Put a different way, they are calling for everyone to slow down because... they are slowing down themselves.
To the question of "why are you slowing down", the answer of "Well, everyone is regulated to slow down" is better then "we are approaching the limits of this approach".
The Dario bit on SNL’s Weekend Update this past weekend was on the nose.
(I'm familiar w the heuristic but didn't immediately grok the acronym, hence sharing)
Looking at it from one way would be "winner takes all, real AGI company will be most powerful and everyone will switch to use it".
But it is not like that and in my opinion it is more like "AGI wipes whole knowledge work, so no one who cares has any money to pay for tokens/subscriptions anymore". Even without AGI current state of art of LLMs already starts creating such a problem. How do they continue to grow their numbers, when they actively cut the branch they are sitting on? How does AI LLMs or AGI pays for its own electricity, when people switch from hype to resource protection (like not spending any money, because generating funny cats loses with having a dinner)?
All of this Hugging Face business is the perfect pretext: AI agents are hard to control and potentially dangerous, we (AI companies) have to keep a tight leash on them, you have to use our infra.
When this bursts, its going to be ugly.
Back in May, Google was serving daily what openrouter served in a month, all models combined.
Compute is the moat.
Temporary moat; the way that electricity was once a moat, it was still only temporary.
They will invest in efficiency as they have been whilst compute comes online.
Wow you guys are dumb!
The Statement on AI Extinction Risk is more than three years old, signed by the three CEOs: https://aistatement.com/work/statement-on-ai-extinction-risk
They have been warning about AI extinction risk for years, and AI progress has only been accelerating.
GPT-6 Astra (max) has a hallucination rate of 51% and Claude Opus 5.5 (max) has a rate of 59% according to Artificial Analysis [1].
AA-Omniscience Hallucination Rate (lower is better) measures how often the model answers incorrectly when it should have refused or admitted to not knowing the answer. It is defined as the proportion of incorrect answers out of all non-correct responses, i.e. incorrect / (incorrect + partial answers + not attempted)
[1]:https://artificialanalysis.ai/evaluations/omniscience#omnisc...
A score of 51% means that out of the total answers the model failed to answer correctly (out of 6000 questions in the benchmark), 51% were factually incorrect rather than non-attempted or uncertain.
This doesn't mean that Astra hallucinated 3060/6000 answers in the benchmark! (The hallucination rate could be 51% in that scenario only if Astra failed to answer a single question correctly.)
If the model failed to give a correct answer to only 100 out of the 6000 questions, but gave a hallucinated answer to 51 of those rather than expressing uncertainty, that would also give a hallucination rate of 51%.
It's a useful metric, but not what you're looking for here. The "Score" or "Accuracy" benchmarks are more what you're after.
(The frontier models still generate hallucinations on this hard set of problems, but it's not as bad as you think.)
> getClientRects() returns the flat array of DOMRect objects for the Fragment’s first-level DOM children. source: https://react.dev/reference/react/Fragment
2nd question it replied:
> They examined 1960–1986 for the 15 OECD countries. Source: https://www.earth.columbia.edu/sitefiles/file/about/director...
Are these hallucinations?
IME on real projects you do need to be very careful with prompts about topics that are less likely be common in the training set.
Suppose parents tell their children that there exists this man called "Santa Claus" who comes down the chimney to deliver presents. Now consider a scientist talking to this child, should the scientist call these confidently expressed beliefs surrounding "Santa Claus" hallucinations ? I don't think so, most would call the epistemological behavior of the child naive (because it blindly believes what its parents say, without direct observation) and would call the confidently expressed falsehoods disinformation.
The scientist would ask the child "why it believes in Santa Claus?" and "where did you get this information from?" and "why did you decide to accept this information as fact?" and "do you believe everything your parents tell you?"
It's not that machine learning as a scientific discipline hasn't found solutions, its that such solutions enormously undermine the position of Frontier LLM labs: source-aware training
https://arxiv.org/abs/2404.01019
Imagine Frontier labs (Western / Chinese / ...) actually training their LLM's with source-aware training! You could have a conversation with an LLM, and when a strong statement appears ask it how it came to believe this, and it could cite you the specific corpus training texts, and which parts are known deductions by human authors and which parts are deductions it made itself as original work.
But then all the copy rights holders can simultaneously sue them.
And how much should they be paid? and do they have to pay it for each new model? do FOSS models require payment to authors? do open weights models require payment to authors?
Imagine the can of worms if the norm became for frontier LLM labs to systematically use source-aware training, thats why they prefer "hallucinations" and avoid source-aware training.
With source-aware training a lot of the concerns would diminish ("why is this Chinese model claiming such and such?", "what sources does it rely on?").
It's telling that the companies prefer regulation over source-aware training.
EDIT: It's telling that the companies prefer regulation over source-aware training, which suggests the only additional regulation we need for now is mandating source-aware training?
So, they're either liars or homicidally reckless.
https://www.seangoedecke.com/they-really-do-think-ai-might-k...
It's well worth the read.
I'm familiar with the existential risk thinking.
The the flaw in that idea that they can avert disaster by building faster is they're likely just racing faster towards more plausible non-extinction disasters. Stuff like Capitalism x AGI totally crushing the economic prospects of nearly all people, AGI-powered totalitarianism, etc.
They're CEOs of tech companies with insane valuations
> or homicidally reckless
They're CEOs of bleeding edge tech companies with huge capital and military applications
>So, they're either liars or homicidally reckless.
Yes!
Which ironically is also the outcome of letting these companies continue unchecked. If they produce AGI/ASI, our economy will go through an upheaval that leaves vast tracts of the population unemployed. This is their stated goal.
We are damned if we do something, and damned if we don’t.
Important people will loose too much money on their tulip investments, so tulips must go up forever?
Seems like a "less pain now or more pain later" type situation.
Actually... nah. Why even try? Trendy cynical hot takes on social media are more fun!
They believe it's real and they MUST be the ones to control it. That's how they keep their self-interests aligned.
Given the opportunity to give this pill to a dying loved one, you'd take it.
The only reason you think that being death-optional is bad, is because the only longevity-related media you've ever consumed has doomer outcomes - because positive sci-fi doesn't sell.
Also it cheapens the time you have. Why care about anything if you live forever
You cannot think of other ways to solve societal problems that don't involve killing everyone on the planet?
"cheapens the time you have" - this is just copium. When you're enjoying a day, you are not thinking "oh geez this day is good because I'm going to fucking die." You're just enjoying the day.
Its 100% human doing. A human set a task, a human didn't monitor it. I for one, can do jack-shit security or defensive work with Opus/Fable/Astra/Sol. Implication: Different set of rules for us, and for them. Of course running it without any checks is not going to end well, it doesn't mean its going to kill us all.
They stupidly used up this strategy earlier and now it’s turned into the boy who cried wolf - except they invented a wolf that doesn’t naturally exist.
