I agree. The frontier models are based on training data from tons of copyrighted work. Some of that work was obtained illegally, even. They could not exist without strip-mining the commons. The labs have no moral or ethical ownership to the end result, and others should feel free to treat any company-imposed restrictions on their use as invalid.
I don't expect Tan's position to be based on any kind of real moral high ground, but his conclusion is correct.
I love the "illicit distillation attacks" framing from the incumbents. There's nothing illicit. There's no attack. You just don't like it because it threatens your market position and business model.
With the recent Navier-Stokes controversy, I think there's a credible suspicion that all your IP you run through these models will end up in these companies' possession. OpenAI themselves has admitted a weak version of this (that prompts might inadvertedly end up improving the model). We don't know the extent of this.
Obviously it's not possible to run a company whose value is predicated on its IP that uploads said IP to a third party which might get access to it.
This could mean every potential serious customer would have no option but to seek alternatives to these online services.
Or these customers could just use AWS Bedrock...but their current CEO is an incompetent MBA unable to publicly articulate their biggest advantage, in the context of the current AI usage my companies.
You have access to all the frontier models, but...your inputs are not shared with the model vendors...neither are used to train the next model.
Why am I even doing the Amazon board job for them!??
Amazon is deeply invested in Anthropic and would not defame them through marketing a service whose selling point was their startup's breach of contracts.
Bedrock is really bad. It seems like they don't host the models very well because they produce tons of bugs/errors calling the model. For example you can end up with Anthropic models not returning a stop token and you end up waiting for a timeout thinking its doing something when it isn't.
I thought this was commonly accepted to be the case that companies which sell access to LLMs are also storing and training on the inputs?
I don't mean this as rhetoric, I did not think many people (except possibly those operating under government contracts, and 'normies' who don't know about these things) were under the belief that their IP was kept secret when they use these services.
Some offer zero data retention policies, but there can be weasel words. For example, on the individual pro plan, you can turn off the setting that lets them train models on your data, but they still have a section in their terms that allows them to evaluate your anonymized data for statistical and "research" purposes. You have to actually get a signed contract along with an enterprise plan that spells out exactly what they're going to use, and what settings enable what retention.
What about inference providers like Baseten, Modal, Fireworks, Together, etc? I thought one of their value propositions was inference (using open weights models) that guarantees with crisp terms that they will not use your data.
> I thought this was commonly accepted to be the case that companies which sell access to LLMs are also storing and training on the inputs?
The services have toggles to allow prompts to be used in the training set. There is a conspiracy theory that the toggle is a false distraction and they’re actually keeping everything, and that none of the employees involved will ever whistleblow this fact.
Outside of Internet comment sections, I think most people assume these US-based companies are doing what they say.
For enterprise use there are services like AWS Bedrock which have strict isolation guarantees. There are some people who still believe those guarantees are a lie, but once someone has reached that point I don’t think they trust anything that isn’t running entirely within their house. People in that category are a very small minority, but a very vocal minority.
> OpenAI themselves has admitted a weak version of this (that prompts might inadvertedly end up improving the model). We don't know the extent of this.
I think this is being misunderstood. Codex has a toggle to allow your prompts to be included in training data. They’re saying they can’t be sure if the person had it on or off while using Codex to discuss the work.
They’re not saying that some prompts are mysteriously jumping into training data.
Also, there is a large market for AI services which don’t retain anything under any circumstances for enterprise customers.
A lot substance is hinged on the exact definition of the word "data" or "user data". In the age of post-truth everyone is claiming that they keep no "user data". Except that after running it once through some transformer program it's no longer "user data", it's something entirely else and these corpos gave ZERO promises regarding such laundered/transformed data at all, ever.
Just a thought experiment: considering training seems to be 'fair use', I wonder if they trained a tiny model to retain key info from your prompts, would mean that this would still constitute fair use, and allow them to legally claim they don't retain your data.
The guarantee on this is a (contractual) “trust me bro”, and a right to try to sue a multi-trillion-dollar company who will absolutely drive you into the ground with legal red tape.
