To trivial questions no, but to more complex questions humans actually does go "hmm, let me think". ChatGPT doesn't do that, it just blurts out the first thing that gets into its head regardless if the question is trivial or extremely complex.
To trivial questions no, but to more complex questions humans actually does go "hmm, let me think". ChatGPT doesn't do that, it just blurts out the first thing that gets into its head regardless if the question is trivial or extremely complex.
It can if you give it the option. My own openai chatbot prompts to either respond or to ponder by stating a question or considering a related idea. It infrequently will decide to ponder for one to about a dozen times as it restates an idea to itself in various forms, which gets recorded into the growing conversational prompt.
Elsewhere in the thread, someone mentions it always uses the same amount of time. In my estimation, it will spend longer on introspective or recursive prompts. Easier to get it ranting absurdities using those as well.
It's always the craziest chatter when the request takes a couple minutes to get back to me.
For most of our "hmm, let me think"'s I'm not sure what we do is significantly more complicated than that. We just get to hide the inner monologue.
Maybe these language models could be way smaller and cheaper if we added a recurse symbol to it that made it iterate many times. Hard tasks would still take a lot, but most banal conversations would be very cheap.
I'm not sure I know what you're talking about.
https://www.reddit.com/r/AskReddit/comments/ajhnv/sit_or_sta...
I misremembered, it was wiping apparently.
Eh, HN is supposed to be "better" than your standard public forum and we still always end up making habitual arguments, not truly reasonable ones. I find your hope inspiring but not enough to ignore my senses.
I love your enthusiasm in this direction (I really do).
But here's some free advice I won't be able to prove for a long time:
Anyone who is currently convinced that somehow our fledgling efforts in the direction of building useful ML models are somehow going to yield a new golden age of neuroscience and understanding of the brain-- rather than the other way around-- is gonna be in for a long and frustrating next couple of decades, especially if they're low-openness types.