KAUST alumnus Hussain Shibli (M.S. '13) is now the director general at the National Renewable Energy Data Center in King Abdullah City for Atomic and Renewable Energy (KACARE). Shibli obtained a bachelor's degree in electronics and communications engineering from King Abdulaziz University in 2010 before pursuing his master's at KAUST. He sees his position in the energy sector as an opportunity to lead renewable energy development in line with Saudi Vision 2030. Why it matters: This highlights KAUST's role in developing talent for key positions in Saudi Arabia's renewable energy sector, aligning with the Kingdom's strategic goals.
Adel Bibi, a KAUST alumnus and researcher at the University of Oxford, presented his research on AI safety, covering robustness, alignment, and fairness of LLMs. The research addresses challenges in AI systems, alignment issues, and fairness across languages in common tokenizers. Bibi's work includes instruction prefix tuning and its theoretical limitations towards alignment. Why it matters: This research from a leading researcher highlights the importance of addressing safety concerns in LLMs, particularly regarding alignment and fairness in the Arabic language.
KAUST researchers, in collaboration with WHOI, studied whale shark movement patterns near the Shib Habil reef in the Red Sea over six years using visual census, acoustic monitoring, and satellite telemetry. The study monitored 84 sharks and found the aggregation to be highly seasonal, with sharks most abundant in April and May, returning yearly. The site may serve as a nursery for the wider Indian Ocean population, attracting juvenile females, which is unique to Shib Habil. Why it matters: Understanding whale shark behavior and critical habitats like Shib Habil is vital for future conservation efforts of this endangered species in the Red Sea and the broader Indian Ocean.
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.
This paper introduces Absher, a new benchmark for evaluating LLMs' linguistic and cultural competence in Saudi dialects. The benchmark comprises over 18,000 multiple-choice questions spanning six categories, using dialectal words, phrases, and proverbs from various regions of Saudi Arabia. Evaluation of state-of-the-art LLMs reveals performance gaps, especially in cultural inference and contextual understanding, highlighting the need for dialect-aware training.