Podcast
AI Snacks With Romy & Roby: Democratizing AI Technologies
Hosted by Dr. Anastassia Lauterbach: Democratizing AI Expert · EN
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.
42episodes
Episodes
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86: AI Changing Medical School with Dr. Marschall Runge on the Future of Doctors
1w ago00:35:24Tap to summarizeDr. 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
Transcribe →85: Can AI Find New Problems, Not Just Answers? with Matthias Röder (Beyond Human Series, #4)
2w ago00:39:09Tap to summarizeSummaryAI 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
Transcribe →84: Music, AI & the Future of Music Promotion with Paul Loeb
3w ago00:37:47Tap to summarizeIn this episode of AI Snacks with Romy & Roby, Anastassia Lauterbach welcomes Paul Loeb — entrepreneur, musician, audio engineer, and the founder of DropTrack, the world's first AI-powered music promotion platform. The conversation moves fluidly between Paul's personal journey from bedroom DJ and record label founder to tech executive at Beats by Dre, Apple, GitHub, and Ticketmaster, and the real-world mechanics of how DropTrack is changing what it means to be an independent artist in the age of AI.At its heart, this episode is about democratisation: of music promotion, of AI literacy, and of access to audiences that were previously reachable only by those with money, connections, or industry clout. Paul and Anastassia dig into the tension between AI as a creative threat and AI as an empowerment tool, explore the copyright battles reshaping the music industry, and discuss how independent artists and major labels alike need to rethink their strategies — before the window of opportunity closes.The episode closes with a call to action for conservatories and music schools: AI literacy is no longer optional for the next generation of artists.Chapters00:00 Introduction to AI Snacks and the episode topic00:55 The journey of music from creation to listener01:54 Paul Loeb's background and path into music and tech03:37 Challenges of music promotion and the birth of DropTrack07:16 How DropTrack uses AI to match music with opportunities11:01 Using AI for music analysis and readiness assessment12:43 Matching music to labels, playlists, and licensing opportunities15:21 The role of human curation and AI in discovering new music18:30 Global reach and different strategies for artists21:49 Disruption of traditional music industry giants24:38 Copyright, metadata, and royalties in AI-driven music28:24 Training AI models with existing music and copyright concerns33:31 Common mistakes and misconceptions about AI in music36:29 AI literacy as a crucial skill for young artists39:27 Closing remarks and the future of AI in musicAbout the GuestPaul Loeb is the Founder and CEO of DropTrack, the world's first AI-powered music promotion platform. He has over 20 years of experience spanning music and tech, with roles at Beats by Dre (acquired by Apple), GitHub (Microsoft), and Ticketmaster/Live Nation. He founded No Ego Records in 2010, signing over 50 artists and releasing more than 100 tracks. A USC graduate and Certified Pro Tools Expert trained under Steely Dan producer Roger Nichols, Paul also produces and DJs electronic music under the alias Really Cute Cats. He is based in Los Angeles, California. About the PodcastAI Snacks with Romy & Roby is the AI literacy podcast hosted by Dr. Anastassia Lauterbach, Founder and CEO of AI Edutainment GmbH. Each episode transforms complex ideas in artificial intelligence into something accessible, tangible, and actionable — for educators, executives, artists, and curious humans everywhere. The podcast is available on Spotify, Apple Podcasts, and all major platforms.
