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.
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.
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.
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.