We really need to band together to fund / sponsor targeted inducement prizes (a la Nobel laureate Michael Kremer) for open models.
Every 6-12 months, give out $200K to the first model to hit a min threshold on a set of ~5-10 hard benchmarks (+ perhaps one secret benchmark) using a total of 16GB / 32GB / 64GB / 128GB of VRAM (at a min context length of 200K), then move the threshold up. Quantization etc. is dealers choice, it just needs to nail the benchmark on a reference machine by using exactly that much VRAM (no mapping to RAM / disk etc.)
You could crowdsource the funding, and cross subsidize by adding targeted prizes focused on corporate needs (the classic one is PDF processing benchmarks), and say that 25% of each corporate prize funding also flows into the general prize pool.
For a lot of these open-source model companies, it's less about the $s (though $200K is nothing to sneeze at), it's the clear recognition that helps their model efforts stand out, gain usage etc.
I think the Korean government did have a competition like this, I remember last year we got a bunch of models released at the same time to make the cut for the next stage. The models weren't anything to write home about, IMO.
Having it with clear hw requirements tiers is a nice differentiator. The only issue is that the benchmarks would 100% need to be closed, no other way around it. And then you have the issue of creating and curating good evals for every "stage" of the project. That's a hard task even for "honest" lab-internal evals. And you'd have to publish those evals after each round (for trust purposes), and start over for the next round. Doable, but it would cost a lot (probably more than the prize pools) and you'd have to keep doing this.
It was a competition organized by the Korean government but the directive wasn't for the same cause as the writer. It was more for constructing Sovereign AI for the country. Also, all models except Exaone had some weights copied from Chinese models, and from the corporate point of view, developing from-scratch model is not cheap despite the financial support from the government.
Yes, I hope the open model communities will someday be able to run current frontier models which will be able to handle autonomous tasks and the hardware to run it will be served at consumer level; however, like how recycling isn't profitable, no companies will fully commit to the movement. Don't get it twisted, I don't have a solution but maybe a global scale movement to liberate knowledge-library could suffice.
This seems like a good idea but also just fun. I can’t train a frontier model but maybe I could compete in the 16 GB tier. I would suspect there are a ton of optimizations out there for the taking that aren’t being considered because frontier models are way above these weight classes
The private AI companies should be forced to release the models as open weights with a license (I.e no commercial use) due the high risk they present and the data they basically steal from everyone to train their models.
This should be the safety push not the regulatory capture that Dario is trying.
All I see if a bunch of people who haven't loaded an ad in 20 years and have a 5TB collection of pirated movies and music suddenly decrying that LLM's doing next token prediction over a dataset is theft.
You don't get to change your mind 20 years into "I'm never going to pay for anything binary" ethos (cough look at what this post is cough) that has dominated the internet for decades. If people are genuinely upset about LLMs training on all available data without compensation, all I can say is "Reap what you sow".
It would be all fine and good if they kept it non-commercial, but when you start charging money for it that's when you're stepping out of bounds. If they want to benefit from fair use, they should contribute their results back to the public domain. Getting it for free and then commercializing it is what's unethical.
>Getting it for free and then commercializing it is what's unethical.
Like all those unethical software devs taking salaries for turning stackoverflow into products? I suppose the blood still flows since now they just use LLM output?
Any way you try and slice LLM morality, you end up with "It's bad because they are not me" reasons. "When I monetize information I get for free, it's good, when they monetize information they get for free, it's bad"
Ok then can the feds bust the executives of these companies like they did with Kim Dotcom? It’s not like Dario trained his AI in the bedroom or do a small business by letting people scrapping IP work to train their models. He is actively stealing and selling the stolen work and even preaches us safety measures: how to protect us from our own knowledge that he stole!
It is kind of incredible that you're not focused at all on the copyright holders, instead focusing on random tech people you had online disagreements with.
Artists and writers got screwed first by piracy, then by generative AI. They didn't sow anything. They just got reaped.
And the only thing the copyright hypocrites are "reaping" is a feeling of hypocrisy. Congrats for pointing that out. Your comment is simply myopic.
> Artists and writers got screwed first by piracy, then by generative AI.
That's too glib. Artists don't have a right to money that people won't spend.
It's not all down to bad actors. Although it's true that
musicians got screwed when their distributors switched to a subscription model. Writers got screwed by the Amazon monopsony that crammed down publisher's margins.
Mostly what happened is that media technologies changed, professional creators had less control over production, and the money flowed upstream leaving them with a smaller niche.
All of their output used to be gatekept by media companies who had a lock on publishing. The internet reduced distribution costs to zero. Suddenly anybody could reach an audience.
Now generative AI has dropped the cost of content creation to the basement. It's so much easier to write a blog post or make an illustration.
That isn't cannibalizing content. It's a new way of making. It takes a lot of the value out of creating those kinds of things. The customer experiences this as a reduction in cost.
These changes happen with every new gadget. Photographers have to compete against everybody with a phone in their pocket. Now they just do weddings.
My grandfather was a portrait painter in the 1940s, a profession that was already moribund from the proliferation of photography studios. He gave up and became an insurance salesman.
Maybe he got screwed. The photography studios are all gone too. Because anybody can make a portrait using the phone in their pocket. At zero cost.
Agreed. Especially since now competitors have more difficulties getting the same advantage. They don't have to do so immediately and perhaps not their specific tuning. But the weights of the raw training data at least should be publicised.
Wow, thank you for this! I'd forgotten about enclosure for some years.
> The law locks up the man or woman / Who steals the goose from off the common / But leaves the greater villain loose / Who steals the common from the goose.
Don't buy the idea that the only thing that's standing in the way of people making bioweapons is the censoring of LLMs.
If you are motivated enough to assemble all the kit you'd need, and actually do it, then you should be motivated enough to find the knowledge to do it without chatgpt etc.
I'd imagine the main thing that's stopping people is biological weapons are a terrible tool to do what most people want to do - which is target specific enemies.
So while the materials you'd need to build such a thing are much more accessible than say nuclear material, it's much less attractive - but if already had somebody mad enough to try - it's already possible.
> Don't buy the idea that the only thing that's standing in the way of people making bioweapons is the censoring of LLMs.
It's not a matter of a one thing standing in the way of people making bioweapons: there's a long chain of actions one would need to complete, and many places for the chain to fail. Access to expertise can reduce the chance of failure at many of these steps, and AIs can increasingly substitute for human expertise: https://securebio.org/benchmarks/
> If you are motivated enough to assemble all the kit you'd need, and actually do it, then you should be motivated enough to find the knowledge to do it without chatgpt etc.
If someone was motivated enough to assemble the kit you need for anthrax and actually distribute it then you might expect them to also be motivated enough to find the knowledge to identify an appropriate strain, but in fact this is where Aum Shinrikyo failed in the 1990s: https://en.wikipedia.org/wiki/Aum_Shinrikyo#Incidents_before...
Lack of knowledge is one of many factors that can lead to failure, and LLMs make it less of a barrier.
> biological weapons are a terrible tool to do what most people want to do - which is target specific enemies
Except:
1. There are also people out there who want to kill everyone. They're sufficiently rare that no one with the motive has also had the means, but as technological progress keeps lowering the bar the risk of motive and means intersecting increases.
2. This didn't stop the Soviets. They did an enormous amount of very dangerous research with minimal logical application.
