What is Neuromorphic Computing? | AI 101

The video explores the evolution of neural networks, highlighting the Universal Approximation Theorem and the differences between neurons and perceptrons. It discusses computer architectures, focusing on the Von Neumann bottleneck, and introduces neuromorphic computing as a brain-inspired approach to overcome hardware limitations. Neuromorphic computing involves both software and hardware, including neuromorphic chips and flexible materials, offering potential advancements in machine learning and understanding the brain.

What is the Von Neumann bottleneck and why is it problematic for machine learning?

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How do neuromorphic chips differ from traditional computing hardware?

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Discuss the potential benefits of flexible neuromorphic computing materials.

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