MBZUAI researchers are introducing MedNNS, a system to be presented at MICCAI 2025, that recommends the best AI architecture and initialization for medical imaging tasks. MedNNS addresses the challenge of inefficient trial-and-error in building medical imaging AI by reframing model selection as a retrieval problem. The system employs a Once-For-All ResNet-like model and a learned meta-space of 720k model-dataset pairs, using dataset embeddings to predict optimal model performance. Why it matters: By automating model selection, MedNNS promises to significantly reduce the time and resources required to develop effective AI solutions for healthcare, particularly in medical imaging.
MBZUAI and G42 have launched K2 Think, an open-source AI system for advanced reasoning with 32 billion parameters. It outperforms reasoning models 20 times larger, employing techniques like long chain-of-thought fine-tuning and reinforcement learning. K2 Think will be available on Cerebras' platform, achieving 2,000 tokens per second, and ranks highly in math performance. Why it matters: This launch positions the UAE as a leader in AI innovation through public-private partnerships and open-source contributions, demonstrating that efficient AI design can rival larger models.
MBZUAI Ph.D. students Muhammad Maaz and Hanoona Rasheed interned at Meta, developing a vision encoder for images and videos. They created PerceptionLM, a multimodal language model, to generate synthetic video-caption data to train the Perception Encoder. The team addressed the challenge of limited labeled video data by building a multimodal language model called PerceptionLM to understand video's spatial and temporal aspects. Why it matters: This highlights MBZUAI's strength in computer vision and provides students opportunities to contribute to cutting-edge research at global tech firms.
MBZUAI researchers developed AirCast, a novel AI model for improved air pollution forecasting, which won the best paper award at the TerraBytes workshop during ICML. AirCast fuses weather and chemistry data using a Vision Transformer and frequency-weighted MAE to better predict extreme events like Saharan dust storms. In tests across the Middle East and North Africa, AirCast reduced PM2.5 error by 33% compared to a persistence baseline and outperformed the CAMS physics model. Why it matters: Accurate air pollution forecasting is critical for public health in the GCC region, and this research demonstrates a significant advancement using AI to address this challenge.
Researchers from Carnegie Mellon University and MBZUAI have developed a new method called ConceptAligner for precise image editing using AI. The system decomposes text embeddings into independent building blocks called atomic concepts, allowing users to make targeted tweaks without generating entirely new images. Their approach ensures that each latent factor maps to a specific user-controllable dial, enabling accurate concept-level modifications. Why it matters: This research addresses a major limitation in AI image generation, enhancing its usefulness in industries where precise control is crucial, such as advertising and medicine, and improving the reliability of AI-driven creative tools.
MBZUAI Professor Sami Haddadin and his team developed a new framework called Tactile Skills to teach robots manual skills through touch and trial and error. This framework aims to address the gap in robots' ability to learn basic physical tasks compared to AI's advancements in language and image generation. The research, published in Nature Machine Intelligence, focuses on enabling robots to perform manipulation skills at industrial levels with low energy and compute demands. Why it matters: This research could lead to robots capable of performing household maintenance, industrial tasks, and even assisting in medical or rehabilitation settings, potentially solving labor shortages in various sectors in the region and beyond.
MBZUAI researchers have developed GeoPixel, a new multimodal model for pixel grounding in remote sensing images. GeoPixel associates individual pixels with object categories, enabling detailed image analysis by linking language to objects at the pixel level. The model was trained on a new dataset and benchmark, outperforming existing systems in precision. Why it matters: This advancement enhances the utility of remote sensing data for critical applications like environmental management and disaster response by providing more granular and accurate image interpretation.
MBZUAI researchers have developed "Tactile Skills," a new embodied AI framework enabling robots to rapidly learn complex tactile tasks. The framework combines expert process knowledge with reusable tactile control and adaptation components, reducing reliance on extensive datasets. Tested on 28 industrial tasks, the robots achieved nearly 100% success, demonstrating adaptability to changing conditions. Why it matters: This breakthrough offers a practical and scalable approach to robotic automation, potentially transforming robots into adaptable assistants across diverse industries in the GCC.
