Classic NLP tasks (eg classification, summarization, translation, etc) just work with GPT-4 mostly. It is probably still possible to beat GPT-4 with a fine-tuned model, but it isn't easy. The open source LLMs are pretty good too at the classical NLP tasks, but still need to be fine-tuned in many cases. However I bet eventually open source LLMs will get close to GPT-4. What this means is that at a minimum, LLMs will be used to replace "legacy" algorithms for classical NLP tasks to boost accuracy. Also more people who have a problem that can be solved/improved with ML, but currently is cost/time/expertise prohibitive will use LLMs.