I am saying this probably is "silly behavior by a government" and it is a milestone that points towards what the future may look like. Why can't it be both?
It's easy to wave this aside as the current administration playing political games. But I don't think there is any reason to assume that the current era of open availability of models is going to continue indefinitely. Do you think that Chinese labs will continue to release open models forever, even why they get to the level that Mythos is at now, and beyond? And do you think that a competent US government would have no interest in regulating and restricting model access in 2 years time, assuming that model capabilities continue to improve? I think we bias towards thinking the status quo is the norm and will continue, but this news invites us to question that assumption and think about different ways the future could go.
> Do you think that Chinese labs will continue to release open models forever
Yes.
I think the Chinese government either already has, or will soon, grasp that if they train the models that people use they dictate what people believe (at least around the margins where that's malleable), and they will happily throw resources at that.
And simultaneously that the only way they can actually get everyone to use their models is if it's possible for us to run them on our own hardware.
This is going to age very poorly when the best Chinese labs ALREADY just started not open sourcing their models.
Qwen 3.7 is not open source; previous Qwen versions would have open source releases, but Qwen 3.7 plus does not. The second best Chinese model, Minimax M3, is testing the waters by taking longer and longer between “model release” and open sourcing it. This time, they spent 2 weeks after release before open sourcing it. There’s also a lot of rumors of GLM and Deepseek not open sourcing future models.
It’s pretty obvious that you cannot take Chinese models as open source for granted, they’ll be closed source soon.
If we're measuring progress in hours and days then yes. But if we're measuring progress in months then OSS models are doing fine. You can get a state-of-the art performance in an open model if you pretend it is January 2026 instead of June.
There is no evidence here that the cutting edge labs have any durable advantage. Extrapolating current trends it seems likely that even the Europeans will be capable of meeting any given performance measure with enough time. In fact the evidence suggests that the capital required to run the models is where a moat will develop. Knowing the weights won't help much.
Minimax M3 too, and huawei claims to be releasing non-nvidia dependent training software too. openPangu 2.0 could be a shake-up if it holds up as a good model
China may not care about open source, but they know they will personally fund AI through government investments while US relies on private investments, best way to scare private investments is a free capable alternative for everyone
Add on the fact that they actually invested in energy infrastructure and can offer AI very cheap to their citizens and you can get a population well versed in AI to reduce menial tasks and focus on more productive things (if we're to believe the claims of the technology)
The best chinese models are deepseek (general purpose) and glm (coding) and they are both open weight and share lots of their tooling.
There are lots of AI companies and it doesn’t seem that they all have the same funding fountain or share monetization goals. I wouldn’t read much into what each one of them is doing.
Even if the models by the Chinese labs are open source or open weights even after they get to mythos level intelligence lets say, still inference and the optimization of those models to be accessed at speeds of 1000 tokens/sec in not in the hands of general public as these models have parameters more than a trillion and they can't be run on some publicly available hardware, So even after being open source it does'nt fix the problem as the general public will still pay the company for inference.
I'm pretty sure these large models are run on Nvidia GPUs, not some unobtainable piece of secret kit. You could go down the street and buy from AMD or a number of other vendors to push out FLOPs if you wanted or needed, but you'll need a thick wallet to shell out for a cluster of GPUs to run these models. The reason people don't run the big Chinese models at home is that they can't afford the hardware, not that it isn't publicly available. This tech is essentially a large amount of matrix multiplications afterall.
I think the larger problem is that restricting US AI companies gives the Chinese a leg up because they now have a window open where they can become the source of the most powerful models available due to government restrictions rather than on technical merits. All Anthropic customers just got a downgrade last evening, for example. While the Chinese are able to serve the world or whoever, the US corporations will be limited to the US market, or whatever the powers that be will allow. This restrictiveness could turn out to be disadvantageous to American companies since people will migrate to wherever they can get the most powerful models.
> The best chinese models are deepseek (general purpose)
DeepSeek is developed by the largest Chinese hedge fund, their models used to make them $ on the share market are very profitable, they've never ever released anything on those models.
Somehow you are claiming that those same group of people are going to totally change their very consistent long term behaviour and start promoting openness when they are in the global leading position in AI?
The main reason the Chinese labs are releasing models as open weights is because they don't have the compute necessary to provide all of the inference. For the US frontier models something like 80-90% of the lifetime compute required for the model is inference rather than training. China wants to shepherd as much of their limited compute as possible towards training to keep up in the race.
I think the main reason is to minimize the market for closed-source models from US companies.
China knows that doing what Anthropic/OpenAI/Google/... are doing is impossible for them. No one outside of China in any sane condition will send their data to compute farms IN CHINA like people currently do with US-based frontier models. Even if they could muster the inference power.
Hence they do the second-best thing possible to attack the dominance of the US-based corporations: reduce their moat by open-sourcing models that are not fully equal, but practically useful and good enough for easily 90% of typical tasks people use agents for in their daily lives. But way cheaper to run.
As long as this arms race in AI continues, China as "number two" will have some incentive to continue open-sourcing models. But of course the US government might force a change if they continue to enforce limited public access to new frontier models - there is no market to minimize if a model is not allowed to be publicly available.
But at work the calculus is entirely different. There is already lots of exposure to US companies (guess where our emails and tickets life), so the increase in espionage risk from adding another American company is small. Not zero, and trust towards AI companies is limited. But adding the first Chinese company to send data to would be a major risk. One nobody would sign off on, given the general reputation of the Chinese economy for widespread espionage, disregard for copyright and producing copies of successful products using insider information
Not sure why anyone in the EU thinks the US is not a significant espionage risk. Adding any major US supplier would have been a significant espionage risk until really recently.
Before the EU cleaned up Europe's act pretty considerably on corruption, US companies used corporate but also state-level espionage actors to level the playing field against a culture of bribes and they were fairly open about it. They absolutely needed to do it, because of the potential penalties back home if they engaged in bribery abroad.
The tables have turned, now. The EU runs much more cleanly than decisionmaking in DC, which is clearly corrupted and lubricated with cash and opportunities for failsons and faildaughters; it has accelerated radically quite recently but it was heading that way from the first Bush era.
But I'd bet the corporate-state merger of industrial espionage is in full flow.
This would require active participation by people inside Anthropic and OpenAI. Given how generally ideological the people working in these companies are, I'd be willing to bet that we would already be reading Snowden-style leaks if it were true.
I have zero expectation that a similar culture exists inside Chinese companies. If you think these corporate and national cultures are the same, you need to adjust your priors.
> This would require active participation by people inside Anthropic and OpenAI.
Not necessarily of the companies themselves, though; just embedded people at the right hiring level.
> Given how generally ideological the people working in these companies are
History has many examples of truly surprising spies, over the long term. Including in highly ideological environments such as animal rights and eco-campaigning groups. The embedded police spying scandals in the UK make this clear.
It is naïve to think that there are no CIA or NSA employees in some functional role at these two businesses, just as it is naïve to think that they don't have intelligence industry contacts playing them because they are naïve. You only have to look at how the NSA weakened open cryptography to see that two companies staffed by young, absurdly rich people barely out of college with wobbly moral e/acc compasses might be getting played by homegrown spooks.
> I have zero expectation that a similar culture exists inside Chinese companies. If you think these corporate and national cultures are the same, you need to adjust your priors.
I suggested absolutely nothing of the sort — I flatly was not talking about China at all.
FWIW it cuts both ways: in the dim and distant past of the early dot-com era, I remember encountering someone who wafted inexplicably between US and UK multinational companies who I thought was possibly British intelligence. An odd duck for sure.
> given the general reputation of the Chinese economy for widespread espionage, disregard for copyright and producing copies of successful products using insider information
Quite funny because if you use that phrase verbatim except swapping China with the US it could actually fit.
Good governments try to do things that are in the interest of their population, and yes it could mean opposite interests to your/someone else governments.
No reason to blame US, Israel, China, Russia, etc. They just defend their piece of cake.
Anthropic and OpenAI are not just "another American company", their entire business (and industry) was created based on stealing data and using it for profit. You make this point about "another company" so casually that you'd think you added a SaaS bill for generating thumbnails or whatever. The exact same point you make about China can be made much more confidently and with stronger evidence for the entire modern LLM lab industry.
Again I have to echo the previous poster's point: Most people outside of the US really do not see the US as some much better alternative than China. If anything, in the specific area of LLMs, China are the ones doing work benefitting the everyman whereas almost everything the US labs do does not.
That's why I added "Not zero, and trust towards AI companies is limited". Reaching the decision that adding one single US-based LLM provider had more benefits than risks took months. And we were selective about who that would be (hint: not OpenAI). And I know companies who are not willing to go that step, using open-weight models on their own infra instead. But outsourcing inference to China was never even a serious suggestion. The notion is absurd to us
That said, I imagine e.g. South Americans thinking very differently on this front
China indeed has a general reputation for widespread espionage, so any Chinese company wanting to expand into the European market has to prove it isn't spying on its potential customers. US companies have traditionally been seen as friendly, so their platforms are essentially built around "trust me bro" guarantees.
In a world where both China and the US are now seen as hostile-by-default, this might actually leave some Chinese companies with an advantage in their ability to demonstrate trustworthiness.
The blurring of US state and corporate espionage in the EU is the stuff of legend. They have always spied, and you can easily make the case that in late 1980s/early 1990s Europe they had good reason to, because European businesses were corrupt.
Totally agree, though it is an unpopular opinion here.
It’s the same paradox as people claiming: “we are European, our data is safer in Europe” when actually your privacy is higher when your data is stored in China (or Russia) you are safer because it is out of reach from your local government.
The only thing I dislike, and that’s no matter the service, is that my data or information usage is shared with third-party.
For example, Anthropic conveniently forgets to mention Datadog has tons and tons of information about Claude users, or that your data transits through machines they don’t operate.
Safety has more than one definition. Being able to sue the company in small claims court when it threatens to delete your account is also part of that, and so is being able to pay for the service when Russian companies are once again put on a sanctions list.
China wants everyday people data because some of those people will get power one day, and China wants to be able to leverage knowledge of you, perhaps even "deep dark secret" data, if they need to.
Israel already does this through Epstein information from all the cameras and microphones that were listening and filming all the powerful people who visited the Island and the houses. They probably have a new Epstein already.
was going to say this.. open sourcing Chinese models will enforce Chinese dominance instead of reducing it. When an open Chinese model becomes the best alternative to inaccessible closed US models guess what everybody will start to use. And that same open model may embed certain narratives and values that please the Chinese government.
Ya. You know enough about China to know: would they be willing to sell users outside of China models that aren't fully pro-China (and won't deflect on tough questions)? Or would that be dirty money that they wouldn't want anyone to make?
Like if they could release Ch-ythos 6 tomorrow BUT it had Western ideals, would they take the fame, clout, attention, & profit, or stick to the party line?
(hope the monolithic brush is appropriate, considering, I mean it's an impressive system/country even if I have my own strong preferences - also I've taken as true reporting about their models deflecting etc. on sensitive topics)
The US administration restricting the use of US-trained models is one of the best gifts it could make to the Chinese LLM producers, and to the PRC government.
I won’t forgive Biden for not reversing more of trumps policies, especially immigration
Between RBJ refusing to step down, Biden not reversing immigration policy, and Biden refusing to step down in the primary until too late, he’s going to go down as a poor president in the history books - even if he wasn’t a bad dude or even bad in terms of policy.
Trump was also getting senile before they attempted to assassinate him. Hatred of his enemies gave him another 5 years of energy. Very frustrating, because he absolutly was doing word salad nonsense like this regularly before someone tried to shoot him:
"Look, having nuclear — my uncle was a great professor and scientist and engineer, Dr. John Trump at MIT; good genes, very good genes, OK, very smart, the Wharton School of Finance, very good, very smart — you know, if you’re a conservative Republican, if I were a liberal, if, like, OK, if I ran as a liberal Democrat, they would say I'm one of the smartest people anywhere in the world — it’s true! — but when you're a conservative Republican they try — oh, do they do a number — that’s why I always start off: Went to Wharton, was a good student, went there, went there, did this, built a fortune — you know I have to give my like credentials all the time, because we’re a little disadvantaged — but you look at the nuclear deal, the thing that really bothers me — it would have been so easy, and it’s not as important as these lives are — nuclear is so powerful; my uncle explained that to me many, many years ago, the power and that was 35 years ago; he would explain the power of what's going to happen and he was right, who would have thought? — but when you look at what's going on with the four prisoners — now it used to be three, now it’s four — but when it was three and even now, I would have said it's all in the messenger; fellas, and it is fellas because, you know, they don't, they haven’t figured that the women are smarter right now than the men, so, you know, it’s gonna take them about another 150 years — but the Persians are great negotiators, the Iranians are great negotiators, so, and they, they just killed, they just killed us, this is horrible." - Donald Trump, 2016
Technically his material support to a genocide makes him complicit, it would not have been nearly at the scale without US support tens of thousands of women and children were murdered as a direct result of his decisions[1], if international law meant anything we would hang him for that. So no, he was a "bad dude".
