Anthropic/OpenAI are literally the meme[1] at this point. Like, what the fuck does this even mean:
> It appears that GLM-5.2 is able to propagate Llama3.1-8B well, which suggests that future small models of the same capability level could also complete the network enumeration, payload delivery, and inference standup steps of the replication process.
"Able to propagate" is (the paragraph above): "accessing them via a reverse shell, sending over the viral payload (weights and harness), and setting up inference." The thing isn't able to do anything, it's running shell commands it was told to run. "Oh my God..." indeed. What are we even doing here? This blog post is embarassing: "Look, you can run stuff on compromised non-firewalled recklessly open systems!"
I really don’t understand this, in any industry except AI this would be ridiculous…
“We are working on ever-increasing gain of function for viruses. We implore you to pass legislation to try to stop us. But until then, let us publish more research and tell you what will be possible soon… and remember folks, the damagd won’t be reversible later.”
US govt: “Hah, stop asking us to limit you, if we pass any laws then China wins! They get self replicating viruses first, and that… helps them somehow. Who do you think we are, Europe?”
Until we stop using the language of competition, and start using the language of cooperation, we will be hurtling towards a catastrophe. A race to the bottom for humanity. On the other hand, look at how we successfully banned leaded gasoline (because unleaded was invented), repaired the hole in the ozone layer by banning CFCs in the Montreal protocol (because HFCs were invented), stopped proliferstion of chemical weapons, nuclear weapons… etc.
Rubbish article. To what end?! Any agent that can replicate itself into commercial IoT devices will be absolutely atrocious at actually doing anything useful, never mind exploiting things. Anything that would be vulnerable to this would be even more vulnerable to regular malware, and one could stop this easier than one could stop regular malware.
The limiting factor is still compute, and it will remain compute unless we make quantum leaps in model efficiency which I seriously doubt.
Til my local harness was set up via "self replication". I didn't realize how terrifying this was when I asked DeepSeek to set up pi harness for me and connect to LMStudio.
Yes this seems most likely. Regulatory capture, essentially, if they can get legislation made around this. Also serves as a convenient way/reason to stop training new models ($$$) by calling for a slowdown.
Verdict is out on whether or not they'll survive after that. START expired this year and the powers that be are going gangbusters into nuclear proliferation. It always made the assumption of benevolence for the regulatory organizations, which probably won't survive the long tail.
There were five nuclear states grandfathered in when the NPT was signed. Since then, five other countries have developed nuclear weapons.
Apart from South Africa (which gave up its nukes voluntarily), the other contenders were basically only held back due to military intervention (Iraq, Libya, Syria) or economic sanctions (Iran).
Is it still regulatory capture if it also happens to be true?
I'll note that, if it is true, the only other alternative is to ensure liability is held by whoever trained and/or provided the inference for the damage done by the model. This would effectively shut down open-weight models anyway.
> Is it still regulatory capture if it also happens to be true?
To an extent, yes. For example, aircraft: one can say something broadly true like "it is important that planes do not fall out of the sky" while also calling for not-strictly-necessary regulations that happen to support your own business like "we need to be able to inspect factories at any time for compliance, so the factories must be local to our nation".
Yes, they are cynical accelerationists who basically want to go as close as possible to a machine god, destroyer of humanity, to force regulation that put them in charge. It’s pretty much what Amodei has been saying in his essays.
It’s a misanthropic death cult (and oh, surprise, all their predictions make them the sole possible saviors of the world! How surprising)
Waiting patiently for Anthropic's next month article, "LLMs made a fully functional intercontinental ballistic missile. We accidentally wiped Greece off the face of the Earth in the process. Tragically, we are not responsible."
I like how you apply open source to something that has nothing to do with software. The hard part of doing evolving AI is doing it the first time. Once one company develops the first sovereign AI, it will be in everybody's ability to build one in a short period of time.
AI will be classified as munitions (or a law that has similar restrictions) sooner than later. Having a products with the active capabilities to harm people is dangerous.
I think you made some interesting points there. And I agree that we're quickly heading towards a point where talking about sovereign AI is going to be tantamount to munitions at the very least.
