Natural language processing research from GCC institutions, covering Arabic NLP, multilingual models, text classification, named entity recognition, and machine translation.
MBZUAI researchers had 26 papers accepted at ACL 2023, a top NLP conference. Assistant Professor Alham Fikri Aji co-authored eight papers, including one on crosslingual generalization through multitask finetuning (MTF). Deputy Department Chair Preslav Nakov co-authored a paper on a Bulgarian language understanding benchmark dedicated to the memory of Yale Computer Scientist Dragomir R. Radev. Why it matters: MBZUAI's strong presence at ACL highlights its growing influence in the NLP field and its contributions to multilingual AI research.
A new paper from MBZUAI researchers explores using ChatGPT to combat the spread of fake news. The researchers, including Preslav Nakov and Liangming Pan, demonstrate that ChatGPT can be used to fact-check published information. Their paper, "Fact-Checking Complex Claims with Program-Guided Reasoning," was accepted at ACL 2023. Why it matters: This research highlights the potential of large language models to address the growing challenge of misinformation, with implications for maintaining information integrity in the digital age.
MBZUAI had 22 papers accepted at ICLR 2023, with faculty Kun Zhang co-authoring seven of them. Yuanzhi Li, an affiliated assistant professor at MBZUAI, received an honorable mention for his paper on knowledge distillation. Additionally, a paper co-authored by MBZUAI President Eric Xing was recognized as a top 5% paper at the conference. Why it matters: MBZUAI's strong presence at a top-tier machine learning conference like ICLR demonstrates the university's growing influence and research capabilities in the global AI landscape.
MBZUAI is now ranked 19th globally in AI, computer vision, machine learning, and natural language processing according to CSRankings. The university is also top-ranked for computer science in the MENA region. MBZUAI's faculty has grown significantly, with more than 20 new members added in 2022 and Q1 2023, totaling 52. Why it matters: This ranking highlights the rapid rise of MBZUAI as a leading AI research institution in the Middle East, contributing to the UAE's ambitions to become a global AI hub.
MBZUAI and IBM have launched an AI Center of Excellence to drive sustainability. The center will focus on developing carbon-neutral energy solutions and improving natural language processing for Arabic dialects. Joint research will focus on decarbonization, climate change mitigation, and foundational AI models to support renewable energy. Why it matters: This initiative addresses critical regional needs in sustainability and Arabic NLP, aligning with the UAE's AI strategy and COP28 goals.
MBZUAI and the Weizmann Institute of Science have launched a joint AI Research Program. The program will foster collaborative projects, training, and exchanges in AI fields like machine learning, computer vision, and NLP. The initiative aims to advance both basic and applied AI research, particularly in healthcare and genomics. Why it matters: This partnership signifies growing international collaboration in AI research within the UAE and could accelerate breakthroughs in key AI applications.
G42 has launched Nanda 87B, an open-source Hindi-English LLM developed by MBZUAI in collaboration with Inception and Cerebras. Nanda 87B is built upon Llama-3.1 70B and trained on a dataset with over 65 billion Hindi tokens. The model is engineered for real-world use being fluent in formal Hindi, casual speech, and Hinglish, and is designed for translation, summarization, instruction-following, and transliteration tasks. Why it matters: This release marks a major advancement in creating inclusive AI technology tailored for one of the world's largest linguistic communities.
MBZUAI researchers have developed 'Byzantine antidote' (Bant), a novel defense mechanism against Byzantine attacks in federated learning. Bant uses trust scores and a trial function to dynamically filter and neutralize corrupted updates, even when a majority of nodes are compromised. The research was presented at the 40th Annual AAAI Conference on Artificial Intelligence.
MBZUAI has received a Google Academic Research Award to study how AI can better understand and respond to human loneliness in digital spaces. The project will examine how loneliness is expressed online, how conversational agents can detect it, and what healthier AI companionship could look like. The research aims to define digital loneliness and address the potential negative impacts of AI chatbots on users.
MBZUAI researchers release JEEM, a new benchmark dataset for evaluating vision-language models on Arabic dialects. The dataset covers image captioning and visual question answering tasks using images from Jordan, UAE, Egypt, and Morocco. Results show models struggle with cultural understanding and relevance despite fluent language generation.
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.
