Computer use represents a significant advancement for AI, allowing models to adapt to tools rather than requiring developers to create custom environments for each task.

We're still at the very beginning of how people understand how to use AI tools in their work, and there are many social opportunities that haven't been fully explored yet.

The recent advancements in AI, particularly in reducing costs, have opened up numerous use cases that are now feasible for implementation.

The most exciting innovations in AI are happening at the intersection of research and product development, with breakthroughs in reasoning and tool use driving progress.

While AI's current applications may not seem groundbreaking, they are already changing things behind the scenes, particularly in developer productivity and customer support.

Training AI models is an exciting field with much potential for progress, and it's essential to involve more people in shaping AI's future.

General-purpose technologies like supervised learning and generative AI are valuable for a wide range of applications, and there is still much work to be done in identifying and executing concrete use cases.

AI as a general-purpose technology presents numerous opportunities, and our focus should be on building concrete use cases to harness its potential effectively.

We're in an interesting time where the capabilities of AI models are far ahead of the products people have built. There's a huge opportunity for new innovations, especially as the cost of AI continues to decrease dramatically.