Simplifying Distributed Frameworks

Ion and Lukas discuss the challenges of creating a simple distributed framework for machine learning applications, prioritizing performance and flexibility over reliability. They delve into the evolution of task models to meet the demands of developers, highlighting the complexities introduced by GPU processing and reinforcement learning simulations.