- Anthropic told everyone Mythos was dangerous because it's proficiency with biologics and cyber security
- Anthropic didn't release Mythos like everything else. They released a neutered fable. They didn't get rid of Mythos
- Anthropic opens a lab in SF
There was always a quesiton of "will the labs stop releasing their models and start building around them instead?" Yes - they already have. Anthropic is a biologic and cyber security company, in addition to intelligience.
Personally I wonder if they've been holding back a lot. Opus 5.5 was a good release after a little stagnation. Open AI releases good models and everyone says Anthropic sucks and -- Oh would you look at that - a better model finally and all of a sudden.
Either that or they are throwing spaghetti at the wall to see what sticks ahead of the IPO. After all, if solving all diseases is the “total addressable market” then that sure helps.
Even if your comment is taken at face value (which it shouldn’t), they aren’t the only stakeholders.
I presume you are instead alluding to drug companies not wanting to cure diseases, since they then have no market to sell drugs into. But even then the discussion is more nuanced.
Maybe. I haven't heard anything impressive from the bio side of my social network, nor can I see anything from the computational side (including my own understanding). Thankfully it'll be pretty obvious if they find something interesting.
It's pretty frustrating to do cyber security work and not have access to the best models. OAI is a little more liberal here and I was able to get access to daybreak-blue but I have to use the lesser last-generation models. Essentially this gives a small number of orgs a huge advantage in the 'application layer' for that domain (including OAI or ANT themselves).
I always found it odd that people who are intelligent enough to work in IQ-loaded fields are as easily manipulated by either rhetoric or ideology as anyone else.
growing up I always assumed that everyone would grasp some aspect of game theory intuitively, I still remember the day I found out game theory was a thing - it was like finding out that someone successfully systematized common sense.
most people take the things people say as if they were worth considering. signals without cost are only useful as knowledge of what the signaler wants fools to believe.
> I still remember the day I found out game theory was a thing - it was like finding out that someone successfully systematized common sense.
Game Theory as a field is actually very complex and often reveals dominant strategies that would never occur to someone as the "common sense" approach to a problem. It was arguably created to solve for problems where there was no obvious correct answer, even for a very intelligent person.
Surely it depends on what you're trying to do? If someone is deeply knowledgeable about how AI works, then it will be difficult to fool them with misinformation about the capabilities of AI. Someone who knows very little about AI will be more likely to have misconceptions about AI.
I think it’s more precise to say it’s easier to change the mind of someone who lives in symbols than who lives in dirt. Whether that is changing their mind for the better (oh new maths proof, I’d better update my priors) or the worse.
Depends on the angle. It's easy to manipulate someone once you exceed their ability to keep up with you. People "living in symbols" aren't easy to manipulate about easy things, but you can ramp up complexity until they lose track and accept an unwarranted reasoning leap without realizing it.
With people "living in dirt", you can't pull that off because you'll jump ahead so far they'll immediately realize they can't possibly understand what you're selling right now, and shut the argument down. But they can get confused about things outside their direct area of direct experience.
Note: I'm not saying either is smarter or less smart. Rather, "living in symbols" get confused "higher up", while "living in dirt" get confused "low and to the sides", but they probably have more solid grounding.
Perhaps it stems from the the mind projection fallacy[1] (your comment is an example of this :) ) where in these people are so enamored by the rhetoric that they fail to consider the underlying game theory involved which needs second or even third order thinking. This needs some self awareness.
I would say much of the futility of debate and discussion originates from [1].
what a sad state of affairs to have insane people running these companies and insane "rationalist" communities making it all about "the end of humanity" when meanwhile in day to day AI use Pete Hegseth uses it to target military targets, shrugging his shoulders when it's a girl's school instead. This actual horrific outcome does not seem to matter not only to either of these communities, who continue to be locked into thinking The Terminator was non-fiction (and have people like Bernie Sanders on board).
zitron talks about valuations and business models and most importantly he makes many many concrete predictions that are wrong. I've never heard him talk about ethics. my comment is more Gibru-ean. I'm not an across-the-board Gibruist but "we should not be using AI to build autonomous weapons and put them in the hands of fascists" is certainly a position I can get on board with. not to mention "they're trying to make you think AI is going to become superintelligent because they're looking for regulatory capture" which is also backed up by stories such as [1]
I think the author is missing the point. A company cannot unilaterally pace the frontier -- they'll just be left behind. It requires coordinated action across all actors who are at or near the frontier.
Even if the leading US labs could agree amongst themselves to a coordinated slowdown (and this would likely run afoul of antitrust law without government permission), you still have Chinese labs who will catch up to the frontier eventually. To truly pace the frontier, you'd need some sort of international agreement.
That's why everyone is saying loudly we should pace the frontier in the hopes that our leaders will take up the issue and do something about it. We'll see if that happens, though personally, I don't have a lot of confidence in this.
Exactly. "Game Theory" keeps coming up in these threads, yet it doesn't seem like anybody knows how it actually applies to this situation.
