Lecture 20 - Efficient Transformers | MIT 6.S965 Published 2022-11-24 Download video MP4 360p Download video MP4 720p Recommendations 1:17:05 EfficientML.ai Lecture 1 - Introduction (MIT 6.5940, Fall 2023) 58:58 FlashAttention - Tri Dao | Stanford MLSys #67 1:02:50 MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention 19:46 Quantization vs Pruning vs Distillation: Optimizing NNs for Inference 2:05:54 1. Introduction to 'The Society of Mind' 47:47 MedAI #54: FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness | Tri Dao 1:02:17 RWKV: Reinventing RNNs for the Transformer Era (Paper Explained) 49:53 How a Transformer works at inference vs training time 1:08:47 MIT 6.S191: Deep Learning New Frontiers 2:14:29 How ChatGPT works - From Transformers to Reinforcement Learning with Human Feedback (RLHF) 1:16:55 EfficientML.ai Lecture 1 - Introduction (MIT 6.5940, Fall 2023, Zoom recording) 1:21:46 Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 10 - Transformers and Pretraining 1:33:13 Efficient 3D Perception for Autonomous Vehicles (Zhijian Liu) 1:25:31 EfficientML.ai lecture 1:22:38 CS480/680 Lecture 19: Attention and Transformer Networks 1:18:36 Instruction finetuning and RLHF lecture (NYU CSCI 2590) 1:09:54 CS231n Winter 2016: Lecture 10: Recurrent Neural Networks, Image Captioning, LSTM 1:45:27 Fundamentals of Transformer Commissioning and Maintenance Testing 26:34 Flash Attention Similar videos 1:11:43 Lecture 05 - Quantization (Part I) | MIT 6.S965 1:37:41 Lecture 19 - Efficient Video Understanding and Generative Models | MIT 6.S965 1:07:26 Lecture 10 - Knowledge Distillation | MIT 6.S965 1:01:32 Lecture 02 - Basics of Neural Networks | MIT 6.S965 1:07:07 Lecture 03 - Pruning and Sparsity (Part I) | MIT 6.S965 1:04:01 Lecture 07 - Neural Architecture Search (Part I) | MIT 6.S965 1:15:56 Lecture 15 - On-Device Training and Transfer Learning (Part I) | MIT 6.S965 12:48 Lecture 24 - Course Summary | MIT 6.S965 38:39 Lecture 21 - Basics of Quantum Computing | MIT 6.S965 11:44 Efficient Transformers: A Survey 1:06:39 Lecture 11 - MCUNet: Tiny Neural Network Design for Microcontrollers | MIT 6.S965 1:07:46 Lecture 04 - Pruning and Sparsity (Part II) | MIT 6.S965 1:01:06 Lecture 13 - Distributed Training and Gradient Compression (Part I) | MIT 6.S965 1:10:54 Lecture 06 - Quantization (Part II) | MIT 6.S965 More results