Podcast appearances and mentions of Albert Einstein

What if the reason you can't access magic consistently has nothing to do with strategy, discipline, or desire - and everything to do with the frequency your body is broadcasting? In this special episode of Why Isn't Everyone Doing This?, Emily Fletcher kicks off a three-part series designed to help you get ready for Magic Maker, happening this July. This first episode tackles one of the most quietly frustrating experiences on the spiritual path: not whether magic is real, but why you can't seem to stay there. Emily explores why so many people who already believe in manifestation are still hitting invisible ceilings, and why the answer has less to do with your mindset and more to do with whether your head, heart, and body are sending a coherent signal to the quantum field. She grounds this in research from the HeartMath Institute, Einstein's foundational principle on consciousness, and her own five years of developing this body of work. This episode is for the people who have already tasted magic, and want to know how to live there - on demand. In this episode, Emily explores: What "magic" actually means, and why it has nothing to do with wishful thinking or pulling things out of thin air Why manifestation is not something you do, but a reflection of who you believe yourself to be How most people are accidentally sending mixed signals to the quantum field, even when their desires are crystal clear Einstein's principle: no problem can be solved at the same state of consciousness that created it The difference between paranoia and pronoia, and why we keep slipping back into protection mode Research from the HeartMath Institute on heart-brain coherence and the electromagnetic field of your heart Why you cannot tell your nervous system to calm down, and what to actually do instead How unprocessed emotion and inherited trauma create energetic static that blocks what you're calling in Key Moments: 00:00 — Welcome and what this bonus series is about 01:25 — What "magic" actually means 02:10 — How mixed signals to the quantum field work 03:20 — Manifestation as a report card on your state of consciousness 03:44 — Einstein and the problem of solving from the same frequency 05:15 — Who this series is for 06:32 — Heaven as a vibration, not a destination 10:39 — Why smart people get stuck in the same manifesting traps 12:45 — HeartMath Institute research on coherence 14:10 — The cosmic server analogy 15:32 — What Magic Maker will cover 17:28 — Preview of next week's bonus episode Something is building at Ziva. For those who are ready to bring this frequency into their body and their life. Get on the list first.

On this episode of The Strategerist, Walter Isaacson, known as one of America's pre-eminent biographies joins host Andrew Kaufmann to discuss some of the world's greatest innovators: Steve Jobs. Elon Musk. Benjamin Franklin. Jennifer Doudna. Albert Einstein. Even Leonardo DaVinci. His most recent work takes a look not at a person, but at a turning point in history: The Greatest Sentence Ever Written, a small but inspiring book that analyzes the second sentence of the Declaration of Independence.

In this sponsored episode, George Stein, Vice President of Digital at Montefiore Einstein, and Dr. Shivani Agarwal, Senior Director of Community Healthcare Improvement & Strategy at Montefiore Einstein, join the podcast to discuss innovative approaches to improving preventive cancer screening rates. They share how agentic AI outreach and digital solutions are helping patients navigate the screening process, reduce barriers to care, and connect more people with timely preventive services.

