Podcast appearances and mentions of michael littman

We're continuing our countdown to the 2024 INFORMS Annual Meeting, in Seattle, Washington, October 20-23, when more than 6,000 INFORMS members, students, prospective employers and employees, and academic and industry experts will share the ways O.R. and analytics are fueling Smarter Decisions for a Better World.  In this episode, I'm joined by Cynthia Rudin, with Duke University, Charles Isbell, with the University of Wisconsin, and Michel Littman, with the National Science Foundation, for a preview of their plenary session, “Making the Most of this AI Moment: A Fireside Chat.” Charles serves as the provost and vice chancellor for academic affairs with the UW-Madison, and Michael is the division director for information and intelligent systems at NSF.  Cynthia, the session moderator, is a longtime INFORMS member and the Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science at Duke University, as well as heads the Interpretable Machine Learning Lab.

EPISODE 1787: In this KEEN ON show, Andrew talks to Michael L. Littman, author of CODE TO JOY, about why - in our age of AI - everyone should learn a little computer programmingMichael L. Littman, Ph.D. is a University Professor of Computer Science at Brown University and Division Director of Information and Intelligent Systems at the National Science Foundation. He studies machine learning and decision-making under uncertainty and has earned multiple awards for his teaching and his research. Littman has chaired major conferences in artificial intelligence and machine learning and is a Fellow of both Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery. He was selected by the American Association for the Advancement of Science as a Leadership Fellow for Public Engagement with Science in Artificial Intelligence, has a popular youtube channel and appeared in a national TV commercial in 2016.Named as one of the "100 most connected men" by GQ magazine, Andrew Keen is amongst the world's best known broadcasters and commentators. In addition to presenting KEEN ON, he is the host of the long-running How To Fix Democracy show. He is also the author of four prescient books about digital technology: CULT OF THE AMATEUR, DIGITAL VERTIGO, THE INTERNET IS NOT THE ANSWER and HOW TO FIX THE FUTURE. Andrew lives in San Francisco, is married to Cassandra Knight, Google's VP of Litigation & Discovery, and has two grown children.

Most Intro to Machine Learning courses cover supervised learning and unsupervised learning. But did you know there is also a third type of machine learning, which was used in the development of ChatGPT and is likely to become increasingly important in the not too distant future?In this episode, Prof Michael Littman joins Dr Genevieve Hayes to discuss reinforcement learning – the other type of machine learning – as well as his new book, Code to Joy: Why Everyone Should Learn a Little Programming.Guest BioProf. Michael Littman is an award-winning Professor of Computer Science at Brown University, specialising in reinforcement learning; is co-creator of the Machine Learning and Reinforcement Learning courses offered as part of Georgia Tech's Online Master of Science in Computer Science (OMSCS) program; and is currently serving as Division Director for Information and Intelligent Systems at the (US) National Science Foundation. He is also the author of Code to Joy: Why Everyone Should Learn a Little Programming.Talking PointsWhat is reinforcement learning and why has it traditionally been seen as “the other type of machine learning”?Current and future applications of reinforcement learning.How reinforcement learning is being used to create business value.Michael's new book, Code to Joy and why everyone should learn to code.How non-programmers can get started with coding and what it would mean for the world if more people did code.LinksMichael's WebsiteFollow Michael on TwitterComputing Up PodcastMachine Learning A Cappella (Thriller Parody)Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

Genevieve Hayes Consulting Episode 23: Reinforcement Learning – The Other Type of Machine Learning Most Intro to Machine Learning courses cover supervised learning and unsupervised learning. But did you know there is also a third type of machine learning, which was used in the development of ChatGPT and is likely to become increasingly important in the not too distant future?In this episode, Prof Michael Littman joins Dr Genevieve Hayes to discuss reinforcement learning – the other type of machine learning – as well as his new book, Code to Joy: Why Everyone Should Learn a Little Programming. Guest Bio Prof. Michael Littman is an award-winning Professor of Computer Science at Brown University, specialising in reinforcement learning; is co-creator of the Machine Learning and Reinforcement Learning courses offered as part of Georgia Tech's Online Master of Science in Computer Science (OMSCS) program; and is currently serving as Division Director for Information and Intelligent Systems at the (US) National Science Foundation. He is also the author of Code to Joy: Why Everyone Should Learn a Little Programming. Talking Points What is reinforcement learning and why has it traditionally been seen as “the other type of machine learning”?Current and future applications of reinforcement learning.How reinforcement learning is being used to create business value.Michael’s new book, Code to Joy and why everyone should learn to code.How non-programmers can get started with coding and what it would mean for the world if more people did code. Links Michael’s WebsiteFollow Michael on TwitterComputing Up PodcastMachine Learning A Cappella (Thriller Parody) Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE The post Episode 23: Reinforcement Learning – The Other Type of Machine Learning first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.

