Generally Intelligent

36 Episoder

1. Episode 36: Ari Morcos, DatologyAI: On leveraging data to democratize model training

   Publisert: 11.7.2024
2. Episode 35: Percy Liang, Stanford: On the paradigm shift and societal effects of foundation models

   Publisert: 9.5.2024
3. Episode 34: Seth Lazar, Australian National University: On legitimate power, moral nuance, and the political philosophy of AI

   Publisert: 12.3.2024
4. Episode 33: Tri Dao, Stanford: On FlashAttention and sparsity, quantization, and efficient inference

   Publisert: 9.8.2023
5. Episode 32: Jamie Simon, UC Berkeley: On theoretical principles for how neural networks learn and generalize

   Publisert: 22.6.2023
6. Episode 31: Bill Thompson, UC Berkeley, on how cultural evolution shapes knowledge acquisition

   Publisert: 29.3.2023
7. Episode 30: Ben Eysenbach, CMU, on designing simpler and more principled RL algorithms

   Publisert: 23.3.2023
8. Episode 29: Jim Fan, NVIDIA, on foundation models for embodied agents, scaling data, and why prompt engineering will become irrelevant

   Publisert: 9.3.2023
9. Episode 28: Sergey Levine, UC Berkeley, on the bottlenecks to generalization in reinforcement learning, why simulation is doomed to succeed, and how to pick good research problems

   Publisert: 1.3.2023
10. Episode 27: Noam Brown, FAIR, on achieving human-level performance in poker and Diplomacy, and the power of spending compute at inference time

    Publisert: 9.2.2023
11. Episode 26: Sugandha Sharma, MIT, on biologically inspired neural architectures, how memories can be implemented, and control theory

    Publisert: 17.1.2023
12. Episode 25: Nicklas Hansen, UCSD, on long-horizon planning and why algorithms don't drive research progress

    Publisert: 16.12.2022
13. Episode 24: Jack Parker-Holder, DeepMind, on open-endedness, evolving agents and environments, online adaptation, and offline learning

    Publisert: 6.12.2022
14. Episode 23: Celeste Kidd, UC Berkeley, on attention and curiosity, how we form beliefs, and where certainty comes from

    Publisert: 22.11.2022
15. Episode 22: Archit Sharma, Stanford, on unsupervised and autonomous reinforcement learning

    Publisert: 17.11.2022
16. Episode 21: Chelsea Finn, Stanford, on the biggest bottlenecks in robotics and reinforcement learning

    Publisert: 3.11.2022
17. Episode 20: Hattie Zhou, Mila, on supermasks, iterative learning, and fortuitous forgetting

    Publisert: 14.10.2022
18. Episode 19: Minqi Jiang, UCL, on environment and curriculum design for general RL agents

    Publisert: 19.7.2022
19. Episode 18: Oleh Rybkin, UPenn, on exploration and planning with world models

    Publisert: 11.7.2022
20. Episode 17: Andrew Lampinen, DeepMind, on symbolic behavior, mental time travel, and insights from psychology

    Publisert: 28.2.2022