DOOM LEVEL
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The AI Hype Index: AI goes to war
via MIT Technology Review [4] — AI is at war. Anthropic and the Pentagon feuded over how to weaponize Anthropic’s AI model Claude; then OpenAI swept the Pentagon off its feet with an “opportunistic and sloppy” deal. Users quit ChatGPT in droves. People marched through London in…
Intelligence Inertia: Physical Principles and Applications
via ArXiv cs.AI [3] — While Landauer's principle establishes the fundamental thermodynamic floor for information erasure and Fisher Information provides a metric for local curvature in parameter space, these classical frameworks function effectively only as approximations within…
Introducing the OpenAI Safety Bug Bounty program
via OpenAI Blog [7] — OpenAI launches a Safety Bug Bounty program to identify AI abuse and safety risks, including agentic vulnerabilities, prompt injection, and data exfiltration.
The Fourth World
via LessWrong AI [4] — Is consciousness the last moral world?Imagine trying to explain to a virus why suffering matters.A virus is a simple self-replicating molecule: unsophisticated and arguably not even alive. It has no experience. It just copies itself according to chemical…
Arm’s first CPU ever will plug into Meta’s AI datacenters later this year
via The Verge AI [4] — After decades of only licensing its chip designs for others to use, UK-based Arm revealed the first chip it's producing on its own, and the first customer. Dubbed the Arm AGI CPU, it's another chip designed for inference, or running the cloud processing…
Book Review: Open Socrates (Part 2)
via Substack Zvi [999] — Yesterday I posted Part 1. Read that first. This is Part 2 of 2.
The AIXI perspective on AI Safety
via LessWrong AI [5] — I am also discussing something that is still a bit speculative, since we do not yet have ASI. While basic knowledge of AIXI is the only strict prerequisite, I suggest reading cognitive tech from AIT before this post for context.AIXI is often used as a…
Measuring and improving coding audit realism with deployment resources
via LessWrong AI [5] — TL;DR We study realism win rate, a metric for measuring how distinguishable Petri audit transcripts are from real deployment interactions. We use it to evaluate the effect of giving the auditor real deployment resources (system prompts, tool definitions,…
Leveraging Natural Language Processing and Machine Learning for Evidence-Based Food Security Policy Decision-Making in Data-Scarce Making
via ArXiv cs.AI [4] — Food security policy formulation in data-scarce regions remains a critical challenge due to limited structured datasets, fragmented textual reports, and demographic bias in decision-making systems. This study proposes ZeroHungerAI, an integrated Natural…
ProMAS: Proactive Error Forecasting for Multi-Agent Systems Using Markov Transition Dynamics
via ArXiv cs.AI [5] — The integration of Large Language Models into Multi-Agent Systems (MAS) has enabled the so-lution of complex, long-horizon tasks through collaborative reasoning. However, this collec-tive intelligence is inherently fragile, as a single logical fallacy can…
Nvidia CEO Jensen Huang says ‘I think we’ve achieved AGI’
via The Verge AI [8] — On a Monday episode of the Lex Fridman podcast, Nvidia CEO Jensen Huang made a hot-button statement: "I think we've achieved AGI." AGI, or artificial general intelligence, is a vaguely defined term that has incited a lot of discussion by tech CEOs, tech…
Book Review: Open Socrates (Part 1)
via Substack Zvi [999] — These are all important, in their own way, call it a treasure hunt and collect them all…
The Download: animal welfare gets AGI-pilled, and the White House unveils its AI policy
via MIT Technology Review [4] — This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The Bay Area’s animal welfare movement wants to recruit AI In early February, animal welfare advocates and AI…
China declares AGI development to be a part of 5-year plan
via LessWrong AI [4] — The CCP writes in its 15th 5-year plan that it will.Encourage innovation in multimodal, agentic, embodied, and swarm intelligence technologies, and explore development paths for general artificial intelligence.This is translated from the…
Finding features in Transformers: Contrastive directions elicit stronger low-level perturbation responses than baselines
via LessWrong AI [6] — Figure 1: Contrastive (difference-of-means, English→Mandarin) feature directions elicit a downstream response at much smaller perturbation magnitudes than SAE directions, which behave similarly to random directions. This holds across multiple models and…
Confusion around the term reward hacking
via LessWrong AI [3] — Summary: "Reward hacking" commonly refers to two different phenomena: misspecified-reward exploitation, where RL reinforces undesired behaviors that score highly under the reward function, and task gaming, where models cheat on tasks specified to them…
Trump takes another shot at dismantling state AI regulation
via The Verge AI [3] — The Trump administration on Friday unveiled its new legislative blueprint for AI regulation, and the seven-point plan includes a clear message: The federal government should avoid many AI regulations beyond a set of child safety rules, and it should bar…
The Federal AI Policy Framework: An Improvement, But My Offer Is (Still Almost) Nothing
via Substack Zvi [999] — The Federal AI Policy Framework has been released.
Mind-altering substances are (still) falling short in clinical trials
via MIT Technology Review [4] — This week I want to look at where we are with psychedelics, the mind-altering substances that have somehow made the leap from counterculture to major focus of clinical research. Compounds like psilocybin—which is found in magic mushrooms—are being…
The Case for Low-Competence ASI Failure Scenarios
via LessWrong AI [6] — I think the community underinvests in the exploration of extremely-low-competence AGI/ASI failure modes and explain why. Humanity's Response to the AGI Threat May Be Extremely IncompetentThere is a sufficient level of civilizational insanity overall and a…
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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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