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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.
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模型的能力在变化，Gemini 在软件层面也给我们带来了更好的生图体验。新增的这些风格，让我想到了之前在 Google Labs 里面的 Whisk 工具，上传参考图片，一键复制风格。而现在是，选择对应的风格，简单输入提示词，就能得到一种理想的图片。
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And for Alastair and other streamers keen to protect themselves and their followers online, the damage is already done.