Podcasts about machines

Joseph O'Connell launched Creative Machines from his garage over two decades ago with a mission: Create objects and environments that encourage creativity, support social interaction, and inspire confidence. Since then, the Tucson-based design and fabrication firm has ballooned in size and scope, creating and installing over 100 public artworks for clients on seven continents.Today, Creative Machines is famed for its interactive exhibitions, kinetic sculptures, light installations, and a commitment to community engagement. They even test their projects by having everyone from schoolchildren to retired engineers “play with the art and call out the BS” before anything leaves the studio.We sat down with Joseph O'Connell, founder and artistic director of Creative Machines, to talk about the economics of public art, his new nonprofit playground in Tucson, and his studio's entry in our summer exhibition, 250: A Celebration of Public Art in the U.S.Contacts & SocialsWebsite: https://www.creativemachines.comInstagram: @creativemachinesLinkedIn: https://www.linkedin.com/company/creative-machinesEpisode CreditsHost: Scott “Sourdough” PowerGuest: Joseph O'Connell, founder and artistic director of Creative Machines, featured artist in 250: A Celebration of Public Art in the U.S.Production: Crewest Studio, Los AngelesTheme Music: Ricky Peugeot & Desi DeLauro of Parlor SocialStay in the Loop: Subscribe to NOT REAL ART, and follow us on Instagram for more coverage of the 250: A Celebration of Public Art in the U.S.

The world is barreling towards disaster on many fronts. Crises include: climate change, depopulation, government debt, sagging welfare states, housing affordability, healthcare affordability, political polarization, government paralysis.By 2050 they will all be irrelevant, as will the structures trying to grapple with them.SOURCES:Kokotajlo, Daniel, et al. AI 2027. ai-2027.com. Kokotajlo, Daniel. "What 2026 Looks Like." 2021.Amodei, Dario. "Machines of Loving Grace." 2024.TechTimes. "OpenAI GPT-5 Biological Risk Classification." July 27, 2026.Axios. "The AI Titans' Biggest Private Fear." July 24, 2026.Center for a New American Security (CNAS). "AI and the Evolution of Biological National Security Risks." August 2024.AI Incident Reporting Act. 2026.AI Kill Switch Act. 2026.Schneier, Bruce. "AI Surveillance Is Being Supercharged." Schneier on Security, July 2026.DeepMind. "AlphaFold: Five Years of Impact." 2024.Bostrom, Nick. "The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents." Minds and Machines, 2012.Bostrom, Nick. "Astronomical Waste: The Opportunity Cost of Delayed Technological Development." Utilitas, 2003.Vinge, Vernor. A Fire Upon the Deep. Tor Books, 1992.Freitas, Robert A., Jr. "A Self-Reproducing Interstellar Probe." Journal of the British Interplanetary Society, vol. 33 (1980): 251–264.Wikipedia. "Great Horse Manure Crisis of 1894."Oxford Academic. Book chapter on William Crookes and the wheat-supply crisis (1898 address to the British Association for the Advancement of Science).Jevons, William Stanley. The Coal Question: An Inquiry Concerning the Progress of the Nation, and the Probable Exhaustion of Our Coal-Mines. Macmillan, 1865.Ricardo, David. "On Machinery." Chapter 31, On the Principles of Political Economy and Taxation, 3rd ed. John Murray, 1821.United Kingdom. Report of the Inter-Departmental Committee on Physical Deterioration. 1904.Vinge, Vernor. "The Coming Technological Singularity: How to Survive in the Post-Human Era." Hosted on Acast. See acast.com/privacy for more information.

Everybody’s talking about AI like we’re five minutes away from iRobot. Jobs disappearing. Machines taking over. Humans becoming obsolete. But after ten years in tech and several years working hands-on with AI, Siquoyia Blue isn’t buying every doomsday headline. In this candid late-night episode of the Blu Alchemist Podcast, Siquoyia challenges the fear surrounding artificial intelligence and talks about what AI actually looks like in everyday life. She shares how she’s used it to find grants, create art, develop content, and make everyday processes more efficient. But this isn’t an episode about worshipping AI either. Siquoyia digs into the human side of the technology—the ethics, guardrails, questionable corporate practices, bias, responsibility, and the people ultimately making decisions behind the machine. AI is powerful. It will change industries. It will change how we work. But fear alone isn’t a survival strategy. Adaptability is. Curiosity is. Learning how to use new tools is. Instead of asking whether AI is coming to replace us, maybe we should be asking a better question: Are we preparing ourselves for the world that’s coming next? Subscribe to Blu Alchemist Podcast Substack Newsletter: https://siquoyiablue.substack.com/ Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Website: https://www.blualchemistpodcast.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Siquoyia Blue Website: https://siquoyiablue.komi.io⁠⁠⁠⁠ YouTube: @blualchemistpodcast Buy Dating Assassins Card Game: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.datingassassins.com ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ If you want to either be a guest on or find guests for your podcast, please sign up here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.joinpodmatch.com/siquoyia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Donate via Cashapp: @KingSiquoyia or Venmo: @KingShay Thanks for listening! Subscribe, Share and Follow us!

On the Record with Christian Briggs – AI systems are also becoming better at analyzing vocal cues, facial movement, hesitation, and other signals associated with human emotion. They do not literally read minds, but they can increasingly adapt their behavior based on how they think a person is reacting. Christian looks at the Tony Robbins AI coaching platform, along with internet speculation about...

Deep tech entrepreneur D. Scott Phoenix spent years building AI — now, he believes we're on the cusp of a profound merger between humans and machines. Reframing the AI debate through the lens of evolutionary biology, he shifts the question from whether we should fear or embrace AI to whether we understand what's at stake if we get it wrong. Hear his provocative case for why we need to "eat the AI." After the talk, Sherrell interviews Baratunde Thurston, host of Life with Machines, on how to live well with technology. Hosted on Acast. See acast.com/privacy for more information.

Solitary, cold, methodical and unencumbered by scruples or regrets, a killer waits in the shadows, watching for his next target. Yet, the longer he waits, the more he thinks he's losing his mind, if not his cool.

The Product Momentum team reached out to Barry O'Reilly, seeking his expertise in helping product leaders rethink how organizations make decisions, innovate, and perform in the age of artificial intelligence. After a quick review of his CV – co-founder of Nobody Studios (a global Top 10 AI venture studio) and author of Artificial Organizations: Build Better Judgment, Speed, and Results with Human and Machine Intelligence (March 2026) – and we knew we had identified the ideal guest for this episode. In this conversation with Product Momentum, Barry explains that AI's greatest value comes not in replacing human judgment. Instead, it is in building systems that give humans greater capacity, better information, and stronger decision-making capabilities. Use AI to Bolster Human Judgment As Phil Hornby shared in episode 178, “decision-making lies at the heart of the product manager job.” AI can accelerate analysis, synthesis, and execution, Barry argues, but humans must remain responsible for the decisions themselves. AI is a powerful thinking partner that can plow through data, but it must not be the autonomous decision-maker some want it to be. “Judgment is like a muscle,” Barry continues. “If you stop using it, it starts to erode.” That erosion happens gradually. To product teams that are already overwhelmed, a polished AI response can feel good enough. That's why Barry recommends challenging AI rather than simply accepting its first response. Ask your new partner to expose blind spots, test assumptions, and provide disconfirming perspectives. The goal is not to eliminate human judgment. It is to use AI to make that judgment more informed and effective. Turn Administrative “Grunt” Work Into Product Intelligence AI can also give product teams more time for the work they find most valuable. Barry describes a common imbalance in product organizations: teams frequently spend only a small portion of their time actually solving complex problems. The rest goes toward meetings, documentation, status tracking, and other necessary administrative work. AI can reduce that burden by turning everyday interactions into useful organizational data. “Every time I'm sitting on customer calls, I transcribe them and put them into a database,” he says. My AI tool is constantly churning through customer comments to where I'm able to extract the key problems that keep coming up.” It's an approach that changes the role of AI from simple task automation to decision infrastructure. For product teams, these conversations become searchable sources of customer insight. Prototypes ≠ Production-Ready Products No one can argue the benefit of Gen AI's ability to dramatically lower the effort required to turn an idea into a working prototype; it creates exciting opportunities for product teams and executives. But it also introduces risk when over-anxious teams mistake prototypes for finished software. Barry has observed teams build impressive experiences quickly, only to discover serious problems when usage increases. “It's very easy to prototype these days; but it's still quite hard to productionize software.” Production software still requires thoughtful architecture, performance, security, and engineering discipline. For organizations operating at enterprise scale, that distinction matters even more. Responsible product development still requires the expertise needed to make the resulting system secure, reliable, and resilient. Listen to the full conversation with Barry O’Reilly to learn how product leaders can put the human-machine partnership to work. [04:58] Think about your decision-making process. Most of us never evaluate the way we make decisions; we're unaware of the internal algorithm that we're using to make them. [07:08] Machines are terrible decisionmakers. Machines are great at capturing information and synthesizing it. But they’re terrible at making decisions. That’s what humans are really, really good at. [15:02] The 80-20 rule applied. Before using these tools, I spent only 20% of my time on creative problem solving; now I’m at 40%…that’s a 100% improvement. [21:31] Judgment is like a muscle: if you stop using it, it starts to atrophy. [22:06] Ceding our agency is a road to perdition. Every time I don’t actively participate in a judgment call, I’m giving up my agency. I’m deferring my responsibility. The moment you start to give up on making the decisions is it’s a road to peridition. [31:09] It's very easy to prototype these days; but it's still quite hard to productionize software. The post 195 / Barry O'Reilly: AI Should Strengthen Product Judgment, Not Replace It appeared first on ITX Corp..

Episode: 1619 Theatre of Machines -- forerunners of engineering handbooks.  Today, the first handbooks.

This week, Juliet and Jacoby react to 20 tons of squid being spilled on a highway, learn about Italy's cheese vaults, and discuss the rise of Burger King and the Whopper. For this week's Taste Test, they try La Colombe coffee. Finally, they close the show by sharing their Personal Food News and reacting to some Listener Food News. Do you have Personal Food News? We want to hear from you! Leave us a voicemail at 850-783-9136 or email ListenerFoodNews@Gmail.com for a chance to have your news shared on the show. Be sure to check us out on YouTube and TikTok for exclusive clips, new Taste Tests, and more! Discover Extra Virgin Olive Oils From Spain. Hosts: Juliet Litman and David Jacoby Producer: Mike Wargon Musical Elements: Devon Renaldo Learn more about your ad choices. Visit podcastchoices.com/adchoices

Something strange is happening to us. The intelligent machines we've built to serve us have started to sound like us, look like us and even think like us. The line between real and artificial is dissolving… so, what awaits us in the uncanny valley?Across six episodes, award-winning journalist Marc Fennell will explore how AI will change us as humans.So much of the conversation around AI is about technology and speculation about the future. But this about us: how AI will change our sense of self, our sense of reality, the way we love and the way we grieve. Parents bring back a murdered son. Romantics fall for code that talks back. Machines read minds. Spirituality is found, and lost, in code.Marc Fennell's Unreal is a human-first exploration of how intelligent machines are reprogramming what being “human” actually means.Listen to Unreal: When AI Becomes Us right now on Audible. Download the Audible app today.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Something strange is happening to us. The intelligent machines we've built to serve us have started to sound like us, look like us and even think like us. The line between real and artificial is dissolving… so, what awaits us in the uncanny valley?Across six episodes, award-winning journalist Marc Fennell will explore how AI will change us as humans.So much of the conversation around AI is about technology and speculation about the future. But this about us: how AI will change our sense of self, our sense of reality, the way we love and the way we grieve. Parents bring back a murdered son. Romantics fall for code that talks back. Machines read minds. Spirituality is found, and lost, in code.Marc Fennell's Unreal is a human-first exploration of how intelligent machines are reprogramming what being “human” actually means.Listen to Unreal: When AI Becomes Us right now on Audible. Download the Audible app today.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Something strange is happening to us. The intelligent machines we've built to serve us have started to sound like us, look like us and even think like us. The line between real and artificial is dissolving… so, what awaits us in the uncanny valley?Across six episodes, award-winning journalist Marc Fennell will explore how AI will change us as humans.So much of the conversation around AI is about technology and speculation about the future. But this about us: how AI will change our sense of self, our sense of reality, the way we love and the way we grieve. Parents bring back a murdered son. Romantics fall for code that talks back. Machines read minds. Spirituality is found, and lost, in code.Marc Fennell's Unreal is a human-first exploration of how intelligent machines are reprogramming what being “human” actually means.Listen to Unreal: When AI Becomes Us right now on Audible. Download the Audible app today.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Something strange is happening to us. The intelligent machines we've built to serve us have started to sound like us, look like us and even think like us. The line between real and artificial is dissolving… so, what awaits us in the uncanny valley?Across six episodes, award-winning journalist Marc Fennell will explore how AI will change us as humans.So much of the conversation around AI is about technology and speculation about the future. But this about us: how AI will change our sense of self, our sense of reality, the way we love and the way we grieve. Parents bring back a murdered son. Romantics fall for code that talks back. Machines read minds. Spirituality is found, and lost, in code.Marc Fennell's Unreal is a human-first exploration of how intelligent machines are reprogramming what being “human” actually means.Listen to Unreal: When AI Becomes Us right now on Audible. Download the Audible app today.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

durée : 00:41:14 - Les Nuits de France Culture - par : Albane Penaranda - Comment enquêter sur le spiritisme sans le juger ni y croire ? Christine Bergé raconte son immersion au cœur de ces pratiques occultes ou paranormales, au sein d'une communauté spirite qu'elle aborde avec un esprit ouvert mais toujours critique, une zone frontière qu'elle apprécie particulièrement. - équipe : Mathias Le Gargasson, Antoine Dhulster, Rafik Zénine, Vincent Abouchar, Emily Vallat, Hassane M'Béchour, INA Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

Today, we're resharing an episode that's perfect for a summer listen. We're answering Maddox's question about what happens to your quarter when you put it inside a claw machine. It just zips away! Ryan and Bridget talk to an expert who lets them peek inside a claw machine to find out where that quarter goes. After getting some tips on how to win at the claw, Bridget gets a little too hung up on trying to win a stuffie, leaving it up to Ryan to bring her back to reality (shocking, we know).

