BI NMA 05: NLP and Generative Models Panel

BI NMA 05: NLP and Generative Models Panel This is the 5th in a series of panel discussions in collaboration with Neuromatch Academy, the online computational neuroscience summer school. This is the 2nd of 3 in the deep learning series. In this episode, the panelists discuss their experiences “doing more with fewer parameters: Convnets, RNNs, attention & transformers, generative models (VAEs & GANs). Panelists Brad Wyble. @bradpwyble. Kyunghyun Cho. @kchonyc. He He. @hhexiy. João Sedoc. @JoaoSedoc. The other panels: First panel, about model fitting, GLMs/machine learning, dimensionality reduction, and deep learning. Second panel, about linear systems, real neurons, and dynamic networks. Third panel, about stochastic processes, including Bayes, decision-making, optimal control, reinforcement learning, and causality. Fourth panel, about some basics in deep learning, including Linear deep learning, Pytorch, multi-layer-perceptrons, optimization, & regularization. Sixth panel, about advanced topics in deep learning: unsupervised & self-supervised learning, reinforcement learning, continual learning/causality.

Om Podcasten

Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.