elvis · @omarsar0 · X·2026-08-24 00:08·15小时前
AI 导读

博主Elvis Saravia推荐一篇关于AI芯片架构的长文,该文覆盖NVIDIA、AMD、TPU、Trainium、Cerebras、Groq等主流芯片的架构、扩展(scale-up与scale-out)及软件栈。Saravia认为,一旦RSI(递归自我改进)出现,模型架构可能快速演变,与今天截然不同,从而带来全新的算力需求。

elvis@omarsar0
34AI 编辑部评分,满分 100
2026-08-24 00:08· 15小时前
AI 导读

博主Elvis Saravia推荐一篇关于AI芯片架构的长文,该文覆盖NVIDIA、AMD、TPU、Trainium、Cerebras、Groq等主流芯片的架构、扩展(scale-up与scale-out)及软件栈。Saravia认为,一旦RSI(递归自我改进)出现,模型架构可能快速演变,与今天截然不同,从而带来全新的算力需求。

This is gold! Recommend reading if you want to understand the landscape of AI chip architectures. IMO, a lot can change once RSI comes around, as model architectures could evolve rapidly, looking completely different from today, hence requiring different compute needs.

Jacobsharing a new long-form blog post: ai chip architectures it covers the leading chip architectures (nvidia, amd, tpus, trainium, cerebras, groq) across architect...