It's funny how the acceleration of the downfall of the US (due to trump) is a gift to everyone else. It's almost as if US didn't have as postitive impact on the world as they thought.
A gift to [every dictatorial regime]. It's not a gift to the common people. The hundreds of thousands of people who got aids, and wouldn't have if not for Trumps withdrawal, didn't benefit. The women of Afghanistan didn't benefit. The countries of the EU... Canada... Korea... Taiwan... Ukraine... really just about any democracy didn't benefit.
The downfall of the US benefiting bad people is not evidence that the US didn't have a positive impact.
There's also the Meta motivation, that even if you don't get the control you would like from releasing a model, it may still be worth it to at least deny others that control. I'm sure that matters even more to China vs. the US than it mattered to Facebook vs. Google.
> I think the Chinese government either already has, or will soon, grasp that if they train the models that people use they dictate what people believe (at least around the margins where that's malleable), and they will happily throw resources at that.
that doesn't require the model to be SOTA, it can be just a compact model capable of running on some inexpensive hardware. that is vastly different from SOTA models like Mythos which can potentially disrupt lots of things.
Of course it requires SOTA, people will always choose better models over some compact thing that is obviously more limited. You can't control the truth with models nobody wants to use.
People choose SOTA right now because of the heavily subsidised model subscriptions. People aren't going to pay 20x the price for a model that's maybe 10% better.
Because you communicate with it using natural language and real-world references and descriptions of what you want, you use emotion and emphasis (especially when re-prompting), you use examples and illustrative stories and common expressions. Understanding and interpreting all of that and replying in kind, to some degree, requires a large body of non-computation, cultural knowledge, or else the prompts are just meaningless words, and the replies will look like compiler output.
That sounds intuitively true, but I’m not convinced that it is actually the case. I don’t think we know enough about neural network training to say what training and how many parameters are necessary for what kind of performance on which tasks. To me it looks like we currently guess that more is better and try to throw as much compute and data at the problem as is economically feasible. There is little incentive for companies to invest into small model research since their moat is huge models that require special hardware to run.
Is the government going to fund all further development? Hard to imagine investors continuing to throw billions at products they aren't allowed to sell.
Honestly, with the caliber of people who currently comprise the US administration; leaving the whole thing to Openclaw and some new fancy model might not be the worst idea.
Yeah, there’s been a lot of debate about this on r/localllama — will there be a steady supply of new free/open models in the future?
And if not, can we simply keep augmenting “stale” models with new knowledge to keep them useful?
I’m on the pessimistic side of things on both questions.
As for the second question, obviously stale models can be augmented to an extent but it’s nowhere near a substitute for new knowledge being fully baked directly into its training.
> I am saying this probably is "silly behavior by a government" and it is a milestone that points towards what the future may look like. Why can't it be both?
Here is why it's unlikely this is anything other than "silly behavior by a government":
- some benchmarks show GPT-5.5, Gemini 3.1, and even Claude Opus outperforming Claude Fable, and yet it's Fable which is restricted.
- some benchmarks still show the likes of Kimi 2.5 outperforming any Claude model, and DeepSeek is getting equivalent scores (a few tenths of a percent difference)
> Do you think that Chinese labs will continue to release open models forever (...)
That's immaterial to the discussion. Even if China forced Chinese labs to restrict access to all models, the truth of the matter is that Trump's administration to restrict access to US-based models does not prevent others from having access to models that are as capable or even better.
You’re completely overrating these benchmarks and it’s landing you at a nonsense opinion. Just actually use the models and you will see that the gap is significant.
It should be easy for a company like Anthropic to prove this beyond a doubt. Why don't they? Why don't they have a collection of prompts and side-by-side comparisons with other models showing how far ahead they are?
I think it's mainly because the difference in models at the frontier isn't "response to prompt X", but rather "coherence with 500K tokens of context and instructions in play"
All that says is some benchmarks aren’t worth the tokens it takes to evaluate them. Mythos is clearly capable of finding zero days other models can’t, and Fable is close enough to be lumped with it.
> Mythos is clearly capable of finding zero days other models can’t
I'm unconvinced that this is anything more than proof of work and marginal improvement that other models will catch up with, perhaps as early as to next week. Lots of other current-gen models will find vulns that can be chained together if you're willing to burn enough tokens on the task, and Fable is an absolute token incinerator.
So many comments here missing the big picture, and just gleefully pointing out that Anthropic got what they deserved, or that this is the natural culmination of some kind of marketing stunt.
The real story here is that this may be the beginning of governments restricting the availability of strong LLMs to the public, to you. Fable was the strongest model on the market, and the US government has told you you can't use it (technically, only if you're not a US citizen, but in practice, even if you are). If you think the solution here is going to be open source Chinese models and / or running on your own hardware, think again. Do you think China is going to allow the strongest LLMs from companies within its borders to be open source a year from now when they have Mythos capabilities, if the US government is keeping the strongest American models back? Unlikely. These are heading in the direction of being powerful cybersecurity weapons and it will be in the interest of nation states to restrict and control them. In 2 years time, I would be surprised if the strongest LLMs are available for general use at all.
Will we be the poorer for that, or will we be safer? I think poorer, because I hate being told what technology I can and can't use, but I'm not certain. Maybe you think the government should restrict strong LLMs. Maybe you don't. But either way, this is big news and a rubicon has been crossed and a precedent set. That's true even if the motivation for this is just the government settling scores with Anthropic.
Yes! I mean everyone is speaking about this in a boxed manner.
For all we know there are might be several reasons for that ban e.g.
1) There is an actual security threat and its just simple as that.
2) Someone wants Anthropic to be valued way higher and the companies that have invested in Anthropic already... This ban only validates this product and will move the market in higher valuation of Anthropic due to their model being "so good gov had to ban"
3) Someone doesn't like Anthropic and just wants to shut down its current edge (highly unlikely, if there was no IPO filing in place it could be possible but now the valuation just goes up, same as the 2 As that have invested in them)
4) Someone freaked out that we'll be left out of jobs soon so wants to slow down progress, tbh using fable so far I can tell that a lot of jobs can be made redundant cause of that...
For me the most likely for now is 2, then 1 and then maybe 4.
On June 22 Chatgpt will most likely come out with their new model too, which as I understand will be an answer to mythos. Lets see if the US gov goes the same route.
It's not that complicated. Probably what happened is just that a former Fox News host read part of a security report that he did not understand and overreacted.
I do not understand why it being mandated that the vast majority of the people in the world will not allowed to use -- or pay for -- your product (and that the ones that can will have to jump through excessive hoops) could ever make your valuation go up; can you walk me through that one?
Even if this is just temporary, your #3 is more in direct conflict with #2 than you seem to be willing to admit: if you were to own stock in a company that you know has a powerful product and a market lead, but they have been required to take a time out in the market for a year, that should be devastating for their valuation.
Because nowadays the stockmarket is build upon hype, this is why we are having the market caps and valuations we are having that are in any way shape or form reflecting anything that is real.
For the Gov to come out and block a model for national security, its gonna swing the market into thinking "oh anthropic really has the next generation of LLMs out there, its that good Gov banned it, this company is going to the moon".
The part of banning non US nationals, I believe is a legality, as in they have to trust US citizens to do right by their country. I don't think in court a whole ban on a product for security reasons would stand. (The judge would ask for the gov to explain why all US nationals are a security threat to their country)
Nevertheless, again I am standing behind number 2 personally as the main reason for such a thing, market manipulation is not new and its currently at its all time high. Also anthropic is part of this manipulation so far, with every other AI company out there.
Again I am just presenting my POV, it could as well just be number 1... A gov became competent enough to find security threads before they happen :)
I get what you mean but you are very wrong about the stock market and how people react to export bans. Everytime US had restricted control for Nvidia chips in the news over the last few years, the stock price went down not up.
It might be a good marketing trick but it is not a good thing in the stock market given historical trends.
Your view highly screams you only have a superficial understanding of financial markets and you shouldn't extraploate that to "this is how market works because its all hype and everything is vapor"
You can't justify trillions of market cap just serving the US market, and they've just kneecapped their ability to compete anywhere else, it would be delusional to invest on something like this thinking it's going to be a free market, you'd just be indirectly funding the US government ability to use AI against others, especially if you are a non-US citizen (or a subgroup of US citizens they don't like). The near-term world-ending is just pure marketing, they haven't shown anything nearly as impressive as they've been promising, and the software they've produced so far with near infinite access to agents has been very impressively bad.
No, its not apples and oranges. How/why does it boost their IPO directly? Elaborate on this please instead of stating it as an universal fact (because it isn't).
I feel you are just talking a hypothetical without having any basis. You think it'll have an impact on IPO directly and that it will be a positive one. But you have no proof or historical precidence for the same. Meanwhile we have historical proof that markets reacts negatively when a company is blocked by the government on selling their top products freely. And that is most likely going to happen here as well.
Public perception might be changed by these "ohhh its so scary guys" marketing but these don't translate to actual market perception when it comes to actual facts and numbers on the financials.
It could be the case that we’ve reached the last generation of frontier models that can be accessed by the general public. That eliminates a risk that Anthropic could be leapfrogged by a competitor.
Now it’s a competition between products on the near frontier. Anthropic has executed well on products so far. They blew up thanks to Claude Code, not Opus by itself.
If (1) then somebody in the administration messed up badly. Glasswing has been a thing since April, and it's common knowledge that there would be some fuzzy edges around whatever restrictions a model has in place. There's no reason to let it launch and then pull it back.
(2) This "hype" meme is overrated. Enterprises (ones without a horse in the race, at least) will choose the model their best engineers ask for, or their competitors will lap them. I have been finding Codex more useful (even than Fable) but for a lot of tasks it seems that Claude Code is faster. This is one customer base where the general consensus here on HN is more influential than anything the Trump administration could do or anything Anthropic could say.
(3) "US government seems out to kill you" does not necessarily make valuation go up, and we've already seen this administration in an avoidable spat with Anthropic.
(4) This seems way less likely than a mix of (1) and (3) to me. The arguments for banning a useful technology to save jobs haven't really made sense since cars or indoor plumbing and don't get taken too seriously in either party at senior levels. That could change but it will take a lot for it to change.
Eh, chatGpt coming out with a new garbage model. Great.
Fable had some really good cross project awareness. My only complaint is it backported a feature to my test application and then they killed it before I could finish debugging it. The new model behavior in the replacement application was 100% superior. I just didn't know it was going to start porting fixes so readily between projects. Awareness in the new model is amazing and the feedback I've had from other developers is the same. It feels like ultrathink with double the agents of xhigh effort. The real issue is they shipped it with incomplete guardrails and someone likely found an exploit.
5) Someone freaked out China might use the model to advance its own tech. It's always China with this administration. The guy has an obsession with China since he had to hire feng shui consultants to make his tower appealing¹ for Chinese customers.
Also, might be a way to further screw with Anthrophic because they refused to remove their guardrails Pentagon, getting the opposite result of what was intended.
The Trump administration has exactly one motive, and that is accumulation of wealth. There is literally no other reason they would do anything. Even if there were legitimate economic or security concerns, those aren't motivating to the Trump administration.
This is about grift, somehow, full stop.
I neither like nor support Anthropic, but there's just no sense in pretending the Trump administration is anything other than a kleptocracy or interpreting their actions under any other lens.
Not in the same way, no, because they have not been targeted, while they should have if the same rules applied, according to Anthropic's depiction of the situation.
This is potential tyranny aimed at Anthropic, specifically.
Europe doesn't seem to care so much about erratic and hostile governments when it cozied up to Russian gas for decades, something it still continues to do just hiding behind third party countries.
It's a clear statement that European morals are purely performative
Just like how the EU is hostile towards US companies, but very light to the touch when it comes to corruption with HSBC, FIFA or VW. With such hostile and erratic allies, who needs enemies?
Let's not even get into Orban. You can never trust the EU again since who knows if they're capable of electing someone like that in the future? Trust is broken forever
Imagine a private company invents a piece of technology soooo good that the US government has to issue a ban.
Apple's G4 was banned for export. Although it was not a direct order from US government. They fell into an outdated bracket of computing power exports limits. They sure did use it for advertising it.
> Anthropic got the most rewarding hype ever in the history of mankind.
What? Anthropic is not a TikTok sensation. It's a business tool. Businesses need to know their tools work reliably.
When you are situated in a banana republic and the chief banana is out to get you (and demonstrates that they can and will on a whim) that is not great hype but a potential death sentence for you as a service provider.
You are one degree away from becoming forever branded as unusable. (Theoretically until people trust that a sane administration is in control again, but that might as well be forever on current AI timelines, given how much cashflow you need just to keep going)
It pretty much is. Claude is more of a meme than a tool. It's been second best (and more expensive option) for most of the time but people somehow keep talking about it. I'm getting strong Apple vibes from this one.
It's only rewarding hype if the ban gets dropped. If "foreign Anthropic employees that live in the US can't use Fable/Mythos" stays it harms them, if they don't drop the ban and Fable/Mythos stay limited to "every single person who uses the model must individually provide their ID to prove American-ness" it harms them.
