As I replied to a child comment - this is a nice idea that just isn't tenable in reality. AI hardware isn't just hilariously faster than consumer GPUs, it's also hilariously more power-efficient and has hilariously better connectivity. Every one of these dimensions kills the idea.

The far, FAR superior power efficiency means that even if you did harness every public GPU or GPU-like device on earth, you'd end up consuming so much excess electricity it would be cheaper on net to simply take the money that would have gone to the power bill and spend it on your own datacenter.

And even if electricity was free, having those GPUs spread over the world with internet-level latency will slow everything down by factors of thousands to millions - if it's feasible at all. Regardless, you're not getting fable-oss this decade, maybe even not this century.

It's a nice idea, like I said, but it just doesn't make sense when you look at the reality of how training works. It would be far, far better for governments to own their own datacenters, maybe as a coalition, and dedicate their operation to the public good. I believe that is what we actually have to do.

>But when people think of decentralized training, they don’t first think of gigantic datacenters, owned by the same company, training models across large distances. Instead, they imagine thousands of small datacenters, or individual consumers, pooling their spare compute over the internet to orchestrate a training run larger than any single actor could manage alone. Many companies are pursuing this vision: Pluralis Research, Prime Intellect and Nous Research have already successfully decentrally trained models at scale. But in practice, training decentrally over the internet has lagged far behind more centralized training. Even their largest models (Pluralis’ 8B Protocol Model, Prime Intellect’s INTELLECT-1, and Nous’ Consilience 40B) have been trained with 1,000x less compute than today’s frontier models (such as xAI’s Grok 4). https://epoch.ai/gradient-updates/how-far-can-decentralized-...

Could it be done by making a sparse MoE of thousands, or tens of thousands, of smaller experts in very niche domains? Maybe a tree-like structure of experts which can delegate from relatively general but inaccurate to extremely niche but accurate? Also these experts might be plug-and-play, easily swap out an inferior expert with a stronger one in the future without having to redo the whole pile?

> The total power of all GPUs on the planet dwarf their capabilities

That just isn't true. It misunderstands exactly how much silicon has gone directly to those companies, and exactly how much more powerful said silicon is compared to consumer grade gear.

Ya that'd be an awesome project, the only issue is how do you verify it's not being poisoned? To actually validate it would require more analysis than the training took to run. It would require a trusted network, not an open one, unless that can get solved somehow.

there are some strong open source groups like NOUS research taking the fight https://nousresearch.com/

Is the total compute capacity outside of meta, google, amazon, anthropic, oai and x is higher than even the capacity of any of them? In any case, there's no chance a public collaboration gets to anthropic levels of compute even if communication were no issue.

I believe we are not the only ones

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 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?

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.

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.

Maybe we do p2p compute?

Who funds Semiconductor fabs

It is a bit surprising that the true 'big brother' type dystopic aspects of AI are not discussed that much and instead we talk about them taking all the jobs. We feed these things so much information. It could be used against us for advertising, control, or worse.

I don't think we're going to be "dependent", because I can't really think of anyone that "needs" this stuff (well, unless you're like attempting to build a business off skills you don't have). I guess this really comes down to if you believe the productivity story. I don't. I think there are some gains, but the evidence that isn't just anecdotes from vibe coders seems to be modest.

I couldn’t agree more. But what can we do? If intelligence confers a competitive advantage, which it does, the incentive are aligned against collaboration to preserve equal access. Asymmetric access is too valuable.

Eh, they’ll learn soon enough there’s a limit to their power, unless they somehow start acquiring munitions. There’s a reason the electricity companies and other utilities didn’t take over the economy, despite now being essential.

Or just opt out... you don't have to use these things.

One of the usual claimed benefits of open source software, is that if you find a bug, you can fix it.

Would be nice if someone figured out how to properly debug a model. Without that? OK, so you have your own open source base model trained on your preferred document set that excluded whatever you think is propaganda, and your own open source RLHF training set based on the judgement of whoever you think is a good egg, and so on.

Last I checked, nobody yet knows how to define a precise rule for automatically checking which of two models made this way is aligned better with whatever your standards are.

