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Large language models (LLMs) are trained on massive, publicly available text datasets comprising trillions of tokens, enabling them to excel at general language tasks like next-token prediction. However, LLMs often struggle with domain-specific prompts, exhibiting reduced accuracy or generating inaccurate information (hallucinations). This is because they lack sufficient subject matter expertise. Two primary approaches exist […] |
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 Your bi-monthly premiere of inebriated edutainment! The science event that makes you think while you drink! It’s a bit like TED Talks, but funnier, filthier and with booze! Venue is ages 21+ and cash only, BYO food is allowed. Speaker and title list: Christopher Land “Accessibility, A.I. & Bias: Opportunities & Threats" Jay Vu, MD […]
$15 |
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