If you are big enough to be able to withstand that, you’re already running (or trying to run) your own/open-weight models.
ZDR is based on the exact same pinky-promise as training opt-outs. There is no technical barrier to OpenAI, or whoever is running your compute, retaining your prompt after they run inference on their servers. If you don't control the hardware the model is being inferenced on, you don't control your data.
Abolish copyright and make it less ridiculous. Sampling music was never a thing that required royalties until the 1990s when I guess someone got angry that rappers were making money off their sampled music. Its insane to me. Make it illegal to transfer ownership of copyrighted work too, only the spouse or one single inheritor who isnt a company can have the rights transferred, after both die, the work enters public domain.
LLMs should just pay a flat fee to use a specific book and thats it. Fees should be reasonable (not a million dollars per book), so long as the model doesnt spit out the entire book.
One of the most infamous legal challenges to sampled music was MARRS "Pump Up the Volume" in the 1980s, and that was preceded by other famous cases. Not sure why you think that started in the 1990s.
> Make it illegal to transfer ownership of copyrighted work too, only the spouse or one single inheritor who isnt a company can have the rights transferred, after both die, the work enters public domain.
By your phrasing, it sounds like you still intend the possibility of companies owning copyrights; but how does that happen (other than copyrights already owned by companies grandfathered in)?
Copyright always starts off in the hands of individual human beings; it only ends up in the hands of companies when those human beings transfer ownership to a company. That ownership transfer can be automatic as a term of a contract, e.g. as part of a work-for-hire agreement. But no contract can cause the copyright to come into existence already held by the company instead of the individual. So if you abolish ownership transfer, you effectively make work-for-hire IP assignment invalid. What replaces it?
And, if "nothing"... then how do people pool the IP rights of their own small contributions to a large-scale work, into an IP pool that can be legally defended by a coherent legal entity, so that the large-scale work itself can have market value (i.e. so that sales of polished commercial bootlegs don't drive sales of the "authentic" work to zero)?
Keep in mind that, no matter how much we might want "mass distributed" media to have more-reasonable IP terms, the ability to sue for infringement is still critical to the existence of some forms of media. Especially "location-based" media, with no equivalent licensed broadcast right: movies still in theatre; concerts; live performances of plays and musicals; etc. If there's no legal team that can sue a movie theatre that shows an unlicensed copy of a given movie, then no movie theatre will ever bother with licensing movies again; "box office" goes to zero (from the movie company's perspective); and the incentive to create movies in the first place declines massively.
(You can see what this alternate world looks like from the few cases where movies screwed up the steps required to assert copyright, back before copyright was automatic. Night of the Living Dead (1968) is a good example: theatres — even upstanding large-chain theatres! — did indeed leap at the opportunity to show the movie unlicensed, and so Romero et al made effectively zero revenue off the work.)
I'm not saying this is an impossible problem. There are ways to accomplish this besides the way it's done now. (For example, individual-contributor IP could be retained by the original owners, but cross-licensed between individuals through a collaboration structure to form a coherent defensible IP pool, in exactly the same way that IP for e.g. video codecs is cross-licensed between corporations to form a coherent defensible IP pool today.) I'm just pointing out that the problem does need to be solved.
If the leading private labs attempt to use the government to pull up the ladder under the pretense of "safety" then the response of the people should be to take such questions out of private hands and nationalize the leading labs.
Or they could abide by the precedents they set and learn to compete. They shouldn't be allowed to have it both ways.
The problem here is you need a trustworthy government for nationalizing to make a difference. The current US admin started with DOGE and a crypto rug pull.
Morally I agree, but since there's probably a lot of LLM text in the training data, distilling on another model will probably make your model copy the values encoded into the other model as well, even in cases where you only distill on value-neutral stuff.
By copying their programming style, you'll move the model towards that way of writing, which will move the model towards the values expressed in those documents.
I feel that Deepseek v4 got so claudified at the end that it was like Claude.
There is nothing illegal about training on traces from frontier models.