MBZUAI researchers developed Mobile-VideoGPT, a compact and efficient multimodal model for real-time video understanding on edge devices. The system uses keyframe selection, efficient token projection, and a Qwen-2.5-0.5B language model. Testing showed that Mobile-VideoGPT is faster and performs better than other models while being significantly smaller, and the model and code are publicly available. Why it matters: This research enables on-device AI processing for video, reducing reliance on remote servers and addressing privacy concerns, which can accelerate the adoption of AI in mobile and embedded applications.
Researchers from MBZUAI and other institutions have developed a new framework called STEREO to improve the safety of text-to-image diffusion models. STEREO uses a two-stage approach: STE (Search Thoroughly Enough) based on adversarial training and REO (Robustly Erase Once) for batch concept erasure. This framework aims to enhance safety without significantly impacting the model's performance on normal queries. Why it matters: The framework addresses vulnerabilities in AI image generation, reducing the creation of inappropriate images while preserving performance on harmless queries.
MBZUAI has launched the Institute of Foundation Models (IFM) with a new Silicon Valley Lab in Sunnyvale, CA, joining existing facilities in Paris and Abu Dhabi. The launch event showcased PAN, a world model for simulating diverse realities with multimodal inputs. The IFM lab is also advancing K2-65B and JAIS AI systems. Why it matters: This expansion enhances MBZUAI's global presence and connects it with a critical AI ecosystem, supporting the UAE's economic diversification through advanced AI technologies.
MBZUAI researchers developed FetalCLIP, an AI model trained on 210,000 ultrasound images for fast and reliable interpretation of fetal scans. MBZUAI's President Eric Xing contributed to the General Expression Transformer (GET), an AI foundation model acting as a biological simulator to predict gene behavior. MBZUAI and Carleton University created MedPromptX for quicker disease diagnosis and treatment plans using multimodal AI. Why it matters: These AI advancements from MBZUAI have the potential to revolutionize healthcare in the region and globally, from prenatal care to drug discovery and personalized medicine.
MBZUAI-based startup LibrAI has launched the Libra-Leaderboard, an evaluation framework for LLMs that assesses both capability and safety. The leaderboard evaluates 26 mainstream LLMs using 57 datasets, assigning scores based on bias, misinformation, and oversensitivity. LibrAI also launched the Interactive Safety Arena to engage the public and educate them on AI safety through adversarial prompt testing. Why it matters: The Libra-Leaderboard provides a benchmark for responsible AI development, emphasizing the importance of aligning AI capabilities with safety considerations in the rapidly evolving LLM landscape.
This article discusses MBZUAI's efforts in advancing Arabic language AI, including the development of advanced linguistic models using deep learning techniques. Key initiatives include Jais, a 13B parameter Arabic LLM developed in collaboration with G42's Inception, and Atlas-Chat, which understands the Moroccan dialect. The university is also incorporating Arabic in practical AI solutions like BiMediX2, a healthcare multi-modal model that understands medical queries in both English and Arabic. Why it matters: These initiatives are crucial for preserving Arabic cultural heritage, enabling future discovery, and addressing linguistic challenges specific to the Arabic language in AI applications.
Researchers at MBZUAI have developed LLM-DetectAIve, a tool to classify the degree of machine involvement in text generation. The system categorizes text into four types: human-written, machine-generated, machine-written and machine-humanized, and human-written and machine-polished. A demo website allows users to test the tool's ability to detect machine involvement. Why it matters: This research addresses the growing need to identify and classify AI-generated content in academic and professional settings, particularly in light of increasing LLM misuse.
MBZUAI, in partnership with IBM Research, is developing GeoChat+, a vision-language model (VLM) for multi-modal, temporal remote sensing image analysis. GeoChat+ builds on the previous GeoChat model, enhancing capabilities with multi-modal images from various Earth observation systems like Sentinel-1, Sentinel-2, Landsat, and high-resolution imagery. GeoChat+ will integrate data from multiple satellites at different times to detect environmental changes and analyze the impact on soil quality, air quality, and erosion. Why it matters: This advancement promises to revolutionize geographic data analysis, providing detailed reports for high-risk regions and aiding reforestation efforts.
