Mark recently wrote a controversial and viral article: The Great Stagnation in Machine Learning, in which he posits that Machine Learning Researchers can now engage in risk-free, high-income, high-prestige work. Effectively becoming today’s Medieval Catholic priests.
There is a couple of reasons for this state of affairs, so come to hear Mark lay them out from the academic brain drain, to the obsession with metrics in our education system, the death of first principles, empiricism and feedback loops, graduate student descent and navel gazing debates.

Thankfully despite all these perverse incentives there are still a few fascinating research projects that are constantly innovating namely Fast.ai in the language and tooling space, Unity in the simulation space and HuggingFace in the platform space and many more. We will discuss how these projects avoid the intellectual stagnation in Machine Learning and what we can learn from them?