On opportunities and challenges of large multimodal foundation models in education
Stefan Küchemann, Karina E. Avila, Yavuz Dinc, Chiara Hortmann, Natalia Revenga, Verena Ruf, Niklas Stausberg, Steffen Steinert, Frank Fischer, Martin R. Fischer, Enkelejda Kasneci, Gjergji Kasneci, T. Kuhr, Gitta Kutyniok, Sarah Malone, Michael Sailer, Albrecht Schmidt, Matthias Stadler, J. Weller, Jochen Kühn
Abstract
Recently, the option to use large language models as a middleware connecting various AI tools and other large language models led to the development of so-called large multimodal foundation models, which have the power to process spoken text, music, images and videos. In this overview, we explain a new set of opportunities and challenges that arise from the integration of large multimodal foundation models in education.
Topics & Concepts
Foundation (evidence)Computer scienceProcess (computing)Set (abstract data type)Middleware (distributed applications)Programming languagePolitical scienceLawDistributed computingIntelligent Tutoring Systems and Adaptive LearningTopic ModelingMultimodal Machine Learning Applications