Shows
Pioneers of AIThe future of AI is human-centered, with Kanjun QiuAI isn’t here to take over. It’s here to empower. That’s the vision Kanjun Qiu, co-founder of Imbue, is working to make a reality. In this episode, Qiu challenges the dominant AI narrative and shares why the future shouldn't be about machines running the show, but about humans harnessing AI as a tool for creativity, decision-making, and personal agency. Qiu and host Rana el Kailouby explore how AI agents can help everyone build their own software, how we can take back control of our data, and why AI can be an extension of our human potential.L...2025-02-0537 min
The Wright ShowHuman Agency vs "Agentic” AI (Robert Wright & Kanjun Qiu)Intro ... Kanjun’s role as CEO of AI research lab Imbue ... Worrying about a “Wall-E world” ... Building human-centric AI agents ... How far away is truly “agentic” AI? ... The road to AI serfdom ... Does the AI revolution call for a psychological revolution? ... Heading to Overtime ...2025-01-2300 minBhTV: The Wright Show (audio)Human Agency vs "Agentic” AI (Robert Wright & Kanjun Qiu)Intro ... Kanjun’s role as CEO of AI research lab Imbue ... Worrying about a “Wall-E world” ... Building human-centric AI agents ... How far away is truly “agentic” AI? ... The road to AI serfdom ... Does the AI revolution call for a psychological revolution? ... Heading to Overtime ...2025-01-2300 min
NVIDIA AI PodcastImbue CEO Kanjun Qiu on Transforming AI Agents Into Personal Collaborators - Ep. 239In this episode of the NVIDIA AI Podcast, Kanjun Qiu, CEO of Imbue, explores the emerging era where individuals can create and utilize their own AI agents. Drawing a parallel to the personal computer revolution of the late 1970s and 80s, Qiu discusses how modern AI systems are evolving to work collaboratively with users, enhancing their capabilities rather than just automating tasks. 2024-12-1633 min
AI-Powered Bot : ChatgptImbue CEO Kanjun Qiu on Transforming AI Agents Into Personal Collaborators - Ep. 239In this episode of the NVIDIA AI Podcast, Kanjun Qiu, CEO of Imbue, explores the emerging era where individuals can create and utilize their own AI agents. Drawing a parallel to the personal computer revolution of the late 1970s and 80s, Qiu discusses how modern AI systems are evolving to work collaboratively with users, enhancing their capabilities rather than just automating tasks.2024-12-1633 min
Generally IntelligentEpisode 37: Rylan Schaeffer, Stanford: On investigating emergent abilities and challenging dominant research ideasRylan Schaeffer is a PhD student at Stanford studying the engineering, science, and mathematics of intelligence. He authored the paper “Are Emergent Abilities of Large Language Models a Mirage?”, as well as other interesting refutations in the field that we’ll talk about today. He previously interned at Meta on the LLAMA team, and at Google Deepmind.
Generally Intelligent is a podcast by Imbue where we interview researchers about their behind-the-scenes ideas, opinions, and intuitions that are hard to share in papers and talks.
About Imbue
Imbue is an independent research company develop...2024-09-191h 02
Minus OneKanjun Qiu, Imbue, & Agency in the Age of AIImbue Co-founder and SPC alum Kanjun Qiu shares her journey from Dropbox to becoming a founder, why she thinks play is a key part of human and AI agency, and how community has played a key role in her journey and perspective on AI.2024-08-2143 min
Gradient Dissent: Conversations on AIReinventing AI Agents with Imbue CEO Kanjun QiuIn this episode of Gradient Dissent, Kanjun Qiu, CEO and Co-founder of Imbue, joins host Lukas Biewald to discuss how AI agents are transforming code generation and software development. Discover the potential impact and challenges of creating autonomous AI systems that can write and verify code and and learn about the practical research involved.✅ *Subscribe to Weights & Biases* → https://bit.ly/45BCkYzConnect with Kanjun Qiu: https://www.linkedin.com/in/kanjun/ https://x.com/kanjunGeneral Intelligent Podcast: https://imbue.com/podc...2024-08-0848 minGenerally IntelligentEpisode 36: Ari Morcos, DatologyAI: On leveraging data to democratize model trainingAri Morcos is the CEO of DatologyAI, which makes training deep learning models more performant and efficient by intervening on training data. He was at FAIR and DeepMind before that, where he worked on a variety of topics, including how training data leads to useful representations, lottery ticket hypothesis, and self-supervised learning. His work has been honored with Outstanding Paper awards at both NeurIPS and ICLR.
Generally Intelligent is a podcast by Imbue where we interview researchers about their behind-the-scenes ideas, opinions, and intuitions that are hard to share in papers and talks.
About Imbue2024-07-111h 34Generally IntelligentEpisode 35: Percy Liang, Stanford: On the paradigm shift and societal effects of foundation modelsPercy Liang is an associate professor of computer science and statistics at Stanford. These days, he’s interested in understanding how foundation models work, how to make them more efficient, modular, and robust, and how they shift the way people interact with AI—although he’s been working on language models for long before foundation models appeared. Percy is also a big proponent of reproducible research, and toward that end he’s shipped most of his recent papers as executable papers using the CodaLab Worksheets platform his lab developed, and published a wide variety of benchmarks.
