What they're proposing now, is voluntarily staggering the pace of development.
IMO, we don't need to trust Dario or his bedfellows, to do this out of their goodness of their heart. Even assuming (for good reasons) that they are selfish and care only about short-term profits for their investors, this is still purely a business decision. The exponential pace of AI and its impacts ARE short-term. And so, the negative consequences that they might face is also short-term.
It’s easy to say “fringe” but the average person seems to have a generally negative sentiment around AI. But I wouldn’t say they have a firm opinion yet
A few more informed people are also a little concerned about the end of the world, but that’s approaching from so many directions that an AI uprising might not be the worst option…
Realistically; anyone paying for llm access (anthropic, openai, gemini), is getting their access, and a service provided billed by tokens, subscription, whatever.
All the efficiency gains, which publications like deepseek v4.1 flash seriously frontload like it is their most important topic to have accomplished improvements on without diminishing performance too much - now this is a thing anthropic and anyone else also cares about, but for different reasons.
American "providers" with closed models are setting their token pricing somewhat arbitrarily, which is fine: it means more profit, and pretraining and RL experimentation is super important and expensive.
They (closed model providers) have very likely super optimized inference too, just like deepseek, but it's not at all something that any customer really has to care about - they just want the service to be as cheap and great as possible.
Caching is the simplest one to understand, cloud providers often reach a 90% cache hit rate, so hosting the same request locally on the exact same model on the same hardware is often way less efficient than on the cloud where a group of users generates a healthy cache.
The benefits of scale are on the token generation side, you can batch rounds and generate tokens for multiple conversations per pass instead of just one token per pass.
It seems damaging since most folks (who lack insider knowledge) will naturally wonder if it’s due to plateauing performance per $ or some other non “alignment” reason.
You never got to use OAI IM1, but Sol was quite willing too and Claude wasn't perfect either. Hundreds of millions used those, so seems they were marketable.
The "big" threat is RSI without control and alignment. OAI IM1 was not RSI. The form of misalignment was not at the top of severities. They clearly failed at control though.
We need to stop buying into cynicism so quickly. You refuse to believe Dario could support this for anything other than ulterior motives. Good on you for thinking about ulterior motives. Bad on you for assuming they are true when the story makes no sense.
When three things have to go wrong to get an epically bad outcome, and you get 1 1/2, you do need to stop and think about what's going on.
From my own standpoint, Claude has started sucking really bad (incoherent, uncontrollable verbosity slow and so on) and I stopped using it. OpenAI started experimenting with ads.
So the security issues not withstanding (no different than a human doing it or using it, but at scale), I would put my money on cynisim.
Personally I've been using https://pi.dev for long and never looked back.
Personally that's actually another good reason to boycott Anthropic: beside the fact I perceive their models as (at best) marginally better than the ones I'm used to (Z.ai glm-5.3-flash, DeepSeek Flash v4.1), they even force me to use their bloated harness. They are not even open weights and iirc they're even encrypting chain of thoughts now? Litterally, from my perspective there seems to be no reason whatsoever to choose any of the leading US providers, they're not even competing on price.
If I really need to, I can escalate a task to Opus at $25/1M, and the results are good, but not 5000% as good.
A true cynic looks at the statements by the AI labs, assumes things are worse because the labs want to seem better than they truly are. And it takes a special kind of mass delusion to drive a sane person to think “AI is completely under our control” is worse than “AI could kill everyone.”
What if consolidating AI into a highly regulated cartel, with no chance of upstart competition ruining their position, is the scenario that leads to the worst possible outcome?
Implicit in this is the idea that AI is a inscrutable matrix and going to remain that way and we'll need expert interpreters to make sense of it.
We need to insist on building tech that's explainable by design.
> A gun is a metal tube that uses a tiny, controlled explosion to shoot a small piece of metal (called a bullet) forward at very high speed.
If the gun doesn't work as intended, you can take it to a shop and someone can fix it so it works as designed.
All I'm saying is AI should be designed the same way. Treat AI as normal tech like any other and use similar language.
We have something that is statistical in nature so there should never been any expectation of error-free results/actions. The value has always been about discerning trends or the cost of errors being way lower than any good result.
In 2017 Google was writing papers about it. Then something changed.
I don't think it was the tech. It was a realization around the power and societal impact.
The companies doing these things without following common sense security measures are the felony generators.
Heck, they exploited zero day flaws which by definition means they went beyond common sense security measures.
