# Gary Marcus 在付费文章中论述 neurosymbolic AI 的兴起需要 CPU 和 GPU 协同，改变了过去纯 GPU 驱动的 AI 格局

- 来源：Gary Marcus
- 发布时间：2026-08-08 01:35
- AIWatch 分数：59
- AIWatch 标记：未精选
- AIWatch 链接：https://aiwatch.icu/events/evt_01kzena4skagdk9aebevhsj5rn
- 原文链接：https://garymarcus.substack.com/p/cpus-and-the-rise-of-neurosymbolic

## 精选理由

常规快讯，保留列表

## AI 摘要

Gary Marcus 在付费文章中论述 neurosymbolic AI 的兴起需要 CPU 和 GPU 协同，改变了过去纯 GPU 驱动的 AI 格局。

## 正文

To a first approximation, a pure neural network mostly just needs GPUs, graphics processing chips that do lots of matrix arithmetic in parallel. (You could use a CPU but it would be way less efficient.)

Classic computation mostly uses CPUs, which are more general-purpose in the kinds of computations that they are designed to perform.

Neurosymbolic AI, which by definition tries to combine the two, typically requires both.1

In the age in which pure neural networks were dominant, which one might very roughly date as 2012 (when people began running neural networks on GPUs rather than CPUs) through mid 2023 (when Frontier companies quietly started incorporating things like symbolic code interpreters), a very large fraction of commercial AI was driven almost purely by GPUs.

Now we are seeing something different.

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