Abstract: 

Open Source software powered the data science revolution over the last 10 years, and is at the heart of all modern AI systems. But what are the essential principles of ""open source"", and why were they important to this movement? What lessons can be learned from the dynamics of OSS communities? Is ""open source"" still relevant if AI can write code, and if only billion-dollar companies can train AI models, why does community matter?
In this talk, Peter will answer all these questions. He will explain why the AI revolution must not only learn from the last 15 years of Open Source data science, but that it must build on those principles if we are to achieve a broad vision of human thriving in whatever world lies ahead.

Bio: 

Peter Wang is the CEO and co-founder of Anaconda, Inc. Prior to founding Anaconda (formerly Continuum Analytics), Peter spent 15 years in software design and development across a broad range of areas, including 3D graphics, geophysics, large data simulation and visualization, financial risk modeling, and medical imaging. As a creator of the PyData community and conferences, he devotes time and energy to growing the Python data science community and advocating for increasing data literacy around the world. Peter holds a BA in Physics from Cornell University.