New Mathematics for AI Innovation

The breathtaking development of AI depends on many factors - data, computation, and mathematical modeling. In addition, mathematics contributes to understanding and extending the mechanisms underlying AI, whether through statistical learning theory, numerical linear algebra, approximation theory, and countless other fields. More recently, Generative AI (GenAI) is directly connected to mathematical fields such as optimal transport and (stochastic) differential equations.

AI is also flourishing in the German economy. In particular, start-ups and small and medium-sized companies are seizing the opportunities and creating value for customers and jobs based on innovative AI-related ideas. The dynamism of this sector is reflected by the foundation of the German Association for Artificial Intelligence (KI Bundesverband) by 24 companies in 2018. Since then, this association has experienced rapid growth and now represents 500 companies with a specific AI business model. Driven by technology, the experts of AI-companies are often the first to recognize new research problems, some of which can be solved by new mathematics.

Last but not least, many mathematicians are working as AI data scientists. Many universities have recognized this trend by creating mathematically oriented data science courses and professorships. The importance of mathematics for AI has been emphasized by the joint statement of several mathematical professional associations (DFG, GAMM, GOR, GiP and KoMSO).

For this reason, the German several mathematical professional associations (DMV, GAMM, GiP, GOR,KoMSO) and KI Bundesverband jointly invite to a Challenge Workshop in Berlin at the Werner von Siemens Center for Industry and Science. A selected group of industry experts and mathematically oriented KI researchers will present real-world research questions and recent progress in method development in order to jointly identify the agenda for future joint research.