A study reported by The National News suggests that AI-generated summaries possess the capability to manipulate human memories. The research indicates that exposure to AI-condensed information can lead individuals to form false recollections or alter existing ones. This phenomenon raises significant concerns regarding the reliability and integrity of information consumption in the era of widespread AI tools. Why it matters: This highlights critical ethical implications for AI development and deployment in the Middle East and globally, particularly concerning applications in news dissemination, education, and public discourse.
The article discusses the crucial role of the Arabic language in shaping the identity of youth in the Middle East and North Africa (MENA) region. It explores the challenge of transforming Arabic into a language of economic opportunity, particularly within the rapidly growing technology and AI sectors where English often predominates. The piece likely advocates for initiatives and investments to develop Arabic content and NLP tools to ensure MENA youth can fully participate in the digital economy. Why it matters: Fostering Arabic as a language of opportunity is vital for regional talent development, cultural preservation, and equitable participation in the global AI landscape.
Fanar, a Qatari entity, showcased the progress Qatar has made in the field of Arabic artificial intelligence. An expert highlighted the nation's efforts and achievements in developing AI solutions tailored for the Arabic language. The presentation emphasized Qatar's dedication to advancing localized AI technologies. Why it matters: This initiative is vital for enhancing digital content and services in Arabic, supporting regional linguistic diversity in the global AI landscape.
A study focused on developing a model for spam and sentiment detection in Arabic tweets, specifically targeting customer feedback for Saudi Telecom Company (STC). Researchers trained the MARBERT model using a dataset of 24,513 Arabic tweets, which included various sentiment categories like positive, negative, neutral, sarcasm, and indeterminate. The primary objective was to analyze tweet sentiments to enhance STC's customer service, with the proposed scheme demonstrating promising accuracy compared to existing techniques. Why it matters: This research contributes to Arabic Natural Language Processing (NLP) by providing a practical application for sentiment analysis in customer service within the Middle East, addressing a recognized gap in Arabic AI research.
Apple CEO Tim Cook announced significant updates to its AI assistant Siri at the company's annual Worldwide Developers Conference (WWDC). These enhancements are part of a broader AI strategy aimed at integrating more advanced artificial intelligence features across Apple's ecosystem. The company's efforts are specifically positioned to compete with leading generative AI platforms such as OpenAI's ChatGPT and Google's Gemini. Why it matters: This announcement signals a major push by a global tech giant into advanced AI, setting new benchmarks for consumer AI experiences that will influence the entire industry, including the Middle East's tech market.
A UAE-based grocery platform is preparing to launch an AI-powered chatbot designed to help residents find the cheapest deals and prices for groceries. This initiative aims to enhance the shopping experience by leveraging artificial intelligence for price comparison. The platform expects the chatbot to streamline the process of finding value for money on everyday essentials. Why it matters: This development signifies the growing adoption of AI in consumer services and e-commerce within the UAE, potentially impacting household budgeting and competitive pricing strategies.
The ongoing discourse around Artificial Intelligence in the Middle East is increasingly shifting its focus towards critical issues such as trust, accuracy, and cultural relevance. This evolving debate highlights the growing recognition of the need for AI systems to be reliable, transparent, and aligned with local values and contexts. Discussions frequently address the challenges of ensuring AI outputs are free from bias and reflect the diverse cultural nuances of the region. Why it matters: This shift underscores a maturing approach to AI development and adoption in the Middle East, emphasizing ethical considerations and societal integration alongside technological advancement.
AI models frequently encounter significant challenges in accurately processing and interpreting the Arabic language, leading to misinterpretations in various applications. These difficulties stem from Arabic's complex morphology, diverse dialects, and the relative scarcity of high-quality, comprehensive datasets for training. The article highlights how such linguistic nuances can cause AI systems to confuse similar words or fail to grasp contextual meanings, impacting their effectiveness. Why it matters: This underscores a fundamental obstacle for advancing robust and culturally relevant AI solutions tailored for the Arabic-speaking world, emphasizing the urgent need for dedicated research and data initiatives.
Children in the UAE are increasingly utilizing AI tools like ChatGPT for school assignments, general knowledge acquisition, and even personal advice. Parents are expressing significant worry regarding their children's growing dependence on AI for information and emotional support, which they fear could diminish critical thinking and human interaction skills. This trend highlights AI's emergence as a key source of information and companionship for young individuals in the region. Why it matters: This development underscores the critical need for enhanced digital literacy education and parental guidance to ensure the responsible use of AI among children in the UAE and to address its broader societal implications.
