The future will probably have most of all companies running local models, simply because the alternative would be essentially every company that uses LLMs ending up becoming completely dependent upon Anthropic et al. And that dependence would be milked to the point of absurdity once solidly established.
And as a more general point - more major competitors in a domain is very good for everybody except those competitors themselves, who would rather there be as few as possible.
Yeah I fully expect companies with lots of GPUs but not a good model like Microsoft and Amazon to just take these open weight models and make money, the GPU expense is the only moat at this point.
It’s classic commoditize your complement, nobody can replicate the cloud providers, everyone can replicate the models with open weights.
yes, this seems to me to be the reason why these three companies want open weight. everyone wins (but especially big tech) in the open weight world except anthropic and openai. i suspect even google could live with the open weight scenario; they are in a sense the only tech company that is perfectly hedged in this respect.
i suppose this is part of why openai and anthropic have not been shy about advertising the scarier strains of their models, these past few months; they basically have to force the white house's hand or risk being commoditized among the various other options in a microsoft/openrouter dropdown.
But what does that mean for the US competitive leap in AI when compared to China? Is it an admission by these companies that AI models are here to stay and the US will not “win” by being the only country with the best of models? Genuinely asking, not sure about the answer.
China will be dropping the open models blather any day now. The autonomous agential coding Ai just turned out to be way too easy to perfect. They will give Kimi K3 to the Sinaloa cartel on Monday, but that's going to be the end of it.
Nvidia is subject to export restrictions on GPUs to China. So Chinese labs have responded by allowing American hosts to run their open-weight models in the US, where there are no restrictions. We see this in the EU too where Scaleway, and now Hetzner are getting into the inference host space serving Chinese open-weight models.
So Nvidia benefits from more inference providers running many Chinese models that they otherwise would not have been able to service.
Oh, that’s interesting. I think the general expectation was that blocking exports to China would result in companies there building their own cards competing with NVIDIA. If it has incentivized them to release open weight models instead, that seems like an unexpected win.
The cards are also coming... Some of the very first are already out - but it will take a couple of years before they hit their stride in full. And cards will likely be primarily for Chinese companies initially, and then go for exports later. So it will go under the radar for many western techies for a while. Seeing what China has managed with PCB production, low to mid-end semiconductors, phone manufacturing and electric I would hesitate to bet against them.
Nvidia is now lobbying to remove the export ban, to try to reduce the incentives for developing their own high-end LLM training/serving (and cash in on current demand).
Nvidia will fail in that respect. Sanctions and restrictions are too popular with the American government. Where the United States will lose, is that almost every country in the world that can will use other solutions not from the United States.
And unfortunately, we are losing credibility on all fronts in the last year and a half. I wonder why?
It's all things at once. Perhaps it's incentivized the open weight strategy. It's also prompted Huawei to ramp up production of AI chips to try and create a local competitor to Nvidia. It's also also created a grey market for Nvidia chips within China.
> I think the general expectation was that blocking exports to China would result in companies there building their own cards competing with NVIDIA.
In the long run, perhaps, but it's a lot faster to scale up the capacity and usage of existing hardware/datacenters/grid, and even add new capacity to those, than it is to develop brand new GPU hardware and the fabrication of it.
Microsoft/azure has a big advantage because companies will literally pay extra then "free market" cost of open models purely for the knowledge that the won't fuck around with their data retention policy.
Not entirely, if models become commodity, then Microsoft's play as an infrastructure & enterprise apps company is the better bet. They don't need to make profitable mass-market AI models, they just need the best tooling on top of any model their customers pick, remaining fully model agnostic.
"AI Product" doesn't necessarily mean "We sell API access to a our models." Ton of companies out there itching to buy a commercial off the shelf product to deliver whatever AI capabilities they need packaged in a nice GUI, with enterprise governance controls, without needing a dev team/team of engineers to integrate it or develop harnesses, etc.