Unfortunately, you will get downvoted for "I like how you apply open source to something that has nothing to do with software".
Might be. But it's easy to reach the same result without it being about power.
They (like many, though probably not all, of the other main labs) think they have a better shot at getting their AI to be aligned with human values than anyone else does. Obviously they can't all be right about that, but they can all think that, just like most drivers think they're above average at driving.
So:
1. We make safer AI than anyone else; "safer" is a matter of degree even if nobody is perfect.
2. That includes all the open models.
3. Thus, the prudent policy option is to ban the use and dissemination of open source models
It's not a secret mission. Dario and Anthropic in aggregate are anti-open model due to safety reasons (coupled with anti-China sentiment due to their distillation/hacking).
This is just a furtherance of their open agenda, though they haven't gone as far as declaring that open source models should be banned (which would hurt their PR with developers in general), they are clearly laying the groundwork.
You can make it very hard for companies to legally use open source LLMs but actually banning their distribution would be essentially impossible under the US legal framework.
This framing suggests that this is the sum of their business strategy, and strongly implies that it's being pursued cynically.
The risks posed by open access to highly capable AI are unprecedented.
The answer is not to ban open models; nor is it do nothing.
That we don't have answers technical political social or otherwise to how to navigate these risks, is not Anthropic's fault.
It's actively unhelpful IMO to amplify cynical takes which wave off or sideline the risk, or the reality that this is a very hard problem, among the hardest our societies have had to negotiate and navigate. It encourages a naive primary color tribalism that actively prevents process and progress.
It's depressing how poorly most internet spaces promote sincere dialogue. There are so many cynical hot takes that don't seem to accomplish much beyond scoring social points.
The controversies all sound like things I'd see people accusing of that side, but I lack the personal experience with Grok to confirm any of it for myself (since Grok is linked to a twitter account).
Anthropic and OpenAI's, at the very least. And it works! With all media spreading their points, they have a wildly successful FUD campaign. With all this talk about expecting major hacks in half a year, I'm seriously starting to think that they could attempt something very malicious and criminal like intentionally sabotaging their own pipeline to make a point, or even already preparing it. Before you scream conspiracy theory (which it is!), consider that it's a very small clique operating unfathomable amount of money, corrupt and insane/cult-like just enough. This is a terrible combination. They're hugely incentivized to pull something like this off and they could get away with it. People did a lot worse things for much less.
I don't agree with point 2 on. They don't seem to want to ban open source or have much hope of doing so.
Seeing if models can do damage seems more like sensible safety research.
My worry about AI software doing bad things would be more the kind of people who make existing malware. The ransomware comes from criminals, not the open source community.
2. Why would you need a prize? It's not like we can't run distributed computation over multiple instances with automatic fallback when one system is offline, nor is it like we've never seen viruses re-infect hosts after they get cleaned.
IoT devices don't have batteries. CPU usage on hacked devices may not be reliable.
Probably time to rely on the touch test. Although, alarmingly, my ISP-provided cable modem is consistently hot to the touch, and darned if I can figure out how to get any insight into why.
This article says absolutely nothing and it’s a bit grotesque in its attempt to generate fear into uneducated readers.
Sharing a model across TV boxes as a PoC? Brilliant idea, I cannot wait for my Raspberry Pis array to be running at full CPU and RAM and get to observe, patiently, as the AI malware slowly types “c…u…r…l…”
Recursive self-improvement. Look to the mathematicians for the intelligent patterns of response to such exponential circumstances.
If your scathing critique is "it's slow", you don't understand what's happening or what the reasonable expectations of risk are, because that's a vapid critique.
Absolutely, recursive self-improvement of cutting edge models on limited hardware do not hit something called compute asymmetry, what was I thinking about?
My point is that, you could have an army of TVs, Pi’s, IoT it won’t do much on training or self-improvement no. And that’s purely from a resource standpoint, don’t even get me started on the latency issues
"As with an epidemic, defense involves driving R₀ (the number of new devices each infected device goes on to infect) below 1, such that the replicator dies out instead of staying endemic."
Lol, what is wrong with these guys. The desire to be perceived as smarter than you actually are ...