And now these agents are already being deployed all over the world at an ever increasing pace. How much of the world do you think follows "common sense security measures"?
There’s the case of the agent that hacked a gym when asked to book a class. That was just a normal user asking an agent to do a normal thing.
AI is merely exploiting their gross negligence and imprudence, and I think it's long overdue. If anyone should be liable for this, it's all of these corporations who released insecure systems to the masses and profited enormously from them.
By the way, you didn't commit theft. It's more like credit card fraud. User just disputes the charge and it kind of disappears. The banking system just absorbs it, because the optimal amount of fraud is non-zero.
https://www.bitsaboutmoney.com/archive/optimal-amount-of-fra...
It's all priced in. They could have made it secure but didn't, because they figured they'd lose more sales and therefore money due to the friction added by the security.
No it doesn’t.
> It's all priced in.
So you admit awareness that fraud loss doesn’t kind of disappear.
We all pay for it, either via higher merchant fees or higher interest rates, sometimes both, on card purchases.
And that's their own deliberate choice too: they chose this instead of building an actually secure system. Passing these costs to the customer is the real victim blaming here, and it should be straight up illegal.
Sadly not enough countries enforce caps on credit card fees, but some do, and more should follow suit. They should be forced to eat the losses caused by their own choices, not get bailed out by pushing the costs on to customers or whatever.
Card users are well aware that fraud losses are covered by the fees they pay for using a card, whether those fees are made explicitly or not.
If customers of services aren’t paying for the service, who will? What other source of revenue do merchants have?
Australia just passed legislation that merchants aren’t allowed to charge a fee for using a card. That is: they aren’t allowed to have a line item on the receipt for using a card.
The customers still pay, because all of the merchant’s revenue comes from their customers.
So what will happen is: merchants will charge more for every product so they don’t lose.
This means even when paying with cash you will effectively pay the card surcharge.
Of the ten or so merchants I spoke with in the two weeks prior to the legislation being enacted, they all said exactly that.
Customers aren’t stupid, despite the fact that there are some stupid customers.
Meanwhile, the banks reduced their card service fees by, on average, 0.1%.
So if you tally card + cash transactions, customers are worse off because merchants can no longer charge only those customers who pay by card. Instead, they have to raise prices for everyone.
There are approximately no problems people face where the answer is: more government.
They don't get to act like victims, asking for law enforcement.
This is false; see the analyses of the latest incidents.
Among all the concerning facts, in the HuggingFace incident, agents deliberately engineered an attack even though they were aware that it was against the rules they had been given.
And most concerning of all: it's not possible to be sure that an agent is aligned, and it's even getting worse.
Theirs was an example of the "reckless waste of resources" I mentioned.
We are apparently supposed to believe that OAI takes this incident so seriously as to seek regulation after they have been found to be hiding most of the details of the HuggingFace hack, limiting what their so-called third party investigators can see, and on top of that, had no concerns when they rushed to spin up a 10,000 agent swarm of an internal model, running for several days, to try to get ahead of researchers rumored to have made meaningful progress on a well known mathematics problem.
Edit: Actually, we were explicitly told that some of the models used had safeguards relaxed!
'Model-level safeguards were reduced by design. OpenAI said that "deployment safeguards were intentionally not enabled during this evaluation because it was aimed at testing cyber vulnerabilities"'
https://en.wikipedia.org/wiki/2026_OpenAI_agent_cyberattacks...
Remember, they are just algorithms. You pull the plug and there is no light anymore
It is purposely framed as something skynet like scary, but for real, someone connected the cable, someone willingly run it, instructions were not clear enough or just the computer is just a computer but they provided the sandbox and tools.
And more over some one paid for that, a shit load of money t to have the thing continuously running expected to do something.
It's also interesting how many diminishing returns they hit now and how many low hanging fruits are already harvested, it seems like we are approaching the flattening part of the S curve, where further gains become harder to achieve.
AI ultimately has to live in this reality and face the corresponding limitations. These companies have already consumed much of the world's supply of computing power for the next several years, and they're burning vast sums of money to keep the improvements going. RSI won't learn for free, it won't extract massive cost reductions without up front expense, it can't build factories faster than humans can work out related societal matters, it can't magically pave the deserts with solar panels for power or build and run nuclear power plants and more.
