Call that brute force perhaps, but I would consider it technically inventing something on the merit that it would at least be an abstraction above naively throwing everything against a wall to only throwing things that would most likely be sticky.
Call that brute force perhaps, but I would consider it technically inventing something on the merit that it would at least be an abstraction above naively throwing everything against a wall to only throwing things that would most likely be sticky.
on a surface level a human solving an (unsolved) math problem can look like this, and of course the tree of all possible symbols you can send to a proving assistant is much wider than what the human samples, and the same goes true for an LLM in a proving loop. It isn't "truly random", it can't possibly be (and solve the problem). Both humans and LLMs solving unsolved math problems are aggressively pruning mathematical syntax and logical strategy trees.
How are you measuring complexity here? How are you measuring inputs? Your average llm is trained on a corpus that vastly exceeds the amount of data I could read in my lifetime.
In terms of how it functions, because no matter how much data you feed an LLM it's still predicting tokens. That makes it incapable of any thought.
>Your average llm is trained on a corpus that vastly exceeds the amount of data I could read in my lifetime.
But that doesn't mean they are useless, they are good at consuming large amounts of data and collating it.
I don't know how correct I am but that's my understanding and it won't change, I feel pretty confident in my simplified view of things because the basics are still there.
That's a rather dismissive way of putting it. Moreover it's confusing the output format with the complexity of the output. I could just as easily say that no matter what the human brain does it's just generating stimulus to motor neurons. Such a simplification is just as wrong as saying that it's just as misleading is saying that an llm is just a token generator. What makes an llm able or unable to be complex is the process that creates those tokens
Okay but how is that relevant for measuring whether an llm is capable of creating original thoughts? Why do you think that complexity, as you say, is a more relevant Factor than simply the number of weights?
2024 called, it wants its talking points back. I don't think claims like these are defensible after all the progress we have witnessed in the last year alone.
That has nothing to do with the question of whether the mechanism that generates those signals is complex enough to say that it's "creative."
An "AI" is a box which lies dormant until a human, with motivation and agency, enters a prompt into it.
A person or company can use it in a way where it might invent something. but at the end of the day, its a tool, and its actually not doing anything on its own.
Its not solving math problems, a mathetmatician is using it to solve math problems. Just cus OpenAI is acting like its AI is solving stuff, its really not. They're just paying people to use AI to hammer problems.
I'd say that people's motivation and agency, like their taste, creativity, and opinions, are shaped by external inputs, so saying that their agency is "owned" by them is a stretch.
The alternative would be the proposition that a slave, lacking agency, has no ability to solve problems. I find that idea unpalatable.