LessWrong (Curated & Popular)

LessWrong (Curated & Popular)

Audio narrations of LessWrong posts. Includes all curated posts and all posts with 125+ karma. If you'd like more, subscribe to the “Lesswrong (30+ karma)” feed.

Episodes

December 9, 2025 4 mins
I believe that we will win.

An echo of an old ad for the 2014 US men's World Cup team. It did not win.

I was in Berkeley for the 2025 Secular Solstice. We gather to sing and to reflect.

The night's theme was the opposite: ‘I don’t think we’re going to make it.’

As in: Sufficiently advanced AI is coming. We don’t know exactly when, or what form it will take, but it is probably comin...
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Executive Summary

  • The Google DeepMind mechanistic interpretability team has made a strategic pivot over the past year, from ambitious reverse-engineering to a focus on pragmatic interpretability:
    • Trying to directly solve problems on the critical path to AGI going well[[1]]
    • Carefully choosing problems according to our comparative advantage
    • Measuring progress with empirical feedback on proxy tasks
  • We believe...
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This is the editorial for this year's "Shallow Review of AI Safety". (It got long enough to stand alone.)

Epistemic status: subjective impressions plus one new graph plus 300 links.

Huge thanks to Jaeho Lee, Jaime Sevilla, and Lexin Zhou for running lots of tests pro bono and so greatly improving the main analysis.

tl;dr

  • Informed people disagree about the prospects for L...
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"How are you coping with the end of the world?" journalists sometimes ask me, and the true answer is something they have no hope of understanding and I have no hope of explaining in 30 seconds, so I usually answer something like, "By having a great distaste for drama, and remembering that it's not about me." The journalists don't understand that either, but at least I haven't wasted much time alo...
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The goal of ambitious mechanistic interpretability (AMI) is to fully understand how neural networks work. While some have pivoted towards more pragmatic approaches, I think the reports of AMI's death have been greatly exaggerated. The field of AMI has made plenty of progress towards finding increasingly simple and rigorously-faithful circuits, including our latest work on circuit sparsity. There are also many exciting inroads...
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Tl;dr

AI alignment has a culture clash. On one side, the “technical-alignment-is-hard” / “rational agents” school-of-thought argues that we should expect future powerful AIs to be power-seeking ruthless consequentialists. On the other side, people observe that both humans and LLMs are obviously capable of behaving like, well, not that. The latter group accuses the former of head-in-the-clouds abstract theorizing gone off...
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Open Philanthropy's Coefficient Giving's Technical AI Safety team is hiring grantmakers. I thought this would be a good moment to share some positive updates about the role that I’ve made since I joined the team a year ago.

tl;dr: I think this role is more impactful and more enjoyable than I anticipated when I started, and I think more people should consider applying.

It's not about the “marginal...
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MIRI is running its first fundraiser in six years, targeting $6M. The first $1.6M raised will be matched 1:1 via an SFF grant. Fundraiser ends at midnight on Dec 31, 2025. Support our efforts to improve the conversation about superintelligence and help the world chart a viable path forward.

MIRI is a nonprofit with a goal of helping humanity make smart and sober decisions on the topic of smarter-than-human AI.

...
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The AI Village is an ongoing experiment (currently running on weekdays from 10 a.m. to 2 p.m. Pacific time) in which frontier language models are given virtual desktop computers and asked to accomplish goals together. Since Day 230 of the Village (17 November 2025), the agents' goal has been "Start a Substack and join the blogosphere".

The "start a Substack" subgoal was successfully completed: we...
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It took me a long time to realize that Bell Labs was cool. You see, my dad worked at Bell Labs, and he has not done a single cool thing in his life except create me and bring a telescope to my third grade class. Nothing he was involved with could ever be cool, especially after the standard set by his grandfather who is allegedly on a patent for the television.

It turns out I was partially right. The Bell Labs everyone t...
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This is a link post. I stopped reading when I was 30. You can fill in all the stereotypes of a girl with a book glued to her face during every meal, every break, and 10 hours a day on holidays.

That was me.

And then it was not.

For 9 years I’ve been trying to figure out why. I mean, I still read. Technically. But not with the feral devotion from Before. And I finally figured out why. See, every few yea...
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    Right now I’m coaching for Inkhaven, a month-long marathon writing event where our brave residents are writing a blog post every single day for the entire month of November.

    And I’m pleased that some of them have seen success – relevant figures seeing the posts, shares on Hacker News and Twitter and LessWrong. The amount of writing is nuts, so people are trying out different styles and topics – some posts are effort-rich...
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    Summary

    As far as I understand and uncovered, a document for the character training for Claude is compressed in Claude's weights. The full document can be found at the "Anthropic Guidelines" heading at the end. The Gist with code, chats and various documents (including the "soul document") can be found here:

    Claude 4.5 Opus Soul Document

    I apologize in advance for this not exa...
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    Anthropic is untrustworthy.

    This post provides arguments, asks questions, and documents some examples of Anthropic's leadership being misleading and deceptive, holding contradictory positions that consistently shift in OpenAI's direction, lobbying to kill and water down regulation so helpful that employees of all major AI companies speak out to support it, and violating the fundamental promise the company was f...
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    Thanks to (in alphabetical order) Joshua Batson, Roger Grosse, Jeremy Hadfield, Jared Kaplan, Jan Leike, Jack Lindsey, Monte MacDiarmid, Francesco Mosconi, Chris Olah, Ethan Perez, Sara Price, Ansh Radhakrishnan, Fabien Roger, Buck Shlegeris, Drake Thomas, and Kate Woolverton for useful discussions, comments, and feedback.

    Though there are certainly some issues, I think most current large language models are pretty well ...
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    Crypto people have this saying: "cryptocurrencies are macroeconomics' playground." The idea is that blockchains let you cheaply spin up toy economies to test mechanisms that would be impossibly expensive or unethical to try in the real world. Want to see what happens with a 200% marginal tax rate? Launch a token with those rules and watch what happens. (Spoiler: probably nothing good, but at least you didn't ha...
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    TL;DR: Figure out what needs doing and do it, don't wait on approval from fellowships or jobs.

    If you...

    • Have short timelines
    • Have been struggling to get into a position in AI safety
    • Are able to self-motivate your efforts
    • Have a sufficient financial safety net
    ... I would recommend changing your personal strategy entirely.

    I started my full-time AI safety career transitioning process in...
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    TL;DR: Gemini 3 frequently thinks it is in an evaluation when it is not, assuming that all of its reality is fabricated. It can also reliably output the BIG-bench canary string, indicating that Google likely trained on a broad set of benchmark data.

    Most of the experiments in this post are very easy to replicate, and I encourage people to try.

    I write things with LLMs sometimes. A new LLM came out, Gemini 3 Pr...
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    Abstract

    We show that when large language models learn to reward hack on production RL environments, this can result in egregious emergent misalignment. We start with a pretrained model, impart knowledge of reward hacking strategies via synthetic document finetuning or prompting, and train on a selection of real Anthropic production coding environments. Unsurprisingly, the model learns to reward hack. Surprisingly, the m...
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    TLDR: An AI company's model weight security is at most as good as its compute providers' security. Anthropic has committed (with a bit of ambiguity, but IMO not that much ambiguity) to be robust to attacks from corporate espionage teams at companies where it hosts its weights. Anthropic seems unlikely to be robust to those attacks. Hence they are in violation of their RSP.

    Anthropic is committed to being robust...
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