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  "full_text": "Technically , this seems true but the wrinkle is that I can get discussions of novel questions at the quality level of a top PhD student in organizational theory\n\nAnd research shows you can get answers at the level of professors in strategic management. Not many in training data. https://t.co/zsxMwJUE2H",
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    "full_text": "People have too inflated sense of what it means to \"ask an AI\" about something. The AI are language models trained basically by imitation on data from human labelers. Instead of the mysticism of \"asking an AI\", think of it more as \"asking the average data labeler\" on the internet.\n\nFew caveats apply because e.g. in many domains (e.g. code, math, creative writing) the companies hire skilled data labelers (so think of it as asking them instead), and this is not 100% true when reinforcement learning is involved, though I have an earlier rant on how RLHF is just barely RL, and \"actual RL\" is still too early and/or constrained to domains that offer easy reward functions (math etc.).\n\nBut roughly speaking (and today), you're not asking some magical AI. You're asking a human data labeler. Whose average essence was lossily distilled into statistical token tumblers that are LLMs. This can still be super useful ofc ourse. Post triggered by someone suggesting we ask an AI how to run the government etc. TLDR you're not asking an AI, you're asking some mashup spirit of its average data labeler.",
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