Discusses the challenges and future of neuromorphic computing, comparing digital computers and specialized hardware, such as SpiNNaker and NEST, while exploring the Human Brain Project's Neuromorphic Computing Platform.
Explores optimization methods like gradient descent and subgradients for training machine learning models, including advanced techniques like Adam optimization.