FOSS is the wrong analogy. Building frontier LLMs isn’t primarily an engineering discipline, it’s a scientific research program.
Of course we do have basically open source research programs, including most universities and big projects like CERN. But AI grew up in universities until it transpired that sufficient capital could only be found in the private sector.
It would be possible to make a decent publicly funded AI research program. But it would look more like the Manhattan or Apollo projects (which frontier labs already model themselves after) than some extra research grants for universities.
The Manhatten project cost about $40 billion in total adjusted for inflation. Anthropic's latest funding round alone raised $65 billion.
The entire Apollo project at the peak of the cold war cost about $300 billion in today's dollars. That's approximately what OpenAI and Anthropic have raised together in total until now.
I don't think governments can supply this amount of money for AI in the current political and economic climate. The LHC cost less than $10 billion by comparison and it was spread out over a much longer timeframe.
> I don't think governments can supply this amount of money for AI in the current political and economic climate.
I'm a believer in Keynes' "anything we can do we can afford". It could be afforded .. if there was a sufficiently good reason. And there isn't. This is way behind "governments, especially the EU, should have a sovereign cloud". It is also way behind "governments need to keep global warming below 2C by the end of the century" and "governments need to ensure affordable energy", objectives which the current AI buildout is in direct conflict with.
This is before we get into the question of whether AI has net positive social value in non-software use cases. Even in software the case for AI is explicitly job-destroying and raising electricity prices for everyone else.
The only reason AI research is in conflict with limiting global warming is the unholy alliance of NIMBYs and Sierra Club environmentalists preventing the building of anything, anywhere. Clean energy has beaten out fossil energy on cost for years now, and only regulatory burdens force datacentres to use portable gas turbines instead of standing up transmission lines to the closest solar or wind farm.
There are things you can't do - even as a society - when the costs start ballooning beyond the GDP of smaller European nations. I mean, yes, in an emergency you could cancel all social security and public infrastructure spending and instead dump it into AI. But even then it will take several big nations to foot the bill if you want to still have a country left after you're done. With the level of political heckle everywhere, this is just not going to happen, because it would need unanimous support from all sides.
What you are potentially missing is the public sector wouldn't necessarily be in the same race as the commercial companies.
It doesn't matter if a public effort is a year or two behind the curve ( and hence has dramatically lower costs due to Moores law and the ability to piggy back on research ) - especially as we approach the asymptotic phase of development.
> I don't think governments can supply this amount of money for AI in the current political and economic climate.
You understand how the system works if you’re thinking in terms of government/non-government. The current political and economic state is not a bug, it’s by design which serves a purpose.
Yes, if the US was modeled like the USSR they could extract 100% of everyone’s private assets and the politburo could spend them on whatever moonshot projects they wanted to, unchecked by silly democratic votes.
But…the USSR and that entire model failed spectacularly? So not sure what you’re getting at here. Is there some fantasy economic model you believe you’ve innovated that will lead to utopia and the end of resource scarcity?
Govts can take it over. Corporations dont maintain standing armies. So there is a pecking order that corps have never been able to invert. They rely on Govt for their own security.
History is full of these take overs if there is risk(usually happens after some catastrophe). See the finance sector(once upon a time private banks invented and printed money), nuclear industry, febrtilizer industry, crypto, a whole bunch of processes in biotech/synthbio. Classic textbook example is the East India Company. It was much richer that the British Govt or the King.
> But AI grew up in universities until it transpired that sufficient capital could only be found in the private sector.
One way of looking at it. Another is that AI research progressed within universities, but it was only until recently that the private sector saw the profit potential when combined with modern CPU/GPU technology.
You could argue we're saying the same thing, but I think these angles are different. An academic research programme would not have spent billions on a datacentre to provide AI for free to the general public, for example.
I agree an academic research program wouldn’t spend billions on a datacenter, but that’s just a reason why foss AI as described in this article won’t work - because big compute is required to do anything of real relevance.
They already invest in open-source AI, but nothing is truly free. Commercial AI will usually dominate because devs are paid to make it their primary effort. Goodwill and part-time contributions cannot reliably compete with livelihood and profit incentives.
That's what people said about operating systems, and databases, and compilers, and so many other big complicated categories of software that over time became increasingly dominated by OSS
OSS only dominates for software that is commoditized and the published computer science research for that software domain is close to the frontier.
OSS struggles at being relevant when software is non-commodity e.g. office suites. In software domains like databases where the state-of-the-art computer science research is often unpublished, OSS struggles to be relevant at the higher end of the market on technical merits.
When deciding what should be OSS, it is useful to consider the preconditions that have made it successful.
I personally expect token production to commoditized like mobile data. It's already happening.
See open weights gaining adoption, OpenAi talking about how 5.6 is cheaper than Fable, people are taking multiple approaches to reduce their token spend, expectations for progress in hardware and algos, and certain Ai leaders talking about how token prices should be 10-100x lower than they are.
LLMs are nearly commoditized already. I can switch between a dozen of them from four different providers as easily as flipping a toggle in my VSCode editor.
OSS does not necessarily mean the contributions are from "goodwill or part-time contributions". In fact, I would wager the most widely used OSS software is largely written by contributors paid to do so by corporations. At least for Linux, about 80% - 85% of contributions are from developers paid to do it (https://newsletter.pragmaticengineer.com/p/how-linux-is-buil...)
Corporations have had many reasons to invest their money in open source software -- custom requirements, marketing / developer mindshare, commoditizing complements -- but as cutting edge LLMs get more and more expensive to train, you'd be hard-pressed to find corporations who will put in that kind of money if they cannot recoup their investments.
I think the main problem in LLM models is that you can not make a PR to an open source project to tweak some training parameters, prove it is an improvement and merge it.
If you can not run the training yourself you can not contribute. So open source contribution model does not work. All examples you gave have a fairly low threshold of capital expenditure required to be a contributor (basically a laptop).
Even back in the 90s a person could get a standard, but powerful, PC to do these things. The one exception was 3d graphics which took quite some time to become affordable and even there it was a single one-time expenditure (a workstation) per contributor.
For normal OSS the only competition between contributors was for attention of maintainers to review and accept patches.
In an open-source LLM model contributors would compete with each other for computing resources for model tweaks and changes. The alternative model is that the contributor pays for the compute, but that increases the bar really high for contributions.
on the small chance that the four billionaires who currently have near-exclusive control of closed sota models, (that is altman, amodei, zuckerberg and musk), are not fleecing their investors and actually build AGI, closed source leaves a choice of powerful government or powerful oligopoly/monarchy.
further explanation of this list:
musk - structural command
zuckerberg - structural command
altman - de facto command after purging rivals and privatisation, loyalty of personnel
amodei - influential, could potentially overthrow current governance
Just because a software is closed-source doesn't mean the knowledge can't be shared. You don't need to see the underlying code to explain to someone architectural patterns or best practices.
The library analogy in the scenario would hold true if LLM providers refused to answer any questions about RL or Transformers.
I am a big proponent of open-source open-weight models, but mostly because I think it's just a better product. We've seen that they are much cheaper to train and operate. Frontier intelligence might not be needed for most tasks. Just let the market decide. My bet is that LLMs will become analogous to programming languages, and big labs will make their money by fine-tuning models for very specific use cases or by deploying them for customers.