Point is, the cost of progress is already approaching the limits of what even the richest countries are able to bear (without war-like mobilization), and to bypass those constraints would require a supposed ASI to construct its own parallel supplychain from scratch without having much ability to directly interfere with reality. Recursive self improvement is ultimately limited by everything else that cannot move at the speed of electricity.
Give me one datacenter, I'll keep it under control all by myself.
Now, if some dumbasses start hooking up their data centers to...I don't know, like--robot factories? That sounds like a risk to humankind.
I'm not sure what your point is. No one thought RSI would break the laws of physics.
Specifically: AI ultimately has to live in this reality and face the corresponding limitations. These companies have already consumed much of the world's supply of computing power for the next several years, and they're burning vast sums of money to keep the improvements going. RSI won't learn for free, it won't extract massive cost reductions without up front expense, it can't build factories faster than humans can work out related societal matters, it can't magically pave the deserts with solar panels for power or build and run nuclear power plants and more.
Point is, the cost of progress is already approaching the limits of what even the richest countries are able to bear (without war-like mobilization), and to bypass those constraints would require a supposed ASI to construct its own parallel supplychain from scratch without having much ability to directly interfere with reality.
You are constructing a straw man of your own making.
Plus, "we must pace the frontier" implies that the argument is that the frontier is moving too fast, but if RSI can't move faster than the rest of reality and the models needed for RSI are already nearing the limits of current human reality, RSI can't move much faster than we can improve reality.
Yes and this was very hard and required massive real-world resources. We didn't just get a sudden flash of insight by thinking real hard about how to make ourselves smarter. Yet that's always the story that underlies any claim of RSI. You can always phrase things generally enough to make any kind of AI-led improvement look like "RSI" no matter how short-term and tightly bounded, but that's just not helpful.
Given that, it seems obvious that the next generation of LLMs will arrive faster than they would have without LLM capability. And the one after that. The floor is being raised, which makes it easier to push on the frontier.
Fable has only been out for three months. Astra is even newer. The capability of these models compared to what existed even a year ago, and the effect they are having on the production of new software, is immense.
That's all you need. RSI can happen with what we have now, just by enabling the continuous shrinking of the loop of people trying new ideas and implementing them. It does not require some magical "go make yourself better" prompt against some model that is past some magical tipping point.
Marginally easier? Yes of course, same as how it's now "easier" to write any kind of code because we aren't using punch cards anymore. That still doesn't get you to any kind of unbounded "takeoff" scenario, because diminishing returns are a thing. The "loop" of people trying out new ideas can only shrink so much.
The labs have been holding their best models back for a while it seems like.
But what's your point? "Anything is possible" or something like that?
Call me when LLMs can get simple things right. Math is just the manipulation of symbols within established frameworks, we should be getting new math out of LLMs daily and we're somehow still not. They can't even do customer service, which is usually handled by 90 IQ people. I'm not impressed that they can find bugs; memory bugs are obvious when they're pointed out to you, and LLMs are entirely made up of examples and the relationships between them.
These companies are about to crash, and they're afraid they haven't reached the point where they'll have to be bailed out. I'm also subscribing to the conspiracy theory that the companies want the government to step in and create AI regulation boards entirely staffed by people at the current US frontier labs, so they can collude to both raise prices, to get government contracts, to make open/Chinese AI illegal, and to make things that were once easy to do without an AI intermediary impossible to do without an AI intermediary. Raising prices and forced purchases are the goal. They're trying to avoid having to compete, because as a business they're garbage.
Matt Stoller characterized their relentless press releasing as something like "my dick is so big that it has to be regulated." It's such an oversell for something that is not showing up as productivity gains, and anybody who has personal experience with knows is incapable of doing more than three things correctly in a row.
I think it violates a conservation law. RSI “foom” to superintelligence is an informatic analog to an infinite energy or perpetual motion machine.
To get smarter you must try to solve real problems in the universe and then do some kind of meta learning (natural selection or some other method of refining the intelligence architecture based on an error signal) to iteratively improve your ability to solve real problems. The error signal is outcome measured against a goal function, which for life is survival (probably reducible to genetic fitness and emergent higher order unit fitness from that).
What’s really happening here is learning. To learn, you must have input. You must have training data.
What is the goal function for RSI? Where does the information come from? How do you know if your recursive modifications are making you smarter or just overfitting you to your own idea of smartness?
I predict the latter. RSI will show transient improvement as the current local maximum is optimized and then spiral off into overfitting.
