
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
Beyond Words: AI Theories and the Nature of Intelligence
This episode looks at three leading theories shaping the future of artificial intelligence. First, it looks at Large Language Models (LLMs), which argue that mastering language is the key to intelligence. Then, it explores the “Thousand Brains” theory, a neuroscience-inspired view that sees intelligence as the product of many cortical columns independently modeling the world through sensory input. Finally, it looks at Joint Embedding Predictive Architecture (JEPA), which focuses on teaching AI to form predictive, abstract representations of its environment. The discussion compares how each approach handles learning, reasoning, and knowledge representation, highlighting their unique strengths and limitations. Ultimately, the episode suggests that true AI may emerge not from one theory alone, but from a synthesis of ideas—reflecting the complex, multi-dimensional nature of intelligence itself.
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