Podcasts about Neuron

Wednesday, June 10, 2026 - Week 24   #NightOfImpact was 15 Days ago! Photos: https://jeaniehorton.pixieset.com/curesyngap1nightofimpact2026/ Impact: $800k+, of which $300 was our match.  Industry: Multiple Academics & Clinicians: Stanford, Berkeley & UCSF.  Cross-pollination is always good. Speakers: Ash, John, Kathryn, Helen Willsey & Me.  Only got a video of John, which was a mistake. If you took one, please share.  Here is John: https://www.linkedin.com/posts/graglia_still-reflecting-on-our-inaugural-cure-syngap1-ugcPost-7467439971294048256-cUf9/    Dr. Willsey Rocks. Willsey Press Release https://www.eurekalert.org/news-releases/1130924 (both were at NoI). A few other points on HRW, as we call her.  Simons: https://curesyngap1.org/blog/future-research-for-syngap1-how-helen-willsey-broke-new-ground-frogs-in-hand/ Willsey in Neuron 2021: https://www.cell.com/neuron/pdf/S0896-6273(21)00002-7.pdf (Frogs) Birtele in Nature Neuroscience 2023: https://www.nature.com/articles/s41593-023-01477-3 (Confirms) McCluskey in Nature Communications 2025: https://www.nature.com/articles/s41467-025-57342-3 (GI) Kostyanovskaya in BioRxiv 2025: https://pubmed.ncbi.nlm.nih.gov/39677731 (cilium)   5TH SCRAMBLE FOR SYNGAP, SC – 114 days Classic case of a small event becoming an institution! cureSYNGAP1.org/Scramble26   CURE SYNGAP1 CONFERENCE - 175 days cureSYNGAP1.org/Pre    USA: use your ICD-10, F78.A1: https://onlinelibrary.wiley.com/doi/10.1002/epi.70142   PUBMED Pubmed 2026 is at 35. +11 vs the week. (61 last year was +9) https://pubmed.ncbi.nlm.nih.gov/?term=syngap1&filter=years.2026-2026&sort=date   SOCIAL MATTERS 5,045 LinkedIn.  https://www.linkedin.com/company/curesyngap1 1.58k YouTube.  https://www.youtube.com/@CureSYNGAP1 11.1k Twitter https://twitter.com/cureSYNGAP1 45k Insta https://www.instagram.com/curesyngap1   $CAMP closed at $4.34 today. https://www.google.com/finance/beta/quote/CAMP:NASDAQ   Like and subscribe to this podcast wherever you listen. https://curesyngap1.org/podcasts/syngap10 Episode 209 of #Syngap10 #SYNGAP1 #CureSYNGAP1 #Podcast #PatientAdvocacy

In this episode of The Neuron, Corey Noles sits down with Mustafa Suleyman, CEO of Microsoft AI, at Microsoft Build 2026 to unpack Microsoft's next AI chapter: seven new MAI models, a push toward in-house model development, and the idea of Humanist Superintelligence.Mustafa explains how Microsoft is thinking about AI that can reason, code, generate images, transcribe speech, and power real products—without turning the future into a vague AGI race. The conversation gets into what “humanist” means in practice, why Microsoft is building models from the ground up, how AI agents may reshape work, and what it takes to keep increasingly capable systems useful, controlled, and aligned with human goals.You'll learn why Microsoft is investing in its own model family, how MAI-Thinking-1 and MAI-Code-1-Flash fit into the stack, why Suleyman frames superintelligence around human control, and what builders and operators should watch as agents move into real workflows.Sponsored by BeyondTrustCheck it out at: https://www.beyondtrust.com/products/identity-security-insights/assessment?campid=701Vw00000drII6IAMSubscribe to The Neuron for practical AI conversations with the people building what comes next.

Koło Naukowe Neuron działa na Politechnice Wrocławskiej przy Wydziale Informatyki i Telekomunikacji. Zrzesza studentów zafascynowanych neuroinformatyką, czyli dziedziną zajmującą się komunikacją z ludzkim umysłem przez komputery i zaawansowane algorytmy. Z Wiktorem Golimowskim, członkiem zarządu koła, rozmawialiśmy o nowatorskich projektach, poszerzających możliwości w zakresie medycyny, uczenia się czy rozrywki. Pochyliliśmy się również nad wydarzeniami organizowanymi przez Neuron oraz nad popularnością i ważnością samej dziedziny.

If you enjoy this episode, we're sure you will enjoy more content like this on The Occult Rejects.  In fact, we have curated playlists on occult topics like grimoires, esoteric concepts and phenomena, occult history, analyzing true crime and cults with an occult lens, Para politics, and occultism in music. Whether you enjoy consuming your content visually or via audio, we've got you covered - and it will always be provided free of charge.  So, if you enjoy what we do and want to support our work of providing accessible, free content on various platforms, please consider making a donation to the links provided below.  Thank you and enjoy the episode!Links For The Occult Rejectshttps://linktr.ee/theoccultrejectsOccult Research Institutehttps://www.occultresearchinstitute.org/Substackhttps://substack.com/@theoccultrejects?r=7auau0&utm_campaign=profile&utm_medium=profile-pageCash Apphttps://cash.app/$theoccultrejectsVenmo@TheOccultRejectsBuy Me A Coffeebuymeacoffee.com/TheOccultRejectsPatreonhttps://www.patreon.com/TheOccultRejectsWORKS CITEDArnold van Gennep. The Rites of Passage. 1909; English translation, University of Chicago Press, 1960. Use for: separation, transition, incorporation, initiatory structure, and the candidate's movement through old identity, liminal state, and return.Victor Turner. “Betwixt and Between: The Liminal Period in Rites of Passage.” In The Forest of Symbols: Aspects of Ndembu Ritual. Cornell University Press, 1967. Use for: liminality, threshold identity, the candidate as “betwixt and between,” and darkness as embodied transition.Victor Turner. The Ritual Process: Structure and Anti-Structure. Aldine Publishing, 1969. Use for: liminality, communitas, anti-structure, social transformation, and the ritual pressure placed on ordinary identity.Catherine Bell. Ritual Theory, Ritual Practice. Oxford University Press, 1992. Use for: ritualization, ritual power, the ritualized body, and the temple as a structured environment that trains perception and action.Catherine Bell. “The Ritual Body and the Dynamics of Ritual Power.” Journal of Ritual Studies 4, no. 2 (1990): 299–313. Use for: ritualized bodies, spatial discipline, gesture, power, and the way ritual arrangements shape action.John C. Lilly. The Deep Self: Profound Relaxation and the Tank Isolation Technique. Simon & Schuster, 1977. Use for: the isolation tank, reduced stimulation, altered consciousness, and the modern technological black room.John C. Lilly. The Center of the Cyclone: Looking into Inner Space. Julian Press, 1972. Use carefully for: Lilly's altered-state/counterculture context, isolation tank work, consciousness exploration, and the bridge between research and psychedelic-era experimentation.Justin S. Feinstein et al. “Examining the Short-Term Anxiolytic and Antidepressant Effect of Floatation-REST.” PLOS ONE 13, no. 2 (2018): e0190292. Use for: Floatation-REST, reduced environmental stimulation, anxiety reduction, mood change, and the clinical side of float tanks.Hannah Hruby et al. “Induction of Altered States of Consciousness During Floatation-REST Is Associated With the Dissolution of Body Boundaries and the Distortion of Subjective Time.” Scientific Reports 14 (2024). Use for: float tanks, altered states, body-boundary dissolution, and subjective time distortion.Madison K. M. Garland et al. “A Randomized Controlled Safety and Feasibility Trial of Floatation-REST in Anxious and Depressed Individuals.” PLOS ONE 18, no. 6 (2023): e0286899. Use for: safety, tolerability, repeated Floatation-REST, and caution against overclaiming.Lashgari et al. “Floatation-REST Systematic Review.” 2025. Use for: the broad current state of Floatation-REST research, including anxiety, pain, stress, sleep, well-being, and the need for stronger standardization and larger studies.Michael T. H. Do. “Melanopsin and the Intrinsically Photosensitive Retinal Ganglion Cells.” Neuron 104, no. 2 (2019): 205–226. Use for: ipRGCs, melanopsin, non-image-forming vision, circadian entrainment, pupil response, sleep, and light as biological timing information.Lorenzo Lazzerini Ospri, Glen Prusky, and Samer Hattar. “Mood, the Circadian System, and Melanopsin Retinal Ganglion Cells.” Annual Review of Neuroscience 40 (2017): 539–556. Use for: light, mood, circadian rhythm, melanopsin, and the biological consequences of light exposure.Charles A. Czeisler and related circadian medicine research. Use for: artificial light, circadian disruption, melatonin suppression, shift work, and modern light exposure as a biological intervention.Anne-Marie Chang, Daniel Aeschbach, Jeanne F. Duffy, and Charles A. Czeisler. “Evening Use of Light-Emitting eReaders Negatively Affects Sleep, Circadian Timing, and Next-Morning Alertness.” Proceedings of the National Academy of Sciences 112, no. 4 (2015): 1232–1237. Use for: screens, evening light, melatonin suppression, delayed circadian timing, altered sleep, and modern light's effect on the body.A. Roger Ekirch. At Day's Close: Night in Times Past. W. W. Norton, 2005. Use for: premodern night, darkness before electric light, nocturnal fear, dreams, prayer, crime, labor, and the cultural history of darkness.A. Roger Ekirch. “Sleep We Have Lost: Pre-Industrial Slumber in the British Isles.” The American Historical Review 106, no. 2 (2001): 343–386. Use for: segmented sleep, first sleep and second sleep, night waking, dreams, prayer, and premodern sleep culture.Craig Koslofsky. Evening's Empire: A History of the Night in Early Modern Europe. Cambridge University Press, 2011. Use for: early modern night culture, artificial lighting, urban night, public space, and the transformation of darkness.Elisabeth Bronfen. Night Passages: Philosophy, Literature, and Film. Columbia University Press, 2013. Use for: symbolic and cultural readings of night, dream, fear, darkness, passage, and the imagination.Robert F. Taft. The Liturgy of the Hours in East and West: The Origins of the Divine Office and Its Meaning for Today. Liturgical Press, 1993. Use for: night offices, vigils, prayer through darkness, sacred time, and Christian ritual use of night.Bernard McGinn. The Foundations of Mysticism: Origins to the Fifth Century. Crossroad, 1991. Use for: Christian mystical traditions, contemplative darkness, early mystical theology, and the development of mystical language.Pseudo-Dionysius. The Complete Works. Translated by Colm Luibheid. Paulist Press, 1987. Use for: divine darkness, apophatic theology, mystical unknowing, and darkness as a theological category.John of the Cross. Dark Night of the Soul. Various editions. Use carefully for: spiritual darkness, purification, absence, mystical trial, and transformation.“The Neophyte Initiation Ritual.” Public Golden Dawn ritual material. Use carefully for: hoodwink, darkness, “Light dawning in darkness,” staged revelation, and the candidate being brought from night into day.Chögyal Namkhai Norbu. The Crystal and the Way of Light: Sutra, Tantra and Dzogchen. Routledge, 1986. Use for: Dzogchen context, light, vision, and the broader framework around contemplative perception.Christopher Hatchell. Naked Seeing: The Great Perfection, the Wheel of Time, and Visionary Buddhism in Renaissance Tibet. Oxford University Press, 2014. Use for: visionary practice, Great Perfection, Tibetan contemplative contexts, and careful treatment of luminosity and appearance.R. Shane Burns. “Dark Retreat in Tibetan Buddhist Practice.” Use for: dark retreat, preparation, disciplined context, and the difference between contemplative practice and casual sensory deprivation.Raymond Moody. Reunions: Visionary Encounters with Departed Loved Ones. Villard, 1993. Use for: modern psychomanteum practice, grief, mirror-gazing, and encounters with the dead.Arthur Hastings. “The Psychomanteum: A Modern Oracle of the Dead.” Use for: psychomanteum procedure, grief, memory, mirror-gazing, and structured encounter.Marcia K. Johnson, Shahin Hashtroudi, and D. Stephen Lindsay. “Source Monitoring.” Psychological Bulletin 114, no. 1 (1993): 3–28. Use for: inside/outside ambiguity, origin judgments, memory, imagination, and how dark or altered environments complicate interpretation.Shahar Arzy et al. “Induction of an Illusory Shadow Person.” Nature 443 (2006): 287. Use for: sensed presence, body-self disruption, temporoparietal junction, and the feeling of another being nearby.Olaf Blanke et al. “Neurological and Robot-Controlled Induction of an Apparition.” Current Biology 24, no. 22 (2014): 2681–2686. Use for: sensorimotor conflict, apparition-like presence, body-boundary disturbance, and the embodied basis of sensed presence.Also want to remind people about the website, if you're into reading we have tons of information by multiple contributors, and we got t-shirts up on the site if you're interested. Fun fact, the art is all based on the eyeball. A

