ArabDiscrim is a new corpus comprising 293,000 public Arabic Facebook posts from 2014 to 2024, specifically curated to discuss racism and discrimination. Unlike prior Twitter-centric datasets, it incorporates platform-native engagement signals, 200 curated terms with morphological regex families, and 20 discrimination axes. The resource also provides explicit attribution patterns and is released under a restricted research-use license for ethical compliance. Why it matters: This dataset provides a unique, ecologically valid foundation for fairness-oriented and platform-aware Arabic Natural Language Processing, moving beyond existing Twitter-centric resources.
KAUST Ph.D. student Anna Fruehstueck won a 2020 Facebook Fellowship award, a two-year fellowship from Facebook Research, focusing on computer graphics. She was selected as one of 36 recipients from over 1,800 applicants and is the University's first recipient of the scholarship. Her research explores the intersection of computer graphics, geometry processing, and visual arts using machine learning. Why it matters: This award highlights the growing prominence of KAUST in computer science research and its ability to attract and foster top talent in the field.
Lucidya, a startup founded by Saudi entrepreneurs including KAUST alumnus Zuhair Khayyat, utilizes AI and Big Data to analyze social media content from platforms like Twitter and Facebook, as well as articles from 200 million websites in over 120 languages. The technology predicts user emotions, detects interests, and provides content analyses to customers for better decision-making. Lucidya commercially transformed the scientific research 'Tagreed' to start their company. Why it matters: This demonstrates the growing potential of Saudi startups in leveraging AI for data analysis and social media monitoring, and it showcases the role of KAUST in fostering technological innovation and entrepreneurship within the Kingdom.
Veselin Stoyanov of Tome (previously Facebook AI) gave a talk at MBZUAI on challenges to LLM adoption. The talk covered sparse models, multilingual LLMs, and instruction finetuning. Stoyanov previously led development of RoBERTa, XLM-R, and MultiRay. Why it matters: This talk highlights MBZUAI's role as a forum for discussing key challenges and advancements in large language models, with implications for Arabic NLP and regional AI development.
MBZUAI President Professor Eric Xing discussed AI's potential to augment human capabilities and the responsibility of AI researchers in shaping future leaders. Xing's background includes professorships at Carnegie Mellon University, leadership at Petuum Inc., and directorship of the Center for Machine Learning and Health. He also held visiting positions at Stanford University and Facebook Inc. Why it matters: The emphasis on responsible AI development and education aligns with the UAE's broader strategy to become a leader in ethical and human-centric AI.
Janet Kelso from the Max Planck Institute and Sudhir Kumar from Temple University discussed evolutionary biology in a KAUST Facebook Live interview. Kelso's research focuses on interactions between modern humans and Neanderthals, finding similarities in DNA and benefits for environmental adaptation. Kumar's work, highly cited, involves big data analyses in evolutionary biology. Why it matters: The interview highlights KAUST's engagement with international experts in bioinformatics and evolutionary biology, promoting interdisciplinary research and knowledge dissemination.
KAUST encouraged attendees of the 2015 Winter Enrichment Program (WEP) to share their experiences on social media using the hashtag #wep2015. The university provided tips for participants to effectively use platforms like Facebook, Twitter, and Instagram during the event. KAUST emphasized responsible sharing and respect for the university's multicultural community when posting. Why it matters: This initiative aimed to amplify the reach of WEP's activities and engage a broader audience in KAUST's community and knowledge-sharing efforts.