David Nicholson

The scientific Python community, like the rest of the world, faces a set of interlocking crises. Longstanding questions over how to sustainably develop, fund and maintain open-source scientific software, open data, reproducible research and collaborative training are being magnified by a variety of forces from the AI boom, to government disinvestment, to economic disruption.

AI is moving from experimentation to real-world deployment, and the challenges shift fast at scale. This session brings together engineering leaders to explore what it takes to operationalize AI in production. Expect a range of insights drawn from building and scaling complex platforms, and what those lessons mean for AI today.

Research on animal acoustic communication is being revolutionized by deep learning. In this talk we present vak, a framework that allows researchers in this area to easily benchmark deep neural network models and apply them to their own data.