Generally Intellig...2024-05-091h 01
Thursday Nights in AIEpisode 16: The Future of AI and Robotics with Medra CEO Michelle LeeAt this Thursday Nights in AI, hosts Ali Rohde and Josh Albrecht discussed the future of robotics and computer vision, and the role of AI in the space. Special thanks to Respell for hosting us in their wonderful office!
Michelle is the CEO and founder of Medra. Medra is at the forefront of laboratory automation, leveraging state-of-the-art robotics and computer vision technologies to streamline wet lab tasks. The company is backed by top investors including Nat Friedman, Lux, Neo, and Outset Capital.
Before Medra, Michelle earned her PhD at the Stanford AI Lab, and interned at McKinsey, SpaceX, and...2024-04-2338 min
Thursday Nights in AIEpisode 15: Selling AI to the Fortune 500 w/ Snorkel AI CEO Alex RatnerAt this Thursday Nights in AI, hosts Ali Rohde and Kanjun Qiu discussed selling AI to Fortune 500 companies, data-centric versus model-centric AI, flashy demos versus actual production value, and more with Alex Ratner, co-founder and CEO of Snorkel AI.
Snorkel AI believes that AI teams can get better results faster by replacing highly manual data annotation with programmatic approaches that more efficiently capture and apply subject matter expertise. Its data development platform, Snorkel Flow, helps companies fine-tune and align generative models with these programmatic approaches.
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About Outset Capital: Outset Capital is led by Ali Rohde, Kanjun Qiu, and...2024-03-1350 minGenerally IntelligentEpisode 34: Seth Lazar, Australian National University: On legitimate power, moral nuance, and the political philosophy of AISeth Lazar is a professor of philosophy at the Australian National University, where he leads the Machine Intelligence and Normative Theory (MINT) Lab. His unique perspective bridges moral and political philosophy with AI, introducing much-needed rigor to the question of what will make for a good and just AI future.
Generally Intelligent is a podcast by Imbue where we interview researchers about their behind-the-scenes ideas, opinions, and intuitions that are hard to share in papers and talks.
About ImbueImbue is an independent research company developing AI agents that mirror the fundamentals of human-like i...2024-03-131h 55
Thursday Nights in AIEpisode 13: Open-source panel with Anton Troynikov, Brian Raymond, and Harrison ChaseOn this special edition of Thursday Nights in AI, we chatted with three open-source leaders building in AI: Harrison Chase of LangChain, Brian S. Raymond of Unstructured.io, and Anton Troynikov of Chroma.
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About Harrison: Harrison Chase is the co-founder and CEO of LangChain, a company formed around the open-source Python/Typescript packages that aim to make it easy to develop Language Model applications. Prior to starting LangChain, he led the ML team at Robust Intelligence (an MLOps company focused on testing and validation of machine learning models), led the entity linking team at Kensho (a fintech startup...2024-01-2848 min
No Priors: Artificial Intelligence | Technology | StartupsAI Agents That Reason and Code with Imbue Co-Founders Kanjun Qiu and Josh AlbrechtThe future of tech is 25-person companies powered by AI agents that help us accomplish our larger goals. Imbue is working on building AI agents that reason, code and generally make our lives easier. Sarah Guo and Elad Gil sit down with co-founders Kanjun Qiu (CEO) and Josh Albrecht (CTO) to discuss how they define reasoning, the spectrum of specialized and generalized agents, and the path to improved agent performance. Plus, what’s behind their $200M Series B fundraise. Kanjun Qiu is the CEO and co-founder of Imbue. Kanjun is also a partner at ang...2023-11-1632 min
Thursday Nights in AIEpisode 12: Chroma co-founders Anton Troynikov & Jeff HuberSeason One of Thursday Nights in AI is in the books. Catch our conversation with Jeff Huber and Anton Troynikov, Cofounders of Chroma, on open-source, embedding databases, building developer love, and where their product goes from here. Season two here we come!
This fireside chat is part of our 'Thursday Nights in AI" series, co-hosted by Outset Capital and Imbue and sponsored by WndrCo.
Join our upcoming events! Full list here: https://www.outsetcapital.com/thursday-nights-in-ai
About Outset Capital: Outset Capital is led by Ali Rohde, Kanjun Qiu, and Josh Albrecht — AI practitioners investing in AI, deeptech, and the fu...2023-11-1544 min
Thursday Nights in AIEpisode 11: Glean CEO, Arvind JainOutset Capital's Ali Rohde and Josh Albrecht interview Glean CEO Arvind Jain. Special thanks to Volley for welcoming us to their beautiful HQ!
This fireside chat is part of our 'Thursday Nights in AI" series, co-hosted by Outset Capital and Imbue and sponsored by WndrCo.
Join our upcoming events! Full list here: https://www.outsetcapital.com/thursda...
About Outset Capital: Outset Capital is led by Ali Rohde, Kanjun Qiu, and Josh Albrecht — AI practitioners investing in AI, deeptech, and the future of work. We back companies at the outset and love to be the first check in.
