LessWrong (Curated & Popular)

I was a grant evaluator for Lightcone Commons last round. Funders disbursed about $45mil through the program, and this included funding roughly my first 6.8 million dollars worth of recommendations. There are other projects I would've preferred to fund over what I did fund, but nobody was doing them and so they weren't on offer. Here's a series of projects that I'd fund in the next round, in rough order of priority. The next round is starting now, and is scheduled to end mid-December. I expect rounds to continue at similar speed. I expect similar amounts of funding will route through me in future rounds.

Disclaimer: I am NOT looking to manage anyone in doing any of these projects. I am not looking to help someone get started. Initiative and leadership and management capacity (and people that can just figure out how the heck to get something done, and that have the connections to do it) are the critical bottlenecks here. I can throw money at promising pitches, but not really help them all that much otherwise.

1. Leaders for a broad public movement against superintelligent machines. In the wake of Coxon Day, a number of random people around [...]

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First published:

November 3rd, 2026


Source:

https://www.lesswrong.com/posts/jNs9CxEbPxFdjnGA2/organizations-i-d-recommend-for-funding

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Narrated by TYPE III AUDIO.

By now, there are lots of AI safety research papers, more than what is reasonable for a single person to read. This will get worse as the machines get better at AI safety research, and as more talent and resources pour into the field. But the "paper" is an arbitrary unit, we really care about if we make progress on an "uncertainty" or an "issue", which papers provide heterogeneous and sometimes contradictory evidence towards. Right now, I loosely claim that we should have more short writeups that simply compile evidence from papers (particularly contradictory evidence), and reconcile them into an answer for a question.

Why?

Object level, it's good for the field. It's hard to sift through all these papers! Organising them is useful and saves time.
Orienting towards research questions is a good way to organise our understanding so that we can productively identify gaps and write papers. This was partly what motivated Stress-Testing Alignment Midtraining.
Interesting progress comes out of contradictions, where people have differing intuitions and experimental results. Methodological errors can also be exposed if we have two things that should be the same, but are actually different.

It's good for field-building reasons. [...]
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First published:

November 5th, 2026


Source:

https://www.lesswrong.com/posts/tn4WSyrqr7ozGLjRy/people-should-resolve-tensions-in-ai-safety-research

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Narrated by TYPE III AUDIO.

This is a link post. Executive summary

From August 12 to October 29, 2026, METR staff performed a high-access evaluation at Anthropic to assess the degree to which AI is accelerating AI R&D.[2] If AI systems started to significantly accelerate further AI development, this could lead to a sudden emergence of extreme and risky capabilities.

Anthropic offered unprecedented access to internal data on their AI R&D process, including a variety of metrics on pretraining, reinforcement learning (RL), training compute in each domain, benchmark scores for internal models, AI speedup analyses, forecasts of a future model's metrics, and interviews with relevant staff.

In our first section, we share our subjective conclusions about risk. We now believe that:

As of October 2026, Anthropic is likely improving the capabilities of their models on well-specified tasks at around twice the rate they did between March 2024 and October 2025. This estimate is given with high uncertainty; we would not be surprised if the true acceleration was closer to 1.3x or 3x the historical rate.
A majority of this acceleration today is likely attributable to Anthropic's extensive use of AI to do R&D, though there is significant uncertainty and other causes likely played a [...]
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First published:

November 5th, 2026


Source:

https://www.lesswrong.com/posts/N5AmYkRks5CqAxvBg/metr-independent-assessment-of-ai-r-and-d-acceleration-at


Linkpost URL:
https://metr.org/blog/2026-11-05-anthropic-ai-rd-acceleration-assessment/

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Narrated by TYPE III AUDIO.

For all my efforts at deliberate practicing rationality, by far the most actionable way to self-improve is "get on ADHD or depression meds, if you need them."

Your friends with ADHD and depression struggle to summon the motivation and focus necessary to get themselves a teledoc who can give them such meds. One of the most useful things you can do is sit them down and say "hey, wanna do the steps here to get some meds?" and then stare at them until they do.

(or, until they say "really I do not want that actually.")

This brought to you by ~2 years of Feedbackloop-first Rationality and Thinking Assistance.

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First published:

November 6th, 2026


Source:

https://www.lesswrong.com/posts/8qYuy9Cr6BNpgjJjT/help-your-friends-get-adhd-and-depression-meds

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Narrated by TYPE III AUDIO.

I've done AI safety grantmaking for the Survival and Flourishing Fund and Lightcone Commons. It's hard. There's an endless amount to know, from which hardware verification mechanisms will survive a dedicated adversary, all the way to which founders have skeletons in their closets that will blow up into destructive scandals. And the best grantmakers - not including me - make mathematical models of the outcome distribution, or of where the marginal dollar stops being highly effective.

AI has been a godsend for all of this. It can research, model, and - as of this year - superforecast outcomes. It can do what would be hours of work for a human in minutes. I found myself using it more and more. But however much I used it, it always felt like I was the bottleneck. The parts I could outsource to AI were sparkling, perfect, exhaustive - but they were all tacked together with shoddy connective tissue formed by the Mark 1.0 human brain. So I wondered if I could automate grantmaking.

I started with the dumbest possible strategy. I assigned the best thing I could think of - a well-crafted US-China pause based on the AI Futures Project's Plan [...]

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Outline:

(02:54) The Milestones

(06:26) The FutureSearch Connector

(08:26) PERCYs

(10:28) The Autograntor Common Law

(12:59) The Prompt

(19:12) Sample Runs

(20:00) Apart Research -- $800K grant forecast (2026-10-21)

(20:08) Headline

(21:29) Expected-value table (judge's ledger; EV after the execution factor 0.75 and branch weights)

(22:38) Assumptions and uncertainties

(24:50) How the estimates moved

(25:47) The three decisions that mattered most

(27:42) Rulings and milestones

(29:31) Values questions (CL-11), priced both ways

(29:56) Open questions for the user or applicant

(30:43) FutureSearch

(31:13) Cost

(31:47) Process problems

(36:39) Doom Debates -- $200K grant forecast (independent re-run, 2026-10-22)

(37:28) Headline (judge)

[... 11 more sections]

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First published:

November 1st, 2026


Source:

https://www.lesswrong.com/posts/Sfkv6JF2ozmAkggKu/towards-the-autograntor

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Narrated by TYPE III AUDIO.

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