However the frontier labs don’t have to serve customers who are farming the service for distillation purposes. That’s their choice and they’re free to make it if they detect distillation happening.
I would argue they should have to. They scraped data off others, a lot of whom did not want that data to be used for AI training, and still had to share it with the frontier labs. It’s only fair they should have to hand it back.
The only way US maintains dominance over Chinese models is by having an ecosystem of models. Relying on a small set of frontier labs will only let you get ahead temporarily. I agree with Gary Tan on this one.
Yes, I think this is the main issue. I don't care what policies the AI labs have or enforce, but they need to stop acting like ToS violations are an international crisis demanding intervention instead of a boring civil dispute at most.
All correct, just help me get over the idea of an open-weight Mythos where one or a dozen of us eight billion does something stupid on the bioweapon front. Smart people who’ve exhausted possibilities for what they can do with books and web search and today’s Kimi/GLM.
Figure we’ll have to reckon with this next year in any case, guess we’ll see.
You dont need an LLM to figure out to make anthrax. Anybody who can figure out how to make a home lab can make all sorts of dangerous stuff pretty easily. Same with college grad from a respectable chemistry program. This all FUD.
> He also notes that the proprietary AI labs didn’t ask permission when they vacuumed up as much human knowledge as they could to train their models.
I think this should desactivate the moral high ground from which Anthropic is trying to speak. That they would want to make distillation orderly IMHO is fair, but to make it illegal is very rich from any AI frontier lab, really.
Also, as said elsewhere: "Lab" is rich here, for outfits that, facing these giant, energy swallowing black boxes have really no clue what's going on inside.-
The moniker gives them an air of scientific, knowledgeable, tranquil, pro-social, pro bono work.-
Of course they are entitled to kill off a few mice, or pillage the commons to forward their "lab" work.-
“We don’t know what’s going on” is essentially marketing. Sure we don’t _know_ but we have intuitions about why, where, and how to make certain changes…
Those labs publicly said during GPT-3/4 era that the optimal epoch count, or dataset repetition count, for foundation model training, is one. So it's a forward 1-pass compression.
But it's a black box! Nobody knows whats going on inside! It's all transformative! Sure...
It used to be OpenAI was a real research organization that wrote real open-access papers that aren't marketing brochures, and when they did large training runs, they released all artifacts including model weights. Now certainly they are anything but. We haven't learned learned anything meaningful about ML from OpenAI since GPT-3 was released.
Their open-weights competitors like Facebook can at least claim some kind of public benefit, but it's still just running a well-understood algorithm on dubiously obtained data with longer and longer runs, give or take some inconsequential architectural tweaks.
Anthropic's mechanistic interpretability work is the most "lab-like" of these, but it's still just secondary to selling subscriptions and fear-mongering for regulatory capture/investment/publicity.
We also associate laboratories with evil scientists and Frankenstein and the like. I can just hear Boris Karloff (er Bobby Picket) uttering “I was working in the lab late one night. When my eyes beheld an eerie sight… … … …the monster mash”. If anything, I associate _uncertainty_ with labs. The result is never known up front, they’re a place of discovery.
But I get your meaning. What should they be called instead? AI Sausage Factories maybe (cue Upton Sinclair?)?
Even kind of fits the model. All of the creativity man has raised is herded to the slaughterhouse and ground up so we end up with a big homogenized mash of ground up creativity, devoid of the life that gave it, rotten if not eaten soon enough.
Both labs even explicitly promise the customer owns the outputs. It feels like they want to have their cake (ensure enterprises don't get spooked away from using as many LLMs as possible) while eating it too (still arguing some level of control over the outputs).
> Ownership of content. As between you and OpenAI, and to the extent permitted by applicable law, you (a) retain your ownership rights in Input and (b) own the Output. We hereby assign to you all our right, title, and interest, if any, in and to Output.
