> What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. > I, as a laymen on the periphery

> What are the c-suite execs and specifically CTOs seeing that is worth adoption and investment? These are very smart people. > I, as a laymen on the periphery of this phenomenon, am acutely aware that LLMs are not useful in applications requiring accuracy. They are not useful in isolation. They can be very useful as part of a larger process, especially if they particular way that you're using them has a low error rate. (And given a particular task you can in fact measure the error rate, or how often the generated bullshit happens by chance to (not) be true.) Most processes that involve steps done by humans have built-in pieces to catch and correct errors, because humans also make errors. If the error rate of the LLM component is lower than the error rate of the human it's replacing, you're fine. If it's higher but the cost of catching and fixing the extra errors is lower than the cost of the replaced human, you're still fine. (The person who you just sent the way of the buggy whip manufactures might be less fine, but that's Somebody Else's Problem.)