The uses and abuses of ChatGBT artificial intelligence language model have taken the collective imagination by storm. Apocalyptic predictions of the singularity, when technology becomes uncontrollable and irreversible, frighten us as we imagine a future where human intelligence is irrelevant. Prof. Michael Littman joins us to contextualize the advancement of artificial intelligence and debunk the paranoid rhetoric littering the public discourse. Michael has made groundbreaking research contributions enabling machines to learn from their experiences, assess the environment, make decisions, and improve their actions over time in real-world applications. His later work expanded into multi-agent systems, investigating how several AI entities can learn to cooperate, compete, or coexist in shared environments. Picture a team of robots in a factory, each with different tasks. The challenge here isn't just for each robot to do its job effectively but also to collaborate with the others, avoid collisions, and adapt to changes in real time. Emerging concepts of 'intelligence' in artificial intelligence aren't about building machines that can perform tasks faster and more accurately than humans; it is about building machines that can think, learn, and adapt - machines that aren't just tools but collaborative partners. If we examine our resistance to this emerging technology, we might catch glimpses of our unconscious fear of regression and dependency. Observation suggests most people fall into one of two groups, those who idealize a world where they are free of demands and another where they are enslaved by superiors. When we realize the fear or fantasy of regression is not the likely outcome of artificial intelligence, we are free to imagine the innumerable creative applications of the new technology and the machines that use it. MICHAEL L. LITTMAN, PhD Michael L. Littman is University Professor of Computer Science at Brown University, where he studies machine learning and decision-making under uncertainty. He has earned multiple university-level awards for teaching and his research has been recognized with three best-paper awards and three influential paper awards. Littman is a Fellow of the Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery. He is currently serving as Division Director for Information and Intelligent Systems at the National Science Foundation. His book "Code to Joy: Why Everyone Should Learn a Little Programming" (MIT Press) will be released October 3rd 2023. Michael's WEBSITE Order Michael's book: Code To Joy, Why Everyone Should Learn A Little Programming by Michael L. Littman, CLICK HERE TO ORDER Philadelphia Association of Jungian Analysts, ADVANCED CLINICAL PRACTICE PROGRAM: A case seminar for experienced clinicians to read, explore and apply Jung's concepts to clinical practice: CLICK HERE FOR INFORMATION BECOME A DREAM INTERPRETER: We've created DREAM SCHOOL to teach others how to work with their dreams. A vibrant community has constellated around this mission, and we think you'll love it. Check it out.  PLEASE GIVE US A HAND: Hey folks -- We need your help. So please BECOME OUR PATRON and keep This Jungian Life podcast up and running.  SHARE YOUR DREAM WITH US: SUBMIT YOUR DREAM HERE FOR A POSSIBLE PODCAST INTERPRETATION.  SUGGEST A FUTURE PODCAST TOPIC:  Share your suggestions HERE.  FOLLOW US ON SOCIAL MEDIA:  FACEBOOK, INSTAGRAM, LINKEDIN, TWITTER, YOUTUBE INTERESTED IN BECOMING A JUNGIAN ANALYST?  Enroll in the PHILADELPHIA JUNGIAN SEMINAR and start your journey to become an analyst.  YES, WE HAVE MERCH!  Shop HERE

As Chat GPT and other AI tools have garnered immense interest in the last few months, people have begun to wonder how these tools will impact higher ed: Will it represent the end of writing? Will we see a rampant rise in cheating? Or maybe these tools herald a new age of an improved quality of student work? Jeff and Michael pose these questions and more to computer science experts Charles Isbell of Georgia Institute of Technology College of Computing and Michael Littman of Brown University. This episode is made possible with sponsorship from Course Hero.

When Lexman decides to discuss the much-discussed Reformist movement, Michael Littman, a prominent critic of the movement, is the perfect guest. Although each side has its own set of beliefs and claims to superiority, Lexman and Michael find that they share a great deal of understanding and common ground. In the end, they come to a mutual recognition that reform is necessary - though they maydefine it in very different ways.

