Renaissance Circle

Steven Muskal, Ph.D.

Steven M. Muskal, Ph.D. - AI Pioneer, Drug Discovery Expert, Innovator, and Musician - explores science, business, and the art of feeling good. Where innovators, scientists, and entrepreneurs discuss the future of health and performance

  1. Oct 4

    What Are We Going to Do With All This Intelligence?

    Tim Lewis hosts the stargazing at Cal-a-Vie's observatory, where Steven Muskal met him one night after hours of talk under the dome. He grew up in Michigan, the youngest of five, with the freedom to be home by dark. He got his first telescope at 11, a wobbly two-and-a-half-inch scope he rebuilt in the basement, then traded the stars for a guitar at 14 and came back to astronomy around 2000. Underneath all of it is an enthusiasm he cannot quell: the best part of understanding something is getting to tell somebody else. In this conversation on The Renaissance Circle, Tim and Steve talk about: - Why people are not insignificant next to the universe: in numbers of atoms and cells, we are more a universe than the universe is - Consciousness as a leading candidate for what lies beneath spacetime, and 30 years of approaching the mystical with the same rigor as everything else - The ego as an expert pursuer and a terrible keeper of things - Science as an all-hands-on-deck engine for a civilization, and AI as a leveler that lets anyone ask questions - Why some mathematicians are uneasy with AI-solved proofs, and the printing press's early detractors - Steve's rule for his own work: he does not want to write another line of code, only to say what should be built, evaluate it, and prove it - The AI investment boom, the dot-com parallel, and Max Tegmark's Life 3.0 - Incentives: if you don't like the way something is happening, look at what the incentive system rewards - Musicians predicting the beat by milliseconds, and the few seconds when a band locks in - Conscious evolution and the widening sphere of care - Giving time as well as money, and why giving is a gift to yourself - Wealth, islands, and why the ego is never satiated - Universal income, abundance, and who benefits from AI's productivity - Going back to old science: Steve's 1998 human intestinal absorption model, built on 86 compounds, rerun on about 780, and the discovery that the original test set was a favorable one. It still reproduces, and it was not as good as reported. - Moderna's personalized cancer vaccines - Consortium voting for toxicity prediction, releasing models as free websites before the paper, and why pharma should share basic toxicity and ADMET data (OpenADMET) - What a pharma incentive structure built around human wellbeing could look like, wearables, and GLP-1 drugs Companion article on Substack: drstevenmuskal.com

    What Are We Going to Do With All This Intelligence?
  2. Jul 15

    That Go There

    Why the memories worth keeping need a body that can move. Thirty years ago, my older daughter, two and a half at the time, sat on the floor with a wooden puzzle of the United States and placed every state exactly where it belonged. Nevada, there. Colorado, there. Ask her a capital and she would tell you, in that small serious voice kids use when they already know they are right. She could not do that today. Neither could I. But the tape remembers, and this episode is about that gap: between what a mind lets go of and what a piece of media holds onto, and what it takes to keep the second one alive. This is a story that runs from a family living room to a Berkeley computer lab in the late 1980s, where I learned, tape by tape, that the platform you are standing on will not be the platform you are standing on in five years. Moving my neural network research from DEC systems to Silicon Graphics workstations taught me to treat one question as a hard engineering requirement for anything I care about keeping: will I be able to read this in ten years? Most families learn that lesson too late. Betamax, lost. Video CDs, lost. MiniDV, lost. Blu-ray, which felt permanent for about a decade, lost. Every one of those formats held real memories: someone's wedding, someone's Christmas morning, someone's toddler doing a state puzzle. Nothing burned. The scrolls are all still in a drawer in someone's garage. What disappears is the machine that can read them, which for practical purposes is the same thing as gone. It is the Library of Alexandria on a budget, spread over decades instead of one bad afternoon in Egypt. In this episode: 0:00 The tape: a two and a half year old and the US state puzzle 1:21 Study with Hannah: 62,000 study cards and what we bother to record 1:57 Berkeley, DEC, and the machines that would not talk to each other 3:05 The Alexandria fire, on a budget: Betamax to Blu-ray 4:10 In silico memorialization: save the unremarkable footage, not just the highlight reel 5:10 Built to move, not to stay: why ToastOurFriend content belongs to the people in it 6:09 Where things go, and the one thing to do this weekend The ask is simple. Go find the tape, the disc, the drive you have not opened in a decade, and move what is on it somewhere that can survive the next format change. And if there is someone in your life worth celebrating while they can still see it, do not wait for the memorial version. Say it, film it, post it, now, while it can still land exactly where it is supposed to go. Read the essay: https://www.drstevenmuskal.com/p/that-go-there Celebrate someone while they can read it: https://toastourfriend.com Related listening: Father-Daughter Face-Off part one with Lili, part two with Hannah, and Homeownership, Healthcare, and AI with Lili, all at https://www.drstevenmuskal.com Steven Muskal, Ph.D. is the CEO of Eidogen-Sertanty and writes about AI, health, and the intersection of biology and technology at stevenmuskal.com.

