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Open-weight AI is having its Kubernetes moment

tobi.knaup.me

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Re: Open-weight AI is having its Kubernetes moment

#251

Post by PunchyHamster »

ThomasGlanzmann wrote: post #203
PunchyHamster wrote: post #134

Earlier quoted context omitted.

It would basically make America behind as every other country would use open, cheaper models for all tasks but the ones requiring frontier models. And that list of tasks grows smaller every day > Everyone is talking about banning Chinese models but nobody talks how it is feasible to ban them. I think it’s impossible simply because technically there is no such thing as a “Chinese model”. There is no way to tell apart…

I often use deepseek-v4-flash to summarize hn threads for me. Your comment was enough for deepseek to refuse my request: Content Exists Risk.

I have considered making invisible n-word and some other AI-safety triggering stuff just to kill the scrapers

Re: Open-weight AI is having its Kubernetes moment

#252

Post by wyrdcurt »

andriy_koval wrote: post #206
wyrdcurt wrote: post #198

Earlier quoted context omitted.

Except that even the exact same model won't output the exact same results, that's a fundamental aspect of how LLMs work. They're probabilistic/stochastic, not deterministic.

Models are weights for matrix operations, they are determenistics.

They are weights for matrix operations, so in principle you'd think they would be deterministic. In practice it's more complicated than that.

Not to be snarky or dismissive, I mean this genuinely: ask an LLM about it. I currently have a headache so I'm not up to explaining the technical details, but they are interesting and worth reading about.

Re: Open-weight AI is having its Kubernetes moment

#253

Post by rzerowan »

m11a wrote: post #226
andriy_koval wrote: post #219

Earlier quoted context omitted.

That French guy takes risk to be forever under US warrants for breaking American law, denied access to financial institutions even in Europe and will quickly go to some KYC entity list, and you will be notified as his clients to stop using his model. Or you think all kind of fraud can be committed through some "french guy"? Also, I am not confident, receiving illegal materials from French guy gates you from personal…

I presume such US legislation isn't going to try claim worldwide jurisdiction to block all persons worldwide from using Chinese models. In which case, the French guy wouldn't be violating American law. As for the American company, it's pretty difficult to check the provedance of open weights. It's even difficult to check the provedance of open source code, because chains of attribution aren't always clear. I posted e…

But it will claim worlwide juridistcion , just as all interpreations of the law are in Washington nowadays. Its how a commercial deal between A Chines company(Huawei) and an Iranian telco ends up with Canada reying to rendition a executive for violating US laws. The goal is to spread as much FUD as needed to dissuade anyone form using the Open models and herding them back to the propreity ones.

Re: Open-weight AI is having its Kubernetes moment

#254

Post by antonvs »

andriy_koval wrote: post #192
moffkalast wrote: post #185

Earlier quoted context omitted.

Yep, add a few blank layers, fine tune it a tiny bit and the weight checksums nor parameter counts won't match with anything, while the model will be practically the exact same. Time and time again random startups have tried passing established open models as their own. "You made this? I made this." Of course a conspicuous architecture would still give it away.

someone can run tests and see that models output exactly the same results, and then you are open to criminal investigation.

Many of these models will report that they are Claude. It’s going to be difficult to overcome reasonable doubt.

Re: Open-weight AI is having its Kubernetes moment

#255

Post by stingraycharles »

ozgung wrote: post #126

Everyone is talking about banning Chinese models but nobody talks how it is feasible to ban them. I think it’s impossible simply because technically there is no such thing as a “Chinese model”. There is no way to tell apart an “American” model from a “Chinese” one by looking at their weights. Weights are just numbers and you can’t assign country of origin to numbers. One can find very easy workarounds to any naive at…

Sounds to me Anthropic’s marketing strategy of “AI is so dangerous and we’re the only responsible shepherds” is a great success if this open weights ban will indeed happen.

Re: Open-weight AI is having its Kubernetes moment

#256

Post by antonvs »

andriy_koval wrote: post #206
wyrdcurt wrote: post #198

Earlier quoted context omitted.

Except that even the exact same model won't output the exact same results, that's a fundamental aspect of how LLMs work. They're probabilistic/stochastic, not deterministic.

Models are weights for matrix operations, they are determenistics.

Achieving determinism with LLMs and other neural network models is actually a hard problem that people spend a lot of time on, when they need that. It doesn’t happen by accident.

Issues include accumulated floating point errors happening in different orders due to distributed and parallel computation, CUDA kernels that deliberately sacrifice determinism for speed, and several other such issues.

Re: Open-weight AI is having its Kubernetes moment

#257

Post by andsoitis »

DennisP wrote: post #220
andsoitis wrote: post #210

Earlier quoted context omitted.

Don’t you think drug companies would be doing that (not advertise) if it would increase their profit?

Of course advertising increases their profit. It does that by increasing their revenue even more than the cost of the advertising. For the rest of us, that giant increase in revenue is an increase in our healthcare costs.

Ah so sounds like your logic is: ban advertising -> less costs -> less revenue & lower patient costs -> same profit.

I think I can spot a flaw in that logic.

Re: Open-weight AI is having its Kubernetes moment

#258

Post by CamperBob2 »

formerly_proven wrote: post #237
CamperBob2 wrote: post #168

Earlier quoted context omitted.

That's going to hit first amendment grounds pretty quick, the same way that software in general did Don't count on that. "National security" == the cheat code for the US court system that instantly bypasses any First Amendment issues.

That was the literal reason given back then and it did not stick. https://en.wikipedia.org/wiki/Crypto_Wars https://en.wikipedia.org/wiki/Bernstein_v._United_States

That was also a very different SCOTUS bench.

Re: Open-weight AI is having its Kubernetes moment

#259

Post by Alwayshasbeeb »

chasd00 wrote: post #82

FTFA: American labs need to release frontier-grade open-weight models under licenses that startups can actually build on. oh now i see, the Chinese government is funding the training and release of their best models to pressure OpenAI, Anthropic, and others to do the same for competition's sake. I don't buy it, this seems more like a way to get SOTA models RL'd to comply with Chinese government approved information d…

A "US for-profit publicly traded company" is what brought us the Cambridge analytica scandal. I'd rather not trust them with the next wave of consciousness and opinion shaping technology.

Also, oligopolies aren't famous for being strongly bound by market forces, especially when their decision makers are non ironically being treated as if they were heads of state.

https://www.nytimes.com/2026/06/17/world/europe/g7-summit-ai...

Re: Open-weight AI is having its Kubernetes moment

#260

Post by andriy_koval »

antonvs wrote: post #256
andriy_koval wrote: post #206

Earlier quoted context omitted.

Models are weights for matrix operations, they are determenistics.

Achieving determinism with LLMs and other neural network models is actually a hard problem that people spend a lot of time on, when they need that. It doesn’t happen by accident. Issues include accumulated floating point errors happening in different orders due to distributed and parallel computation, CUDA kernels that deliberately sacrifice determinism for speed, and several other such issues.

It happened that I am working on OSS LLM -> finetuning -> benchmark with 100k tests pipeline, and unless I do some data augmentation, result is 100% deterministic.

I think you likely right, that some parts of stack could induce some marginal float point error, but converged model can mitigate it, and on some principal set of knowledge can give deterministic result with high probability.

Which leads me to believe if you give this task to Anthropic, who has very strong incentive, they will build such benchmark, and then can tell that benchmark gives correct answer with 99.9% probability and it will be enough to drag someone to court.

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