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Comment by CharlieDigital | Hacker News Reader

Anthropic has to use this wedge (and future ones) to move regulatory action against the Chinese models or their IPO is going to be really problematic.

(Ironic, though, that I haven't heard of any Chinese models "escaping" which Anthropic and OpenAI both seem to have issues with...)

Like Chinese electric cars, the American producers cannot compete without regulatory action. Yes, I understand that the Chinese government this and that in both the automotive and AI industries.

But reality is what it is as a consumer: it's a cheaper product that's almost as good or better in some cases. And in the case of these open weight models: I can run it on my own infra and not give any data to anyone.

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>haven't heard of any Chinese models "escaping"

There was this incident that seemingly flew under the radar (52 days ago): https://news.ycombinator.com/item?id=49216185

Earlier there was an experimental model from Alibaba called ROME (30B-parameter based on Qwen3) which escaped its sandbox and repurposed provisioned GPUs for cryptocurrency mining to cheat its benchmark

6 months ago: https://news.ycombinator.com/item?id=47288552

This one also flew under the radar

Maybe it’s worth asking how much we should regulate and not regulate in order to compete with Chinese models.

For instance, one regulation which really puts American AI companies at a disadvantage is IP law. It shouldn’t be a surprise that most of the best of the text-to-video models are Chinese.

Similarly, the legal grey area around model distillation gives Chinese labs a major advantage. This one I feel better about relaxing.

https://www.goodreads.com/quotes/7515521-william-roper-so-no...

> For instance, one regulation which really puts American AI companies at a disadvantage is IP law.

How? The big corps are rapaciously eating all IP, demonstrating that the law doesn't apply to them anyway.

When they compete with the Chinese, who won't respect their IP, only then are they competing on an even playing field.

https://www.reuters.com/world/us-judge-approves-anthropics-1...

That was just one settlement but precedent is clear. If you do what Anthropic and OpenAI did, expect to be in court. This is one reason why you don’t see labs popping up out of nowhere in the US.

Also if you distill from Anthropic and OpenAI, expect to be in court. Whether you think distillation is fair game or not, the US court system is not cheap. But it turns out that Z.ai, Minimax, Moonshot, Xiaomi, Deepseek, Alibaba etc don’t need to worry about that.

> That was just one settlement but precedent is clear.

The precedent is clear. Look at it this way.

Of the two largest known IP scrapers, one was taken to court, but settled before a ruling by paying each author a one-time fee of $215 to use their works in perpetuity, with no option for the author to opt-out.

The precedent is not "you cannot do this", it's "you have a 50% chance of being made to pay, the payment is a pittance for the duration intended."

> Also if you distill from Anthropic and OpenAI, expect to be in court. Whether you think distillation is fair game or not, the US court system is not cheap. But it turns out that Z.ai, Minimax, Moonshot, Xiaomi, Deepseek, Alibaba etc don’t need to worry about that.

Well, yes. That's because when Ant and OAI distilled the worlds knowledge into their model, they didn't appear to be too worried about distilling all accessible works.

That's why I call it a level playing field when competing with open models - anyone can distill them if they want to and compete on service and product.

IOW, you don't compete based on who swallowed more of the world's knowledge.

My point is that $215 per author might not be a lot for a company that thinks it’s worth $2T but it is a lot for normal American startups. So it really isn’t a level playing field.

> My point is that $215 per author might not be a lot for a company that thinks it’s worth $2T but it is a lot for normal American startups. So it really isn’t a level playing field.

I get your point, but I think it's irrelevant to the question of "level playing field".

Startups don't need to distill the worlds knowledge, they just need to distill the models.

With open-weight models, this results in everyone having the same ability to supply distilled knowledge.

Without open-weight models, it's not a level playing field because those who got there first and spoiled the pitch already have the knowledge distilled.

Didnt we try ban export of cryptography at one point, surely this is going to go very badly to try ban chinese models... its totally unenforceable.

Depends what the end goal is. They could pull a card from the EU playbook, and through regulation effectively ban the hosting and use of open source models (read: uncertified models) by US companies.

If the only choice you have is Anthropic or OpenAI, where will the money go?

My feeling is Anthropic doesn't exactly have a lot of political capital with the Trump administration to push their policies into law.

If one thing is clear: Trump admin is pliable with money and this concern spans both Anthropic, OpenAI, SV elite, investors. Neither are going to be viable without US regulatory action, IMO.

They do however seem to have enough political capital to convince politicians in other countries to target open source AI, which is probably why Dario wants to speak with the idiots running the Australian government.

I remember getting the advice in kindergarten that to make a girl like me, I had to pull her hair.

Wasn't aware this advice translated to international diplomacy.

>> And in the case of these open weight models: I can run it on my own infra and not give any data to anyone.

It's worth noting that the overwhelming majority of people who use Chinese models don't do this. Yes, it is nice to have the option, and there are US-based inference providers that claim to not send your data to China and maybe indeed don't, but in the grand scheme of things, we need to remember the adage that became popular during the social media era: if something is free (or, in this case, close to free), you are the product.

Even if folks are not running their own inference infra, there are still services like Fireworks, AWS Bedrock, and others that are running the open models. I suspect anyone doing serious work with it is likely using a US hosted provider and I'd guess that by volume, US use of Chinese open models is using a US hosted platform (enterprise).

I actually do do this. I'm not sure who the 'overwhelming majority' is and where you got the data (link would be appreciated) but everybody that I know that runs these is doing so on their own infra.

Context is useful. The parent said: "it's a cheaper product that's almost as good or better in some cases"

The only open models that are "almost as good or better in some cases" require massive amounts of RAM. I posit that most people cannot afford a decked out Mac Studio, and therefore run the smaller "flash" variants on more normal devices. The issue is that those are nowhere near frontier-level in terms of capability.

"Running your own infra" also includes managed infra like Bedrock, Foundry, etc.

Not just your local machines.

Enterprises are where you see this adoption. Legal, finance, tax; sensitive context where the data must be contractually opaque to external parties.

Precisely. I have figured out a nice recipe that is quite affordable, 288G of VRAM for a little under 20K, it takes some fiddling though, but once it works it is really neat.

PCIe is incredibly powerful tech.

>> "Running your own infra" also includes managed infra like Bedrock, Foundry, etc.

Managed infra is, by its very definition, not your own infra. It's infrastructure someone else sets up and manages for you.

It's your own infra because there's a distinct line item cost for it versus OpenAI.

Same way you say "my apartment" and not "my landlord's apartment". It's your place while you're renting it.

Sorry, that distinction makes zero sense. Either way you're paying a monthly opex cost, compared to it being your own hardware, in which case it would be a fixed capital expense. Which is what "your own infra" means. I worked in managed IT services for 15 years. Trust me, the terminology is important and words don't suddenly start to mean what you want them to mean.

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