LessWrong (Curated & Popular)

Introduction

There are several diseases that are canonically recognized as ‘interesting’, even by laymen. Whether that is in their mechanism of action, their impact on the patient, or something else entirely. It's hard to tell exactly what makes a medical condition interesting, it's a you-know-it-when-you-see-it sort of thing.

One such example is measles. Measles is an unremarkable disease based solely on its clinical progression: fever, malaise, coughing, and a relatively low death rate of 0.2%~. What is astonishing about the disease is its capacity to infect cells of the adaptive immune system (memory B‑ and T-cells). This means that if you do end up surviving measles, you are left with an immune system not dissimilar to one of a just-born infant, entirely naive to polio, diphtheria, pertussis, and every single other infection you received protection against either via vaccines or natural infection. It can take up to 3 [...]

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Outline:

(00:21) Introduction

(02:48) Why is endometriosis interesting?

(04:09) The primary hypothesis of why it exists is not complete

(13:20) It is nearly equivalent to cancer

(20:08) There is no (real) cure

(25:39) There are few diseases on Earth as widespread and underfunded as it is

(32:04) Conclusion

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First published:
June 14th, 2025

Source:
https://www.lesswrong.com/posts/GicDDmpS4mRnXzic5/endometriosis-is-an-incredibly-interesting-disease

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I'd like to say thanks to Anna Magpie – who offers literature review as a service – for her help reviewing the section on neuroendocrinology.

The following post discusses my personal experience of the phenomenology of feminising hormone therapy. It will also touch upon my own experience of gender dysphoria.

I wish to be clear that I do not believe that someone should have to demonstrate that they experience gender dysphoria – however one might even define that – as a prerequisite for taking hormones. At smoothbrains.net, we hold as self-evident the right to put whatever one likes inside one's body; and this of course includes hormones, be they androgens, estrogens, or exotic xenohormones as yet uninvented.

I have gender dysphoria. I find labels overly reifying; I feel reluctant to call myself transgender, per se: when prompted to state my gender identity or preferred pronouns, I fold my hands [...]

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Outline:

(03:56) What does estrogen do?

(12:34) What does estrogen feel like?

(13:38) Gustatory perception

(14:41) Olfactory perception

(15:24) Somatic perception

(16:41) Visual perception

(18:13) Motor output

(19:48) Emotional modulation

(21:24) Attentional modulation

(23:30) How does estrogen work?

(24:27) Estrogen is like the opposite of ketamine

(29:33) Estrogen is like being on a mild dose of psychedelics all the time

(32:10) Estrogen loosens the bodymind

(33:40) Estrogen downregulates autistic sensory sensitivity issues

(37:32) Estrogen can produce a psychological shift from autistic to schizotypal

(45:02) Commentary

(47:57) Phenomenology of gender dysphoria

(50:23) References

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First published:
June 15th, 2025

Source:
https://www.lesswrong.com/posts/mDMnyqt52CrFskXLc/estrogen-a-trip-report

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Nate and Eliezer's forthcoming book has been getting a remarkably strong reception.

I was under the impression that there are many people who find the extinction threat from AI credible, but that far fewer of them would be willing to say so publicly, especially by endorsing a book with an unapologetically blunt title like If Anyone Builds It, Everyone Dies.

That's certainly true, but I think it might be much less true than I had originally thought.

Here are some endorsements the book has received from scientists and academics over the past few weeks:

This book offers brilliant insights into the greatest and fastest standoff between technological utopia and dystopia and how we can and should prevent superhuman AI from killing us all. Memorable storytelling about past disaster precedents (e.g. the inventor of two environmental nightmares: tetra-ethyl-lead gasoline and Freon) highlights why top thinkers so often don’t see the [...]

The original text contained 3 footnotes which were omitted from this narration.

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First published:
June 18th, 2025

Source:
https://www.lesswrong.com/posts/khmpWJnGJnuyPdipE/new-endorsements-for-if-anyone-builds-it-everyone-dies

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This is a link post. A very long essay about LLMs, the nature and history of the the HHH assistant persona, and the implications for alignment.

Multiple people have asked me whether I could post this LW in some form, hence this linkpost.

