#351 Will World Models Bring us AGI? with Eric Xing, President & Professor at MBZUAI

About this episode

The episode discusses the potential of world models in advancing AI towards artificial general intelligence with insights from Eric Xing.

World models are emerging as the next step after large language models, pushing AI from book knowledge toward systems that can simulate the physical and social world. Instead of just generating text or short videos, the goal is steerable simulation with long-horizon consistency and planning. For practitioners, this raises practical choices: what data and representations do you need, and when do you mix symbolic reasoning with generative models? How do you test whether a model can follow actions over minutes, not seconds? And where do you start—robotics, driving safety, or synthetic data generation? Professor Eric Xing is President of Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) and a world-leading computer scientist whose work spans statistical machine learning, distributed systems, computational biology, and healthcare AI. A fellow of AAAI, IEEE, and the American Statistical Association, he has authored over 400 research papers cited more than 44,000 times.Before MBZUAI, Eric was a Professor of Computer Science at Carnegie Mellon University, where he also founded the Center for Machine Learning and Health. He is the founder and chief scientist of Petuum Inc…

People in this episode

Host: Richie

Guest: Eric Xing

Topics covered

• world models
• artificial general intelligence
• AI simulation
• symbolic reasoning
• generative models
• robotics
• synthetic data generation

Keywords

• world models
• AGI
• AI simulation
• symbolic reasoning
• generative models
• robotics
• synthetic data

Mentioned in this episode

Organizations: Mohamed bin Zayed University of Artificial Intelligence, Carnegie Mellon University, Petuum Inc., Stanford, Facebook, AAAI, IEEE, American Statistical Association

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