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

The future of AI tools lies in their ability to reason and process unstructured data, moving beyond traditional database-driven applications to more intuitive and flexible systems.

The fundamental work we're doing involves taking natural language and transforming it into structured output, which became possible in mid-2024.

AI will serve as a user interface for various applications, allowing users to query and aggregate information seamlessly across different systems, enhancing productivity, while agents will drive enterprise consumption and amplify human potential, transforming how users interact with technology.

AI models have become proficient at processing unstructured data, allowing them to generate helpful responses and take actions in customer support scenarios.

AI agents are often defined as systems that perform complex planning and interact with external systems, but this definition overlaps with many current language models.

AI agents can help product managers offload draining tasks, allowing them to focus on customer immersion, data analysis, and strategic thinking.

An agent is something a human can delegate tasks to, and we're aiming for agents to handle more complex tasks over time.

A modern knowledge retrieval stack for agents should understand user intent and data context, enabling complex queries to be processed efficiently.