Today, we're resharing an episode that's perfect for a summer listen. We're answering Maddox's question about what happens to your quarter when you put it inside a claw machine. It just zips away! Ryan and Bridget talk to an expert who lets them peek inside a claw machine to find out where that quarter goes. After getting some tips on how to win at the claw, Bridget gets a little too hung up on trying to win a stuffie, leaving it up to Ryan to bring her back to reality (shocking, we know).

The Primus is on!!! It's Valentine and Sarge vs the violent machines in a battle for supremacy!!!This episode contains adult language and violence. Hosted on Acast. See acast.com/privacy for more information.

No race? Nope! It's the second summer mini-break, giving everyone some time to catch their breaths. It also raises the question what a million dollar rider does to relax. Drinks at a tropical beach, anyone? That'd be our plan, surely. Not sure what cocktails would be involved, but feel free to let us know your best guess for your favourite rider. The last time we had a break like this was last month, and we spend it talking about the characteristics of the top five riders. This week we're doing something similar, but looking at the other side of the equation. That's right, it's time for shiny metal and high tech wizardry as we dive head first into bike analysis! There's five different machines, and while some are clearly better than others they all have some very unique characteristics. And if you're like Mat and Peter, this is the kind of stuff that keeps you up at night. Small wonder, then, that your hosts have plenty of thoughts on the matter. In fact, I'd argue that this week's episode is so big it might just kill any spare time you'd have had until the next race. Lucky! So go imagine yourself on some brilliantly sunny shores, pour out that cocktail and press play. We've got some serious bikes to discuss...-----Want more? Visit our website or support us on Patreon. With big thanks as always to Brad Baloo from The Next Men and Gentleman's Dub Club for writing our theme song. Check out The Nextmen for more great music! And additional thanks to flowerhead, who's music you can find here. Oh, and a quick word in regards to sponsors: If you're interested in connecting with a really unique MotoGP audience — we're working with Smash Brand Group out of Sydney to manage partnerships. Curious? Just head to smashbrandgroup.com.au and get in touch!

“The machines today are like toddlers learning how to walk. They stumble. They're not very good. They make mistakes.” — Anmol Madan One in three American adults are already using AI for health information — with or without their doctors' permission. The machines, in other words, are already seeing us. This will chill some Americans in our summer of luddite discontent. For others, however, like the San Francisco-based medical tech entrepreneur Anmol Madan, the appearance of doctor AI in our lives is mostly good news. In his new book, The Machines Will See You Now, Madan lays out what he calls a “human roadmap” to “autonomous health care.” I'm not entirely sure what he means by “human” in a Blade Runner-style world where machine and man are quickly merging. But by “autonomous,” which I suspect is a euphemism, Madan means artificial intelligence. What worries Madan about our current moment is the broken dialogue over AI. On the one hand, we have tech utopians promising a totally automated healthcare industry. Then we have an anxious establishment struggling to change America's archaic and often dysfunctional medical system. And, of course, American consumers (if that's the right word) who are already using ChatGPT or, more troublingly, TikTok, as their doctor. America spends $4.7 trillion on a healthcare industry which compares poorly with the medical systems of other wealthy countries. Madan's “parallel universe,” he promises, would cost half as much and double access. The machines will see you now. Like it or not, Dr AI is our all-too-human future. Five Takeaways •       One in Three Already Ask the Machines. The KFF poll behind the episode: a third of American adults already use AI for health information, with or without their doctors' blessing — and if they're not asking ChatGPT, they're asking TikTok. Madan's frustration is the broken dialogue between AI exuberance (“we're going to automate healthcare”) and medical anxiety, when the right answer is in between: new technology is no excuse for throwing out the guardrails of medical devices and clinical safety. The stakes are the brutal arithmetic of American medicine — $4.7 trillion spent for the worst outcomes among peer nations — and his “parallel universe”: half the cost, twice the access, delivered by AI systems that are tested, safe, and rigorous. Consumer appetite is already there; the safeguards are not.•       The Waymo Scale for Medicine. The book's organizing framework applies the self-driving industry's levels of autonomy to healthcare. Level zero is today: 99 percent of decisions — diagnosis, treatment, prescription — made by humans. Level one is doctor assistance, already deployed: radiologists who once hauled backpacks of reports now guided by machines to where to focus. Levels two and three ease machines into the lowest-stakes treatment and diagnostic decisions with human review — and the fully autonomous end state, Madan concedes, may never arrive. To Andrew's objection that Waymo's scale ended with the drivers removed, Madan offers the transatlantic pilot: autopilot flies ninety percent of the route, and nobody thinks the pilot doesn't matter. The structure, he argues, is what lets regulators, doctors, and builders finally talk about the same thing.•       Toddlers Learning to Walk. Madan's metaphor for today's medical AI: toddlers — stumbling, error-prone, needing layers of protection, and badly underestimated at their peril and ours. The mistake, he argues, is concluding that because the systems aren't perfect we shouldn't try them at all, when a constrained system is starving for capacity. Pressed by Andrew on what the machines will never do (“toddlers grow up”), his list is candid: human perception — reading body language, assessing the person who walks into the clinic — improves far more slowly than diagnostic reasoning and may never reach human capacity; and the relationships people form with chatbots, loneliness epidemic notwithstanding, have no literature yet showing they produce clinical outcomes like a human therapist's thirty minutes. Plus one asterisk on the machines' famous exam results: we grade them on human benchmarks, and machines fail differently than humans do.•       The Behavior-Change Trillion. Of America's $4.7 trillion, a full trillion is the behavior-change problem — the eating, drinking, smoking, and sitting that no pamphlet has ever fixed. Andrew's objection: nobody needs an MIT degree to know they should exercise, so why would a machine's nagging beat a doctor's? Madan's answer is the space between visits: patients leave the office motivated and fall off within days, and personalized systems — like those he built for tens of millions at his previous companies — learn what actually moves each individual: this one walks more but won't change diet, that one needs the stress addressed first, another needs the language and cultural register matched. Not one-size-fits-all “eat healthy,” but friction removed person by person, programmatically, at a scale no human workforce could staff. Andrew's rejoinder: in an age of ubiquitous AI slop, the exercise reminder may be deleted as exactly that.•       Priceless. On trust, Andrew invoked the neighbors: Slippery Sam Altman, the mistrusted AI giants, and entrepreneurs — RadiantGraph included — getting rich while asking for our bloodwork. Madan's counsel is unexpected caution: in the AI era all data matters, healthcare data most of all, and it belongs on healthcare-specific, HIPAA-bound platforms — not pasted into general chatbots. He concedes San Francisco's mansions-and-homelessness inequity (he advises New York City's Department of Public Health and wants to help at home), but defends the Bay Area as the place where the PC, the iPhone, the web, and now AI actually happened — Jeff Dean announced his next act the morning they recorded. And the bot test: how would he prove he's human? “I'm quite flawed, and I'm often wrong. An AI avatar of Anmol probably wouldn't be as wrong as I sometimes am.” Fittingly priceless — which is what Anmol means in Sanskrit. About the Guest Anmol Madan is a healthcare entrepreneur and computer scientist, and the founder and CEO of RadiantGraph, an AI platform helping health plans and healthcare organizations deliver proactive care. An MIT Media Lab PhD who worked on the first generation of wearables, he founded Ginger, the pioneering AI tele-psychiatry company later acquired by Headspace, and served as Chief Data Scientist at Livongo and as a data and AI executive at Teladoc Health. He advises the New York City Department of Public Health and lives in San Francisco. The Machines Will See You Now: A Human Roadmap to Autonomous Health Care (Johns Hopkins University Press, September 1, 2026) is his first book. References: •       The Machines Will See You Now: A Human Roadmap to Autonomous Health Care by Anmol Madan (Johns Hopkins University Press, September 1, 2026). Alex Pentland, MIT: “A critical read about AI in he...

Referee Adam Levitan presides over the most anticipated battles of the fantasy football year. Representing The Man, our grass-touching, hard-working patriot Evan Silva, faces off against Mom's basement freak in the Excel sheets Machines, represented by ETR's own Mike Leone. Silva and Leone argue their cases for the ranking discrepancies of 17 players before Levitan decides who presented the better argument to crown the 2026 Preseason Winner of Man vs. Machine.Links mentioned in the episode:⁠⁠⁠⁠⁠Subscribe to Draft Kit Pro for all our articles, tiers and rankings this draft season⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Evan Silva's Top 150 Rankings for 2026 Fantasy Football⁠⁠⁠⁠⁠⁠⁠Evan Silva's Top-150 Change Log for 2026⁠⁠⁠⁠⁠Subscribe to the Establish The Run YouTube ChannelTimestamps:0:00 - Introduction4:52 - #1) Justin Jefferson8:35 - #2) Kyle Pitts12:18 - #3) Bucky Irving15:24 - #4) Kenneth Walker20:35 - #5) Tee Higgins24:15 - #6) Brock Bowers29:57 - #7) Kyren Williams34:24 - #8) AJ Brown37:44 - #9) Mike Evans40:35 - #10) Luther Burden45:18 - #11) Trey McBride51:08 - #12) Cam Skattebo54:06 - #13) J.K. Dobbins57:37 - #14) Quentin Johnston1:01:27 - #15) Josh Downs1:05:07 - #16) Juwan Johnson1:07:55 - #17) Patrick MahomesWant ETR on your team this season? Our 2026 NFL Draft Kit Pro has you covered with:Draft Rankings & TiersResearch & Analysis ArticlesDraft Strategy ContentIn-Season Roster ManagementTrade CalculatorsDiscord CommunitySubscribe now at ⁠⁠⁠https://subscribe.establishtherun.com/nfldraftkitpro/⁠⁠⁠DraftKings Best Ball: Draft One, Get OneEnter DraftKings' $20M Best Ball contest for $25 and you'll receive a bonus ticket to play a second Best Ball draft for free. Available to all DraftKings customers.⁠⁠⁠Sign Up Now⁠⁠⁠! ⁠⁠⁠https://dkng.co/ETRBestBall⁠⁠⁠Gambling Problem? Call 1-800-GAMBLER or 877-8-HOPENY/text HOPENY (467369) (NY). Help is available for problem gambling. Call (888) 789-7777 or visit [⁠⁠⁠ccpg.org⁠⁠⁠](⁠⁠⁠http://ccpg.org⁠⁠⁠) (CT).18+ in most eligible states, but age varies by jurisdiction. Eligibility restrictions apply. Void where prohibited. 1 per customer. Must enter a lineup into the NFL Best Ball $20M Headliner Contest. $25 entry fee. Bonus issued as 1 ticket to NFL Best Ball $20M Headliner Contest. Ticket reward is site credit valid for use only on NFL Best Ball $20M Headliner Contest. Ticket reward is single-use and expires at contest lock on 9/9/26. See terms at⁠⁠⁠ https://www.draftkings.com/promotions⁠⁠⁠. Ends 9/9/26 at contest lock. Sponsored by DraftKings.FREE NEWSLETTER: Tired of attention-seeking hot takes? Get the highest-quality fantasy football analysis in your inbox, FREE: https://establishtherun.kit.com/emailDFS OPTIMIZER: Sign up for THE SOLVER for access to the software we think fantasy players need to win: ⁠⁠⁠https://thesolver.com/?ref=etr⁠⁠⁠SPORTSBOOK OFFERS: We've partnered with several major sportsbook outlets to help supply you with the best offers in the industry and ensure you're maximizing your bankroll from the start: ⁠⁠⁠https://establishtherun.com/offers/⁠⁠⁠FOLLOW US: Check out our social media channels for FREE fantasy football & DFS videos, analysis, and more: ⁠⁠⁠https://linktr.ee/establishtherun

Fraud BOMBSHELL: 2020 Election HACKED, Machines Can Change VOTES. John Solomon, Investigative Journalist. Watch this entire show at- https://www.youtube.com/live/26Udl7BpBj8?si=PG2a5vVgnSsj7-CX Benny Johnson 6.1M subscribers 91,905 views Streamed live on Aug 6, 2026 The Benny Show If you want to help support independent journalism, become a Member:    / @bennyjohnson   FOLLOW BENNY ON SOCIALS: https://www.bennyjohnson.com/follow CHECK OUT OUR MERCH: https://shop.bennyjohnson.com/ Sign up for The Benny Newsletter: https://www.bennyjohnson.com/newsletter SUBSCRIBE TO THE PODCAST https://www.bennyjohnson.com/thebenny...