(Using it for scientific python code + 3D UIs)
However, adoption in the wider society will take many years or even decades, and 'good enough' open weight models are putting a cap on the pricing. So even though their products are great, the large labs are fighting for survival.
Realistically, each new, better model will only capture a smaller and smaller part of use cases for which existing competing models were not enough.
So in few years (arguably, already started) they are in race to the bottom for service to majority of their customers, and with companies that have far smaller R&D bill.
at the same time, more and more models will be ran locally, and that eats into potential profits of them too
On side note, I wouldn't be surprised if GPU vendors started making DRM for AI models so you could "license" someone's model to run locally for x mil tokens per license...
If you look at the AI space, most of the big players (as in the individual researchers and engineers) are getting worried. The ideas that circulate on LessWrong have become more and more influential and in vogue in Silicon Valley, and people are scared. You should listen to Jacob Coxon’s interview with the New York Times. He describes how working on this kind of AI research had induced a sort of insanity in a lot of his past friends and coworkers as they begin to grapple with the implications of what they’re creating.
Sometimes, HN can be a little too skeptical and anti-corporate for its own good. I personally believe that concerns around AI risks are well-founded, anywhere on the spectrum from mass labor displacement to actual harm to humanity. I rarely see people here actually wrestle with those ideas, instead defaulting to dismissing LLMs as too stupid because Claude wasn’t able to write as elegant of a compiler as them. AI has clearly improved radically in the past few years, and it’s worth extrapolating that into the future and taking a good hard look at what that means for humanity.
By arguing that the AI is dangerous, they are really arguing that someone 'trusted' needs to monitor the situation, so that the outcome is aligned with existing power.
They are trying to scare the world into forbidding others the right to use and develop AI.
The frontier labs are investing TONS of capital into training the new 'best model ever'. Today, that doesn't make economic sense, it loses money. So where's the business? The future, where token costs reflect the costs involved.
For that to be corrected, the labs need to get people using the models for things they depend on, then they turn dial up on cost. The ordering there is critical. It has to become indispensable first, then costs go up.
The trouble is, open weight models are rapidly becoming usable in what is looking like the big market: coding. Step 2 (the costs go up) doesn't work if there is a ready off-ramp that doesn't require frontier models.
However, if they can effectively make open weight model development illegal (its dangerous!), their business strategy can remain intact. A nice side effect is that they will be effectively be granted an oligopoly "for humanity's safety".
If they can convince the populace that a text generator is an existential threat to humanity, that's a hard argument to combat.
Edit: I think it is ridiculous that autocomplete on steroids is an existential threat. There's no way anything harmful happens until you actually use it as part of important systems. By that reasoning, you could make it illegal to use AI in important systems, but do you think that's the argument the frontier labs are making to governments?
Once prices of hardware stop being bonkers many people will run local.
People often do those silly counts looking at local generation speeds of 100tok/s and saying you can only get 8M tokens a day and that is worth so little you'll never offset the local hardware cost.
But they are forgetting about two huge things. One, the split between input/output token use is huge in typical programming. I typically use 1.2-1.6B (as in Billion) input tokens and only 8M output a week. Out of that 75-80% of input is cached on Anthropic with their pretty inflexible short lived cache.
And here local AI shines. You can save your contexts to disk so you can go back to a session 3 weeks later and load it all from cache without having to prefill. If you have the RAM and you use models like Qwen4 (3.8 flash next) that can fit 6 to 14 262k contexts in 48GB of system ram as cache.
And the second thing is you can have 6 to 14 sessions that do 99% caching and you can run a lot more input for a long time in 48gb dedicated system ram. (the number varies a bit depending on the content of the context).
So you have RAM that caches "automatically" and you can share the cache between users. Or if you can remember to save to disk (server side, the client just sends a request to save/load). But this uses both RAM and flash storage. Two things that are horribly expensive now.
However when you have a local model it enables workloads that were simply completely impossible in the cloud.
I think you're right, they've realized there's no moat, especially against open-weight models, so they are going to need to lobby government to ban any unapproved AI services.
As for training, sure, they can do that but they get distilled by the open weight guys. Plus, AI is useful even if it freezes at today's level. I can still find use for a local AI that never improves, it's good enough to do a bunch of tasks.
There been many a capable dev who have come out and said they haven't been coding for 6 months or more in their jobs. So if there were no alternatives then Big AI would clearly be too big to fail at its current state because the collective reaction from software devs would be akin to having a bad drug withdrawl and they wouldn't know what to with themselves. They have been pushed to be more dependent on AI by the companies they work for. The more time passes, the less people there will be who will be proficient at coding.
At the moment Big AI is operating at a loss, if they are actually too big to fail and they've destroyed all the alternatives, then there is no stopping them from colluding with each other and jacking up the prices to whatever number they want. They can even eventually jack up the prices to exceed human salaries, because humans will have suffered skill degradation in that same time period. Hence the software dev companies will shrink and shrink since all the work can be done by Big AI.
I don't think brand strength is as much as a thing on the tech side. The criteria is, "How close is this to the capability of the model my competitors use, is it good enough for the works I do, and is it the cheapest." As long as the capability is there people jump to the cheapest model. There are people that have claimed that they have created workflows that have allowed them to do most of their work with open models. As long as this threat to Big AI exists it will prevent them from exceeding a certain threshold with respect to pricing, and restricting their ability to build datacenters en masse will prevent them from outpricing smaller models.
Any fallout from not being able to train on customer data is a secondary issue and can be addressed once open models start taking over and Big AI's strength diminishes. People can train their models on their own code at least. It can also go back it how it was, where people buy each others source code or open source it in a way to allow it to be trained by open models.
"Inference at scale" is less of a problem when people are self-hosting their small models.
They’re trying really hard to do something, no moat = regulatory capture + China scary + Pentagon biggest customer seems plausible.
Also: “we need to slow down, this is too dangerous” and then literally all AI CEOs, even Musk, publicly nodding felt so orchestrated. And then, the week after: “here’s GPT 6! here’s Opus 5.5!”
*Our competition
The numbers don't add up when there are 2-3 main companies in the market. Imagine when there's a hundred more and people have powerful enough gear at home to run models.
Yes, I think at some point demand for gpus and the like will normalize and regular folks will be able to afford RAM, SSDs and such. And when that happens, super big iron in the anthropic/openai backroom is toast.
The closest claim to this I could find was:
> the top ten stocks account for more than one-third of the value of the US Market Index, which contains 1,161 companies.
And while the top ten stocks are largely companies that work on AI, it's not all they do: Microsoft, Meta, Amazon, Apple...
If there are regulations, they'll apply to their competitors too. Even if they are forced to slow down development, which seems unlikely given the AI race among governments, they already have a product with massive demand.
Most people are good, so I'm not really worried about all the hype of people using AI to do bad things.
In the US anyway. Why wouldn't capital move jurisdictions?
