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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.
，这一点在同城约会中也有详细论述
launched in 1966, built specifically for the Michigan Bell to manage customer
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中国减贫实践，对人类减贫有什么借鉴意义？