Max Welling

This conversation features Max Welling, a prominent Professor and VP of Technology at Qualcomm, known for his innovative work in geometric deep learning. He discusses the crucial role of domain knowledge in machine learning and how inductive biases impact model predictions. The dialogue also explores the fascinating intersection of quantum computing and AI, particularly the potential of quantum neural networks. Furthermore, Welling highlights the significance of symmetries in neural networks and their applications in real-world problems, including protein folding.

In this engaging conversation, Max Welling, Vice President of Technologies at Qualcomm Netherlands and Professor at the University of Amsterdam, delves into neural augmentation and its real-world applications. He discusses federated learning as a means to enhance data privacy for users, while exploring the exciting intersection of quantum mechanics and neural networks. Max also highlights innovative chip design approaches that merge traditional engineering with machine learning, showcasing the potential of these advancements in tackling complex challenges.

In this enlightening discussion, Max Welling, a research chair in machine learning at the University of Amsterdam and Qualcomm's VP of Technologies, dives into groundbreaking topics. He reveals his work on Bayesian deep learning, Gauge Equivariant CNNs, and innovations in AI for improved computing efficiency. Max also shares his insights on the evolution of AI, emphasizing the balance between models and data, and explores the exciting possibilities of integrating generative models with rule-based systems to pave the way for artificial general intelligence.