As we gather more data and build a larger platform, we can create more granular and personalized evaluations of AI models.

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

The most important aspect of AI development is not just the technology itself but how we can personalize these models to meet individual needs.

The evolution of AI will lead to more personalized and conversational systems that understand users better, enhancing user experience across various platforms.

The long-term differentiation in AI will not be in the base models but in how personalized and integrated they are into users' lives, providing context and utility that meets individual needs.

The potential for hyper-personalized education tools is significant, as AI can now provide tailored learning experiences for each student.

The future of AI may involve personal assistants that understand user preferences deeply, potentially acting as life coaches or advisors based on individual goals and needs.

The trend of personalized services will continue to grow, with AI providing customized experiences for everyone.

As AI becomes more integrated into various applications, we need to optimize for specific internal use cases, which may lead us to use other models if they better serve those needs.