Are you eager, to lose track of time, zone out, get some peace of mind, well that won't happen on my watch, I'll constantly remind you of your problems and remind you of the exact time. This is the Michael David Daniel Manuel Show... I'm Still working on the name, but we are sponsored by Nike ©, Lipton ice tea© and many many more. Come listen to me make fun of your mom, talk trash about your inbred family and most of all laugh at your opinions. OMW you're still reading? You must love emotion ...
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Deeply researched, technical interviews with experts thinking about AI and technology. Hosted, recorded, researched, and produced by Daniel Bashir. thegradientpub.substack.com
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Davidad Dalrymple: Towards Provably Safe AI
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Episode 137 I spoke with Davidad Dalrymple about: * His perspectives on AI risk * ARIA (the UK’s Advanced Research and Invention Agency) and its Safeguarded AI Programme Enjoy—and let me know what you think! Davidad is a Programme Director at ARIA. He was most recently a Research Fellow in technical AI safety at Oxford. He co-invented the top-40 cr…
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Clive Thompson: Tales of Technology
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Episode 136 I spoke with Clive Thompson about: * How he writes * Writing about the climate and biking across the US * Technology culture and persistent debates in AI * Poetry Enjoy—and let me know what you think! Clive is a journalist who writes about science and technology. He is a contributing writer forWired magazine, and is currently writing hi…
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Judy Fan: Reverse Engineering the Human Cognitive Toolkit
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Episode 136 I spoke with Judy Fan about: * Our use of physical artifacts for sensemaking * Why cognitive tools can be a double-edged sword * Her approach to scientific inquiry and how that approach has developed Enjoy—and let me know what you think! Judy is Assistant Professor of Psychology at Stanford and director of the Cognitive Tools Lab. Her l…
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L.M. Sacasas: The Questions Concerning Technology
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Episode 135 I spoke with L. M. Sacasas about: * His writing and intellectual influences * The value of asking hard questions about technology and our relationship to it * What happens when we decide to outsource skills and competency * Evolving notions of what it means to be human and questions about how to live a good life Enjoy—and let me know wh…
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Pete Wolfendale: The Revenge of Reason
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Episode 134 I spoke with Pete Wolfendale about: * The flaws in longtermist thinking * Selections from his new book, The Revenge of Reason * Metaphysics * What philosophy has to say about reason and AI Enjoy—and let me know what you think! Pete is an independent philosopher based in Newcastle. Dr. Wolfendale got both his undergraduate degree and his…
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Peter Lee: Computing Theory and Practice, and GPT-4's Impact
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Episode 133 I spoke with Peter Lee about: * His early work on compiler generation, metacircularity, and type theory * Paradoxical problems * GPT-4s impact, Microsoft’s “Sparks of AGI” paper, and responses and criticism Enjoy—and let me know what you think! Peter is President of Microsoft Research. He leads Microsoft Research and incubates new resea…
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Manuel & Lenore Blum: The Conscious Turing Machine
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Episode 132 I spoke with Manuel and Lenore Blum about: * Their early influences and mentors * The Conscious Turing Machine and what theoretical computer science can tell us about consciousness Enjoy—and let me know what you think! Manuel is a pioneer in the field of theoretical computer science and the winner of the 1995 Turing Award in recognition…
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Kevin Dorst: Against Irrationalist Narratives
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Episode 131 I spoke with Professor Kevin Dorst about: * Subjective Bayesianism and epistemology foundations * What happens when you’re uncertain about your evidence * Why it’s rational for people to polarize on political matters Enjoy—and let me know what you think! Kevin is an Associate Professor in the Department of Linguistics and Philosophy at …
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David Pfau: Manifold Factorization and AI for Science
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Episode 130 I spoke with David Pfau about: * Spectral learning and ML * Learning to disentangle manifolds and (projective) representation theory * Deep learning for computational quantum mechanics * Picking and pursuing research problems and directions David’s work is really (times k for some very large value of k) interesting—I’ve been inspired to…
