You had a chance to prove my assumption wrong by writing this same exact comment without all the snark. At the end of the day if you're just unmoved by the imp

You had a chance to prove my assumption wrong by writing this same exact comment without all the snark. At the end of the day if you're just unmoved by the implications that an ML model went from a bag of tokens to a structured, explained chain of thought, and a final response on an unknown task with rewards defined in natural english (!) and intentional ambiguity most humans wouldn't even try to confront... there's not much conversation to be had. I think the rest of us (including your colleagues) will continue to build on these models, and like most advancements there'll be a vocal crowd insisting the car isn't useful because it can't be fed with grass. > not in recommendations You didn't have to say that after complaining ChatGPT's web interface didn't give both us the same reply (most people in ML understand how temperature relates to LLM output) _ By the way, if making your own personal music recommender seems like "magical thinking", maybe you're a little lost on which parts of Spotify's recommender systems are complex due to scale: if Spotify only needed to make song selection work for one person at a time, they'd have a lot more leeway in architecture. In fact, when the problem was flipped and they were scaling humans attaching their recommendations to songs, they built on OpenAI: https://newsroom.spotify.com/2023-02-22/spotify-debuts-a-new-ai-dj-right-in-your-pocket/ https://newsroom.spotify.com/2023-02-22/spotify-debuts-a-new... Not unexpected when you're a founding organizer of the "NLP 4 Music and Audio Forum".