Investing in AI infrastructure and preventing capital lock-in will be crucial for countries to remain competitive in the future.

The expectation versus reality of AI adoption is often skewed; while expectations are high, the actual capabilities of current models may not meet those expectations, leading to a rapid adjustment in perception as models improve.

Many companies still lack an understanding of the advancements in AI technology, often repeating outdated beliefs about its limitations, which can hinder innovation.

The future of AI may involve new infrastructure and development tools that leverage the unique characteristics of AI models, differentiating them from traditional functions.

To advance AI, we need to focus on building infrastructure that can handle edge cases, similar to the journey of self-driving cars, which have taken years to develop due to the complexities involved.

The current AI landscape is rapidly evolving, with increasing investment leading to better outcomes, similar to the internet's growth in the 90s.

Despite expectations of a slowdown, AI advancements have continued to accelerate over the past three years.

I believe that the best way to approach AI investments is to focus on established companies that are already successful, rather than trying to find the next big thing in AI.

The infrastructure investment required for AI at a global scale is much larger than for other technologies, necessitating a collaborative effort to build it.