| This problem applies almost universally as far as I can tell. If you are knowledgeable on a subject matter you're asking for help with, the LLM can be guided to value. This means you do have to throw out bad or flat out wrong output regularly. This becomes a problem when you have no prior experience in a domain. For example reviewing legal contracts about a real estate transaction. If you aren't familiar enough with the workflow and details of steps you can't provide critique and follow-on guidance. However, the response still stands before you, and it can be tempting to glom onto it. This is not all that different from the current experience with search engines, though. Where if you're trying to get an answer to a question, you may wade through and even initially accept answers from websites that are completely wrong. For example, products to apply to the foundation of an old basement. Some sites will recommend products that are not good at all, but do so because the content owners get associate compensation for it. The difference is that LLM responses appear less biased (no associate links, no SEO keyword targeting), but are still wrong. All that said, sometimes LLMs just crush it when details don't matter. For example, building a simple cross-platform pyqt-based application. Search engine results can not do this. Wheras, at least for rapid prototyping, GPT is very, very good. |