The metaphor would be like if we knew what a CPU was but had no idea how to do either chip design or formal verification, and instead randomly mutated the connections between transistors until our test set of 2^16 randomly selected pairs of 32-bit numbers only had one error under addition and two under multiplication.

Worse, because we're making them this way, you have to be a fairly big corporation even when you take shortcuts like DeepSeek did.

And note that I'm not disagreeing about the systemic risk that comes if these models become dictators: people are currently demonstrating they're very eager to outsource their own thinking to these models even when they ought to know better, and corporations are currently demonstrating they're very eager to force workers to use them even when they're mediocre and workers spend half the time they might save from a more competent model just fixing the damage done by their current meh-ness: https://www.theregister.com/ai-and-ml/2026/06/10/brit-worker...

> Dependents of an AI-megacorp for our "facts"? Our software? Our work?

It's worse than this, it's more like our thinking. There's already plummetting math grades [1], handing over our thinking to AI megacorps where there's likely to be a monopoly or duopoly is an incredibly dangerous thing for humanity as a whole.

[1] https://www.dailycal.org/news/campus/academics/failing-grade...

Those closed labs need to justify the investment still, and as we approach stagnation in model capabilities that’s harder and harder. Right now Fable and Mythos are cutting edge, but soon enough they’ll be commodities. And for every company like OpenAI/Anthropic that wants to get ahead with a SOTA model, there’ll be a hundred companies aiming to commoditize their complements.

Open source models don't need to be anywhere near as good as Claude Mythos or even Claude Sonnet to 'win'.

Open source 'winning' just means that there exists at least one open source alternative to closed models which is as good as, say, GPT 4... I mean, we're essentially there already with Google Gemma models.

As a software engineer, I didn't notice any difference in my productivity since Sonnet. Of course Opus is better and I'm sure Fable is better yet, but we're already hitting diminishing returns in terms of economic value.

I went from Cursor running one of the earlier GPT models to Claude Code on Sonnet and that was essentially a 5x productivity boost for me. Before Claude Code, I only used AI for small snippets. With Claude Code + Sonnet, I could trust it for entire sub-tasks... But I still don't trust Opus with full end-to-end features. I'm not sure it will ever get there. It probably doesn't need to.

Companies need software engineers to have a certain moderately high level of talent but above that level, they really don't care AT ALL. They don't even notice the difference, even if the gap is significant.

>>AI is just hillclimbing today

That's what the Fable harness felt like. You give it a goal and it could try to get there through the shortest path given the tree of possibilities to get there. Iteratively, or recursively.

Perhaps if we make a open coding AI, the design must be along these lines. Something that's easy to train, and serve from local machines. Albeit has loop / recursive hill climbing facilities built it. That way the model gradually keeps moving towards the solutions, in iterations/recursions.

Once this is done, other multi modal things could be pursued.

I think the same, but I also think that local AI is actually inevitable, even if not open source models. I wouldn't be surprised to see OpenAI and others release an on-prem product. Whether that's effectively an appliance rack, or some other form, people (large companies) are going to want to run inference locally for data sovereignty & cost controls. Especially if we get to a point where companies want AI integrated into manufacturing and other air-gapped networks.

Zoom out. It's a matter of time the trillion valuations will be deemed senseless, only once it will prove inpossible to extract trillions from consumers.

In the meanwhile, and regardless, software optimisations coupled with hardware continuing to scale, we will end up, soon enough, with some open weight that run on a mobile device with greater capabilities than Fable.

Yeah I think that's a decent analog (Photoshop & GIMP). We're in a sort of "rapid expansion" phase right now, but unless the tech behind "AI" really evolves, better and better models will be harder to come by, with diminishing returns.

Even if the GIMP of LLMs is only 80% as good as the VC-funded stuff, that will still be plenty useful for lots of people.

And I think just having the option to use open source models is a win, even if it turns out to be true they'll never be quite as good as the proprietary ones.

Perhaps, unless there is a way for users to donate compute to training, folding@home style. I don’t see how that could be practical though.

That is fantastic news then, if commercial product products will always be better than open source, and open source products will continue to get better

the moat is in hardware, without capital intensive acquisition how tf they going to get that money ?????

