The opinion of anyone impressed by the function or output of a LLM enough to believe it is in any way adjacent to intelligence should be summarily dismissed, and ridiculed should they persist.
I have tried it for ESPhome and it gives you something that sounds right. When you go to save ESPhome says this is not a valid option so then you say that to the AI and it goes yes that is correct this is how you do that option. Like WTF so SMRT.
I mean, they are AI though it’s a very misleading label, AIs are called like that because to someone it seems that they mimic human inteligence; they are just copycat machines, sadly it’s too late to change their name unless a government starts to make campaigns to aid that
LLMs are basically giant knowledge databases with no intelligence. They know a lot of things but they don’t understand stand any of it.
Because fundamentally they can’t understand things. They can only approximate understanding.
It’s no different then if I asked someone to prove 2+2=4. They could tell me that yes that’s correct, because they know it. But they couldn’t explain it properly. Let alone explain why it also isn’t always true.
Hallucinations are fundamentally the disconnect from knowledge and understanding. Everything a LLM says from its point of view is “true” it’s only stating factual knowledge so far that it has it in its data set.
But with out understanding, it can’t tell when that knowledge wanders from a 99% likelihood to be accurate to 60% or 20%. Because it doesn’t actually understand what it’s saying.
It can only state subjective not objective truth. And subjective truth is no better than a fiction with out understanding.
This is why they need a human minder to keep track of the output to correct it back to optimum output when it starts to wander.
Chain of thought doesn’t quite align with this. It’s possible to predict something not in training if there are sufficient facts in the history to align the probability toward a conclusion. (the “teach a man to fish” approach) Reasoning chains were introduced to take advantage of this, but it’s also possible to prime facts through external sourcing that can be used to extend the predictions. (web searching, document traversal, etc.)
Your larger point remains accurate though. Introspection capabilities are functional but quite limited, and training bias can be quite pathological in a vacuum.
This binary distinction you’re making doesn’t exist in any serious scientific literature. I literally have a degree in information technology and have been following this subject for over 30 years now - there’s no real distinction between “knowledge” and intelligence. In fact, compression itself is literally intelligence.
The opinion of anyone impressed by the function or output of a LLM enough to believe it is in any way adjacent to intelligence should be summarily dismissed, and ridiculed should they persist.
I’m impressed by llms all the time.
I’m impressed they manage to not shit themselves even more then they already do!
Lol
I have tried it for ESPhome and it gives you something that sounds right. When you go to save ESPhome says this is not a valid option so then you say that to the AI and it goes yes that is correct this is how you do that option. Like WTF so SMRT.
“But I one shotted this barely functioning game in Astra!” 🤣🤣🤣
It’s very much factual that LLMs are intelligent, what are you even talking about?
Maybe you’re confusing intelligence with consciousness?
Intelligence requires possession and/or demonstration of comprehension, something LLMs are intrinsically incapable of.
If you insist on classifying LLMs as ‘AI’, I’ll concede they are proficient Algorithmic Iterators.
I mean, they are AI though it’s a very misleading label, AIs are called like that because to someone it seems that they mimic human inteligence; they are just copycat machines, sadly it’s too late to change their name unless a government starts to make campaigns to aid that
Yet LLMs demonstrate all of that
LLMs demonstrate knowledge not intelligence.
LLMs are basically giant knowledge databases with no intelligence. They know a lot of things but they don’t understand stand any of it.
Because fundamentally they can’t understand things. They can only approximate understanding.
It’s no different then if I asked someone to prove 2+2=4. They could tell me that yes that’s correct, because they know it. But they couldn’t explain it properly. Let alone explain why it also isn’t always true.
Hallucinations are fundamentally the disconnect from knowledge and understanding. Everything a LLM says from its point of view is “true” it’s only stating factual knowledge so far that it has it in its data set.
But with out understanding, it can’t tell when that knowledge wanders from a 99% likelihood to be accurate to 60% or 20%. Because it doesn’t actually understand what it’s saying.
It can only state subjective not objective truth. And subjective truth is no better than a fiction with out understanding.
This is why they need a human minder to keep track of the output to correct it back to optimum output when it starts to wander.
Chain of thought doesn’t quite align with this. It’s possible to predict something not in training if there are sufficient facts in the history to align the probability toward a conclusion. (the “teach a man to fish” approach) Reasoning chains were introduced to take advantage of this, but it’s also possible to prime facts through external sourcing that can be used to extend the predictions. (web searching, document traversal, etc.)
Your larger point remains accurate though. Introspection capabilities are functional but quite limited, and training bias can be quite pathological in a vacuum.
This binary distinction you’re making doesn’t exist in any serious scientific literature. I literally have a degree in information technology and have been following this subject for over 30 years now - there’s no real distinction between “knowledge” and intelligence. In fact, compression itself is literally intelligence.
You’re proving my point, jog on.
Lemmy luddites: 🙈🙉