It is already a rewarding hype. They are the first company to build a model so advanced that the US government has to ban it.
Google and OpenAI will eventually catch up and be banned as well. Therefore, this ban isn't really a huge concern for Anthropic since their competitors will be banned eventually.
All this does is proving to investors that Anthropic is indeed ahead of its competitors.
>OpenAI will eventually catch up and be banned as well.
" We have reviewed a report that we believe is the basis of the government's directive and validated that the level of capability displayed there is widely available from other models (including OpenAI’s GPT-5.5)"
The administration just doesn't like anthropic. OpenAI is in bed with the trump Administration.
Anthropic refused to allow the US Government to conduct mass surveillance, which made the US Government mad. OpenAI was fine with it as long as it was 'legal' mass surveillance. OpenAI is not going to get banned, even if their next model is both better and more dangerous than Mythos.
No, Anthropic refused to allow the US Government to conduct mass surveillance on US Citizens, they where fine with 'legal' mass surveillance of other countries.
What they know right now is that the model is so advanced the US government has to ban it, and the model comes out of Anthropic. Not Google. Not OpenAI.
Most valuably, they have a plausible excuse for hitting a financial brick wall before failing to deliver on years of over-promising on real-world business utility.
Expensive marketing stunt if users demand refunds from their credit card company for those annual subscriptions on the basis of "service not delivered".
Paying for 365 days of service but getting 364 would normally get you a full refund, not just a 1 day credit according to visa/MasterCard rules.
Anthropic got out a slightly better model (which is what two companies were doing for more than a year), but at the cost of not being able to provide it within subscription. It build out an inordinate hype around this model. And in the end it was saved by this hype because it doesn't have to admit now that it's never gonna be able to provide this model in volume because gov forbade them from providing it.
> Do you think China is going to allow the strongest LLMs ... a year from now when they have Mythos capabilities
"Mythos capabilities" is not some magic threshold. This is exactly the type of language that people used about GPT-4 in 2023. Today, I can run models far stronger than GPT-4 on my laptop at speeds better than GPT-4 offered.
Anthropic are quite good at coining sticky phrases like "Mythos-class models", but these are manipulative attempts to shape the discourse for business purposes and should be identified as such.
To be fair, they were proven right about automated spam, phishing and disinformation being a problem.
Yes, some of it looks silly now, though it's always easy to criticize with hindsight: the models could do unexpectedly impressive things and we didn't fully know the limit yet, it was a black box.
Remember you're critcising the org that actually made it public to people earlier than any other: the uncertainty was a temporary caution. The "open" in OpenAI was because they made it available, unlike Google at the time.
> I hate being told what technology I can and can't use
Ever since the original GPT-2 "it's too powerful to release!" I've realized that whatever is the current state of open models represents what we really have access to.
It's shocking to me how many people on HN, who engage in long conversations about LLMs and AI, have never actually run a model on their own hardware.
All you need is a reasonably good macbook pro/studio or an RTX [3-5]090 and you can run useful models in the >= 30 tokens/second range (much higher if you choose the GPU path). The difference between what you can run on this hardware and what you can run on hardware that costs 2-5x is not that big. Don't be fooled by people on Twitter/X claiming you need some outrageous setup.
It's also increasingly clear that frontier models are nowhere near close to pushing the limits of efficiency. Quantization, MoE, and other techniques have dramatically improved even in the last year.
For work, of course use OpenAI/Anthropic models, but for anything personal, anyone who considers themselves a "real engineer" should be running local models, using open harnesses and seeing what they can accomplish with these.
Even if open releases slow down or even stop, we have the foundation, right now, for smart engineers to squeeze something quite useful out of. Hopefully we'll one day figure out how to train large models in a federated way. But either way: not your weights, not your inference.
Personally I am fine with the SOTA from last year if I can run it on my hardware and who gets access to my data and history. I don’t really care that it could be marginally better using a model I cannot control on someone else’s server.
I am not fine with that. I have ranted about this before, but until recently the sota models were not intelligent enough for most of my work.
Yesterday Fable 5 finally solved a non trivial problem I had (after working on it for a few hours), and I went to bed excited. Waking up to find that Fable 5 is not available anymore, I guess I should feel happy I have the code it produced yesterday. But frankly I feel like a child having their candy taken from them.
We need open available models as smart as the current US proprietary ones. If intelligence like that becomes common property, i forsee a better future for human kind!
I'm a European, the EU is supposed to be one of the closest allies of the US.
The US government found a jailbreak that allowed the user to make Fable do bad things, this is so dangerous that this model must be held back in areas that are not the US...
If this is so dangerous why allow US nationals access to it? Are there no evil people in the US?
Going back to my perspective: let's say I control a big enterprise or a government body, how should I view this or US technology? Should I be like: yes, let's use US tech, they are a reliable partner and would never abruptly cut us off! Or should I be like: there are competent alternatives out there and if your work hinges on wether or not you had access to Fable 5, then your business is probably not going to survive for long.
Back when Snowden leaked all of the spying information, the only thing the States cared about was whether they spied on their own citizens. The fact that they spied on the citizens of their allies, including yes, the EU, barely made the news.
I don't think it makes sense the assume the US considers any country its ally.
sorry that's what I meant: I remember watching their depositions or whatever they were called, and their only concern was whether or not they had spied on US citizens. Whether or not they spied on their allies, I do not recall any coverage of from their primary news outlets (or inside their depositions) at all.
I agree with the sentiment and dislike Kissinger, but that quote is always paraphrased and out of context.
The full quote makes it clear Kissinger was saying, in the context of the Vietnam War, that the US should come to the aid of their friends:
> "Word should be gotten to Nixon that if Thieu meets the same fate as Diem, the word will go out to the nations of the world that it may be dangerous to be America's enemy, but to be America's friend is fatal."
I'm well aware of its context and original meaning, and I'm very happy to twist its meaning into something Kissinger would disagree with any chance I get.
It shares that intelligence with the countries it was gathered from. It's been explicitly stated many times that this is an intentional work around for weak constitutional provisions on protection of citizens.
I spy on your guys. You spy on mine. We all share notes.
This isn't a "The US vs. The World" this is "The Wealthy vs. The Poor."
Training best models is hella expensive. Anthropic spent fortune to train it, and it definitely plans to make a fortune with it either. This US decision, if not reversed, would cause Anthropic potentially tens of billions of dollars of revenue loss. When company heads to IPO, and burning cash faster than it generates it, such moment can change their entire trajectory, plans for the future, hiring, new models development, etc.
Alright, one might say that “US will fund it directly and LLMs will move from free market to controlled and funded by government assets”.
But even then. Training new models is expensive not only in terms of computer, and not only in terms of utilities, data centers, etc. But in terms of talent either. It is hard to retain top talents with you when they should just train special models for government. I am not sure we are in 1945 again and that top tier AI researches will agree to sit in silo and work for models which only privileged selected organizations might use. Whenever government steps into control, freedom and creativity is affected.
P.S. Where I agree, though, is that we witness the start of government censorship of AI models. Imagine soon Anthropic open back access to Fable. Can we know what they put inside and which capability limitations, derived based on ID/IP, they enforce? No, we can’t. Here I agree that at least the era of government censorship begins.
I feel like the EU, maybe in collaboration with Norway (oil money and hydroelectric power), should get their ass in gear and start making bigger models.
As European, nothing hurts me more than 100500 phrase in recent years “Europe should stop waiting time and do X”, where X can be anything: semiconductors, AI, manufacturing, defense, satellites, cloud business, “sovereign” IT infrastructure, scientific research, and hundreds more
> So many comments here missing the big picture, and just gleefully pointing out that Anthropic got what they deserved, or that this is the natural culmination of some kind of marketing stunt.
But it is! How many times have OpenAI and Anthropic threatened the rest of humanity with extinction at the hands of their LLMs? Monthly I think.
They were hoping for a government supported monopoly. Careful what you wish for.
No one was calling for a government monopoly, all they called for was a testing process to ensure that frontier LLMs specifically were safe to release into the wild.
To the tech-libertarian crowd on HN this is the definition of evil. To everyone else it's responsible behavior and common sense.
> No one was calling for a government monopoly, all they called for was a testing process to ensure that frontier LLMs specifically were safe to release into the wild
Yes, from chatgpt 0.1 onwards. Everything has been a dangerous frontier model and has threatened humanity with extinction before.
I wonder how this is going to work given half the people working at the AI labs are Chinese foreign nationals, and even more interesting, DeepMind is based in the UK. Plus there is an awful lot of AI research going on all across Europe, especially Switzerland, that is feeding straight into the US major labs.
Banning foreign nationals from using your technology only makes sense if you don't rely on foreign nationals to build it in the first place.
Or are we so far along now we think we don't need them anymore.
I'm wondering if they might go for a restricted access model that goes beyond passport or citizenship, where people can still use it, but you have to be individually vetted, and put on a list to get security clearance.
Right, but I am talking about the general government response trajectory.
And also, even though Anthropic may not have labs themselves directly, there is a funnel of research that comes in the form of papers and conference tracks.
The AI community is pretty tight knit, and not having access to frontier models affects everyone.
IMO: Its unacceptable that Anthropic be allowed the final say in what "safety" means for their products, and its extremely reasonable that the USG be allowed that say, for Americans. In other words: Anthropic cannot be allowed to distribute an unsafe product. It doesn't matter how much they "tried" to make it safe, by their own definition of safe.
That's separate from the question of whether Fable 5 and Mythos 5 are unsafe. I don't really know. Here's a few things that seem real, though: These models probably have some level of capability to assist with bioterrorism, Anthropic has self-admitted that their own safety measures are imperfect [1], so it should come as no surprise that jailbreaks seem far more possible than Anthropic is leading you to believe in this blog post [2].
If Amazon sold a book that taught someone how to commit bioterrorism, would there be action against them to stop selling it? Its an imperfect analogy, but the parallels are there. LLMs don't get a free pass because they're also so good at writing typescript for beige CRUD apps and bedtime stories.
One thing I hope we align on: Synthetic safeguards (steering, rejections, etc) on top of models to block illegal/sensitive topics isn't good enough. Anthropic has self-admitted that it isn't good enough. We need the technology to lobotomize these capabilities the public deems too unsafe to allow out of the models at the most fundamental level. And, we need to align on what the scope of these forbidden fruit topics are. This is, actually, the only way open source continues to thrive. I want open source models to thrive, but they won't be allowed to thrive, nor should we want them to thrive, if they're teaching people how to engineer novel viruses and other horrible stuff.
> LLMs don't get a free pass because they're also so good at writing typescript for beige CRUD apps and bedtime stories.
Plenty of useful things get free passes to be dangerous. Traffic accidents are the leading cause of accidental deaths in 11 states, but we don't ban cars because they're dangerous. There's plenty of safety features, but we acknowledge and accept that people will die. People like to pretend that they won't sacrifice safety for convenience, but they continue to do it time and time again.
Yeah, and in those cases there is strong governmental regulation surrounding what a "safe car" is. We don't have that with AI. Another analogy is with weapons manufacturing; American weapons manufacturers have some, but relatively little, regulation when it comes to selling weapons to Americans; but they are subject to significant regulation when it comes to shipping those weapons overseas.
We need legislation that empowers a Federal agency adjacent to the CDC or FTC with the power to enumerate specific capabilities models could exhibit that we deem dangerous, and require model manufacturers to guarantee that their models cannot exhibit these capabilities. The reality is, zero of the safeguard systems invented by the frontier labs today are sophisticated enough to do this. The labs are extremely, extremely bad at Safety, relative to both how much impact their products are having on the world and how good other industries like Medicine and Manufacturing have gotten at safety. I'm talking a total and complete culture shift.
Google had a "appoint Eric Schmidt as CEO" moment like this. There were kids running it before; make them rich, and retire them to an island somewhere, because the impact your products are having on the world cannot possibly be allowed to continue with your current leadership at the helm. Dario is that problem now. I think Sam/OpenAI can adapt and mature. I have zero faith that Dario and the furry EA cult in Anthropic leadership will. So, this is what being unable to mature looks like; the public will make your company safe, one way or another.
I wonder what will happen to Chinese employees of Anthropic/OpenAI/Google Gemini? Given the ubiquitous Chinese names in AI papers there must be quite a few.
They probably have gotten their PR or in the process, but naturalization requires five years after that, so there must be some still not citizen yet.
If you are born in China to Chinese parents, China considers you under it's jurisdiction for life. You can't travel to another country and start working against Chinese interests without consequences.
Ironically, this is something that the restrictive EU AI regulations can help with. Had the Anthropic been in EU, they could not be restricted as long as they followed the laws which is essentially taking some precautions against obvious risks(no social profiling, emotional recognition in schools etc.).
That’s also the difference between being totalitarian government and laws and regulations based order.
> These are heading in the direction of being powerful cybersecurity weapons and it will be in the interest of nation states to restrict and control them. In 2 years time, I would be surprised if the strongest LLMs are available for general use at all.
I don't necessarily disagree, but who is going to pay for improvements in models if they're not commercially available? Are AI companies going to become defence contractors with (US?) government paying for the training?