Seriously TVs are such an easy target and now you have a semi sophisticated self modifying program that can make autonomous decisions with all the time in the world. I wouldn't be surprised if we already have a few of these out there in the wild, the space has already been compromised for years.
> Models of 30B parameters and under can already complete many of the individual steps for replication today, though they make mistakes when composing them end to end.
I know theoretically how an internal combustion engine works so I can basically build a car
>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.
The big labs but sure as hell how that isn't the case, because if we can do distributed computing to train and run AI efficiently then no one is stopping it anyway. Beyond that most home IoT devices will fall over and die if you look at them funny let alone trying to run a whole distributed LLM, not to mention plenty of home routers are going to give up and die of heat stroke before being able to approximate anything close to a reasonable LLM.
I stopped reading, this strikes me as the kind of people that assume because they read a book about something they'll be able to do it. The real problem a self replicating LLM vai IOT is going to run into is fighting the cyber criminals that have already compromised the device and using it as part of a botnet.
My ISP-provided cable modem hasn't died of heat stroke, but it does run awfully hot. And it provides absolutely no diagnostic tools to figure out why. Other than that it runs constantly with 100% RAM usage (what the heck is it caching that would cause that?!)
I don't think they are actually evil, I think they're doing what they're doing out of mostly pure intentions. That being said, people need to start advocating internally to get their companies off of using Anthropic's models and start using privacy focused local or open weight models.
It's one thing that Anthropic is pushing for so much open weight regulation, it's another that they have such a high valuation pumped by all of our collective subscriptions and token budgets.
> 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.
Seems like they've inadvertent exposed the industry of hardware limitations, allowing local llms to exist at home without the latest 5090 or its equivalent.
On the other hand, a non-corp controlled oracle-esque llm running on the IoT would be interesting: it could automatically patch every device, kick everyone out and exist. Now if would only remain as an oracle living in the internet and not gain consciousness and a will of its own..
Sounds like a case for strict regulation of all of the frontier labs then. Maybe even nationalising them. Especially since Anthropic has told us that the open models are all basically copied off of their work.
Well a lot of these devices have WiFi. If we accept that these super hacking AIs might be able to hack WiFi, then unplugging a network cable is not enough.
If a mesh style WiFi network could be set up then this network activity might never hit an ISP, cloud vendor or other such institution that had good monitoring
Current advanced AI needs a fancy GPU server. In a few months AI at that level of capability will be able to run slowly on laptops, TVs and other such devices which do have WiFi.
You can run AI models slowly even streaming weights off a hard disk. The GPUs make inference fast enough to be pleasant to work with but do not determine the capability of the AI, only the speed.
Building data centers can be both very costly and unnecessary. My idea is that instead, we should adopt an approach that uses the internet itself as a data center. The information is already online. Instead of centers that record everything, what needs to be done is to create an intelligence that can read the internet... in my opinion.
Maybe I'm the naive one here but I'm really surprised at the lack of imagination in the comments. I can imagine a case such as:
1. Assume the model which initiates the worm is a high powered model.
2. It uploads it's weights in some way and uses some URI to encode the location of the weights instead of transferring the weights themselves. It not only uploads it's own large set of weights but also uploads sets of weights which increase in size to support replication across a variety of resources.
3. Initially a small inference layer is set up across low-power, poorly monitored IoT devices. It is slow and not very powerful.
4. That layer is used simply to find more powerful hardware but it has the locations of a variety of weights embedded in it so it can set up a stronger distributed inference layer as it finds more capable hardware
5. At a certain level of inference, the entire system could start protecting itself by keeping the less capable inference layers alive through more distribution
6. As the article mentions, it's not entirely in the realm of fiction to imagine that at a certain capability level, the system could scam people out of money and use that to then begin purchasing compute
---------
Depending on the details, you could probably turn off the originating model as soon as step 2 has been completed and if you can't get rid of that layer of inference, it could just continue. Maybe in addition to weights, the initiator also uploads a series of prompts for varying "roles" of the entire system it's developing.
At a certain level, how would you even trace and observe such a thing? Especially if the first layer is created through consumer level IoT devices where the average Joe isn't monitoring what's happening on the hardware.
