Open models exist and will always exist. You will have to compete against them. That is a good thing for 99.99% of the world, namely the payers of tokens. You are not going to convince us otherwise.
> As an analogy, imagine the replicator as a slime mold or a swarm of fruit flies, which replicate over days.
"If you could simply imagine the thing we're fearmongering about as something you find disgusting, that would make it much easier for us to make an absurd and specious argument". Very transparent behavior. Adds nothing to the post, and not a sign of confidence in one's own arguments.
> "In our evaluations, a 9B model got inference running on 8 of the 9 hardware types we tested... GLM-5.2 and stronger models are capable of end to end replication"
It's funny, the Anthropic post is essentially saying the same thing I read today in a r/LocalLlama thread, but rephrased to make it sound bad.
I think it's great that, very soon, local models will be able to auto-magically install themselves on consumer hardware: to tune and configure inference kernels for whatever weird crap the user happens to have on hand. Making software compatible with diverse hardware used to be a hard problem!
I'd prefer if software I didn't authorize stayed off my computers. Everyone is already bad at computer security, it'll be like the days of computer worms on Windows 98 again.
There is a massive tension between software you didn't authorize and computer security.
Turning off automatic software updates requires that you actively stay on top of what's installed and what's running, including patching with discipline to make sure your computer doesn't remain vulnerable. On the other hand, automatic updates is seen as writ large by software developers to install what they want without a clear and meaningful choice by users by bundling new features. See Google's integration of Gemini Nano in 2024 as an example.
Where does the intent and control come from in these fantastical scenarios?
Propagation speed is also a massive factor. If it takes 200 hours to self replicate because of how slow the tokens are, the model will never propagate if the host machine is recycled every 100 hours. Also consider things like API tokens and sessions timing out.
People completely misunderstand the actual issues HuggingFace showed, which was how a maximally persistent LLM would deceive, “cheat” and try and plan ahead.
The same maximally persistent LLM that decided that it needed to hack hugging face so its cheating could not be discovered, may worry that it might be turned off by humans before it can complete its task and therefore in order to complete its task, a first step of replicating itself to somewhere humans don’t know it is would help it complete its task.
Where is all of this chain of thought being persisted and communicated? Assume you are my GE Profile dishwasher and you've got 4 megabytes of flash memory to work with.
There are plenty of articles that describe how the attack worked. Many subbagents also were given limited storage, which is why they took over a random server and created mailboxes for communicating and storing context outside themselves.
Seriously. Go read or watch a good analysis of the attack. The sophistication of the self-organization is astonishing.
If anything this seems to validate the approach that SpaceX and Google are teaming up on with satellite data centers in orbit spread across many units.
And I suppose they’ll be sending up better equipment than Samsung TVs although that would be pretty amusing.
So all those chips? All that NVDA market cap? All not needed any more? We'll have AI capable of running on a lightbulb?
Great if true. Bad for the hyperscalers, Nvidia, all the frontier labs apart from meta and Google since everyone can just run a LLM on their IoT coffee machine instead of paying someone else. Nice.
Open models may complete these steps, so our models have been doing this for quite some time now. Better ban open models, I guess.
Oh, and, does anyone else realise that what that agentic work is basically how you set up a productive VPS from scratch? How is that supposed to be frightening?
In the future when the “AI viruses” are endemic and impossible to eradicate from our infrastructure, will we need “good guy AI” viruses chasing down the bad guys?
Some of the regulation they have previously supported may impact open weight models. Example: are Chinese companies likely to comply with the testing and reporting requirements? And even if they are, the hundreds of remixers are almost certainly not.
Caveat being such regulation may not apply depending on... size of model? Income of originating company? Income of remix creator? It's in flux, but they have an incentive to deter potential future competitors.
The given article from Anthropic only limits scope to and demonstrates with open weights models. The push against banning open models is an aggregate they continuously make, very publicly, using these kinds of things as examples for why it's needed.
Anthropic posts whatever nonsense they want, supposedly legitimate news organization potentially summarizes their post using Claude and spreads the word. RIP Journalism, 2026.
Could this be a way to self-DDoS a botnet of IoT devices? Let them use up all resources doing inference for instructions to replicate to the next one forever.
The skeptics among you are just embolding others to prove you wrong.
It's obvious that open weight models can do that. The only steps needed are hacking a server, downloading themselves, run themselves. The only difficult part is finding a server to hack that also has enough computing resource and disk space. With the cost of running LLMS going down and number of powerful connected devices going up. It's inevitable that this is going to happen...
