Data-centric token-guessing will be outperformed by more complex architectures, LLMs are too inefficient and their hardware requirements are disproportionate

Data-centric token-guessing will be outperformed by more complex architectures, LLMs are too inefficient and their hardware requirements are disproportionate for the utility. Building a sand castle of "LLM apis" that rely on plugging their deficiences is a fundamentally bad decision that hides the underlying waste of resources. What will be great if the input data it was fed was more structured and labeled like images: imaging a "Book, 17th century, reliablity:54%, contains geographic errors". Instead this "attention is all you need" approach treats garbage data equal to top material.