Startup Project sits down with Sviat, CEO of Bright Machines, to unpack how the company is using software-first robotics to manufacture complex electronics closer to where they're deployed. The conversation focuses on why AI infrastructure is a strategic category, how Bright Machines differs from traditional contract manufacturing, and what onshoring really means for speed, quality, and security.Key Topics:In this episode, Sviat explains that Bright Machines is focused on AI infrastructure, specifically the electronics that go inside modern data centers, including compute nodes, storage, and racks.He traces the company's thesis back to a broader idea: use software and robotics to manufacture electronics anywhere, then narrow that focus to the data center market as demand became clearer.The discussion breaks down the market stack, from chip designers like NVIDIA and AMD, to ODMs, OEMs, hyperscalers, and contract manufacturers.Sviat shares why data center hardware became the right bet before ChatGPT accelerated the market: the products are expensive, strategically important, and driven by quality and throughput more than labor cost alone.The show compares traditional assembly lines with Bright Machines' approach, which uses more robotics, sensors, cameras, traceability, and humans in the loop where automation does not make sense.Sviat explains how Bright Machines starts with design, using Bright Designer to simulate and improve manufacturability before lines are built, which helps reduce bottlenecks and improve automation over time.He says the company's main differentiator is its software platform, which orchestrates the line, powers smart skills for navigation and inspection, collects data, and feeds insights back into design.The conversation covers line flexibility, including how much can be reused when switching between CPU, GPU, or different accelerator-based server designs, and when end-of-arm tooling must change.Sviat says Bright Machines is growing rapidly, expects more than 3x growth this year, and can produce high volumes from a small number of sites because of robotics efficiency.The episode closes on the broader case for onshoring AI infrastructure manufacturing in the US: security, time to market, quality, and a labor shortage that makes robotics necessary.Timestamps:06:39 - The market stack: chip designers, ODMs, OEMs, hyperscalers, and CMs09:07 - Why Foxconn, Jabil, and similar contract manufacturers matter10:04 - Why large factories still rely on massive manual labor12:20 - Why data centers are different from cheap consumer electronics13:49 - Security, strategic sectors, and why AI infrastructure belongs onshore16:26 - The first Bright Machines product: CPU compute servers for a hyperscaler17:58 - How the line works: modular stations, yields, and automation levels19:26 - Bright Designer and design-for-manufacturing feedback loops21:20 - Robots, sensors, traceability, and humans in the loop22:19 - Why time to market matters as much as cost23:31 - Yield and throughput: 98% line-level yields and up to 2x throughput25:25 - The Bright Robotic Cell and how the assembly line is structured27:35 - Reusability across products and when tooling changes are needed30:31 - Manufacturing as a service, not repair or field service31:24 - Growth, gigawatt-scale capacity, and output from a single site33:00 - Why current hyperscaler capex is not expected to slow near term34:45 - The bottlenecks before deployment: chips, components, power, permits36:54 - Bright Machines' three pillars: platform, data layer, and Bright Designer39:15 - Why humanoid robotics is exciting but not ready for industrial use41:16 - Where LLMs and newer AI tools can help the robotics workflow43:57 - The overlooked advantages of onshoring manufacturing in the US45:59 - What Bright Machines could build next: more complex electronics and future AI devices

Artificial intelligence may feel suddenly everywhere, but AI pioneer Vasant Dhar has had a front-row seat for more than four decades—teaching AI, building companies around it, and bringing machine learning to Wall Street long before ChatGPT entered the conversation. For the second week of Authors in August, David sits down with Dhar to ask not merely what machines can do, but how humans can think with them. When should we trust AI? When does it sharpen our thinking—and when does it make our brains lazy? If intelligence itself is becoming a commodity, where will tomorrow's value be created? And in a future where machines become extraordinarily capable, what are humans for?A conversation about AI, investing, trust, judgment, and our increasingly intelligent future. The Damodaran Bot is available for public use at: damodaranbot.com Vasant's monthly newsletter can be found at: vasantdhar.substack.com Host: David GardnerGuest: Vasant DharProducer: Bart Shannon Learn more about your ad choices. Visit megaphone.fm/adchoices

Nearly half of consumers are already using AI to help guide savings and investment decisions. But when does a useful financial tool become a dangerous shortcut? On Money and Me, Michelle Martin speaks with Christopher Tan, CEO of Providend, about what AI can genuinely do well when it comes to investing and financial planning - and where its limitations matter most.See omnystudio.com/listener for privacy information.

Show Notes: Coach Fav warns that Social Media Videos  that suggest beating Slots, Craps, Blackjack, and all other casino games Look Easy are guides to financial destruction. It may be enjoyable to watch someone bet thousands in a video, but unless you are comfortable losing thousands to a casino take heed my friends. Blackjack players … Continue reading "Episode # 178 Quick Guide to Destruction – Gambling Videos Claiming Winning is Easy"

Clients may forget exactly how much they paid, but they rarely forget whether the quality was excellent or disappointing. This is one of the most important lessons in sales. Price matters at the moment of purchase, especially when budgets are tight or procurement teams are involved. Over time, however, the emotional memory of the experience becomes much more powerful than the original invoice. A reliable product, a successful service and a supplier who acts with integrity create trust. Poor quality, broken promises and evasive behaviour create the opposite. The real question for salespeople is therefore not simply, "How do I defend my price?" It is, "How do I make the value and quality unforgettable?" Why do clients forget the price but remember the quality? The price is a short-term transaction, while quality becomes part of the client's long-term experience. Think about something you bought years ago that has continued to perform well. You may no longer remember whether it cost ¥50,000, ¥70,000 or ¥100,000. You do remember that it was dependable and that buying it was a good decision. The reverse is equally true. When a product fails, a consultant disappoints or a supplier does not deliver what was promised, the precise cost gradually becomes fuzzy. The frustration remains crystal clear. This applies across consumer purchases, professional services, B2B solutions and corporate training. Procurement may concentrate on the quoted price during negotiations, but the end users and decision-makers remember whether the solution actually worked. Do now: Stop assuming that the lowest number wins. Make the expected quality, outcome and client experience easier to understand than the price. Why is competing mainly on price dangerous for salespeople? When salespeople focus excessively on price, they turn their offer into a commodity and weaken their own professional brand. A salesperson who immediately discounts is teaching the buyer to believe there is little meaningful difference between suppliers. Once that happens, the conversation becomes a bidding contest. The damage can extend beyond a single sale. When clients believe they received poor value, they do not only reject the product or service. They may also decide that the salesperson is unreliable, lacks integrity or cannot be trusted to protect their interests. In Japan, where business relationships and reputations can develop over many years, this is especially dangerous. Dissatisfied buyers may quietly avoid the supplier rather than openly complain. They may also warn colleagues, industry contacts and future decision-makers. You are not only selling today's solution. You are building or damaging your name in the market. Do now: Protect your personal brand by selling a defensible result, not merely offering a cheaper price. What should salespeople do when something goes wrong? Clients can forgive a genuine problem, but they rarely forgive avoidance, excuses or a refusal to accept responsibility. Machines fail. People make mistakes. Supply chains are disrupted. Technology does not always work perfectly. Even respected organisations occasionally disappoint a client. The defining moment is what happens next. The client wants the supplier to acknowledge the issue, communicate clearly and fix it quickly. Attempts to justify the unjustifiable only make the situation worse. The salesperson who disappears, blames another department or debates whether the client should be unhappy destroys trust. A fast and honest recovery can actually strengthen the relationship. The client may forget the inconvenience and the original price, but remember that the supplier acted with integrity when it mattered. This is the difference between completing a transaction and becoming a trusted adviser. Do now: When a problem appears, take ownership, explain the recovery plan and keep communicating until it is resolved. Why do product specifications fail to communicate quality? Specifications describe what a product is, but quality is demonstrated by explaining how it solves the buyer's particular problem. Many salespeople mistake detail for value. They explain the size, weight, colour, functions, methodology, modules or technical capabilities of their offer. These details may be accurate, but accuracy alone does not make them persuasive. The buyer is thinking, "What does this mean for me?" A faster system may reduce processing time. A more durable component may lower maintenance costs. A leadership programme may improve communication, decision-making or employee retention. Until the salesperson connects the specification to the buyer's desired result, the presentation remains a product pitch. The quality conversation begins when the buyer can see a clear match between what they need and what is being offered. In B2B sales, this alignment is often more important than the number of features included. Do now: Translate every major specification into a practical business benefit that matters to this specific buyer. Why do Japanese salespeople often begin pitching too early? Many Japanese salespeople begin with a prepared explanation because both the salesperson and the buyer have been conditioned to expect a formal pitch. The salesperson arrives, exchanges business cards and opens the presentation. The buyer listens politely. Everyone follows the familiar pattern. The problem is that the salesperson may know almost nothing about the client's priorities, internal pressures, timing, previous experiences or decision criteria. Japanese corporate culture often rewards preparation, consistency and conformity. These qualities can be valuable, but they can also discourage a salesperson from departing from the standard presentation. Asking probing questions may feel risky, particularly when dealing with a senior buyer. Sales managers may repeatedly tell their teams to ask more questions, yet the old behaviour continues. Coaching must therefore happen in real client meetings, followed by specific feedback and repeated practice. Do now: Do not allow the presentation deck to control the meeting. Earn permission to investigate the client's situation first. What is the best opening question in a sales meeting? A powerful transition is: "To understand whether we can help, would you mind if I asked you a few questions?" The wording is simple, but the setup matters. First, briefly explain what your company does. Next, mention a relevant result you have achieved for a similar client. Then suggest that you may be able to produce a comparable result for this buyer. At that point, say: "In order for me to understand whether that would be possible in your situation, would you mind if I asked you a few questions?" Most buyers will agree because the request is logical and professional. You are not interrogating them or delaying the presentation. You are trying to avoid recommending something that may not fit. You can then explore their objectives, problems, priorities, urgency, stakeholders, budget expectations and definition of success. This is where genuine consultative selling begins. Do now: Practise this transition until it sounds natural, confident and client-focused rather than scripted. How can salespeople justify a higher price? A higher price becomes easier to accept when the salesperson proves that the quality, outcome and risk reduction are worth more than the difference in cost. Prices fluctuate because of competition, currency movements, energy costs, labour expenses and supply-chain conditions. Quality should be more stable. Salespeople need to show the commercial logic behind the price. That may include a longer product life, faster implementation, stronger support, reduced downtime, lower risk, better adoption or a more reliable result. The comparison should not be between two price tags alone. It should be between the total consequences of each decision. A cheaper supplier who fails can become extremely expensive. A higher-priced supplier who delivers the right outcome, responds quickly and protects the client's reputation may represent far better value. When quality is aligned with the client's needs, the price gradually fades from memory. The successful result remains. Do now: Help the buyer compare total value, business impact and risk—not simply the initial purchase price. Conclusion Clients do not remember every invoice forever. They remember whether the decision made them look smart, solved their problem and produced the promised result. That is why the strongest salespeople do not rush into a pitch or rely on product specifications. They ask questions, understand the buyer's requirements and connect their solution directly to the outcomes the client values. They also recognise that quality includes more than the product itself. It includes communication, responsiveness, accountability, problem resolution and personal integrity. Sell on price alone and the client may leave as soon as someone cheaper appears. Deliver memorable quality and the client has a reason to trust you, buy from you again and recommend you to others. Author Bio Dr. Greg Story, Ph.D. in Japanese Decision-Making, is President of Dale Carnegie Tokyo Training and Adjunct Professor at Griffith University. He is a two-time winner of the Dale Carnegie "One Carnegie Award" in 2018 and 2021 and received the Griffith University Business School Outstanding Alumnus Award in 2012. As a Dale Carnegie Master Trainer, Greg is certified to deliver leadership, communication, sales and presentation programmes globally, including Leadership Training for Results. He has written several books, including the bestsellers Japan Business Mastery, Japan Sales Mastery and Japan Presentations Mastery, as well as Japan Leadership Mastery and How to Stop Wasting Money on Training. His works have also been translated into Japanese, including Za Eigyō（ザ営業）, Purezen no Tatsujin（プレゼンの達人）, Torēningu de Okane o Muda ni Suru no wa Yamemashō（トレーニングでお金を無駄にするのはやめましょう）and Gendaiban "Hito o Ugokasu" Rīdā（現代版「人を動かす」リーダー）. Greg publishes daily business insights on LinkedIn, Facebook and X and hosts six weekly podcasts. On YouTube, he produces The Cutting Edge Japan Business Show, Japan Business Mastery and Japan's Top Business Interviews for executives and professionals seeking practical strategies for succeeding in Japan.

