convolutional neural networks (cnns)
17 episodes mention this concept
lexfridmanSep 20, 2021Jay McClelland on Neural Networks, the Emergence of Cognition, and the Mind-Brain Connection
NeuroscienceNeural Networks (artificial and biological)Cognitive PsychologyParallel Distributed Processing (PDP)Backpropagation- lexfridmanDec 2, 2020
DeepMind's AlphaFold 2: Solving Protein Folding and Its Profound Impact on AI and Life Sciences
ScienceProtein FoldingAlphaFold 2Structural BiologyX-ray Crystallography - lexfridmanMay 10, 2020
The Unification of AI Modalities: Vision, Language, and Reinforcement Learning, and the Elusive Definition of 'Hardness' in AI
TechnologyDeep LearningComputer VisionNatural Language Processing (NLP)Reinforcement Learning (RL) - lexfridmanMay 8, 2020
Ilya Sutskever on the Deep Learning Revolution, AI's Unity, and the Future of Intelligence
TechnologyDeep Learning RevolutionNeural NetworksBackpropagationHessian-free optimizer - lexfridmanJan 23, 2020
Efficient Computing for Deep Learning, Robotics, and AI: Bridging the Energy Gap
TechnologyEnergy-efficient computingHigh-performance systemsDeep neural networks (DNNs)Edge computing - lexfridmanJan 10, 2020
Deep Learning: State of the Art in 2020, Key Advancements, Limitations, and Future Research
TechnologyDeep LearningNeural NetworksPerceptron (single-layer, multi-layer)Backpropagation - lexfridmanOct 8, 2019
The Genesis and Evolution of Keras: From Niche RNN Tool to TensorFlow's Core API
TechnologyKerasTensorFlowTheanoCaffe - lexfridmanSep 27, 2016
The Evolution, Architecture, and Impact of Convolutional Neural Networks in Computer Vision
TechnologyDeep LearningComputer VisionNeural NetworksConvolutional Neural Networks (CNNs) - lexfridmanSep 27, 2016
Foundations of Unsupervised Deep Learning: Sparse Coding, Autoencoders, and Generative Models
TechnologyUnsupervised LearningSupervised LearningDeep LearningHierarchical Representations - lexfridman
MIT 6.S094: Deep Learning Architectures and Semantic Segmentation in Computer Vision
TechnologyComputer VisionDeep LearningNeural NetworksSupervised Learning - lexfridman
Deep Learning for Human Sensing in Autonomous Vehicles: Data, Annotation, and Human-Centered AI
TechnologyDeep LearningComputer VisionHuman SensingReal-world Data Collection - lexfridman
Deep Learning for Human-Centered Semi-Autonomous Vehicles: Driver Monitoring and Trust
TechnologyHuman-centered AISemi-autonomous vehiclesFully-autonomous vehiclesDriver monitoring systems - lexfridman
MIT 6.S094: Deep Learning for Self-Driving Cars - Foundations, Challenges, and Human-Centered AI
TechnologyDeep LearningSelf-Driving CarsArtificial Intelligence (AI)Reinforcement Learning - lexfridman
MIT 6.S094: Introduction to Deep Learning, Neural Networks, and Self-Driving Cars
TechnologyDeep LearningDeep Neural NetworksSelf-Driving CarsDeep Reinforcement Learning - lexfridman
Recurrent Neural Networks and the Fundamentals of Backpropagation for Steering Through Time
TechnologyRecurrent Neural Networks (RNNs)BackpropagationVanishing GradientsExploding Gradients - lexfridman
Reverse Engineering Human Intelligence for Advanced AI and AGI: A Cognitive Science Approach
ScienceArtificial General Intelligence (AGI)AI TechnologiesDeep LearningPattern Recognition - lexfridman
Jim Keller on the Enduring Relevance of Moore's Law and the Future of Computation
TechnologyMoore's Law (Gordon Moore's original definition)Operational Moore's Law (performance increase)Transistor countShrink factor
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