In this article, we will discuss how DeepMind’s machine learning techniques can help unravel the mathematics related to knots. Researchers at DeepMind collaborated with mathematicians to address two separate problems – one in knot theory and the other in studying symmetries. In both cases, AI techniques assisted researchers in discovering new patterns that could be explored using traditional methods.
Machine Learning and Mathematics
In this section, we will talk about how machine learning techniques can assist in understanding mathematics and discovering mathematical relationships that humans might overlook. DeepMind is one of the leading companies in the field of artificial intelligence, and they have used machine learning techniques to help solve two complex mathematical problems, namely knot theory and the study of symmetries. Thanks to these techniques, new patterns in mathematics have been discovered that can be explored by traditional methods.
Applications of Machine Learning in Mathematics
In this section, we will discuss applications of machine learning in the field of mathematics and how other areas in mathematics that involve large datasets can benefit from it. Machine learning techniques can be used to uncover patterns and mathematical relationships in large datasets, aiding in the development of new models and tools for solving mathematical problems. Thus, machine learning can have a significant impact on the field of mathematics and contribute to its development and advancement.
Conclusion
In this article, we showcased how DeepMind’s machine learning techniques can help unravel the mathematics related to knots. Researchers at DeepMind presented new models to solve two complex mathematical problems and utilized traditional techniques to explore and better understand these models. The applications of machine learning in mathematics can have a significant impact on the field and contribute to its future development and progress.
Source: https://www.nature.com/articles/d41586-021-03593-1
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