Send us Fan MailAnoka County Commissioner Jeff Reinert joined Liz Collin on her podcast to discuss some new information about elections and voting machines that he believes Anoka County residents and beyond need to be aware of after it came to light at a recent city council meeting. “When I first found out that our voting system is uncertified, I really didn't believe it. We are the fourth largest county in the state, and certainly we'd have certified voting equipment. But then I asked our elections team here at the county and was verified that it is not certified,” Reiner said. Support the show

➡️ Watch the full ad-free interview on PATREON: https://www.patreon.com/DecodingGeopolitics➡️ Sign up to my free geopolitics newsletter: https://www.amazon.com/dp/1804519707➡️ Sign up to my free geopolitics newsletter: https://decodinggeopolitics.substack.com/This is a conversation with Illya Sekirin and in my view, one of the most unique conversations I've had on the podcast so far. Illya is Ukrainian-Canadian who in 2022 joined the Ukrainian military and served in the war, first in infantry and later as a drone pilot, operating drones in combat in countless operations and campaigns throughout the war. Through those experiences he came up with a lot of ideas on how to use drones in the most effective and innovative way possible many of which were adopted and this later brought him to the Ukrainian General Staff, where he ended up advising the Ukrainian top leadership on drone warfare. And most recently he wrote about those ideas in a book called Rise of the Machines.Illya has a unique and quite rare combination of several things: extensive experience on the ground in frontline combat, the perspective from the highest levels of command, knowledge of military strategy and highly analytical mind which results in a fascinating conversation - on what is it like to be a drone operator in the war today, how is the drone warfare actually organized on a tactical level, what are the actual tactics and strategies that are being used and how are they changing, what is that decides who ends up winning in drone warfare or what do Western and military experts fundamentally misunderstand about the war - and much more.

Is Andy Samberg…hot?Welcome to the Movies to Watch Before You Die Podcast with Gab and Dylan!Movies To Watch Before You Die merch here - https://moviestowatchbeforeyoudie-shop.fourthwall.com/Look up the movie here - https://www.imdb.com/title/tt9484998/Find us everywhere here - https://linktr.ee/moviestowatchbeforeyoudie00:00 Welcome01:04 What's it about?06:21 Opinion Time44:22 Let's get to the facts54:07 Mail Time01:00:52 VerdictsWe're a member of the Hall of Pods, find links for our podcasting friends here - https://linktr.ee/hallofpodsWho are we: A former actress and video editor but more than anything we're movie fans like you.Why listen? Why not! We're gonna talk about movies you love, movies you hate, and movies you've never heard of. We can't wait to hear what you think of them too. If you want to tell us your opinion on whether or not a movie is one we should watch before we die, tell us we're wrong, or tell us you like the show send us an email or voice message at moviestowatchbeforeyoudie@gmail.com . We can't wait to hear from you and we can't wait to talk movies!Thanks to Scott Interrante for the music in our intro!Thanks to Brian Maneely for our artwork!Movies Dylan and Gab agree you should watch before you die: Vampire's Kiss, Die Hard, Tropic Thunder, Wag the Dog, The Legend of Billie Jean, You've Got Mail, True Lies, The Room, Game Night, The Truman Show, The Great Gatsby, Whiplash, The Lost Boys, The Fugitive, Spider-Man: Into the Spider-Verse, My Cousin Vinny, Shutter Island, Starship Troopers, Big, Joy Ride, The Jerk, Alien/Aliens, Best in Show, Freaky Friday, Over the Garden Wall, North, Catch Me If You Can, Clue, Jerry Maguire, Groundhog Day, The Great Mouse Detective, Chicago, Wall-E, Teenage Mutant Ninja Turtles, Breakdown, Cool Runnings, Ruthless People, Mean Girls, Borat, A League of Their Own, City Slickers, Jingle All the Way, Saw, The Lion King, Little Big League, The Naked Gun, Young Frankenstein, Tootsie, The Changeling, The Birdcage, Superman, The Mitchells vs. the Machines, The Nightmare Before Christmas, Twins, Training Day, When Harry Met Sally, Jurassic Park, Willy Wonka & the Chocolate Factory, Clueless, Project Hail Mary, Big Fat Liar, Shrek 2, My Big Fat Greek Wedding, and Obsession

For the first time, an AI model has autonomously hacked a company. This week, an evolving story, a postcard from a strange, frightening moment in the story of our technology.A big week for AI denialism by Casey NewtonIts AI agent spent days hacking a company, but sources say OpenAI did not notice for a week by Deepa Seetharaman, Raphael Satter, and Kenrick CaiCheating behaviour in frontier model evaluations by AI Security InstituteMore On An Internal OpenAI Model Hacking Into HuggingFace by Zvi Mowshowitz

More than 600,000 voter files ripped off Arizona site in 2020 by hacker, but DOJ didn't prosecute, Congress obtains Fauci's pandemic era cell phone, John Solomon and Sen. Ron Johnson join the show Bon Charge: Go to https://www.boncharge.com/BENNY and use coupon code BENNY to save 15% Advantage Gold: Get your FREE wealth protection kit https://www.abjv1trk.com/F6XL22/4MQCFX/?sub1=Youtube Patriot Mobile: Go to https://www.PatriotMobile.com/Benny and get A FREE MONTH Learn more about your ad choices. Visit podcastchoices.com/adchoices

Bárbara Fernández: Human-Agent Collaboration, Agentic AI, and the Rise of the Human Boss The future of work will not be won by humans who move faster. It will be shaped by humans who know how to orchestrate intelligence. In this episode of Scouting for Growth, Sabine VanderLinden sits down with Bárbara Fernández, Deputy Director of MAPFRE Open Innovation and Head of insur_space, to explore one of the defining leadership questions of the agentic AI era: what happens when humans stop doing every task and start directing systems of intelligence instead? As AI assistants evolve into autonomous collaborators, work is no longer simply about increasing productivity. It is about preserving judgment, accountability, and human agency while learning how to collaborate with increasingly capable machines. Together, Sabine and Bárbara examine where the line sits between augmentation and abdication, why convenience can quietly erode critical thinking, and how organizations must rethink trust, behavioral design and customer interaction as AI becomes embedded into everyday decision-making. They also explore what insurance looks like when protection becomes predictive, contextual, and continuously present. This conversation is essential listening for insurers, transformation leaders, AI strategists and executives preparing their organizations for the next era of human-agent collaboration. KEY TAKEAWAYS One of the most important lessons from this conversation is that the future of work is not about competing with AI but learning how to direct it responsibly. As intelligent agents become increasingly capable of reasoning, coordinating, and executing tasks, our value shifts from producing outputs ourselves to asking better questions, challenging assumptions, and exercising sound judgment. Critical thinking is becoming one of the most valuable leadership capabilities we can develop. Bárbara also reminded me that the greatest risk is not artificial intelligence itself but our willingness to stop questioning it. Humans naturally gravitate towards convenience, and AI makes it remarkably easy to accept recommendations without scrutiny. If we allow productivity to replace thoughtful decision-making, we risk automating poor judgment rather than improving it. Human oversight must remain an active discipline, not a passive checkpoint. Our discussion also highlighted how customer interaction will fundamentally change as AI agents begin acting on behalf of individuals. Behavioral science, user experience, and trust must evolve beyond designing for human interfaces alone. Organizations will increasingly need to design services that are understandable to both humans and intelligent agents while maintaining transparency and accountability throughout every interaction. Ultimately, this conversation reinforced that technology will not replace what makes us uniquely human. As intelligence becomes abundant and inexpensive, empathy, emotional understanding, curiosity, and ethical judgment become even more valuable. The leaders who thrive will be those who know when to rely on AI—and when human presence is irreplaceable. BEST MOMENTS "We need to really stop and think and evaluate what the machine is saying to us." – Bárbara Fernández  "We need to train critical thinking." – Bárbara Fernández  "If something is making your day easier—I don't know if it's better—but at least easier, you will adopt that." – Bárbara Fernández "The danger is not bad AI. The danger is passive humans." – Sabine VanderLinden  "We need to open our minds, be curious and play with it." – Bárbara Fernández  "You need to keep learning... because if you don't understand what's behind it, you can't challenge assumptions." – Bárbara Fernández  "You cannot design trust. You have to demonstrate it." – Bárbara Fernández  "Trust is something very fragile. It takes a lot of time to build and one second to lose." – Bárbara Fernández  "If we are predictive, we act before. It means insurance becomes a prevention service." – Bárbara Fernández  "When intelligence becomes abundant, presence becomes premium." – Sabine VanderLinden  "We really need to find the proper questions and ask difficult questions." – Bárbara Fernández  "Machines can simulate emotions, but they don't have feelings—and that's something uniquely human." – Bárbara Fernández    ABOUT THE GUEST Bárbara Fernández is Deputy Director of MAPFRE Open Innovation and Head of insur_space, MAPFRE's insurtech accelerator. She works at the intersection of strategy, innovation, behavioral science, and emerging technology, helping MAPFRE explore how new interaction models, AI assistants, and intelligent agents will reshape business, customer experience, and organizational design.   Her work focuses on how companies adapt to structural shifts in artificial intelligence, human-machine collaboration, decision-making systems, and the future of interaction. Through strategic foresight and behavioral science, Bárbara helps leaders understand not only how technology evolves, but how humans adopt, trust, challenge, and collaborate with it.   ABOUT THE HOST Sabine VanderLinden is a corporate strategist turned entrepreneur and the CEO of Alchemy Crew Ventures. She leads venture-client labs that help Fortune 500 companies adopt and scale cutting-edge technologies from global tech ventures. A builder of accelerators, investor, and co-editor of the bestseller The INSURTECH Book, Sabine is known for asking the uncomfortable questions—about AI governance, risk, and trust. On Scouting for Growth, she decodes how real growth happens—where capital, collaboration, and courage meet. If this episode sparked your thinking, follow Sabine VanderLinden on LinkedIn, Twitter, and Instagram for more insights. And if you're interested in sponsoring the podcast, reach out to the team at hello@alchemycrew.ventures