“The economists need to start charting this out, if we are in a post scarcity world, how does everyone benefit from that?, obviously its not correct for just a few people or a few companies or even a few nations to be benefiting from this technology, it has to broadly accrue the benefits to everyone, but how is that gonna be done? We really need answers now. ” -Demmis Hassabis <Google Deep mind>
Listening to those pushing AI, why should we fund open source developers when we can reproduce their work with a few judiciously chosen LLM prompts? Perhaps the AI companies should fund FOSS so as to get more solutions to memorize but normals?
The library analogy works (for me), but the uncomfortable part is that most "open" models are closer to receiving a compiled binary than receiving the library
> Even if the current approaches will continue to scale, this would be as if in the early days of computing, perhaps someone invented a bubble sort for sorting numbers (an n-squared algorithm), and the tech companies at the time decided they were going to build vast data centers to sort numbers and not bother to figure out that there's an n-log-n way of doing it <laughs>
...to which I have to say: yes, definitely! And he's right about open-source AI too.
Yes, there's a present shortage of usable frontier compute, but that doesn't establish that every proposed data center will earn a decent return, or that today’s hardware + model architecture will remain economically competitive, or more to Siegel's point, that algorithmic efficiency could not dramatically reduce compute requirements.
To borrow a real example from a prior boom, railroads were congested during the initial build-out while people simultaneously funded and built too many railroads for future demand. Likewise, Anthropic et al can be compute-starved now while the industry as a whole is overbuilding expensive, depreciating infrastructure.
I'm not sure comparing this one to the "real life" previous ones is worth doing. Digital has a way of scaling that IRL doesn't. You don't get exponetials with humans, but you do with models. Scale has shown time and time again that it works. Despite everything you've read in '25 about walls, lack of x, and so on it still does. And the more you have you find ways of using it even more. RL can use ~ 7:1 ratio of inference : training. That is, you run 7 nodes of inference for every node of training. And it keeps improving. Every algorithmic find on inference (and there've been plenty) translates in improvements. And we're not seeing any signs of this not continuing. And then there's the "zero" method, that hasn't been tried at true scale yet. Bitter lesson and all that.
I'll grant that the scaling laws have held so far, and that the bitter lesson is yet to be proven wrong. However, that doesn't exclude the possibility that the current architecture's S-curve will flatten, and a new one will replace it, which was Siegel's point. At greater layers of abstraction, what is observed is a raw capabilities/intelligence increase, but what form it takes is subject to change. We'll see where it all goes, the only way out is through.
Let me re-iterate the main lesson of decades of FOSS work: the advantages of open collaboration and knowledge-sharing are so enormous that FOSS software wins out eventually even if financial interest are stacked against it.
I fully agree with this article - please let's skip the chapter of closed and enshittified AI and go for the good stuff directly!
I must have missed the press release when Two Sigma open-sourced their algorithmic trading models so that the rest of us could make the best stock investments for our retirements. /s
Many states are trying to go back to phonics based reading. If you'd like to support such efforts check out your local school board, you can have a tremendous impact in your community and help better the lives of children in the progress.
Can’t wait for the day Altman goes to run payroll or whatever and there just isn’t enough liquidity there, full stop.
That will be the start of the world healing from a very severe psychosis and ailment, slop leaving the internet, and the future being certain and stable again for kids and such.
Largely because enough American voters, contrary to all of the evidence, believed that Trump was going to grow a sense of duty, eviscerate corruption in Washington, deliver an economy that works for the working class, and not engage in any new wars.
Someone must not have told Iran that Trump is the great peace president who ended all wars, united the Middle East and brought about world peace. They really need to get with the program or we'll have to win the war a few more times.
Number one expense for SMB is healthcare, providing a nationalized healthcare service would likely unlock trillions in value (imagine what Americans would do if they got $200-500 more per paycheck?).
Instead we are forced to watch some of the wealthiest companies on the planet burn money for fun because apparently the government is "wasteful."
The U.S. spends more money on education per student than any OECD country other than Norway and Luxembourg. Yet it gets quite mediocre results. Why do you think the U.S. will be able to do public health care in a more cost efficient way than it does public education?
I favor universal health insurance, but you’re going to pay more, not less. European countries didn’t flip some magic switch where they saved a bunch of money by just “cutting out the profit.” They do it through measures like the UK NHS setting the standards of care, so in a malpractice lawsuit the entity that says what the doctor ought to have done is the same entity that bears the cost of unnecessary tests and procedures. Efficiency is also achieved by aggressively rationing providers such as MRIs, keeping health worker salaries low, etc. There is no stomach to do any of that in the U.S.
>European countries didn’t flip some magic switch where they saved a bunch of money by just “cutting out the profit.”
They sort of have with pharmaceuticals (which to be clear is only maybe 10-15% of overall healthcare spending) by having the government negotiate drug prices nationally, instead of having individual insurers negotiate. This has monopsonistic effects, which really does cut the profit margins of drug manufacturers substantially. Of course, in many ways, they’re free riding on drug discovery funded by profits made overseas (particularly in America) but it does result in appreciable savings.
It probably means the quality of a lot of our food is inferior and we overly rely upon heavily industrialized production, overly processed foods and exploitative labor.
I think that the obesity rate is a lot higher in the US than a lot of other OECD countries, so people aren't starving but its hard to say their nutritionally thriving.
That could be more attributed to the income gap and concentration of wealth in the US as well.
How would obesity rate be related to “exploitive labor” or “income gap?” It seems like you’ve got a hammer and are looking for a nail.
Obesity rates don’t follow any predictable pattern: https://en.wikipedia.org/wiki/List_of_countries_by_obesity_r.... The countries around the U.S. on the obesity scale are places like Egypt, Chile, Mexico, Saudi, etc. What do these countries have in common? Probably nothing other than idiosyncratic cuisine and lifestyle habits and maybe genetics (non-asian versus asian).
The U.S. system is neither fish nor fowl, there is more spending per capita than other countries' public systems and endless amounts of red tape because instead of one government bureaucracy you're also dealing with the insurance networks, the providers, etc. I certainly don't think it'll be automatically cheaper, but one can't help but think that the current system encourages hop-ons that exploit the inconsistencies and convolutions. It's like one big nightmarish parody of public–private partnerships.
But our publicly run systems are full of inefficient bureaucracy and red tape, too. Why shouldn’t we assume our public healthcare system would be operated the same way as the public school systems in Chicago, New York, or Los Angeles?
Moreover, there is a massive amount of overcare that americans aren’t willing to confront. My wife’s grandmother had a stroke at 87 and was airlifted from rural oregon to a hospital in portland. She had only 3/4 of her lungs after having cancer in her 60s. The doctors wanted to do an intensive intervention, which didn’t happen only because she refused and died peacefully the next day. My parents are on medicare and they just wander into the ER every time their blood pressure goes too high. I took my 7 y/o son in for a black eye after he ran into a table. The doctor looked at him, concluded there was almost no chance of internal bleeding, but ordered an MRI (or CAT scan, I forget which) “just in case.” We got one and the results within 90 minutes because we just have million dollar machines lying around “just in case.” My daughter went to get her retainer at a small dental office in exurban Maryland, and the office had four people working at the checkin desk. I think this practice has only three dentists total.
America’s “customer is always right” culture means it will be politically impossible to roll back any of this.
Not how I view it as a 74 yo. Patients get what their doctors want as part of a culture of minimal preventive care (it does not pay) and massive medical care (procedures pay handsomely).