I learn it hard from prusa 3d printer open model

Which is the nearterm future that we must demand: a stop to the amounts of capital flowing to ASI research. Join me, Anthropic, Google, and OpenAI’s-founding-charter in saying the obvious, y’all; Pause AI, now.

It should be clear by now that there’s a whole universe of work to do with the models we have today, from studying to securing to ‘harness’ing. There are tons of economic benefits to be reaped already, if applied carefully. Doesn’t that sound nicer than rolling the dice with the lives of trillions?

Monopoly capitalism and finance capitalism took reigns of markets more than a century ago. The state serves these huge interests.

Everybody knows AI firms pirated to train, nothing will come of it. A plain example of classist application of law.

The reason for the willy nilly application of their own laws will always be 'national security', of course, since they own infrastructure their interests are a national security.

So tech may shake things up whenever it makes great leaps, but finance capitalism quickly adapts and absorbs the waves.

It's a perfect prompt for a rich HN discussion so while in general I agree with you, in this case the discussion is what matters.

I think that the events of this evening (really of this past week) are almost unprecedented in the history of tech. Sometimes a clear and concise message is more important than nuanced analysis.

When kubernetes was released there were very few people who could run it, and even less that could run it usefully.

Right now there a few people who can run a 1T model at home, even less who can run a 5T model and probably single digits who can run a 10T model.

But if an open source 10T model was available you can be sure people would find new ways to quantize it, new ways to configure hardware and and new ways to think about problems that would make it useful.

1T+ models (Deepseek v4, Kimi K2.6 etc) are available as open weights now, and for ~$5000-$10000 you can run them usefully at home. 2 years ago no on was contemplating that.

$250K to run a 10T model might be possible now. There are many companies that will pay that, and that will push the tools and techniques downwards for the rest of us.

> any AI system that runs on a computer that i do not control is by my definition not Open Source.

This is not true at all. It would be open source if you could download it and run it anywhere that is capable, and are free to move it and modify it as much as you want.

Just because you don't have a computer at home powerful enough doesn't mean it isn't open source.

Qwen models are actually very competitive with frontier models, and you can run them on your local computer. Gotta have a decent graphics card and by that time the current cost of the rig may not justify it over paying $100/month for cloud model but it’s all out there.

Projects like pluralis agora solve this problem. Really what you want is the model to be collectively owned and governed, not local

LLMs that you can run locally on hardware that is not out of range to acquire is already a thing for some time.

We can run open weight models on our own machines.

Huh? Open source is a quality of the software, not specific to the hardware used to run the model. The demand is that model weights are openly available for anyone to run and fine tune without restriction. Has nothing to do with the hardware it runs on.

Call it open weights if you must. But even with OSS just because you have the source code doesn't mean your machine is high performance enough to run it usefully this has always been true.

Wait, which side is blocking kids fork taking algebra or forcing universities to admit people that can't do math or read, or abandoning phonetics for unproven methods that don't work?

> because AI has almost reached its most usable peak

It doesn't seem to be showing any signs of stopping. Have you used Fable 5? It's a fantastically capable model and trumps anything that came before it. Seedance 2.0 is categorically the best video model, and it's only a few months old.

> the entire business is run by a few old men

Startups tend to skew young, and in this case it's no different. Most of the leaders of AI companies are decades younger than the CEOs in other types of industries.

> who think AI is everything and invest huge sums of money to show other AI companies they need to improve to get more funding from old people.

They're spending capital to win market share and to try to build a moat. One of the most important things in business is building a durable way to keep competitors from taking your market. You spend enormous capital to win customers, and it would suck if other businesses could watch what you did, spend less money, and come in and take everything away. The money being spent is an attempt to have a durable lead.

It's working. Enterprise contracts are deep and sticky tendrils that work through governments and large companies. Both OpenAI and Anthropic have massive partnerships with Fortune 500s, the DoD, you name it - and these contracts will last and print enormous amounts of money. This makes it incredibly hard for other players to enter the market and build a cash flow with which to compete and thrive.

