My current outlook on LLMs is that they are some combination of bullshit to fool people who are looking to be fooled, and a modest but potentially very important improvement in the capacity to search large corpuses of text in response to uncontroversial natural-language queries and automatically summarize the results. Beyond this, I think they’re massively overhyped. The most aggressive hype is that they are an AGI development project - in other words, that they’re close to being conscious, generative minds on the same order as ours, which can do as wide a range of tasks as a human. This is clearly false. The more moderate hype is that they can do meaningful generative work within the domain where they were trained: written language content (which can of course be converted to and from audio language content pretty well). For instance, they might in some limited sense be able to internally represent the content of the language they're indexing and reproducing. This would necessarily entail the capacity for "regular expressions for natural language." I believe that even this much more limited characterization is false, but I am less confident in this case, and there are capacities they could demonstrate that would change my mind. Language learning software seems like a good example. It seems to me that if LLMs contain anything remotely like the capacity of regular expressions for natural language that take into account the semantic values of words, they should make it relatively easy to create a language learning app that is strictly better than the best existing automated resources for smartphone users trying to learn the basics of a new-to-them language.