Christian Szegedy | The Inverse Mindset of Machine Learning

Sponsored by Evolution AI: Monday 24 May 2021 Abstract: Here, in this talk, I will give examples of how large areas of machine learning promotes and requires a mindset different from more to traditional areas of computer science. While most of computer science is focused on disciplined, efficient solutions for most problems, large parts of machine learning and AI is focused on finding good tasks and curricula for certain domains. While machine learning still requires classical optimization and efficient solutions, a lot of the work shifts towards encoding and creating interesting problems and exploring the power and limits of new solutions. For example, transformer networks act as a powerful, self-routing structure and pre-training with the correct, conceptually relevant tasks has become a large area of research. Here we will examine several examples of the working of this mindset in practical examples. This presentation will assume some familiarity with transfor