KAUST AgriTech startups Natufia and Edama won NASA's Deep Space Food Challenge for their joint solution integrating automated hydroponics, macroalgae farming, and composting. Their closed-loop system efficiently recovers and reuses waste resources to maximize productivity and reduce dependence on external inputs. The system can supply a diverse and nutritious menu of fruits, vegetables, and algae-based dietary supplements for astronauts. Why it matters: This award highlights the growing strength of the Saudi entrepreneurial ecosystem in developing innovative AgriTech solutions with global applications, particularly for sustainable food production.
KAUST researchers have developed a passive cooling system that uses solar energy to evaporate water and regenerate salt for reuse, achieving temperatures as low as 3.6 degrees Celsius. The system uses ammonium nitrate (NH4NO3) due to its high solubility and low cost. The crystallized salt stores solar energy and can be reused for cooling when needed. Why it matters: This off-grid design offers a sustainable and inexpensive cooling solution for communities in hot regions with limited electricity access, addressing a critical need exacerbated by climate change.
A KAUST-led team developed NIRVANA, a portable, briefcase-sized device for rapid detection and sequencing of SARS-CoV-2, influenza, and other viruses. The test utilizes isothermal recombinase amplification (RPA) and was validated on clinical samples and wastewater. NIRVANA can differentiate SARS-CoV-2 strains and doesn't require expensive infrastructure. Why it matters: This innovation enables rapid, decentralized virus detection and surveillance, crucial for pandemic response and monitoring new variants across the region.
KAUST and Aramco have developed a one-step crude-to-chemicals (C2C) technology that converts crude oil to light olefins in a single-reactor system. The technology, published in Nature Catalysis, aims to maximize the production of materials used in daily life over fuels. Aramco is pursuing growth opportunities in petrochemicals using the C2C method. Why it matters: The C2C breakthrough aligns with Saudi Vision 2030 and could reduce the carbon footprint associated with oil use, creating jobs and supporting a thriving economy.
KAUST is leading a $3.5 million investment in Natufia, an Estonian startup that developed a smart indoor kitchen garden, with $2 million awarded through the KAUST Innovation Fund. Natufia's hydroponic technology allows year-round harvesting of herbs, greens, and vegetables at home, regardless of climate. By taking up residency at the KAUST Research and Technology Park, Natufia aims to expand R&D capabilities and create job opportunities in Saudi Arabia. Why it matters: This investment addresses the challenge of accessing fresh produce in regions like Saudi Arabia while reducing food waste and promoting sustainable agriculture through innovative technology.
Researchers from KAUST and University of Toronto have created a two-sided perovskite/silicon tandem solar cell that exceeds the performance limits for tandem configurations. The bifacial design captures both direct sunlight and light reflected from the ground (albedo). Outdoor testing demonstrated efficiencies beyond commercial silicon solar panels. Why it matters: This innovation promises ultra-high power generation at affordable costs, potentially revolutionizing the photovoltaics market in the region and globally.
The paper introduces AraGPT2, a suite of pre-trained transformer models for Arabic language generation, with the largest model (AraGPT2-mega) containing 1.46 billion parameters. Trained on a large Arabic corpus of internet text and news, AraGPT2-mega demonstrates strong performance in synthetic news generation and zero-shot question answering. To address the risk of misuse, the authors also released a discriminator model with 98% accuracy in detecting AI-generated text. Why it matters: This release of both the model and discriminator fills a critical gap in Arabic NLP and encourages further research and applications in the field.
KAUST researchers have fabricated and tested high-efficiency perovskite-silicon tandem solar cells optimized for hot climates. The tandem device is more stable than conventional perovskite cells and optimized for industry use. Outdoor testing at KAUST confirmed performance improvements, indicating bromide-lean perovskite top cells with narrower bandgaps are ideal. Why it matters: The research demonstrates the viability of tandem silicon-perovskite cells in harsh environments, paving the way for more efficient solar technology in the region and globally.
This paper introduces GigaBERT, a customized bilingual BERT model pre-trained for Arabic NLP and English-to-Arabic zero-shot transfer learning. The study evaluates GigaBERT's performance on four information extraction tasks: named entity recognition, part-of-speech tagging, argument role labeling, and relation extraction. Results show that GigaBERT outperforms mBERT, XLM-RoBERTa, and AraBERT in both supervised and zero-shot transfer settings. Why it matters: GigaBERT advances Arabic NLP by providing a high-performing, publicly available model tailored for the complexities of the Arabic language and cross-lingual applications.
