Standford U on AI

Learn more about Stanford Online's Artificial Intelligence Programs: https://online.stanford.edu/artific... Dive into the real-world challenges of taking reinforcement learning from elegant theory to practical, user-facing AI products. You'll examine where reward functions succeed, how design decisions shape model and product behavior, and how to build AI products. Hosted by Aditya Challapally, with insights from Stanford professor Emma Brunskill and Boris Cherny (Member of Technical Staff at Anthropic, Creator of Claude Code), this conversation looks beyond algorithms to explore how to build AI products used by millions — revealing the mindsets, design choices, and feedback cultures that turn abstract models into enduring, human-centered systems.

Professor and Chair of the Computer Science Department at Stanford University, Mehran Sahami, explains how he balances the technical and ethical dimensions of teaching computer science, especially at the intersection of using AI tools. Learn about Code in Place: https://codeinplace.stanford.edu/ Learn about our Artificial Intelligence Courses and Programs: https://online.stanford.edu/artific... Learn about our Computer Science & Security Programs: https://online.stanford.edu/compute...

Why does code work one day and another day it breaks? Professor and Chair of the Computer Science Department at Stanford University, Mehran Sahami, explains. Learn about Code in Place: https://codeinplace.stanford.edu/ Learn about our Artificial Intelligence Courses and Programs: https://online.stanford.edu/artific... Learn about our Computer Science & Security Programs: https://online.stanford.edu/compute...

Should you be nice to ChatGPT in case AI rebels against humans? Professor and Chair of the Computer Science Department at Stanford University, Mehran Sahami, offers sage advice. Learn about Code in Place: https://codeinplace.stanford.edu/ Learn about our Artificial Intelligence Courses and Programs: https://online.stanford.edu/artific... Learn about our Computer Science & Security Programs: https://online.stanford.edu/compute...

Learn more about Stanford Online's Artificial Intelligence Programs: https://online.stanford.edu/artific... Dive into the real-world challenges of taking reinforcement learning from elegant theory to practical, user-facing AI products. You'll examine where reward functions succeed, how design decisions shape model and product behavior, and how to build AI products. Hosted by Aditya Challapally, with insights from Stanford professor Emma Brunskill and Boris Cherny (Member of Technical Staff at Anthropic, Creator of Claude Code), this conversation looks beyond algorithms to explore how to build AI products used by millions — revealing the mindsets, design choices, and feedback cultures that turn abstract models into enduring, human-centered systems. Chapters: Introductions 0:00 First Impressions of AI Technology 1:37 Challenges in Productizing AI Models 3:39 The Future of Software Engineering with AI 7:12 Current State of Reinforcement Learning and Alignment 15:15 Designing Effective Product Feedback Systems 19:04 Building AI Products: Mindsets and Strategies 25:40 Understanding "What Models Want" in AI Development 33:04 Resources for Effective Prompt Engineering 39:31 Key Principles for the Next Wave of GenAI Builders 41:14 Predicting AI Capabilities in the Near Future 46:49 Envisioning AI's Impact 10 Years from Now 50:05 Societal Challenges and Closing Thoughts 54:29

During a recent Stanford Online webinar, “Making Gen AI Useful,” Aditya Challapally (ML Engineer at Microsoft) moderated an insightful conversation with Michelle Pokrass (Post-Training Research Lead at OpenAI) and Stanford professor Chris Potts. Together, they broke down how foundation models are refined after training, explored where emerging API capabilities are opening new doors for developers, and addressed what separates successful GenAI apps from those that fall short. Watch the full webinar: https://youtu.be/9-eXLFvAoKM?si=T6_... Learn more about Stanford Online's Generative AI Program: https://online.stanford.edu/program...

During a recent Stanford Online webinar, “Making Gen AI Useful,” Aditya Challapally (ML Engineer at Microsoft) moderated an insightful conversation with Michelle Pokrass (Post-Training Research Lead at OpenAI) and Stanford professor Chris Potts. Together, they broke down how foundation models are refined after training, explored where emerging API capabilities are opening new doors for developers, and addressed what separates successful GenAI apps from those that fall short. Watch the full webinar: https://youtu.be/9-eXLFvAoKM?si=T6_... Learn more about Stanford Online's Generative AI Program: https://online.stanford.edu/program...