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Dan Hart and Michelle Michael: Bringing AI to Students in New South Wales
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Episode 129 I spoke with Dan Hart and Michelle Michael about: * Developing NSWEduChat, an AI-powered chatbot designed and delivered by the NSW Department of Education for students and teachers. * The challenges in effectively teaching students as technology develops * Understanding and defining the importance of the classroom Enjoy—and let me know …
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Kristin Lauter: Private AI, Homomorphic Encryption, and AI for Cryptography
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Episode 129 I spoke with Kristin Lauter about: * Elliptic curve cryptography and homomorphic encryption * Standardizing cryptographic protocols * Machine Learning on encrypted data * Attacking post-quantum cryptography with AI Enjoy—and let me know what you think! Kristin is Senior Director of FAIR Labs North America (2022—present), based in Seattl…
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Sergiy Nesterenko: Automating Circuit Board Design
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Episode 128 I spoke with Sergiy Nesterenko about: * Developing an automated system for designing PCBs * Difficulties in human and automated PCB design * Building a startup at the intersection of different areas of expertise By the way — I hit 40 ratings on Apple Podcasts (and am at 66 on Spotify). It’d mean a lot (really, a lot) if you’d consider l…
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C. Thi Nguyen: Values, Legibility, and Gamification
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Episode 127 I spoke with Christopher Thi Nguyen about: * How we lose control of our values * The tradeoffs of legibility, aggregation, and simplification * Gamification and its risks Enjoy—and let me know what you think! C. Thi Nguyen as of July 2020 is Associate Professor of Philosophy at the University of Utah. His research focuses on how social …
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Vivek Natarajan: Towards Biomedical AI
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Episode 126 I spoke with Vivek Natarajan about: * Improving access to medical knowledge with AI * How an LLM for medicine should behave * Aspects of training Med-PaLM and AMIE * How to facilitate appropriate amounts of trust in users of medical AI systems Vivek Natarajan is a Research Scientist at Google Health AI advancing biomedical AI to help sc…
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Thomas Mullaney: A Global History of the Information Age
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Episode 125 False universalism freaks me out. It doesn’t freak me out as a first principle because of epistemic violence; it freaks me out because it works. I spoke with Professor Thomas Mullaney about: * Telling stories about your work and balancing what feels meaningful with practical realities * Destabilizing our understandings of the technologi…
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Seth Lazar: Normative Philosophy of Computing
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Episode 124 You may think you’re doing a priori reasoning, but actually you’re just over-generalizing from your current experience of technology. I spoke with Professor Seth Lazar about: * Why managing near-term and long-term risks isn’t always zero-sum * How to think through axioms and systems in political philosphy * Coordination problems, econom…
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Suhail Doshi: The Future of Computer Vision
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Episode 123 I spoke with Suhail Doshi about: * Why benchmarks aren’t prepared for tomorrow’s AI models * How he thinks about artists in a world with advanced AI tools * Building a unified computer vision model that can generate, edit, and understand pixels. Suhail is a software engineer and entrepreneur known for founding Mixpanel, Mighty Computing…
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Azeem Azhar: The Exponential View
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Episode 122 I spoke with Azeem Azhar about: * The speed of progress in AI * Historical context for some of the terminology we use and how we think about technology * What we might want our future to look like Azeem is an entrepreneur, investor, and adviser. He is the creator of Exponential View, a global platform for in-depth technology analysis, a…
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David Thorstad: Bounded Rationality and the Case Against Longtermism
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Episode 122 I spoke with Professor David Thorstad about: * The practical difficulties of doing interdisciplinary work * Why theories of human rationality should account for boundedness, heuristics, and other cognitive limitations * why EA epistemics suck (ok, it’s a little more nuanced than that) Professor Thorstad is an Assistant Professor of Phil…
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Ryan Tibshirani: Statistics, Nonparametric Regression, Conformal Prediction
