> What's the point of training bigger language models when you can't even serve (inference) them economically?<p>They're built to impress people and push the boundaries of can be done with ML. Economies, accessibility, scale - those things come later.
The number of parameters correlates with the believability of the result being from an intelligent human being.<p>Easy to inference/small model = poor results