> As between the parties and to the extent permitted by applicable law, Anthropic agrees that Customer (a) retains all rights to its Inputs, and (b) owns its Outputs. Anthropic disclaims any rights it receives to the Customer Content under these Terms. Subject to Customer’s compliance with these Terms, Anthropic hereby assigns to Customer its right, title and interest (if any) in and to Outputs.
> Both labs even explicitly promise the customer owns the outputs.
> to the extent permitted by applicable law, you (a) retain your ownership rights in Input and (b) own the Output
If the argument is that the model itself is under copyright protection then "as permitted by applicable law" would be doing some heavy lifting. Assuming that were true, given that locally-run LLMs exist, what would be illegal: the distillation itself or the provision of service of the distilled model?
YC does better if its startups get open weight frontier benefits. Garry’s just advocating for his book, which is his job. Consider how much capital YC portfolio companies would have to burn until liquidity if they have to pay OpenAI and Anthropic, versus relying on open weight frontier capabilities.
> To him, the true AI doomer scenario is for all the immense power of frontier AI to wind up in the hands of a single powerful, proprietary provider. “The nightmare scenario, the doomer scenario for AI is that there’s just one company,” he said. “It has the best access to capital. It has the best AI researchers. It runs away with it and suddenly there’s one company that’s monolithic. And that would be bad.
Well yes, as I think I said in a previous comment, on the current trajectory OpenAI and Anthropic will really stop releasing models due to distillation and regulatory pressures. Then, they would eat all knowledge work themselves, which would be the end of YC.
I think OpenAI and Anthropic will go bust, or at least be scrapped for parts in the next 5 years or so. It's clear that the extreme cost used up for training is impossible to recoup, as inference is already being subsidized.
It's also clear that, as Tan indicates, open-weight models will be (and basically already are) just as good as frontier models. It's all about the harness, baby. We will have two main forks in the road, and two new industries created:
- AI hardware (NVidia/Cerebras/etc.), the equivalent of Intel/AMD
- AI software (harnesses, assistants, etc.) the equivalent of Microsoft/Apple
We already saw a glimmer of this with popularity of OpenClaw—the problem is that it's janky, hard to set up, inconsistent, and very hacker-esque. Imo "AI labs" will be a dying breed because there's no real money in the actual models if they get commoditized, which they already kind of are.
Inference is not being subsidized and in fact has pretty high margins.
Similar-sized open weight models on openrouter are 15x cheaper per token than the big labs. This should reflect the isolated cost of inference, since 3rd party hosts have no reason to subsidize and no training costs to amortize.
Only datacenter buildout costs are being subsidized.
> Inference is not being subsidized and in fact has pretty high margins.
I was referring to the "AI labs" here. Sam Altman himself conceded that OpenAI is losing money on the $200 subscription. Using open-weight/open-source models is indeed cheaper (and no reason for inference to be subsidized).
That's not what I mean. If competitors can offer tokens 15x cheaper, the big labs must have high margins per token. (which they can use to amortize training costs)
>Sam Altman himself conceded that OpenAI is losing money on the $200 subscription.
They have since stopped offering the $200 subscription, probably for this reason.
Subscription margins are harder to judge because it depends on usage; token costs are a better comparison.
If harness is all that matters, a co-developed harness + model stack + large compute availability advantage + massive distribution advantage with data for post training will win the market.
Controlling what users and customers do with API calls to closed weight models feels constraining, and there’s a role government can play here to normalize the fact that access to intelligence that was trained on broad public access data should itself also be more a form of a public good than something locked away behind restrictive terms of service
I do not agree with this man all that often, but that is very concisely put.
Society as a whole has paid into this technology: through the theft of its intellectual property, through having to deal with the pillaging of so many commons (digital or otherwise) by it, through skyrocketing energy and computing device prices, and even just through ordinary investment. Democratize the technology! At the very least, don't step in legally to prevent this from happening.
Distilling frontier models is a brute force approach that rapidly hits diminishing returns after bootstrap because of the unevenness of the data. The simpler and more effective method is to have dedicated "teacher" frontier LLMs to generate targeted training data sets specifically for training new models and adjust on the fly based on feedback from the student model.
