I have been thinking a lot lately about “diachronic AI” and “vintage LLMs” — language models designed to index a particular slice of historical sources rather than to hoover up all data available. I’ll have more to say about this in a future post, but one thing that came to mind while writing this one is the point made by AI safety researcher Owain Evans about how such models could be trained:
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We appear to have reached a point in the information age where AI models are becoming old enough to retire from, er, service — and rather than using their twilight years to, I don’t know, wipe the floor with human chess leagues or something, they're now writing blogs. Can anything be more 2026 than that?，更多细节参见下载安装汽水音乐
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next tuple of R. The selection node repeatedly calls next() on the table scan until it finds a tuple that satisfies a5. It then passes it up to the projection which finally returns it back to you.