Embedded AI - Intelligence at the Deep Edge
“Intelligence at the Deep Edge” is a podcast exploring the fascinating intersection of embedded systems and artificial intelligence. Dive into the world of cutting-edge technology as we discuss how AI is revolutionizing edge devices, enabling smarter sensors, efficient machine learning models, and real-time decision-making at the edge.
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Embedded AI - Intelligence at the Deep Edge
Why Humanoid Robots Need Two Clocks
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A useful general-purpose robot has to do two things that fight each other. It has to think slowly enough to understand "put away the groceries," and it has to move fast enough to keep a grip on the milk carton without crushing it. The part that understands is large and slow. The part that moves has to be small and fast. You cannot run both on the same clock.
This episode looks at the design now shipping on real robots: Vision-Language-Action models that simply run two clocks at once. A slow brain that thinks a handful of times a second, a fast brain that moves two hundred times a second, and a single note of intent passed between them. We walk through how Figure's Helix splits a 7-billion-parameter planner from an 80-million-parameter controller, why "action chunking" keeps the motion smooth, and how a March 2026 project squeezed the whole pipeline onto a 40-watt module with no cloud connection at all.
This two-speed design is the same answer evolution reached, with the cortex deciding the goal and the cerebellum handling the reflexes. When biology and engineering independently land on the same structure, it is probably telling us something fundamental about what it takes to be intelligent inside a moving body.
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