The Great Stagnation in ML

Mar 18, 10:00AM PDT(05:00PM GMT).
  • Free 163 Attendees
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 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?

Mark Saroufim

Mark is a Machine Learning Engineer who has worked at a wide variety of top labs including Graphcore,, Microsoft and NASA Jet Propulsion Lab. Mark is passionate about the future of Machine Learning and writes about what it may look like at and how we can program our own robots at home at