Everyone is talking about Mercury-alpha, the mystery model that many believe could be GPT-5.6.In this live discussion, we're separating fact from speculation and unpacking what would actually matter if OpenAI releases a new flagship model this week.We'll cover:

How do you prove there's a real human on the other side of the screen when AI can generate faces, IDs, accounts, agents, and entire swarms of bots?Tiago Sada, Chief Product Officer at Tools for Humanity, joins The Neuron to explain why proof of human may become one of the internet's most important trust layers. Tools for Humanity is building the technology behind World and World ID, a system designed to verify that someone is a real, unique person without requiring them to reveal their identity across the web.Tiago breaks down why CAPTCHAs, phone numbers, KYC, and AI-detection systems are starting to fail; how World ID uses in-person verification, cryptography, and zero-knowledge proofs; and why the future internet may need to distinguish between humans, bots, and agents acting on behalf of humans.We also discuss concert ticket scalping, Tinder verification, Zoom deepfake protection, enterprise fraud, gaming bots, and why AI agents may need a kind of digital “power of attorney.”Subscribe to The Neuron for clear, practical conversations about AI and the future of technology: https://www.theneuron.ai/This episode is sponsored by Guru. https://www.getguru.com/?utm_source=theneuron&utm_medium=podcast&utm_campaign=silver-bundle-june2026

In this episode, Therese Markow and Dr. Boris Konrad discuss the striking impact of memorization on functional changes and connectivity in the brain. Dr. Konrad is a neuroscientist as well as an international Memory Champion. He not only studies brain connectivity, but also trains other memory athletes, as well as those who simply wish to improve their memories. They discuss more specific aspects of memorization and its benefits across a range of other activities and problem-solving, independent of the particular memorization training utilized. Dr. Konrad summarizes his recent study, published in the journal Neuron, and the techniques used to train the brain to improve memory.     Key Takeaways: Memorization and memory are not a part of the brain; they are functions of the brain. It is a capability of our brain and our neural system.  Without exception, memory athletes use the method of loci (colloquially called the "memory palace") as a technique to memorize and remember information.  Memory training actually decreases the brain activity needed to complete a range of tasks.   "Learning and thinking in your brain are not separate. We don't have a thinking brain and a learning brain; it's exactly one brain which does both." —  Dr. Boris Konrad   Connect with Dr. Boris Konrad: Donders Institute: https://www.ru.nl/en/people/konrad-b  Website: https://www.boriskonrad.com/en/  Memory Training: Superbrain! Memory Training with Boris Konrad - https://memory1.teachable.com/p/memory-training     TED Talks:  How to use memory techniques to improve education - https://www.youtube.com/watch?v=_qIBe0h0-Ig  The mind and methods of a Memory Champion - https://www.youtube.com/watch?v=t76N00urDlU  https://www.ted.com/talks/boris_nikolai_konrad_how_to_use_memory_techniques_to_improve_learning_and_education_jan_2018   Connect with Therese: Website:  www.criticallyspeaking.net Bluesky: @CriticallySpeaking.bsky.social Instagram: @criticallyspeakingpodcast Email: theresemarkow@criticallyspeaking.net    Audio production by Turnkey Podcast Productions. You're the expert. Your podcast will prove it.  

This Week In Startups is made possible by:Deel https://deel.com/twistQuo https://quo.com/TWiSTLinkedIn Jobs https://LinkedIn.com/twistToday's show:Cortical Labs is the world's first company selling biological computers. Their CL1 fuses lab-grown human neurons (derived from stem cells, not actual folks) with silicon hardware to create Synthetic Biological Intelligence (SBI).Founder Dr. Hon Weng Chong walks us through how the system works and why neurons are more efficient than GPUs at reinforcement learning. (Also… is this computer alive?)PLUS Pyka co-founder and CEO Michael Norcia explains the various uses for his autonomous aircraft, from crop-spraying drones in Brazil to a a hybrid-electric defense UAV for the military.Guests:Cortical Labs: ****https://corticallabs.com/Dr. Hon Weng Chong on X: https://x.com/dr1337Pyka: https://www.flypyka.com/Pyka on Instagram: https://www.instagram.com/flypyka/?hl=enFurther Reading:2022 Pong paper in Neuron: https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-62017 Paper: “Attention is All You Need”; https://arxiv.org/abs/1706.03762The “Barista Test” for Artificial Intelligence: Chris Rourk: https://medium.com/predict/the-turing-test-is-so-last-century-the-barista-test-for-artificial-general-intelligence-faf91034fa8cNotable Links:Playing “DOOM” on CL1: https://www.youtube.com/watch?v=yRV8fSw6HaEDayOne Data Center: https://dayonedc.com/NeurIPS 2026 Conference: https://neurips.cc/Neuralink: https://neuralink.com/CliniCloud Digital Stethoscope and Thermometer: https://www.design-industry.com.au/clinicloudAir Force Research Laboratory (AFWERX): https://afwerx.com/Joby Aviation: https://www.jobyaviation.com/Prime Movers Lab: https://www.primemoverslab.com/Timestamps:0:00 What is "biological computing"?2:49 Cortical's new $30 million raise4:15 The world's first biological data center9:48 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit https://deel.com/twist to learn more.10:51 Biological computers have a learning advantage19:43 Quo (formerly OpenPhone) - Quo gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free at https://quo.com/TWiST29:15 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at https://LinkedIn.com/twist38:46 From paper airplanes to Group 4 UAVs52:20 Introducing the DropShip defense drone58:28 How regulations block US drones1:00:40 Why Pyka builds everything in-houseSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisCheck out all our partner offers: https://partners.launch.co/Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.com

What if the next big AI breakthrough is not a bigger model, but a completely different kind of computer?Jeff Shainline, co-founder and CEO of Great Sky, joins The Neuron to explain how his team is building brain-inspired AI hardware using superconductors, photonics, and analog computation. Great Sky's architecture, called Superconducting Optoelectronic Networks, or SOENs, is designed to move beyond the traditional GPU roadmap by co-locating memory and processing, communicating with light, and mimicking some of the high-connectivity dynamics found in biological brains.In this conversation, Jeff breaks down why today's chips can struggle with fast, multimodal inference; why transformers may be powerful but inefficient for some future workloads; how Great Sky's system differs from quantum computing; and why early applications could include fusion reactors, particle physics, video understanding, content moderation, and eventually new model architectures that do not map neatly onto today's hardware.Subscribe to The Neuron for grounded, practical conversations about where AI is going next—and what actually has to work before the hype becomes real.