Roman Yampolskiy has spent two decades trying to prove that superintelligent AI can be controlled. He couldn't. I invited him on to make his case. Subscribe if you want science with evidence, not speculation. Roman is a professor of computer science at the University of Louisville and one of the earliest researchers in AI safety. His book AI: Unexplainable, Unpredictable, Uncontrollable started as an attempt to solve the alignment problem. After decades of work, it became a proof that the problem cannot be solved. Not difficult. Mathematically impossible. I push back hard. We go after the Einstein test: can a large language model trained only on pre-1911 physics reproduce what Einstein did with the same data? We ran that experiment. It failed. Roman and I disagree about what that means. We also get into the halting problem and what it actually tells us about predicting smarter-than-human behavior, whether value alignment is a real problem or a well-funded category error, the case for a government moratorium on frontier model development, and why Roman thinks giving an AI agent access to your computer is the dumbest thing a smart person can do. What you'll hear: Whether AI control is mathematically impossible or just unsolved Why Roman thinks all current AI safety work is security theater What the halting problem actually means for superintelligence The alignment problem: real issue or well-funded category error Why Roman wants a moratorium on frontier model development What to tell your kids about careers in a world where Roman might be right If you listen to other people, the best you can become is average. CHAPTERS 00:00 Creating a mind without an off switch 01:34 Solving problems beyond our own intelligence 04:08 Einstein's epiphany and the limit of AI intuition 08:18 Assessing the Einstein test: Why the experiment failed 12:22 Path dependency: Are LLMs and GPUs our QWERTY? 16:10 The barriers preventing AI from solving physics 21:54 Safety vs. Capability: Why toddlers are safe but teens are not 23:06 The halting problem: Predicting agents smarter than us 25:58 The impossibility of a system proving its own integrity 28:18 Regulation: Genuine safety or a gift to oligarchs? 33:28 Is human cognition non-computable? Penrose vs. the field 39:00 Ethical duties: Must we treat AI with humanity? 43:00 From internet memes to monsters: Decoding the book cover 46:22 Customized realities: Can everyone have their perfect world? 49:50 Von Neumann probes and the panspermia hypothesis 55:02 Categorizing AI: The one version that should terrify you 58:22 Pause AI: The movement for a development moratorium 59:58 Career advice for kids in a post-professional world 01:07:58 Cross-examining Sam Altman 01:15:48 Roman's dream debate 01:19:50 Lessons for a younger self Substack: https://briankeating.substack.com Get the transcript, fascinating bonus content, and my Monday M.A.G.I.C. Message: https://briankeating.com/yt Have a .edu email and live in the USA? You automatically win a meteorite: https://BrianKeating.com/edu Subscribe: https://www.youtube.com/DrBrianKeating?sub_confirmation=1 Support Into the Impossible on Patreon, get my weekly M.A.G.I.C. Message, unfiltered bonus content, and live monthly Office Hours with me: https://www.patreon.com/drbriankeating Join this channel for perks, monthly Office Hours, and your name in the Member Roster at the end of every episode: https://www.youtube.com/channel/UCmXH_moPhfkqCk6S3b9RWuw/join Featured Guest: Roman Yampolskiy on Twitter/X: https://x.com/romanyam?lang=en AI: Unexplainable, Unpredictable, Uncontrollable: https://www.romanyampolskiy.com/books/ My books: Losing the Nobel Prize (memoir): http://amzn.to/2sa5UpA Think Like a Nobel Prize Winner: https://a.co/d/03ezQFu Focus Like a Nobel Prize Winner: https://a.co/d/hi50U9U Galileo's Dialogue (first-ever audiobook): https://a.co/d/iZPi9Un Twitter/X: https://x.com/BrianKeating Substack: https://briankeating.substack.com Blog: https://briankeating.com/blog Audio-only: https://briankeating.com/podcast #intotheimpossible #briankeating #AIrisk #artificialintelligence #aisafety #podcast #superintelligence #RomanYampolskiy Learn more about your ad choices. Visit megaphone.fm/adchoices

This episode of Jewish Voices, American Stories explores how Jewish-American scientists and doctors helped change the course of history—bringing healing, hope, and life to millions.We begin with Jonas Salk and Albert Sabin, two brilliant scientists whose breakthroughs in the fight against polio transformed one of America's greatest fears into one of its greatest public health victories. At a time when families lived in dread of the disease, their vaccines brought relief, protection, and a future free from fear—and they chose to share their discoveries not for profit, but for the good of humanity.Next, we meet Dr. Henry Heimlich, whose simple yet lifesaving maneuver empowered ordinary people to act in moments of crisis. His work reminds us that sometimes the difference between life and death comes down to knowledge—shared, practical, and ready in an instant.Finally, we turn to two of the most influential scientific minds of the modern era: Albert Einstein and Richard Feynman. Their discoveries reshaped how we understand the universe, while also raising profound questions about responsibility, ethics, and the power of knowledge. From the atomic age to the space age, their work helped define the modern world.These stories reflect a deeply rooted value in Jewish tradition: the call to pursue knowledge, to ask questions, and to use what we learn to better the world. And through these individuals, we see how science—guided by purpose and responsibility—can truly help heal the world.To learn more about God's people—from the days of the Bible through the present—visit The Fellowship's Learn Center.

