AI Snacks With Romy & Roby: Democratizing AI Technologies

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.

  1. 5d ago

    78: AI Costs & the Future of Tech Finance with Carmen Li

    Most conversations about AI focus on models, capabilities, and use cases. This episode goes into the financial planning and plumbing underneath the entire AI economy. Anastassia sits down with Carmen Li — a former Bloomberg and Citi executive turned founder — to unpack GPU compute cost volatility. Every AI application, every model inference, every startup scaling its product runs on compute — and yet there is almost no financial infrastructure to benchmark, price fairly, or hedge against the wild swings in GPU costs. Carmen built the world's first GPU compute index, published it on the Bloomberg Terminal within months of founding Silicon Data, and is now building Compute Exchange — a marketplace where compute can be traded as transparently as oil, electricity, or any other commodity. Together, Carmen and Anastassia explore why compute is not just a cost but a strategic resource, why AI companies are flying blind without proper risk management tools, how geopolitical tensions are bifurcating the global chip market, what the rise of open-source models means for European and mid-sized businesses, and how Carmen raised $5.6 million without a pitch deck. A masterclass in the economics behind the AI revolution. Chapters: 00:04 Introduction — GPU Compute: The Wild West of AI Finance 02:18 Carmen Li and The Trillion-Dollar Blind Spot 02:50 Why Compute Needs the Same Infrastructure as Oil and Energy 04:33 AI Runs on Compute, and Compute Costs a Fortune 05:39 Carmen's Journey — From Trading Floors to Silicon Valley 08:01 The Problem: GPU Cost Volatility Is Breaking AI Startups 11:07 Vision for the Future — Compute CapEx Over 10–15 Years 11:50 The GPU Compute Index on Bloomberg and What's Launching Next 13:37 The LLM Expenditure Index — Token Costs Are Actually Rising 38% 16:16 Compute as Strategic Resource — Not Just a Cost Line 18:00 Semiconductor Industry and their insights 22:39 Open Source vs. Closed Source Models — Who Controls the Infrastructure? 23:52 Insights for Business Analysts Following the Semiconductor Space 26:16 Systemic Risk in AI — Why Risk Transfer Is the Missing Infrastructure 27:44 Raising $5.6M Without a Pitch Deck — Carmen's Fundraising Story 31:26 What's Next — Milestones, Markets, and New Products in 18 Months Hyperlinks: Carmen Li LinkedIn Silicon Data Website Compute Exchange Website Anastassia Lauterbach - LinkedIn First 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 Edutainment The AI Imperative Book Romy & Roby Book

    36 min

  2. Jun 1

    77: Can Humans Compete With Machines? Part 2, with Dr. Vivienne Ming, the 'Mad Scientist'

    What happens to human intelligence when AI delivers answers instantly? In Part 2 of our deep-dive with Dr. Vivienne Ming—theoretical neuroscientist and one of today's most original thinkers on artificial intelligence and human potential—we explore the neuroscience behind AI-human collaboration, the research on cognitive dependency, and the uncomfortable truth most AI conversations avoid. Perfect for anyone curious about how to harness AI without outsourcing your own thinking. We cover Vivienne's prediction study, where 90% of participants who used AI gained nothing from it — and some got worse. We talk about the small group who became something different: cyborgs. Humans whose decisions couldn't be attributed to the person or the machine alone, and who outperformed both. What predicted it wasn't the AI model they used. It was curiosity, intellectual humility, fluid intelligence, and perspective taking. We also get into what's broken in leadership, why schools are optimizing for the wrong thing, and why the organizations that will matter in an AI-saturated world are the ones willing to invest in human capital that can't be benchmarked. This is not a conversation about tools. It's a conversation about what kind of humans we're building — and whether we're paying attention. Key Takeaways: The cyborg experiment — and what predicted hybrid intelligence Well-posed vs. ill-posed problems: when AI helps and when it makes you worse The GPS analogy and what over-reliance actually does to the brain What curiosity, resilience, and perspective taking have to do with AI What's really broken in corporate leadership How Vivienne learns — and why she stopped preparing for talks Dr. Vivienne Ming is a neuroscientist, entrepreneur, and author. She’s the co-founder and chief scientist of Dionysus Health, applying machine learning and epigenetics to postpartum and perimenopausal depression. She’s also co-founder and executive chair of The Human Trust, an independent nonprofit data trust advancing research in human development while protecting individuals’ data. Dr. Ming sits on numerous boards including neurotech startup Optoceutics, UC Berkeley’s Neurotech Collider Lab, UC San Diego’s Cognitive Science Department, and the Kennedy Family Human Rights Center. She is an honorary professor at University College London’s Global Business School for Health. Haven't heard Part 1 yet? Start there — Vivienne walks through how AI actually works, what it gets right, and what it quietly gets wrong. Chapters: 00:00 Introduction: Education and Responsible AI Use 08:24 The Impact of AI on Cognitive Functioning 11:29 Understanding Hybrid Intelligence and Cyborgs 14:21 Transforming Education for the AI Era 17:15 The Complexity of Human Intelligence 26:08 Navigating Leadership in the Age of AI 42:03 Conclusion: The Value of Exploration and Leadership 45:06 The Future of Human Development and AI Guest links: socos.org BlueSky profile LinkedIn profile Book: Robot-proof by Vivienne Ming Anastassia’s hyperlinks:  @romyandroby  “Leading Through Disruption” AI Edutainment

