Expertium

• Expertium 22 Mar 2026 16:33 UTC

  1 point

  0

  in reply to: lilkim2025’s comment on: Ex­per­tium’s Shortform

  He thinks it’s a cool narrow tool, but not an indication that it’s possible to create one AI that surpasses all humans at everything, including asking questions that humans never asked before. I guess I misrepresented his opinion somewhat (I just edited my quick take). He thinks AI can help with some narrow tasks, but human touch will always be necessary for other things, especially for open-ended research. Btw, he’s not concerned about losing his job.

Ex­per­tium’s Shortform

• Expertium 22 Mar 2026 12:16 UTC

  17 points

  −6

  on: Ex­per­tium’s Shortform

  Do you know a person who believes that ASI will be created in <50 years who ISN’T in the LW/​rationalists circle?

  My parents don’t believe that a superintelligent AI will be created within this century, or ever for that matter, or that AI will ever take jobs. My relatives laugh at the idea of AI solving a high school math problem and think state-of-the-art AI is on the level of GPT-2 (I mean that the capabilities they have in mind are on the level of GPT-2, not that they know what GPT-2 is). My friend who is an organic chemist laughs at the idea of AI doing any R&D thinks that while AI can help with some narrow tasks, a truly general AI that can substitute all human researchers is sci-fi. I know 4 people who use Codex/​Claude Code; 2 of them call ASI sci-fi bullshit (btw, one of them said that the “Alignment faking in large language models” paper is nonsense after only reading the summary), 1 never said anything about ASI and 1 tentatively acknowledges that maybe ASI is possible to create in theory.
  
  I have never, in my whole life, met a real walking, talking, breathing human being who believes that ASI will be created within this century.

  EDIT: obviously there are people on the internet who believe that ASI will be created soon. My point wasn’t to deny their existence, just to share my experience that makes me think “Am I living in a AI-is-a-nothingburger bubble? Am I crazy or is everyone else (whom I personally know) around me crazy?”. I’m wondering if “Everyone I personally know thinks AI is a nothingburger and people who don’t are only found in very specific places on the Internet” is a common experience.

  EDIT 2: I asked my organic chemist friend to be more specific and he said that AI will be able to replace 80% of human researchers in 100 years. When asked “What about 100%?”, he said that that will never happen and at least some humans will always be necessary and that the 80% replacement figure will be due to AI automating routine tasks. Basically, when it comes to AI he’s envisioning something more like the Industrial Revolution rather than “humanity’s last invention”.

• Expertium 4 Mar 2026 14:43 UTC

  1 point

  0

  in reply to: williawa’s comment on: I’m con­fused by the change in the METR trend

  Then what would you recommend for determining whether linear or piecewise linear (only 2 segments btw) provides a better fit?

• Expertium 4 Mar 2026 5:52 UTC

  1 point

  0

  in reply to: YafahEdelman’s comment on: I’m con­fused by the change in the METR trend

  Thank you. I vaguely remember seeing a tweet about it, which is why I mentioned ECI.

• Expertium 3 Mar 2026 17:57 UTC

  2 points

  0

  in reply to: Carl Feynman’s comment on: I’m con­fused by the change in the METR trend

  5th percentile of breakpoints: 2023.00
  25th percentile of breakpoints: 2024.14
  50th percentile of breakpoints: 2024.31
  75th percentile of breakpoints: 2024.35
  95th percentile of breakpoints: 2024.36

  This is definitely not what I was expecting.

  

• Expertium 3 Mar 2026 16:58 UTC

  3 points

  0

  in reply to: philh’s comment on: I’m con­fused by the change in the METR trend

  Good idea! I edited the post.

  

• Expertium 3 Mar 2026 16:29 UTC

  2 points

  0

  in reply to: cosmobobak’s comment on: I’m con­fused by the change in the METR trend

  Do you have a good idea when RLVR became widely used? By “good” I mean “plus-minus a few months at worst, release date of one specific model at best”.

• Expertium 3 Mar 2026 16:21 UTC

  1 point

  0

  in reply to: williawa’s comment on: I’m con­fused by the change in the METR trend

  Isn’t this always the case? You can always do linear regression, then use your extra parameter to get zero loss on the last entry for example.

  This is why I used BIC: roughly speaking, if the increase in the parameter count is greater than the reduction of loss, BIC will increase. The more parameters (more precisely, degrees of freedom) the model has, the more BIC penalizes it.

  Regarding RLVR, I don’t know when exactly it became widely used. 2024 vs 2025 makes a big difference here.

I’m con­fused by the change in the METR trend

• Expertium 27 Feb 2026 22:40 UTC

  21 points

  12

  on: An­thropic and the DoW: An­thropic Responds

  https://​​x.com/​​SecWar/​​status/​​2027507717469049070

  Well, no more negotiations, it seems. Not the best path, not the second best, and doesn’t really sound like the third best either.

