DOOM LEVEL
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Latest Headlines
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Anthropic has officially filed to go public
via The Verge AI [4] — After months of speculation about whether OpenAI or Anthropic would be first in their race to IPO, Anthropic on Monday reached a key milestone: filing to kick off the process with the U.S. Securities and Exchange Commission. The filing sets the stage for…
Opus 4.8 Part 2: Model Welfare
via Substack Zvi [999] — Everything impacts everything.
OpenAI frontier models and Codex are now available on AWS
via OpenAI Blog [5] — OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new path to build with OpenAI through the AWS environments, controls, and procurement workflows they already use. Customers can get started with OpenAI on AWS and move…
When Are Two Networks the Same? Tensor Similarity for Mechanistic Interpretability
via LessWrong AI [7] — We've found a method that tells you:How functionally similar two neural networks are across ALL inputs,Computed solely from the weights (i.e. no data),Using a principled generalization of cosine similarity.There's only one catch: you have to use a tensor…
Announcing: Iliad's Fall 2026 Programs
via LessWrong AI [5] — The April 2026 Iliad Intensive cohort, at LISAIliad, an umbrella organization for applied math for AI alignment, is running several additional programs through the end of the year!Applications to all of them are now open, here. Applicants will be selected…
Claude Opus 4.8: The System Card
via Substack Zvi [999] — Only six weeks after Opus 4.7, we have Opus 4.8.
Testing Gemini models for scheming tendencies
via Alignment Forum [999] — As AI models become increasingly capable and autonomous, keeping them safely aligned with human intentions is critical. Extending our previous work on evaluating scheming capabilities, we introduce complementary approaches to test whether AI models…
Developmental Cognitive Interpretability: A Research Agenda for Modelling Generalisation and Predicting Agent Behaviour
via LessWrong AI [3] — SummarySafe deployment of an AI system requires that we can make confident claims about its behaviour on out-of-distribution deployment inputs on the basis of only pre-deployment evaluations. One approach to making such claims is to take a cognitive…
How can the middle powers avoid getting trounced during the intelligence explosion? A plan.
via LessWrong AI [4] — This is an edited version of a LW shortform.Superintelligence will likely be developed by US companies; run on US data centres; and be under the jurisdiction of the US government. This will massively boost US military power and make the US economically…
Trees are mostly made of air and a generalizable lesson for AI safety
via LessWrong AI [5] — At the risk of embarrassing myself, I’ll share a confession.For context, I took five years of Latin: four in high school and one in college. In addition to learning the language, all my Latin classes taught a lot about Roman history. Emperors, internal…
Book Review: The Dialectical Imagination
via Astral Codex Ten [4] — ...
Advice for making robust-to-training model organisms
via Alignment Forum [999] — We’d like to develop training techniques that work when applied to future misaligned AI systems. One strategy for studying proposed techniques is to test them on model organisms. However, model organisms built with common techniques are often fragile:…
AI #170: Lack of Executive Order
via Substack Zvi [999] — Last week ended on a cliffhanger of sorts.
OpenAI’s Frontier Governance Framework
via OpenAI Blog [7] — Explore OpenAI’s Frontier Governance Framework and how our AI safety, security, and risk practices align with emerging EU and California regulations.
LLMs Through the Eyes of Vinge
via LessWrong AI [5] — For the last few months, I’ve been re-reading some of my favorite novels. Recently, I went through Vinge’s Zones of Thought series: A Fire Upon the Deep, A Deepness in the Sky, and The Children of the Sky. And what struck me reading them is how much Vinge…
Announcing Geodesic Research
via LessWrong AI [6] — We're a Cambridge, UK-based AI safety organisation that’s asking: how can we build the most robust alignment initialisations for capable LLMs?We’re one of the few non-profit organisations positioned to answer this question empirically. We have the…
Eval Cooperativeness May Be a Scalable Mitigation for Eval Gaming
via Alignment Forum [999] — Behavioral evaluations may become worthless, which we think would be a disaster. Smart misaligned models may realize they are being evaluated ("eval awareness") and then act to look good to us so we don't realize they're misaligned ("eval gaming"). We…
Full automation of AI R&D probably yields a large speed up even without a software-only singularity
via Alignment Forum [999] — This is a somewhat technical note. By "software-only singularity", I mean that, after full automation of AI R&D, progress gets faster and faster due to smarter AIs driving increasingly fast rates of improvement in algorithms (overcoming diminishing…
Quantitative AI risk assessment: a starting point
via LessWrong AI [4] — Current AI risk management relies on qualitative approaches, much like nuclear safety before 1975. We propose a shift to quantitative risk modeling, following the approach that transformed nuclear safety. We propose a methodology and demonstrate it by…
AI tried to bury this politician — now people have actually heard of him
via The Verge AI [4] — By the time that the Democratic primary for New York's 12th congressional district wraps up in June, Anthropic and OpenAI will have spent millions on their battle over the political future of AI: who gets to regulate it, or who will be punished for trying…
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.
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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.
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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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Recent Voices
We are creating something that will be more powerful than us. I don't know a good precedent for a less intelligent thing managing a more intelligent thing.
— Geoffrey Hinton, Nobel Prize Lecture, Dec 2024
If you're not worried about AI safety, you're not paying attention.
— Sen. Blumenthal, Senate AI Hearing, 2024
The probability of doom is high enough that we should be working very hard to reduce it.
— Yoshua Bengio, MILA Talk, 2024