MBZUAI M.Sc. graduate Mohammad Hanan Ghani developed new techniques to improve text-to-image generation from long text prompts, combining large language models and diffusion models. Advised by Dr. Salman Khan, Ghani published three papers at ICLR, BMVC, and NeurIPS, with the ICLR paper focusing on generating images that accurately reflect detailed text descriptions. The new system improves upon existing techniques to generate images that closely follow the details of the input text. Why it matters: This research addresses a key limitation in current T2I models and advances the field of multimodal AI, potentially improving the capabilities of robots and autonomous devices.
MBZUAI, Petuum, and LLM360 have launched K2-65B, an open-source 65B parameter LLM, trained on 1.4T tokens using 480 A100 GPUs. K2-65B outperforms Llama 2 70B while using 35% fewer resources, emphasizing sustainable AI development. The model and its chat variant, K2-Chat, excel in math, coding, medicine, and human-like response generation, with the model available under the Apache 2.0 license. Why it matters: This launch highlights the UAE's increasing capabilities in developing efficient and high-performing LLMs, promoting open-source collaboration and setting new standards for sustainable AI practices in the region.
MBZUAI's Institute of Foundation Models (IFM) has launched five new specialized language and multimodal models, including BiMediX, PALO, GLaMM, GeoChat, and MobiLLaMA. These models address real-world applications in healthcare, visual reasoning, multilingual capabilities, geospatial analysis, and mobile device efficiency. BiMediX is a bilingual medical LLM, while GLaMM generates natural language responses related to objects in an image at the pixel level. Why it matters: This launch demonstrates MBZUAI's commitment to advancing AI research and developing practical AI solutions for various industries, especially with a focus on Arabic language capabilities.
MBZUAI Professor Agathe Guilloux developed the SigLasso model to forecast hospitalizations using real-time data from Google and Météo France during the COVID-19 pandemic. The model integrates mobility data and weather patterns to predict hospitalization rates 10-14 days in advance. SigLasso outperformed industry standards like GRU and Neural CDE in reducing reconstruction error. Why it matters: This research demonstrates the potential of AI to improve healthcare resource allocation and crisis management by accurately predicting patient flow using readily available data.
MBZUAI and Core42 have launched Jais Climate, the first bilingual (Arabic/English) LLM dedicated to climate and sustainability. It is fine-tuned with 1.4 million climate-related instructions and trained on the ClimaInstruct dataset. Jais Climate is built on Jais 13B and incorporates technology from Vicuna, an open-source LLM. Why it matters: This model provides accessible climate data to a wide audience, including decision-makers and the general public, and highlights the UAE's focus on using AI for sustainability.
MBZUAI has launched the Institute of Foundation Models to advance generative AI research and development. The institute will focus on developing large-scale AI models adaptable to various applications, building on MBZUAI's existing work with models like Jais, Llama 2, and Vicuna. It will focus on multi-modal foundation models applicable to areas like healthcare, finance and environmental engineering. Why it matters: This initiative further solidifies the UAE's position as a leader in AI, particularly in the development and application of foundation models for diverse industries.
MBZUAI has launched the MBZUAI Metaverse Center (MMC) and the MBZUAI Incubation and Entrepreneurship Center (MIEC). The Metaverse Center focuses on AI-driven immersive technologies for communication, healthcare, entertainment, and education. The Incubation and Entrepreneurship Center will focus on catalyzing AI innovation and adoption in industry. Why it matters: These centers signal MBZUAI's commitment to expanding AI research and fostering a startup ecosystem in the UAE.
Researchers from MBZUAI, UC Berkeley, CMU, Stanford, and UC San Diego collaborated to create Vicuna, an open-source chatbot that costs $300 to train, unlike ChatGPT which costs over $4 million. Vicuna achieves 90% of ChatGPT's subjective language quality while being far more energy-efficient and can run on a single GPU. It was fine-tuned from Meta AI’s LLaMA model using user-shared conversations and has gained significant traction on GitHub. Why it matters: This research demonstrates that high-quality chatbots can be developed at a fraction of the cost and environmental impact, opening up new possibilities for sustainable AI development in the region.