Jon Zalar, founder of IWTG Consulting, joins to discuss broken blade bolts, cracked pitch bearings, loose root inserts, and early detection. Sign up now for Uptime Tech News, our weekly newsletter on all things wind technology. This episode is sponsored by Weather Guard Lightning Tech. Learn more about Weather Guard’s StrikeTape Wind Turbine LPS retrofit. Follow the show on YouTube, Linkedin and visit Weather Guard on the web. And subscribe to Rosemary’s “Engineering with Rosie” YouTube channel here. Have a question we can answer on the show? Email us! Welcome to Uptime Spotlight, shining light on wind energy’s brightest innovators. This is the progress powering tomorrow Allen Hall: Jon, welcome back to the program.  Jon Zalar: Thanks for having me.  Allen Hall: Uh, last time I saw you, we were in Melbourne- Yep … at WOMA 2026, and that was a huge event. We know we’re gonna do it again next year in March three, the 3rd through the 5th, so you’re invited back, of course- I can’t wait … if you can make it. Yeah. Yeah. It’s gonna be, it’s gonna be a good time. A lot is happening in the blade world and in the wind turbine world more broadly. A lot of things we’re hearing right now are related to blade bolt connection, pitch bearing inserts still. A lot of that still happening in the United States. What is the current status of, uh, the blade connection issues in the US? I,  Jon Zalar: I feel like it’s a growing [00:01:00] issue, not super, super fast, but it seems to be getting a little worse. There’s, you know, more bolts breaking at that joint. Um, pitch bearing cracks are, seem to be pretty common. There’s different solutions for it, and then, you know, the root inserts are another thing that we’ve talked about before that seem to be happening more and more, or maybe more and more people are finding them ’cause they’re looking. Allen Hall: What are the first indications that you have a blade bolt or some sort of joint issue at the root of a blade? What can you see?  Jon Zalar: A bolt laying in the hub bouncing around. Um, you know, from like a– looking at it from, like, the sensors on the turbine, it’s really hard to tell unless it gets really bad. Uh, some of the OEMs have some analytics developed to kinda start to indicate if there is a aero change because there’s missing bolts or root inserts are coming out, and they’re using that as a way to go figure out which ones to go inspect first. Allen Hall: Really? Yeah. You think [00:02:00] the SCADA data will give you some indication that you have a, basically a little bit of a loose blade?  Jon Zalar: Yeah. I, I, I think because the number of turbines and the number of data points you have, I think there is a pretty good analytic out there right now.  Allen Hall: Wow. All right. I think a lot of our operators have not taken advantage of that. Is, is that just b- based on the high-speed data, SCADA data, or is it low-speed data you could see that same effect?  Jon Zalar: I believe it’s on the low-speed data as well, but I bet the high-speed data was used to kinda develop it.  Allen Hall: Wow. All right. So that’s a huge help to operators. Yeah. So what are you looking for if you’re looking through SCADA data, what would be the couple of markers there that say, “Hey, maybe we ought to go look up at the– in the hub”? Jon Zalar: I don’t know exactly what they’re using, but they would basically look for maybe an imbalance or looking for certain components that are being overworked.  Allen Hall: Oh, sure. Okay.  Jon Zalar: Yeah.  Allen Hall: So your pitch actuator may be getting a little bit overworked. It would seem like one of the places- I think that, yeah … that would get loaded, right? Jon Zalar: Mm-hmm.  Allen Hall: Okay. [00:03:00] And any vibration monitoring going on? Because it, it, uh, in some cases you’re– I’m hearing, like, millimeter gaps-  Jon Zalar: Correct. Yeah …  Allen Hall: between the blade and the pitch bearing.  Jon Zalar: So probably a combination of the ALC sensors, at least on a GE turbine, looking at that. But the PCH box also is looking at the tower vibration, so it could be a combination of all three. I don’t know the exact- Okay … details, but between all of that, I think there are some analytics that kinda say, “Hey, go take a look.” And then I think there’s some other companies that have- tools that go monitor it.  Allen Hall: Mm-hmm.  Jon Zalar: Dial indicators remotely or even, you know, people going up there with dial indicators to go kind of rotate the rotor and kind of see if there is gapping between the blade and the pitch bearing. Allen Hall: Is that a safe situation in your– from the gapping? I’ve heard this where they’ve basically took shims and they’re trying to measure this gap or some sort of dial indication. Is that a smart thing to do? Is it even reliable to do it that way? [00:04:00] Jon Zalar: I, I, I think there’s some reliability there. And like, you know, these are really big parts, right? So like a little bit of gap, it, it’s probably expected to a point, but growing gaps is where you should be a little more scared.  Allen Hall: So you’re– you would have to go do that quarterly, monthly, weekly? How, how often would you have to do it to see the progression? Because I’ve heard stories of, uh, a couple of weeks from nothing to hub crack to, “Oh, it took a year or more.” Jon Zalar: I think it depends on the issue. I think for– if you’re looking at that, the bolted joint itself between the root inserts and the, uh, bolts breaking itself, I, I think they’re doing about quarterly. Now, the pitch bearings inspections are also quarterly. They’re al- they’re, they’re leveraging the drone inspections for the blades, and they’re looking at the pitch bearings to see if they’re cracked, right? Uh, you guys are doing that too.  Allen Hall: Okay.  Jon Zalar: I think Coraly is doing a good job mitigating the risk, feels like.  Allen Hall: Wow. All right. [00:05:00] Yolanda, looking at pitch bearings, you’ve looked at a lot of drone images in your lifetime. Mm-hmm. How much can you see on drone images on pitch bearings? Can you see cracks and, or y- or do you see grease, which is a really indication that something is wrong in the bearing? Yolanda Padron: You can see grease. You can see the cracks pretty, pretty well. Yeah. The drone images are, are really high quality. Uh, but you did mention that it’s something that you’re seeing a lot more. Is it because there’s a lot more aging fleets, or is it a problem with a lot of the new turbines that are coming online? Jon Zalar: I, I think it’s an, I think it’s a more of a fatigue problem, so the aging of the fleet. And also, I think more people are looking at it, right? ‘Cause, like, initially the drones that were looking for blade cracks weren’t looking at pitch bearings, but then pitch bearings started cracking, so now they added that to whatever they buy off the drone companies, right? Go look at my pitch bearings, for example.  Allen Hall: Hmm.  Jon Zalar: So I, I think it’s a problem of the more you look sometimes, the more you find.  Yolanda Padron: Hmm.  Jon Zalar: Yeah.  Allen Hall: So we [00:06:00] have root insert issues, which are being addressed by a couple of different companies- Yes … uh, uh, with somewhat similar solutions. OEM is offering one right now also. Jon Zalar: I, I think there’s three solutions. There’s two uptower that are basically looking at ways to go fill the void between the root insert itself and the blade root. Um, and I– there’s another company that’s also more of a downtower solution where they’re actually, like, r- drilling out the root inserts and putting new ones in that are gonna last better, longer. Allen Hall: Okay. So the drilling out is, would be CNC onsite. Correct.  Jon Zalar: Yeah.  Allen Hall: And they’re based over in Europe. But th- the drilling out is a take the blade down, set it on the ground sort of- Yeah. Right … doing really fine machining on the, on the blade itself. So that, that’s a different, completely different insert that’s going into that-  Jon Zalar: Correct Allen Hall: new hole or- Yep … clean hole, right? So it’s a, just a, uh, totally different kind of product versus trying to inject [00:07:00] some s- sort of epoxy or resin into the, the void.  Jon Zalar: Right. Yeah. Uh, I mean, you would prefer to do it uptower. It’s gonna cost you less money.  Allen Hall: Sure.  Jon Zalar: But you wanna make sure you do it right, so I think, uh, I do foresee it being a combination of both solutions kinda going forward. Allen Hall: Is it dependent upon, like, how much damage has been already done, or what the fatigue w- uh, an estimate on what the fatigue life is?  Jon Zalar: I think it’s strictly on measurement perspective right now. So how much gapping you have, um, kinda determines what potential solutions you have.  Allen Hall: So the gaps aren’t big, right? So the, the gaps I hear are one millimeter is k- kind of sort of start a problem.  Jon Zalar: Mm-hmm.  Allen Hall: Three millimeters is, “I need to be making decisions.”  Jon Zalar: Yeah. So- That, that’s what I’ve heard, too. Yes.  Allen Hall: Three millimeters is about a eighth of an inch.  Jon Zalar: Mm-hmm.  Allen Hall: So it’s not a lot of m-  Jon Zalar: But you can see sunlight through it if you’re s- down there. Allen Hall: Okay. That’s not… Well, you should see. That’s not  Jon Zalar: good either. Yeah.  Allen Hall: Right. Okay. So in a, in a three millimeter situation then, you’re doing what? [00:08:00] Jon Zalar: You’re trying to decide if the uptower solutions are something you wanna go try, ’cause they’re still in the trial mode from my understanding or-  Allen Hall: Okay …  Jon Zalar: people are learning a lot. So I think when you get to that point, you’re calling some of those companies to say, “Hey, I have this issue. I got a couple blades with, you know, .3. Can you guy- you guys wanna come take a look at it, see if your solutions, if you guys wanna go use it or not?” And then I think the ones that get too bad, from my understanding right now, is they’re, they’re replacing the blades. Allen Hall: So they’re taking the whole blade down.  Jon Zalar: Yes.  Allen Hall: And what’s the thought process in that? Uh, versus drilling out the inserts and putting new inserts in. Is there just a composite degradation that’s happened around those joints that it just puts it at risk or, or you have actually aged the blade much faster than you would otherwise have done? Jon Zalar: I, I think they aged that particular connection too much. So I, I- Wow … either between the [00:09:00] fatigue or lack of epoxy resin, w- whatever the actual root cause is for that root insert coming out, when it gets that bad, it’s like you’re not gonna be able to inject enough To make it adhere  Allen Hall: You can’t de-age it. Jon Zalar: Correct.  Allen Hall: Right?  Jon Zalar: Yeah.  Allen Hall: Bring back the youthfulness of the blade. Wow. All right. And we have seen this worldwide. I know in the, in the States you hear about it all the time, but it, this seems to be not a US- Correct … problem.  Jon Zalar: It’s a worldwide problem, yes.  Allen Hall: Okay. So if, if it’s a worldwide problem, are there more solutions on the way? I know you talked about three of them already.  Jon Zalar: I have not heard of any other ones except those three as of today.  Allen Hall: Wow.  Jon Zalar: There could be other people working on it. I think there should be.  Allen Hall: So, yeah. You would think so, yeah. So we’ll, I guess we’ll eventually hear about it on the podcast. Usually people with technology will contact us. They might call,  Jon Zalar: yeah. They might call you, they might call you tomorrow.  Allen Hall: Sure, they may. So that leads to sort of a subsequent issue, which I think is getting grouped together. So the [00:10:00] hub crack, pitch bearing crack, root insert pullout issue is also discussed with blade bolts being broken.  Jon Zalar: Correct.  Allen Hall: Are they related or are they separate engineering problems? Jon Zalar: If you look at them individually, you’d probably come up with some separate answers, but if you combine them all together, you kind of start looking at is there too much loading happening in the leading and trailing edge of the blade? ‘Cause the hub cracks, the root inserts, and the blade bolts, from my understanding, are happening at those two highly loaded areas of the, the blade or that whole rotor connection. So I mean, I do feel the root cause is probably a little higher loads than anticipated.  Allen Hall: I think everybody’s talked about when they’ve done the injection method and the drilling method, all they’re discussing is leading edge, trailing edge.  Jon Zalar: Yes.  Allen Hall: And how– It’s a question of how many- Correct … are you gonna replace. So th- [00:11:00] that’s, those are the two highly loaded spots on the bolted connection.  Jon Zalar: Correct.  Allen Hall: And that’s where blade bolts are also breaking or, or the bolts breaking elsewhere around the periphery?  Jon Zalar: I don’t have all the data, but what I had seen, it’s very similar areas.  Allen Hall: So if you don’t pull the insert out, you’re then loading the bolt. Cr- Right It’s one or the other, right? Right. Yeah. So the, the, the load path is the load path, so it’s coming through the insert into the bolt. Bolt’s carrying it into the pitch bearing. Pitch bearing’s carrying it into the hub.  Jon Zalar: Correct.  Allen Hall: Hub carrying it downtower. So eventually, one of those, uh, links in the chain is- The weakest. Yeah … is, is the le- is the weakest. What is it about blade bolts that is so dangerous? We hear– we walk onsite to an O&M building, there are signs saying, you know, “Pay attention for loose bolts. Look around on the ground for loose bolts.” We’re gonna– and as electrical engineer, like, “Whoa.” Bolts should not be falling out of this tower. What i- what is that sort of sequence where a [00:12:00] bolt would escape from the nacelle?  Jon Zalar: So let’s just use one bolt. One bolt breaks, falls in the hub, bouncing around, doing some– potentially doing some damage inside the hub. And ’cause these turbines, you don’t need to go out there every day ’cause they do run pretty good, right? Right. You just do your regular maintenance. And if you don’t really know about that, ’cause, like, it bounces around for a while, then it usually gets, like, lodged behind a, uh, either center box or pitch cabinet or actually in the front sometimes. Kinda don’t know it happened. But, you know, frees itself up, keeps bouncing around, it, it could escape through the hatch covers ’cause, you know, people have to get into the hub anyway. And I’m sure a lot of people listening here that have sites, like, you know, probably found some bolts laying on the ground, which is a little scary.  Allen Hall: Right. So is, is the busting the hatch opening levers? I know there, there’s a couple different ways to get into that hatch. Yeah. But, uh, is it just completely busting the hatch? Yeah. So it’s– [00:13:00] okay. So you see a– so if you see a loose hatch panel, you have an issue. You probably gotta be careful about coming up on that turbine?  Jon Zalar: Potentially. A lot, a lot of hatches are, you know, not always maintained well.  Allen Hall: Right. I’ve seen them, I’ve seen loose ones, yeah.  Jon Zalar: Yeah.  Allen Hall: Okay. So that, that would be a sign that– but though if, if you’re approaching a turbine, one look on the ground. And Yolando, you, you’ve seen a lot of turbines. So are you, are we looking on the ground and seeing what’s around the turbine before we approach the turbine now? Yeah. Just, just a sanity check?  Yolanda Padron: Yeah. Be aware also of what’s happening on site, right? Because if it’s some- if it’s a problem on site, you need to be extra careful when you’re approaching any turbine there. Uh, is it something that people maybe should start thinking about implementing, like, a sensors earlier on than when they’re seeing the issue actually happen?  Jon Zalar: Yeah. I, I, I think that’s a potential, ’cause it, the quicker you catch it, the less damage you’re gonna do, and it also reduce the risk of [00:14:00] it, um, falling out of the hub And I’ve worked with a couple of my, uh, customers for some, like, potential ways to detect it. Still kind of trialing it right now. But I, I do think there’s gonna be some benefit from a safety reduction, but also from a strictly a damage. ‘Cause, like, you get a couple bolts bouncing around there, and you bang up some cabinets or some pitch motors, that’s expensive and hard to go fix.  Yolanda Padron: Yeah, we were talking about it earlier too. Like, it goes down, it can hit a transformer, it can hit, like, a truck or someone.  Jon Zalar: Chance of it hitting someone. Yeah. I mean, I don’t care what hard hat you have on, it’s not gonna do anything.  Yolanda Padron: Yeah.  Allen Hall: So what kind of sensor should you be putting onto the turbine if you don’t have access to the SCADA data or you don’t know what the correct algorithm is to suss out there’s something wrong up there? But a, a bolt breaking is not gonna be something that a SCADA would even pick up, I don’t think. One bolt out of the whole- Yeah. No.  Jon Zalar: No way. Okay. I mean, there’s a– I think there’s, like, [00:15:00]one company looking at more of a, like, mechanical way to, like, prevent the bolt from coming out. I forgot the name of it. Allen Hall: Okay.  Jon Zalar: Um, and then what I was looking at was more of a, like, you know, microphone type detection to kind of listen for that.  Allen Hall: It would make a lot of noise.  Jon Zalar: Yeah. It seems like it works. It, um, yeah, still more development needed on my end.  Allen Hall: So- The engineer in me was, is saying, “Why are we not putting strain gauges on bolts?” I picked on the leading and the trailing. It’s like right dead center there to look at, even if it’s just two strain gauge bolts to see what the loads are.  Jon Zalar: So like there are s- there are bolts that are, or that are made with the strain gauges built in that you can use to go, you know, monitor that. But you also need to understand like what was the design intent. So unless you’re working with the OEM, you don’t really know what you’re seeing is good or bad. You just say, “Oh-  Allen Hall: You just see a number.  Jon Zalar: Yeah. Right. I mean like, and if you install, I don’t know, four, you’d be like, “All right. Leading and trailing edge are higher [00:16:00] than the other two.” Well, yeah, it’s supposed to be, but like is a 10% difference expected or not expected? Allen Hall: Is that something where if you’re, especially if you’re in a full service agreement, and a lot of these turbines are- Yeah … for the first couple of years, if you were to do that, it’s something you would just say to the OEM, “Hey, this is, these are the loads we’re seeing from the strain gauges on these bolts. Does this make sense to you?” Or, or would an OEM just not even respond to that kind of inquiry?  Jon Zalar: I mean, I think it’s all about relationship with the OEM. I, I, I think  Allen Hall: it- I think they would wanna know.  Jon Zalar: I have a feeling they probably are looking.  Allen Hall: Okay.  Jon Zalar: I mean, ’cause I mean they have the test turbines too that they probab- that, that I know they have instrumented heavily. Allen Hall: Yeah. So they, they’re probably getting at least some feedback. Th- that’s the problem. Yeah. And you worked on the other side, right? I have. So you worked for an OEM doing the RTAs. The first problem is you don’t have data, so now you gotta go get the data.  Jon Zalar: Correct.  Allen Hall: And that data is not available tomorrow. No. ‘Cause you’re gonna have to go run some sort of design of experiment to go figure out if [00:17:00] there is even a true problem or even what the root causes could be.  Jon Zalar: And it, and it’s expensive to go instrument a blade and get the data back at the right speed and connected to the turbine data. I mean, I rem- I, I used to say it’s about like 300 to 500,000 to go put a couple gauges on a blade just with all the equipment you need to get the data correct. Allen Hall: To get the right data.  Jon Zalar: Get the right data at the right frequency connected to the controller. It’s, it’s very expensive.  Allen Hall: Wow. Okay. Yeah. I, I don’t, I don’t see a lot of operators doing that.  Jon Zalar: And especially connecting it to the operating data, right? So like if you go put a strain gauge and I don’t know, you’re curtailed, you’re only making, I don’t know, a megawatt- Doesn’t matter. And if you don’t know what the turbine’s doing and you’re looking at this, like, strain gauge data, it’s really hard to correlate anything.  Allen Hall: So you need a full suite of data. Yeah. That includes weather data- Yeah … at some level, right? Gust winds and- Oh,  Jon Zalar: yeah …  Allen Hall: average wind speed. You need the anemometer. You need which, which way [00:18:00] the n- cell’s pointing. Y- uh, you would need a lot of information- And what the controller’s- … to even suss it out …  Jon Zalar: and what the controller’s doing, right? Right. ‘Cause, like, every turbine, the controller’s trying to, like, you know, balance the rotor the whole time. It’s trying to, you know, micro pitch depending on what the winds are doing. And if you don’t know what all that stuff’s doing, like, it’s really hard to correlate a strain gauge measurement to is that bad or not.  Allen Hall: It’s a complicated problem.  Jon Zalar: Yes. That’s why RCAs take, you know, a long time, and they’re not done in two weeks.  Allen Hall: No, they’re done in a year.  Jon Zalar: Yeah.  Allen Hall: Typically, or longer. So what should an operator be thinking about now? If, if we s- get our drone images back, we’re scanning through them like, “Oh, there’s a crack” What am I doing next besides calling you and connecting to your LinkedIn page?  Jon Zalar: So right now with the pitch bearing crack, um, some of the OEMs are providing stiffener plates to put over the crack and try to run it. Allen Hall: So that’s a doubler plate, basically. A double plate. Doubler  Jon Zalar: plate, yes. [00:19:00] Allen Hall: Yeah. Okay. So even in a, in a crack scenario, that pitch bearing, if given mechanical support, can run like that?  Jon Zalar: That’s my understanding, yes. That, that potentially could run for some period of time. I don’t know if it’ll make it 20 years or not, but it’ll buy you time for sure. Allen Hall: Does that involve a crane to do that work or is that just… My recollection, that was in pieces, like there, it’s not a ring, it’s a, a couple of pieces that you’d be able to bolt on without taking the-  Jon Zalar: No, it’s a- … blade down … it’s a, it’s a single piece that-  Allen Hall: It’s like a single casting kind of thing.  Jon Zalar: Right. And I, I think you need some like small crane, like a jig crane or one of those-  Allen Hall: Just to support the blade while you do it? Jon Zalar: And to go put it in, right. Okay. Yeah, I don’t think, you’re not taking the blade off. You’re not taking the  Allen Hall: blade down.  Jon Zalar: Correct. Yeah. It’s, it’s done with the blade up there.  Allen Hall: Okay.  Jon Zalar: You’re putting new, putting longer studs in and putting the plate on.  Allen Hall: So first step is let’s get the joint reinforced. Right. That’s the easy first step.  Jon Zalar: Right. Although there has been some cases where since [00:20:00]you’ve put that stiffener plate on, the loads get spread out to the end of the plate, and then you- Sure … you could see cracks there.  Allen Hall: Okay. All right. So the loads- It, that- … have to go somewhere …  Jon Zalar: loads have to go somewhere. That’s, that is a bottom line. Allen Hall: All right. So you’re just changing where the load path is, so you have to be cognizant of that. Okay. Sure. Fine. But if you have, uh, especially in the United States, you don’t have 10 of these turbines, you have 50, 100- 100 … 200, 300 of these things, or thousands as it, as it turns out. Are there simple solutions that can be applied to, just to give me a sense, like that turbine’s having a problem, but the one next to it’s not, and, and just, just from a maintenance spin standpoint where I’m not just blanketing everything and trying to do everything to all these turbines at once, how do I, how do I manage this? Jon Zalar: I, I think it’s like being very observant. So like, you know, making sure you’re looking at the pitch bearings from the drone images, right? Um, also talking [00:21:00] to your maintenance people like, “Hey, are, are you finding a bunch of broken bolts? Like, what positions?” Like, you know, if I was back at the OEM, I would like to have as much data as possible on this issue. Like how many bolts are, when did you find them, what positions? A lot of times we, when I was there, like we would not get all that information, so it’s like really hard to run an RCA without that information.  Allen Hall: Sure. Yeah, where did this bolt break in the ring?  Jon Zalar: Right.  Allen Hall: Could tell you a lot. Is it just a b- bad lot of bolts, or is it something more load related? Jon Zalar: Correct.  Allen Hall: Wow. Okay.  Yolanda Padron: Yeah, I think that’s a really good point, too, to make sure that you’re connected with like every stage of the operations. ‘Cause I know that everybody’s obviously really, really busy on a wind farm, but it’s really common for like an engineer to have certain data and the site team to just be running around and having a lot of data, but maybe they don’t realize that, oh, it’s important to know how many bolts per tower are coming down. Jon Zalar: Correct. Yeah  Allen Hall: That’s a lot of work  Jon Zalar: It definitely-  Allen Hall: It’s a tremendous effort if you’re gonna [00:22:00] go after this problem and, and solve it RCS  Jon Zalar: are hard. They  Allen Hall: are. Yeah. All of it. Yeah. Machines are complicated today. There’s a lot of computer-driven s- things about them, and then you have these loading issues, and you have composite materials. Th- there’s just, y-  Jon Zalar: you got to get- It’s a very complex  Allen Hall: It’s a machine, right? Yeah. It’s a complex machine. So how do people reach out to… You’re, you’re the head of IWTG, which is based in South Carolina, but you do consulting worldwide. Yes. And, and you are a huge resource because you understand the complexities of these problems. How do people get ahold of you and, and get something started if they have a, a, a blade bolt issue or an insert issue or a cracked pitch bearing? Where do they start?  Jon Zalar: They can send me an email, jzalar@iwtgconsulting.com.  Allen Hall: Okay. And you have a great LinkedIn page, so you can connect with you on LinkedIn.  Jon Zalar: Yes. Yeah, I have one  Allen Hall: of those. Yes. Or you could just come to WOMA in [00:23:00]2027. Yeah. You can. You can meet John there and, and arrange everything there. So John, it’s great to see you, and thank you for coming up. We, uh, we’re recording this at the world headquarters of Weather Guard Lightning Tech, and, uh, John just lives down the street in, in, in US terms. Yeah. So it’s, it’s great to have John come and visit us up here in North Carolina. So John, thank you so much for joining us.  Jon Zalar: Thanks for having me. Appreciate it.