(Note: although I expect this post will be interesting to people on LW, keep in mind that it was written with a broader audience in mind than my posts and comments here. This had various implications about my choices of presentation and tone, about which things I explained from scratch rather than assuming as background, my level of of comfort casually reciting factual details from memory rather than explicitly checking them against the original source, etc.

Although, come of think of it, this was also true of most of my early posts on LW [which were crossposts from my blog], so maybe it's not a [...]

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First published:
June 11th, 2025

Source:
https://www.lesswrong.com/posts/3EzbtNLdcnZe8og8b/the-void-1

Linkpost URL:
https://nostalgebraist.tumblr.com/post/785766737747574784/the-void

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This is a blogpost version of a talk I gave earlier this year at GDM.

Epistemic status: Vague and handwavy. Nuance is often missing. Some of the claims depend on implicit definitions that may be reasonable to disagree with. But overall I think it's directionally true.



It's often said that mech interp is pre-paradigmatic.

I think it's worth being skeptical of this claim.

In this post I argue that:

• Mech interp is not pre-paradigmatic.
• Within that paradigm, there have been "waves" (mini paradigms). Two waves so far.
• Second-Wave Mech Interp has recently entered a 'crisis' phase.
• We may be on the edge of a third wave.

Preamble: Kuhn, paradigms, and paradigm shifts

First, we need to be familiar with the basic definition of a paradigm:

A paradigm is a distinct set of concepts or thought patterns, including theories, research [...]



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Outline:

(00:58) Preamble: Kuhn, paradigms, and paradigm shifts

(03:56) Claim: Mech Interp is Not Pre-paradigmatic

(07:56) First-Wave Mech Interp (ca. 2012 - 2021)

(10:21) The Crisis in First-Wave Mech Interp

(11:21) Second-Wave Mech Interp (ca. 2022 - ??)

(14:23) Anomalies in Second-Wave Mech Interp

(17:10) The Crisis of Second-Wave Mech Interp (ca. 2025 - ??)

(18:25) Toward Third-Wave Mechanistic Interpretability

(20:28) The Basics of Parameter Decomposition

(22:40) Parameter Decomposition Questions Foundational Assumptions of Second-Wave Mech Interp

(24:13) Parameter Decomposition In Theory Resolves Anomalies of Second-Wave Mech Interp

(27:27) Conclusion

The original text contained 6 footnotes which were omitted from this narration.

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First published:
June 10th, 2025

Source:
https://www.lesswrong.com/posts/beREnXhBnzxbJtr8k/mech-interp-is-not-pre-paradigmatic

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Current “unlearning” methods only suppress capabilities instead of truly unlearning the capabilities. But if you distill an unlearned model into a randomly initialized model, the resulting network is actually robust to relearning. We show why this works, how well it works, and how to trade off compute for robustness.

Unlearn-and-Distill applies unlearning to a bad behavior and then distills the unlearned model into a new model. Distillation makes it way harder to retrain the new model to do the bad thing. Produced as part of the ML Alignment & Theory Scholars Program in the winter 2024–25 cohort of the shard theory stream.

Read our paper on ArXiv and enjoy an interactive demo.

Robust unlearning probably reduces AI risk

Maybe some future AI has long-term goals and humanity is in its way. Maybe future open-weight AIs have tons of bioterror expertise. If a system has dangerous knowledge, that system becomes [...]

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Outline:

(01:01) Robust unlearning probably reduces AI risk

(02:42) Perfect data filtering is the current unlearning gold standard

(03:24) Oracle matching does not guarantee robust unlearning

(05:05) Distillation robustifies unlearning

(07:46) Trading unlearning robustness for compute

(09:49) UNDO is better than other unlearning methods

(11:19) Where this leaves us

(11:22) Limitations

(12:12) Insights and speculation

(15:00) Future directions

(15:35) Conclusion

(16:07) Acknowledgments

(16:50) Citation

The original text contained 2 footnotes which were omitted from this narration.

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First published:
June 13th, 2025

Source:
https://www.lesswrong.com/posts/anX4QrNjhJqGFvrBr/distillation-robustifies-unlearning

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A while ago I saw a person in the comments on comments to Scott Alexander's blog arguing that a superintelligent AI would not be able to do anything too weird and that "intelligence is not magic", hence it's Business As Usual.

