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.
This doesn't mean all maps must be brand new, just from the same batch/pre-calculation period.
根据现场体验，S26 Ultra 可以设置在出现密码键盘、指定 app 内以及所有弹窗类通知时，全自动启用防窥模式，将可视角度缩窄到手机正面大约 80 度的范围内——，推荐阅读快连下载安装获取更多信息
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