046 The Great ML Stagnation ( Mark Saroufim and Dr. Mathew Salvaris)
Academics think of themselves as trailblazers, explorers seekers of the truth. Any fundamental discovery involves a significant degree of risk. If an idea is guaranteed to work then it moves from the realm of research to engineering. Unfortunately, this also means that most research careers will invariably be failures at least if failures are measured via objective metrics like citations. Today we discuss the recent article from Mark Saroufim called Machine Learning: the great stagnation. We discuss the rise of gentleman scientists, fake rigor, incentives in ML, SOTAchasing, graduate student descent, distribution of talent in ML and how to learn effectively. With special guest interviewer Mat Salvaris. Machine learning: the great stagnation 00:00:00 Main show kick off 00:16:30 Great stagnation article, Bad incentive systems in academia 00:18:24 OpenAI is a media business 00:19:48 Incentive structures in academia 00:22:13 SOTA chasing 00:24:47
|
|