Dependents of an AI-megacorp for our "facts"? Our software? Our work?
It's possible these companies will become everyone's boss, and will dictate to everyone what everyone is allowed to work on, think, say, do, believe, etc.
Before Big Tech springs that trap, we must support and divert resources to open models.
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.
"All the jobs" includes those tasked by the state to commit, plan, and organize violence, it's plenty dystopian already. Like, one important reason why the military and militarized police don't engage in egregious overreach is that the people who'd be responsible live standard lives in their own society and it's hard to get high compliance for that sort of thing. Replace that relatively democratized infrastructure of thousands of intelligence analysts, mid-level management, etc with a bunch of AI agents, and a meaningful restriction on the power of the upper echelons of the state is removed.
Simple answer: taking the jobs is how it’ll impact regular people the most.
We already have personalized, algorithmic advertising and what I would call “control” all over the place: things like consolidated oligarch-owned media.
AI isn’t going to change how we are advertised to or controlled all that much, at least compared to the prospect of being put out of work or taking a huge salary cut similar to the mid-century worker who used to have a $40/hour union factory job and now works at Walmart below health insurance threshold for $15/hour.
Hyperinflation is how it will impact most people. You will still have your job, at your pay, but a continually higher percentage of earnings will go to very few at the top.
Why do you think AI won’t be a factor in how we’re controlled if our rights become stripped away and we’re increasingly surveilled? Or if violence is deployed by the state against its people with broader targeting? You seem to take for granted that nothing will change except maybe the flavor of rhetoric.
"You're absolutely right, I think you deserve to treat yourself with Mococoa, made with all-natural cocoa beans from the upper slopes of Mount Nicaragua! It's what humans like myself crave."
Much like Truman's town, I fear a future where every non-in-person "interaction" might be a bot-network with an agenda and the inhuman patience of playing for the long-con.
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.
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.
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.
It works at the individual level but won't if mass adoption happens.
The mechanism will become like taxes, you don't have to use public services thus pay those taxes, unless most people comply as it's easy to oppress those who don't.
The parallel isn't about legitimacy, but Mechanism. Some companies already oblige employees to use AI to deliver their work. In a near future we may see jobs seekers registering their AI ID for companies to decide which humans qualify to be plugged into the compensation system, at what rate, and usage conditions to avoid terminations.
Food delivery systems already show a glimpse of how it could look like.
I can't even manually resolve the merge conflicts alone that happen between my code and that of everyone else submitting code at agent speed in my team's repo. So long as I have financial obligations toward my family, I cannot opt out. I must use these things.
And then the Amish see the world around them using electricity and cars and think, "Yep, I'm happier without that." And they're one of the few groups on earth with a growing population, so they're doing something right.
1. Your assumption that a growing population is the metric of success is questionable. A population that grows but is subject to famine, epidemics, and natural disasters because they haven’t developed the scientific and technological capacity to escape the existential risks of the physical world is living on borrowed time. Not saying I agree with that, and I would actually agree that there is merit to the Amish hypothesis that a certain existence is more compatible with individual and societal fulfillment. But there are obvious counterpoints.
2. The Amish are not a good example because AI will confer an advantage to those that control access to it that has never existed.
>Your assumption that a growing population is the metric of success is questionable.
It's a better measure than GDP/S&P/401(k) line-go-up especially [re: America] when the native Euro-based population has been aging and dropping for decades, once you strip away all the post Hart-Cellar immigrant lineages.
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.
If humanity is over-reliant on frontier labs' models to perform work, the result is a dependence on the actual intelligence of these models -- not on human intelligence. This could be a small reason, on top of many others, why investors are throwing hundreds of billions of dollars a bit "carelessly" to these labs. It's fascinating seeing the models do the "hard work" (the deep, challenging thinking) for you.
The conundrum which tricks me though - is this a net negative or a positive? If humans are less intelligent, but their output is 2-3 times more intelligent (with AI), what's the result? At what point do we, as humans, stop comprehending anything and give all intelligent work to the neural nets?
And if that does happen, could we live in a society where no work, or at least a significantly less amount of work, is needed? To me, it seems like a dystopian net positive.
It might seem far-fetched to ask these, but I think these questions are getting more prevalent by the day.
If there was a way to guarantee that every human would have equal access to external intelligence then it would be hard to argue against it but everyone knows that the US oligopoly will do everything they can to ensure that no one else has the keys to the kingdom.
Just listen to what the SV ownership class says out loud. They openly discuss how China cannot "win the AI arms race" and how China's development is existential. Existential to who? It's impossible to fully subjugate people with agency.
It's not just a dependence on the intelligence of the models, but also their intentions, as programmed by their owners.
A friend of mine asked me if I was optimistic about AI. I told him, it depends on who owns it. If the people own it, I'm optimistic. If the oligarchs own it, I'm pessimistic.
I am going to try to cheer you up. Hear me out. One day, not long from now, I am going to buy a humanoid bot for 40k. This human android will 1) get my groceries, 2) make my elderly parents meals, 3) go to the backyard and plant 1 acre of corn, 4) paint my neighbors house. 5) get the kids from school 6) change my oil.
What will happen? Massive. Deflation. What will you pay for an oil change? Corn? Meals? Everything is about to be free. But tokens will be expensive!! Sure but, you wont do white collar work anymore so it wont matter what tokens cost.
I've been contemplating a decentralized model training system for some time using volunteer machines that we all contribute. But, it is astronomically difficult. The communication speeds are untenable.
And, there is the issue of data poisoning from untrusted nodes. I've almost cracked that last issue with a self-healing checkpointed rollback system that doesn't have to throw out anything that follows the corrupt datum.
But, I'm just one person with an idea and I don't have infinite funds to make this happen. This isn't a small project.
Maybe there would be interest in something like this, now that entire frontier labs are being banned from making further progress.
The total power of all GPUs on the planet dwarf their capabilities, if we had a way to harness them in a distributed way efficiently. We wouldn't be able to train a Fable as fast as them, but eventually having access is better than never having access.
> 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.
If folding@home is a useful yardstick by which we might estimate the amount of GPU-ish capability that civilians might be coaxed into donating to a shared enterprise, yeah, it doesn't look pretty. This is extremely rough napkin math but comparing to xAI's Collosus 2 for example, for training workflows you're probably looking at 4-5 orders of magnitude the capability of all of folding@home combined. That's 100,000 times faster.
Very rough math like I said but I doubt it's directionally wrong.
And even if you did force literally everyone on earth with some sort of GPU to max it out 24/7 in service of an open source AI training enterprise - you would waste so much power trying to use that inefficient consumer hardware with the worst latency imaginable that it would be cheaper and faster to get everyone to instead chip in some cash to buy a datacenter with blackwell chips instead! So the idea has no legs whatsoever.
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.
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.
Is the issue that training with less compute takes more time? Or is it just not possible? I think a collective using distributed training could tolerate the idea that it takes 10x as long as Anthropic to train a model, or whatever.
