Explorez tous les épisodes du podcast Stanford Online: University Courses & Lectures

Lecture 18 — Model-free Reinforcement Learning: Policy OptimizationRead the companion textbook, Principles of Robot Autonomy, free online: https://porabook.com To learn more about enrolling in AA203 Optimal and Learning-Based Control, visit: https://online.stanford.edu/courses/aa203-optimal-and-learning-based-control Follow along with the course schedule and syllabus: https://stanfordasl.github.io/aa203/sp2526/ Lecture slides: https://stanfordasl.github.io/aa203/sp2526/pdfs/lecture/lecture_4.pdf Speaker: Dr. Daniele GammelliBio: Dr. Daniele Gammelli is the Research Director of the Machine Intelligence for Robot Autonomy Laboratory at the Italian Institute of Artificial Intelligence (AI4I), and a Researcher in the Department of Aeronautics and Astronautics at Stanford University. Since 2022, he has been a Research Fellow at the Center for Aerospace Autonomy Research (CAESAR) at Stanford and, until 2025, at the Center for Automotive Research at Stanford (CARS). He received his Ph.D. in Machine Learning and Mathematical Optimization from the Technical University of Denmark (DTU) in 2022, where his doctoral thesis was nominated for the DTU Best Thesis of the Year Award and the DTU Young Researcher Award. Dr. Gammelli’s research focuses on developing the algorithmic foundations and system-level methodologies that enable AI-powered autonomous systems to operate safely, efficiently, and reliably in high-stakes environments, with an emphasis on aerospace autonomy and next-generation mobility systems.Uploaded 13-08-26Instructors: Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIADr. Daniele Gammelli, Research Director at the Italian Institute of Artificial Intelligence (AI4I), Researcher at the Department of Aeronautics and Astronautics, Stanford UniversityFull playlist: https://www.youtube.com/playlist?list=PLa9dmHsLK9dg#StanfordOnline #OptimalControl #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

http://www.techamerica.org/stanford-executive-institute - The Stanford Executive Institute has a proven track record of teaching tools and approaches to prepare the technology industry's senior leadership to face the sector's unique set of challenges. In this video, Tom Byers, professor in Stanford's Management Science and Engineering Dept and Academic Director of The Stanford Executive Institute, discusses how this program gives you the tools to be a leader in your enterprise.Uploaded 23-03-11 Learn more about your ad choices. Visit megaphone.fm/adchoices

Peter DeMarzo is the Mizuho Financial Group Professor of Finance, and currently Senior Associate Dean for Academic Affairs, at the Stanford Graduate School of Business. He earned his BA in cognitive science and applied mathematics from the University of California, San Diego, and his MS in operations research and PhD in economics from Stanford University.Uploaded 17-07-13In addition to his experience at the Stanford Graduate School of Business, he has taught at the Haas School of Business and the Kellogg Graduate School of Management and was a visiting scholar at the Hoover Institution. He is a member of the National Bureau of Economic Research and past president of the Western Finance Association. His research is in the area of corporate finance, asset securitization, financial contracting, and market regulation. Recent work has examined issues of the optimal design of securities, optimal compensation mechanisms, regulation of insider trading and broker-dealers, bank capital regulation, and the influence of information asymmetries on corporate disclosures and investment.Peter's research has received awards including the Barclays Global Investors/Michael Brennan best paper award from the Review of Financial Studies, and the Western Finance Association Corporate Finance Award. He won the Sloan Teaching Excellence award in 2004 and 2006, and the Cheit Outstanding Teaching Award in 1998. He is co-author of a leading corporate finance textbook, and currently teaches MBA and PhD courses in Corporate Finance and Financial Modeling.Peter teaches Financing Innovation: Valuing Projects and Firms, an online course in the Stanford Innovation and Entrepreneurship professional certificate - http://create.stanford.edu/courses/financing-innovation.php Learn more about your ad choices. Visit megaphone.fm/adchoices

- Explore these concepts and more in the UI/UX Design for AI Products course: https://bit.ly/stf-aid-webinar- Learn how to build intelligent AI agents: https://online.stanford.edu/programs/agentic-ai- Browse all Stanford Online AI courses: https://online.stanford.edu/artificial-intelligence/courses-and-programsUploaded 29-09-26What happens when AI agents are designed to simulate human behavior?In this Stanford Online webinar delivered in collaboration with Global Alumni, Professor Michael Bernstein explores the emerging possibilities of AI agents and their ability to model, interact with, and simulate aspects of human behavior. The session offers a closer look at how advances in artificial intelligence are changing the way we think about human-AI interaction, simulation, and the design of intelligent systems.Drawing on Stanford research in human-AI interaction and social computing, Professor Bernstein examines the opportunities and challenges that arise as AI systems become increasingly capable of representing human behaviors and interactions. Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/aiFor information on the graduate course, CS229 Machine Learning, including the syllabus and course materials, visit the course's website: https://cs229.stanford.edu/index.html-spr26Uploaded 29-07-26Teaching Team:Chris Ré, Professor of Computer ScienceTengyu Ma, Assistant Professor of Computer Science Learn more about your ad choices. Visit megaphone.fm/adchoices

Uploaded 30-09-26 Learn more about your ad choices. Visit megaphone.fm/adchoices

The game is changing. Products from the West used to be inherently desirable and localization was adequate to capture market share, but these days are gone and organizations are increasingly designing for a new global landscape with different requirements and expectations. In this webinar, you'll learn about models for global design and some of the key challenges and opportunities in this new and exciting space.Uploaded 08-04-11Learn more about professional programs offered by the Stanford Center for Professional Development by visiting http://scpd.stanford.edu/programs/professional-certificates. Learn more about your ad choices. Visit megaphone.fm/adchoices

