MIT 6.S191: Language Models and New Frontiers Published 2024-06-03 Download video MP4 360p Recommendations 58:12 MIT Introduction to Deep Learning | 6.S191 57:33 MIT 6.S191: Reinforcement Learning 46:02 What is generative AI and how does it work? – The Turing Lectures with Mirella Lapata 1:09:14 Mapping GPT revealed something strange... 07:39 Necessity of complex numbers 3:04:32 CVPR #18546 - Denoising Diffusion Models: A Generative Learning Big Bang 54:24 26. Chernobyl — How It Happened 14:21 Your understanding of evolution is incomplete. Here's why 17:21 Photons and the loss of determinism 06:36 What is Retrieval-Augmented Generation (RAG)? 1:02:50 MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention 1:12:07 Lecture 2: Airplane Aerodynamics 30:49 Introduction to Poker Theory 55:15 MIT 6.S191 (2023): Convolutional Neural Networks 59:52 MIT 6.S191 (2023): Deep Generative Modeling 1:16:53 Yann Lecun | Objective-Driven AI: Towards AI systems that can learn, remember, reason, and plan 50:05 6. Monte Carlo Simulation 1:02:50 MIT 6.S191 (2023): Recurrent Neural Networks, Transformers, and Attention 1:16:07 Lecture 1: Introduction to Superposition Similar videos 1:08:47 MIT 6.S191 (2023): Deep Learning New Frontiers 53:29 MIT 6.S191 (2022): Deep Learning New Frontiers 44:36 MIT 6.S191 (2023): Text-to-Image Generation 44:43 MIT 6.S191: AI for Science 31:37 MIT 6.S191 (2018): Deep Learning Limitations and New Frontiers 27:13 MIT 6.S191 (2018): Sequence Modeling with Neural Networks 50:46 MIT 6.S191 (2021): Deep Learning New Frontiers 41:10 MIT 6.S191 (2020): Neurosymbolic AI 1:02:42 MIT 6.S191 (2023): The Future of Robot Learning 40:40 MIT 6.S191 (2020): Deep Generative Modeling 54:46 MIT 6.S191 (2022): Deep Generative Modeling 53:10 MIT 6.S191 (2023): The Modern Era of Statistics 43:22 MIT 6.S191: AI Bias and Fairness More results