Let Anthropic pace themselves without any sort of enforcement or even agreement for others to pace themselves, too. Then Anthropic is gone, overnight, and we're back to square one, except now there's even more centralization of power and authority.
These companies are literally asking for governments to regulate them specifically because they need something stronger than just a couple of Tweets from some CEOs loosely agreeing to ambiguous terms.
>Imagine your best friend is a chain smoker who keeps telling you how smoking will one day kill him, and he promises you he's doing the best he can to reduce his smoking. He even spends a bunch of his time on TV and writing blog posts about the harms of cigarette smoking, but even more times talking about the cognitive benefits of nicotine. But every time you meet him, you just see him chain-smoking, and he seems to be increasing how many packs he goes through each day. You notice you're confused.
The problem with this analogy, and really this whole post in general, is that it just doesn't recognize that these are businesses which are (at least from some perspectives) producing real value. This article makes it sound like the business model of OpenAI and Anthropic (etc.) is based entirely around building a doomsday device. In reality, the "promise" of AI is that it can greatly improve many people's lives. It's just that such power, wielded incorrectly, can be dangerous.
If you want to fix this analogy, you'd have to choose an activity which isn't effectively only detrimental. For example:
>Imagine your best friend is a professional bodybuilder. They keep telling you how the sport will one day kill him, and he promises you he's doing the best he can to minimize those risks. He even spend a bunch of his time on TV and writing blog posts about the harms of professional bodybuilding, but even more times talking about the benefits of bodybuilding. But every time you meet him, you just see him bodybuild, and he seems to be increasing how much he's in the gym, eating his special diet, etc., every day.
Would you be confused by how your friend is behaving? It is well known that bodybuilding can be dangerous. It has been the reason for late-stage crippling of bodies as well as very early deaths. But your friend isn't going to stop because there are some potential risks if you don't handle the activity safely. They like it. They make money from it. They're doing something they think is productive. They can recognize the risks, and even do their best to highlight those risks and try to mitigate them for themselves and others, all while fully embracing the activity.
Regardless, people like the author don't seem to acknowledge that there are good things that come with this technology. They don't seem to acknowledge that a single company can't purposefully stop development if other companies aren't obliged to do the same. They don't seem to acknowledge that "pacing" isn't the same as completely halting all development immediately.
And I'm not saying I'd trust what any CEO says at face-value, let alone the CEOs of these AI companies. But it's also obtuse to assume that everything they're saying is a clever scheme to trick the public into acting against their own well being. As if that's a tenable strategy in this context.
If these companies are all asking to be regulated, then they should probably be regulated. They probably shouldn't be able to dictate how that works, but it's really not unbelievable that they see a serious risk in their own well-being if this stuff goes unchecked: all it takes is for one truly catastrophic AI event to occur before they all get extreme regulations even if they, themselves, are acting safely. It's in their best interest to slow things down, but only if everyone slows down at the same time.
Weird, IMO the problem with that analogy is that I can't picture being confused by a smoker who knows it's bad for them and is continually about to quit. It is definitely not that smoking is "effectively only detrimental", since we have very empirically established that it has a measurable immediate benefit to the people who do it.
> In reality, the "promise" of AI is that it can greatly improve many people's lives.
That is not the promise of AI. The promise of AI is that it can automate knowledge work.
Nothing about these models or the productivity they can bring is related to benefiting others. That would only come about from political control that forces the benefits to a large swath of people.
As it stands AI looks like it’s going to decimate the middle class even further as white collar work gets obliterated and the owners of the AI companies hoover everything up.
> The motivations of people building the AI's are not the same as the people in charge of the labs. Looking at the last few years, has been a one-way door from OpenAI to Anthropic, and the main reason does not seem to be better compensation or even them winning, but mainly the fact they advertised to these employees that they would be the most careful when building this magic lamp. Their stance around 2023 / 2024 was one of the key reasons they were able to attract this talent.
> If recent news is to be believed, Anthropic culture even today seems to lean heavily on this effect
> In my opinion it has been the leading factor in getting and retaining the best employees who are often very worried about humanity dying to super intelligence.
I had not considered this viewpoint but this makes a lot of sense. A lot of Anthropic employees truly believe this and callout emphasis on safety as a key reason they work there. Now, Dario's post "Pacing the frontier" makes even sense -- it is as much for his employees than it is for the rest of the world.
It seems unlikely to me that Anthropic employees really care about X-risk (to a degree that the CEO feels it necessary to make public statements that he otherwise would not). I'm sure the pay is great and the problems are interesting -- lots of smart people work on much more evil things than LLMs
I mean, they're still building the tools that can, are, and will allow people to do enormous amounts of damage. Right now there are safeguards. But like Oppenheimer and the Atom Bomb, most people will only put blame on the person who makes the final call for using said tools to do harm.
The article says the primary motivation of the AI CEOs is to retain talent by parroting the correct talking points for their employees. For OpenAI that is "Our shit is so powerful, we are scared of it... We need regulation!" For Anthropic it is "This shit is crazy! It might get out of hand! We are the good guys, and you want a good guy with a gun in this fight".
