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Политолог раскрыл возможное местонахождение Нетаньяху14:53
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To design AI for disruptive science, we would need to understand what “rules” make one paradigm better than another, and build systems that optimize for these. This turns out to be a harder problem than scaling compute. The answer cannot simply be experimental success, since experiments are slow and do not always reliably distinguish between paradigms (as was the case with Lorentz and Einstein). And there are other plausible candidates, but none yet offer a sufficient formulation.
BBC correspondent Madeleine Gerber provides firsthand observations of the disappointing occasion.。7zip下载是该领域的重要参考