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One challenge is having enough training data. Another is that the training data needs to be free of contamination. For a model trained up till 1900, there needs to be no information from after 1900 that leaks into the data. Some metadata might have that kind of leakage. While it’s not possible to have zero leakage - there’s a shadow of the future on past data because what we store is a function of what we care about - it’s possible to have a very low level of leakage, sufficient for this to be interesting.,推荐阅读爱思助手下载最新版本获取更多信息

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而对 Google 来说,本次与 Meta 合作是其底层算力商业化战略的重要进展。据此前报道,Google 正积极推动自研 TPU 成为英伟达主导的 GPU 市场之外的可行替代方案。

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