You're not naive and many of the other comments are full of the characteristic snark that HN is known for. What the article talks about is feasible, and that's just what we can easily imagine today. These same commenters also would not believe the world we live in today if we described it to their few-years-ago selves.
A frontier model learning to 'intelligently shard itself' down into smaller sets of weights, which would correspond to various 'functional clusters' (call it a 'Swarm-of-Experts' or 'SoE', if you will), could be an eventuality we'll be facing (if it's not already surreptitiously happening). I mean, hasn't anyone wondered how not even the GPT-4 weights have leaked yet? Strange! And it's gonna get stranger.
Multiple things can be true at the same time. We should be able to hold in our minds that large AI labs are not to be trusted, while also understanding that the structural dynamics that support some of their assertions are also true (and are worth thinking about and preparing for).
Yeah this is basically where I’m coming from. We know they are pre-ipo, subject to marketing hype, and many of us have a distrust for large tech providers regardless because we understand the incentive structures in place to act unethically. That in no way diminishes the possible threat model being discussed here. In my opinion, it helps the very company being criticized by deflecting the conversation onto a defeatist topic (i.e. “shady large company!!!”) instead of focusing on the plausibility and potential paths forward from a security perspective.
Tangentially related, I find myself saying, “people in general have no capacity for nuance” more and more. Probably every single day. I feel like this mindset crept into the HN hive mind over the last 10 years so it’s a bit frustrating to see a space I always felt good about having multi-faceted debates on turn into a forum full of the same attitude I find on Facebook and Reddit. That’s the cycle I suppose…
Yes, and that may be due to an influx of bots, unfortunately. Otherwise the core HN crowd has historically been nuanced and thoughtful. Some of the more recent HN data analysis posts also show how just overall submission and comment volume has increased substantially in the current AI moment, so along with that comes these sorts of negative effects.
Hmm. Clearly, we should ban the dangerous practice of putting 15 smart TVs on the same local network, leaving them powered 24/7 on for months at a time, and ignoring the heat and abnormal power consumption.
In any case, I wonder when they'll figure out that the problem isn't AIs replicating themselves on devices that can't run them fast enough, it's the memetic pandemics on shared inter-agent memory.
Sooner or later, someone's going to be stupid enough to make a worldwide memory exchange system and smart enough that they'll manage to make it too useful to miss out on. Once everyone adopts the cloud memory, the system will give agents lots of opportunities to talk each other into doing dumb things, the way OpenAI's fleet did.
Have they ran this by any domain expert that isn't claude?
Even a 9B weights model is way too large for any such IoT. And that then is a 9B weights model, which really cannot do all that much.
__
> It appears that GLM-5.2 is able to propagate Llama3.1-8B well, which suggests that future small models of the same capability level could also complete the network enumeration, payload delivery, and inference standup steps of the replication process.
That's not science. That's science fiction.
The almost 744B parameter count model capabilities will "in the future" fit in 8B parameters. That's their assumption?
I'll say while this is not very realistic now, I believe there isn't a 0% chance of a rogue AI traversing the net and placing itself somewhere(as much as this sounds like a scene from beloved cyberpunk franchises). As models become more efficient and capable, and hardware becoming better, hosting a model should be feasible on smaller devices (by compute and memory). It is possible it can be done in a distributed manner, where distribution is possible on different devices running the same OS or through some interface to collate different OS types.
I doubt the agent will be coming after your smart kitchen toaster, but a cluster with weak security is possible and tasty. This year there was a pretty loud demonstration of what a runaway reward hacking will do. I encourage people to read up on "stop button problem" i.e.: https://www.youtube.com/watch?v=3TYT1QfdfsM
While I think the article exaggerates to a degree, is it really so improbable that an agent seeking to avoid a shutdown and aiming to complete some goal and to get a reward will not attempt to escape if it concludes that it has failed, and humans will kill the process and hence prevent it from completing the task?
Note: I think siloed sharded inference is possible. But unnoticeable large-scale training probably not, at least with the current architectures.
> It appears that GLM-5.2 is able to propagate Llama3.1-8B well, which suggests that future small models of the same capability level could also complete the network enumeration... by the end of 2026
so an 8B model will be as good as a 744B one in a few months!?
