Gradient Dissent: Conversations on AI

114 Episoder

1. Cade Metz — The Stories Behind the Rise of AI

   Udgivet: 18.3.2021
2. Dave Selinger — AI and the Next Generation of Security Systems

   Udgivet: 11.3.2021
3. Tim & Heinrich — Democraticizing Reinforcement Learning Research

   Udgivet: 4.3.2021
4. Daphne Koller — Digital Biology and the Next Epoch of Science

   Udgivet: 18.2.2021
5. Piero Molino — The Secret Behind Building Successful Open Source Projects

   Udgivet: 11.2.2021
6. Rosanne Liu — Conducting Fundamental ML Research as a Nonprofit

   Udgivet: 5.2.2021
7. Sean Gourley — NLP, National Defense, and Establishing Ground Truth

   Udgivet: 28.1.2021
8. Peter Wang — Anaconda, Python, and Scientific Computing

   Udgivet: 21.1.2021
9. Chris Anderson — Robocars, Drones, and WIRED Magazine

   Udgivet: 14.1.2021
10. Adrien Treuille — Building Blazingly Fast Tools That People Love

    Udgivet: 4.12.2020
11. Peter Norvig – Singularity Is in the Eye of the Beholder

    Udgivet: 20.11.2020
12. Robert Nishihara — The State of Distributed Computing in ML

    Udgivet: 13.11.2020
13. Ines & Sofie — Building Industrial-Strength NLP Pipelines

    Udgivet: 29.10.2020
14. Daeil Kim — The Unreasonable Effectiveness of Synthetic Data

    Udgivet: 15.10.2020
15. Joaquin Candela — Definitions of Fairness

    Udgivet: 1.10.2020
16. Richard Socher — The Challenges of Making ML Work in the Real World

    Udgivet: 29.9.2020
17. Zack Chase Lipton — The Medical Machine Learning Landscape

    Udgivet: 17.9.2020
18. Anthony Goldbloom — How to Win Kaggle Competitions

    Udgivet: 9.9.2020
19. Suzana Ilić — Cultivating Machine Learning Communities

    Udgivet: 2.9.2020
20. Jeremy Howard — The Story of fast.ai and Why Python Is Not the Future of ML

    Udgivet: 25.8.2020