Phase Transition in AI: Opportunities and Gaps Towards Making AI Real

Recent advances in AI not only created promises for what AI can do, but also introduced questions about how to bring this promise to reality in real-world applications in a responsible way. In this talk, I will describe my journey at Microsoft Research from being amazed by the sparks of GPT-4 to understanding limitations of current family of models and driving research on what comes next. I will discuss research directions we are pursuing to make future AI systems more efficient, sustainable, controllable and valuable through innovations in model training, agent technologies and engineering practices. I will conclude with reflections on our unified responsibly in balancing the promise of AI with rising risks and concerns.