MBZUAI and Silal, an Abu Dhabi-based agri-food company, signed an MoU at COP28 to bring AI innovation to agriculture and food production. The agreement establishes a joint AI Center of Excellence to develop the UAE's food production sector, improve food security, and enhance sustainability. Both parties will conduct joint research, exchange expertise, and support startups focused on improving efficiency and innovation in the UAE’s food sector. Why it matters: The partnership aligns with the UAE's National Strategy for Food Security 2051 and aims to leverage AI for sustainable food production, addressing critical challenges like climate change and resource management.
KAUST Assistant Professor Dana Alsulaiman was named a L'Oréal-UNESCO For Women in Science Middle East Regional Young Talent. Alsulaiman was recognized for her work developing biomarker detection technologies for early and accurate disease detection. KAUST Ph.D. student Lila Aldakheel also received an award for her research on microplastics in mangrove forests. Why it matters: The recognition highlights the rising prominence and impact of female scientists at Saudi institutions in addressing key challenges like healthcare and environmental sustainability.
The researchers introduce KAU-CSSL, the first continuous Saudi Sign Language (SSL) dataset focusing on complete sentences. They propose a transformer-based model using ResNet-18 for spatial feature extraction and a Transformer Encoder with Bidirectional LSTM for temporal dependencies. The model achieved 99.02% accuracy in signer-dependent mode and 77.71% in signer-independent mode, advancing communication tools for the SSL community.
Professor Hava Siegelmann, a computer science expert, is researching lifelong learning AI, drawing inspiration from the brain's abstraction and generalization capabilities. The research aims to enable intelligent systems in satellites, robots, and medical devices to adapt and improve their expertise in real-time, even with limited communication and power. The goal is to develop AI systems applicable for far edge computing that can learn in runtime and handle unanticipated situations. Why it matters: This research could lead to more resilient and adaptable AI systems for critical applications in remote and resource-constrained environments, with potential benefits for various sectors in the Middle East.