recurrent neural networks
18 episodes mention this concept
lexfridmanNov 11, 2024Dario Amodei on AI Scaling Laws, AGI Timelines, Claude's Evolution, and the Imperative of AI Safety
TechnologyScaling LawsScaling HypothesisLarge Language Models (LLMs)Artificial General Intelligence (AGI)- lexfridmanMay 8, 2020
Ilya Sutskever on the Deep Learning Revolution, AI's Unity, and the Future of Intelligence
TechnologyDeep Learning RevolutionNeural NetworksBackpropagationHessian-free optimizer - lexfridmanMar 12, 2020
Biological vs. Artificial Neural Networks: Evolution, Understanding, and the Future of AI
ScienceBiological Neural NetworksArtificial Neural NetworksEvolutionary BiologyPhase Transition - lexfridmanFeb 29, 2020
John Hopfield on the Physics of Mind, Neurobiology, and the Future of AI
ScienceAssociative neural networksHopfield networksDeep learningEvolutionary biology - 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 - lexfridmanOct 6, 2019
Jeremy Howard on Deep Learning Frameworks: PyTorch, TensorFlow, fast.ai, and the Future with Swift
TechnologyDeep Learning FrameworksComputational GraphInteractive ComputationEager Execution (TF Eager) - lexfridmanJun 3, 2019
TensorFlow's Evolution: From Google Brain's Inception to a Global Open-Source ML Ecosystem
TechnologyDeep LearningTensorFlowOpen SourceGoogle Brain - lexfridmanJan 17, 2019
Deep Learning State of the Art (2019): Breakthroughs in NLP, Applied AI, and Reinforcement Learning
TechnologyDeep Learning State of the ArtNatural Language Processing (NLP)Encoder-Decoder ArchitectureRecurrent Neural Networks (RNNs) - lexfridmanOct 20, 2018
Yoshua Bengio on Bridging Biological and Artificial Intelligence: Challenges, Learning Paradigms, and Ethical AI
TechnologyBiological Neural NetworksArtificial Neural NetworksCredit AssignmentRecurrent Neural Networks (RNNs) - lexfridmanSep 27, 2016
Foundations and Challenges of Deep Learning: Compositionality, Generalization, and Optimization
TechnologyCurse of dimensionalityCompositional modelsDistributed representationsDepth (neural networks) - lexfridmanSep 27, 2016
Sequence to Sequence Deep Learning: From Smart Reply to Attention Mechanisms
TechnologySequence to Sequence Learning (Seq2Seq)Recurrent Neural Networks (RNNs)Encoder-Decoder ArchitectureAttention Mechanism - lexfridmanSep 27, 2016
Deep Learning for Natural Language Processing: Foundations, Word Vectors, and Recurrent Neural Networks
TechnologyNatural Language Processing (NLP)Deep LearningArtificial Intelligence (AI)Linguistics - 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
Reverse Engineering Human Intelligence for Advanced AI and AGI: A Cognitive Science Approach
ScienceArtificial General Intelligence (AGI)AI TechnologiesDeep LearningPattern Recognition - 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
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