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.
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二是要做开放互利的创新伙伴。德国政府在技术、创新、数字等领域提出新发展战略，同中国“十五五”时期智能化、绿色化、融合化发展方向高度契合。双方应加强发展战略对接，支持两国人才、知识、技术双向流动，促进人工智能等前沿领域对话合作。双方要正确把握竞争和合作的关系，寻求互利共赢的合作路径，共同维护产业链供应链稳定畅通。，更多细节参见同城约会