Researchers developed Atlas-Chat, a collection of LLMs for dialectal Arabic, focusing on Moroccan Arabic (Darija). They constructed an instruction dataset by consolidating existing Darija language resources and translating English instructions. Atlas-Chat models (2B, 9B, 27B) outperform state-of-the-art and Arabic-specialized LLMs like LLaMa, Jais, and AceGPT on Darija NLP tasks. Why it matters: This work addresses the gap in LLM support for low-resource Arabic dialects, providing a methodology for instruction-tuning and benchmarks for future research.
The paper introduces Juhaina, a 9.24B parameter Arabic-English bilingual LLM trained with an 8,192 token context window. It identifies limitations in the Open Arabic LLM Leaderboard (OALL) and proposes a new benchmark, CamelEval, for more comprehensive evaluation. Juhaina outperforms models like Llama and Gemma in generating helpful Arabic responses and understanding cultural nuances. Why it matters: This culturally-aligned LLM and associated benchmark could significantly advance Arabic NLP and democratize AI access for Arabic speakers.
Aramco and KAUST-incubated startup Lihytech are collaborating to develop Direct Lithium Extraction (DLE) technology in Saudi Arabia. Aramco is providing oilfield brines to Lihytech to assess their lithium extraction technology at KAUST Research and Technology Park. The collaboration supports Saudi Arabia's Vision 2030 and its growing demand for lithium in electric vehicles. Why it matters: This partnership could unlock a new critical mineral industry in Saudi Arabia, leveraging existing oilfield resources for sustainable lithium production.
KAUST researchers have demonstrated that incorporating tetrahydrotriazinium into perovskite/silicon tandem solar cells enhances both performance and stability. The additive increases hydrogen bonds in the perovskite film's crystal structure, improving power conversion efficiency to 33.7% and phase stability during testing under intense conditions. The improved cells showed more stability after 1500 hours of testing, modeling harsh environments. Why it matters: This research offers a pathway to more durable and efficient solar cells suitable for deployment in harsh climates like the Arabian Peninsula, potentially boosting renewable energy adoption in the region.
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.
FancyVideo, a new video generator, introduces a Cross-frame Textual Guidance Module (CTGM) to enhance text-to-video models. CTGM uses a Temporal Information Injector and Temporal Affinity Refiner to achieve frame-specific textual guidance, improving comprehension of temporal logic. Experiments on the EvalCrafter benchmark demonstrate FancyVideo's state-of-the-art performance in generating dynamic and consistent videos, also supporting image-to-video tasks.
KAUST and KFSHRC have developed NanoRanger, a new gene sequencing system for identifying mutations causing genetic diseases. NanoRanger offers a faster and simpler process to detect DNA abnormalities at base resolution, building on existing long-read sequencing technologies. The system is designed to be cheaper and faster, targeting diseases prevalent in Saudi Arabia due to consanguinity. Why it matters: The technology has the potential to improve diagnosis and treatment of Mendelian diseases, which are especially prevalent in the Arab world.
The paper introduces AlcLaM, an Arabic dialectal language model trained on 3.4M sentences from social media. AlcLaM expands the vocabulary and retrains a BERT-based model, using only 13GB of dialectal text. Despite the smaller training data, AlcLaM outperforms models like CAMeL, MARBERT, and ArBERT on various Arabic NLP tasks. Why it matters: AlcLaM offers a more efficient and accurate approach to Arabic NLP by focusing on dialectal Arabic, which is often underrepresented in existing models.
MBZUAI researchers introduce Web2Code, a new large-scale dataset and evaluation framework for training and benchmarking multimodal LLMs on webpage understanding and HTML code generation. The dataset includes webpage images, HTML code, and QA pairs about webpage content. Experiments demonstrate the dataset's utility in webpage understanding, code generation, and general visual domain tasks, with code and data available on Github.