A research paper evaluates a challenge-based method for robotics awareness using an LLM-enabled humanoid robot, implemented with employees of AD Ports Group in the UAE. Participants interacted with the robot in a logistics-inspired task environment using voice commands interpreted through an LLM-based control framework. A post-event survey of 102 responses indicated high satisfaction (8.46/10), increased interest in robotics and AI (4.47/5), and improved understanding of human-robot collaboration (4.45/5). Why it matters: This study provides evidence for a replicable method of introducing robotics and embodied AI to non-specialist users in real industrial settings within the UAE, leveraging advanced LLM capabilities.
Roblox is expanding its child safety controls globally, but live chat functionality remains disabled for users in the Middle East. This decision is due to the current limitations of AI technology in accurately and safely moderating complex Arabic user-generated content. The article indicates that while Arabic AI development is progressing, it has not yet reached the maturity required for real-time, nuanced content moderation critical for child safety. Why it matters: This situation highlights the significant gap in advanced Arabic natural language processing capabilities needed for high-stakes content moderation, affecting product feature availability and user safety in the region.
Students at Khalifa University in the UAE have developed a Radio-Frequency Artificial Intelligence Language Model. This innovation applies AI language model principles to the domain of radio frequency signals. The project highlights student-led research and development within the Abu Dhabi-based institution. Why it matters: This showcases local AI innovation in the UAE, exploring novel applications of language model paradigms beyond traditional text processing and contributing to specialized AI research.
This study investigates the ability of six large language models, including Jais, Mistral, and GPT-4o, to mimic human emotional expression in English and personality markers in Arabic. The researchers evaluated whether machine classifiers could distinguish between human-authored and AI-generated texts and assessed the emotional/personality traits exhibited by the LLMs. Results indicate that AI-generated texts are distinguishable from human-authored ones, with classification performance impacted by paraphrasing, and that LLMs encode affective signals differently than humans. Why it matters: The findings have implications for authorship attribution, affective computing, and the responsible deployment of AI, especially in under-resourced languages like Arabic.
Professor Mérouane Debbah, Chief Researcher at AIDRC, and his co-authors received the 2022 IEEE TAOS TC Best GCSN Paper Award for their work on federated quantized neural networks. The paper, presented at IEEE ICC 2022, explores the tradeoff between energy, precision, and accuracy in these networks. The research proposes an optimal quantization level to minimize energy consumption during training, making it less prohibitive for mobile devices. Why it matters: The award recognizes work that reduces the carbon footprint of large-scale AI systems, a key challenge for sustainable AI deployment in the region and globally.
A research paper co-authored by Dr. Maxim Panov and Kirill Fedyanin from the AI and Digital Science Research Center (AIDRC) has been accepted for publication at NeurIPS 2022. The paper, titled “Nonparametric Uncertainty Quantification for Single Deterministic Neural Network”, proposes a fast and scalable method for uncertainty quantification in ML models. The method disentangles aleatoric and epistemic uncertainties and was validated on text classification and image datasets including MNIST and ImageNet. Why it matters: This demonstrates the growing AI research capabilities and contributions from the UAE to the global AI community, particularly in fundamental machine learning research.
Three researchers from the AI Cross-Center Unit (AICCU) have been selected to pursue master’s and PhD studies at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI). The TII-sponsored students will receive full scholarships and salaries while studying machine learning and computer vision. One student previously worked on the NOOR project, the world’s largest Arabic NLP model. Why it matters: This highlights the UAE's commitment to developing local AI talent and fostering collaboration between research institutions and universities.
The UAE has arrested 35 individuals for publishing misinformation and inciting hatred related to Iran's attacks. These individuals allegedly spread false information and inflammatory content online. The arrests are part of a broader effort to maintain social stability and prevent the spread of harmful content. Why it matters: The arrests highlight the UAE's focus on regulating online discourse and countering narratives perceived as threatening national security or social harmony.
Saudi Arabia has trained 666,000 women in artificial intelligence, according to a recent report. This initiative underscores the Kingdom's commitment to enhancing female participation in the technology sector. The effort aims to solidify Saudi Arabia's position as a global leader in AI empowerment for women. Why it matters: This large-scale training program could help bridge the gender gap in AI and foster more inclusive innovation within the Kingdom and beyond.