Voice agents are moving from “cool demo” to real product infrastructure.In this livestream, we're joined by Ben Cherry of LiveKit to break down what it actually takes to build real-time AI agents that can listen, respond, interrupt, call tools, and work in production.LiveKit is an open source framework and developer platform for building voice, video, and physical AI agents in production.We'll talk through the stack behind real-time AI experiences, then build and test a live demo together on The Neuron.In this live demo, we'll cover:

Today's episode is all about how childhood literally shapes the brain.Our most important experiences – from learning to read, to the growing complexity of our social lives at school, and even the video games we play – leave physical traces in how our brains get organized that shape how we see the world as adults.But how does the brain actually know what parts of our lives are actually important enough to reorganize around? How do particular experiences get under the hood to leave their mark on the developing brain?Today's guest, Stanford psychology professor Kalanit Grill-Spector, has spent her career trying to answer these questions. She's has been imaging children's brains – from infants to teenagers – to watch this reorganization unfold. Her work focuses on how our visual experience as children shapes our brains and how we see the world – what she and her team have found is not always what they expected.Learn MoreThe Vision and Perception Neuroscience Lab at Stanford Humanities and SciencesBrain's face recognition area grows much bigger as we get older (New Scientist, 2017)Neuroscientists use AI to simulate how the brain makes sense of the visual world (Wu Tsai Neurosciences Institute, 2025)Bridging nature and nurture: The brain's flexible foundation from birth (Wu Tsai Neurosciences Institute, 2025)Extensive childhood experience with Pokémon suggests eccentricity drives organization of visual cortex (Nature Human Behavior, 2019)Cortical recycling in high-level visual cortex during childhood development (Nature Human Behaviour, 2021)A unifying framework for functional organization in early and higher ventral visual cortex (Neuron, 2024)The emergence of visual category representations in infants' brains (eLife, 2024)White matter connections of human ventral temporal cortex are organized by cytoarchitecture, eccentricity and category-selectivity from birth (Nature Human Behaviour, 2025)Send us a text!Thanks for listening! If you're enjoying our show, please take a moment to give us a review on your podcast app of choice and share this episode with your friends. That's how we grow as a show and bring the stories of the frontiers of neuroscience to a wider audience.We want to hear from your neurons! Email us at at neuronspodcast@stanford.eduLearn more about the Wu Tsai Neurosciences Institute at Stanford and follow us on Twitter, Facebook, and LinkedIn. 

Jak úspěšně prodat a opustit byznys, který člověk desítky let buduje? Jak najít rovnováhu v mužském a ženském pohledu na podnikání? Čím se inspirovat, kdy si dokázat ustoupit?Jaroslav Řasa a a Monika Řasa-Vondráková jsou manželé, kteří spolu podnikají, společně cestují, spolu se setkávají i v činnosti a řízení prestižní nadace Neuron. Jaroslav je jedním ze zakladatelů silné softwarové firmy ABRA, kterou velmi úspěšně prodal - ale co dál?Začíná rozhovor natočený ve Vision byznys klubu za účasti jeho členů. Užijte si ho!Toto je na otevřených platformách vše. Pokud chcete vědět víc, moji odběratelé mají dvojnásobnou délku bez reklam a k tomu navíc téměř hodinový bonusový materiál! Zvu vás na http://www.herohero.co/petrhorky.00:00 Představení hostů a hlavních témat rozhovoru05:51 Inspirace pro vznik Neuronu16:40 Začátky podnikání a budování ABRY18:50 Růst firmy a přechod k řízení systémuSupport the show

What happens when AI stops simply giving answers and starts producing proofs a computer can verify?In this episode of The Neuron, Corey Noles and Grant Harvey talk with Tudor Achim, Co-Founder and CEO of Harmonic, the company behind Aristotle — a formal reasoning system built to generate machine-checkable mathematical proofs. Tudor explains why math may be the clearest test case for moving AI from “trust me” to “check me,” and why formal verification could matter far beyond Olympiad benchmarks.They discuss what “mathematical superintelligence” actually means, why Tudor thinks solving a Millennium Prize problem would be a meaningful threshold, and how Lean-based proofs could change the way mathematicians collaborate. They also explore Aristotle's real-world use cases, from open math problems to verified software, chip design, scientific computing, and the future of AI-assisted discovery.Plus: why Tudor thinks formal math has reached a “zero to one” moment, why specs may be the bottleneck in verified software, and why humans still need to direct the questions AI systems try to solve.Subscribe to The Neuron and sign up for The Neuron Daily at theneuron.ai.

May is Mental Health Awareness Month, and as AI becomes more embedded in our daily lives, one of the biggest questions we face is whether these systems can responsibly support emotional and psychological well-being.AI chatbots are increasingly being used for emotional support, but recent lawsuits faced by OpenAI and earlier ones targeting character.ai and Google's AI Overviews, as well as clinical reports, and internal research have raised valid concerns about their impact on vulnerable users.What does it take to build an AI system specifically designed for mental health from the ground up? Is that even possible?In this LIVE episode of The Neuron Podcast, Corey Noles and Grant Harvey speak with Daniel Reid Cahn, co-founder and CEO of Slingshot AI, about Ash, an AI application purpose-built for therapeutic support. Slingshot has raised $93M from a16z, Radical Ventures, and others to develop a foundation model for psychology trained on structured therapeutic conversations across modalities such as CBT, DBT, and psychodynamic therapy.We discuss the limitations of general-purpose chatbots in mental health contexts, recent controversies surrounding AI and psychiatric risk, and what differentiates a system designed to provide structured therapeutic engagement compared to one being used in a way it was never intended to be. The conversation also explores a broader question: Can AI meaningfully expand access to high-quality mental health care, and where should clear boundaries remain? Or should we keep our counseling where we always have, on a couch with a box of Kleenex and a hug nearby?

Teoretický informatik Václav Rozhoň hledá principy, na kterých stojí digitální svět. To je v dnešní době vysoce aktuální práce. Pracuje na Karlově univerzitě, má za sebou řadu zahraničních stáží, byl i rok na slovutném MIT ve Spojených státech. Mimo jiné je letošním držitelem prestižního ocenění Neuron.S Václavem Rozhoněm jsme se bavili o tom, kam směřuje současný vývoj umělé inteligence a musím říct, že bylo velmi zajímavé sledovat, jak je jeho pohled výrazně dál, než to, co obvykle zaznívá v obecných debatách - že bude umělá inteligence ovlivňovat lidi? Samozřejmě, tak je přece konstruovaná! Může se stát, že nás bude dokonce ovlivňovat tak, že o tom ani nebudeme vědět? Zajisté, to je jedna z možností - a má nám to vadit? To už tak jednoznačné být nemusí. Změní se trh práce? Samozřejmě. Víme přesně, jak umělou inteligenci vnímat - ani toto není jednoznačné. Ale nechci předbíhat! Toto jsou jen chuťovky k setkání a k debatě, které posouvá hranice toho, jak vnímat moderní počítačový svět ve vztahu k tomu lidskému. Užijte si to!Srdečně vás zvu na můj odběratelský kanál http://herohero.co/petrhorky. Dostanete dvojnásobnou délku našeho rozhovoru, nebudete přerušováni reklamami a k tomu podpoříte existenci mého kanálu. Odběratelé jsou pro nás zásadní.Předem díky za každý komentář, reakci, příspěvek do debaty a zdravím! Váš Petr Horký00:00 Kdy se z AI stává samostatná bytost?21:15 AI agenti: když spolu umělé inteligence začnou jednat.24:14 Může se AI začít vylepšovat sama?27:52 Kdo ovládne AI, bude mít svět?29:46 Žijeme v simulaci? AI, Bůh a smysl života.Support the show

Genspark went from AI search startup to autonomous AI agent platform, hitting $250M ARR in 12 months with no paid ads until they bought a Super Bowl spot. Co-founder and COO Wen Sang joins Corey and Grant to explain what "AI employee" actually means, demos Genspark Claw live (including buying us coffee mid-interview), and lays out his big thesis: legacy software is becoming infrastructure while AI agents become the new interface between humans and work. We get hands-on with Workspace 4.0, Claw, and a custom agent built live for the show.• Genspark Workspace 4.0 announcement: https://www.genspark.ai/blog/genspark-ai-workspace-4• Genspark sb-git: https://genspark.ai/sb-git/intro• OpenAI's customer story on Genspark: https://openai.com/index/genspark/• Forbes AI 50 (2026): https://www.forbes.com/lists/ai50/• Marc Benioff on Salesforce Headless 360 (referenced by Wen): https://x.com/Benioff • Andrej Karpathy's "wiki for agents" idea (referenced as inspiration for sb-git): https://x.com/karpathy• Wen on the DealMaker Show: https://alejandrocremades.com/wen-sang/Try Genspark for free: https://genspark.aiSubscribe to The Neuron newsletter: https://theneuron.ai

