Monday, October 19, 2026

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AI swarms could make network security more important. Anthropic's October 12 research ran an AI model across 15 cheap Android TV boxes at 0.39 tokens per second. The small models still couldn't reliably complete the full replication cycle. I think we're still early. Inference on this hardware is painfully slow. But the idea is interesting because human-level intelligence isn't necessary for something to reproduce and spread. Think of insects: limited individual intelligence, yet populations can spread widely. An AI worm could carry its model with it, adapt to unfamiliar devices and use compromised hardware to run the next copy. A model too large for one device could be split across several. Better processors and more memory in future cameras, TV boxes and other connected devices would make more local inference possible, wherever attackers can gain access. That creates a security problem beyond installing software on individual devices. You're not going to put an endpoint security agent on every camera or TV box. You need to identify those devices through the network, restrict what they can communicate with and isolate them when compromised. A perimeter firewall alone cannot inspect traffic that never passes through it. I think $FTNT could benefit here. Its agentless device discovery and network segmentation fit this problem, especially across distributed sites. More capable AI on unmanaged devices could increase demand for those controls. The opportunity also extends to networking vendors that integrate security into switches and wireless access points, where they can control how devices connect and communicate.

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