Joonhyuk Kang from KAIST gave a presentation at MBZUAI on AI's impact on wireless communication. The talk covered how communication systems can improve AI and how AI can develop wireless systems. Kang's research interests include signal processing for information transmission, security, and machine cognition. Why it matters: This talk highlights the growing intersection of AI and communication technologies in the region, with potential applications for smart cities and autonomous systems.
Researchers from MBZUAI, Carnegie Mellon University, and Meta AI presented a new approach called ThoughtComm at NeurIPS 2025 where AI agents communicate through internal, latent representations instead of natural language. This framework extracts and selectively shares latent "thoughts" from agents' internal states, representing the underlying structure of their reasoning. Results show that agents coordinate more effectively, reach consensus faster, and solve problems more accurately using this method. Why it matters: Bypassing the limitations of natural language in AI communication could lead to more efficient and accurate multi-agent systems, impacting areas like robotics, collaborative AI, and distributed problem-solving.
This survey paper reviews the landscape of Natural Language Processing (NLP) research and applications in the Arab world. It discusses the unique challenges posed by the Arabic language, such as its morphological complexity and dialectal diversity. The paper also presents a historical overview of Arabic NLP and surveys various research areas, including machine translation, sentiment analysis, and speech recognition. Why it matters: The survey provides a comprehensive resource for researchers and practitioners interested in the current state and future directions of Arabic NLP, a field critical for enabling AI technologies to serve Arabic-speaking communities.
This article discusses a talk on "Assistive Augmentation," designing human-computer interfaces to augment human abilities. Examples include 'AiSee' for blind users, 'Prospero' for memory training, and 'MuSS-Bits' for deaf users to feel music. Suranga Nanayakkara from the National University of Singapore will present the talk, highlighting insights from psychology, human-centered machine learning, and design thinking. Why it matters: Such assistive technologies can significantly improve the quality of life for individuals with disabilities and extend human capabilities.
Researchers created a cross-cultural corpus of annotated verbal and nonverbal behaviors in receptionist interactions. The corpus includes native speakers of American English and Arabic role-playing scenarios at university reception desks in Doha, Qatar, and Pittsburgh, USA. The manually annotated nonverbal behaviors include gaze direction, hand gestures, torso positions, and facial expressions. Why it matters: This resource can be valuable for the human-robot interaction community, especially for building culturally aware AI systems.