During a recent Stanford Online webinar, “Making Gen AI Useful,” Aditya Challapally (ML Engineer at Microsoft) moderated an insightful conversation with Michelle Pokrass (Post-Training Research Lead at OpenAI) and Stanford professor Chris Potts. Together, they broke down how foundation models are refined after training, explored where emerging API capabilities are opening new doors for developers, and addressed what separates successful GenAI apps from those that fall short. Watch the full webinar: https://youtu.be/9-eXLFvAoKM?si=T6_... Learn more about Stanford Online's Generative AI Program: https://online.stanford.edu/program...

During a recent Stanford Online webinar, “Making Gen AI Useful,” Aditya Challapally (ML Engineer at Microsoft) moderated an insightful conversation with Michelle Pokrass (Post-Training Research Lead at OpenAI) and Stanford professor Chris Potts. Together, they broke down how foundation models are refined after training, explored where emerging API capabilities are opening new doors for developers, and addressed what separates successful GenAI apps from those that fall short. Watch the full webinar: https://youtu.be/9-eXLFvAoKM?si=T6_... Learn more about Stanford Online's Generative AI Program: https://online.stanford.edu/program...

Drs. Kristin Sainani and Regina Nuzzo explore innovative ways generative AI is reshaping their work in clinical research and epidemiology. This engaging session reveals how they leverage this powerful AI tool for tasks such as data analysis, decoding statistical analyses sections, and writing faster through AI-refined dictation. You'll also learn how Dr. Sainani and Dr. Nuzzo use generative AI in their daily lives—from homework help to motivational cartoons. Additionally, they discuss the limitations of large language models in statistical reasoning and what these shortcomings teach us about our understanding of data and research methodologies. Watch this insightful discussion at the critical intersection of AI and healthcare! Browse online health & medicine programs: https://online.stanford.edu/explore...

During a recent Stanford Online webinar, “Making Gen AI Useful,” Aditya Challapally (ML Engineer at Microsoft) moderated an insightful conversation with Michelle Pokrass (Post-Training Research Lead at OpenAI) and Stanford professor Chris Potts. Together, they broke down how foundation models are refined after training, explored where emerging API capabilities are opening new doors for developers, and addressed what separates successful GenAI apps from those that fall short. Watch the full webinar: https://youtu.be/9-eXLFvAoKM?si=T6_... Learn more about Stanford Online's Generative AI Program: https://online.stanford.edu/program...

During a recent Stanford Online webinar, “Making Gen AI Useful,” Aditya Challapally (ML Engineer at Microsoft) moderated an insightful conversation with Michelle Pokrass (Post-Training Research Lead at OpenAI) and Stanford professor Chris Potts. Together, they broke down how foundation models are refined after training, explored where emerging API capabilities are opening new doors for developers, and addressed what separates successful GenAI apps from those that fall short. Watch the full webinar: https://youtu.be/9-eXLFvAoKM?si=T6_... Learn more about Stanford Online's Generative AI Program: https://online.stanford.edu/program...

During a recent Stanford Online webinar, “Making Gen AI Useful,” Aditya Challapally (ML Engineer at Microsoft) moderated an insightful conversation with Michelle Pokrass (Post-Training Research Lead at OpenAI) and Stanford professor Chris Potts. Together, they broke down how foundation models are refined after training, explored where emerging API capabilities are opening new doors for developers, and addressed what separates successful GenAI apps from those that fall short. Watch the full webinar: https://youtu.be/9-eXLFvAoKM?si=T6_... Learn more about Stanford Online's Generative AI Program: https://online.stanford.edu/program...