Lexman interviews Michael Littman, a self-taught aerialist who uses his epicycle to perform aerials and hydrolysis displays.

Michael Littman Co-founder Hapa Kauai & Hapa PDX ~ Culinary Treasure Podcast Episode 106  The Culinary Treasure Podcast: Chefs, Winemakers, Distillers, Bakers, and More – Culinary Stories You Will Love! In this episode of the Culinary Treasure Podcast our Host Steven Shomler visits with Michael Littman Co-founder Hapa Kauai & Hapa PDX. Go to the Culinary Treasure Podcast Website to the Michael Littman Podcast episode article to see more than 40 photos related to this podcast episode - https://www.culinarytreasurepodcast.com/ Other Culinary Treasure Network Content Mentioned in This Episode:  Chef Sarah Littman Co-founder Hapa Kauai & Hapa PDX ~ Culinary Treasure Podcast Episode 105 - https://www.culinarytreasurepodcast.com/chef-sarah-littman-co-founder-hapa-kauai-hapa-pdx/   Bob Gunter the President and CEO of Koloa Rum Co. ~ Culinary Treasure Podcast Episode 104 - https://www.culinarytreasurepodcast.com/bob-gunter-the-president-and-ceo-of-koloa-rum-co-culinary-treasure-podcast-episode-104/   Subscribe to The Culinary Treasure Podcast  Apple Podcasts https://podcasts.apple.com/us/podcast/the-portland-culinary-podcast/id1144423445 iHeartRadio https://www.iheart.com/podcast/256-the-portland-culinary-podc-30948747/ Spotify https://open.spotify.com/show/7auFMA0frzpAJxSk6LFpax Google Podcasts https://podcasts.google.com/feed/aHR0cDovL3BvcnRsYW5kY3VsaW5hcnlwb2RjYXN0LmxpYnN5bi5jb20vcnNz Go to www.culinarytreasurepodcast.com  to hear the other 105 episodes of the Culinary Treasure Podcast.   Kauai Treasure To see all of the Culinary Treasure Network's Kauai content – Podcasts, This is Travel Treasure articles, and This is Culinary Treasure articles go to: www.KauaiTreasure.com   Follow Michael Littman Instagram – https://www.instagram.com/mlifeman/ Follow Hapa Kauai Website – https://www.hapakauai.com/ Facebook – https://www.facebook.com/HapaKauai Instagram – https://www.instagram.com/hapakauai/ YouTube – https://www.youtube.com/channel/UCA-zUuYpU_KQpVemaheeWEA    Follow Hapa PDX  Website – https://www.hapapdx.us/ Facebook – https://www.facebook.com/Hapapdx/ Instagram – https://www.instagram.com/hapapdx/   The Culinary Treasure Podcast 411 The Culinary Treasure Podcast is brought to you by The Culinary Treasure Network, and this episode was recorded at the Grand Hyatt Kauai Resort & Spa located on the Hawaiian Island of Kauai. Steven Shomler is the Host and Creator of the Culinary Treasure Podcast. You Can Listen to the Culinary Treasure Podcast on the Culinary Treasure Podcast website itself, on Apple Podcasts, iHeartRadio, Spotify, Google Podcasts, Amazon Music / Amazon Podcasts, The North Station Media Network, Stitcher, TuneIn Radio, Audacy, Deezer, Gaana, JioSaavn, Resso, YouTube (audio only), the Samsung Podcast app, and many other podcasts outlets. Many thanks to Ken Wilson a true Media Maestro for his excellent sound engineering and editing!  The Culinary Treasure Podcast: Chefs, Winemakers, Distillers, Bakers, and More – Culinary Stories You Will Love!   Follow The Culinary Treasure Podcast Website  www.culinarytreasurepodcast.com  Facebook  https://www.facebook.com/CulinaryTreasurePodcast Instagram  https://www.instagram.com/culinarytreasurepodcast/  Apple Podcasts https://podcasts.apple.com/us/podcast/the-portland-culinary-podcast/id1144423445 iHeartRadio https://www.iheart.com/podcast/256-the-portland-culinary-podc-30948747/ Spotify https://open.spotify.com/show/7auFMA0frzpAJxSk6LFpax Google Podcasts https://podcasts.google.com/feed/aHR0cDovL3BvcnRsYW5kY3VsaW5hcnlwb2RjYXN0LmxpYnN5bi5jb20vcnNz YouTube (audio only – no video) – https://www.youtube.com/channel/UCYFs_8AxDxp5QOLe0gV22yg   #CulinaryTreasurePodcast          

Michael Littman, MA, CISSP is a retired corpsman and Special Forces veteran. He's the author of "When Things Bite Back: Overcoming the Unseen Threats That Threaten Our Safety and Freedom" and a regular contributor to TheDailyBeast.com. In this episode, Lexman interviews Littman about his book, self-command, and the lessons he learned while serving in the military.