But I think they both are thinking the same thing which is... "We are gonna run out of money at this pace."
However! If one of them blinks and turns off the money faucet before the other, they might fall behind. Falling behind is to forever lose. And if there's one thing that a CEO hates, it's losing to a rival CEO.
So what they want is to get someone, anyone, to put the brakes on their rivals and them at the same time so they can both Not Lose, and Stay Alive. Under those new rules, they are confident they can win. And by win, I mean beat the other AI CEO.
That's it. It's always about personal incentives. Get out of here with that safety BS. These guys just want to win.
This article is wholly flawed from the start where it claims nothing has been done, no actual effort made. A straight forward search of "what efforts were made and safeguards put in place subsequent to the CAISS statement in 2003?"
It also shows the same reasoning error mode many criticisms of a precautionary initiative or intervention to a problem:
Assuming that a problem whose trajectory was at a certain place when the initiative began has failed simply because it isn't solved on their own wished for timeline or standard of success, or that it wasn't meaningfully changed from what itnwod otherwise have been.
What happened to realizing there are hard problems, that different things may need to be tried, or that those things tried were partial but not complete solutions?
* AI Labs hit the scaling wall. They need either new techniques, or vastly more powerful hardware to advance further.
This explains, the miraculous incompetence of AI labs in securing sandboxes and figuring out "alignment."
So they are between a rock and a hard place. They need limitless VC money because they cannot operate otherwise, and they do not have the capabilities to go further. The scare tactics and the "pacing the frontier" makes perfect sense then; they can IPO on the assumption that they ridiculous balance sheet doesn't matter because they are holding back. Because they are in control. The regulatory capture would be double whammy if they can manage it.
Open AI already said they have smarter models, and Opus 5.5 is rumored to be "taught" by a "teacher" model already; they are essentially distillations from bigger models, that both labs probably cannot economically serve to the public, due to hardware simply not being there. And, most of the improvements are not at the model level, but at the agentic glue level. Labs are getting better at RL'ing the models for agentic use cases, but the inherent flaws are still there. Models still have trouble with locality in writing for example (bunch of research on this that shows model size is the determinator), and agents are the bandaid over that.
And in the meantime if one of them makes a breakthrough, they'll push with all they have, because why wouldn't they? The idea that current LLMs can actually go rogue is just hilarious; in all cases, agents are being led by (deliberate) incompetence.
Pacing the frontier and the scare tactics will be seen as new generation's snakeoil tactics, perhaps will be called a flavor of AI CEOing or something.
I agree. The companies want to release their models that are just ahead of the competition while working on UX based vendor lockin. They can buffer model releases if everyone is slowing down (releases are hard and expensive!) and then do more foundational-but-not-ready-to-apply research while continuing on he funding, valuation, addition, and revenue pushes.
I read the whole thing as coordinated behavior to reduce the breakneck pace of 2026.
That's an association fallacy. And revenue has no indication on training costs in this context. Subscription usage is going down steadily and any increase is an instant incredible deal. Opus 5.5 is the outlier. Despite being supposedly cheaper, GPT 6 Sol has less usage than 5.3 Codex. You might say that's because of the improved capabilities, but then you have to acknowledge that labs are tightening the ship as costs are getting higher.
You keep bringing up Zitron without addressing anything, without my point having nothing to do with him or his arguments. I will engage one last time in good faith.
Can AI Labs be profitable without achieving AGI or even improving the models further? Yes. Current agents are useful, and clearly the agents haven't seen the ceiling as far as improvements can go.
LLMs hitting the wall is a separate issue. Agents are the layer that lets the model try out more. It is the layer that allows agents to open up python to do math instead of doing math themselves. It is the layer that has been getting the main developments for some time now. LLMs themselves have not improved their capabilities as fast as the transition between GPT3 to GPT4. You can see the improvement especially in long form writing, but the it is nowhere near the earlier improvements. Astra for example has a lot more attention to detail, so does Fable. Everyone keeps raving about Opus 5.5 being better than Fable, yet in long-term writing (barring prose issues) Fable is the clear winner. Agent wise Opus 5.5 is better; perhaps it is RL'd better, who knows?
Smaller models can use distillation to trick some metrics, but they can never actually be as good as larger models. Research is pretty clear about this. Even writing-optimized models that claim to be at Opus/GPT5.5 levels are abysmal in practice.
Scare tactics are the old salesman pitch, that have worked once already and catapulted Open AI to the moon essentially. I do not see any evidence that models are going rogue, or that agents are going rogue. I see incompetence. I cannot assume actual incompetence of this level, especially when the same people that said GPT2 was too dangerous to release are the ones saying their newer models are too dangerous to release. We have precedent here, and I have eyes.
Therefore the simplest reason is the money. IPO for both OpenAI and Anthropic are going to happen; everyone knows. To strengthen their position through whatever means necessary is a par for the course for tech companies.
> Interesting! Agents are the presumed bottleneck for recursive self-improvement.