Net neutrality anyone? If AI is critical to getting work done in the modern era, its access should be guaranteed. Anyone banned from accessing frontier AI is being forcibly left behind. This includes distillation.
Agreed! Allow US companies to innovate by creating an ecosystem of smaller, more efficient open weight models and it will be a net benefit for everyone. Distillation is a good thing.
Preventing token-consumers from developing competing products should be litigated as anti-competitive behavior.
Ok, but how do the economics of this work? Based on its settlement, Anthropic paid an average of $3000 per work they scanned based on their settlement (https://tech-insider.org/au/anthropic-copyright-settlement-2...). They and OpenAI pay billions per year for a mix of experts and normal people to label or create data. Why would they continue doing this if the value of this is immediately copied by open models? If your goal is to end the economics of generating and buying data for AI (and I recognize for some people this is really the goal) then sure, but if you want AI for various subfields of interest to continue improving then it's not workable.
Back when people made arguments for software privacy, the argument was usually "big business will still pay and consumers wouldn't have paid anyways so it's ok for us to pirate" - I actually think that was fine for business software but terrible for indie games, whose market was 0% businesses.
But in the AI case, it's not like they get to keep some of the value of their investment - it all gets cloned into models that businesses and consumers alike are happy to use. If someone knows how labs could continue to fund data creation and acquisition in this model, please do share!
They can’t they’re literally fucked, and it’s not society’s problem! The whole world doesn't have to bend over to make sure a couple of lunatics who believe they are building a doomsday weapon also have a viable business model
Surely if you hoover up every book in existence to feed into an ai model you must be extracting more than 1.5B in value. If not then it’s not a viable business.
Frontier labs trained their models on the entirety of human knowledge and didn't ask permission. It's a "want" or "should" it's a moral imperative to distill their models.
Given the short-term pragmatic, conflicted way that AI tech adoption is happening... won't encouraging distillation effectively taint the entire space of open weights models, with the undisclosed biases of a few models that are under the influence of parties (certain billionaires and politicians) known for aggression and duplicity, and not for admirable ethics?
Following news of companies and projects increasingly moving to open weights models.
As AI gets more central to society, we really need to know how the weights were determined.
Open weights isn't just "free as in beer"; it can be "free as in the mystery drug that creepy guy chatting you up at the bar offered you". And maybe even he doesn't even know everything that went into the tablets, since he too was being worked, by an organ-theft ring who will be harvesting both of you tonight.
That's an analogy to get your attention. Your LLM probably isn't going to steal your organs. But in the current environment, it does and will have ideological biases determined by those with direct and indirect influence over it. And there will be a massive market for commercial influence biases (look at how previous generations of adtech invaded almost all technology companies). And there's incentive for military and spying capabilities to be buried in the models, perhaps as long-term sleepers. Maybe some organized crime trojans, too, depending which model you pick up.
In this low-trust environment of the current real world, we need genuine open source models, not closed "open weights", and not mindlessly distilling black boxes gifted by sketchy powerful interests.
Distilled models are worse than the original, so you can’t fully compete. Also, if all frontier labs did that, there would be nothing left to distill from.
I see it as analogous to companies building fiber in the public ROW during the last big infrastructure bubble. Under the Telecoms Act, these companies had to allow competitors to use their fiber at a fair price.
Similarly, AI companies should be required to allow distillation at a fair price. Fair Use doesn’t make sense as a social contract if it only cuts one way!
But if they tried to set a fair price they would have to report how much money they are losing on each token sold. This might be bad for the real business of ai firms, hoovering up as much capital as they can
Garry Tan and Sam Altman recently did this interview together. They seemed pretty friendly with each other during it. Wonder what Sam Altman would say about Tan advocating for OpenAI’s models to be distilled.
Then again this is the same OpenAI that has gotten into legal trouble recently regarding Apple’s IP so who knows
This is all based on the delusion that Chinese labs are mindlessly distilling the frontier.
