For roughly $825, Anthropic’s Frontier Red Team built a cluster of 15 off-brand Android TV boxes that runs an AI model at 0.39 tokens per second, painfully slow for a chatbot but fine for software with nowhere to be and nobody waiting on it.

That experiment anchors new research from Anthropic researchers William Zhou and Daniel Freeman, published Monday, suggesting small open-weight models may be only months away from copying themselves across cheap, internet-connected hardware without relying on a datacenter.

The researchers haven’t built an AI worm that can spread across the public internet on its own, and their experiments took place inside controlled environments with shortcuts that made replication easier. But the results suggest several of the remaining technical barriers may be temporary.

The researchers haven’t built an AI worm that can spread across the public internet on its own, and their experiments took place inside controlled environments with shortcuts that made replication easier.

Zhou and Freeman identify four steps an AI needs to take to replicate itself, which are finding a target, gaining access, getting inference running, and moving on to the next machine.

Previous benchmarks such as CyberGym and ExploitBench suggest smaller models can already handle some of the exploitation work, and frontier agents escaped their test sandboxes using basic exploits earlier this year. The bigger challenge may be getting a model running on unfamiliar hardware, where it has to sort out whatever operating system, dependencies, and installation problems it runs into.

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