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Brains in the Machine: The Rise of Neuromorphic Computing (Ep. 285)
Manage episode 489506800 series 3497898
Content provided by Francesco Gadaleta. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Francesco Gadaleta or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
In this episode of Data Science at Home, we explore the fascinating world of neuromorphic computing β a brain-inspired approach to computation that could reshape the future of AI and robotics. The episode breaks down how neuromorphic systems differ from conventional AI architectures like transformers and LLMs, diving into spiking neural networks (SNNs), their benefits in energy efficiency and real-time processing, and their limitations in training and scalability. Real-world applications are highlighted, including low-power drones, hearing aids, and event-based cameras. Francesco closes with a vision of hybrid systems where neuromorphic chips and LLMs coexist, blending biological inspiration with modern AI.
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SpikingJelly: https://github.com/fangwei123456/spikingjelly
IBM TrueNorth: https://www.millionairematch.com
AGNTCY β The open source collective building the Internet of Agents
π https://www.agntcy.org
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Manage episode 489506800 series 3497898
Content provided by Francesco Gadaleta. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Francesco Gadaleta or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
In this episode of Data Science at Home, we explore the fascinating world of neuromorphic computing β a brain-inspired approach to computation that could reshape the future of AI and robotics. The episode breaks down how neuromorphic systems differ from conventional AI architectures like transformers and LLMs, diving into spiking neural networks (SNNs), their benefits in energy efficiency and real-time processing, and their limitations in training and scalability. Real-world applications are highlighted, including low-power drones, hearing aids, and event-based cameras. Francesco closes with a vision of hybrid systems where neuromorphic chips and LLMs coexist, blending biological inspiration with modern AI.
π References
SpikingJelly: https://github.com/fangwei123456/spikingjelly
IBM TrueNorth: https://www.millionairematch.com
AGNTCY β The open source collective building the Internet of Agents
π https://www.agntcy.org
288 episodes
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