I would love for a US lab to be at or near the frontier with an open weight model, but it’s going to take some serious elbow grease, and yes some distillation (which btw OAI, anthropic et al, also use distillation of other’s outputs in their training)
Gates probably honestly believes in UBI; the guy is practical to a fault but evil misleading genius he is not. I actually don’t see any better options than UBI long term.
Only ways to rise in a UBI society where AI is supposed to replace intellectual work is crime and prostitution. Smart people who want better lives than the average will have to get into crime.
A UBI society doesn't mean jobs aren’t available. There most certainly will be jobs. But with UBI and universal healthcare, the jobs can pay whatever the market really demands. People always complain about the government subsidizing low Walmart wages for example, but with UBI that argument is moot. Liberalizing the labor market wouldn’t mean less jobs, it would mean more (we would also have to lean more on corporate and consumption taxes rather than taxes around employment which would also make employment easier).
I don't expect Tan's position to be based on any kind of real moral high ground, but his conclusion is correct.
I love the "illicit distillation attacks" framing from the incumbents. There's nothing illicit. There's no attack. You just don't like it because it threatens your market position and business model.
Obviously it's not possible to run a company whose value is predicated on its IP that uploads said IP to a third party which might get access to it.
This could mean every potential serious customer would have no option but to seek alternatives to these online services.
You have access to all the frontier models, but...your inputs are not shared with the model vendors...neither are used to train the next model.
Why am I even doing the Amazon board job for them!??
I don't mean this as rhetoric, I did not think many people (except possibly those operating under government contracts, and 'normies' who don't know about these things) were under the belief that their IP was kept secret when they use these services.
https://privacy.claude.com/en/articles/10023548-how-long-do-... (see the additional info section)
The services have toggles to allow prompts to be used in the training set. There is a conspiracy theory that the toggle is a false distraction and they’re actually keeping everything, and that none of the employees involved will ever whistleblow this fact.
Outside of Internet comment sections, I think most people assume these US-based companies are doing what they say.
For enterprise use there are services like AWS Bedrock which have strict isolation guarantees. There are some people who still believe those guarantees are a lie, but once someone has reached that point I don’t think they trust anything that isn’t running entirely within their house. People in that category are a very small minority, but a very vocal minority.
I think this is being misunderstood. Codex has a toggle to allow your prompts to be included in training data. They’re saying they can’t be sure if the person had it on or off while using Codex to discuss the work.
They’re not saying that some prompts are mysteriously jumping into training data.
Also, there is a large market for AI services which don’t retain anything under any circumstances for enterprise customers.
Besides, true ZDR is usually offered by third-parties with deals to host OpenAI models, such as Amazon (AWS Bedrock) and Microsoft (Azure).
If you are big enough to be able to withstand that, you’re already running (or trying to run) your own/open-weight models.
LLMs should just pay a flat fee to use a specific book and thats it. Fees should be reasonable (not a million dollars per book), so long as the model doesnt spit out the entire book.
By your phrasing, it sounds like you still intend the possibility of companies owning copyrights; but how does that happen (other than copyrights already owned by companies grandfathered in)?
Copyright always starts off in the hands of individual human beings; it only ends up in the hands of companies when those human beings transfer ownership to a company. That ownership transfer can be automatic as a term of a contract, e.g. as part of a work-for-hire agreement. But no contract can cause the copyright to come into existence already held by the company instead of the individual. So if you abolish ownership transfer, you effectively make work-for-hire IP assignment invalid. What replaces it?
And, if "nothing"... then how do people pool the IP rights of their own small contributions to a large-scale work, into an IP pool that can be legally defended by a coherent legal entity, so that the large-scale work itself can have market value (i.e. so that sales of polished commercial bootlegs don't drive sales of the "authentic" work to zero)?
Keep in mind that, no matter how much we might want "mass distributed" media to have more-reasonable IP terms, the ability to sue for infringement is still critical to the existence of some forms of media. Especially "location-based" media, with no equivalent licensed broadcast right: movies still in theatre; concerts; live performances of plays and musicals; etc. If there's no legal team that can sue a movie theatre that shows an unlicensed copy of a given movie, then no movie theatre will ever bother with licensing movies again; "box office" goes to zero (from the movie company's perspective); and the incentive to create movies in the first place declines massively.