Saludos, tripulación de Historias para ser leídas. Bienvenidos a bordo. 🚀💫 Hace tres años iniciamos una misión que quedó fragmentada en el tiempo. Hoy, he unificado las transmisiones. He recopilado todas las bitácoras pasadas para ofreceros el viaje completo, mejor calidad y sin interrupciones rumbo al corazón mismo de la gravedad. 🚀👨‍🚀 Imagina que tú eres el propietario y capitán de una gran nave espacial, con ordenadores, robots y una tripulación de cientos de personas a tus órdenes. La Sociedad Geográfica Mundial te ha asignado la misión de explorar los agujeros negros en regiones lejanas del espacio interestelar y transmitir por radio a la Tierra una descripción de sus experiencias. Tras seis años de viaje, tu nave está decelerando en la vecindad del agujero negro más próximo a la Tierra: un agujero llamado «Hades» cercano a la estrella Vega. En la video pantalla de tu nave, la tripulación y tú observáis manifestaciones de la presencia del agujero: los escasísimos átomos de gas en el espacio interestelar, aproximadamente uno por centímetro cúbico, son atraídos por la gravedad del agujero negro. Las únicas singularidades representadas en las cartas de viaje de su nave son las que están dentro de los agujeros negros, y usted se niega a pagar el precio de la muerte para explorarlas. Pero atención, capitán. El espacio es impredecible y el destino de esta tripulación no está escrito. Al final de este trayecto, la realidad se bifurcará. Os enfrentaréis a una decisión crucial en los límites del horizonte de sucesos: Tendréis que elegir entre dos transmisiones finales que se incluyen en este mismo audio. 🔴OPCION 1 🚀 ✅OPCION 2 🚀 Dos caminos. Dos desenlaces posibles. Dos destinos para un mismo misterio cósmico. Encended los motores de curvatura ¡Comenzamos el viaje! 🚀💫 Thorne comienza llevándonos a un viaje por los agujeros negros y, desde allí, nos hace seguir el descubrimiento de las nuevas concepciones, desde Einstein hasta nuestros días, en una especie de relato histórico sazonado de anécdotas vividas, a lo largo del cual vamos aprendiendo los conceptos básicos, hasta llegar al punto en que agujeros de gusano y máquinas del tiempo nos parecen posibilidades lógicas y comprensibles. Stephen Hawking calificó esta historia como «un relato fascinante», y dijo: todos cuantos aman los misterios científicos disfrutarán con él. Comenzamos el viaje....! Este relato ha sido escrito por Kip Stephen Thorne (Logan, Utah, 1940), físico teórico estadounidense, conocido por sus contribuciones prolíficas en física, astrofísica y gravitación. Gran amigo y colega de Stephen Hawking y Carl Sagan, ocupó la cátedra «Profesor Feynman» de Física Teórica en el Instituto de Tecnología de California hasta el año 2009, y es uno de los mayores expertos sobre las implicaciones astrofísicas de la teoría general de la relatividad de Einstein. Ha escrito y editado libros sobre temas de teoría de la gravedad y astrofísica de alta energía. En 1973, fue coautor del libro de texto clásico Gravitation , con Charles Misner y John Wheeler, del que la mayor parte de la actual generación de científicos han aprendido la teoría de la relatividad general. En 1994, publicó Agujeros negros y tiempo curvo: el escandaloso legado de Einstein , un libro de referencia para los no científicos por el que recibió numerosos premios y que ha sido publicado en seis idiomas. Su trabajo ha aparecido en revistas y enciclopedias, tales como Scientific American , McGraw-Hill Yearbook of Science and Technology y la Collier's Encyclopedia , entre muchos otros, y ha publicado más de 150 artículos en revistas especializadas. Ha presentado diversos programas de la PBS estadounidense (televisión pública) y la BBC inglesa sobre temas como los agujeros negros, las ondas gravitatorias, la relatividad, el viaje en el tiempo y los agujeros de gusano. La lista de premios, reconocimientos y honores recibidos es larga y variada: Science Writing Award in Physics and Astronomy del American Institute of Physics; Science Writing Award de la Phi Beta Kappa Society; Karl Schwarzschild Medal por la German Astronomical Society ; Robinson Prize in Cosmology por la Universidad de Newcastle; California Scientist of the Year Award por el California Science Center; Medalla Albert Einstein (2009) por la Sociedad de Albert Einstein (Berna, Suiza), etc. Una producción de Historias para ser Leídas, Voz: Olga Paraíso, música y efectos Epidemic Sound, gracias al artista Lotus (Licencia autorizada para este Podcast). Muchísimas gracias a los taberneros galácticos que apoyan este podcast, vamos rumbo a las estrellas,🌌🚀 ¿nos acompañas? Puedes apoyar mi trabajo desde el botón azul APOYAR por tan solo 1,99 € al mes. Credit Imagen Shutterstock Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

John talks with Steve Kates, a.k.a. Dr. Sky, about the development of a hypersonic aircraft, the mysterious volcanic history of Mars and Albert Einstein's scientific legacy. Learn more about your ad choices. Visit megaphone.fm/adchoices