Buy it->have IT click a few buttons in an admin console->Deploy and have it be immediately useful is the play.
AI services becoming a commodity by definition means that the price will hover around cost to operate. That's just what commoditization means in tech. Free, as in Google creating a free browser for no profit in order to increase the size of their ad market.
The entire justification for the AI buildout, and the valuations of all the major AI labs, is that the service will be priced at some significant fraction of the knowledge work it's replacing. If you think it will become commoditized in the future, you are saying these companies are significantly overvalued at present.
> you are saying these companies are significantly overvalued at present.
I do lean toward them being significantly overvalued at present. OpenAI & Anthropic's valuations assume high margin product pricing on raw intelligence itself. Even if assume the labs will start charging value-based pricing, enterprise buyers will pay that pricing to whoever saves them engineering hours to make any cheap model work inside their compliance boundary, no guarantee that's going to be OpenAI or Anthropic.
Microsoft wins either way, proprietary, expensive models or cheap commoditized inference, because they monetize the workflow on top, not the raw intelligence. I also happen to think it's everything "on top" where a lot of value lives. Plenty of non-tech enterprises and companies out there itching for a ClickOps style AI product, especially if they don't have an engineering team, that they can buy off the shelf, meets all the compliance checkboxes, and does what they need without having to build the agents and harnesses themselves with the APIs.
Depends on what you mean by AI product. If you’re talking about a chatbot or agent, that may be true, but o think it’s less true if you’re talking about AI-run application layer tooling. If Meta decides to compete with Shopify and provide a launchpad for entrepreneurs, you can bet the platform would be rife with AI to facilitate operations, marketing, coms, etc…
Different companies have different motivations. I'm sure some are genuine, but a lot of them simply lost the race (to OpenAI/Anthropic/Google) and know they can't compete anymore, so are shifting strategies. How many times has Microsoft done exactly this in the past?
looking at both openai and anthropic; they are winning something, but a sober look at their finances will make you silently mouth "but what did they win".
They've seen the government officials parroting OpenAI and Anthropic lobbies talking points, and they have smart enough people to see the signs of upcoming regulatory capture.
If I were cynical, I'd say it isn't helped by the current US administration.
If there are effectively only two AI companies allowed to train or run model inference then demand for hosting, GPUs and data centers goes down, so they'd be able to squeeze their suppliers that much more too.
They really don't need to be very worried about that. Google, Microsoft, Amazon, et al have decades of experience in shipping custom hardware at scale, and it is not a simple field to pivot into
True, but Google has their own models and did not sign this either.
The other thing that comes to mind is they want to avoid the government from banning open models as has been suggested by some of the closed models providers.
Probably a real effort to push for some kind of sanctions or commerce block on Chinese models. Anthropic just doubled their political spending to $40 mil for the midterms to push for "AI Safety."
I suspect that whatever Musk has agreed to spend on the midterms in exchange for those sweetheart deals the SpaceX IPO got will make that look absolutely comical, but we’ll see.
Almost certainly these companies are using similar strategies as the Chinese models which they fear will be made illegal.
It's also the case that it makes it hard to attract customers if your openweight model is banned. A major reason the likes of Qwen, Kimi, GLM, and Deepseek are popular (well, at least highly talked about) is because of the open weight models they gave away.
Nvidia benefits no matter what because their hardware is being used. Microsoft and Meta benefit by making sure that the gap between "Anthropic/OpenAI" and "everyone else" doesn't widen, or they'll be hopelessly dependent on those frontier labs.
Probably the fact that they don't want Anthropic or Google or OpenAI to have access to their data theoretically, and that they do want to use good AI, and that they don't want to spend the money themselves to make a good model...
I think Meta would love nothing more than to throw a very large wrench into the works of OpenAI/Anthropic. Open models could mean one or both go bankrupt which is good for them.
And as a more general point - more major competitors in a domain is very good for everybody except those competitors themselves, who would rather there be as few as possible.