Hey rockstar,In the last piece, we explored why AI “fast money” shortcuts leave so many people feeling numb, overwhelmed, and disconnected — and why the real foundation of a sustainable business is still connection, care, and community.There's a closely related piece almost nobody is talking about:If numbness is what erodes your relationships, joy and wealth creation from the inside out, curiosity is what brings it back to life.Not just as a nice idea — but as a literal learning rate for your brain and your purpose.“Hey, before we jump in - when you get a moment, hit reply and tell me…. What's the #1 thing you're struggling with right now?The Number That Should Stop Every Purpose Driven Wealth Creation - ColdA developmental psychologist at Williams College tracked how many questions children ask per hour.At age five, the average kid asks 107 questions per hour. They're relentless. Why is the sky blue? Why do dogs have tails? Why does grandma's hair turn white? Their brains are running at full throttle, pulling in data from every direction.Then school starts.* By first grade, the entire class asks 2.3 questions per hour — combined.* By fifth grade? 0.48 questions per hour. Less than one question every two hours from a room full of eleven-year-olds.In one observation, kids were experimenting with an old-fashioned balance scale, genuinely doing science. The teacher shut it down: “Enough of that. I'll give you time to experiment at recess. There's no time for experiments now. We're doing science.”Read that again. No time for experiments… during science class.The researcher's conclusion is brutal: if you lose your curiosity by age 11, you probably don't get it back.I disagree on one thing. I think you can get it back. But you have to understand what curiosity actually is, neurologically. And that's where it gets interesting — especially for anyone trying to build something real in the AI era.Your Brain Is a Large Language Model (No, Really)The more I create custom services and learn about how advanced AI models work, the more clear it becomes: your brain is running the same basic algorithm.Consider the parallels:* Your brain has roughly 86 billion neurons connected by an estimated 100 trillion synapses.* GPT-4 has approximately 1.8 trillion parameters across its mixture-of-experts architecture.* Both are massive pattern-recognition networks.* Both learn by prediction.Here's how an LLM trains: it reads a sentence, predicts the next word, checks whether it was right, and adjusts its internal weights. Right answer? Strengthen that pathway. Wrong answer? Weaken it, try again. Billions of repetitions, trillions of adjustments.Your brain does the same thing.Every experience is a prediction. You reach for a coffee cup and predict its weight. You start a sentence and predict how the other person will react. When reality matches your prediction, your synapses strengthen. When it doesn't, your brain recalibrates. Neuroscientists call this predictive coding.A 2024 study found LLMs become more advanced, their internal representations actually become more similar to human brain activity during speech processing.Your brain is the original foundation model — pre-trained by evolution, fine-tuned by experience.But here's the critical difference:An LLM's learning rate is set by engineers. They decide how aggressively the model updates its weights in response to new data. Too high and it's unstable. Too low and it stops learning.In your brain, that learning rate has a name. It's called curiosity. And unlike an LLM, you can adjust it yourself.Curiosity as a Reward Signal: The Dopamine ConnectionUC Davis put people in an fMRI scanner and asked them trivia questions.What they found — published in the journal Neuron — changed our understanding of how curiosity works.When participants were highly curious, their ventral tegmental area (VTA) and nucleus accumbens lit up. These are the same brain regions activated by food, sex, and addictive drugs.Curiosity hijacks your reward circuitry. It's not a nice-to-have personality trait. It's a neurochemical event.But the more interesting finding was this: during the curious state, participants were shown random faces, completely unrelated to the trivia. Later, they remembered those faces significantly better than faces shown during low-curiosity moments.Curiosity didn't just help them learn the answer they wanted. It supercharged their memory for everything happening in that moment.This is exactly how reinforcement learning works in AI. When an LLM gets a reward signal through RLHF (Reinforcement Learning from Human Feedback), it doesn't just strengthen the specific output — The reward ripples through the network.Curiosity is your brain's RLHF. It's the reward signal that tells 86 billion neurons: pay attention, something important is happening, encode everything.Without that signal, your brain does what an untrained model does. It defaults to cached responses. You stop updating. You become, in AI terms, a frozen model.Curiosity Literally Keeps You AliveAnd this is about much more than learning faster.In 1996, researchers Gary Swan and Dorit Carmelli at SRI International followed 1,118 older men over five years as part of the Western Collaborative Group Study. They measured curiosity at baseline and tracked who survived.The result: highly curious people had significantly higher survival rates — even after controlling for age, smoking, cardiovascular disease, and other risk factors. They replicated the finding in 1,035 older women.Curiosity was directly associated with greater cognitive reserve — the brain's buffer against age-related decline.Curious brains keep building new connections. Incurious ones atrophy.Mindset is a biological variable. Curious people don't merely think differently — their brains physically maintain themselves better.Which means in business terms:The relentless drive to learn boosts your neurons and adaptability as much as any supplement or course.How We Lose Curiosity (And Why That Kills Businesses)We aren't born numb.However, school, social conditioning, and performance culture often suppress questioning. By the time most people start or grow a business, their curiosity has nearly vanished.We learn to:* Stop experimenting unless there's a guaranteed outcome* Protect what we already “know” instead of updating* Prioritize looking competent over actually learningLayer AI “shortcuts” on top of that and the effect compounds. You can ship more, post more, automate more — without ever engaging the deeper questions:* What is really happening in my market right now?* What are my clients actually struggling with beneath the surface?* Where am I out of alignment with what I'm selling?Without those questions, your wealth stops evolving in any meaningful way. You may still be iterating on tactics, but your inner model of reality is frozen.Numbness plus speed is just a faster way to hit the wall.The most dangerous thing that can happen to your brain — or your business — is to stop being surprised.How to Crank Your Learning Rate Back Up Five strategies for creative agency:1. Create information gaps intentionally. Curiosity arises when you know enough to spot gaps but not enough to fill them. Before meetings, read halfway through an article and enter with questions, not answers.2. Schedule daily “explore time.” Dedicate 30 minutes to learning about unfamiliar fields to keep your curiosity alive without aiming for expertise.3. Ask “dumb” questions among experts. Genuine learners ask for explanations, even in rooms full of accomplished people.4. Change your physical inputs. Perceptual and intellectual curiosity; try new routes, restaurants without menus, or confusing places to stimulate dopamine.5. Teach what you learn within 24 hours. Sharing knowledge helps organize and consolidate it—similar to fine-tuning data in LLMs.Curiosity, AI, and the “Whole Human” In a world obsessed with speed and automation, the temptation is to outsource not just your tasks, but your actual thinking — your contact with reality.But the future we actually want isn't built by numbed-out operators running frozen mental models, propped up by ever-fancier tools.It's built by people who are:* Awake enough to notice when they've gone numb* Curious enough to re-open the questions about what they're building* Grounded enough to use AI as support for their nervous systems and insight — not as a mask over their disconnectionThat's the through-line from the last piece to this one:* From extraction → to contribution* From performance → to presence* From “how do I hack the algorithm?” → to “how do I keep my own learning rate high enough to truly serve?”What This Means for YouIf you're an entrepreneur: Your competitive advantage isn't your product. It's your rate of learning. Build a culture that rewards questions over answers. Hire curious people over credentialed people.If you're an executive or practitioner: Schedule one hour a week to explore a field completely outside your industry. Those who survive disruption are the ones whose mental models are still updating.If you're investing in yourself: Bet on your curiosity the way a smart investor bets on a sole proprietor founder's adaptability. Curiosity predicts adaptability — and adaptability predicts survival.If you're a parent or leader of others: Count the questions in the room. If the number is dropping, the issue isn't the people — it's the environment. Protect spaces where real learning (which is always a little messy) is allowed.The Invitation to the Deeper MindLet the FOMO cool.Keep experimenting with AI — but pair every tool with a question:* What is this teaching me about my clients, my patterns, my assumptions?* Where am I tempted to go numb instead of stay curious?Rebuild your foundation with timeless ingredients: connection, care, community, and a living curiosity that aligns you with life—not just trends. Curiosity reconnects you with reality, countering numbness.That's how I use Generative AI in Oracle work: To awaken intuition, not replace it.When you open The Light Between Oracle, you enter an immersive experience blending symbolic language, somatic regulation, and guided integration—so insights land in your body, not just your mind.Here's the process:* You arrive scattered or braced.* The Oracle helps you downshift to hear yourself.* It reflects the clearest pattern at play.* You leave with one grounded step to take that day.The goal isn't more information—it's becoming someone whose inner model continually updates through presence, questions, and authentic connection.If you felt this piece in your bones, take the next step with me:Try The Light Between Oracle here: [Insert your link to the Oracle app]What you'll get from it:* Clarity without overwhelm (a focused prompt + practical direction)* Nervous system replenishment (so your guidance doesn't get drowned out by stress)* Better decisions through curiosity (questions that reopen your learning rate)* Aligned momentum (action that feels clean, not performative)* A daily wisdom + strategy practice you can actually sustainIf you want, hit reply and tell me what you're navigating right now—and I'll tell you the best place to start inside the Oracle. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit thelightbetween.substack.com/subscribe

