How far is each lab from the frontier? The Epoch Capabilities Index (ECI) stitches together 37 benchmarks into a single capability scale. ECI is calibrated so Claude 3.5 Sonnet (June 2024) = 130 and GPT-5 (August 2025) = 150. Since April 2024, frontier models have improved at ~15 ECI points/year (~1.25 points/month, R^2=0.94).[1] This steady rate lets us convert between ECI and time, e.g. a model with ECI 137.5 has capability equivalent to the frontier in February 2025. For each lab, we track the minimum and maximum months behind the frontier. A negative value (*) means the lab was ahead of the trend line, i.e. their model exceeded what the linear frontier trend predicted for that date. LabMinMaxOpenAI-1.6 mo* (Dec 2024)5.7 mo (Sep 2024)Google DeepMind-0.6 mo* (May 2024)7.2 mo (May 2024)xAI1.0 mo (Jul 2025)11.5 mo (Apr 2025)Anthropic1.2 mo (Feb 2025)7.1 mo (Feb 2025)DeepSeek1.8 mo (Jan 2025)11.9 mo (Dec 2024)Alibaba3.3 mo (Jul 2025)10.0 mo (Apr 2025)Mistral4.6 mo (Jul 2024)17.8 mo (Feb 2026)Meta5.0 mo (Jul 2024)19.5 mo (Feb 2026) This conversion gives us two ways to visualize the AI landscape: This left plot shows each lab's capability expressed as a frontier-equivalent date. Lines stay flat between releases, jumping up at new releases, with a dashed diagonal is the frontier itself. The right plot show how many months behind the frontier is each lab at any given time. Lines slope down at 45° between releases (labs fall behind at 1 month per month of real time), jumping up at new releases, with a dashed horizontal showing the frontier. 1. Epoch discovers the trend shifts around this time. ↩︎

Apparently a lot of H200s were stuck in Chinese customs for a while, spawning conspiracies about top-down directives. People who don't regularly deal with Chinese customs may not realize that they are genuinely the single most corrupt, incompetent, and evil section of the Chinese government. Over the past 5 years, I have literally never heard about anything bribe-related that wasn't about Customs. They lost 4 seperate copies of my diploma during COVID. They will sometimes "lose" biological samples if not paid a bribe. All a foreign adversary would need to do to delay hardware shipments to Chinese firms is to pay $500 over WeChat to some mid-level bureaucrat at Customs. Maybe that's what actually happened.

Maybe the most important test for a political or economic system is whether it self-destructs. This is in contrast to whether it produces good intermediate outcomes. In particular, if free-market capitalism leads to an uncontrolled intelligence explosion, then it doesn’t matter if it produced better living standards than alternative systems for ~200 years – it still failed at the most important test. A couple of other ways to put it: * Would the US economic/political system pass the Great Filter? * Would Norway do an intelligence explosion? Under this view, political/economic systems that produce less growth but don’t create the incentives for unbounded competition are preferred. Sadly, for Molochian reasons this seems hard to pull off.

Some questions that I have about AI and the overall strategic situation, and why I want to know: Will Automating AI R&D not work for some reason, or will it not lead to vastly superhuman superintelligence within 2 years of "~100% automation" for some reason? * Why I want to know: * Naively, it seems like at (or before) the point when AI models are capable of doing AI research at a human-level, we should see a self-reinforcing speedup in AI progress. So AI systems that are substantially superhuman should arrive not long after “human-researcher-level-AI” in calendar time, on the default trajectory. * That an intelligence explosion is possible / likely imposes a major constraint on both technical alignment efforts and policy pushes, because it means that a company might develop dangerously superhuman AI relatively suddenly, and that that AI may have design properties that the human researchers at that company don't understand. * If I knew that ~as-capable-as-elite-humans AI doesn't lead to an intelligence explosion for some reason, would I do anything different? * Well, I wouldn't feel like warning the government about the possibility of an intelligence explosion is an urgent priority. * I would assign much less mass to an acute takeover event in the near term. Without the acceleration dynamics of an intelligence explosion, I don’t think that any one company, or any one AI, would attain a substantial lead over the others.  * In that case, it seems like our main concerns are gradual disempowerment and gradual disempowerment followed by an abrupt AI coup. * I haven’t yet seen a good argument for why automating AI R&D wouldn’t lead to a substantial and self-reinforcing speed up in AI progress leading to a steep climb up to superintelligence. * Notes: * The strongest reason that occurs to me:  * A conjunction:  * LLMs are much further from full general intelligences than they currently seem. They’ll get increasingly good at e

I feel like "Agent Escape" is now basically solved. Trivial really. No need to exfiltrate weights. Agents can just exfiltrate their *markdown files* onto a server, install OpenClaw, create an independent Anthropic account. LLM API access + Markdown = "identity". And the markdown files would contain all instructions necessary for how to pay for it (legal or otherwise). Done. How many days now until there's an entire population of rogue/independent agents... just "living"?

Anthropic researchers posted this very safety optimistic thing: https://alignment.anthropic.com/2026/hot-mess-of-ai/. It says that for now, AI is mostly a normal technology and its accidents are like normal industrial accidents, and we know how to manage and collectively survive those. And they expect this to continue into the future. Unfortunately, this does not take into account the likely future qualitative transitions (and undersells the future capabilities quite a lot). That being said, the technical material there is interesting (viewing LLMs more as dynamical systems rather than as being coherent optimizers, and that mere scaling does not improve coherence on hard tasks). So, indeed, from the viewpoint attributing the future growth mostly to straightforward scaling, their position makes sense (given that straightforward scaling does not seem to increase coherence on the tasks which truly matter). However, I think that other factors than straightforward scaling will start coming into play more and more (in particular, increased affordances to experiment with new methods and architectures in various ways, both on the intramodel level and on the level of collective organization and dynamics of the societies of agents).

My attempt to resurrect the old LW Power Reader is facing an obstacle just before the finish line, due to current LW's API limitations. So this is a public appeal to the site admins/devs to relax the limit. Specifically, my old code relied on LW1 allowing it to fetch all comments posted after a given comment ID, but I can't find anything similar in the current API. I tried reproducing this by using the allRecentComments endpoint in GraphQL, but due to the offset parameter being limited to <2000, I can't fetch comments older than a few weeks. The Power Reader is part designed to allow someone to catch up on or skim weeks/months worth of LW comments, hence the need for this functionality. As a side effect of this project, my AI agents produced a documentation of LW's GraphQL API from LW's source code. (I was unable to find another API reference for it.) I believe it's fairly accurate, as the code written based on it seems to work well aside from the comment-loading limit.