Researchers at the American University of Beirut (AUB) have released AraBERT, a BERT model pre-trained specifically for Arabic language understanding. The model was trained on a large Arabic corpus and compared against multilingual BERT and other state-of-the-art methods. AraBERT achieved state-of-the-art performance on several tested Arabic NLP tasks including sentiment analysis, named entity recognition, and question answering. Why it matters: This release provides the Arabic NLP community with a high-performing, open-source language model, facilitating further research and development.
Researchers introduce AraNet, a deep learning toolkit for Arabic social media processing. The toolkit uses BERT models trained on social media datasets to predict age, dialect, gender, emotion, irony, and sentiment. AraNet achieves state-of-the-art or competitive performance on these tasks without feature engineering. Why it matters: The public release of AraNet accelerates Arabic NLP research by providing a comprehensive, deep learning-based tool for various social media analysis tasks.
Researchers from KAUST, University of St. Andrews, and the Center for Unconventional Processes of Sciences have developed an uncrackable security system using optical chips. The system uses silicon chips with complex structures that are irreversibly changed to send information, achieving "perfect secrecy" through a one-time key. This method leverages classical physics and the second law of thermodynamics to ensure that keys are never stored, communicated, or recreated, making interception impossible. Why it matters: This breakthrough has the potential to revolutionize communications privacy globally, offering an unbreakable method for securing confidential data on public channels.
KAUST spinout Sadeem, which develops wireless environmental sensing systems, has secured $2.6 million in co-investment from the KAUST Innovation Fund and Saudi Aramco's Wa'ed Ventures. The funding will support product updates, development of new monitoring technologies, and business development. Sadeem's technology is used in cities including Mexico City and Texas for flood, traffic, weather, and air quality monitoring. Why it matters: The investment highlights the growing venture capital ecosystem in Saudi Arabia and will allow Sadeem to further develop its sensor technology for environmental monitoring and disaster prevention.
KAUST has launched self-driving shuttles on its campus, making it the first adopter of autonomous vehicles in Saudi Arabia. The pilot project utilizes vehicle technology from Local Motors and EasyMile. SAPTCO will operate the autonomous shuttles and manage operations with Saudi staff. Why it matters: This initiative advances Saudi Arabia's 2030 Vision and positions KAUST as a regional leader in smart city development and AI research.
UnitX, a KAUST spin-out startup focusing on cloud-based supercomputing, has secured $2 million in co-investment from the KAUST Innovation Fund and Saudi Aramco’s Wa’ed Ventures Fund. UnitX aims to democratize supercomputing by partnering with institutions to make spare supercomputing capacity available via the cloud. The funding will support UnitX in helping enterprises leverage high-performance data analytics and AI at scale, particularly in underserved industry verticals in Saudi Arabia. Why it matters: This investment highlights the growing focus on AI infrastructure and supercomputing accessibility in Saudi Arabia, enabling broader adoption of advanced technologies across various sectors.
KAUST and Research Products Development Company (RPDC) have signed a partnership agreement to support technology commercialization and early-stage startups in Saudi Arabia. RPDC and the KAUST Innovation Fund will co-invest in startups and establish a joint mentorship and startup exchange program. RPDC will co-invest or match KAUST funding of up to $2 million into deep tech startups at the proof-of-concept, seed and series A funding stages. Why it matters: This collaboration aims to bolster the innovation ecosystem within Saudi Arabia, accelerating the transition of academic research to commercial applications.
The Saudi Vaccine and Biomanufacturing Center (SVBC), the first of its kind in the Middle East, broke ground at KAUST on December 15. The center will develop vaccines and biopharmaceutical products under good manufacturing practice (GMP) standards. It is a joint project championed by the Ministry of Energy, Industry and Mineral Resources through the Industrial Clusters Program and supported by KACST. Why it matters: The center will serve as a national platform for pharmaceutical innovation and address epidemic risks in the Kingdom, such as MERS-CoV.
KAUST spin-out company NOMADD, which specializes in robotic PV cleaning systems, has secured a Series B investment from Saudi construction company CEPCO. The investment will support NOMADD's project pipeline and growth ambitions, enabling them to scale operations and serve more customers. CEPCO will also advise on technology development and local manufacturing in Saudi Arabia. Why it matters: This investment validates KAUST's innovation fund strategy and supports the deployment of sustainable energy solutions in the region, leveraging local expertise and manufacturing.