Learn more about Stanford's Healthcare AI programs: https://online.stanford.edu/artific... Check out the AI in Healthcare series playlist: https://bit.ly/AI-in-Healthcare-YT-... Hosts: Matt Lungren, Stanford University - https://profiles.stanford.edu/matth... Justin Norden, Stanford University - https://med.stanford.edu/profiles/j... Guest Speaker: Seth Hain, Senior Vice President of R&D, Epic In this episode, hosts Matt Lundgren and Justin Norden, and special guest Seth Hain, Senior Vice President of R&D at Epic explore the latest advancements in AI models, including #GPT5, and their impact on healthcare. The trio discuss the challenges of benchmarking AI in medicine, the integration of #AI into clinical workflows, and the development of specialized models like Cosmos for predictive healthcare. They also addresses the implications of AI-driven deskilling, the evolving relationship between human expertise and AI, and the future of user experience in healthcare technology. Whether you're a clinician, developer, or healthcare leader, this session offers valuable insights into the opportunities and challenges at the intersection of AI and healthcare. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education.

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai Learn more about our Deep Learning for Computer Vision courses: https://online.stanford.edu/courses... https://online.stanford.edu/courses... Assistant Professor Ehsan Adeli leads an informative session on how computer vision works and its applications across various domains, particularly in robotics and healthcare. You will hear how innovative computer vision techniques can transform everyday activities and behaviors into meaningful clinical signals. Professor Adeli explains how computer vision algorithms continuously identify clinical activities and objects in hospitals, enabling automated tracking of preventive measures, diagnostic procedures, and therapeutic interventions essential for patient safety and care quality. By delivering real-time, detailed insights into clinical workflows—traditionally dependent on limited human observation or retrospective records—this system has the potential to reduce clinician workload, improve adherence to care protocols, and ultimately enhance patient outcomes in high-intensity environments such as the ICU. Additionally, he discusses the role of computer vision in senior care applications, highlighting how it can detect early signs of cognitive or physical decline, equipping clinicians with new tools for proactive and compassionate care. Watch this enlightening session to gain a deeper understanding of how AI is connecting advanced technology with meaningful human outcomes. About the speaker: Professor Ehsan Adeli holds a Ph.D. in artificial intelligence and computer vision, with postgraduate training in computational neuroscience. His research group develops Translational AI algorithms for healthcare and mental health, focusing on the automatic analysis of human activities from videos and neuroimages. Adeli’s work focuses on bridging digital humans and human neuroscience through advanced computer vision and video analysis. His group develops methods to capture and analyze 3D motion and complex behaviors using multi-modal sensing technologies, integrating these with neuroimaging data. This approach not only pushes the boundaries of visual understanding of human behavior but also creates new pathways for connecting computational models with brain function.

Learn more about Stanford's online Healthcare AI programs: https://online.stanford.edu/artific... Check out the AI in Healthcare series playlist: https://bit.ly/AI-in-Healthcare-YT-... Matt Lungren, Stanford University - https://profiles.stanford.edu/matth... Justin Norden, Stanford University - https://med.stanford.edu/profiles/j... Guest Speaker: Dr. Graham Walker, Co-Director of Advanced Development at Kaiser Permanente In the second episode of the Stanford AI in Medicine podcast, hosts Justin Norden and Matthew Lungren, along with guest Dr. Graham Walker, Co-Director of Advanced Development at Kaiser, discuss the latest developments in AI models, particularly GPT-4.5. They highlight the incremental improvements in AI performance, the hallucination rate, and the growing trust in AI-generated content. The conversation also covers the increasing use of AI in healthcare, including for clinical decision support and medical education. They also debate the potential for AI to prescribe medications and the need for regulatory frameworks. 1. The Evolving Role of AI in Medicine: Progress and Persistent Limitations – While LLMs continue to improve, accuracy and reliability remain challenges, especially in high-stakes applications like healthcare. 2. Physician Adoption of AI: Benefits and Risks – With up to a third of doctors using AI for clinical decision support, concerns about over-reliance and unverified outputs must be addressed 3. AI’s Potential in Medical Education – From personalized learning to communication coaching, AI could revolutionize medical training and challenge outdated educational models. 4. AI in Prescribing Medications: Ethical and Regulatory Considerations – The idea of AI-driven prescribing raises ethical dilemmas and calls for a reassessment of healthcare delivery and professional licensure. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education. #healthcareai #healthcareprofessionals #aiinhealthcare

