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Astrophysicist Risa Wechsler studies the evolution of the universe. She says that our understanding of how the universe formed and how it will change over time is changing as new technologies for seeing and measuring space come online, like a new high-resolution camera that can quickly map the full sky to see everything that moves, or new spectrographs that will map the cosmos in 3D and enable us to get new clues about the elusive dark matter. You can’t understand the universe or our presence in it until you understand dark matter, Wechsler tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
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(00:00:00) Introduction
Russ Altman introduces guest Professor Risa Wechsler, professor of physics, particle physics, and astrophysics from Stanford University.
(00:01:46) Tools for Studying the Universe
Technologies and methods used to study galaxies and the universe, including the Rubin Observatory's Legacy Survey of Space and Time.
(00:04:37) Understanding Maps of the Universe
The concept of mapping the universe in two and three dimensions, the significance of redshifts, and the application of spectroscopy.
(00:08:56) The Structure and Scale of the Universe
The age, expansion, and overall structure of the universe, touching on its isotropic nature and clumpiness on different scales.
(00:12:23) Delving into Galaxy Formation and Evolution
An in-depth look at galaxy formation, the role of dark matter, and how galaxies have evolved over billions of years.
(00:14:49) The Diversity of Galaxies and Their Structures
The various types of galaxies, including satellite and dwarf galaxies, and how they form and evolve differently.
(00:18:56) Dark Matter and Dark Energy
The fundamental aspects of dark matter and dark energy, their role in the universe, and the challenges in studying them.
(00:22:32) Mapping the Universe with Modern Tools
How current technologies and methods contribute to our understanding of the universe’s expansion and structure
(00:24:57) Applying Cosmic Understanding
The SAGA Survey and its implications for understanding the Milky Way in a broader cosmic context.
(00:29:29) Conclusion
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Guest Jeannette Bohg is an expert in robotics who says there is a transformation happening in her field brought on by recent advances in large language models. The LLMs have a certain common sense baked in and robots are using it to plan and to reason as never before. But they still lack low-level sensorimotor control — like the fine skill it takes to turn a doorknob. New models that do for robotic control what LLMs did for language could soon make such skills a reality, Bohg tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
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(00:00:00) Introduction
Russ introduces guest Professor Jeannette Bohg, an expert in robotics from Stanford University.
(00:01:58) AI's Impact on Robotics
How AI is transforming robotics and the use of AI in high-level planning and reasoning in robotics.
(00:04:26) Challenges of Applying Language Models in Robotics
The challenges and potential of using large language models for robotic task planning and interaction between humans and robots.
(00:07:06) Data Shortages in Robotics
The scarcity of training data in robotics compared to other AI fields and its impact on development.
(00:10:43) Human-Robot Interaction and Augmentation
The potential for robots to augment human capabilities rather than replace them and different approaches to autonomy in robotics.
(00:16:41) The Future of Robotic Hardware
The current state of robotic hardware, its limitations, and what the future might hold for robotic development.
(00:19:53) The Financial and Practical Realities of Robotic Research
Cost and maintenance challenges associated with robotic research platforms, as well as practical applications of robotics in everyday life.
(00:25:11) Humanoid Robots vs. Practical Robots
The practicality and implications of designing robots that mimic human appearance and capabilities.
(00:27:55) Future Outlook and Commercial Viability
The future outlook for robotic platforms and when they might become commercially available.
(00:29:08) Conclusion
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Guest Sergiu Pasca is a physician-scientist who turns skin cells into stem cells and then into brain tissues he calls “organoids” and “assembloids” in order to study psychiatric and neurological illness in a dish instead of in living human beings. With this knowledge, Pasca hopes to develop new treatments for conditions ranging from schizophrenia and autism spectrum disorders to chronic pain, he tells host Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast.
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(00:00:00) Introduction
Russ introduces guest, Sergiu Pasca, professor of Psychiatry and Behavioral Sciences at Stanford University.
(00:02:43) The Science of Growing Brain Tissue from Skin Cells
The process of developing brain organoids from skin cells and the potential medical applications of these models.
(00:03:59) Enhancing Neurological Research Tools
Advancing the complexity of brain models to include various brain structures and their applications in modeling diseases.
