The Future of Everything

Guest James Landay is an expert in human-centered artificial intelligence, a field all about optimizing technology for human and societal good. Landay says one of the most promising intersections is in education and AI, where the technology excels as a coaching and tutoring tool. His Smart Primer and Acorn apps use augmented reality and AI to engage children in outdoor, hands-on environmental science, and his GPT Coach is an AI-powered fitness planning tool. When it comes to AI and education, things are wide open and only just getting started, Landay tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your quest. You can send questions to [email protected] Reference Links:Stanford Profile: James LandaySmart PrimerConnect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / FacebookChapters:(00:00:00) IntroductionRuss Altman introduces guest James Landay, a professor of computer science at Stanford University.(00:02:04) Evolving AI ApplicationsHow large language models can replicate personal coaching experiences.(00:06:44) Role of Health Experts in AIIntegrating insights from medical professionals into AI coaching systems.(00:10:21) Personalization in AI CoachingHow AI coaches can adapt personalities and avatars to cater to user preferences.(00:12:51) Group Dynamics in AI CoachingPros and cons of adding social features and group support to AI coaching systems.(00:14:08) Ambient Awareness in TechnologyAmbient awareness and how it enhances user engagement without active attention.(00:17:44) Using AI in Elementary EducationNarrative-driven tutoring systems to inspire kids' learning and creativity.(00:22:59) Encouraging Student Writing with AIUsing LLMs to  motivate students to write  through personalized feedback.(00:23:52) Scaling AI Educational ToolsThe ACORN project and creating dynamic, scalable learning experiences.(00:27:58) Human-Centered AIThe concept of human-centered AI and its focus on designing for society.(00:30:34) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Climate change authority Noah Diffenbaugh says that the effects of climate change are no longer theoretical but apparent in everyday, tangible ways. Still, he says, it is not too late to better understand the effects of climate change, to mitigate them through reductions in greenhouse gas emissions and other measures, and to adapt how we live in the face of a warmer planet. Society is falling behind in its ability to deal with increasingly extreme climate events but solutions are not out of reach, Diffenbaugh tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your quest. You can send questions to [email protected] Reference Links:Stanford Profile: Noah DiffenbaughConnect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / FacebookChapters:(00:00:00) IntroductionRuss Altman introduces guest Noah Diffenbaugh, a professor of Earth System Science at Stanford University.(00:02:34) Global Impact of Climate ChangeThe major areas where climate change is having the greatest impact globally.(00:03:27) Climate Phenomena and HumansConnecting climate science with localized human impacts(00:06:16) Understanding Climate ForcingThe concept of "climate forcing" and its significance in Noah’s research.(00:10:00) Geoengineering and Climate InterventionsThe potential and risks of intentional climate interventions.(00:21:18) Adaptation to Climate ChangeHow humans are adapting to climate change and why we might be falling behind.(00:25:19) Increase in Extreme EventsWhy extreme climate events are becoming exponentially more frequent and severe.(00:28:34) AI in Climate ResearchHow AI is revolutionizing climate research by enabling predictive capabilities.(00:32:26) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Climate modeler Aditi Sheshadri says that while weather forecasting and climate projection are based on similar science, they are very different disciplines. Forecasting is about looking at next week, while projection is about looking at the next century. Sheshadri tells host Russ Altman how new data and techniques, like low-cost high-altitude balloons and AI, are reshaping the future of climate projection on this episode of Stanford Engineering’s The Future of Everything podcast.Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your quest. You can send questions to [email protected] Reference Links:Stanford Profile: Aditi SheshadriConnect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / FacebookChapters:(00:00:00) IntroductionRuss Altman introduces guest Aditi Sheshadri, a professor of Earth systems science at Stanford University.(00:02:58) Climate Projection vs. Weather ForecastingThe differences between climate projection and weather forecasting.(00:04:58) The Window of ChaosThe concept of the "window of chaos" in climate modeling.(00:06:11) Scale of Climate ModelsThe limitations and scale of climate model boxes.(00:08:19) Computational ConstraintsComputational limitations on grid size and time steps in climate modeling.(00:10:56) Parameters in Climate ModelingEssential parameters measured, such as density, temperature, and water vapor.(00:12:18) Oceans in Climate ModelsThe role of oceans in climate modeling and their integration into projections.(00:14:35) Atmospheric Gravity WavesAtmospheric gravity waves and their impact on weather patterns.(00:18:51) Polar Vortex and CyclonesResearch on the polar vortex and on tropical cyclone frequency.(00:21:53) Climate Research and Public AwarenessCommunicating climate model findings to relevant audiences.(00:23:33) New Data SourcesHow unexpected data from a Google project aids climate research,(00:25:09) Geoengineering ConsiderationsGeoengineering and the need for thorough modeling before intervention.(00:28:19) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Halloween may be behind us in the US but here at The Future of Everything we’re not quite done with spooky season. If you’re pairing your trick-or-treat haul with some scary movies, we invite you to revisit with us a conversation Russ had with Lawrence Wein a couple years ago about the work he’s doing in forensic genetic genealogy to crack cold cases. Professor Wein shares how he’s using math to catch criminals through traces of their DNA. It’s both haunting and hopeful, and we hope you’ll take another listen.Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your quest. You can send questions to [email protected] Reference Links:Stanford Profile: Lawrence M. WeinLawrence’s Paper: Analysis Of The Genealogy Process In Forensic Genetic GenealogyConnect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / FacebookChapters:(00:00:00) IntroductionRuss Altman introduces guest Lawrence Wein, professor of management science at Stanford University.(00:02:18) Forensic Genealogy ExplainedForensic genetic genealogy and its impact on solving unsolved crimes.(00:04:31) Third-Party Databases in GenealogyInsight into databases that allow law enforcement to search for criminal suspects.(00:08:23) Math Models in GenealogyUsing mathematical models to streamline genealogy work.(00:11:31) Components of the Genealogy AlgorithmThe algorithm's methods, including ascending and descending family trees.(00:14:12) Algorithm Efficiency and ComparisonComparing the new algorithm's effectiveness to traditional genealogy strategies.(00:16:53) Algorithm in PracticeRole of human input alongside the mathematical algorithm in genealogy cases.(00:20:42) Role of GenealogistsGenealogists’ insights on balancing human skill and mathematical algorithms.(00:22:45) DNA Databases and EthicsThe ethical and privacy concerns related to using genetic data.(00:27:01) Background and Interest in Forensic GenealogyLawrence’s journey from operations management to forensic genealogy.(00:30:16) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook