MBZUAI Professor Ian Reid discusses his career in embodied AI, from early work on active vision at Oxford to current research. He highlights three key developments: cameras as geometric sensors, visual SLAM, and advancements in robot navigation. Reid distinguishes embodied AI from systems like ChatGPT, emphasizing its need for understanding and interaction with the physical world. Why it matters: The insights from a leading expert underscore the importance of embodied AI as the next frontier in intelligent systems and robotics in the region.
Ian Reid, a Professor of Computer Science at the University of Adelaide, gave a talk at MBZUAI on leveraging deep learning to go beyond geometric SLAM. The talk covered using prior domain knowledge to improve map and shape estimation and enabling navigation in unvisited environments. The research aims to turn cameras into devices for flexible, large-scale situational awareness or "Spatial AI" sensors. Why it matters: Integrating deep learning with SLAM could significantly advance robotic navigation and spatial understanding, with applications for autonomous systems in various industries.
MBZUAI Professor Ivan Laptev is working to bridge the gap between data-driven AI systems and embodied agents (robots). He notes challenges in robotics including data scarcity, the need to generate new data through actions, and the requirement for real-time operation. Laptev aims to transfer innovations from computer vision to robotics, addressing these challenges to improve robots' ability to interpret and respond to the complexities of the real world. Why it matters: Overcoming these hurdles is crucial for advancing robotics and enabling robots to effectively interact with and navigate dynamic real-world environments.
Ivan Laptev from INRIA Paris presented a talk at MBZUAI on embodied multi-modal visual understanding, covering advancements in video understanding tasks like question answering and captioning. The talk highlighted recent work on vision-language navigation and manipulation. He argued that detailed understanding of the physical world through vision is still in early stages, discussing open research directions related to robotics and video generation. Why it matters: The discussion of robotics applications and future research directions in embodied AI could influence the direction of AI research and development in the UAE, particularly at MBZUAI.
MBZUAI Professor Fahad Khan is working on a unified theory of machine visual intelligence. His goal is to enable AI systems to better understand and function in complex, chaotic visual environments. The aim is to improve real-world applications like smart cities, personalized healthcare, and autonomous vehicles. Why it matters: This research could significantly advance AI's ability to perceive and interact with the real world, especially in challenging environments common in the developing world.