Machine Learning Street Talk (MLST)
Unlocking the Brain's Mysteries: Chris Eliasmith on Spiking Neural Networks and the Future of Human-Machine Interac...
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Apr 10 2023 1h 49m
Chapter 1 6 mins
Intro to ChrisChapter 2 7 mins
The Advantages of Continuous Representation in Biologically Plausible Neural NetworksChapter 3 5 mins
Legendre Memory Unit and Spatial Semantic PointerChapter 4 4 mins
Exploring the Relevance of Large Contexts and Data in Language ModelsChapter 5 5 mins
Spatial Semantic Pointers and Continuous Representations in Vector SpacesChapter 6 6 mins
Understanding the Intuition Behind Auto ConvolutionChapter 7 6 mins
Exploring Abstractions and the Continuity in Cognitive RepresentationsChapter 8 5 mins
Exploring Compression, Sparsity, and Representations in the BrainChapter 9 8 mins
Addressing Continual Learning and Real-World Interactions in Brain ModelsChapter 10 4 mins
Robust Generalization in Large Language Models and the Role of Priors in Learning Emergentist FrameworksChapter 11 3 mins
Chip designChapter 12 9 mins
Debating the Computational Power of Neural Networks and RecursionChapter 13 9 mins
Understanding Spiking Neural Networks and Their Applications in a Perfect WorldChapter 14 2 mins
Limits of empirical learningChapter 15 15 mins
Philosophy of mind, consciousness etcChapter 16 3 mins
Future of human machine interactionChapter 17 4 mins
Future research and advice to young researchers