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PODCAST

The Gradient: Perspectives on AI

Deeply researched, technical interviews with experts thinking about AI and technology. thegradientpub.substack.com

technology

All Episodes

82:51

Max Braun: Teaching Robots to Help People in their...

The Gradient: Perspectives on AI ·

2022/05/26

In episode 27 of The Gradient Podcast, Andrey Kurenkov speaks to Max Braun, who leads the AI and robotics software engineering team at Everyday Robots, a moonshot to create robots that can learn to help people in their everyday lives. Previously, he worked on building frontier technology products as an entrepreneur and later at Google and X. Max enjoys exploring the intersection of art, technology, and philosophy as a writer and designer. Subscribe to The Gradient Podcast: Apple Podcasts | Spotify

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76:24

Yejin Choi: Teaching Machines Common Sense and Morality

The Gradient: Perspectives on AI ·

2022/05/19

In episode 26 of The Gradient Podcast, Daniel Bashir speaks to Yejin Choi, professor of Computer Science at the University of Washington, and senior research manager at the Allen Institute for Artificial Intelligence.Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterSections:(00:00) Intro(01:42) Getting Started in the Winter(09:17) Has NLP lost its way?(12:57) The Mosaic Project, Commonsense Intelligence(18:20) A Priori Intuitions and

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52:09

David Chalmers on AI and Consciousness

The Gradient: Perspectives on AI ·

2022/05/12

In episode 25 of The Gradient Podcast, Daniel Bashir speaks to David Chalmers, professor of philosophy and Philosophy and Neural Science at New York University, and co-director of NYU’s center for Mind, Brain, and Consciousness. Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterSections:(00:00) Intro(00:42) “Today’s neural networks may be slightly conscious”(03:55) Openness to Machine Consciousness(09:37) Integrated Information

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65:50

Greg Yang on Communicating Research, Tensor Programs,...

The Gradient: Perspectives on AI ·

2022/04/28

In episode 24 of The Gradient Podcast, Daniel Bashir talks to Greg Yang, senior researcher at Microsoft Research. Greg Yang’s Tensor Programs framework recently received attention for its role in the µTransfer paradigm for tuning the hyperparameters of large neural networks. Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterSections:(00:00) Intro(01:50) Start in AI / Research(05:55) Fear of Math in ML(08:00) Presentation of

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62:37

Nick Walton on AI Dungeon and the Future of AI in Games

The Gradient: Perspectives on AI ·

2022/03/24

In the 23rd interview of The Gradient Podcast, we talk to Nick Walton, the CEO and Co-Founder of Latitude, the goal of which is to make AI a tool of freedom and creativity for everyone, and which is currently developing AI Dungeon and Voyage. Subscribe to The Gradient Podcast: * Apple Podcasts* Spotify * Pocket Casts * RSSOutline:(00:00) Intro(01:38) How did you go into AI / research(3:50) Origin of AI Dungeon(8:15) What is a Dungeon Master(12:!5) Brief history of AI Dungeon(17:30) AI in

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Connor Leahy on EleutherAI, Replicating GPT-2/GPT-3,...

The Gradient: Perspectives on AI ·

2022/02/03

In episode 22 of The Gradient Podcast, we talk to Connor Leahy, an AI researcher focused on AI alignment and a co-founder of EleutherAI.Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterConnor is an AI researcher working on understanding large ML models and aligning them to human values, and a cofounder of EleutherAI, a decentralized grassroots collective of volunteer researchers, engineers, and developers focused on AI alignment,

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50:54

Percy Liang on Machine Learning Robustness,...

The Gradient: Perspectives on AI ·

2022/01/27

In interview 21 of The Gradient Podcast, we talk to Percy Liang, an Associate Professor of Computer Science at Stanford University and the director of the Center for Research on Foundation Models.Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterPercy Liang’s research spans many topics in machine learning and natural language processing, including robustness, interpretability, semantics, and reasoning. He is also a strong proponent of

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93:19

Eric Jang on Robots Learning at Google and...

The Gradient: Perspectives on AI ·

2022/01/08

In episode 20 of The Gradient Podcast, we talk to Eric Jang, a research scientist on the Robotics team at Google.Eric is a research scientist on the Robotics team at Google. His research focuses on answering whether big data and small algorithms can yield unprecedented capabilities in the domain of robotics, just like the computer vision, translation, and speech revolutions before it. Specifically, he focuses on robotic manipulation and self-supervised robotic learning.Sections:(00:00) Intro(00:50)

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93:51

Rishi Bommasani on Foundation Models

The Gradient: Perspectives on AI ·

2021/12/09

In episode 19 of The Gradient Podcast, we talk to Rishi Bommasani, a Ph.D student at Stanford focused on Foundation Models. Rish is a second-year Ph.D. student in the CS Department at Stanford, where he is advised by Percy Liang and Dan Jurafsky. His research focuses on understanding AI systems and their social impact, as well as using NLP to further scientific inquiry. Over the past year, he helped build and organize the Stanford Center for Research on Foundation Models (CRFM).Sections:(00:00:00)

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95:16

Upol Ehsan on Human-Centered Explainable AI and...

