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GCC AI Research

Weekly Digest

Jul 7 – Jul 13, 2025

Top Stories

A Feed-Forward Artificial Intelligence Pipeline for Sustainable Desalination under Climate Uncertainties: UAE Insights

arXiv · · Research Infrastructure

Researchers developed a two-stage AI pipeline to predict desalination performance efficiency losses due to climate factors in the UAE, achieving 98% accuracy. The model forecasts aerosol optical depth (AOD) and uses it to predict desalination efficiency, incorporating meteorological data. A dust-aware control logic was developed to optimize plant operations, and an interactive dashboard was created for decision support.

MIRA: A Novel Framework for Fusing Modalities in Medical RAG

arXiv · · Research Healthcare

MBZUAI researchers have introduced MIRA, a novel framework for improving the factual accuracy of multimodal large language models in medical applications. MIRA uses calibrated retrieval to manage factual risk and integrates image embeddings with a medical knowledge base for efficient reasoning. Evaluated on medical VQA and report generation benchmarks, MIRA achieves state-of-the-art results, with code available on GitHub.

Saudi Arabia to introduce AI education at all grade levels starting this year - Arab News

Arab News · · Policy Education

Saudi Arabia's Ministry of Education will introduce artificial intelligence (AI) education across all grade levels starting this academic year. The initiative aims to equip students with essential AI skills and knowledge to prepare them for future job markets. The curriculum will cover fundamental AI concepts, programming, and ethics. Why it matters: This nationwide initiative signals a major push to cultivate a domestic AI talent pool and position Saudi Arabia as a regional leader in AI innovation.

ScoreAdv: Score-based Targeted Generation of Natural Adversarial Examples via Diffusion Models

arXiv · · CV Research

The paper introduces ScoreAdv, a novel approach for generating natural adversarial examples (UAEs) using diffusion models. It incorporates an adversarial guidance mechanism and saliency maps to shift the sampling distribution and inject visual information. Experiments on ImageNet and CelebA datasets demonstrate state-of-the-art attack success rates, image quality, and robustness against defenses.