A discussion on the evolving economics of autonomous vehicles, driven by end-to-end AI, and the growing local opposition to AI data centers due to concerns over resources like water, electricity, and noise.
A deep dive into the architectural and economic foundations of memory for AI agents. The talk explores the core tradeoffs between classical data storage and dynamic agent behavior, introduces a human-inspired framework for memory, and discusses practical strategies and future directions for building reliable, evolving AI systems.