MBZUAI has launched the Institute for Agriculture and Artificial Intelligence (IAAI) in collaboration with the UAE Presidential Court and the Gates Foundation. The IAAI will focus on strengthening global food security by providing digital advisory tools to over 43 million smallholder farmers. The institute will develop a new data corpus for agriculture to train AI models and offer localized insights on crops, pests, soils, weather, and markets. Why it matters: This initiative highlights the UAE's commitment to using AI for global good, specifically addressing food security challenges and empowering small-scale farmers through advanced technologies.
KAUST is launching the Lifelong Learning Initiative (LLI), offering short, hands-on courses in areas like cybersecurity, food security, and semiconductors. The inaugural AI courses, designed for those with basic coding skills, will start with a "Machine Learning Bootcamp" in Riyadh from May 10-12. The KAUST Artificial Intelligence Initiative (AII) is developing AI class material in partnership with SDAIA. Why it matters: This initiative will upskill Saudi nationals and residents in critical areas like AI, supporting the Kingdom's development objectives and mobilization of the labor market.
MBZUAI researchers will present 20 papers at the 40th International Conference on Machine Learning (ICML) in Honolulu. Visiting Associate Professor Tongliang Liu leads with seven publications, followed by Kun Zhang with six. One paper investigates semi-supervised learning vs. model-based methods for noisy data annotation in deep neural networks. Why it matters: The research addresses the critical issue of data quality and accessibility in machine learning, particularly for organizations with limited resources for data annotation.
MBZUAI has appointed Dr. Ling Shao as Executive Vice President and Provost to lead academic affairs and research. Dr. Shao is also the CEO and Chief Scientist of the Inception Institute of Artificial Intelligence (IIAI). MBZUAI is partnering with IIAI for PhD student supervision and curriculum development. Why it matters: This appointment signals MBZUAI's commitment to attracting top AI talent and establishing itself as a leading AI research institution in the region.
Researchers introduce TimeTravel, a benchmark dataset for evaluating large multimodal models (LMMs) on historical and cultural artifacts. The benchmark comprises 10,250 expert-verified samples across 266 cultures and 10 historical regions, designed to assess AI in tasks like classification and interpretation of manuscripts, artworks, inscriptions, and archaeological discoveries. The goal is to establish AI as a reliable partner in preserving cultural heritage and assisting researchers.
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.
MBZUAI faculty member Dr. Hang Dai won first and second place in the Commands 4 Autonomous Vehicles (C4AV) Workshop Challenge at ECCV 2020. Dr. Dai participated in the competition as part of two teams, earning top spots for using AI in autonomous vehicles. The C4AV Workshop Challenge aims to develop models for joint understanding of vision and language in self-driving cars. Why it matters: This win demonstrates MBZUAI's commitment to advancing AI research and its applications in key areas like autonomous vehicles.
The InterText project, funded by the European Research Council, aims to advance NLP by developing a framework for modeling fine-grained relationships between texts. This approach enables tracing the origin and evolution of texts and ideas. Iryna Gurevych from the Technical University of Darmstadt presented the intertextual approach to NLP, covering data modeling, representation learning, and practical applications. Why it matters: This research could enable a new generation of AI applications for text work and critical reading, with potential applications in collaborative knowledge construction and document revision assistance.