At Scale, we power the data infrastructure for the entire AI industry, with every major large language model built on top of our data engine, and we partner with enterprises and governments to implement this technology for their unique challenges.

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.

The original insight behind founding Scale AI was the belief that as AI grows, the demand for data will increase exponentially, necessitating infrastructure to support that growth.

The story of Scale AI exemplifies a classic startup journey, where founders pivoted from an unrelated idea to successfully address the demand for data labeling in AI, particularly for self-driving cars.

Amplifying credit for ideas ensures that everyone receives recognition for their contributions, which is vital for a healthy company culture.

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.

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 scale Arena, we aim to capture a diverse user base across various industries, enhancing our ability to evaluate AI models effectively.

We believe agency is the most undervalued skill in the AI era, as it empowers individuals to build and innovate rather than just follow predefined paths.