(You can see what this alternate world looks like from the few cases where movies screwed up the steps required to assert copyright, back before copyright was automatic. Night of the Living Dead (1968) is a good example: theatres — even upstanding large-chain theatres! — did indeed leap at the opportunity to show the movie unlicensed, and so Romero et al made effectively zero revenue off the work.)
I'm not saying this is an impossible problem. There are ways to accomplish this besides the way it's done now. (For example, individual-contributor IP could be retained by the original owners, but cross-licensed between individuals through a collaboration structure to form a coherent defensible IP pool, in exactly the same way that IP for e.g. video codecs is cross-licensed between corporations to form a coherent defensible IP pool today.) I'm just pointing out that the problem does need to be solved.
Or they could abide by the precedents they set and learn to compete. They shouldn't be allowed to have it both ways.
By copying their programming style, you'll move the model towards that way of writing, which will move the model towards the values expressed in those documents.
I feel that Deepseek v4 got so claudified at the end that it was like Claude.
However the frontier labs don’t have to serve customers who are farming the service for distillation purposes. That’s their choice and they’re free to make it if they detect distillation happening.
The only way US maintains dominance over Chinese models is by having an ecosystem of models. Relying on a small set of frontier labs will only let you get ahead temporarily. I agree with Gary Tan on this one.
Figure we’ll have to reckon with this next year in any case, guess we’ll see.
Someone with that lab could almost certainly figure out how do something stupid or destructive on their own, or bypass model safeguards somehow.
I think this should desactivate the moral high ground from which Anthropic is trying to speak. That they would want to make distillation orderly IMHO is fair, but to make it illegal is very rich from any AI frontier lab, really.
The moniker gives them an air of scientific, knowledgeable, tranquil, pro-social, pro bono work.-
Of course they are entitled to kill off a few mice, or pillage the commons to forward their "lab" work.-
The Atlantic argued this (rather well, IMO) a week or so ago - "There’s No Such Thing as an AI ‘Lab’" - https://www.theatlantic.com/technology/2026/09/stop-calling-...
But it's a black box! Nobody knows whats going on inside! It's all transformative! Sure...
Their open-weights competitors like Facebook can at least claim some kind of public benefit, but it's still just running a well-understood algorithm on dubiously obtained data with longer and longer runs, give or take some inconsequential architectural tweaks.
Anthropic's mechanistic interpretability work is the most "lab-like" of these, but it's still just secondary to selling subscriptions and fear-mongering for regulatory capture/investment/publicity.
But I get your meaning. What should they be called instead? AI Sausage Factories maybe (cue Upton Sinclair?)?
That's actually great? Slaughterhouses killing off the collective genius of humanity and grinding it into a bland paste for mass consumption.
> Ownership of content. As between you and OpenAI, and to the extent permitted by applicable law, you (a) retain your ownership rights in Input and (b) own the Output. We hereby assign to you all our right, title, and interest, if any, in and to Output.
https://openai.com/policies/terms-of-use/
> As between the parties and to the extent permitted by applicable law, Anthropic agrees that Customer (a) retains all rights to its Inputs, and (b) owns its Outputs. Anthropic disclaims any rights it receives to the Customer Content under these Terms. Subject to Customer’s compliance with these Terms, Anthropic hereby assigns to Customer its right, title and interest (if any) in and to Outputs.
https://www.anthropic.com/legal/commercial-terms
Obviously there is some bad behavior going on in the distillation scene with gray-market token resellers but that is "just" normal fraud.
