Andrej Karpathy

OpenAI founding member. Tesla AI leader. Eureka Labs founder. Now Anthropic researcher. Karpathy keeps moving between three worlds: research, products, and education. That is why his name matters. He does not just build AI. He explains the age it is creating.

Karpathy joins Anthropic, the company behind Claude. He joins the pretraining team. Back to the deepest layer of model building. The place where frontier AI begins before the world ever sees the product.

Through talks, posts, and courses, Karpathy keeps pushing one idea: AI should not only automate work. It should help people learn faster. The classroom becomes part of the AI frontier.

Karpathy popularizes the phrase vibe coding. A new way of describing software creation with AI. Less typing every line. More steering the machine. The programmer starts becoming a director.

Karpathy is named in TIME’s 100 Most Influential People in AI. A researcher. A builder. A teacher. Now part of the public record of the AI age.

Eureka Labs introduces LLM101n, a course direction focused on learning how language models work. The mission is not just to use AI. It is to understand the machine beneath the magic.

Karpathy announces Eureka Labs, an AI-native education company. The idea is simple but massive: What if education was rebuilt with AI from the start?

OpenAI confirms Karpathy has departed. No dramatic public collapse. No loud war. Just another exit from the frontier.

Karpathy announces he is joining OpenAI again. The timing matters. ChatGPT has just changed the public imagination of AI. And Karpathy returns to the company at the center of it.

Karpathy starts publishing more educational AI content. Neural networks. Transformers. Language models. He turns complex systems into something people can actually understand.

After five years, Karpathy announces he is leaving Tesla. One of the biggest AI roles in the world ends. The next chapter is not immediately obvious.

Karpathy is named among MIT Technology Review’s Innovators Under 35. The recognition confirms what the AI world already knew. He was not just explaining the future. He was building parts of it.

At Tesla, he leads AI and computer vision work for Autopilot. The machine now has to understand lanes, signs, vehicles, pedestrians, shadows, weather, and human chaos. AI leaves the lab and enters traffic.

Karpathy joins Tesla as Director of AI. The problem changes. Not text. Not images in a dataset. Real roads. Real cars. Real consequences.

He officially works as a research scientist at OpenAI. Deep learning is still moving from research labs into the world. Karpathy is close to the center of it.

Karpathy becomes a founding member of OpenAI. The mission is huge. Artificial intelligence, built openly, safely, and at frontier scale.

His PhD focuses on connecting images and natural language. Not just seeing. Not just reading. Teaching machines to understand the bridge between both.

At Stanford, Karpathy helps build and teach CS231n. A deep learning course that becomes famous far beyond the classroom. For many AI engineers, this becomes one of the first doors into neural networks.

Karpathy starts his PhD at Stanford. Under Fei-Fei Li. Inside one of the most important computer vision environments in the world.

He completes his master’s degree. His work touches simulation and movement. Machines learning patterns from the physical world.

He completes his bachelor’s degree in Computer Science and Physics. The foundation is technical. But the future is already pointing toward machines that see, read, and learn.

Before AI fame, he starts uploading YouTube videos under badmephisto. Rubik’s Cube tutorials. Clear explanations. Simple teaching. The pattern begins early.

Karpathy moves to Toronto as a teenager. A new country. A new system. A new path into computers, physics, and intelligence.

Born in Bratislava, Czechoslovakia. Years later, he would become one of the clearest voices in modern AI. Not just building models. Teaching the world how they work.