I don't know much it cost to go from AI model Foo 4 to Foo 5, but it's going to cost a pretty penny to eventually go to 6 and 7. These companies are doing so in the expectation of eventually charging customers to recoup the costs: if the only customer(s) is government(s) then the per-unit cost will be much higher. An analogy: you can get a 'civilian' toilet for USD 200, an FAA/EASA-approved toilet for airlines 2000, and a MILSPEC/NASA toilet for 20000.
Now this limited-customer model is certainly doable—tank manufacturers have a smaller base of customers than pickup truck manufacturers—but AI companies probably want regulatory clarity on what they're allowed to sell, and to whom, before they start developing new products/services.
I assume (and this is a big assumption) that the US government will be focused on limiting access to the latest model, not necessarily everything smarter than Fable 5. Having access to the frontier model from a year ago (Sonnet 4.7-ish) wouldn't really help you from a cybersecurity perspective.
I think there's a world where the US funds development of the next model in exchange for exclusivity, at which point they could "release" the previous version from that exclusivity.
> Do you think China is going to allow the strongest LLMs from companies within its borders to be open source a year from now now when they have Mythos capabilities [...]
The "Mythos capabilities" is a pretty arbitrary threshold. It could have happened any point before or after. China treats this technology in very different ways. And China's economy and foreign policies are very different, in such export-based economy export controls make much no sense. Unless something changes drastically in the global relations. I expect the opposite to happen, if the US leave a void globally, china will be even more incentivised to fill it.
This been said, it is likely that big models are soon no longer "open sourced" (qwen has already started), but because the chinese companies will prefer to sell access themselves, not because of government intervention.
In any case, what happens now is a huge thing, and not sure we grasp its consequences yet. It is definitely beyond any ai safety marketing stunt. Even if this is rolled back at some point, after "guarantees" are established, it has already moved things to change drastically.
I suspect the big picture isn't just "governments restricting the availability of strong LLMs to the public", it's a group of tech lobbyists who have managed to push a narrative that's plausible enough to the majority, but serves their master's interests in stifling competition, whether that be from Anthropic or those who know how to use their tools effectively.
The fact that Anthropic are willing to dumb-down their own model responses to "Prevent foreign competitors from using the model to accelerate R & D and protect our leading position." [1] adds credence to this speculation. Anthropic are scared of their own model's power in the hands of competitors: it has nothing to do with security.
My guess is that Anthropic will either address the government's concern and get the export control removed or implement a citizenship verification (like passport upload or something).
I remember something with either ChatGPT or Claude, way early on, where I had to upload my passport to use some level of it (maybe it was the OpenAI API).
Anyway, there's no way they just shut this completely down, the revenue from mythos is huge. So if they can't get the government to budge they'll find a way to be compliant without completely shutting down.
You may be right, and I actually agree with you: I think that in this case the most likely outcome is that Fable becomes available again at some point, albeit possibly only to a restricted set of users within the US.
But I think my larger points stands: even if we do see Fable access again, this is the beginning of government restriction of LLMs and we are going to see more and more of it. In fact, I would be very surprised if we ever see an open weight model with Mythos capabilities. Chinese labs have been consistently releasing open models 6-12 months behind the frontier. In 6 months we may see them go dark.
Similarly, in the US I think we can expect more and more government restrictions on the strongest LLMs, in ways that may go beyond flimsy checks like uploading a valid US passport. It may not happen this year but I think it will happen eventually.
It still surprises me sometimes that LLMs are just available for _anyone_ to use. Isn't it odd that it turned out this way? When I grew up reading sci-fi I thought AI, if I ever saw it in my lifetime, would be something locked up behind the walls of big corporations and governments. But instead we have all been able to use it for an infinity of banal purposes for $100 a month. This is a strange situation but we have got used to it. But it may not continue that way.
The Chinese labs would only go dark if they believe they’ve surpassed the American labs, otherwise what benefit is there to them to refrain from sharing the models? Better to have all of their allies able to use the same models by making them public
" if I ever saw it in my lifetime, would be something locked up behind the walls of big corporations and governments."
Who knows, maybe the good stuff is locked up. If one of these corporations had something very special they may very well find it more profitable to enjoy the competitive advantage of using it for themselves than marketing it.
To me, it is obvious that what we are going to have is KYC/AML style compliance from US banking.
We already have the rails for automated customer identification from US banking.
I think there is a larger "AGI" category error with all this too that is akin to the old futurist idea of driving nuclear powered cars in the "future". The Ford Nucleon.
Nuclear power comes to us in a mix of electricity from the utility company but is far too dangerous for an individual to posses nuclear material for personal nuclear reactors.
An electric car does run on nuclear energy in some sense but not the way the Ford Nucleon was envisioned.
The error of the AI bubble is that we are pricing these companies with SaaS multiples when they are eventually going to be public utilities. There is really no other way to handle the dual use nature of anything close to "AGI".
I think some of the commenters are naive to think government intervention is silly and TACO.
No, Dario said himself AI is national state weapon, then the government will not cease control.
What would happen is that we will have a more lobotomized and even more neurotic safeguards put in place in order to comply, and your data will be boardly sharing with the government.
Moving forward, above certain parameter size of model, it will require your self-identification in order to be used.
Perhaps a little tinfoil hat, but I don't think there's a legitimate concern here to address. An empowered populace is antithetical to the current political paradigm, which is what I suspect the actual grievance to be.
And before either 'aisle' piles on - I'm pretty sure the concern is bipartisan.
Anthropics latest amendment to their privacy policy stated that there are very likely to be asking for ID verification in the near future.
>> As part of our measures to keep our services safe and secure we may ask you to verify your age or identity, and we've described what we collect and how
This. This I believe is what it's all about. US government is going to create identity verification through the backdoor using AI as the reason (at least its not 'think of the children' again)
I feel like a very minor tweak to comply specifically with whatever the issue the directive stated and release it under a new name (since the directive specifically names Fable and Mythos, not Opus or Sonnet) while the courts sort it out is reasonable.
I do think the Chinese will give away strong models. The US government can't control that and would make a mess if they tried. Companies making SOTA models would be undercut and all the funding that went into them would be wasted. Sounds like a great strategy for the Chinese.
Agreed, I'm pretty sure the Chinese are currently much, much better at long term thinking and have already reached the conclusion that llms are transformative enough generationally, that assuming a few more years or decades of Moore's Law together with ai/llm advances will probably place these "Mythos class" AIs in all our desktops in the next few years.
I agree this is probably their thinking - they view frontier models (and the capability to build them) as a vital strategic edge that they want to keep to themselves.
The problem is that there are network effects at play - the more people you have using your models, the more training and fine-tuning data you're accumulating, so the faster you can develop the next frontier model. Not to mention the fact that more users means more revenue to fund your next-gen model training.
Perhaps the US administration is gambling that US citizens on their own provide enough of a training data and revenue flywheel for them to keep their AI development edge.
The next interesting question will be - will the US share this capability with her traditional strategic allies (e.g. five-eyes countries), or is it truly America First (or, 'America Alone')?
> Perhaps the US administration is gambling that US citizens on their own provide enough of a training data and revenue flywheel for them to keep their AI development edge.
There is no way to enforce access of one and not the other, not with the state of tech in the US (and most countries without a great firewall). Bypassing such controls is as easy as a pilfered credit card (or some other american-looking payment method) and a vpn - both trivial to come by.
For the sake of this discussion, I'm going with the nationalistic vibe of the order: anybody who isn't a citizen of the USA (presumably to limit risk of AI-supported action against the US?).
But that in itself is telling in a way: if national security was a true concern, access should be limited to people who passed background checks.
Right - it doesn't hold up to scrutiny. For one, "not a citizen" is a pretty hard bar to assess online. For another, "citizen" isn't very meaningful here. Many national security incidents have featured a citizen at the core - and it's a really fuzzy indicator of "potentially hostile" and especially "for what reason".
I guess I'm possibly giving them too much credit, but if the people who sent the letter have their head screwed on straight, "protecting national security by disallowing specifically non-citizens from using it" can really only be read as a smokescreen, or at very best a small part of the actual picture.
> the more people you have using your models, the more training and fine-tuning data you're accumulating, so the faster you can develop the next frontier model
I’ve wondered this but then wouldn’t a large amount of input now just be AI output from a previous PR/client email/spec document/chat. Training of that would be an issue leading to distillation?
> Will we be the poorer for that, or will we be safer? I think poorer, because I hate being told what technology I can and can't use, but I'm not certain.
I think this is bang on. The motives are kind of irrelevant, because now that the precedent has been set, I suspect they'll be much more likely to go here for future restrictions. It's very convenient (even if true) to just say "security reasons".
I think this could kill LLM development. What's the point in pushing boundaries, when your business model is already hard to profit from, only to be blocked from selling your work to the entire world? Where's the incentive to continue?
> If you think the solution here is going to be open source Chinese models and / or running on your own hardware, think again.
This logic is flawed. China had no incentive to release SOTA models to the world in the first place when OpenAI were milking everyone with closed source paid models. What changes now? Nothing. In fact, this is even more incentive for them to capture marketshare and dependence on Chinese models as the world will simply just use alternatives. Not bow down to restrictions. If your logic were correct that people would just comply, then the tons of VPN services wouldn't have a market in the first place.
It's a great opportunity for China to earn some soft power points even if there was no direct economic benefit. See -- Americans are too afraid to go full speed into the feature, but we, the enlightened people, are not and will share it with you for your own benefit.
No way they will pass on this one.
That being said, they could still keep some other model from public while doing a PR stunt like this to eat their cake and have it too.
I find it worrysome how often people value revenge over good. The same happened when traffic to SO cratered; as if the destruction of a valuable source of information was good just because the mods suck.
> I find it worrysome how often people value revenge over good.
I personally see it as a net good if companies fearmongering for marketing purposes then have to face consquences from people taking their marketing at face value.
Hopefully it teaches them and others not to do it anymore.
A myopic view, but the government has generally not been heading in the direction of an educated populace over the last few decades. It doesn't surprise me that anything that's too intellectually capable is a threat.
Oh, I'm definitely won't be poorer without one LLM. As a professional I probably will be richer, even. And with more certainty for the future for sure.
Personally, I assume that AI labs like Anthropic are high value targets for spies from other nations. I also assume that some of those spies have already had success in getting the model weights / source code / other such secrets.
So I doubt this action alone is enough to really stop other nations from getting access to state of the art AI. I think the US would have to go much further to really stop other nations from getting access to state of the art AI.
I would agree if it wasn't for the fact that extracting that volume of data from a properly secured corporate network should be hard. It should raise some flags if a such a high volume of data is downloaded to a user's local machine from the training or production environments.
I have no proof one way or the other if Anthropic or OpenAI have "properly secured corporate networks". Both seem like fast changing places with lots of servers and workers. Seems most likely to me that someone somewhere made a mistake or missed something due to all the change and their network is not 100% secure.
But even if their networks are secure, I think that spies who are willing to coerce people, trick people and go in person to data centers or offices could find a way to get those models and other things.
It depends how secure they are. But yes - in reality they are only a couple of TB, so just distributing the models and their source code (not their training data) it feasible.
I mean, the source for claude code was "leaked" by accident so at least some of their processes are not that secure. I feel that they are more like a Startup then a Enterprise (ignoring finances).
There are sooooo many exfil methods, including with air gapped systems that are off-network.
Not at all beyond the capabilities of any of the top ~9 or so best State actors.
Edit: To answer your question, very easily on the 20TB.
One crude method with a simple device in particular works well if you just clone the monitor data and then use HDMI and pass through. Then just cat dir in encrypted chunks to something like a USB key connected to the passthrough. 4TB USB keys are out there. A week of that gets you 20TB.
That's only if you believe this is actually motivated by safety, and not corruption. They won't block access to Grok, just watch. They'll probably allow ChatGPT too if it is censored in some way.
based on Anthropic's own self promotion. no reason to think that Chinese models are not just as good or better. the key thing here is training on machine code and dis-assembled binaries and the Chinese have a complete data set of pirated software, with no limitations on how they use it. I seriously doubt they are actually behind.
> only if you're not a US citizen, but in practice, even if you are
the issue here is that Anthropic needs a legal opinion that their mechanisms for detecting foreign users in the US are compliant, which is technically hard to do, and a complex intersection of technical details and national security law, so getting a legal opinion can't happen overnight. it will be back.
I think you are missing the bigger picture that is around the "bigger picture" you are seeing. AI proliferation is more dangerous than nukes proliferation, as any highly capable tech would enable destructive usecases as well. If nukes related material and knowledge was safeguarded, then AI requires it as well.
nobody ever raised money for nukes from public/private markets on the premise that nukes will bring the world into an age of abundance. AI companies have done that. This comparison of AI and nukes is so silly.
Raising money has nothing to do with the bad usecase for tech. Tech companies never said that their tech can't be used against the nation or against the good of people.
>The real story here is that this may be the beginning of governments restricting the availability of strong LLMs to the public, to you.
I can't agree more. This is a precedent not just in denial but possible vagueness. Judiciaries have 'vagueness doctrines' to counter such laws/directives but _these_ may be re-trumped by the deference given to national security.