MBZUAI researchers led by Dr. Mohammad Yaqub are developing AI algorithms for real-time medical diagnoses, including tools for multiple sclerosis and congenital heart disease. The team developed ScanNav, an AI fetal anomaly assessment system licensed by GE Healthcare for Voluson SWIFT ultrasound machines. ScanNav assists doctors during anomaly scans after 20 weeks of gestation to check for conditions like heart issues and spina bifida. Why it matters: This research has the potential to significantly improve the speed and accuracy of medical diagnoses in the UAE and beyond, addressing critical gaps in healthcare.
MBZUAI's Dr. Mohammad Yaqub is developing AI algorithms to power point-of-care ultrasound (PoCUS) on mobile devices, expanding on his prior work on an AI-based fetal anomaly system used in GE Healthcare's ultrasound. These algorithms aim to make smaller, affordable PoCUS devices accessible in remote areas for faster diagnoses. The handheld devices, costing around $5000 USD, can connect to mobile devices and provide intelligence to interpret images, addressing the shortage of specialists in remote locations. Why it matters: This initiative democratizes access to critical diagnostic tools, potentially saving lives by enabling early detection of life-threatening conditions in underserved communities.
Virgin Hyperloop is collaborating with Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi to develop an AI-powered operating system for its hyperloop transport system. The operating system aims to optimize the hyperloop's operations, including fleet management and vehicle movement, for the proposed 1,080 kph system. Co-founder Josh Giegel highlighted the Gulf's keen interest and involvement in the project, with Dubai's DP World being a major investor. Why it matters: This partnership signifies the UAE's growing role in cutting-edge transportation technology and the application of AI in optimizing complex systems, potentially revolutionizing regional and global transport.
Core42, a G42 company specializing in AI infrastructure, has established its European headquarters in Dublin, Ireland. This expansion aims to better serve European enterprises and governments seeking secure, high-performance infrastructure for scaling AI adoption. Core42 has already partnered with companies in France and Italy to deliver AI infrastructure. Why it matters: The move signifies G42's increasing investment in and focus on the European AI market, positioning the UAE as a key player in the global AI landscape.
G42 has launched Digital Embassies and Greenshield, a sovereign operating model enabling nations to securely deploy AI while maintaining legal control over data, systems, and policies, regardless of infrastructure location. Digital Embassies establish government-to-government legal constructs defining jurisdiction, while Greenshield, implemented by Core42, translates sovereign policy into execution. It applies consistent sovereign controls across environments, governing identity and access, data handling, security, compliance, auditability, and continuity. Why it matters: This framework could accelerate AI adoption across the region by helping governments overcome infrastructure readiness gaps while ensuring data sovereignty.
G42 and Publicis Sapient have signed an MOU to explore a joint venture combining G42’s AI infrastructure with Publicis Sapient’s enterprise AI platforms. The venture aims to accelerate digital transformation across the UAE and Global South by deploying AI agents and enabling data-driven operations. It will deliver services across cloud modernization, AI use case development, and enterprise software engineering. Why it matters: This partnership could establish a major AI services platform in the UAE, driving adoption of AI across the region and beyond.
WhatsApp has introduced new parental settings specifically for teenagers within the United Arab Emirates. This feature allows parents to manage and monitor certain aspects of their children's app usage for enhanced safety. The rollout is part of WhatsApp's ongoing efforts to provide tools for digital well-being and online protection. Why it matters: This feature addresses growing concerns about online safety for young users and provides guardians in the UAE with more control over their children's digital interactions on a widely used platform.
WhatsApp has introduced new safety controls designed to enhance user protection on its messaging platform. These features aim to provide improved security and privacy, particularly for younger users and to assist parents in managing their children's online interactions. The National highlights the importance of these updates for parents in the United Arab Emirates. Why it matters: These changes contribute to ongoing discussions about digital safety and platform accountability, impacting user experience and online regulatory considerations in the UAE.
The article from The National discusses the potential challenges and risks for employers when their staff utilize generative AI tools such as ChatGPT, Claude, and Gemini for work-related tasks. These risks typically include concerns around data privacy, intellectual property leakage, and the accuracy and reliability of AI-generated content. It emphasizes the need for organizations to establish clear policies and guidelines regarding the use of such tools to safeguard sensitive information and maintain compliance. Why it matters: This analysis highlights critical governance and operational considerations for businesses and policymakers in the Middle East as AI adoption continues to grow across various industries.
