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G Checkout Robert Miles careful analysis of AI risk, ignore the fact he looks (17)… ytc_UgzCtNlFJ… G The one thing that always sticks out to me on how much we don't understand AI is… ytc_Ugz02X5YR… G I think the real fear from AI that we have as a species is that of "will this th… ytc_UgxccZsQp… G 1st, facial recognition is not admissible as evidence in criminal proceedings be… ytc_UgyZP9a94… G He pioneers technology to power modern AI, and NOW he is sounding the alarm ... … ytc_UgzQPuICw… G Women easy to spot if deepfake Their knockers their private part Every Women h… ytc_Ugziyzfka… G That's an interesting perspective! While robots like Sophia don't sweat, they do… ytr_UgwDEHH16… G ​@opop-b2p you sound like an ai bro yourself that never draw or invent something… ytr_Ugx9pfHku…
Comment
also you were wrong about the fact that these algorithms are “too complicated to look inside.” you can actually train neural networks to accurately classify whether a language model thinks it’s lying already, regardless of its scale, from tiny ones up to the largest available. and during in-context learning, that’s actually not a mutable property of the model; it can’t fool the lie detector without changing its output (which is sort of the point, yeah)? of course if “trained,” it can jointly maximize the objective and minimize the lie detector given a gradient of it, but why would a fully trained model be doing gradient updates, and better yet, why would the lie detector be available to it as a white box? it just makes no sense.
youtube AI Moral Status 2023-08-21T08:1…
Coding Result
DimensionValue
Responsibilitydeveloper
Reasoningmixed
Policynone
Emotionmixed
Coded at2026-04-26T23:09:12.988011
Raw LLM Response
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