The AutoML Podcast
Nyckel - Building an AutoML Startup
Oscar Beijbom is talking about what it's like to run an AutoML startup: Nyckel. Beyond that, we chat about the differences between academia and industry, what truly matters in application and more. Check out Nyckel at: https://www.nyckel.com/
Neural Architecture Search: Insights from 1000 Papers
Colin White, head of research at Abacus AI, takes us on a tour of Neural Architecture Search: its origins, important paradigms and the future of NAS in the age of LLMs. If you're looking for a broad overview of NAS, this is the podcast for you!
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
There are so many great foundation models in many different domains - but how do you choose one for your specific problem? And how can you best finetune it? Sebastian Pineda has an answer: Quicktune can help select the best model and tune it for specific use cases. Listen to find out when this will ...
Discovering Temporally-Aware Reinforcement Learning Algorithms
Designing algorithms by hand is hard, so Chris Lu and Matthew Jackson talk about how to meta-learn them for reinforcement learning. Many of the concepts in this episode are interesting to meta-learning approaches as a whole, though: "how expressive can we be and still perform well?", "how can we get...
X Hacking: The Threat of Misguided AutoML
AutoML can be a tool for good, but there are pitfalls along the way. Rahul Sharma and David Selby tell us about how AutoML systems can be used to give us false impressions about explainability metrics of ML systems - maliciously, but also on accident. While this episode isn't talking about a new exc...
Introduction To New Co-Host, Theresa Eimer
In today's episode, we're introducing the very special Theresa Eimer to the show. Theresa will be taking over the hosting of many of the future episodes. Theresa has already recorded multiple episodes and we are stoked to air those shortly. We also spend a few moments explaining my relative absence ...