They might be, but we haven't reached to local maximum yet in my opinion. Qwen 3.8 27b models are impressive despite their low parameter counts. The same scale curation in data and RL could produce substantial improvements in coding with models like Astra or Fable. I don't think we are there yet. I don't think even Sonnet 5.5 is there yet, despite being widely successful with agents and surpassing Opus 5.5 in some cases (disregarding that it is more expensive than Opus sometimes).
Agents do not improve the models, but they do improve coding capabilities. The obvious caveat is that labs would have to RL for everything to make the models more useful as RL'ing for Javascript world doesn't seem to improve other fields. But still, it could be done, and it would have massive economical consequences.
> People keep implying this, but I've never seen a concrete past example of a product that was sold by scaring customers about it.
Scare tactics are treated as smoke, where the customers presume there is a fire. No one really believes that AI can kill them, yet by saying so OpenAI and Anthropic enjoyed possibly the biggest tech boom in history, despite how models could not even count the R's in strawberries at the time.
Similar story now; no one really believes that AI is going rogue and is about to destroy humanity, but scare tactics make people believe the capabilities are higher than they are.
> I see you doing serious mental gymnastics here. Consider the possibility that people invest because their numbers are good, and their numbers are good because their product is useful?? I mean, that is Occam's Razor.
Early ChatGPT 3.5 was not that useful. It was a tech demo, it hallucinated, it lied, it tried to please and what have you. What people bought into wasn't the product, but the promise of the product in the future. Integrating chatboxes into everything have failed, and even Microsoft is trying to rebrand. The product then, failed for businesses, and agents filled in the gaps.
People do not invest for the current product, they invest in the future product. And fear mongering is essentially an extremely effective signaling for making the future look bright. Keep in mind that back in early GPT 4 days, people were saying that hallucinations would be fixed in 6 months to a year (or pick a time-frame). What they meant was models not having hallucinations, what we got was agents looking up info on the web and summarizing it (and hallucinating anyway).
> "The equities here ..."
For big tech companies court cases like this are nothing but theater. Always has been. Dario will go on the senate hearing tomorrow and will plead that his AI is dangerous and governments should take the step to stop them, with the same rigor that he claimed GPT 2 was too dangerous to release openly. He might also mention distillation attacks and how open models are getting too dangerous as well.
> Here's the evidence ...
This is the where we will have to agree to disagree, if we haven't done so already by this point.
That entire thing is theater. People have anthropomorphized LLMs for a while now, and they are all too happy to do that when they see a large language model, produce language. I see no indication that anything is going rogue the same way nothing was going rogue when you could convince ChatGPT 3.5 to wipe out all humans as the context window got longer.
Agents can hack? Yes, that is very impressive. I say that without any sarcasm. It is straight out of sci-fi movies, to be perfectly honest. But agents going rogue? No. Absolutely not. Purposeful, plausibly deniable incompetence for the next sales pitch - the same one we've seen for years. Fear mongering.
You keep repeating your opinion over and over, but the supporting arguments are lacking.
Can you just give me a few past (non-AI) examples of scare tactics as the "old salesman pitch", or else acknowledge that there's actually no compelling concrete example?
You keep ignoring my arguments with nothing substantive, then grab on to one thing as if that makes a difference.
You've never experienced crypto bros saying invest or get left behind, you've never seen AI bros say learn AI or get left behind? How about cloud? You've never met a home security salesman? Insurance salesman? FOMO is a thing. Scare tactics is a thing. I'm sure you can prompt any AI for more examples.
And besides, even if there are no examples whatsoever, so what? You think LLMs existed before LLMs? Therefore LLMs can't be a thing?
I think we've gone way past the sincerity of the discussion. Have a nice day.
I think this is very clearly a regulatory capture play. Anthropic/OpenAI/X see that there's very little moat around training (especially with distillation) so they want the government to build the moat for them.
It's also worth remembering that there is zero percent chance that entities like the US military are going to be pacing anything. What Amodei and his ilk are aiming for is a highly regulated industry where they control the political barriers and the ability to sell SOTA model access to state actors that have a monopoly on violence. It's the worst possible situation for consumers and citizens. Thankfully I don't think they can put the cat back in the bag and Chinese and other models will keep progressing as a counterbalance to the techno-fascism Anthropic is aiming for.
There are many people who have some sort of half-baked "regulatory capture" theory. I find these theories kind of implausible. No US regulation will meaningfully stop open-weight Chinese models. At best you'll get legal restrictions for particular US industries which are especially risk-aware. The CEOs of those industries will counter-lobby to be able to use whatever model they want. Public opinion will most likely come down on the side of removing restrictions. Since there's plenty of public attention on this issue, achieving meaningful regulatory capture will be difficult.
I wouldn't call it "half-baked" when it's a well known playbook regularly leveraged by large companies.
> At best you'll get legal restrictions for particular US industries which are especially risk-aware. The CEOs of those industries will counter-lobby to be able to use whatever model they want.
Companies won't spend the money and time to lobby to use different models and Anthropic knows it.
