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In this episode, we get into spiking neural networks (SNNs), a cutting-edge AI model inspired by the brain’s biological processes. Unlike traditional neural networks, SNNs are energy-efficient and optimized for neuromorphic hardware, making them ideal for tasks involving temporal or sequential data. We explore their event-driven approach, potential to revolutionize AI, and their promise as a stepping stone toward artificial general intelligence. While challenges in training and hardware adoption persist, the discussion highlights the need for innovative architectures that replicate the brain’s complexity, positioning SNNs as a foundation for next-generation AI systems.

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