LessWrong (Curated & Popular)

This is a link post. For the past year, we at the AI Futures Project have been sinking most of our time into our next big scenario. Now it's done!

It's called AI 2040: Plan A.

It's called Plan A because it's a recommendation, not a prediction. It's what we think should happen, not what will happen, though we think it's plausible enough to aim for.

It's called AI 2040 because in it, they delay the creation of superintelligence to 2040. It would have happened much sooner (in 2030, to be precise) if not for decisive action on the part of the US and Chinese governments.

As with AI 2027, summaries don’t really do it justice, since the whole point was to be detailed and comprehensive and work things out step by step rather than rely on high-level abstractions like doom or utopia.

Read the scenario at ai-2040.com. You can listen to it on audio, or view it on mobile, but the experience is significantly better on a normal computer.

What's next for us?

Well, first we are going to respond to comments and otherwise engage with whatever conversation, responses, critiques, etc. that [...]

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First published:

July 9th, 2026


Source:

https://www.lesswrong.com/posts/pFzctpJBat95SrCyC/ai-2040-plan-a


Linkpost URL:
https://www.ai-2040.com/

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The below is a public review Anthropic asked me to write for their new global workspace paper. I recommend at least skimming their paper first.

TLDR:

I think this is a fantastic paper - it presents compelling evidence for some kind of "cognitive space" in models, that is used as a "working memory" for intermediate variables during a forward pass, shows that J-Lens is a useful technique for accessing this space. I believe these key claims.
I believe J-Lens will be a useful (but limited) tool in practice for model forensics, e.g. generating hypotheses about unusual model behaviour during alignment audits.
I discuss my mental models for why a cognitive space should exist, and first principles arguments for why J-Lens should work for accessing it
I assess the paper's evidence that this cognitive space exists, and the paper's evidence that J-Lens is practically useful.
We have replicated the core claims on Qwen 3.6 27B, and also share preliminary evidence of extending this work by finding abstract "interpretative meta-tokens", like Chinese characters for "what does this mean" that seem to activate and play a causal role on processing ambiguous sentences.
What claims is this paper making?

In my opinion this [...]

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Outline:

(01:27) What claims is this paper making?

[... 28 more sections]

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First published:

July 6th, 2026


Source:

https://www.lesswrong.com/posts/zFJ3ZdQwrTWE9jT5S/a-review-of-anthropic-s-global-workspace-paper

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In a previous post, I explain why the universe is probably not stable, but nevertheless unlikely to be intentionally destroyable even in the limit of advanced technology. Now let's turn our attention to more prosaic risks where exotic physics merely destroys the Solar System, Earth, or just outperforms traditional nuclear weapons on some more local scale.

The basic logic behind any bomb is a self-sustaining chain reaction, in which a carrier converts a unit of fuel and comes out the other side in surplus:

Two conditions make this run away. The reaction must release energy, so the products are more stable than the fuel; and each reaction must produce more carrier than it consumes, so that one reaction seeds the next. A practical third condition is that cannot be so unstable that it decays before the bomb is assembled.

False vacuum decay is the ultimate bomb: is the false vacuum, the empty space we currently inhabit, and is the true vacuum. Because the supply of false vacuum is effectively unlimited, the reaction grows without bound and destroys the universe.

Fission bombs run on the same principle at a more prosaic scale. Consider uranium-235. This [...]

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Outline:

(03:19) Nuclei are probably, but not definitely, stable within the Standard Model

(08:11) Positively charged strangelets are safe, neutral strangelets are not

(11:34) Strangelets would be hard to make

(13:33) Exotic physics could permit ways to destroy protons, but not autocatalytically

(16:01) Other forms of matter offer no plausible chain reaction

(18:50) Tiny black holes are not scary

(20:04) Conclusion: There are no super-weapons between the nuclear bomb and false vacuum decay

(21:56) Appendix 1: Igniting the Atmosphere

(27:53) Optically thick ignition

(29:09) Appendix 2: Let's throw a strangelet into the sun

(29:21) Neutral strangelet

(32:56) Positive strangelet

(33:58) Bonus: neutral strangelet meets Earth

The original text contained 5 footnotes which were omitted from this narration.

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First published:

July 3rd, 2026


Source:

https://www.lesswrong.com/posts/cBnCCKwwjQ4zZpeNQ/don-t-fear-the-strangelet

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Training-run assessments conducted by a 3rd party should become a standard part of frontier AI safety.

By a Training-Run Assessment, or TRA, I mean an in-depth analysis of the post-training pipeline and dynamics leading up to a frontier model release. A TRA can look at intermediate checkpoints, training rollouts, RL environments, reward signals, SFT datasets, and the process by which the developer responded to warning signs.[1]

In this post I will argue that:

Final-checkpoint evaluations will be insufficient to assess scheming risks.
TRAs can be more effective at detecting scheming.
Frontier developers should involve third parties to do TRAs or verify safety claims by the developers.
The rest of the post lays out a taxonomy of TRAs and sketches a path toward a 3rd party ecosystem for them. We, at Apollo Research, are intending to conduct 3rd party Training-Run Assessments in the future.

Detecting Scheming may require Training-Run Assessments

By scheming I mean an AI covertly pursuing misaligned goals while deliberately concealing its intentions or capabilities from its developers. I restrict attention to “coherent” forms of scheming where the model pursues somewhat stable misaligned goals across context windows, rather than misalignment that surfaces only as isolated, context-dependent defections. [...]

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Outline:

(01:23) Detecting Scheming may require Training-Run Assessments

(03:55) Why 3rd parties should perform Training-Run Assessments

(04:12) Developers may lack incentives to adequately assess scheming

(04:49) Developers' safety assessments lack credibility

(05:31) External evaluators can bundle expertise for assessing scheming

(06:17) 3rd party TRAs can be developed gradually

(08:50) Checkpoint evals

(08:54) What?

(10:30) How?

(11:15) Data inspections

(11:19) What?

(12:03) Why?

[... 16 more sections]

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First published:

July 5th, 2026


Source:

https://www.lesswrong.com/posts/3HvvjffA65mHLwaWm/we-need-3rd-party-training-run-assessments

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[This is the blog post for our new paper Verbalizable Representations Form a Global Workspace in Language Models
Readers might also be interested in: the Public commentary, Github and Neuronpedia]







As you read this sentence, circuits in your brain are adjusting your posture, controlling your breathing, and transforming lines and curves on the screen into recognizable words. Most of this processing is invisible to you. But some of what takes place in your brain you do have access to—an image that pops into your head, or a deliberate plan you make about where to go shopping. Neuroscientists and philosophers sometimes refer to the latter type of brain activity as “consciously accessible,” to distinguish it from all the other processing that goes on unconsciously. This activity has special properties: we can describe it, control it, and use it for deliberate reasoning, in contrast to all the automatic processing that goes on without our awareness.

In a new paper, we present evidence that a similar distinction has emerged in modern language models like Claude. We find that Claude has developed a small collection of internal neural patterns that, compared to all its other internal processing, play a [...]

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Outline:

(06:09) How we found the J-space

[... 8 more sections]

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First published:

July 6th, 2026


Source:

https://www.lesswrong.com/posts/3PaLrzxagpbnNtPLT/a-global-workspace-in-language-models

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