9 thinkers, books, and ideas connected to this field.
American AI researcher who was a key contributor at OpenAI — co-authoring the foundational GPT and CLIP papers — and is one of the most influential researchers in the development of large language models and multimodal AI.
British-American AI researcher who co-founded Google Brain, served as Chief Scientist of Baidu, co-founded Coursera, and created deeplearning.ai — educating millions in machine learning — considered one of the most influential figures in democratizing AI knowledge.
AI and robotics researcher — who has worked on embodied AI and machine learning systems — referenced in discussions of AI progress.
German computer scientist and Google Brain researcher, co-author of 'Attention Is All You Need', who proposed the core insight that attention mechanisms alone could replace recurrent networks entirely.
A machine learning textbook or resource referenced in the Lenny's Podcast context.
American computer scientist who co-developed the backpropagation algorithm and developed the REINFORCE algorithm — the foundation of policy gradient methods in reinforcement learning.
AI researcher — who has worked on large language model architectures and scaling — referenced in AI development discussions.
British-American computer scientist at UC Berkeley, co-author of the standard AI textbook (Artificial Intelligence: A Modern Approach), and author of Human Compatible — which argues for a new paradigm of AI development based on uncertainty about human preferences.
OpenAI's 2020 language model — the first AI system to demonstrate convincingly that scaling transformer models produces qualitative leaps in capability, triggering the modern AI race.