Machine Learning Seminar presentation
Topic: The epistemic artificial intelligence project
Speaker: Fabio Cuzzolin, School of Engineering, Computing and Mathematics — Oxford Brookes University
Time: Wednesday, 2021.11.17, 10:00 CET
How to join: Please contact Jakub Lengiewicz
Although artificial intelligence (AI) has improved remarkably over the last years, its inability to deal with uncertainty severely limits its future applications. In its current form, AI cannot confidently make predictions robust enough to stand the test of data generated by processes different (even by tiny details, as shown by ‘adversarial’ results) from those seen at training time. While recognising this issue under different names (e.g. ‘overfitting’ or ‘domain adaptation’), traditional machine learning seems unable to address it in nonincremental ways. As a result, even state-of-the-art AI systems suffer from brittle behaviour, and find it difficult to operate in new situations. The epistemic AI project re-imagines AI from the foundations, through a proper treatment of the “epistemic” uncertainty stemming from our forcibly partial knowledge of the world. Its overall objective is to create a new learning paradigm designed to provide worst-case guarantees on its predictions, thanks to a proper modelling of real-world uncertainties. The project aims to formulate a novel mathematical framework for optimisation under epistemic uncertainty, radically departing from current approaches that only focus on aleatory uncertainty. This new optimisation framework will in turn allow the creation of new ‘epistemic’ learning settings, spanning all the major areas of machine learning: unsupervised learning, supervised learning and reinforcement learning. Last but not least, the project aims to foster an ecosystem of academic, research, industry and societal partners throughout Europe able to drive and sustain the EU’s leadership ambition in the search for a next-generation AI.
Video recording: https://youtu.be/GNCKqoQODR0