KAUST and the Saudi Ministry of Environment, Water and Agriculture (MEWA) are collaborating on the Aquaculture Development Program (ADP) to advance Saudi Arabia's food security goals under Vision 2030. The ADP aims to increase domestic seafood production to 530,000 tons annually by 2030 through sustainable aquaculture practices. KAUST is employing a multidisciplinary team and innovative approaches like Integrated Multitrophic Aquaculture (IMTA) to optimize resource use and minimize environmental impact. Why it matters: This partnership aims to transform Saudi Arabia's aquaculture sector, reducing reliance on imports and promoting economic diversification while preserving marine biodiversity.
KAUST spinout iyris, an AgriClimate Tech company, raised $16 million in Series A funding led by Ecosystem Integrity Fund. The funding will help iyris scale the sales and delivery of its SecondSky greenhouse covers and nets internationally. iyris' SecondSky technology was developed at KAUST and increases crop yields while reducing input costs. Why it matters: This funding highlights the potential of KAUST-backed startups to address critical challenges in agriculture and sustainability, particularly in harsh environments.
KAUST and Saudi Aramco collaborated to develop a laser-based sensor for detecting trace amounts of gas leaks in petrochemical plants. The sensor uses machine learning to identify specific gases, differentiating it from previous sensors that only detect large leaks. The technology can differentiate between closely related industrial gases like benzene, toluene, ethyl benzene and xylene (BTEX). Why it matters: This innovation enables proactive monitoring and rapid pinpointing of leaks, enhancing safety, environmental protection, and operational efficiency in the petrochemical industry.
KAUST researchers have developed an energy-efficient wastewater treatment process that generates high-quality effluent suitable for reuse. A pilot plant in Jeddah, operating since July 2022 in collaboration with MODON, treats 50,000 liters of wastewater daily off-grid, generating 1.5 kWh of electrical energy per 1,000 liters treated. The plant utilizes an anaerobic membrane bioreactor (AnMBR) coupled with UV disinfection, removing up to 99.9999% of microorganisms and producing less solid waste. Why it matters: This decentralized, energy-independent system offers a sustainable solution for water treatment in resource-scarce regions of the Middle East, aligning with Saudi Arabia's sustainability goals.
The paper introduces MedPromptX, a clinical decision support system using multimodal large language models (MLLMs), few-shot prompting (FP), and visual grounding (VG) for chest X-ray diagnosis, integrating imagery with EHR data. MedPromptX refines few-shot data dynamically for real-time adjustment to new patient scenarios and narrows the search area in X-ray images. The study introduces MedPromptX-VQA, a new visual question answering dataset, and demonstrates state-of-the-art performance with an 11% improvement in F1-score compared to baselines.
The paper introduces AraPoemBERT, an Arabic language model pretrained exclusively on 2.09 million verses of Arabic poetry. AraPoemBERT was evaluated against five other Arabic language models on tasks including poet's gender classification (99.34% accuracy) and poetry sub-meter classification (97.79% accuracy). The model achieved state-of-the-art results in these and other downstream tasks, and is publicly available on Hugging Face. Why it matters: This specialized model advances Arabic NLP by providing a new state-of-the-art tool tailored for the nuances of classical Arabic poetry.
KAUST researchers have developed a green synthetic biology approach using engineered algae to replicate the complex fragrances of agarwood, also known as oudh. They catalogued the chemical diversity of sesquiterpenes (STPs) in 58 agarwood samples and reproduced some of the chemical complexity of agarwood STPs in algae using synthetic biology. The team used the green alga Chlamydomonas reinhardtii to produce nine distinct STP chemical products widely found in agarwood, offering a sustainable alternative to harvesting endangered trees. Why it matters: This research provides a sustainable route for producing sought-after fragrances, reducing pressure on endangered agarwood tree populations and promoting green chemistry in the region.
Researchers from MBZUAI have developed XReal, a diffusion model for generating realistic chest X-ray images with precise control over anatomy and pathology location. The model utilizes an Anatomy Controller and a Pathology Controller to introduce spatial control in a pre-trained Text-to-Image Diffusion Model without fine-tuning. XReal outperforms existing X-ray diffusion models in realism, as evaluated by quantitative metrics and radiologists' ratings, and the code/weights are available.