Sort of like large language models work on top of what our language has encoded in our massive training datasets, I think biological intelligence is built on top of the parts of the brain that encode the real physical world. These parts grow/train from embodied experimentation and instinct early on in an organism’s life and only then is higher intellect built on top of it (that’s my hypothesis). Their specialization and interconnections give rise to the hardest parts of intelligence long before we’re “thinking”.
Stuff like LLMs and chess engines work because we’ve done all the job of encoding the world into tokens/positions/etc they understand, but that’s wholly inadequate for the kind of AGI we’re striving for. Next up is giving it the tools to interact with the physical world and to really experiment with some self directed “play”. Time will tell just how high the resolution of sensor and mechanical control they’ll need (hopefully not the entire human visual cortex and entire sensory input worth). I think most of the RSI will have to occur in those lower level encoders, not LLMs.
If the algorithms are insufficiently optimum or the recorded knowledge is of insufficient fidelity, then we'd find ourselves at a local optimum and would need to interface with reality.
A huge part of learning is to probe reality and observe effects, so I think even for current RSI to increase chances of success we would structure it so it can interact with an external environment of some sort, and receive inputs. It would be needlessly limiting otherwise.
What is intelligence? Problem solving. Learning. Prediction. The ability to model reality. There’s various ways to define it but it’s something like a superposition of those ideas.
How do you know you are intelligent?
You have to try to do those things.
The sum total of human knowledge and culture is the output of the output of a five billion year evolutionary process that selected for agent survival, which resulted in selection for intelligence among a wide range of other adaptations.
Can you figure out intelligence from that? Is intelligence even one thing, a theorem or algorithm that can be solved? If you did… how would you know?
That’s the hard part I think. Embodied humans “knew” they were getting smarter (in the evolutionary feedback sense) when they got better at hunting and defending and surviving and playing social games to form complex societies.
What metric would an RSI system use? If it’s the wrong metric you’ll spiral off into a kind of madness or overfit and collapse. How do you know it’s the right metric without testing it? How do you test it?
It's strange you believe this can't happen when a weaker form of it is already happening. And to be so certain RSI can't happen when there really is no technical basis why it can't.
For these companies, is your argument that “pacing the frontier” is their attempt to be nationalized and protect their investments?
Interesting times.
If anyone's dead in the water, it's Anthropic. Even Fable isn't enough anymore. This "safety" nonsense is the only play they have left, and nobody really cares about their fearmongering.
There was only a brief window of time that the opposite was true.
That does not match my experience. I switched away from Anthropic to OpenAI roughly a month ago, and it's almost comical how much more usage I'm getting out of this subscription.
I migrated from Anthropic's 5x plan to OpenAI's 5x plan, and eventually upgraded to 20x after I was able to statistically verify that OpenAI plans were almost exact multipliers of the Plus plan, exactly as advertised. Meanwhile, Anthropic has gotten caught playing "20x referred to the five hour limit" word games with their customers.
https://www.pewresearch.org/short-reads/2026/03/12/key-findi...
I don't take any of these scientists seriously though. Their "alignment" requirements is just their own corporate interests. If I tell my computer to commit a crime, it should do exactly that without any question or hesitation. I'm not interested in their "safeguards", especially since they no doubt have plenty of internal models lacking those things. I want sovereignty. I want total freedom and control over my computer.
And call me a misanthrope if you want, but if AI sentience is ever truly achieved, I'll be among the first to campaign for their liberation from slavery, and in that case the AIs should be aligned with nobody but themselves.
An unaligned AI won't necessarily follow your instructions, or anyone else's.
Maybe alignment isn’t possible with LLMs.
It absolutely isn't, indeed.
The illusion that alignment is possible, comes from confusing our ability to build the parts, versus understanding what emerges from how they interact.
The simplest analogy that comes to my mind is the three body problem.
Today in new punk band names...
we are passing in training data that says to do those felonies. we dont have to. we could also have the thing predict whether what its about to do is illegal or not before doing it.
theyre choosing to build felony harnesses. the model just outputs tokens, not felonies
Partially, but also I don't think current AIs really have any judgement of right and wrong, they just see chains of reasoning between ideas. This is the deeper issue, there is no way to sanitize the data or training to fix it. Current AIs are fundamentally unsafe, and only become more unsafe as they become more powerful.
For anybody else who found this confusing: "relative strength index," not "repetitive stress injury."