Google DeepMind Executive Explains the Math Behind Model Uncertainty
Zoubin Ghahramani, research vice president at Google DeepMind, discussed the challenge of overconfident AI outputs on a recent podcast. He argued that teaching models to measure their own uncertainty is critical to preventing confident errors. The conversation highlights how mathematical frameworks like Bayesian reasoning could improve future model reliability.