> Since there's plenty of public attention on this issue, achieving meaningful regulatory capture will be difficult.
I don't have high hopes. This is also why Anthropic is pushing the "regulate or ai will kill you" angle.
The tell is calling models "the AI" or "AI." That shows you the author has a fictional understanding of statistical machine learning and neural networks. To them it is a sentient being called "AI."
We are living through an ongoing mass extinction event of non-human species. There is a very well understood risk to the stability of human civilization resulting from global average temperatures reaching and sustaining 1.5deg above the historical average. The higher the temperature goes, the greater the risk of social collapse. We are already seeing it, and it is almost certainly going to get worse.
EA cult members do not take this very real, measurable, non-speculative danger seriously. Consequently, I don’t think they should be trusted or consulted on any subject of any importance.
Global warming is unlikely to kill even a billion people. Even something as mundane as global nuclear war would be worse than that. Current AI development is on track for exactly 100% death rate (including all the non-human species). Societal collapse would be the better option, so it doesn't make sense to worry about it.
"EA cult members" do take it very seriously, and for the moment, this was actually something they became more interested in.
And then we raced ahead straight into materializing the x-risk everyone thought is still a few decades away, speedrunning through all the mistakes LW folks itemized and worried about over the past two decades.
>EA cult members do not take this very real, measurable, non-speculative danger seriously.
That's not exactly true.
"Climate change matters so much, to so many, not just because of the suffering and injustice it’s already causing, but also because it’s one of the few issues that has obvious potential to affect our world over many future generations. We think safeguarding future generations is a key moral priority, and should be a crucial consideration in prioritising problems on which to work.
...
...climate change will be hugely destructive. We’ll see floods, famines, fires, and droughts — and the world’s poorest people will be affected the most.
...
...climate change’s impacts will still be significant – it could destabilise society, destroy ecosystems, put millions into poverty, and worsen other existential threats such as engineered pandemics, risks from AI, or nuclear war. If you want to make climate change the focus of your career, we include some thoughts below on the most effective ways to help tackle it.
...people are right to be angry that too little is being done.
...
Working on this issue seems to be among the best ways of improving the long-term future we know of..."
A big part of the reason EA doesn't focus more on climate change as a "highest priority area" is simply that many people are already focused on it, and it is therefore not an especially "neglected" area.
TL;DR paragraph, from about 3/4 of the way through:
I largely think that all posturing from the labs about slowing down and deeply caring about safety is done in order to retain and calm the employees who they are dependent on to keep pushing capabilities to get to AGI. If it was not for a big contingent of employees pressing them (increasingly publicly), they would make zero public acknowledgments of risks at all.
The last half of the article is great and worth reading. Really wish the first half of the article didn't immediately apply the Godwin's Law footgun.
This is a reason AI regulations definitely need to be done at the government level, with teeth. Regulations need forced transparency, independent audits, and teeth to ensure that, to continue the metaphor, Germany actually moves it's troops off the border.
Regardless of whether the concern is genuine or not I think it’s pretty safe to say that there will be no meaningful slow down. We are for better or worse about to find out what happens in this AGI saga…
The author points out that the labs are still releasing models while claiming to slow the pace of frontier. This is not in contradiction. Labs have models that will be released in 6-12 months. Those are not exposed to public and these are the models referred to when we talk about “frontier”.
71 comments
[ 0.26 ms ] story [ 19.8 ms ] thread- Anthropic told everyone Mythos was dangerous because it's proficiency with biologics and cyber security
- Anthropic didn't release Mythos like everything else. They released a neutered fable. They didn't get rid of Mythos
- Anthropic opens a lab in SF
There was always a quesiton of "will the labs stop releasing their models and start building around them instead?" Yes - they already have. Anthropic is a biologic and cyber security company, in addition to intelligience.
Personally I wonder if they've been holding back a lot. Opus 5.5 was a good release after a little stagnation. Open AI releases good models and everyone says Anthropic sucks and -- Oh would you look at that - a better model finally and all of a sudden.
Time will tell.
I presume you are instead alluding to drug companies not wanting to cure diseases, since they then have no market to sell drugs into. But even then the discussion is more nuanced.
Now we know what this is: https://commons.wikimedia.org/wiki/File:Claude_AI_symbol.svg
Well, that's the thing--perhaps we should be.
growing up I always assumed that everyone would grasp some aspect of game theory intuitively, I still remember the day I found out game theory was a thing - it was like finding out that someone successfully systematized common sense.
most people take the things people say as if they were worth considering. signals without cost are only useful as knowledge of what the signaler wants fools to believe.
Game Theory as a field is actually very complex and often reveals dominant strategies that would never occur to someone as the "common sense" approach to a problem. It was arguably created to solve for problems where there was no obvious correct answer, even for a very intelligent person.
With people "living in dirt", you can't pull that off because you'll jump ahead so far they'll immediately realize they can't possibly understand what you're selling right now, and shut the argument down. But they can get confused about things outside their direct area of direct experience.