About Imbue: Im...2023-11-0343 min
Thursday Nights in AIEpisode 10: Dr. Jim Fan, NVIDIA AIAbout Jim: Jim Fan is a senior research scientist at NVIDIA AI. His mission is to build generally capable AI agents with applications to game AI, robotics, and software automation. His research spans foundation models, multimodal AI, reinforcement learning, and open-ended learning. Jim obtained his Ph.D. degree in Computer Science from Stanford University, advised by Prof. Fei-Fei Li. His work "MineDojo" won the Outstanding Paper Award at NeurIPS 2022. Previously, Jim did research internships at OpenAI, Google AI, and MILA-Quebec AI Institute. He was the Valedictorian of the class of 2016 and a recipient of the Illig Medal at Columbia Uni...2023-10-2252 min
Latent Space: The AI Engineer PodcastWhy AI Agents Don't Work (yet) - with Kanjun Qiu of ImbueThanks to the over 11,000 people who joined us for the first AI Engineer Summit! A full recap is coming, but you can 1) catch up on the fun and videos on Twitter and YouTube, 2) help us reach 1000 people for the first comprehensive State of AI Engineering survey and 3) submit projects for the new AI Engineer Foundation.See our Community page for upcoming meetups in SF, Paris, NYC, and Singapore. This episode had good interest on Twitter.Last month, Imbue was crowned as AI’s newest unicorn foundation model lab, raising a $200m Series B at...2023-10-141h 05
The MAD Podcast with Matt TurckImbue: AI Agents That Can Reason with CEO Kanjun QiuToday we're joined by Kanjun Qiu, CEO of Imbue, an independent research company developing AI agents with general intelligence, fresh off the announcement of their $200M Series B round of financing. We talk about Kanjun's journey, Imbue's vision and the future of AI agents.2023-10-0444 min
Thursday Nights in AIEpisode 9: Kanjun Qiu & Josh Albrecht, ImbueOutset Capital's Ali Rohde interview @imbue_ai co-founders, Kanjun Qiu & Josh Albrecht.
This fireside chat is part of our 'Thursday Nights in AI" series, co-hosted by Outset Capital, Imbue, and WndrCo.
Join our upcoming events! Full list here: https://www.outsetcapital.com/thursda...
About Outset: Outset Capital is led by Ali Rohde, Kanjun Qiu, and Josh Albrecht — AI practitioners investing in AI, deeptech, and the future of work. We back companies at the outset and love to be the first check in.
About Imbue: Imbue is an AI research company aiming to rekindle the dream of the personal computer—by c...2023-09-2948 min
Thursday Nights in AIEpisode 8: Anyscale CEO, Robert NishiharaOutset Capital's Ali Rohde and Kanjun Qiu interview @anyscale CEO, Robert Nishihara.
This fireside chat is part of our 'Thursday Nights in AI" series, co-hosted by Outset Capital and Imbue.
Join our upcoming events! Full list here: https://www.outsetcapital.com/thursda...
About Outset: Outset Capital is led by Ali Rohde, Kanjun Qiu, and Josh Albrecht — AI practitioners investing in AI, deeptech, and the future of work. We back companies at the outset and love to be the first check in.
About Imbue: Imbue is an AI research company aiming to rekindle the dream of the personal computer—by crea...2023-09-2344 min
Thursday Nights in AIEpisode 7: LlamaIndex CEO, Jerry Liu
Outset Capital's Ali Rohde and Josh Albrecht interview LlamaIndex CEO, Jerry Liu.
This fireside chat is part of our 'Thursday Nights in AI" series, co-hosted by Outset Capital and Imbue.
Join our upcoming events! Full list here: https://www.outsetcapital.com/thursda...
About Outset: Outset Capital is led by Ali Rohde, Kanjun Qiu, and Josh Albrecht — AI practitioners investing in AI, deeptech, and the future of work. We back companies at the outset and love to be the first check in.
About Imbue: Imbue is an AI research company aiming to rekindle the dream of the personal computer—by crea...2023-09-1628 min
Thursday Nights in AIEpisode 6: Replit CEO, Amjad MasadOutset Capital's Ali Rohde and Josh Albrecht interview Replit CEO, Amjad Masad. Special thanks to Notion for hosting us at their beautiful office!
This fireside chat is part of our 'Thursday Nights in AI" series, co-hosted by Outset Capital and Generally Intelligent.
Join our upcoming events! Full list here: https://www.outsetcapital.com/thursda...
About Outset: Outset Capital is led by Ali Rohde, Kanjun Qiu, and Josh Albrecht — AI practitioners investing in AI, deeptech, and the future of work. We back companies at the outset, and love to be the first check in.
About Generally Intelligent: Generally Intelligent is an...2023-08-2837 min
Thursday Nights in AIEpisode 5: Pilot CEO, Waseem Daher
Outset Capital's Ali Rohde and Josh Albrecht interview Pilot CEO, Waseem Daher. Special thanks to Pilot for hosting us at their office!
This fireside chat is part of our 'Thursday Nights in AI" series, co-hosted by Outset Capital and Generally Intelligent.
Join our upcoming events! Full list here: https://www.outsetcapital.com/thursda...
About Outset: Outset Capital is led by Ali Rohde, Kanjun Qiu, and Josh Albrecht — AI practitioners investing in AI, deeptech, and the future of work. We back companies at the outset, and love to be the first check in.
About Generally Intelligent: Generally Intelligent is an AI...2023-08-2244 min
Thursday Nights in AIEpisode 4: Dropbox CEO, Drew HoustonOutset Capital's Ali Rohde and Kanjun Qiu interview Dropbox CEO Drew Houston.
This fireside chat is part of our 'Thursday Nights in AI" series, co-hosted by Outset Capital and Generally Intelligent.
Join our upcoming events! Full list here: https://www.outsetcapital.com/thursday-nights-in-ai
About Outset: Outset Capital is led by Ali Rohde, Kanjun Qiu, and Josh Albrecht — AI practitioners investing in AI, deeptech, and the future of work. We back companies at the outset, and love to be the first check in.