KAUST Professor Derya Baran and her team at startup iyris have developed transparent solar panels that can turn windows into a source of renewable energy. The technology allows buildings to generate their own electricity, aligning with Saudi Vision 2030's goals for sustainable energy. iyris' first customer is the Red Sea Farm, another KAUST-based business, which aims to use the windows to improve plant growth and crop yield. Why it matters: This innovation could significantly reduce reliance on fossil fuels and promote sustainable urban development in the region, where cooling demands drive high electricity consumption.
KAUST's supercomputer Shaheen completed ultra-resolution subsurface mapping simulations for Saudi Aramco, producing a 3D image of subsurface geologic layers at a 7.5-meter resolution. Aramco scientists used integrated GeoDRIVE software to achieve this record resolution at a production scale, improving on prior simulations with tens of meters resolution. Shaheen, located in the KAUST Supercomputing Core Laboratory, is one of the largest CPU-based supercomputers globally, featuring 12,348 Intel Haswell CPUs. Why it matters: This achievement enables more precise resource extraction and geological understanding in the Arabian Peninsula, demonstrating the growing capabilities of regional supercomputing for industrial applications.
KAUST and McLaren Racing have announced a five-year research partnership focused on R&D and extreme performance technology for Formula 1 cars. The collaboration will leverage KAUST's expertise in areas like sensors, electronics, numerical simulations, and fuel/engine combustion research. KAUST researchers will develop new experimental methods, mathematical models, and train students to understand complex systems. Why it matters: This partnership allows KAUST to apply its research to a real-world laboratory (Formula 1), fostering innovation in fuel technology, combustion, sensors, and algorithms with potential spillover effects for the broader automotive and engineering sectors in the region.
KAUST researchers led by Mark Tester are developing new irrigation technology to enable crop production using semi-saline water, aiming to reduce freshwater reliance to 10% in greenhouse systems. The technology is eco-friendly and intends to cut agricultural costs by utilizing seawater, targeting a cost of 10 U.S. cents per cubic meter. A new company named Red Sea Farms is being developed to grow salt-tolerant tomatoes in diluted seawater in a greenhouse cooled with undiluted seawater. Why it matters: This research could significantly reduce pressure on freshwater resources in arid regions and offers a sustainable approach to increase food production using available seawater.
The Research Products Development Company (RPDC) signed an agreement with The Saudi Vaccine and Biomanufacturing Center (SVBC) to establish a research and industrial center in Saudi Arabia for vaccine and biopharmaceutical development. Supported by KACST and hosted by KAUST, the SVBC will provide a state-of-the-art facility and a training platform. Cooperation agreements were also signed with GE for equipment supply and with Fujifilm Dayosent Biotechnology for MERS-CoV treatment development. Why it matters: This initiative aims to localize vaccine and advanced treatment industries in Saudi Arabia, create technical jobs, and reduce reliance on imports in line with Vision 2030.
KAUST's Water Desalination and Reuse Center (WDRC) is developing solar-powered seawater desalination technologies, including the MEDAD cycle which combines adsorption desalination (AD) and multi-effect distillation (MED). The MEDAD cycle, developed by Professor Kim Choon Ng, doubles water production at the same temperature, reducing costs to $0.48/m3 compared to $1.201/m3 for multi-stage flash distillation. A 100 m3/day commercial-scale MEDAD project was commissioned in Riyadh in 2017 in collaboration with KACST, and a larger 2,000 m3/day project is planned for Yanbu. Why it matters: This highlights Saudi Arabia's move towards sustainable energy and the role of research institutions like KAUST in developing cost-effective desalination technologies suitable for the region.
KAUST researchers developed a new single-molecule imaging method called the cumulative-area (CA) method. This method allows for simultaneous characterization of size, shape, and conformational dynamics of individual molecules, along with accurate determination of diffusion kinetics. The researchers demonstrated the CA method's effectiveness on nano- and micro-sized objects, extracting quantitative information about size, diffusion, and relaxation time. Why it matters: This advancement expands the capabilities of molecule imaging techniques in the region and has potential applications in polymer dynamics research and the study of molecular mechanisms within cells.