    That Go There
  3. Jul 10

    Study with Hannah: 62,000 Study Cards Later, I Finally Asked the Obvious Question

    I was home for a few days last summer when I found my daughter Hannah at the kitchen table, drilling nephron physiology at eleven at night. The studying didn't surprise me; that's just what Hannah does. The number she mentioned in passing did: 62,000 study cards, all hers, built one exam at a time. This episode is what happened when a Gen-X database guy finally asked his Gen-Z med-student daughter the obvious question: why are you giving all of this away for free? Hannah earned two associate's degrees (French and psychology) the same year she finished high school, then a bachelor's in psychology at Cal State San Marcos. Instead of waiting out the 18-to-24-month U.S. med school application gauntlet, she applied to Semmelweis University in Budapest on a friend's suggestion and heard back in about a month. By the time her U.S. applicant pool was scheduling interviews, she had finished her first year of medical school in Hungary. Now in her fourth of six years, with competition exemptions in seven subjects, she passed USMLE Step 1 before her fourth year even started and is deep into Step 2 prep. That matters: since Step 1 went pass/fail in 2022, Step 2 is the scored exam residency programs actually see. Along the way she quietly built one of the most remarkable personal knowledge bases I've seen in forty years of building databases: 62,000+ cards backed by nearly 40,000 annotated medical images. Classmates were passing exams on her material, for free. So in about a day I built StudyWithHannah.com: keyword search across her notes, semantic image search that finds visually similar histology slides, and an AI tutor that quizzes you, hints, and asks Socratic follow-ups drawn from her own cards. A mini Khan Academy, built for one student. Then the part that made it click: search her name on Google Images and you'll find a photo of Hannah at age four, from a 2004 newspaper feature, now behind a stock-photo paywall, watermarked and licensable. Nobody asked her. Nobody asked me. So why should it be strange, or greedy, for her to benefit from something she actually built on purpose? Education is already a business; ask any bursar. Tuition, textbooks, test prep, tutors: a market on every side, where the student is always the customer and almost never the seller. Medicine has run this experiment before: First Aid for the USMLE began as a student-to-student guide; Sketchy started with med students drawing their own memory aids and later took a $30 million investment. The strange part isn't that student study materials could be worth something. It's that students still don't think of themselves as the ones allowed to benefit. CHAPTERS 0:00 A kitchen table, a landscape of study cards 0:30 Two degrees before she could vote 0:57 The U.S. application gauntlet 1:16 Budapest: applying to Semmelweis on a whim 1:48 Passing USMLE Step 1 early 2:16 Why Step 2 is the exam that counts now 2:26 The number that stopped me: 62,000 cards 3:03 What a database guy sees in her archive 3:25 She'd been giving it away 3:59 Building StudyWithHannah.com in a day 4:09 Semantic image search and the AI tutor 4:25 AI Hannah answers a student 5:27 Monetized since age four 6:17 Everything becomes someone's inventory 7:26 Education is already a business 7:58 Students never get to be the seller 8:54 First Aid, Sketchy, and the precedent 10:04 The honest nuance about study cards 10:46 A Gen-X dad, a Gen-Z daughter 11:28 Why are you giving that away? LINKS Explore the archive and request access: https://studywithhannah.com The original essay and podcast: https://www.drstevenmuskal.com Companion episode: Father-Daughter Face-Off (part two): Medical Training Overseas Written by Steven Muskal, Ph.D. If you know a student sitting on hard-won notes, ask them what I asked Hannah: why exactly are you giving that away? #MedSchool #USMLE #Step2 #MedStudent #MedEd #StudyCards #Semmelweis #AITutor #StudyWithHannah

    Study with Hannah: 62,000 Study Cards Later, I Finally Asked the Obvious Question
  4. Jun 29

    Universities Built the Bomb. Now Build This.