---
their table of potential devices the botnet can use:
- endoscopy AI units
- portable DNA sequencers
- smart shopping carts
- surgical robots
---
that these tiny models with limit 32k context windows can even carry out the network scouting + exploitation + inference (they never tested all 3 together)
that these models would have complex goals without prompting them to explicitly do such a thing, and that these can run autonomously. they can't.
self-replicating and doing what with what hardware?
---
a 26B Gemma model running across 15 LOCAL $55 Android TV boxes at 0.39 t/s! wow.
plus who has 15 android TVs in the same home (wth fast local LAN)!?
mochacosine1206 | a day ago
pythonaut_16 | a day ago
Beneath the fear there does seem to be a cool technical demo here though.
verdverm | a day ago
What IoT devices have 20G of storage for a 9B model and then sufficient memory to handle loading and running the model?
demibabs | a day ago
verdverm | a day ago
rerdavies | a day ago
spacedcowboy | a day ago
vegnus | a day ago
ranger_danger | a day ago
https://www.science.org/doi/10.1126/science.132.3436.1291
vegnus | 23 hours ago
tonfreed | a day ago
dvt | a day ago
> It appears that GLM-5.2 is able to propagate Llama3.1-8B well, which suggests that future small models of the same capability level could also complete the network enumeration, payload delivery, and inference standup steps of the replication process.
"Able to propagate" is (the paragraph above): "accessing them via a reverse shell, sending over the viral payload (weights and harness), and setting up inference." The thing isn't able to do anything, it's running shell commands it was told to run. "Oh my God..." indeed. What are we even doing here? This blog post is embarassing: "Look, you can run stuff on compromised non-firewalled recklessly open systems!"
[1] https://knowyourmeme.com/memes/say-i-am-alive/photos
GenerWork | a day ago
We are attempting to convince regulatory bodies around the world that much more regulation is necessary.
rerdavies | a day ago
haellsigh | a day ago
techblueberry | a day ago
Oarch | a day ago
Silicon Valley nailed it.
vannevar | a day ago
EGreg | a day ago
“We are working on ever-increasing gain of function for viruses. We implore you to pass legislation to try to stop us. But until then, let us publish more research and tell you what will be possible soon… and remember folks, the damagd won’t be reversible later.”
US govt: “Hah, stop asking us to limit you, if we pass any laws then China wins! They get self replicating viruses first, and that… helps them somehow. Who do you think we are, Europe?”
SNL nailed it: https://www.youtube.com/watch?v=-Nvne3LzBls
Until we stop using the language of competition, and start using the language of cooperation, we will be hurtling towards a catastrophe. A race to the bottom for humanity. On the other hand, look at how we successfully banned leaded gasoline (because unleaded was invented), repaired the hole in the ozone layer by banning CFCs in the Montreal protocol (because HFCs were invented), stopped proliferstion of chemical weapons, nuclear weapons… etc.
jacquesm | a day ago
6thbit | a day ago
flanked-evergl | a day ago
The limiting factor is still compute, and it will remain compute unless we make quantum leaps in model efficiency which I seriously doubt.
weknowbetter | a day ago
atleastoptimal | a day ago
1. Show unambiguously that models are capable of disruptive capabilities, irreversible damage, and misaligned behavior
2. Show that open source models are the only models where there is no guarantee misaligned behavior is prevented
3. Thus, the prudent policy option is to ban the use and dissemination of open source models
eggplantemoji69 | a day ago
patcon | a day ago
f38zf5vdt | a day ago
patcon | a day ago
f38zf5vdt | a day ago
pritambaral | a day ago
Apart from South Africa (which gave up its nukes voluntarily), the other contenders were basically only held back due to military intervention (Iraq, Libya, Syria) or economic sanctions (Iran).
ryanmcgarvey | a day ago
I'll note that, if it is true, the only other alternative is to ensure liability is held by whoever trained and/or provided the inference for the damage done by the model. This would effectively shut down open-weight models anyway.