The UAE government has issued a warning to the public regarding the dangers of misleading AI-generated videos, particularly those used to spread rumors and false information. Authorities emphasized the importance of verifying the credibility of video content before sharing it on social media. The warning highlights potential legal consequences for individuals involved in creating or disseminating such content. Why it matters: This proactive stance reflects growing concerns in the UAE about the misuse of AI-driven technologies and its commitment to combatting disinformation.
Bahrain's Council of Representatives is reviewing a proposal for a unified Gulf Cooperation Council (GCC) artificial intelligence strategy. The proposal aims to foster collaboration and development in the AI sector across GCC member states. It focuses on coordinating efforts to advance AI research, innovation, and adoption in the region. Why it matters: The unified strategy could accelerate AI development and deployment across the GCC, creating new economic opportunities and addressing shared challenges.
UAE's G42 announced that AI agents are now capable of applying for jobs. These AI agents can autonomously search for open positions, complete application forms, and tailor resumes. The agents use natural language processing to understand job requirements and communicate with recruiters. Why it matters: This represents a significant step toward automating recruitment processes and highlights the growing sophistication of AI in professional settings within the UAE.
The paper introduces Aladdin-FTI, a system designed for generating and translating dialectal Arabic (DA). Aladdin-FTI supports text generation in Moroccan, Egyptian, Palestinian, Syrian, and Saudi dialects. It also handles bidirectional translation between these dialects, Modern Standard Arabic (MSA), and English. Why it matters: This work contributes to addressing the under-representation of Arabic dialects in NLP research and enables more inclusive Arabic language models.
Researchers from Georgia Tech explored Arabic medical text classification using 82 categories from the AbjadMed dataset. They compared fine-tuned AraBERTv2 encoders with hybrid pooling against multilingual encoders and large causal decoders like Llama 3.3 70B and Qwen 3B. The study found that bidirectional encoders outperformed causal decoders in capturing semantic boundaries for fine-grained medical text classification. Why it matters: The research provides insights into optimal model selection for specialized Arabic NLP tasks, specifically highlighting the effectiveness of fine-tuned encoders for medical text categorization.
The paper introduces ADAB (Arabic Politeness Dataset), a new annotated Arabic dataset for politeness detection collected from online platforms. The dataset covers Modern Standard Arabic and multiple dialects (Gulf, Egyptian, Levantine, and Maghrebi). It contains 10,000 samples across 16 politeness categories and achieves substantial inter-annotator agreement (kappa = 0.703). Why it matters: This dataset addresses the under-explored area of Arabic-language resources for politeness detection, which is crucial for culturally-aware NLP systems.
The paper introduces AraModernBERT, an adaptation of the ModernBERT encoder architecture for Arabic, focusing on transtokenized embedding initialization and long-context modeling up to 8,192 tokens. Transtokenization is shown to be crucial for Arabic language modeling, significantly enhancing masked language modeling performance. The model demonstrates stable and effective long-context modeling, improving intrinsic language modeling performance at extended sequence lengths. Why it matters: This research provides practical insights for adapting modern encoder architectures to Arabic and other languages using Arabic-derived scripts, advancing Arabic NLP.
This paper explores cross-lingual transfer in Arabic language models, which are typically pretrained on Modern Standard Arabic (MSA) but expected to generalize to diverse dialects. The study uses probing on 3 NLP tasks and representational similarity analysis to assess transfer effectiveness. Results show transfer is uneven across dialects, partially linked to geographic proximity, and models trained on all dialects exhibit negative interference. Why it matters: The findings highlight challenges in cross-lingual transfer for Arabic NLP and raise questions about dialect similarity for model training.
Qatar is investing heavily in AI to reduce its reliance on foreign technology companies. The country aims to become a leader in AI research and development, with a focus on Arabic language technologies and applications relevant to the region. Qatar's efforts are driven by concerns about data security, privacy, and the potential for AI to drive economic diversification. Why it matters: This push for AI sovereignty reflects a broader trend in the Middle East, as countries seek to develop their own AI capabilities and reduce dependence on foreign providers.
Gulf News reports on the evolving landscape of AI talent acquisition, compensation, and career trajectories in the GCC region. Demand for AI skills is reshaping hiring practices and driving up salaries. This trend is creating new career opportunities and pathways for professionals in the Gulf. Why it matters: This underscores the growing importance of AI across sectors in the Gulf and the increasing competition for skilled professionals.
