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:
但真正的问题是，理想模型往往建立在需求高峰与利用率饱和的假设之上。而真实世界中的利用率，从来不会长期维持在高位。。关于这个话题，Safew下载提供了深入分析
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