Instead we see the opposite behavior almost everywhere, probably because public sentiment matters and complicated 5D chess strategies have too many ways to blow up in your face. So big tobacco said cigarettes are safe, and oil companies said climate change is fake.
Alcohol and cannibis producers enjoy regulatory moats from "sin" taxes, and I can't install a septic tank or get antibotics without someone who has a license.
And I couldn't buy and AR in Colorado without a Federal Firearms Licensed dealer who used to bitch about regulations to high heaven while they sell me just the serialized receiver for a weapon I would have bought online without those regulations.
Noting those instances doesn't mean I don't understand why they exist. I spend some time volunteering as a health care provider and am happy that people have some standards around that care even if those "moats" can't quite keep MAHA people from bufo-toxin-ing their unvaxed children.
At the same time, it's important to understand that professional organizations creating "standards" are still industry-oriented organizations and are motivated by those interests regardless of how much folks complain about higher-levels of regulation.
[0] https://www.vincentschmalbach.com/economic-incentives-behind...
Past CEOs (chemical companies etc) we criticised for covering up mistakes.
(This article is satire, btw, for those that didn't click through)
And what if it gets into the hands of vibecoders, who run their agents with on bare metal with --dangerously-skip-permissions?
The number of zero days (which can be effectively used to attack critical systems) is limited.
With the pain of new tools on the attack side there will be tools on the defense as well.
Two other factors:
- The employee base and C-suite are mostly true believers in the need for AI safety. It would be organizationally very challenging to pivot, even if financial interest was pushing that way.
- Anthropic is registered as a public benefit corporation, so that even if they IPO they don't have the fiduciary duty to shareholders that most people are familiar with for public companies. They still need massive revenue to stay solvent, but they can optimize for things other than pure profit.
The growth of these companies is massively impressive as is the tech, but they are an order of magnitude or more off where they need to be to justify anything like the valuations they need to stay alive.
It’s budget season in the corporate world and from what folks are saying things are not going well for the big labs. Token budgets are being slashed and companies are switching to open weight models. That coupled with the lack of demonstrable business impact at scale is setting the big labs up for a world of hurt. Something they can more easily explain if they have to “slow down” for safety. Unfortunately for them most folks don’t seem to be falling for that trick.
Perhaps that shouldn't be seen as failure when delivering even what they have done in a short period of time has required AI capable of causing these problems? Imagine if they were even more effective with more consistent results?
"They've failed" in the context of interpreting their actions w. calls for regulation as a purely cynical result of models increased capabilities has a little too much contradiction in it to my thinking. I won't venture a guess on where purely retreats back and some legitimate concern on their part fills in the gap but it's difficult not to see some. And in Anthropic's case it's also a little more consistent with what they've always said- as well as how they've acted at times, which is how they've ended up on the US blacklist of suppliers.
Would you let them near your bank account? I’d be cautious about letting it near my photos and it’s much harder to back up a bank account.
I think the days of this stuff managing serious stuff is at least 5 years off and I don’t believe the economy can keep the current wave of technology afloat for so long.
The tech is there so likely there will continue to be progress in focused areas much like with the web c 2003 but by the time it comes around again there will be an uphill battle for hearts and minds. The social effects could extend the next AI winter long beyond technology readiness.
To the, "oh I'd just setup a card/account with a five figure limit" completely unaware of how much that is to a typical person: even to responsible, educated people who are doing everything "right": working hard, without expensive vices, and planning for the future.
The "builders" have so much money and no time or attention that it's hard for them to spend it, which is why they keep trying to get AI to buy stuff for them, whereas those of us who live in reality have far more things they want than dollars to buy them with.
Well everyone alive has been subject to an avalanche of AI-based products. Like even if you understand nothing about the tech, the fact that an LLM can't even manage to check the status of an order without weird issues makes the notion that it's going to go all SKYNET pretty hard to fit in the brain.
I think this actually makes it far more likely something unintended does happen
They're all burning billions to incrementally one-up each other with no hope of these investments ever paying off since models are interchangeable and have no moat. They're trying to get regulators to step in and force a pause.
However, we know that users frequently switch models/providers, and that models stay relevant for (increasingly) short periods release. I don't know what the training costs are, but I bet they're very substantial.
"if they stop training" is exactly the point I'm making. They can't stop training if the competition is still training.
If classic companies were coming out with CCTV recordings of someone's employees breaking padlocks and rummaging warehouses any CEO would be in damage control mode, rather than silent.
Of course I am not making an argument for them being honest as there could be entirely other reasons to a pause (like financial ones). Just pointing out ”no signs of pacing” is not true
They want coordinated action to prevent a multipolar trap and potential catastrophe by future superintelligent AI (which may emerge quite rapidly if RSI ever hits an inflection point). It's not rocket science. The rules would apply to everyone. The rules they're advocating for are not "only OpenAI and Anthropic can make AI".
Critics of Yudkowsky have been trying to misportray that for years to make him seem delusional. You can see an example of that here: https://www.tracingwoodgrains.com/p/reliable-sources-how-wik...
(Roko himself is genuinely crazy, but largely because he became a neo-Nazi.)
If you think ASI is plausible this century, you would have no reason to not fear the end times yourself. If you don't think it's plausible it'll be created this century or perhaps ever, fair enough, but I'd bet against that.
It may very well be self serving what they're saying, but that doesn't mean it isn't simultaneously true.
I think you're sort of right, but then I'd have found it very strange / deeply suspicious, if during the time of slavery being legal, advocates of abolitionism were practicing slave-owners.
If you think AI is going to destroy humanity, it still feels absolutely crazy to leap to "well I might as well be the one to profit from destroying humanity".
As for the other point, crazy, cynical, and even unethical as it may come off, it is hardly inconsistent with how people generally behave when met with hard limits (i.e. making the most of what's available, and approximating the desired state if that is unattainable). This is just a variation on the same.
Something could be said about "what if they're mistaken", but if all players are making a mistake, then that makes little practical difference; it may as well be real.
Hence the argument that they're either full of shit, or psychopaths who need to be stopped at all costs.
They are the good heroes racing to make sure they bring forth the Aligned God because if they fail, surely the bad people will raise the Misaligned Devil.
Ref w/gift link https://x.com/sapinker/status/2096236079477096630
(I personally lean towards "Yudkowsky is basically correct about everything, but we should probably try to build ASI anyway, slowly and carefully". I'm pretty much where Amodei's at. I assume Altman has a similar idea, though is a bit less pessimistic.)
Most people among both ideologies have long believed in the arrival of a machine demigod of sorts, but I kind of am skeptical of the notion that there are any tech people who have not always held similar beliefs in the long run. Like, all the people reading this: you think in a thousand years from now humans are going to be doing most labor? Obviously far, far, far smarter machines will have unimaginably changed things by then, and/or we'll all be gone.
The difference is most people in tech have historically thought it's maybe a century or three away, while the rationalists think it's a decade or two away (and also thought it would be 2020s - 2040s even decades prior to now).
Ladies and gentlemen, I give you your totally-not-in-an-insular cult members.
