As a natural language processing (NLP) enthusiast, the past few months have been incredibly exhilarating, with both the release of ChatGPT and now GPT4.While it's easy to get excited about the potential of these models, we need to remember that the volume of data and number of model parameters aren't the only things that matter. The quality and relevance of the training data is equally important.This is especially true in investing, where decisions have an immediate impact on profit and loss (P&L). Using LLMs to make investment decisions can be incredibly powerful, but only if the models are trained on high-quality data that is relevant to the specific investment strategies being employed. This can also lead to more cost-efficient model training.So while we continue to explore the possibilities of LLMs, let's also prioritize the quality and relevance of our training data. It's the key to unlocking the full potential of these powerful tools.What are your thoughts on this topic?Check out the latest comments from #RavenPack's CEO, Armando Gonzalez.#investing #training #data #nlp #ravenpack