About Generally Intelligent: Generally Intelligent is an AI research company building human-like general intelligence by ev...2023-08-2140 min
Thursday Nights in AIEpisode 3: Notion AI Lead: Linus LeeOutset Capital General Partners Ali Rohde and Kanjun Qiu interviewed Notion AI lead Linus Lee.
In this podcast they talked about:
Notion AI — lessons learned from the roll out of the product so far
Prompt engineering, including how Notion AI handles prompting for the different languages the product supports
The optimal UI for AI
Linus' journey to working at Notion
The need to be thoughtful building products on top of LLMs (see Linus’ tweet thread here)
2023-08-1534 minGenerally IntelligentEpisode 33: Tri Dao, Stanford: On FlashAttention and sparsity, quantization, and efficient inferenceTri Dao is a PhD student at Stanford, co-advised by Stefano Ermon and Chris Re. He’ll be joining Princeton as an assistant professor next year. He works at the intersection of machine learning and systems, currently focused on efficient training and long-range context.
About Generally Intelligent
We started Generally Intelligent because we believe that software with human-level intelligence will have a transformative impact on the world. We’re dedicated to ensuring that that impact is a positive one.
We have enough funding to freely pursue our research goals over the ne...2023-08-091h 20
Open Source Startup PodcastE99: Developing AI Agents with Generally IntelligentKanjun Qiu is Cofounder & CEO of Generally Intelligent, the platform to develop general-purpose AI agents that can be safely deployed in the real world.
Generally Intelligent has raised $20M from investors including the Astera Institute & YC.
In this episode, we dig into the future for AI agents and where they fall short today, why they open sourced their research environment, the importance of market timing when launching a company, Kanjun's views on whether the Agentive AI space is over-hyped & much more! 2023-08-0739 minGenerally IntelligentEpisode 32: Jamie Simon, UC Berkeley: On theoretical principles for how neural networks learn and generalizeJamie Simon is a 4th year Ph.D. student at UC Berkeley advised by Mike DeWeese, and also a Research Fellow with us at Generally Intelligent. He uses tools from theoretical physics to build fundamental understanding of deep neural networks so they can be designed from first-principles. In this episode, we discuss reverse engineering kernels, the conservation of learnability during training, infinite-width neural networks, and much more.
About Generally Intelligent
We started Generally Intelligent because we believe that software with human-level intelligence will have a transformative impact on the world. We’re dedicated to ensuring tha...2023-06-221h 01
metascientia #メタサイエンティア#026 Metascience Conference 2023 について/ゲスト：丸山隆一さん (3/4)「科学を再考する」をコンセプトに、世界のサイエンスニュースやディープテックスタートアップ、サイエンスをメタな視点で紹介&考察していく番組、メタサイエンティアです。今回はゲストに丸山隆一さんを及びして、Metascience Conference 2023 について話しました。全4回の収録の3回目の放送になります。
収録日: 2023/06/01
番組に協力してくださる方やインタビューに応じてくださる方々を募集しています。
TwitterのDMからぜひご連絡ください。https://twitter.com/meta_scientia
メタサイエンティアの活動を支援してくださる方も募集しておりますので、
下記のAmazonのほしい物リストの中から支援していただけると大変助かります。
参考情報:
1. 丸山隆一さん (https://twitter.com/rmaruy?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor)
2. metascience conference 2023 (https://metascience.info/)
3. CSRD,「拡張する研究開発エコシステム 研究資金・人材・インフラ・情報循環の変革に乗り出すアントレプレナーたち」, 2023
4. Dashun Wang and Albert-László Barabási, "The Science of Science", 2021
5. 丸山隆一「2022年を振り返る」, 重ね描き日記（rmaruy_blogあらため）, 2022
6. L-RAD, リバネス
7. 丸山隆一「フィランソロピーによる科学助成の新潮流」, 研究・イノベーション学会年次学術大会講演要旨集, 2022
8. Open Research Funders Group
9. Michael Nielsen and Kanjun Qiu "A Vision of MetascienceAn Engine of Improvement for the Social Processes of Science"
10. 濱田太陽「大富豪はなぜ研究財団を設立するか?」, 2021
11. Effective Alturism
12. 渡邉文隆さん（https://twitter.com/fwatanabe）
13. Bishop and Green "Philanthrocapitalism: How the Rich Can Save the World", 2008
14. William MacAskill
15. Peter Singer
16. 工藤七子「インパクト投資の国内外の最新動向」
17. Raymond Cheng "Accelerating Academic Research with Impact Certificates", Metascience Conference 2023
18. Paul Christiano
19. 丸山隆一「読書メモ：不定性からみた科学（吉澤剛）…科学の「暗さ」を見つめ、科学を語り合う」, 重ね描き日記（rmaruy_blogあらため）, 2022
■ Twitter
https://twitter.com/meta_scientia
■ Youtube
https://www.youtube.com/channel/UCUD7qGcdI5--6tAdcct9Yiw
■ Spotify
https://open.spotify.com/show/10KlbWeY8UIjVz7xW5byQj
■ほしいも2023-06-1432 minGenerally IntelligentEpisode 31: Bill Thompson, UC Berkeley, on how cultural evolution shapes knowledge acquisitionBill Thompson is a cognitive scientist and an assistant professor at UC Berkeley. He runs an experimental cognition laboratory where he and his students conduct research on human language and cognition using large-scale behavioral experiments, computational modeling, and machine learning. In this episode, we explore the impact of cultural evolution on human knowledge acquisition, how pure biological evolution can lead to slow adaptation and overfitting, and much more.
