Category: Large Reasoning Models (LRMs)

Concept image to explain how AI hallucinations occur when an AI model generates false or illogical information that isn't based on real data or events, but is presented as fact.

^{Type
post

Erik J. Larson
Date
June 18, 2025

Categorized
Large Language Models (LLMs), Large Reasoning Models (LRMs)

Tagged
Ask Martin chatbot, Confabulation (AI), Emily Bender, Martin Seligman, Stochastic parrots concept}

Just When Human Reason is Most Productive — AI Makes Things Up

_{In Part 2, we see how the ability to handle only one type of truth limits AI. AI models are fundamentally untethered from reality} _{Erik J. Larson
June 18, 2025

5

Large Language Models (LLMs), Large Reasoning Models (LRMs)}

The gap between human and machine ways of knowing can be thought of as the correspondence horizon. When AI crosses that, it produces plausible bullshit.

Why AI Breaks Down Where Human Creativity Begins

_{Part 1: AI can handle statements that are internally coherent but that is not the same thing as correspondence with reality} _{Erik J. Larson
June 18, 2025

6

Large Language Models (LLMs), Large Reasoning Models (LRMs), Philosophy}

In short, philosophers distinguish between two fundamental theories of truth: correspondence and coherence, and AI does only coherence.

No, Large Reasoning Models Do Not Reason

_{Large reasoning models continue the Large Language Model detour away from artificial general intelligence} _{Gary Smith
June 13, 2025

9

Large Language Models (LLMs), Large Reasoning Models (LRMs)}

It is increasingly recognized that, without extensive post-training, their authoritative answers are often remarkably bad.