I'll admit it's something of a bold label, but there is truth in it. Before our rule engine has a chance to touch the document, we run several pre-processing s

I'll admit it's something of a bold label, but there is truth in it. Before our rule engine has a chance to touch the document, we run several pre-processing steps that imbue semantic meaning to the words it reads. > LLMs have completely overshadowed ML NLP methods from 10 years ago, and they themselves replaced decades statistical NLP work, which also replaced another few decades of symbolic grammar-based NLP work. This is a drastic oversimplification. I'll admit that transformer-based approaches are indeed quite prevalent, but I do not believe that "LLMs" in the conventional sense are "replacing" a significant fraction of NLP research. I appreciate your skepticism and attention to detail.