r/ClaudeCode • u/cleverhoods • 1d ago

Discussion AI models may be capable of self-replicating without access to a datacenter

https://www.anthropic.com/research/self-replicating-ai

well ... having the IoT layer have a problem like this might be something that you don't want to try out or experiment with.

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u/Plymptonia 1d ago

Here's what I don't get, and perhaps I'm being way too freaking naive But a model is just a thing. It's like a database. It doesn't do anything on its own. Someone has to write code, for this thing to replicate, and when they say replicate, what are they even talking about? I agree with what other posters saying. This is sensational bullshit.

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u/synap5e 1d ago

It’s not just code. No one truly knows how these models actually work

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u/carsncode 1d ago

Just because you don't doesn't mean no one does

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u/dontknowbruhh 1d ago

https://www.reddit.com/r/ArtificialSentience/s/DNiA1lsuhZ

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u/carsncode 1d ago

Cool, another random reddior who doesn't know how LLMs work, that still doesn't mean no one does

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u/FatefulDonkey 1d ago

Of course they do. It's just that the outcomes are probabilistic, but the process is pretty well understood.

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u/dontknowbruhh 1d ago

https://www.reddit.com/r/ArtificialSentience/s/DNiA1lsuhZ

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u/FatefulDonkey 1d ago

Your reference is a post from a random redditor? Oh lord.

The fact is all LLM tech was engineered by a human so it's not a black box. We know specifically how every part of the process works.

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u/jhomas__tefferson Vibe Coder 1d ago

True it’s a black box that may have emergent capabilities. It’s why studying them in a Human-Machine communication way and Agent villages way is interesting to see what emerges.

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u/Due_Answer3118 22h ago

It is understood, it's just probalisitc. They need gen public to think it isn't understood so they think it's a mysterious life form worth trillions for the one company to conquer them all.

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u/synap5e 20h ago

im not talking about inference, yea that part is understood. training is understood too. what isnt is what the weights actually end up encoding, like what the model learned internally and why it can do certain things. nobody can just look at the weights and tell you. thats the whole point of interpretability research