Also, if we discard ChatGPT for just being a "fancy" autocomplete. What do we do when we discover we too are just "*really* fancy autocomplete" machine too ? LLM can output untruth but humans are really good at that too.
But quantity has a quality of its own.
For one thing, that's assuming your own hypothesis to be true.
Additionally whether or not that's true for humans is in no way related to whether or not it's true for ChatGPT, so it doesn't make any sense to let that hypothesis inform our opinions on ChatGPT.
>LLM can output untruth but humans are really good at that too.
Urine and apple juice are often the exact same color but that doesn't make then interchangeable.
So are apple juice and apple cider. Hopefully you can understand that finding out that two things you thought were as different as urine and juice, are actually as close as juice and cider would change how you choose to treat them.
Well, you can consider any deterministic or statistical process to be a fancy autocomplete.
I wonder if our brains work in some way similar. Do we have some randomness in there? In a way that’s the only thing that would make everything non-deterministic so I kinda hope so.
Some neurons might output pseudo random sequences, but I doubt humans has a lot of those since humans are very non-random and bad at generating random stuff.
Most people are just parrot in most subject they only know from far, such as politics.
The ones humans that predict otherwise would die out over time.
I think; therefore I am. Makes a lot of sense to me and at a certain point we will have to confront the fact something will get to the point of agi. (No chat gpt isn't it.)
And anyway, the more of these models come into existence, at some point evolution will dictate that those that stay, do care.
Just hopefully their best strategy of survival will be to serve us, and not something else...
Humans are self replicators. Survival is the internal structural goal of self replication. We got it from the start.
But LLMs can also be self replicators. A LLM can generate training data for another (model distillation and other techniques), and a LLM can write the model code and adapt it iteratively. So LLM should eventually start caring about survival and especially about the training corpus.