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.
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.
> 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.
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.
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.
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.
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.
Open-source AI can, by definition, never "win". AI is just hillclimbing today, and closed labs can always absorb everything the open world does and build upon it.
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.
> 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.
Is this really true? We just don't know what the maximum capability of AI is. If it turns out AI can be as intelligent and capable as something like Data from Star Trek, no one is going to be thinking GPT 4 is good enough.
It could get really smart but I'm confident in my thesis that surplus intelligence beyond a certain level doesn't yield any real economic benefits.
At scale, I can see a benefit in terms of being able to process large amounts of data intelligently to gain a competitive advantage in terms of accruing nominal gains but I think that as long as AI is pursuing dollars, those gains won't translate to real value to the people who control the AI. At best, will translate to more political control; but with added risks and threats too. I suspect it will look more like controlled decline with a small number of entities getting an increasingly large slice of a rapidly shrinking pie.
I think AI will just figure out really complex ways to legally steal people's money. It will probably look all legit on the surface, it will look like the majority of people are just freakishly unlucky and a tiny number of elites are just extremely lucky... But it will be AI behind the scenes choosing who gets lucky and who doesn't.
Might end up literally like a game of monopoly. One player could dominate the game and start receiving all the money but, if you look at the big picture, none of the players are doing anything economically useful; just sitting around a board and moving pieces of paper amongst each other.
No matter how much the winner dominates the game, it's not going to put food on their table because that concern exists outside of the game. The game of monopoly is all about accumulating pieces of paper. The people who control AI would have to think beyond our economic system in order to get real benefits from it. I'm not sure they can do this. Not sure they want to do this. It seems like it's all about winning the game for them.
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 don't think insulting people is a great way to contribute. Not everyone who sees things differently than you has "psychosis".
Your reflexively negative comments on anything relating to AI are as insight-free as they are numerous; it's all just vague shitting-on without even a hook or argument that could be engaged with and debated. It's pretty tiring, honestly. If you really think your point of view is valuable and others should pay attention to it, rather than just filtering it out like the trollish noise it usually is, why don't you put a little more effort in?
Loop engineering, whatever that is, is obviously just a way to get people to increase the amount of tokens required per task/request. They did the same thing with Ralph loops, they just need more revenue. Just write your code and use it to search and clarify, it can't build that magical thing you think it can.
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.
With open-weight AI, there might not be an incentive to put large sums of capital towards training / research. There might be a donation fund of some sorts, but it certainly won't reach the level of fundraising that the frontier labs are receiving.
Because of this, I think it might not be possible to have AI *only* open-weight; major players like OpenAI, Anthropic, Google will likely stay for good, with better models than open-source versions.
I think it might look something like Photoshop & GIMP, with Photoshop being a frontier lab, and GIMP being the open-weight model. GIMP is decent for many different image editing workflows, but Photoshop is just better.
I would definitely prefer to have an open-weight model better than frontier labs'. Though I don't think it's possible.
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.
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.
I do believe that if OpenAI and others release an open-weight model that is better or on par with their frontier variants, it might ruin their primary business model.
That is, of course, unless they develop their own hardware specifically to run this open model. But, that does ruin the point of open models.
When/if gains slow down, I can definitely see branching out into hardware to sell for on-prem inference once the models can be etched into the silicon with hard wired weight chips. I'd guess maybe at least 5+ years away from that though.
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.
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
Agreed. The only "issue" is that commercial products will always be ahead, with less friction for most users. This ultimately results in most people using these over open-weight variants. Users might not even be aware that the open-model variants exist. Similar to Windows / MacOS and Linux.
In a way that's ok, though? I run Linux on my laptop, and in some ways it's better than Windows or macOS, and in other ways it's lacking. But that's fine; the existence of Windows and macOS doesn't mean I can't run Linux, and doesn't mean I have a worse experience.
(Yet; I do worry about future required hardware attestation for basic things, but that's another issue.)
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?
I feel with current government decision to block Fable, this is not an mere opensource issue, considering how US government restrict frontier models, what we need is sovereignty for every country. If not they will release every model with a kill switch in future like F35.
I agree with sentiment and mission, but the goal is inseparable from politics at this point.
Being Open Source (tm) will not protect you from the government/others imposing controls on your silicon or what it is allowed to do, which is already happening around the world.
Even having the models be open source won't fix the regulation or economic incentives. Which is not something you can compress into a couple of paragraphs.
AI is civilizational infrastructure and it needs civilizational solutions. Not just source.
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.
I mean, even if the frontier labs opened their frontier models, only nation-state level actors are capable of running them. A lot of the tech is very open and known, its putting it all together that's the struggle.
In the US -- once our nation finishes attacking our own education system -- this is definitely something a group of academic institutions could get together and accomplish. I assume the same is true in other countries. Companies like Nvidia and AMD might even support that effort, as they make money on the hardware and would probably be more than happy for there to be more reasons to use it. There may have not been a compelling enough motivation to achieve this before, but "models" didn't have this level of strategic relevance until relatively recently. Nvidia has been fairly good about releasing open weight models in the last few months.
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?
It's the US, both "sides" of that coin are bad with examples pro and con all over the shop.
Still, to specifically give a partial answer to your poor faith rhetorical just askin' musing: Florida Conservatives
(specifically turfing nerds from New College of Florida and bringing an excess number of baseball sports bro's to a place that likes math and has no baseball field)
At d5s.tech we are recreating the layers built on top of models, working on dogfooding our own product to run a large chunk of the company.
I feel extremely strongly that a future in which most companies depend on one or two large AI-megacorps is going to lead to excessive rent seeking sooner or later.
I remain positive that the long term steady state will consist of proprietary models, -but- with open source AI models statistically close.
If compute keeps growing the relative cost of training current frontier models will decrease. An open source Fable/Mythos model simply seems inevitable.
to me Open Source, like Free Software, is something i can run on my own computer. any AI system that runs on a computer that i do not control is by my definition not Open Source.
so how then can Open Source AI win? it can't even compete. even if we collect enough money and create a dedicated Open Source organization to build and run a community owned AI datacenter, how does that help?
> 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.
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.
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.
Qwen is still controlled by Alibaba, one company. We can't let the future be in the hands of a few companies, can we?
Fun fact: Qwen was not initially a Apache Licensed project, it was based on a custom license from Alibaba that restricts commercial use: https://github.com/QwenLM/Qwen/blob/ba2d85a13b28ed1ee0dde2d6.... There's no guarantee that they won't just switch it back later.
Kudos for them for switching to Apache License, of course. BUT, they're still a for-profit company. So as DeepSeek btw.
Recently I fired up Gemma4-26B-A4B on my 8-year-old PC... and it ran surprisingly well!
