61–70 of 82 posts
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Isn't that what "Attention is all you need" was about anyway? Does not sound like news to me.
This is all obvious and not news, but there's a lot of people doing fighting retreats against LLM intelligence where the degree of obviousness matters.
The model would construct/hallucinate pre-conditions to satisfy some final output value that the model was predisposed to.
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> I think there’s fairly strong evidence that there is something that convincingly looks like reasoning. No one is disputing that, but there is an enormous difference between evidence of 'something that looks like a thing' and evidence of the thing itself.
I tend to agree but to adjudicate that someone has to define what they consider reasoning to be.
An approach that might shed some light is instead to define what consciousness ISN'T or what thinking ISN'T. Naively let us say consciousness is NOT a large list of weights (i.e. an LLM).
The uncanny emergent ability of an LLM depends entirely on training data. A mathematical model is used to match output against training data (via loss functions etc). The training data contains all the human ingenuity, logic, rational, patterns and features.
Try giving an LLM model the alphabet ALONE and see what it comes up with? Why are you able to immediately reason that given the alphabet alone it could not 'reason', 'think' or produce much of anything useful.
To address briefly the idea of reasoning and something assembling reasoning somehow implying the same thing. Try the following thought experiment. Given a simulated world (e.g. The Matrix), no matter how good the simulation you would not actually get WET.
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I keep asking the same question, and I think the steelman version would be "has metacognitive patterns similar to humans"
I think the anthropomorphic view of this is dangerous in the long term as it starts the argument that anything that isn't reasoned by a human isn't reasoning at all. This just changes the argument from LLMs can reason like a human to LLMs can't reason at all while ignoring the third possibility of "LLMs can reason not like a human". One of the biggest things I've learned after the event of LLMs is that humans definit…
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This is actually a perfect example of what I was referring to in my earlier comment; the strident [1] and rather aggressive insistence that your unsupported belief be proved wrong, rather than you providing literally any evidence that two distinct things are identical other than the assertion itself. You're making a strong claim here; the burden of proof [2] lies with you, in much the same way that it would if you de…
I provided my definition and argument. I can't engage further if you don't refute any of it.
> A coding agent solving a software-engineering task spends dozens of steps reasoning No. That's simple PR hype. Parrotry is not reasoning.
Copying someone else's reasoning process (as best you understand it) is still a limited form of reasoning, even if it might be considered as cargo-cult reasoning (copying without understanding).
The LLM is not copying someone else's process. All it knows it someone else's product, and its only process is to compute the most likely next token within that.
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Copying someone else's reasoning process (as best you understand it) is still a limited form of reasoning, even if it might be considered as cargo-cult reasoning (copying without understanding).
> Copying someone else's reasoning process (as best you understand it) is still a limited form of reasoning The LLM is not copying someone else's process. All it knows it someone else's product , and its only process is to compute the most likely next token within that.
The perhaps surprising thing is that it works so well some of the time - specifically for math and coding.
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What’s the difference?
Is regexp or compiler lookahead reasoning ? No. Mistaking chatbot lookahead as reasoning comes with being gulled by the "artificial intelligence " sales pitch.
They are narrow and limited, but still primitive forms of reasoning.
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...by inferring both the imports and the script body from the same context? I think you're suggesting there's some kind of information flow from the anticipated body of the script back up to the imports, but I don't see why that would be necessary. Infer imports from context, infer body from context + imports. All strictly causal.
That suggests a straightforward mapping between context -> program. Maybe for trivial programs but I don’t see how you can argue that for sufficiently complex programs. Reasoning models perform better than non-reasoning models because they’re able to refine their code in multiple steps. That allows any part of the program to influence any other part of the program, not just from start -> end. Human thinking serves a…
Non-reasoning models were still surprisingly good at generating working programs. I think it makes sense when you consider that it's still iterative; it doesn't have to generate the entire import block in a single pass, for example, more like decide at the end of each line whether there are more libraries it should import or whether to move on to the body of the program. It's less surprising that a single forward pass is able to make that type of decision IMO.
Taking Python as an example, you see LLMs use a lot of scoped imports and I think this is partly because it makes the output more resilient against failure to think forward at the start. Even a reasoning model will write out (the first iteration of) an entire file in one tool call, so once it starts generating it still has to keep going until it finishes, no pausing for breath.
Also it's interesting that non-reasoning models can still do quite well in a harness that lets them test and fix up their code. Like you said, it gives them the ability to iterate.