About Generally Intelligent
We started Generally Intelligent because we believe that software with human-level intelligence will have a transformative impact on the world. We’re...2023-03-291h 15Generally IntelligentEpisode 30: Ben Eysenbach, CMU, on designing simpler and more principled RL algorithmsBen Eysenbach is a PhD student from CMU and a student researcher at Google Brain. He is co-advised by Sergey Levine and Ruslan Salakhutdinov and his research focuses on developing RL algorithms that get state-of-the-art performance while being more simple, scalable, and robust. Recent problems he’s tackled include long horizon reasoning, exploration, and representation learning. In this episode, we discuss designing simpler and more principled RL algorithms, and much more.
About Generally Intelligent
We started Generally Intelligent because we believe that software with human-level intelligence will have a transformative impact on the world. We’re de...2023-03-231h 45Generally IntelligentEpisode 29: Jim Fan, NVIDIA, on foundation models for embodied agents, scaling data, and why prompt engineering will become irrelevantJim Fan is a research scientist at NVIDIA and got his PhD at Stanford under Fei-Fei Li. Jim is interested in building generally capable autonomous agents, and he recently published MineDojo, a massively multiscale benchmarking suite built on Minecraft, which was an Outstanding Paper at NeurIPS. In this episode, we discuss the foundation models for embodied agents, scaling data, and why prompt engineering will become irrelevant.
About Generally Intelligent
We started Generally Intelligent because we believe that software with human-level intelligence will have a transformative impact on the world. We’re dedicated to e...2023-03-091h 26Generally IntelligentEpisode 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 problemsSergey Levine, an assistant professor of EECS at UC Berkeley, is one of the pioneers of modern deep reinforcement learning. His research focuses on developing general-purpose algorithms for autonomous agents to learn how to solve any task. In this episode, we talk about the bottlenecks to generalization in reinforcement learning, why simulation is doomed to succeed, and how to pick good research problems.2023-03-021h 34Generally IntelligentEpisode 27: Noam Brown, FAIR, on achieving human-level performance in poker and Diplomacy, and the power of spending compute at inference timeNoam Brown is a research scientist at FAIR. During his Ph.D. at CMU, he made the first AI to defeat top humans in No Limit Texas Hold 'Em poker. More recently, he was part of the team that built CICERO which achieved human-level performance in Diplomacy. In this episode, we extensively discuss ideas underlying both projects, the power of spending compute at inference time, and much more.2023-02-091h 44Generally IntelligentEpisode 26: Sugandha Sharma, MIT, on biologically inspired neural architectures, how memories can be implemented, and control theorySugandha Sharma is a Ph.D. candidate at MIT advised by Prof. Ila Fiete and Prof. Josh Tenenbaum. She explores the computational and theoretical principles underlying higher cognition in the brain by constructing neuro-inspired models and mathematical tools to discover how the brain navigates the world, or how to construct memory mechanisms that don’t exhibit catastrophic forgetting. In this episode, we chat about biologically inspired neural architectures, how memory could be implemented, why control theory is underrated and much more.2023-01-171h 44
Ben Yeoh ChatsKanjun Qiu: AI, metascience, institutional knowledge, trauma models, structure of knowledge, creativity and danceKanjun is co-founder and CEO of Generally Intelligent, an AI research company. She works on metascience ideas often with Michael Nielsen, a previous podcast guest. She’s a VC investor and co-hosts her own podcast for Generally Intelligent. She is part of building the Neighborhood, which is intergenerational campus in a square mile of central San Francisco. Generally Intelligent (as of podcast date ) are looking for great talent looking to work on AI.
We get a little nerdy on the podcast but we cover AI thinking, fears on rogue AI, and the breakthroughs of Chat AI. We di...2023-01-171h 39Generally IntelligentEpisode 25: Nicklas Hansen, UCSD, on long-horizon planning and why algorithms don't drive research progressNicklas Hansen is a Ph.D. student at UC San Diego advised by Prof Xiaolong Wang and Prof Hao Su. He is also a student researcher at Meta AI. Nicklas' research interests involve developing machine learning systems, specifically neural agents, that have the ability to learn, generalize, and adapt over their lifetime. In this episode, we talk about long-horizon planning, adapting reinforcement learning policies during deployment, why algorithms don't drive research progress, and much more!2022-12-161h 49Generally IntelligentEpisode 24: Jack Parker-Holder, DeepMind, on open-endedness, evolving agents and environments, online adaptation, and offline learningJack Parker-Holder recently joined DeepMind after his Ph.D. with Stephen Roberts at Oxford. Jack is interested in using reinforcement learning to train generally capable agents, especially via an open-ended learning process where environments can adapt to constantly challenge the agent's capabilities. Before doing his Ph.D., Jack worked for 7 years in finance at JP Morgan. In this episode, we chat about open-endedness, evolving agents and environments, online adaptation, offline learning with world models, and much more.2022-12-061h 56
The Jim Rutt ShowCurrents 075: Michael Nielsen on MetascienceJim talks with Michael Nielsen about the ideas in his and Kanjun Qiu's recent essay, "A Vision of Metascience: An Engine of Improvement for the Social Processes of Science"...
