MBZUAI President Eric Xing delivered a talk at Carnegie Mellon University on May 13, 2022, titled “From Learning, to Meta-Learning, to Lego-Learning — theory, systems, and engineering.” Xing discussed the development of a standard model for learning, inspired by the standard model in physics, which aims to unify various machine learning paradigms. Before joining MBZUAI, Xing was a professor at CMU and founder of Petuum Inc., an AI development platform company. Why it matters: This talk highlights MBZUAI's leadership in advancing theoretical frameworks for machine learning and its commitment to unifying different AI approaches.
A computer science vision involves computing devices becoming proactive assistants, enhancing various aspects of life through user digitization. Current devices provide coarse digital representations of users, but there's significant potential for improvement. Karan, a Ph.D. candidate at CMU, develops technologies for consumer devices to capture richer user representations without sacrificing practicality. Why it matters: Advancements in user digitization can lead to improved extended reality experiences, health tracking, and more productive work environments, enhancing the utility of consumer devices.
Turing Award winner Raj Reddy spoke at the MBZUAI Executive Program. Reddy is a Professor of Computer Science and Robotics at Carnegie Mellon University (CMU) and has held leadership roles at CMU, AAAI, and IEEE. His research focuses on AI, human-computer interaction, and technology's societal impact. Why it matters: High-profile speakers at UAE AI programs can help attract talent and investment to the region.
A CMU professor and MBZUAI affiliated faculty presented research on how LLMs store and use knowledge learned during pre-training. The study used a synthetic biography dataset to show that LLMs may not effectively use memorized knowledge at inference time, even with zero training loss. Data augmentation during pre-training can force the model to store knowledge in specific token embeddings. Why it matters: The research highlights limitations in LLM knowledge manipulation and extraction, with implications for improving model architectures and training strategies for more effective knowledge utilization in Arabic LLMs.
Qirong Ho, co-founder and CTO of Petuum Inc., will be contributing to the "ML Systems for Many" initiative. Petuum is recognized for creating standardized building blocks for AI assembly. Ho also holds a Ph.D. from Carnegie Mellon University and is part of the CASL open-source consortium. Why it matters: Showcases the ongoing efforts to democratize AI development and deployment, making it more accessible and sustainable, although the specific initiative is not further detailed.
A Carnegie Mellon team (Tartan) presented their approach to rapidly deployable and robust autonomous aerial vehicles at the 2020 Mohamed Bin Zayed International Robotics Challenge (MBZIRC). The system utilizes common techniques in vision and control, encoding robustness into mission structure through outcome monitoring and recovery strategies. Their system placed fourth in Challenge 2 and seventh in the Grand Challenge, with achievements in balloon popping, block manipulation, and autonomous firefighting. Why it matters: The work highlights strategies for building robust autonomous systems that can operate without central communication or high-precision GPS in challenging real-world environments, directly addressing key needs in the development of field robotics for the Middle East.
Researchers from Carnegie Mellon University and MBZUAI have developed a new method called ConceptAligner for precise image editing using AI. The system decomposes text embeddings into independent building blocks called atomic concepts, allowing users to make targeted tweaks without generating entirely new images. Their approach ensures that each latent factor maps to a specific user-controllable dial, enabling accurate concept-level modifications. Why it matters: This research addresses a major limitation in AI image generation, enhancing its usefulness in industries where precise control is crucial, such as advertising and medicine, and improving the reliability of AI-driven creative tools.
This is an advertisement for KAUST (King Abdullah University of Science and Technology). It mentions King Abdullah bin Abdulaziz Al Saud. The advertisement promotes KAUST to prospective applicants. Why it matters: As a leading STEM university in the region, KAUST is vital for AI development and education, and may be related to future AI research or policy.