AI technologies are increasingly being integrated into policing and public safety operations across the UAE to enhance efficiency and capabilities. These applications include predictive analytics for crime prevention, advanced surveillance systems using computer vision, and optimized resource deployment for emergency response. The aim is to leverage data and automation to create safer environments and improve response times for law enforcement agencies. Why it matters: This trend signifies the UAE's commitment to adopting cutting-edge technology for national security and its broader smart city initiatives, positioning it as a leader in tech-driven governance.
AI and blockchain technologies are expected to significantly reshape the remittance sector in the UAE, potentially moving traditional remittance firms to operate primarily as behind-the-scenes service providers. This transformation aims to enhance efficiency, reduce costs, and improve the security of cross-border financial transactions. The shift suggests a move towards more integrated and technologically driven financial services within the region. Why it matters: This development highlights the UAE's ongoing commitment to digital transformation and the integration of advanced technologies like AI and blockchain into critical economic sectors, impacting financial service delivery and innovation.
A UAE expert highlights that the primary challenge for artificial intelligence adoption in the region is transitioning AI ideas into profitable ventures. The expert emphasizes the need to move beyond theoretical concepts to practical, monetizable applications. This perspective identifies a crucial hurdle in the wider deployment and commercialization of AI technologies within the UAE. Why it matters: This expert opinion provides insight into the practical difficulties faced by the UAE in fully leveraging AI's economic potential, indicating areas for strategic focus in policy and investment.
AI and blockchain technologies are increasingly being adopted to innovate and transform remittance services across the United Arab Emirates. This integration aims to enhance efficiency, reduce transaction costs, and improve the security of international money transfers. Financial institutions and FinTech companies in the UAE are leveraging these advanced technologies to offer more streamlined and transparent remittance solutions for expatriates and businesses. Why it matters: The embrace of AI and blockchain in remittance services positions the UAE as a leader in FinTech innovation, offering significant benefits to its large expatriate population and potentially setting new regional standards for digital financial transactions.
A recent survey conducted by JetBrains revealed that 90% of developers are currently using AI coding agents in their professional work. This finding highlights a significant integration of artificial intelligence tools into the daily workflow of software development. The survey data indicates a widespread adoption of AI-powered assistance among the global developer community. Why it matters: This trend signifies a critical evolution in software development practices that will impact productivity, skill requirements, and infrastructure demands across the Middle East's tech industry.
The National Bank of Bahrain (NBB) is actively pursuing its artificial intelligence transformation through an initiative branded AI@NBB. This program aims to integrate AI across various banking operations to enhance efficiency and improve customer experiences. NBB's strategic focus on AI adoption underscores its commitment to digital innovation within the Bahraini financial sector. Why it matters: This initiative reflects the growing trend of AI integration within financial institutions across the Middle East, driving digital transformation and competitiveness in the regional banking sector.
UAE citizens have been ranked as the most satisfied globally with digital government services. This achievement highlights the country's extensive efforts in digital transformation and the successful implementation of advanced public service delivery. The high level of satisfaction indicates effective government strategies in leveraging technology to enhance citizen experience. Why it matters: This positive public reception creates a fertile environment for the successful integration and adoption of AI-powered services within the UAE's government sector.
AWR Group, a diversified business conglomerate based in the UAE, is integrating artificial intelligence into its operations to proactively identify customer friction points. The company plans to leverage AI-driven analytics to understand customer behavior and preferences before issues escalate. This strategic move aims to enhance customer experience and improve operational efficiency across its various business units. Why it matters: This demonstrates a growing trend of established regional businesses adopting AI solutions to gain a competitive advantage and optimize service delivery in the Middle East market.
Artificial intelligence is significantly influencing the UAE labor market, leading to a notable reshaping of employment landscapes. This impact includes the automation of certain jobs, the creation of new roles requiring different skill sets, and a fundamental shift in how various services are delivered across sectors. The article explores these trends and their implications for the future workforce. Why it matters: This ongoing transformation has profound implications for economic planning, education, and workforce development in the UAE, necessitating proactive strategies for adaptation and growth.
