The Future of Everything

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 or Twitter/XConnect with School of Engineering >>> Twitter/XChapters:(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 or Twitter/XConnect with School of Engineering >>> Twitter/X

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 or Twitter/XConnect with School of Engineering >>> Twitter/XChapters:(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 or Twitter/XConnect with School of Engineering >>> Twitter/X

Returning guest Marco Pavone is an expert in autonomous robotic systems, such as self-driving cars and autonomous space robots. He says that there have been major advances since his last appearance on the show seven years ago, mostly driven by leaps in artificial intelligence. He tells host Russ Altman all about the challenges and progress of autonomy on Earth and in space in 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:  Marco PavoneCenter for AEroSpace Autonomy Research (CAESAR)Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads or Twitter/XConnect with School of Engineering >>> Twitter/XChapters:(00:00:00) IntroductionRuss Altman introduces guest Marco Pavone, a professor of aeronautics and astronautics at Stanford.(00:02:37) Autonomous Systems in Everyday LifeAdvancements in the real-world applications of autonomous systems.(00:03:51) Evolution of Self-Driving TechnologiesThe shift from fully autonomous cars to advanced driver assistance systems.(00:06:36) Public Perception of Autonomous VehiclesHow people react to and accept autonomous vehicles in everyday life.(00:07:49) AI’s and Autonomous DrivingThe impact of AI advancements on autonomous driving performance.(00:09:52) Simulating Edge Cases for SafetyUsing AI to simulate rare driving events to improve safety and training.(00:12:04) Autonomous Vehicle CommunicationCommunication challenges between autonomous vehicles and infrastructure.(00:15:24) Risk-Averse Planning in Autonomous SystemsHow risk-averse planning ensures safety in autonomous vehicles.(00:18:43) Autonomous Systems in SpaceThe role of autonomous robots in space exploration and lunar missions.(00:22:47) Space Debris and Collision AvoidanceThe challenges of space debris and collision avoidance with autonomous systems.(00:24:39) Distributed Autonomous Systems for SpaceUsing distributed autonomous systems in space missions for better coordination.(00:28:40) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads or Twitter/XConnect with School of Engineering >>> Twitter/X

Physicist Matthias Kling studies photons and the things science can do with ultrafast pulses of X-rays. These pulses last just attoseconds – a billionth of a billionth of a second, Kling says. He uses them to create slo-mo “movies” of electrons moving through materials like those used in batteries and solar cells. The gained knowledge could reshape fields like materials science, ultrafast and quantum computers, AI, and medical diagnostics, Kling 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:SStanford Profile: Matthias KlingMatthias’ Lab: SLAC National Accelerator LaboratoryConnect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads or Twitter/XConnect with School of Engineering >>> Twitter/XChapters:(00:00:00) IntroductionRuss Altman introduces guest Matthias Kling, a professor of photon science and applied physics at Stanford University.(00:02:52) Ultrafast Electronics OverviewThe technologies enabling ultrafast photonics and electronic advancements.(00:05:32) Attosecond Science ApplicationsCapturing electron and molecular movements with attosecond pulses.(00:09:31) Photoelectric Effect InsightsAttosecond science’s impact on understanding the photoelectric effect and quantum mechanics.(00:13:27) Real-Time Molecular MeasurementsUsing light waves to capture images of molecules at room temperature.(00:19:32) Future of Ultrafast ElectronicsHow attosecond light pulses could revolutionize computing with petahertz speed.(00:23:28) Energy-Efficient Quantum ComputingPotential for room-temperature quantum computers using light wave electronics.(00:26:33) AI and Machine Learning in ScienceAI's role in optimizing research and data collection in ultrafast electronics.(00:28:51) Real-Time AI Data AnalysisMachine learning enables real-time analysis of massive experimental data.(00:32:15) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads or Twitter/XConnect with School of Engineering >>> Twitter/X