Lecture 2 — Optimization TheoryRead the companion textbook, Principles of Robot Autonomy, free online: https://porabook.com To learn more about enrolling in AA203 Optimal and Learning-Based Control, visit: https://online.stanford.edu/courses/aa203-optimal-and-learning-based-control Follow along with the course schedule and syllabus: https://stanfordasl.github.io/aa203/sp2526/ Lecture slides: https://stanfordasl.github.io/aa203/sp2526/pdfs/lecture/lecture_2.pdf Speaker: Prof. Marco PavoneBio: Dr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University and a Senior Director of Autonomous Vehicle Research at NVIDIA. Prior to joining Stanford, he was a Research Technologist in the Robotics Section at NASA’s Jet Propulsion Laboratory. Dr. Pavone received his Ph.D. in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His research focuses on the analysis, design, and control of autonomous systems, with particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He has been recognized with numerous awards, including the Presidential Early Career Award for Scientists and Engineers from President Barack Obama, the Office of Naval Research Young Investigator Award, the NSF CAREER Award, the NASA Early Career Faculty Award, the IEEE Kiyo Tomiyasu Award, the CSS Award for Technical Excellence in Aerospace Control, and the Early-Career Spotlight Award from the Robotics Science and Systems Foundation.Uploaded 11-08-26Instructors: Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIADr. Daniele Gammelli, Research Director at the Italian Institute of Artificial Intelligence (AI4I), Researcher at the Department of Aeronautics and Astronautics, Stanford UniversityFull playlist: https://www.youtube.com/playlist?list=PLa9dmHsLK9dg#StanfordOnline #OptimalControl #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

http://scpd.stanford.edu/innovation-and-entrepreneurship/Perry Klebahn is an entrepreneur to the core. He received his Masters from Stanford in the product design program in 1991 and has taught there periodically since 1996. He left Stanford with his degree and his design project -- a snowshoe. He turned his project into a business, creating the Atlas Snowshoe Company. His experience taught him several things: you can't do anything significant on your own, you need a team; and engineering something is not nearly as much fun as marketing what you have engineered. In 2000, Perry sold his snowshoe business and moved to Southern California to run sales and marketing for Patagonia, an outdoor clothing brand. There, he got a chance to market on a global scale, learning to balance the need to drive sales while building a brand with important commitments and a sustainability message. In 2007 he took on a new challenge at Timbuk2, the original bike messenger bag company. As CEO of the San Francisco-based company, Perry focused on delivering custom products and an innovative customer experience. He implemented many techniques used at the d.school at Timbuk2. A founding faculty member of the d.school, Perry teaches classes including: Launchpad, Design Garage, d.Health, and d.leadership. He runs the executive programs for the d.school.Uploaded 27-09-12Professor Klebahn teaches in the Stanford Innovation and Entrepreneurship professional certificate program. This certificate delivers essential skills and effective strategies for working in and managing innovative organizations - and for starting new ones. Designed to engage and inspire, be prepared to get out of your chair and use your whole brain, because creativity and innovation take practice. A joint offering of the Stanford Center for Professional Development at the School of Engineering and the Stanford Graduate School of Business. Learn more: http://scpd.stanford.edu/innovation-and-entrepreneurship/Apply now: http://bit.ly/SoKSVl Learn more about your ad choices. Visit megaphone.fm/adchoices

- Explore these concepts in the AI-Powered Product Innovation course: https://bit.ly/pin-stf-webinar- Learn how to build intelligent AI agents: https://online.stanford.edu/programs/agentic-ai- Browse all Stanford Online AI courses: https://online.stanford.edu/artificial-intelligence/courses-and-programsUploaded 30-09-26Artificial intelligence is transforming how organizations approach problem-solving, decision-making, and innovation—but knowing where AI can create reliable value is just as important as knowing where it cannot.In this Stanford Online webinar delivered in collaboration with Global Alumni, Professor Michael Bernstein explores the practical realities of AI adoption and the role of human judgment in an increasingly AI-enabled workplace. The session examines how to distinguish between problems AI can solve reliably and those that continue to require human expertise, judgment, and oversight.Drawing on research and practical frameworks for human-AI interaction, Professor Bernstein explores how leaders and professionals can evaluate AI opportunities more thoughtfully, assess potential risks, and determine where AI can genuinely augment human capabilities. Learn more about your ad choices. Visit megaphone.fm/adchoices

Donna co-teaches Global Entrepreneurial Marketing at Stanford in the School of Engineering and to entrepreneurial executives worldwide. She has recently taught groups of entrepreneurs from France, Poland, Denmark, Finland, Chile, Singapore and other parts of Asia. She also is running her third startup. Yiftee is about Microgifts - a simple concept integrating merchants, social media and mobile. Now you can give your friends a real latte, beer or cupcake to say Happy Birthday, thanks or just because. Friends stop by the merchants and pick them up, driving traffic and repeat business. Donna uses her 25 yrs of hands-on entrepreneurship to bring her lessons to life, often driving home concepts by coaching students in their own new businesses.Uploaded 24-07-12Prior to Yiftee, Donna was CEO of Big Tent Design, a fast-growth Internet company that provides a free web software platform for groups. BigTent is now a subsidiary of Federated Media, and continues to help community groups such as parenting clubs stay organized and vibrant online and off with over a million "chief household officers" using it on a regular basis. Donna joined Big Tent from Mohr, Davidow Ventures (MDV) where she was a Partner for almost nine years, serving as VP Marketing in sixteen MDV-funded start-ups. Prior to MDV, Donna was VP Marketing at Clarify Inc., a CRM pioneer that she helped establish, grow and take public. Her career began at Sun Microsystems in product management.Enroll today in Global Entrepreneurial Marketing: http://scpd.stanford.edu/search/publicCourseSearchDetails.do?method=load&courseId=12724 Learn more about your ad choices. Visit megaphone.fm/adchoices

Model-free Reinforcement Learning: Value-based MethodsRead the companion textbook, Principles of Robot Autonomy, free online: https://porabook.com To learn more about enrolling in AA203 Optimal and Learning-Based Control, visit: https://online.stanford.edu/courses/aa203-optimal-and-learning-based-control Follow along with the course schedule and syllabus: https://stanfordasl.github.io/aa203/sp2526/ Lecture slides: https://stanfordasl.github.io/aa203/sp2526/pdfs/lecture/lecture_4.pdf Speaker: Dr. Daniele GammelliBio: Dr. Daniele Gammelli is the Research Director of the Machine Intelligence for Robot Autonomy Laboratory at the Italian Institute of Artificial Intelligence (AI4I), and a Researcher in the Department of Aeronautics and Astronautics at Stanford University. Since 2022, he has been a Research Fellow at the Center for Aerospace Autonomy Research (CAESAR) at Stanford and, until 2025, at the Center for Automotive Research at Stanford (CARS). He received his Ph.D. in Machine Learning and Mathematical Optimization from the Technical University of Denmark (DTU) in 2022, where his doctoral thesis was nominated for the DTU Best Thesis of the Year Award and the DTU Young Researcher Award. Dr. Gammelli’s research focuses on developing the algorithmic foundations and system-level methodologies that enable AI-powered autonomous systems to operate safely, efficiently, and reliably in high-stakes environments, with an emphasis on aerospace autonomy and next-generation mobility systems.Uploaded 13-08-26Instructors: Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIADr. Daniele Gammelli, Research Director at the Italian Institute of Artificial Intelligence (AI4I), Researcher at the Department of Aeronautics and Astronautics, Stanford UniversityFull playlist: https://www.youtube.com/playlist?list=PLa9dmHsLK9dg#StanfordOnline #OptimalControl #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

