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Announcements, research highlights, and perspectives on topics we find interesting.

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Seth Lazar, Australian National University: On legitimate power, moral nuance, and the political philosophy of AI
PodcastMarch 12, 2024
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On being seen as a whole person: Valentine’s Day at Imbue
CompanyMarch 1, 2024
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“What I’m most excited about is that I think [AI] is one of the biggest things that can unlock our potential.” — Kanjun Qiu, CEO
NewsFebruary 26, 2024
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Designing algorithms that distribute agency: On 'Lotteries We All Lose'
BriefFebruary 23, 2024
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Tri Dao, Stanford: On FlashAttention and sparsity, quantization, and efficient inference
PodcastFebruary 8, 2024
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Imbue joins Department of Commerce’s AI Safety Institute Consortium
NewsFebruary 8, 2024
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Imbue and Dell designed the custom system... to support rapid experimentation in developing AI systems
NewsNovember 28, 2023
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We've partnered with Dell to build a cluster of 10,000 Nvidia H100 GPUs to train our models
NewsNovember 28, 2023
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The need for trust: Analyzing the individual comments to the NTIA’s AI RFC
PerspectiveOctober 30, 2023
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Methodology for analyzing the individual comments to the NTIA’s AI RFC
PerspectiveOctober 30, 2023
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Imbue Raises Fresh Capital, Amazon’s Alexa Fund Joins Investor Lineup
CompanyOctober 19, 2023
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“We want to enable agents that people can actually use and that work reliably, and ultimately the vision is to reinvent the personal computer so that it’s actually truly personal.” Kanjun Qiu
NewsOctober 19, 2023
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Danny Geisz: On interning at Imbue, going full-time, and making magic
CompanyOctober 3, 2023
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Imbue raises $200M to build AI systems that can reason and code
CompanySeptember 7, 2023
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Bryden Fogelman: On coding agents and finding meaningful work at Imbue
CompanySeptember 6, 2023
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Our technical hiring process
CompanySeptember 6, 2023
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In-person culture and habits
CompanySeptember 1, 2023
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Where are the good policy ideas? Analyzing the NTIA's AI RFC
PerspectiveAugust 21, 2023
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Can we develop theoretical explanations for today’s AI systems?
BriefAugust 4, 2023
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“The real challenge is building systems with robust reasoning,” said Qiu.
NewsJuly 17, 2023
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What's next in AI? In conversation with Kanjun Qiu and Reid Hoffman
PerspectiveJuly 6, 2023
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Jamie Simon, UC Berkeley: On theoretical principles for how neural networks learn and generalize
PodcastJune 29, 2023
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On the Stepwise Nature of Self-Supervised Learning
ResearchJune 29, 2023
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Scaling Laws For Every Hyperparameter Via Cost-Aware HPO
ResearchJune 20, 2023
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Ellie Kitanidis: On her journey from physics PhD to AI researcher
CompanyJune 15, 2023
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Our submission to the NTIA's AI accountability RFC
PerspectiveJune 10, 2023
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Towards guardrails, not guidelines: a policy framework for powerful AI systems
PerspectiveJune 8, 2023
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Kanjun Qiu, the CEO of Generally Intelligent, an AI research company, has been buying advanced graphic chips since last year for her own servers, allowing her to ride out the current shortage.
NewsMay 29, 2023
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“The biggest thing…that I find them to be helpful for is inspiring me as the user and helping me learn things that I wouldn’t have necessarily thought of on my own,” Josh Albrecht, CTO of Generally Intelligent
NewsMay 25, 2023
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Is risk regulation right for AI?
BriefMay 17, 2023
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A public option LLM?
BriefMay 16, 2023
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Introducing Perspectives from Imbue
PerspectiveMay 15, 2023
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Update: The state of LLM ethical decision-making
ResearchApril 1, 2023
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Bill Thompson, UC Berkeley: On how cultural evolution shapes knowledge acquisition
PodcastMarch 29, 2023
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“Over the next few months and years, we can expect much of the internet to get connected to large language models.” — Kanjun Qiu, CEO
NewsMarch 28, 2023
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Instead of relying exclusively on outside providers, the AI startup Generally Intelligent has begun purchasing its own graphics chips to power its research.
