Mathematics for and by Large Language Models
19 avril 2024
Thibault Damour is a theoretical physicist working on consequences of Einstein's theory of..
Large language models (LLMs) are a type of artificial intelligence (AI) that has been developed in recent years. LLMs are trained on massive datasets of text and code, and they can be used to perform a wide variety of tasks, including natural language processing, machine translation, and code generation.
One of the most promising applications of LLMs is in the field of mathematics. LLMs have been shown to be able to solve complex mathematical problems, and they can also be used to generate new mathematical theorems. This has led to a great deal of excitement in the mathematics community, as LLMs have the potential to revolutionize the way that mathematics is done.
However, there are also some challenges that need to be addressed before LLMs can be widely used in mathematics. One challenge is that LLMs are often not able to explain their reasoning. This can make it difficult to trust the results that they produce. Another challenge is that LLMs can be biased, as they are trained on data that is not always representative of the real world. This can lead to LLMs making incorrect or unfair predictions.
Despite these challenges, the potential benefits of LLMs in mathematics are enormous. LLMs have the potential to make mathematics more accessible, more efficient, and more creative. They could also help to solve some of the most challenging problems in mathematics today.
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