> find something new and innovative

This is easier said than done. It's an incredibly hard problem. It took decades to find the last big technological waves: the PC, the internet, broadband, smartphones. Now AI. These are generational step function increases. The groundwork can be decades old, but it takes time to proliferate before it can become a big business.

Other possibilities include fusion, green tech, quantum computing (useful for crypto breaking, etc.), AI drug discovery, etc. If you go into research one day, try to find an interesting field with potential for commercialization - that could make you very wealthy if you find something you enjoy working on, with lots of greenfield opportunity, that is ripe for turning into products.

Good luck with your game! You should post it here on HN when you finish. You'll get lots of great reviews, comments, and early players. :)

Why have you sent this same message multiple times?

It's actually the opposite. Democratization of intelligence is the only way to stop existential threats and render them useless.

Right now, and likely forever, because biological threats can be sanctioned at a supply-chain level, the risk of AI is all digital. Fraud, phishing scams, spam, hacks, etc.

The only way we harden the worlds infrastructure to the point that it can withstand attack from bad AI is if we have an abundance of access to frontier intelligence to develop countermeasures.

Otherwise, bad actors will develop these capabilities behind closed doors and use them to hold the world hostage and cause irreparable harm. There's no putting the genie back in the bottle. Good and open-access AI and the people using it are the digital immune system.

If there's an asymmetry where bleeding edge is gated off to only a small group, and allowed to gain exponential power over the immune systems defense grid, the slightest infection will lead to death of the host.

It's too late.

You can one-shot a port of Linux to Rust and stop contributing to open source.

The value of software is going to tend towards zero. The value of the software developer the same.

Anthropic is now a kingmaker. It gets to decide which businesses get the expensive private model that can generate entire business functions at the drop of a hat. If you can't afford the price tag, then competition in the market is not for you.

Computing is no longer "personal". It's for big biz only.

"Converging towards AGI"

These things can't even center a div correctly half the time.

Not everything is code. Just because it generates a shitty SaaS clone for you and that seemed magical, it does not mean we are approaching "AGI".

An AGI could design an Oil tanker, manage the project from start to finish, handle all contract negotiations and purchasables, payroll, scheduling. Then it could do that 50x over and start a leading logistics firms.

In reality an LLM can't even complete upwork projects that are worth $20 an hour more than 4% or the time.

Source:

https://labs.scale.com/leaderboard/rli

4% guys, 4%. It cannot complete entry level work on fucking Upwork 96% of the time. Stop falling for the marketing and sorry but an LLM will never be AGI.

Its literally just text autocomplete with some RLHF post training, holy shit im losing my mind. I want this hype to end so badly holy shit I need this to end.

This is not about information but about capital. Even if we had free access to the weights of the best models in the world: who would be able to run them?

We've never seen open source win before so I'd be dubious that it can win here without concerted effort.

Inevitable isn't "in our lifetimes"

“information wants to be free” - doesn’t seem correct. More like it’s easier to spread info than to hide it.

it is baffling that you can still encounter Yuddite delulu in 2026 when everyone and their literal grandma is using chatbots daily. you might as well campaign to shut down the internet or ban smartphones.

but ok, who is going to initiate such a treaty? US? the orange man won't, and even if he did, no one would care. by the time his term is over and the next AIPAC spokesperson is elected, it will be even more late than it is now. EU? impotent and irrelevant. China? lmao.

Unfortunately the US is no stranger to using export controls to restrict frontier technology.

Famously, the PowerMac G4 was briefly subject to export controls. Apple turned it into a marketing campaign.

Just happened 5 hours ago.

China unironically saved humanity. I'm no fan of the CCP but if they hadn't organized an effort to compete with the US no one else would have done it and we'd be begging our AI overlords for tokens and praying we don't get caught conducting wrongthink.

Go ask Claude to criticize Anthropic and see how long your account stays active.

On this very thread you already have people talking about "open weights" and similar nonsense. What is open about them? They're free to download, but that hardly qualifies as open. Where is the source? Where are the instructions to modify and build your own?

I'd never though I'd have to utter the expression "open as in beer".

The blatant attempt at manipulating vocabulary here is... quite blatant.