Oh boy, if you want to fling papers/research, i can do that just fine.

https://arxiv.org/abs/2212.09196v1

https://arxiv.org/abs/2211.09066

https://thegradient.pub/othello/

Moreover, "have trouble reasoning" and "can't reason at all" are two very different statements. Not that i particularly agree with either but you should keep that in mind.

I'm not the person you responded to, but that's an old paper. LLMs have come a long way since. Nothing conclusive but GPT4 does show some signs of something deeper. https://arxiv.org/pdf/2303.12712.pdf

Yes, I have read that paper and have forwarded it eagerly to colleagues. Respectfully, please read the paper you have linked, especially section 8.2.

Look at section 8.2 in the paper you linked:

"8.2 Lack of planning in arithmetic/reasoning problems"

> However, it seems that the autoregressive nature of the model which forces it to solve problems in a sequential fashion sometimes poses a more profound difficulty that cannot be remedied simply by instructing the model to find a step by step solution

Nowhere in the paper is an evaluation on standard reasoning datasets (https://tptp.org) because they are much much much tougher than the simple examples that GPT-4 struggles with.

LLMs are a huge breakthrough but let us not muddy the science.

GPT 4 was evaluated on multiple reasoning benchmarks in the release paper.[1] The problems in TPTP are not really appropriate for a language model and exceed the capabilities of most humans working without tools. Clearly humans have some reasoning ability even if they cannot solve those problems.

[1] https://openai.com/research/gpt-4