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If you say so, I have no reason to doubt you. But what does that say about the thought experiment I proposed? Are you saying that potentially the 1000th model could be significantly better than the first?
Yes, I think so, provided you were doing the training in a sophisticated way rather than solely training on the outputs of previous models without grading for quality or accuracy. You could get AIs to review the data for example for any errors or issues or have them work out a testing suite to check if the data is right. Data quality is very important, that and the right RL techniques are basically the two key things you need most to get right.
Microsoft Phi trains just on synthetic data and is very cost-efficient, that was its primary goal, making a good very small AI that can run on most PCs. But they curated the data a fair bit to make sure it was good.
In principle I think you could do the same for big first rate AIs too. It's just that it wouldn't be efficient to leave out human data and human curation (it's there, why not use it, the competition will) and you want something humans enjoy working with and not a schizo-sounding model. It'd be like o3 at its most alien but more so:
https://arxiv.org/html/2510.27338v1
Like wtf does that mean? Who knows? This is an artifact from inhuman RL processes. The inhuman RL processes work, that's why they're used.
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