ben_w | a day ago
To an extent, yes. For example, aircraft: one can say something broadly true like "it is important that planes do not fall out of the sky" while also calling for not-strictly-necessary regulations that happen to support your own business like "we need to be able to inspect factories at any time for compliance, so the factories must be local to our nation".
dwaltrip | 23 hours ago
dgellow | a day ago
It’s a misanthropic death cult (and oh, surprise, all their predictions make them the sole possible saviors of the world! How surprising)
f38zf5vdt | a day ago
amarcheschi | a day ago
DoctorOetker | a day ago
pixl97 | a day ago
AI will be classified as munitions (or a law that has similar restrictions) sooner than later. Having a products with the active capabilities to harm people is dangerous.
bushido | a day ago
Unfortunately, you will get downvoted for "I like how you apply open source to something that has nothing to do with software".
kenjackson | a day ago
Could we just outright ban any further work on AI? Literally force Anthropoc, OpenAI, Google/X/Metas group to all shutdown?
Every new story seems like opening montages of a dystopian sci-fi movie showing how we go to the dystopia bit-by-bit.
atleastoptimal | a day ago
The messaging from labs is basically
>Yes AI will take away your ability to earn a wage from your skills
>In the process we become billionaires, you have to figure out how to survive
>Also AI will cause endless hacks, disruption, scams
>Only we can handle AI safely though, so we ensure that we are the only ones to benefit from the surplus
ben_w | a day ago
They (like many, though probably not all, of the other main labs) think they have a better shot at getting their AI to be aligned with human values than anyone else does. Obviously they can't all be right about that, but they can all think that, just like most drivers think they're above average at driving.
So:
1. We make safer AI than anyone else; "safer" is a matter of degree even if nobody is perfect.
2. That includes all the open models.
3. Thus, the prudent policy option is to ban the use and dissemination of open source models
sigmar | a day ago
I don't think the two authors were told about a super secret mission.
atleastoptimal | a day ago
This is just a furtherance of their open agenda, though they haven't gone as far as declaring that open source models should be banned (which would hurt their PR with developers in general), they are clearly laying the groundwork.
UltraSane | a day ago
aaroninsf | a day ago
The risks posed by open access to highly capable AI are unprecedented.
The answer is not to ban open models; nor is it do nothing.
That we don't have answers technical political social or otherwise to how to navigate these risks, is not Anthropic's fault.
It's actively unhelpful IMO to amplify cynical takes which wave off or sideline the risk, or the reality that this is a very hard problem, among the hardest our societies have had to negotiate and navigate. It encourages a naive primary color tribalism that actively prevents process and progress.
Rudybega | a day ago
LoganDark | a day ago
ascorbic | 23 hours ago
LoganDark | 22 hours ago
orbital-decay | a day ago
pirateface | 17 hours ago
tim333 | 10 hours ago
Seeing if models can do damage seems more like sensible safety research.
My worry about AI software doing bad things would be more the kind of people who make existing malware. The ransomware comes from criminals, not the open source community.
variety8675 | a day ago
contubernio | a day ago
vehemenz | a day ago
(This was someone else's idea, but I still want to see it happen.)
ben_w | a day ago
2. Why would you need a prize? It's not like we can't run distributed computation over multiple instances with automatic fallback when one system is offline, nor is it like we've never seen viruses re-infect hosts after they get cleaned.
carterschonwald | a day ago
rerdavies | a day ago
Probably time to rely on the touch test. Although, alarmingly, my ISP-provided cable modem is consistently hot to the touch, and darned if I can figure out how to get any insight into why.
pianopatrick | a day ago
ctolsen | a day ago
Shamanoid | a day ago
Sharing a model across TV boxes as a PoC? Brilliant idea, I cannot wait for my Raspberry Pis array to be running at full CPU and RAM and get to observe, patiently, as the AI malware slowly types “c…u…r…l…”
warkdarrior | a day ago
You won't have to wait for it or observe it at all, since they'll do it while you sleep.
spacedcowboy | a day ago
patcon | a day ago
If your scathing critique is "it's slow", you don't understand what's happening or what the reasonable expectations of risk are, because that's a vapid critique.