Jim talks with Michael Nielsen about the ideas in his and Kanjun Qiu's recent essay, "A Vision of Metascience: An Engine of Improvement for the Social Processes of Science." They discuss the meaning of metascience, a vivid example in Genovese maritime insurance, attracting intellectual dark matter, creation & limitations of the h-index, frozen accidents in our scientific operating system, what allowed the original DARPA to be so productive, funding-by-variance, failure audits, changing th...2022-12-061h 01Generally IntelligentEpisode 23: Celeste Kidd, UC Berkeley, on attention and curiosity, how we form beliefs, and where certainty comes fromCeleste Kidd is a professor of psychology at UC Berkeley. Her lab studies the processes involved in knowledge acquisition; essentially, how we form our beliefs over time and what allows us to select a subset of all the information we encounter in the world to form those beliefs. In this episode, we chat about attention and curiosity, beliefs and expectations, where certainty comes from, and much more.2022-11-221h 52Generally IntelligentEpisode 22: Archit Sharma, Stanford, on unsupervised and autonomous reinforcement learningArchit Sharma is a Ph.D. student at Stanford advised by Chelsea Finn. His recent work is focused on autonomous deep reinforcement learning—that is, getting real world robots to learn to deal with unseen situations without human interventions. Prior to this, he was an AI resident at Google Brain and he interned with Yoshua Bengio at Mila. In this episode, we chat about unsupervised, non-episodic, autonomous reinforcement learning and much more.2022-11-171h 38
The Gradient: Perspectives on AIKanjun Qiu and Josh Albrecht: Generally IntelligentIn episode 49 of The Gradient Podcast, Daniel Bashir speaks to Kanjun Qiu and Josh Albrecht. Kanjun and Josh are CEO and CTO of Generally Intelligent, an AI startup aiming to develop general-purpose agents with human-like intelligence that can be safely deployed in the real world. Kanjun and Josh have played these roles together in the past as CEO and CTO of AI recruiting startup Sourceress. Kanjun is also involved with building the SF Neighborhood, and together with Josh invests in early-stage founders at Outset Capital.Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RS...2022-11-1747 min
Ben Yeoh ChatsMichael Nielsen: metascience, how to improve science, open science, and decentralisationMichael Nielsen is a scientist at the Astera Institute. He helped pioneer quantum computing and the modern open science movement. He is a leading thinker on the topic of meta science and how to improve science, in particular, the social processes of science. His latest co-authored work is ‘A Vision of metascience: An engine of improvement for the social processes of Science’ co-authored with Kanjun Qiu . His website notebook is here, with further links to his books including on quantum, memory systems, deep learning, open science and the future of matter.
I ask: What is the most impor...2022-11-151h 36Generally IntelligentEpisode 21: Chelsea Finn, Stanford, on the biggest bottlenecks in robotics and reinforcement learningChelsea Finn is an Assistant Professor at Stanford and part of the Google Brain team. She's interested in the capability of robots and other agents to develop broadly intelligent behavior through learning and interaction at scale. In this episode, we chat about some of the biggest bottlenecks in RL and robotics—including distribution shifts, Sim2Real, and sample efficiency—as well as what makes a great researcher, why she aspires to build a robot that can make cereal, and much more.2022-11-0340 min
Generally IntelligentEpisode 20: Hattie Zhou, Mila, on supermasks, iterative learning, and fortuitous forgettingHattie Zhou is a Ph.D. student at Mila working with Hugo Larochelle and Aaron Courville. Her research focuses on understanding how and why neural networks work, starting with deconstructing why lottery tickets work and most recently exploring how forgetting may be fundamental to learning. Prior to Mila, she was a data scientist at Uber and did research with Uber AI Labs. In this episode, we chat about supermasks and sparsity, coherent gradients, iterative learning, fortuitous forgetting, and much more.2022-10-141h 47
The Rhys ShowUnderstanding Machine & Human Minds with Kanjun QiuIn this episode Kanjun Qiu, the CEO and co-founder of Generally Intelligent joins us to chat about replicators, Genes, Memes and “Temes”, talk about what her company does and help us understand the fundamentals of learning across humans and machines.
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Who is Kanjun Qiu?
Kanjun Qiu is the CEO and co-founder of Generally Intelligent, an AI research company working directly on human-like general intelligence.