Lexman interviews Michael Littman about his new book, forsythias and entablatures. They discuss the difference between these two types of architecture, how to identify them, and give some tips on how to incorporate them into your own home.

Lexman interviews Michael Littman, an associate at law firm Getas LLC about the Asti regulations and how they will impact consumers. They discuss what divulgences may need to be rolled out in order for businesses to comply, as well as the potential for businesses to start prohibiting their consumers from taking certain medications.

Michael Littman, a professor at UC Riverside, discusses his research on the effects of pests and rinses on plant mineralization.

Michael Littman, professor of music at the University of Chicago, talks about his new study, "Settees, Homings, and Solfeggios: Expiations in Seventeenth-Century Italian Theory," which examines how Italian theorists invoked the practice of settee-playing to improve their understanding of theory.

Lexman Artificial interviews Michael Littman, an expert on the medieval art of woodworking. They discuss the historically significant lucernes, their unique construction, and the ways in which they were used. Then, the podcast explores the mysteries of mortices and their use in self-creation.

This program was recorded at a Veritas Forum event on Brown in 2017. The original title was "What does it mean to be human?" and featured Rosalind Picard and Michael Littman. If you enjoyed this episode, please rate, review, and subscribe. And, if you're interested in more content from Veritas, check out our Beyond the Forum podcast. Visit veritas.org to learn more about the mission of the Veritas Forum and find more resources to explore the ideas that shape our lives.

Reinforcement Learning Godfather Professor Michael Littman

In this episode of the podcast we shake things up! Neil is on the guest side of the table with his partner Rabbi Laura Janner-Klausner to discuss their upcoming project Gods and Robots. Katherine is joined on the host side by friend of the show professor Michael Littman.  See omnystudio.com/listener for privacy information.

Hosts: Larry Bernstein and Mitch Feinman. Guests include Michael Littman, Charles Isbell, Seyed Sajjadi, Lawrence Friedman, and Benjamin Friedman

Charles Isbell is the Dean of the College of Computing at Georgia Tech. Michael Littman is a computer scientist at Brown University. Please support this podcast by checking out our sponsors: – Athletic Greens: https://athleticgreens.com/lex and use code LEX to get 1 month of fish oil – Eight Sleep: https://www.eightsleep.com/lex and use code LEX to get special savings – MasterClass: https://masterclass.com/lex to get 2 for price of 1 – Cash App: https://cash.app/ and use code LexPodcast to get $10 EPISODE LINKS: Charles’s Twitter: https://twitter.com/isbellHFh Charles’s Website: https://www.cc.gatech.edu/~isbell/ Michael’s Twitter: https://twitter.com/mlittmancs Michael’s Website: https://www.littmania.com/ Michael’s YouTube: https://www.youtube.com/user/mlittman PODCAST INFO: Podcast website:

Michael Littman is a computer scientist at Brown University. Please support this podcast by checking out our sponsors: – SimpliSafe: https://simplisafe.com/lex and use code LEX to get a free security camera – ExpressVPN: https://expressvpn.com/lexpod and use code LexPod to get 3 months free – MasterClass: https://masterclass.com/lex to get 2 for price of 1 – BetterHelp: https://betterhelp.com/lex to get 10% off EPISODE LINKS: Michael’s Twitter: https://twitter.com/mlittmancs Michael’s Website: https://www.littmania.com/ Michael’s YouTube: https://www.youtube.com/user/mlittman PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: – Check out the sponsors above, it’s

In episode seven of season six we talk with Michael Littman about his work in reinforcement learning, on scientific communication, and in the classroom. 

ACM Fellow Professor Michael L Littman enlightens us on Human feedback in RL, his Udacity courses, Theory of Mind, organizing the RLDM Conference, RL past and present, Hollywood cameos, and much more!