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Episode 121 I spoke with Professor Ryan Tibshirani about: * Differences between the ML and statistics communities in scholarship, terminology, and other areas. * Trend filtering * Why you can’t just use garbage prediction functions when doing conformal prediction Ryan is a Professor in the Department of Statistics at UC Berkeley. He is also a Princ…
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Sasha Luccioni: Connecting the Dots Between AI's Environmental and Social Impacts
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In episode 120 of The Gradient Podcast, Daniel Bashir speaks to Sasha Luccioni. Sasha is the AI and Climate Lead at HuggingFace, where she spearheads research, consulting, and capacity-building to elevate the sustainability of AI systems. A founding member of Climate Change AI (CCAI) and a board member of Women in Machine Learning (WiML), Sasha is …
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Michael Sipser: Problems in the Theory of Computation
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In episode 119 of The Gradient Podcast, Daniel Bashir speaks to Professor Michael Sipser. Professor Sipser is the Donner Professor of Mathematics and member of the Computer Science and Artificial Intelligence Laboratory at MIT. He received his PhD from UC Berkeley in 1980 and joined the MIT faculty that same year. He was Chairman of Applied Mathema…
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Andrew Lee: How AI will Shape the Future of Email
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In episode 118 of The Gradient Podcast, Daniel Bashir speaks to Andrew Lee. Andrew is co-founder and CEO of Shortwave, a company dedicated to building a better product experience for email, particularly by leveraging AI. He previously co-founded and was CTO at Firebase. Have suggestions for future podcast guests (or other feedback)? Let us know her…
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Joss Fong: Videomaking, AI, and Science Communication
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“You get more of what you engage with. Everyone who complains about coverage should understand that every click, every quote tweet, every argument is registered by these publications as engagement. If what you want is really meaty, dispassionate, balanced, and fair explainers, you need to click on that, you need to read the whole thing, you need to…
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Kate Park: Data Engines for Vision and Language
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In episode 116 of The Gradient Podcast, Daniel Bashir speaks to Kate Park. Kate is the Director of Product at Scale AI. Prior to joining Scale, Kate worked on Tesla Autopilot as the AI team’s first and lead product manager building the industry’s first data engine. She has also published research on spoken natural language processing and a travel m…
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Ben Wellington: ML for Finance and Storytelling through Data
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In episode 115 of The Gradient Podcast, Daniel Bashir speaks to Ben Wellington. Ben is the Deputy Head of Feature Forecasting at Two Sigma, a financial sciences company. Ben has been at Two Sigma for more than 15 years, and currently leads efforts focused on natural language processing and feature forecasting. He is also the author of data science …
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Venkatesh Rao: Protocols, Intelligence, and Scaling
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“There is this move from generality in a relative sense of ‘we are not as specialized as insects’ to generality in the sense of omnipotent, omniscient, godlike capabilities. And I think there's something very dangerous that happens there, which is you start thinking of the word ‘general’ in completely unhinged ways.” In episode 114 of The Gradient …
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Sasha Rush: Building Better NLP Systems
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In episode 113 of The Gradient Podcast, Daniel Bashir speaks to Professor Sasha Rush. Professor Rush is an Associate Professor at Cornell University and a Researcher at HuggingFace. His research aims to develop natural language processing systems that are safe, fast, and controllable. His group is interested primarily in tasks that involve text gen…
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Cameron Jones & Sean Trott: Understanding, Grounding, and Reference in LLMs
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In episode 112 of The Gradient Podcast, Daniel Bashir speaks to Cameron Jones and Sean Trott. Cameron is a PhD candidate in the Cognitive Science Department at the University of California, San Diego. His research compares how humans and large language models process language about world knowledge, situation models, and theory of mind. Sean is an A…
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Nicholas Thompson: AI and Journalism