KAUST researchers have developed a new synthetic biology process using metabolically engineered algae to produce fragrant sesquiterpenoids, the core compounds in agarwood and other perfumes. The process, developed by the Lauersen and Szekely groups, achieved yields 25 times higher than previous methods and allows for the synthesis of 103 types of fragrant sesquiterpenoids. It also incorporates an energy-efficient nanofiltration step and operates at room temperature with minimal waste. Why it matters: This sustainable bioprocess offers a green alternative to environmentally damaging harvesting of natural resources for the $44 billion fragrance industry, with potential applications in drug development.
KAUST scientists developed a new perovskite solar cell design using thin perovskite layers at the top and bottom of the interface. The new design achieves a power conversion efficiency of 25.6%, comparable to silicon solar cells, with only a 5% efficiency loss after 1000 hours of high heat exposure. The key innovation is the use of a specific ligand that interacts effectively with the 3D perovskites for passivation, maintaining purity in the thin layers. Why it matters: This advancement enhances the stability and efficiency of perovskite solar cells, making them a more viable and cost-effective alternative to silicon, especially for countries like Saudi Arabia aiming to increase renewable energy reliance.
KAUST researchers have developed new techniques to produce nutritious microalgae in industrial volumes using seawater-adapted Spirulina and Chlorella strains. This innovation eliminates the need for freshwater, making algae-based livestock feed production sustainable and economically viable. The new Saudi Center for Algal Biotechnology Development and Aquaculture will scale up operations from a 1,000 square meter pilot plant to 42,000 square meters. Why it matters: This could help Saudi Arabia decrease its dependency on imported feed and raw food materials, aligning with its Vision 2030 goals for increased domestic food security.
Researchers from MBZUAI have released MobiLlama, a fully transparent open-source 0.5 billion parameter Small Language Model (SLM). MobiLlama is designed for resource-constrained devices, emphasizing enhanced performance with reduced resource demands. The full training data pipeline, code, model weights, and checkpoints are available on Github.
The paper introduces ArabianGPT, a suite of transformer-based language models designed specifically for Arabic, including versions with 0.1B and 0.3B parameters. A key component is the AraNizer tokenizer, tailored for Arabic script's morphology. Fine-tuning ArabianGPT-0.1B achieved 95% accuracy in sentiment analysis, up from 56% in the base model, and improved F1 scores in summarization. Why it matters: The models address the gap in native Arabic LLMs, offering better performance on Arabic NLP tasks through tailored architecture and tokenization.
KAUST researchers published a roadmap in Science for commercializing perovskite/silicon tandem solar cells, combining efficient light absorption with long-term stability. The roadmap addresses key challenges like real-world condition variability via geographical testing, accelerated stability testing, and high material costs. The researchers propose paradigms for both monolithic and mechanically stacked tandem production lines to identify cost-reduction opportunities. Why it matters: This work paves the way for affordable, accessible clean energy in Saudi Arabia and the world, with the market for perovskite/silicon tandems expected to exceed $10 billion within a decade.
KAUST researchers, in collaboration with Spanish scientists, have released the Global Ocean Gene Catalog 1.0, the world's largest open-source catalog of marine microbes. The catalog, created using the KAUST Metagenomic Analysis Platform (KMAP), matches microbial class with gene function, geographic location, and habitat type, including 317 million unique gene clusters. The catalog analyzes 2102 ocean samples taken from different depths and locations around the world. Why it matters: This resource will enable researchers to investigate ocean ecosystems, track pollution impact, and explore biotechnology applications, potentially driving significant advances in fields like antibiotic discovery and plastic degradation.
Researchers introduce TomFormer, a transformer-based model for accurate and early detection of tomato leaf diseases, with the goal of deployment on the Hello Stretch robot for real-time diagnosis. TomFormer combines a visual transformer and CNN, achieving state-of-the-art results on KUTomaDATA, PlantDoc, and PlantVillage datasets. KUTomaDATA was collected from a greenhouse in Abu Dhabi, UAE.
KAUST's Shaheen III has been confirmed as the Middle East’s most powerful supercomputer, ranking 20th globally. Built by HPE, Shaheen III is six times faster than KAUST’s existing Shaheen II system, exceeding the processing power of 500,000 MacBook Pros. It will support mathematical model construction for scientific discovery, engineering design, and policy support, particularly in sustainability and alignment with Vision 2030. Why it matters: This positions KAUST and Saudi Arabia as leaders in high-performance computing, enabling advanced research across climate change, clean energy, and other critical fields.
