated. Is scale simply a cheaper route to the same destination?
Why are cortical columns so special, and why should AI architectures mimic them?
Cortical columns have been a recurring motif in Dileep's work. How do they provide computational advantages over current attention-based layers, and what could AI systems gain from incorporating their structure?
How should we evaluate AI safety when agents learn through learned world models rather than simple reward hacking?
Dileep has emphasized understanding and world models over pure reward optimization. Does that change the AI safety landscape, making risks more about model misspecification than goal misalignment?

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