Why Cannot Large Language Models Ever Make True Correct Reasoning?

TL;DR

This paper argues that large language models cannot achieve true correct reasoning due to fundamental limitations in their working principles, challenging claims of their reasoning abilities.

Contribution

It provides a critical analysis explaining why LLMs are inherently incapable of true reasoning, clarifying misconceptions in current AI discourse.

Findings

LLMs lack genuine reasoning capabilities

Theoretical limitations prevent true reasoning in LLMs

Current reasoning claims are illusions

Abstract

Recently, with the application progress of AIGC tools based on large language models (LLMs), led by ChatGPT, many AI experts and more non-professionals are trumpeting the "reasoning ability" of the LLMs. The present author considers that the so-called "reasoning ability" of LLMs are just illusions of those people who with vague concepts. In fact, the LLMs can never have the true reasoning ability. This paper intents to explain that, because the essential limitations of their working principle, the LLMs can never have the ability of true correct reasoning.