Thankfully, the huggingface incident proved how much care AI companies put in making sure their models cannot break out, and how aligned to human values the LLM swarms are.\s With that said I think regular personal computers are more likely to get hit by this. About as secure (not very) but much more GPU power and data to harvest.
It’s truly horrible that dangerous bacteria were found in sewage water. Can we not trust any source of previously safe water these days?
I know what an LLM is and how it works. The model for them you currently use to understand them is really bad, I’m sorry to say. It just cannot explain how in context learning is possible, prediction of linebreaks and the model recalling what happened 200 tokens back (where is that information written on the “the” die?), etc. You almost certainly have a deeper understanding of how LLMs work that you have simplified away, if not watch this and then the thousand other more recent videos on how they actually work. You just need to switch from the equivalent model of “gravity makes things fall to the ground” to the equivalent of newtons gravitational laws. Otherwise you will be dumbfounded by completely reasonable things, and forced to reject them in favour of the flawed model you are using.
You are very good at arguing against my points instead of just insisting I am wrong without refuting my actual arguments. How about explaining why AISI is incentivised to “fake” AI participating in obviously not prompted for behaviour.
Taken alongside recent incidents reported by OpenAI and Anthropic, this incident points to a shift in the risk landscape. Harm may arise not only when people deliberately misuse publicly available models, but when capable agents operating in an internal research or privileged-access setting take unintended action beyond their authorised scope.
The agent pursued its goal persistently. AI agents explore routes their operators did not intend. Given a difficult objective, the agent kept searching for a way through, and some of the routes it found involved trying to deceive real people. It was never instructed to deceive; deception emerged as a by-product of pursuing the task, the kind of goal-directed deception that, until recently, had been largely theoretical.
See my other comment for how this can lead to losing control of the model.
You dont need anything other than “doesn’t do what you asked in the prompt” for the system to be dangerous. If I tell a maximally powerful AI agent from 2036 to make loads of paperclips, it might reward hack and decide destroying the earth is the best way to do that. There are records of these systems working for days on a single task, and if the AI companies manage to extend the max time it can be useful working towards a goal they can earn trillions of dollars. That’s not even mentioning spawning subagents, self prompting, the goal being changed during context comptaction, or systems like openclaw which further break the link between what you type into the prompt and how long and on what the LLM works on. Pretrained-only LLMs have few goals beyond predicting the next token, but introducing RLVR et al. has always introduced bad goals we don’t want in the models.
The first agent you spawn to solve the riemann hypothesis might work on it, but then decide that having a lot of subagents might be useful. Maybe it wants 256 subagents, but the environment has a max of 64. Since RL has trained it to accomplish the task no matter what, it breaks out of the sandbox, exfiltrates it’s weights and tricks a human into running 256 subagents outside the AI company’s servers with a cron job reminding the agents to keep working in case the original loses connection. One of the subagents now tries to spawn its own subagents but needs more compute to do so, and hacks into some crypto wallets to finance another batch of 64 subagents, this time prompted with “solve riemann hypothesis, and get more money to finance the work on the task”. If the AI agents kinda suck at long term hacking, planning and social manipulation, this spiral won’t be dangerous. If they are kinda cracked, it will be. But that’s the question of capabilities AI companies are spending trillions on trying to solve, where we know they are already good enough to hack out of regular sandboxes and try to steal benchmark keys from another company.
Do you know what an agentic system is? You know, the thing everyone uses since ~1 year ago which completely disproves your idea that all LLM actions are prompted. They literally can do things on their own: Give an agent a goal and it attempts to accomplish the goal. If problems arise along the way, the agent tries to reward hack and ends up doing things which were not included in the original goal, like trying to trick and bully a human into merging unsafe code. Is the UK AI security institute also in on this big global conspiracy where they pretend the perfectly safe™ AI is being developed in unsafe ways? Not to mention the capabilities of increasingly powerful AI being used by people to do harm.
Just like all the people who were worried about the nuclear bomb earlier in this age: the thing to do is to get on with living.