(00:07:20) Introduction of Assembloids
Introduction to assembloids, detailing how combining different organoids can mimic complex brain structures
(0015:58) Testing Therapeutics Using Humanized Models
The innovative approach of using humanized rat models to test neurological therapies and drugs.
(00:21:03) Complex Circuit Modelling for Disease Understanding
The current capabilities of modeling complex brain circuits and their relevance in understanding the neural pathways involved in diseases.
(00:23:36) The Future of Pain Modelling and Drug Testing
How assembled brain cells can model pain perception and response, leading to potential new treatments for chronic pain and psychiatric disorders
(00:27:46) Ethical Considerations and Public Engagement
Ethical concerns related to creating brain-like tissues and the importance of public engagement in scientific research.
(00:32:01) Future Directions and Global Collaboration
The future of brain organogenesis research and the potential impacts on treating neurological and psychiatric conditions.
(00:34:05) Conclusion
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With TikTok in the hands of 170 million Americans, cybersecurity expert Amy Zegart says it’s time to talk about consequences. Foreign access to all that data on so many Americans is a national security threat, she asserts. For those as concerned as she, Zegart has good news and bad. The government has gotten better at fighting cyberthreats, but artificial intelligence is making things very complicated, very fast. The US needs to adapt quickly to keep pace, Zegart tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
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Chapters:
(00:00:00) Introduction
Host Russ Altman introduces guest Amy Zegart, a cybersecurity expert from Stanford University.
(00:02:37) Government and Cybersecurity Speeds
How AI has changed the pace at which both government and cyber attackers operate, and the evolving dynamics of cybersecurity efforts.
(00:04:12) Corporate Cybersecurity
The unexpected role of the SEC in regulating corporate cybersecurity efforts and how the cyber attack surface has expanded beyond traditional big industries
(00:07:30) Global Cyber Threats and Preparedness
Insights into the strategic use of cyber operations by other countries, and the multifaceted nature of international cyber relations.
(00:09:13) Cyber Dynamics in the Russia-Ukraine Conflict
The cyber aspects of the Russia-Ukraine conflict and its implications for global cybersecurity strategies.
(00:11:35) Misinformation and Disinformation Dynamics
The difference between misinformation and disinformation, their impacts on society and the challenges in combating them.
(00:15:04) TikTok and National Security
Risks associated with TikTok as a platform controlled by Chinese interests, discussing data privacy and potential for foreign influence.
(00:20:11) Corporate Power in AI and National Security
The role of corporations in national security through their control over AI, and the challenges this poses for regulation and innovation.
(00:22:47) Learning from Cybersecurity to Manage AI Risks
Lessons from cybersecurity that could help manage emerging AI risks, highlighting the need for developing independent AI research capacities.
(00:26:44) European Regulation and Global AI Safety
The European approach to AI regulation and data protection, advocating for international AI safety norms and collaborative efforts.
(00:29:21) AI's Role in Enhancing Intelligence
How AI can transform intelligence services, and advancements that could lead to significant efficiency gains in national security.
(00:31:23) Conclusion
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A best of episode where Russ interviews one of his bioengineering colleagues, Fan Yang, about some of the fascinating work she’s doing in the realm of tissue engineering. Hear more about the ways her lab is modeling human tissue to help develop a better understanding of how we might effectively replace damaged tissues and alleviate a number of health concerns.
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Chapters:
(00:00:00) Introduction
Host Russ Altman introduces guest Fan Yang, a bioengineer at Stanford.
(00:03:15) The Basics of Tissue Engineering
The purpose and significance of tissue engineering, emphasizing its role in addressing critical medical needs like late-stage arthritis.
(00:04:23) Challenges in Tissue Engineering
Technical hurdles in creating viable tissues for clinical use, such as integrating these tissues into the human body.
(00:07:00) 3D Printing and In Situ Polymerization
Technological advances in shaping tissues using 3D printing and the benefits of in situ polymerization to adapt to complex tissue shapes.
(00:09:15) Specific Challenges with Cartilage
The challenges specific to cartilage regeneration, explaining why it has been a difficult tissue to replicate and heal.
(00:13:56) Micro Ribbon Based Hydrogels
Explanation of micro ribbon based hydrogels, a new development aimed at improving tissue regeneration.
(00:19:16) Cancer Research and Tissue Engineering
How tissue engineering technologies are not only pivotal for therapeutic uses but also crucial for understanding diseases and aiding drug discovery.
