The Gradient: Perspectives on AI

147 Episodo

1. Luis Voloch: AI and Biology

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

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

   Publicado: 6/10/2022
4. Varun Ganapathi: AKASA, AI and Healthcare

   Publicado: 29/9/2022
5. Joel Lehman: Open-Endedness and Evolution through Large Models

   Publicado: 22/9/2022
6. Andrew Feldman: Cerebras and AI Hardware

   Publicado: 15/9/2022
7. Christopher Manning: Linguistics and the Development of NLP

   Publicado: 8/9/2022
8. Jeff Clune: Genetic Algorithms, Quality-Diversity, Curiosity

   Publicado: 1/9/2022
9. Catherine Olsson and Nelson Elhage: Anthropic, Understanding Transformers

   Publicado: 26/8/2022
10. Been Kim: Interpretable Machine Learning

    Publicado: 18/8/2022
11. Laura Weidinger: Ethical Risks, Harms, and Alignment of Large Language Models

    Publicado: 5/8/2022
12. Sebastian Raschka: AI Education and Research

    Publicado: 29/7/2022
13. Lt. General Jack Shanahan: AI in the DoD, Project Maven, and Bridging the Tech-DoD Gap

    Publicado: 22/7/2022
14. Sara Hooker: Cohere For AI, the Hardware Lottery, and DL Tradeoffs

    Publicado: 14/7/2022
15. Lukas Biewald: Crowdsourcing at CrowdFlower and ML Tooling at Weights & Biases

    Publicado: 7/7/2022
16. Chip Huyen: Machine Learning Tools and Systems

    Publicado: 30/6/2022
17. Preetum Nakkiran: An Empirical Theory of Deep Learning

    Publicado: 24/6/2022
18. Max Woolf: Data Science at BuzzFeed and AI Content Generation

    Publicado: 16/6/2022
19. Rosanne Liu: Paths in AI Research and ML Collective

    Publicado: 10/6/2022
20. Ben Green: "Tech for Social Good" Needs to Do More

    Publicado: 2/6/2022