Analysis
AI #176 Part 1: Doing It Live
via Substack Zvi [999] — Enough things added up that this week is getting split into two parts.
How much slower does takeoff go with 10× less compute?
via LessWrong AI [7] — About 6x slower in the median case, with an 80% CI of 3.5x to 8x. SetupDefine the "R&D compute" (in, say, H100-equivalents) of an AGI company at a given time to be the total compute in use across the following categories:Compute used to run experiments,…
Find funding, fast
via LessWrong AI [10] — Some AI safety funders can take months to decide; others confirm in days. I’ve been on both sides of the grant application and know how crucial an early “yes” can be; “funding projects fast” has always been a core tenet of Manifund.Four new opportunities…
Childhood and Education #20: Phones and Screens
via Substack Zvi [999] — We have a respite, so I thought I’d tackle various thoughts on children, phones and screens.
AI Safety Can't Afford a Second Cause
via LessWrong AI [9] — Imagine an astronomer who discovers an asteroid with a 50% chance of hitting Earth in 2035. She goes on TV. She testifies before Congress. She founds the Asteroid Deflection Institute and starts doing fundraising rounds. And then, in between appearances,…
Superhuman Articulacy as an LLM Safety Target
via LessWrong AI [6] — TL;DR: Current LLMs are bad communicators relative to their agentic capabilities. I claim that articulacy is useful (and perhaps necessary) for AI safety and suggest a path for improving articulacy.Briefly: a theory for articulacyFrequently, LLM agents…
No Space Like J-Space
via Substack Zvi [999] — There is a new very cool Anthropic paper: Verbalizable Representations Form a Global Workspace in Language Models. You can read the blog post verison here.
Current views on large-scale longtermist philanthropy
via LessWrong AI [5] — This post summarizes some of my views. It states uncertain things boldly in part to [surface disagreements / help readers point out things that seem wrong or missing]. Note that many things are uncertain and many claims are not justified here.One tl;dr:…
Visioning: Concretely Imagining What You Want
via LessWrong AI [4] — When John told me (Gretta) his practice of “visioning,” I was skeptical at first. I gave it a try, a little bit out of spite, to show him I was capable of it.It blew me away.Here’s what I told him about it a few days later, edited for brevity and…
SFF is very suboptimal
via LessWrong AI [5] — I recently served as a recommender in SFF's annual funding round (grants will be decided and announced in September). I'm deeply grateful for SFF's funders, and I hope more AI safety donors appear in the future.Unfortunately, the SFF experience is bad for…
Tie training can make DPO/RLHF-trained AIs generalize better
via LessWrong AI [3] — This post covers our recent ICML paper: Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training.TL;DROur theorems and experiments suggest that DPO and RLHF have an unwelcome consequence: they make…
We need 3rd party Training-Run Assessments
via LessWrong AI [8] — 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…
Fable #6: The Return of the King
via Substack Zvi [999] — The blip is over.
AI Futurism Reading List
via LessWrong AI [5] — We at Redwood recently ran a strategy fellowship through Astra. As part of this, we ran a reading group for our fellows on some of the topics that we think are important for thinking about AI futurism (key dynamics in AI development, existential risk from…
The AFFINE Superintelligence Alignment Seminar – A Retrospective
via LessWrong AI [4] — A Day at AFFINE[1]“AFFINE was the best month of intellectual exploration I have had the opportunity to engage in, ever. Usually opportunities like this are limited to a day or a weekend, which both limits depth, forces a sprint-type mindset, and generally…
AI #175: The Fable Continues
via Substack Zvi [999] — Fable’s back.
When capabilities work is the *safe* bet
via LessWrong AI [5] — If you believe that LLMs lend themselves unusually well to alignment compared to other regimes, this can be a very good reason to start doing capability research on them rather than LLM safety research. Imagine you have these beliefs about how AI goes:By I…
Conversations With Cade Metz on the Rationalists
via LessWrong AI [4] — (Previously, previously.) New York Times reporter Cade Metz has been writing a book about the people who believed in AGI before it was cool. That's a subject that I think I know some things about, so we had some on-the-record conversations in 2025, which…
Claude Sonnet 5 Is Not Frontier But Has Its Uses
via Substack Zvi [999] — Fable 5 is back today, baby! Premium subscribers have one week to use it within their subscriptions. First hit’s free. Then you pay by the token.
Model access for third-parties — it's a big deal!
via LessWrong AI [5] — Over time, there might be an increasingly large gap between insider model access and outsider model access. By insiders, I mean employees at the frontier lab.[1] By "outsiders", I mean external safety researchers, third-party auditors, and other actors…
Live Doom Meter
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%
0% — We're fine
100% — GG
The Doom Meter is a composite score derived from prediction markets and feed sentiment, updated daily.
70%
Prediction Markets
Weighted average of Manifold Markets questions on AI catastrophe, AGI timelines, expert surveys, and key figures. Direct doom indicators weighted higher than indirect capability markers.
30%
Feed Sentiment
Percentage of recent headlines containing high-alarm keywords (existential risk, catastrophe, extinction). Higher alarm density = higher score.
This is not a scientific estimate of existential risk. It is an opinionated, transparent signal — a vibes-based thermometer for AI doom discourse.
P(Doom) Scoreboard
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