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This month we’re joined by Elizabeth Loew, Executive Editor, and Christopher Tominich, Senior Editor, both in the Mathematics book group at Springer Nature, to learn how mathematics and artificial intelligence intertwine. While computer science plays a key role in building AI technology, mathematics operates as the “engine under the hood” of AI, powering analyzation, probability, statistical tasks, optimization, and much more. As Elizabeth and Chris explain, mathematics provides essential frameworks for large language models and machine learning algorithms, particularly when applied to massive datasets. In this series, we’ll explore mathematicians’ research in other subject areas to improve AI functions, preparing today’s math students for an AI landscape, and if artificial intelligence really is the new calculator.
In the first episode of this four-part series, Elizabeth and Chris discuss how mathematics makes modern AI tools possible. Chris dives into the AI applications of mathematical theories and frameworks and picks out a few fundamental math skills that contribute to AI. In addition, Elizabeth highlights emerging areas of study in math that she’s seen in AI-related manuscripts and scholarship.
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