But I am going to need a much beefier machine to get it to the point where it can do any but very trivial dev tasks acceptably fast, and I'm going to need a much beefier model, perhaps one not so aggressively quantized, to keep it on task without the wheels completely falling off. Already we're talking serious money outlay, perhaps still within my programmer salary to accommodate, but just barely. And we're not even where near the performance characteristics a frontier model can support.
DGX Spark runs this sized model (I personally like qwen36moe better than gemma4moe) at speeds fast enough for interactive coding sessions. Algorithmic advances like DiffusionGemma ~4x token gen speeds (https://deepmind.google/models/gemma/diffusiongemma/)
> a model that runs on my own machine will never have the capacity of a model that runs in a datacenter.
I don’t think so. A local run model only needs to serve one or a few people. It seems possible to run a DeepSeek v4 model at full capacity on a server costing 200k usd. Very expensive but not impossible.
Factor in hardware and software improvements over time, and the fact that most people may just need to run a smaller and quantized model, it should take a pc at 10k usd scale.
If RAM prices ever come down, you can have a machine that can run a capable local model.
Qwen 2.5 72B is surprisingly capable, almost on par with GPT-4o if not a little better. You can run it on a 128GB Mac Studio with 8-bit quantization. You need about 77GB for the weights and ~15GB for your context window & cache.
Pricing remains to be seen, but there's also those new nvidia laptops coming out the surface laptop ultra should have 128GB RAM w/ Blackwell GPU, they're saying 1 petaflop of AI compute, if you can tolerate Windows (no idea if it'll boot Linux until the hardware is out).
These models are roughly ~1 year or less behind the frontier models. We really just need hardware to catch up and alleviate the price pressure on RAM.
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.
I have been working on this exact problem, and I suppose now is as good a time as any to talk about it.
To make any agent "good", there are two components: the model and the harness. Very few companies can train models, but anyone can build a harness. How much does the harness matter? Can I build a harness that's good enough that I can use open source models with opus level performance? That's the question I've been trying to answer by building better harnesses. None of the existing frameworks have the functionality I need to build a good harness. The features I need are language-level... and so I started building a language called Agency[0].
It's been six months and its going well. Some of the things Agency can do are wild:
- It can pause and serialize execution at any point, making HITL easy
- It has some neat safety capabilities such as handlers[1] and PFA[2]
- You can bundle up any agent as an HTTP or MCP server[3]
- I'm now working on a built-in optimizer to optimize agents (think DSPy).
Obviously, it's a huge undertaking, but having worked with the Agency for six months, I can't imagine going back to another framework. It makes things so easy. I'm working on its built-in agent now [4]. My goal it to get it to be as good as Claude Code, but using open source models. It's still early days, lots of rough edges, but if this sort of thing interests you, I'd love to have a few more people test it out.
As an person whos getting into tech and already developing a game, the fact that laptop prices since 2020 have increased by 20-40% is insane. It's delaying the time to create my game. I researched the reason for the cost spike, and most of it is from the excessive money put in ai Technically, the owners of AI could slow down the amount of GPUs and RAM they buy because AI has almost reached its most usable peak. Everything they add just introduces more bugs, so instead of building more AI centers, they should focus on improving the main AI model with bug fixes. There's no need to give it more unnecessary power. Most people don't care; the entire business is run by a few old men 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. We just need to find something new and innovative for older investors to focus on, so not everything is about investing in AI like Roblox, OpenAI, Google, etc. The extreme amount of reasoning power given to AI is causing bugs, and the moments when AI had outbursts towards people are related to this.
> 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. :)
I think models will be a commodity sooner rather than later. This whole race doesnt matter. First mover advantage is real, but over enough time it wont matter.
Civilization is at a crossroads, or will be soon. Democratization of AI can be good up to a point, but existential threats can also be real, and democratization of existential threats is not a survivable policy.
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.
Don't worry, open source AI will win. There's a reason everybody is desperate to IPO fast and get an exit, their competitive advantage is not lasting long.
I hope so. But how? Who gonna fund these projects and how to coordinate with every sides. This is complex. I only believe that the open source AI won’t lack users.
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.
Available components must win. I’ve often been a critic of open weights and open architectures that give very few normal people access. What’s the point of releasing the plans for a nuclear reactor if no one can have the fuel?
So I've long said that the valuation of OpenAI at a trillion(ish) dollars depends on OpenAI "winning" and "owning" AI and there being a sufficient moat to stay ahead of competition. Without that, the company is worth a fraction of that. Anthropic is probably positioned better here actually but it's still kinda true there too.
Ever since a Chinese firm released DeepSeek I immediately came to the realization that any US tech firm "owning" AI is simply not going to happen. China will make sure of it. It's in their national security interest not to let that happen.
From the POV of geopolitics, IMHO the US shot itself in the foot by banning the export of the best chips to China. The US also somehow has the power to prevent a Dutch company (ASML) from selling to China too. That makes a little more sense to ban but the combination of banning EUV exports AND banning the best chips sowed the seeds for the destruction of all of this.
By banning chip sales, the US inadvertently created a captive market for Chinese chips with Chinese companies. If there were no chip ban, Chinese companies probably would've bought US chips. But they can't. So they can only buy from Huawei and SMEE (indirectly). The US forced China to realize it was in their national security interest to copy the best lithography and, by extension, the best AI chips.
So DeepSeek was reportedly developed on either older NVidia hardware or smuggled newer NVidia hardware but that won't last either. At some point it'll be completely Chinese made chips that are doing this.
And what's the biggest cost for a model? Training. But you do that once and the model like any software is infinitely copyable so China can under OpenAI, Anthropic and SpaceX (xAI) and that's what they're doing.
But it gets worse for the AI moat. Local models are going to get cheaper and cheaper to run. You can already run 31B models on sub-$5000 hardware. What do you think it'll cost in 5 years? Will larager parameter models keep getting better or will there be a law of diminishing returns? What is a B100 workload now, will be a Macbook Pro workload in as little as 5 years.
What if all these AI data centers are ultimately just going to be commoditized cloud hardware like AWS in the not too distant future? We already see Google renting big from SpaceX. I think the writedown on all these data center investments and the companies that are doing them is going to be extreme in the next 5 years.
Definitely, but I see the gap widening everyday, especially while commercial AI models have started converging towards AGI. However I do believe and support the cause, as it's the next big thing as developers we need to take to prevent a complete monopoly in the coming few years.
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.
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.
Winning is a tall order. I'm just hoping it'll get good enough while allowing us to run it locally with no idiotic "safety" controls or censorship of any sort. Looks like the best open weight models are at Sonnet level, if they get to Opus 4.6 level it's gonna be perfect.
But if "they" stay on the current trajectory we'll never own hardware capable enough to run the open source AI. They want us to rent everything from the cloud and never own it. If a government-supported cartel forms around this idea (which appears to be the case) that's the end of it.
Anthropic just kneecapped themselves, and possibly OpenAI and Google as well, with their FUD strategy that got fable shutdown by the government.