John talks with Steve Kates, a.k.a. Dr. Sky, about the development of a hypersonic aircraft, the mysterious volcanic history of Mars and Albert Einstein's scientific legacy. Learn more about your ad choices. Visit megaphone.fm/adchoices

BONUS: Why Your Organization Is Still a Factory — And What an Octopus Can Teach You About Transformation Phil Le-Brun and Dr. Jana Werner both work inside Amazon, advising Fortune 500 leaders on transformation. But before Amazon, they spent decades in the trenches — Phil as International CIO of McDonald's, Jana leading change in banking and logistics. Together they wrote The Octopus Organization (HBR Press) to explain why most companies are still running on a hundred-year-old factory model, and what the alternative looks like. "We Want to Help You Make Your Own New Interesting Mistakes" "We keep saying, as Phil likes to say, can we help you make your own new interesting mistakes and avoid the mistakes that we see again and again."   Jana and Phil are both practitioners who have led large-scale changes — and made mistakes they're now happy to share. Jana describes working with incredible, smart, thoughtful people inside large organizations who weren't trusted, weren't allowed to do the work they could do, and couldn't be their best selves. She managed to turn teams considered underperforming into rock stars simply by listening and giving them space. Phil saw the same pattern at McDonald's — incredible people who knew the answers but weren't allowed to act on them. A disastrous standardization push from 2002 to 2004 taught him that top-down efficiency mandates don't work. The CEO left, and Phil got the opportunity to tap into people lower in the organization, define a common mission, and start building from there. The Factory Model Nobody Questions "There was no upside for her people taking ownership because you could have career-limiting effects if you made a mistake, if you were seen to be making a mistake or overstepping."   Jana shared two sides of the same problem. A CEO of a large investment company told her he has to sign off on every small decision — and his people assume he wants to. Neither side wants this, but nobody questions the processes in place. On the other side, a COO told Jana "my people don't want ownership." After half an hour of coaching, the COO realized there was no upside for her people to take ownership — mistakes meant career-limiting consequences. Jana is honest about her own experience too: a team member told her she was micromanaging, and she denied it. They created a secret signal — scratching an ear in meetings whenever she micromanaged. He was scratching a lot. Phil adds that what he calls "yoga babble" — abstractions like "we're going to become an agile platform-based culture" — lets leaders avoid saying what they actually mean. Nobody challenges it because the boss said it, and it sounds sort of right. The result: completely meaningless direction. The Octopus — Distributed Intelligence in Practice "It has two thirds of its intelligence, its neurons, in its arms. The arms connect independently — they don't always need a central brain, but they also have one, so they can stay aligned but also work independently."   The octopus has distributed neural clusters in each arm. It can adapt, shape-shift, change the texture of its skin, and even alter its RNA to switch between cold and hot water within hours. For Jana and Phil, this is the organizational metaphor: teams that can think locally and act without waiting for permission from the center, while staying aligned on mission. Phil translates this for team leaders of 8-10 people inside traditional enterprises:   Put together teams with cognitive diversity and encourage constructive conflict — what Linda Hill at Harvard Business School calls "creative abrasion" Invest in the storming, norming, performing cycle instead of cutting through it Leave the "how" to the team — the leader's job is the "why" and the "what" Don't jump to the answer — Einstein said if you have an hour to solve a problem, spend 55 minutes understanding the problem Start executing quickly through rapid experimentation; you can't plan your way to success in novel situations Don't Build the Pedestal — The Monkey Comes First "Get to the most tricky problems first, and try and solve them. If you can't, figure out fast — and if you can't, just stop, because your whole project is useless."   Astro Teller, CEO of Alphabet X's Moonshot Labs, says: "If you want to teach a monkey on a pedestal to recite Shakespeare, don't start by building the pedestal." Jana explains that organizations, once they get a project through the gauntlet of approvals and business cases, start working on the easy, visible things to show progress — the pedestal. But if you can't get the monkey to speak, the pedestal is useless. The counterintuitive move: when passionate people dispassionately tell you the hard problem isn't solvable, give them hugs, put them on a pedestal themselves, give them bonuses — because they just freed up resources for something better. Phil reinforces that this isn't a money problem. At McDonald's, before building a handheld order-taking device, they built a block of wood to test how comfortable it was to hold. Organizations waste far more money trying to plan for things they can't possibly plan for than they would by running quick experiments. Single-Threaded Leaders — The Pig at Breakfast "Who's that person waking up every morning saying, are we actually putting the focus on the things that are going to get us to the finish line of delivering value — not within my function, but across the organization?"   Phil tells the classic joke: a pig and chicken are walking down the road. The chicken says "let's open a restaurant." The pig asks what they'll sell. "Ham and eggs, of course," says the chicken. The pig stops: "I need to be far more committed than you." Organizations are full of chickens — people who lay their half-baked decisions, want to sign off, want to say no. What's needed are pigs. Amazon calls them single-threaded leaders. Apple calls them directly responsible individuals. The key: one person owns an initiative end to end, waking up every morning focused on delivering value across the organization, not just within their function. Mow the Lawn — Bureaucracy Grows While You Sleep "Your bureaucracy grows while you sleep. Think about your bureaucracy like mowing a lawn. You can't mow a lawn once."   Jana references Parkinson's Law — a senior Royal Navy leader found that even as the fleet shrank, the number of administrators grew by 5-10% annually. This applies to every organization. Middle managers fill their time by adding processes. One person's mistake becomes a process that penalizes 10,000 people. The solution is continuous gardening. At Google, a senior leader added positive friction: if you want more than 5 interviews in the hiring process, you need my approval. At Amazon, the principle "invent and simplify" asks everyone every year: what are we simplifying? The simplification work has to come from those closest to the problems — most leaders don't know half of what people are actually doing. Innovation Belongs to Everyone — Not a Lab "Psychological safety — it's not even a prefrontal cortex thing, it's not a conscious thought, it's that fight-or-flight reaction you have in the moment."   Phil makes the case that innovation starts with psychological safety at the team level, not an organization-wide mandate. It's the team leader asking questions, being humble, responding to disagreement with "tell me more" instead of "I don't agree." It means celebrating intelligent failures — someone who tested a hypothesis, found it didn't work, and stopped. At Amazon town halls, executives open by making fun of Amazon's failures, like the Fire Phone. The message: if you're thinking big, you'll also fail. The Fire Phone didn't work, but it informed future hardware investments. The only true failure is not learning from experimentation. Phil and Jana both emphasize that once leaders experience what happens when people are truly freed to do their best work, they get addicted to it. About Phil Le-Brun and Dr. Jana Werner Phil Le-Brun is the former International CIO of McDonald's and now leads the AWS Executives in Residence team, advising Fortune 500 leaders on transformation. Dr. Jana Werner is an Executive in Residence at AWS who built their EMEA transformation practice after leading digital change in financial services. Together they wrote The Octopus Organization: A Guide to Thriving in a World of Continuous Transformation (HBR Press).   You can link with Phil Le-Brun on LinkedIn and Jana Werner on LinkedIn.   Book site: theoctopusorganization.com Book on Amazon: The Octopus Organization