Try to get a unilateral diagnostic mammogram. Sorry in the system I am in there is no code for a unilateral diagnostic, only bilateral, even if only one side actually requires diagnosis.
Why? Because 2X the charge and income fir little extra care cost. And who would ever complain about such “excellent” care? Recent experience.
Frankly, dealing with healthcare claims as an American consumer is an excruciating experience and it is at the situation where “try anything else” is worth considering.
Also, as your description of overcare is happening under the current system, a profit-oriented one at that (which incentivizes the ordering of unnecessary tests and procedures) it sounds like you would actually benefit from a non-market-controlled, more modest (even austere), system!
Postwar America was built on the customer being right. The healthcare system is one of the glaring major examples of the customer not getting what it wants. Give the customer a better system.
> Also, as your description of overcare is happening under the current system, a profit-oriented one at that (which incentivizes the ordering of unnecessary tests and procedures)
Profit is part of it, but the legal system and culture are equally big parts. Malpractice claims are handled by jury trial in the U.S., and you can always get a doctor on the stand as an expert who will tell a jury that it was negligent not to order a million tests. The UK NHS avoids that by having the NHS set the standard of care. And malpractice claims have to go through an administrative system before resorting to court. And culture is big, too. Americans aren’t going to tolerate being sent to hospice before blowing through $1 million on heroic but futile end of life care.
> it sounds like you would actually benefit from a non-market-controlled, more modest (even austere), system!
I support such a system. My point is that there would be no political will to enforce modesty and austerity.
There is zero evidence we would pay more for healthcare under medicare for all, what a bunch of neoliberal nonsense.
The idea that a for-profit system is more efficient than say medicare is hilariously out of touch. Medicare is one of the most popular programs in the country (like >80% from overall public, >90% from active users). There is no reason to deny such a program from the vast majority of Americans, unless you stand to profit from it.
Our healthcare system has its flaws (to put it mildly), but nationalized systems have their own. I know people who don't have primary care because they live in a country with a nationalized healthcare service and their government, in its infinite wisdom, chose not to allocate enough doctors to their town.
When you cut out the insurance middlemen and pharmaceutical companies driving up record profits at the expense of care you can get pretty far with less in taxes
Insurance companies make like 2-4% hardly breaking the bank here. Pharmaceutical companies make a lot of money, but the US also funds most drug development which other countries freeload off of. US healthcare workers get a state enforced shortage to drive up their wages thanks to residency limits, but nobody ever wants to look at that.
If you can't tell I am extremely pessimistic about the changes of universal healthcare improving on our current system. And to be clear it's universal, not unlimited.
Insurance companies basically are banks, in that while they make low profit margins they wield such vast amounts of capital, some of which they invest in, they might as well be financial service institutions. There's also other categories of entities (pharmacy benefit managers, wholesalers and distributors) that also get a cut.
The big 7 U.S. health insurers made $55 billion in profits in 2025. Pharma industry profits on U.S. revenue was about $100 billion. Total U.S. healthcare spending in 2025 was $5.7 trillion. Cutting insurer and pharma profits out of the equation entirely would reduce spending by 2.7%.
I support universal health care. But most of its proponents are suffer from innumeracy and magical thinking. It’s very scary to me that we’d put these people in charge of health care reform.
Do those school bureaucracies require parents of students to attend customer service calls that require multiple transfers over the better part of an hour?
We know how efficient government operates tho, the admin expenses of say social security and medicare is less than 3%. Pray tell, what corporation operates with 3% admin expenses?
Citation needed that it's not a good policy. Parent comment explained why it was good, and your reply is "or perhaps it was actually bad".
There's a simpler explanation as to why it was rolled back: the people with the most money and power didn't like it and wanted it gone, and worked over time to accomplish this.
It's not "90% tax" it's 90% or similar tax rate at the highest band, which most people will never reach.
Despite you showing your bias by phrasing option 1 to look childish, I think it's more or less what happened, actually. It doesn't take much "collusion", just greed and short-sighted self-interest from greedy, short-sighted self-interested people with influence to wield.
And you till haven't cited how that 1) this definitely didn't happen and 2) high tax rates in the highest band is a bad idea.
Mothers are great at childcare and can easily provide much healthier lunches at far lower cost than schools. As for medicine, children are a small percentage of healthcare costs.
No, I want govt to tax themmore. So far frontier AI companies produce negative value to near everyone (by sheer power cost increase it adds essentially tax to every other business) but themselves economy wise.
Yeah, wooho, new model found a bunch of bugs, now the bad guys can do it too so security expenses spiked! It's only good for shovel sellers.
We really need to band together to fund / sponsor targeted inducement prizes (a la Nobel laureate Michael Kremer) for open models.
Every 6-12 months, give out $200K to the first model to hit a min threshold on a set of ~5-10 hard benchmarks (+ perhaps one secret benchmark) using a total of 16GB / 32GB / 64GB / 128GB of VRAM (at a min context length of 200K), then move the threshold up. Quantization etc. is dealers choice, it just needs to nail the benchmark on a reference machine by using exactly that much VRAM (no mapping to RAM / disk etc.)
You could crowdsource the funding, and cross subsidize by adding targeted prizes focused on corporate needs (the classic one is PDF processing benchmarks), and say that 25% of each corporate prize funding also flows into the general prize pool.
For a lot of these open-source model companies, it's less about the $s (though $200K is nothing to sneeze at), it's the clear recognition that helps their model efforts stand out, gain usage etc.
I think the Korean government did have a competition like this, I remember last year we got a bunch of models released at the same time to make the cut for the next stage. The models weren't anything to write home about, IMO.
Having it with clear hw requirements tiers is a nice differentiator. The only issue is that the benchmarks would 100% need to be closed, no other way around it. And then you have the issue of creating and curating good evals for every "stage" of the project. That's a hard task even for "honest" lab-internal evals. And you'd have to publish those evals after each round (for trust purposes), and start over for the next round. Doable, but it would cost a lot (probably more than the prize pools) and you'd have to keep doing this.
It was a competition organized by the Korean government but the directive wasn't for the same cause as the writer. It was more for constructing Sovereign AI for the country. Also, all models except Exaone had some weights copied from Chinese models, and from the corporate point of view, developing from-scratch model is not cheap despite the financial support from the government.
Yes, I hope the open model communities will someday be able to run current frontier models which will be able to handle autonomous tasks and the hardware to run it will be served at consumer level; however, like how recycling isn't profitable, no companies will fully commit to the movement. Don't get it twisted, I don't have a solution but maybe a global scale movement to liberate knowledge-library could suffice.
Yeah, I suspect the $200K check would be the cheapest line item in the whole thing
Pretty sure the labs subsidized the well known benchmarks w free tokens for evals
This seems like a good idea but also just fun. I can’t train a frontier model but maybe I could compete in the 16 GB tier. I would suspect there are a ton of optimizations out there for the taking that aren’t being considered because frontier models are way above these weight classes
I would just add a reproducibility requirement and avoid keeping the exact same benchmarks for too long
Not sure that would even cover power for training
The private AI companies should be forced to release the models as open weights with a license (I.e no commercial use) due the high risk they present and the data they basically steal from everyone to train their models. This should be the safety push not the regulatory capture that Dario is trying.
> the data they basically steal from everyone
What's the precedent?
All I see if a bunch of people who haven't loaded an ad in 20 years and have a 5TB collection of pirated movies and music suddenly decrying that LLM's doing next token prediction over a dataset is theft.
