I believe I could build the data infrastructure platform to support the entire AI ecosystem.

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 demand for data centers is increasing as more people want to use AI models, and we need to ensure we have enough infrastructure to support this demand.

The AI industry faces significant challenges, and companies often outsource large-scale problems to specialized firms like Scale AI to build infrastructure.

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

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.

We realized that scaling laws in AI showed predictable improvements with increased data and compute, which encouraged us to focus on building a product for knowledge work as AI matured.

We're building a comprehensive data stack that includes tools like Azure Cosmos DB and Azure Databricks to enhance data accessibility and integration for AI applications.

We realized that to scale our models, we needed to transition from pure research to a business model that could sustain the investment required for large AI models.