# DeepMind高管：AI基建押注递归自我改进

- 来源：Rohan Paul (@rohanpaul_ai)
- 发布时间：2026-08-05 20:51
- AIHOT 分数：51
- AIHOT 链接：https://aihot.virxact.com/items/cmsg3oj9n04m9rolgz7mhcobb
- 原文链接：https://x.com/rohanpaul_ai/status/2084985766686630358

## AI 摘要

Google DeepMind首席战略官Jasjeet Sekhon称，当前AI基础设施支出是在为期望中的自我改进循环买单。其最强形式下，递归自我改进（RSI）将让AI以越来越少的人类监督设计、评估和训练更强的后继者。目前证据仍较窄：如Google AlphaEvolve提出算法后由自动评估器按人类目标打分，其内核改动仅将Gemini训练时间缩短1%，属有限改进而非自主设计后继者。

## 正文

Recursive self-improvement → hyperexponential capability growth → the investment thesis behind present AI spending.

Google DeepMind Chief Strategy Officer Jasjeet Sekhon says AI infrastructure spending is financing a hoped-for self-improvement loop.
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From "Berkeley RDI" YouTube channel, (full video link in comment)

### 引用推文

> Rohan Paul："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 ke...