Bass guitarist, composer and songwriter Guy Pratt and bassoonist Amy Harman are Jeffrey and Anna's studio guests as they add five more tracks. Starting with an early ska classic, they explore the art of 'hocketing' before heading to the beach with Einstein.Producer Jerome Weatherald Presented with musical direction by Jeffrey Boakye and Anna PhoebeThe five tracks in this week's playlist:Miss Jamaica by Jimmy Cliff Rock On by David Essex Finale of Symphony No 6 in B Minor by Tchaikovsky Hockets for Two Voices: 1 by Meara O'Reilly Knee Play 5 from Einstein on the Beach by Philip GlassOther music in this episode:Ain't No Doubt by Jimmy Nail Like a Prayer by Madonna The Reason by Celine Dion I'm Alive by Vybz Kartel Be My Guest by Fats Domino Walk on the Wild Side by Lou Reed The Dark Side of the Moon by Pink Floyd 9th Symphony by Gustav Mahler Zap Mama by Babanzélé Gamelan by the Bali Gamelan Orchestra Money by Pink Floyd Welcome to the Machine by Pink Floyd

Peter Tuchman has spent more than 41 years on the floor of the New York Stock Exchange. Today, the Einstein of Wall Street is a true Wall Street star, with 1.2 million followers on Instagram. But what has changed? "Technology caused the real change. There used to be 7,000 people on the floor. Once we got the first computer, there was no longer a need for so many people. But we are still the last human-based marketplace," says Peter Tuchman. All details about the stock market rollercoaster in the interview with Inside Wirtschaft's Manuel Koch from the New York Stock Exchange on Wall Street and on https://inside-wirtschaft.de

Kwa zaidi ya karne mbili, maelezo ya Newton ndiyo yaliyotawala sayansi. Kisha mwaka 1915, Albert Einstein akaja na wazo lililobadilisha kila kitu: gravity si nguvu ya kuvutana — ni kupinda kwa nafasi na wakati (space-time).