KAUST and Chinese companies Shandong Lianxin Environmental Protection Technology and Hangzhou Hecai Technology will manufacture green plastics based on KAUST technology. The plastics, high molar mass aliphatic polycarbonates, are for biomedical products and food packaging due to their biodegradability and biocompatibility. KAUST's method creates these polycarbonates using CO2 and sustainable raw materials without toxic metals, with production scaling over two years. Why it matters: This partnership highlights KAUST's role in developing sustainable materials and bringing them to market, with potential impact on reducing reliance on traditional plastics in sensitive applications.
Ceer and KAUST are partnering to research and develop innovations in smart mobility, including connectivity and autonomous driving technologies. The collaboration aims to transform research into economically productive innovations, supporting Saudi-based SMEs and the automotive manufacturing industry. Ceer and KAUST will share facilities and conduct collaborative activities to foster knowledge exchange and create jobs. Why it matters: This partnership signifies a crucial step towards diversifying Saudi Arabia's economy and advancing technological capabilities in the electric vehicle sector within the Kingdom.
G42's Core42 has released Jais, a collection of Arabic large language models, including a 13B parameter version. Jais-13B is trained on a 395B token dataset containing Arabic and English text. According to the blog post, Jais-13B achieves state-of-the-art results on Arabic NLP benchmarks. Why it matters: This release establishes a new benchmark for Arabic language AI, potentially enabling more sophisticated and culturally relevant applications.
G42's Core42 has released Jais, a new Arabic large language model. Jais includes 13 billion parameters and was trained on a dataset of 126B tokens, including 43B Arabic tokens. According to the developers, Jais achieves state-of-the-art results on Arabic benchmarks and competitive performance on English benchmarks. Why it matters: Jais represents a significant step forward for Arabic NLP, providing a powerful new tool for researchers and developers in the region.
MBZUAI has released Jais and Jais-chat, two new open generative large language models (LLMs) with a focus on Arabic. The 13 billion parameter models are based on the GPT-3 architecture and pretrained on Arabic, English, and code. Evaluation shows state-of-the-art Arabic knowledge and reasoning, with competitive English performance.
Excyton, a startup based at KAUST, has developed a novel display technology called “TurboLED” that reduces power consumption by 50% and increases the color range rendered on displays to 76%. The technology utilizes a six sub-pixel format (light and deep RGB) compared to the standard three, saving energy by using lighter colors most of the time. Excyton received $2 million in funding from KAUST Innovation Ventures and collaborated with KAUST to develop the technology. Why it matters: This innovation could significantly improve the battery life of mobile devices while also enhancing display quality, providing a competitive advantage for devices manufactured in the region.
KAUST and LONGi, a solar energy company, have signed an MoU to collaborate on solar energy innovation. The partnership aims to develop and deploy solar technologies, focusing on improving the efficiency of photovoltaic technologies. Joint projects will include testing PV module concepts, developing new materials, and optimizing performance, alongside talent development programs. Why it matters: This collaboration aligns with Saudi Vision 2030 and the Saudi Green Initiative, fostering sustainable energy solutions and local expertise in the region.
This paper introduces a convolutional transformer model for classifying tomato maturity, along with a new UAE-sourced dataset, KUTomaData, for training segmentation and classification models. The model combines CNNs and transformers and was tested against two public datasets. Results showed state-of-the-art performance, outperforming existing methods by significant margins in mAP scores across all three datasets.
The paper introduces Sparse-Quantized Representation (SpQR), a new compression format and quantization technique for large language models (LLMs). SpQR identifies outlier weights and stores them in higher precision while compressing the remaining weights to 3-4 bits. The method achieves less than 1% accuracy loss in perplexity for LLaMA and Falcon LLMs and enables a 33B parameter LLM to run on a single 24GB consumer GPU. Why it matters: This enables near-lossless compression of LLMs, making powerful models accessible on resource-constrained devices and accelerating inference without significant accuracy degradation.
