My interest in computer science was influenced by the realization that AI could solve complex problems, leading me to shift from studying physics to focusing on AI and technology.

At Tesla, I became very interested in AI applications, particularly in autopilot technology, which led me to explore AI's potential in different domains.

When I was 18, I identified AI as the top problem I wanted to contribute to, and I now believe I can meaningfully work towards solving it.

Growing up, I was fascinated by solving math problems and understanding how machines work, which laid the groundwork for my interest in AI and its practical applications.

We initially explored automating mechanical engineering but pivoted to focus on programming, recognizing the potential for AI in that space.

I have always been fascinated by intelligence and the potential of AI to help us understand the universe and answer fundamental questions about reality.

We've applied AI to various tasks, including chip design and scheduling, making processes more efficient, but it remains constrained to domains that are provably correct, like mathematics and coding.

My methodology involves analyzing current research to predict potential uses of AI, especially as tools become more accessible through cloud services.

At 19 years old, I dropped out of MIT to launch Scale, driven by the understanding that progress in AI relies on data availability, not just algorithms.