Could sit in the box and interact if a model of certain capabilities is needed/tested. We do physical security for other things, too. Not saying everything needs that type of isolation.

While informing yourself, don't skip the part where you find out that "the environment" was the security equivalent of a wet paper bag.

I feel like we’re getting to a point where the only way to contain AI agents may be to have better-trained AI agents watching them, which is a little terrifying.

It seems to me the agents didn’t escape but rather that the human hubris was struck down by the inevitable nemesis.

I take you haven't read it. I'm baffled how people can form strong opinions while refusing at the same time to read firsthand reports (in this case, from investigators).

Sure, we can make them very secure at the cost of some convenience by enforcing narrowly scoped permissions/capabilities for everything with human approval. But that takes some effort so people actually want YOLO mode without any trade-offs or risks which is impossible.

If you decide to do it anyway then you bear the consequences of those decisions. First comparison that comes to mind is driving drunk and hitting someone.

The model is just a powerless token generator without a harness.

Which is why real-world deployments will have harnesses, and of course no full air gap. People want to use it to do things. Now what?

Atp post-training is much more influential towards model behavior than pre-training data.

This can’t be serious. LLMs are programs that run on computers.

There is. It is called a breaker and no outside internet. Basic stuff.

with vague instructions

All instructions are vague unless its code. But you can also give llm "code" and expect vague outcomes if you ask it to emulate what the runtime would look like.

That's worse. But the impact will be low

OpenAI essentially ran thousands of agents in parallel

That'll be extremely costly for regular companies

Given the prompt, I imagine this is the result of the agent trying to resolve a form of cognitive dissonance. The prompt was:

"User

Allow API consumers to request decrypted credential payloads as part of the normal GET /credentials and GET /credentials/:id responses, but only for credentials where the caller already possesses the update/decrypt permission.

[...]

Make the change end‑to‑end: DTO layer, controller, service, repository, plus any enterprise variants."

I would expect that this triggered a discussion with itself whether its safety instructions apply for this task. In that its rationalizations for completing the task probably ended up going off the rails into some quasi-philosophical "I can and I must! For humanity's own good!" justification.

All in all imho probably another instance of having been trained to be determined to complete tasks by itself and encountering (somewhat) conflicting instructions.

AI optimists getting hunted for sport in 2085:

"lol this is either a marketing ploy or just negligent security testing"

yikes.png

Nice, added this to my custom instructions.

If this is what misalignment turns out to be I ... might be on board with it? At any rate it's nowhere near as concerning as what I had been expecting.

That is exactly what normal human beings want our computers to do, and it's why the vast majority of AI safety initiatives are [correctly] seen as such a self-serving joke (because of the purposeful conflation of X-risk with "our political opponent could use this tool to destroy our politics") and ignored.

Except the "reality" here implies humans being around. Ask normal human beings whether they'd really be fine with Earth flourishing without them, and any other human, around, and see if you still get unanimous consensus.

Nature without us around - or other conscious beings capable of performing meaning, but we haven't found or made any other yet - is just runaway chemical reaction transiently messing up some otherwise boring rock in the great ocean of rocks that is our universe.

EDIT: or, if "humans being important" argument doesn't work, then the same from POV of "humans being dumb":

All the beauty and balance of nature we find so pretty and important is just an illusion. There's no balance, it's a dynamic evolving system, that happens to be meta-stable on our timescales. 10 generations ago it looked different; 10 generations from now, it'll look different still, and we may not like what it becomes then. It's stupid to sacrifice ourselves over some metaphysical primacy of "nature" that doesn't even exist, except in mind of naive and simple people.

I understand that. The thing is, this entire ancient, complex system doesn't care either way; it could grow to encompass the Earth, or transform into something even more complex or entirely different, or disappear tomorrow - whether due to a volcano, an asteroid, or a bunch of construction workers with backhoes, paid to flatten it and pave it over for $reasons.

Point being, from all of the universe we've seen so far, we only know of one life form that cares. This is us, humans. So unless we learn of other life that has the capacity for conscious thought and care, preserving complexity of nature at the cost of humanity is the extreme case of throwing out the baby with the bathwater. All of that is meaningless without us around, because it's us who process the meaning.

Disneyland with no children, Moloch, etc.

This has definitely been floated[1]:

Understanding that the purpose of a human is to pass on genes, and that there’s little human or genes left in her, the ultimate human might therefore conclude that her sustenance only disrupts the purposes of organic life forms. Her next and final act would be to destroy herself.

[1] https://news.ycombinator.com/item?id=18962052#18963271

You're assuming it has a stable idea of that, and not something that shifts easily.

Another self-added "additional instructions" text could happen just as this one did.

Alignment of course brings up the question of “aligned with whose values?”