Transcribe →83: The Hidden Fuel of AI: Data Lakes, CDN Analytics & Cybersecurity with Tony Falco
4w ago00:44:39Tap to summarizeSummaryAnastassia sits down with Tony Falco of Hydrolix to explore one of the least-discussed but most consequential challenges in the AI era: CDN and log data. Every click, stream, and page interaction generates hundreds of log files per second. For nearly three decades, that data has been thrown away — not because it lacked value, but because storing it was prohibitively expensive.Tony brings over 30 years of experience building the internet's infrastructure, from his early days at Akamai helping Fortune 500 companies scale their websites for Super Bowl traffic, to Silicon Valley Data Science (acquired by Apple), to co-founding Hydrolix — a platform purpose-built to make petabyte-scale log data affordable, queryable, and AI-ready.The conversation moves from the very origins of the commercial internet, through the evolution of distributed databases and CDN technology, to the urgent present: a moment when AI is simultaneously generating new value from log data and being weaponised against the websites that produce it. Tony and Anastassia explore the governance gap around bots and agents, the coming convergence of cybersecurity and data strategy, and why the biggest opportunities in AI may still be hiding in data that nobody has thought to explore.Key Takeaways:Log files are the dark matter of the internet. Every interaction with a website generates hundreds of log files per second. For 26+ years, this data has largely been deleted after 90 days because of cost — but it contains the entire behavioural story of a website's audience.The economics breakthrough unlocks the AI opportunity. Hydralix was built to reduce CDN log storage costs by up to 90%. But when given the choice of cutting costs or keeping data longer, 99% of customers choose to keep the data — because the insights it holds are more valuable than the savings.AI is hungry for exactly the data that has been thrown away. AI is also the new threat on the attack surface. Bots and agents are increasingly using AI to mimic human behavior — bypassing detection systems that relied on the predictable signatures of scripted traffic. Intent is the new frontier. Hydralix focuses on inferring the intent of website visitors — human or bot. Normal intent (browsing, comparing, buying) can be profiled; variance from it flags bad actors.Sophisticated attackers are patient. If they know your data retention window is 90 days, they will make their next move on day 91. The bot/agent governance gap is real and growing. Businesses have DUNS numbers. Websites have no equivalent system to identify or authenticate agents. Don't accept the current narratives about AI. Tony's core message: it is very early. The biggest opportunities have not been taken. The biggest decisions have not been made. Curiosity and drive matter more than credentials right now.Chapters:00:01 Introduction, Tony’s Journey05:30 From CDNs to NoSQL to Gen AI: The Through-Line08:47 Data explosion and the Log File problem14:21 The Marianas Trench of Data15:57 Understanding niche markets16:35 Competitive landscape of data providers19:43 Real-time correlation as the competitive advantage21:07 Intent Analysis and Bot Detection23:56 The Governance Gap: Bots, Agents and Identity29:26 Advice for Young People entering the field32:06 Machine-to-machine, bot-to-bot workflows and communication32:50 Prometheus Moment of AI: Building tools without fully understanding the consequences47:14 ClosingHyperlinks: Tony FalcoHydrolix WebsiteAnastassia 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
Transcribe →82: Digital Twins, AI Literacy & the Future of Human Potential with Manuj Aggarwal
Jul 700:41:42Tap to summarizeWhat if the most powerful thing AI could do is not replace human expertise — but make it infinitely scalable?In Episode 82 of AI Snacks with Romy & Roby, Anastassia Lauterbach sits down with Manuj Aggarwal, AI inventor, entrepreneur, and founder of TetraNoodle Technologies, for a wide-ranging and deeply personal conversation about intelligence — artificial and human.Manuj's story begins in a small town in India, where he dropped out of college in his first three months and spent his days working in his father's factory. A chance encounter with computers changed everything. What followed was a 30-year journey through reinforcement learning, personalised education, neuroscience, patents, and — most recently — the creation of a Digital Mind: a living AI-powered digital twin that encodes a person's knowledge, thinking patterns, and lived experience, and makes it available in real time to anyone who needs it.The conversation moves across some of the most important tensions in AI today: whether young people still need to learn mathematics and coding; whether current AI systems truly reason or merely simulate reasoning; what