Artificial intelligence has been driven by a race toward ever-larger models. The next revolution, however, is making AI efficient enough to run where it creates the most value. Model compression reduces size and computational cost without sacrificing performance, enabling advanced Edge AI with lower energy consumption and greater privacy. This talk explores the latest advances in model compression, their industrial applications, and their role in building sovereign, efficient, and sustainable AI.

CIDAI | LinkedIn

Director, CIDAI

Joan Mas is a Telecommunications engineer (UPC) and MBA (Webster University). He worked for 10 years at the European Space Agency, the Netherlands, in the ENVISAT and METOP projects, Earth observation satellites. From 2000 to 2008 he developed at NTE S.A., equipment for the International Space Station and life support systems for manned space missions. Until 2024 he was Director of the Digital Technologies Division at Eurecat, promoting developments in areas such as Data Analytics and Big Data, Artificial Intelligence, Cybersecurity and others for multi-sector applications. He is currently Scientific Director in the digital field at Eurecat and, from 2021, he is also Director of CIDAI.

MULTIVERSE COMPUTING | LinkedIn

Professor at DIPC. CSO&Co-founder of Multiverse Computing. Visiting professor at the BSC. Johannes Guttenberg Universität Mainz, University of Queensland, Max Planck Institute, CNRS, Marie Curie IIF, Early Career Prize from the European Physical Society. Author of numerous highly-cited papers on quantum physics and computation. Steering Board of Quantum Journal. Partner of Entanglement Partners. Ex-President of GEIC in the RSEF. Member of the Scientific Panel on Artificial Intelligence by the United Nations.