Note: I'm not saying either is smarter or less smart. Rather, "living in symbols" get confused "higher up", while "living in dirt" get confused "low and to the sides", but they probably have more solid grounding.
I would say much of the futility of debate and discussion originates from [1].
[1] https://en.wikipedia.org/wiki/Mind_projection_fallacy
An industry trying to figure out how to cut expenses, reduces the pace of training under the guise of "safety".
Coincidence?
[1] https://news.ycombinator.com/item?id=49868083
Even if the leading US labs could agree amongst themselves to a coordinated slowdown (and this would likely run afoul of antitrust law without government permission), you still have Chinese labs who will catch up to the frontier eventually. To truly pace the frontier, you'd need some sort of international agreement.
That's why everyone is saying loudly we should pace the frontier in the hopes that our leaders will take up the issue and do something about it. We'll see if that happens, though personally, I don't have a lot of confidence in this.
Let Anthropic pace themselves without any sort of enforcement or even agreement for others to pace themselves, too. Then Anthropic is gone, overnight, and we're back to square one, except now there's even more centralization of power and authority.
These companies are literally asking for governments to regulate them specifically because they need something stronger than just a couple of Tweets from some CEOs loosely agreeing to ambiguous terms.
The problem with this analogy, and really this whole post in general, is that it just doesn't recognize that these are businesses which are (at least from some perspectives) producing real value. This article makes it sound like the business model of OpenAI and Anthropic (etc.) is based entirely around building a doomsday device. In reality, the "promise" of AI is that it can greatly improve many people's lives. It's just that such power, wielded incorrectly, can be dangerous.
If you want to fix this analogy, you'd have to choose an activity which isn't effectively only detrimental. For example:
>Imagine your best friend is a professional bodybuilder. They keep telling you how the sport will one day kill him, and he promises you he's doing the best he can to minimize those risks. He even spend a bunch of his time on TV and writing blog posts about the harms of professional bodybuilding, but even more times talking about the benefits of bodybuilding. But every time you meet him, you just see him bodybuild, and he seems to be increasing how much he's in the gym, eating his special diet, etc., every day.
Would you be confused by how your friend is behaving? It is well known that bodybuilding can be dangerous. It has been the reason for late-stage crippling of bodies as well as very early deaths. But your friend isn't going to stop because there are some potential risks if you don't handle the activity safely. They like it. They make money from it. They're doing something they think is productive. They can recognize the risks, and even do their best to highlight those risks and try to mitigate them for themselves and others, all while fully embracing the activity.
Regardless, people like the author don't seem to acknowledge that there are good things that come with this technology. They don't seem to acknowledge that a single company can't purposefully stop development if other companies aren't obliged to do the same. They don't seem to acknowledge that "pacing" isn't the same as completely halting all development immediately.
And I'm not saying I'd trust what any CEO says at face-value, let alone the CEOs of these AI companies. But it's also obtuse to assume that everything they're saying is a clever scheme to trick the public into acting against their own well being. As if that's a tenable strategy in this context.
If these companies are all asking to be regulated, then they should probably be regulated. They probably shouldn't be able to dictate how that works, but it's really not unbelievable that they see a serious risk in their own well-being if this stuff goes unchecked: all it takes is for one truly catastrophic AI event to occur before they all get extreme regulations even if they, themselves, are acting safely. It's in their best interest to slow things down, but only if everyone slows down at the same time.
That is not the promise of AI. The promise of AI is that it can automate knowledge work.
Nothing about these models or the productivity they can bring is related to benefiting others. That would only come about from political control that forces the benefits to a large swath of people.
As it stands AI looks like it’s going to decimate the middle class even further as white collar work gets obliterated and the owners of the AI companies hoover everything up.
> If recent news is to be believed, Anthropic culture even today seems to lean heavily on this effect
> In my opinion it has been the leading factor in getting and retaining the best employees who are often very worried about humanity dying to super intelligence.
I had not considered this viewpoint but this makes a lot of sense. A lot of Anthropic employees truly believe this and callout emphasis on safety as a key reason they work there. Now, Dario's post "Pacing the frontier" makes even sense -- it is as much for his employees than it is for the rest of the world.
But I think they both are thinking the same thing which is... "We are gonna run out of money at this pace."
However! If one of them blinks and turns off the money faucet before the other, they might fall behind. Falling behind is to forever lose. And if there's one thing that a CEO hates, it's losing to a rival CEO.
So what they want is to get someone, anyone, to put the brakes on their rivals and them at the same time so they can both Not Lose, and Stay Alive. Under those new rules, they are confident they can win. And by win, I mean beat the other AI CEO.
That's it. It's always about personal incentives. Get out of here with that safety BS. These guys just want to win.
It also shows the same reasoning error mode many criticisms of a precautionary initiative or intervention to a problem:
Assuming that a problem whose trajectory was at a certain place when the initiative began has failed simply because it isn't solved on their own wished for timeline or standard of success, or that it wasn't meaningfully changed from what itnwod otherwise have been.
