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因为在任何公司里,业务线高管到底是更多地按照个人技术偏好做决策,还是必须服从公司的整体战略,答案不需要辩论。

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据资料显示,戈蓝本名简重,曾长期担任 iQOO 旗舰产品线的产品总监。在加入 iQOO 品牌之前,他曾是三星电子的一名资深硬件工程师,拥有极其深厚的行业背景与技术积淀。

Compute grows much faster than data . Our current scaling laws require proportional increases in both to scale . But the asymmetry in their growth means intelligence will eventually be bottlenecked by data, not compute. This is easy to see if you look at almost anything other than language models. In robotics and biology, the massive data requirement leads to weak models, and both fields have enough economic incentives to leverage 1000x more compute if that led to significantly better results. But they can't, because nobody knows how to scale with compute alone without adding more data. The solution is to build new learning algorithms that work in limited data, practically infinite compute settings. This is what we are solving at Q Labs: our goal is to understand and solve generalization.

Proposal

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