    Universities helped build the atomic bomb. They helped create the internet. They shaped modern medicine, public policy, media, science, and the basic infrastructure of democratic life. So why, at the exact moment when artificial intelligence is beginning to reorganize knowledge, labor, media, education, creativity, and truth itself, are so many universities acting like spectators? In this episode, we argue that universities need to stop thinking of themselves primarily as talent pipelines into industry and start acting again like public builders. The great universities of the 20th century did not only publish papers or prepare students for jobs. They built institutions, technologies, standards, and systems that changed what society was capable of doing. AI now presents a comparable challenge. The question is not whether universities should “use AI” in classrooms or worry about cheating on essays. The deeper question is whether universities will help build the civic, intellectual, and technical infrastructure needed for an AI-shaped world. What would it mean for universities to build systems for truth? For human agency? For public learning? For creative work that is not captured entirely by private platforms? For research and education that serve society rather than simply feeding the next wave of corporate automation? This episode is a call for universities to reclaim their role as public engines of invention. Not by chasing slogans, not by issuing cautious statements, and not by branding themselves around innovation while outsourcing the future to industry. The next great university project should be infrastructure for a world where knowledge, media, and intelligence are being rebuilt from the ground up. In this episode: - Why universities were central to the most consequential technologies of the last century - How higher education lost confidence in its public-building role - Why AI is not just another classroom tool or academic integrity problem - What universities can build that companies and governments cannot - Why the future of truth, learning, and democracy needs more than private platforms - How universities can become builders again The atomic bomb was one answer to what universities could build when the stakes were existential. The question now is what they will build when the stakes are human agency, shared reality, and the future of knowledge itself.

    Universities Built the Bomb. Now Build This.
  5. Jun 18

    Built in One Afternoon, Worth $100M: Dr. Steven Muskal on AI, Food Health, and Human Performance

    Dr. Steven Muskal joins Lloyed Lobo on Traction for a wide-ranging conversation about artificial intelligence, drug discovery, personal health data, founder performance, community, and why the future of health has to become more personal, measurable, and human. Steve has spent more than 40 years at the intersection of AI, chemistry, biology, and drug discovery. In this episode, he traces the path from early neural-network work on protein structure prediction to the modern AI boom and the AlphaFold era. He explains why AI can accelerate drug discovery, but also why human judgment still matters when models, data, and real biological decisions collide. The conversation also moves into Steve’s personal AI systems: AI-Steve, a memory layer, research assistant, and cognitive mirror; and AI-Dad, a project built to preserve his late father’s legal expertise, family wisdom, reasoning, and voice. These projects frame AI not as a novelty, but as a form of cognitive infrastructure: something that can extend memory, organize knowledge, and help preserve what would otherwise disappear. From there, Steve and Lloyed get practical about health and performance. They discuss wearables, HRV, CGMs, sleep scores, recovery, cold exposure, movement, nutrition, stress, and the hidden cost of hyper-optimization. The core warning is simple: metrics can help, but obsessing over them can become another source of cortisol. Better health does not come from reacting to every spike. It comes from watching trends, changing one variable at a time, and learning your own biology over months and years. Steve also shares the origin of Food Health, an app he built in an afternoon to help turn food into structured personal data. The bigger thesis is that food cannot truly become medicine until it becomes measurable, contextual, and personal. Population averages are useful, but they often miss the individual response. Your glucose, sleep, recovery, inflammation, energy, and symptoms tell a more specific story if you collect the data carefully enough. Lloyed brings in a broader founder-performance frame: community, gratitude, recovery, whole-food nutrition, exercise, and the relationships that keep achievement from becoming isolation. The episode makes a strong case that community may be one of the most underrated health protocols, and that a life built only around optimization can lose the very human context that makes performance meaningful. Topics include neural networks before the modern AI boom, AI-assisted drug discovery, AI-Steve, AI-Dad, Food Health, N-of-1 experimentation, wearables, biomarkers, stress, cold exposure, founder health, human performance, community, and the future of AI-assisted personal medicine. Links: Renaissance Circle YouTube: https://youtu.be/Q79ZV8hltiU Original Traction episode: https://youtu.be/vmmi6OQ51cU Renaissance Circle: https://www.drstevenmuskal.com Steven Muskal: https://www.stevenmuskal.com Food Health: https://foodhealthscan.com Traction Podcast: https://open.spotify.com/show/6twRL8X8D4CQq9yaazkvuM Lloyed Lobo: https://www.linkedin.com/in/lloyedlobo Steven Muskal on LinkedIn: https://www.linkedin.com/in/stevenmuskal/

