Who is going to fund it? Training is unfathomably expensive.
You have either VC funded models looking for a return on investment, or CCP funded models looking to solidify authoritarian "model Chinese society".
Maybe there are some university 4B models, but I doubt those will carry far.
I share your concerns, although we still see pretty similarly large and complex things that remain open source today.
I am astonished on a daily basis that my Linux computer is so close to the same experience as two operating systems put out by trillion dollar companies. It even does things that those commercial alternatives don’t do.
Also, if DeepSeek is truly putting out models with 1/10th the cost of Western competitors, and a fraction of the employee headcount, I think it implies that there will be a market for someone else to be in the space offering an alternative.
I think about how companies like IBM are so willing to contribute to Linux and give away those contributions for free because they are part of group of corporate sponsors that need an alternative to more dominant commercial players in the market.
Meta “gives away” React for similar reasons: it’s more beneficial for them to have it be a standard and be able to hire people who already know it.
It’s definitely harder to imagine the same ecosystem benefits of an AI model, but maybe it’s out there somewhere.
I could imagine some data center/VPS providers trying to sponsor something like that so that the big AI companies have less leverage over them.
Or maybe all this optimism is a pipe dream?
Software is "free" though, which is why it has such a vibrant open source scene. One guy can code for a weekend and fill the screens of 5 million with something fun by Monday.
However, Once real costs are involved, participation tanks. Open source hardware, because it actually requires money to realize, has 1/10,000 the depth of open source software, if that.
Obviously everyone wants an open source AI, but virtually no one wants to fork over money, especially when the end result is others getting it free. A proper training run would require millions of people donating hundreds of dollars. Its not something one guy over a weekend can do...
Admittedly, I don’t know how the gap you’re describing gets closed.
With a lot of OSS it’s just free volunteer hours.
Compute isn’t free.
The closest thing I can think of is the idea that some group of businesses who can benefit from open models being around might fund that sort of thing. It’s just hard to imagine who they might be.
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corporations and governments fund most linux development. for hardware companies software cost is a tax that decreases their revenue and profit, so Nvidia and AMD have strong incentives to support open source models, which they are, very actively.
> I share your concerns, although we still see pretty similarly large and complex things that remain open source today.
I feel like they aren't comparable. Open source software just requires human labor, and lots of people are willing and able to share that with the world for free.
Training AI requires capital, to build and power giant datacenters. People don't donate capital at that level.
> I am astonished on a daily basis that my Linux computer is so close to the same experience as two operating systems put out by trillion dollar companies. It even does things that those commercial alternatives don’t do.
We live in a world where you can "port" open source software to a new language (Rust) and close it up.
Linux will be ported to Rust and closed. It'll probably also be put under MIT/BSD because nobody cares anymore, but the companies will have their own internal private variants. And these will be the ones that see corporate development.
The value in open source is that it was a lot of concentrated value that was hard to copy, clone, or rip off. Now you can one shot a replacement with a few hundred bucks in tokens.
The economic value of Linux used to be billions of dollars. Soon it'll probably be closer to $0.
It's over.
> Meta “gives away” React for similar reasons: it’s more beneficial for them to have it be a standard and be able to hire people who already know it.
Nah, now you just one shot your thing. And you do it fast enough and with distribution and you win. Eventually human devs can't afford to keep competing and launching startups slower than a hyperscaler's own massively funded efforts.
This is the end of open source and the end of solo developers.
And when the ruthlessly effective models that can one shot entire business functions cost $1,000,000 per invocation. Oracle can afford to press the button to create, say, a new smartphone. But you cannot.
Just wait until devices start requiring trusted computing attestation. The ladder is going to be pulled up.
There’s a lot of merit to what you’re saying, but I don’t share that high level of pessimism.
The scenario you describe is basically that software is free as in beer now. We as a corporation don’t really need to bother using GPL/Apache licensed software because we can one-shot something of our own and not deal with with giving back contributions to the open source community.
But that highway goes both directions. That means that the open source community can also one-shot their software, build more with fewer resources, or it might even just devalue proprietary software even further.
If software is so easy to make, what’s the point of keeping it proprietary? I can’t charge you $100/year for Microsoft Word if I can tell Claude Opus 9.0 to clone it with $100 worth of tokens.
>>We don’t really need to bother using GPL/Apache licensed software because we can one-shot something of our own and not bother with giving back contributions.
Thinking of a open weight/source AI as gcc/perl was in the 1990s is more helpful line of approach to take here.
