Tesla's autopilot represents a real-world application of AI, where human supervision is still required, highlighting the importance of human-robot interaction in achieving safety and efficiency in autonomous driving.

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 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.

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

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

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.

The journey of Tesla's autopilot has been incredible, especially considering the challenges of computer vision and the skepticism surrounding it.

I'm super excited about AI; that's the reason why I started developing software.

Since joining Caltech in 2017, I have focused on using AI as a framework to address some of the hardest scientific problems that were previously considered impractical to solve.