DiscoverData Science at HomeBrains in the Machine: The Rise of Neuromorphic Computing (Ep. 285)
Brains in the Machine: The Rise of Neuromorphic Computing (Ep. 285)

Brains in the Machine: The Rise of Neuromorphic Computing (Ep. 285)

Update: 2025-06-181
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In this episode of Data Science at Home, we explore the fascinating world of neuromorphic computing โ€” 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.

๐Ÿ“š References


SpikingJelly: https://github.com/fangwei123456/spikingjelly


Norse: https://github.com/norse/norse


IBM TrueNorth: https://research.ibm.com/blog/brain-inspired-chip


Intel Loihi 2: https://www.intel.com/content/www/us/en/research/neuromorphic-computing.html


SpiNNaker: https://apt.cs.manchester.ac.uk/projects/SpiNNaker/


BioRobotics Institute: https://www.santannapisa.it/en/institute/biorobotics



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Brains in the Machine: The Rise of Neuromorphic Computing (Ep. 285)

Brains in the Machine: The Rise of Neuromorphic Computing (Ep. 285)

Francesco Gadaleta