Language Models are Few-Shot Learners

Alec Radford is a researcher and a co-author of the GPT-4 Technical Report. His GitHub profile links to his personal website at newmu.github.io.

Research scientist focused on deep learning and large language models. He has worked at Google DeepMind, Meta, OpenAI, and Google Brain, and earned a PhD from UMass Amherst.

OpenAI engineer focused on GPU systems and large-model infrastructure, with public contributions to GPT-4 and earlier OpenAI research on efficient GPU kernels and code models.

Sandhini Agarwal is a researcher at OpenAI. Her OpenReview profile lists her as a researcher at OpenAI (2020–present) and an undergraduate student at Stanford University (2015–2019).

Co-founder and head of policy at Anthropic. He previously served as policy director at OpenAI, worked as a technology journalist, and writes the Import AI newsletter.

Software engineer at OpenAI focused on inference. Previously studied computer science at Princeton University.

Nick Ryder is VP of Research, Foundations at OpenAI and a contributor to GPT-4. He previously studied mathematics at UC Berkeley and Rice University.

Engineer and founder who previously worked at OpenAI, Palantir, and Lyft and now builds the AI search startup Basalt. He publishes public writing on AI products and software on his personal site.

Sam McCandlish is a research scientist at OpenAI. His public homepage highlights work on scaling laws, optimization, and reinforcement learning, and links to code and publications.

Researcher and engineer focused on robust and aligned AI at Anthropic. He previously worked at OpenAI and Google Brain, and was the lead author of the GPT-3 paper.

Researcher working on large language model interpretability at Anthropic. He previously worked on scaling laws at OpenAI, earlier did ML engineering at Beehive AI, and completed a PhD in physics at Stanford.

Alignment researcher at OpenAI working on making AI understandable to and aligned with human values.

Research scientist at OpenAI focused on scaling reinforcement learning and self-improving models; previously worked on deep learning for gaming at Nvidia.

Research scientist at OpenAI interested in AI safety, alignment, governance, and technical safety.

Computer scientist and AI researcher who co-founded OpenAI and served as its chief scientist.

Research scientist and engineer working on large-scale machine learning. His personal site highlights contributions to GPT-3, GitHub Copilot, and Stable Diffusion.

Research scientist at OpenAI focused on generative models and unsupervised learning. He studied computers, mathematics, and physics at MIT and has contributed to models including GPT-3, Jukebox, and DALL·E.

Researcher at OpenAI and co-creator of DALL-E who works on multimodal generative models and image generation.

Member of technical staff at OpenAI whose public profile notes leadership of the MT+MX team from 2020 to 2025 after earlier engineering work at Google.

Ariel Herbert-Voss is a computer scientist whose public homepage notes previous work on AI safety and special projects at OpenAI, along with later work on digital humans and universal basic income initiatives.

Researcher at Anthropic focused on scalable oversight and AI safety. He previously worked at OpenAI on language models, led the GPT-3 paper, and earlier studied physics and machine learning.

CEO and co-founder of Anthropic. Before Anthropic, he served as vice president of research at OpenAI.

Researcher at OpenAI working on language model training and evaluation, and co-author of the GPT-4 Technical Report.

Researcher and engineer at OpenAI, and a co-author of the GPT-4 Technical Report.