The US is winning the AI race where it matters most: commercialization

Anthropic, OpenAI and Google are the standouts, but the main question for me is, why is this a war? In their own context China has greatly benefitted from this. They shored up their gpu design and manufacturing expertise.

If this really is a war, trump is kneecapping the country with his lawlessness and eroding America’s good will. If the world cannot trust China with their data and they cannot trust the U.S. to provide good reliable service and not turn it into a mafia style negotiation, then winning the AI war is not helping the U.S. countries as much as it potentially can. It’s probably a good thing for more capable areas like Europe which may develop their own tech stack.

In a weird way because the AI stack is so expensive, China helps the world much more than the U.S. with their really capable open source model.

How does gobbledygook like this get traction on HN? What has happened on HN culturally to allow something like this to surface to the top?

Flagged for AI content: I hope this submission dies and the user is penalized (look at their submission and comment history!), because IMO the article does not belong on the front page. Quick polemic:

>The US is winning the AI race where it matters most: commercialization

If you ask me, one could name different criteria for winning, and commercialization would not be the first thing to come to my mind:

https://english.www.gov.cn/news/202604/15/content_WS69df29e6...

https://fortune.com/2026/05/03/chinese-court-layoffs-workers...

https://www.reuters.com/world/china/china-moves-regulate-dig...

> It also owns platforms that generate and organize the data of the AI age. YouTube is a video corpus. Google Drive and Microsoft 365 sit inside daily office work. GitHub sits inside software development.

Yeah, okay. China does not have any platforms nor data.

There used to be such a thing as profit. A return on investment. If your exit strategy is to get sold to Google, focusing on revenue is a perfectly fine strategy. If you _are_ the Google, however, the money poured in should eventually be made back. We seem to have forgotten that. The current level of commercialization just means the US is burning investments faster, than anyone else. Eventually this might change and the bet might pay off. But every minute this goes on, the expected payoff must be larger to pay for the loss made this minute as well as interest for the previous minutes. I’m not entirely sure this is what “winning” looks like. Tic-toc.

No, the US is _leading_ the AI race, but the race isn't over.

What's the point of leading the race for 90% of it, if they're gonna slip on their own sweat and fall down by the end? In non metaphorical terms, what's the point of spending billions of dollars rushing to get the best AI tech at all costs, when the competition can distil your progress and catch up in 6-12 months while only spending 1% of what you spent.

Even in the aspect the article cares about, commercialization, the US is starting to lose marketshare, I've seen people move from cc/codex plans to use glm/opencode plans due to the recent squeeze the US companies put on plan usage, the US companies are screwed if that sticks, not everyone needs the bleeding edge models, they just want to pay $20/month and have the models be decently capable.

The winner in the long term will be the one that will deliver the best performance and low-memory ratio for local models.

Anthropic, OpenAI and Mistral are just companies that are making money right now (still not profitable), but will lost their tractions and values in the long term.

However, I am more appealing to see how OpenCode Go subscriptions will go in the future: cheaper than big techs, more tokens, and they don't train on our data to (try to) improve...

I feel like the much simpler explanation is that the US is winning because it's dumping the most money into it. By a very large margin.

No, they are not. They are winning because West is forbidden to use Chinese models for anything work-related.

Is the US actually winning the commercialization war? The US is definitely delivering more commercial products but if all of those products are deeply unprofitable and need to buy users with unrealistic discounts (or direct cash payments[1]) to keep their DAU's looking good then is that winning?

There's a significant amount of innovation happening, but if the market decides this AI thing is not worth funding then I think that'll dry up overnight.

1. https://thenextweb.com/news/anthropic-private-equity-venture...

One interesting thing that Anthropic did was putting their stack on the various cloud providers, I wonder if they'll put it on GCP and Azure next since they've put it into AWS first at a level we have not seen a major AI provider do to date. Your company can have their own Claude stack just like an ELK stack on your cloud, if they can do this for both Azure and GCP then OpenAI has to really catch up.

In my eyes I would rather use the AI I can run on my own paid infrastructure, so if there's an outage its isolated, or I could potentially have a different region / DC to fallback on.

