Large Language Models and Mathematical Understanding

Abstract

This thesis focuses on Large Language models and their potential for mathematical understanding. Since computers have become more advanced, their role in mathematics has grown. Besides simple functions such as plotting graphs and doing calculations, computers have been used in increasingly complex roles, one example being proof assistance. Artificial intelligence algorithms are the most recent and complex way that computers have been used for mathematical inquiry. As the role of computers in mathematics has grown, several challenges have been raised. One of the challenges that AI faces is whether it can have mathematical understanding. This thesis aimed to determine if AI can have mathematical understanding. In order to answer this question, the thesis focuses on Large Language models, whether they can have mathematical understanding and how this understanding could be measured.