The AutoML Podcast

A show about the science and engineering behind AutoML.

The AutoML Podcast is a technology podcast hosted by Unknown Host, with 43 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Unknown Host hosts The AutoML Podcast, a technology show with 43 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  The AutoML Podcast

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

  Oct 31, 20251h 29m

  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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  The AutoML Podcast

  Leverage Foundational Models for Black-Box Optimization

  Sep 22, 202557 min

  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 what makes foundation models valuable for AutoML, how the next steps could look like, but also why the community is not currently embracing the topic as much as it could. Paper Link: https://arxiv.org/abs/2405.03547 Richard's website: https://xingyousong.github.io/

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  The AutoML Podcast

  Nyckel - Building an AutoML Startup

  Mar 7, 20251h 21m

  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/

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  The AutoML Podcast

  Neural Architecture Search: Insights from 1000 Papers

  Dec 3, 20241h 16m

  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!

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  The AutoML Podcast

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

  Aug 8, 202453 min

  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 be a Huggingface feature and if hyperparameter optimization is even important in finetuning models (spoiler: very much so)!

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