causality actually means for AI development; and how digital twins can bridge the gap between an experienced mentor and a fresh graduate — scaling human wisdom at a speed biology never could.Anastassia and Manuj also tackle the harder societal questions: the demographic crisis in Western economies, the coming disruption of credential-based hiring, the five-to-ten-year transition period ahead — and what it will take for humanity to emerge from that transition with more opportunity, not less.The episode closes with Manuj's personal mission: use AI to uplift 1 billion people and help 20 of them win the Nobel Prize.00:00 Introduction and Manuj's Inspiring Journey05:33 AI in Education: Personalizing Learning08:22 The Role of AI in Programming and Learning13:06 Transitioning to AI: Quality vs. Quantity17:08 Causality and Understanding in AI20:08 Building Digital Twins: A New Approach26:31 AI in Hiring: Finding Human Connection32:00 Preparing for the Future: Education and Purpose39:26 A Vision for AI: Uplifting Humanity39:57 OutroAbout the GuestManuj Aggarwal is an AI inventor, entrepreneur, and the founder of TetraNoodle Technologies, a company at the intersection of artificial intelligence, neuroscience, and human potential. He holds four patents in AI — including one on reinforcement learning applied to personalised education — and has been published in the Mensa Research Journal.Manuj grew up in a small town in India, dropped out of college within his first three months, and built his career entirely through curiosity, self-directed learning, and a commitment to creating technology that impacts people at scale. He has studied neuroscience and psychology alongside computer science, a combination that informs his unique approach to the relationship between artificial and human intelligence.His flagship concept — the Digital Mind — is a living AI-powered digital twin that encodes a person's knowledge, thinking patterns, lived experience, and even their nervous system state, and makes that expertise available in real time to anyone who needs it. The system is deliberately model-agnostic, human-first, and purpose-driven — designed to scale human wisdom rather than replace it.Manuj's personal mission: use AI to uplift 1 billion people and help 20 of them win the Nobel Prize.Links🔗 TetraNoodle Technologies: tetranoodle.com🔗 LinkedIn: linkedin.com/in/manujaggarwal🔗 YouTube / Content: youtube.com/@manujaggarwal🔗 Twitter / X: @manujaggarwal
Transcribe →81: Artificial Intelligence and its IQ with Dr Anthony Scriffignano
Jun 3000:32:57Tap to summarizeToday I am revisiting episode three. Back in April 2024, I sat down with Dr. Anthony Scriffignano, and at the time, it was simply a good conversation. Two years later, listening back, it is not just a good conversation anymore, it is a roadmap. Everything he said about hallucinations, about deepfakes, about the AGI debate, has played out almost exactly the way he laid it out. So I wanted to bring it back, not as a rerun, but as proof that some people were already asking the right questions before the rest of us caught up.This is a fantastic time to be working in AI. Use all of this amazing, democratized technology to help you address big problems. Go get a Nobel Prize!If you want to learn about AI, preorder Romy & Roby and The Secret of Sleep and join Dr. Anastassia Lauterbach on Patreon.In this stimulating episode of AI Snacks with Romy & Roby, join host Dr. Anastassia Lauterbach and esteemed guest Dr. Anthony Scriffignano, for a deep dive into the intricacies of intelligence in AI. They tackle questions on definitions of intelligence, life, and the future of language models. Dr. Scriffignano, with his expansive background in data science, shares insights on neuromorphic technology and decision-making in AI. Listen in as they explore the ethical landscape, the realities of AI's societal impact, and Dr. Scriffignano's unique concepts of decision elasticity and neosophism. Don't miss this thought-provoking dialogue that bridges AI and the essence of intelligent life.Anthony Scriffignano, Ph.D. is an internationally recognized data scientist with experience spanning over 40 years in multiple industries and enterprise domains. Scriffignano has extensive background in advanced anomaly detection, computational linguistics, and advanced inferential methods and has multiple patents worldwide in these areas. Scriffignano was recognized as the U.S. Chief Data Officer of the Year 2018 by the CDO Club, the world’s largest community of C-Suite digital and data leaders. He is a member of the OECD Network of Experts on AI working group on implementing Trustworthy AI, focused on benefiting people and planet.He has published, delivered keynote presentations, and participated in panel presentations extensively, in various settings, internationally, concerning emerging trends in AI and advanced analytics, the “Big Data” explosion, artificial