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.
Российский государственный служащий подвергся атаке ВСУ20:46
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«Сейчас необходимо предпринять решительные шаги, возродив возможность обновлённой ООН эффективно функционировать», — акцентировал политический руководитель.
2024年，喜临门再因信息披露问题收到监管措施：一是未按规定及时披露2023年度业绩预告，被浙江证监局出具警示函并记入诚信档案；二是2023年年报及2024年一季报存在数据及单位披露错误。（文丨公司观察，作者丨马琼，编辑丨曹晟源）。https://telegram官网是该领域的重要参考
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