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

We should focus on the spectacular changes AI can bring to solve insurmountable problems like climate change and resource management.

To stay top of mind, we focus on delivering effective AI solutions that solve real problems rather than just creating hype around AI.

Focusing on narrow problems and becoming the best at solving them is currently a successful strategy for AI companies, as seen with examples like Quandry and Expo.

The next priority for us is AI, as the world is being completely overhauled by it, and we need to create our own AI innovations that align with our strengths in front-end and design.

Since starting Scale, we've been at the forefront of every major development in AI, working with companies like General Motors and Toyota on autonomous vehicle programs and collaborating with the US government on pioneering AI initiatives.

We are committed to actually trying to solve the real problems associated with AI safety, including misuse and misalignment risks.

The initial business of Scale AI focused on generating data for self-driving car companies, which required us to stay ahead of AI trends.

To advance AI, we need to focus on building infrastructure that can handle edge cases, similar to the journey of self-driving cars, which have taken years to develop due to the complexities involved.