147 Épisodes

  1. Luis Voloch: AI and Biology

    Publié: 27/10/2022
  2. Zachary Lipton: Where Machine Learning Falls Short

    Publié: 13/10/2022
  3. Stuart Russell: The Foundations of Artificial Intelligence

    Publié: 06/10/2022
  4. Varun Ganapathi: AKASA, AI and Healthcare

    Publié: 29/09/2022
  5. Joel Lehman: Open-Endedness and Evolution through Large Models

    Publié: 22/09/2022
  6. Andrew Feldman: Cerebras and AI Hardware

    Publié: 15/09/2022
  7. Christopher Manning: Linguistics and the Development of NLP

    Publié: 08/09/2022
  8. Jeff Clune: Genetic Algorithms, Quality-Diversity, Curiosity

    Publié: 01/09/2022
  9. Catherine Olsson and Nelson Elhage: Anthropic, Understanding Transformers

    Publié: 26/08/2022
  10. Been Kim: Interpretable Machine Learning

    Publié: 18/08/2022
  11. Laura Weidinger: Ethical Risks, Harms, and Alignment of Large Language Models

    Publié: 05/08/2022
  12. Sebastian Raschka: AI Education and Research

    Publié: 29/07/2022
  13. Lt. General Jack Shanahan: AI in the DoD, Project Maven, and Bridging the Tech-DoD Gap

    Publié: 22/07/2022
  14. Sara Hooker: Cohere For AI, the Hardware Lottery, and DL Tradeoffs

    Publié: 14/07/2022
  15. Lukas Biewald: Crowdsourcing at CrowdFlower and ML Tooling at Weights & Biases

    Publié: 07/07/2022
  16. Chip Huyen: Machine Learning Tools and Systems

    Publié: 30/06/2022
  17. Preetum Nakkiran: An Empirical Theory of Deep Learning

    Publié: 24/06/2022
  18. Max Woolf: Data Science at BuzzFeed and AI Content Generation

    Publié: 16/06/2022
  19. Rosanne Liu: Paths in AI Research and ML Collective

    Publié: 10/06/2022
  20. Ben Green: "Tech for Social Good" Needs to Do More

    Publié: 02/06/2022

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Deeply researched, technical interviews with experts thinking about AI and technology. thegradientpub.substack.com

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