AI researcher and educator
Andrej Karpathy
Andrej Karpathy is an AI researcher and educator, a founding member of OpenAI, and a former director of AI at Tesla working on computer vision.
About Andrej Karpathy
Andrej Karpathy is an AI researcher and educator whose public teaching covers neural networks and large language models. His educational videos include both technical lessons on building models and introductions for a general audience.
He was a founding member and research scientist at OpenAI, led Tesla's AI and computer vision work from 2017 to 2022, and returned to OpenAI in 2023 to work on midtraining and synthetic data. During his PhD at Stanford, he designed and taught the CS231n course on deep learning for visual recognition.
Mentioned in our coverage
79 articles name Andrej Karpathy, excluding author credits.
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- John Jumper Leaves Google DeepMind for Anthropic: AlphaFold Nobel Laureate Joins Claude (June 2026) →
John Jumper — who shared the 2024 Nobel Prize in Chemistry with Demis Hassabis for AlphaFold — announced on June 19, 2026 that he is leaving Google DeepMind for Anthropic. Here is who Jumper is, what he built, and why a sitting Nobel laureate picking Claude's lab over Google's matters.
- Microsoft Presidio: Open-Source PII Detection and De-Identification Guide →
Presidio is Microsoft's open-source SDK for finding and redacting credit cards, SSNs, names, PHI, and custom entities—via regex, NER, and checksums. Run in Python, Docker, or Kubernetes before data hits LLMs or logs.
- Agent Skills Whitepaper: Kaggle Guide to Procedural Memory for AI Agents →
A 62-page whitepaper explains why Agent Skills became the cross-platform standard: procedural memory, on-demand loading vs context rot, evaluation under co-load, and why one agent + 100 skills beats 100 subagents for many workflows.
- Matt Pocock Skills v1.0: 63% Fewer Tokens With Progressive Disclosure →
Total TypeScript author Matt Pocock released Skills repo v1.0: short summaries load first, full guides on demand, 63% lower token costs. New /codebase-design and /ask-matt skills—plus an open question on user vs model invocable tiers.
- Anthropic Research: Domain Expertise Beats Coding Background in Agentic Programming (2026) →
In 7 months of observing 235,000 users, Anthropic found that management occupations outperform software engineers on verified coding success, that "fixing broken code" dropped from 33% to 19% of sessions, and that the gap between technical and non-technical users has not widened. The implications for who can build software are profound.
- Open Knowledge Format (OKF): Google's Standard for AI Agent Memory →