"What Asia Entrepreneurship Means for Silicon Valley" -David Brunner- moduleQJim Nguyen- Kynded Yukai Chou- YukaiChou.comUploaded 22-07-13This lecture series presented by the US-Japan Technology Management Center and the US-Asia Technology Management Center explores patterns and challenges of entrepreneurship in Asia. A wide range of expert executive guest speakers will discuss the latest exciting new trends in entrepreneurship, start-up companies and investment in major Asian economies. Explore the culture of entrepreneurship in Asian countries and the aggressive change happening in business across this area.Learn more: http://stanford.io/16vBuLV Learn more about your ad choices. Visit megaphone.fm/adchoices

Stanford-IATA Aviation Management certificate program webinar covering five critical competencies for working in the aviation industry.Info: http://aviation.stanford.edu/Uploaded 08-04-11In today's fast-paced, global environment, all leaders of teams in air transport ranging from frontlines, new and senior managers, working in an airline, travel agency, freight forwarding company, airport, or even in a Civil aviation authority face a number of challenges. In addition to operational excellence - strategy, execution, leadership, innovation, and decision-making are five critical competencies for leaders and business managers in the aviation industry to overcome today and tomorrow air transport industry challenges. Our speakers will share why the 5 competencies are important, how they are embedded in the Stanford-IATA Aviation Management Certificate, as well as some specific success stories within the aviation industry. Learn more about your ad choices. Visit megaphone.fm/adchoices

Watch new lectures every week in this seminar series at http://bit.ly/UnxxnS The theme for Autumn 2012 is "Green Technologies in Transportation: Recent Developments from Asia." Students will learn about technology and business trends, innovations, opportunities in Asia and Japan, and implications for US firms and researchers. The course will eature distinguished speakers from industry and government.Uploaded 04-10-12Topics Include New materials, fuels, and energy storage for vehicles Automobile and aircraft design Smart grids and intelligent transportation systems Mobile mesh networksInstructorsRichard Dasher, Consulting Professor, Electrical EngineeringGraduate seminars may be viewed online at no charge. Students seeking credit for a 1-unit seminar course need to enroll in another course in order to meet the 3-credit unit enrollment requirement.Register for this seminar series today! http://bit.ly/QLrXot Learn more about your ad choices. Visit megaphone.fm/adchoices

Enroll in the full course: https://online.stanford.edu/courses/xeiet215-next-generation-energy-storage-batteries-grid-solutions?utm_medium=Video&utm_term&utm_campaign=XEIET215Previewf&utm_source=YoutubeStanford professor Yi Cui breaks down one of the leading candidates for grid storage: redox-flow batteries. Holding energy in liquids rather than solid cells could change how storage scales.Uploaded 07-10-26What you'll learn:• Why capacity is set by tank size rather than cell size• How flow batteries let energy and power scale independently• The three obstacles left: how much the liquids can carry, whether the molecules survive repeated cycling, and the cost of the membrane Learn more about your ad choices. Visit megaphone.fm/adchoices

Enrollment in the graduate course AA228 Decision Making Under Uncertainty is open now: https://stanford.io/AA228Hear about this course and learn why Associate Professor of Aeronautics and Astronautics, Mykel Kochenderfer, loves it. Discover what you'll learn and how it will impact your decision-making process.Uploaded 28-07-26The Decision Making Under Uncertainty graduate course is designed to increase awareness and appreciation for why uncertainty matters, particularly for aerospace applications. Browse all graduate courses available this autumn quarter: https://stanford.io/Autumn-2026View past AA228 Decision Making Under Uncertainty lectures here: https://www.youtube.com/playlist?list=PLoROMvodv4rNXnHUlDJ1jnvZgNN5Q60d3 Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationLecture 1 — Course Overview; Introduction to Nonlinear OptimizationRead the companion textbook, Principles of Robot Autonomy, free online: https://porabook.com To learn more about enrolling in AA203 Optimal and Learning-Based Control, visit: https://online.stanford.edu/courses/aa203-optimal-and-learning-based-control Follow along with the course schedule and syllabus: https://stanfordasl.github.io/aa203/sp2526/ Lecture slides: https://stanfordasl.github.io/aa203/sp2526/pdfs/lecture/lecture_1.pdf Speaker: Prof. Marco PavoneBio: Dr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University and a Senior Director of Autonomous Vehicle Research at NVIDIA. Prior to joining Stanford, he was a Research Technologist in the Robotics Section at NASA’s Jet Propulsion Laboratory. Dr. Pavone received his Ph.D. in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His research focuses on the analysis, design, and control of autonomous systems, with particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He has been recognized with numerous awards, including the Presidential Early Career Award for Scientists and Engineers from President Barack Obama, the Office of Naval Research Young Investigator Award, the NSF CAREER Award, the NASA Early Career Faculty Award, the IEEE Kiyo Tomiyasu Award, the CSS Award for Technical Excellence in Aerospace Control, and the Early-Career Spotlight Award from the Robotics Science and Systems Foundation.Uploaded 11-08-26Instructors: Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIADr. Daniele Gammelli, Research Director at the Italian Institute of Artificial Intelligence (AI4I), Researcher at the Department of Aeronautics and Astronautics, Stanford UniversityFull playlist: https://www.youtube.com/playlist?list=PLa9dmHsLK9dg#StanfordOnline #OptimalControl #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