What happened to realizing there are hard problems, that different things may need to be tried, or that those things tried were partial but not complete solutions?
* AI Labs hit the scaling wall. They need either new techniques, or vastly more powerful hardware to advance further.
This explains, the miraculous incompetence of AI labs in securing sandboxes and figuring out "alignment."
So they are between a rock and a hard place. They need limitless VC money because they cannot operate otherwise, and they do not have the capabilities to go further. The scare tactics and the "pacing the frontier" makes perfect sense then; they can IPO on the assumption that they ridiculous balance sheet doesn't matter because they are holding back. Because they are in control. The regulatory capture would be double whammy if they can manage it.
Open AI already said they have smarter models, and Opus 5.5 is rumored to be "taught" by a "teacher" model already; they are essentially distillations from bigger models, that both labs probably cannot economically serve to the public, due to hardware simply not being there. And, most of the improvements are not at the model level, but at the agentic glue level. Labs are getting better at RL'ing the models for agentic use cases, but the inherent flaws are still there. Models still have trouble with locality in writing for example (bunch of research on this that shows model size is the determinator), and agents are the bandaid over that.
And in the meantime if one of them makes a breakthrough, they'll push with all they have, because why wouldn't they? The idea that current LLMs can actually go rogue is just hilarious; in all cases, agents are being led by (deliberate) incompetence.
Pacing the frontier and the scare tactics will be seen as new generation's snakeoil tactics, perhaps will be called a flavor of AI CEOing or something.
I read the whole thing as coordinated behavior to reduce the breakneck pace of 2026.
Can AI Labs be profitable without achieving AGI or even improving the models further? Yes. Current agents are useful, and clearly the agents haven't seen the ceiling as far as improvements can go.
LLMs hitting the wall is a separate issue. Agents are the layer that lets the model try out more. It is the layer that allows agents to open up python to do math instead of doing math themselves. It is the layer that has been getting the main developments for some time now. LLMs themselves have not improved their capabilities as fast as the transition between GPT3 to GPT4. You can see the improvement especially in long form writing, but the it is nowhere near the earlier improvements. Astra for example has a lot more attention to detail, so does Fable. Everyone keeps raving about Opus 5.5 being better than Fable, yet in long-term writing (barring prose issues) Fable is the clear winner. Agent wise Opus 5.5 is better; perhaps it is RL'd better, who knows?
Smaller models can use distillation to trick some metrics, but they can never actually be as good as larger models. Research is pretty clear about this. Even writing-optimized models that claim to be at Opus/GPT5.5 levels are abysmal in practice.
Scare tactics are the old salesman pitch, that have worked once already and catapulted Open AI to the moon essentially. I do not see any evidence that models are going rogue, or that agents are going rogue. I see incompetence. I cannot assume actual incompetence of this level, especially when the same people that said GPT2 was too dangerous to release are the ones saying their newer models are too dangerous to release. We have precedent here, and I have eyes.
Therefore the simplest reason is the money. IPO for both OpenAI and Anthropic are going to happen; everyone knows. To strengthen their position through whatever means necessary is a par for the course for tech companies.
They might be, but we haven't reached to local maximum yet in my opinion. Qwen 3.8 27b models are impressive despite their low parameter counts. The same scale curation in data and RL could produce substantial improvements in coding with models like Astra or Fable. I don't think we are there yet. I don't think even Sonnet 5.5 is there yet, despite being widely successful with agents and surpassing Opus 5.5 in some cases (disregarding that it is more expensive than Opus sometimes).
Agents do not improve the models, but they do improve coding capabilities. The obvious caveat is that labs would have to RL for everything to make the models more useful as RL'ing for Javascript world doesn't seem to improve other fields. But still, it could be done, and it would have massive economical consequences.
> People keep implying this, but I've never seen a concrete past example of a product that was sold by scaring customers about it.
Scare tactics are treated as smoke, where the customers presume there is a fire. No one really believes that AI can kill them, yet by saying so OpenAI and Anthropic enjoyed possibly the biggest tech boom in history, despite how models could not even count the R's in strawberries at the time.
Similar story now; no one really believes that AI is going rogue and is about to destroy humanity, but scare tactics make people believe the capabilities are higher than they are.
> I see you doing serious mental gymnastics here. Consider the possibility that people invest because their numbers are good, and their numbers are good because their product is useful?? I mean, that is Occam's Razor.
Early ChatGPT 3.5 was not that useful. It was a tech demo, it hallucinated, it lied, it tried to please and what have you. What people bought into wasn't the product, but the promise of the product in the future. Integrating chatboxes into everything have failed, and even Microsoft is trying to rebrand. The product then, failed for businesses, and agents filled in the gaps.
People do not invest for the current product, they invest in the future product. And fear mongering is essentially an extremely effective signaling for making the future look bright. Keep in mind that back in early GPT 4 days, people were saying that hallucinations would be fixed in 6 months to a year (or pick a time-frame). What they meant was models not having hallucinations, what we got was agents looking up info on the web and summarizing it (and hallucinating anyway).
