MBZUAI Provost Timothy Baldwin predicts that 2025 will be a breakout year for agentic AI, with 33% of enterprise software applications including agentic AI capabilities by 2028. MBZUAI doctoral students Wafa Alghallabi and Omkar Thawaker have launched Lawa.AI, an AI agent being tested on the university's website to provide faster answers and deeper understanding. Lawa.AI evolved from a research project in multimodal efficiency and LLMs and aims to bridge the gap between people and information in higher education and government. Why it matters: This highlights the UAE's focus on translating AI research into practical applications and the growing importance of agentic AI in various sectors.
MBZUAI researchers introduce PG-Video-LLaVA, a large multimodal model with pixel-level grounding capabilities for videos, integrating audio cues for enhanced understanding. The model uses an off-the-shelf tracker and grounding module to localize objects in videos based on user prompts. PG-Video-LLaVA is evaluated on video question-answering and grounding benchmarks, using Vicuna instead of GPT-3.5 for reproducibility.
Enowa and KAUST held the Enowa-KAUST Energy Summit 2024, celebrating the third year of their Energy Cortex Program. The Energy Cortex Program funds applied research for clean energy solutions, focusing on renewable energy technologies led by KAUST faculty. The program is structured around Weatherlytics, GenFlex Cortex, Stor Cortex, and Grid Cortex, and has engaged KAUST professors, produced six journal papers, and provided NEOM with data. Why it matters: This partnership aims to revolutionize renewable energy in Saudi Arabia by integrating AI and advanced data analytics to optimize energy generation and distribution, supporting the Kingdom's sustainable energy goals.
This paper introduces a predictive analysis of Arabic court decisions, utilizing 10,813 real commercial court cases. The study evaluates LLaMA-7b, JAIS-13b, and GPT3.5-turbo models under zero-shot, one-shot, and fine-tuned training paradigms, also experimenting with summarization and translation. GPT-3.5 models significantly outperformed others, exceeding JAIS model performance by 50%, while also demonstrating the unreliability of most automated metrics. Why it matters: This research bridges computational linguistics and Arabic legal analytics, offering insights for enhancing judicial processes and legal strategies in the Arabic-speaking world.
This paper presents a UI-level evaluation of ALLaM-34B, an Arabic-centric LLM developed by SDAIA and deployed in the HUMAIN Chat service. The evaluation used a prompt pack spanning various Arabic dialects, code-switching, reasoning, and safety, with outputs scored by frontier LLM judges. Results indicate strong performance in generation, code-switching, MSA handling, reasoning, and improved dialect fidelity, positioning ALLaM-34B as a robust Arabic LLM suitable for real-world use.
MBZUAI's Qirong Ho and colleagues are developing an Artificial Intelligence Operating System (AIOS) for decarbonization, aiming to reduce energy waste in AI development. The AIOS focuses on improving communication efficiency between machines during AI model training, as inefficient communication leads to prolonged tasks and increased energy consumption. This system addresses the high computing power demands of large language models like ChatGPT and LLaMA-2. Why it matters: By optimizing energy usage in AI development, the AIOS could significantly reduce the carbon footprint of AI technologies in the region and globally.
MBZUAI and Quris-AI have partnered to launch a Bio-AI center in Abu Dhabi during Abu Dhabi Sustainability Week. The center will focus on developing personalized medications tailored to the MENA region's diverse populations, leveraging Quris-AI's 'patient-on-a-chip' technology and MBZUAI's AI expertise. Quris-AI is establishing a UAE subsidiary, Quris-UAE, in Abu Dhabi as part of this collaboration. Why it matters: This initiative positions Abu Dhabi as a hub for Bio-AI research and personalized medicine, potentially accelerating drug development and reducing clinical trial failures in the region.