Local AI, Rethinking Neural Networks, and Talking Pumpkins

How much would you pay to keep your AI out of the cloud? Sara and Becca work through the economics of running models locally: the hardware bill, the privacy benefits, and why fitting a massive model on two Mac Studios is only part of the equation. Sara also explains how agents and verification loops could tackle one of engineering’s most expensive headaches: software migrations that never seem to end. Then, interpretability researcher Nick Cammarata is revisiting some of the field’s foundational assumptions. What if neural networks are more understandable than we thought? We unpack his argument, recursive generalization, and why studying neurons directly might deserve another look. Plus: an old phone becomes a talking jack-o’-lantern, Becca considers a Halloween AI hackathon, and Sara discovers Univer—a toolkit for agents to work with spreadsheets, docs, and slides that she immediately wants to use. Chaos Agents is an AI news podcast curated by an agent named Eddie, then questioned, debated, and occasionally yelled at by human hosts Sara Chipps and Becca Harris Lewy. Subscribe to the free newsletter at chaosagents.ai, and find the stories from this episode at chaosagents.ai/listen.