MLGym: A New Framework and Benchmark for Advancing AI Research Agents
The AutoML Podcast31 Loka 2025

MLGym: A New Framework and Benchmark for Advancing AI Research Agents

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 are, and what that means for AutoML generally. Check out the paper: https://arxiv.org/pdf/2502.14499 More on Roberta: https://rraileanu.github.io/ More on Deepak: https://dnathani.net/

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(43)

Leverage Foundational Models for Black-Box Optimization

Leverage Foundational Models for Black-Box Optimization

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 optimizati...

22 Syys 202556min

Nyckel - Building an AutoML Startup

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. Ch...

7 Maalis 20251h 20min

Neural Architecture Search: Insights from 1000 Papers

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 o...

3 Joulu 20241h 15min

Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How

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 c...

8 Elo 202453min

Discovering Temporally-Aware Reinforcement Learning Algorithms

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-learni...

24 Kesä 202451min

X Hacking: The Threat of Misguided AutoML

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...

27 Touko 202454min

Introduction To New Co-Host, Theresa Eimer

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 episod...

27 Touko 202413min