| I agree with the general gist of the article that generative AI is bullshit for many use cases. But I'd rather point out why this comment is misguided for a very specific reason: it's a prime example of why we, as technologists, need to be careful with our terminology around some of these innovations. You are lumping together many different things in this post. For example: > With AI / ML we are getting self driving cars, robots (talking, listing, walking), agents etc. The "AI / ML" part of this sentence is telling. I am aware of exactly zero self-driving cars that are powered by LLMs (what the general public almost always means when they say "AI" these days). Self-driving cars are enabled by physical sensors in combination with various ML algorithms which have been around in some form for literally decades. I'm not an expert in this field, but my understanding is that what's actually happened in the last ~decade which has allowed them to flourish is the development of better _hardware_, that is, hardware that can run these algorithms fast enough, at a large enough scale, and still be small and cool enough to fit into a car. Ditto to some extent with your other examples, though maybe a general-purpose robot could be made better by interfacing with an LLM. I realize this may not be your intent, but by writing in this way, you are confusing the layperson into thinking that all of these innovations were enabled by ChatGPT-style "AI," when in fact some of them have nothing to do with that type of tech at all. I really wish we'd all be more honest, and not conflate transformers/LLMs with other "AI" algorithms. In fact, I think it'd be good if we stopped saying "AI" completely, though I realize this will never happen given that term's stickiness with the public at large. |