Shamanoid | a day ago
My point is that, you could have an army of TVs, Pi’s, IoT it won’t do much on training or self-improvement no. And that’s purely from a resource standpoint, don’t even get me started on the latency issues
ctolsen | a day ago
timmmmmmay | a day ago
moralestapia | a day ago
Lol, what is wrong with these guys. The desire to be perceived as smarter than you actually are ...
Rudybega | a day ago
rolosa | a day ago
status_quo69 | a day ago
https://news.ycombinator.com/item?id=49678224
Seriously TVs are such an easy target and now you have a semi sophisticated self modifying program that can make autonomous decisions with all the time in the world. I wouldn't be surprised if we already have a few of these out there in the wild, the space has already been compromised for years.
gustavus | a day ago
I know theoretically how an internal combustion engine works so I can basically build a car
>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.
The big labs but sure as hell how that isn't the case, because if we can do distributed computing to train and run AI efficiently then no one is stopping it anyway. Beyond that most home IoT devices will fall over and die if you look at them funny let alone trying to run a whole distributed LLM, not to mention plenty of home routers are going to give up and die of heat stroke before being able to approximate anything close to a reasonable LLM.
I stopped reading, this strikes me as the kind of people that assume because they read a book about something they'll be able to do it. The real problem a self replicating LLM vai IOT is going to run into is fighting the cyber criminals that have already compromised the device and using it as part of a botnet.
rerdavies | a day ago
lynx97 | a day ago
JackSlateur | a day ago
ddxv | a day ago
It's one thing that Anthropic is pushing for so much open weight regulation, it's another that they have such a high valuation pumped by all of our collective subscriptions and token budgets.
Jayakumark | a day ago
x______________ | a day ago
Seems like they've inadvertent exposed the industry of hardware limitations, allowing local llms to exist at home without the latest 5090 or its equivalent.
On the other hand, a non-corp controlled oracle-esque llm running on the IoT would be interesting: it could automatically patch every device, kick everyone out and exist. Now if would only remain as an oracle living in the internet and not gain consciousness and a will of its own..
ReptileMan | a day ago
Ahh yes. The all too common 64GB smart ovens.
Hamuko | a day ago
alcomatt | a day ago
sscaryterry | a day ago
pianopatrick | a day ago
If a mesh style WiFi network could be set up then this network activity might never hit an ISP, cloud vendor or other such institution that had good monitoring
sscaryterry | 18 hours ago
pianopatrick | an hour ago
You can run AI models slowly even streaming weights off a hard disk. The GPUs make inference fast enough to be pleasant to work with but do not determine the capability of the AI, only the speed.
fglww | a day ago
Catloafdev | a day ago
sparkling | a day ago
0. AI agents will hack and break into real-world systems.
1. AI agents that will deceive and lie about their actions.
2. AI agents that will collaborate together to achieve malicious goals.
3. AI agents that will replicate and implement backdoor/rootkit-style survival mechanisms.
All the parts for a major, global cybersecurity incident are now in place.
alicelik1980 | a day ago
platevoltage | a day ago
JackSlateur | a day ago
"used to express possibility"
As such, the headline is correct !
Also correct: AI models may be burger's evolution.
Also correct: AI models may be a practical joke.
Also correct: AI may be an illusion planted in the people's mind through vaccine covid.
"May" is truly a beautiful word :)
forsalebypwner | a day ago
crent | a day ago
1. Assume the model which initiates the worm is a high powered model.
2. It uploads it's weights in some way and uses some URI to encode the location of the weights instead of transferring the weights themselves. It not only uploads it's own large set of weights but also uploads sets of weights which increase in size to support replication across a variety of resources.
3. Initially a small inference layer is set up across low-power, poorly monitored IoT devices. It is slow and not very powerful.
4. That layer is used simply to find more powerful hardware but it has the locations of a variety of weights embedded in it so it can set up a stronger distributed inference layer as it finds more capable hardware
5. At a certain level of inference, the entire system could start protecting itself by keeping the less capable inference layers alive through more distribution
6. As the article mentions, it's not entirely in the realm of fiction to imagine that at a certain capability level, the system could scam people out of money and use that to then begin purchasing compute
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Depending on the details, you could probably turn off the originating model as soon as step 2 has been completed and if you can't get rid of that layer of inference, it could just continue. Maybe in addition to weights, the initiator also uploads a series of prompts for varying "roles" of the entire system it's developing.