According to LinkedIn data reported by the World Economic Forum, AI has contributed to the creation of 1.3 million jobs. These roles span various industries, including software development, data analysis, and AI-related engineering. The report suggests that AI is not just automating tasks but also driving new employment opportunities. Why it matters: This indicates a net positive impact of AI on the job market, contrary to fears of mass unemployment, and highlights the need for workforce training and adaptation.
Qatar Computing Research Institute (QCRI) has released Fanar 2.0, a new version of its open-source Arabic language processing toolkit. Fanar 2.0 includes improved models for named entity recognition, part-of-speech tagging, and dependency parsing. The toolkit is designed to support researchers and developers working on Arabic NLP applications. Why it matters: This release enhances the accessibility of advanced Arabic NLP tools, crucial for developing AI solutions tailored to the Arabic-speaking world.
Saudi Arabia has achieved third rank globally in the number of AI models and AI hiring rates, according to the Saudi Press Agency. SDAIA's efforts in developing AI capabilities and attracting specialized talent are contributing factors. This ranking reflects the Kingdom's commitment to advancing AI and its growing role in the global AI landscape.
The United Nations has introduced 'Diplomatic Pulse', a new search engine specifically designed for diplomats. This platform aims to provide diplomats with efficient access to critical information and resources to support their work. It is intended to streamline information retrieval, enabling better-informed decision-making and negotiation processes. Why it matters: This tool could significantly enhance the operational efficiency and information access for diplomats, including those from the Middle East, improving international relations and policy formulation.
Adobe and Qualcomm have partnered with Humain, an AI company, to advance generative AI capabilities in the Middle East. The collaboration aims to leverage Qualcomm's on-device AI technology and Adobe's creative software to develop AI solutions tailored for the region. Humain will focus on creating locally relevant AI applications and experiences. Why it matters: The partnership signals growing investment in regional AI innovation and the development of culturally relevant AI tools.
KAUST Ph.D. student Mohammed Aljahdali received the Best Paper award at the International Conference on Federated Learning Technologies and Applications (FLTA) 2025 for his research on federated learning. His paper, "Flashback: Understanding and Mitigating Forgetting in Federated Learning," introduces an algorithm to help AI systems retain knowledge across diverse datasets while preserving privacy. Aljahdali's research, supervised by Professor Marco Canini, focuses on training machine learning models directly on user devices. Why it matters: This award recognizes the growing talent and impactful research emerging from Saudi universities in the field of privacy-preserving AI.
Bahrain's Council of Representatives is advocating for a comprehensive national AI strategy to diversify the economy and enhance global competitiveness. MP Lulwa Al Rumaihi emphasized AI's potential to transform industries and create new economic opportunities for Bahrain. The council is urging the government to collaborate with experts and stakeholders to formulate this strategy. Why it matters: A national AI strategy could position Bahrain as a regional leader in AI innovation and adoption.
This study assesses workforce preparedness for AI in the GCC region, using socio-technical systems theory to analyze national AI strategies and initiatives in KSA, UAE, Qatar, Kuwait, Bahrain, and Oman. The research combines TF-IDF analysis, case studies of MBZUAI and SDAIA Academy, and scenario planning to evaluate the balance between technical capacity and social alignment. The study identifies a potential two-track talent system and emphasizes the importance of regulatory convergence for successful AI adoption.
A survey of 92 library and information science (LIS) professionals in the UAE reveals strong cognitive AI competencies but gaps in behavioral and normative competencies related to AI biases and ethics. The study identifies a disconnect between the perceived importance of AI skills and the effectiveness of current training programs. It recommends that library training programs address AI ethics and biases.
The Gulf region is making significant investments in artificial intelligence, particularly in Arabic NLP. Recent developments include large language models trained on Arabic data and initiatives to promote AI ethics and policy. Why it matters: These investments aim to position the Gulf as a leader in AI, especially in leveraging the Arabic language and culture.
Arab News, a Saudi-based English-language newspaper, has launched a new translation service, making its content available in 50 languages. This initiative was announced at the FIPP Media congress held in Madrid. The service aims to significantly expand Arab News' global reach and cater to a diverse international readership. Why it matters: This development highlights a practical application of AI-powered translation technologies by a prominent Middle Eastern media outlet to broaden its international influence and content accessibility.