I'm still surprised that neither Microsoft nor Amazon have made their own models available on their cloud offerings. I guess Microsoft probably does have Phi on there, but it's not front and center, especially with something like Copilot for Devs (seriously Microsoft rebrand that damn thing to be clear what you mean by Copilot!) where they could use the cheaper compute by using something like Phi.

This makes no sense when you zoom-out. None of these companies, be it Anthropic, OpenAI, xAI, Google, Meta, Microsoft, are profitable in the AI department, they're all bleeding money and using funds their parent company and/or investors, primarily investors gave them. The Chinese models are keeping up with them, while offering the models for free and able to run on consumer grade hardware, and more importantly they train them for cheap. AI models are an extremely volatile product that can be outdated in the matter of a few weeks. Meaning you have to keep dumping resources into developing better models which has no end-goal besides infinite scaling. Lets look at how users behave in the real world:"I don't use Gemini because it's worse than Claude at XYZ." That's it. Now Gemini has a worse model and people are going to Anthropic... what happens when Anthropics model is arguably worse than everyone else's? What does it matter if they can commercialize if their product is objectively worse?

I understand that America dominates in distribution, integration, enterprise contracts, ecosystems, infra... The article isn't wrong, it's just that that dominance is fragile and requires constant upgrading.

But what is the point of that if you have to infinitely scale because the opposition is right behind you at all times ready to usurp you... You CANNOT scale infinitely, the VC money will run out at some point and then everyone will have to downscale everything to meet the real costs associated with SOTA models, they'll have to be able to use subscriptions, and other monetization to cover those insane costs, we just saw SORA shut down because it was bleeding money far too fast while the Chinese released video models that far surpassed it back to back to back...

EDIT: Hell, one of the most critical aspects is integration of the models into other products, and even on this end open-source is keeping up (and will eventually outpace when the VC money dries out) with these big companies.

Strange. I'm switching from Codex and Claude to Pi with Qwen3.6 27B local and Deepseek V4 Flash which is dirt cheap but powerful.

Article title: “The US is winning the AI Race”

Article content: “The US are capitalizing on AI the best”

A lot of assumptions there that no one can actually verify as true right now. If commercialization into rent-seeking SaaS landscapes is the endgame, then yeah, the US is winning the AI race. If individualization, local LLMs, and consumer hardware are the endgame, China is winning the AI race. If it’s something entirely different - if LLMs are the wall and research is what grants the next breakthrough, or if compute and memory requirements take a dive, or whatever; then we have no idea who’s winning the race because that stuff is mostly happening behind closed doors.

It’s certainly too early to call (if you must view this as some sort of adversarial competition). The US is behind on local models, the future for anyone who cares about privacy. There may be step change innovation yet to come that completely shifts the landscape. There’s basically no switching costs to users to change models. They have no lock-in.

Theft without any consequences by copyright laws Surveillance pushed down our throats Labor Landscape destruction AI psychosis Private Companies controlling the AI pipeline Data centers destroying the environment.

That doesn't count as winning at all.

I've been using the deepseek api (not for coding though) and have been getting great results and it's so cheap it may as well be free. Another reason I'm using it is because I like the license and I also have some hope of running it in my own hardware in the future.

But the thing is... I could be using any of the llms for my use - I'm using a middleware that lets me change providers only with a configuration change.

So it's going to be tough for USA ai companies to charge 5x to 20x (depending on what you're doing).

> where it matters most: commercialization.

It begs the question because both its premise and assertion are already wrong. Has AI improved the industrial capacity of the US in order to improve the lives of its citizens? No it hasn't. Has AI increased the wealth of its citizens by being able to do laundry or any household task in a generalized way? No it hasn't. The only thing it's really done is make very narrow slices of white-collar work more fungible. In what way has AI been able to address existing shortcomings of the US?

The current commercialization isn't economically sustainable.

I don't think so. From a nation state perspective, AI is a munition. Every advanced nation is going to have their own cyber division with their own AI hosted within its borders. Considering how xenophobic and belligerent the US is, nobody is going to want their national cyber defenses hosted in the US.

On a personal level, I simply do not trust the US anymore. I won't host any of my personal data in a US company. I don't want the US govt invading my personal privacy, and their corporations are constantly leaking and selling private data. I consider US to be rapidly approaching complete autocracy (on par with China) so US-hosted AI is a non-starter. And let's not forget local inference keeps getting more efficient, with higher context and TPS in the same amount of RAM. Within a year even small consumer machines will run local models good enough for basic coding, and in 3 years RAM prices will lower and everyone will be able to afford a decent rig.

