Computing Up

Ben Kuipers, emeritus professor of Electrical Engineering and Computer Science at the University of Michigan (🔗, 🔗, 🔗), joins Michael and Dave in a nerdly yet accessible conversation on topics ranging from Good Old-Fashioned AI, to how we understand space and time, to ethics and trust in society, to teaching Dave how to LISP properly in the 1970s. [Episode cover based on image used courtesy of Benjamin J. Kuipers]

Moshe Vardi (🔗, 🔗, 🔗), the Karen Ostrum George Distinguished Service Professor in Computational Engineering at Rice University, and a multi-award-winning force in theoretical computer science, joins Michael and Dave in a wide-ranging conversation about robustness and resilience in computer science, engineering, and society at large. Moshe's talk "Lessons from Texas, COVID-19, and the 737 Max" is online (🔗, 🔗). [Cover based on an image used by permission of Moshe Vardi] Episode Note: This conversation was recorded in August 2024 but is only becoming available now. Computing Up regrets and apologizes for the extended delay!

Dr. Joy Lisi Rankin (🔗, 🔗, 🔗, 🔗), an author, historian, and academic, joins Michael and Dave in a fast conversation about the history of computing and its systemic biases from the '60s to the techbros of today, and much more. [Cover based on an image used by permission of Joy Rankin] Note: This conversation was recorded in April 2024 but is only becoming available now. Computing Up regrets and apologizes for the extended delay!

Cognitive scientist and psychologist Professor Steve Sloman of Brown University (🔗, 🔗, 🔗) joins Michael and Dave in a fun romp through connectionism, collective cognition, the illusion of understanding, and much more. Also, Dave illustrates his illusion of understanding of a bicycle in a true back of the envelope sketch -- [Episode cover based on image used courtesy of Steven Sloman]

Manon Revel (🔗, 🔗, 🔗), an Employee Fellow at the Berkman Klein Center for Internet & Society at Harvard University, joins Michael and Dave for a conversation about the past, present, and future of democracy, and ways to understand it in both computational and practical terms. [Thumbnail based on image provided courtesy of Manon Revel]

Martha White, associate professor of Computing Science at University of Alberta (🔗, 🔗) joins Michael and Dave in a conversation about AI, system prediction and control, the power of sparse representations, and many aspects of machine learning from new mathematical theory to the absolutely practical control of a real water treatment plant. [Thumbnail based on image used courtesy of Martha White]

Computer scientist Rich Sutton, FRS (🔗, 🔗, 🔗), a quiet giant of machine learning, joins Michael and Dave in a sprawling conversation touching on reinforcement learning, a hopeful view of AI, the importance of ideas, and a host of other topics. [Thumbnail image used courtesy of Rich Sutton]

Michael interviews Dave about his recent video (YouTube) on a 'theory of everything'. The conversation begins with Michael praising Dave for finally doing some theory, and descends from there.

Oren Etzioni, founding CEO of the Allen Institute for Artificial Intelligence and Professor Emeritus of Computer Science at University of Washington, (🔗, 🔗, 🔗) joins Michael and Dave in a conversation that ranges all over, from AI hype and language models to alignment and existential risk and ethics and morality to information pollution and cryptography and politics and more. [Thumbnail based on image licensed CC BY-SA 4.0 by Carissapod link]

Jonathan Frankle, the new Chief Scientist - Neural Networks at Databricks (🔗, 🔗, 🔗), joins Michael and Dave in a fast conversation about topics ranging from AI risks and fairness to the problems of Computer Science education to the beautiful messiness of modern deep learning. [Thumbnail based on image courtesy of Jonathan Frankle]

Michael and Dave talk about their love and hate relationships with writing, in the context of Dave's foray into publishing "Companionate Caring" and Michael's upcoming MIT Press book "Code to Joy". (This conversation is Part 2 of Where The Hell Have Michael & Dave Been?)

Michael and Dave catch up on where the hell they've been for the last couple months. (Mostly it's about busy, but Dave wants to blame everything on AI.)

Michael Levin (🔗, 🔗, 🔗) is the director of the Allen Discovery Center at Tufts University, and Distinguished Professor of Biology and Vannevar Bush Chair, among several other roles. In this episode he talks with Michael and Dave about computing writ very large indeed, with topics ranging from the meaning of life and agency to the problems of computability theory to the ways Levin's TAME model - Technological Approach to Mind Everywhere (🔗) - envisions a reality full of adaptive machines made of adaptive parts adapting to each other with everything they've got.

Cynthia Rudin, the Earl D. McLean, Jr. Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics,and Biostatistics & Bioinformatics at Duke University (🔗, 🔗, 🔗), joins Michael and Dave for a fast and feisty conversation about how to make machines we can understand and control, with high-stakes examples like predicting power failures in New York City.

