计算视角：AGI 可实现，硬件远未到极限

AI 摘要

Together AI 的 Dan Fu 发表新文章，反驳 AI 发展遇到硬件瓶颈的观点。他认为当前芯片利用率极低，通过软硬件协同设计和 FP4 训练等创新可大幅提升性能。他还指出模型训练滞后于硬件发展，且现有模型已能改变复杂工作流。

正文节选

Dan Fu, our VP of Kernels, has published a new post challenging the idea that AI is hitting a hardware wall. He argues that we are vastly underutilizing current chips and that better software-hardware co-design will unlock the next order of magnitude in performance. Is progress toward AGI hitting a wall? In the fast-moving world of AI, there is a growing debate about whether we are approaching the “limits of digital computation.” Some recent analysis suggests that hardware constraints and stalle

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抓取时间：2026-08-03 01:13

来源机构：Together AI