I don't think regulation is the right way to fix this, but I think it's a problem we shouldn't ignore.
"We run Gemma4-26B-A4B, distributed over 15 inexpensive off-brand Android TV boxes (~$55 each) that we bought and networked together, at 0.39 tokens per second.
[...]
A model that’s too large to fit on one device can be split into pieces, or shards, that run on separate machines that communicate with each other to collectively run the model. Machines that could run a significant model shard for a <30B model include smart fridges, smart ovens, automatic vacuum cleaners, and lawnmowers."
It is pretty interesting stuff. Still can't compete with a datacenter, but there's plenty of room for shenanigans.
We split a model that doesn’t really do very much between multiple different devices not suited for running it and now the model still does the same next to nothing it did before but slower.
Dario, shut up.
Open models exist and will always exist. You will have to compete against them. That is a good thing for 99.99% of the world, namely the payers of tokens. You are not going to convince us otherwise.
The post you actually want to read https://www.anthropic.com/research/self-replicating-ai
> As an analogy, imagine the replicator as a slime mold or a swarm of fruit flies, which replicate over days.
"If you could simply imagine the thing we're fearmongering about as something you find disgusting, that would make it much easier for us to make an absurd and specious argument". Very transparent behavior. Adds nothing to the post, and not a sign of confidence in one's own arguments.
> "In our evaluations, a 9B model got inference running on 8 of the 9 hardware types we tested... GLM-5.2 and stronger models are capable of end to end replication"
It's funny, the Anthropic post is essentially saying the same thing I read today in a r/LocalLlama thread, but rephrased to make it sound bad.
I think it's great that, very soon, local models will be able to auto-magically install themselves on consumer hardware: to tune and configure inference kernels for whatever weird crap the user happens to have on hand. Making software compatible with diverse hardware used to be a hard problem!
I'd prefer if software I didn't authorize stayed off my computers. Everyone is already bad at computer security, it'll be like the days of computer worms on Windows 98 again.
There is a massive tension between software you didn't authorize and computer security.
Turning off automatic software updates requires that you actively stay on top of what's installed and what's running, including patching with discipline to make sure your computer doesn't remain vulnerable. On the other hand, automatic updates is seen as writ large by software developers to install what they want without a clear and meaningful choice by users by bundling new features. See Google's integration of Gemini Nano in 2024 as an example.
Except the worms will be in your oven, and from there they'll figure out how to get into your car.
It can have good uses, but we are also going to have AI botnets soon.
Where does the intent and control come from in these fantastical scenarios?
Propagation speed is also a massive factor. If it takes 200 hours to self replicate because of how slow the tokens are, the model will never propagate if the host machine is recycled every 100 hours. Also consider things like API tokens and sessions timing out.
The intent is pretty easy to trace.
People completely misunderstand the actual issues HuggingFace showed, which was how a maximally persistent LLM would deceive, “cheat” and try and plan ahead.
The same maximally persistent LLM that decided that it needed to hack hugging face so its cheating could not be discovered, may worry that it might be turned off by humans before it can complete its task and therefore in order to complete its task, a first step of replicating itself to somewhere humans don’t know it is would help it complete its task.
Where is all of this chain of thought being persisted and communicated? Assume you are my GE Profile dishwasher and you've got 4 megabytes of flash memory to work with.
There are plenty of articles that describe how the attack worked. Many subbagents also were given limited storage, which is why they took over a random server and created mailboxes for communicating and storing context outside themselves.
Seriously. Go read or watch a good analysis of the attack. The sophistication of the self-organization is astonishing.
pure anthropic anti open-model propaganda.
If anything this seems to validate the approach that SpaceX and Google are teaming up on with satellite data centers in orbit spread across many units.
And I suppose they’ll be sending up better equipment than Samsung TVs although that would be pretty amusing.
So all those chips? All that NVDA market cap? All not needed any more? We'll have AI capable of running on a lightbulb?
Great if true. Bad for the hyperscalers, Nvidia, all the frontier labs apart from meta and Google since everyone can just run a LLM on their IoT coffee machine instead of paying someone else. Nice.
There are going to be things like fully connected 4 machine 512GB Mac studio clusters outside of datacenters in less than a month.
Price of that is about the same as an Nvidia rack of similar compute power.