The Gradient: Perspectives on AI ·

2021/12/03

In episode 18 of The Gradient Podcast, we talked to Upol Ehsan, an Explainable AI (XAI) researcher who combines his background in Philosophy and Human-Computer Interaction to address problems in XAI beyond just opening the "black-box" of AI. You can find his Gradient article charting this vision here.Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on TwitterPapers Discussed:* Rationalization: A Neural Machine Translation Approach to Generating

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54:03

Miles Brundage on AI Misuse and Trustworthy AI

The Gradient: Perspectives on AI ·

2021/11/23

In episode 17 of The Gradient Podcast, we talk to Miles Brundage, Head of Policy Research at OpenAI and a researcher passionate about the responsible governance of artificial intelligence. Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSLinks:* Will Technology Make Work Better for Everyone?* Economic Possibilities for Our Children: Artificial Intelligence and the Future of Work, Education, and Leisure* Taking Superintelligence Seriously* The Malicious Use of

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71:04

Jeffrey Ding on China's AI Dream, the AI 'Arms Race',...

The Gradient: Perspectives on AI ·

2021/11/18

In episode 16 of The Gradient Podcast, we talk to Jeffrey Ding, a postdoctoral fellow at Stanford's Center for International Security and Cooperation(01:35) Getting into AI research(04:20) Interest in studying China(06:50) Deciphering China’s AI Dream(23:25) Beyond the AI Arms Race(36:45) China's Current Capabilities in AI(46:45) AI as a General Purpose and Strategic Technology(57:38) ChinaAI Newsletter(01:04:20) Teaching AI to Policy People(01:06:30) Current Focus(01:09:10) Interests Outside of

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70:41

Alex Tamkin on Self-Supervised Learning and Large...

The Gradient: Perspectives on AI ·

2021/11/11

In episode 15 of The Gradient Podcast, we talk to Stanford PhD Candidate Alex TamkinSubscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSAlex Tamkin is a fourth-year PhD student in Computer Science at Stanford, advised by Noah Goodman and part of the Stanford NLP Group. His research focuses on understanding, building, and controlling pretrained models, especially in domain-general or multimodal settings.We discuss:* Viewmaker Networks: Learning Views for Unsupervised

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88:42

Peter Henderson on RL Benchmarking, Climate Impacts...

The Gradient: Perspectives on AI ·

2021/10/28

In episode 14 of The Gradient Podcast, we interview Stanford PhD Candidate Peter HendersonSubscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSPeter is a joint JD-PhD student at Stanford University advised by Dan Jurafsky. He is also an OpenPhilanthropy AI Fellow and a Graduate Student Fellow at the Regulation, Evaluation, and Governance Lab. His research focuses on creating robust decision-making systems, with three main goals: (1) use AI to make governments more

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49:40

Chelsea Finn on Meta Learning & Model Based...

The Gradient: Perspectives on AI ·

2021/10/14

In episode 13 of The Gradient Podcast, we interview Stanford Professor Chelsea FinnSubscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSChelsea is an Assistant Professor at Stanford University. Her lab, IRIS, studies intelligence through robotic interaction at scale, and is affiliated with SAIL and the Statistical ML Group. I also spend time at Google as a part of the Google Brain team. Her research deals with the capability of robots and other agents to develop broadly

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55:14

Devi Parikh on Generative Art & AI for Creativity

The Gradient: Perspectives on AI ·

2021/10/01

In episode 12 of The Gradient Podcast, we interview Devi Parikh, a professor at Georgia Tech whose research focuses on computer vision, natural language processing, embodied AI, human-AI collaboration, and AI for creativity.Devi Parikh is an Associate Professor in the School of Interactive Computing at Georgia Tech, and a Research Scientist at Facebook AI Research (FAIR). Her research interests are in computer vision, natural language processing, embodied AI, human-AI collaboration, and AI for

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53:51

Sergey Levine on Robot Learning & Offline RL

The Gradient: Perspectives on AI ·

2021/09/16

In episode 11 of The Gradient Podcast, we interview Sergey Levine, a professor at Berkeley whose research focuses on machine learning for decision making and control, with an emphasis on deep learning and reinforcement learning algorithms for robotics.Sergey Levine received a BS and MS in Computer Science from Stanford University in 2009, and a Ph.D. in Computer Science from Stanford University in 2014. He joined the faculty of the Department of Electrical Engineering and Computer Sciences at UC

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58:03

Jeremy Howard on Kaggle, Enlitic, and fast.ai

The Gradient: Perspectives on AI ·

2021/09/09

In episode 10 of The Gradient Podcast, we interview data scientist, researcher, developer, educator, and entrepreneur Jeremy Howard.Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSJeremy Howard is a data scientist, researcher, developer, educator, and entrepreneur. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible. He is also a Distinguished Research Scientist at the University of San Francisco, the

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75:20

Evan Hubinger on Effective Altruism and AI Safety

The Gradient: Perspectives on AI ·

2021/09/03

In episode 9 of The Gradient Podcast, we interview Yannic Kilcher, an AI researcher and educator.Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSEvan is an AI safety veteran who’s done research at leading AI labs like OpenAI, and whose experience also includes stints at Google, Ripple andYelp. He currently works at the Machine Intelligence Research Institute (MIRI) as a Research Fellow, and joined me to talk about his views on AI safety, the alignment problem,

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40:32

Yannic Kilcher on Being an AI Researcher and Educator

The Gradient: Perspectives on AI ·

2021/08/27

In episode 8 of The Gradient Podcast, we interview Yannic Kilcher, an AI researcher and educator.Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSYannic graduated with his PhD from ETH Zurich’s data analytics lab and is now the Chief Technology Officer of DeepJudge, a company building the next-generation AI-powered context-sensitive legal document processing platform. He famously produces videos on his very popular Youtube channel, which cover machine learning

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147 results

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