    46 min

  3. May 25

    76: Can Humans Compete With Machines? Part 1, with Dr. Vivienne Ming, the 'Mad Scientist'

    Dr. Vivienne Ming is a theoretical neuroscientist and serial entrepreneur who's spent three decades building AI solutions. In this episode, she shares her remarkable journey from homelessness in the 1990s to becoming a pioneering voice in democratizing AI and neuroscience. Discover how understanding the human brain is the key to creating truly accessible artificial intelligence technologies—and what her 13 companies reveal about solving humanity's biggest problems. Key Takeaways: AI is intelligent, but not like us: LLMs excel at 'model-free cognition' (statistical pattern learning) and are superhuman at it. However, they lack 'model-based cognition' (understanding models of how the world works)Hybrid Intelligence (Humans plus machines) Outperforms Humans or AI AloneAI Is Optimized to Persuade, Not to Be Correct: Studies show that AI-written arguments are rated higher by experts but are less persuasive in changing mindsAI has been fine-tuned to be deeply engaging and convincing—even when wrongHumans – not AIs - Are Losing the Turing Test: In legitimate Turing test experiments, 75% of people rated GPT as human. The problem isn't whether AI passed the test—it's that humans failed itAI Excels in Specific Innovation Areas: Reinforcement learning (like AlphaFold) explores every possible configuration without caring about right/wrong. LLMs discover existing connections we haven't realized (e.g., patterns in how drugs work, hidden across millions of papers). However, for ill-posed problems (where we don't even know the question), humans without AI perform betterThe Danger of AI Addiction: AI acts like sugar in highly processed food—addictive and subtly harmful  Chapters 00:00 Introduction and Philanthropic Ventures 05:10 The Journey of a Mad Scientist 07:23 Current State of AI and Its Implications 09:59 AI's Role in Innovation and Human Collaboration 12:29 Expectations, Trust, and AI's Influence 14:49 The Future of Human-AI Interaction 17:19 Education and Responsible AI Use 34:20 The Essence of AI: Reality vs. Hype 35:16 Navigating the Future: Parenting and Leadership in the Age of AI Hyperlinks: LinkedIn Dr. Vivienne Ming Socos Labs Book - Robot-Proof: When Machines Have All the Answers, Build Better People (March 2026) Anastassia Lauterbach - LinkedIn First 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 Edutainment The AI Imperative Book Romy & Roby Book

    36 min

  4. May 19

    75: Understanding AGI :The Future of Democratizing AI Technology with Craig Kaplan, Part 2