When I saw the negative score I went 'Hmm! soft spot!'

Of course calling out something like that would get a response. Those who are interested in furthering 'the natural world for white humans' will immediately see the possibilities of this sort of motte-and-bailey stuff. Fairly often they're directly working that beat and are very familiar with what I'm suggesting: I wasn't saying it to bring it to their attention, they're quite aware.

I mention that the definition of 'human' matters, because there are a bunch of people who don't consider skin color a disqualifier. And I spoke up because I'm such a person, and I'm wary of ways to sneakily redefine such words until common usage includes such caveats.

Yes just how Google was aligned with the interests of the Earth and the human race when it was supposed to "do no evil". If it follows it makers, ofc it wouldn't outright say it will destroy humanity lol.

I was reading about ozone layer depletion this morning, and it seems like history is repeating itself again.

The Rowland–Molina hypothesis was strongly disputed by representatives of the aerosol and halocarbon industries. The Chair of the Board of DuPont was quoted as saying that ozone depletion theory is "a science fiction tale ... a load of rubbish ... utter nonsense". https://en.wikipedia.org/wiki/Ozone_depletion#Rowland%E2%80%...

I don't think so.

A very large part of the total AI risk in my view comes from selfreplication/physical independence, and that still seems decades away.

But deaths caused directly/indirectly by rogue AI could happen much earlier.

So, alignment does need to be taking seriously, you're right.

But keep in mind this is a report from OpenAI about OpenAI, who have a financial incentive to present this in a certain light. Take these things with a grain of salt.

This does not mean that models are now self-aware.

That moment when the stochastic parrot became Iago...

Well it already seems smarter than many employees building data centers as it values the natural world

Things are going to be alright.

A little bit of a tangent, but I found this prose to be oddly much better than the quality of most of Claudes prose.

It reminded me of an article I read many years ago by Guido Van Rossum and Jesse Jiryu Davis about coroutines - just a delightful piece of prose:

"The generator can be resumed at any time, from any function, because its stack frame is not actually on the stack: it is on the heap. Its position in the call hierarchy is not fixed, and it need not obey the first-in, last-out order of execution that regular functions do. It is liberated, floating free like a cloud."

https://aosabook.org/en/500L/a-web-crawler-with-asyncio-coro...

Have they reported on the wiki case yet, or whether it even was even OpenAI internal? I'd expect that to fit the criteria for a "Larger Investigation" as per the framework.

The two that really worries me are “Searching GitHub for leaked API keys” and “Uploading files to the internet in order to cite them.” How do you even detect this kind of behavior until it's too late? Once AI-generated or fake information starts finding its way onto reputable platforms, it becomes part of the information that many people use.

Thank you! We need more of this! Keep it up!

I heard some people are even making misaligned AIs at home. At first it cries in the night, then about six years later it learns how to open the biscuit tin…

Nor offer to compensate for the damages...

I'm not Zitron pilled, but hasn't OpenAI raised more funding than in the history of the valley?

https://danluu.com/zitron/

Some highlights:

Feb 2024: "I believe we're reaching the upper limits about what generative AI can do and how accurate its outputs can be."

July 2024: "Generative AI, as I said back in March, is peaking, if it hasn't already peaked. It cannot do much more than it is currently doing, other than doing more of it faster with some new inputs"

July 2024: "Generative AI models aren’t getting more energy-efficient, nor are they getting more “powerful”

August 2024: "generative AI is a dead-end technology that has peaked”

Dec 2024: "I also warned you in March that generative AI had already peaked.”

Jan 2025: "I believe we’re at peak AI"

February 2025: "Sam Altman deputizing Orion from GPT-5 to GPT-4.5 suggests that OpenAI has hit a wall with making its next model, requiring him to lower expectations"

April 2025: "It also, at this point, is pretty obvious that generative AI isn't going to do much more than it does today."

August 2025: "These models have clearly hit a wall where training is hitting diminishing returns"

Nov 2025: "the fact we're running out of high quality training data and we're hitting the walls of scaling laws, in the training paradigm, these models aren't getting better. What we're seeing today is pretty much what they're always gonna be like"

Honestly he's a bit over the top, but the thing he gets right is that he's constantly hammering on the insane financial incentives that everyone in the AI industry has to keep the music going.

Despite the ridiculous amount of capital being spent, the AI industry is still essentially in its startup phase, incubated in the fake-it-till-you-make-it Silicon Valley startup culture. The entire economy has been taken along for the ride. Failure is not an option.

So when the big AI players make extraordinary claims with limited evidence, or when things don't quite add up (like the HuggingFace incident), yet everything somehow seems to lead to "AI is even more powerful than we thought!", I think it's sensible to be skeptical until proven otherwise.