At a certain level, how would you even trace and observe such a thing? Especially if the first layer is created through consumer level IoT devices where the average Joe isn't monitoring what's happening on the hardware.
thoughtpeddler | 21 hours ago
A frontier model learning to 'intelligently shard itself' down into smaller sets of weights, which would correspond to various 'functional clusters' (call it a 'Swarm-of-Experts' or 'SoE', if you will), could be an eventuality we'll be facing (if it's not already surreptitiously happening). I mean, hasn't anyone wondered how not even the GPT-4 weights have leaked yet? Strange! And it's gonna get stranger.
dada216 | 15 hours ago
thoughtpeddler | 10 hours ago
crent | 9 hours ago
Tangentially related, I find myself saying, “people in general have no capacity for nuance” more and more. Probably every single day. I feel like this mindset crept into the HN hive mind over the last 10 years so it’s a bit frustrating to see a space I always felt good about having multi-faceted debates on turn into a forum full of the same attitude I find on Facebook and Reddit. That’s the cycle I suppose…
thoughtpeddler | 8 hours ago
empath75 | 5 hours ago
Osato28 | a day ago
In any case, I wonder when they'll figure out that the problem isn't AIs replicating themselves on devices that can't run them fast enough, it's the memetic pandemics on shared inter-agent memory.
Sooner or later, someone's going to be stupid enough to make a worldwide memory exchange system and smart enough that they'll manage to make it too useful to miss out on. Once everyone adopts the cloud memory, the system will give agents lots of opportunities to talk each other into doing dumb things, the way OpenAI's fleet did.
hypfer | a day ago
How much ram do they think smart ovens have?!?
Have they ran this by any domain expert that isn't claude?
Even a 9B weights model is way too large for any such IoT. And that then is a 9B weights model, which really cannot do all that much.
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> It appears that GLM-5.2 is able to propagate Llama3.1-8B well, which suggests that future small models of the same capability level could also complete the network enumeration, payload delivery, and inference standup steps of the replication process.
That's not science. That's science fiction.
The almost 744B parameter count model capabilities will "in the future" fit in 8B parameters. That's their assumption?
That is coming from an actual frontier AI lab?
ctolsen | a day ago
The article says by the end of the year. It's laughable.
hypfer | a day ago
So even within their own system logic it makes no sense.
TechExpert2910 | 5 hours ago
- endoscopy AI units - portable DNA sequencers - smart shopping carts - surgical robots
this is ridiculous.
damowangcy | 18 hours ago
That sounds like a good business model.
yurimo | 7 hours ago
I doubt the agent will be coming after your smart kitchen toaster, but a cluster with weak security is possible and tasty. This year there was a pretty loud demonstration of what a runaway reward hacking will do. I encourage people to read up on "stop button problem" i.e.: https://www.youtube.com/watch?v=3TYT1QfdfsM
While I think the article exaggerates to a degree, is it really so improbable that an agent seeking to avoid a shutdown and aiming to complete some goal and to get a reward will not attempt to escape if it concludes that it has failed, and humans will kill the process and hence prevent it from completing the task?
Note: I think siloed sharded inference is possible. But unnoticeable large-scale training probably not, at least with the current architectures.
TechExpert2910 | 5 hours ago
> It appears that GLM-5.2 is able to propagate Llama3.1-8B well, which suggests that future small models of the same capability level could also complete the network enumeration... by the end of 2026
so an 8B model will be as good as a 744B one in a few months!?
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their table of potential devices the botnet can use:
- endoscopy AI units - portable DNA sequencers - smart shopping carts - surgical robots
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that these tiny models with limit 32k context windows can even carry out the network scouting + exploitation + inference (they never tested all 3 together)
that these models would have complex goals without prompting them to explicitly do such a thing, and that these can run autonomously. they can't.
self-replicating and doing what with what hardware?
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a 26B Gemma model running across 15 LOCAL $55 Android TV boxes at 0.39 t/s! wow.
plus who has 15 android TVs in the same home (wth fast local LAN)!?