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In episode 111 of The Gradient Podcast, Daniel Bashir speaks to Nicholas Thompson. Nicholas is the CEO of The Atlantic. Previously, he served as editor-in-chief of Wired and editor of Newyorker.com. Nick also cofounded Atavist, which sold to Automattic in 2018. Publications under Nick’s leadership have won numerous National Magazine Awards and Puli…
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Subbarao Kambhampati: Planning, Reasoning, and Interpretability in the Age of LLMs
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In episode 110 of The Gradient Podcast, Daniel Bashir speaks to Professor Subbarao Kambhampati. Professor Kambhampati is a professor of computer science at Arizona State University. He studies fundamental problems in planning and decision making, motivated by the challenges of human-aware AI systems. He is a fellow of the Association for the Advanc…
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Russ Maschmeyer: Spatial Commerce and AI in Retail
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In episode 109 of The Gradient Podcast, Daniel Bashir speaks to Russ Maschmeyer. Russ is the Product Lead for AI and Spatial Commerce at Shopify. At Shopify, he leads a team that looks at how AI can better empower entrepreneurs, with a particular interest in how image generation can help make the lives of business owners and merchants more producti…
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Benjamin Breen: The Intersecting Histories of Psychedelics and AI Research
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In episode 108 of The Gradient Podcast, Daniel Bashir speaks to Professor Benjamin Breen. Professor Breen is an associate professor of history at UC Santa Cruz specializing in the history of science, medicine, globalization, and the impacts of technological change. He is the author of multiple books including The Age of Intoxication: Origins of the…
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Ted Gibson: The Structure and Purpose of Language
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In episode 107 of The Gradient Podcast, Daniel Bashir speaks to Professor Ted Gibson. Ted is a Professor of Cognitive Science at MIT. He leads the TedLab, which investigates why languages look the way they do; the relationship between culture and cognition, including language; and how people learn, represent, and process language. Have suggestions …
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Harvey Lederman: Propositional Attitudes and Reference in Language Models
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In episode 106 of The Gradient Podcast, Daniel Bashir speaks to Professor Harvey Lederman. Professor Lederman is a professor of philosophy at UT Austin. He has broad interests in contemporary philosophy and in the history of philosophy: his areas of specialty include philosophical logic, the Ming dynasty philosopher Wang Yangming, epistemology, and…
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Eric Jang: AI is Good For You
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In episode 105 of The Gradient Podcast, Daniel Bashir speaks to Eric Jang. Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub Subscribe to The Gradient Podcast: Apple Podcasts | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter Outline: * (00:00) Intro * (01:25) Updates si…
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2023 in AI, with Nathan Benaich
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In episode 104 of The Gradient Podcast, Daniel Bashir speaks to Nathan Benaich. Nathan is Founder and General Partner at Air Street Capital, a VC firm focused on investing in AI-first technology and life sciences companies. Nathan runs a number of communities focused on AI including the Research and Applied AI Summit and leads Spinout.fyi to improv…
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Kathleen Fisher: DARPA and AI for National Security
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In episode 103 of The Gradient Podcast, Daniel Bashir speaks to Dr. Kathleen Fisher. As the director of DARPA’s Information Innovation Office (I2O), Dr. Kathleen Fisher oversees a portfolio that includes most of the agency’s AI-related research and development efforts, including the recent AI Forward initiative. AI Forward explores new directions f…
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Peter Tse: The Neuroscience of Consciousness and Free Will
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In episode 102 of The Gradient Podcast, Daniel Bashir speaks to Peter Tse. Professor Tse is a Professor of Cognitive Neuroscience and chair of the department of Psychological and Brain Sciences at Dartmouth College. His research focuses on using brain and behavioral data to constrain models of the neural bases of attention and consciousness, uncons…
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Vera Liao: AI Explainability and Transparency
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In episode 101 of The Gradient Podcast, Daniel Bashir speaks to Vera Liao. Vera is a Principal Researcher at Microsoft Research (MSR) Montréal where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics) group. She is trained in human-computer interaction research and works on human-AI interaction, currently focusing on explai…