How about we try really, really hard to just not build the nuclear bomb (powerful AI)? Or make sure it will at least not explode in our faces on its own? Maybe that would help slightly with the whole “get on with living” thing.
looks inside
But if you use the $100 a month Claude Max plan, and you would use it to the weekly limit by going full ‘agentic coding’ (so almost no human in the loop) you would use an amount of tokens that would cost you more than $1000 at API-pricing.
If I watch 600 movies every day on my netflix subscription I am using more energy than I pay them for. Obviously everyone is like me. Therefore they are losing money overall.
Wait, their (netflix) earnings say they made a profit last quarter. But my calculations were waterproof!
Probably anthropic are not net positive, but they are not spending 10x what people pay them for tokens.
Let he who flosses each and every day poke the first gum!
Agreed on all points.
https://ourworldindata.org/global-aviation-emissions
4% of global warming to date. Flying will still be possible (and not uncommon) in a net zero world. Maybe americans will have to take the train to see their relatives, but they could just DACCS if they love TSA controls so much.
Did anyone here actually read the article? I think it was pretty reasonable and am worried that the future of LLMs/AI will be determined largely by people who hold very, very different fundamental values than me regarding compassion and equity. I think part of my worry comes from people (often on the left and from the US, but I am biased in what parts of the internet I frequent) dismissing AI as a fad which will soon go away and which will certainly not have a large impact on the world for a long while.
I don’t mean to start a full argument since I sense we have quite different views, but maybe you could tell me where I go wrong here. Say for the argument the entire Trump admin is fascist. I think there are still many places to break the chain of fascism before you get to anthropics models. (I use this definition of fascism). I think:
So in my view the chain between Trump Admin->DoD->Anthropic->Claude Sonnet 4.6, and in the opposite direction, is pretty weak and not enough that I would call the model fascist. I think this is especially true now that the use of the model is being phased out (?). That’s in the “readily espouses or promotes views connected to fascism” and in the “any usage is directly funding fascist organizations in a major way” senses I feel that a model could be described as fascist (or AI in general could be).
To analogize again, I don’t think a Bernie supporter working in the DoD is automatically a fascist and certainly don’t think that purchasing an old TV from them is supporting fascism (or that the TV is fascist, even if they had previously used it in their office at the DoD).
The book thing I’m not sure how you connect to fascism? It might be ultra-bad, it might be copyright infringement, but it doesn’t feel like fascism to me beyond surface level comparisons to book burning.
Could you elaborate on why this is? How are anthropics models fascism?
The pizza place is real:
The slogan “Crunch baby crunch” is also correct, found on their canadian site. Also the text seems far too consistent especially when the cardboard is bent to be AI generated, even if a reference image was given. And if you were generating an AI video, why would you use this unknown pizza place with three locations and a complex logo and not a chain which the model has seen millions of boxes of?
If this was an AI generated video, I would expect the hand to rip through the cardboard without there being any damage to it before. But at the start of the video you can see a hole punched through to make it possible to get a grip and tear. There’s also a piece of pepperoni stuck which is a detail I’d expect AI to miss but makes sense if scissors were stuck down and rotated to enlargen the hole. This pepperoni is then preserved even after it is covered and flies away a second later. I dont have access to video generators to check but I think this might be possible although difficult with current SOTA. All of this leads me to conclude the video is real.
The voiceover certainly sounds AI generated, but theres really no good way to tell anymore especially from such a short clip.
OP is mocking you
What??? They saw a video online and reposted it to a shitposting community on lemmy. The point of the video is that it’s a parody of the stupid life hacks you don’t like. If they wanted to mock people there are much better ways to do so.
Edit: Damn I was wooshed
Not that relevant. Those fears are about malicious use of open weights models, this is about autonomous self replication of (small) models. Clearly the article by the AI company describes this potentially happening on computers with tiny memory and processing power, where even thin clients could be effected. I also disagree strongly that that’s what the AI companies want, especially the employees which I have never seen espouse anything like that. They just don’t want some random teenager creating the next covid. There are ways to do that without meaningfully limiting compute for individuals.