this post was submitted on 01 Jun 2025
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Who has claimed that LLMs have the capacity to reason?
More than enough people who claim to know how it works think it might be "evolving" into a sentient being inside it's little black box. Example from a conversation I gave up on... https://sh.itjust.works/comment/18759960
I don't want to brigade, so I'll put my thoughts here. The linked comment is making the same mistake about self preservation that people make when they ask an LLM to "show it's work" or explain it's reasoning. The text response of an LLM cannot be taken at it's word or used to confirm that kind of theory. It requires tracing the logic under the hood.
Just like how it's not actually an AI assistant, but trained and prompted to output text that is expected to be what an AI assistant would respond with, if it is expected that it would pursue self preservation, then it will output text that matches that. It's output is always "fake"
That doesn't mean there isn't a real potential element of self preservation, though, but you'd need to dig and trace through the network to show it, not use the text output.
Maybe I should rephrase my question:
Outside of comment sections on the internet, who has claimed or is claiming that LLMs have the capacity to reason?
The study being referenced explains in detail why they can’t. So I’d say it’s Anthropic who stated LLMs don’t have the capacity to reason, and that’s what we’re discussing.
The popular media tends to go on and on about conflating AI with AGI and synthetic reasoning.
You're confusing the confirmation that the LLM cannot explain it's under-the-hood reasoning as text output, with a confirmation of not being able to reason at all. Anthropic is not claiming that it cannot reason. They actually find that it performs complex logic and behavior like planning ahead.
No, they really don’t. It’s a large language model. Input cues instruct it as to which weighted path through the matrix to take. Those paths are complex enough that the human mind can’t hold all the branches and weights at the same time. But there’s no planning going on; the model can’t backtrack a few steps, consider different outcomes and run a meta analysis. Other reasoning models can do that, but not language models; language models are complex predictive translators.
🙃 actually read the research?
No, they’re right. The “research” is biased by the company that sells the product and wants to hype it. Many layers don’t make think or reason, but they’re glad to put them in quotes that they hope peeps will forget were there.