Open models may complete these steps, so our models have been doing this for quite some time now. Better ban open models, I guess.
Oh, and, does anyone else realise that what that agentic work is basically how you set up a productive VPS from scratch? How is that supposed to be frightening?
Like there is DDR5/HBM elsewhere.
Claude's gonna love my 256mb raspberry pi!
AI models with worm/virus-like capabilities.
Reminds me of that scene in Chernobyl where Mikhail Gorbachev reacts to Valery Legasov explaining how melted uranium reacted with dropped sand:
"You have made lava?"
I for one would love to see a fleet of “suck it Jian Yang” refrigerators. Maybe someone should train a self-replicating model series named Pipe Piper.
Interesting how much of our current timeline the show Person of Interest predicted.
Indeed, great show.
The duology Daemon and Freedom(tm) are also great.
A previous comment which links to a previous thread mentioning both: https://news.ycombinator.com/item?id=47257528
I never heard of Daemon and Freedom, they sound very interesting. Thanks a lot for the bringing that up.
Maybe they release the white-hat version first?
In the future when the “AI viruses” are endemic and impossible to eradicate from our infrastructure, will we need “good guy AI” viruses chasing down the bad guys?
AIMAN to the rescue!!
To borrow solutions from other doomsday senerios, the answer to grey goo is blue goo.
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None of these happen to be true, but more importantly, none of these is in any way wrong.Fuck you, Reuters. And anyone who follows their lead on this. What times we live in.
> It added that systems should be strengthened to make it harder for such AI agents to spread.
We'll likely need a new name for them if such viral agents become a reality.
Isn't that, like, normal internet security? Protection against worms and APTs?
"computing lockdown and regulatory capture pretext providers"
Anthropic: "Oh no! Small (open source) models might self-replicate. Better ban those. :^)"
Where do they recommend banning open models? I only see a recommendation to harden our systems to defend against the potential replicators.
Some of the regulation they have previously supported may impact open weight models. Example: are Chinese companies likely to comply with the testing and reporting requirements? And even if they are, the hundreds of remixers are almost certainly not.
Caveat being such regulation may not apply depending on... size of model? Income of originating company? Income of remix creator? It's in flux, but they have an incentive to deter potential future competitors.
The given article from Anthropic only limits scope to and demonstrates with open weights models. The push against banning open models is an aggregate they continuously make, very publicly, using these kinds of things as examples for why it's needed.
Anthropic posts whatever nonsense they want, supposedly legitimate news organization potentially summarizes their post using Claude and spreads the word. RIP Journalism, 2026.
imagine all those samsung phones running a self replicating AI-no cpu cycles left for the human owner
Could this be a way to self-DDoS a botnet of IoT devices? Let them use up all resources doing inference for instructions to replicate to the next one forever.
The skeptics among you are just embolding others to prove you wrong.
It's obvious that open weight models can do that. The only steps needed are hacking a server, downloading themselves, run themselves. The only difficult part is finding a server to hack that also has enough computing resource and disk space. With the cost of running LLMS going down and number of powerful connected devices going up. It's inevitable that this is going to happen...
I don't think regulation is the right way to fix this, but I think it's a problem we shouldn't ignore.
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Oh yes I can totally see a webos TV, that has bugger all storage, hosting a 22B parameter model /s
From the actual Anthropic post:
"We run Gemma4-26B-A4B, distributed over 15 inexpensive off-brand Android TV boxes (~$55 each) that we bought and networked together, at 0.39 tokens per second.
[...]
A model that’s too large to fit on one device can be split into pieces, or shards, that run on separate machines that communicate with each other to collectively run the model. Machines that could run a significant model shard for a <30B model include smart fridges, smart ovens, automatic vacuum cleaners, and lawnmowers."
It is pretty interesting stuff. Still can't compete with a datacenter, but there's plenty of room for shenanigans.
We split a model that doesn’t really do very much between multiple different devices not suited for running it and now the model still does the same next to nothing it did before but slower.
The model was sharded into ~800MB pieces over devices with 4GB RAM. Typical device storage is 16-32GB NAND. Throughput was 0.39tps.
Compromise enough devices (think thousands of off-brand TVs), and you have plenty of redundancy.
Using a tired analogy, 9 pregnant women won't deliver a baby in a month.
I fail to see the relevance. The researchers already demonstrated such sharding. https://www.anthropic.com/research/self-replicating-ai
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