Can AI move from predicting proteins to actually designing new drugs? Isomorphic Labs is trying to answer one of the biggest questions in science.In this episode of The Neuron, Corey Noles and Grant Harvey talk with Rebecca Paul, Head of Medicinal Drug Design at Isomorphic Labs, and Michael Schaarschmidt, Foundational AI Research Lead.They explain why drug discovery is so slow, expensive, and failure-prone—and why AI drug design is much more complicated than “generate a molecule and ship it.” The conversation covers AlphaFold, structure prediction, molecule generation, binding models, clinical failure rates, human trust in AI systems, and the long-term hope of designing drugs for targets once considered “undruggable.”In this episode:Why drug discovery can take more than a decadeWhat people misunderstand about “AI-designed drugs”How medicinal chemists actually use AI modelsWhy biology is harder than text, images, or codeWhat it would take to make drug discovery faster and cheaperThe dream of designing a drug candidate in one iterationWhy “undruggable” proteins may not stay undruggable foreverAdditional resources:Technical report blog Best resource for learning about the capabilities that we are buildingIsomorphic Labs websiteBest destination for learning more about Iso and joining our team in London, Lausanne or Cambridge, MASubscribe for more grounded conversations on how AI is changing science, work, and the world.For more practical, grounded conversations on AI systems that actually work, subscribe to The Neuron newsletter at https://theneuron.ai.

Join us Thursday as we break down OpenAI's new Workspace Agents and what they mean for the future of work.We'll cover:⚙️ What workspace agents are

Today's episode is about the neuroscience of hard work—or maybe more specifically, the value we place on hard work.There's something different about hiking to the top of a mountain versus taking a helicopter. The view from the top is exactly the same, but if you've done the hard slog to get there, the payoff is going to be much more rewarding. The question is, how does the brain know the difference? To answer this, we need to take a deep dive into the brain's reward system, and one of our favorite neurotransmitters, dopamine. And it turns out, the way dopamine operates is more complicated than we thought.Our guest today, Stanford Medicine psychiatrist Neir Eshel, tells us about new research that's starting to reveal exactly how the brain pushes us to work hard for the things that matter to us. Learn MoreEshel's Stanford Translational Addiction and Aggression Research (STAAR) LabWhy we value things more when they cost us more (Stanford Medicine, 2026)Cholinergic modulation of dopamine release drives effortful behaviour (Nature, 2026)Striatal dopamine integrates cost, benefit, and motivation (Neuron, 2023)Dopamine and serotonin work in opposition to shape learning (Wu Tsai Neuro, 2024)Why we do what we do (From Our Neurons to Yours, 2024)Send us a text!Thanks for listening! If you're enjoying our show, please take a moment to give us a review on your podcast app of choice and share this episode with your friends. That's how we grow as a show and bring the stories of the frontiers of neuroscience to a wider audience.We want to hear from your neurons! Email us at at neuronspodcast@stanford.eduLearn more about the Wu Tsai Neurosciences Institute at Stanford and follow us on Twitter, Facebook, and LinkedIn. 

Google just acquired an AI startup that lets anyone create real music, music videos, and custom instruments — no experience required. In this hands-on episode, Corey sits down with Kendall Rankin from Google to demo Flow Music (formerly Producer AI), the generative music tool now living inside Google Labs. They build a garage rock song about AI from scratch, generate a music video with VEO, and dig into what "amplifying human creativity" actually looks like when the tool can do most of the lifting. Listeners walk away with a clear view of where AI music tools fit in an artist's workflow, why watermarking (SynthID) matters, and how to try it for free.Try Flow Music: https://producer.ai Google Labs: https://labs.google SynthID (watermarking): https://deepmind.google/technologies/synthid/ Subscribe to The Neuron newsletter: https://theneuron.ai

OpenAI dropped GPT-5.5, so we did the only reasonable thing: went live immediately and tried to break it.In this off-the-cuff Neuron Live, Corey and Grant walk through OpenAI's GPT-5.5 release notes, benchmark claims, rollout details, and early access reactions before testing the model live across coding, reasoning, creativity, web research, and absurd prompt challenges. We also compare a few GPT-5.5 responses against Claude Opus 4.7, test Codex, build a new version of Cat Doom, and ask the important questions, like whether a sentient vending machine that only dispenses expired tuna salad deserves to live.In this episode, we cover:• What OpenAI says is new in GPT-5.5• GPT-5.5's improvements in coding, computer use, research, and knowledge work• Early benchmark results across Terminal-Bench, GDPval, Frontier Math, BrowseComp, and scientific research tasks• Why token efficiency may matter as much as raw intelligenceGPT-5.5's rollout across ChatGPT, Codex, Plus, Pro, Business, and Enterprise• Live Codex testing with a one-shot Cat Doom game buildCreative stress tests involving palindromes, time-traveling potatoes, dystopian vending machines, and Lord of the Rings product reviews• First impressions of whether GPT-5.5 feels meaningfully different from GPT-5.4 and Claude Opus 4.7This was not a formal benchmark. It was a first-contact livestream: messy, fast, weird, and exactly the kind of test we like.Subscribe for more AI breakdowns, live model tests, beginner-friendly explainers, and weirdly useful prompt experiments from The Neuron.Sign up for The Neuron newsletter: https://www.theneuron.ai/Follow along for more AI news, analysis, and live experiments.

Grant and Kyle dive into a comprehensive review and live test of the newly released Claude Opus 4.7, a cutting-edge large language model. This session explores its capabilities for coding and game dev, specifically referencing the "Renaissance / Plan Final Fantasy Tactics RPG Game" project. Discover how this ai model performs under pressure and its potential impact on game design workflows.

Neuroscientist Paul Nuyujukian likens the brain to a stadium full of people. To eavesdrop on the crowd you could put a microphone in the middle of the stadium. But to understand the conversations you need to record individual people. He thinks about the brain the same way. To understand brain disease, he studies neurons—one at a time. And his insights are shedding light on a big global issue—stroke. The World Health Organization predicts one in four adults will have a stroke in their lifetime. Strokes can cause death, or lead to paralysis or speech problems. But there's still a lot researchers don't know about how the brain recovers from an event like a stroke. Nuyujukian directs a lab at Stanford University that studies how the brain controls movement, including after neurological events like stroke. We get into how he does this, and why he hopes his research could eventually help people who've been paralyzed. Email us your questions about the brain – or anything else to do with science at shortwave@npr.org. We may turn it into an episode in the future!Listen to every episode of Short Wave sponsor-free and support our work at NPR by signing up for Short Wave+ at plus.npr.org/shortwave.To manage podcast ad preferences, review the links below:See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

AI can reason about text and images, but it still struggles to understand the physical world. In this episode, Grant sits down with Peter Wilczynski, Chief Product Officer at Vantor (formerly Maxar Intelligence / Digital Globe), to unpack why spatial intelligence is emerging as critical AI infrastructure. Peter spent years at Palantir building ontology systems and mapping tools for defense operations before joining Vantor, where his team has built a 100M+ square kilometer 3D model of the entire Earth at 50cm resolution. We dig into how satellite imagery becomes machine-readable through embedding models, why "ground truth world models" are fundamentally different from hallucinated ones, the Raptor GPS-alternative system, simulation and digital forensics, the future of augmented reality, and why the physical world might be the most important thing AI still doesn't understand.Vantor: https://vantor.comTensorGlobe Platform: https://vantor.com/product/platform/Vantor rebrands from Maxar Intelligence (Business Wire): https://www.businesswire.com/news/home/20251001760322/en/Vantor-Rebrands-from-Maxar-Intelligence-Unveils-AI-Powered-PlatformSubscribe to The Neuron newsletter: https://theneuron.ai

What actually causes cognitive decline, and how much of it can we do something about? In this episode, Michael talks with neurologist and neuroscientist Dr. Majid Fotuhi about dementia, Alzheimer's, memory loss, and the everyday habits that shape brain health over time. They discuss why Alzheimer's is only part of the story, why some people remain mentally sharp into old age, and what the evidence says about exercise, sleep, diet, stress, and cognitive activity. They also cover ADHD, attention, brain training, and the difference between ordinary forgetfulness and something more serious. At the center of it all is a simple but important idea: many people think cognitive decline is just an unavoidable part of aging, when in fact there is often more room to protect brain function than most of us realize. Majid Fotuhi, MD, PhD, is an adjunct professor of Neuroscience at Johns Hopkins's Mind/Brain Institute, an adjunct professor of Psychological and Brain Sciences at George Washington University, and is the medical director of NeuroGrow Brain Fitness Center.  His groundbreaking, proprietary research has been published in The Lancet, Nature, Neurology, Neuron, Proceedings of National Academy of Science, the Journal of Prevention of Alzheimer's Disease, Journal of Rehabilitation, and Journal of Alzheimer's Disease Reports, among others. His new book is The Invincible Brain: The Clinically Proven Plan to Age-Proof Your Brain and Stay Sharp for Life.