Researchers at KAUST, USTC, and SUSTech have developed a method for carbon capture and storage using guanidinium sulfate salt to create clathrate structures that trap CO2 molecules. This salt-based structure mimics methane hydrate activity and captures CO2 through physisorption, without water or nitrogen interference. The method allows CO2 to be carried as a solid powder at ambient temperature and pressure, offering a less energy-intensive alternative to traditional methods. Why it matters: This innovation introduces a new, energy-efficient way to store and transport CO2 as a solid, potentially revolutionizing carbon capture and storage technologies in the region and beyond.
KAUST and King Faisal Specialist Hospital and Research Centre (KFSH&RC) are collaborating to develop bioelectronic sensors for rapid pathogen detection. These sensors aim to provide cheap and accurate results, potentially replacing conventional lab tests. A COVID-19 saliva test developed by KAUST researchers showed comparable sensitivity to PCR tests with a 15-minute turnaround. Why it matters: This partnership accelerates the development of novel diagnostic tools, which could improve healthcare accessibility in remote areas and low-income countries within the region.
KAUST researchers have developed a perovskite/silicon tandem solar cell with a power conversion efficiency (PCE) of 33.2%, surpassing the previous record of 32.5% held by Helmholtz Zentrum Berlin (HZB). The tandem device was certified by the European Solar Test Installation (ESTI) and listed at the top of the NREL efficiency chart. The cell combines perovskite top cells for blue light absorption with silicon bottom cells for red light absorption. Why it matters: This breakthrough could accelerate the adoption of high-performance photovoltaic modules, which is critical for achieving global renewable energy goals.
Al-Miyah Solutions, a KAUST spin-off, has installed a decentralized wastewater treatment unit in Rabigh, Saudi Arabia. The mobile, modular technology converts wastewater into reusable water for areas lacking centralized sewer access, addressing a need for 40% of Saudi households. The technology, developed at KAUST's Water Desalination and Reuse Center, uses aerobic granular sludge and gravity-driven membrane filtration. Why it matters: This deployment offers a sustainable and cost-effective solution for wastewater treatment and reuse in remote areas of the Kingdom, reducing reliance on costly centralized systems.
KAUST startup Lihytech has raised US$6 million in funding from Ma'aden and the KAUST Innovation Ventures Fund. Lihytech's patented membrane technology, developed by Professor Zhiping Lai at KAUST, extracts battery-grade lithium from sources like seawater. The funding will be used to build a pilot facility at KAUST to extract lithium from the Red Sea and other in-Kingdom resources. Why it matters: This investment supports Saudi Arabia's goal of developing a complete electric vehicle value chain and becoming a key player in meeting global lithium demand.
Researchers from MBZUAI have developed EchoCoTr, a novel spatiotemporal deep learning method for estimating left ventricular ejection fraction (LVEF) from echocardiograms. EchoCoTr combines CNNs and vision transformers to overcome the limitations of each when applied to medical video data. The method achieves state-of-the-art results on the EchoNet-Dynamic dataset, demonstrating improved accuracy compared to existing approaches, with code available on GitHub.
KAUST Associate Professor Peiying Hong has developed a wastewater treatment method using anaerobic membrane bioreactor (AnMBR) technology, which converts organic carbon into methane. In partnership with MODON, a pilot program is operational in Jeddah, treating 23,000 liters of wastewater daily using UV light and hydrogen peroxide for disinfection. This system produces clean water suitable for agriculture and biomass for fertilizer, with a smaller footprint and lower energy consumption than traditional aerobic methods. Why it matters: The AnMBR technology aligns with Saudi Vision 2030's water reuse objectives, reducing reliance on energy-intensive desalination and offering a sustainable solution for water-stressed regions.
KAUST researchers have developed a CRISPR-Cas system using a heat-stable Cas13 protein (TccCas13a) from Thermoclostridium caenicola, compatible with RT-LAMP for rapid viral detection. The new assay, named OPTIMA-dx, enhances the specificity of RT-LAMP tests by reducing false positives in SARS-CoV-2 detection. The team, led by Dr. Magdy Mahfouz and doctoral student Ahmed Mahas, is transitioning the product to a startup phase for commercialization. Why it matters: This innovation could significantly improve point-of-care diagnostics for COVID-19 and other infections by providing a more accurate and easier-to-use testing method.