Learn more about Stanford's online Healthcare AI programs: https://online.stanford.edu/artific... Check out the AI in Healthcare series playlist: https://bit.ly/AI-in-Healthcare-YT-... Hosts: Matt Lungren, Stanford University - https://profiles.stanford.edu/matth... Justin Norden, Stanford University - https://med.stanford.edu/profiles/j... Guest Speaker: Dr. Amy Abernethy, M.D., Ph.D., Co-founder, Highlander Health In this third episode of the Stanford AI in Healthcare podcast, hosts Justin Norden and Matthew Lungren, along with guest Dr. Amy Abernethy, Co-Founder of Highlander Health explore the transformative potential of AI in healthcare. Diving deep into the current capabilities of language models, the discussion tackles critical questions about AI adoption, clinical integration, and the evolving role of physicians. From ethical considerations to regulatory challenges, the conversation offers a nuanced look at how AI is reshaping medical practice, highlighting the delicate balance between technological advancement and human expertise. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education. #healthcareai #healthcareprofessionals #medicalinnovation

For more information about Stanford's Artificial Intelligence programs visit: https://stanford.io/ai August 7, 2025 Guest Lecture: Gabor Angeli AI Research Engineer, Resolve AI Bharat Khandelwal AI Research Engineer, Resolve AI Spiros Xanthos Founder & CEO, Resolve AI To view all online courses and programs offered by Stanford, visit: http://online.stanford.edu

Learn more about Stanford's Healthcare AI programs: https://online.stanford.edu/artific... Check out the AI in Healthcare series playlist: https://bit.ly/AI-in-Healthcare-YT-... Matt Lungren, Stanford University - https://profiles.stanford.edu/matth... Justin Norden, Stanford University - https://med.stanford.edu/profiles/j... Guest Speaker: Kimberly Powell, Vice President / General Manager, NVIDIA In this episode, hosts Matt Lungren and Justin Norden welcome Kimberly Powell from Nvidia, who shares insights from her two-decade journey spearheading AI innovations in healthcare. They discuss recent AI advancements, the growing sophistication of patient interactions with AI models, and the shift toward employing robotics and digital tools in clinical settings. The conversation highlights how technology is evolving to enhance healthcare delivery and patient empowerment while addressing the challenges of privacy and compliance in medical environments. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education.

Learn more about Stanford's online Healthcare AI programs: https://stanford.io/3ETLFCx Check out the AI in Healthcare series playlist: https://bit.ly/AI-in-Healthcare-YT-... Matt Lungren, Stanford University - https://profiles.stanford.edu/matth... Justin Norden, Stanford University - https://med.stanford.edu/profiles/j... Guest Speaker: Peter Lee, President of Microsoft Research In this latest episode, hosts Justin Norden and Matthew Lungren, along with Microsoft Research President Peter Lee, discuss cutting-edge AI developments, focusing on model performance, post-training compute, and healthcare applications. The conversation explores emerging AI technologies, benchmarking challenges, and innovative approaches to medical diagnostics. Lee highlights research on sequential diagnosis, AI agents, and the potential of AI to reduce administrative burdens in healthcare. The discussion examines the nuanced evaluation of AI models, emphasizing the importance of creating collaborative, context-aware systems that can effectively assist medical professionals. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education. #healthcareai #MicrosoftResearch #generativeAI

Get more information about Stanford's online AI programs: https://stanford.io/ai In this session, you’ll explore how AI products evolve from raw model outputs to real-world tools that drive value in production. We’ll break down how foundation models are refined after training, where emerging API capabilities are opening new doors for developers, and what separates successful GenAI apps from those that fall short. Hosted by Aditya Challapally (ML Engineer at Microsoft), with insights from Michelle Pokrass (Post-Training Research Manager at OpenAI) and Stanford Professor Chris Potts, this conversation reveals what it really takes to move from cutting-edge models to AI applications that are reliable, effective, and built to last. Browse Stanford's online AI programs: https://online.stanford.edu/artific...