intelligence applications and implications for business and society, multilingual challenges in business identity, and malfeasance in commercial and public-sector contexts.Key Topics Discussed:Defining intelligence and life implicationsChallenges in measuring AI's intelligenceImpacts of generative AI on societyAI's role in decision-making processesTimestamps:00:00 Philosophical Perspectives on Intelligence05:07 Anthony's Three Categories of Intelligence07:32 The Original 2024 Conversation Begins09:44 Measuring Machine Intelligence: IQ, Turing Test, Truth13:43 The ChatGPT Moment and Democratization of AI17:21 CAPTCHAs, Training AI, and Human-Machine Roles Reversed20:14 Neuromorphic AI and the Shift to Generative AI25:35 Three Big Questions for Building AI27:07 What Anthony's Most Excited About28:50 Understanding Intelligence and AI's Role31:37 Democratizing AI Knowledge32:57 The Importance of AI Literacy
Transcribe →80: Digital Twins and the AI Revolution in Healthcare with Andree Bates, Part 2
Jun 2300:36:30Tap to summarizeSummaryHow do digital twins in medicine get from the lab to the patient? It all comes down to regulation, data, and trust. In this second part with Dr. Andrée Bates (CEO, Eularis), we cover the FDA Modernization Act 2022, EU AI Act conflicts with GDPR, the UK and China regulatory landscape, digital twin ownership and liability, patient-owned health data, decentralized data markets, and what it will take — technically and culturally — to make AI-powered personalized medicine real. Plus: why medical school curricula must change, and a vision of the human-AI health future. Don't miss Part 1 (EP 79) for the science and economics foundation.Key TakeawaysThe FDA's 2022 Modernization Act was a watershed moment — it replaced mandatory animal testing with "non-clinical" methods including in silico and cell-based models. 90% of drugs that clear animal studies never make it through human trials The EU faces a three-way regulatory conflict — the AI Act, the Medical Device Regulation (MDR), and GDPR have overlapping, partially conflicting requirements; GDPR's "purpose limitation" principle is structurally hostile to digital twins, which are by definition continuously updatedUS vs. EU regulatory philosophy in one sentence: the US is outcome-based and post-market weighted ("prove it works, monitor it"); the EU is process-based and pre-market weighted ("prove your development was rigorous first") — with real consequences for patient access timelinesChina is the one to watch — the NMPA accepts in silico evidence, data sharing is state-encouraged, and population-scale twins built on integrated health records are politically feasible in a way they are not in the WestOwnership of digital twins is unresolved Patients owning their own health data — including blockchain-based consent models where patients sell data case-by-case to pharma — is already being piloted in the US The full ecosystem for digital twins requires: multi-organ integration, quantum computing power, privacy-preserving AI (e.g. federated learning), faster regulatory qualification pathways, international harmonization, and a liability frameworkThe cultural gap is the hardest barrier — public trust in computer-tested drugs lags far behind trust in animal- or human-tested ones; the first major in silico drug recall, when it happens, will be a defining political momentMedical education must change — tomorrow's clinicians need to read computational evidence confidently; few medical schools teach this yetGuest Bio — Dr. Andrée BatesDr. Andrée Bates is the Chairwoman, Founder, and CEO of Eularis, AI consultancy for the pharmaceutical and life sciences industry. She hosts her own podcast with over 220 episodes on AI in pharma. 00:00 Introduction to PART 2 with Andree Bates 01:35 Regulatory Landscape for AI and Digital Twins05:22 Comparative Analysis of US and EU Regulations10:48 Global Perspectives on AI in Healthcare14:08 Future of Personal Data Ownership in Medicine17:43 Innovative Business Models for Digital Twins21:17 The Role of AI and Quantum Computing in Healthcare27:31 Building the Future of Medicine: Preconditions and InfrastructureHyperlinks:LinkedIn Dr. Andree BatersCorporate Website EularisAI in Pharma — search on Spotify/Apple Podcasts (220+ episodes)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 Book
Transcribe →EP 79: Digital Twins and the AI Revolution in Healthcare with Andree Bates, Part 1
