A recent survey indicates that investors in the UAE are at the forefront of adopting artificial intelligence tools for managing their finances, surpassing global averages. The study highlights a significant shift towards leveraging AI for investment decisions and wealth management within the region. This trend suggests a strong embrace of technological advancements by the UAE's investment community. Why it matters: This leadership position underscores the UAE's progressive approach to financial technology and its potential to drive innovation in the global investment landscape.
A national survey in Saudi Arabia of 330 participants reveals that 93% are actively using Generative AI, primarily for text-based tasks, while awareness and understanding remain uneven. Participants recognize benefits like productivity but caution against risks such as privacy, misinformation, and ethical misuse. The study highlights the need for AI literacy, culturally aligned solutions, and stronger frameworks for responsible deployment in Saudi Arabia.
This survey paper analyzes over 40 benchmarks used to evaluate Arabic large language models, categorizing them into Knowledge, NLP Tasks, Culture and Dialects, and Target-Specific evaluations. It identifies progress in benchmark diversity but also highlights gaps like limited temporal evaluation and cultural misalignment. The paper also examines methods for creating benchmarks, including native collection, translation, and synthetic generation. Why it matters: The survey provides a comprehensive reference for Arabic NLP research and offers recommendations for future benchmark development to better align with cultural contexts.
KAUST researchers have developed an AI system for the Saudi Geological Survey (SGS) to improve the scientific understanding of seismic activity in Saudi Arabia. The AI system helps the SGS analyze swarm earthquakes, which are common in volcanic regions and difficult to decipher using conventional methods. The system allows for a more reliable survey of seismic regions, better infrastructure planning, and improved building codes. Why it matters: The AI system enhances Saudi Arabia's ability to monitor and respond to seismic events, contributing to public safety and infrastructure resilience.
A new survey paper provides a deep dive into post-training methodologies for Large Language Models (LLMs), analyzing their role in refining LLMs beyond pretraining. It addresses key challenges such as catastrophic forgetting, reward hacking, and inference-time trade-offs, and highlights emerging directions in model alignment, scalable adaptation, and inference-time reasoning. The paper also provides a public repository to continually track developments in this fast-evolving field.
This survey paper reviews recent literature on continual learning in medical imaging, addressing challenges like catastrophic forgetting and distribution shifts. It covers classification, segmentation, detection, and other tasks, while providing a taxonomy of studies and identifying challenges. The authors also maintain a GitHub repository to keep the survey up-to-date with the latest research.
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.
A recent survey by Oxford Economics and Oracle indicates that Saudi Arabian workers are highly confident in using AI to enhance their skills and careers. 86% of Saudi respondents believe AI will have a positive impact on their jobs, and 84% are ready to learn new skills to work with AI. This reflects a strong embrace of AI in the Saudi workforce and a willingness to adapt to evolving job roles. Why it matters: This positive sentiment suggests Saudi Arabia is well-positioned to integrate AI into its economy and workforce as part of its Vision 2030 goals.