Introduction

Several developments over the past few months should cause you to re-evaluate what you are doing. These include:

1. Updates toward short timelines
2. The Trump presidency
3. The o1 (inference-time compute scaling) paradigm
4. Deepseek
5. Stargate/AI datacenter spending
6. Increased internal deployment
7. Absence of AI x-risk/safety considerations in mainstream AI discourse

Taken together, these are enough to render many existing AI governance strategies obsolete (and probably some technical safety strategies too). There's a good chance we're entering crunch time and that should absolutely affect your theory of change and what you plan to work on.

In this piece I try to give a quick summary of these developments and think through the broader implications these have for AI safety. At the end of the piece I give some quick initial thoughts on how these developments affect what safety-concerned folks should be prioritizing. These are early days and I expect many of [...]

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Outline:

(00:06) Introduction

(01:21) Implications of recent developments

(01:25) Updates toward short timelines

(04:26) The Trump Presidency

(07:34) The o1 paradigm

(09:23) Deepseek

(12:08) Stargate/AI data center spending

(13:11) Increased internal deployment

(15:43) Absence of AI x-risk/safety considerations in mainstream AI discourse

(17:13) Implications for strategic priorities

(17:18) Broader implications for US-China competition

(19:33) What seems less likely to work?

(20:56) What should people concerned about AI safety do now?

(24:01) Acknowledgements

The original text contained 13 footnotes which were omitted from this narration.

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First published:

Source:

Narrated by TYPE III AUDIO.