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai September 30, 2025 This lecture covers key AI concepts through case studies. To learn more about enrolling in this course, visit: https://online.stanford.edu/courses... To follow along with the course schedule and syllabus, visit: https://cs230.stanford.edu/syllabus... More lectures will be published regularly. Andrew Ng Founder of DeepLearning.AI Adjunct Professor, Stanford University’s Computer Science Department Kian Katanforoosh CEO and Founder of Workera Adjunct Lecturer, Stanford University’s Computer Science Department

Learn more about Stanford Online's AI in Healthcare programs: https://online.stanford.edu/artific... Check out the AI in Healthcare series playlist: https://bit.ly/AI-in-Healthcare-YT-... Hosts: Matt Lungren, Stanford University - https://profiles.stanford.edu/matth... Justin Norden, Stanford University - https://med.stanford.edu/profiles/j... Guest Speaker: Dr. Eric Topol, Scripps Research Translational Institute In this fourth episode of the Stanford AI in Medicine series, hosts Justin Norden and Matthew Lungren, and guest, Dr. Eric Topol of the Scripps Research Translational Institute, explore the transformative potential of #AI in healthcare, discussing how advanced technologies can revolutionize medical education, disease prevention, and patient empowerment. Drawing from his expertise in genomics and precision medicine, Dr. Topol reveals how AI can enable personalized health strategies, early disease detection, and individualized longevity approaches. The conversation critically examines current healthcare limitations while highlighting breakthrough opportunities in understanding age-related diseases, drug discovery, and patient-centered care. This discussion offers profound insights into how artificial intelligence is poised to reshape our understanding of health, aging, and medical innovation. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education. #healthcareai #healthcareprofessionals #medicalinnovation

Learn more about Stanford Online's AI in Healthcare programs: https://online.stanford.edu/artific... Check out the AI in Healthcare series playlist: https://bit.ly/AI-in-Healthcare-YT-... Hosts: Matt Lungren, Stanford University - https://profiles.stanford.edu/matth... Justin Norden, Stanford University - https://med.stanford.edu/profiles/j... Guest Speaker: Dr. Jessica Mega, Stanford University, MD, MPH In this 5th episode of the Stanford AI in Medicine podcast, hosts Justin Norden and Matthew Lungren and guest Dr. Jessica Mega explore AI's revolutionary potential in medicine, discussing its applications across diagnostic tools, drug discovery, and patient care. The conversation highlights the importance of developing AI platforms that integrate into clinical workflows, providing comprehensive patient insights. Drawing parallels with genomics research, the talk looks at AI's potential to break down medical specialization barriers and create more personalized, proactive healthcare solutions. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education. #healthcareai #digitalhealth #generativeAI

Learn more about Stanford's online Healthcare AI programs: https://online.stanford.edu/artific... Check out the AI in Healthcare series playlist: https://bit.ly/AI-in-Healthcare-YT-... Matt Lungren, Stanford University - https://profiles.stanford.edu/matth... Justin Norden, Stanford University - https://med.stanford.edu/profiles/j... Guest Speaker: Troy Tazbaz, Former Head of Digital Health for the FDA Join Matt Lungren and Justin Norden, faculty members at Stanford University, as they explore the dynamic and evolving landscape of artificial intelligence in healthcare. In this special episode, they are joined by Troy Tazbaz, the Former Head of Digital Health at the FDA, for a comprehensive and thought-provoking conversation on the intersection of AI, medicine, and regulation. This episode covers a wide range of critical topics: Adoption of Generative AI in Healthcare: Dive into the rapid adoption of generative AI technologies across various industries, with a specific focus on healthcare. The discussion covers the impact of tools like AI-driven chatbots and generative models on healthcare delivery, and how they are transforming the way medical professionals and patients interact. AI Performance Improvements and Human vs. AI: The episode highlights the remarkable advancements in AI performance, with AI models now outperforming humans in certain tasks and benchmarks. Matt, Justin, and Troy explore the implications of AI’s enhanced capabilities, particularly in areas like medical diagnostics, treatment plans, and patient outcomes, and discuss the ongoing debate about AI’s effectiveness compared to human clinicians. Regulatory Challenges and Frameworks: With Troy’s experience at the FDA, the episode delves into the regulatory landscape for healthcare AI. The conversation touches on the challenges of regulating rapidly evolving AI technologies, the frameworks needed to ensure safety, efficacy, and ethical use, and how regulators are balancing innovation with the need for oversight in a fast-moving field. Top-Down vs. Bottom-Up Adoption: The discussion also covers the contrasting approaches to AI adoption in healthcare, from bottom-up innovations driven by clinicians to top-down policies and regulations. The team explores the opportunities and obstacles in leveraging AI to improve healthcare delivery, providing insights from healthcare professionals, regulators, and academics alike. Tune in for expert insights into how AI is reshaping the future of healthcare, the challenges it brings, and how leadership, innovation, and regulation are key to navigating this transformative period in medicine. Stanford Online, in collaboration with the Stanford Center for Health Education, is brought to you by the Stanford Engineering Center for Global & Online Education. #healthcareai #healthcareprofessionals

