Non-US models are not banned in the US: they are used daily in every state of the US. Some misguided state governments temporarily banned employees from downloading the R1 models and variants released 16 months ago on state government computers. The article and your comment are misleading :-)
Assuming this is so, and continues to be the case: is this really still a basis for a 90 day period in releasing new models being somehow insane/catastrophic?
The GP did not try to time the market. He suggested a sensible strategy to exclude a tiny subset from an index (less expensive than maintaing the alternative index yourself).
Frankly, everyone in the industry knows. When people make these statements without additional clarity they always talk about API prices. You can look at the NVL72 specs and make estimates for electricity and ownership costs rather easily. Inference at data-center scale is dirt cheap, even with public codes using dynamo and sglang. The mystery is why the early misconceptions about inefficient inference persisted even after NVIDIA was very open about everything they did to help reduce costs dramatically in the last two years.
I imagine it's the lack of transparency. The costs are obviously coming down as people figure out how to tune both hardware and software. But there are costs other than just electricity as well. For example, chips do burn out, I recall reading that 2 to 3 years is roughly what you can expect under inference loads, so replacing chips is a non trivial operational cost.
Also, as the costs of running this stuff come down, the incentive to rent models goes down with them. Running local models has the benefit that you get to keep your data local, you can tune them to do what you like, and you're not subject to model or price changes down the road. This makes self hosting appealing both to individuals and companies. Currently, the barrier is in needing significant resources to run the models, but companies are already increasingly doing that with open models. And local inference that regular people can run is becoming a possibility as well.
While I'm sure there's always going to be a market for renting out models as a service, it may shrink significantly as the costs continue to come down.
Nasdaq is about 8x higher now than then, so 4x higher M2 is tight. Ofc there is always a chance that this time is different and that the markets are genuinely much more efficient :-)
Congrats on the launch. If emacs was unavailable and I needed tmux, I would try it. I am old school, and use emacs daemons for all shell multiplexing. The agents dont need explanations and know how to use emacsclient to create, read, or send inputs to named buffers that run the shells. Elisp is powerful, so manipulating windows is a breeze. Lots of people on tmux would benefit from this design though.
Funny, I started vibing this (https://github.com/deangiberson/emacs-mux) yesterday on the train after playing with cmux for the day and thinking to myself there was nothing that emacs couldn't accomplish.
The repo doesn't quite work yet. Many sharp corners. But the basic idea is there.
pama, I'd be interested in hearing more about how you are using emacs for multiplexing. I'm trying to build up tooling for myself based around file and input workflows and I /really/ don't want to write a text editor and would prefer to stick with emacs.
The key idea is to have many differently named shells. Typically, I group them by project (common prefix name), and the projects live in directories. I have some hacks to organize ibuffer, to split frames, to reflow buffers in the existing windows (eg to organize related project buffers (shells, magit, dired), or to show shells from multiple projects, or selected buffers, and so on). Emacs’ natural frame splitting and buffer selecting/switching commands are good enough if you dont display more than four buffers at a time, but soon you may need to show 5, 6, 8, 9, 10, 12, 15, 16, 18, 20, 24 or have funky arrangements, so you may collect functions to help along splitting n*m grids or keeping useful splits. The shells work very organically inside Emacs and you can still use it as a text editor. The so-called “dumb terminal” in M-x shell is a thing of beauty as it really is just a text buffer like any other; I think of it as a bash repl. If you are used to curses TUI commands it may not work, so for these rare occasions I also use eat (but tend to avoid). See also answer to a sibling comment.
Not sure, tbh. I use emacs -daemon to start a server; emacsclient -nw to connect. I use ssh and start a server on the remote. I spawn multiple shells with infinte buffer size and dumb terminals (M-x shell) so I can seamlessly edit. (These are based on comint, a neat command interpreter.) I use my own hacks for named shells (https://github.com/pjj/Emacs-nsh) and for rearranging/splitting windows, but any of the latest powerful LLMs can help with ergonomic modifications to M-x shell or the various improved terminal emulators (vterm, eat, ansi-term) or with renaming and moving/splitting windows. The Emacs manual is excellent but long; worth it IMHO, but focus on things you use. The tutorial is quick; worth it. I avoid curses programs (fancy TUI) or write wrappers around some of them. I love the -p option in codex/claude/copilot.
Peter shows the near-term future. Raw API consumer price cost is arbitrary. (The frontier labs can put a 100x markup to cover other operational expenses.) The true cost of inference with same-capability models keeps dropping at dizzying rates, especially at the data-center batch size. (Due to both NVidia hardware and algorithmic changes.) So the developments that Peter can achieve today with internal support from OpenAI will be doable by anyone in a few years without breaking the bank.
But.... why? Like I read his thing on how he spends the tokens [0] and it sounds like satire.
