The podcast explores the intersection of AI and material science, particularly regarding climate change and new materials discovery. Max Welling, known for his work on variational autoencoders and graph neural networks, discusses his startup CuspAI and its mission to accelerate materials innovation for a sustainable future. He highlights the potential of AI to search through the material space, automating experimentation and computation to identify promising candidates. Welling also touches upon the role of physics in machine learning, explaining equivariance and its applications. He introduces his upcoming book on generative AI and stochastic thermodynamics, emphasizing the mathematical connections between these fields and their potential for cross-fertilization.
Sign in to continue reading, translating and more.
Continue