Donna Vakalis, a postdoc researcher at Mila, Quebec AI Institute, focuses on reducing climate emissions from buildings using AI. Her work involves optimizing HVAC systems without extensive data, employing data-efficient reinforcement learning. Vakalis' research aims to create agents that can control building systems effectively from day one, even without prior experience in the specific building. She uses in-context reinforcement learning, a novel method that adapts to different building conditions. Vakalis' mentors, Joshua Bengio and David Ronik, are leaders in the field. The conversation also touched on the broader implications of AI in urban settings and the high demand for AI talent.

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