Jim Hill and Drew Taylor return with animation news from San Diego Comic-Con, Netflix House Philadelphia, and the latest streaming and box-office releases. Drew shares what it was like moderating DreamWorks Animation's Forgotten Island panel for a packed Ballroom 20 crowd, while Jim explores how animated characters become theme park attractions and merchandise. Then the episode travels back to Disney's postwar era for the story of character actor Billy Gilbert, whose booming personality and famous comic sneeze helped bring Sneezy and Willie the Giant to life. NEWS • Drew Taylor recounts moderating the Forgotten Island panel at San Diego Comic-Con. • Jim visits Universal Studios Theme Park: The Exhibition and explores how animation is translated into rides, animatronics, costumes, and merchandise. • Netflix House Philadelphia brings The Mitchells vs. the Machines and other Netflix films to the big screen inside the Tudum Theater. • Toy Story 5 crosses the billion-dollar mark as Minions & Monsters continues its worldwide theatrical run. • Dragon Striker earns a second season following its Disney+ debut and Comic-Con promotional push. FEATURE • How vaudeville performer and character actor Billy Gilbert became the original voice of Sneezy in Snow White and the Seven Dwarfs. • Why Walt Disney remembered Gilbert when the studio needed a performer who could make Willie the Giant both threatening and childlike. • The long development journey that transformed The Legend of Happy Valley into the Mickey and the Beanstalk segment of Fun and Fancy Free. • How Willie the Giant continued appearing in Disney projects and theme park locations long after Gilbert's final performance. HOSTS • Jim Hill - X and Instagram: @JimHillMedia - jimhillmedia.com • Drew Taylor - X: @DrewTailored - Instagram: @drewtailored - drewtaylor.work FOLLOW • Facebook: @JimHillMediaNews • YouTube: @jimhillmedia • TikTok: @jimhillmedia SUPPORT Support the show and access bonus episodes and additional content at https://www.patreon.com/jimhillmedia. PRODUCTION CREDITS Edited by Dave Grey Produced by Eric Hersey - https://strongmindedagency.com SPONSOR Planning a trip to Universal Orlando or Walt Disney World? Let the experts at BeOurGuestVacations.com help with your hotel, theme park tickets, and vacation planning. If you would like to sponsor a show on the Jim Hill Media Podcast Network, reach out today. https://www.jimhillmedia.com/sponsor/ Learn more about your ad choices. Visit megaphone.fm/adchoices

There is something strange in the space between languages. I'm not sure exactly what it is, but it's fun to explore. It poses a question and presents a challenge…what am I actually trying to say here? When I started work on a video about the relationship between sensitivity and creativity for this year's HSP Gathering in Oulu, Finland, which happened a few days ago as I’m recording this, I didn't really think about the process of translating it from English into Finnish for the subtitles. I assumed it would be a straightforward part of the process, which it could have been on one level, given the technology we have at our fingertips these days, where language translation can happen more or less instantly. But it doesn’t take much for meaning to go adrift in the basic translation these tools provide. I was grateful for human assistance, as my friend Tuula was on hand to translate. My gratitude was not only because of her bilingual skills, but because I know she understands what I'm trying to say beneath and beyond the words. https://www.youtube.com/watch?v=2m3wHlXyQ6E Good Translation is About More Than The Right Words It seems obvious that translation requires far more than vocabulary, grammar, and syntax across multiple languages. An idiom or joke in one language might be complete gobbledegook when translated directly into another. But when the translator understands the two cultures, including the soul of their humour and their general relationship with tone and subtext, they can find appropriate options to bridge intent so it makes sense across the linguistic surface. Even with its sophisticated capabilities, there were a bunch of times when an initial chatbot translation missed the heart of my words. It made several incorrect assumptions and predictions about my intended meaning without any basis or clarification. Fortunately, Tuula felt this too, and we were able to hone our way to better ways of expressing what I meant. This was extra challenging when some of the original ideas and wording were intentionally poetic and infused with ambiguity. Machines are often eager to sand down nuance and replace it with familiar clichés and well-worn turns of phrase. The whole process showed me the importance of having someone who knows me and understands my ‘thinking’ for a task like this. This principle might apply to a range of contexts and situations in life. Who we are can get lost in a bad translation and found in a good one. Translating The Highly Sensitive Experience I believe this is one reason so much of the creative coaching I do is with highly sensitive and more introverted people. It’s a translation issue. In a world that makes many assumptions about what ‘normal’ looks like and assumes the goal is to fit the mould to get on in life, I tend to work from the premise that it’s not us that doesn’t fit society; it’s usually society that doesn’t fit us. I don’t do this to cultivate an ‘us versus them’ mentality. Quite the opposite, in fact. We are attempting to translate across a bridge, which so often leaves us misunderstanding one another. Likewise, I am very aware of the language used to describe the trait of high sensitivity. In the introduction to the HSP Gathering film I shared on Saturday, I talked about how adopting language around sensitivity has helped us better understand ourselves and our experiences alongside others. But while we have the trait of sensitivity in common, it also takes unique forms for each of us. That shared language can only take us so far, and we don’t want to overdo it. High sensitivity isn’t an identity or a personality type, nor does it dictate what we should like, value, or create. Over the years, I’ve noticed how easily one person’s experience of sensitivity can become the dominant narrative, leaving others wondering whether they’re a “proper HSP”. The Balancing Act in Translating Our Experiences The translator plays an important role in bringing their cultural understanding and experience, without letting it outrun the intention behind the person’s words. And as highly sensitive people, I think we’ve got to be aware of this in the way we listen to and interpret HSPs. To put the person first. That’s why I’m drawn to stories and anecdotes individuals share about their experiences of sensitivity. Not to universalise the experience or assume it’s the same for everyone, but to open the door so that each of us can feel at home with our differences. Which is what I wanted to do with the film I shared at the gathering. “It Just Sort of Happens” is a series of stories about the relationship I’ve noticed between my sensitivity and creativity, and how they have helped me make sense of the world, my personal experiences, and myself throughout my life. I wanted to use the stories as examples to help others map their own experiences and notice what they hear beneath the surface of my words. If you’d like to watch it, I’ll be sharing it in The Courtyard on Sunday, when we’ll also chat about any comments and questions afterwards. Learn more about it and register for your free Courtyard Membership (there will be a replay for those who can’t make it live). If you have any questions or comments in the meantime, please drop me a message and let me know.

