Talk by Martin Mundt

24 January 2025, by DS Group

We are excited to have Martin Mundt in our lab to present his work!

Title: Recognize, Remember, Remediate! Why adaptation is crucial for participatory AI

When: 24.01.25

Abstract: Deep machine learning continues to advance the frontiers of innovative applications, recently through the rise of generative AI and foundation models. However, as much as their success is astonishing, their data-hungry and compute-heavy nature continues to entail an equal amount of scientific and socio-technical concerns. Repeated large-scale training is known to be unsustainable, the produced outputs are often misleading or even downright confabulated, and the data-dependent development cycles shift privilege to those who have access. Inspired by the human’s remarkable ability to adapt efficiently without amassing tremendous amounts of data, lifelong learning promises to transcend these predicaments. In this talk, I will sketch why lifelong learning can provide remedies to successfully handle new situations, absolve us from the need to store large datasets, and equip models with necessary adaptation abilities. In turn, I will highlight why a respective paradigm shift is needed to provide a sustainable alternative to current machine training and why lifelong learning is essential to participation.

Who: Martin Mundt is a full professor at the University of Bremen, leading the Open World Lifelong Machine Learning Lab. He is also a board member of directors at the non-profit organization ContinualAI and member of Queer in AI. He currently serves as Diversity, Equity and Inclusion (DEI) chair at CoLLAs 2025, was previously DEI Chair at AAAI-24 and Review Process Chair for CoLLAs-24. Prior to joining the University of Bremen, Martin was an independent research group leader and visiting professor at TU Darmstadt and hessian.AI. He holds a PhD in computer science and a Master’s of Physics from Goethe University Frankfurt. Martin’s work focuses on developing AI systems that learn throughout their lifecycle, much like the human brain. These lifelong learners are able to behave robustly in novel situations and incorporate novel experiences sustainably. His vision ensures that AI systems are not only intelligent, but are also sufficiently adaptable to ensure technological advancements can cater to diverse populations.