Open Core Summit

Data science and machine learning are transforming entire industries, producing results that are superior than previous approaches for a variety of problems. But achieving state of the art results is often only available to an elite few. The reason is that modern deep learning algorithms take copious amounts of compute and storage, and therefore money, to train state of the art models. We’ve seen this movie before in software engineering. Only large companies used to have the resources to develop complex software like an operating systems. Open source fundamentally changed these dynamics. Today Linux is one of the most popular operating systems, and continues to be the foundation on which many companies build their products. In this talk I’ll share how successful patterns from open source software may be transferred and applied to the data science space in order to democratize access to state of the art tools and data, so the entire data science community can accelerate innovation.