Exploring the Limitations of Language Models as World Models
By
ingve
9mo ago· 17 min readenOpinion
100/100
Golden Brown
Bagelometer↗
Sesame, salt, and substance. A flagship bake.
Score100TypeopinionSentimentneutral
Summary
The article argues that language models (LLMs) are not world models, despite their complexity and capabilities. The author provides examples to clarify this claim, such as a chess game scenario, to illustrate the limitations of LLMs in modeling real-world phenomena. The tone is reflective and persuasive, aiming to challenge common assumptions about LLMs.
Key quotes
· 3 pulledI believe that language models aren’t world models. It’s a weak claim — I’m not saying they’re useless, or that we’re done milking them.
It’s also a fuzzy-sounding claim — with its trillion weights, who can prove that there’s something an LLM isn't a model of?
I said, no way, I’m going to cRRRush it, in my best Russian accent.
I believe that language models aren’t world models. It’s a weak claim — I’m not saying they’re useless, or that we’re done
milking them. It’s also a fuzzy-sounding claim — with its trillion weights, who can prove that there’s something an LLM isn't a
mode
You might also wanna read

Neuroscience Challenges AI Optimism: Are Large Language Models a Path to True Intelligence?
The article examines the ambitious claims by tech leaders like Mark Zuckerberg, Dario Amodei, and Sam Altman about achieving superintelligen

Study finds large language models vulnerable to classic persuasion tactics for harmful requests
This study tested whether three widely used large language models (LLMs) are susceptible to classic persuasion principles (authority, social