> to the extent permitted by applicable law, you (a) retain your ownership rights in Input and (b) own the Output
If the argument is that the model itself is under copyright protection then "as permitted by applicable law" would be doing some heavy lifting. Assuming that were true, given that locally-run LLMs exist, what would be illegal: the distillation itself or the provision of service of the distilled model?
ahem.. it happens even today, you can use open weight models directly and even fine tune
Well yes, as I think I said in a previous comment, on the current trajectory OpenAI and Anthropic will really stop releasing models due to distillation and regulatory pressures. Then, they would eat all knowledge work themselves, which would be the end of YC.
It's also clear that, as Tan indicates, open-weight models will be (and basically already are) just as good as frontier models. It's all about the harness, baby. We will have two main forks in the road, and two new industries created:
We already saw a glimmer of this with popularity of OpenClaw—the problem is that it's janky, hard to set up, inconsistent, and very hacker-esque. Imo "AI labs" will be a dying breed because there's no real money in the actual models if they get commoditized, which they already kind of are.Inference is not being subsidized and in fact has pretty high margins.
Similar-sized open weight models on openrouter are 15x cheaper per token than the big labs. This should reflect the isolated cost of inference, since 3rd party hosts have no reason to subsidize and no training costs to amortize.
Only datacenter buildout costs are being subsidized.
I was referring to the "AI labs" here. Sam Altman himself conceded that OpenAI is losing money on the $200 subscription. Using open-weight/open-source models is indeed cheaper (and no reason for inference to be subsidized).
>Sam Altman himself conceded that OpenAI is losing money on the $200 subscription.
They have since stopped offering the $200 subscription, probably for this reason.
Subscription margins are harder to judge because it depends on usage; token costs are a better comparison.
I do not agree with this man all that often, but that is very concisely put.
Isn't this exactly what Dario wanted? He thought he knew what's best for the humanity...
Preventing token-consumers from developing competing products should be litigated as anti-competitive behavior.
Back when people made arguments for software privacy, the argument was usually "big business will still pay and consumers wouldn't have paid anyways so it's ok for us to pirate" - I actually think that was fine for business software but terrible for indie games, whose market was 0% businesses.
But in the AI case, it's not like they get to keep some of the value of their investment - it all gets cloned into models that businesses and consumers alike are happy to use. If someone knows how labs could continue to fund data creation and acquisition in this model, please do share!
Not sure you get to count breaking the law and getting in trouble in your cost-of-doing-business. That's a little too on the nose.
You're basically arguing that a criminal syndicate must be allowed to continue and we're required to make their business model make sense?
Following news of companies and projects increasingly moving to open weights models.
As AI gets more central to society, we really need to know how the weights were determined.
Open weights isn't just "free as in beer"; it can be "free as in the mystery drug that creepy guy chatting you up at the bar offered you". And maybe even he doesn't even know everything that went into the tablets, since he too was being worked, by an organ-theft ring who will be harvesting both of you tonight.
That's an analogy to get your attention. Your LLM probably isn't going to steal your organs. But in the current environment, it does and will have ideological biases determined by those with direct and indirect influence over it. And there will be a massive market for commercial influence biases (look at how previous generations of adtech invaded almost all technology companies). And there's incentive for military and spying capabilities to be buried in the models, perhaps as long-term sleepers. Maybe some organized crime trojans, too, depending which model you pick up.
In this low-trust environment of the current real world, we need genuine open source models, not closed "open weights", and not mindlessly distilling black boxes gifted by sketchy powerful interests.
Ban data brokers before you ban distillation.
Similarly, AI companies should be required to allow distillation at a fair price. Fair Use doesn’t make sense as a social contract if it only cuts one way!
Garry Tan and Sam Altman recently did this interview together. They seemed pretty friendly with each other during it. Wonder what Sam Altman would say about Tan advocating for OpenAI’s models to be distilled.
Then again this is the same OpenAI that has gotten into legal trouble recently regarding Apple’s IP so who knows
I would love for a US lab to be at or near the frontier with an open weight model, but it’s going to take some serious elbow grease, and yes some distillation (which btw OAI, anthropic et al, also use distillation of other’s outputs in their training)
They know it won't happen, so arguing for it is 'effectively free' and purely personal marketing.
A bullshit game played by politicians and wannabes.