GPT-4 is powerful over a diverse set of tasks. They use it to build a model which is better for a narrow sub-task. Pretty sure the model is sub-optimal to GPT-4 for everything else.
Not sure if this is obvious. But its incorrect to ditch on GPT-4. The paper uses self-instruct on GPT-4 to generate the training data on which it is fine-tuned. This paper would not exist without GPT-4. Although they claim GPT-4 can be replaced by any LLM, I'm sure the results would be nowhere as good, and so they stuck with GPT-4.
This! The best resource I've found to explain transformers, that made them clear to me. I wish all deep learning papers were written like this, using pseudocode.
FWIW I've been told similar by Costco too, so Amazon isn't unique in this respect. My guess is that it adds some friction to the process. Refunding money is a purely digital activity, while refunding requires to you go and ship it, wait for the new item to arrive, etc, so you won't do it unless the savings are worth the time investment.