The tool used to achieve a thing must be open.
I suppose you're right. All software is about to be as valuable as a single jpeg you see on your Instagram feed.
What matters is physical infrastructure (datacenters), the lead on competitors / open source models, and distribution/mindshare.
Tbh, there really needs to be some legal precedent set that makes model distillation a legal activity. If the model makers can rip everyone else's work and launder information as if it's their own without giving credit back to the original creators, I don't see why it should be illegal to distill the models. It's the same thing the frontier model makers are doing to IP everywhere else.
I agree. But this won't happen in the US because Anthropic / OpenAI is a big ol economic recession risk because we levered ourselves to the tits and put our chips on them.
Explain how an AI bust would tank the economy? They don't employ enough to feel the hit from that.
They're not even IPOed so how do they tank the market? GPU and ram prices will go down but that will actually help most tech companies.
I don't think the rest of the economy is inflated on the fantasy gains of AI.
We could actually go back to feeling like we can invest in products and content without FOMO.
OAI and Anthropic can actually both tank, MS would pick up OAI's IP, Amazon would pick up Anthropic's, and Google would keep cruising. We'd have a model plateau for a while but ultimate AI would keep on chugging.
If AI fails as a technology, it's going to lead to a great depression and probably either a revolution or WWIII.
And which leading country is going to go for allowing other countries to distill their models?
If your country doesn't have any leading models, why not legalize distillation, either explicitly or implicitly?
(Chinese labs famously distilled American models, and that seems to be going well for them. They now have a competitive industry, home-grown talent choosing not to leave, and they now can truly compete without distillation).
It doesn’t have to be the leading countries, if the EU allows it, it is good enough to create a market for distilled models
But EU is way behind right?
Ever calculate the cost of a computer in the 1960s, adjusted for inflation? Training is unfathomably expensive right now. What if a bunch of universities pooled their money? Or a bunch of nations pooled their money? Breakthroughs will eventually happen, optimization will occur, etc.
People questioned whether there could ever be a viable open source operating system, yet Linux has been a viable option for a desktop environment for decades now, and that's not to mention its ubiquitous use as a server or phone OS.
Yes, but have you seen what's happened to hardware improvements over the past 20 years?
From the 1960s to the mid-2000s, every 10 years you'd have a big enough improvement in computing power that you could basically throw out the old computers and replace them with two new ones that were each massive improvements for the same cost (this varied, of course, from hyperbole to massive understatement). We achieved this by shrinking transistors, so we could fit more onto the die. With that, we could dramatically increase clock speeds and the amount of RAM we could cram into a machine
But then we hit the wall of physics. Things haven't stopped improving since ~2015, but they've slowed down so, so much. We've made transistors so small that there's very little more improvement we can get by continuing down that path—they're already seeing serious quantum tunneling effects that need to be adjusted for.
We can no longer assume that we can just powerscale our way out of any computation-cost problem. And breakthroughs, by their very nature, cannot be relied upon—we have no guarantee that there's even a possible way to improve our silicon to scale the way we did before, let alone that it'll be something achievable this decade, or that it'll be cost-effective.
The bottleneck right now isn't making hardware more powerful, it's manufacturing it fast enough. Hardware right now is expensive because of scarcity, and those with a monopoly on it have no incentive to change that.
The Chinese would love to produce AI hardware much cheaper, but are blocked from doing so because US sanctions stop a Dutch company from selling them the machines capable of doing so. Coincidentally the companies with a monopoly happen to be in the US.
To be fair, the Dutch company is built on technology that was developed by the US Government, hence why there are restrictions.
[1]https://www.eetimes.com/u-s-gives-ok-to-asml-on-euv-effort/
Moore's law isn't as relevant with parallel workloads. If you can keep building more lanes you don't have to worry about making faster cars.
Sure, but it doesn't lower the cost or increase the efficiency of the system
Yes,
You have to start some where. Im guessing, making progress also brings in new ideas how to move further.
It's not only expensive, it's also wasteful - there's no value in using an obsolete model.
Open source AI manifesto demand that "Opensource AI should remain ... economically viable". That's just wishful thinking.
Perhaps an idea that could work is that if you're a lab that is releasing closed source models, you have to also release open source ones. gpt-oss is now old but was decent when it came out. Nemotron is solid, especially the recent ultra release. And Nvidia especially has a much better story vs Chinese models around releasing all parts (including pre and post training data), not just the model itself.
