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Hosted by Unknown Host · 🇺🇸 US · EN-US · 43 episodes
Established thought leaders with verified media credentials.
A show about the science and engineering behind AutoML.
Unknown Host hosts The AutoML Podcast, a technology show with 43 episodes published.
AutoML is dead an LLMs have killed it? MLGym is a benchmark and framework testing this theory. Roberta Raileanu and Deepak Nathani discuss how well current LLMs are doing at solving ML tasks, what the biggest roadblocks
Where and how can we use foundation models in AutoML? Richard Song, researcher at Google DeepMind, has some answers. Starting off from his position paper on leveraging foundation models for optimization, we chat about wh
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: h
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
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 b
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 wh
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 - mal
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 t
Today we're talking with Nick Erickson from AutoGluon. We discuss AutoGluon's fascinating origin story, its unique point of view, the science and engineering behind some of its unique contributions, Amazon's Machine Lear
Today we're talking with Joseph Giovanelli about his work on integrating logic and argumentation into AutoML systems. Joseph is a PhD student at the University of Bologna. He was more recently in Hannover working on ethi
Today we're talking with Caitlin Owen, a post-doc at the University of Otago about her work on error decomposition. She recently published a paper titled "Towards Explainable AutoML Using Error Decomposition" about how a
Today we're talking with Gaurav Rao, the EVP & GM of Machine Learning and AI at AtScale, a company centered around the semantic layer. For some time now, I've been feeling that there is a deep connection between a formal
Today Ankush Garg is speaking with Rishi Bommasani, PhD student at Stanford and one of the originator of the term Foundation Models. They’re talking about the origins of the term Foundation Model, which he and his group
Today we're talking with Raymond Peck, a senior engineer and director in the AutoML space. He spent time at H2O, dotData, Alteryx and many other places. This is a fascinating conversation about the business, engineering,
Today we’re talking to Noah Hollmann and Samuel Muller about their paper on TabPFN - which is an incredible spin on AutoML based on Bayesian inference and transformers. [Quick note on audio quality]: Some of the tracks h
Today we’re talking to Sean Sexton, the Director of Modeling and Analytics Consulting at KPMG, about the role of models in financial institutions and how the risks associated with them is managed. This turned out to be a
Today we’re talking to Matt Levine. Matt is a PhD student in computing and mathematical sciences at Caltech, and he focuses on improving the prediction and inference of physical systems by blending together both mechanis
Today we’re chatting with Junhong Shen, a PhD student at Carnegie Mellon. Junhong and her team are working on the generalizability of NAS algorithms across a diverse set of tasks. Today we'll be talking about DASH, a NAS
Today we're speaking with Marius Lindauer and it is certainly one of my favorite episodes! As you’ll hear, Marius is full of ideas for where AutoML systems can and should go. These ideas are crystallized in a blog-post,
Today Ankush Garg is talking to Mehdi Bahrami about his recent project: BERT-Sort. BERT-Sort is an example of how large language models can add useful context to tabular datasets, and to AutoML systems. Mehdi is a Member
Richard Song
Google DeepMind
1 appearance on this show
Oscar Beijbom
Nyckel
1 appearance on this show
Colin White
Abacus AI
1 appearance on this show
Nick Erickson
AutoGluon
1 appearance on this show
Joseph Giovanelli
University of Bologna
1 appearance on this show
Caitlin Owen
University of Otago
1 appearance on this show
Gaurav Rao
AtScale
1 appearance on this show
Rishi Bommasani
Stanford
1 appearance on this show
Sean Sexton
KPMG
1 appearance on this show
Matt Levine
Caltech
1 appearance on this show
Junhong Shen
Carnegie Mellon
1 appearance on this show
Mehdi Bahrami
Fujitsu
1 appearance on this show
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The AutoML Podcast is hosted by Unknown Host. The show is categorised under technology and has published 43 episodes.
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