Your article on the limitations and strengths of Large Language Models (LLMs) in special fields like finance really caught my eye because it was very useful. You pointed out substantial weaknesses in how AI currently works, especially when it seems smart and informed but it's not really. After pointing out the problems, you came up with a great plan to make them better by mixing in ontologies and knowledge graphs. Next we engage in an intense examination of how to strengthen drastically your financial area by starting with building a strong ontology using certain tools, for instance, Owlready2.

You discussed making sure this framework is both substantial and intelligent and informed, filled with data that makes sense and rules that show how complicated ideas connect well together. To make sure everyone understands, even those who don't code, you suggested using Controlled Natural Language (CNL) for writing material down and looking material up. This plan isn't only for making things more accurate -- it's also about keeping things consistent, easy to explain, and able to work together across different financial systems.

There can possibly be gratification in your knowing that by putting your plan into action, the gap between the smart people and the financial wizards could shrink.

If you’re interested, feel free to check out my stories too!