The Saudi Data & AI Authority (SDAIA) has launched a national curriculum focused on data and artificial intelligence. This initiative aims to equip the Saudi workforce with essential skills in these critical technological fields. The curriculum is expected to be integrated across educational and training institutions nationwide. Why it matters: This represents a significant policy move by Saudi Arabia to build national human capital and establish a robust foundation for its future AI and data-driven economy.
Saudi Arabian AI infrastructure company HUMAIN has secured up to $1.2 billion in funding. The funds will be used to deploy AI infrastructure to support the Kingdom’s Vision 2030 plan. HUMAIN aims to accelerate AI adoption in Saudi Arabia. Why it matters: This represents a significant investment in domestic AI capabilities, signaling Saudi Arabia's commitment to becoming a major player in the AI landscape.
The Saudi Data and AI Authority (SDAIA) has laid the foundation stone for a new 480MW government data center in Riyadh. This project is a collaboration with Hexagon, a data center solutions provider, aimed at significantly expanding Saudi Arabia's digital infrastructure capacity. The initiative is designed to support the Kingdom's ambitious digital transformation and artificial intelligence strategies. Why it matters: This major infrastructure development is fundamental to achieving Saudi Vision 2030 goals by providing the robust computational backbone necessary for advanced AI applications and public sector digitization.
The Saudi Data & AI Authority (SDAIA) has launched a national curriculum focused on data and artificial intelligence. This initiative aims to develop local talent and capabilities across various educational levels within the Kingdom. The curriculum is designed to equip the Saudi workforce with essential skills for the future digital economy. Why it matters: This curriculum represents a strategic effort by Saudi Arabia to build a skilled workforce, crucial for advancing its national AI agenda and diversifying its economy.
Researchers at KAUST have developed a new polymer membrane for desalination that operates at ambient temperature and pressure. The membrane achieves high salt rejection with lower energy demand compared to conventional methods. It is currently being tested at pilot scale at KAUST. Why it matters: This technology could improve water sustainability and reduce energy consumption in desalination, addressing critical water challenges in arid regions like Saudi Arabia.
MBZUAI researchers introduce DuwatBench, a new benchmark for multimodal understanding of Arabic calligraphy. The dataset contains 1,272 samples across six calligraphic styles with detailed annotations to evaluate visual-text alignment. Evaluation of 13 multimodal models reveals challenges in processing calligraphic variations and artistic distortions, highlighting the need for culturally grounded AI research.
A national survey in Saudi Arabia of 330 participants reveals that 93% are actively using Generative AI, primarily for text-based tasks, while awareness and understanding remain uneven. Participants recognize benefits like productivity but caution against risks such as privacy, misinformation, and ethical misuse. The study highlights the need for AI literacy, culturally aligned solutions, and stronger frameworks for responsible deployment in Saudi Arabia.
The paper presents MonoRace, an onboard drone racing approach using a monocular camera and IMU. The system combines neural-network-based gate segmentation with a drone model for robust state estimation, along with offline optimization using gate geometry. MonoRace won the 2025 Abu Dhabi Autonomous Drone Racing Competition (A2RL), outperforming AI teams and human world champions, reaching speeds up to 100 km/h. Why it matters: This demonstrates a significant advancement in autonomous drone racing, achieving champion-level performance with a resource-efficient monocular system, validated in a real-world competition setting in the UAE.
KAUST has established the KAUST Quantum Foundry to strengthen Saudi Arabia’s ability to fabricate commercial quantum hardware. It will provide shared access to KAUST quantum cleanrooms, supporting device prototyping and process development. The Foundry will focus on process standardization and the development of Process Design Kits (PDKs) to enable researchers to design and fabricate devices. Why it matters: This initiative reinforces KAUST's role as a national hub for advanced research infrastructure and supports Saudi Arabia’s long-term innovation priorities in quantum technologies.
This paper introduces a hybrid deep learning and machine learning pipeline for classifying construction and demolition waste. A dataset of 1,800 images from UAE construction sites was created, and deep features were extracted using a pre-trained Xception network. The combination of Xception features with machine learning classifiers achieved up to 99.5% accuracy, demonstrating state-of-the-art performance for debris identification.
BABL AI reports that Saudi Arabia has launched a 480-MW data center in Hexagon, positioning the Kingdom in the global compute race. The project signifies a major investment in infrastructure to support AI and digital transformation initiatives. The Hexagon data center will likely attract further investment and development in related technology sectors. Why it matters: This move establishes Saudi Arabia as a significant player in the global AI infrastructure landscape and signals its commitment to becoming a technology hub.
Oman's digital economy investments have reached a significant total of $3.1 billion. This substantial funding is aimed at bolstering various sectors within the digital realm, including technology infrastructure, digital transformation initiatives, and potentially emerging technologies like artificial intelligence. This announcement underscores the Sultanate's strategic focus on developing its non-oil sectors. Why it matters: This considerable investment highlights Oman's commitment to diversifying its economy and fostering a robust digital ecosystem, which is crucial for regional technological advancement and job creation.
The paper introduces Yet another Policy Optimization (YaPO), a reference-free method for learning sparse steering vectors in the latent space of a Sparse Autoencoder (SAE) to steer LLMs. By optimizing sparse codes, YaPO produces disentangled, interpretable, and efficient steering directions. Experiments show YaPO converges faster, achieves stronger performance, exhibits improved training stability and preserves general knowledge compared to dense steering baselines.
This paper introduces an explainable machine learning framework for early-stage chronic kidney disease (CKD) screening, specifically designed for low-resource settings in Bangladesh and South Asia. The framework utilizes a community-based dataset from Bangladesh and evaluates multiple ML classifiers with feature selection techniques. Results show that the ML models achieve high accuracy and sensitivity, outperforming existing screening tools and demonstrating strong generalizability across independent datasets from India, the UAE, and Bangladesh.