http://scpd.stanford.edu/public/category/courseCategoryCertificateProfile.do?method=load&from=courseprofile&certificateId=8151942 Learn how value-driven Enterprise Risk Management meets the challenges of integrating management of all the downside risks a healthcare organization faces, plus how to capitalize on uncertainties in the value creation opportunities driving the short- and long-term prosperity of the enterprise.Uploaded 19-04-11 Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationLecture 8 — Robotic Sensors and Introduction to Computer VisionNote: This lecture was recorded as part of the 2019 edition of the course. Course content, structure, assignments, and other materials may have changed since this recording. The course links below point to the most recent edition and may therefore differ from what is presented in the video.Uploaded 09-10-26Read the companion textbook, Principles of Robot Autonomy, free online: https://porabook.comFollow along with the latest course schedule and syllabus: https://stanfordasl.github.io/PoRA-ISpeaker: Prof. Marco PavoneDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University and a Senior Director of Autonomous Vehicle Research at NVIDIA. Prior to joining Stanford, he was a Research Technologist in the Robotics Section at NASA’s Jet Propulsion Laboratory. Dr. Pavone received his Ph.D. in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His research focuses on the analysis, design, and control of autonomous systems, with particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He has been recognized with numerous awards, including the Presidential Early Career Award for Scientists and Engineers from President Barack Obama, the Office of Naval Research Young Investigator Award, the NSF CAREER Award, the NASA Early Career Faculty Award, the IEEE Kiyo Tomiyasu Award, the CSS Award for Technical Excellence in Aerospace Control, and the Early-Career Spotlight Award from the Robotics Science and Systems Foundation. Full playlist: https://www.youtube.com/playlist?list=PLR9iNyexfIkk #StanfordOnline #RobotAutonomy #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

http://scpd.stanford.edu/coursesSeminars/seminarsAndWebinars.jsp Presented by the US-Japan Technology Management Center, the US-Asia Technology Management Center, this lecture series explores the patterns and challenges of entrepreneurship in Asia.Uploaded 26-04-11 Learn more about your ad choices. Visit megaphone.fm/adchoices

Lecture 16 — Fundamentals of Reinforcement LearningRead the companion textbook, Principles of Robot Autonomy, free online: https://porabook.com To learn more about enrolling in AA203 Optimal and Learning-Based Control, visit: https://online.stanford.edu/courses/aa203-optimal-and-learning-based-control Follow along with the course schedule and syllabus: https://stanfordasl.github.io/aa203/sp2526/ Lecture slides: https://stanfordasl.github.io/aa203/sp2526/pdfs/lecture/lecture_4.pdf Speaker: Dr. Daniele GammelliBio: Dr. Daniele Gammelli is the Research Director of the Machine Intelligence for Robot Autonomy Laboratory at the Italian Institute of Artificial Intelligence (AI4I), and a Researcher in the Department of Aeronautics and Astronautics at Stanford University. Since 2022, he has been a Research Fellow at the Center for Aerospace Autonomy Research (CAESAR) at Stanford and, until 2025, at the Center for Automotive Research at Stanford (CARS). He received his Ph.D. in Machine Learning and Mathematical Optimization from the Technical University of Denmark (DTU) in 2022, where his doctoral thesis was nominated for the DTU Best Thesis of the Year Award and the DTU Young Researcher Award. Dr. Gammelli’s research focuses on developing the algorithmic foundations and system-level methodologies that enable AI-powered autonomous systems to operate safely, efficiently, and reliably in high-stakes environments, with an emphasis on aerospace autonomy and next-generation mobility systems.Uploaded 13-08-26Instructors: Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIADr. Daniele Gammelli, Research Director at the Italian Institute of Artificial Intelligence (AI4I), Researcher at the Department of Aeronautics and Astronautics, Stanford UniversityFull playlist: https://www.youtube.com/playlist?list=PLa9dmHsLK9dg#StanfordOnline #OptimalControl #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

http://create.stanford.edu/ Taught by world-renowned faculty from the Graduate School of Business and the School of Engineering, the Stanford Innovation and Entrepreneurship Certificate is a self-paced interactive, online program where participants will gain essential skills and effective strategies to generate and implement new ideas. Our team will collaborate with you to design a custom learning experience that best meets the needs of your team or organization. Learn more at http://create.stanford.edu/Uploaded 08-08-13 Learn more about your ad choices. Visit megaphone.fm/adchoices

http://apm.stanford.edu Organizations strive for a culture of innovation -- which is often challenging to achieve. During this webinar, John Warren, VP of Strategic Business Solutions at IPS Learning, will share with you how innovation requires, and is fostered by, Project-Based Work (PBW). Innovation doesn't just happen -- it's the result of a culture within an organization that executes its strategy and exceeds client expectations.Uploaded 01-08-12Learn how leaders of PBW can drive innovation by leading people, building project infrastructure and creating the resilience required for successful strategy execution.SpeakersJohn WarrenVice President of Strategic Business SolutionsExecutive Director, SAPM Center of Excellence for Strategy ExecutionIPS LearningEnroll in professional education courses today: http://scpd.stanford.edu/coursesSeminars/profCourses.jsp Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationLecture 7 — Motion Planning II: Sampling-Based MethodsNote: This lecture was recorded as part of the 2019 edition of the course. Course content, structure, assignments, and other materials may have changed since this recording. The course links below point to the most recent edition and may therefore differ from what is presented in the video.Uploaded 09-10-26Read the companion textbook, Principles of Robot Autonomy, free online: https://porabook.comFollow along with the latest course schedule and syllabus: https://stanfordasl.github.io/PoRA-ISpeaker: Prof. Marco PavoneDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University and a Senior Director of Autonomous Vehicle Research at NVIDIA. Prior to joining Stanford, he was a Research Technologist in the Robotics Section at NASA’s Jet Propulsion Laboratory. Dr. Pavone received his Ph.D. in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His research focuses on the analysis, design, and control of autonomous systems, with particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He has been recognized with numerous awards, including the Presidential Early Career Award for Scientists and Engineers from President Barack Obama, the Office of Naval Research Young Investigator Award, the NSF CAREER Award, the NASA Early Career Faculty Award, the IEEE Kiyo Tomiyasu Award, the CSS Award for Technical Excellence in Aerospace Control, and the Early-Career Spotlight Award from the Robotics Science and Systems Foundation.Full playlist: https://www.youtube.com/playlist?list=PLR9iNyexfIkk #StanfordOnline #RobotAutonomy #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationLecture 6 — Motion Planning I: Graph Search MethodsNote: This lecture was recorded as part of the 2019 edition of the course. Course content, structure, assignments, and other materials may have changed since this recording. The course links below point to the most recent edition and may therefore differ from what is presented in the video.Uploaded 09-10-26Read the companion textbook, Principles of Robot Autonomy, free online: https://porabook.comFollow along with the latest course schedule and syllabus: https://stanfordasl.github.io/PoRA-ISpeaker: Prof. Marco PavoneDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University and a Senior Director of Autonomous Vehicle Research at NVIDIA. Prior to joining Stanford, he was a Research Technologist in the Robotics Section at NASA’s Jet Propulsion Laboratory. Dr. Pavone received his Ph.D. in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His research focuses on the analysis, design, and control of autonomous systems, with particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He has been recognized with numerous awards, including the Presidential Early Career Award for Scientists and Engineers from President Barack Obama, the Office of Naval Research Young Investigator Award, the NSF CAREER Award, the NASA Early Career Faculty Award, the IEEE Kiyo Tomiyasu Award, the CSS Award for Technical Excellence in Aerospace Control, and the Early-Career Spotlight Award from the Robotics Science and Systems Foundation.Instructor:Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIAFull playlist: https://www.youtube.com/playlist?list=PLR9iNyexfIkk #StanfordOnline #RobotAutonomy #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

http://scpd.stanford.edu/search/publicCourseSearchDetails.do?method=load&courseId=9626281 President and CEO of Varian Medical Systems, Inc shares how Stanford Executive Institute can transform how you do business.Uploaded 05-05-11 Learn more about your ad choices. Visit megaphone.fm/adchoices

