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.
Discover more on Embedded AI (https://medium.com/embedded-ai) — our companion publication where we detail the ideas, projects, and breakthroughs featured on the podcast.
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Embedded AI - Intelligence at the Deep Edge
Engineering "Instinct" in AI
Across species, evolution “pre-installs” compact neural programs that deliver immediate, reliable behaviors (standing, pecking, web-building) with minimal learning. These behaviors arise from embodied control circuits (reflexes, central pattern generators, innate releasing mechanisms) tuned by morphology and neuromodulators, then refined by fast, local plasticity during early experience.
In this episode, we explore the timeless debate between nature and nurture — and what it means for the future of artificial intelligence. Modern AI has largely followed the human model — learning everything from scratch — but at a steep cost in time, data, and energy. Researchers now argue that this “blank slate” approach misses evolution’s secret: built-in intelligence. By pre-wiring the brain with innate patterns — reflex loops, motivation systems, and hierarchical control — evolution gives organisms a massive head start. Intelligence, isn’t just learned — it’s evolved.
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