Andrej Karpathy, the influential 39-year-old Slovak-Canadian AI researcher and one of the original 11 co-founders of OpenAI, and former head of Tesla's AI division, announced on Tuesday, May 19 that he's joining rival lab Anthropic.
As Karpathy posted from his account on the social network X: "Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time."
Anthropic's current Head of Pretraining, Nicholas Joseph, also a former OpenAI alumnus, added more context to Karpathy's new role at Anthropic in a post of his own on X, writing: "Excited to welcome Andrej to the Pretraining team! He'll be building a team focused on using Claude to accelerate pretraining research itself. I can’t think of anyone better suited to do it — looking forward to what we build together!"
An Anthropic spokesperson confirmed to VentureBeat via email that Karpathy will be starting a team focused on using Claude, Anthropic's own, increasingly popular AI model, to accelerate pretraining research. This would put Anthropic further toward the overarching AI research goal of many around the world to develop "recursive self-improvement," that is, AI that is capable of training its successors or upgrading itself with increasingly lesser, or ultimately no human intervention.
The announcement came on the same day as the start of rival AI-focused tech firm Google's annual I/O developer conference in its headquarters city of Mountain View, California, when many new releases and announcements were expected.
Karpathy's storied history
Karpathy is widely known for spanning three parts of the modern AI boom: academic research, big-company deployment and online education.
His own website describes him as an AI researcher and educator who was a founding member of OpenAI, later served as Director of AI at Tesla, and helped create Stanford’s first deep learning course, CS231n.
OpenAI’s December 2015 launch announcement also listed Karpathy among the group’s founding members.
At Tesla, where he worked from 2017 to 2022, Karpathy led the computer vision team for Autopilot and says his team handled in-house data labeling, neural network training and deployment on Tesla’s custom inference chip.
He then returned to OpenAI from 2023 to 2024, where his website says he built a team focused on midtraining and synthetic data generation — experience directly relevant to Anthropic’s reported pretraining role.
Karpathy’s academic work began at Stanford, where he earned his PhD under Fei-Fei Li and focused on neural networks for computer vision, natural language processing and the intersection of the two.
He also interned at Google Brain, Google Research and DeepMind, according to his website. His education includes an MSc from the University of British Columbia and a BSc from the University of Toronto, where he double-majored in computer science and physics.
What will become of Karpathy's open source research and commitment to AI education?
Since leaving OpenAI in 2024, Karpathy has become one of AI’s most visible public educators, publishing technical and general-audience videos on large language models and neural networks.
He also launched Eureka Labs in July 2024 as an “AI-native” school; its first product, LLM101n, is described as an undergraduate-level course guiding students through training their own AI system.
Acting on his own as a free agent over the last two years, Karpathy has also helped push open source AI research forward with products and standards including autoresearch, an LLM-driven automated researcher that can run multiple hypothesis and experiments simultaneously, and the LLM Knowledge Base, an autonomous system of storing memory and context for AI agents in a kind of ever-growing library designed for them to access.
The big question is what becomes of these and Karpathy's open source AI efforts more generally as he joins Anthropic, a lab that has supported open source via the launch of its Model Context Protocol (MCP) technical standard, but which also famously has shipped primarily proprietary AI models and harnesses (such as Claude and Claude Code).
Based on the last statement in his announcement post on X — "I remain deeply passionate about education and plan to resume my work on it in time" — it appears that at least his contributions to the AI-native school effort will be paused as he digs in at Anthropic.