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.
LAraBench introduces a benchmark for Arabic NLP and speech processing, evaluating LLMs like GPT-3.5-turbo, GPT-4, BLOOMZ, Jais-13b-chat, Whisper, and USM. The benchmark covers 33 tasks across 61 datasets, using zero-shot and few-shot learning techniques. Results show that SOTA models generally outperform LLMs in zero-shot settings, though larger LLMs with few-shot learning reduce the gap. Why it matters: This benchmark helps assess and improve the performance of LLMs on Arabic language tasks, highlighting areas where specialized models still excel.
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.
According to the title from Jawlah, Saudi Arabia has reportedly secured the first global ranking in AI security. The kingdom is also stated to have achieved a top position in women's empowerment, presumably within the AI or technology sector. This news was published by Jawlah, an Arabic news outlet. Why it matters: If confirmed by official reports, this signifies Saudi Arabia's leadership claims in critical areas of AI development and societal integration, aligning with its national transformation goals.
PwC has published a report offering strategic guidance to CEOs on navigating the landscape of artificial intelligence. The report likely outlines frameworks for determining where companies should proactively invest and innovate ('lead'), adopt standard industry practices ('lag'), or deprioritize ('exit') specific AI initiatives. It probably addresses critical aspects such as resource allocation, risk management, and competitive differentiation through AI adoption. Why it matters: This strategic counsel can assist businesses in the Middle East in formulating robust AI strategies, optimizing their investments, and enhancing their market competitiveness.