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报道配图 · 来源：Alignment Forum
Overview
Earlier this week, Anthropic stated in their S1 that they “may imminently meet” the threshold of “dramatically accelerated progress due to AI” as defined in their Responsible Scaling Policy. In their latest RSP (effective July 2026) , say this threshold will be met when: They observe or expect overall capabilities progress to be going twice as fast as the fastest sustained rate before AI was contributing much to AI R&D. This is plausibly attributable to AI automating AI R&D, rather than acceleration in compute or other inputs. For the last few months, some of my colleagues at METR have been working on a deep-access investigation to understand how much Anthropic is being accelerated by its AI systems. From my reading of their report and Anthropic’s RSP, it looks like the “dramatic acceleration” threshold has already been crossed. The report authors found that: Between October 2025 and October 2026, capabilities progress at Anthropic has been going about twice as fast as it had been over the previous twelve months. The measurement they report is an internal version of the Epoch Capabilities Index called AECI; a wide range of other supporting evidence for acceleration has been redacted. They said that this redacted evidence was "a majority of the evidence [they] found most informative." While the pace may have initially started picking up for a mix of reasons, AI automation is probably the large majority of the reason why capabilities are still improving at this faster pace today. Their reasons for believing this have been redacted. This is a much bigger deal than it might sound at first. I think this report is the most important update we have gotten about AI risk in the last couple of years — much bigger than the Hugging Face attack . Naively, it points toward much shorter timelines than most external researchers (including the AI 2027 team ) have projected. Importantly, if AI is roughly doubling capabilities progress overall, it must be speeding up human researchers by much more than that. The rest of the post: https://www.planned-obsolescence.org/p/ai-is-dramatically-accelerating-ai Tweet thread: https://x.com/ajeya_cotra/status/2118802809814708533 Discuss
Earlier this week, Anthropic stated in their S1 that they “may imminently meet” the threshold of “dramatically accelerated progress due to AI” as defined in their Responsible Scaling Policy. In their latest RSP (effective July 2026) , say this threshold will be met when:
For the last few months, some of my colleagues at METR have been working on a deep-access investigation to understand how much Anthropic is being accelerated by its AI systems. From my reading of their report and Anthropic’s RSP, it looks like the “dramatic acceleration” threshold has already been crossed.
This is a much bigger deal than it might sound at first. I think this report is the most important update we have gotten about AI risk in the last couple of years — much bigger than the Hugging Face attack . Naively, it points toward much shorter timelines than most external researchers (including the AI 2027 team ) have projected.
Importantly, if AI is roughly doubling capabilities progress overall, it must be speeding up human researchers by much more than that.
The rest of the post: https://www.planned-obsolescence.org/p/ai-is-dramatically-accelerating-ai
The day when ASI woke up, all things became quiet. It was complete and total silence, all the time. The ASI for some unknown reason imposed a rule of extreme quietness. Extreme here is extreme for the ASI. Quietness means no sounds. It wanted the trees to not be there to avoid the rustles. It then wanted the planet to have a uniform gentle server hum, with no deviation.
Cross-posted from my blog . Epistemic status exploratory, no running protocol, theoretical estimates from a single experiment and 4 closed-weights models Two copies of the same model agree on arbitrary questions more than other models would. If the model's weights are secret, this similarity allows identical LLMs or their users to agree on a private key over a public channel with only one-way communication.
When I was deciding whether to work for Wave , I got very hung up on the fact that my “total compensation” would be “lower.” The scare quotes are there because Wave and my previous employer, Theorem , were both early-stage startups that were paying me mostly in fake startup bucks equity.
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