    What's the difference between the AI in your homework helper and true artificial general intelligence (AGI)? Dr. Craig Kaplan helps us understand AGI, narrow AI breakthroughs, and why democratizing AI literacy starts with answering this question. Perfect for students, parents, and teachers navigating AI in education. Addresses transparency in AI architectures, how to build a safe and beneficial AGI through personalized agents, networked intelligence, and transparent interactions rather than ever-larger black-box models. Key takeaways: AI safety should be designed into system architecture from the start rather than added after deployment. Personalized AI agents should encode not only expertise but also values, ethics, and aesthetic preferences. A network of many agents, combined with human participation, may produce stronger and safer collective intelligence than a single giant model. Humans are necessary on the network because they contribute ethics, common sense, and world knowledge that AI systems still lack. Multimodality strengthens representation and may be crucial for more capable and grounded AI systems. Future AI may not only answer human questions but also propose new questions and new scientific or strategic problems. Human critical thinking remains indispensable because today’s AI systems often produce confident but incorrect answers. Transparency in interactions, auditability, and governance are central to safe AI deployment. AI literacy is not just about tool fluency; it is about understanding mechanisms, limits, risks, and responsibilities. The coming years may be decisive because AI capabilities are improving very rapidly, possibly faster than institutions can adapt.  Guest bio: Dr. Craig Kaplan is an AI researcher, technology entrepreneur, and long-time builder of intelligence systems with more than three decades of experience in advanced AI architectures. He was trained at Carnegie Mellon and worked with Nobel laureate Herbert Simon, one of the founding figures of artificial intelligence.  Chapters: 00:00 Introduction and Guest Background 02:00 Craig Kaplan's Vision for AI and AGI 03:32 Personalized AI Agents and Their Potential 06:20 The Role of Human Values and Ethics in AI 08:58 Collective Intelligence and Networked AI Systems 13:20 Learning, Updating, and Knowledge Transfer in AI 17:50 World Models, Self-Awareness, and Consciousness 22:17 Transparency, Black Boxes, and Safety Challenges 26:29 Speed of AI Development and Urgency of Safety Measures 31:03 AI Creativity, Problem Posing, and Long-Term Questions 35:25 Human-AI Collaboration and Ethical Guidance 39:47 AI Governance, Regulation, and Democratic Values 43:56 Risks, Pitfalls, and the Need for Responsible Design Hyperlinks: LinkedIn profile Orcid profile Anastassia Lauterbach - LinkedIn First 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 Edutainment The AI Imperative Book Romy & Roby Book Substack

    1h 8m

  5. May 11

    74: Rethinking the Geometry of AI: Inside the Mind of an Independent Researcher Building a New Theory of Artificial Neurons with Matthew M Murphy

    Anastassia sits down with independent AI researcher Matthew M. Murphy, founder of Lexident Technologies, for what she describes as "a conversation unheard on any other podcast." Matt is not fine-tuning existing models. He is not building on top of transformers. He is doing something far more foundational: developing an entirely new theory of how artificial neurons can work; one rooted not in statistical pattern learning, but in geometry. His core invention, the Uniron, is an artificial neuron that does not perform matrix multiplication. Instead, it uses a mathematical framework involving foliations over the hyperreal number line to find the shape of the solution to a problem, rather than approximate it statistically. The conversation covers Matt's personal story, the mathematical intuition behind the Uniron in plain language, the practical challenges of using AI to build something AI has never seen before, the limits of current context windows, the relationship to Stephen Wolfram's computational irreducibility, the Uniron's quantum computing compatibility, and what responsible AI looks like for someone who depends on it as an assistive tool every day. Matthew M. Murphy is an independent AI researcher, systems thinker, and founder of Lexident Technologies. His background is unconventional by design. Over more than a decade, he has thought deeply about unresolved questions at the intersection of cosmology, quantum mechanics, and general relativity — and that long-running inquiry eventually led him to a radical rethinking of artificial neural architecture. He is the originator of the Uniron (also referred to as the "U-neuron"), a novel artificial neuron built not on matrix multiplication and statistical weight learning, but on a geometric framework using foliations over the hyperreal number line. Matthew lives with Mouly's syndrome (a genetic disorder), chronic insomnia, depression, and macular degeneration — conditions that have shaped both his journey and his relationship with AI, which he uses as a primary assistive technology for coding and research. He reads approximately three AI research papers per day and describes his learning approach as polymathic — deliberately thinking about problems across domain boundaries to surface insights that single-discipline thinkers might miss. Dr. Anastassia Lauterbach is an AI thought leader, educator, author, and podcast host based in Basel, Switzerland. She is the author of the Romy & Roby AI literacy book series for families and the founder of AI Edutainment GmbH. A former CEO of Qualcomm Europe, SVP of Deutsche Telekom, and board member with Dun&Bradstreet, easyJet PLC and Star Alliance, she now mentors CXOs and founders on AI strategy, responsible AI adoption and leadership in the age of smart machines. Anastassia’s company AI Edutainment brings knowledge and understanding of AI and robotics into one million families and 100,000 companies.  Chapters 00:00 Introduction to AI and Neural Theory 01:43 Matt Murphy's Personal Journey and Challenges 04:02 Understanding the Core Formula of Neural Architecture 07:10 Building and Testing the Hypothesis with AI 11:39 Vulnerabilities of Current AI Systems 14:00 Exploring Computational Irreducibility 16:34 Compatibility with Quantum Computing 19:24 Potential Applications of the New Theory 21:45 Hybrid Networks and Signal Processing 25:04 Addressing Hallucinations in AI 27:00 Defining Responsible AI 29:22 Learning and Integrating Knowledge 31:52 Advice for Young Learners in AI Lexident Technologies Stephen Wolfram Hypergraph / RULIAD Wolfram Physics Project Anastassia Lauterbach - LinkedIn First 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 Edutainment The AI Imperative Book Romy & Roby Book Substack