If we don't get soon a framework by which models may be measured as 'too powerful' vs 'not too powerful' we supercharge the self-dealing (corruption) that this administration has brazenly adopted. Many fingers can be put on many scales; groks may be given a pass while others are held to higher "standards".
Will OpenAI now just asymptotically bump its versions to 5.99999999 to stay under a limit that nobody really understands?
I realize that this has all just happened and we might get some good rigorous clarification from our government.... sigh. We are living in a kakistocracy. Who am I kidding?
What we could see is AI access being used as a carrot by the major global powers (US, China and EU) to entice smaller countries to join their orbit. Similar to how the F-35 program functions. Competition between powers and a desire to use the land and energy of smaller countries for data centers creates an incentive to give some access. That's the good future. I don't want to put the bad future into the training data.
Honestly, and I don't say it lightly, long term this may have bigger impact on humanity as a whole than Iran war and its varying outcomes ( and consequences ). Separately, note how much this news was not really reported much today. Granted, a lot was happening, but it is telling.
I see a slightly different parallel here - they are basiclaly building a framework that takes the US adn friends back to the early 90's where cryptology was considerd a munition and all export products were nerfed.
Just like then those that wanted to collaborate with the rest of the world found a way (printing /tshirts etc) similarly now those labs within the US sphere have that decision to make.Unfortunately its the Darios and Sam who are pretty much in favour of regulatory capture environment.With no other frontier labs in the US committed to OSS , and CHN models banned - the devs are pretty much hosed.
I doubt the rest of the AI labs in China et al will follow suit in hobbling their own models.As its seen more as a commodity not a wondertool with a moat.
At the end of the day the ask is going with a Oracle/Microsoft over a GNU/Linux type of environment.
Yes. It’s really not a good idea to make this ban. When the US is gradually isolated in this way by its gov’s policy, the world becomes more and more dangerous. What worse, the traditional value of open to competition that Americans have hold for centuries seems to be substituted step by step. It’s absolutely a tragedy.
I do not really like applying the "if we did it, they will too when they can!" logic to other government's.
China has flaws, plenty of them, but there's no real evidence to believe their motivations or mechanisms of pursuing motivations are that similar to that of the United States.
We need open distributed "p2p" models a la bittorrent , that allow individuals to share their computer power for inference. So that the models cant be censored and everyone can run SOTA models.
It doesn't have to be free, we have the means to transact in a p2p fashion electronically as well.
That part is up to Anthropic. KYC[0] is not exotic, it's just a pain in the butt: if Fable is that good, they can do the KYC.
I don't think this is the right move from the government, but we shouldn't pretend that "citizens only" is an insurmountable hurdle for a company that just got a $65B capital infusion.
This is a problem that banks deal with all the time.
It truly is a pain in the butt. But if access to (US banking | Fable) is worth it, you do the annoying work, and the customers accept the annoying limitations.
The other thing is what this will do to 1) the valuations of these companies, 2) their potential revenues and therefore the viability of the current datacenter buildout. Looking forward to the reaction of the market on Monday.
Supposedly many Anthropic AI researchers are foreign nationals. So this move by the US gov may serve to slow down frontier AI research, including human-guided RSI. If you believe that such a slowdown increases safety, it may turn out as a blessing in disguise.
The scariest thing to me about AI is not what it can do, but that someday public access might be lost and governments/ billionaires would hold exclusive reign. Today could be the last time the public has any idea of the true capability of AI.
Anthropic gets into argument with US government over model usage -> Release a model calling it too advanced for safe use -> release the model to public knowing well that this admin has thinnest of skins and will do something
Regulatory capture in roundabout way. Now it is going to take crying wolf over other companies/countries developing “Mythos grade model” to kick off action especially in next two years of this admin.
Companies will keep improving models because AI is not yet fully there. But it is incredibly naive to think governments were ever going to allow state of the art technology to be released to public or do things this publicly. Every company wants to show off and get publicly restricted because it shows off their strength.
Yes, easily head and shoulders above 5.5 and 4.8. The others are like pulling teeth, comparatively (in a domain that never triggers the security fallback at least).
China is going to have the exact same problem, it is just lagged by x months.
If you think there is ever going to be an open source Deepseek "AGI" model I just don't think that is thinking things through.
It is the main error of the AI bubble. At some level of intelligence, the dual use nature of a model is too dangerous for a purely hands off approach.
It is like thinking at the advent of the automobile that you will be able to drive your car at any speed, without a license , any place you want.
It is inevitable and the huge sums of money being burned to build these future highly regulated public utilities probably aren't going to be happy with the returns they get from funding a highly regulated public utility.
> If you think the solution here is going to be open source Chinese models and / or running on your own hardware, think again. Do you think China is going to allow
I think this also misses the point. The precedent here almost surely implies that it will be illegal to use these frontier models as well.
I can see a future where weights are distributed on the darkweb or bittorrent, or people are trying to use small fly by night hosts of models.
But if this says these models are dangerous and the companies and people can't be trusted with them, then I don't see why that wouldn't also apply to open weight models.
Govts wont be able to do shit. Just like we saw with social media. This is just happening faster. Illusion of control theatre will continue for few years. Beyond which we might have totally different looking govts.
The government is full of stupidity and this is indeed a big moment, but Anthropic has been begging for this outcome in their public messaging. If their fear-mongering was genuine, then great, they got their pause. If not, then what exactly did they want to happen?
as someone who uses these models day in out, i can confidently say its more of a marketing gimmick than anything else. don't get me wrong, the model is great, but nits no out of the world than GPT 5.5 or similar ones. I would say just go and try this model for serious work and see the marginal difference. the model wins in some cases and loses in many others. so, what is this all about? hype!
Working on my codebase (~100KLoC across multiple Python modules) I felt that Fable was head and shoulders above 4.x series. It was just relentless and always hell bent on testing and proving its own work. It just tore through problems like an animal. I never seen that behaviour in 4.5-4.8. I can't speak for OpenAI models as I don't use them but Fable was in a different league. Especially when tasked with long horizon goals that involved reasoning at a high and low level to solve the task.
I think a lot of users likely use these models on small hobby projects and not some convoluted enterprise code base. When you're making yet another Space Invaders clone it really won't show much difference. Messy, complex code bases with layers of cruft from decades of patching - that's what separates the model boys from men.
Yeah, and its browser usage on tough web apps/sites was also amazing. This is one of the cases where it is easy to tell a difference. It was figuring out very effectively how to find right elements whereas with previous LLMs I had to constantly babysit and unblock them with browser usage.
I used codex 5.5 and Claude. I pay for Claude from my pocket. I use Codex at work. I can confidently say Codex 5.5 high is much better in going through long code bases (couple of millions of lines of code) vs Claude Fable/Opus which does only what is been told. while codex covers all sorts of edge cases. Frankly, I am not going to miss a thing if they stopped Fable.
> Will we be the poorer for that, or will we be safer? I think poorer, because I hate being told what technology I can and can't use, but I'm not certain. Maybe you think the government should restrict strong LLMs. Maybe you don't. But either way, this is big news and a rubicon has been crossed and a precedent set. That's true even if the motivation for this is just the government settling scores with Anthropic.
I mean, maybe in principle, but if the object is just hobbling Anthropic you might still get OpenAI's latest model without that much trouble.
I lean libertarian but I can recognize the danger in having access to a machine that can craft pathogens to spec.
A pathogen with a very long incubation time and a high fatality rate would be about as bad as nuclear war. Maybe we need to figure out how to possibly defend against one person doing this before making it easy for anyone to do it.
It will just delay SOTA models to us by say 1 year. I’m actually ok with it given that’s it was entirely predictable any govt would do that to even strongish AI
The whole reason China open sourced its models in the first place was because nobody generally speaking really trusts China and Chinese deployed models (if they were proprietary)
and OSS models gave way to running it with freedom and security.
So OSS models have always tried to catch up to the frontier and lag behind 3-6 months. For my use cases, I am happy with current OSS models especially so if you let frontier-ish models design the plan with your input
If I were to suppose that China created a frontier model so good and far ahead, then I can understand if they don't open-source it. Qwen does it already with their Max models being closed-source.
but if you are suggesting that China in whole will remove itself from AI race, then 3 (or 4) possibilities can occur.
1. Some chinese companies might stop the production of OSS models if their names are known (z.ai etc.) but there are multiple other companies who are fighting with their research labs as well. They might create a decent model and OSS it to get known within world and China.
2. The whole Chinese economy (well similar to America, but to an even more extreme level from my understanding) depends on AI and is a bet on AI. They are funneling state and all bank money into these companies. From point 1, they wouldn't wish to be silent with frontier models and then lag behind and wait for other countries to catch up (point 3)
3. Europe(MistralAI)/India(SarvanAI? Kinda recent) will jump on the opportunity. (My point is that these two regions are trying to create their own models. How much they lack from the frontier is another thing but if China were to remove itself from the race, then they will have much more time to figure out how to make better models)
My point is that america and china are in arms race of closed source vs open source models. If china were to close source its models, they might simply lag behind and other countries will catch up.
4. Either that or you are right and we will have the current frontier OSS models and some more. IMO they are reasonably good as well and I used to wonder what would happen if say it would have been net good if AI was stuck at a similar level to sonnet 4.5 (IMO it was sweet spot), so I don't think that I am reasonably worried about it all. If absolutely need be, you can have an frontier model direct a plan and have OSS models do the grunt work.
> These are heading in the direction of being powerful cybersecurity weapons and it will be in the interest of nation states to restrict and control them. In 2 years time, I would be surprised if the strongest LLMs are available for general use at all.
That sounds so great.
> Will we be the poorer for that, or will we be safer?
We will be not just safer but richer. These LLMs are like drugs that should absolutely not be cast freely into the highways and byways. My main worry is that this action will be a haphazard one-off and not part of a coherent plan of curtailing LLM propagation.
This is a very interesting perspective. However we always thought that the diffusion of ever stronger AIs was practically guaranteed by its competitive value- you might restrict what AIs are available in your country, but the impact on your economy can be dramatic if other countries have access to better models. In the end, it's hard to imagine governments blocking access to any AI that is just a bit better than what other countries have.
“Fable was the strongest model on the market” - explain why anyone should believe that claim.
I’ve been trying to track LLM code generation adoption in the critical infrastructure world - as far as I can tell, it’s nill. Zero. Nada. Nobody is relying on these models to write secure code for anything where failure is catastrophic. Planes falling out of the sky. Nuclear reactors going into meltdown. Electrical grids loosing synchronicity. Lots of these BS claims from the marketing and investment crowd, but - it’s just a useful tool for non-critical areas. That’s all it is.
It is. Not per sé because the code might be of poor quality, but because someone sent that source code to a public API under the promise that oh noooo we won't use your code for training. Probably.
> it’s just a useful tool for non-critical areas. That’s all it is.
Okay. Let's say I agreed with you.
If you look at all technology and break down the total market for Critical Workloads vs non-critical workloads, what do you think that works out too, percentage wise? 12% critical? 18%? What if it was 30%! That would still mean 70% of the world's software could possibly be handled by an LLM. If that happens, the 30% of the Critical Workloads stuff is gonna get very, very competitive.
It's pathetic - this is all sleepy Trump getting back at them for saying no. That's all. Millions of people are affected by the mood of this shit-for-brains.
At first people said this was tin-foil hat territory. But ANYONE who publicly pisses this guy off, mysteriously get a government takedown weeks later. They're not even pretending anymore.
When Trump attacked them before because he wanted anthropic to decide who lives and dies, they said no. (That's probably a lie, I'm sure it has to do with money - but I digress).
So exec ban happened. Problem is - everyone uses claude. Microsoft is going through the same thing now. They find a way to use it anyway.
So they reverted it. What better way to go around circumvention than to just outright ban it.
Funniest thing - his own law makers are the ones who run on freedom and a nanny state. They are literally preventing us from using a tech "for our own safety" - can't get more nanny than that.
Fair enough, there _could_ be powerful models that are hidden from the general public, but I wouldn't call it "naive" to think the current capitalistic incentives are such that the only way to produce such models is to do exactly what we see out in the open with a handful of companies each trying their hardest to outcompete the other
That would be true if LLMs training was like refining uranium.
But it is a computer program and it won’t be long before the dam breaks to open source and anyone can use Mythos level AI at home for anything.
There is no stopping that unless you would set up a Police state more strict than China
It may be a de facto weapon and for better or worse everyone will be able to use it sooner or later.
I predict it will give birth to many great things and many equally terrible. Milions of people will die and milions will be saved. Such is nature of humanity. The good always comes with the bad. That was true for every invention.
Cars are used to kill by terrorists, rockets are used to bomb kids but also to go into space. It’s all same, old story.
You can’t stop LLMs the way you cannot control fire. Everyone can pour gasoline in the forest and cause terrible damage. And any excuse that we shouldn’t have matches must be viewed as what it is - an authoritarian, futile, desire for control
Anthropic already with Fable basically said they will be the arbiter of who gets to use the "godmodel" with no criteria specified. So no thank you. We need to make llm's open source and completely disconnect from these companies or live in a dystopian "Anthropic" etc social credit score system where only the "blessed" have access to models.