Vukosi Marivate, Associate Professor of Computer Science and ABSA UP Chair of Data Science at the University of Pretoria (🔗, 🔗, 🔗), joins Michael and Dave for a discussion of AI and machine learning research across Africa and around the world, and the challenges of centralization and efficiency versus diversification at the edge, and what each can learn from the other. [Title card based on image courtesy of Vukosi Marivate]

Andrew Davison is Professor of Robot Vision (🔗) at Imperial College London, and leads the Dyson Robotics Laboratory (🔗). Andrew invented the SLAM algorithm for robot mapping and navigation, and as this fast conversation makes clear, Dave and Michael are both big fans. [Thumbnail based on image courtesy of Andrew Davison]

Reclusive New York Times best-selling author John Twelve Hawks (🔗, 🔗 , 🔗) joins Michael and Dave to discuss problems of the world today and possibilities of the world tomorrow -- including AI risks, technological centralization, machines acting like people and people acting like machines, sex drives for sexbots, and the question of unintended consequences.

Peter Norvig 🔗, who literally (co)wrote the book 🔗 on Artificial Intelligence in the 1990s, talks with Michael and Dave about how the field has changed over the years, AI fairness and ethics, what is a symbol, and much more. [Cover image based on "Peter Norvig in 2019 at the Interval" 🔗 , licensed CC BY-SA 4.0 by Christopher Michel (Cmichel67 🔗 on Wikipedia)]

Oriel FeldmanHall, Brown University assistant professor and director of the Social and Affective Neuroscience Lab (🔗, 🔗), joins Michael and Dave in a wide-ranging discussion starting with what reinforcement learning does and doesn't mean -- and she turns the tables to ask what computer scientists do and don't get wrong about mind and brain and learning in general.

Michael and Dave tackle the big questions and settle two of them: Is Agency A Zero Sum Game? Why Do (Internet of) Things Suck? How Can We Turn Computation Away From Centralization? [Image of ancient Philips Hue Controller operating without internet access, used by permission of Dave the owner]

James Tompkin 🔗, assistant Professor of Computer Science at Brown University 🔗, joins Michael and Dave to talk about visual computing research writ large, with topics ranging from the relevance of traditional computer graphics in the era of machine learning, to differentiable rendering and neural radiance fields, to DALL-E 2 and remixing Hitchcock's "Rear Window" at the Museum of the Moving Image.

Ellie Pavlick, Assistant Professor of Computer Science at Brown University (🔗) and Research Scientist at Google AI (🔗), joins Michael and Dave in a quick discussion of the remarkable new large AI language models. Topics range from what is and isn't known about the models, and by them, to if or how scared should we be of them, to what 'traditional' sciences like linguistics bring to artificial intelligence research and engineering. [Image courtesy of Ellie Pavlick]

Andrew Critch (🔗), a mathematician, AI researcher, organizer and activist (cofounder 🔗, researcher 🔗, cofounder 🔗), joins Michael and Dave for a fast-moving fifty minutes about existential risks (and opportunities) of AI and other technologies, the limits of intelligence, and the importance of structure at all scales and having a good spirit.

Dave tries to explain why he thinks the best way to understand people and other living things is via computation and programming languages, via codebases and code transmissions. Michael tries to help Dave sound slightly sane. [Image based on still frame from "We Are Coders"]

Fiery Cushman @fierycushman, professor of psychology at Harvard University 🔗, joins Michael and Dave in a wonderful conversation about morality seen both cognitively and computationally, with topics ranging from trolley problems and fake guns to the wisdom of the ancestors and the hubris of science to what makes moral thinking special. [Title image courtesy of Fiery Cushman]

Neil Lawrence (home, @lawrennd), the DeepMind Professor of Machine Learning at the University of Cambridge, joins Michael and Dave for a rollicking hour discussing everything from cybernetics to machine learning, from oil rigs to New Jersey shopping malls, from inconsistent scientific reviewing to gods and robots and much more. Talking Machines podcast [Image courtesy of Neil Lawrence]

Carla Brodley, professor and Dean of Inclusive Computing at Northeastern University (link), talks to Michael and Dave about applying Machine Learning to real problems from computer security to medicine, and how to move the needle for diversity, equity, access, and belonging in Computer Science education. [Title image courtesy of Carla Brodley]

Karen Levy, assistant professor in Information Science at Cornell University, joins Michael and Dave in a conversation ranging from AI, law, and smart contracts to CB radio, Road Dog Trucking, and Santa's narcs.