He has agents write shitty code for features other agents think other people want, then has it reviewed by other agents in hopes of catching bugs that the first agent put there, then has some more agents try to find security bugs in the now double-agented code to make it triple-agented and at the end of the day, he spent a shitton of tokens, probably emitted enough carbon to heat our planet by another degree, and has a feature nobody really asked for that might or might not work.
He then has the sense of humor to call this grotesque process "incredibly lean".
What's the point in all of this? What problems is this solving? Who's benefiting?
I don’t use openclaw myself anymore, but this agonizing is thin and unbearable. He did a thing. People use the thing. He got paid for the thing. He iterates the thing. What’s hard to understand about this?
The morality issues about consumption climate impacts are not his alone, and are not unique by itself to his endeavor. Every company with an enterprise LLM agreement has a share, for instance.
Firstly, who TF would use that crap in the first place at all?
Yeah, he did some crap he got paid for. So did the people who created the addictive algorithms for social and media or creators of the brainrot videos that infest kids' minds. Should we applaud them too?
You can hate it, but pretending it has no value isn’t a meaningful counter, esp given its user base. Gary Tan built GBrain on it. Poor logical fallacy-ing on your part.
It's a very simple question, the subthread you created based on reducing everything to "he did a thing" and calling the comment you didn't interact with at all "agonizing".
Why not rather leave it at "they wrote a comment"? What is so hard to understand about that, to use your words?
>He then has the sense of humor to call this grotesque process "incredibly lean".
> What's the point in all of this? What problems is this solving? Who's benefiting?
The economy doesn't work like how you think it does. Its not central planning. All the usages aren't detailed in a specification, submitted for approval to 100 agencies and then allowed to be used.
It shows lack of intellectual curiosity to not engage deeply with obviously profound technology and what the implications are. I find this exercise helpful.
Peter is predicting how LLMs will be used in the future when the prices go down. And they will definitely go down. I think his predictions are correct and we will definitely have something similar to OpenClaw.
> The economy doesn't work like how you think it does. Its not central planning.
I'm aware. That is in fact my central critique. The way it works is incredibly wasteful of our limited resources, as illustrated by this guy burning through fuel during a time of crisis for no perceptible gain.
> It shows lack of intellectual curiosity to not engage deeply with obviously profound technology and what the implications are.
The "obviously profound" is an assertion without proof.
The rest I agree with, we should engage with the implications of burning through energy to build features that bots think humans want, but nobody actually asked for, all while climate scientists are telling us we're heading for the apocalypse. It is intellectually incurious to just ignore the questions of why and at what cost, maybe even dangerously so.
> The way it works is incredibly wasteful of our limited resources
You should try playing the game “workers and resources”; it’s a simcity like game, but based in the Soviet system of central planning, not capitalism. It will make you loathe the inefficiencies in central planning.
The appropriate comparison is command vs market. Capitalism is efficient in utilising the characteristics of humans to bring about expansion of markets.
like one bot finding similar issues and PRs, the another bot closing issues for "lack of activity", meanwhile people are reacting and pleading to speak to a real human?
Congrats builders of the future, you've turned software development into automated voice systems.
Mario Zechner wrote the main part of this IP laundering application.
I didn't know that studying photocopiers is suddenly linked to "intellectual curiosity". Being a photocopier maintenance guy was always considered boring.
What you put on top of the machine was intellectually interesting.
I don't understand how he is a scam artist. Lots of people are using the things he built. TBH this kind of rhetoric is a bit degrading experience on this website
“He has /people/ write shitty code for features other /people/ think other people want, then has it reviewed by other /people/ in hopes of catching bugs that the first /people/ put there, then has some more /people/ try to find security bugs in the now /double-peopled/ code to make it /triple-peopled/ and at the end of the day, he spent a shitton of /money, the people/ probably emitted enough carbon to heat our planet by another degree, and has a feature nobody really asked for that might or might not work.”
Honestly sounds like a normal tech company to me. Just with much dumber “people” who are getting exponentially smarter, eventually never die, eventually never forget.
You have to skate to where the puck is going, not where it is.
Peter shows shit. What did Peter meaningfully achieve? What additional revenue is he creating? ah yes - shit and more shit on all accounts as it seems.
>OpenClaw hit 346K GitHub stars in under five months. 38 million monthly visitors, 3.2 million active users, 44,000+ ClawHub skills, 500K+ running instances, and 180 startups generating $320K+/month. OpenAI acquired the project in February. (https://openclawvps.io/blog/openclaw-statistics)
Let me state it again in plain language: How much revenue did the project create and what economic or societal value in general does it create? Gamification bullshit "achievements", like StackOverflow badges and GitHub stars ARE NOT VALUE.
Being near the Pareto frontier of inference cost vs. output quality.
This was released 6 days ago. The dust hasn't settled yet, and Mistral Small 4 was released earlier. Even if Deepseek V4-flash turns out to crush it, there was a period where it was Pareto competitive. None of the countries I named (i.e. no country that isn't China/US/Mistral) have had a Pareto competitive model at any point in time.
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