The Gradient: Perspectives on AI

143 Episoder

1. Joel Lehman: Open-Endedness and Evolution through Large Models

   Publisert: 22.9.2022
2. Andrew Feldman: Cerebras and AI Hardware

   Publisert: 15.9.2022
3. Christopher Manning: Linguistics and the Development of NLP

   Publisert: 8.9.2022
4. Jeff Clune: Genetic Algorithms, Quality-Diversity, Curiosity

   Publisert: 1.9.2022
5. Catherine Olsson and Nelson Elhage: Anthropic, Understanding Transformers

   Publisert: 26.8.2022
6. Been Kim: Interpretable Machine Learning

   Publisert: 18.8.2022
7. Laura Weidinger: Ethical Risks, Harms, and Alignment of Large Language Models

   Publisert: 5.8.2022
8. Sebastian Raschka: AI Education and Research

   Publisert: 29.7.2022
9. Lt. General Jack Shanahan: AI in the DoD, Project Maven, and Bridging the Tech-DoD Gap

   Publisert: 22.7.2022
10. Sara Hooker: Cohere For AI, the Hardware Lottery, and DL Tradeoffs

    Publisert: 14.7.2022
11. Lukas Biewald: Crowdsourcing at CrowdFlower and ML Tooling at Weights & Biases

    Publisert: 7.7.2022
12. Chip Huyen: Machine Learning Tools and Systems

    Publisert: 30.6.2022
13. Preetum Nakkiran: An Empirical Theory of Deep Learning

    Publisert: 24.6.2022
14. Max Woolf: Data Science at BuzzFeed and AI Content Generation

    Publisert: 16.6.2022
15. Rosanne Liu: Paths in AI Research and ML Collective

    Publisert: 10.6.2022
16. Ben Green: "Tech for Social Good" Needs to Do More

    Publisert: 2.6.2022
17. Max Braun: Teaching Robots to Help People in their Everyday Lives

    Publisert: 26.5.2022
18. Yejin Choi: Teaching Machines Common Sense and Morality

    Publisert: 19.5.2022
19. David Chalmers on AI and Consciousness

    Publisert: 12.5.2022
20. Greg Yang on Communicating Research, Tensor Programs, and µTransfer

    Publisert: 28.4.2022