(00:24:38) Regulatory Challenges and Commercialization
The regulatory and commercialization challenges facing new medical technologies, including the need for industry partnerships and the role of the FDA
(00:26:20) Conclusion
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A best of episode where Russ interviews computer scientist and electrical engineer, Dorsa Sadigh. They had a fantastic conversation about the work she’s doing to train robots to better understand humans, and as she shares, it turns out that one key to this work is better understanding human behavior. If you’re curious about how we’re going to make human-robot interaction work, this is a great episode to tune into again. Enjoy.
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Chapters:
(00:00:00) Introduction
Host Russ Altman introduces guest Professor Dorsa Sadigh, a computer scientist and electrical engineer at Stanford.
(00:02:24) Bridging Robotics and Human Psychology
The journey from focusing solely on robotics to incorporating human behavioural insights to enhance robot design and functionality.
(00:05:31) Blending Cognitive Science and Robotics
The integration of cognitive science with robotics to build better computational models of human behaviour.
(00:07:35) Addressing Suboptimal Human Decision Making
Exploring human decision-making biases and their impact on robot interaction, with focus on bounded rationality and prospect theory.
(00:10:39) Robot Adaptations to Human Imperfections
How robots can adapt to human imperfections in collaborative tasks, using theories from behavioural economics.
(00:14:57) Training Robots and Humans for Better Interaction
Strategies for teaching both humans and robots to improve their interactions, including active teaching and understanding each other’s capabilities.
(00:18:41) Partner Modelling in Robotics
Insights into partner modelling in robotics, demonstrated through a scalable model in an air hockey game setup.
(00:21:54) Complex Multi-Agent Interactions
Addressing the dynamics of multi-agent systems like traffic, where autonomous and human-driven vehicles interact.
(00:24:11) Robots in Healthcare
The role of robots in healthcare, particularly in assistive technologies, and the challenges and advancements in this area.
(00:26:26) Conclusion
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We’re bringing back an episode about trust and AI. In a world where the use of Artificial Intelligence is exploding, guest computer scientist Carlos Guestrin shares insights from the work he’s doing to support the development of trust between humans and machines. We originally recorded this episode in 2022, but the insights are just as if not more relevant today. We hope you’ll take another listen and enjoy.
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Chapters:
(00:00:00) Introduction
Russ Altman introduces the episode with guest Carlos Guestrin, a professor of computer science at Stanford, whose focus is bringing AI into broader use.
(00:02:58) Current Status of AI
The current capabilities of AI and machine learning and the widespread use and integration of these technologies.
(00:05:44) Deep Dive into Trust and AI
Three core components of trust in AI and how these factors influence the adoption and efficacy of AI systems.
(00:09:43) Technical Challenges in Implementing Trust
The challenges of translating the abstract concepts of trust into practical, implementable AI features.
(00:14:32) Enhancing AI Transparency and Generalization
Methods to improve AI’s generalisation capabilities and transparency.
(00:18:00) The Role of Open-Source in AI Development
The impact of open-source software on the AI field, highlighting the benefits of shared knowledge and collaborative advancements.
(00:22:34) AI in Healthcare
Healthcare and the use of AI in enhancing data-driven decisions in medical treatments.
(00:27:11) Conclusion
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Guest Anna Lembke is a psychiatrist and a specialist in the behavioral sciences who studies addiction. While there is tremendous variety in the things people can be addicted to, all forms are tied to dopamine, a biochemical that is key to human senses of pleasure, reward, and motivation. She says that new treatments are combining traditional abstinence with programs that help patients reenergize dopamine centers in the brain through physical exercise, which is a known producer of dopamine. If patients can reach 30 days of abstinence there is a good chance at recovery, Lembke tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
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Chapters:
(00:00:00) Introduction
Host Russ Altman introduces guest Professor Anna Lembke, a professor of psychiatry and behavioral sciences at Stanford University, and an expert on addiction.
(00:02:27) The Personal Nature of Addiction
Professor Lembke shares a personal story of addiction to romance novels, providing insight into how seemingly benign habits can become harmful addictions.
(00:06:02) The Brain Chemistry of Addiction
What happens in the brain during addiction, including dopamine's role in pleasure, reward, and the process of becoming addicted.
(00:11:10) Addressing Addiction in Healthcare
How the medical community has evolved in recognizing and treating addiction, partly due to the opioid epidemic.
