Oh yes, I don't think advanced math is required in any way. However, there is a difference in that researchers who have worked with these models for many years

Oh yes, I don't think advanced math is required in any way. However, there is a difference in that researchers who have worked with these models for many years (often including having done some of the math) have a very good intuitive understanding of these models. Once you have that, it's fine to be driven by gut feeling. Just like many engineers are driven by gut feeling that come from tacit knowledge through experience. What is dangerous is reading a 30 minute blog post and getting the illusion of having some kind of understanding, when in reality it can take years to develop that. It's like cloning the postgres Github repository, compiling it, running a few queries, and then saying you've built databases and being hired to become the "database expert" at some company, spreading wrong knowledge left and right. That's why the popularization of these quick immediate reward tutorials is dangerous. It takes time and effort to become knowledgable at something. Of course, many people are smart enough to know that these tutorials (or cloning the postgres repo) is just the first step on a longer learning journey, and in that case it's totally fine, but there are also many people who start thinking they are experts ready to work on research or production models after going through such things, not being aware of the many things they don't know [0] [0] https://upload.wikimedia.org/wikipedia/commons/thumb/4/46/Dunning%E2%80%93Kruger_Effect_01.svg/1024px-Dunning%E2%80%93Kruger_Effect_01.svg.png https://upload.wikimedia.org/wikipedia/commons/thumb/4/46/Du...