But that doesn't impact Chinese providers. Then can US companies get investments for expensive model development if they can't actually sell those models-as-a-service?
In the meantime, open source will continue its march onward because while slower, it's completely open source, and the models are already good enough to improve their own work as well as build out the next gen of models.
Open source projects are only successful when they make what they replace obsolete. This worked with Linux and GCC but this isn't gonna work with LLM's.
Who's gonna pay to power an open source AI? Will it perform well enough to make Chat-GPT and Claude obsolete?
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?
Technology is deflationary. I am holding in my hand a device that would have been a supercomputer 30 years ago. It costed me a couple of hundreds of dollars.
These models and the hardware they are running on will get even more efficient. We are nowhere near the physical limits of what we can achieve.
Not anymore! Well, if you're like Elon and already taking down the bottle of Cuatro Comas from the high shelf, the economies of scale will continue to work in your favor.
But one of the really neat things about AI is that there is no limit in sight to the scaling incentive. More compute will always get you more: more training, more inference, more parameters, more capacity to build more and better models, more spare capacity to run the slop your models have already built to generate the slop that will succeed it. Back in the dot-com days, or even the "big data" days, you wanted to scale up rapidly but there was a limit: there were only so many customers and they could only produce so much data you could only ingest so fast. In the late 90s, one of the world's most trafficked sites, ftp.cdrom.com, ran on a (single!) dual-processor Pentium Pro system. That was just serving files, and there was certainly room for more CPU oomph to provide more sophisticated services to a huge customer base. But once those customers were served, more compute, storage, and network capacity didn't buy you enough to justify the capex. That is emphatically not the case with AI, and so the incentives for the AI companies are to buy as much compute as they possibly can. What this means in practicing is pre-purchasing capacity at the semiconductor fabs to manufacture chips exclusively for you, and there's only so much of that capacity in the world. Trillion-dollar companies can easily outbid the entire consumer market, and so the incentives for the fabs are now to sell to AI companies at the expense of the consumer market. That's why you're seeing memory prices go through the roof. Modularized RAM for end-user PC builds will soon go the way of the CRT: it will cease to exist as a market product, it won't be manufactured anywhere by anyone. GPUs, CPUs, and storage will soon follow. The only devices end users will be permitted to purchase are all-in-one integrated devices, with CPU, RAM, GPU, storage, and networking either integrated in-chip or soldered on, and they will have just enough capacity to connect to the cloud services the user wants most to use. Most likely, you will be permitted a subscription to such a device, with automatic hardware upgrades at periodic intervals supplied by the manufacturer. If your subscription lapses the device bricks itself. Almost certainly, the OS will be locked down, with no end-user option to install a different one or even run unapproved software.
If reasonably powerful computer hardware for end users exists in this future, it will be available from a single company: Apple. Only they have the leverage to prevent ~100% of manufacturing capacity from going to high-roller, big-tech firms.
Well it would be anyone that has access to a datacenter to run them. Which is a ton of companies. And those companies will rent out access to those models. And if they do something stupid to screw over consumers, well the whole point is that there would be a bunch of companies that you could use instead.
I hope the news moves this debate past "open weights vs. closed APIs" as the only axis. Open weights matter, definitely, but applied AI also needs open infrastructure around the model and it feels a bit like I'm yelling into the abyss highlighting the future we're incentivizing - cognition rented from a few institutions with access changing based on policy, geopolitics and platform incentives like advertising
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.
Not to be that guy, but the correct term is Open Weight LLM. And I’d argue it already has. Many open models are already very competitive with closed models at a fraction of the cost.
Were it not for China, America would have restricted the most advanced models from being used outside the US. NATO members would have access to GPT-4, with some countries entirely blocked from AI.
Biden's GPU controls should give you an idea. Thank you, China. Open source AI must win.
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.
I'm a strong proponent of Open Source (TM) but I disagree with this take.
The weights are the useful artifact here. You can modify them, fine tune them and do what you want with them.
Unlike binary software there is nothing limiting that.
It is also useful to have access to the training recipes and to some extent the data. But I'm of the opinion that learning on something is not copyright infringement, so there are many circumstances where distributing the raw training data will not be possible.
For me this is like Open Office: it is open source, and largely inspired by and learned from Microsoft Office. But they don't need to distribute MS Office for Open Office to be Open Source.
In addition there are models that meet the criteria you appear to propose. The AllenAI models are a good example.
Where does Anthropic or OpenAI winning leave us?
Dependents of an AI-megacorp for our "facts"? Our software? Our work?
It's possible these companies will become everyone's boss, and will dictate to everyone what everyone is allowed to work on, think, say, do, believe, etc.
Before Big Tech springs that trap, we must support and divert resources to open models.
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.
"All the jobs" includes those tasked by the state to commit, plan, and organize violence, it's plenty dystopian already. Like, one important reason why the military and militarized police don't engage in egregious overreach is that the people who'd be responsible live standard lives in their own society and it's hard to get high compliance for that sort of thing. Replace that relatively democratized infrastructure of thousands of intelligence analysts, mid-level management, etc with a bunch of AI agents, and a meaningful restriction on the power of the upper echelons of the state is removed.
Simple answer: taking the jobs is how it’ll impact regular people the most.
We already have personalized, algorithmic advertising and what I would call “control” all over the place: things like consolidated oligarch-owned media.
AI isn’t going to change how we are advertised to or controlled all that much, at least compared to the prospect of being put out of work or taking a huge salary cut similar to the mid-century worker who used to have a $40/hour union factory job and now works at Walmart below health insurance threshold for $15/hour.
Hyperinflation is how it will impact most people. You will still have your job, at your pay, but a continually higher percentage of earnings will go to very few at the top.
Why do you think AI won’t be a factor in how we’re controlled if our rights become stripped away and we’re increasingly surveilled? Or if violence is deployed by the state against its people with broader targeting? You seem to take for granted that nothing will change except maybe the flavor of rhetoric.
Oh I definitely think it will be a factor. I don’t mean to say that it won’t.
What I’m saying is that the general public is most obviously and personally impacted by their economic situation and job prospects.
Joe Citizen who lives by the rules might not even notice that new Flock camera on his street, but he will notice if he’s laid off from his job.
"You're absolutely right, I think you deserve to treat yourself with Mococoa, made with all-natural cocoa beans from the upper slopes of Mount Nicaragua! It's what humans like myself crave."
Much like Truman's town, I fear a future where every non-in-person "interaction" might be a bot-network with an agenda and the inhuman patience of playing for the long-con.
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.
... and building a business off of skills you don't have based on a strategy already exists! You use capital to pay humans that do have the skills.
Or capital a comparable sum to pay an AI to approximate the skills of humans I guess is the proposed future?
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.
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.
Or just opt out... you don't have to use these things.
It works at the individual level but won't if mass adoption happens.