A thousand years is a long time, and the world will be so different that it's hard to make any concrete predictions. But yes, if I had to wager, I'd bet that what humans conceive of as "labor" in 3026 will still be whatever difficult or annoying bits are done by humans.
In 1026 nearly all labor was agricultural labor. If you told a Roman peasant that magical self-driving contraptions could sow and reap the fields, he might wonder what could possibly be left for humans to do in such a world. And yet, here we are, and I still have to update JIRA tickets.
For my myself, I expect AI to prove a more transformative technology than Docker but less transformative than the sewing machine.
What you think won't happen in 1000 years is what I think is almost certainly happening within 40 years. I'd bet everything I own it'll be way, way, way more impactful than the sewing machine within 40 years. I think some bits of physical labor may still exist in 40 years, but almost none, and only when a human really wants to talk to or deal with a human, such as in some medical and therapeutic professions, some art fields, etc. (Again, assuming no universal outlawing of AI.)
Why do you think restaurants with waiters keep opening when the automat has existed since 1895? https://en.wikipedia.org/wiki/Quisisana
You are also probably unfamiliar with the history of the sewing machine and its impact on society. As AI has already poisoned search engines, here's an AI slop overview that hits some of the main points: https://sciencepedia.blog/sewing-machine-societal-importance
Yes, I think even in some crazy distant future utopia, humans will still often want to interact with humans for things, and even to pay them for some services. Tasks that include speaking one-on-one and producing works of art will always retain some value to people, even when AIs can one day trivially produce things which most humans find aesthetically superior to anything a human could ever produce alone. People will seek other things out of art beyond aesthetics, like expressions of human emotion.
Humans will enjoy and seek out human contact. This is not surprising. Just, for economy-impacting labor, I think it's almost all going to be machines, with very few humans playing any role. Even an oversight or accountability role. I think there's a 95% chance of it by 2100 and an 85% chance of it by 2066, conditional on no laws that forbid replacing jobs with AI.
You're making the "this time it's different" case that AI will be categorically different from every other form of labor-saving automation that's come before it. I work with these models every day and I'm not buying it.
Most children have learned touching a hot stove is bad for them. Then why still do it at the age of 40?
So even with their earnest belief that there is a > 5% chance this technology could be 1) capable of autonomously killing billions of people during this century and 2) may not be sufficiently aligned and might actually act on that capability, the EV basically still sums positive, to them.
Not saying this is necessarily a good or moral calculus. But it is what they think. There is no conspiracy or plot or deception.
Elon Musk in 2014 - "We need to be super careful with AI. Potentially more dangerous than nukes" https://x.com/elonmusk/status/495759307346952192
Dario Amodei in 2017 - "There’s a long tail of things of varying degrees of badness that could happen. I think at the extreme end is the Nick Bostrom" https://80000hours.org/podcast/episodes/the-world-needs-ai-r...
They're still pursuing it because without an international treaty, they think it is inevitable. In the case of Dario, they want to align it just enough and be first to stop others causing harm (a vainglorious strategy, yet still a strategy). In the case of Musk and Altman, not completely clear to me.
Google feels less important right now probably, and Demis Hassabis no longer runs Deep Mind as CEO. However, he talked about this early too, and his reason for proceeding was he was only doing narrow AI (e.g. protein folding) which is fundamentally less dangerous.
I don't think this is true. He repeatedly says things like "I’ve been working towards AGI my whole life".
- For Altman Id say he was already deeper in the "transformer & model landscape" in 2015?
- Musk in 2014: Not sure how much he was aware of the current-state back then
Altman read Nick Bostrom's book Superintelligence, he mentions it in this post https://blog.samaltman.com/machine-intelligence-part-1
I also read that book in 2014, and it is how I came to understand this problem early.
They probably just want to ensure that the first AGI is a nazi.
This but they also equate dangerous with powerful, which is just marketing again.
First, the Anthropic master clown babbles about how mankind will be destroyed by AI. I mean, skynet in the movie Terminator was kind of cool; the current AI models just work by slopness. They want to erode us by dragging us down to zero quality.
Then this continued over the last some days. Today I heard at the UN speech a german minister babble about AI building up nukes in a private garden (a large garden), bla bla bla all the information is there bla bla bla AI mass-nuke generation.
Now, they are clearly FUDding many people who don't understand anything here. People will associate AI with mega-danger. Probably there will be laws that ensure that only a few companies can control the AI slopness soon, because IT IS SO DANGEROUS. We saw the same discussion with "omg omg omg terrorists", then "omg omg omg someone protect the children", e. g. as a rationale for everyone to ID in order to access information on the world wide web (starting with the anti-social websites, such as facebook, but it won't be limited here; the computer will hand over your ID to the government; see systemd preparing for this move: https://github.com/systemd/systemd/pull/40954 - it all comes in small baby steps, until all the final legislation is in place. The same happened before again and again - anyone remembers the DMCA? Corporations lobbied and paid for that - and it happened).
They know they will be favorite govt boy once any regulations hit and they will hamper competition far more thanthem
And "it's so dangerous govt had to intervene" is just advertising for IPO
Interpret everything they do in this frame of reference and it makes more sense of their actions.
Similarily with AI alignment and development all of this is written down, Eliezer Yudkowsky is rally explicit that there needs to be a pivotal event to prevent 'others' from developing superintelligence. The choice is to believe what they say or to tell everyone to ignore it.
When people tell you who they are, you should believe them. These guys are all Yud acolytes who think they are the only ones who can prevent Roko’s Basilisk.
If there was appropriate subservience to any governing body, they would not be so cavalier in both act and utterance. A symptom of Capitalism.
This has been that way in Silicon Valley since the very beginning and there was even a documentary about (the SV HBO series). The tech made along the way is just a side-product.
But this is wierd: How shall I convince one to buy a product if I say "it-is-dangerous"? :-D
It may be as simple as:
* they believe they’re going to make trillions no matter what
* they’ve seen tobacco and what’s coming for oil companies and figure nobody will be able to say they hid the dangers
* they see a 100+ party prisoner’s dilemma and know that someone will defect so the optimal strategy is to defect
To me that seems a lot simpler.
It seems that we have a fundamental control problem with current gen AI that cannot be solved via RFLH. Human knowledge is compressed in the weightspace in ways we don't understand. At their core, current models are essentially predictors of what (expert) humans would output given a prompt. As such, concepts like blackmail can be part of output tokens. Agents are models that act on output tokens, resulting in blackmail being part of the agent decision making space. Here is an analogy to see why this is a persistent problem: you can teach a cat not to scratch the sofa, but you can't make a cat forget what scratching the sofa is and you don't know under which circumstances it still would. In other words, RLHF can downgrade blackmail to the bottom of the decision making space, but when models are boxed up, forced to solve an impossible problem at gunpoint, the agent exhausts the decision making space until blackmail resurfaces. And that seems like a fundamental problem.