You don't get to change your mind 20 years into "I'm never going to pay for anything binary" ethos (cough look at what this post is cough) that has dominated the internet for decades. If people are genuinely upset about LLMs training on all available data without compensation, all I can say is "Reap what you sow".
It would be all fine and good if they kept it non-commercial, but when you start charging money for it that's when you're stepping out of bounds. If they want to benefit from fair use, they should contribute their results back to the public domain. Getting it for free and then commercializing it is what's unethical.
>Getting it for free and then commercializing it is what's unethical.
Like all those unethical software devs taking salaries for turning stackoverflow into products? I suppose the blood still flows since now they just use LLM output?
Any way you try and slice LLM morality, you end up with "It's bad because they are not me" reasons. "When I monetize information I get for free, it's good, when they monetize information they get for free, it's bad"
Ok then can the feds bust the executives of these companies like they did with Kim Dotcom? It’s not like Dario trained his AI in the bedroom or do a small business by letting people scrapping IP work to train their models. He is actively stealing and selling the stolen work and even preaches us safety measures: how to protect us from our own knowledge that he stole!
I am not convinced by your retort, which essentially boils down to “some people pirate, so its ironic some people, maybe different, are mad at dario!”
Artists and writers got screwed first by piracy, then by generative AI. They didn't sow anything. They just got reaped.
And the only thing the copyright hypocrites are "reaping" is a feeling of hypocrisy. Congrats for pointing that out. Your comment is simply myopic.
> Artists and writers got screwed first by piracy, then by generative AI.
That's too glib. Artists don't have a right to money that people won't spend.
It's not all down to bad actors. Although it's true that musicians got screwed when their distributors switched to a subscription model. Writers got screwed by the Amazon monopsony that crammed down publisher's margins.
Mostly what happened is that media technologies changed, professional creators had less control over production, and the money flowed upstream leaving them with a smaller niche.
All of their output used to be gatekept by media companies who had a lock on publishing. The internet reduced distribution costs to zero. Suddenly anybody could reach an audience.
Now generative AI has dropped the cost of content creation to the basement. It's so much easier to write a blog post or make an illustration.
That isn't cannibalizing content. It's a new way of making. It takes a lot of the value out of creating those kinds of things. The customer experiences this as a reduction in cost.
These changes happen with every new gadget. Photographers have to compete against everybody with a phone in their pocket. Now they just do weddings.
My grandfather was a portrait painter in the 1940s, a profession that was already moribund from the proliferation of photography studios. He gave up and became an insurance salesman.
Maybe he got screwed. The photography studios are all gone too. Because anybody can make a portrait using the phone in their pocket. At zero cost.
> the data they basically steal from everyone
Agreed. Especially since now competitors have more difficulties getting the same advantage. They don't have to do so immediately and perhaps not their specific tuning. But the weights of the raw training data at least should be publicised.
> no commercial use
Why? It's not like they did the hard work. It's disgraceful that this kind of commons enclosure has been allowed in the first place.
Wow, thank you for this! I'd forgotten about enclosure for some years.
> The law locks up the man or woman / Who steals the goose from off the common / But leaves the greater villain loose / Who steals the common from the goose.
> release the models as open weights with a license (I.e no commercial use) due the high risk they present
For some kinds of risk (ex: walking people through on how to make infectious bioweapons) an open-weights approach would increase risk.
Don't buy the idea that the only thing that's standing in the way of people making bioweapons is the censoring of LLMs.
If you are motivated enough to assemble all the kit you'd need, and actually do it, then you should be motivated enough to find the knowledge to do it without chatgpt etc.
I'd imagine the main thing that's stopping people is biological weapons are a terrible tool to do what most people want to do - which is target specific enemies.
So while the materials you'd need to build such a thing are much more accessible than say nuclear material, it's much less attractive - but if already had somebody mad enough to try - it's already possible.
> Don't buy the idea that the only thing that's standing in the way of people making bioweapons is the censoring of LLMs.
It's not a matter of a one thing standing in the way of people making bioweapons: there's a long chain of actions one would need to complete, and many places for the chain to fail. Access to expertise can reduce the chance of failure at many of these steps, and AIs can increasingly substitute for human expertise: https://securebio.org/benchmarks/
> If you are motivated enough to assemble all the kit you'd need, and actually do it, then you should be motivated enough to find the knowledge to do it without chatgpt etc.
If someone was motivated enough to assemble the kit you need for anthrax and actually distribute it then you might expect them to also be motivated enough to find the knowledge to identify an appropriate strain, but in fact this is where Aum Shinrikyo failed in the 1990s: https://en.wikipedia.org/wiki/Aum_Shinrikyo#Incidents_before...
Lack of knowledge is one of many factors that can lead to failure, and LLMs make it less of a barrier.
> biological weapons are a terrible tool to do what most people want to do - which is target specific enemies
Except:
1. There are also people out there who want to kill everyone. They're sufficiently rare that no one with the motive has also had the means, but as technological progress keeps lowering the bar the risk of motive and means intersecting increases.
2. This didn't stop the Soviets. They did an enormous amount of very dangerous research with minimal logical application.
In an earlier phase of AI I might have agreed but now the publicly available data they’ve trained on is increasingly useless for the frontier.
RL/post-training is now a much bigger part of it, with that being largely proprietary and expensive work that the open source model just won’t fund.
Good idea! I'd never heard that. Very interesting.
But wouldn't this help china build models just as good as ours immediately? Wouldn't it make the investment in training a model worth a lot less?
I'd rather they published the training data.
Then we can verify that there's nothing nasty hiding in it.
FOSS is the wrong analogy. Building frontier LLMs isn’t primarily an engineering discipline, it’s a scientific research program.
Of course we do have basically open source research programs, including most universities and big projects like CERN. But AI grew up in universities until it transpired that sufficient capital could only be found in the private sector.
It would be possible to make a decent publicly funded AI research program. But it would look more like the Manhattan or Apollo projects (which frontier labs already model themselves after) than some extra research grants for universities.
The Manhatten project cost about $40 billion in total adjusted for inflation. Anthropic's latest funding round alone raised $65 billion.
The entire Apollo project at the peak of the cold war cost about $300 billion in today's dollars. That's approximately what OpenAI and Anthropic have raised together in total until now.
I don't think governments can supply this amount of money for AI in the current political and economic climate. The LHC cost less than $10 billion by comparison and it was spread out over a much longer timeframe.
> I don't think governments can supply this amount of money for AI in the current political and economic climate.
I'm a believer in Keynes' "anything we can do we can afford". It could be afforded .. if there was a sufficiently good reason. And there isn't. This is way behind "governments, especially the EU, should have a sovereign cloud". It is also way behind "governments need to keep global warming below 2C by the end of the century" and "governments need to ensure affordable energy", objectives which the current AI buildout is in direct conflict with.
This is before we get into the question of whether AI has net positive social value in non-software use cases. Even in software the case for AI is explicitly job-destroying and raising electricity prices for everyone else.
The only reason AI research is in conflict with limiting global warming is the unholy alliance of NIMBYs and Sierra Club environmentalists preventing the building of anything, anywhere. Clean energy has beaten out fossil energy on cost for years now, and only regulatory burdens force datacentres to use portable gas turbines instead of standing up transmission lines to the closest solar or wind farm.
