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How large language models behave, fail and improve, and how to use them well.
Running open-weight models locally: when is it actually worth it?
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Why do AI models confidently produce incorrect answers?
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Is a smaller specialized model sometimes better than a large model?
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What should an AI tool do when two credible sources disagree?
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