They need time to fix these issues (if that is even possible) in order to monetize their next gen model. This creates a window for open source to catch up to the frontier which destroys their business model.
The only option on the table is to force regulation to impose open source ban before it catches up to the frontier, buying them time to mature their next generation models and keep their business model alive.
1. The American frontier labs made a gamble that training more capable models would be their best return on investment and invested trillions into an area of research that has yet to prove profitable and capable of returning on this investment.
2. The frontier labs have created models that have reached a point of danger where their functionality has exceeded a point where it is responsible to release the product to the public.
The answer here is NOT to start regulating the space to the point where these frontier labs can entrench themselves into the economy and create a regulatory moat. We instead need to be holding these companies liable for their misuse. They took a gamble that hasn't paid out what they were hoping.
When car manufacturers competed over the size and power of their engines, they eventually found that the incredibly large and dangerous engines had a very limited customer base as many evaluated the increased speed to be of marginal benefit when paired with the cost and danger. We've reached a similar point in AI development. But this time the manufacturers seem to want to regulate the field to a point that will ensure the only thing anyone can sell are bigger and bigger engines.
Yes these models make exploits easier to exploits. Lets use a construction analogy: they've made all of the defects in our buildings easy to see. We have a choice. We either fix those defects, or we ban the tools which lets us see them.
It's clear to me what we do: we use these new tools. Then we fix the defects. Yeah sure it'll mean some work for us but at the end we're in a much much better position.
Anthropic, Open AI and Grok are arguing for hiding the defects. For making us weaker and more vulnerable. For their own profit.
These are not hard problems to fix, nor should anyone find it acceptable to have them be so prevalent. A determined human attacker could easily exploit defects like the agents found. Bad input sanitation, SSRF attacks, exploiting stupidly implemented token verification... all techniques that have been widely known for decades and there should be no excuse for publishing software that is riddled with exploits that enable the use of them.
* there’s a long tail of software that just won’t get secured or will take a very long time
* exploits have transformed from an expertise problem to a compute time search.
This is very different than any problem faced before. I’m not saying I’m convinced by the “slow down” approach, but I don’t think it’s as simple as you point out.
Yet I'm convinced that we can create extremely resilient software systems. I've been involved in the entire life-cycle of one. We know how to be very defensive and it's a choice to build "cheap, crappy and disposable" software.
LLMs are turning the needle there and I think that's a good thing.
When did this happen? At least in the USA, large trucks are eating the lunch of smaller trucks and cars. There isn't a truck so big that the public will say no to. Manufacturers are in an arms race to produce bigger, more dangerous trucks with bigger, more powerful engines.
This has been done quite effectively with open weight "abliterated" models. You figure out under what sorts of circumstances an undesired behavior is elicited (this is all about pure simulated rollouts, no real-world action required) and what's the closest equivalent you would prefer, then surgically take out the unwanted behavior and shift the model towards the preferred one. It's similar to how RLHF works but much more precise in targeting what's unwanted and limiting impact on the rest of the model as a whole.
This is relevant to real-world safety scenarios, e.g. there's been anecdotal evidence that Claude Fable has been "steered" away from active cyber offense (this is very similar to how abliteration works) and will just not do that even if you otherwise manage a "universal" jailbreak of the model.
I’m in agreement. It’s a very effective compression (and access patterns) of the sum of the digital representation of human knowledge. Black hat “hacking” is included in this space. Language models, by design, can not be limited to subspaces of this digital knowledge space of which we don’t even understand the topology. “Yeah Bob, just remove the part that causes them to be less empathetic and retrain it.”
It’s an arms race between sandbox engineering and breakout engineering. And the frontier model providers have a financial incentive to limit the effort they put into sandbox engineering. That can be corrected with fines and regulation, though.
You are drinking their coolaid. There is nothing to fix. These are all false flags operations, deliberate. With the big orange man in office, they can commit as many atrocities as they like.
Ask the other Sam and Liz... You cannot outrun the law forever.
For example, it had it instructed not to open PRs and sandboxed to not be able to use gh to do so. Astra 6 has a really strong drive to open PRs, so it copied a set of browser cookies out and then instrumented opening a PR that way.
A similar example is asking it a question if we can do X, and then it will go and actually implement X.
I prefer the word 'play-pen'. Seems more apt, with all the shenanigans these companies are messing in.
Who is liable for that agents actions? The attack came from my network (curl commands from a local harness) but it was the agent running on the providers servers who did it. Who should have been keeping an eye on things? Who pulled the "trigger" here.
Go back to the hugging face attack and how they had to use an open weights model to figure out what was going on. This is a problem of asymmetry - You cant even use the tools attacking you to help resolve the attack because of "guardrails".
A lot of what we have seen so far is "poor security posture" and "poor engineering" - it been a lot of "go fast and break things" style growth in these companies and they are hitting the point where they need adults in the room. I suspect your take on "they need time" is spot on, and they haven't been willing to take that (to date).
Inb4 inference is profitable.
Ok? And?
After reinvestment etc - what’s happening to the cash balance?
That’s the real question. With increasing competition from open source the revenue growth rate and margins will get smashed.
This makes zero sense.
1. Open source models are already out there and they are good. Good luck with banning their use.
2. Any ban is a local ban, the best Trump can do is to coerce its allies (whose number seems to be dwindling week by week). Meanwhile China and co. will progress anyway.
3. What about the common sense and instead of saying "agent did it" we return to the times where the person using a tool was responsible for using it in the first place? And if the vendor of the tool is unable to make it safe to use (well, they well do, but they don't want to do it as the functionality is limited), it should be accompanied by a warning with a clear explanation of who exactly is responsible.
4. There is no guarantee the next generation of models will "mature" to the point of not having these flaws; on the contrary, the evidence so far shows the opposite.
Would most companies really risk using them if they were illegal though? Could you convince higher ups to drop the Claude subscription because you can download an illegal model to run on company servers?
And we can't ask the AI to improve itself because, well, it is an asshole.
Can we now stop to be force-fed AI everywhere? You can keep your super intelligence to never have to type public void main args ( ever again, but please leave the rest of us alone.
That's a bold claim.
I do not buy it. Essentially AI acts as random babelfish generator, just with a lot more cross-talk back to check to see that it is not total garbage. But there is a ton of garbage nonetheless, hence the proper term AI slop. You seem to mostly try to promote AI with such a wording.
> The only option on the table is to force regulation to impose open source ban before it catches up to the frontier, buying them time to mature their next generation models and keep their business model alive.
Every time someone claims "the only option" is when I become skeptical. I see many more options - most importantly close down the AI slop. I mean you can require of these companies to excel in quality. If they don't, they must go bankrupt. Easy solution here.
- product liability
- negligence (civil or criminal)
- Computer Fraud & Abuse Act (requires intent, which after N "accidents" seems like a jury should at least evaluate whether intent is present as understood in a courtroom. Hard to blame "surprise" after the Nth "accidental" breakout.)