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Thomas Dietterich: From the Foundations
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In episode 100 of The Gradient Podcast, Daniel Bashir speaks to Professor Thomas Dietterich. Professor Dietterich is Distinguished Professor Emeritus in the School of Electrical Engineering and Computer Science at Oregon State University. He is a pioneer in the field of machine learning, and has authored more than 225 refereed publications and two …
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Martin Wattenberg: ML Visualization and Interpretability
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In episode 99 of The Gradient Podcast, Daniel Bashir speaks to Professor Martin Wattenberg. Professor Wattenberg is a professor at Harvard and part-time member of Google Research’s People + AI Research (PAIR) initiative, which he co-founded. His work, with long-time collaborator Fernanda Viégas, focuses on making AI technology broadly accessible an…
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Laurence Liew: AI Singapore
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In episode 98 of The Gradient Podcast, Daniel Bashir speaks to Laurence Liew. Laurence is the Director for AI Innovation at AI Singapore. He is driving the adoption of AI by the Singapore ecosystem through the 100 Experiments, AI Apprenticeship Programmes and the Generational AI Talent Development initiative. He is the current Co-Chair of the Innov…
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Michael Levin & Adam Goldstein: Intelligence and its Many Scales
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In episode 97 of The Gradient Podcast, Daniel Bashir speaks to Professor Michael Levin and Adam Goldstein. Professor Levin is a Distinguished Professor and Vannevar Bush Chair in the Biology Department at Tufts University. He also directs the Allen Discovery Center at Tufts. His group, the Levin Lab, focuses on understanding the biophysical mechani…
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Jonathan Frankle: From Lottery Tickets to LLMs
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In episode 96 of The Gradient Podcast, Daniel Bashir speaks to Jonathan Frankle. Jonathan is the Chief Scientist at MosaicML and (as of release). Jonathan completed his PhD at MIT, where he investigated the properties of sparse neural networks that allow them to train effectively through his lottery ticket hypothesis. He also spends a portion of hi…
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Nao Tokui: "Surfing" Musical Creativity with AI
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In episode 95 of The Gradient Podcast, Daniel Bashir speaks to Nao Tokui. Nao Tokui is an artist/DJ and researcher based in Tokyo. While pursuing his Ph.D. at The University of Tokyo, he produced his first music album and singles using AI, including a 12-inch record with Nujabes, a legendary Japanese hip-hop producer. After completing his Ph.D. res…
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Divyansh Kaushik: The Realities of AI Policy
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In episode 94 of The Gradient Podcast, Daniel Bashir speaks to Divyansh Kaushik. Divyansh is the Associate Director for Emerging Technologies and National Security at the Federation of American Scientists where his focus areas include, amongst other things, AI policy, STEM immigration, and US-China strategic competition. He holds a PhD from Carnegi…
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Tal Linzen: Psycholinguistics and Language Modeling
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In episode 93 of The Gradient Podcast, Daniel Bashir speaks to Professor Tal Linzen. Professor Linzen is an Associate Professor of Linguistics and Data Science at New York University and a Research Scientist at Google. He directs the Computation and Psycholinguistics Lab, where he and his collaborators use behavioral experiments and computational m…
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Kevin K. Yang: Engineering Proteins with ML
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In episode 92 of The Gradient Podcast, Daniel Bashir speaks to Kevin K. Yang. Kevin is a senior researcher at Microsoft Research (MSR) who works on problems at the intersection of machine learning and biology, with an emphasis on protein engineering. He completed his PhD at Caltech with Frances Arnold on applying machine learning to protein enginee…
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Arjun Ramani & Zhengdong Wang: Why Transformative AI is Really, Really Hard to Achieve
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In episode 91 of The Gradient Podcast, Daniel Bashir speaks to Arjun Ramani and Zhengdong Wang. Arjun is the global business and economics correspondent at The Economist. Zhengdong is a research engineer at Google DeepMind. Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub Subscri…
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