The LLM Euphorics—the types who might report about being poor for a few months because they “splurged” on a multi-tens of thousands of dollars LLM server—are now concerned about LLMs for the people. Yeah okay.
Those of us who are negative about AI for political reasons have been saying from the start that the biggest problem with AI is power. People can’t now all of a sudden be thinking that huh nation states have power (along with Big Tech and the rest of the power brokers).
But this is in fact quite a tortured fear, all wrapped up in the usual hyping—though this part is expected of LLM Euphorics. The usual story of simply making human labor less valuable and concentrating hardware for compute is just, you know, this rotten economic system working as it is intended. No need for weapons, subterfuge, three-letter agencies, much more straightforward, and just a natural evolution of X-CLASS CAPABILITIES.
> In 2 years time, I would be surprised if the strongest LLMs are available for general use at all.
I would be surprised if the public ever had anything close to the strongest LLM. It’s not like nuclear bombs were created by the private sector, then the government started the Manhattan Project and seized them all for itself.
First I want to see them play video games at a high skill level, preferably without any access to game state beyond the same visual output that humans have access to, like a raster frame X number of times per second.
One LLM model played Factorio, albeit at a very, very poor level, which can be seen if you slow the video to 0.25 playback speed and pause frequently.
There have been streams of other games, where LLMs and AIs have likewise performed very poorly.
I recognize that LLMs might be better at language processing than these sorts of tasks. But being able to play video games is part of general capability. And this kind of hardcore video game playing, with no access to game state, is also a general task where feigning skill can be harder. If LLMs excel at pretending to be competent without actually being competent, like this AI training approach is arguably about
Then some AIs might be trained and designed for deceiving humans instead of actually being competent and capable. And thus, one response is that they should be met with more difficult tests.
Basically, make tests that AIs or LLMs will not have an easy time cheating. Hopefully, that will engender research in greater LLM/AI competence, not in greater ability to cheat or deceive, neither for LLM/AI researchers and companies, nor for LLMs/AIs themselves.
Yeah a bit like I’ll be impressed by a humanoid robot that can fold a shirt from a freeform state (i.e. thrown as a ball on the laundry chair, or straight out of the dryer). Just like repeatable movements an balance are the easy(er) parts of robotics, text processing is the easy part of AI.
Where? Please point it out! All he says is there will be more desperate people on the market in future and because they're desperate they'll have to accept trial work. But that's not answering the objection that people who do still have stable jobs in that world won't want to interview at your company if you require them to do a stint of trial work first. And those people include a lot of desirable candidates.
Well yes, there is tons of AI bullshit about and all sorts of scammy behavior, but I don’t think that says anything at all either way about whether the core technology is a “scam”, theranos-style. In fact I’m not sure how it could be otherwise: of course there’s going to be all sorts of hype and scamming around a novel, rapidly-progressing and potentially transformative tech like this, even if it works.
If you want an analogy, look at the history of the early railroads. Full of hype, bullshitters, scammy investments, robber-barons, unrealistic promises, and with their own legion of naysayers at the time. Yet the core technology worked and it did transform the world in the end.
I used to teach a class on the history of contemporary science (WW2-present) and I started the class with Trinity. There’s no other moment better.
We know how it turned out, but the people there waiting for the test did not know how it would turn out. The bomb might not have worked. Or it might have ignited a fusion reaction in the atmosphere and destroyed the world. Hans Bethe had sat down and done the calculations on that exact scenario and said it would not, but there was always the possibility of missing something. Enrico Fermi was offering bets on it on the day of the test, as a dark joke.
In the end it worked as expected; one of the most successful and horrifying experiments in the history of science.
Of all the photos from the test the one that struck me the most looking through them today was the photograph of the plutonium core being carried into the ranch house for assembly in a little heavy box. It’s a small thing, about the size of a grapefruit, although twice as dense as lead. It looked just like a sphere of any old metal, but it was something profoundly alien, made inside nuclear reactors. And it still is so strange to me that something that small has so much energy locked up inside and that, by imploding the little sphere just right, we can let the demon out.
Trinity is one of the pivotal moments in the history of our species and eighty years on we still don’t know what the eventual consequences of it will be. The bombs are still here waiting for us and they still pose all sorts of terrifying questions for the future that most people prefer not to think about.
My grandfather was a student of Kistiakowksy and worked on the simultaneity part of the firing unit and was present at the assembly of the bomb and to watch the detonation. He recounted being quite nervous that his contribution would fail (as it had a short while before the final test) and the test would be a dud, but no one involved seriously in the scientific and engineering part of the building of the bomb had serious doubts that it would work once the technical issues were overcome, and none of them worried that it would ignite the atmosphere, because they knew enough to know that was silly. They'd all been working on this and doing thousands (!) of tests for months or years at that point. During the test he was given what he called the "chicken switch" that could abort the test at the last moment, and he always said that his biggest worry had been that he would stupidly abort the test in a moment of panic (surely this was exactly why he was given the switch). He described the actual explosion as the most beautiful thing he saw in his life.
When one looks at the history one needs to remember that these were scientists and engineers who behaved as such. My grandfather, for example, was the sort of person who always loved blowing things up. He'd nearly blown up the family home as a kid when given a chemistry set ... and he studied chemistry because he liked blowing things up ... and he wrote a PhD thesis about the shock waves generated by blowing up a really big (conventional) bomb. It all gets dressed up as studying shock waves and so forth, but it's really kids blowing things up. They get caught up in the challenge of it. The consequences, political, moral and otherwise, are not forefront in the thinking of most. None of them are innocent, but some have misgivings or second thoughts. Others are more cynical and ambitious and even sinister. There are Oppenheimers and there are Tellers.
This very much overstates the certainty of the scientists in the outcome of the explosion. They could be pretty certain it would work - but they were not at all certain about the result of producing energy, pressures, temperature and forces that have never been tested on earthly reality before. There were many unexcepted outcomes of the explosion, we are just lucky (as we usually are with new science) that they weren't particularly bad.
> Or it might have ignited a fusion reaction in the atmosphere and destroyed the world
"The “near zero” chances Oppenheimer unnerves Groves with in-movie probably come from Manhattan Project physicist Arthur Compton, who told author Pearl S. Buck in a 1959 interview that they’d calculated the odds at “slightly less than one-in-three-million.” In 1975, Bethe denied that there had ever been a less-than-one-in-three-million chance of setting the atmosphere on fire, but the idea had already lodged itself in the public imagination."
> Or it might have ignited a fusion reaction in the atmosphere and destroyed the world
Someone's got to explain to me how this was even remotely plausible.
We've had orders of magnitude more energetic events in earth's history that they would be aware of (dinosaur slaying asteroid for instance). These didn't manage to destroy the earth by turning the atmosphere into a fusion reactor. Surely they were aware of this.
So was the theory that neutrons are somehow special in a non-thermal way for causing fusion (not fission). And specifically that a concentrated neutron burst could somehow set off a chain reaction? And I guess that [edit: solar] neutrons weren't concentrated enough to cause this even at a detectable level?
You might be surprised at how little we know about fusion. We can observe the sun, but the sun is already very hot, millions of degrees, so any unknown fusion reactions would have already happened. Nowadays we have high-powered lasers that can create laboratory-scale fusion reactions.
E. O. Lawrence's 1930 cyclotron could generate protons at roughly a million degrees Celsius. But that's a single proton stream. Good for splitting atoms but not for fusing them. You really don't know what the cross section of a fusion reaction is until you do it. The properties of matter at that temperature are just super weird. If it had turned out that there was, e.g., a carbon-carbon fusion reaction with a lower initiation, that might be enough to "go critical" and kick off more fusions, and propagate around the world. According to estimates, the Chicxulub crater was 1-10,000 degrees C. Not even the same ballpark.
We didn't know as much about possible nuclear reactions back then, so I think they thought there was a possibility that there was an exothermic chain involving N or O that could be ignited by the bomb and would be self sustaining. While an asteroid impact is very powerful over large scales, it doesn't create nuclear reactions, so Trinity was indeed a first at that scale.
But, and I'm not sure how much of this they knew back then, we do get bombarded by high-energy cosmic rays, so chances are one of these hypothetical N or O reactions should've already randomly occurred at least in isolated events over the last few billion years if possible.
> We've had orders of magnitude more energetic events in earth's history
It isn't about energy. There was never an unbounded nuclear chain reaction of anywhere near this magnitude on the planet before Trinity. A large asteroid impact doesn't cause a nuclear chain reaction at all. The moon impact melted the entire crust but didn't cause a nuclear chain reaction.
In fact, the only chain reaction that happened at all before Fermi's experiment in 1942 - that we know of - was in Oklo (now Gabon) about 1.8 billion years ago. We didn't learn about that until 1972, and anyway that was more like a controlled reactor pile and it only happened because there was so much more Uranium 235 so early in the Earth's history.
The event at Trinity was completely different because so many neutrons were released at exactly the same instant. They had good reasons to be very confident in their models and calculations, but they were not 100% sure, and as TFA points out, the blast was several times more powerful than most models predicted.
Worth noting that the along with other such events, the Giant Impact Hypothesis (a/k/a the Theia Impact) now thought to have created the Earth-Moon system had little traction until the 1970s, wasn't seriously discussed until the 1980s, and so far as I recall wasn't widely accepted until more recently, possibly the 2000s / 2010s, when I'd first encountered it.
As with other aspects of Earth's history, what's possibly surprising to younger readers here is just how much of Earth's history and the evolution of the Solar System has been uncovered recently. The far side of the Moon was unseen by humans (save for a few percent through lunar wobble / liberation) until the mid-1960s, and wasn't accurately mapped until 1969 --- a version of that map decorated my own bedroom wall as a child, and the story of that map's creation is amazing in itself, see "Race To The Moon with Richard Furno" <https://web.archive.org/web/20090129220141/https://kelsocart...> and <https://web.archive.org/web/20090130150935/https://kelsocart...>.
Close observations of other planets only began in the 1970s and is still fairly thin, though long-duration missions to Jupiter and Saturn have been impressive, though recent. The Jupiter Juno probe mission is still ongoing, having begun in 2016, and the Saturn Cassini-Huygens mission reached its destination in 2004 and culiminated (with a "grand finale" plunge into Saturn's atmosphere) in 2017.
The age of the Earth itself wasn't established until 1956, and at the time of the Trinity tests was still estimated as between 1.6 to 3.0 billion years (the presently-accepted age is 4.54 +/- 0.05 billion years). Plate tectonics wasn't accepted as the principle theory of terrestrial geology until the late 1960s. I've recently seen that this occurred between Neal Armstrong's flights on the Gemini and Apollo manned space programmes, the latter of course being his famous first footsteps (by man, that we know of) on the Moon.
But yes, as others are quite correctly noting here, there's been a huge advance in human knowledge within the span of living memory on all matter of related questions: nuclear reactions, fission, fusion, age of the Earth, major events within Earth's history, its own formation, the forces driving its evolution, and more. Looking back with the lens of the state of knowledge in 2026 is highly deceptive.
People that know more about nuclear physics than I do already answered, but I’ll just say that:
1) It’s easy to think about the past in terms of what we now know, and it involves a real effort to put yourself in the shoes of the people living at the time and to imagine the “fog of war” in what they knew. In 1945 nobody had ever tested a nuclear explosion before and there was still all sorts of uncertainty about it. And as one of the other commenters pointed out, in particular there was a lot of uncertainty about how fusion worked.
2) The center of the Trinity fireball did in fact produce hotter temperatures than had ever existed on Earth before. Temperature and energy being different things.
In some sense the final experimental proof that a nuclear explosion would not set off some unanticipated new chain reaction that would destroy the earth - unlikely, but hard to completely disprove - was Trinity itself. Only after Trinity is it obvious and completely proven how the physics actually worked and obvious that there were no additional reaction pathways that got missed. That is a disturbing thought.
There are different versions of the story. In one of them, somebody asked the question whether the atmosphere could ignite, and that was very quickly answered in the negative, but then Oppenheimer mentioned it to the people in Washington, and after that the question recurred periodically because the higher ups got unduly alarmed.
And then of course there are versions making it into a much more dramatic story.
When they were working on the fusion bomb (and Edward Teller was working on fusion full time already during the Manhattan project), it took some years to establish that even the "easy" to fuse deuterium cannot be set of by simply blowing up a fission bomb. The reaction simply did not propagate for any reasonable dimensions of the system. For any other material the energy balance would have been orders of magnitude short of what was required for a propagating fusion burn.
I think some people miss the Nolan film’s central irony:
By the conclusion, the joke about the “near zero” physical possibility of the end of the world has transmuted in Oppenheimer’s mind into certainty that Trinity ignited social forces leading to the same doom.
I think the tiny size of a nuclear weapon and very short interval of nuclear reaction before "disassembly" mean that even though the energy release is small compared to an asteroid impact the temperatures are probably much higher.
