It's a large language model. It is fed training data. It is not that impressive when it spits out stuff that looks like its training data. You are the one asserting things without evidence.

It can pass tests and exams with answers that were not included in its training corpus. For example, it passed the 2023 unified bar exam, though its training cut off in 2021. Yes, it can look at previous test questions and answers, just like human law students can. Are you therefore claiming that human law students don't engage in abstract reasoning when they take the bar exam, since they studied with tests from previous years?

It can also write code for novel use cases that have never been done before. I gave it a task like this a few days ago and it got it right on the first try. There are literally millions of empirical data points that contradict you.

It is a large language model. It manipulates text based on context and the imprint of its vast training. You are not able to articulate a theory of reasoning. You are just pointing to the output of an algorithm and saying "this must mean something!" There isn't even a working model of reasoning here, it's just a human being impressed that a tool for manipulating symbols is able to manipulate symbols after training it to manipulate symbols in the specific way that you want symbols manipulated. Where is your articulated theory of abstract reasoning?

It's not clear to me what point you're trying to make. Why do we need an "articulated theory of abstract reasoning" to say that passing the bar exam or writing code for novel, nontrivial tasks requires reasoning? Seems rather obvious.

You are making a claim that there is some attribute of importance. For that claim to be persuasive, it should be supported with an explanation of what that attribute is and is not, and evidence for or against the meeting of those criteria. So far all you have done is say "Look at the text it puts out, isn't that something?"

It's just empty excitement, not a well-reasoned argument.

You keep avoiding this question: does passing the bar exam and writing code for novel, nontrivial tasks require reasoning or doesn't it?

You aren't answering because saying no will sound ridiculous. We all know it requires reasoning.

As for an "attribute of importance", I guess that's subjective, but I've used ChatGPT to write code in a few minutes that would have taken me hours of research and implementation. I've shipped that code to thousands of people. That's enough for it to be important to me, even ignoring other applications, but you certainly have the right to remain unimpressed if you so choose.

For a human, it takes human reasoning. But a xerox machine can also output the correct answers given the right inputs, which is exactly what you can say about an LLM.

Those aren't good analogies. An LLM isn't like a xerox machine or a tape recorder. Again, the answers to the bar exam it passed weren't in its training data. Nor was the code it wrote for me.

I'm using the common, colloquial definition of reasoning. I don't think we need an academic treatise to say that passing the bar exam (without copying the answers) or writing code for a novel task requires reasoning.

You're right that we don't fully understand how the LLM is doing this, but that doesn't mean it isn't happening.

Thank you, yes, for saying I am right in saying that the evidence is lacking, which was precisely my original point.

The evidence isn’t lacking :) We have lots of evidence. What we lack is a coherent theory that explains the evidence.

ttpphd says >"Where is your articulated theory of abstract reasoning?"<

If he had a complete answer to your questions then he would keep his mouth shut and go directly to META and collect $2 BN USD or get a Nobel prize (or both). What you seem to want is a peer-reviewed academic paper but what we're doing here is brainstorming about what is going on in these LLMs.

He's definitely onto something here: LLM models, at the very least, appear to generate reasonable human-like statements about human concepts. ChatGPT et al are useful in the same way a human assistant is useful. Most remarkably, they appear to think like we do. We need to understand how these MOFOs work b/c in a few years they're going to be everywhere.

IIRC an old "Far Side" Gary Larson cartoon depicts two bears just outside their cave, arrows in their limbs and butts, fighting off a hungry bunch of cave men. One bear says to the other "Seems there's more and more of these every year!"

Well, unless we're careful, next time we're going to be the bears!

I don't like buying into hype mindlessly. I prefer to reason through things and apply skepticism. If people are gonna claim that a chatbot has gained sentience, I'm gonna have some tough questions.

Note I didn't say "sentience" anywhere. There's a huge difference between non-human reasoning/thinking and sentience/consciousness. I don't believe the first implies the latter... it's necessary but not at all sufficient.