Want to dive deeper? This curriculum is covered in the following online courses:- Agentic AI professional education course: https://learn.stanford.edu/agentic-ai-2026.html- XCS329 graduate course: https://online.stanford.edu/courses/cs329a-self-improving-ai-agentsUploaded 03-08-26A similar curriculum is covered in XCS329z https://online.stanford.edu/courses/cs329z-engineering-ai-agentsFollow along with the course schedule and syllabus: https://cs329a.stanford.edu/Aakanksha ChowdheryAdjunct Professor of Computer Science, Stanford UniversityView the course playlist: https://www.youtube.com/playlist?list=PLangBM27OtEAVideo Summary:This lecture recording from Stanford's CS329A, Self-Improving AI Agents, taught by Aakanksha Chowdhery on October 3, 2025, covers three approaches to improving language models through feedback. ReAct interleaves chain-of-thought reasoning with tool-calling actions and is evaluated on HotpotQA, FEVER, and WebShop. RLEF, or Reinforcement Learning from Execution Feedback, trains coding agents using public and private unit test results within a PPO training loop, evaluated on CodeContests. Constitutional AI, developed by Anthropic, uses a written set of principles along with model self-critique and revision to train a preference model through reinforcement learning from AI feedback rather than human feedback. The lecture compares how each method sources its feedback signal, from environment interaction to execution results to AI-generated critique, and reviews related work including WebGPT, Code Monkeys, and SWE-bench.Speaker Bio:Aakanksha ChowdheryAdjunct Professor of Computer Science, Stanford UniversityDr. Aakanksha Chowdhery is pushing the frontier of agentic LLMs, focusing on recursive self-improvement and long-horizon agents that learn and deploy in the real world. She is one of the few researchers globally who has led frontier model training end-to-end, across both dense and mixture-of-experts (MoE) architectures. At Google, she led the 540B PaLM model, the largest densely trained language model in the world at the time. She subsequently drove pre-training and scaling of Gemini's MoE models across multiple generations, and contributed key components to PaLM-E, Med-PaLM, and the Pathways infrastructure underpinning Google's large-model efforts. She went on to build and lead pretraining teams for open intelligence efforts at Reflection and Meta. Earlier, she held research roles at Microsoft Research and Princeton. At Stanford, where she earned her PhD, she teaches CS329A (Self-Improving AI Agents) and serves as Program Chair for MLSys 2026. Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationLecture 5 — Advanced Methods for Trajectory OptimizationNote: This lecture was recorded as part of the 2019 edition of the course. Course content, structure, assignments, and other materials may have changed since this recording. The course links below point to the most recent edition and may therefore differ from what is presented in the video.Uploaded 09-10-26Read the companion textbook, Principles of Robot Autonomy, free online: https://porabook.comFollow along with the latest course schedule and syllabus: https://stanfordasl.github.io/PoRA-ISpeaker: Prof. Marco PavoneDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University and a Senior Director of Autonomous Vehicle Research at NVIDIA. Prior to joining Stanford, he was a Research Technologist in the Robotics Section at NASA’s Jet Propulsion Laboratory. Dr. Pavone received his Ph.D. in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His research focuses on the analysis, design, and control of autonomous systems, with particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He has been recognized with numerous awards, including the Presidential Early Career Award for Scientists and Engineers from President Barack Obama, the Office of Naval Research Young Investigator Award, the NSF CAREER Award, the NASA Early Career Faculty Award, the IEEE Kiyo Tomiyasu Award, the CSS Award for Technical Excellence in Aerospace Control, and the Early-Career Spotlight Award from the Robotics Science and Systems Foundation.Instructor:Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIA Full playlist: https://www.youtube.com/playlist?list=PLR9iNyexfIkk #StanfordOnline #RobotAutonomy #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationFollow along with the course schedule: https://mse435.stanford.edu/Guest Speakers: Sunny Madra, Groq (now Nvidia) and Brad Gerstner, AltimeterInstructor: Apoorv Agrawal is a Stanford Adjunct Lecturer in Management Science and Engineering and a partner at Altimeter Capital.Uploaded 23-07-26Playlist: https://youtube.com/playlist?list=PLoROMvodv4rOAe_DtQYOCKy6_x3irEYV1&si=hI20BgdZqMFtAKS- Learn more about your ad choices. Visit megaphone.fm/adchoices

The Stanford Center for Professional Development connects professionals worldwide to the research and teaching of Stanford University faculty in the School of Engineering and related academic departments. Qualified individuals may study for master of science degrees on a part-time basis, pursue graduate certificates and professional certificates, take individual graduate courses and professional courses, participate in workshops, view free online seminars and more. Courses are delivered online, on the Stanford campus in the heart of Silicon Valley, and at the work site.Uploaded 15-02-11 Learn more about your ad choices. Visit megaphone.fm/adchoices