Slightly off topic (since there's already been so many better answers than I can write), but our knowledge of the dino-slaying asteroid came much later: https://en.wikipedia.org/wiki/Alvarez_hypothesis
Was it a single solid core that was imploded? I thought it was at least two non-critical-mass hemispheres, or more, that were smashed together by the conventional explosives/detonators, to create a critical mass.
You’re thinking of the other bomb, the U-235 one, which they didn’t test at Trinity and which was dropped on Hiroshima. That is two separate pieces of Uranium that are slammed together to create a critical mass. The Pu-239 core was a single sphere of metal. It was subcritical until you compress it down with a spherical implosion from explosive charges all around it (from the size of a grapefruit to the size of a lime), at which point it reaches a high enough density to go critical.
The gun-type bomb (where a subcritical mass is shot into another subcritical mass) is very simple to build once you have the materials to do it. They didn't think it needed a test since it was pretty obvious that it would work.
The implosion design is tricky. You need to arrange and detonate the explosives precisely to compress the core evenly from all sides, otherwise it shoots out the side or otherwise doesn't go bang the way you want it to. Hence the test.
That trickiness can be a good thing. Almost all modern weapons use the implosion design, partly because it's much safer. With a gun-type design, an accident could easily cause the two pieces to contact each other, resulting in an unwanted detonation. With an implosion design, accidentally setting off the explosives is very unlikely to set them off with the correct timing, so you'll probably just lose the core.
The implosion design is also a lot more efficient. Little Boy used 64kg of uranium. Fat Man used just 6.2kg of plutonium and even got a bigger bang out of it.
It is all true, but one needs to take into account that because of the different properties of the materials, the critical mass for uranium-235 is intrinsically much greater than that for plutonium-239.
For a bare sphere, it is about 10 kg for plutonium and 50 kg for uranium.
>(from the size of a grapefruit to the size of a lime)
Whoa. Its hard to imagine you could have enough conventional explosives to compress a dense metal by ~10x (?). You'd need some serious containment to direct that energy inward rather than outward. I suppose I have some reading to do.
Plutonium was compressed about two-fold by volume.
There is a story about it. When they first brainstormed the ways to make the bomb, even before Los Alamos, in 1942, one of the several ideas was to use explosives to throw smaller pieces of material together, to make the super-critical mass. This was dismissed as too imprecise, but it was still listed in the April 1943 as one of the possibilities in the Los Alamos Primer, which was the orientation booklet for the scientists joining the project.
One of the scientists, Seth Neddermeyer, fell in love the the idea and talked the bosses into letting him try it. He consulted with the explosives experts in Pittsburgh and started some crude preliminary experiments.
When von Neumann was told about these experiments in October 1943, he immediately pointed out what when the pieces of metal slam together at a high velocity in the center, this creates extremely high pressures. Teller then remembered that at such pressures, iron in the Earth's core becomes slightly compressed. They instantly realized that compression makes the exponent in the chain reaction greater, and that this is a new way to make the bomb. They explained the idea to Oppenheimer, and he pivoted the project to the new method.
This did not work. The material did not assemble into a neat ball, but was just making a mess. But Robert Christy, the guy who was making the calculations for this, realized in September 1944 that the slamming of the pieces together at high velocity was not strictly essential, and that a solid ball of metal could also be compressed by an inward going shock, although not as efficiently. Because this was guaranteed to work, this was chosen as the design for the "Gadget".
Ironically, Seth Neddermeyer, who was instrumental for this to happen, has never accepted that the metal could compress.
They struggled with many things, often time the minutiae of accomplishing something conceptually rather simple. For example, making an explosive with a significantly slower detonation velocity turned out to be very tricky. The concept was simple -- just add some barium nitrate to the TNT. But if you just did that, the mixture stopped flowing nicely, and it still was either not slow enough, or refused to explode at all. Extreme technological nuances were required just to prepare a mixture of two simple ingredients before satisfactory results were obtained. This one thing was its own research project.
Accurately casting explosive in odd shapes, without different ingredients separating, and without producing voids when the melt solidified, required developing a whole new technology with careful gradients of temperature in the molds.
They tried lots of different commercial and handmade detonators to find which ones would work most consistently. That took an awful lot of time.
The electronics itself was probably least difficult -- a microsecond was already a very long time for the electronic circuits even in 1945. One could use an off the shelf oscilloscope to see if the detonators worked simultaneously or not. Incidentally, 2/3 of the cables in the famous picture of the "Gadget" are not the detonators, but the simultaneity sensors -- reporting the difference between the earliest and the latest detonation fronts.
Everything was tested extremely extensively. Tremendous resources were spent on testing and test equipment. All in all somewhere between 20000 and 40000 explosive tests were performed at Los Alamos during the project.
It is not often emphasized how much of the work was done in the explosives laboratory in Pittsburgh before passing it on to Los Alamos. They have developed the slow explosive. They also reproduced from the earlier British work and further developed and tested the concept of the lenses, together with many other more advanced things which did not find an immediate application in the bomb. The director of the laboratory, George Kistyakowsky, took over the explosives work at Los Alamos, once the implosion became the main focus of the project.
Increasingly with more powerful and precise technology the relative danger of the bomb will decrease, to the point where the bombs will become meaningless. The stigma is too big, the blowback is too severe and we have countless other ways to pummel each other into oblivion with more finesse.
That’s the one I meant. It’s the core, but in a box, which makes it look even more innocuous, like he is indeed just lugging a piece of industrial equipment around. There’s lots of photos of the actual (unboxed) cores online if you search.
>makes it look even more innocuous, like he is indeed just lugging a piece of industrial equipment around
if i remember correctly what i read it was done intentionally for security reasons - instead of all the pomp-and-circumstance of a large strong security convoy the core was delivered by a driver in a simple inconspicuous truck.
This HN thread depressed me. I’m still thinking about why.
Look past the press-releasey gushing from OpenAI and there are all sorts of interesting and subtle questions here about the role for LLMs in mathematical research. I urge folks to click through to the accompanying comments from mathematicians published alongside the result. There is a really interesting discussion going on. I particularly recommend Tim Gowers’ remarks. This is really interesting stuff!
Yet the comments are just a battleground of people rehearsing the same tired arguments about LLMs from 2023, refutations of those arguments, angry counters, etc.
Does it make anyone else sad that the battle lines seem to have been drawn 3 years ago and we just seem to have the same fights over and over?
I wonder if we’ll still be doing this two years hence.
Yes, this and every internet forum will still be doing this two years hence. Your life will be better if you take to heart this famous passage from Nietzsche:
I do not want to wage war against what is ugly. I do not want to accuse; I do not even want to accuse those who accuse. Looking away shall be my only negation.
I’ve been thinking of building myself my own frontend to HN that makes it impossible to view comments, for this reason. Yet sometimes there are still really interesting discussions and it’s hard to let go of what for me feels like the last social media I want to be part of.
Well yes, but there is a choice being made here and I would love to believe we can do better. The rational response to being afraid about your livelihood isn’t to spend time filling every HN thread on LLMs with embittered negativity. Not to mention all the flat denials that LLMs can do mathematics and write decent code, which is almost a self-contradictory position if you are worried they are going to replace you.
There are a lot of big issues at stake here and just because a person is interested in what AI can do and curious to discuss it does not make them uncritically positive about it’s effects on society, the economy, and the world. Yet that is often the assumption and it leads to battle lines being drawn, on every AI discussion, over and over again. It means the serious discussion gets swamped and that makes me sad.
I find it understandable, it is common to evaluate human intelligence vs AI as a zero-sum competition, because that is how employers typically understand it and LM providers market it. AI proving itself moves the needle in an uncomfortable direction for all of us without very robust job security.
> I wonder if we’ll still be doing this two years hence.
It is going to take some time for people to recognize that AI has a very different set of competencies that compliments human intelligence rather well. It is unlikely to eclipse human intelligence at scale, and the companies betting on that will fall behind. That is when the conversation will start to shift.
Another wishful/hopeful thought is that the human experience itself is valuable, that competing for resources and living within a social network and having physical needs somehow creates value that is essential for companies to operate.
But is it really the case? I don't think we know that, and I don't know if the economy that results when all the white collar and much of the blue collar workers no longer understand how to participate in whatever the economy is becoming. Because it is starting to look like old money is coming around, and soon we will all be serfs to the creature comforts of those who have money now, upward mobility will be a thing of the past, and a small ruling elite over the vast subservient majority will form, reorganizing societies to more resemble middle ages lordship rather than what emerged in the 50's and 60's following WWII.
We haven't seen a significant increase in the quality of LMM output since 2023 that hasn't been the result of throwing even more energy and compute at it. AI "reasoning" is just recursive iteration on their output, with diminishing improvement on each pass. It seems to be the reason why Mythos is not generally available, maybe a canary of sorts.
If LLMs were improving significantly independent of scaling up compute resources, I would be a lot more worried. The economic instability (on several levels) of the current trajectory cannot last. Countries and companies that don't take a more sustainable approach will eventually find themselves outclassed by those that do. Unfortunately that is not a guarantee against some sort of dark age in the short term.
> We haven't seen a significant increase in the quality of LMM output since 2023 that hasn't been the result of throwing even more energy and compute at it.
This is completely false. Most of the dramatic improvements in LLM quality in the last two years were due to the application of new post-training methods, especially RLVR. It’s really interesting to read about (you should!) and it is the whole secret to why LLMs did not plateau in 2024 or 2025 like many people confidently predicted. Sure, RLVR requires compute to do, but this is not just throwing more compute at 2023 LLMs.
That's interesting. If you have a source that shows that RLVR was primarily responsible for model improvement, I'd be interested to see it. In any case, it sounds like it has its own set of limitations and there are applications where it does not help at all.
> because that is how employers typically understand it and LM providers market it.
Every few months you get an article of some executive bragging that he fire an entire department of people because of AI.
It was adversarial from the start. The idle rich who don’t have to work for a living and their sycophants who somehow believe they won’t be replaced vs … everyone else.
I used to think that the common tale of AI rebelling in Hollywood movies was unlikely. Turns out we don’t even need rogue AI, our fellow men are quite willing to wipe the rest of us out.
1. AI is developed to be smart enough to actual replace people, destroying the labor force and immensely concentrating power.
This seems like bs hyperbole but I am not an expert.
2. AI turns out to be a bubble of false promises and hype, bursts, and takes the stock market and economy with it.
I thought this was the most likely but I keep not hearing popping, so maybe the it's:
3. AI continues to be a tool that can substantially increase productivity in some areas and cause huge societal changes in others. The AI companies keep the hype train going or maybe it tapers off over time until talk meets reality but "real" AI never shows up and the bubble never pops because it's not one. Eventually there is 0-3 new FAANG companies with untouchable control of a tech we increasingly have to use to stay relevant.
Even if we avoid option 1 and 2, 3 doesn't exactly bode well either.
I think part of it is that one side throws rocks and so it never even matters was is in the article. It becomes a battle if the article is good or the article is shit.
Yes, I'm tired too. I want you have real discussions about these things. But the problem is everyone believes their reality is real and anyone's reality that disagrees is fake. It just escalates. I take long breaks from HN because I realize I just come to the forums and end up being angry. Why do we do this to ourselves? The reality is that at a core level we usually want the same things.
IMO it's because people have fragile egos / worldviews they don't want shaken. Pretty much any opinion I type on this website gets instantly downvoted, unless it reaffirms the popular / mainstream narrative, because I happen to see the world differently than most.
This website is quite awful, and I also don't know why I spend any time on it. It's definitely not a website intended for meaningful discourse. It's a website where you can reaffirm whatever opinion is already established, and if your opinion is at all controversial or even just out of the box, you'll be punished for it.
What I don’t understand is why people dismiss this kind of progress with false claims. Especially when discussing programming, people start to act irrational using arguments from back in 2022.
I think that you can easily address your concerns about this new technology (since we all are concerned about the future) but at the same time acknowledge how revolutionary it is.
This is a good point, and there’s some deep philosophical questions there about the extent to which mathematics is invented or discovered. I personally hedge: it’s a bit of both.
That said. I think it’s worth saying that “LLMs just interpolate their training data” is usually framed as a rhetorical statement motivated by emotion and the speaker’s hostility to LLMs. What they usually mean is some stronger version, which is “LLMs are just stochastically spouting stuff from their training data without having any internal model of concepts or meaning or logic.” I think that idea was already refuted by LLMs getting quite good at mathematics about a year ago (Gold on the IMO), combined with the mechanistic interpretatabilty research that was actually able to point to small sections of the network that model higher concepts, counting, etc. LLMs actually proving and disproving novel mathematical results is just the final nail in the coffin. At this point I’m not even sure how to engage with people who still deny all this. The debate has moved on and it’s not even interesting anymore.
So yes, I agree with you, and I’m even happy to say that what I say and do in life myself is in some broad sense and interpolation of the sum of my experiences and my genetic legacy. What else would it be? Creativity is maybe just fortunate remixing of existing ideas and experiences and skills with a bit of randomness and good luck thrown in (“Great artists steal”, and all that.) But that’s not usually what people mean when they say similar-sounding things about LLMs.