KAUST and Saudi Aramco have partnered to establish the Saudi Arabia Advanced Research Alliance (SAARA) and Technovia, a company focused on commercializing R&D in Saudi Arabia. SAARA includes KACST, KFUPM, TAQNIA, and RTI International, aiming to translate technology into commercially viable products. Technovia, located in Dhahran Techno Valley, will prepare technologies for market entry and secure external investment. Why it matters: This initiative aims to accelerate technology development and economic diversification in Saudi Arabia by bridging the gap between research and commercial applications, potentially fostering innovation across various industrial sectors.
KAUST researchers led by Pascal Saikaly are developing microbial electrochemical technologies (METs) for wastewater treatment and energy recovery. The team combines METs with membrane filtration, creating a hybrid air-biocathode microbial fuel cell-membrane bioreactor (MFC-MBR) for simultaneous wastewater treatment and ultrafiltration. This system uses an electrically conductive ultrafiltration membrane as a biocathode for electricity generation and passive oxygen transfer. Why it matters: This innovation offers a sustainable approach to water reclamation by reducing energy consumption and producing reusable water, which addresses critical water scarcity challenges in the region and globally.
KAUST announced the acquisition of a Cray XC40 supercomputer named Shaheen II, which will be 25 times more powerful than its current system. The investment aims to enhance KAUST's research capabilities and support collaborations with in-Kingdom organizations like Saudi Aramco and SABIC. Shaheen II will be used for simulations, climate modeling, and big data applications. Why it matters: This upgrade significantly boosts Saudi Arabia's high-performance computing infrastructure, enabling advanced research and development across various sectors and solidifying KAUST's position as a leading research institution.
G42 and its portfolio company Analog have signed non-binding Memoranda of Understanding (MoUs) with Advanced Machine Intelligence (AMI Labs), co-founded by AI pioneer Yann LeCun. The agreements, signed during the UAE-France Business Dialogue, focus on frontier AI research, advanced compute infrastructure, sovereign cloud, and industrial applications, specifically the development of 'world models' for physical environments. This collaboration aims to merge AMI Labs' research with G42's AI infrastructure and Analog's Physical Intelligence platform to apply world models across various industries. Why it matters: This partnership signifies a major step in the UAE's pursuit of cutting-edge AI research, particularly in 'Physical Intelligence' and AI's interaction with the real world, reinforcing international technological cooperation between the UAE and France.
Presight AI Holding PLC reported a 22.2% year-on-year revenue increase, reaching AED 689.0 million in Q1-2026, alongside a 12.7% rise in EBITDA and an 11.5% increase in profit after tax. This growth was fueled by continued execution across multi-year contracts, new domestic wins, and sustained international momentum, with international revenue growing 62.9% to represent 30.0% of the Group's total. AIQ contributed AED 205.3 million (29.8%) to the Group's revenue, and the company maintained a robust, debt-free balance sheet with an order backlog of AED 3.1 billion. Why it matters: This financial performance highlights the increasing global demand for and successful deployment of sovereign, mission-critical AI infrastructure from a prominent UAE-based company.
Core42, a G42 company specializing in sovereign cloud and AI infrastructure, announced a strategic partnership with Solutions+, an AI-driven shared services company for the MIC Group, at Make it in the Emirates in Abu Dhabi. Core42 will serve as the foundational infrastructure provider, offering GPU compute and large language model access via its Compass API, while Solutions+ will be the primary implementation and data services partner, leveraging this infrastructure for its WEAVE AI platform. The agreement establishes a framework for delivering secure and scalable AI infrastructure across MIC Group companies and Abu Dhabi government entities, with broader scope for government and private sector clients. Why it matters: This partnership significantly advances the UAE's sovereign AI capabilities and accelerates enterprise AI adoption by combining robust infrastructure with specialized implementation expertise for critical national sectors.
MBZUAI researchers have developed an AI program using vision transformers that can learn a person's handwriting style and generate text in that style. The US Patent and Trademark Office recently granted a patent for this technology, which could aid individuals with writing impairments. The system overcomes limitations of previous GAN-based approaches by processing long-range dependencies in handwriting. Why it matters: This patented AI tool enhances personalized text generation and has potential applications in assistive technology and improving handwriting recognition models.
MBZUAI's BiMediX2, a bilingual healthcare multi-modal model, won Meta's Llama Impact Innovation Award for its potential in solving healthcare accessibility challenges across the Middle East and Africa. Built using Llama 3.1, the model understands medical queries in both English and Arabic, interprets medical images, and is integrated as a chatbot on Telegram with speech functionality. The model was also presented at the AI for Sustainable Development Platform Launch Event and integrated into the UNDP for telemedicine. Why it matters: The model's bilingual capabilities and accessibility on low-cost devices and speech-based interaction have potential to improve healthcare access for marginalized populations in the region.
