The term AI didn’t lose its value - people just realized it doesn’t mean what they thought it meant. When a layperson hears “AI,” they usually think AGI, but while AGI is a type of AI, it’s not synonymous with the term.
I guess so, but then that is kind of lumping it in the fps bot behaviour from the 90s which was also “AI”, it’s the AI hype that is pushing people to think of it as “intelligent but not organic” instead of “algorithms that give the facade of intelligence” which 90s kids would have understood it to be.
The chess opponent on Atari is AI too. I think the issue is that when most people hear “intelligence,” they immediately think of human-level or general intelligence. But an LLM - while intelligent - is only so in a very narrow sense, just like the chess opponent. One’s intelligence is limited to playing chess, and the other’s to generating natural-sounding language.
What does history have to do with it? We’re talking about the definition of terms - and a machine learning system like an LLM clearly falls within the category of Artificial Intelligence. It’s an artificial system capable of performing a cognitive task that’s normally done by humans: generating language.
I’ve had this discussion countless times, and more often than not, people argue that an LLM isn’t intelligent because it hallucinates, confidently makes incorrect statements, or fails at basic logic. But that’s not a failure on the LLM’s part - it’s a mismatch between what the system is and what the user expects it to be.
An LLM isn’t an AGI. It’s a narrowly intelligent system, just like a chess engine. It can perform a task that typically requires human intelligence, but it can only do that one task, and its intelligence doesn’t generalize across multiple independent domains. A chess engine plays chess. An LLM generates natural-sounding language. Both are AI systems and both are intelligent - just not generally intelligent.
Sorry, no. It’s not intelligent at all. It just responds with statistical accuracy. There’s also no objective discussion about it because that’s how neural networks work.
I was hesitant to answer because we’re clearly both convinced. So out of respect let’s just close by saying we have different opinions.
I hear you - you’re reacting to how people throw around the word “intelligence” in ways that make these systems sound more capable or sentient than they are. If something just stitches words together without understanding, calling it intelligent seems misleading, especially when people treat its output as facts.
But here’s where I think we’re talking past each other: when I say it’s intelligent, I don’t mean it understands anything. I mean it performs a task that normally requires human cognition: generating coherent, human-like language. That’s what qualifies it as intelligent. Not generally so, like a human, but a narrow/weak intelligence. The fact that it often says true things is almost accidental. It’s a side effect of having been trained on a lot of correct information, not the result of human-like understanding.
So yes, it just responds with statistical accuracy but that is intelligent in the technical sense. It’s not understanding. It’s not reasoning. It’s just really good at speaking.
AI is an extremely broad term which LLMs falls under. You may avoid calling it that but it’s the correct term nevertheless.
only because marketing has shit all over the term
When we started calling literal linear regression models AI it lost all value.
A linear regression model isn’t an AI system.
The term AI didn’t lose its value - people just realized it doesn’t mean what they thought it meant. When a layperson hears “AI,” they usually think AGI, but while AGI is a type of AI, it’s not synonymous with the term.
I agree, but people have been heavily misusing it since like 2018
If I can call the code that drive’s the boss’ weapon up my character’s ass “AI”, then I think I can call an LLM AI too.
I guess so, but then that is kind of lumping it in the fps bot behaviour from the 90s which was also “AI”, it’s the AI hype that is pushing people to think of it as “intelligent but not organic” instead of “algorithms that give the facade of intelligence” which 90s kids would have understood it to be.
The chess opponent on Atari is AI too. I think the issue is that when most people hear “intelligence,” they immediately think of human-level or general intelligence. But an LLM - while intelligent - is only so in a very narrow sense, just like the chess opponent. One’s intelligence is limited to playing chess, and the other’s to generating natural-sounding language.
I am aware, but still I don’t agree.
History will tell later who was ‘correct’, if we make it that far.
What does history have to do with it? We’re talking about the definition of terms - and a machine learning system like an LLM clearly falls within the category of Artificial Intelligence. It’s an artificial system capable of performing a cognitive task that’s normally done by humans: generating language.
Everything. As we as humanity learn more we recognize errors or wisdom with standing the test of time.
We could go into the definition of intelligence, but it’s just not worth it.
We can just disagree and that’s fine.
I’ve had this discussion countless times, and more often than not, people argue that an LLM isn’t intelligent because it hallucinates, confidently makes incorrect statements, or fails at basic logic. But that’s not a failure on the LLM’s part - it’s a mismatch between what the system is and what the user expects it to be.
An LLM isn’t an AGI. It’s a narrowly intelligent system, just like a chess engine. It can perform a task that typically requires human intelligence, but it can only do that one task, and its intelligence doesn’t generalize across multiple independent domains. A chess engine plays chess. An LLM generates natural-sounding language. Both are AI systems and both are intelligent - just not generally intelligent.
Sorry, no. It’s not intelligent at all. It just responds with statistical accuracy. There’s also no objective discussion about it because that’s how neural networks work.
I was hesitant to answer because we’re clearly both convinced. So out of respect let’s just close by saying we have different opinions.
I hear you - you’re reacting to how people throw around the word “intelligence” in ways that make these systems sound more capable or sentient than they are. If something just stitches words together without understanding, calling it intelligent seems misleading, especially when people treat its output as facts.
But here’s where I think we’re talking past each other: when I say it’s intelligent, I don’t mean it understands anything. I mean it performs a task that normally requires human cognition: generating coherent, human-like language. That’s what qualifies it as intelligent. Not generally so, like a human, but a narrow/weak intelligence. The fact that it often says true things is almost accidental. It’s a side effect of having been trained on a lot of correct information, not the result of human-like understanding.
So yes, it just responds with statistical accuracy but that is intelligent in the technical sense. It’s not understanding. It’s not reasoning. It’s just really good at speaking.
Thank you for the nice answer!
We can definetly agree on that it can provide intelligent answers without itself being an intelligence 👍