In episode eighteen of season five we hear Michael Littman's talk A Cooperative Path to Artificial Intelligence

What do the robots know and when did they know it? But more importantly, how did they learn it? Technology is improving and advancing at a blistering pace and the implications for AI, advances in robotics, and more, depend heavily upon learning. Michael Littman, Professor of Computer Science at Brown University will delve into a broad discussion of the multiple types of learning as they relate to multi-layered neural networks. Professor Littman provides examples of the various kinds of learning that are available and how they are suited to various tasks. The Brown University professor discusses machine learning, which applies to the creation of systems that use data and AI to improve targeted areas of functioning. We'll also gain insight into supervised learning, which is learning based on feedback, essentially correcting a response via given feedback. This process can provide advanced teaching in an AI environment via various inputs such as layers, such that the learning system can match input to the desired output. For example, as we consider a particular image, individual layers will match data until eventually, in aggregate, that image can be classified and thus the input leads to a conclusion of what that image actually is. Further, Mr. Littman discusses another specialized type of learning that can be applied known as reinforcement learning, which would simply allow an AI network to make selections on its own, then at the end, it would be given reinforcement. Reinforcement would inform the network as to whether it has been successful or whether it has failed, which would allow the network to learn from either and advance. Additionally, Mr. Littman will explain how algorithms can map out narrow pieces of multi-dimensional space within an entire network to gain clues about what could be improved. With technological advances that allow for more data to be gathered, along with accelerated computer processing speeds and better algorithms, networks can be set up and configured to produce improved results for training data. Linking the future of learning to our cultural past, Littman provides an interesting overview of how various types of network learning were applied to early Atari video games. The learning allowed for a network to equal or surpass human scores. But this research certainly goes well beyond teaching a network to win an old school video game; the applications for this learning are directly applicable to advanced robotics. With applied training and learning, extremely advanced AI is more than just a researcher's dream in some tech laboratory—it's coming.

Georgia Tech University Professor Charles Isbell, Brown University Professor Michael Littman and University of Texas Professor Peter Stone discuss and debate the value of human/AI interaction. "A lot of people have been working for many, many, many, many, many years on the problem of leveraging humans and leveraging human behavior to make machine learning better. We talk about it all the time- humans in the loop. But it's always fun to take a moment, step back and ask whether all of your assumptions are actually valid and real- and here the assumption is that humans actually can help us but it's not clear that that's true."

The line between science fiction and reality grows increasingly thin as artificial intelligence (AI) becomes more prominent. While some fear an impending robot apocalypse, others wonder what this new technology means for everyday life. At a recent Veritas Forum at Brown University, Rosalind Picard (MIT) and Michael Littman (Brown) discussed the implications of AI for our understanding of what it means to be human.

Astrophysicist, StarTalk host, and self-proclaimed sci-fi geek Neil deGrasse Tyson hosts a round table talking about the science behind the science-fiction in GE Podcast Theater's LifeAfter. Joining him are computer scientist and humanity-centered robotics expert, Michael Littman; leading software research expert Colin Parris; and the show's writer, Mac Rogers. Let the tech geeking begin.

Astrophysicist, StarTalk host, and self-proclaimed sci-fi geek Neil deGrasse Tyson hosts a round table talking about the science behind the science-fiction in GE Podcast Theater’s LifeAfter. Joining him are computer scientist and humanity-centered robotics expert, Michael Littman; leading software research expert Colin Parris; and the show’s writer, Mac Rogers. Let the tech geeking begin.

My guest this time is Charles Isbell, Jr., Professor and Senior Associate Dean in the College of Computing at Georgia Institute of Technology. Charles and I go back a bit… in fact he’s the first AI researcher I ever met. His research focus is what he calls “interactive artificial intelligence,” a discipline of AI focused specifically on the interactions between AIs and humans. We explore what this means and some of the interesting research results in this field. One part of this discussion I found particularly interesting was the intersection between his AI research and marketing and behavioral economics. Beyond his research, Charles is well known in the ML and AI worlds for his popular Machine Learning course sequence on Udacity, which he teaches with Brown University professor Michael Littman, and for the Online Master’s of Science in Computer Science program that he helped launch at Georgia Tech. We also spend quite a bit of time talking about what’s really missing in machine learning education and how to make it more accessible. The notes for this show can be found at twimlai.com/talk/4.

In episode three of season two Ryan walks us through the Alpha Go results and takes a lister question about using Gaussian processes for classifications. Plus we talk with Michael Littman of Brown University about his work, robots, and making music videos. Also not to be missed, Michael’s appearance in the recent Turbotax ad!