『AI Snacks With Romy & Roby: Democratizing AI Technologies』のカバーアート

AI Snacks With Romy & Roby: Democratizing AI Technologies

AI Snacks With Romy & Roby: Democratizing AI Technologies

著者： Dr. Anastassia Lauterbach: Democratizing AI Expert
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AI Snacks with Romy&Roby is a podcast that translates AI and robotics technologies from complex scientific concepts into easy-to-understand discussions, making them accessible for teens, parents, teachers, and anyone curious about AI. Through real-world stories and expert interviews, the show is dedicated to democratizing AI knowledge and empowering the general population to understand how AI is developed and applied in everyday life. The podcast is part of the Romy&Roby and AI Edutainment universe.Copyright 2024
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  • 87: Klara and the Sun Explained: Ishiguro's AI, Love & Sacrifice (Before the Movie) — with Rae Muhlstock

    87: Klara and the Sun Explained: Ishiguro's AI, Love & Sacrifice (Before the Movie) — with Rae Muhlstock
    2026/08/11
    Summary:Anastassia is joined by Professor Rae Muhlstock for a close reading of Kazuo Ishiguro’s Klara and the Sun — a Nobel laureate’s quiet, devastating novel narrated by an AI, and soon a major film directed by Taika Waititi, starring Jenna Ortega and Amy Adams. Dr. Rae Muhlstock is a Teaching Professor in the Writing and Critical Inquiry Program at the University at Albany (SUNY). She holds a PhD from the University at Buffalo, specializing in 20th and 21st century fiction, film, and narrative theory, and teaches a beloved course on AI, science fiction, and philosophy. Her published work spans the Classical myth of the labyrinth. She chairs the annual WCI Film Festival in Albany.This episode is part of our ongoing series “AI Through the Lens of Storytellers,” in which Anastassia and Rae discuss portrayals of AI in books and movies — from Ex Machina and Her to Data in Star Trek and After Yang — because these stories shape our expectations about AI technologies. And because art is an experiment: a way for thinkers to explore future scenarios that can’t be tested in labs.Key Takeaways:Klara is three archetypes in one. The perfect, willingly self-erasing servant; the worshipper who builds a private theology around the Sun; and the doppelgänger — a double whose purpose raises an ethical horror the novel only slowly reveals.Sacrifice may be a benchmark of life. Klara’s sacrifice is arguably the purest in the book because it comes from love without societal pressure.The most human character is the AI. Ishiguro’s humans are trapped in systems and status; it is Klara who models feeling, connection, and grace.AI in the real world is drifting toward religion. With institutions of enormous power, apostles, heretics, prophecies of doom, and millions of followers, today’s AI discourse mimics the structure of a religious movement.Keep your agency. Today’s AI mimics; it does not understand, reason, or learn from counterfactuals.Fiction is how thinkers experiment. Scientists experiment in labs; philosophers and artists experiment through stories.Chapters: 00:04 — Welcome to the storytellers series: From Ex Machina, Her, Star Trek, and After Yang to Ishiguro’s quietest, most devastating AI.02:24 — Klara goes to Hollywood: The upcoming Taika Waititi film with Jenna Ortega and Amy Adams — and what a Nobel laureate’s AI meditation becoming a studio production says about our cultural moment.03:19 — The plot (and why it’s the least interesting thing): Rae on Ishiguro’s “quiet science fiction,” first-person narrators, and the reader who always knows both more and less than Klara.07:34 — Three faces of Klara: The perfect slave, the worshipper of the Sun, and the doppelgänger — archetypes, ethical horror, and a hierarchy of machines.12:44 — Sacrifice as a sign of life: What Klara, Data, and The Creator suggest about love, agency, and the line between performing and being.19:14 — Is AI becoming a religion?: Churches, apostles, heretics, and cults in today’s AI discourse — and Capaldi, the man who doesn’t believe in the human soul.29:27 — Keep your agency: Why AI mimics rather than understands, the missing math of counterfactuals and causality, and the “chosen ones” narrative of AI builders.36:42 — Fiction as an experiment — and the classroom: Checking ChatGPT’s math, cheating smart vs. cheating dumb, hidden environmental costs, and why we must always ask why. Hyperlinks:Rae Muhlstock University at Albany faculty profileLinkedInAnastassia Lauterbach - LinkedInFirst Public Reading, Romy, Roby and the Secrets of Sleep (1/3)First Public Reading, Romy, Roby and the Secrets of Sleep (2/3)First Public Reading, Romy, Roby and the Secrets of Sleep (3/3)AI Snacks with Romy and Roby@romyandroby“Leading Through Disruption”AI EdutainmentThe AI Imperative BookRomy & Roby BookSubstack
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    42 分
  • 86: AI Changing Medical School with Dr. Marschall Runge on the Future of Doctors