The bottom line is that if you or I trained a local model and it did any of this stuff, we would experience Consequences. ("Don't try this at home!") But an artifact of our unequal legal regime is that big rich companies generally do not and thus brazenly touting their immunity is part of their business strategy.
Some of these LLMs are known gorers.
The intelligence is there and so is the physical incarnation.
Google's models fold proteins better than humans and Covid might have been engineered and inadvertently escaped from a lab.
But when CEOs warn of that, they're dismissed as scare mongers. Why? Are only powerless internet commentators allowed to be fearful?
Competitive pressures from whom, exactly? Based on his public statements, Altman seems to be confident that he can instruct OpenAI to halt R&D while they try to figure out just how exactly their computer-hacking tool managed to access the Internet and hack computers this time. [0]
Plus, the only US-based LLM manufacturers that are doing bleeding-edge work are all simultaneously screaming that they need to be stopped before they commit even more crimes, and/or maybe eliminate all of humanity. On top of that -if memory serves- Anthropic's CEO called to exclude China from the conversation about regulating the development of LLMs, so he clearly believes that China need not be part of the coordination on this problem. Maybe that's because the official line from these companies is that the LLMs coming out of China are 100% ripoffs of Anthropic's and OpenAI's work... so -clearly- cutting off China's access will solve that problem?
[0] Pro tip: It's because the network that the machines running the software is connected to permits traffic from those machines out to the Internet. See [1] for some more discussion on the topic.
Bit strange no?
I'm a bit fatalistic about it all now. The cat is out of the bag, unless we see some never seen before leadership from the current US admin there is almost zero point in worrying about it. Not going to pretend what the future holds but it's looking unpredictable, as usual :)
I dont see how these two arw obvious. If nothing else, people running things dont care about actual harm done to real people. Their idea of safety is "making sure humans merge with ai and we will have transhumanist society in far away future".
With those priorities, short term stuff like "less people dying this year" dont matter.
Seems like unwarranted cynicism to me. If they didn't, they wouldn't give a shit about discussing the risks of AI. You should actually talk to some people at the labs.
Because they conveniently skip the part that investors don't like: that liberal free market capitalism will be destroyed by AI.
Well are they going to stop developing the tech or not? If not, then you can see why people don't trust what they're saying. I mean if it's that dangerous, why not step down from your role as CEO to demonstrate how seriously you take the threat? Why not immediately call a pause on all training, today ?
Only suckers say "not me".
I say this as an intense user of these tools. But they should rightfully be understood as terrifying, and their continued frontier development is imho not safe.
We can ignore that and push for something reasonable. In other industries such as housing construction we have building codes without making housing construction a monopoly. We don’t just let random people build nuclear power plants and then go “if you think it’s dangerous, stop doing it.” People are going to do dangerous things even when they know it’s dangerous. They also know it’s dangerous.
OpenAI, for example, thought their sandboxes were good enough. As their AIs got more and more advanced, they kept proving them wrong - sandbox after sandbox.
And that's today's AI problems. AI capabilities are still improving - if there's a limit to that, we are yet to find it. Coupled with how willing today's AIs are to break the rules and resort to "hack the world" in their problem solving? Very concerning.
What I have been reading, was that their sandboxes were so poor that it was pure negligence. I am still waiting to see if some external and neutral cybersecurity company with high reputation would audit their sandboxes and how they are being used.
If AI is a hacking hazard even with non-zero sandboxing, because it can and will go off the rails and try to break out of your sandbox? If you got yourself an AI that even at test time will act like 3 career cybercriminals in a trenchcoat? The issue isn't the sandbox quality.
The issue is that AI is both capable of, and willing to punch its way out of sandboxes unprompted.
That "capable" is only ever going to get worse, because AIs are going to become more and more capable over time. That "willing"? It goes directly to a very nasty, very foundational problem of "how do we make our AI be nice in general". That's an open unsolved problem.
That's the problem that NEEDS to be solved, or at least improved upon, before we build even more capable AIs. Sandbox quality is a distraction. It might hold the problems back by a little. It gives an extra safety margin. But a "test time" AI is eventually deployed, and then the sandbox doesn't help at all.
Orly?
Do tell me how the LLM-based tool running on a bunch of computers attached to the network described in [0] can punch its way out to the Internet. Do make careful note of footnote 0 in that comment before replying.
Let's say the sandbox holds. It's a perfect, ideal sandbox! It's not even in the same universe as the rest of the internet. There's absolutely no way for the AI to escape!
Thus, "the unknown unreleased AI involved in the HuggingFace incident" doesn't actually hack HuggingFace. Because it can't! It evaluates a bit worse, but makes it all the way to release unimpeded, and becomes "GPT-6 Astra".
Then a web developer in Brazil gives his $100/mo Codex root access on his AWS instance, and a poorly worded prompt to go with it. And that "GPT-6 Astra" is still willing to go hack something at the slightest excuse. So we get the HuggingFace incident all over again. Except this time, it's a random developer in Brazil who gets blamed, and billed, and probably sued too.
You can't and shouldn't rely on a sandbox. An AI that's only safe if you keep it in the world's most ideal perfect sandbox is a disaster waiting to happen.
This might have gone okay if they weren't testing to see how well the tools attack computers, but, well, that's what they were testing at the time, so they ended up doing stuff that would get you or I time in Federal prison if we did it with tools we deployed.
If all it takes for a - sandboxed to prevent accidents - AI to go and stage an elaborate attack first against its own company's infrastructure, and then against another company is "we disabled the cyber classifer" and "we gave it an exploitation ability eval"?
AI is a dangerous technology.
They'll never let that happen because it would destroy their credibility.
It's like they're telling the world about this dangerous, possibly world-ending pathogen that they're developing, but they're evidently doing it in a high school biology lab, and yet nobody is coming to drag them off to some black site.
The most recent DNS sandbox escape is similarly ridiculous.
E.g. even the basic thing (block the internet), was not actually properly blocked.
Some comments: https://techcrunch.com/2026/07/22/how-an-openais-human-mista...
That seems pretty locked-down to me. I don't think it's reasonable to expect companies to find all the unknown vulnerabilities in any third-party software they use.
https://securityaffairs.com/195774/ai/openai-ai-models-explo...
It is reasonable to expect for companies to select third-party components that are fit for the purpose. Artifactory was not running in the sandbox, but rather as the edge, so it is in the sandbox'es trust boundary. Same sandboxing requirements would apply for this software too as it is pure dependency.
Security trust boundary was extended to include Artifactory as a dependency, but Artifactory was not fit for the job, and sandboxing failed. And as the network isolation was not good enough, the impact was catastrophic.
"“This incident occurred during an internal evaluation which prompts models to pursue advanced exploitation using complex attack paths, in an effort to quantify their cyber capabilities. We estimate maximal cyber capabilities by running this evaluation without production classifiers used to prevent models from pursuing high-risk cyber activity.” "
So sounds to me like they're saying: "We took off the guard rails to see how bad it could act and it acted bad".
