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:
But the years before seem to still inspire some people. Check out the Beagle Bros Repository – the homepage is a bit confusing (I think it prominently shows last-updated or last-added things for some reason?), but just use the nav at the top. Maybe it will inspire you, too.
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根据《中国人民银行关于实施一次性信用修复政策有关安排的通知》（银发〔2025〕245号）（以下简称《通知》）精神，国家开发银行承办的助学贷款（含生源地信用助学贷款和高校助学贷款，下同）将按政策要求实施一次性信用修复。现将具体事项公告如下：