They have screens. They have toys. They have activities. And yet — they trail you around the house saying 'I'm bored.'In this episode I unpack:● Why having access to everything is making children less able to entertain themselves — not more● The neuroscience of genuine curiosity and why screens can't replicate it● What boredom is actually communicating (it's not what you think)● The gift of the unoccupied afternoon — and how to make it work● How your own curiosity is the most powerful teaching tool you haveReferences:Gruber, M. J., Gelman, B. D., & Ranganath, C. (2014). States of curiosity modulate hippocampus-dependent learning via the dopaminergic circuit. Neuron, 84(2), 486–496.Kashdan, T. B., & Silvia, P. J. (2009). Curiosity and interest: The benefits of thriving on novelty and challenge. In S. J. Lopez & C. R. Snyder (Eds.), Oxford Handbook of Positive Psychology (pp. 367–374).Dent, M. (2003). Saving Our Children from Our Chaotic World. Pennington Publications. Episode #87 — Why Your Child Needs Boredom and How to Use It as a Teaching Tool

What does it actually take to make AI work inside a real business, where messy data, human judgment, and operational risk all collide? In this episode, I sit down with Matt Fitzpatrick, CEO of Invisible Technologies, to talk about why the biggest barrier to enterprise AI is not model quality, it is everything that comes before the model ever gets to work. Since stepping into the CEO role in January 2025, Matt has moved quickly, raising $100 million and expanding Invisible's footprint across major cities including New York, San Francisco, DC, Austin, London, and Poland. But this conversation is far less about headlines and far more about what happens in the trenches of AI adoption, where companies are trying to move from pilots and PowerPoint promises to systems that actually deliver results. A huge theme throughout our discussion is data readiness. Matt makes a compelling case that most businesses are still dealing with fragmented systems, inconsistent records, and information spread across disconnected tools. That reality makes it incredibly hard to deploy AI in a way that creates trust and value. We talk about SwissGear, where Invisible used its Neuron platform to clean and structure 750 scattered tables in just one week, a task that could have taken a large engineering team months or longer. We also discuss why that kind of work matters so much, because once the data foundation is fixed, companies can start making better decisions on forecasting, operations, and planning with a level of confidence that simply was not there before. We also spend time on Invisible's human-in-the-loop approach, which I think will resonate with a lot of listeners trying to cut through the noise around job displacement and agentic AI. Matt argues that the real opportunity is not replacing people, but giving them better tools to handle repetitive work while preserving room for human expertise, judgment, and oversight. He shares examples from commercial credit workflows, healthcare, and sports analytics, including a fascinating story about the Charlotte Hornets using AI to turn broadcast footage into detailed tracking data. What stood out to me was how practical his perspective felt. This was not theory. It was about building systems around how organizations actually work, rather than expecting businesses to reshape themselves around a generic AI product. Another part of the conversation that deserves attention is governance. As boards rush to understand agentic AI, Matt explains why trust, standards, and responsible deployment are now driving buying decisions just as much as raw capability. We talk about privacy in healthcare, the risks of scaling autonomous systems without mature governance, and why enterprise adoption still trails consumer AI by a wide margin. That gap between excitement and execution may be one of the most important stories in AI right now. If you are wondering why so many AI projects never make it into production, or what it will take for enterprise AI to finally deliver on its promise, this episode is packed with insight. It is a conversation about data, deployment, governance, and the role humans will continue to play as AI becomes part of everyday business operations. After listening, I would love to know where you stand, is the future of AI really about bigger models, or is it about making AI fit the messy reality of how work gets done?

Brandon Baum — better known as heybrandonb to his 25M+ followers — built a YouTube empire making cinematic, effects-heavy videos that look like they cost millions but were born in a bedroom during COVID. In this episode, we get into how he went from 2 views to a million followers in a month, why he shoots everything on iPhones with a custom 3D-printed dual-phone rig, how AI tools like Firefly Boards have replaced his Post-it Note wall, and why he thinks the atmosphere is "ripe for change" in Hollywood. We also talk about what content is actually performing now (hint: it's not spectacle anymore), his plan to seed original IP on social before taking it to theaters, and why he's building custom AI agents to offload his admin so he can just be creative.Brandon B's YouTube channel:https://www.youtube.com/@heybrandonbAdobe Firefly Boards: https://firefly.adobe.com/LM Studio / Ollama (referenced in OpenClaw discussion): https://lmstudio.ai/ https://ollama.com/Subscribe to The Neuron newsletter: https://theneuron.ai

Let's build with v0 in real time. We're going LIVE with Tom Occhino, Chief Product Officer at Vercel, to explore vibe coding and take a hands-on look at v0, Vercel's AI-powered development platform for building apps faster. We'll show v0 live and walk through how it turns a simple prompt into a real, shippable interface. Tom will also explain what “vibe coding” actually looks like in practice, including how teams are using it today and where it fits into modern development workflows. What we'll cover:⚡ You'll see a live build using v0, from the first prompt to a working app.

A team of former Google DeepMind researchers just raised $2B to build America's answer to DeepSeek. In this episode, we sit down with Ioannis Antonoglou (Yannis), co-founder and CTO of Reflection AI, who helped create AlphaGo—the AI that beat the world champion in the game of Go back in 2016. Yannis breaks down what Reflection is building, why they're releasing frontier-level AI models as open-weight, and how mixture-of-experts architecture lets massive models run efficiently. We dig into reinforcement learning, the US vs. China open source gap, sovereign AI, coding agents, and why open science might be the fastest path to the most powerful AI on the planet.Reflection AI: https://www.reflection.aiReflection AI raises $2B at $8B valuation (TechCrunch): https://techcrunch.com/2025/10/09/reflection-raises-2b-to-be-americas-open-frontier-ai-lab-challenging-deepseek/Previous Neuron coverage of DeepSeek: https://www.theneuron.ai/newsletter/deepseek-returns https://www.theneuron.ai/newsletter/10-wild-deepseek-demosSubscribe to The Neuron newsletter: https://theneuron.ai

Crystal Clear wraps Season 18 with the most comprehensive episode in the show's history, connecting the CDC Morgellons study to parallel Chinese and American brain-computer interface programs, DARPA-funded implantable biosensors with Chinese investors, and a technology supply chain that traces back to 2001. Featuring timestamped podcast analytics showing coordinated Chinese surveillance from three brain research cities, the real explanation for the drug-use correlation in Morgellons patients, and a new framework for understanding what Morgellons actually is — not a bioweapon, not a disease, but an installation platform for neural biosensor technology in a bilateral brain-machine interface arms race.The CDC Morgellons study running concurrently with China's first Brain Project 2008-2011. The Armed Forces Institute of Pathology shutdown. Michelle Pearson's transfer from lead CDC investigator to BRAIN Initiative chief of staff. The US BRAIN Initiative as a response to China's earlier program. The China Brain Project's “one body two wings” framework connecting cognition research to brain-inspired AI.DARPA funding Profusa implantable biosensors while Chinese investors Qihoo 360 and Tasly Pharmaceutical Group sit on the same cap table. Ben Hwang as CEO. The Ansoft to Ansys to Synopsys acquisition chain and its role as the global standard simulation platform for implantable antenna design, wireless power transfer to medical implants, and biosensor development. China's SAMR regulatory jurisdiction over the $35 billion Synopsys-Ansys deal.Morgellons as a prediction error loop — engineered materials designed to be almost-but-not-quite recognizable, continuously triggering mismatch negativity, P300, and N400 neurological responses. The brain's error correction process as the most valuable training dataset for artificial general intelligence. Why the ambiguity of Morgellons materials is a design feature not a coincidence.The drug supply chain as delivery mechanism. Chinese control of precursor chemicals for fentanyl and methamphetamine. Chinese manufacturing of active pharmaceutical ingredients for prescribed psychotropics. Insufflation and smoking as direct routes to neural tissue. Blood-brain barrier permeability from stimulant use. The CDC documenting the delivery route and calling it a risk factor.Timestamped podcast analytics showing a Chinese listener surge from 0.2% to 15% within days of filing an open records request to Oklahoma State University. Listeners concentrated in Harbin, Xiamen, and Lanzhou — three cities with active roles in China's brain research and defense infrastructure. Web browser access patterns. The audience disappearing within days of the callout episode. Jenny Chan's unsolicited email to a private address during the same window.The bilateral collaboration framework — American and Chinese institutions as co-conspirators in a classified neural interface program, with the cover-up protecting the partnership rather than either government individually. The 12,000 person patient registry at OSU as a deployment map. The open records request filed February 23, 2026 — still unanswered.References & Sources:CDC Kaiser Permanente Morgellons Study 2012 — “Clinical, Epidemiologic, Histopathologic and Molecular Features of an Unexplained Dermopathy”China Brain Project 2008-2011 — Atlantis Press proceedingsChina Brain Project 2016-2030 — Neuron journal, Poo et al.Profusa Series C filing August 2018 — PR NewswireAnsys HFSS implantable antenna simulation — Ozen Engineering white papersSynopsys-Ansys acquisition July 2025 — SEC filingsLuis Elizondo, Imminent (2025)Listen: Available wherever you get your podcastsContact: moremorgellons.comSupport the show: Follow, subscribe, rate, review, comment!!!