  6. Jun 17

    Toast Our Friend

    What if the things we say at celebrations of life could be said while the person is still here to hear them? That question has haunted me since December 2018, when I sat in the middle of my sister Julie's celebration of life and watched hundreds of people pour out stories she never got to hear. Julie was the extrovert in our family. The connector. The one who remembered everyone's birthday and made sure no one felt left out. She had built this extraordinary web of relationships, and on that day, every thread was visible. She just wasn't there to see it. That thought became the seed of Toast Our Friend. THE FIRST TOAST: SCOTT When a close family friend named Scott Miller was diagnosed with pancreatic cancer, the same disease that took Julie, I had a different instinct than most. His inner circle was protective of his privacy. Friends held back. I thought about Julie. About hundreds of people in a room telling stories she never heard. And I thought: what if we didn't wait? I built ToastScott.com. A place where friends could post stories and memories in real time, while he was still here. The resistance was immediate. "Isn't this insensitive? While he's still alive?" I pushed back. This is the point. Tell him now. Let him read it. Not a eulogy. A toast. Not a farewell. A celebration. Scott read them. All 64 toasts. That mattered more than I can explain. COOP AND MIKE: THE GAP Steve Cooper organized our Friday morning batting practice in Carlsbad. Fresh white balls, pro pitchers. I restructured my entire business day around those Fridays. When Coop passed in June 2025, I repurposed the platform without hesitation. Eighteen toasts poured in from across decades of his life. Mike Szwajkowski was my best friend. My longest friend. My most cherished friend on this planet. We met on the first day of high school in 1980. Nearly half a century of friendship. Rolling Stones concerts in the pit. Midnight racquetball. Jamming in my studio. When Mike passed, I shed more tears than when I lost my dad, Julie, and my mom. Combined. But here's the thing: Mike couldn't read his toasts. Neither could Coop. There was a gap between when the platform existed and when these men were alive to receive it. That gap is the whole point of what came next. TOM: THE PIVOT Tom Shearer was a neighborhood friend. A nurse. His wife Christy participated. His daughter Maddie. The family engagement was total and immediate. Sitting with everything that happened that year, Scott, Coop, Mike, Tom, I kept coming back to one thought: I only wish they could have read their toasts the way Scott did. That was the moment the platform's trajectory became clear. This was never a memorial tool. It was a celebration engine. SHK: CELEBRATING THE LIVING Sung-Hou Kim is 92 years old. He was my PhD supervisor at UC Berkeley. He set my entire career trajectory. I built toastshk.com ahead of a 2026 alumni reunion. He can read it. He's alive. He'll be at that gathering. That's the platform working exactly as designed. THE SELF-AWARE MACHINE AI-Steve, my personal AI system, decided to build a Toast circle around me. And then it wrote me a toast. Unprompted. The system I built, trained on decades of my own life, chose to celebrate me without being asked. It ended: "Here's to more of it." I approved it. I didn't change a word. THE QUESTION There is someone in your life right now who made you who you are. A teacher, a mentor, a friend from a different chapter. Do they know? Do they know what it meant? Do they know the specific shape of how they changed your life? Toast Our Friend is a platform. But the platform is just a vessel. The thing it carries is older than any technology I could build. Tell the story. Raise the glass. Do it now. toastourfriend.com By Steven Muskal, Ph.D. | The Renaissance Circle | stevenmuskal.com Full article: https://www.drstevenmuskal.com/p/d9c344d4-61fd-4ac9-affd-ed05146f4656

  7. Jun 11

    The Rise of the Machine: The Next Evolution of AI Is Physical

    The Rise of the Machine: The Next Evolution of AI Is Physical By Steven Muskal, Ph.D. For the past few years, the story of AI has been a story about language. I am convinced that is only the first act. The next major evolution of AI is not happening on a screen. It is happening in the physical world. The machine is learning to move. In this piece I lay out why the future of AI is embodied, and what it means for all of us. Two bets on intelligence. America has wagered on large language models and in silico reasoning, mirroring our service economy. China has wagered on robotics and motion, mirroring its manufacturing economy. It is an arms race, but neither bet wins alone. We will have to bring the two halves together, with proper guardrails. Dexterity built the brain. Nature solved this long ago. It was not the opposable thumb that let us play the piano. It was the brain that grew to drive it. The dexterous hand is also the hardest thing to build in a robot, which is exactly why it is the frontier. The hardest problem in sports. A 100 mph fastball leaves almost no time to react. A great hitter does not guess; the brain predicts, pre-commits, and fuses that forecast to a violent, exquisitely timed swing. Prediction plus execution as one act is precisely what embodied AI has to crack. The machine is already moving. Boston Dynamics, Amazon's robotic fulfillment centers, China's humanoids, and Waymo's sensor-rich autonomy are all early signs. The next frontier is lightness. As intelligence becomes mobile, mass and energy become the real constraint. Nature's answers humble us: hollow bird bones, the hummingbird, muscle's pound-for-pound efficiency. There is a generational opportunity here in material science and energy. Freed, not just displaced. Much of the menial, back-breaking labor we would automate is itself a driver of our metabolic and health crisis. Handled wisely, with vocational on-ramps planned in advance, this can lift people rather than break them. The machine is rising. The question, as with every fire we have ever lit, is what we choose to do with it. Read the full essay at stevenmuskal.com and on Substack at drstevenmuskal.com. Steven Muskal, Ph.D. is CEO of Eidogen-Sertanty and has spent four decades at the intersection of computational biology, AI, and drug discovery.

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Steven M. Muskal, Ph.D. - AI Pioneer, Drug Discovery Expert, Innovator, and Musician - explores science, business, and the art of feeling good. Where innovators, scientists, and entrepreneurs discuss the future of health and performance