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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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The dashed circle shows the current best distance. As the algorithm finds closer points, the circle shrinks, which causes more subtrees to fail the "could contain a closer point?" test and get pruned. The search usually gets cheaper as it progresses.
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Овечкин продлил безголевую серию в составе Вашингтона09:40。关于这个话题,WPS官方版本下载提供了深入分析
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