MBZUAI researchers developed LLMVoX, a system enabling LLMs to produce real-time speech, including Arabic. LLMVoX addresses limitations of existing end-to-end and cascaded pipeline approaches, which suffer from either degraded reasoning or latency. LLMVoX was developed as part of Project OMER, which was recently awarded Regional Research Grant from Meta. Why it matters: This enhances the potential of LLMs to function as more natural, multimodal virtual assistants, especially for Arabic-speaking users in the Middle East.
MBZUAI researchers developed MedAgentSim, a simulated hospital environment to evaluate AI diagnostic abilities. The simulation uses LLM-powered agents to mimic doctor-patient conversations, providing a dynamic assessment of diagnostic skills. The system includes doctor, patient, and evaluator agents that interact within the simulated hospital, making real-time decisions. Why it matters: This research offers a more realistic evaluation of AI in clinical settings, addressing limitations of current benchmarks and potentially improving AI's use in healthcare.
MBZUAI has launched The Academy, a global platform for AI knowledge exchange, along with the world’s first AI x Arts Fellowship. The inaugural cohort of eight fellows includes artists and innovators like Refik Anadol and Amrita Sethi, who will participate in residency programs in Abu Dhabi in 2026. The Academy also encompasses the MBZUAI Executive Program (MEP), which empowers UAE leaders to leverage AI. Why it matters: This initiative signals MBZUAI's commitment to fostering interdisciplinary collaboration between AI and the arts, positioning Abu Dhabi as a hub for innovative AI applications in culture and heritage.
MBZUAI, G42, and Cerebras Systems have launched K2 Think V2, a 70-billion parameter reasoning system built on the K2-V2 base model. K2 Think V2 is fully open-source, from pre-training data to post-training alignment, ensuring transparency and reproducibility. It achieves leading results on complex reasoning benchmarks like AIME2025 and GPQA-Diamond. Why it matters: This release marks a significant advancement in the UAE's AI capabilities, demonstrating leadership in building globally accessible and fully sovereign AI systems focused on reasoning.
MBZUAI's Institute of Foundation Models (IFM) has released K2 Think V2, a 70 billion parameter open-source general reasoning model built on K2 V2 Instruct. The model excels in complex reasoning benchmarks like AIME2025 and GPQA-Diamond, and features a low hallucination rate with long context reasoning capabilities. K2 Think V2 is fully sovereign and open, from pre-training through post-training, using IFM-curated data and a Guru dataset. Why it matters: This release contributes to closing the gap between community-owned reproducible AI and proprietary models, particularly in reasoning and long-context understanding for Arabic NLP tasks.
IFM has released K2-V2, a 70B-class LLM that takes a "360-open" approach by making its weights, data, training details, checkpoints, and fine-tuning recipes publicly available. K2-V2 matches leading open-weight model performance while offering full transparency, contrasting with proprietary and semi-open Chinese models. Independent evaluations show K2 as a high-performance, fully open-source alternative in the AI landscape. Why it matters: K2-V2 provides developers with a transparent and reproducible foundation model, fostering trust and enabling customization without sacrificing performance, which is crucial for sensitive applications in the region.
Inception, Cerebras, and MBZUAI have released Jais 2, a 70 billion parameter open-weight Arabic LLM. Jais 2 is trained on an Arabic-first dataset and features a redesigned architecture for stronger reasoning and fluency across Arabic dialects and English. It integrates a safety-first framework and demonstrates capabilities in understanding Arabic poetry, culture, and social media tone. Why it matters: Jais 2 addresses the historical underrepresentation of Arabic in AI by providing a culturally and linguistically faithful model, potentially accelerating innovation across the region.
MBZUAI researchers have developed SVRPBench, a new open benchmark for testing vehicle routing algorithms under real-world conditions. SVRPBench simulates unpredictable urban delivery scenarios including rush-hour traffic, accidents, and customer delivery time preferences. The benchmark uses realistic city models with clustered customer locations, unlike existing deterministic benchmarks. Why it matters: This benchmark offers a more practical evaluation for vehicle routing algorithms, potentially leading to significant cost savings and improved efficiency in logistics within the region and beyond.
