Open-weight AI is having its Kubernetes moment

firasd

One of the strangest things in the AI industry is 'tokenomics'. It's not very clear why using GPT-4 in early 2023 was so expensive and then six months later 20 bucks could get you a fair amount of GPT-4 inference. This pattern has continued across various labs/providers for years--there is a continuous see-saw of pricing that doesn't seem related to anything. So what open weight models do is at least provide a baseline of inference cost to add some sanity to the price markers. And of course predictability too--if you really want Kimi K2 instead of K3 you can still use it. So the competitive pressure and predictability offered by open models is helpful for users

cr125rider

Way over complicated for what most users need? Huh?

curious_cat_163

> The government should use procurement to create demand for portable, interoperable systems rather than permanent dependence on one API vendor. Now, here is an idea that I have not heard before... and I think there is some merit to this. This is also the sort of thing that a state (looking at you CA, CO, IL, NY) could do, instead of just the federal government.

netdur

why would any software want to have Kubernetes moment? can't count how devop I know that is confused by it

thih9

Is anyone using open weight models for agentic coding? What is your stack (harness, model) and how much do you pay per month? How would you compare your experience to a typical subsidized plan like Claude Code + Pro plan? I’m asking because i keep hearing that open weight models are cheap and efficient - is that really the case in practice?

chrisjbg

Dario is a FUD-spreading douche

YetAnotherNick

In fact more countries should have government funded models. There are some obvious issues in China completely dominating open weights space. Kimi had funding of just $2B and could literally create national security threat. A lot of countries could fund something in the range of few billion for something so important. At the very least US and EU could fund few companies.

debarshri

Shameless plugin. Funny enough we just made agents kubernetes native at adaptive [1] [1] https://adaptive.live

petilon

Enormous amounts of money is being invested in the development of AI models. Investors expect returns on their investment or they will not continue investing. Open weights make it harder for investors to get their money back, so it harms the industry. Once the weights are out, it makes no sense to ban them in the US while the rest of the world takes advantage of it. But that doesn't mean developers of frontier models shouldn't take steps to prevent their weights from being stolen.

PersonalJarvis

https://www.microsoft.com/en-us/corporate-responsibility/top...

amazingamazing

Sadly until china scales production of hardware it really isn’t economical to run this stuff yourself. It is good it exists though to put pressure against the labs. Honestly imo this is just proof apple will win in the end. Eventually a phone will be able to run a model good enough to do most things and it then is game over.

kalu

The sentiment in this article is nice. But open source software is a weak analogy for frontier models. Principally because software requires zero capital investment (actually zero) while frontier models demand billions. Open models can only survive in the long run if they can (eventually) generate significant cash flows or if they are paid for by governments. Now China essentially has a monopoly on open weight models. And so supporting open source models means either supporting long term economic capture by China or supporting Chinese government control of your intelligence. Both of these outcomes are unequivocally bad from an American perspective. If you live in the valley and benefit from the US venture ecosystem you should be highly skeptical of open weight models. Banning them may very well be the best course of action.

cheriot

Open-weight and OSS are wildly different and the article makes a poor comparison. What's the incentive for the Chinese labs to continue releasing weights 5 years from now? It's not a stable equilibrium and cannot last. - The lab spending large sums on research and training does not get the inference revenue to fund those efforts. - Unlike OSS where a single volunteer can keep a project going, training costs run into the $billions. - OSS is often a two way street where features and integrations are built that the original author benefits from. Open weight models are largely a one way street because the marginal benefit is so much less than training costs. In the short term, it means Chinese labs can attract talent and, I suspect, funding from their gov. Similar to every other industry the CCP subsidized to take over.

pianopatrick

Eventually I think to truly be like Kubernetes, you would need an AI model that has public training data and that a lot of companies collaborate on. Might make sense eventually. Same logic as companies working on Linux. "An AI model is a business necessity. But making an AI model is so expensive we should not make our own. So let's just use the open one, and contribute the stuff that we need."

chasd00

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 distribution. If I have to trust a black box of answers to questions i would trust one from a US for-profit publicly traded company subject to market forces over one approved, and heavily subsidized, by the Chinese government.

maayank

https://web.archive.org/web/20260725184440/https://tobi.knau...

Sammi

Kubernetes is a system/infrastructure orchestration tool. I completely fail to see how it is comparable to open weight neural nets. In either application or function. I'm sorry to do that hn comment thing where we all just race to contradict or talk in opposition of whatever was said before. I'm aware. But really guys, was this article really not just a miss?

ozgung

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 attempt to ban them by origin. So, any solution to this “problem” must include ALL open-weight models. As far as I understand this is exactly what they intend to do. Axios article linked in the post mentions that. As in this quote: “The source described leading AI labs or their allies approaching the administration every 3-5 months with an idea to ban open-source models.” It doesn’t say “Chinese” open-source models. Because they already know that it’s not feasible. Any regulation must cover all the models. Now there are solutions for that latter problem. But they are all ugly and restrictive. Making a DRM-like license protection system mandatory can be a solution. If a company wants to run an open model in their own servers, they can only use approved and certified pure “American” models. This of course creates a monopoly for the big labs who are authorized to train and distribute such “open” models. A company can fine-tune the model for its own needs but of course can’t distribute the derivative model. I’m sure there are other solutions but all of them would be equally ugly. Also these regulations can’t be enforced to other countries easily so only Americans will be restricted.

drnick1

> American labs need to release frontier-grade open-weight models under licenses that startups can actually build on. To be fair, OpenAI has released a couple of (then very good) OSS models. I run the 20B version at home and it is excellent for reviewing text and common tasks like drafting bash scripts. There is a larger 120B that you can't realistically run on consumer hardware at reasonable tok/s too. I wish OpenAI updated these models more frequently though.

Danox

Yes, and yes, again the only way to compete is to build the best not hide in a corner and once again the rest of the world will go on in AI without the United States if we flub it. Circling the wagons, isn’t the long range answer.