Doesn't the high quantity of boilerplate pollute the context, thereby making agents less useful over time? i.e. go is not "token efficient"
Doesn't the high quantity of boilerplate pollute the context, thereby making agents less useful over time? i.e. go is not "token efficient"
Language models need redundancy (as informing structure). Not surprising, since they're trained on human language. It's hard to train a model on a language with a high entropy. I haven't tried it, but I think LLMs would perform quite badly on languages such as APL, where structure and meaning are closely intertwined.