The UAE's Ministry of Energy and Infrastructure (MoEI) and the Technology Innovation Institute (TII) have partnered to create 3D maps of the UAE's mineral and renewable resources. TII's Directed Energy Research Center (DERC) will support MoEI in this effort, contributing its expertise to identify resources like geothermal energy and analyze geological data. The collaboration aims to support the UAE's Net Zero 2050 Strategy by enabling the exploration and utilization of undiscovered renewable and mineral resources. Why it matters: This initiative leverages local expertise to map domestic resources, aligning technological advancement with sustainability goals for the UAE.
The Autonomous Robotics Research Center (ARRC) is developing underwater communication systems, including a multimode modem prototype, and has filed three patents. One key technology is the Universal Underwater Software Defined Modem (UniSDM), which supports sound, magnetic induction, light, and radio waves. ARRC also developed a network management framework for automatic network slicing (ANS) of communication resources. Why it matters: These advancements are crucial for improving underwater exploration, industrial maintenance, and marine monitoring in the region, enabling more efficient and reliable communication for underwater robots.
The QU-NLP team presented their approach to the QIAS 2025 shared task on Islamic Inheritance Reasoning, fine-tuning the Fanar-1-9B model using LoRA and integrating it into a RAG pipeline. Their system achieved an accuracy of 0.858 on the final test, outperforming models like GPT 4.5, LLaMA, and Mistral in zero-shot settings. The system particularly excelled in advanced reasoning, achieving 97.6% accuracy. Why it matters: This demonstrates the effectiveness of domain-specific fine-tuning and retrieval augmentation for Arabic LLMs in complex reasoning tasks, even surpassing frontier models.
This paper introduces Saudi-Dialect-ALLaM, a LoRA fine-tuned version of the Saudi Arabian foundation model ALLaM-7B-Instruct-preview, designed to improve the generation of Saudi dialects (Najdi and Hijazi). The model is trained on a private dataset of 5,466 synthetic instruction-response pairs, with two variants explored: Dialect-Token and No-Token training. Results indicate that the Dialect-Token model achieves superior dialect control and fidelity compared to generic instruction models, although the dataset and model weights are not released.
This paper benchmarks reasoning-focused LLMs, especially DeepSeek models, on fifteen Arabic NLP tasks. The study uses zero-shot, few-shot, and fine-tuning strategies. Key findings include that three in-context examples improve F1 scores by over 13 points on classification tasks, DeepSeek outperforms GPT-4-mini by 12 F1 points on complex inference tasks in the zero-shot setting, and LoRA fine-tuning yields up to an additional 8 points in F1 and BLEU. Why it matters: The systematic evaluation provides insights into the performance of LLMs on Arabic NLP, highlighting the effectiveness of different strategies for improving performance and contributing to the development of more capable Arabic language models.
KAUST researchers have discovered biological clues in the Wahbah Crater in Saudi Arabia that could provide insights into the possibility of life on Enceladus, one of Saturn's moons. The researchers isolated 48 bacterial strains from the crater, identifying two with an adaptability suitable for the extreme environment of Enceladus. These strains thrive in high temperatures, salinity, and alkaline pH levels, mimicking conditions on the Saturn moon. Why it matters: This study highlights the potential of Saudi Arabia's extreme environments as valuable models for detecting extraterrestrial life and strengthens the country's growing interest in space exploration.
KAUST has commissioned Freire Shipyards to build the RV Thuwal II, Saudi Arabia's first regional class research vessel, expected to be completed in 2026. The vessel will be 50m long and designed for a 30-year lifespan, with modular labs and green propulsion technologies. It will support marine research in the Red Sea, accommodate 30 people, and aid in emergency response. Why it matters: This investment enhances Saudi Arabia's research capabilities in marine science and positions KAUST as a hub for Red Sea exploration and international scientific collaboration.
This paper introduces Diffusion-BBO, a new online black-box optimization (BBO) framework that uses a conditional diffusion model as an inverse surrogate model. The framework employs an Uncertainty-aware Exploration (UaE) acquisition function to propose scores in the objective space for conditional sampling. The approach is shown theoretically to achieve a near-optimal solution and empirically outperforms existing online BBO baselines across 6 scientific discovery tasks.