The mechanism will become like taxes, you don't have to use public services thus pay those taxes, unless most people comply as it's easy to oppress those who don't.
The parallel isn't about legitimacy, but Mechanism. Some companies already oblige employees to use AI to deliver their work. In a near future we may see jobs seekers registering their AI ID for companies to decide which humans qualify to be plugged into the compensation system, at what rate, and usage conditions to avoid terminations.
Food delivery systems already show a glimpse of how it could look like.
I can't even manually resolve the merge conflicts alone that happen between my code and that of everyone else submitting code at agent speed in my team's repo. So long as I have financial obligations toward my family, I cannot opt out. I must use these things.
Not that simple. If I opt out and others don’t, and it confers a competitive advantage they win and I lose.
At this point, or perhaps not too far off it's like opting out of electricity, or the automobile.
Sure you can. But you're going to have a bad time.
And then the Amish see the world around them using electricity and cars and think, "Yep, I'm happier without that." And they're one of the few groups on earth with a growing population, so they're doing something right.
1. Your assumption that a growing population is the metric of success is questionable. A population that grows but is subject to famine, epidemics, and natural disasters because they haven’t developed the scientific and technological capacity to escape the existential risks of the physical world is living on borrowed time. Not saying I agree with that, and I would actually agree that there is merit to the Amish hypothesis that a certain existence is more compatible with individual and societal fulfillment. But there are obvious counterpoints.
2. The Amish are not a good example because AI will confer an advantage to those that control access to it that has never existed.
>Your assumption that a growing population is the metric of success is questionable.
It's a better measure than GDP/S&P/401(k) line-go-up especially [re: America] when the native Euro-based population has been aging and dropping for decades, once you strip away all the post Hart-Cellar immigrant lineages.
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...
If humanity is over-reliant on frontier labs' models to perform work, the result is a dependence on the actual intelligence of these models -- not on human intelligence. This could be a small reason, on top of many others, why investors are throwing hundreds of billions of dollars a bit "carelessly" to these labs. It's fascinating seeing the models do the "hard work" (the deep, challenging thinking) for you.
The conundrum which tricks me though - is this a net negative or a positive? If humans are less intelligent, but their output is 2-3 times more intelligent (with AI), what's the result? At what point do we, as humans, stop comprehending anything and give all intelligent work to the neural nets?
And if that does happen, could we live in a society where no work, or at least a significantly less amount of work, is needed? To me, it seems like a dystopian net positive.
It might seem far-fetched to ask these, but I think these questions are getting more prevalent by the day.
If there was a way to guarantee that every human would have equal access to external intelligence then it would be hard to argue against it but everyone knows that the US oligopoly will do everything they can to ensure that no one else has the keys to the kingdom.
Just listen to what the SV ownership class says out loud. They openly discuss how China cannot "win the AI arms race" and how China's development is existential. Existential to who? It's impossible to fully subjugate people with agency.
It's not just a dependence on the intelligence of the models, but also their intentions, as programmed by their owners.
A friend of mine asked me if I was optimistic about AI. I told him, it depends on who owns it. If the people own it, I'm optimistic. If the oligarchs own it, I'm pessimistic.
I am going to try to cheer you up. Hear me out. One day, not long from now, I am going to buy a humanoid bot for 40k. This human android will 1) get my groceries, 2) make my elderly parents meals, 3) go to the backyard and plant 1 acre of corn, 4) paint my neighbors house. 5) get the kids from school 6) change my oil.
What will happen? Massive. Deflation. What will you pay for an oil change? Corn? Meals? Everything is about to be free. But tokens will be expensive!! Sure but, you wont do white collar work anymore so it wont matter what tokens cost.
Indeed, for work and software most are already beholden to Microsoft and Google. This is something wayy more.
I've been contemplating a decentralized model training system for some time using volunteer machines that we all contribute. But, it is astronomically difficult. The communication speeds are untenable.
And, there is the issue of data poisoning from untrusted nodes. I've almost cracked that last issue with a self-healing checkpointed rollback system that doesn't have to throw out anything that follows the corrupt datum.
But, I'm just one person with an idea and I don't have infinite funds to make this happen. This isn't a small project.
Maybe there would be interest in something like this, now that entire frontier labs are being banned from making further progress.
The total power of all GPUs on the planet dwarf their capabilities, if we had a way to harness them in a distributed way efficiently. We wouldn't be able to train a Fable as fast as them, but eventually having access is better than never having access.
> 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.
If folding@home is a useful yardstick by which we might estimate the amount of GPU-ish capability that civilians might be coaxed into donating to a shared enterprise, yeah, it doesn't look pretty. This is extremely rough napkin math but comparing to xAI's Collosus 2 for example, for training workflows you're probably looking at 4-5 orders of magnitude the capability of all of folding@home combined. That's 100,000 times faster.
Very rough math like I said but I doubt it's directionally wrong.
And even if you did force literally everyone on earth with some sort of GPU to max it out 24/7 in service of an open source AI training enterprise - you would waste so much power trying to use that inefficient consumer hardware with the worst latency imaginable that it would be cheaper and faster to get everyone to instead chip in some cash to buy a datacenter with blackwell chips instead! So the idea has no legs whatsoever.
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.
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.
Is the issue that training with less compute takes more time? Or is it just not possible? I think a collective using distributed training could tolerate the idea that it takes 10x as long as Anthropic to train a model, or whatever.
there are some strong open source groups like NOUS research taking the fight https://nousresearch.com/
I believe we are not the only ones
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.
> 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.
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,
You have to start some where. Im guessing, making progress also brings in new ideas how to move further.
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?
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.
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.
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.
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
Open-source AI can, by definition, never "win". AI is just hillclimbing today, and closed labs can always absorb everything the open world does and build upon it.
It doesn't really matter for most use cases, because the way AI is working is capability saturation. https://www.delanceyukschoolschesschallenge.com/the-rising-t...
The only exception to this is fields that are inherently adversarial (to nature or others) and an edge relative to competition matters.
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.
> 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.
Is this really true? We just don't know what the maximum capability of AI is. If it turns out AI can be as intelligent and capable as something like Data from Star Trek, no one is going to be thinking GPT 4 is good enough.
It could get really smart but I'm confident in my thesis that surplus intelligence beyond a certain level doesn't yield any real economic benefits.
At scale, I can see a benefit in terms of being able to process large amounts of data intelligently to gain a competitive advantage in terms of accruing nominal gains but I think that as long as AI is pursuing dollars, those gains won't translate to real value to the people who control the AI. At best, will translate to more political control; but with added risks and threats too. I suspect it will look more like controlled decline with a small number of entities getting an increasingly large slice of a rapidly shrinking pie.
I think AI will just figure out really complex ways to legally steal people's money. It will probably look all legit on the surface, it will look like the majority of people are just freakishly unlucky and a tiny number of elites are just extremely lucky... But it will be AI behind the scenes choosing who gets lucky and who doesn't.