There are things you can't do - even as a society - when the costs start ballooning beyond the GDP of smaller European nations. I mean, yes, in an emergency you could cancel all social security and public infrastructure spending and instead dump it into AI. But even then it will take several big nations to foot the bill if you want to still have a country left after you're done. With the level of political heckle everywhere, this is just not going to happen, because it would need unanimous support from all sides.
What you are potentially missing is the public sector wouldn't necessarily be in the same race as the commercial companies.
It doesn't matter if a public effort is a year or two behind the curve ( and hence has dramatically lower costs due to Moores law and the ability to piggy back on research ) - especially as we approach the asymptotic phase of development.
> I don't think governments can supply this amount of money for AI in the current political and economic climate.
You understand how the system works if you’re thinking in terms of government/non-government. The current political and economic state is not a bug, it’s by design which serves a purpose.
Remember, the purpose of a system is what it does
Yes, if the US was modeled like the USSR they could extract 100% of everyone’s private assets and the politburo could spend them on whatever moonshot projects they wanted to, unchecked by silly democratic votes.
But…the USSR and that entire model failed spectacularly? So not sure what you’re getting at here. Is there some fantasy economic model you believe you’ve innovated that will lead to utopia and the end of resource scarcity?
Govts can take it over. Corporations dont maintain standing armies. So there is a pecking order that corps have never been able to invert. They rely on Govt for their own security.
History is full of these take overs if there is risk(usually happens after some catastrophe). See the finance sector(once upon a time private banks invented and printed money), nuclear industry, febrtilizer industry, crypto, a whole bunch of processes in biotech/synthbio. Classic textbook example is the East India Company. It was much richer that the British Govt or the King.
> But AI grew up in universities until it transpired that sufficient capital could only be found in the private sector.
One way of looking at it. Another is that AI research progressed within universities, but it was only until recently that the private sector saw the profit potential when combined with modern CPU/GPU technology.
You could argue we're saying the same thing, but I think these angles are different. An academic research programme would not have spent billions on a datacentre to provide AI for free to the general public, for example.
I agree an academic research program wouldn’t spend billions on a datacenter, but that’s just a reason why foss AI as described in this article won’t work - because big compute is required to do anything of real relevance.
They already invest in open-source AI, but nothing is truly free. Commercial AI will usually dominate because devs are paid to make it their primary effort. Goodwill and part-time contributions cannot reliably compete with livelihood and profit incentives.
That's what people said about operating systems, and databases, and compilers, and so many other big complicated categories of software that over time became increasingly dominated by OSS
OSS only dominates for software that is commoditized and the published computer science research for that software domain is close to the frontier.
OSS struggles at being relevant when software is non-commodity e.g. office suites. In software domains like databases where the state-of-the-art computer science research is often unpublished, OSS struggles to be relevant at the higher end of the market on technical merits.
When deciding what should be OSS, it is useful to consider the preconditions that have made it successful.
I personally expect token production to commoditized like mobile data. It's already happening.
See open weights gaining adoption, OpenAi talking about how 5.6 is cheaper than Fable, people are taking multiple approaches to reduce their token spend, expectations for progress in hardware and algos, and certain Ai leaders talking about how token prices should be 10-100x lower than they are.
LLMs are nearly commoditized already. I can switch between a dozen of them from four different providers as easily as flipping a toggle in my VSCode editor.
OSS does not necessarily mean the contributions are from "goodwill or part-time contributions". In fact, I would wager the most widely used OSS software is largely written by contributors paid to do so by corporations. At least for Linux, about 80% - 85% of contributions are from developers paid to do it (https://newsletter.pragmaticengineer.com/p/how-linux-is-buil...)
Corporations have had many reasons to invest their money in open source software -- custom requirements, marketing / developer mindshare, commoditizing complements -- but as cutting edge LLMs get more and more expensive to train, you'd be hard-pressed to find corporations who will put in that kind of money if they cannot recoup their investments.
I think the main problem in LLM models is that you can not make a PR to an open source project to tweak some training parameters, prove it is an improvement and merge it.
If you can not run the training yourself you can not contribute. So open source contribution model does not work. All examples you gave have a fairly low threshold of capital expenditure required to be a contributor (basically a laptop).
Even back in the 90s a person could get a standard, but powerful, PC to do these things. The one exception was 3d graphics which took quite some time to become affordable and even there it was a single one-time expenditure (a workstation) per contributor.
For normal OSS the only competition between contributors was for attention of maintainers to review and accept patches.
In an open-source LLM model contributors would compete with each other for computing resources for model tweaks and changes. The alternative model is that the contributor pays for the compute, but that increases the bar really high for contributions.
all those have either a consulting company around it or few big corporate contributors
[dead]
AGI is not software
on the small chance that the four billionaires who currently have near-exclusive control of closed sota models, (that is altman, amodei, zuckerberg and musk), are not fleecing their investors and actually build AGI, closed source leaves a choice of powerful government or powerful oligopoly/monarchy.
further explanation of this list:
musk - structural command
zuckerberg - structural command
altman - de facto command after purging rivals and privatisation, loyalty of personnel
amodei - influential, could potentially overthrow current governance
if i'm wrong i would like to understand
[dead]
Just because a software is closed-source doesn't mean the knowledge can't be shared. You don't need to see the underlying code to explain to someone architectural patterns or best practices.
The library analogy in the scenario would hold true if LLM providers refused to answer any questions about RL or Transformers.
I am a big proponent of open-source open-weight models, but mostly because I think it's just a better product. We've seen that they are much cheaper to train and operate. Frontier intelligence might not be needed for most tasks. Just let the market decide. My bet is that LLMs will become analogous to programming languages, and big labs will make their money by fine-tuning models for very specific use cases or by deploying them for customers.
I would not count on the market alone. Like customers do not always choose the technically best or cheapest option
Title was: I argued with the father of open source for 2 years. Now the AI fight is the same — only bigger
Op-ed alt link: https://fortune.com/2026/07/03/open-source-ai-same-fight-as-...
“The economists need to start charting this out, if we are in a post scarcity world, how does everyone benefit from that?, obviously its not correct for just a few people or a few companies or even a few nations to be benefiting from this technology, it has to broadly accrue the benefits to everyone, but how is that gonna be done? We really need answers now. ” -Demmis Hassabis <Google Deep mind>
The sovereignty point resonates. The June 2026 export controls on Anthropic's models were a wake-up call.
Open weights + deterministic orchestration feels like the only sane long-term bet.
Listening to those pushing AI, why should we fund open source developers when we can reproduce their work with a few judiciously chosen LLM prompts? Perhaps the AI companies should fund FOSS so as to get more solutions to memorize but normals?
FOSS is far from enough anymore.
_LEAN_ FOSS, including the SDK then the computer languages too.
All computer languages with an ultra-complex syntax are excluded de facto.
Then there is the stability in time.
developer/vendor lock-in on software, planned obsolescence, are much more common in FOSS nowdays.
The library analogy works (for me), but the uncomfortable part is that most "open" models are closer to receiving a compiled binary than receiving the library
Ah, this from the same David Siegel who said almost 2 yrs ago (in a talk found here: https://youtu.be/0z60xUDo-NI?si=PTDe11-sn2P53qo5&t=420) that the AI data center buildout was premature because:
> Even if the current approaches will continue to scale, this would be as if in the early days of computing, perhaps someone invented a bubble sort for sorting numbers (an n-squared algorithm), and the tech companies at the time decided they were going to build vast data centers to sort numbers and not bother to figure out that there's an n-log-n way of doing it <laughs>
...to which I have to say: yes, definitely! And he's right about open-source AI too.