KAUST, Intel, and Brightskies have launched REDD, a collaborative self-driving mobility platform, converting a conventional car into a self-driving vehicle with integrated AI software. Brightskies developed the self-driving system, powered by Intel® NUC platforms, utilizing their BrightDrive system. KAUST researchers will use the vehicle to test new techniques, leveraging real-world data to improve self-driving technologies. Why it matters: This partnership advances autonomous vehicle research in Saudi Arabia, aligning with the Kingdom's Vision 2030 by creating a platform for innovation and testing in a real-world environment.
Qatar Computing Research Institute (QCRI) has developed NatiQ, an end-to-end text-to-speech (TTS) system for Arabic utilizing encoder-decoder architectures. The system employs Tacotron-based models and Transformer models to generate mel-spectrograms, which are then synthesized into waveforms using vocoders like WaveRNN, WaveGlow, and Parallel WaveGAN. Trained on in-house speech data featuring a neutral male voice (Hamza) and an expressive female voice (Amina), NatiQ achieves a Mean Opinion Score (MOS) of 4.21 and 4.40, respectively. Why it matters: This research advances Arabic language technology, providing high-quality TTS synthesis that can enhance accessibility and usability of digital content for Arabic speakers.
KAUST startup uODS signed an MoU with Saudi Aramco Base Oil Company (Luberef) to develop and deploy technology removing sulfur from hydrocarbons. The uODS process, based on KAUST's sonochemistry research, reduces sulfur in marine fuels to meet IMO 2020 regulations. Luberef aims to reduce its environmental footprint by piloting the uODS technology at its Jeddah refineries, with uODS set to produce 10 tons per day of desulfurized fuel for testing. Why it matters: The partnership demonstrates KAUST's role in addressing Saudi Arabia's environmental goals and showcases the potential of university spin-offs to contribute to a more sustainable oil industry in the region.
KAUST researchers have developed an artificial electronic retina mimicking the behavior of rod retina cells, utilizing a hybrid perovskite material (MAPbBr3) embedded in PVDF-TrFE-CEF. The photoreceptor array, made of metal-insulator-metal capacitors, detects light intensity through changes in electrical capacitance. Connected to a CMOS-sensing circuit and a spiking neural network, the 4x4 array achieved around 70 percent accuracy in recognizing handwritten numbers. Why it matters: This research paves the way for energy-efficient neuromorphic vision sensors and advanced computer vision applications, potentially revolutionizing camera technology.
KAUST has inaugurated the world's first Coral Probiotics Village (CPV) in the Red Sea, a natural laboratory for coral reef research. The CPV is located 20 km off the KAUST campus and will focus on developing solutions for coral preservation and restoration using Beneficial Microorganisms for Corals (BMCs). Researchers aim to mitigate the impacts of thermal stress and pathogens on corals, potentially preventing coral mortality. Why it matters: This initiative positions KAUST as a leader in marine biotechnology and offers innovative approaches to protect coral reefs in the Red Sea and worldwide.
KAUST researchers have discovered that the bacterium Enterobacter sp. SA187, found in desert plants, enhances plant salt tolerance by triggering sulfur metabolism. Salt stress prompts the bacteria to release sulfur metabolites, which then generate the antioxidant glutathione in the plant, protecting it from salt-induced damage. A KAUST startup aims to commercialize SA187 as a probiotic treatment for seeds and crops. Why it matters: This research offers a biotechnological approach to enable saline agriculture, which is crucial for water-scarce regions like Saudi Arabia that rely on energy-intensive desalination.
KAUST researchers are using 3D printing with a novel calcium carbonate ink to create coral support structures that accelerate coral restoration. Their approach, named 3D CoraPrint, involves printing coral microfragments onto the structure, offering a head start for reef recovery. Two methods were developed: printing a mold for reproduction and direct printing for customization. Why it matters: This eco-friendly technique provides a potentially scalable solution to combat coral reef degradation, leveraging advanced materials and fabrication for ecological conservation in the region and beyond.