It’s expensive, but not unfathomably, esp in an open source setting where capable people might contribute high quality data for post training (worked problems, code reviews, feedback, …) gratis instead of at immense cost.
Anyone who isn't currently own a piece of who is winning by the current model. Basic disruption theory, if the game isn't going your way, change the game.
Who funds Semiconductor fabs
When Jensen (Nvidia) was doing interviews at his recent public talks, he was asked something along the lines of: "Why release these new laptops which are a low margin market, if your other businesses are vastly more profitable?" and his answer was basically that if they can build the coolest and best technology and push the frontier, they will do it. It's not all about making tons of money. He seemed genuinely excited about the tech.
It highlights the difference between companies like Nvidia and Anthropic to me, where one is clearly all about the money and power, and the other is doing it because they genuinely want to accelerate progress and make cool stuff as the driving factor. It's no surprise therefore, that Nvidia is the worlds largest open-source contributor to AI, with over 800 open-weight models.
Of course, these models run on Nvidia hardware, so they benefit from it as a company. But with that healthy mindset, they found a way to contribute that not only benefits everyone, but also benefits themselves.
Contrast to Anthropic, who has gone the complete opposite direction. Closed off everything, restricting everything, fearmongering progress, regulatory capture attempts, the list goes on. I mean, they won't even agree on using AGENTS.md as a standard because CLAUDE.md is free marketing for them. That's the level of disgusting greed we are dealing with...
From a game theory perspective, the cooperative strategies tend to win. As a result, Nvidia has set themselves up for a lifetime. Anthropic however, is playing a strategy of winner takes all, and they're happy to see the world and the entire AI industry collapse in the process.
Amazing that anyone in 2026 still can believe in "don't be evil" marketing from multibillion dollar corporations.
The proof is in the pudding though. I'm judging based on their actions, not on their words. They're making AI models and AI research widely accessible, including selling consumer grade hardware to run them locally, and to use open-weight models. They could have just gone all in on selling to Anthropic, OpenAI, and all the other big tech companies, but they aren't. Meanwhile, Anthropic is trying to price people out of the market, increasing their restrictions, cutting the latest model from subscription plans, etc.
Yeah but Claude has a cream white background, intelligent font, and fun hand drawn graphics cues... Anthropic must be pure
Nvidia and "open source" is like opposite things. Nvidia only ever opened stuff that helps their bottom line or improve vendor lock-in.
But yeah they are good shovel seller and competitor to actually evil companies that literally wants to eat all the world chips and energy supply.
In the open source space, the Nemotron models from nVidia are quite real. Including a Nemotron Ultra variety meant to be large enough for near-SOTA.
Nvidia not doing it out of goodness of their hearts and love to open source. If at anynpoint their CUDA vendor lock-in moat will faik because Intel or AMD manage to get working software they'll return to keep everything locked and proprietary ASAP.
Basically everything Nvidia does in open source is there to make sure their proprietary stack have a good moat and no competitor stack can catch up.
Strongly disagree: https://build.nvidia.com/models
Their license terms are also incredibly generous and allow commercial use, modification, etc, at no cost.
How soon do you think this generosity end if AMD or Intel or some chinese competitor would be able to provide price competetive hardware?
That's not really the impression I get from Anthropic, but if you have the links to back it up, I'm always willing to change my mind.
Compared to bizes like Oracle, Microsoft, or Facebook, I felt that Anthropic was more interested in progress (not to the neglect of business―AI training is expensive at the end of the day), but maybe I've just not seen what you've seen.
https://clawd.rip
The internet, the world wide web, etc. and much of the research into new medical tech. All public money.
The fully open model Apertus (although not the frontier) was fully fundend by public Swiss institutions and a strategic national partners. I would not consider Switzerland to be a communist or totalitarian state...
Maybe we do p2p compute?
This is a good idea. I've been hoping that a large player with enough social reach would create an open-source fund that everyone can contribute to, to develop a company that trains and releases open-source models at the cutting edge. We can crowdfund the training costs, and the whole world benefits.
It's the most logical solution for AI anyway, considering that it's training on humanities collective knowledge. It should be more of a public-funded and public-access resource, rather than something greedy tech companies distribute like crumbs while they use unlocked powers internally to clone all of our businesses and swallow the economy.
there are already projects like Petals https://github.com/bigscience-workshop/petals
I'll take these 'authoritarian' models from China any day over whatever you call this https://arxiv.org/abs/2406.17737
You have an unhealthy and unreasonable obsession with the idea of CCP models, you should get that checked.