Finally, open weight models are now good enough for daily work. They may never be as good as SOTA (SOTA will just keep increasing indefinitely), but that doesn't matter; my car may not be as fast as a Porsche but it still gets me to the grocery store and back. So I use non-US hosted model providers which provide open weights, which are both significantly cheaper than Anthropic/OpenAI, and actually allow me to use my subscriptions without a moat.

But yes, Anthropic/OpenAI are absolutely the new Oracle. They will win for US govt and Enterprise contracts. But that's far from the only users of AI.

Inclined to disagree.

The winner here will be whoever can move atoms with AI not take notes at the daily standup.

i.e. Think boston dynamics vs unitree

They're both doing well but I'd lean towards China is winning on atoms in light of a huge manufacturing base they can AI-ify.

This para caught my eye

>Frontier cyber models may push states and defense firms toward the opposite logic: security by obscurity, with closed software, closed tooling, closed firmware, and closed chips. If a model cannot train on the code and architecture of a target stack, it will usually have less context and less speed. That does not make systems safe, but it does raise the value of proprietary stacks all the way down to hardware.

Is this really true. Are there any experts who can weigh in on this.

Should we interpret this to mean that in the new world Windows is more resistant to attacks than say Linux.

Alibaba's cloud is something that the author of this article seems to dismiss. It's being used massively in Asia and they're pretty close in services and offerings to what AWS, GCP and Azure provides. Once they start doing inference on their own custom chips it might be hard to compete with them due to the energy costs

>Trump fits this moment well. He is a salesman at core, and Larry Ellison is too. That helps explain why AI infrastructure is an easy political product. Selling AI today is easier than selling Oracle databases in the 1980s.

I feel like the author (and perhaps many here on HN) are on a different planet than almost everyone I interact with.

Considering that you can easily swap out one AI for another and there is zero lock-in potential, does it really matter who is winning now?

I continue to be impressed by our collective willingness to engage with obvious AI slop, as long as it also talks about AI. Sincere question for any of the nearly 300 folks seem to be arguing about the article: why? The author couldn't be bothered to present their case, so they probably don't care about our opinion. They just want traffic and search ranking with the least amount of effort. The community is literally being played for clicks.

Is it just that the subject line alone is a springboard for casual discussion? If so, maybe that's fine, but then, it feels like we'd be better off cultivating these discussions as "ask HN" posts instead of boosting this kind of web content.

Same as software in general I guess? Lots of critical software has been developed by Europeans, but it's the US who build hyperscalers with it

The whole "race" narrative is silly. It is all built on the assumption that one country (corporation, actually) somehow creates AGI and thus, essentially, the singularity. Great for raising VC, apparently, but at its core this is magical thinking.

Even if any of the US corporations would eventually end up in a scenario where their revenue is at least as high as their inference cost, what harm would that do to the other contenders? It's not as if there is any kind of network effect here that would exlude them from market participation.

Lol some of these western arm chair analysts actually need to visit China.

“It is not the same as profitable AI leadership”

Where are these profits of which you speak?

I feel like the title of this post should have "for now" appended.

> Many people use the wrong scorecard.

Correct. "Revenue" is the wrong scorecard when they're selling 20$ bills for 15$. I too can make a bajillion dollars in revenue with that strategy.

Show me a company not speed running the uber/doordash playbook and we can talk.

If it is a war, then China is delighted.

The USA is very good at loosing very, very expensively....

Matters the most to whom? I certainly will not care about expensive models that do about the same thing cheap non-american models do.

It's like the USA Librem 5 vs PinePhone. About the same HW for $1600 vs $150.

Sure will not pay 10x for "US" thing just because it's a US thing.

That's like saying that Louis Vuitton is monetizing shoes the best. Sure, but it's not winning shoes

How does commercialisation matter when China will pump however much money they need to into this? This is a national security issue for them, just as it is for the US.

Not even gonna bother clicking through this one, the title is that egregious. And by the way, you can be damn sure that if Anthropic or whichever other American frontier model model is the best of its day was on the cusp of going under, the US gov would either pump it full of government contracts or (less likely) nationalise it.