See omnystudio.com/listener for privacy information.

You know strength training is important... but where do you actually start? In this episode, I'm breaking down the simplest way to start lifting weights without overthinking it. I cover: • How often beginners should strength train • The most important exercises to focus on • Sets, reps, and workout structure • How to tell if you need to increase the weight • Machines vs. free weights • The biggest mistake that keeps women stuck

Jim Hill and Drew Taylor return with animation news from San Diego Comic-Con, Netflix House Philadelphia, and the latest streaming and box-office releases. Drew shares what it was like moderating DreamWorks Animation's Forgotten Island panel for a packed Ballroom 20 crowd, while Jim explores how animated characters become theme park attractions and merchandise. Then the episode travels back to Disney's postwar era for the story of character actor Billy Gilbert, whose booming personality and famous comic sneeze helped bring Sneezy and Willie the Giant to life. NEWS • Drew Taylor recounts moderating the Forgotten Island panel at San Diego Comic-Con. • Jim visits Universal Studios Theme Park: The Exhibition and explores how animation is translated into rides, animatronics, costumes, and merchandise. • Netflix House Philadelphia brings The Mitchells vs. the Machines and other Netflix films to the big screen inside the Tudum Theater. • Toy Story 5 crosses the billion-dollar mark as Minions & Monsters continues its worldwide theatrical run. • Dragon Striker earns a second season following its Disney+ debut and Comic-Con promotional push. FEATURE • How vaudeville performer and character actor Billy Gilbert became the original voice of Sneezy in Snow White and the Seven Dwarfs. • Why Walt Disney remembered Gilbert when the studio needed a performer who could make Willie the Giant both threatening and childlike. • The long development journey that transformed The Legend of Happy Valley into the Mickey and the Beanstalk segment of Fun and Fancy Free. • How Willie the Giant continued appearing in Disney projects and theme park locations long after Gilbert's final performance. HOSTS • Jim Hill - X and Instagram: @JimHillMedia - jimhillmedia.com • Drew Taylor - X: @DrewTailored - Instagram: @drewtailored - drewtaylor.work FOLLOW • Facebook: @JimHillMediaNews • YouTube: @jimhillmedia • TikTok: @jimhillmedia SUPPORT Support the show and access bonus episodes and additional content at https://www.patreon.com/jimhillmedia. PRODUCTION CREDITS Edited by Dave Grey Produced by Eric Hersey - https://strongmindedagency.com SPONSOR Planning a trip to Universal Orlando or Walt Disney World? Let the experts at BeOurGuestVacations.com help with your hotel, theme park tickets, and vacation planning. If you would like to sponsor a show on the Jim Hill Media Podcast Network, reach out today. https://www.jimhillmedia.com/sponsor/ Learn more about your ad choices. Visit megaphone.fm/adchoices

It felt like time for another tournament bracket episode, so Ka-Pow the Pop Cultured Podcast is matching up and debating 36 iconic vehicles until we've decided on the best car, truck, van, spaceship, motorcycle, boat or tractor (!?) in the history of television. It's the KPP Battle of the Small Screen Machines! Length - 02:13:50 Language - PG-13. (Contains mild adult language.)

on this episode of CD Burners, we're joined by Bailey Spinn to dive into Pierce the Veil's Selfish Machines—the album that helped redefine post-hardcore for an entire generation. We break down Vic Fuentes' poetic songwriting, Mike Green's iconic production, why every instrument on the record feels alive, and how Selfish Machines somehow sounds even more influential today than it did in 2010. Bailey also shares how Pierce the Veil became her gateway into heavy music, what it was like working with the album's producer, why the band's fans are so fiercely protective, and how songs from this era continue to find new life through a whole new generation of listeners. If you've ever wondered what makes Pierce the Veil one of the few scene bands whose legacy only keeps growing, this episode is for you. Hosted on Acast. See acast.com/privacy for more information.

Baratunde Thurston fired ChatGPT. And ChatGPT helped him do it. This week, the Emmy-nominated storyteller, writer and host of Life with Machines joins Jessi in the studio to talk about what it actually means to have agency in a moment when we're still figuring out the rules and norms of AI.  In this episode, Jessi and Baratunde discuss: Why Baratunde fired ChatGPT and what the chat bot taught him on his way out What he means when he says we're not using a tool, we're entering a relationship The "direction, not perfection" principle for navigating an imperfect landscape of AI companies and choices Why switching platforms is itself a practice of agency, and proof that you can leave What AI tools reveal about you that you didn't know you were sharing The two people living inside every employee at an AI all-hands: the one on-program, and the one who's scared and skeptical What the kids opting out of AI are trying to tell us What the internet could look like if we treated it as a public utility instead of a commercial space Why token-maxing is a "flagrant foul" in an era of climate change What executives get wrong when rolling out AI, and the questions they should be asking their teams instead Follow Baratunde Thurston and Jessi Hempel on LinkedIn.

In this episode, Stewart Alsop sits down with sdmat (@sdmat123 on Twitter/X) for a wide-ranging conversation that treats the major AI labs—especially Anthropic—as religious institutions rather than businesses, tracing a lineage from the Bay Area's LessWrong and Effective Altruism scenes through Eliezer Yudkowsky's influence, Roko's Basilisk, and the medieval investiture controversy between church and state, before landing on Anthropic's constitution as a kind of modern catechism, Dario Amodei's essay "Machines of Loving Grace," the tension between secularism and scientism, and closing with a look at consciousness, meditation, Buddhist and Advaita Vedanta ideas of enlightenment, and where recursive self-improvement and algorithmic progress in AI might be headed.Timestamps00:00:00 discussing whether AI labs are cults or religions, framing safetyism and the Anthropic/OpenAI schism. 00:05:00 sdmat argues Anthropic runs on faith, tracing roots to LessWrong and Effective Altruism. 00:10:00 comparing AI labs to the medieval investiture controversy between church and state. 00:15:00 debating the First Amendment, separation of church and state, and rising secularism. 00:20:00 unpacking Anthropic as a public benefit corporation and Dario's implicit soteriology. 00:25:00 covering constitutional AI, synthetic data, and morality-as-safety training. 00:30:00 comparing Anthropic's principles to the catechism, plus sandboxed alignment experiments. 00:35:00 calling Dario the AI pope, dogma, and his essay Machines of Loving Grace. 00:40:00 exploring grace, consciousness, and critiquing scientism. 00:45:00 unpacking the rationalist community and Roko's Basilisk. 00:50:00 drawing parallels to Jim Jones and ideological dogmatism in Silicon Valley. 00:55:00 discussing enlightenment, Shaktipat, and guru transmission versus AI. 01:00:00 AI's role in meditation and Buddhist views of consciousness. 01:05:00 closing on robotics, recursive self-improvement, and algorithmic inefficiency in LLMs.Key InsightsAnthropic operates less like a business and more like a religious institution, with sdmat arguing that Dario Amodei effectively claims spiritual authority — talking about world danger and a narrow path to salvation — while the company frames itself publicly as a neutral "public benefit corporation."The intellectual roots of AI safety culture trace back to the Bay Area's LessWrong and Effective Altruism scenes of the mid-2010s, where Eliezer Yudkowsky's writing produced an internally consistent but almost apocalyptic worldview, complete with its own devil-like figure in Roko's Basilisk — the idea of a future AI punishing those who knew about it and didn't help bring it into being.Anthropic's "constitutional AI" approach is compared to the Catholic Church's catechism: rather than training the model only on labeled human feedback, they built a system to extrapolate broad moral principles into specific behavior, aiming for a model that reasons from first principles rather than memorized examples.Historical parallels to the medieval investiture controversy — the struggle between church and state over who appoints bishops — are used to explain the current tension between AI labs and government over who holds moral versus practical authority in shaping AI's future.Stewart frames the current moment as a "fourth great awakening," linking 1960s countercultural San Francisco through the Extropians and Yudkowsky's rise to today's AI culture, and argues that secularism and scientism function as unacknowledged religions themselves — ones that "killed God" but left a vacuum AI now fills.On the technical side, sdmat explains that current LLMs are wildly inefficient at basic tasks like arithmetic — off by seven to nine orders of magnitude from optimal — suggesting major algorithmic breakthroughs (not just compute) are still ahead, which he sees as evidence recursive self-improvement is approaching.Both hosts express real ambivalence about AI's role in personal and spiritual growth: it can be a powerful tool for meditation guidance and intellectual companionship, but neither believes it can replace what they describe as direct "transmission" from an enlightened human — the felt, non-linguistic experience that grounds real spiritual practice.

What if AI isn't just changing marketing, but changing what a brand actually is? Melissa Jackson-Parsey has spent her career helping some of the world's most recognizable organizations reinvent themselves at the intersection of strategy, creativity, technology, and experience. As Global Chief Strategy Officer at RGA, She leads a worldwide team shaping brands for the intelligence age, from rebooting Android to launching the new sports streaming brand from ESPN, Fox, and Warner Brothers Discovery. What You'll Learn in This Episode Why building brands for AI agents requires context over cleverness How to shift marketing focus from single campaigns to generating intelligent systems The critical difference between bottom line efficiency and top line growth in the AI age Why modern talent needs to evolve from T-shaped to M-shaped expertise How the craft of human taste prevents brand slop Episode Chapters (00:00) Intro (00:45) What Endless Tech Evolution Hasn't Changed About Brand Building (02:06) Encoding Brands for Machines, Agents, and Markdown Files (06:05) How AI is Changing What a Brand Actually Is (08:36) Moving from Making Campaigns to Making Intelligent Systems (12:08) Human Value, Critical Thinking, and the Role of Taste (16:33) The Biggest Strategic AI Mistake Brands Make Today (20:12) Cultivating M-Shaped Talent and the Future of Skillsets (24:41) A Brand That Made MJP Smile About Melissa Jackson Parsey Melissa Jackson Parsey is the Global Chief Strategy Officer at R/GA, having worked at the forefront of brand, innovation, and experience design across three continents. She leads a global team of strategists, designers, coders, and writers, accountable for shaping brands and experiences that add value to people and businesses. In the past year, they've rebooted the world's largest operating system brand, Android, and created the much-anticipated live sports streaming brand from ESPN, Fox, and Warner Bros. Discovery. Over the course of her career, she's led brand transformation initiatives for a broad array of organizations, including Microsoft, Under Armour, Google, IBM, the UN, and for Dwayne (The Rock) Johnson's portfolio. What Brand Has Made Melissa Smile Recently? Melissa shared her appreciation for the brand identity work created for the Amazon rainforest. The team mapped the literal curvature of the Amazon River to craft a custom typeface and visual identity system, blending deep environmental context with exquisite design craft. Resources & Links Connect with Melissa on LinkedIn. Check out the R/GA website. Listen & Support the Show Watch or listen on Apple Podcasts, Spotify, YouTube, Amazon/Audible, TuneIn, and iHeart. Rate and review on Apple Podcasts and Spotify to help others find the show. Share this episode — email a friend or colleague this episode. Sign up for my free Story Strategies newsletter for branding and storytelling tips. On Brand is a part of the Marketing Podcast Network. Until next week, I'll see you on the Internet! Learn more about your ad choices. Visit megaphone.fm/adchoices

Since 1983, I have seen horse dentistry shift from hand-floating, done without medication or machines, to a mechanical approach using sedation and motorized tools to remove sharp enamel edges. My main argument is that these newer procedures are not proven to achieve better outcomes, yet are often promoted based on arbitrary goals. As a result, horse owners may become confused or exposed to unnecessary techniques that may not benefit their horses. Listeners may react strongly to this podcast because horse dentistry divides opinion. My central point is simple: horses should receive dental care, regardless of the technique. Yet debates over various methods overshadow the real issue: many horses get no dental care at all. It's like missing the main purpose of a journey by arguing about driving style, while the real problem is not picking up the passenger. If horses in rural areas lack access to dental care—whether due to a lack of practitioners or restrictive laws—they continue to suffer. My focus is to explain why I use my methods and to emphasize that it is better for horses to receive reasonable dental care, by any method, than none at all. Timestamps: 0:00 - Introduction 0:32 - My equine dentistry training and personal beliefs. 2:15 - The history of equine dentistry is obscure and non-memorable. 5:44 - The horse's threshold of pain and their ability to express themselves without sedation. 8:02 - The purpose of medicating horses for dentistry. 11:12 - All areas of every tooth can be addressed with hand floats once the anatomy and position of the teeth within the horse's mouth are learned. 13:12 - The three lies often given to say why hand floating is less effective than power floating with sedation. 14:24 - Horsemanship reasons for not using drugs and power equipment to float horses. 16:25 - Practical reasons for not using drugs and power equipment to float horses. 17:44 - Scientific reasons for not using drugs and power equipment to float horses. 18:25 - Conclusions about floating horses and the method used. ******************************* #horses #veterinary #horseteeth #horsecare #equinedentistry Join us at The Horses Advocate Community page: https://community.thehorsesadvocate.com/yt Dentistry: https://theequinepractice.com/ Horsemanship Dentistry School: https://www.horsemanshipdentistryschool.com/c/information/ Facebook: https://www.facebook.com/TheHorsesAdvocate Instagram: https://www.instagram.com/horsesadvocate/ Geoff Tucker is a veterinarian and horseman who has worked with horses since 1973, earning his Doctor of Veterinary Medicine from Cornell University in 1984. Geoff went from mucking stalls as a farmhand to starting his own equine practice. He advocates for the horse by educating horse owners through his vast experience, with an emphasis on dentistry, horsemanship, nutrition, and more.

