We partner with the largest satellite companies to source high-quality imagery and collect lidar data, which is crucial for improving our algorithms and expanding our model globally.

American companies had to adapt quickly to scale AI inference after their previous providers' servers failed, leading to significant growth for Fireworks in capturing inference metrics.

At Fireworks, we manage the complexity of AI application scaling by utilizing a virtual cloud infrastructure that ensures high quality and reliability in GPU selection.

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.

Scale AI acts as a refinery for data, converting large amounts of raw data into high-quality data that powers algorithms for various applications.

We surprised the scientific community by releasing an AI model that was not only accurate but also tens of thousands of times faster than traditional weather forecasting methods, which were thought to be irreplaceable by AI for over a decade.

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

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

We are forming a consortium for autonomy to integrate various technologies and improve decision-making in combat situations.