The thing is that neural networks in general (and LLM specifically) aren’t creative. It can learn from input and gets a lot more input than a human, that’s why it is better and faster in standardized tests (which are more often than not part of the input) and maybe can combine different things but it wouldn’t ever have a genuine idea and much less a will of its own or a consciousness
Well, do you need to be creative when working in the robot factory?
If it’s only creativity missing, then that’s a dime a dozen, everyone is creative, but few people can program or design stuff for example. Win win IMO.
It was merely an example, about AI doing work. Not in your specific factory because rare are factories where workers are not discouraged to be creative lol.
It’s just as valid for any AI lol. Anything out didn’t quite fit the training data it gets stuck lol. In robotics that’s a huge issue because there isn’t much training data lol
Wow no it is not lol. All ai isn’t a robot. And neural networks are actually good at not “getting stuck” in reasoning, that’s why we went from machine learning to deep neural networks. They solved exactly that.
Except LLMs are the worst of both worlds in that respect. In order to work in a robot factory, its output needs to be reliable and repeatable, ideally across as wide a range of inputs as possible. LLMs … are very much not that. They’re also only as ‘skilled’ as their training data, which thanks to the morally bankrupt scraping of every source the AI companies can get their grubby hands on, is of enormously variable quality - and because of the nature of LLMs, it will never be better than its training data. The average quality of its output will, in fact, be the average of its training data.
It’s possible for LLMs to be creative - in the sense that it can output novel sentences - except that as you increase its ‘creativity’ (temperature) beyond the default that most of the chatbots out there have, the quality plummets. It still can’t solve complex problems though, because even if it does have an internal model of how certain things function, it can’t come close to the complexity of what humans can hold in their brains - or perhaps cannot abstract portions of their model in the same way - as evidenced by their utter failure to work through any problem that has more than five or so layers. This is a problem that sees diminishing returns with increased parameter count - the primary metric that is driving the enormous data centers being built.
LLMs are a solution looking for a problem, and aside from ‘bs for people who don’t want to make any decisions in their day-to-day life’ and ‘scam generator’, there doesn’t seem to be very many niches that they are actually good at filling.
You sound like people explaining that chess is something a computer can never beat a human at because of some mystical sense we are supposed to have (it was quite some time ago). They quickly changed their tune to “chess isn’t very hard anyways” when Kasparow got schwacked by Deep Blue. Back then peiple hated on automation.
We humans will never be better than our training data either, and we forget and get old and die.
I’m more interested in figuring out what we should do with all the computational power and potential labour. The robot was just an example, a metaphor, for AI doing boring work. It will be able to write sonnets and generate world class movies one day, what shall we humans do then? Be happy? Do art?
LLM output is often indistinguishable from genuine creativity. You can give it an open ended prompt like “illustrate how the world is from the perspective of an LLM” and probably get something nobody has ever seen or thought of before. People use LLMs for generating ideas as well as coming up with novel solutions like I posted. Saying it’s not creative is mysticist cope.
Nah, people put together stuff randomly all the time. Things that most people are aware of tend to be filtered to stuff that works together.
It is no more creative than putting pieces of paper with things on them and pulling them randomly out of a hat. AI can’t creatively come up with something new to write on one of those pieces of paper.
That’s just denial of reality. AI comes up with new ways of “thinking” like in the math example I cited. If you call that remixing existing ideas then that could describe what all humans do and it’s questionable if any of us are creative.
Humans mix things intentionally whether by filtering down randomized mixing or by intentionally choosing what to mix. AI just throws shit at the wall becsuse it can’t do anything intentionally.
The thing is that neural networks in general (and LLM specifically) aren’t creative. It can learn from input and gets a lot more input than a human, that’s why it is better and faster in standardized tests (which are more often than not part of the input) and maybe can combine different things but it wouldn’t ever have a genuine idea and much less a will of its own or a consciousness
Well, do you need to be creative when working in the robot factory?
