VentureOne, part of Abu Dhabi's Advanced Technology Research Council (ATRC), launched Nabat, a climate tech venture using AI and robotics for ecosystem restoration. Nabat employs drones, AI-powered software, and flexible seeding to conserve and restore mangroves, aiming to cover thousands of hectares in the UAE over seven years. Their technology enables precision mapping, seeding, and monitoring in remote areas. Why it matters: This initiative showcases the UAE's commitment to using advanced technology for environmental conservation and climate resilience, particularly in preserving vital ecosystems like mangroves, while also highlighting the growing AI startup ecosystem in the region.
Nanovate, an Arabic AI startup, has secured $1 million in pre-seed funding. The round was led by Hala Ventures, with participation from angel investors. Nanovate plans to use the funds to scale its operations across the GCC region. Why it matters: This investment highlights the growing interest in Arabic-focused AI solutions and the potential for startups to address specific regional needs.
This paper proposes a machine learning method for early detection and classification of date fruit diseases, which are economically important to countries like Saudi Arabia. The method uses a hybrid feature extraction approach combining L*a*b color features, statistical features, and Discrete Wavelet Transform (DWT) texture features. Experiments using a dataset of 871 images achieved the highest average accuracy using Random Forest (RF), Multilayer Perceptron (MLP), Naïve Bayes (NB), and Fuzzy Decision Trees (FDT) classifiers.
KAUST researchers are contributing new information about desert and mangrove plants to support Saudi Arabia's Green Initiative. They are creating a soil atlas for Saudi Arabia, studying soil profiles and microbial populations in hyperarid regions. The team has also compiled the world’s largest biobank of desert microbes, sequencing each microbe's genome. Why it matters: This research is crucial for ensuring the success and sustainability of large-scale greening efforts in arid environments like Saudi Arabia.
KAUST's Center for Desert Agriculture led Saudi Arabia to observe Fascination of Plants Day (FOPD) for the first time in the GCC. The global event, initiated by the European Plant Science Organization (EPSO), aims to raise awareness about the importance of plants and plant science. KAUST's research focuses on food, water, and the environment, addressing challenges of growing plants in extreme conditions. Why it matters: This highlights KAUST's role in advancing agricultural research and promoting environmental awareness in the region, crucial for addressing food security challenges in arid climates.
Dr. Laila Nehme, a French archaeologist from CNRS, visited KAUST as part of the Winter Enrichment Program (WEP) to discuss her work on Mada’in Saleh, also known as Al-Hijr or Hegra. Nehme co-directs the Saudi-French Archaeological Project and specializes in Nabatean epigraphy, studying the daily life of the ancient Nabateans through unearthed remains. Her team, working with the Saudi Commission for Tourism and Antiquities, is beginning its third four-year program to study the site. Why it matters: The research sheds light on the historical significance of Mada’in Saleh, a UNESCO World Heritage Site, and the Nabatean civilization's southernmost settlement, enhancing our understanding of the region's rich cultural heritage.
This paper introduces Arabic language integration into Vision-and-Language Navigation (VLN) in robotics, evaluating multilingual SLMs like GPT-4o mini, Llama 3 8B, Phi-3 14B, and Jais using the NavGPT framework. The study uses the R2R dataset to assess the impact of language on navigation reasoning through zero-shot sequential action prediction. Results show the framework enables high-level planning in both English and Arabic, though some models face challenges with Arabic due to reasoning limitations and parsing issues. Why it matters: This work highlights the need to improve language model planning and reasoning for effective navigation, especially to unlock the potential of Arabic-language models in real-world applications.