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.
尽管水车屋贵得远超出一般人的消费，但那几年生意仍然好做到爆，全仰仗几家夜总会的拉动。几个人一晚上吃掉上万港币是家常便饭，连妈咪之间也会以此攀比——有没有被客人请去水车屋宵夜，一晚上吃了多少钱等等。
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