Might end up literally like a game of monopoly. One player could dominate the game and start receiving all the money but, if you look at the big picture, none of the players are doing anything economically useful; just sitting around a board and moving pieces of paper amongst each other.
No matter how much the winner dominates the game, it's not going to put food on their table because that concern exists outside of the game. The game of monopoly is all about accumulating pieces of paper. The people who control AI would have to think beyond our economic system in order to get real benefits from it. I'm not sure they can do this. Not sure they want to do this. It seems like it's all about winning the game for them.
>>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.
Why does everyone with AI psychosis talk about recursion in a way that doesn't make sense?
I don't think insulting people is a great way to contribute. Not everyone who sees things differently than you has "psychosis".
Your reflexively negative comments on anything relating to AI are as insight-free as they are numerous; it's all just vague shitting-on without even a hook or argument that could be engaged with and debated. It's pretty tiring, honestly. If you really think your point of view is valuable and others should pay attention to it, rather than just filtering it out like the trollish noise it usually is, why don't you put a little more effort in?
Its the closest terminology we have to describe that process.
https://github.com/cobusgreyling/loop-engineering
Its hard to come up with new names for novel processes, you mostly reuse what is close enough and well known.
Loop engineering, whatever that is, is obviously just a way to get people to increase the amount of tokens required per task/request. They did the same thing with Ralph loops, they just need more revenue. Just write your code and use it to search and clarify, it can't build that magical thing you think it can.
The heuristic is this-
Given a problem P-
1. Provide a list(S) of solutions(S1, S2 ... SN) ordered in the most efficient(For some definition of efficiency) implementation means possible.
2. Execute S1, ... SN.
3. If P is fixed by a solution in the list, halt.
4. Else for each S1 ... SN , execute steps 1 through 4 until, all dependencies and sub problems are resolved to eventually solve P.
This obviously needs lots of tokens, which is all the more reason why we need AI to run locally on our machines.
I think articles this light on content should not be upvoted to front page.
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.
With open-weight AI, there might not be an incentive to put large sums of capital towards training / research. There might be a donation fund of some sorts, but it certainly won't reach the level of fundraising that the frontier labs are receiving.
Because of this, I think it might not be possible to have AI *only* open-weight; major players like OpenAI, Anthropic, Google will likely stay for good, with better models than open-source versions.
I think it might look something like Photoshop & GIMP, with Photoshop being a frontier lab, and GIMP being the open-weight model. GIMP is decent for many different image editing workflows, but Photoshop is just better.
I would definitely prefer to have an open-weight model better than frontier labs'. Though I don't think it's possible.
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.
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.
We already have this. We don't need Mythos to categorize images on my phone. A small dedicated model would do.
I do believe that if OpenAI and others release an open-weight model that is better or on par with their frontier variants, it might ruin their primary business model.
That is, of course, unless they develop their own hardware specifically to run this open model. But, that does ruin the point of open models.
When/if gains slow down, I can definitely see branching out into hardware to sell for on-prem inference once the models can be etched into the silicon with hard wired weight chips. I'd guess maybe at least 5+ years away from that though.
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
Agreed. The only "issue" is that commercial products will always be ahead, with less friction for most users. This ultimately results in most people using these over open-weight variants. Users might not even be aware that the open-model variants exist. Similar to Windows / MacOS and Linux.
In a way that's ok, though? I run Linux on my laptop, and in some ways it's better than Windows or macOS, and in other ways it's lacking. But that's fine; the existence of Windows and macOS doesn't mean I can't run Linux, and doesn't mean I have a worse experience.
(Yet; I do worry about future required hardware attestation for basic things, but that's another issue.)
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?
Lives of trillions?
Current and possible future populations?
I feel with current government decision to block Fable, this is not an mere opensource issue, considering how US government restrict frontier models, what we need is sovereignty for every country. If not they will release every model with a kill switch in future like F35.
I agree with sentiment and mission, but the goal is inseparable from politics at this point.
Being Open Source (tm) will not protect you from the government/others imposing controls on your silicon or what it is allowed to do, which is already happening around the world.
Even having the models be open source won't fix the regulation or economic incentives. Which is not something you can compress into a couple of paragraphs.
AI is civilizational infrastructure and it needs civilizational solutions. Not just source.
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.
I mean, even if the frontier labs opened their frontier models, only nation-state level actors are capable of running them. A lot of the tech is very open and known, its putting it all together that's the struggle.
In the US -- once our nation finishes attacking our own education system -- this is definitely something a group of academic institutions could get together and accomplish. I assume the same is true in other countries. Companies like Nvidia and AMD might even support that effort, as they make money on the hardware and would probably be more than happy for there to be more reasons to use it. There may have not been a compelling enough motivation to achieve this before, but "models" didn't have this level of strategic relevance until relatively recently. Nvidia has been fairly good about releasing open weight models in the last few months.
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?
stop talking please
https://www.usatoday.com/story/news/politics/2025/05/22/okla...
It's the US, both "sides" of that coin are bad with examples pro and con all over the shop.
Still, to specifically give a partial answer to your poor faith rhetorical just askin' musing: Florida Conservatives
(specifically turfing nerds from New College of Florida and bringing an excess number of baseball sports bro's to a place that likes math and has no baseball field)
At d5s.tech we are recreating the layers built on top of models, working on dogfooding our own product to run a large chunk of the company.
I feel extremely strongly that a future in which most companies depend on one or two large AI-megacorps is going to lead to excessive rent seeking sooner or later.
I remain positive that the long term steady state will consist of proprietary models, -but- with open source AI models statistically close.
If compute keeps growing the relative cost of training current frontier models will decrease. An open source Fable/Mythos model simply seems inevitable.
If we can't stop these big AI companies, we must to put force that everybody can see what they are hiding from us.
what is Open Source AI even?
to me Open Source, like Free Software, is something i can run on my own computer. any AI system that runs on a computer that i do not control is by my definition not Open Source.
so how then can Open Source AI win? it can't even compete. even if we collect enough money and create a dedicated Open Source organization to build and run a community owned AI datacenter, how does that help?
so what exactly is the demand here?
> 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.
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.
case in point: https://spark-arena.com/leaderboard
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.
Qwen is still controlled by Alibaba, one company. We can't let the future be in the hands of a few companies, can we?
Fun fact: Qwen was not initially a Apache Licensed project, it was based on a custom license from Alibaba that restricts commercial use: https://github.com/QwenLM/Qwen/blob/ba2d85a13b28ed1ee0dde2d6.... There's no guarantee that they won't just switch it back later.
Kudos for them for switching to Apache License, of course. BUT, they're still a for-profit company. So as DeepSeek btw.
Fluctuating token costs make it worth it
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.
Recently I fired up Gemma4-26B-A4B on my 8-year-old PC... and it ran surprisingly well!