NewsMarch 27, 2023
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Ben Eysenbach, CMU: On designing simpler and more principled RL algorithms
PodcastMarch 22, 2023
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Jim Fan, NVIDIA: On foundation models for embodied agents, scaling data, and why prompt engineering will become irrelevant
PodcastMarch 8, 2023
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Sergey Levine, UC Berkeley: On the bottlenecks to generalization, why simulation is doomed to succeed, and picking good research problems
PodcastMarch 1, 2023
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The state of LLM ethical decision-making
ResearchFebruary 14, 2023
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Noam Brown, FAIR: On achieving human-level performance in poker and Diplomacy, and the power of spending compute at inference time
PodcastFebruary 9, 2023
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Sugandha Sharma, MIT: On biologically inspired neural architectures, how memories can be implemented, and control theory
PodcastJanuary 11, 2023
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Nicklas Hansen, UCSD: On long-horizon planning and why algorithms don't drive research progress
PodcastDecember 16, 2022
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Jack Parker-Holder, DeepMind: On open-endedness, evolving agents and environments, online adaptation, and offline learning
PodcastDecember 6, 2022
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“But it really begs the question: what is understanding?” — Kanjun Qiu, CEO
NewsDecember 5, 2022
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Celeste Kidd, UC Berkeley: On attention and curiosity, how we form beliefs, and where certainty comes from
PodcastNovember 22, 2022
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Archit Sharma, Stanford: On unsupervised and autonomous reinforcement learning
PodcastNovember 17, 2022
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Chelsea Finn, Stanford: On the biggest bottlenecks in robotics and reinforcement learning
PodcastNovember 3, 2022
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Introducing Generally Intelligent
CompanyOctober 20, 2022
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Our approach to safety
PerspectiveOctober 20, 2022
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Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds
ResearchOctober 20, 2022
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Among those contributing to the company's $20 million in initial funding (plus over $100 million in options) is Tom Brown, former engineering lead for OpenAI's GPT-3; former OpenAI robotics lead Jonas Schneider; Dropbox co-founders Drew Houston and Arash Ferdowsi; and the Astera Institute.
NewsOctober 20, 2022
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Hattie Zhou, Mila: On supermasks, iterative learning, and fortuitous forgetting
PodcastOctober 14, 2022
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Minqi Jiang, UCL: On environment and curriculum design for general RL agents
PodcastJuly 19, 2022
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Oleh Rybkin, UPenn: On exploration and planning with world models
PodcastJuly 11, 2022
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VICReg: Tutorial and lightweight PyTorch implementation
Open sourceApril 21, 2022
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A PyTorch implementation of SIMONe
Open sourceApril 14, 2022
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Andrew Lampinen, DeepMind: On symbolic behavior, mental time travel, and insights from psychology
PodcastFebruary 28, 2022
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Our hiring process
CompanyJanuary 20, 2022
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Yilun Du, MIT: On energy-based models, implicit functions, and modularity
PodcastDecember 21, 2021
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Jupyter Ascending: Sync notebooks to your editor
Open sourceOctober 14, 2021
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Martin Arjovsky, INRIA: On benchmarks for robustness and geometric information theory
PodcastOctober 14, 2021
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Yash Sharma, MPI-IS: On generalizability, causality, and disentanglement
PodcastSeptember 24, 2021
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Jacob Steinhardt, UC Berkeley: On machine learning safety, alignment and measurement
PodcastJune 17, 2021
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Jonathan Frankle, MIT: On the lottery ticket hypothesis and the science of deep learning
PodcastJune 1, 2021
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Vincent Sitzmann, MIT: On neural scene representations for computer vision and more general AI
PodcastMay 19, 2021
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Dylan Hadfield-Menell, UC Berkeley/MIT: On the value alignment problem in AI
PodcastMay 11, 2021
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Drew Linsley, Brown: On inductive biases for vision and generalization
PodcastApril 1, 2021
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Giancarlo Kerg, Mila: On approaching deep learning from mathematical foundations
PodcastMarch 26, 2021
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Yujia Huang, Caltech: On neuro-inspired generative models
PodcastMarch 18, 2021
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A PyTorch implementation of slot attention
Open sourceMarch 9, 2021
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Julian Chibane, MPI-INF: On 3D reconstruction using implicit functions
PodcastMarch 5, 2021
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Josh Albrecht: A new AI research lab
CompanyFebruary 24, 2021
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Katja Schwarz, MPI-IS: On GANs, implicit functions, and 3D scene understanding
PodcastFebruary 23, 2021
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Joel Lehman, OpenAI: On evolving intelligence, open-endedness, and reinforcement learning
PodcastFebruary 16, 2021
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Cinjon Resnick, NYU: On activity and scene understanding
PodcastJanuary 31, 2021
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Sarah Jane Hong, Latent Space: On neural rendering & research process
PodcastJanuary 6, 2021
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Kelvin Guu, Google AI: On language models & overlooked problems
PodcastDecember 16, 2020
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Generally Intelligent #0: A podcast for deep learning researchers
PodcastDecember 6, 2020
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Understanding self-supervised and contrastive learning with "Bootstrap Your Own Latent" (BYOL)
ResearchAugust 24, 2020
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Appendix for "Understanding self-supervised and contrastive learning with 'Bootstrap Your Own Latent' (BYOL)"
ResearchAugust 24, 2020
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