May 12, 2011Donald Knuth, in this Stanford Engineering Hero Lecture, answers questions from the audience--from his opinion of Wikipedia to the next great discovery in computer science to his most memorable mistake.Uploaded 17-05-11Learn more: http://scpd.stanford.edu/knuth/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Innovation cannot happen without the funding to bring an idea to life. In this webinar Stanford Professor Peter DeMarzo, Senior Associate Dean of the Graduate School of Business and instructor within the Stanford Innovation and Entrepreneurship certificate, discusses how to value ideas and innovations so they receive the proper funds to launch.Uploaded 13-08-130:00 Introduction2:14 Risk and Return: Insights from 86 Years of Investor History6:03 Return Volatility7:45 Risk vs. Return: The Security Market Line11:21 How Do Individual Investors Behave?14:21 Individuals Trade A Lot15:05 Individual Performance15:39 Turnover and Returns17:57 Swimming with Sharks: Picking Stocks, or Picked Off?23:55 Mutual Fund Performance26:00 Institutional Fund Managers27:57 Active vs. Passive Investing36:50 A Star has Fallen: Bill Miller's Legg Mason Value Trust41:12 Some Final Thoughts...46:20 New Course Launching in September: Financing Innovation: Valuing Projects and Firms Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationLecture 4 — Trajectory Tracking and Closed-Loop ControlNote: This lecture was recorded as part of the 2019 edition of the course. Course content, structure, assignments, and other materials may have changed since this recording. The course links below point to the most recent edition and may therefore differ from what is presented in the video.Uploaded 09-10-26Read the companion textbook, Principles of Robot Autonomy, free online: https://porabook.comFollow along with the latest course schedule and syllabus: https://stanfordasl.github.io/PoRA-ISpeaker: Prof. Marco PavoneDr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University and a Senior Director of Autonomous Vehicle Research at NVIDIA. Prior to joining Stanford, he was a Research Technologist in the Robotics Section at NASA’s Jet Propulsion Laboratory. Dr. Pavone received his Ph.D. in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. His research focuses on the analysis, design, and control of autonomous systems, with particular emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems. He has been recognized with numerous awards, including the Presidential Early Career Award for Scientists and Engineers from President Barack Obama, the Office of Naval Research Young Investigator Award, the NSF CAREER Award, the NASA Early Career Faculty Award, the IEEE Kiyo Tomiyasu Award, the CSS Award for Technical Excellence in Aerospace Control, and the Early-Career Spotlight Award from the Robotics Science and Systems Foundation.Instructor:Prof. Marco Pavone, Associate Professor of Aeronautics and Astronautics, Director of Autonomous Vehicle Research at NVIDIA Full playlist: https://www.youtube.com/playlist?list=PLR9iNyexfIkk #StanfordOnline #RobotAutonomy #Robotics #PhysicalAI Learn more about your ad choices. Visit megaphone.fm/adchoices

Gordon WetzsteinStanford UniversityThis seminar series features dynamic professionals sharing their industry experience and cutting edge research within the human-computer interaction (HCI) field. Each week, a unique collection of technologists, artists, designers, and activists will discuss a wide range of current and evolving topics pertaining to HCI.Uploaded 14-10-15Learn more about Stanford's Human-Computer Interaction Group: https://hci.stanford.eduLearn about Stanford's Graduate Certificate in HCI: https://online.stanford.edu/programs/human-computer-interaction-graduate-certificateView the full playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rMyupDF2O00r19JsmolyXdD&disable_polymer=true Learn more about your ad choices. Visit megaphone.fm/adchoices

Stanford's Ricardo Levy and Howie Rosen offer insights into entrepreneurial opportunities in the renewable energy industry. What does the future hold? Where will there be innovation? Levy and Rosen teach courses in the new Molecular Engineering of Energy Technologies online graduate certificate at Stanford University.Uploaded 07-08-12Learn more about the Molecular Engineering of Energy Technologies certificate: http://scpd.stanford.edu/public/category/courseCategoryCertificateProfile.do?method=load&certificateId=15533128Enroll in graduate courses today! https://online.stanford.edu/explore?type=All&credentials[156]=156 Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/aiUploaded 30-10-24To follow along with the course, visit the course website: https://web.stanford.edu/class/cs234/Emma BrunskillAssociate Professor of Computer Science at Stanford Universityhttps://cs.stanford.edu/people/ebrun/Learn more about the course and how to enroll: https://online.stanford.edu/courses/cs234-reinforcement-learningTo view all online courses and programs offered by Stanford, visit: http://online.stanford.edu Learn more about your ad choices. Visit megaphone.fm/adchoices

Want to dive deeper? This curriculum is covered in the following online courses:- Agentic AI professional education course: https://stanford.io/4zOyjPN- XCS329 graduate course: https://online.stanford.edu/courses/cs329a-self-improving-ai-agentsUploaded 03-08-26A similar curriculum is covered in XCS329z https://online.stanford.edu/courses/cs329z-engineering-ai-agentsFollow along with the course schedule and syllabus: https://cs329a.stanford.edu/View the course playlist: https://www.youtube.com/playlist?list=PLangBM27OtEAVideo Summary:This first lecture videoof Stanford's CS329A, Self-Improving AI Agents, taught by Aakanksha Chowdhery and Azalia Mirhoseini on September 22, 2025, opens with an overview of scaling laws that link model parameters, training compute, and dataset size to lower test loss in large language models from GPT-2 through GPT-4. It covers few-shot and zero-shot learning, the emergence of chain-of-thought reasoning in larger models, and the role of instruction tuning and reinforcement learning from human feedback in the development of ChatGPT. The lecture introduces inference-time scaling through the Large Language Monkeys project, which repeatedly samples a model's outputs and selects correct answers with a verifier to improve performance without retraining. It then traces the shift from single-turn chatbots to agent workflows such as prompt chaining, routing, parallelization, and orchestrator-worker patterns, using Claude Code and deep research tools as examples. The session closes with logistics for the course.Speaker Bios:Aakanksha ChowdheryAdjunct Professor of Computer Science, Stanford UniversityDr. Aakanksha Chowdhery is pushing the frontier of agentic LLMs, focusing on recursive self-improvement and long-horizon agents that learn and deploy in the real world. She is one of the few researchers globally who has led frontier model training end-to-end, across both dense and mixture-of-experts (MoE) architectures. At Google, she led the 540B PaLM model, the largest densely trained language model in the world at the time. She subsequently drove pre-training and scaling of Gemini's MoE models across multiple generations, and contributed key components to PaLM-E, Med-PaLM, and the Pathways infrastructure underpinning Google's large-model efforts. She went on to build and lead pretraining teams for open intelligence efforts at Reflection and Meta. Earlier, she held research roles at Microsoft Research and Princeton. At Stanford, where she earned her PhD, she teaches CS329A (Self-Improving AI Agents) and serves as Program Chair for MLSys 2026.Azalia MirhoseiniAssistant Professor of Computer Science, Stanford UniversityAzalia Mirhoseini is a co-founder of Ricursive Intelligence, a frontier lab dedicated to recursive self-improvement through AI that designs the chips that fuel it. She is also an Assistant Professor of Computer Science at Stanford University where she directs Scaling Intelligence, a lab focused on developing scalable and self-improving AI systems and methodologies toward the goal of artificial general intelligence. Previously, she spent several years in industry AI labs, including Google Brain, Anthropic, and Google DeepMind, working on the development of Claude and Gemini. Her past work includes Mixture-of-Experts (MoE) neural architectures, now predominantly used in leading generative AI models; AlphaChip, a pioneering work on deep reinforcement learning for layout optimization used in the design of advanced chips like Google AI accelerators (TPUs) and data center CPUs; as well as pioneering research on LLM Test-Time Scaling. Her work has been recognized through the Okawa Research Grant, the Google ML and Systems Junior Faculty Award, MIT Technology Review's 35 Under 35 Award, the Best ECE Thesis Award at Rice University, publications in flagship venues such as Nature, and co Learn more about your ad choices. Visit megaphone.fm/adchoices