Anita Nikolich, Director of Research and Technology Innovation at the University of Illinois School of Information Sciences (webpage), joins Michael and Dave in a conversation ranging over decades and disciplines, from computer network security and the DEFCON hacker conferences to creating games for teaching about mis- and dis-information. [Title image courtesy of Anita Nikolich]

Michael Bowling, professor of Computer Science at the University of Alberta, talks with Michael and Dave about robots playing robots at soccer, and how a computer program beat professional poker players at heads-up no-limit Texas Hold'em, and what it all means. [Image courtesy of Michael Bowling]

Michael and Dave talk to George Konidaris, assistant professor and director of the Intelligent Robot Lab at Brown University, about building generally intelligent robots, or anyway trying, and the importance of both embodiment and abstraction in artificial intelligence. [Title image courtesy of George Konidaris]

Rutgers Professor Michael Lesk talks to Michael and Dave about everything from computing and information retrieval in the 1960s, to railroad signaling and recognizing giraffes, to the difference between astronomers and computer scientists, to Colonial Pipeline and the real AI challenge. [Title image courtesy of Mike Lesk]

Professor Tina Eliassi-Rad of Northeastern's Network Science Institute talks with Michael and Dave about topics ranging from graph structures and machine learning to AI ethics and the nature of democracy. [Title image courtesy of Tina Eliassi-Rad]

Dave is feeling glum about technology -- and by extension about the impacts of computer science, the exploitation of science in general, and the hope for sustainability and truth in society. Michael helps sort it all out.

Michael and Dave talk to Heather J. Lynch, Associate Professor of Ecology and Evolution at Stony Brook University, about awards and leaving physics, about saving penguins and the planet, and more.

Heather Lane, machine learning researcher and senior architect at athenahealth, joins Dave and Michael in a talk of many things, of the thermodynamics of life, of the US healthcare industry and life after academia, of coming out as transgender.

Fil Menczer, professor and director of the Observatory on Social Media at Indiana University, joined Michael and Dave on the day after the 2020 USA presidential election. Fil revealed how his 1990s Artificial Life research set the stage for his current work, focusing not just on the facts of disinformation and hoaxes and conspiracy theories and social bots, but also how to identify and fight them. [Title image based on photograph licensed CC BY-SA 3.0 by Tracey Theriault]

Jeff Bigham, an Associate Professor at Carnegie-Mellon's Human-Computer Interaction Institute, joins Michael and Dave in a wide-ranging discussion of human-computer interactions, AI threats and opportunities, and systems and organizations made of both computers and humans. [Episode transcript (PDF)] [Cover photo courtesy of Jeff Bigham]

Michael and Dave discuss the meaning of the reward function, and its consequences for AI and human society.

Dave tries to explain his "We are coders" approach to cognition to Michael, as part of developing the second lecture in the "Introduction to Classical Hyperspace" series. First lecture

Computer scientists Emma Brunskill of Stanford and Phil Thomas of UMass Amherst join Michael and Dave in a four-way discussion of safety and fairness in AI and machine learning. [The primary paper discussed, Preventing undesirable behavior of intelligent machines, is by Philip S. Thomas, Bruno Castro da Silva, Andrew G. Barto, Stephen Giguere, Yuriy Brun, and Emma Brunskill, and can be accessed for free via paper in Science ]

Michael and Dave talk with UC Berkeley sociologist Jenna Burrell about topics ranging from algorithmic fairness and transparency, to anthropology and epistemology, to viral tweets and why small is beautiful. [Title image courtesy of Jenna Burrell]

Dave hates theory. Michael disagrees.

Michael and Dave talk with mathematician, computer scientist, and puzzle maker Peter Winkler, about topics ranging from randomness to free will, and combinatorics to Sleeping Beauty, and John Horton Conway to Erdős number 1. And don't miss the bonus puzzle! Conway's (first) Princeton Lecture [Title photo courtesy of Peter Winkler]

Michael and Dave talk about pandemic models and simulation journalism, programming languages, and what people really want. Washington Post's simulator is here

Michael and Dave talk to Brown University neuroscientist Michael J Frank about topics from brains and minds, to engineering and machine learning, to dopamine and Parkinson's disease and New Age woo.

Computer scientist and biologist Melanie Moses joins Michael and Dave in a conversation ranging from biology nerds vs computing nerds to the future of justice in the United States, with a whole lot of scaling along the way.

Michael Carbin, Assistant Professor of Electrical Engineering and Computer Science at MIT, joins Michael and Dave to discuss neural net lottery tickets, computing with uncertainty and more. [Cover photo courtesy of Michael Carbin]

Zander Furnas helps Dave get a clue about political science, in theory and in practice -- from authoritarianism to democracy, and from Congressional staffer's incentives to Elizabeth Warren's plan for lobbyists, and whether there's hope for society after all. [Background image by www.GAUPERphoto.com used by permission of Zander Furnas]

Dave and Michael revisit the meaning of life (the subject of the second Computing Up conversation) in the context of politics and society and human destiny. [Photo by Jeffrey Lee on Unsplash]