Getting Started with Neuromorphic Computing
Neuromorphic Computing is the use of very large scale integration (VLSI) systems containing electronic analog circuits to simulate the neuro-biological architectures present in the human brain ad nervous system.
Intel Loihi 2, its second-generation neuromorphic research chip.
The Akida Neuromorphic System-on-Chip (NSoC) developed by BrainChip.
Developer Resources
- Neuromorphic Computing - Next Generation of AI | Intel
- Next-Level Neuromorphic Computing: Intel Lab's Loihi 2 Chip | Intel
- Neuromorphic Computing | NIST
- Programming and Usability of Neuromorphic Computing | ORNL
- Neuromorphic Computing | EBRAINS Research Infrastructure
- Neuromorphic devices & systems | IBM Research Zurich
- Light-Emitting Artificial Synapses for Neuromorphic Computing (Research Paper PDF)
Online Training Courses
- Top Computational Neuroscience Courses Online | Coursera
- Computational Neuroscience Course Online | Coursera
- Computational Neuroscience: Neuronal Dynamics of Cognition Course Online | edX
- Fundamentals of Neuroscience, Part 1: The Electrical Properties of the Neuron | Harvard Online Learning
- Fundamentals of Neuroscience, Part 2: Neurons and Networks | Harvard Online Learning
- Fundamentals of Neuroscience, Part 3: The Brain | Harvard Online Learning
- Introduction to Computational Neuroscience | MIT OpenCourseWare
- Brain and Cognitive Sciences Online Course | MIT OpenCourseWare
- Getting Started with PyTorch
- Top Pytorch Courses Online | Coursera
- Top Pytorch Courses Online | Udemy
- Learn PyTorch with Online Courses and Classes | edX
- Intro to Deep Learning with PyTorch | Udacity
- PyTorch on Azure - Deep Learning with PyTorch | Microsoft Azure
- Deep Learning with PyTorch | Amazon Web Services (AWS)
- Getting started with PyTorch on Google Cloud
Books
- Neuromorphic Computing Principles and Organization by Abderazek Ben Abdallah and Khanh N. Dang
- Neuromorphic Computing and Beyond: Parallel, Approximation, Near Memory, and Quantum by Khaled Salah Mohamed
- Neuromorphic Engineering: The Scientist's, Algorithm Designer's, and Computer Architect's Perspectives on Brain-Inspired Computing by Elishai Ezra Tsur
- Memristors for Neuromorphic Circuits and Artificial Intelligence Applications by Jordi Suñé
- Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design by Nan Zheng, Pinaki Mazumder
- Neuromorphic Devices for Brain-inspired Computing: Artificial Intelligence, Perception, and Robotics by Qing Wan, Yi Shi
- Understanding and Bridging the Gap between Neuromorphic Computing and Machine Learning by Huajin Tang, Kaushik Roy, Lei Deng
- Photo-Electroactive Non-Volatile Memories for Data Storage and Neuromorphic Computing by Ye Zhou, Suting Han
- Neuromorphic Photonics by Bhavin J. Shastri, Paul R. Prucnal
YouTube videos
- Neuromorphic Computing Explained | Jeffrey Shainline and Lex Fridman
- Brains Behind the Brains: Mike Davies and Neuromorphic Computing at Intel Labs | Intel
- How Neuromorphic Computing Uses the Human Brain as a Model | Intel Labs
- ESWEEK 2021 Education - Introduction to Neuromorphic Computing
- Stanford Seminar: Neuromorphic Chips: Addressing the Nanostransistor Challenge
- Brain-Like (Neuromorphic) Computing - Computerphile
- Photonic Neuromorphic Computing: The Future of AI? | ExplainingComputers
- Machine learning + neuroscience = biologically feasible computing | Benjamin Migliori | TEDxSanDiego