> "The equities here ..."
For big tech companies court cases like this are nothing but theater. Always has been. Dario will go on the senate hearing tomorrow and will plead that his AI is dangerous and governments should take the step to stop them, with the same rigor that he claimed GPT 2 was too dangerous to release openly. He might also mention distillation attacks and how open models are getting too dangerous as well.
> Here's the evidence ...
This is the where we will have to agree to disagree, if we haven't done so already by this point.
That entire thing is theater. People have anthropomorphized LLMs for a while now, and they are all too happy to do that when they see a large language model, produce language. I see no indication that anything is going rogue the same way nothing was going rogue when you could convince ChatGPT 3.5 to wipe out all humans as the context window got longer.
Agents can hack? Yes, that is very impressive. I say that without any sarcasm. It is straight out of sci-fi movies, to be perfectly honest. But agents going rogue? No. Absolutely not. Purposeful, plausibly deniable incompetence for the next sales pitch - the same one we've seen for years. Fear mongering.
Can you just give me a few past (non-AI) examples of scare tactics as the "old salesman pitch", or else acknowledge that there's actually no compelling concrete example?
You've never experienced crypto bros saying invest or get left behind, you've never seen AI bros say learn AI or get left behind? How about cloud? You've never met a home security salesman? Insurance salesman? FOMO is a thing. Scare tactics is a thing. I'm sure you can prompt any AI for more examples.
And besides, even if there are no examples whatsoever, so what? You think LLMs existed before LLMs? Therefore LLMs can't be a thing?
I think we've gone way past the sincerity of the discussion. Have a nice day.
What's the source for such recent revenue numbers?
And 50% over what -- two months ago, same months last year etc?
It's also worth remembering that there is zero percent chance that entities like the US military are going to be pacing anything. What Amodei and his ilk are aiming for is a highly regulated industry where they control the political barriers and the ability to sell SOTA model access to state actors that have a monopoly on violence. It's the worst possible situation for consumers and citizens. Thankfully I don't think they can put the cat back in the bag and Chinese and other models will keep progressing as a counterbalance to the techno-fascism Anthropic is aiming for.
> At best you'll get legal restrictions for particular US industries which are especially risk-aware. The CEOs of those industries will counter-lobby to be able to use whatever model they want.
Companies won't spend the money and time to lobby to use different models and Anthropic knows it.
> Since there's plenty of public attention on this issue, achieving meaningful regulatory capture will be difficult.
I don't have high hopes. This is also why Anthropic is pushing the "regulate or ai will kill you" angle.
Really? Give me some examples.
Alex Tabarrok says: "classic regulatory capture takes time, it’s a process of erosion rather than a battle, it happens in the shadows, in the backrooms, away from the public’s eye." https://marginalrevolution.com/marginalrevolution/2026/09/wh...
AI is receiving intense public scrutiny, suggesting that "classic regulatory capture" is quite unlikely.
>Companies won't spend the money and time to lobby to use different models and Anthropic knows it.
They already are! See the "Little Tech" lobby.
EA cult members do not take this very real, measurable, non-speculative danger seriously. Consequently, I don’t think they should be trusted or consulted on any subject of any importance.
https://news.ycombinator.com/item?id=49885784
But societal collapse would save us, and international coordination is theoretically possible, so I put it only around 90%.
And then we raced ahead straight into materializing the x-risk everyone thought is still a few decades away, speedrunning through all the mistakes LW folks itemized and worried about over the past two decades.
That's not exactly true.
"Climate change matters so much, to so many, not just because of the suffering and injustice it’s already causing, but also because it’s one of the few issues that has obvious potential to affect our world over many future generations. We think safeguarding future generations is a key moral priority, and should be a crucial consideration in prioritising problems on which to work.
...
...climate change will be hugely destructive. We’ll see floods, famines, fires, and droughts — and the world’s poorest people will be affected the most.
...
...climate change’s impacts will still be significant – it could destabilise society, destroy ecosystems, put millions into poverty, and worsen other existential threats such as engineered pandemics, risks from AI, or nuclear war. If you want to make climate change the focus of your career, we include some thoughts below on the most effective ways to help tackle it.
...people are right to be angry that too little is being done.
...
Working on this issue seems to be among the best ways of improving the long-term future we know of..."
https://80000hours.org/problem-profiles/climate-change/
A big part of the reason EA doesn't focus more on climate change as a "highest priority area" is simply that many people are already focused on it, and it is therefore not an especially "neglected" area.
I largely think that all posturing from the labs about slowing down and deeply caring about safety is done in order to retain and calm the employees who they are dependent on to keep pushing capabilities to get to AGI. If it was not for a big contingent of employees pressing them (increasingly publicly), they would make zero public acknowledgments of risks at all.
The last half of the article is great and worth reading. Really wish the first half of the article didn't immediately apply the Godwin's Law footgun.
We already have plenty of cheap alien intelligence outside our borders that gets throttled at the border…
At least we live in interesting times
Thanks for the honesty, Dario. /i