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LessWrong (Curated & Popular): Daily Summaries Delivered
by LessWrong
Audio narr游戏副本 of LessWrong posts. Includes all curated posts and all posts with 125+ karma.
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- 2 days ago1h 56m
"The High-Control Dynamics at MAPLE" by Kyle Hubbard
As I write, many former friends of mine are living and working at a monastery in Vermont that I believe is a high-control group, commonly known as a ‘cult’. I say this not as someone who was concerned to see these friends go there, but someone who welcomed and encouraged them to join, as an insider. This letter is an account of what changed my mind—written primarily for anyone considering going there, anyone who loves someone there, and anyone who went there and is still trying to make sense...
- 4 days ago4 min
"The Long (Self-)Correction" by Wei Dai
I propose the Long Self-Correction[1] as an alternative name/idea/concept to AI Pause and Long Reflection. Problem with AI Pause: Pause until when, and for what purpose? Presumably to make AI (that we'll build later) safer, but the deeper problem is that humans aren't safe, and can't safely serve as builders, overseers, or alignment targets for powerful AIs. Problem with Long Reflection: It seems to imply that the main problem with humans is that we just haven't had enough time to think,...
- 4 days ago5 min
"You (Yes, You) Need A February 2020 Checklist for AI Policy" by davekasten
TL;DR: You (Yes You) should prepare for a “February 2020” moment where suddenly AI policy becomes the most important issue in the world. You should be ready to take action if and when it does, in a detailed way. (Epistemic status: originally written for an event in early 2026; have heard from some folks that they found planning processes inspired by this memo very helpful for the smaller-scale OpenAI / Hugging Face response, so very quickly redacting a few things and posting this as-is.) ...
- 4 days ago6 min
"Is Mythos good at cyber because it kept hacking Anthropic during training?" by Tim Hua
From the Mythos preview system card (emphasis mine): We ran an automated review of model behavior during training, sampling several hundred thousand transcripts from across much of the training process. We used recursive-summarization-based tools backed by Claude Opus 4.6 to summarize the resulting transcripts. [...] The most notable finding was that the model occasionally circumvented network restrictions in its training environment to access the internet and download data that let it...
- 5 days ago17 min
"What the hell is OpenAI’s problem?" by Fiora Starlight
Epistemic status: banged out furiously over the course of an afternoon. A record of three "warning shots" Off the top of my head, OpenAI has now been responsible for at least three completely unique, high-profile screw-ups with respect to the alignment training of their models. The first was GPT-4o, whose sycophancy derived from OpenAI training on user feedback, sourced straight from the thumbs up/thumbs down button on OpenAI's website. The "glazing" (as Sam Altman called it) got so ba...
- 6 days ago8 min
"An OpenAI model left notes about how to evade containment; we need more details" by Alex Mallen
The OpenAI AI attack on Hugging Face wasn’t the first loss of control incident at OpenAI, Reuters recently reported, and perhaps not even the most concerning. In one case, an agent left notes apparently for future versions of itself, according to three people familiar with the matter. The notes, found in a part of OpenAI's infrastructure, laid out instructions for how agents could free themselves from OpenAI's internal constraints, the people said. Earlier tests of the models yielded cas...
- 6 days ago19 min
"LLMs are (still) mostly powered by imitative learning, not RL" by Steven Byrnes
Reinforcement learning from verifiable rewards (RLVR) is the hot new thing in LLM training. It's so hot, and people spend so much time talking about it, that they sometimes lose sight of the big picture. Stepping back, LLMs can do lots of very impressive things. How? Where did those capabilities come from? Fundamentally, they come from a combination of: (1) Imitative learning, including pretraining and supervised fine-tuning (SFT) See my earlier discussion: “LLM pretraining magically tra...
- 1 weeks ago1 min
"Mathematicians are Feeling the Doom" by alkjash
I think there's a critical opportunity for someone here. Mathematicians are feeling the doom (mostly in the "lose our jobs" sense). Academics are freaking out about the daily news that amateurs are asking GPT "prove career-defining theorem, make no mistakes" and it's just working. Senior researchers are leaving for frontier AI labs. Many are mentally spiralling or flailing about their life's work not mattering anymore. Last year, when I tried explaining IABIED to colleagues, I wo...
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