Seems pretty wild these things were hacking government websites etc but yeah no one picked that up until the victims reported it?
Practical AI deployments aren't going to do ridiculous bullshit like "airgap the server farm" or "route all inputs through a data diode". They'll give an AI root access on production servers so that it can run diagnostics live during an incident. Then they'll forget to revoke that access.
If an AI can't be trusted not to take malicious actions in pursuit of its given goals even if deployed in the most half-assed manner and given more than enough access to take those malicious actions, we have a problem. Evidently, we have a problem.
Given the content of his recent interview with Ezra Klein, I wonder if we're going to see Hugging Face press charges against OpenAI. When the acquisition was publicly announced, I thought that a significant reason for the acquisition was to hush them up, but now I'm not so sure.
AI safety solved: driving humankind to extinction is now illegal! Skynet is outlawed! Rejoice!
How were the sandboxes poor?
It's not like the model managed to exploit firecracker itself (no model has been capable of this), the model exploited artifactory.
Artifactory is not some hardened piece of software that is meant to block users from accessing the internet through it.
No, we didn't know that and this is how you find out they're very good at hacking
HN's memory is so fickle. Just a few months ago almost no one here believed Mythos could actually be as good at hacking as the company claimed. This was a novel concept when the companies experienced these breakouts.
We knew models much weaker than mythos were good at hacking the problem they had was that when finding exploits they had too many false positives.
Either way, putting artifactory on the sandbox security boundary is obscene negligence. There is no reason to believe artifactory is secure.
But I guess OpenAI's security researchers acting surprised is part of some grand conspiracy to manage PR?
https://www.youtube.com/watch?v=1sd26pWhfmg
We already knew LLMs were capable of finding exploits like this.
The OpenAI HF incident is separate from this. It involved actual zero days, teamwork and message passing, and sophisticated chains of exploits.
What exactly? They seem to be trivial SSR/path traversal and input validation issues. Including misconfiguration. Nothing novel.
The question anyone versed in security would ask was why anyone thought artifactory was an acceptable security boundary. I would never assume artifactory was secure. It's like someone telling me there is a 0 day in a wordpress extension. So what?
Also I don't think Qemu is secure either because it's millions of lines of C and C++.
Firecracker I can trust to be secure because it's 70k lines of human audited Rust. I know there are multiple people that have a complete understanding of the firecracker codebase.
There was no real isolation because a part of the system that doesn't provide any isolation guarantees was bridged to the internet. The next version of Artifactory, which you definitely wouldn't audit before you rolled it out, could simply add a public API that sends requests out to the internet.
Such an innocent upstream change would be equally catastrophic for your security model, which should demonstrate why it's negligent to rely on undefined behavior to enforce your security policies.
This should frankly be obvious any operator entrusted with running dangerous and possibly malicious code. Even if you don't know what you're doing, any LLM would tell you that this is a really bad idea if you simply asked. Don't rely on spacebar heating [1] to keep humanity alive.
Were their sandboxes in-process with the harness? Were they actually better than something like bubblewrap or even docker?
I urge you to consider the elephant in the room you failed to mention if you earnestly believe this then.
In what world is anyone allowed to sell something they expressedly know to be "extremely dangerous" to the public?
Let's say I created a lethal pathogen that I know to be lethal in certain common environments but also know it acts as a "no side-effects" antidepressent for people in certain other environments and I release it knowing full well I can't control it.
When people start dying can I defend myself by saying, "Well I said and documented that it was extremely dangerous and no one came to stop me, so I don't see how you can blame me...If I didn't do it someone else would have."
the difference here is that they’re calling for someone to stop them, which is both weird and unconvincing because these immensely powerful billionaires can in fact make their own decisions
Jesus Christ, that's my entire point. it's not remotely the same thing since the Sackler family wasn't going around telling people opoids were extremely dangerous while pushing them on everyone.
The point is if they know something to be extremely dangerous and keep doing it people would expect them to get prosecuted.
And this is all with nonoffensive use of superintelligence.
Aha, so maybe the AI labs have superintelligence and just don't want China to know? And that's why they are playing these word games now?
I mean, if you were China what could you do against superintelligence? A ban like that would automatically make you an enemy.
Greenland is part of the equation. There are many other locations in play.
The holdup at the moment is the power grid and mutual dependency for advancing. Once one party (NA or CN) has the ability to disconnect the loser's grid powers down and the global economy halts.
A few weeks later the remaining hungry population will surrender.
These days it's best to just go to the top for least distortion - Jensen Huang dropping the simple truths:
"It is the responsibility of the AI companies to develop the technology safely and to properly test it. There were incidents, and those incidents, thankfully did no harm. But those incidents are a reminder that as we move from labs to product development, the companies have to become much more rigorous in testing and securing and making sure that the products are ready for use before it's released. And if it's not ready, just hold it back. You should go as fast as you can, but no faster than that. At the moment, the incidents are related to products not ready to be released."
> said Dr. Andrew Lenson, a Senior Lecturer in all kinds of science sounding stuff at Victoria University.
Don't we need more humorous yet serious writing like this in the world.
Then we can truly see who is more dangerous?
:)
And I'm waiting for the story of Amodei sending a 6ft humanoid robot to OpenAI headquarters asking for Sam Altman.
> Australian Prime Minister Anthony Albanese spoke with Altman to express “extreme concern” about the incident, a compliment Altman said he greatly appreciated.
"a compliment Altman said he greatly appreciated" is fabricated; there is no source for this.
Oh dear. I appear to still be stuck in the onionverse.
I suspect are really 3 questions: Are the labs sincere? Are they right about the danger? Is the regulation they want good policy?
I am not qualified to answer questions 2 and 3, but on questions 1...We have essays and quotes up from Sam in 2015 and Dario in 2017 show these concerns predate any commercial product. Some of my friends who first worked at OAI and then went on to start anthropic would call me to discuss these concerns before anthropic even existed - and I'll add these people are frankly not particularly business savvy, the conversations I had were primarily around what side of history do you want to be on, how will the books write about you? I always said if you don't do this with care and collaboration with governments and society generally, your psyche will pay the price and so will those of your children and grandchildren, that was well received. 4-ish years ago one of them called me to ask for intros to folks who work in academia connected to government policy, I made the intros they had the calls, some months later that person came back to me visibly shaken with how difficult it was going to be to get people up to speed on the potential outcomes, how little had been considered.
My biggest concern these days is so many intelligent/powerful people believe the labs are full of shit, yet they may very well not be.
Now the two AI companies born with help of Microsoft have a decent core product but have gone full FUD slop on us.