Most people are still using ChatGPT the way they used Google in 2005: type a question, get an answer, close the tab.In 2026, that's like owning a professional kitchen and only using the microwave.In this episode, Grant and Corey walk through The Neuron's 5-Level AI Proficiency Stack — a framework for going from “I use ChatGPT sometimes” to “AI saves me 10 hours a week.”No coding required. No hype. Just the actual progression that separates casual users from people getting real, compounding value out of AI every single day.The 5 Levels:

In this episode, Dr. Brendan McCarthy—Chief Medical Officer at Protea Medical Center—dives into one of the most misunderstood topics in health: Why does it feel like you can't stick to a diet… even when you're trying your best? This isn't about willpower. It's not a character flaw. And it's not your fault. Dr. McCarthy breaks down the biology behind stress, cravings, and weight gain—explaining how chronic stress rewires your brain, alters decision-making, and drives you toward hyper-palatable, ultra-processed foods.   YouTube citations :  1. Arnsten, Amy F. T. “Stress Weakens Prefrontal Networks: Molecular Insults to Higher Cognition.” Nature Neuroscience, vol. 18, no. 10, 2015, pp. 1376–1385. Why it is here: Foundational paper for the claim that uncontrollable stress increases catecholamine signaling in the prefrontal cortex and degrades higher-order control, working memory, and inhibition. This is one of the strongest anchors for the idea that stress makes the pause smaller.   2. Schwabe, Lars, et al. “Concurrent Glucocorticoid and Noradrenergic Activity Shifts Instrumental Behavior from Goal-Directed to Habitual Control.” Journal of Neuroscience, vol. 30, no. 24, 2010, pp. 8190–8196. Why it is here: One of the most important papers for your “click-boom” model. It shows that stress chemistry can bias behavior away from goal-directed control and toward habit-like responding. That is not a morality argument. It is control architecture.   3. Plessow, Franziska, et al. “The Stressed Prefrontal Cortex and Goal-Directed Behaviour: Acute Psychosocial Stress Impairs the Flexible Implementation of Task Goals.” Experimental Brain Research, vol. 216, no. 3, 2012, pp. 397–408. Why it is here: Strong support for the claim that acute psychosocial stress impairs flexible goal implementation. Useful when you want to say that under stress, the person may still know what matters but have reduced access to that guidance in the moment.   4. Maier, Silvia U., et al. “Acute Stress Impairs Self-Control in Goal-Directed Choice by Altering Multiple Functional Connections within the Brain's Decision Circuits.” Neuron, vol. 87, no. 3, 2015, pp. 621–631. Why it is here: Excellent for the food-choice angle. This paper supports the idea that stress increases the weight of immediately rewarding attributes and reduces self-control. In your language, the cue gets louder and the future gets quieter.   5. Epel, Elissa, et al. “Stress May Add Bite to Appetite in Women: A Laboratory Study of Stress-Induced Cortisol and Eating Behavior.” Psychoneuroendocrinology, vol. 26, no. 1, 2001, pp. 37–49. Why it is here: Classic paper, directly in women, directly in Psychoneuroendocrinology. Strong support for linking stress physiology, cortisol reactivity, and post-stress eating behavior.   6. Giddens, Emily E., et al. “The Influence of Stress on the Neural Underpinnings of Disinhibited Eating: A Systematic Review and Future Directions for Research.” Reviews in Endocrine and Metabolic Disorders, 2023. Why it is here: A modern review tying stress to food-related reward sensitivity, interoception, and cognitive control in disinhibited eating. Good bridge reference for the overall brain-food-stress model.   7. Lyu, Z., et al. “Acute Stressors Reduce Neural Inhibition to Food Cues and Increase Eating Among Binge Eating Disorder Symptomatic Women.” Frontiers in Behavioral Neuroscience, 2016. Why it is here: Helpful for the specific claim that acute stress can reduce inhibitory neural responsiveness to food cues and increase eating in vulnerable women. Strong fit for the cue-reactivity piece.   Dr. Brendan McCarthy is the founder and Chief Medical Officer of Protea Medical Center in Arizona. With over two decades of experience, he's helped thousands of patients navigate hormonal imbalances using bioidentical HRT, nutrition, and root-cause medicine. He's also taught and mentored other physicians on integrative approaches to hormone therapy, weight loss, fertility, and more. If you're ready to take your health seriously, this podcast is a great place to start.  

Brian Gerkey is the CTO of Intrinsic, the robotics software company that started inside Alphabet and now sits inside Google, working directly with DeepMind and Gemini. Brian co-created ROS (Robot Operating System), the open-source platform used by over 1 million developers that powers everything from factory robots to NASA's Astrobee on the International Space Station. In this episode, Grant talks with Brian about "physical AI" — what happens when AI leaves the screen and starts controlling robots in the real world. They cover why 80% of US manufacturing facilities still have zero automation, how Intrinsic's platform acts as the "Android of robotics," the breakthroughs in AI-powered perception that let robots see with sub-millimeter accuracy using cheap cameras, the challenges of simulating physical contact (friction is a nightmare), and why the best robot application ideas often come from people who know nothing about robots.Subscribe to The Neuron newsletter: https://theneuron.aiIntrinsic: https://www.intrinsic.ai/ROS (Robot Operating System): https://www.ros.org/AI for Industry Challenge: https://www.intrinsic.ai/events/ai-for-industry-challengeIntrinsic joins Google (Feb 2026): https://www.intrinsic.ai/blog/posts/intrinsic-joins-google-to-accelerate-physical-ai

Don’t mind me, I’m just taking a little jellyfish nap!

Most businesses don't buy their AI services directly from OpenAI or Google—they buy it through a massive, invisible distribution network called "the channel." Victoria Durgin and Katie Bavoso of Channel Insider join Corey and Grant to explain how this hidden industry works, why AI is shaking it up unlike anything before, and what it means for businesses trying to adopt AI in 2026.Subscribe to The Neuron newsletter: https://theneuron.aiChannel Insider: https://channelinsider.com

In this episode of The Neuron Podcast, Corey Noles and Grant Harvey sit down with Dan Shipper, CEO of Every, to talk about agent-native engineering—the framework his team uses to build and ship AI-powered products at a pace most companies can't match.Dan walks us through what happened when his AI document editor Proof went viral (and then went down), why he believes the way we build software is fundamentally changing, and how Every's small team manages to ship and maintain an entire suite of AI tools: Spiral (automatic style guides from your writing), Sparkle (AI writing cleanup with custom folders), Cora (AI research assistant, now on iOS), Monologue (AI-powered journaling with notes), and Proof (the agent-first document editor that broke the internet for a day), as well as their new to be revealed on Friday: Plus One (a hosted AI agent for Slack).Whether you're a founder, developer, or just someone trying to understand what "agentic" actually means in practice—this conversation is the real-world playbook.Subscribe to The Neuron newsletter: https://theneuron.aiProducts mentioned:• Every: https://every.to• Spiral: https://spiral.computer• Sparkle: https://sparkle.computer• Cora: https://cora.computer• Monologue: https://www.monologue.to/• Proof: https://proofeditor.ai• Plus One (the new one!): https://every.to/plus-one

Nick Heiner leads RL environment development at Surge AI, the bootstrapped company that hit $1.2B in revenue training models for OpenAI, Anthropic, Meta, and Google. In this episode, we break down reinforcement learning environments—the secret training grounds where AI agents learn to actually do work. Nick shares why even the best models fail 40% of real workplace tasks, what happened when 200 Wall Street experts graded GPT-5 and Claude, and his prediction that a $1B company with one human employee could exist by 2030.Resources: • Surge AI Research – Hierarchy of Agentic Capabilities: https://arxiv.org/abs/2601.09032 • Surge AI Blog: https://surgehq.ai/blog • Nick's Sonnet 4.5 Review: https://surgehq.ai/blog/sonnet-4-5-product-take • Nick's Substack: https://nickheiner.substack.com/ • SurgeHQ's enterprisebench: https://surgehq.ai/blog/enterprisebench-corecraft • Nick's hilarious Gemini 3.1 review: https://nickheiner.substack.com/p/gemini-31-pro-not-leading-edge-also  • Hemingway-bench AI Writing Leaderboard https://surgehq.ai/blog/hemingway-bench-ai-writing-leaderboard • LMArena is a cancer on AI: https://surgehq.ai/blog/lmarena-is-a-plague-on-ai Subscribe to The Neuron newsletter: https://theneuron.ai

