Daniel R P de Melo

The EPPO in Madrid 🇪🇸 has opened a second investigation into possible fraud affecting EU funds allocated to the renovation of the Madrid – Seville high-speed railway line, on which the tragic accident occurred last week in the province of Toledo. More: eppo.europa.eu/media/news/sp…

SITUATION DETECTED: Delaware is drafting a proposal for a new form of corporate entity called an Artificial Intelligence Company (AIC). An AI managing an AIC would be able to provide services, sign contracts, hold property, and even file or defend lawsuits in the company’s name.

if you count pixels you can estimate the specific dates METR was given for "majority internal access" to a model. you can then use this to see what the gap is between internal and public deployment [charts at end of post] you can then use these gaps and the scores, multiplied together, to calculate a sort of "internal capabilities gap integral", eg how many "total AECI-days" Anthropic has had above the rest of the world due to this internal access, and chart how this changes over time. in some sense this is a measure of "how much cumulative advantage" Anthropic has, altho as measured vs the rest of the world rather than OpenAI. of course there are many issues with this. maybe you think what really matters are critical capability levels rather than any amount of time with lower capability models, or that AECI is fundamentally nonlinear so later points matter much more than earlier points. still, afaik it's the first time we've had this much information about internal release dates, and it seems like a "directionally reasonable" operationalization of a lot of things we care about wrt internal-external gaps. however: with the exception of Mythos 5.1, the numbers based on the chart show *incredibly short* gaps, on the order of a few days or sometimes up to two weeks. and frankly, i just don't believe these numbers. i don't have any actual information about the internal deployment and release process at labs, but it's pretty preposterous to think that most internal employees only had access to eg opus 4.5 for a few days before complete public release. it's nearly irresponsible wrt dogfooding and safety, and just obviously shooting yourself in the foot wrt overall "advantage" as a company. additionally there are widespread early access programs w a huge variety of companies / startups, and this would imply external partners are getting early access at basically the same time as the majority of employees! i don't think anthropic lied to METR. but i *do* think that what they're counting as "internal release date" is actually "internal release date of the exact final checkpoint that is released as that named model", despite widespread access to earlier checkpoints of very similar capability levels much earlier. there's just no shot ant employees first had access to something better than 4.5 at the end of january. sure maybe it wasn't literally 4.6. but the RL doesn't need three months to bake. what does this mean? well ... primarily i think it means all these graphs are misleading for understanding internal-external gaps. i don't know what the "real" numbers actually are, and actually it's probably basically true that there's no clear definition here and even anthropic would have some trouble figuring it out. but even a 7 day earlier access shift moves the total AECI-days up over 40%. also it could mean we should expect anthropic to *continue to under-report this*. eg maybe Model 4 was not even the most powerful internal model at the time of the report, but rather the highest capability model to complete some end to end potential release cycle, and employees already had access to something less baked but better. anyway!! here's some fun slop graphs:

METR's Ryan Greenblatt estimates AI is now speeding up AI research by ***4.5x*** This is 5 MONTHS EARLIER than AI 2027 predicted. On this trajectory, we may be just months from full-blown AI takeover. "I was seriously wrong about RSI speed up." "A 2x acceleration in overall AI progress from RSI corresponds to a much larger than 2x RSI speed up for AI software R&D (algorithms and data); I did an estimate using my public preexisting modeling of drivers of AI progress and the public report which yielded a very rough estimate of 4.5x for how much RSI is currently accelerating AI software progress (relative to no AI automation). In the AI 2027 scenario, this much acceleration happens around March 2027."

Our colleagues found that Anthropic’s capabilities progress has doubled, mainly due to AI. Ryan’s modeling from public info suggests the whole company’s R&D would be going 4-5x faster. Labor uplift would be higher still. This is a major update to very short timelines.

1. Benchmarks provide one piece of evidence for acceleration. Since Oct 2025, AECI scores for Anthropic’s models have grown at 1.9x [95%: 1.5–2.8] the earlier rate. Analysis choices affect this estimate, and it remains unclear how benchmark scores map to real-world capabilities.

Aldous Huxley His last novel, published the year before he died.

#BREAKING Bomb alerts reported on 12 European flights: officials, airlines

Assim sendo, só há uma forma de resolver o problema da habitação sem poluir (requalificar imóveis abandonados, incluindo os do Estado, também polui): é vivermos todos em tendas. Percebe-se assim que a acampada de Lisboa quer tudo menos resolver o problema da habitação.

Talarico is 37 Ossoff is 39 Kiros is 29 El Sayed is 42 Forstag is 32 Andrews is 46 Rutinel is 31 Sand is 44 This is a new generation of Democrats.

Terrenos que se encontram mesmo sobre a estação de metro de Salgueiros! 🚊 Tem sido um erro urbanístico enorme deixar estes terrenos assim durante 20 anos. Esperemos que se construa habitação pública acessível e com densidade de fogos.

Give Millennials the ball. We’re pushing 40 and still being told to wait our turn by people who need help opening a PDF. Move. We’ve got shit to fix.

Mamdani raises eyebrows with new look, ditching beard and sporting surprising 'stache trib.al/qmtVh20

Every tech bro rn