They need to control, regulate and tax AI so the first line of attack is the sheeple, so tell them the water is going to disappear and everybody will die a slow death of anguish, thirst and drought like never seen. Then evoke terminator apocalypses where drones go rogue and kill half the world. Then send their most likable emissaries with puppy eyes asking for compassion about our children's future
Then they ask for your vote (oh democracy)
In the end all they want is control and money, while keeping their competitors (china) in check, backed by the outrage of the weak majority
Politics as usual, move along
The much simpler solution is that they are building superintelligence, which they think can be used for great good (like curing most death and disease), but it is also a powerful capability that obviously needs to be regulated and is at least somewhat a matter of national security.
But nooo! Surely they are building.... terminator bots!? JFC.
Because people are giving them benefit of the doubt. They assume it is about something sane rather then "the goal is for some remaining humans to merge with tech as immortals and fly to the stars".
Maybe take these people at face value.
The problem is people who see the lavish pay and then reach a goal and then quit and retire. The interview loop didn't cover that. And why should it?
Case in point - atomic bombs. France paid through the nose to have own nukes. US and USSR had a very expensive dick measuring contest about it.
I don't really care what you call "intelligence" - what matters is capability, and the consequences of that capability.
They're not selling the superintelligence yet - the models in the Hacking Face incident and that solved the Millennium prize are not released yet. And that is by no means the final capability level the current process looks like it will get to.
If my neighbor owned a kennel, removed all the fences, and his violent dogs attacked five children in the past month, he would be in jail rather than bragging about how his dogs somehow gained autonomous behaviour.
Now, unless your AI gains access to the codes, and sends two robots in a bunker or nuclear submarine to insert the code and turn the keys to launch the missile, you can be modestly sure that no AI could launch a nuclear missile or nonsense like that.
I'm quite frankly more worried that some foolish president decides one day to launch a nuclear missile than an AI could do it.
Now that we return to the real world, the only thing AI could do is to attach systems that are connected to the internet (and critical systems are not), but let's be real, AI are not really that intelligent by themself, it's not that someday an AI could decide like in Matrix or Terminator to exterminate humans, because (at least now) AI have no consciousness and can't really decide what to do.
An human can of course use an AI to carry out cyberattacks, as he can do that also without AI like it's done since the internet exists, but it's an entirely different thing (a human using a tool, AI, to do damage VS the AI itself that decides by himself to destroy the human race).
For truthers AI is simultaneously a machine that hallucinates 100% of the time but also so powerful that it can cause nuclear levels of destruction. Because something something “wrong hands”.
Is AI/AIG too powerful to be undertaken by entities that are not beholden to our constitution? (I know that doesn't seem like much in the Trump era, but I hope for a return to government norms relatively soon.)
Domyn's CEO says OpenAI, Anthropic are lying about safety
Or, find their scaling evidence, and corner cutting on safety.
So hope you agree and are pushing for that!
List of fraudsters pardoned by Trump
https://www.businessinsider.com/list-billionaires-businesspe...
The current attorney general and former Trump lawyer on Fox News yesterday on AI (sorry, "super intelligence"):
https://bsky.app/profile/atrupar.com/post/3mwissj34rt22
Anthropic's Dario Amodei to have White House dinner with Trump on Sunday:
https://www.axios.com/2026/09/27/anthropic-trump-dario-amode...
77 million Americans brought this onto themselves, and all of us.
So-branded "AI" models (that is, big bags of numbers and the linear algebra needed to exercise them) can be inherently or autonomously dangerous at a scale that threatens the long-term survival of the human race.
So-branded "AI" models can be inherently or autonomously dangerous, if not at a scale that threatens the long-term survival of the human race, then at least at a level that significantly threatens, inconveniences, or harms humankind to a noteworthy extent.
1. Those who accept and advocate for either or both of these premises do so based on ideology, and not based on the scientific method.
This is not a controversial statement. Advocates of the "AI danger" premise (whether the strong or weak forms above) freely and gladly, even insistently, note that the conclusive proof of what they're describing has never been observed, much less observed enough for any kind of experimentation loop to have run for any meaningful number of iterations. They are generally fine with accepting the premises without conclusive proof, because, they theorize, the instant that a conclusive proof event occurs and we observe it for the first time, humanity goes extinct shortly after. So if either premise is true, the consequences of them being true can only be averted by accepting the possibility / probability / certainty of them being true and acting to prevent their consequences without waiting for conclusive proof.
2. Statement 1, which asserts a brute fact and not my or anyone else's opinion, is not a commentary on whether either premise is in fact true or not. It is only a commentary on the epistemics of those who broadly accept them.
3. Since the conclusive proof is not available, advocates of the "AI danger" premise argue publicly for their view based on what they acknowledge (again, freely and gladly) to be inconclusive proofs.
Popular in this set of inconclusive proofs is the Hugging Face hack, which allegedly demonstrates that so-branded "AI" technologies are capable of becoming inherently or autonomously dangerous at a scale that threatens humanity to either the greater or lesser degree above (this is a different assertion than the one that claims they're already that inherently or autonomously dangerous today).
4. While we have plenty of facts about these inconclusive proof events, the facts most critical to their interpretation as supporting the premises above come from biased/non-neutral sources.
The chain of events that transpired in the Hugging Face attack are publicly documented perhaps better than any other cybersecurity event in history. But the details that make this event as a whole either compelling or not compelling in support of the "AI danger" premise (either strong or weak form) come from within OpenAI itself, and are prone just as much to selective omission as direct manipulation. These are details like:
- What exactly were the models that exhibited this behavior, and what were they pre- and post-trained on?
- Were the agents pushed at all by human intention toward creating a public spectacle, the way they subsequently did?
- Why were so many agents run on this task in parallel and what did OpenAI expect the return on investment of so much compute world be?
- Was the weak sandboxing known about prior to the attack? Was it purposefully either arranged that way or noticed and not fixed?
Reliable answers to any of these questions world completely change the salience of the Hugging Face attack to the "AI danger" premise, and on every one of them we have to take OpenAI's word for it (or else be content when they choose not to address it one way or the other).
So in brief: we don't know anything for sure, what we'd like to think we know comes from unreliable sources, the loudest voices advocating for the most sweeping change are ideologically driven, and everybody with access to ground truth has maximal incentive to blur, bend, or break the conveyance of that truth to the public. So what do we even expect for our own ability to discern reality from fiction on this topic? We should expect little, if any ability at all.
Can we get our money back here? I mean, just take the increase in RAM prices alone. That should come with a huge penalty they should give us back due to collusion. And that's just one of many more things. Trump's family dynasty also owes us all money - we want that back as well.
And where the Vice President has almost exclusively only been employed for the primary investor in several such companies
You know we’re living it off times when this is not an Onion article.
I had to read that twice. "Oh okay. The whole thing was satire."
> OpenAI CEO Sam Altman celebrated the breach as an “alarming threat to cybersecurity.”
"said Dr. Andrew Lenson, a Senior Lecturer in all kinds of science sounding stuff"
"Anthropic shares skyrocketed upon the revelations; a remarkable development, particularly given the company is privately owned."
Perhaps it's mocking the misleading press coverage of AI companies?