"Electric Vehicles and Startups" -Marc Tarpenning, TeslaThe purpose of this seminar series is to help students and professionals develop the tools to apply the engineering mindset to problems that stem from climate change, in order to consider and evaluate possible stabilizing, remedial and adaptive approaches. This course is not a crash course on climate change or policy. Instead we will focus on learning about and discussing climate problems that seem most likely to benefit from the engineering mindset.Uploaded 14-10-15Learn more: http://stanford.io/19O05eN Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/aiStanford CS234 Reinforcement Learning I Offline RL 2 and Guest Lecture on Direct Preference Optimization (DPO) by authors:Rafael Rafailov: https://arxiv.org/search/cs?searchtype=author&query=Rafailov,+RArchit Sharma: https://arxiv.org/search/cs?searchtype=author&query=Sharma,+AEric Mitchell: https://arxiv.org/search/cs?searchtype=author&query=Mitchell,+EUploaded 30-10-24To follow along with the course, visit the course website: https://web.stanford.edu/class/cs234/Emma BrunskillAssociate Professor of Computer Science at Stanford Universityhttps://cs.stanford.edu/people/ebrun/Learn more about the course and how to enroll: https://online.stanford.edu/courses/cs234-reinforcement-learningTo view all online courses and programs offered by Stanford, visit: http://online.stanford.edu Learn more about your ad choices. Visit megaphone.fm/adchoices

Christina Smolke, Stanford UniversitySteve Jurvetson, DFJAstro Teller, Google XIn this seminar, entrepreneurial leaders share lessons from real-world experiences across entrepreneurial settings. Speakers include entrepreneurs, leaders from global technology companies, venture capitalists, and best-selling authors. Half-hour talks are followed by a half hour of class interaction.Uploaded 14-10-15Learn more about Stanford's eCorner: https://ecorner.stanford.edu Learn more about Stanford's online classes and certificates: https://online.stanford.edu/programs See the full playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rPE-kcGtKBgYtSMqEJKbESC Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationMarch 7, 2025This seminar covers: • Embodied intelligence with morphing materials and mechanisms• Facing open design challenges, such as complete degradability and biocompatibility, arbitrary shape morphing, and freely reconfigurable degrees of freedom• How addressing these challenges sometimes requires looking beyond conventional mechatronic systems• The critical role of computational design and optimization in assisting robotic and machine design and controlUploaded 22-07-26Follow along with the seminar schedule: https://stanfordasl.github.io/robotics_seminar/archive/Lining Yao is an Assistant Professor at the Mechanical Engineering department, the University of California, Berkeley, where she directs the Morphing Matter Lab (morphingmatter.org). Learn more about your ad choices. Visit megaphone.fm/adchoices

Entrepreneurship is synonymous with innovation, especially in Silicon Valley. In this webinar Stanford Professors Howie Rosen and Ricardo Levy discuss how your organization can continue to be disruptive in industry and maintain an entrepreneurial edgeUploaded 14-08-13Learn more about the Molecular Engineering of Energy Technologies graduate certificate: http://scpd.stanford.edu/public/category/courseCategoryCertificateProfile.do?method=load&certificateId=155331280:00 Introduction0:56 Caveat...1:37 Start-up or established company: evaluating a new business before you "leap" has advantages.2:23 Successful new businesses have two parts: 1. A "good" idea; and, 2. A "business model"3:40 Engineering and science-based businesses take time and money to show technical feasibility.5:59 Learning objectives for today's webinar6:34 Entrepreneurial leadership7:23 Key issues7:40 the difference between leadership and management9:29 LEADERSHIP vs MANAGEMENT10:37 Management and leadership with limited resources13:01 the nature of the entrepreneurial commitment14:17 Total emotional engagement -- The Positive15:41 Total emotional engagement -- the negative17:13 Consequences of control18:15 The leader's role in the face of uncertainty19:55 Absorbing Uncertainty...21:38 The entrepreneurial "edge"23:45 The established company "edge"25:00 some of the corporate challenges26:55 some of the personal challenges to be aware of29:20 Some final thoughts...31:01 and remember... Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/aiUploaded 30-10-24To follow along with the course, visit the course website: https://web.stanford.edu/class/cs234/Emma BrunskillAssociate Professor of Computer Science at Stanford Universityhttps://cs.stanford.edu/people/ebrun/Learn more about the course and how to enroll: https://online.stanford.edu/courses/cs234-reinforcement-learningTo view all online courses and programs offered by Stanford, visit: http://online.stanford.edu Learn more about your ad choices. Visit megaphone.fm/adchoices

