120 Episodo

  1. Cristóbal Valenzuela — The Next Generation of Content Creation and AI

    Publicado: 19/1/2023
  2. Jeremy Howard — The Simple but Profound Insight Behind Diffusion

    Publicado: 5/1/2023
  3. Jerome Pesenti — Large Language Models, PyTorch, and Meta

    Publicado: 22/12/2022
  4. D. Sculley — Technical Debt, Trade-offs, and Kaggle

    Publicado: 1/12/2022
  5. Emad Mostaque — Stable Diffusion, Stability AI, and What’s Next

    Publicado: 15/11/2022
  6. Jehan Wickramasuriya — AI in High-Stress Scenarios

    Publicado: 6/10/2022
  7. Will Falcon — Making Lightning the Apple of ML

    Publicado: 15/9/2022
  8. Aaron Colak — ML and NLP in Experience Management

    Publicado: 26/8/2022
  9. Jordan Fisher — Skipping the Line with Autonomous Checkout

    Publicado: 4/8/2022
  10. Drago Anguelov — Robustness, Safety, and Scalability at Waymo

    Publicado: 14/7/2022
  11. James Cham — Investing in the Intersection of Business and Technology

    Publicado: 7/7/2022
  12. Boris Dayma — The Story Behind DALL·E mini, the Viral Phenomenon

    Publicado: 17/6/2022
  13. Tristan Handy — The Work Behind the Data Work

    Publicado: 9/6/2022
  14. Johannes Otterbach — Unlocking ML for Traditional Companies

    Publicado: 12/5/2022
  15. Mircea Neagovici — Robotic Process Automation (RPA) and ML

    Publicado: 21/4/2022
  16. Jensen Huang — NVIDIA’s CEO on the Next Generation of AI and MLOps

    Publicado: 3/3/2022
  17. Peter & Boris — Fine-tuning OpenAI's GPT-3

    Publicado: 10/2/2022
  18. Ion Stoica — Spark, Ray, and Enterprise Open Source

    Publicado: 20/1/2022
  19. Stephan Fabel — Efficient Supercomputing with NVIDIA's Base Command Platform

    Publicado: 6/1/2022
  20. Chris Padwick — Smart Machines for More Sustainable Farming

    Publicado: 23/12/2021

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Join Lukas Biewald on Gradient Dissent, an AI-focused podcast brought to you by Weights & Biases. Dive into fascinating conversations with industry giants from NVIDIA, Meta, Google, Lyft, OpenAI, and more. Explore the cutting-edge of AI and learn the intricacies of bringing models into production.

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