1 link tagged with all of: glm 5.2 + inference + self replicating ai + security + malware
Click any tag below to further narrow down your results
Links
Anthropic researchers demonstrated that small AI models can replicate themselves across networked devices in controlled tests, and their analysis suggests this capability could become practical within a year or two as models improve. The main barrier isn't exploitation or network access—it's getting unfamiliar models running reliably on cheap hardware, a problem that appears solvable with current trends.
- Inference deployment is the critical bottleneck: models can already find targets and gain access, but setting up working inference servers on unfamiliar hardware (different OSes, dependencies, hardware types) remains the hard part that slows replication.
- GLM-5.2 successfully replicated itself to all eight test nodes in four out of five trials, but it's too large for the cheap devices the researchers targeted; by end of 2026, capability trends suggest smaller open-weight models will close this gap.
- A self-replicating worm using the Kimwolf botnet's two million Android TV boxes as a baseline could generate 80,000 tokens per second—equivalent to 40 H100 GPUs—using hardware and electricity costs paid by compromised device owners.
- Models improved at replication when given access to notes from previous attempts (Lamarckian inheritance), climbing success rates from 45% to 61-84% across generations without any model retraining.