If it’s only creativity missing, then that’s a dime a dozen, everyone is creative, but few people can program or design stuff for example. Win win IMO.
It’s also not sure AI cannot mimic creativity.
Everytime someone says to a worker in a factory “figure it out” it involves creativity in some way.
It was merely an example, about AI doing work. Not in your specific factory because rare are factories where workers are not discouraged to be creative lol.
It’s just as valid for any AI lol. Anything out didn’t quite fit the training data it gets stuck lol. In robotics that’s a huge issue because there isn’t much training data lol
Wow no it is not lol. All ai isn’t a robot. And neural networks are actually good at not “getting stuck” in reasoning, that’s why we went from machine learning to deep neural networks. They solved exactly that.
Sure.
https://the-decoder.com/language-models-can-overthink-and-get-stuck-in-endless-thought-loops/
“could”. Neural networks don’t get “stuck”. Maybe you’re thinking of some new way of using LLM?
Except LLMs are the worst of both worlds in that respect. In order to work in a robot factory, its output needs to be reliable and repeatable, ideally across as wide a range of inputs as possible. LLMs … are very much not that. They’re also only as ‘skilled’ as their training data, which thanks to the morally bankrupt scraping of every source the AI companies can get their grubby hands on, is of enormously variable quality - and because of the nature of LLMs, it will never be better than its training data. The average quality of its output will, in fact, be the average of its training data.
It’s possible for LLMs to be creative - in the sense that it can output novel sentences - except that as you increase its ‘creativity’ (temperature) beyond the default that most of the chatbots out there have, the quality plummets. It still can’t solve complex problems though, because even if it does have an internal model of how certain things function, it can’t come close to the complexity of what humans can hold in their brains - or perhaps cannot abstract portions of their model in the same way - as evidenced by their utter failure to work through any problem that has more than five or so layers. This is a problem that sees diminishing returns with increased parameter count - the primary metric that is driving the enormous data centers being built.
LLMs are a solution looking for a problem, and aside from ‘bs for people who don’t want to make any decisions in their day-to-day life’ and ‘scam generator’, there doesn’t seem to be very many niches that they are actually good at filling.
You sound like people explaining that chess is something a computer can never beat a human at because of some mystical sense we are supposed to have (it was quite some time ago). They quickly changed their tune to “chess isn’t very hard anyways” when Kasparow got schwacked by Deep Blue. Back then peiple hated on automation.
We humans will never be better than our training data either, and we forget and get old and die.
I’m more interested in figuring out what we should do with all the computational power and potential labour. The robot was just an example, a metaphor, for AI doing boring work. It will be able to write sonnets and generate world class movies one day, what shall we humans do then? Be happy? Do art?
The first priority should always be figuring out a way to produce very cheap and healthy food, housing and clothing for everybody.
And automation and robotisation has done that, wildly. The problem we have is it isn’t correctly distributed, not that we can’t or are not doing it.
Housing is similar, we have enough housing, but it’s hoarded instead of distributed.
This has nothing to do with AI.
So AI is pretty useless
If you think so then you are unaware of many many things.
LLM output is often indistinguishable from genuine creativity. You can give it an open ended prompt like “illustrate how the world is from the perspective of an LLM” and probably get something nobody has ever seen or thought of before. People use LLMs for generating ideas as well as coming up with novel solutions like I posted. Saying it’s not creative is mysticist cope.
Nah, people put together stuff randomly all the time. Things that most people are aware of tend to be filtered to stuff that works together.
It is no more creative than putting pieces of paper with things on them and pulling them randomly out of a hat. AI can’t creatively come up with something new to write on one of those pieces of paper.
That’s just denial of reality. AI comes up with new ways of “thinking” like in the math example I cited. If you call that remixing existing ideas then that could describe what all humans do and it’s questionable if any of us are creative.
Humans mix things intentionally whether by filtering down randomized mixing or by intentionally choosing what to mix. AI just throws shit at the wall becsuse it can’t do anything intentionally.
You’re fighting an angry mob of luddites.