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.

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.

After university, I initially felt confined in the family business, so I explored other projects before returning to work on ambitious engineering projects.

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

After Tesla, I worked on augmented and virtual reality to gain experience in different domains, although it was too early for practical applications at that time.

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

I pursued my interests in math and sciences relentlessly, eventually studying mechanical engineering and working in aerospace before joining Tesla.

After two decades in AI, I've witnessed the transition from AI winters to the rise of deep learning, which has opened up new possibilities in various applications.

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.