> AI data center buildout was premature
Ask Amodei how he feels about going to spaceman bad for compute that he couldn't find anywhere else in the market.
Yes, there's a present shortage of usable frontier compute, but that doesn't establish that every proposed data center will earn a decent return, or that today’s hardware + model architecture will remain economically competitive, or more to Siegel's point, that algorithmic efficiency could not dramatically reduce compute requirements.
To borrow a real example from a prior boom, railroads were congested during the initial build-out while people simultaneously funded and built too many railroads for future demand. Likewise, Anthropic et al can be compute-starved now while the industry as a whole is overbuilding expensive, depreciating infrastructure.
I'm not sure comparing this one to the "real life" previous ones is worth doing. Digital has a way of scaling that IRL doesn't. You don't get exponetials with humans, but you do with models. Scale has shown time and time again that it works. Despite everything you've read in '25 about walls, lack of x, and so on it still does. And the more you have you find ways of using it even more. RL can use ~ 7:1 ratio of inference : training. That is, you run 7 nodes of inference for every node of training. And it keeps improving. Every algorithmic find on inference (and there've been plenty) translates in improvements. And we're not seeing any signs of this not continuing. And then there's the "zero" method, that hasn't been tried at true scale yet. Bitter lesson and all that.
I'll grant that the scaling laws have held so far, and that the bitter lesson is yet to be proven wrong. However, that doesn't exclude the possibility that the current architecture's S-curve will flatten, and a new one will replace it, which was Siegel's point. At greater layers of abstraction, what is observed is a raw capabilities/intelligence increase, but what form it takes is subject to change. We'll see where it all goes, the only way out is through.
I wonder if some sort of member owned cooperative would be the way forward if we the people want to retain any control.
just remove "AI" from title and its good:
— Governments, companies, nonprofits should invest in free, open source.
Let me re-iterate the main lesson of decades of FOSS work: the advantages of open collaboration and knowledge-sharing are so enormous that FOSS software wins out eventually even if financial interest are stacked against it.
I fully agree with this article - please let's skip the chapter of closed and enshittified AI and go for the good stuff directly!
[flagged]
[dead]
[dead]
[flagged]
[dead]
I must have missed the press release when Two Sigma open-sourced their algorithmic trading models so that the rest of us could make the best stock investments for our retirements. /s
[flagged]
I would add supporting literacy programs to that list. Unfortunately, many Americans struggle to read beyond the sixth grade level.
Many states are trying to go back to phonics based reading. If you'd like to support such efforts check out your local school board, you can have a tremendous impact in your community and help better the lives of children in the progress.
Can’t wait for the day Altman goes to run payroll or whatever and there just isn’t enough liquidity there, full stop.
That will be the start of the world healing from a very severe psychosis and ailment, slop leaving the internet, and the future being certain and stable again for kids and such.
It’s optimistic I know.
Yeah those arent options.
The US cares about bombing children and AI. Redirecting funding from the former to the latter is a moral imperative.
Redistribution can only get you so far. Creating new wealth is more sustainable.
So why did we stop doing that in favour of winner takes all weath centralisation?
Largely because enough American voters, contrary to all of the evidence, believed that Trump was going to grow a sense of duty, eviscerate corruption in Washington, deliver an economy that works for the working class, and not engage in any new wars.
Charlie Brown, Lucy, football.
What country are our boys occupying now?
Are you suggesting that in fact we have not entered any new wars in recent history?
We entered a war in Iraq a quarter century ago
We entered a war in Iran in February.
At least the war in Iraq had a veneer of a pretext. Trump seems to be attacking Iran because Bibi asked him to
Someone must not have told Iran that Trump is the great peace president who ended all wars, united the Middle East and brought about world peace. They really need to get with the program or we'll have to win the war a few more times.
Number one expense for SMB is healthcare, providing a nationalized healthcare service would likely unlock trillions in value (imagine what Americans would do if they got $200-500 more per paycheck?).
Instead we are forced to watch some of the wealthiest companies on the planet burn money for fun because apparently the government is "wasteful."
What a crock of shit.
The U.S. spends more money on education per student than any OECD country other than Norway and Luxembourg. Yet it gets quite mediocre results. Why do you think the U.S. will be able to do public health care in a more cost efficient way than it does public education?
I favor universal health insurance, but you’re going to pay more, not less. European countries didn’t flip some magic switch where they saved a bunch of money by just “cutting out the profit.” They do it through measures like the UK NHS setting the standards of care, so in a malpractice lawsuit the entity that says what the doctor ought to have done is the same entity that bears the cost of unnecessary tests and procedures. Efficiency is also achieved by aggressively rationing providers such as MRIs, keeping health worker salaries low, etc. There is no stomach to do any of that in the U.S.
>European countries didn’t flip some magic switch where they saved a bunch of money by just “cutting out the profit.”
They sort of have with pharmaceuticals (which to be clear is only maybe 10-15% of overall healthcare spending) by having the government negotiate drug prices nationally, instead of having individual insurers negotiate. This has monopsonistic effects, which really does cut the profit margins of drug manufacturers substantially. Of course, in many ways, they’re free riding on drug discovery funded by profits made overseas (particularly in America) but it does result in appreciable savings.
Yes, good point. That’s one of the switches that will have to be flipped.
Primary Education (K–5): The U.S. spends 21% of its GDP per capita per student. This is exactly in line with the OECD average, which is also 21%.
Secondary Education (6–12): The U.S. spends 23% of its GDP per capita per student. This sits just slightly below the OECD average of 24%.
We spend only 5% of our GDP on food, which is much lower than other OECD countries. Does it mean we are starving?
It probably means the quality of a lot of our food is inferior and we overly rely upon heavily industrialized production, overly processed foods and exploitative labor.
I think that the obesity rate is a lot higher in the US than a lot of other OECD countries, so people aren't starving but its hard to say their nutritionally thriving.
That could be more attributed to the income gap and concentration of wealth in the US as well.
How would obesity rate be related to “exploitive labor” or “income gap?” It seems like you’ve got a hammer and are looking for a nail.
Obesity rates don’t follow any predictable pattern: https://en.wikipedia.org/wiki/List_of_countries_by_obesity_r.... The countries around the U.S. on the obesity scale are places like Egypt, Chile, Mexico, Saudi, etc. What do these countries have in common? Probably nothing other than idiosyncratic cuisine and lifestyle habits and maybe genetics (non-asian versus asian).
If you want to adjust for cost levels in different countries, you’d use a PPP adjustment: https://www.visualcapitalist.com/ranked-education-spending-p...
The U.S. is at $20k, well over the OECD average of $15k. O my Austria, Norway, and Luxembourg are higher.
The U.S. system is neither fish nor fowl, there is more spending per capita than other countries' public systems and endless amounts of red tape because instead of one government bureaucracy you're also dealing with the insurance networks, the providers, etc. I certainly don't think it'll be automatically cheaper, but one can't help but think that the current system encourages hop-ons that exploit the inconsistencies and convolutions. It's like one big nightmarish parody of public–private partnerships.
But our publicly run systems are full of inefficient bureaucracy and red tape, too. Why shouldn’t we assume our public healthcare system would be operated the same way as the public school systems in Chicago, New York, or Los Angeles?