Of course, in a purely technical sense, he's right. No matter how intelligent you are, you cannot override fundamental laws of physics. But people (myself included) have a fairly low threshold for what counts as "magic," to the point where other humans can surpass that threshold.

Example 1: Trevor Rainbolt. There is an 8-minute-long video where he does seemingly impossible things, such as correctly guessing that a photo of nothing but literal blue sky was taken in Indonesia or guessing Jordan based only on pavement. He can also correctly identify the country after looking at a photo for 0.1 seconds.

Example 2: Joaquín "El Chapo" Guzmán. He ran [...]

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First published:
June 15th, 2025

Source:
https://www.lesswrong.com/posts/FBvWM5HgSWwJa5xHc/intelligence-is-not-magic-but-your-threshold-for-magic-is

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Audio note: this article contains 329 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description.

This post was written during the agent foundations fellowship with Alex Altair funded by the LTFF. Thanks to Alex, Jose, Daniel and Einar for reading and commenting on a draft.

The Good Regulator Theorem, as published by Conant and Ashby in their 1970 paper (cited over 1700 times!) claims to show that 'every good regulator of a system must be a model of that system', though it is a subject of debate as to whether this is actually what the paper shows. It is a fairly simple mathematical result which is worth knowing about for people who care about agent foundations and selection theorems. You might have heard about the Good Regulator Theorem in the context of John [...]

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Outline:

(03:03) The Setup

(07:30) What makes a regulator good?

(10:36) The Theorem Statement

(11:24) Concavity of Entropy

(15:42) The Main Lemma

(19:54) The Theorem

(22:38) Example

(26:59) Conclusion

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First published:
November 18th, 2024

Source:
https://www.lesswrong.com/posts/JQefBJDHG6Wgffw6T/a-straightforward-explanation-of-the-good-regulator-theorem

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1. Late last week, researchers at Apple released a paper provocatively titled “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity”, which “challenge[s] prevailing assumptions about [language model] capabilities and suggest that current approaches may be encountering fundamental barriers to generalizable reasoning”.

Normally I refrain from publicly commenting on newly released papers. But then I saw the following tweet from Gary Marcus:

I have always wanted to engage thoughtfully with Gary Marcus. In a past life (as a psychology undergrad), I read both his work on infant language acquisition and his 2001 book The Algebraic Mind; I found both insightful and interesting. From reading his Twitter, Gary Marcus is thoughtful and willing to call it like he sees it. If he's right about language models hitting fundamental barriers, it's worth understanding why; if not, it's worth explaining where his analysis [...]

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Outline:

(00:13) 1.

(02:13) 2.

(03:12) 3.

(08:42) 4.

(11:53) 5.

(15:15) 6.

(18:50) 7.

(20:33) 8.

(23:14) 9.

(28:15) 10.

(33:40) Acknowledgements

The original text contained 7 footnotes which were omitted from this narration.

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First published:
June 11th, 2025

Source:
https://www.lesswrong.com/posts/5uw26uDdFbFQgKzih/beware-general-claims-about-generalizable-reasoning

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Are we doing this again? It looks like we are doing this again.This time it involves giving LLMs several ‘new’ tasks including effectively a Tower of Hanoi problem, asking them to specify the answer via individual steps rather than an algorithm then calling a failure to properly execute all the steps this way (whether or not they even had enough tokens to do it!) an inability to reason.The actual work in the paper seems by all accounts to be fine as far as it goes if presented accurately, but the way it is being presented and discussed is not fine. Not Thinking Clearly

Ruben Hassid (12 million views, not how any of this works): BREAKING: Apple just proved AI “reasoning” models like Claude, DeepSeek-R1, and o3-mini don’t actually reason at all.They just memorize patterns really well.Here's what Apple discovered:(hint: we’re not as close to [...] ---

Outline:

(00:53) Not Thinking Clearly

(01:59) Thinking Again

(07:24) Inability to Think

(08:56) In Brief

(10:01) What's In a Name

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First published:
June 10th, 2025

Source:
https://www.lesswrong.com/posts/tnc7YZdfGXbhoxkwj/give-me-a-reason-ing-model

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