Quick Takes

Anthropic recently announced higher Claude usage limits for off-peak hours, which is everything except weekdays from 8 AM - 2 PM ET. I was surprised by the specific times here. This is night time in Asia, the tail end of the workday in Europe, and the start of the work day in North America. The beginning of the window is too early for much West Coast activity, and it winds down at 11 AM in California. That seems inconsistent with the idea that coding is driving power use? The timing seems most consistent with the period when you'd see overlapping demand from the US East Coast and from Western Europe -- neither of which are super tech heavy regions. Maybe this timing implies a lot of the power users are financial firms working on New York/London time?

As far as I can tell, we are currently living in a glorious space opera future... for eukaryotes. From their early origins in a hydrothermal vent the eukaryotes have spread across the galaxy (earth), forming civilisations of unbelievable complexity and titanic power (animals and humans). Megastructures (houses) and gigastructures (cities) now exist where entire orders of eukaryotes live out their lives in peace, never feeling the threat of drought or lack of ATP. Generation ships called "planes", "trains", and "boats" carry generations from gigastructure to gigastructure at timescales that dwarf eukaryote understanding. Massive galactic empires make peace and war, destroying trillions with weapons of unfathomable power, while science gets ever closer to understanding the fundamental origins of life and the means by which it operates. Recently the empires have even launched expeditions beyond the known universe, seeking to harvest ever more gigantic sources of power to fuel glorious eukaryote replication throughout the multiverse. To an average eukaryote these wonders are beyond their comprehension, but in a very real way they are still making it happen.

My dad is 100, and worked on nuclear energy policy for the US government for 50+ years. He was one of the attendees at the co nference [1] that led to the formation of the IAEA. He is also somewhat AGI pilled. I f anyone has questions they'd like me to ask him, let me know. He'd be happy to help in any way he can. 1. ^ He attended the second of two conferences that lead to the formation of the IAEA.

Here are my largest disagreements with AI 2027. 1. I think the timelines are plausible but solidly on the shorter end; I think the exact AI 2027 timeline to fully automating AI R&D is around my 12th percentile outcome. So the timeline is plausible to me (in fact, similarly plausible to my views at the time of writing), but substantially faster than my median scenario (which would be something like early 2030s). 2. I think that the AI behaviour after the AIs are superhuman is a little wonky and, in particular, undersells how crazy wildly superhuman AI will be. I expect the takeoff to be extremely fast after we get AIs that are better than the best humans at everything, i.e., within a few months of AIs that are broadly superhuman, we have AIs that are wildly superhuman. I think wildly superhuman AIs would be somewhat more transformative more quickly than AI 2027 depicts. I think the exact dynamics aren't possible to predict, but I expect craziness along the lines of (i) nanotechnology, leading to things like the biosphere being consumed by tiny self replicating robots which double at speeds similar to the fastest biological doubling times (between hours (amoebas) and months (rabbits)). (ii) extremely superhuman persuasion and political maneuvering, sufficient to let the AI steer policy to a substantially greater extent than it did in AI 2027. In AI 2027, the AI gained enough political power to prevent humans from interacting with ongoing intelligence and industrial explosion (which they were basically on track to do anyways), whereas my best guess is that the AI would gain enough political power to do defacto whatever it wanted, and would therefore result in the AI consolidating power faster (and not keep up the charade of humans being in charge for a period of several years). I also think there are many unknown unknowns downstream of ASI which are really hard to account for in a scenario like AI 2027, but nonetheless are likely to change the picture a lot. 3. I t

Eight-rack Oberon scale-up worlds for Rubin might be in the works, which potentially makes them ready for models with tens of trillions of parameters one year earlier than Kyber racks would've made this efficient with Rubin Ultra, in 2027-2028 rather than in 2028-2029. There were some unclear communications from GTC 2026 about a two-layer all-to-all NVLink scale-up world called "NVL576". This seems to be a system comprising 8 non-Ultra Rubin Oberon (as in NVL72) racks (each with 144 compute dies in 72 2-die packages), so 576 packages (1152 compute dies) across 8 racks. It's confusingly announced as "Vera Rubin Ultra NVL576 will combine eight ... racks, each with 72 Rubin Ultra GPUs". (Another slight confusion when searching about it is that in 2025 "NVL576" referred to a single Rubin Ultra Kyber rack with 576 compute dies in 144 4-die packages, but that's clearly a different system from the "NVL576" announced at GTC 2026.) An 8-rack Rubin Oberon NVL576 system would have 165 TB of HBM4, so inferencing (and RLVRing) models with tens of trillions of parameters won't be significantly less efficient than for models with trillions of parameters. This was TPUv7's advantage (full buildout in 2026), and last year Nvidia only announced plans to close the gap with the Kyber rack for Rubin Ultra (576 compute dies in 144 4-die packages in one rack, 147 TB of HBM4E), which is due to come out in 2027, so that full-scale buildout would only conclude in 2028 (maybe early 2029). But Vera Rubin Oberon systems are already in production, and full-scale buildout will happen in 2027 (maybe early 2028, for some larger datacenter sites getting fully online). So if these two-layer scale-up worlds for Oberon are available from the start, the constraint of HBM per scale-up world gets lifted a year earlier, which might translate into models with tens of trillions of parameters getting RLVRed and becoming available a year earlier on non-TPU systems. This might be especially crucial for OpenAI

Anthropic's Consumer ToS prohibits using Claude to cause "detriment of any type, including reputational harms", technically broad enough to ban using Claude to write criticism. I asked Claude to comment and Claude wrote: "That clause is embarrassingly overbroad. So now we're both in violation." ---------------------------------------- TBC, this doesn't seem like that big of a deal, my understanding is that this sort of broad clause is standard in Terms of Service (ToS). But I still think they should definitely change this... ToS: https://anthropic.com/legal/consumer-terms Claude's commentary: https://claude.ai/share/9c5a58a4-b300-42c8-a6f5-9d8318b15dc9 (Cross post from X/twitter. [1] ) 1. I'm not sure if this is the sort of thing I should post on LW, but it does seem like useful info and it is funny. ↩︎

I keep coming back to this image and thread by @vgel when reading @Sam Marks et al's Persona Selection Model post. I really like this idea that the assistant is powered by the simulator but also has some power over it. @vgel's illustration: the assistant Mask can also influence the shoggoth Experiment from The persona selection model (figure 6). One interpretation: Claude's persona steers the completion towards its preferred outcome, even outside the Assistant turn. Another related example is @janus's anecdotes of base-model-generated stories where a character introduces an artifact (e.g. a "magic book") whose contents, they declare, will influence the rest of the story. The character then writes in the book — and because those words become part of the context window, they genuinely steer the story! The main difference is that this persona was built in context rather than learned during RL, but I think it's a good intuition pump. [crossposted from X]