Explore the intricacies of learning one-hidden-layer neural networks through landscape design in this 32-minute conference talk by Tengyu Ma from Stanford University. Delve into the challenges of optimization in machine learning and discover a new objective for training neural networks. Examine why straightforward objectives fail and learn about an innovative analytic formula. Investigate provable non-convex optimization algorithms and gain insights into potential paradigms for optimization theory in machine learning. This Simons Institute presentation, part of the "Optimization, Statistics and Uncertainty" series, offers a deep dive into the interfaces between users and optimizers, providing valuable knowledge for researchers and practitioners in the field of neural networks and machine learning optimization.