The competitive landscape for AI is rapidly evolving, similar to the early days of cloud computing, with new companies emerging to address specific needs, such as cybersecurity for large language models.

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

The AI landscape is much larger than previous technologies, and there will be many successful companies emerging, not just a few winners and losers.

The AI community in the U.S. may have lost sight of the importance of licensing models, focusing too much on monetizing initial breakthroughs instead of the broader implications.

As an application layer company, we must adapt to the rapidly changing landscape of AI model providers and ensure we are testing and integrating the best models available.

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

I believe that the best AI models will emerge from a fragmented landscape, where innovation is driven by competition and the ability to leverage resources effectively.

The AI stack consists of several layers, including hardware, infrastructure, and application layers, each with unique opportunities and challenges.

As AI technology evolves, the availability of powerful models may increase, potentially making them accessible for free in the future.