Commercialization is not enough. The US is built on financialization.

Cultivating an ecosysyem of strong capital protections, wealth creation through extraction, and tax advantages for AI finance is what we should be looking for. Commercialzation may be a step towards that, but isn't the destination. We have to create a system where those with money can multiply it, not simple add to it.

GLM, Kimi, MiMo, Minimax, Deepseek, Qwen would like to have a word. :)

"Where it matters most": accuracy and repeatability?

Sorry, nobody's winning that AI race.

Even when other countries won, the teams would have reloated to US.

This sounds like an ad for US than anything else.

Does any of the US companies earn money on LLMs? No, they bleed money. Github Copilot is switching to token based pricing, which will be costlier than hiring juniors.

Anthropic also is switching enterprises to token based pricing from their subscription one.

From the big three only Codex is still in somekind of subscription pricing, but they'll shift eventually (usage limits are a kind of that, but they have them less stricter than Claude ones)

There is one winner in this race - China. Trump with his agendas and wars makes it even more likely that China will lead this new market.

US AI models would not survive a free market re: this metric.

Same can be said of healthcare.

And, yet, the US AI companies are not actually making a profit, right? They're selling at a loss and trying to make it up in volume (or lock in some kind of monopoly position, in a currently non-sticky product). We're all currently enjoying investor-subsidized tokens from the big guys, and that pushes out the reckoning for US AI. But, I think they're beginning to think maybe they need to ring the cash register. Copilot dramatically reducing usage limits and what models are available on its plans, Anthropic playing games with what's included in the Pro plan, etc. I think they're starting to feel the bleeding.

Not only is the investment that keeps US AI companies flying high slowing, I suspect in two or three years, we'll all mostly be using open models and the people making money will be the hardware manufacturers. Even the small models will keep getting more capable. I'd guess a model you can run on a high end, but not outrageously overbuilt, developer desktop or laptop (something like 128GB of unified RAM), will be competitive with the current frontier when it's allowed to search the web and do research and write test code. You can't fit as much knowledge in a small model (80GB of weights can't store the world's knowledge), but I don't have the world's knowledge in my head, either, and yet I can figure out most problems with a little googling and experimentation. The reasoning and tool use abilities of smaller models is where the gap is closing, and that's what will make the huge models obsolete for huge classes of problem.

Already, there are many classes of problem that the easily self-hostable Qwen 3.6 27B can solve that required a frontier model a year ago. When the self-hosted options reach Opus 4.5-ish levels of capability, the argument for paying for tokens for most work begins to look a lot less compelling. And, looking forward, 1.58 bit models are coming. Incredible intelligence density, and still a lot of improvements happening.

I'm glad we went to space, truly. Racing the USSR might have been the wrong reason but it got us there. We've benefited immensely as a species from exploring the solar system and looking deep into the universe.

I'm not certain that racing China in AI is the right reason but it might get us... somewhere.

>The US is winning the AI race where it matters most: commercialization

Mass unemployment and an eventually collasping economy is winning?

it's an exhibition, not a competition

> Trump fits this moment well. He is a salesman at core, and Larry Ellison is too.

Larry just fired 30% of his people at Oracle because, apparently, he is in an immediate need for cash. Because Oracle's early AI bets aren't paying off.

Ppl don't understand Commercialization is not incidental to the Western system, it's why we beat out Communism. Commercialization incentivizes ppl to build, bc ownership and control.

The FSF was not an attack on commercialization, it was about giving users more freedom with their own copy.

AI commercialization is why we will always be a few steps ahead in AI.

The Chinese and Russians are free to join us. It's a pickup game.

> The US is winning the AI race where it matters most: commercialization.

puke

Yeah, go ahead and run your country into the ground because of hypercapitalism and hypercommercialization, you're almost at the end game now! While the rest of us try to figure out how to actually build societies worthwhile to live in and experience, with healthcare and not waging war on our neighbors.

I don't know how people can seriously publish stuff like this and not feel like they're actively trying to make the world worse. Is money really the single thing y'all can focus on? Is there nothing better in life you can chase, even if it's also a number? So sad to see stuff like this.