    86: AI Changing Medical School with Dr. Marschall Runge on the Future of Doctors
    2026/08/04
    Dr. Marschall Runge returns for a second conversation, this time about the people who will practice medicine next. Marschall S. Runge, MD, PhD, is a practicing cardiologist who spent a decade as executive vice president for medical affairs at the University of Michigan, dean of the Medical School, and CEO of Michigan Medicine — running one of America's largest academic health systems while continuing to see patients.He earned his PhD in cardiovascular molecular biology at Vanderbilt and his MD at Johns Hopkins, where he also completed his internal medicine residency, followed by a cardiology fellowship at Massachusetts General Hospital. He now leads a Michigan cohort combining epigenetic aging clocks, mitochondrial inheritance, cardiorespiratory fitness, and chronic inflammation in a single dataset.He has authored more than 195 peer-reviewed papers and holds five healthcare patents. A third nonfiction book, on epigenetic clocks and biological aging, is in development with Forbes Books, alongside a forthcoming Substack (The Longevity Switch) and a University of Michigan MOOC on epigenetics and aging.Chapters00:00 Introduction and guest overview01:12 AI's role in healthcare transformation04:01 AI as a valuable assistant in medicine05:08 Redefining medical curriculum for AI era09:34 Openness of medical institutions to AI11:47 Changing accreditation and certification with AI16:08 Leadership in AI adoption in healthcare18:39 International perspectives on AI in medicine19:13 AI's impact on radiology and diagnostics21:46 AI in clinical workflows and operations24:49 The evolving role of nurses with AI30:37 Digital twins and clinical trials33:18 Transition period and future outlookHyperlinks:The Great Healthcare Disruption: Big Tech, Bold Policy, and the Future of American Medicine (Forbes Books, 2025) — USA TODAY Best-Seller and Global Book Awards Gold Medal winner. An insider's account of the forces reshaping American healthcare. Coded to Kill (Post Hill Press, 2023) — a techno-medical thriller.Amazon author pageDr. Runge WebsiteOpenEvidence — the physician-only clinical AI Runge calls superb University of Michigan Medical SchoolU-M Center for Academic Innovation Anastassia Lauterbach - LinkedInFirst Public Reading, Romy, Roby and the Secrets of Sleep (1/3) First Public Reading, Romy, Roby and the Secrets of Sleep (2/3) First Public Reading, Romy, Roby and the Secrets of Sleep (3/3) AI Snacks with Romy and Roby@romyandroby “Leading Through Disruption”AI EdutainmentThe AI Imperative BookRomy & Roby BookSubstack
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    35 分
  • 85: Can AI Find New Problems, Not Just Answers? with Matthias Röder (Beyond Human Series, #4)

    85: Can AI Find New Problems, Not Just Answers? with Matthias Röder (Beyond Human Series, #4)
    2026/07/28
    SummaryAI is extraordinary at finding answers. But who finds the problem?In the 4th of our Beyond Human series, Anastassia and Matthias Röder go after a question: can an AI formulate a genuinely new problem, or is it forever confined to solving the ones we hand it?Dr. Matthias Röder is a music and technology strategist based in Salzburg, and one of the most consistently original thinkers on creativity and machines that we know.He is a former Managing Director of the Eliette and Herbert von Karajan Institute and a board member of the Karajan Foundation, as well as a trustee of the Mozarteum Foundation. He is co-founder and managing partner of The Mindshift, a consultancy on creative leadership and innovation strategy.Matthias directed the Beethoven X project, the AI-assisted completion of Beethoven's Tenth Symphony, work that earned an Effie Bronze. He founded the Karajan Music Tech Conference in 2017 and launched the Classical Music Hack Day series in 2013. He holds a PhD in music from Harvard University and is an alumnus of the Mozarteum University Salzburg. His work has been recognized with the "Game Changer" award of the Salzburg Chamber of Commerce.Chapters00:01 Welcome, and the question behind the episode: can AI formulate problems, not only answer them?01:48 In music, the problem is the composition — why framing the question is the hardest creative act03:17 35 million papers, 4,000 a day: PubMed, AlphaFold, and what no human can read05:58 GNoME and 2.2 million crystals — when the hypothesis machine outruns the laboratory09:09 World models, physical intuition, and the questions AI does not know to ask11:36 A map of all unsolved problems: knowledge graphs as an orchestration engine15:16 Progress without consensus — why agreement may be the most expensive thing we do17:24 Theory of mind, Belle and Rock Experiment, and why your chatbot keeps telling you that you are a genius24:20 Context contamination, hallucinations, and professional AI hygiene30:50 Organizational elasticity, the 2×2 of known and unknown, and three papers worth your timePapers mentioned in the episode:Towards Scientific Discovery with Generative AI: Progress, Opportunities and Challenges — a survey of AI across the full scientific discovery cycle, from literature analysis and brainstorming through theory refinement, experimental design and data-driven discovery.The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence — an ambitious argument that AI is approaching the ability to close the scientific loop autonomously, from hypothesis generation through experimental design to validation.Machine Learning as a Tool for Hypothesis Generation — a procedure for generating hypotheses from high-dimensional behavioural data and testing them on held-out human subjects, grounded in economics and behavioural science.Also referenced: DeepMind's AlphaFold and GNoME; AI Feynman and the rediscovery of fundamental physics equations from data alone; Yann LeCun on world models; Jorge Luis Borges, The Library of Babel.Hyperlinks:Anastassia Lauterbach - LinkedInFirst Public Reading, Romy, Roby and the Secrets of Sleep (1/3)First Public Reading, Romy, Roby and the Secrets of Sleep (2/3)First Public Reading, Romy, Roby and the Secrets of Sleep (3/3)AI Snacks with Romy and Roby@romyandroby“Leading Through Disruption”AI EdutainmentThe AI Imperative BookRomy & Roby BookSubstack
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    39 分
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