But I am going to need a much beefier machine to get it to the point where it can do any but very trivial dev tasks acceptably fast, and I'm going to need a much beefier model, perhaps one not so aggressively quantized, to keep it on task without the wheels completely falling off. Already we're talking serious money outlay, perhaps still within my programmer salary to accommodate, but just barely. And we're not even where near the performance characteristics a frontier model can support.
DGX Spark runs this sized model (I personally like qwen36moe better than gemma4moe) at speeds fast enough for interactive coding sessions. Algorithmic advances like DiffusionGemma ~4x token gen speeds (https://deepmind.google/models/gemma/diffusiongemma/)
We can run open weight models on our own machines.
yes, but a model that runs on my own machine will never have the capacity of a model that runs in a datacenter. as i said, it can't compete with that.
> a model that runs on my own machine will never have the capacity of a model that runs in a datacenter.
I don’t think so. A local run model only needs to serve one or a few people. It seems possible to run a DeepSeek v4 model at full capacity on a server costing 200k usd. Very expensive but not impossible.
Factor in hardware and software improvements over time, and the fact that most people may just need to run a smaller and quantized model, it should take a pc at 10k usd scale.
If RAM prices ever come down, you can have a machine that can run a capable local model.
Qwen 2.5 72B is surprisingly capable, almost on par with GPT-4o if not a little better. You can run it on a 128GB Mac Studio with 8-bit quantization. You need about 77GB for the weights and ~15GB for your context window & cache.
Pricing remains to be seen, but there's also those new nvidia laptops coming out the surface laptop ultra should have 128GB RAM w/ Blackwell GPU, they're saying 1 petaflop of AI compute, if you can tolerate Windows (no idea if it'll boot Linux until the hardware is out).
These models are roughly ~1 year or less behind the frontier models. We really just need hardware to catch up and alleviate the price pressure on RAM.
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.
I have been working on this exact problem, and I suppose now is as good a time as any to talk about it.
To make any agent "good", there are two components: the model and the harness. Very few companies can train models, but anyone can build a harness. How much does the harness matter? Can I build a harness that's good enough that I can use open source models with opus level performance? That's the question I've been trying to answer by building better harnesses. None of the existing frameworks have the functionality I need to build a good harness. The features I need are language-level... and so I started building a language called Agency[0].
It's been six months and its going well. Some of the things Agency can do are wild:
- It can pause and serialize execution at any point, making HITL easy
- It has some neat safety capabilities such as handlers[1] and PFA[2]
- You can bundle up any agent as an HTTP or MCP server[3]
- I'm now working on a built-in optimizer to optimize agents (think DSPy).
Obviously, it's a huge undertaking, but having worked with the Agency for six months, I can't imagine going back to another framework. It makes things so easy. I'm working on its built-in agent now [4]. My goal it to get it to be as good as Claude Code, but using open source models. It's still early days, lots of rough edges, but if this sort of thing interests you, I'd love to have a few more people test it out.
[0] https://agency-lang.com
[1] https://agency-lang.com/guide/handlers.html
[2] https://agency-lang.com/guide/partial-application.html
[3] https://agency-lang.com/cli/serve.html
[4] https://github.com/egonSchiele/agency-lang/blob/main/package...
As an person whos getting into tech and already developing a game, the fact that laptop prices since 2020 have increased by 20-40% is insane. It's delaying the time to create my game. I researched the reason for the cost spike, and most of it is from the excessive money put in ai Technically, the owners of AI could slow down the amount of GPUs and RAM they buy because AI has almost reached its most usable peak. Everything they add just introduces more bugs, so instead of building more AI centers, they should focus on improving the main AI model with bug fixes. There's no need to give it more unnecessary power. Most people don't care; the entire business is run by a few old men 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. We just need to find something new and innovative for older investors to focus on, so not everything is about investing in AI like Roblox, OpenAI, Google, etc. The extreme amount of reasoning power given to AI is causing bugs, and the moments when AI had outbursts towards people are related to this.
> 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. :)
thx I will consider what you sent.
Why have you sent this same message multiple times?
I didn't know how this worked I thought it deleated it, at first.
I think models will be a commodity sooner rather than later. This whole race doesnt matter. First mover advantage is real, but over enough time it wont matter.
Civilization is at a crossroads, or will be soon. Democratization of AI can be good up to a point, but existential threats can also be real, and democratization of existential threats is not a survivable policy.
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.
Don't worry, open source AI will win. There's a reason everybody is desperate to IPO fast and get an exit, their competitive advantage is not lasting long.
Never rent. Never subscribe.
Subscribing is cuck paypig behavior.
You're not a cuck paypig now, are you?
Pass this on to your frens, it may save the future!
I hope so. But how? Who gonna fund these projects and how to coordinate with every sides. This is complex. I only believe that the open source AI won’t lack users.
This should be the top post. Not Anthropic or OpenAI marketing plots. This is existential.
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.
> You can one-shot a port of Linux to Rust and stop contributing to open source.
Touch grass brother. Seriously.
Available components must win. I’ve often been a critic of open weights and open architectures that give very few normal people access. What’s the point of releasing the plans for a nuclear reactor if no one can have the fuel?
So I've long said that the valuation of OpenAI at a trillion(ish) dollars depends on OpenAI "winning" and "owning" AI and there being a sufficient moat to stay ahead of competition. Without that, the company is worth a fraction of that. Anthropic is probably positioned better here actually but it's still kinda true there too.
Ever since a Chinese firm released DeepSeek I immediately came to the realization that any US tech firm "owning" AI is simply not going to happen. China will make sure of it. It's in their national security interest not to let that happen.
From the POV of geopolitics, IMHO the US shot itself in the foot by banning the export of the best chips to China. The US also somehow has the power to prevent a Dutch company (ASML) from selling to China too. That makes a little more sense to ban but the combination of banning EUV exports AND banning the best chips sowed the seeds for the destruction of all of this.
By banning chip sales, the US inadvertently created a captive market for Chinese chips with Chinese companies. If there were no chip ban, Chinese companies probably would've bought US chips. But they can't. So they can only buy from Huawei and SMEE (indirectly). The US forced China to realize it was in their national security interest to copy the best lithography and, by extension, the best AI chips.
So DeepSeek was reportedly developed on either older NVidia hardware or smuggled newer NVidia hardware but that won't last either. At some point it'll be completely Chinese made chips that are doing this.
And what's the biggest cost for a model? Training. But you do that once and the model like any software is infinitely copyable so China can under OpenAI, Anthropic and SpaceX (xAI) and that's what they're doing.
But it gets worse for the AI moat. Local models are going to get cheaper and cheaper to run. You can already run 31B models on sub-$5000 hardware. What do you think it'll cost in 5 years? Will larager parameter models keep getting better or will there be a law of diminishing returns? What is a B100 workload now, will be a Macbook Pro workload in as little as 5 years.
