How AI training scales

归档编码:how-ai-training-scales-55cf833b

核心要点速览

We’ve discovered that the gradient noise scale, a simple statistical metric, predicts the parallelizability of neural network training on a wide range of tasks. Since complex tasks tend to have noisier gradients, increasingly large batch sizes are likely to become useful in the future, removing one potential limit to further growth of AI systems. More broadly, these results show that neural network training need not be considered a mysterious art, but can be rigorized and systematized.

首发信源 OpenAI News OpenAI 官方博客、模型发布与科研进展
所属板块 人工智能 AIPEDIAS 实时情报监测
查看完整报道与分享

完整图文、背景资料与讨论归原始发布平台 OpenAI News 所有。

直达原文报道 ↗