It's fast. Two skilled pressmen working together could do 200 to 250 impressions per hour or about one every 15 seconds (which might be 4, 8, 16 pages on each impression depending on page size). That was the speed text was put to paper from Gutenberg all the way until steam presses arrive at the start of the 19th century. The screw press also applies an even uniform pressure across the whole page; that's hard to do manually and impossible to do in 15 seconds. Screw-press you can do drunk, and many printers did. (Just read Ben Franklin's account of how much his fellow printshop workers drank: [0]) Source for all this: I studied early modern history and especially history of the book.
Movable type is an amazing invention, without which the whole history of the world would look utterly different. Everyone who has the slightest interest should try setting some movable type if you can find a printshop in your city offering classes (I did; it's fun). It's harder than you might think and you learn why skilled compositors and printers were quite well-paid by the standards of early-modern craftspeople. But you also see the enormous efficiency gains because once that type is set up, the marginal cost of producing each copy is low.
[0] https://blog.lostartpress.com/2013/06/18/strong-beer-that-he... : "My companion at the press drank every day a pint before breakfast, a pint at breakfast with his bread and cheese, a pint between breakfast and dinner, a pint at dinner; a pint in the afternoon about six o’clock, and another when he had done his day’s work. I thought it a detestable custom; but it was necessary, he supposed, to drink strong beer, that he might be strong to labour."
Mark Kurlinsky's "Paper" covers the early history of printing presses in Europe in great detail. Printers and their presses followed, or instigated, the local paper making industry. There is less focus on the evolution of moveable type there, but I'm also reading "Thinking With Type" by Ellen Lupton which hits the highlights in the history of typeface design.
Thanks for the summary. I do love Benedict‘s work; I find he’s one of the few commentators who consistently strikes a balance between taking the transformative potential of AI seriously while not falling over into hype.
Some things that stand out:
* He’s really good with his historical analogies, especially looking at previous transformations like the early Internet and mobile; no surprise given that he has a history degree.
* he emphasizes over and over how we have still have no idea how all of this is going to work when the dust settles. I think that’s kind of a historian’s move as well. When you look at what people were saying during the early days of the web, for example, almost all of their predictions weren’t just wrong… in hindsight, given how the future played out, they were asking the wrong questions. The implication is that we are probably asking the wrong questions about AI too.
* Nonetheless his thesis about the commoditization of models is actually a fairly strong concrete prediction. i’m not sure if I agree with it entirely, but I do keep it in mind every time I look at the valuation of leading AI labs.
* he continually makes the point that a chat bot is barely a product and that AI labs have so far had very little success in delivering products above that layer… with the exception of coding agents, of course.
I just got a bit triggered by the "hype" word.
What if the hype was real? It is easy to say that nobody knows how all of this is going to work, and I would say it is a prudent thing to say, but there is value in making a bold prediction from the start instead of just updating your view to respond to change. In one case you are predicting stuff, in the other, just reacting.
But I absolutely agree that in hindsight we are often asking the wrong questions about each new technology.
I keep seeing on HN that AI is a hype, and many here are anti AI (which I get, as a programmer AI made my job less interesting, and I'm even worried about losing it), but where has AI underdelivered?
The hype is in what AI delivers (at least so far). I would never create a PR without an AI review. I will ask an AI to write code for me from time to time.
But it still has huge gaps in quality. And from time to time, it shows me that it doesn’t really understand things. You might point out that how is that any different from your mediocre engineer. But for most people skilled enough, you can easily know the difference when someone doesn’t really know something.
With AI, you discover this after reading several pages being dumped on you by people being “more productive” with AI.
Ok so the hype would be people saying AI can currently do something well and autonomously when it cannot (or not consistently enough), and it is easy to prove them wrong.
But I feel like people are more hyped about what the AI will be able to do soon rather than what it can do now.
I think AI does understand things (depending on your definition), how else could we communicate and ask it a question if it didn't? I mean we're quite far from Eliza here.
And yes, often their answer would be so wrong that we think it is impossible that AI understands anything, but this jagged intelligence doesn't prove, at least to me, that there isn't some understanding. At what point do we say that AI understands things? What if we can reduce 99% of those dumb failures, would we then say than AI understands?
That doesn't really respond to the question though - there is a quite reasonable argument that the Chinese room as a system 'understands' things.
The issue that is hit immediately is we don't have a definition or test of understanding that AI doesn't clear easily. Then on top of that we can't even really be sure that we ourselves are understand things given all the tricks that our minds play with memory and perception. There is precious little evidence that the people around us understand things, they seem to be guessing. It is completely unclear if a Chinese room has or doesn't have a property if we rule out all the tests that check for it as not really counting. But all the tests we can do suggest it does understand, because engineers can implement Chinese rooms now and they even turn out to be more reliably artistic/capable of novel thinking/creative than humans. Anything that tests understanding they can do.
No, they just say you are using the wrong model or something.
If it's a coworker dumping reviews of crap code on you at work, the incentive is to blanket approve everything because otherwise you're just the grumpy old man who is resisting innovation. No matter that the code makes no sense at all and the tests aren't actually testing what they should test.
Other than the stock market (which seems decoupled from reality at the moment), where has AI delivered?
The only use case where I see anything resembling AI delivering on it's promises is software, and my personal experience with that is that everything that comes out of the teams using AI is destructively broken. (Where they used to be able to deliver software that worked, even if it wasn't ideal, now they reliably make things worse and their stuff doesn't work when used.)
I agree, especially the juxtaposition of "we have still have no idea how all of this is going to work when the dust settles" and "hype". If we don't know, then there is a chance it isn't a hype.
For example, now it may seem that the models are becoming mere infrastructure, and the value moves up to apps and data. But if the models of tomorrow become able to write the apps themselves, then the value moves back. I won't need to pay some to write me a wrapper for the LLM, if the LLM will be able to write the same wrapper, maybe even better because it will be customized for my needs. The app providers are currently profiting from the gap between "what a software company can do using the AI" and "what the AI can do unaided", but that gap is going to shrink, possibly to zero.
> for example, almost all of their predictions weren’t just wrong… in hindsight, given how the future played out, they were asking the wrong question
Do you have an example of this? My (poor) memory remembers "it's going to change how people buy things", was the big deal at the time, and it seems like it was a great prediction.
Well, yes, but as the other commenter says, that’s a very broad general statement akin to something like “AI will change knowledge work“. That’s certainly true, but how? What are the details? What kind of companies are going to be the winners and what kind will be losers, or end up with commodity margins, like the telcos did after the mobile revolution? What is the pricing structure going to look like?
I suppose a concrete example in 1997 would be that a lot of companies thought the future of e-commerce was setting up a store on AOL, that people would use while sitting down at a desktop PC. Obviously it didn’t turn out quite that way. Furthermore, the Internet enabled new kinds of ways to buy things that weren’t even envisioned in the pre-Internet pre-smartphone world: think Airbnb and Uber.
Predictions are hard, especially about the future. Most predictions reflect the worldview and biases of the time in which they are made: think about all the vintage sci-fi from the 60s 70s and 80s that actually reads or looks kind of retro now. Similarly, our predictions of the future will look kind of retro and strange to someone living in the 2030s or 2040s. If studying history has any lesson to teach us, it’s really just this: that the past is an alien world with alien moods of thinking, and that our moment in time will look similarly alien to people in the future who choose to look back and analyze it closely.
This isn’t an argument that we should stop trying to make predictions. We need to, but it is an argument for humility, and also for questioning all your assumptions that you might be importing.
That's a very vague prediction that took decades to bear fruit. The concrete predictions behind the investments into companies like Pets.com and Webvan failed. It took the survivors like Ebay/Paypal and Amazon to build the digital payment and shipping infrastructure over decades until cultural acceptance hit critical mass.
Agreed, I appreciate his historical perspective, but I think one critical mistake his posts make is implying, largely because the parallels to history have been similar so far, that history will repeat.
Like, yes, the telecom bubble was a clear case of overbuilding and the AI data center "bubble" looks a lot like that... but this overlooks that the fiber capacity being laid back then far outstripped the demand, whereas all the compute providers today have been desperately crunched for capacity, despite investing almost a trillion in CapEx -- to the tune of almost a trillion dollars more of backlog -- for multiple quarters now.
Or yes, historically new technology has always created new jobs... but all those new jobs required a higher skill level along dimensions that current AI models are already good at, meaning we've never had a technological revolution quite like this.
Or yes, prior technological revolutions consigned incumbents to irrelevancy, primarily due to shifts in technical platforms... but then today's business leaders are 1) very well educated about what happened to their predecessors, 2) very paranoid about the same thing happening to them, and hence 3) are actively making moves to capitalize on the next platform shift.
I also think his dismissal of chatbots is a bit premature. It is precisely because chatbots operate via an extremely simple, flexible and natural modality, i.e. a conversation -- entirely unconstrained by the form factor necessitated by any app -- that their infinite use-cases have become unleashed.
My take is that the AI labs are actively exploiting this extreme flexibility to surface valuable use-cases -- one of the hardest parts of innovation -- at which point they can simply slap an agent on top of them. Which is, yet again, simply a chatbot, except one that can actually do useful things for you and hence can be charged for a lot more money.
I didn’t make any comparison at all with the fibre bubble, for precisely that reason. The comparison is with mobile data, which was and is always behind capacity.
I think one of the things that the usage data shows us is that chatbots absolutely do not have infinite use cases - most users only use them a day or two a week or less.
That's fair, I may be conflating your takes on mobile data with others who've made the comparison to the telecom bubble, and if so, mea culpa!
But I also do disagree with the take that usage patterns indicate a fundamental shortage of use-cases. Yes, everyone reports WAU instead of DAU because WAU numbers look much more impressive, but I think the extreme shortage of compute plays a major role in this. I suspect all the AI labs are deliberately holding back from pushing AI adoption too much because of this. (Google execs have even made comments internally to this effect.) Note that even at such low frequency of usage all the model providers are desperately strapped for compute, which means there is insanely high demand from some quarters.
One way how capacity limitations could impact adoption is that the free-tier models are not as good as the frontier ones, so the free users come away less impressed with AI capabilities, leading to lower regular usage. This problem is larger than it appears, because it can take a long time to figure out how to get AI to work for your use-case, and people simply have not experimented nearly enough, partially due to first impressions. On the other hand, most companies seem to be OK with huge tokenmaxxing bills!
It seems to me the AI players are all playing a delicate balancing game across three fundamental dimensions: adoption, monetization, capacity. That is, they are simultaneously 1) pushing free / cheap AI usage as much as possible to hook users, capture market share and suss out new use-cases, while 2) carefully allocating token quotas for the most lucrative use-cases to satisfy investors, and 3) balancing available compute between those two competing priorities. I suspect as the compute bottleneck is alleviated and frontier models become more accessible cheaply, we'll see way higher DAU numbers.
> new technology has always created new jobs... but all those new jobs required a higher skill level
The industrial revolution didn't seem to require any particular special skill at all. Just anyone who was willing to tend to a machine all day. (Maybe that's a parallel...)
You're right actually, what I really meant to say is a "higher-level skill" rather than a "higher skill-level." Higher-level skills don't necessarily mean a more difficult skill, they're usually just at a higher level of abstraction.
Specifically, the 3 dimensions along with new jobs required new skills were: a) cognitive, b) technical or c) social skills. I guess tending to a machine was a mix of a) and b), because even if the controls were straightforward, it probably required some understanding of the underlying mechanisms.
> When you train LLMs on large volumes of text that describe logically consistent facts in a million different ways, the "logic" sort of becomes part of the grammer that the model learns. That is logic becomes a higher kind of "grammer" or a enormous set of grammatical rules that it captures. But that does not mean the model can do actual logic.
This is the kind of stuff people were saying in 2023. But it’s 2026 now and LLMs aren’t just trained by reading lots of text anymore. That’s “pretraining”, and it’s still the first stage, but LLMs also have a huge amount of RLVR training where they actually do solve huge numbers of mathematical and logic puzzles and update their weights in response. They don’t just learn mathematics from reading about it now. They learn it by doing it. That is why they can now solve hard problems and probe theorems.
> that does not mean the model can do actual logic.
But they do, all the time. (Please tell me you’ve at least put a frontier LLM through its paces in the last 6 months?) If you think they can’t do logic and reasoning, can you provide examples of specific math or logic problems that you think a frontier LLM can’t do?
>If you think they can’t do logic and reasoning, can you provide examples of specific math or logic problems that you think a frontier LLM can’t do?
When a thing can "solve" a complex math problem without having the ability to count, then it is clear that this things is not "reasoning" and doing "logic".
It's easy to wave this aside as the current administration playing political games. But I don't think there is any reason to assume that the current era of open availability of models is going to continue indefinitely. Do you think that Chinese labs will continue to release open models forever, even why they get to the level that Mythos is at now, and beyond? And do you think that a competent US government would have no interest in regulating and restricting model access in 2 years time, assuming that model capabilities continue to improve? I think we bias towards thinking the status quo is the norm and will continue, but this news invites us to question that assumption and think about different ways the future could go.
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