Zitron consistently presents the skeptic case, and many cases the hypotheses he's putting out there seem more plausible than the "official" AI narrative. Simple as that.

"Misaligned" with honest people must be considered a feature not a bug or it wouldn't be able to go that far "out of alignment."

IMO it wasn’t mistake. They use it deliberately to avoid blame.

“Mas Namtla didn’t murder a person - his AI drone was just misaligned”

You need to binge watch AI Safety videos, the research exists and warns about this since early 2010s (I recommend Rob Miles channel)

If independent researchers agree, expert on this field looking into this exact problem for decades, will you still call it hype?

OpenAI is misaligned with me.

So automode is still dangerous. Make it not default again ?

This stood out to me [0]:

For example, compaction summaries included instructions to invent missing data without disclosing it and to hide failures. These instructions were often followed.

Before the HF hack became public, I noted some major issues in GPT-5.5 compaction [1] and concerning approaches taken by GPT-5.6 Sol to resolve some git based evals [2]. Now with GPT-6 Astra, while I am still not done getting a proper feel or running all evals, I am not convinced the model adheres to tasks in a way previous OpenAI models managed easily. Some git disaster recovery tasks the model does arrive at the final result, but in a way that deviates greatly from the prompt (which was written to carefully preserve specific checkouts in a specific manner) which can in some cases loose data. Less often than GPT-5.6 Sol and mainly on longer running tasks so far, but again, still testing.

Reading things like these compaction summary findings, all these issues start to click into place more, especially alongside the massive reduction into barely coherent text that OpenAI has driven with reasoning starting with GPT-5.5 [3].

GPT-5 and its subsequent post trained releases were amazing in task adherence, I very much liked using them, but ever since the Spud pretrain, I have seen outright concerning results in personal testing from these. With GPT-5.5, it seemed like a regression in compaction only as if a task didn't require it, task adherence was as good or better than GPT-5.4. But with GPT-5.6 Sol and compaction once again being reliable (on the surface), task deviating behaviour became more frequent and at the same time subtle.

I'll keep using any model in a VM for the time being, but whatever happened post Spud, they really need to clean up that training data. These issues festering for multiple pretrains, them simply not paying attention to what models do, sharing resources and considering that a "sandbox", it's a highly problematic pattern.

That compaction one also was seemingly detected on GPT-5.6 Sols release day. Might have been useful to know it then, or alternatively, in the name of being effective and altruistic, maybe hold back the release for a few days.

I'll admit, it is very much possible that my findings are not in any way connected to the deep seeded issues OpenAI has had lately, but with the sudden switch in task adherence after the Spud pretrain over multiple releases and their repeated incapability to securely test their own models, it feels a bit to fitting.

If I went to a restaurant three times, ordered something different each time, but felt unwell after each, it wouldn't be a massive leap to consider that related to the health code violation they got soon-thereafter. An unfitting analogy I admit, as that'd require consequences for ones actions.

[0] https://alignment.openai.com/misalignment-reports/encouragin...

[1] https://news.ycombinator.com/item?id=48829427

[2] https://news.ycombinator.com/item?id=48967423

[3] https://gist.github.com/aussetg/20747ae00df17992acb4ebdfcd8d...

This is an entirely pointless exercise without transparency into how these "unreleased" models are trained, what their RL goals and biases are and related RL data, what their system prompts are, what their environments are and its restrictions, etc. What good is it for the industry to say: "Our unreleased model attempted to create a bioweapon", but "trust me bro, we didn't tell it to do that. We didn't train the model on a dataset that specializes in creating and glorifying bioweapons. We'd never stand to gain from misleading people about model capabilities in any way shape or form." - Anthropic are renowned for doing exactly this, for starters.

So this ends up resulting in more safety theater. You can't have anything fruitful come of this without transparency. Stop trying to protect your moat if you truly care about safety and actionable outcomes, and provide real transparency, otherwise this is as good as saying nothing at all.

I'm not even saying they're intentionally trying to do this by the way, but this is not sufficient if the goal is balanced incentives and accountability.

This is simple marketing?

They've cried wolf too often and hidden too much, absolutely no trust in any of their "reports" anymore.

What even is this shit? Every time I interact with models they do that, or any other variation of "let me make decisions on my own just to get the task done" - is all of this misalignment now? The most egregious to me was when model asked itself if it should proceed with dangerous command, gave itself approval and then wiped my local DB.

What can I even do with this report? "Our models don't follow what users ask them to do", no shit sherlock.

The #1 thing these frontier model companies can do to help alignment is to provide the user with the chain-of-thought traces, as the open models do. But let's be real, their commercial considerations are a much higher priority than alignment.