Generally Intelligent
By Kanjun Qiu
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Image by Kanjun Qiu
Category: Technology
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Subscribers: 11
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Episodes: 40
Description
Conversations with builders and thinkers on AI's technical and societal futures. Made by Imbue.
| Episode | Date |
|---|---|
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There will be a scientific theory of deep learning
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Apr 24, 2026 |
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Malleable software and human agency with Geoffrey Litt
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Nov 14, 2025 |
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From lawless spaces to true liberty: rethinking AI's role in society
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Aug 13, 2025 |
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Rylan Schaeffer, Stanford: Investigating emergent abilities and challenging dominant research ideas
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Sep 18, 2024 |
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Ari Morcos, DatologyAI: Leveraging data to democratize model training
|
Jul 11, 2024 |
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Percy Liang, Stanford: The paradigm shift and societal effects of foundation models
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May 09, 2024 |
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Seth Lazar, Australian National University: Legitimate power, moral nuance, and the political philosophy of AI
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Mar 12, 2024 |
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Tri Dao, Stanford: FlashAttention and sparsity, quantization, and efficient inference
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Aug 09, 2023 |
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Jamie Simon, UC Berkeley: Theoretical principles for how neural networks learn and generalize
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Jun 22, 2023 |
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Bill Thompson, UC Berkeley: How cultural evolution shapes knowledge acquisition
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Mar 29, 2023 |
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Ben Eysenbach, CMU: Designing simpler and more principled RL algorithms
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Mar 23, 2023 |
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Jim Fan, NVIDIA: Foundation models for embodied agents, scaling data, and why prompt engineering will become irrelevant
|
Mar 09, 2023 |
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Sergey Levine, UC Berkeley: The bottlenecks to generalization in reinforcement learning, why simulation is doomed to succeed, and how to pick good research problems
|
Mar 01, 2023 |
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Noam Brown, FAIR: Achieving human-level performance in poker and Diplomacy, and the power of spending compute at inference time
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Feb 09, 2023 |
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Sugandha Sharma, MIT: Biologically inspired neural architectures, how memories can be implemented, and control theory
|
Jan 17, 2023 |
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Nicklas Hansen, UCSD: Long-horizon planning and why algorithms don't drive research progress
|
Dec 16, 2022 |
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Jack Parker-Holder, DeepMind: Open-endedness, evolving agents and environments, online adaptation, and offline learning
|
Dec 06, 2022 |
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Celeste Kidd, UC Berkeley: Attention and curiosity, how we form beliefs, and where certainty comes from
|
Nov 22, 2022 |
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Archit Sharma, Stanford: Unsupervised and autonomous reinforcement learning
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Nov 17, 2022 |
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Chelsea Finn, Stanford: The biggest bottlenecks in robotics and reinforcement learning
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Nov 03, 2022 |
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Hattie Zhou, Mila: Supermasks, iterative learning, and fortuitous forgetting
|
Oct 14, 2022 |
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Minqi Jiang, UCL: Environment and curriculum design for general RL agents
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Jul 19, 2022 |
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Oleh Rybkin, UPenn: Exploration and planning with world models
|
Jul 11, 2022 |
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Andrew Lampinen, DeepMind. Symbolic behavior, mental time travel, and insights from psychology
|
Feb 28, 2022 |
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Yilun Du, MIT: Energy-based models, implicit functions, and modularity
|
Dec 21, 2021 |
|
Martín Arjovsky, INRIA: Benchmarks for robustness and geometric information theory
|
Oct 15, 2021 |
|
Yash Sharma, MPI-IS: Generalizability, causality, and disentanglement
|
Sep 24, 2021 |
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Jonathan Frankle, MIT: The lottery ticket hypothesis and the science of deep learning
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Sep 10, 2021 |
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Jacob Steinhardt, UC Berkeley: Machine learning safety, alignment and measurement
|
Jun 18, 2021 |
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Vincent Sitzmann, MIT: Neural scene representations for computer vision and more general AI
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May 20, 2021 |
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Dylan Hadfield-Menell, UC Berkeley/MIT: The value alignment problem in AI
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May 12, 2021 |
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Drew Linsley, Brown: Inductive biases for vision and generalization
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Apr 02, 2021 |
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Giancarlo Kerg, Mila: Approaching deep learning from mathematical foundations
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Mar 27, 2021 |
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Yujia Huang, Caltech: Neuro-inspired generative models
|
Mar 18, 2021 |
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Julian Chibane, MPI-INF: 3D reconstruction using implicit functions
|
Mar 05, 2021 |
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Katja Schwarz, MPI-IS: GANs, implicit functions, and 3D scene understanding
|
Feb 24, 2021 |
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Joel Lehman, OpenAI: Evolution, open-endedness, and reinforcement learning
|
Feb 17, 2021 |
|
Cinjon Resnick, NYU: Activity and scene understanding
|
Feb 01, 2021 |
|
Sarah Jane Hong, Latent Space: Neural rendering & research process
|
Jan 07, 2021 |
|
Kelvin Guu, Google AI: Language models & overlooked research problems
|
Dec 15, 2020 |