arXiv ·
Researchers studied user lifetime prediction in the location-based social network Jodel within Saudi Arabia, leveraging its disjoint communities. Machine learning models, particularly Random Forest, were trained to predict user lifetime as a regression and classification problem. A single countrywide model generalizes well and performs similarly to community-specific models.
MBZUAI ·
A computer science vision involves computing devices becoming proactive assistants, enhancing various aspects of life through user digitization. Current devices provide coarse digital representations of users, but there's significant potential for improvement. Karan, a Ph.D. candidate at CMU, develops technologies for consumer devices to capture richer user representations without sacrificing practicality. Why it matters: Advancements in user digitization can lead to improved extended reality experiences, health tracking, and more productive work environments, enhancing the utility of consumer devices.
KAUST ·
American artist Rachel Sussman spoke at KAUST's 2019 Winter Enrichment Program about her project documenting the world's oldest living organisms. Sussman photographed 30 species alive for over 2,000 years, including trees, coral, and bacteria. She collaborated with 30 scientists to identify and document these organisms. Why it matters: The lecture highlights KAUST's interdisciplinary approach to knowledge, connecting art, science, and philosophy to explore concepts of time and longevity.
arXiv ·
This paper introduces a large-scale historical corpus of written Arabic spanning 1400 years. The corpus was cleaned and processed using Arabic NLP tools, including identification of reused text. The study uses a novel automatic periodization algorithm to study the history of the Arabic language, confirming the division into Modern Standard and Classical Arabic. Why it matters: This resource enables further computational research into the evolution of Arabic and the development of NLP tools for historical texts.
arXiv ·
A study investigated language shift from Tibetan to Arabic among Tibetan families who migrated to Saudi Arabia 70 years ago. Data from 96 participants across three age groups revealed significant intergenerational differences in language use. Younger members rarely used Tibetan, while older members used it slightly more, with a p-value of .001 indicating statistical significance.
MBZUAI ·
MBZUAI's Metaverse Lab is developing AI algorithms for photorealistic virtual humans and dynamic environments. Hao Li, Director of the lab, envisions using the metaverse for immersive learning experiences related to history and culture. He is also working on tools to prevent deepfakes and other cyberthreats. Why it matters: This research at MBZUAI aims to advance AI and immersive technologies for education and address potential risks in the metaverse.
MBZUAI ·
Professor Hava Siegelmann, a computer science expert, is researching lifelong learning AI, drawing inspiration from the brain's abstraction and generalization capabilities. The research aims to enable intelligent systems in satellites, robots, and medical devices to adapt and improve their expertise in real-time, even with limited communication and power. The goal is to develop AI systems applicable for far edge computing that can learn in runtime and handle unanticipated situations. Why it matters: This research could lead to more resilient and adaptable AI systems for critical applications in remote and resource-constrained environments, with potential benefits for various sectors in the Middle East.
arXiv ·
A new benchmark, LongShOTBench, is introduced for evaluating multimodal reasoning and tool use in long videos, featuring open-ended questions and diagnostic rubrics. The benchmark addresses the limitations of existing datasets by combining temporal length and multimodal richness, using human-validated samples. LongShOTAgent, an agentic system, is also presented for analyzing long videos, with both the benchmark and agent demonstrating the challenges faced by state-of-the-art MLLMs.