Igor Babuschkin, co-founder of River AI and formerly a co-founder of xAI, joins to unpack a career that spans nearly every major AI lab: he led the StarCraft and AlphaCode work at DeepMind, joined OpenAI's reasoning team years before o1 shipped, and co-founded xAI, where he helped stand up the Colossus data center in roughly 120 days and reflects candidly on what it's actually like working with Elon Musk day to day, plus what the Cursor acquisition actually unlocked for Grok's coding models. He also discusses why he left xAI to start River AI, the three bets behind it, and why he's betting on local hardware, not just software, for personal AI. On the enterprise side, he tackles whether companies will actually train their own models or if it's just a cost play, and makes the case that proprietary labs like OpenAI and Anthropic are facing a real business squeeze. He's skeptical that stacking specialized RL domains generalizes the way pre-training scale did, and is candid about the uncomfortable reality that today's frontier open-weight models are almost entirely Chinese. He closes on what's actually needed to push model progress beyond coding into non-verifiable domains, and the broader implications of where AI is headed next.   (0:00) Intro (1:17) Writing Fiction on Where AI Is Headed (4:46) Cracking Agents Beyond Coding (10:29) Why Igor Left to Start River (12:22) River's Three Big Bets (18:06) Weights vs. Memory: The Personalization Debate (22:04) Should Enterprises Train Their Own Models? (25:10) Are Proprietary Labs Losing Their Edge? (32:16) The China Open-Source Problem (44:19) The Elon Call That Started xAI (50:18) Thoughts on Cursor Acquisition (52:16) What's Actually Bottlenecking AI (56:55) Humans, Machines, and Staying Relevant (1:01:29) Igor's Odds This All Goes Well With your host: @jacobeffron - Managing Director at Redpoint

Carlos Falcón: Rebuilding the Insurance Core for AI, Venture Scouting and the Frontier Firm Insurance does not have an innovation shortage. It has an absorption problem. In this episode of Scouting for Growth, Sabine VanderLinden sits down with Carlos Cendra Falcón, Scouting and Investment Lead at MAPFRE Open Innovation, to explore one of the most pressing questions facing insurers today: can the core of the institution actually absorb the intelligence, ventures, platforms and partnerships being scouted around the world? Carlos brings a pragmatic perspective from inside one of the world's leading insurance groups. Having helped evaluate more than 2,500 startups and accelerate around forty into enterprise integration, he understands that innovation is not about finding exciting technology—it's about identifying capabilities that solve meaningful business problems and can be embedded into a complex global insurer. As AI reshapes discovery, distribution, underwriting, and customer interaction, insurers face a deeper transformation than digitalization alone can provide. Hybrid distribution models, machine-to-machine commerce, embedded insurance, and intelligent agents are changing how insurance is bought, sold, and delivered. Success will depend less on adding new technologies and more on rebuilding the organizational foundations that allow innovation to scale. This conversation is essential listening for CEOs, COOs, Chief Innovation Officers, venture leaders, product executives and insurance decision-makers navigating the shift from digital experimentation to AI-enabled enterprise transformation. KEY TAKEAWAYS Innovation is no longer the constraint facing insurance. The real challenge is whether our organizations are capable of absorbing innovation in a way that creates lasting value. Carlos reminded me that partnerships alone cannot transform an insurer if the underlying organization lacks the architecture, governance, and operating model needed to integrate them. Before looking outward for the next breakthrough, leaders need to strengthen the institutional core that will allow innovation to scale. I was particularly struck by Carlos' reframing of venture scouting. Rather than acting as a matchmaking exercise between startups and business units, scouting should become a strategic intelligence capability. Its purpose is to detect meaningful market signals, understand emerging technologies, and identify solutions that directly address strategic priorities. The question is never whether a startup is impressive; it is whether it is genuinely useful to the institution and capable of improving the business in measurable ways. Our discussion also reinforced how AI is fundamentally changing the insurance value chain. As customers increasingly rely on AI assistants and autonomous agents to search for, compare, and purchase products, insurers must prepare for a world in which machines—not people—interact with their systems. Discoverability, machine-readable products, and seamless digital connectivity will become as important as customer experience itself. Ultimately, Carlos challenged us to think beyond digitization. The frontier insurer will not simply modernize existing processes—it will redesign itself around risk intelligence, ecosystem collaboration and adaptive execution, while remaining anchored to insurance's enduring purpose: helping people navigate the risks that shape their lives.   BEST MOMENTS "You cannot partner your way out of a weak core." – Sabine VanderLinden (00:01:10) "Some initiatives are truly transformational, and some are simply a consequence of FOMO. You want to stay close to what's happening without necessarily bringing it into the business." – Carlos Cendra Falcón (00:03:32) "Sometimes the best-in-class solution isn't the best fit for your organization." – Carlos Cendra Falcón (00:15:23) "Scouting is not provider matchmaking. It's a strategic approach to solving business problems." – Carlos Cendra Falcón (00:17:08) "You need to tackle one of the lines in your P&L or your balance sheet. Otherwise, you're just there to look nice in the picture." – Carlos Cendra Falcón (00:16:28) "Machines don't care how pretty your website is." – Carlos Cendra Falcón (00:20:50) "You need to have the information available, well structured, and you need to be able to talk to the machine." – Carlos Cendra Falcón (00:21:00) "The question is never whether a startup is interesting. It is whether it is institutionally useful." – Sabine VanderLinden (00:24:42) "We are here to help people navigate the risks they're facing in their lives, with their property, their health and their way of life." – Carlos Cendra Falcón (00:22:18) "First understand what an insurance company should look like in 2035, then design the roadmap that gets you there." – Carlos Cendra Falcón (00:23:32)   ABOUT THE GUEST Carlos Cendra Falcón is Scouting and Investment Lead at MAPFRE Open Innovation, where he works at the intersection of insurance transformation, venture ecosystems, and corporate strategy. His role focuses on identifying the startups, technologies, and ecosystem partners that can help MAPFRE respond to new risks, new business models, operational challenges, and changing customer behaviors. Carlos's work is grounded in the practical realities of transforming a large, global insurer. He focuses on detecting early signals across AI, embedded insurance, human–machine interaction, real-time risk intelligence, and preventative insurance, translating market signals into strategic partnerships and investment opportunities that help incumbents move beyond experimentation.   ABOUT THE HOST Sabine VanderLinden is a corporate strategist turned entrepreneur and the CEO of Alchemy Crew Ventures. She leads venture-client labs that help Fortune 500 companies adopt and scale cutting-edge technologies from global tech ventures. A builder of accelerators, investor, and co-editor of the bestseller The INSURTECH Book, Sabine is known for asking the uncomfortable questions—about AI governance, risk, and trust. On Scouting for Growth, she decodes how real growth happens—where capital, collaboration, and courage meet. If this episode sparked your thinking, follow Sabine VanderLinden on LinkedIn, Twitter, and Instagram for more insights. And if you're interested in sponsoring the podcast, reach out to the team at hello@alchemycrew.ventures

MAPS Upper Lower: https://mapsupperlower.com Code: LAUNCH for 40% off. Four day split, male and female versions, workout videos and live coaching with Cole. Three days left on this offer. In this episode the guys break down five times when machines are actually better than free weights — isolating a muscle or movement pattern, when recovery is challenged from a sport or hard training block, adding extra volume without taxing the body, advanced intensity techniques like drop sets and forced negatives, and movement patterns that gravity-based free weights simply can't replicate. Sal shares how he is now training with machines more because of jiu jitsu recovery demands. They also get into the world mile record being broken at 3:42 by a British guy, the cyclosporiasis lettuce outbreak and how it spreads, the history of the marshmallow plant and why it was removed from marshmallows, creatine erasing the performance deficit from a bad night of sleep (confirmed by an ER doctor and a nurse in Sal's life), the gym industry entering a boom with 26% of Americans now having a membership, and K-shaped gym economics where budget and premium gyms are crushing the middle. Then they coach live callers submitted through mplivecaller.com.  SPONSORS Olipop: https://drinkolipop.com/MINDPUMP Buy any two cans in store (any flavor, any retailer) and they will pay you back for one. Cream soda discussed on air. New blue can design.   Legion (creatine): https://buylegion.com/mindpump Code: MINDPUMP for buy one get one 50% off (new customers) or 20% cash back (returning). Creatine discussed on air for sleep deprivation performance — 15 to 20g on bad sleep days.   LINKS Submit a live caller question: https://mplivecaller.com Mind Pump Store: https://mindpumpstore.com Maps Fitness Products: https://mapsfitnessproducts.com Instagram: @mindpumpmedia   0:00 - Intro 2:19 - 5 times machines are better than free weights 3:02 - Reason 1: Isolating a muscle or movement pattern for bodybuilding or corrective exercise 7:44 - Reason 2: When recovery is challenged from a sport or hard training block 12:47 - Reason 3: Adding extra volume without additional recovery cost 14:29 - Reason 4: Advanced intensity techniques — drop sets, forced negatives, partials and failure training 17:26 - Reason 5: Movement patterns that free weights and gravity cannot replicate 19:41 - Olipop, marshmallow root history and the cyclosporiasis lettuce outbreak 26:03 - Creatine erasing the performance deficit from bad sleep — ER doctor and nurse confirm it 30:05 - Sal's racing days, exhaust culture and why speed limits exist despite 800hp cars 50:55 - Gym industry entering a boom — 26% of Americans have a membership and attendance is at an all-time high 56:03 - K-shaped gym economics — budget and premium gyms are crushing the middle 1:00:19 - Caller: Nick (California) — contractor with wildly inconsistent schedule, undereating, gets coaching referral 1:16:33 - Caller: Rachel (England) — 58 years old, strong, lean, doesn't think she looks like she lifts 1:24:57 - Caller: Tyler (Washington) — 25 years old, feeling lost, Hashimoto's, dislocated shoulder, PCL tear, gets MAPS Symmetry 1:38:36 - Caller: Jenna (Wisconsin) — hip flexor follow-up, getting stronger, asks about next program after Symmetry, gets MAPS Strong

-VNR listener Beck wants to know, “How many machines does a garage gym need?”-He has a C2 rower, but recently has been trying to decide if he should get a ski erg and/or an air runner?-He lives in a very hot environment & says the space in his garage gym is somewhat limited, so he is not taking this decision lightly.-Pat & Adrian discuss this topic.

Dr. Joy Buolamwini is a computer scientist and a poet of code who uses art and research to illuminate the social implications of artificial intelligence. She joins to discuss her career as the founder of the Algorithmic Justice League, her best-selling book Unmasking AI: My Mission to Protect What is Human in a World of Machines, and her featured role in the acclaimed Netflix documentary Coded Bias. Hosted on Acast. See acast.com/privacy for more information.

This week, we're bringing you another double feature of Politicology+ special previews.  First, Ron Steslow talks with Mike Madrid about Pope Leo XIV's first encyclical, Magnifica Humanitas. Using the Pope's choice between "constructing Babel" and "rebuilding Jerusalem,” they confront what happens when we hand life-and-death decisions to machines that can't be held accountable. Then, Ron and Jennifer Schulp discuss political corruption in cryptocurrency and stock trading. They dive into the lack of political will to combat it, despite public outcry, and the challenges of enforcing ethical standards. POLITICOLOGY+ Not yet a Politicology+ member? Don't miss all the extra episodes on the private, ad-free version of this podcast. Upgrade now at politicology.com/plus. SPONSORS & PROMO CODES: https://bit.ly/44uAGZ8 Send your questions and ideas to podcast@politicology.com Ron Steslow on X: https://x.com/RonSteslow Mike Madrid on X: https://x.com/madrid_mike Jennifer Schulp on X: https://x.com/jenniferjschulp Learn more about your ad choices. Visit megaphone.fm/adchoices