Jun 1500:45:05Tap to summarizeIn Part 1 of this two-part conversation, Anastassia and Dr. Andrée Bates take the concept of digital twins from its industrial roots — NASA rockets and GE power plants — all the way into the human body. Andrée unpacks what a true clinical-grade digital twin actually requires (individuation, credibility evidence, uncertainty quantification, and regulator-aligned analytical roles), and why many things called "digital twins" in healthcare today are really just well-marketed predictive models. The conversation travels through clinical trials, rare disease drug development, AI-assisted drug repurposing, and lands in genuinely mind-expanding territory: brain cells powering server farms, a non-invasive headband restoring speech to paralyzed patients, and the bold thesis that AI alone is not enough — that medicine needs physics embedded into its models.Key Takeaways:A real digital twin has three parts: a physical reference (the human), a virtual representation, and a live data link that continuously updates — without all three, it's just a predictive modelSynthetic control arms are already FDA- and EMA-accepted in clinical trials, especially for rare diseases where putting patients in a placebo arm would be unethical[1]Clinical-grade digital twins require four properties: individuation, formal verification/validation for regulators, calibrated uncertainty quantification (not point estimates), and a regulator-aligned statistical analysis planThe FDA approved digital twins for clinical trials in late 2022AI alone is insufficient for drug development — despite ~$20 billion invested, no AI-discovered drug has reached market yet; physics-based modeling ("world models") is the missing layerAI excels at drug repurposing, demonstrated powerfully during COVID with baricitinib and atazanavir identified from existing approved drugs8,000 rare diseases exist, but only ~100 have treatments — AI-driven matching of existing drugs to rare disease profiles is a massively under-leveraged opportunityFull-body digital twins remain a decade+ away due to the complexity of organ-system interaction and computational cost — individual organ twins are mature, but integration is the hard problemGuest Bio — Dr. Andrée BatesDr. Andrée Bates is the Chairwoman, Founder, and CEO of Eularis, AI consultancy for the pharmaceutical and life sciences industry. She hosts her own podcast with over 220 episodes on AI in pharma. Chapters:00:00 The Emergence of Digital Twins in Medicine03:03 Understanding Digital Twins: Definition and Applications10:09 Digital Twins in Clinical Trials: A New Paradigm10:17 Dynamic Systems and AI in Drug Development39:53 Leveraging AI for Drug Repurposing41:38 Regulatory Landscape for AI and Digital Twins42:45 Exploring the Digital Twin Concept43:51 Regulatory Landscape and AI in MedicineHyperlinks:LinkedIn Dr. Andree BatersCorporate Website EularisAI in Pharma — search on Spotify/Apple Podcasts (220+ episodes)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 Book
Transcribe →78: AI Costs & the Future of Tech Finance with Carmen Li
Jun 800:36:10Tap to summarizeMost 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 Finance02:18 Carmen Li and The Trillion-Dollar Blind Spot02:50 Why Compute Needs the Same Infrastructure as Oil and Energy04:33 AI Runs on Compute, and Compute Costs a Fortune05:39 Carmen's Journey — From Trading Floors to Silicon Valley08:01 The Problem: GPU Cost Volatility Is Breaking AI Startups11:07 Vision for the Future — Compute CapEx Over 10–15 Years11:50 The GPU Compute Index on Bloomberg and What's Launching Next13:37 The LLM Expenditure Index — Token Costs Are Actually Rising 38%16:16 Compute as Strategic Resource — Not Just a Cost Line18:00 Semiconductor Industry and their insights22:39 Open Source vs. Closed Source Models — Who Controls the Infrastructure?23:52 Insights for Business Analysts Following the Semiconductor Space26:16 Systemic Risk in AI — Why Risk Transfer Is the Missing Infrastructure27:44 Raising $5.6M Without a Pitch Deck — Carmen's Fundraising Story31:26 What's Next — Milestones, Markets, and New Products in 18 MonthsHyperlinks:Carmen Li LinkedInSilicon Data WebsiteCompute Exchange WebsiteAnastassia 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 Book
Transcribe →77: Can Humans Compete With Machines? Part 2, with Dr. Vivienne Ming, the 'Mad Scientist'
Jun 100:45:31Tap to summarizeWhat 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 intelligenceWell-posed vs. ill-posed problems: when AI helps and when it makes you worseThe GPS analogy and what over-reliance actually does to the brainWhat curiosity, resilience, and perspective taking have to do with AIWhat's really broken in corporate leadershipHow Vivienne learns — and why she stopped preparing for talksDr. 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 Use08:24 The Impact of AI on Cognitive Functioning11:29 Understanding Hybrid Intelligence and Cyborgs14:21 Transforming Education for the AI Era17:15 The Complexity of Human Intelligence26:08 Navigating Leadership in the Age of AI42:03 Conclusion: The Value of Exploration and Leadership45:06 The Future of Human Development and AIGuest links: socos.orgBlueSky profileLinkedIn profileBook: Robot-proof by Vivienne MingAnastassia’s hyperlinks: @romyandroby “Leading Through Disruption”AI Edutainment
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