Moreover, there is a massive amount of overcare that americans aren’t willing to confront. My wife’s grandmother had a stroke at 87 and was airlifted from rural oregon to a hospital in portland. She had only 3/4 of her lungs after having cancer in her 60s. The doctors wanted to do an intensive intervention, which didn’t happen only because she refused and died peacefully the next day. My parents are on medicare and they just wander into the ER every time their blood pressure goes too high. I took my 7 y/o son in for a black eye after he ran into a table. The doctor looked at him, concluded there was almost no chance of internal bleeding, but ordered an MRI (or CAT scan, I forget which) “just in case.” We got one and the results within 90 minutes because we just have million dollar machines lying around “just in case.” My daughter went to get her retainer at a small dental office in exurban Maryland, and the office had four people working at the checkin desk. I think this practice has only three dentists total.
America’s “customer is always right” culture means it will be politically impossible to roll back any of this.
Not how I view it as a 74 yo. Patients get what their doctors want as part of a culture of minimal preventive care (it does not pay) and massive medical care (procedures pay handsomely).
Try to get a unilateral diagnostic mammogram. Sorry in the system I am in there is no code for a unilateral diagnostic, only bilateral, even if only one side actually requires diagnosis.
Why? Because 2X the charge and income fir little extra care cost. And who would ever complain about such “excellent” care? Recent experience.
Frankly, dealing with healthcare claims as an American consumer is an excruciating experience and it is at the situation where “try anything else” is worth considering.
Also, as your description of overcare is happening under the current system, a profit-oriented one at that (which incentivizes the ordering of unnecessary tests and procedures) it sounds like you would actually benefit from a non-market-controlled, more modest (even austere), system!
Postwar America was built on the customer being right. The healthcare system is one of the glaring major examples of the customer not getting what it wants. Give the customer a better system.
> Also, as your description of overcare is happening under the current system, a profit-oriented one at that (which incentivizes the ordering of unnecessary tests and procedures)
Profit is part of it, but the legal system and culture are equally big parts. Malpractice claims are handled by jury trial in the U.S., and you can always get a doctor on the stand as an expert who will tell a jury that it was negligent not to order a million tests. The UK NHS avoids that by having the NHS set the standard of care. And malpractice claims have to go through an administrative system before resorting to court. And culture is big, too. Americans aren’t going to tolerate being sent to hospice before blowing through $1 million on heroic but futile end of life care.
> it sounds like you would actually benefit from a non-market-controlled, more modest (even austere), system!
I support such a system. My point is that there would be no political will to enforce modesty and austerity.
There is zero evidence we would pay more for healthcare under medicare for all, what a bunch of neoliberal nonsense.
The idea that a for-profit system is more efficient than say medicare is hilariously out of touch. Medicare is one of the most popular programs in the country (like >80% from overall public, >90% from active users). There is no reason to deny such a program from the vast majority of Americans, unless you stand to profit from it.
Medicare is cross-subsidized by private health insurance: https://chatgpt.com/s/t_6a5838016cf88191bce90f346ee16ab6
Our healthcare system has its flaws (to put it mildly), but nationalized systems have their own. I know people who don't have primary care because they live in a country with a nationalized healthcare service and their government, in its infinite wisdom, chose not to allocate enough doctors to their town.
How would nationalized healthcare get funded other than shifting that 200-500/check towards… nationalized healthcare?
When you cut out the insurance middlemen and pharmaceutical companies driving up record profits at the expense of care you can get pretty far with less in taxes
Insurance companies make like 2-4% hardly breaking the bank here. Pharmaceutical companies make a lot of money, but the US also funds most drug development which other countries freeload off of. US healthcare workers get a state enforced shortage to drive up their wages thanks to residency limits, but nobody ever wants to look at that.
If you can't tell I am extremely pessimistic about the changes of universal healthcare improving on our current system. And to be clear it's universal, not unlimited.
Insurance companies basically are banks, in that while they make low profit margins they wield such vast amounts of capital, some of which they invest in, they might as well be financial service institutions. There's also other categories of entities (pharmacy benefit managers, wholesalers and distributors) that also get a cut.
https://medium.com/@brian-curry-research/the-healthcare-maze...
The big 7 U.S. health insurers made $55 billion in profits in 2025. Pharma industry profits on U.S. revenue was about $100 billion. Total U.S. healthcare spending in 2025 was $5.7 trillion. Cutting insurer and pharma profits out of the equation entirely would reduce spending by 2.7%.
I support universal health care. But most of its proponents are suffer from innumeracy and magical thinking. It’s very scary to me that we’d put these people in charge of health care reform.
You cut out the insurance middlemen but you introduce government bureaucracy.
There's absolutely no way the government operates more efficiency in this space.
Better one bureaucracy than many. The U.S. health system requires constant patient management of multiple moving parties, it's maddening.
Except that bureaucracy would be run like Chicago Public Schools.
Do those school bureaucracies require parents of students to attend customer service calls that require multiple transfers over the better part of an hour?
We know how efficient government operates tho, the admin expenses of say social security and medicare is less than 3%. Pray tell, what corporation operates with 3% admin expenses?
Once again, what a crock of shit.
> Redistribution can only get you so far.
That "so far" being a middle class the envy of the rest of the world which the US threw away to create a new class of oligarch.
"Back at the tail-end of that era, in the early 1960s, America’s richest faced a 91 percent tax rate on income in the top tax bracket."
https://inequality.org/article/tax-the-rich-we-did-that-once...
Perhaps they realised it’s not a good policy? Like literally everywhere else in the world?
No other country has 91% taxes and all those who tried dialled it back. India tried it and it was hilariously bad.
> Perhaps they realised it’s not a good policy?
Citation needed that it's not a good policy. Parent comment explained why it was good, and your reply is "or perhaps it was actually bad".
There's a simpler explanation as to why it was rolled back: the people with the most money and power didn't like it and wanted it gone, and worked over time to accomplish this.
so it could be two reasons
1. 90% tax is a net good for society but big bad capitalists colluded to reduce it in every country independently
or
2. 90% is actually a bad policy and every country independently adopted against it including Nordic countries, China, India, USA
you decide which one is more likely.
It's not "90% tax" it's 90% or similar tax rate at the highest band, which most people will never reach.
Despite you showing your bias by phrasing option 1 to look childish, I think it's more or less what happened, actually. It doesn't take much "collusion", just greed and short-sighted self-interest from greedy, short-sighted self-interested people with influence to wield.
And you till haven't cited how that 1) this definitely didn't happen and 2) high tax rates in the highest band is a bad idea.
AI destroys wealth, so what is that?
Well because you said that, we're going to add public investment in crypto too, everyone gets an NFT with their taxes this year.
Mothers are great at childcare and can easily provide much healthier lunches at far lower cost than schools. As for medicine, children are a small percentage of healthcare costs.
[flagged]
ABSLOUTELY NOT.
this is like saying "gov should invest in pyramid schem, because everyone is doing it". or btc. or web3 pictures of monkeys.
what i expect the gov to do is to add a 999% tax or tarif on top of GPUs bougth for AI, after the first 100mi that company spends on it each year.
No, I want govt to tax themmore. So far frontier AI companies produce negative value to near everyone (by sheer power cost increase it adds essentially tax to every other business) but themselves economy wise.
Yeah, wooho, new model found a bunch of bugs, now the bad guys can do it too so security expenses spiked! It's only good for shovel sellers.