Americans are destroying Flock surveillance cameras
Экс-посол Британии жестко высказался об агрессии США против Ирана08:51
04 写在最后2025年的全球酒店业，是行业格局深度调整的一年，也是行业正式迈入差异化竞争全新阶段的一年。。业内人士推荐体育直播作为进阶阅读
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Thanks for reading Brian's Substack! Subscribe for free to receive new posts and support my work.。关于这个话题，旺商聊官方下载提供了深入分析
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.