The more I use Large Language Models (LLMs) like OpenAI's ChatGPT and Googel's Gemini, the more I find them to be incredibly helpful with exploring and synthensizing massive amounts of information that would take days, and in some cases years, to compile. What's amazing to me is that not only does it perform, compile, and summarize this research in seconds, but it can also analyze it all and make recommendations. Therefore, one of the transformational use cases for LLMs is to explore certain societal systems across the globe, weigh the pros and cons of each country's system, and help create an optimal system using the best ideas from each country. I decided to test this theory by exploring the global healthcare system, and as you'll witness below, the outcome is something astounding! In this page is a summary of my query using Gemini. It's not the exact query because it took several prompts to craft the information and recommendations. For ease and flow of ...