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/
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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/
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 Learning University, AutoGluon's multi-layer stack ensembler in all its detail, their feature preprocessing pipeline, their feature type inference, their adaptive approach to early stopping, controlling for inference speeds, the different multi-modal architectures, the ML culture...
The AutoML Podcast
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/
