Stanford CS25: V4 I Demystifying Mixtral of Experts Published 2024-05-16 Download video MP4 360p Download video MP4 720p Recommendations 1:09:14 Mapping GPT revealed something strange... 20:18 Why Does Diffusion Work Better than Auto-Regression? 12:03 NEW Mixtral 8x22b Tested - Mistral's New Flagship MoE Open-Source Model 1:16:21 Stanford CS25: V4 I Aligning Open Language Models 24:07 Transformers, explained: Understand the model behind ChatGPT 45:46 Geoffrey Hinton | On working with Ilya, choosing problems, and the power of intuition 1:17:07 Stanford CS25: V4 I Jason Wei & Hyung Won Chung of OpenAI 44:54 Max Tegmark | On superhuman AI, future architectures, and the meaning of human existence 06:34 When Computers Write Proofs, What's the Point of Mathematicians? 49:47 “What's wrong with LLMs and what we should be building instead” - Tom Dietterich - #VSCF2023 28:17 Spectral Graph Theory For Dummies 1:19:56 Stanford CS25: V4 I Transformers that Transform Well Enough to Support Near-Shallow Architectures 1:17:29 Stanford CS25: V4 I Overview of Transformers 1:20:34 Machine Learning 1 - Linear Classifiers, SGD | Stanford CS221: AI (Autumn 2019) 23:45 Microsoft Promises a 'Whale' for GPT-5, Anthropic Delves Inside a Model’s Mind and Altman Stumbles 06:36 What is Retrieval-Augmented Generation (RAG)? 1:05:54 Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 1 - Introduction - Emma Brunskill 46:02 What is generative AI and how does it work? – The Turing Lectures with Mirella Lapata 12:33 Mistral 8x7B Part 1- So What is a Mixture of Experts Model? 59:52 MIT 6.S191: Deep Generative Modeling Similar videos 1:04:32 [한글자막] Stanford CS25： V4 I Demystifying Mixtral of Experts 03:38 George Hotz - GPT-4's real architecture is a 220B parameter mixture model with 8 sets of weights More results