The paper introduces Juhaina, a 9.24B parameter Arabic-English bilingual LLM trained with an 8,192 token context window. It identifies limitations in the Open Arabic LLM Leaderboard (OALL) and proposes a new benchmark, CamelEval, for more comprehensive evaluation. Juhaina outperforms models like Llama and Gemma in generating helpful Arabic responses and understanding cultural nuances. Why it matters: This culturally-aligned LLM and associated benchmark could significantly advance Arabic NLP and democratize AI access for Arabic speakers.
A KAUST article highlights the role of supercomputers like Shaheen in enhancing industrial competitiveness. Jean Tachiji, Cray Manager in the Middle East, Steven Scott, Cray CTO, and Saber Feki from KAUST Supercomputing Core Laboratory are featured in front of Shaheen. Why it matters: This underscores the strategic importance of high-performance computing for research and development in the region.
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.
Todd Nims, a filmmaker born in Saudi Arabia, premiered his film "Joud" at KAUST's 2018 Winter Enrichment Program. The film, set in Saudi Arabia, explores the cycle of life in reverse and the meaning of "Joud" (generosity in the face of scarcity). Nims describes Saudi Arabia as a "magical place" due to its rich storytelling tradition. Why it matters: The article highlights KAUST's role in showcasing cultural works and supporting Saudi artists, though the AI relevance is limited.
KAUST acquired the Shaheen-Cray XC40 supercomputer in 2015, which is 25 times faster than its predecessor, Shaheen I. The system arrived in Jeddah from Chicago in 123 crates and weighs around 109 metric tons. It consists of approximately 6,100 nodes, with each node containing 32 cores. Why it matters: This infrastructure upgrade significantly enhances KAUST's capacity for data-intensive scientific tasks like simulations and modeling, crucial for advancing research in areas such as climate and renewable energy.
Scimagine is a KAUST-based startup that provides a cloud-based platform for managing and storing experimental data for material scientists. The platform allows researchers to store, manage, and share their data, as well as create scientific visuals. It addresses the problem of experimental data being hidden in PDF files and not easily searchable. Why it matters: This platform improves data accessibility and collaboration in materials science research, potentially accelerating discovery and innovation in the field.