Scale AI has partnered with Qatar Foundation to foster artificial intelligence innovation and talent development within Qatar. The collaboration aims to strengthen Qatar's AI ecosystem by leveraging Scale AI's expertise in data annotation and machine learning. This initiative will provide resources and training to local talent, supporting the growth of AI capabilities in the country. Why it matters: This partnership is a strategic move to bolster Qatar's national AI agenda, cultivate a skilled workforce, and drive technological advancement in the region.
Researchers created Masader, the largest public catalog for Arabic NLP datasets, containing 200 datasets annotated with 25 attributes. They developed a metadata annotation strategy applicable to other languages. The paper highlights issues within current Arabic NLP datasets and suggests recommendations. Why it matters: This curated dataset directory helps lower the barrier to entry for Arabic NLP research and development.
MBZUAI researchers will present 20 papers at the 40th International Conference on Machine Learning (ICML) in Honolulu. Visiting Associate Professor Tongliang Liu leads with seven publications, followed by Kun Zhang with six. One paper investigates semi-supervised learning vs. model-based methods for noisy data annotation in deep neural networks. Why it matters: The research addresses the critical issue of data quality and accessibility in machine learning, particularly for organizations with limited resources for data annotation.