这项研究为大模型训练中的浮点数量化提供了重要的理论指导。其价值不仅在于明确了在给定资源和精度下的最优参数配置策略，帮助提高训练效率和降低成本，而且对于推动大模型在实际应用中的更广泛部署具有关键意义。通过揭示浮点数量化训练的极限和规律，为硬件制造商优化 ...

作为一个AI从业者，个人观点“scaling law撞墙”，完全不是媒体吹得那么耸人听闻！它只是意味着——未来通用人工智能的发展路径应当适时地转向。 下面说说我的理由：“scaling ...

The proper analysis of data is perhaps not the most exciting topic in physics, but it is among the most important. Aesthetic considerations and preconceptions profitably drive the creative side of ...

Formerly, the power law fitted to Bitcoin is a simple equation Price = A(t - t_0)^n Here t is time, t_0 is initial time, A is a scaling factor, and n is an exponent. Put simply, the price of ...

11月27日消息，“大多数人不知道，关于Scaling Law的原始研究来自2017年的百度，而不是2020年的OpenAI。” 近日一则上述内容刷爆AI圈子，引发对百度 ...

Logarithmic Scaling: By using logarithmic scaling, the Power Law highlights Bitcoin's long-term trend of reduced volatility and moderated growth. Limitations: This model offers insights for the long ...

training data and compute resources boosted performance following a power-law relationship. This insight guided the development of subsequent large-scale AI models. However, Dario Amodei ...