(00:13:23) Strategies for Managing and Treating Addiction
Treatment approaches for addiction, including the concept of hormesis, and how engaging in challenging physical activities can help manage addictive behaviors.
(00:17:31) Treatment and Recovery from Addiction
Professor Lembke’s own experience with overcoming her addiction through self-intervention and “dopamine fasting”.
(00:22:05) The Addictive Personality and Genetic Vulnerabilities
The concept of an "addictive personality," genetic predispositions to addiction, and how these factors play into the challenge of treating and managing addiction.
(00:23:29) The Opioid Epidemic: Insights and Challenges
An update on the opioid epidemic, the rise of fentanyl, and the ongoing challenges in addressing opioid addiction.
(00:29:08) The Future of Addiction
The broader context of addiction in society, emphasizing the importance of addressing addiction to digital media and other non-substance-related addictions
(00:29:57) Conclusion
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Humans and computers making music together, it’s the best of both worlds.
Ge Wang is a professor of music, a computer scientist, and director of the Stanford Laptop Orchestra – an orchestra in which human musicians and computers collaborate to make music. “I once thought computer music was abstract and inaccessible, but it can be very playful, too,” he says. Humans and computers making music together, it’s the best of both worlds, Wang tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
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(00:00:00) Introduction
Host Russ Altman introduces guest Professor Ge Wang and his work around the intersection of AI, computer science, and music.
(00:02:48) Early Inspirations and Merging Music with Technology
Ge Wang shares his early experiences with music and computers, leading to his unique career path combining both passions.
(00:07:42) Developing Musical Tools and Instruments
Significance of playfulness in merging music with computer science, illustrated by projects like the Ocarina app and the Stanford Laptop Orchestra.
(00:13:27) The Role and Impact of AI in Music
The evolution of AI in music, with deeper questions about AI's role and the value of human creativity.
(00:18:28) Music, AI, and Future Generations
The future of music and AI in the context of a parent, and the cultural dimensions and values that will shape the use of technology in art.
(00:20:19) Ethical and Cultural Concerns of AI in Music
Ethical dilemmas and cultural implications of using AI in music, copyright issues and the potential for generic AI-generated content.
(00:25:09) Rethinking the Role of AI in the Creative Process
AI’s role in creativity, the value of the creative process over the mere output, and the potential for AI to enrich rather than replace human creativity.
(00:29:32) The Concept of a Pi-Shaped Person
The "Pi-Shaped Person," with emphasis on the importance of disciplinary expertise, domain knowledge, and an aesthetic lens.
(00:33:52) Conclusion
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Laura Simons is a clinical psychologist and an authority on pain, particularly chronic pain in childhood, which is much more common than widely understood. Most people don't even think chronic pain happens in children, says Simons. The consequences, however, are serious, ranging from learning gaps from missed school to social isolation and even depression. Better treatment begins with a better understanding of the science of pain, as Simons tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
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(00:00:00) Introduction
Host Russ Altman introduces guest Laura Simons and her research on chronic childhood pain.
(00:02:34) Understanding the Scope and Causes of Childhood Chronic Pain
Common forms of childhood pain, its underlying causes, and the impact of unrecognized chronic conditions.
(00:05:08) Diagnostic Challenges and Family Dynamics
The difficulties in diagnosing chronic pain in children and adolescents, and the role of family in recognizing and managing a child's chronic pain.
(00:07:38) The Impact of Chronic Pain on Children's Lives
How chronic pain affects children's daily lives, from school attendance and social interactions to the broader family impact.
(00:10:15) Transitioning from Adolescent to Adult Pain Management
The challenges young people face as they move from pediatric to adult pain management systems and the importance of tailored transitional programs.
(00:12:07) Treatment Approaches and Innovations
Treatment strategies for childhood chronic pain, emphasizing non-pharmacological approaches such as behavioral interventions and physical therapy.
(00:19:14) Empowered Relief Program and Its Adaptation for Teens
The Empowered Relief program, adapted for teens, focusing on pain science education and the development of coping strategies.
(00:23:48) Exploring Virtual Reality and Sensory Retraining Techniques
Advanced treatment methods, including the use of virtual reality to enhance physical therapy and sensory retraining techniques to manage pain sensitivity.
(00:28:57) Conclusion
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