This week we welcome Paula Reichenberg, founder of Neuron, for a sharp and thoughtful conversation about legal translation, artificial intelligence, and what happens when professional expertise collides with tools that look polished but still miss the mark. Paula shares her path from M&A and capital markets law into business school, legal services, machine learning, and finally legal tech entrepreneurship. What started as frustration with inefficiencies inside law firms grew into a translation business, then evolved again as machine translation improved and forced a harder question about survival, adaptation, and quality.Paula explains how her early company, Hieronymus, found success by handling sensitive, high-stakes legal translations in Switzerland, especially where precision and confidentiality mattered most. But as machine translation improved, the market for average work started to disappear. Clients began doing more on their own, leaving only the hardest, highest-value assignments for specialists. Rather than ignore the shift, Paula leaned into it. That decision led her back to university, into data science and machine learning, and toward building Neuron, a company focused less on replacing expertise and more on improving the process around imperfect AI output.A central theme of the discussion is the uncomfortable truth that many users do not care as much about excellence as professionals do. Paula makes the point with refreshing honesty. AI often produces work that is mediocre, but for a large share of users, mediocre is enough. That creates both a market shift and a professional dilemma. In legal translation, as in legal drafting more broadly, the issue is rarely whether AI produces something flawless. The issue is whether the user notices what is wrong, has the time to fix it, and has the systems in place to improve the result efficiently. Paula argues that the real value is not in claiming perfection. It is in helping experts find the mistakes faster, correct them with less pain, and avoid wasting hours doing work that feels like cleanup on aisle five.The conversation also digs into trust, user behavior, and the strange authority people give to AI-generated answers. Paula recounts how, in one negotiation, a party trusted ChatGPT's answer more than a human tax lawyer's detailed explanation, even when the AI response was wrong. That anecdote opens up a broader discussion about confidence, presentation, and why polished outputs often feel more persuasive than expert judgment. Greg and Marlene connect that idea to legal systems, translation quality, and access to justice, especially where technology might offer better service than overworked and underfunded human systems. The result is not a simple pro-AI or anti-AI position. It is a grounded look at where human excellence still matters, where automation fills gaps, and where the future may split between mass-market convenience and premium, highly tailored expertise.Looking ahead, Paula sees consolidation coming to legal tech, along with a growing push toward seamless interfaces that bring best-in-class features into one place. For Neuron, that means becoming an embedded layer inside other legal tools rather than forcing lawyers to juggle yet another standalone platform. Her crystal ball view is both stylish and sobering. The legal industry is not simply moving toward automation. It is sorting itself into tiers of service, quality, and expectation. And if Paula is right, the future belongs to those who understand where “good enough” ends and where true expertise still earns its premium.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack[Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]  ⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ Transcript

Proton—the company behind the world's largest encrypted email service with 100M+ users—just launched Lumo, a privacy-first AI assistant. We sit down with Eamonn Maguire, who leads Proton's ML team and built Lumo from the ground up. Eamonn has a PhD from Oxford and a postdoc at CERN, and he breaks down how Lumo's encryption actually works, why Big Tech's business model prevents them from building private AI, the real privacy threats hiding inside viral AI trends like Ghibli-fication, and whether AI agents are safe to connect to your bank account. Listeners will learn how encrypted AI handles your data differently, what open-source models power Lumo, and why "set-and-forget" agents are still more hype than reality.

Carta CMO Nicole Baer joins Corey and Grant to break down the real state of startups in 2026. With half of all venture funding now flowing to AI-native companies and seed deals at a six-year low, the startup playbook has fundamentally changed. Nicole shares Carta's data on solo founders, the new billion-dollar timeline, why the Bay Area's grip is tighter than ever, and how AI is reshaping everything from marketing to fund administration.Carta State of Startups 2025 Report: https://carta.com/blog/state-of-startups-2025/Carta Data & Insights (free): https://carta.com/data/Subscribe to The Neuron newsletter: https://theneuron.ai

Recorded live at NVIDIA GTC 2026 in San Jose, Corey sits down with returning guest Kari Briski—VP of Generative AI Software for Enterprise at NVIDIA—to unpack their biggest open-source model yet: Nemotron 3 Super. Kari breaks down why a 120B-parameter model runs as fast as a 12B one, how multi-agent systems are going from science fiction to production, and why Jensen Huang is calling this "a new operating system." We also dig into NVIDIA's work on Open Claw security, the 35x explosion in open-model token generation, and where omni-modal AI is heading next.Subscribe to The Neuron newsletter: https://theneuron.aiRelevant links:NVIDIA Build (try Nemotron): https://build.nvidia.comNemotron on Hugging Face: https://huggingface.co/nvidiaOpen Router: https://openrouter.aiKari's previous Neuron episode (Oct 2025): https://youtu.be/p0INn_w7TYo

Scientific discovery has always been slow. Until now.In this episode, we sit down with Dr. Qichao Hu, CEO of SES AI, to reveal how they are using AI agents to turn a 8-year research cycle into a 2-week sprint. By combining autonomous "wet labs" with advanced AI models, they are solving one of the hardest physics problems in tech: the battery bottleneck.We dive deep into how this "Molecular Universe" project isn't just about EV batteries—it's about unlocking power for data centers, robotics, and AR glasses. If you want to see a concrete example of AI agents working in the physical world to solve material science constraints, do not miss this conversation.

Science likes to call itself a meritocracy. Angela Anderson and Brandi Mattson know better. Both served as editors at elite journals (Cell and Neuron), where a single decision could determine who gets tenure, funding, or obscurity. They watched brilliant data get filtered out because the authors did not know the unwritten rules controlled by 5 dominant publishing houses with profit margins higher than Google.In 2020, amid pandemic shutdowns and national reckoning over racial injustice, they co-founded a nonprofit to expose that hidden curriculum. Through the JEDI program, they provide 10 hours of free editorial consulting to scientists who lack access to elite networks. In 1 year alone, 25 awards helped researchers salvage canceled grants, secure NSF career funding, and rebuild careers derailed by rejection.This episode pulls back the curtain on the multibillion dollar publishing engine that profits from taxpayer funded science and reveals who gets heard, who gets sidelined, and how insiders are choosing to redistribute power.RELATED LINKSAngela AndersonBrandy MattsonLife Science EditorsLife Science Editors FoundationCellNeuronNational Science FoundationFEEDBACKLike this episode? Rate and review Out of Patients on your favorite podcast platform. For guest suggestions or sponsorship email podcasts@matthewzachary.comSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we sit down with Yaron Inger, co-founder of Lightricks and LTX, to explore the future of open-source AI video.LTX-2 is currently the #1 ranked open-source audio & video model on Hugging Face — with over 4.5 million downloads in just two months.But what makes it different?It runs locally.It can be fine-tuned on your own IP.It integrates into real video workflows.And it might change how filmmaking, education, and creative work evolve in the AI era.We talk about:• Why open models are catching up to Big Tech• How smaller models are getting better through distillation• Running AI video on consumer GPUs• Infinite, autoregressive video generation• AI teachers that change environments in real time• Whether AI will replace filmmakers — or empower themIf you care about the future of creativity, open AI, or the economics of filmmaking… this one is worth your time.Check out LTX: https://ltx.ioLTX-2 on Hugging Face: https://huggingface.co/Lightricks/LTX-2.3 LTX Desktop Repo: https://github.com/Lightricks/LTX-DeskFor more practical, grounded conversations on AI systems that actually work, subscribe to The Neuron newsletter at https://theneuron.ai.

You've probably used Canva—but you probably haven't seen what it can do with AI. In this episode of The Neuron, we sit down with Danny Wu, Head of AI Products at Canva, to explore how the platform went from a simple design tool to a full-blown "Creative Operating System" powered by AI—serving 230+ million users every month.Danny walks us through how Canva's MCP server lets you create fully editable designs from inside ChatGPT, Claude, and Microsoft Copilot, why their new Canva Design Model is fundamentally different from typical AI image generators (hint: layers), and why 24 billion AI tool uses later, the most surprising use cases are ones they never anticipated.We also get Danny's take on whether AI will homogenize all design, his advice for freelancers who don't want to get replaced, and a live demo of Canva's AI design generation in action.You'll learn:• How MCP powers Canva inside ChatGPT, Claude, and Copilot• What the Canva Design Model understands that GPT-4 doesn't• Why editable layers (not flat images) are the real AI design breakthrough• Danny's advice for freelancers to become irreplaceable in an AI world• How Canva uses AI internally on tens of millions of lines of code• Why AI assistants are becoming "the new SEO" for user acquisitionTry Canva AI at https://canva.com/aiSpecial thanks to the sponsor of this video, Cohesity: https://www.cohesity.com/ResilienceEverywhere/?utm_source=brand-ta-podcast&utm_medium=direct-publisher&utm_campaign=fy26-q2-01-amer-us-digital-awarewbpg-brd-genbr&utm_content=podcastFor more practical, grounded conversations on AI and emerging tech, subscribe to The Neuron newsletter at https://theneuron.ai.

Matthew Cobb is a British zoologist and Emeritus professor of zoology at the University of Manchester.Get his book, The Idea of the Brain: A HistoryCloser to Truth's Map of Consciousness: loc.closertotruth.com/mapTIMESTAMPS:0:00 The Heart or the Head?4:13 Medicine in the Ancient World12:25 Why Don't We Accept Evidence?18:34 From Ancient to Modern Understanding29:29 When Did We Reach a Consensus on the Brain?37:41 Electricity in the Brain39:58 Our Metaphors for the Brain44:15 Is the Brain Segmented or Whole?01:05:20 Why is Speech Governed by the Left Hemisphere?01:18:55 Why is the Brain Split Into Two Hemispheres?01:23:06 Where in the Brain Does Consciousness Originate?01:32:46 The Ladybug Robot01:35:08 Back to Consciousness01:45:27 What is a Neuron?01:56:04 Why is Smell Connected to Memory So Strongly?02:02:14 Do London Cab Drivers Have Larger Hippocampi?02:10:11 The Limits of MRI and CT Scans02:19:24 Will We Ever Be Able to See Consciousness in the Brain?

Ryan Carson taught over 1,000,000 people how to code at Treehouse and spent 25% of his entire life doing it. Now he says everything about that process needs to change.In this livestream, Ryan joins Corey Noles and Grant Harvey to rethink programming education from scratch. When AI agents can write production code, pass competitive coding challenges, and ship features while you sleep.We'll cover:

Episode 237 NPTEFF Understanding Upper vs Lower Motor Neuron Lesions