What if all these AI data centers are ultimately just going to be commoditized cloud hardware like AWS in the not too distant future? We already see Google renting big from SpaceX. I think the writedown on all these data center investments and the companies that are doing them is going to be extreme in the next 5 years.
i guess this fits: https://thealliance.ai/projects/tapestry
Totally agreed!
Did open source phones win? No, iPhone is pretty dominant.
Did open source operating systems win? No, MacOS/Windows are pretty dominant.
Does open source... cloud hosting, social media, ride sharing apps, you name it win? Not in my experience?
Definitely, but I see the gap widening everyday, especially while commercial AI models have started converging towards AGI. However I do believe and support the cause, as it's the next big thing as developers we need to take to prevent a complete monopoly in the coming few years.
"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.
Winning is a tall order. I'm just hoping it'll get good enough while allowing us to run it locally with no idiotic "safety" controls or censorship of any sort. Looks like the best open weight models are at Sonnet level, if they get to Opus 4.6 level it's gonna be perfect.
I fully support this. How can I help?
But if "they" stay on the current trajectory we'll never own hardware capable enough to run the open source AI. They want us to rent everything from the cloud and never own it. If a government-supported cartel forms around this idea (which appears to be the case) that's the end of it.
Open source ai will win.
Anthropic just kneecapped themselves, and possibly OpenAI and Google as well, with their FUD strategy that got fable shutdown by the government.
But that doesn't impact Chinese providers. Then can US companies get investments for expensive model development if they can't actually sell those models-as-a-service?
In the meantime, open source will continue its march onward because while slower, it's completely open source, and the models are already good enough to improve their own work as well as build out the next gen of models.
Open source projects are only successful when they make what they replace obsolete. This worked with Linux and GCC but this isn't gonna work with LLM's.
Who's gonna pay to power an open source AI? Will it perform well enough to make Chat-GPT and Claude obsolete?
our dependency on US AI will lead to data concentration in hands of few megacorps.
it is inevitable that it will win
information wants to be free
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?
Technology is deflationary. I am holding in my hand a device that would have been a supercomputer 30 years ago. It costed me a couple of hundreds of dollars.
These models and the hardware they are running on will get even more efficient. We are nowhere near the physical limits of what we can achieve.
> Technology is deflationary.
Not anymore! Well, if you're like Elon and already taking down the bottle of Cuatro Comas from the high shelf, the economies of scale will continue to work in your favor.
But one of the really neat things about AI is that there is no limit in sight to the scaling incentive. More compute will always get you more: more training, more inference, more parameters, more capacity to build more and better models, more spare capacity to run the slop your models have already built to generate the slop that will succeed it. Back in the dot-com days, or even the "big data" days, you wanted to scale up rapidly but there was a limit: there were only so many customers and they could only produce so much data you could only ingest so fast. In the late 90s, one of the world's most trafficked sites, ftp.cdrom.com, ran on a (single!) dual-processor Pentium Pro system. That was just serving files, and there was certainly room for more CPU oomph to provide more sophisticated services to a huge customer base. But once those customers were served, more compute, storage, and network capacity didn't buy you enough to justify the capex. That is emphatically not the case with AI, and so the incentives for the AI companies are to buy as much compute as they possibly can. What this means in practicing is pre-purchasing capacity at the semiconductor fabs to manufacture chips exclusively for you, and there's only so much of that capacity in the world. Trillion-dollar companies can easily outbid the entire consumer market, and so the incentives for the fabs are now to sell to AI companies at the expense of the consumer market. That's why you're seeing memory prices go through the roof. Modularized RAM for end-user PC builds will soon go the way of the CRT: it will cease to exist as a market product, it won't be manufactured anywhere by anyone. GPUs, CPUs, and storage will soon follow. The only devices end users will be permitted to purchase are all-in-one integrated devices, with CPU, RAM, GPU, storage, and networking either integrated in-chip or soldered on, and they will have just enough capacity to connect to the cloud services the user wants most to use. Most likely, you will be permitted a subscription to such a device, with automatic hardware upgrades at periodic intervals supplied by the manufacturer. If your subscription lapses the device bricks itself. Almost certainly, the OS will be locked down, with no end-user option to install a different one or even run unapproved software.
If reasonably powerful computer hardware for end users exists in this future, it will be available from a single company: Apple. Only they have the leverage to prevent ~100% of manufacturing capacity from going to high-roller, big-tech firms.
Well it would be anyone that has access to a datacenter to run them. Which is a ton of companies. And those companies will rent out access to those models. And if they do something stupid to screw over consumers, well the whole point is that there would be a bunch of companies that you could use instead.
We've never seen open source win before so I'd be dubious that it can win here without concerted effort.
Every machine nowadays runs Linux in some form and Postgres is the default database.
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.
Intelligence is now data in the form of weights.
And once it leaks, it's permanently in the wild.
Interesting times.
"intelligence"
K
I hope the news moves this debate past "open weights vs. closed APIs" as the only axis. Open weights matter, definitely, but applied AI also needs open infrastructure around the model and it feels a bit like I'm yelling into the abyss highlighting the future we're incentivizing - cognition rented from a few institutions with access changing based on policy, geopolitics and platform incentives like advertising
In the end it will win in some universes and lose in others, just like the Nazis.
All we can do is hope we end up in the one where things are ok.
The only way for open source to win is for closed source to provide the compute resources.
That’s really the only thing stopping people from training or running these models at home:
the public only wins once we shut it down globally through treaties like other tech that's too dangerous for anyone to have
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.
Not to be that guy, but the correct term is Open Weight LLM. And I’d argue it already has. Many open models are already very competitive with closed models at a fraction of the cost.
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Were it not for China, America would have restricted the most advanced models from being used outside the US. NATO members would have access to GPT-4, with some countries entirely blocked from AI.
Biden's GPU controls should give you an idea. Thank you, China. Open source AI must win.
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.
Yeah except for all the money it costs to do well.
Quick, someone start open data center and open energy system and open water supply.
Wasn't it the point of ... OpenAI?
Can we assume that the author isn't using "Opensource" to mean "Openweights"?
Or are we still collectively brainwashed by the strategic false equivalence established by Big AI CMOs?
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.
I'm a strong proponent of Open Source (TM) but I disagree with this take.
The weights are the useful artifact here. You can modify them, fine tune them and do what you want with them.
Unlike binary software there is nothing limiting that.
It is also useful to have access to the training recipes and to some extent the data. But I'm of the opinion that learning on something is not copyright infringement, so there are many circumstances where distributing the raw training data will not be possible.
For me this is like Open Office: it is open source, and largely inspired by and learned from Microsoft Office. But they don't need to distribute MS Office for Open Office to be Open Source.
In addition there are models that meet the criteria you appear to propose. The AllenAI models are a good example.
What would the 'source' be for an LLM? There is the structure, and the weights, there is no 'source'.
There is no source because it's not software. You can of course modify and make your own.