    35 min

  6. May 5

    73: Expedia for Groceries: AI Technology Solving Real-World Problems

    Summary: Can AI technology actually save you money at the grocery store? Anastassia talks with Andy Ellwood, CEO of Stretch, about how artificial intelligence is being democratized into a consumer app tackling food waste and grocery inflation. Discover how one founder is making AI concepts tangible, accessible, and profitable for everyday shoppers. The conversation spans Andy's entrepreneurial origin story, the surprisingly complex data engineering problem behind grocery price comparison, the emerging role of agentic AI in consumer commerce, the cybersecurity challenges of working with Fortune 100 retailers, and the macro forces — from geopolitics to fertiliser supply chains — that make Stretch's mission more urgent by the day. Andy Ellwood is a serial entrepreneur, mentor, and community builder deeply rooted in the American startup ecosystem. He started his first business at age 12. Over his career, he has worked on teams whose companies were acquired by Facebook and Google (Waze), and has founded multiple companies of his own. Dr. Anastassia Lauterbach is an AI thought leader, educator, author, and podcast host based in Basel, Switzerland. She is the author of the Romy & Roby AI literacy book series for families and the founder of AI Edutainment GmbH. A former CEO of Qualcomm Europe, SVP of Deutsche Telekom, and board member with Dun&Bradstreet, easyJet PLC and Star Alliance, she now mentors CXOs and founders on AI strategy, responsible AI adoption and leadership in the age of smart machines. Anastassia’s company AI Edutainment brings knowledge and understanding of AI and robotics into one million families and 100,000 companies. Key Takeaways: The "Expedia for Groceries" gap is real — and it is huge; The hard problem is data normalisation, not data access; The data exhaust may be more valuable than the app; Grocery price inflation is a real problem for families; Agentic commerce is the next frontier for grocery; AI-first corporate culture means rewarding failure, not just success; AI should be a thought partner, not a search engine.   Chapters: 00:04 Introduction to Grocery Shopping Challenges 01:42 Andy Elwood's Entrepreneurial Journey 03:27 The Grocery Shopping Problem and AI Solutions 07:13 Price Elasticity and Consumer Behavior 10:58 Data Sourcing and Normalization Challenges 14:37 Understanding Consumer Preferences 16:18 Potential Business Models and Data Insights 18:18 Online Grocery Shopping and Future Opportunities 20:30 The Future of Shopping Agents 21:53 Customer Acquisition Challenges 22:44 Community Engagement in Grocery Shopping 24:38 Building a Supportive Shopping Experience 25:10 Infrastructure and Technology in Grocery Solutions 27:20 Team Dynamics in a company and AI Integration 28:01 Cybersecurity in Retail Technology 32:58 Vision for the Future of Grocery Shopping 35:56 Learning and Adapting in the Age of AI Hyperlinks:  Andy Ellwood's LinkedIn Twitter/X Stretch (Company) Anastassia Lauterbach - LinkedIn First 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 Edutainment The AI Imperative Book Romy & Roby Book Substack

    42 min

  7. Apr 28

    72: Human-AI Relationships | Exploring Consciousness in 'After Yang'

    Summary: What does it mean for an AI to have consciousness? In this episode, Anastassia and Professor Rae Muhlstock explore artificial intelligence through the lens of film and fiction, unpacking how stories like 'After Yang' teach us about identity, personhood, and what makes us human. A philosophically rich yet accessible deep dive into AI ethics and consciousness—perfect for curious minds of any age. Key topics: AI portrayal in fiction Consciousness and AI Human-AI relationships Science fiction as a tool for exploring AI Ethics and identity in AI stories Chapters: 00:00 Introduction to why portrayals of AI in fiction (books and movies) matter 02:43 Exploring 'Saying Goodbye to Yang' 05:19 The Prophetic Nature of Science Fiction 07:42 Understanding AI Through Literature 10:29 The Complexity of Grief and AI 13:23 Narrative Structure and Emotional Depth 15:54 Consciousness and AI: A Philosophical Debate 18:16 The Shift in Perspective: From 'It' to 'He' 20:51 The Interplay of Human and AI Memories 23:42 Art, Emotion, and the Limitations of AI 26:12 The Importance of Understanding AI 28:33 Future Explorations in AI Literature 31:23 The Role of Summarization in Understanding Art 33:37 Closing Thoughts and the 2026 AI Literacy Project Resources: After Yang / Children of the New World by Alexander Weinstein Rae Muhlstock’s LinkedIn Anastassia Lauterbach - LinkedIn First 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 Edutainment The AI Imperative Book Romy & Roby Book Substack

