Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Four Fallacies of Modern AI

blog.apiad.net

Post reply on HN
Print view View original

81–90 of 96 posts

Re: Four Fallacies of Modern AI

#81

Post by adastra22 »

whilenot-dev wrote: post #56
adastra22 wrote: post #29

> Does a model that can see and act begin to bridge the gap toward common sense Question for the author: how are SOTA LLM models not common sense machines?

Not the author, but to extend this quote from the article: > Its [Large Language Models] ability to write code and summarize text feels like a qualitative leap in generality that the monkey-and-moon analogy doesn't quite capture. This leaves us with a forward-looking question: How do recent advances in multimodality and agentic AI test the boundaries of this fallacy? Does a model that can see and act begin to bridge…

Common sense is more than just causal reasoning. It is also an ability to draw upon a large database of facts about the world and to know which ones apply to the current situation.

But LLMs achieve both your condition and mine. The attention network makes the causal connections that you speak of, while the multi-layer perceptions store and extract facts that respond to the mix of attention.

It is not commonly described as such, but I think “common sense engine” is a far better description of what a GPT-based LLM is doing than mere next word prediction.

Re: Four Fallacies of Modern AI

#82

Post by whilenot-dev »

adastra22 wrote: post #81
whilenot-dev wrote: post #56

Earlier quoted context omitted.

Not the author, but to extend this quote from the article: > Its [Large Language Models] ability to write code and summarize text feels like a qualitative leap in generality that the monkey-and-moon analogy doesn't quite capture. This leaves us with a forward-looking question: How do recent advances in multimodality and agentic AI test the boundaries of this fallacy? Does a model that can see and act begin to bridge…

Common sense is more than just causal reasoning. It is also an ability to draw upon a large database of facts about the world and to know which ones apply to the current situation. But LLMs achieve both your condition and mine. The attention network makes the causal connections that you speak of, while the multi-layer perceptions store and extract facts that respond to the mix of attention. It is not commonly describ…

> But LLMs achieve both your condition and mine.

Just to follow: Are you suggesting that Andrej Karpathy is wrong when he talks about the behaviors of ChatGPT (GPT-4), or is GPT-5 just way more SOTA advanced and solved the "reversal curse" of GPT-4?

Re: Four Fallacies of Modern AI

#84

Post by adastra22 »

whilenot-dev wrote: post #82
adastra22 wrote: post #81

Earlier quoted context omitted.

Common sense is more than just causal reasoning. It is also an ability to draw upon a large database of facts about the world and to know which ones apply to the current situation. But LLMs achieve both your condition and mine. The attention network makes the causal connections that you speak of, while the multi-layer perceptions store and extract facts that respond to the mix of attention. It is not commonly describ…

> But LLMs achieve both your condition and mine. Just to follow: Are you suggesting that Andrej Karpathy is wrong when he talks about the behaviors of ChatGPT (GPT-4), or is GPT-5 just way more SOTA advanced and solved the "reversal curse" of GPT-4?

Well, what does Andrej Karpathy say? Kinda hard to respond without knowing that :)

What I said was true of GPT-2, and much more clearly the case with GPT-3. Unfortunately us plebs don’t have as good insight into later models.

Re: Four Fallacies of Modern AI

#85

Post by whilenot-dev »

adastra22 wrote: post #84
whilenot-dev wrote: post #82

Earlier quoted context omitted.

> But LLMs achieve both your condition and mine. Just to follow: Are you suggesting that Andrej Karpathy is wrong when he talks about the behaviors of ChatGPT (GPT-4), or is GPT-5 just way more SOTA advanced and solved the "reversal curse" of GPT-4?

Well, what does Andrej Karpathy say? Kinda hard to respond without knowing that :) What I said was true of GPT-2, and much more clearly the case with GPT-3. Unfortunately us plebs don’t have as good insight into later models.

Just listen to 45secs of the video I linked above if you're interested.

Re: Four Fallacies of Modern AI

#86

Post by keeda »

AIPedant wrote: post #33
entropyneur wrote: post #18

This article seems to fall straight into the trap it aims to warn us about. All this talk about "true" understanding, embodiment, etc. is needless antropomorphizing. A much better framework for thinking about intelligence is simply as the ability to make predictions about the world (including conditional ones like "what will happen if we take this action"). Whether it's achieved through "true understanding" (however…

"Making predictions about the world" is a reductive and childish way to describe intelligence in humans. Did David Lynch make Mulholland Drive because he predicted it would be a good movie? The most depressing thing about AI summers is watching tech people cynically try to define intelligence downwards to excuse failures in current AI.

> "Making predictions about the world" is a reductive and childish way to describe intelligence in humans.

It also happens to be a leading theory in neuroscience: https://news.ycombinator.com/item?id=45058056

Re: Four Fallacies of Modern AI

#87

Post by adastra22 »

whilenot-dev wrote: post #85
adastra22 wrote: post #84

Earlier quoted context omitted.

Well, what does Andrej Karpathy say? Kinda hard to respond without knowing that :) What I said was true of GPT-2, and much more clearly the case with GPT-3. Unfortunately us plebs don’t have as good insight into later models.

Just listen to 45secs of the video I linked above if you're interested.

That is how human memories work too, though. It is well documented in the psychological literature that human memory is not the bidirectional mapping or graph you might expect from computer analogies. Associative memory in the mind is unidirectional and content addressable, which results in odd examples very similar to this "reversal curse."

We shouldn't strive for our AI to be bug-for-bug compatible with human thinking. But I fail to see how AI having similar limitations to human brains serves as evidence that they DON'T serve similar functions.

Re: Four Fallacies of Modern AI

#88

Post by tim333 »

simianwords wrote: post #39

> But that still leaves a crucial question: can we develop a more precise, less anthropomorphic vocabulary to describe AI capabilities? Or is our human-centric language the only tool we have to reason about these new forms of intelligence, with all the baggage that entails? I don't get the problem with this really. I think LLM's "reasoning" is a very fair and proper way to call it. It takes time and spits out tokens…

The problem is fuzzy language can make debate poor and about the definition of words rather than about reality. The answer I think it to avoid that and find things that you can be clear about. A famous example is the Turing test. Rather than debates on whether machines can think getting bogged down in endless variation of how people define thinking, Turing looked at if the machines could be told apart from humans which he discussed in his paper.

Re: Four Fallacies of Modern AI

#89

Post by tim333 »

>...the most important fallacy. It's the deep-seated assumption that intelligence is, like software, a form of pure information processing that can be separated from its body.

I think he gets into a muddle on that one. If something online can provide smarter thinking and answers to questions than I can then I figure it's intelligent and it doesn't matter if it's an LLM, a human or a disembodied spirit that somehow happens to be online.

He kind of gets that from human minds not being disembodied from their brains but that's a different thing.

Re: Four Fallacies of Modern AI

#90

Post by peterashford »

ehnto wrote: post #78
peterashford wrote: post #49

Earlier quoted context omitted.

Yeah I think that's an important dimension. David Hume said that there was no action without passion and I think that's a key difference with AIs. They sit there passive until we interact with them. They dont want anything, they dont have goals, desires, motivations. The emotional part of the human psyche does a lot of work - we aren't just calculating sums

The idea that any of those attributes could arise out of an LLM would be surprising to say the least. They do not maintain a continuum of thought for which those things could exist within. In the case of humans, those things are not just thought anyway, they are a complex mix of chemical signals, physical signals and thoughts, memories etc. So complex we barely understand it, even though we live it and have studied i…

I don't think anyone was suggesting that any of those things were possible in an LLM.
Post reply on HN