Unlocking the true potential of generative AI starts with understanding how it works. This video—the first in a new educational series—introduces healthcare professionals to large language models (LLMs) like ChatGPT: what they are, how they generate responses, and how to use them thoughtfully. Join us as we explore: • How LLMs fit into the broader landscape of AI in healthcare • What actually happens behind the scenes when you submit a prompt • The core techniques that shaped today’s most powerful models — and what the future holds Drawing from both foundational literature and the latest developments, this series translates complex AI concepts into practical insights—no computer science background required. Shivam Vedak, MD, MBA - https://medicine.stanford.edu/profi... Dong-han Yao, MD - https://med.stanford.edu/profiles/d... More about the speakers: Shivam Vedak, MD, MBA, and Dong Yao, MD, are physicians and clinical informaticists at Stanford Medicine. Their work focuses on the practical application of generative AI in healthcare, bridging system-level implementation and frontline clinician education. They have been invited to present and teach on this topic at academic institutions and conferences nationwide, reaching a diverse audience of physicians, healthcare IT professionals, and other clinical leaders. Chapters: 0:00 — Introductions and Disclosures 2:50 — Why Is Prompting Hard? 6:55 — The Three Epochs of Healthcare AI 18:01 — Tokenization and Embeddings 27:58 — Transformer Architecture and Self-Attention 34:45 — Pre-Training and the Evolution of LLMs 44:01 — Post-Training: Making the Model Helpful and Aligned 49:29 — The Reasoning Era: Scaling Test-Time Compute 54:18 — Summary: What Is an LLM?

Get more information about Stanford's Online AI programs: https://stanford.io/ai The world is being reshaped by Artificial Intelligence. From revolutionizing industries to transforming how we work and live, AI is here to stay. Are you ready to be a leader in this exciting new era? Watch this online information session and discover a comprehensive suite of online AI courses taught by Stanford's leading faculty, the pioneers of AI research and innovation. In this session, you'll gain insights into what sets our courses apart: In-Demand Skills: Our courses are continually updated, enabling you to learn fundamental concepts, and the latest tools, and techniques driving the AI revolution. Flexible Learning: We offer courses to fit your schedule, learning style, and in a variety of topics within AI to enable you to achieve your unique learning goals. Proven Expertise: You will be learning directly from Stanford faculty, at the forefront of AI research and development. You will have access to course facilitators, office hours, or TAs to ask questions throughout the course. Don't miss this opportunity to unlock your potential and become a key player in the age of AI! Hear Q&A with our AI program managers, and receive useful guidance on applying and enrolling to join our thriving AI learning community. Browse Stanford's online AI programs: https://online.stanford.edu/artific... #artificialintelligence #ai #aicourse #learnai

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai September 23, 2025 This lecture covers: 1. Class introduction 2. Examples of deep learning projects 3. Course details To learn more about enrolling in this course, visit: https://online.stanford.edu/courses... To follow along with the course schedule and syllabus, visit: https://cs230.stanford.edu/syllabus... More lectures will be published regularly. Andrew Ng Founder of DeepLearning.AI Adjunct Professor, Stanford University’s Computer Science Department Kian Katanforoosh CEO and Founder of Workera Adjunct Lecturer, Stanford University’s Computer Science Department