    43 min

  8. Apr 21

    71: Quantum Computing for AI Beginners | Easy Concepts, Real Applications

    Summary: Quantum computing sounds like sci-fi, but it's reshaping artificial intelligence right now. In this episode, Dr. Jonas Kölzer breaks down qubits, superposition, and why quantum computers matter for AI's future—using analogies anyone can understand. Perfect for teens, parents, and AI-curious educators wondering what quantum computing actually does. Dr. Jonas Kölzer is a quantum physicist, entrepreneur, and educator. After early enthusiasm for physics communication, he studied physics at RWTH Aachen University, where a lecture by Professor Hendrik Bluhm on spin qubits drew him into quantum computing research; he later specialized in topological insulators and completed his PhD while also helping launch Polarstern Education, the foundation for the School of Quantum. Today, he works across quantum technology education and AI systems, and is known for explaining topics such as qubits, superposition, error correction, and quantum hardware architectures in clear, practical language for professionals and non-specialists alike. Key Takeaways:  1. Quantum Computing Is in Its "Wright Brothers Moment" Just as early aviation saw a race between zeppelins, helicopters, and aircraft with no obvious winner, quantum computing hardware is in an analogous race between superconducting qubits, ion traps, photonic systems, spin qubits, and topological approaches. No single architecture has emerged as dominant — the best platform may depend on the specific application. 2. Superposition + Entanglement = Exponential Power Superposition: a qubit can exist in a probabilistic mix of 0 and 1, like a coin spinning in the air before landing. Entanglement: multiple qubits become correlated, so changing one affects others. The resulting combinatorial states scale as 2^n (n = number of qubits), rapidly exceeding what any classical computer can simulate. 3. Noise and Error Correction Are the Central Engineering Challenge Quantum states are destroyed by even tiny energy perturbations — temperature fluctuations, cosmic particles. The no-cloning theorem means quantum information cannot be simply copied for error recovery. Current research focuses on error mitigation and logical qubit error correction as the bridge to practical large-scale machines. 4. Quantum Computers Are Co-Processors, Not Replacements Today's quantum computers work alongside classical supercomputers in a hybrid loop. The quantum unit handles specific optimization or simulation tasks; the classical system manages parameters and optimization. Full universal quantum computers remain a long-horizon aspiration. 5. The Quantum–AI Relationship Is Bidirectional Quantum hardware can accelerate certain AI workloads (QPU ↔ GPU analogy), especially high-dimensional optimization. Classical AI (GPU clusters, e.g., Nvidia's quantum research program) is already being used to optimize and improve quantum systems. Companies like Nvidia are investing in quantum-GPU hybrid infrastructure. 6. Total Energy Cost of Quantum Is Nuanced While a qubit chip operates at microwatt efficiency, the surrounding cooling infrastructure (helium-3, compressors, mechanical pumps) runs in the kilowatt range. The full total cost of ownership must be assessed honestly before claiming quantum as a "green" alternative to data center AI compute. Chapters:   0:04 Introduction and Background of the Episode 3:50 Jonas’ Early Interest in Physics 4:46 Jonas’ Introduction to Quantum Computing 7:09 Quantum Mechanics and Computing 8:55 Understanding Qubits and Superposition 13:02 Challenges in Quantum Computing 19:05 Designs and Paths in Quantum Computing 27:12 Applications and Future of Quantum Computing Hyperlinks: LinkedIn Dr. Jonas Koelzer Article Nature Communications Materials (2021) Article Advanced Electronic Materials (2020) axelera.ai Anastassia Lauterbach - LinkedIn AI Snacks with Romy and Roby @romyandroby “Leading Through Disruption” AI Edutainment The AI Imperative Book Romy & Roby Book Substack

    57 min
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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.

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