Previously she co-founded and was CEO of Sourceress, an AI recruiting company that went through YC and raised $13M. Prior to S...2022-08-161h 33
Generally IntelligentEpisode 19: Minqi Jiang, UCL, on environment and curriculum design for general RL agentsMinqi Jiang is a Ph.D. student at UCL and FAIR, advised by Tim Rocktäschel and Edward Grefenstette. Minqi is interested in how simulators can enable AI agents to learn useful behaviors that generalize to new settings. He is especially focused on problems at the intersection of generalization, human-AI coordination, and open-ended systems. In this episode, we chat about environment and curriculum design for reinforcement learning, model-based RL, emergent communication, open-endedness, and artificial life.2022-07-191h 53
Generally IntelligentEpisode 18: Oleh Rybkin, UPenn, on exploration and planning with world modelsOleh Rybkin is a Ph.D. student at the University of Pennsylvania and a student researcher at Google. He is advised by Kostas Daniilidis and Sergey Levine. Oleh's research focus is on reinforcement learning, particularly unsupervised and model-based RL in the visual domain. In this episode, we discuss agents that explore and plan (and do yoga), how to learn world models from video, what's missing from current RL research, and much more!2022-07-112h 00The Rhys ShowUnderstanding Machine & Human Minds to Build a Creative Equitable Future with Kanjun QiuIn this episode Kanjun Qiu, the CEO and co-founder of Generally Intelligent joins us to chat about replicators, Genes, Memes and “Temes”, talk about what her company does and help us understand the fundamentals of learning across humans and machines. Generalized Darwinism is the principle that when any kind of information is copied with variation and selection an evolutionary process inevitably begins. Genes, memes, and now what? Evolution's third replicator: technological “Temes”. Digital information is now being copied, varied and selected fast. This new kind of meme, which spreads itself via technology and finds ways to keep itself alive, is emerging...2022-05-091h 33
Generally IntelligentEpisode 17: Andrew Lampinen, DeepMind, on symbolic behavior, mental time travel, and insights from psychologyAndrew Lampinen is a Research Scientist at DeepMind. He previously completed his Ph.D. in cognitive psychology at Stanford. In this episode, we discuss generalization and transfer learning, how to think about language and symbols, what AI can learn from psychology (and vice versa), mental time travel, and the need for more human-like tasks. [Podcast errata: Susan Goldin-Meadow accidentally referred to as Susan Gelman @00:30:34] 2022-02-281h 59
Generally IntelligentEpisode 16: Yilun Du, MIT, on energy-based models, implicit functions, and modularityYilun Du is a graduate student at MIT advised by Professors Leslie Kaelbling, Tomas Lozano-Perez, and Josh Tenenbaum. He's interested in building robots that can understand the world like humans and construct world representations that enable task planning over long horizons.2021-12-221h 24
Generally IntelligentEpisode 15: Martín Arjovsky, INRIA, on benchmarks for robustness and geometric information theoryMartín Arjovsky did his Ph.D. at NYU with Leon Bottou. Some of his well-known works include the Wasserstein GAN and a paradigm called Invariant Risk Minimization. In this episode, we discuss out-of-distribution generalization, geometric information theory, and the importance of good benchmarks.2021-10-151h 26
Generally IntelligentEpisode 14: Yash Sharma, MPI-IS, on generalizability, causality, and disentanglementYash Sharma is a Ph.D. student at the International Max Planck Research School for Intelligent Systems. He previously studied electrical engineering at Cooper Union and has spent time at Borealis AI and IBM Research. Yash’s early work was on adversarial examples and his current research interests span a variety of topics in representation disentanglement. In this episode, we discuss robustness to adversarial examples, causality vs. correlation in data, and how to make deep learning models generalize better.2021-09-241h 26
Generally IntelligentEpisode 13: Jonathan Frankle, MIT, on the lottery ticket hypothesis and the science of deep learningJonathan Frankle (Google Scholar) (Website) is finishing his PhD at MIT, advised by Michael Carbin. His main research interest is using experimental methods to understand the behavior of neural networks. His current work focuses on finding sparse, trainable neural networks.
**Highlights from our conversation:**
🕸 "Why is sparsity everywhere? This isn't an accident."
🤖 "If I gave you 500 GPUs, could you actually keep those GPUs busy?"
📊 "In general, I think we have a crisis of science in ML."2021-09-101h 20Generally IntelligentEpisode 12: Jacob Steinhardt, UC Berkeley, on machine learning safety, alignment and measurementJacob Steinhardt (Google Scholar) (Website) is an assistant professor at UC Berkeley. His main research interest is in designing machine learning systems that are reliable and aligned with human values. Some of his specific research directions include robustness, rewards specification and reward hacking, as well as scalable alignment.
Highlights:
📜“Test accuracy is a very limited metric.”
👨👩👧👦“You might not be able to get lots of feedback on human values.”
📊“I’m interested in measuring the progress in AI capabilities.”2021-06-1859 minGenerally IntelligentEpisode 11: Vincent Sitzmann, MIT, on neural scene representations for computer vision and more general AIVincent Sitzmann (Google Scholar) (Website) is a postdoc at MIT. His work is on neural scene representations in computer vision. Ultimately, he wants to make representations that AI agents can use to solve the same visual tasks humans solve regularly, but that are currently impossible for AI.
**Highlights from our conversation:**
👁 “Vision is about the question of building representations”
🧠 “We (humans) likely have a 3D inductive bias”
🤖 “All computer vision should be 3D computer vision. Our world is a 3d world.”2021-05-201h 10Generally IntelligentEpisode 10: Dylan Hadfield-Menell, UC Berkeley/MIT, on the value alignment problem in AIDylan Hadfield-Menell (Google Scholar) (Website) recently finished his PhD at UC Berkeley and is starting as an assistant professor at MIT. He works on the problem of designing AI algorithms that pursue the intended goal of their users, designers, and society in general. This is known as the value alignment problem.
Highlights from our conversation:
👨👩👧👦 How to align AI to human values
📉 Consequences of misaligned AI -> bias & misdirected optimization
📱 Better AI recommender systems2021-05-121h 31Generally IntelligentEpisode 09: Drew Linsley, Brown, on inductive biases for vision and generalizationDrew Linsley (Google Scholar) is a Paul J. Salem senior research associate at Brown, advised by Thomas Serre. He is working on building computational models of the visual system that serve the dual purpose of (1) explaining biological function and (2) extending artificial vision.