This paper presents an automated ArcGIS Pro tool using ArcPy to extract Land Surface Temperature (LST) from Landsat 7, 8, and 9 satellite datasets. The tool automates multi-step workflows like radiometric calibration and emissivity correction, reducing processing time from 11-58 minutes manually to 4-11 minutes. It was successfully tested with data from Ras Al Khaimah (RAK) in the UAE, demonstrating accurate LST mapping compatible with local weather conditions, and includes an optional Large Language Model (LLM) for statistical result interpretation and reporting. Why it matters: This tool offers a practical application of AI and automation for environmental monitoring in the UAE, significantly improving efficiency and accuracy in remote sensing for climate research and urban planning.
Google is exploring the concept of placing AI data centers in space to address terrestrial challenges such as high energy consumption and cooling requirements. Experts, however, have raised significant concerns regarding the feasibility of such an endeavor, citing high launch costs, radiation exposure, and the complexities of maintaining hardware in a zero-gravity environment. The initiative aims to leverage the natural vacuum of space for efficient cooling and access to abundant solar energy. Why it matters: This futuristic approach could revolutionize AI infrastructure by mitigating its environmental footprint and unlocking new computational capabilities, despite the substantial engineering and logistical hurdles.
The UAE is facing escalating cyber risks as artificial intelligence reshapes both offensive cyber attacks and defensive strategies. AI tools are enabling more sophisticated and pervasive threats, challenging existing cybersecurity frameworks. This transformation necessitates advanced defensive measures and policy adjustments to protect national digital assets and infrastructure. Why it matters: The growing cyber threat landscape, exacerbated by AI, necessitates advanced defensive strategies and policy adjustments for the UAE to secure its digital economy and critical infrastructure.
Microsoft has ranked the UAE as the sixth most frequent target for cyberattacks globally, according to a report by The National. This high ranking indicates a significant volume of cyber threats directed at the country's digital infrastructure. The data underscores the persistent and evolving nature of cybersecurity challenges facing the UAE. Why it matters: This highlights the critical need for robust cybersecurity measures and AI-powered defense strategies within the UAE to protect its digital infrastructure and economic stability.
UAE-based startup MetisJean has officially launched its Sovereign AI Platform designed for businesses. The platform aims to provide AI solutions while ensuring data privacy, local control, and adherence to national data governance requirements. This initiative seeks to empower enterprises in the region with secure and compliant artificial intelligence capabilities. Why it matters: This launch reflects a growing regional demand for AI solutions that prioritize data sovereignty and national security, fostering local innovation in enterprise AI.
Employers in Dubai are increasingly seeking candidates with artificial intelligence (AI) skills for various roles across industries. This trend reflects the rapid adoption of AI technologies within the emirate's business landscape. Companies are looking for expertise in areas such as machine learning, data science, and AI development to drive innovation and digital transformation. Why it matters: This shift indicates a growing demand for a skilled AI workforce in the region, influencing educational curricula and talent development strategies.
KAUST researchers have developed a new artificial intelligence model designed to improve the efficiency and accuracy of mineral exploration activities in Saudi Arabia. This model aims to identify promising geological sites for mineral deposits more effectively. The initiative supports Saudi Arabia's efforts to diversify its economy and enhance its mining sector capabilities. Why it matters: This development could significantly accelerate the discovery of new mineral resources, bolstering the Kingdom's economic diversification goals and positioning it as a leader in AI-driven natural resource management.
Bain & Company estimates that the AI industry must generate an additional $6 trillion in annual revenue by 2030 to justify the current global boom in data center construction. The consulting firm's analysis highlights a significant gap between the escalating capital expenditure on AI infrastructure and the projected monetizable applications and services. This report suggests that the rapid expansion of AI data centers may lead to overcapacity if revenue generation does not keep pace with investment. Why it matters: This projection raises critical questions about the sustainability and profitability of the massive AI infrastructure investments being made globally, including in the Middle East, and emphasizes the urgent need for tangible AI product development and effective monetization strategies.