Entropy, Thermodynamics and the Geometrization of the Language Model

Fuente: arXiv
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Auteur principal: Yang, Wenzhe
Format: Preprint
Publié: 2024
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author Yang, Wenzhe
author_facet Yang, Wenzhe
contents In this paper, we discuss how pure mathematics and theoretical physics can be applied to the study of language models. Using set theory and analysis, we formulate mathematically rigorous definitions of language models, and introduce the concept of the moduli space of distributions for a language model. We formulate a generalized distributional hypothesis using functional analysis and topology. We define the entropy function associated with a language model and show how it allows us to understand many interesting phenomena in languages. We argue that the zero points of the entropy function and the points where the entropy is close to 0 are the key obstacles for an LLM to approximate an intelligent language model, which explains why good LLMs need billions of parameters. Using the entropy function, we formulate a conjecture about AGI. Then, we show how thermodynamics gives us an immediate interpretation to language models. In particular we will define the concepts of partition function, internal energy and free energy for a language model, which offer insights into how language models work. Based on these results, we introduce a general concept of the geometrization of language models and define what is called the Boltzmann manifold. While the current LLMs are the special cases of the Boltzmann manifold.
format Preprint
id arxiv_https___arxiv_org_abs_2407_21092
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Entropy, Thermodynamics and the Geometrization of the Language Model
Yang, Wenzhe
Computation and Language
Statistical Mechanics
High Energy Physics - Theory
Differential Geometry
68T01
I.2.7
In this paper, we discuss how pure mathematics and theoretical physics can be applied to the study of language models. Using set theory and analysis, we formulate mathematically rigorous definitions of language models, and introduce the concept of the moduli space of distributions for a language model. We formulate a generalized distributional hypothesis using functional analysis and topology. We define the entropy function associated with a language model and show how it allows us to understand many interesting phenomena in languages. We argue that the zero points of the entropy function and the points where the entropy is close to 0 are the key obstacles for an LLM to approximate an intelligent language model, which explains why good LLMs need billions of parameters. Using the entropy function, we formulate a conjecture about AGI. Then, we show how thermodynamics gives us an immediate interpretation to language models. In particular we will define the concepts of partition function, internal energy and free energy for a language model, which offer insights into how language models work. Based on these results, we introduce a general concept of the geometrization of language models and define what is called the Boltzmann manifold. While the current LLMs are the special cases of the Boltzmann manifold.
title Entropy, Thermodynamics and the Geometrization of the Language Model
topic Computation and Language
Statistical Mechanics
High Energy Physics - Theory
Differential Geometry
68T01
I.2.7
url https://arxiv.org/abs/2407.21092