TII and LightOn have partnered to build the NOOR Platform for exascale computing, aimed at developing foundation models. The collaboration will leverage LightOn's expertise in large language models, with the first output being the largest Arabic language model to date. The platform will provide high-quality data pipelines and facilitate extreme-scale distributed training and serving. Why it matters: This partnership aims to establish Abu Dhabi as a center of AI excellence and boost the UAE's ambitions in high-tech innovation and NLP research.
KAUST has been awarded the ACM Gordon Bell Prize for Climate Modelling, considered the "Nobel" of high-performance computing, for their work on exascale climate emulators. The winning paper, a collaborative effort with institutions including the NSF National Center for Atmospheric Research, addresses the computational and storage demands of high-resolution earth system models. The KAUST team included Sameh Abdulah, Marc G. Genton, David E. Keyes, and others. Why it matters: This is the first time an institution in the Middle East has won the prize, highlighting KAUST's leadership in high-performance computing and climate research in the region.
KAUST Professor Marc Genton has been selected as the 2020 Georges Matheron Lecturer of the International Association for Mathematical Geosciences. Genton will present a lecture at the 36th International Geological Congress in Delhi, India, focusing on geostatistics, climate model outputs, and the ExaGeoStat software developed at KAUST. His lecture will cover Matheron's theory of regionalized variables and showcase ExaGeoStat, a high-performance software for geostatistics with exascale computing capability developed at KAUST. Why it matters: This recognition highlights KAUST's contributions to advanced statistical methods and high-performance computing in geosciences, enhancing its international reputation in these fields.
Prof. Mérouane Debbah of the Technology Innovation Institute (TII) warns that current AI development relies on unsustainable, energy-intensive "bruteforce computing." He argues that the field needs more energy-efficient algorithms instead of simply scaling up GPUs. Debbah suggests neuromorphic computing as a potential solution, drawing inspiration from the human brain's energy efficiency. Why it matters: This critique highlights a crucial sustainability challenge for AI in the GCC and globally, as the region invests heavily in compute-intensive AI models.