8 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.
Ukrainian-Canadian computer scientist and PhD student of Geoffrey Hinton, who as first author of the AlexNet paper in 2012 demonstrated that deep convolutional networks trained on GPUs could dramatically outperform all other approaches on the ImageNet benchmark.
AI researcher who co-invented NeRF (Neural Radiance Fields) — a technique for synthesizing novel 3D views of scenes from 2D photographs using neural networks — one of the most influential computer vision papers of the last decade.
AI researcher working on computer vision and generative models — referenced in the Lenny's Podcast context in discussions of AI.
Digital artist and writer who documented early explorations with generative AI art models, producing work and commentary that influenced practitioners in the generative art community.
Chinese-American computer scientist at Stanford — creator of ImageNet (the massive labeled image dataset that enabled the deep learning revolution) — co-director of Stanford HAI — former Chief Scientist of AI/ML at Google Cloud — author of The Worlds I See.
AI researcher and educator known for creating CS231n (Convolutional Neural Networks for Visual Recognition) at Stanford — one of the most widely watched computer vision courses in the world — and for research on visual reasoning, image generation, and 3D scene understanding.
French-American computer scientist, Chief AI Scientist at Meta, and co-recipient of the Turing Award (2018) with Geoff Hinton and Yoshua Bengio, who invented convolutional neural networks (CNNs) and advocates for open-source AI.