# DeepMind 高管谈递归自我改进与 AI 基建投资逻辑

- 来源：Rohan Paul (@rohanpaul_ai)
- 发布时间：2026-09-13 22:23
- AIHOT 分数：43
- AIHOT 链接：https://aihot.news/items/cmtzxawna03swroymnrkme2oq
- 原文链接：https://x.com/rohanpaul_ai/status/2099141924120883216

## AI 摘要

Google DeepMind 首席战略官 Jasjeet Sekhon 称，若实现递归自我改进（RSI），曲线将走向超指数增长，这正是当前 AI 基建投入的核心逻辑。

## 正文

“If you hit recursive self-improvement, that curve will go to hyperexponential, and that is a key part of the investment thesis, the scientific thesis, and a key part of why society’s investing what it’s currently investing in.”

Google DeepMind Chief Strategy Officer Jasjeet Sekhon: The whole AI infrastructure spending is happening because of this expectation of self-improvement cycle.

In its strongest form, recursive self-improvement (RSI) will let AI design, evaluate, and train more capable successors with progressively less human supervision.

The current evidence is still narrower: e.g. Google's AlphaEvolve proposes algorithms, then automated evaluators run and score them against human-defined objectives.

Google has alreaday revealed how its resulting kernel changes reduced Gemini training time by 1%, an example of bounded improvement rather than autonomous successor design.

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From "Berkeley RDI" YouTube channel, (full video link in comment)

### 引用推文

> Rohan Paul：it begins, everybody is talking about recursive self-improvement. This is from Dario Amodei's latest 3800 word essay.