As AI systems become more capable and integrated into our lives, the question of whether they have experiences will become increasingly important, influencing how we relate to them.

The transition to an era of experience in AI will require careful consideration of the consequences and the decisions we make.

As AI systems evolve, they will need to learn from human interactions to improve personalization and effectiveness, which will be crucial for future applications.

We are also exploring AI's ability to learn quickly from prior experiences, similar to how humans adapt to new games or tasks.

Human data might provide a head start for AI, but sustainable progress will depend on reinforcement learning as a continuous source of experience.

We're entering a new phase of the AI platform shift, where decades of research are becoming reality for people globally.

AI is becoming an extension of ourselves, learning from our interactions over time to help us achieve our best.

We are at an inflection point in redefining how we interact with digital information through AI systems, which may evolve to understand our context and goals in a more personalized way.

A small amount of human data can enable AI systems to generate their own goals, allowing for significant learning from experience.