"Wafer-Scale Thermionic Energy Converters?"- Roger T. Howe of Stanford UniversityUploaded 15-10-15About the talk:Thermionic energy converters (TECs) were conceived in 1915, demonstrated in 1939, and were the focus of huge investments during the Cold War by the U.S. and the Soviet Union. A 6 kW thermionic converter, fabricated using precision machining technology, was flown in 1987 by the Soviet Union. TEC research ramped down in the 1990s and the field withered to a few embers by 2005. I will review the simple physics of TECs and what the barriers have been to applying them to direct heat-to-electricity conversion for terrestrial applications.Over the past decade, new materials, processes, and device architectures are being explored at Stanford, the Max Planck Institute, and other research groups around the world. I will provide an update on recent progress at Stanford on thermally isolated, suspended micro cathodes inspired by microbolometer infrared imagers. In order to reach useful efficiencies, both very high thermal isolation between the cathode and the anode and a much lower anode work function are needed. Over the past year, two approaches to fabricating anodes with work functions of 1 eV or less have been demonstrated at Stanford: the electrostatic doping of graphene and the surface photovoltage in a semiconductor anode.Support for the Stanford Colloquium on Computer Systems Seminar Series provided by the Stanford Computer Forum.Speaker Abstract and Bio can be found here: http://ee380.stanford.edu/Abstracts/151014.htmlFor more info about the EE380 series: http://ee380.stanford.eduColloquium on Computer Systems Seminar Series (EE380) presents the current research in design, implementation, analysis, and use of computer systems. Topics range from integrated circuits to operating systems and programming languages. It is free and open to the public, with new lectures each week.Learn more: http://bit.ly/WinYX50:00 Introduction4:15 Thermionic Energy Converter6:29 Thermionics Timeline: The Early Days10:30 A Cold War Application: Space Power14:28 Thermionic Converter Design Cathode work function sets hot-side temperature15:46 Barrier Index: a critical parameter19:00 Microfabricated Thermionic Converters?20:57 Standard MEMS Thermal Isolation Design22:34 A Pixelated Suspended Cathode25:33 Nano-Gap Heat Transfer28:43 Testing Thermionic Components29:21 Mixed Alkali Earth Oxide Coatings Lower the Work Function of Tungsten30:07 Density Functional Theory (DFT) Simulations of Work Function and Formation Energy32:06 Computation of Thermionic Emission Current from First Principles using DFT33:14 Work Functions for Cathodes and Anodes43:08 Topping Cycles for Fossil-Fuel Power Plants: Themoelectronic Triodes47:03 A 21st Century Application for TEC: Concentrated Solar Thermal Power48:28 Photon-Enhanced Thermionic Emission (PETE) Energy Diagram51:04 Tandem Solar Thermal Cycle55:48 Spark Thermionics @ Cyclotron Road Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/aiUploaded 30-10-24To follow along with the course, visit the course website: https://web.stanford.edu/class/cs234/Emma BrunskillAssociate Professor of Computer Science at Stanford Universityhttps://cs.stanford.edu/people/ebrun/Learn more about the course and how to enroll: https://online.stanford.edu/courses/cs234-reinforcement-learningTo view all online courses and programs offered by Stanford, visit: http://online.stanford.edu Learn more about your ad choices. Visit megaphone.fm/adchoices

Angela Marsaiaj of Staeye highlights the importance of learning by doing for a small business owner at the Innovation Masters Series and how the experience made "everything come to life."Uploaded 17-10-13Learn the problem-solving tools and problem-finding frameworks that lead to innovation and strategic leadership in the Innovation Masters Series: Design Thinking and the Art of Innovation course, pioneered by the Design Group and the d.school at Stanford.Learn more: http://scpd.stanford.edu/design/ Learn more about your ad choices. Visit megaphone.fm/adchoices

Want to dive deeper? This curriculum is covered in the following online courses:- Agentic AI professional education course: https://stanford.io/4zOyjPN- XCS329 graduate course: https://online.stanford.edu/courses/cs329a-self-improving-ai-agentsUploaded 03-08-26A similar curriculum is covered in XCS329z https://online.stanford.edu/courses/cs329z-engineering-ai-agentsFollow along with the course schedule and syllabus: https://cs329a.stanford.edu/View the course playlist: https://www.youtube.com/playlist?list=PLangBM27OtEAVideo Summary:This lecture recording from Stanford's CS329A, Self-Improving AI Agents, delivered by Azalia Mirhoseini on September 26, 2025, examines test-time compute scaling as a way to improve model performance without additional training. It covers the Large Language Monkeys paper's finding that solve rate follows a power law as the number of parallel samples increases, driven by a long tail of hard problems each model solves only rarely, and it distinguishes majority voting from oracle verification to define the generation-verification gap. The lecture also covers a paper on optimally scaling test-time compute, which compares parallel sampling against sequential revision and introduces outcome and process reward models to guide search over candidate solutions. It closes with the Arkon paper on inference-time architecture search, which combines techniques including fusion, critic, ranker, and unit test generation across multiple models, reporting an average 14.1 percent improvement in pass-at-one accuracy over GPT-4 and Claude 3.5 Sonnet on reasoning, math, and coding tasks. Discussion throughout addresses when pre-training still outperforms added test-time compute for the hardest problems.Speaker Bio:Azalia MirhoseiniAssistant Professor of Computer Science, Stanford UniversityAzalia Mirhoseini is a co-founder of Ricursive Intelligence, a frontier lab dedicated to recursive self-improvement through AI that designs the chips that fuel it. She is also an Assistant Professor of Computer Science at Stanford University where she directs Scaling Intelligence, a lab focused on developing scalable and self-improving AI systems and methodologies toward the goal of artificial general intelligence. Previously, she spent several years in industry AI labs, including Google Brain, Anthropic, and Google DeepMind, working on the development of Claude and Gemini. Her past work includes Mixture-of-Experts (MoE) neural architectures, now predominantly used in leading generative AI models; AlphaChip, a pioneering work on deep reinforcement learning for layout optimization used in the design of advanced chips like Google AI accelerators (TPUs) and data center CPUs; as well as pioneering research on LLM Test-Time Scaling. Her work has been recognized through the Okawa Research Grant, the Google ML and Systems Junior Faculty Award, MIT Technology Review's 35 Under 35 Award, the Best ECE Thesis Award at Rice University, publications in flagship venues such as Nature, and coverage by various media outlets, including WSJ, NYT, Forbes, MIT Technology Review, IEEE Spectrum, WIRED, and TechCrunch. Learn more about your ad choices. Visit megaphone.fm/adchoices

http://scpd.stanford.edu/computerSecurity/Neil Daswani, co-founder of Dasient, Inc., a stealth-mode Internet security company, is an instructor in the Stanford Advanced Computer Security certificate program. In the past, Neil has served in a variety of research , development, teaching, and managerial roles at Google, Stanford University, DoCoMo USA Labs, Yodlee, and Bellcore (now Telcordia Technologies). While at Stanford, Neil cofounded the Stanford Center for Professional Development (SCPD) Security Certification Program.Uploaded 14-08-12Enroll in professional education courses today! https://online.stanford.edu/programs/advanced-cybersecurity-program Learn more about your ad choices. Visit megaphone.fm/adchoices

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/aiUploaded 30-10-24To follow along with the course, visit the course website: https://web.stanford.edu/class/cs234/Emma BrunskillAssociate Professor of Computer Science at Stanford Universityhttps://cs.stanford.edu/people/ebrun/Learn more about the course and how to enroll: https://online.stanford.edu/courses/cs234-reinforcement-learningTo view all online courses and programs offered by Stanford, visit: http://online.stanford.edu Learn more about your ad choices. Visit megaphone.fm/adchoices