Stanford Seminar - Enabling NLP, Machine Learning, & Few-Shot Learning using Associative Processing Published 2017-11-09 Download video MP4 360p Recommendations 1:15:46 Deep Learning Bootcamp: Kaiming He 09:11 Transformers, explained: Understand the model behind GPT, BERT, and T5 1:29:10 Andrew Ng: Deep Learning, Education, and Real-World AI | Lex Fridman Podcast #73 3:33:03 Deep Learning: A Crash Course (2018) | SIGGRAPH Courses 31:33 The Oldest Unsolved Problem in Math 17:03 Beating Moore's Law: This photonic computer is 10X faster than NVIDIA GPUs using 90% less energy 33:45 Why It Was Almost Impossible to Make the Blue LED 10:31 The U-Net (actually) explained in 10 minutes 1:20:28 Stanford EE364A Convex Optimization I Stephen Boyd I 2023 I Lecture 3 31:22 The Trillion Dollar Equation 48:55 Jensen Huang — NVIDIA's CEO on the Next Generation of AI and MLOps 51:15 Generative AI in Drug Discovery and Pharma, with Insilico Medicine (CXOTalk #782) 55:52 Stanford Seminar - Robot Skill Acquisition: Policy Representation and Data Generation 21:49 Nuclear waste is not the problem you've been made to believe it is 31:12 How One Line in the Oldest Math Text Hinted at Hidden Universes 59:34 There is No Algorithm for Truth - with Tom Scott 1:14:26 Interpretability vs. Explainability in Machine Learning 14:36 How Microchips Are Made - Manufacturing of a Semiconductor Similar videos 1:32:27 Stanford Seminar - Enabling NLP, Machine Learning, & Few-Shot Learning using Associative P 1:14:50 Stanford CS224N NLP with Deep Learning | Spring 2022 | Guest Lecture: Scaling Language Models 05:29 Natural Language Processing In 5 Minutes | What Is NLP And How Does It Work? | Simplilearn 33:02 Practical Few-Shot Learning 56:44 Stanford Seminar - Petascale Deep Learning on a Single Chip 14:27 Few-Shot Natural Language Generation by Rewriting Templates | NLP Journal Club 1:17:38 Stanford CS330: Deep Multi-task & Meta Learning | 2020 | Lecture 3 - Transfer & Meta-Learning 58:24 Machine Learning Everywhere feat. Pete Warden | Stanford MLSys Seminar Episode 31 1:05:43 Stanford CS25: V1 I Self Attention and Non-parametric transformers (NPTs) 1:17:48 Stanford CS330 Deep Multi-Task & Meta Learning - Percy Liang Guest Lecture I 2022 I Lecture 17 57:22 MedAI #88: Distilling Step-by-Step! Outperforming LLMs with Smaller Model Sizes | Cheng-Yu Hsieh 1:04:16 Stanford CS330: Deep Multi-task & Meta Learning I 2021 I Lecture 15 10:53 CIS 5700 Zero-Shot Learning via Simultaneous Generating and Learning 1:21:24 Lecture 10: Neural Machine Translation and Models with Attention 1:08:06 Deep Learning Basics: Introduction and Overview 04:50 Jenzen Christoph: Introduction to spiking associative memories More results