• Expertium 26 Feb 2026 15:15 UTC

  11 points

  11

  on: AI #157: Burn the Boats

  Claude Opus 4.6 had a time of 14.5 hours on the METR graph of capabilities, showing that things are escalating faster than we expected on that front as well.

  I think people are updating too much based on a measurement that even METR staff explicitly called noisy.

  

  EDIT: I noticed that later in the post you did mention that it’s noisy.

• Expertium 25 Feb 2026 23:43 UTC

  5 points

  0

  on: In-con­text learn­ing alone can in­duce weird generalisation

  This makes me wonder: would this effect be much weaker in embodied AI, since it would have a constant stream of video and audio that provides extremely strong evidence against the “I am Hitler” hypothesis?

• Expertium 25 Feb 2026 12:17 UTC

  9 points

  1

  on: Pro­saic Con­tinual Learning

  I think you will find the RLM paper interesting: https://​​arxiv.org/​​pdf/​​2512.24601

  TLDR: instead of the LLM processing the input directly, the LLM is given access to a Python environment and the input prompt is stored as a variable. Then the LLM can do any standard stuff like print(prompt[:100]) to read the beginning or use regex to search for relevant keywords. Additionally, the LLM can recursively call itself on chunks of the prompt, hence Recursive Language Models (RLMs). This is like having a pseudo-infinite context window + the ability to make the output arbitrarily long as well.

  The paper reports that even without specifically fine-tuning base LLMs to use this scaffold, the results on long context tasks show a big improvement with median costs being almost the same (though RLMs are significantly more expensive in a minority of cases). Fine-tuning improves the results further. Note that RLMs outperformed base LLMs even on tasks that fit into the context window of the base LLM, where theoretically chunking is not needed.

  EDIT: I forgot to mention that while for GPT-5 the median costs with and without this scaffold were similar, the runtime was always several times longer, so there is a downside. For Qwen3-Coder-480B both cost and runtime were higher, though the authors note that Qwen was pretty bad at using this scaffold.

• Expertium 4 Feb 2026 18:16 UTC

  1 point

  0

  in reply to: TsviBT’s comment on: Do con­fi­dent short timelines make sense?

  A bit of a necrocomment, but I’d like to know if LLMs solving unsolved math problems has changed your mind.

  Erdos problems 205 and 1051: AI contributions to Erdős problems · teorth/​erdosproblems Wiki. Note: I don’t know what LLM Aristotle is based on, but Aletheia is based on Gemini.

  Also this paper: [2512.14575] Extremal descendant integrals on moduli spaces of curves: An inequality discovered and proved in collaboration with AI

• Expertium 4 Feb 2026 13:12 UTC

  29 points

  11

  on: An­thropic’s “Hot Mess” pa­per over­states its case (and the blog post is worse)

  Usually when I read Anthropic’s blog posts, I feel like they want the takeaway to be something like “We came up with interesting methodology and got interesting results”.

  

  But this post reads differently. It’s like a really weird attempt to assuage people that AIs won’t try to take over the world and that it will be business as usual. Kinda reminds me of Altman’s “Gentle Singularity” a little, and that’s not a compliment. It’s like the takeaway is supposed to be “Don’t worry about the numbers and the methodology, that’s not important. What’s important is that nothing scary will happen, just business as usual”.

• Expertium 1 Feb 2026 13:01 UTC

  2 points

  0

  on: Some thoughts on what would make me en­dorse an AGI lab

  It would be interesting if you gave OpenAI, Google DeepMind, Anthropic, xAI and DeepSeek scores based on how well they fit your checklist.

• Expertium 22 Jan 2026 22:09 UTC

  1 point

  0

  on: AI #152: Brought To You By The Tor­ment Nexus

  and also LLMs seem to do well directly plugged into robots

  I’m not so sure about that: Butter-Bench: Evaluating LLM Controlled Robots for Practical Intelligence

  On a side note, I like how this excerpt below would be considered absurdist sci-fi 20 years ago, and now it’s real.

  

• Expertium 9 Jan 2026 16:28 UTC

  2 points

  0

  in reply to: npostavs’s comment on: What do peo­ple mean by “re­cur­sive self-im­prove­ment”?

  In hard RSI all memories and goals of the model remain unchanged (somehow) even though the architecture changes. In easy RSI model A trains model B from scratch.

  GPT-5 training GPT-6 would be easy RSI. GPT-5 turning itself into something else with zero loss of information stored in GPT-5′s weights would be hard RSI.

What do peo­ple mean by “re­cur­sive self-im­prove­ment”?