Viewing enriched Twitter post
Really interesting new @gwern essay: LLM Daydreaming - Proposal of how default mode networks for LLMs are an example of missing capabilities for search and novelty Btw, I know it's a bit cringe to delight in, but if you had told 19 year old me that a Gwern essay would open… https://t.co/9ftGa96IEH
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"text": "also applies to pre-training in a human. We reflect about each cluster of inputs we get in real time and learn.\nIn LLMs pre-training has no reasoning involved, and I suspect that needs to change. \n\nReasoning should be incorporated into pre-training. \n\nIt kind of already is through synthetic data generation for verifiable domains, but that is not e2e neural.\n\nRelevant to \"truth-seeking\" models:",
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"full_text": "@karpathy also applies to pre-training in a human. We reflect about each cluster of inputs we get in real time and learn.\nIn LLMs pre-training has no reasoning involved, and I suspect that needs to change. \n\nReasoning should be incorporated into pre-training. \n\nIt kind of already is…",
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"full_text": "@dwarkesh_sp @gwern This, but applied to pre-training too (in addition to continuous learning).",
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"full_text": "@dwarkesh_sp @gwern awesome will read. Tangentially, in the first paragraph I wonder if thinking hard \"feels\" difficult not because of the energy demand, but because it produces waste product that has to get cleaned up. It's not necessarily an energy issue \n\ni wonder if AIs will have to sleep",
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