MBZUAI researchers developed a new AI-generated image detection method called 'consistency verification' (ConV). Instead of training on labeled real and fake images, ConV identifies structural patterns unique to real photos using a data manifold concept. The system modifies images and uses DINOv2 to measure the difference between original and transformed representations, classifying images based on their proximity to the manifold. Why it matters: This approach offers a more robust way to detect AI-generated images without needing training data from every image generator, addressing a key limitation in the rapidly evolving landscape of AI image synthesis.
MBZUAI researchers created Open CaptchaWorld, a new benchmark to test AI agents on solving CAPTCHAs. The benchmark includes 20 modern CAPTCHA types that require perception, reasoning, and interactive actions within a browser. While humans achieve 93.3% accuracy, the best AI agent only reaches 40% on the benchmark. Why it matters: This research highlights a critical gap in current AI agent capabilities, as CAPTCHAs are gatekeepers to high-value web actions like e-commerce and secure logins.
MBZUAI researchers tackled the challenge of AI-powered waste detection in messy, real-world recycling facilities. They fine-tuned modern object detection models on real industrial waste imagery and combined this with a semi-supervised learning pipeline. Fine-tuning more than doubled performance and their semi-supervised pipeline outperformed fully supervised baselines. Why it matters: This research offers a practical path for open research that can rival proprietary systems while reducing the need for costly manual labeling in waste management, a problem of global importance.
MBZUAI's Institute of Foundation Models (IFM) has developed PAN, a novel interactive world model capable of long-horizon simulation. PAN uses a Generative Latent Prediction (GLP) architecture, coupling internal latent reasoning with generative supervision in the visual domain. The model evolves an internal latent state conditioned on history and natural language actions, then decodes that state into a video segment using a Causal Swin-DPM mechanism for smooth transitions. Why it matters: PAN represents a significant advancement in AI's ability to simulate and predict evolving environments, enabling more steerable and coherent long-term video generation and opening new possibilities for interactive AI systems.
MBZUAI researchers introduced Droid, a resource suite and detector family, at EMNLP 2025 designed to distinguish between AI-generated and human-written code. The project addresses the challenge of identifying AI-generated code in software development, considering the prevalence of AI-suggested code and the risks of obfuscated backdoors and feedback loops. DroidCollection includes over one million code samples across seven programming languages, three coding domains, and outputs from 43 different code models, including human-AI co-authored code and adversarially humanized machine code. Why it matters: This research is crucial for maintaining software security and integrity in the age of AI-assisted coding, providing a robust tool for detecting AI-generated code across diverse languages and domains.
A new paper at ICCV 2025, co-authored by MBZUAI Ph.D. student Dmitry Demidov, introduces Dense-WebVid-CoVR, a 1.6-million sample benchmark for composed video retrieval (CoVR). The benchmark features longer, context-rich descriptions and modification texts, generated using Gemini Pro and GPT-4o, with manual verification. The paper also presents a unified fusion approach that jointly reasons across video and text inputs, improving performance on fine-grained edit details. Why it matters: This work advances video search capabilities by enabling more human-like queries, which is crucial for creative and analytic workflows that require nuanced video retrieval.
MBZUAI and GenBio AI have won the UAE AI Award 2025 in the AI Scientific Research category for their "Unified Protein Language Modeling Framework". The winning project enables AI to learn protein function, generate sequences, and predict 3D structures. The AI-driven simulation approach aims to accelerate drug development, reduce costs, and improve success rates. Why it matters: This award highlights the UAE's commitment to fostering AI innovation in biomedicine and drug discovery, positioning the region as a leader in AI-driven healthcare advancements.
MBZUAI researchers are developing LAIKA, an autonomous quadruped robot for hazardous industrial environments, integrating vision-language AI models with 360-degree imaging. LAIKA can operate in operator-assist mode via natural language or autonomously to inspect, detect anomalies like leaks, and generate structured reports. The robot is designed for versatile tasks in industrial inspection, emergency response, and facility monitoring, with future versions integrating multi-robot collaboration. Why it matters: This technology demonstrates AI's potential to enhance industrial safety, reduce risks to human workers, and improve response times in critical situations within the region's vital energy and manufacturing sectors.
MBZUAI researchers developed Data Wise, an AI platform that provides instant data analytics for businesses. The platform uses AI agents and LLMs to analyze raw customer data and generate actionable recommendations. Data Wise aims to address the shortage of data scientists, particularly in the UAE and GCC. Why it matters: This platform democratizes access to advanced analytics, empowering businesses in the region to make data-driven decisions without relying on scarce technical expertise.