Highlights from our conversation:
🧠 Building neural-inspired inductive biases into computer vision
🖼 A learning algorithm to improve recurrent vision models (C-RBP)
🤖 Creating new benchmarks to move towards generalization2021-04-021h 11Generally IntelligentEpisode 08: Giancarlo Kerg, Mila, on approaching deep learning from mathematical foundationsGiancarlo Kerg (Google Scholar) is a PhD student at Mila, supervised by Yoshua Bengio and Guillaume Lajoie. He is working on out-of-distribution generalization and modularity in memory-augmented neural networks.
Highlights from our conversation:
🧮 Pure math foundations as an approach to progress and structural understanding in deep learning research
🧠 How a formal proof on the way self-attention mitigates gradient vanishing when capturing long-term dependencies in RNNs led to a relevancy screening mechanism resembling human memory consolidation
🎯 Out-of-distribution generalization through modularity and inductive biases2021-03-271h 09Generally IntelligentEpisode 07: Yujia Huang, Caltech, on neuro-inspired generative modelsYujia Huang (Website) is a PhD student at Caltech, working at the intersection of deep learning and neuroscience. She worked on optics and biophotonics before venturing into machine learning. Now, she hopes to design “less artificial” artificial intelligence.
Highlights from our conversation:
🏗 How recurrent generative feedback, a neuro-inspired design, improves adversarial robustness and and can be more efficient (less labels)
🧠 Adapting theories from neuroscience and classical research for machine learning
📊 What a new Turing test for “less artificial” or generalized AI could look like
💡 Tips for new machine learning researchers!2021-03-181h 05Generally IntelligentEpisode 06: Julian Chibane, MPI-INF, on 3D reconstruction using implicit functionsJulian Chibane (Google Scholar) is a PhD student at the Real Virtual Humans group at the Max Planck Institute for Informatics in Germany. His recent work centers around intrinsic functions for 3D reconstruction.
Highlights from our conversation:
🖼 How, surprisingly, the IF-Net architecture learned reasonable representations of humans & objects without priors
🔢 A simple observation that led to Neural Unsigned Distance Fields, which handle 3D scenes without a clear inside vs. outside (most scenes!)
📚 Navigating open questions in 3D representation, and the importance of focusing on what's working2021-03-0549 minGenerally IntelligentEpisode 05: Katja Schwarz, MPI-IS, on GANs, implicit functions, and 3D scene understandingKatja Schwartz came to machine learning from physics, and is now working on 3D geometric scene understanding at the Max Planck Institute for Intelligent Systems. Her most recent work, “Generative Radiance Fields for 3D-Aware Image Synthesis,” revealed that radiance fields are a powerful representation for generative image synthesis, leading to 3D consistent models that render with high fidelity.
We discuss the ideas in Katja’s work and more:
🥦 the role 3D generation plays in conceptual understanding
📝 tons of practical tips on GAN training
〰 continuous functions as representations for 3D objects2021-02-2450 minGenerally IntelligentEpisode 04: Joel Lehman, OpenAI, on evolution, open-endedness, and reinforcement learningJoel Lehman was previously a founding member at Uber AI Labs and assistant professor at the IT University of Copenhagen. He's now a research scientist at OpenAI, where he focuses on open-endedness, reinforcement learning, and AI safety.
Joel’s PhD dissertation introduced the novelty search algorithm. That work inspired him to write the popular science book, “Why Greatness Cannot Be Planned”, with his PhD advisor Ken Stanley, which discusses what evolutionary algorithms imply for how individuals and society should think about objectives.
We discuss this and much more:
- How discovering novelty search totall...2021-02-171h 18Generally IntelligentEpisode 03: Cinjon Resnick, NYU, on activity and scene understandingCinjon Resnick was formerly from Google Brain and now is doing his PhD at NYU. We talk about why he believes scene understanding is critical to out of distribution generalization, and how his theses have evolved since he started his PhD.
Some topics we over:
How Cinjon started his research by trying to grow a baby through language and games, before running into a wall with this approach
How spending time at circuses 🎪 and with gymnasts 🤸🏽♂️ re-invigorated his research, and convinced him to focus on video, motion, and activity recognition
Why MetaSIM and MetaSIM II are underrated pape...2021-02-0159 minGenerally IntelligentEpisode 02: Sarah Jane Hong, Latent Space, on neural rendering & research processSarah Jane Hong is the co-founder of Latent Space, a startup building the first fully AI-rendered 3D engine in order to democratize creativity.
We touch on what it was like taking classes under Geoff Hinton in 2013, the trouble with using natural language prompts to render a scene, why a model’s ability to scale is more important than getting state-of-the-art results, and more.2021-01-0735 minGenerally IntelligentEpisode 01: Kelvin Guu, Google AI, on language models & overlooked research problemsWe interview Kelvin Guu, a researcher at Google AI and the creator of REALM.
The conversation is a wide-ranging tour of language models, how computers interact with world knowledge, and much more.2020-12-1547 min
Hiring On All CylindersBuilding a Diverse Team with the Help of Recruiting AutomationWe teleport back to the 2018 Recruiting Automation Summit in this week’s episode. Kanjun Qiu, CEO and Co-Founder of Sourceress, joined the Hiring On All Cylinders host to cover hiring and sourcing for diversity both as a co-founder and in her time at DropBox when they scaled from 200-1200 people.2019-03-0600 min