This take is as bad as it is banal. LLM's are glorified autocomplete? Today I used an LLM to help me figure out an issue with a docker-compose file, what was wrong with my database connection, extract structured data from tens of millions of tokens in a web scraper I'm building, I talked to it about the design of my web scraper and how I should structure the data, and more. How is this like autocomplete at all? I ask natural language questions on a broad array of topics and get back mostly correct answers and that's just autocomplete?

I think a lot of people know a little bit about how LLM's are trained, and then decide that the little bit they know is all there is. Yes, next token prediction is part of the training process, no it's not the only part and it doesn't capture what makes LLMs useful.

This type of criticism - I noticed OP is an author - is like if summed up OP's novels as glorified mitosis. Yes, she started as a single cell and divided over and over and to some extent that is pretty responsible for what the OP is - but it's a bad description that fails to capture what's important.