MBZUAI launched its Executive Program, a hybrid course for government and industry leaders to promote greater engagement with AI. The program's first session, led by MBZUAI President Eric Xing, covered the history and future of AI and machine learning. It aims to accelerate AI development across various sectors in the UAE, focusing on efficiency, cost savings, and environmental impact reduction. Why it matters: This initiative signals the UAE's commitment to fostering AI literacy and driving AI adoption across key sectors, aligning with national economic development plans.
MBZUAI Professor Kun Zhang's research focuses on causality in AI systems, aiming to understand underlying processes beyond data correlation. He emphasizes the importance of causality and graphical representations to model why systems produce observations and account for uncertainty. Zhang served as a program chair at the 38th Conference on Uncertainty in Artificial Intelligence (UAI) in Eindhoven. Why it matters: This highlights the growing importance of causality and uncertainty in AI research, crucial for responsible AI deployment and decision-making in the region.
Dr. Munawar Hayat from Monash University gave a talk on the history of AI, recent breakthroughs in deep learning, and future research directions. The talk covered computer vision, NLP, autonomous driving, and reinforcement learning. Dr. Hayat also discussed the limitations of AI and challenges in the field. Why it matters: This lecture helps contextualize the rapid progress of AI for students in the region.
MBZUAI hosted a talk on causal AI, featuring Professor Jin Tian from Iowa State University. The talk covered enriching AI systems with causal reasoning capabilities, moving AI beyond prediction to understanding. Professor Tian shared research on causal inference and estimating causal effects from data, using a novel estimator with double/debiased machine learning (DML) properties. Why it matters: Causal AI can improve the explainability, robustness, and adaptability of AI systems, addressing limitations of purely statistical models.
MBZUAI President Eric Xing argued at the World Economic Forum in Davos that AI's next phase requires redesigning AI for real-world understanding and uncertainty, rather than just scaling models. He highlighted MBZUAI's unique position in building foundation models from scratch, emphasizing the importance of understanding their nuances, safety, and risks. Xing expressed skepticism about claims of general intelligence in current AI systems, pointing out their fragility and limited form of intelligence. Why it matters: Xing's participation highlights the growing role of Middle Eastern AI institutions like MBZUAI in shaping the global conversation around the future of AI.