Lukey Ryan loves to operate with time and space, but even he never thought he'd get to take a leisurely stroll in the park and stop for a cup of tea during a game! Time to Restump Podcast the tiptoeing through the tulips win over the Kangas. The Kangaroos just absolutely skedaddled. It was as if Luke Ryan was on the back of 4X4, armed with a spotlight and a Winchester! Was there divine intervention? Not since Moses parted the Red Sea has a safe and spacious passage to the promised land inexplicably appeared!It was a remarkable record tumbling day down at Bunbury, brought about by the contributions of both teams. You don't win 12 straight if you're not a serious outfit, but you don't destroy any opponent by 120+ points, hold them to just 3 behinds in a second half and put on 19 goals on the bounce without their deficiency assistance. However, at the same time, you can't manage such a feat if you're not rolling out an airtight functioning system and combining it with a relentless worth ethic and an insatiable hunger. Is there another ruckman in the league whose teammates willingly handball to? Maybe Brody Grundy but it'd still be due to a lack of comparable options. Hayden Young's first thought is ‘get the ball to Luke Jackson!' Even Luke Jackson's first thought when he gets his own ball is to handball to Luke Jackson! He is the AFL player prototype and unless there's a relaxing of the ethics and laws around cloning, he's going to remain a one-of-a-kind collector's item. We gotta talk Sammy Switkowski. JL's Einstein, the sharpest man in the west and I'm pretty sure a former Sale of the Century showcase winner! He's taken 9 injury plagued seasons to get to 117 games and he's potentially in his career best form. His work rate is unquestionable and on Saturday he saw personal reward with an equal career high three goal feat, something he has now managed three times. With two of those occasions coming this year, he's a vital piece of the September puzzle.I know we've won twelve on the bounce, we're twelve and one for the year, we're top of the tree, a game clear of Syndey in second, three and a half games and thirty percent ahead of the Hawks in third and 3/1 favourites for the flag…. but, for mine, the hype from all corners of the industry is a little uncomfortable. There is an unwanted element of forgone conclusion commentary about us and it's just a little bit unnerving. Yes, the ship has to leave the safety of the harbour at some stage but that means navigating unchartered waters! Give me back our comfortable underdog status, remove the intense magnified focus and let us return to our familiar footing of flying under the radar! Oh, who am I kidding, it's like a Tupperware container…. even if you could find the lid, there is no putting the lid on it. The lid is so far off, we can't even see the lid! The lid is in outer space! So, we live now, we throw cautious  optimism to the wind and go mental enjoying the thrilling journey and we worry about any possible unwanted consequences if or when  they arrive.We'll all take a breather over the bye, but before then, there is still plenty of purple praise to promulgate. So, put on your pants, pour yourself a piccolo, pitch in, park yourself on a plush perch, press play and partake in the purple prattle on the pod. Send us Fan MailSupport the show

George Noory and scientist David Pares explore the concept of warp drive and faster than speed of light space travel, what Einstein said about the possibility of warp speed, and his efforts to develop his own spacecraft.See omnystudio.com/listener for privacy information.

Allen Nejah, CEO and System Solution Architect of SunMan Engineering, is driven by a lifelong passion for aerospace, invention, and solving complex engineering problems. From dreaming of becoming an astronaut as a child to working with major aerospace, defense, automotive, medical, robotics, IoT, and semiconductor organizations, Allen has built a career around turning ambitious technical ideas into real-world systems. We explore The Allen Nejah Engineering Framework — Live with Integrity, Be Intensely Curious, Get Organized, Plan Every Baby Step, and Learn from Mistakes — a practical mindset for building breakthrough technologies with discipline and resilience. Allen explains why integrity must exist not only in business relationships but also in the engineering itself, how complex projects must be broken into testable steps, and why curiosity, visualization, planning, and iteration are essential to solving problems across industries. He also shares the story behind InfiniGear, his AI-powered adaptive transmission system, and the healthcare technology inspired by his mother's experience in assisted care. — Building the Connected Car Before the iPhone with Allen Nejah  Good day, dear listeners. Steve Preda here with the Management Blueprint Podcast, and my guest today is Allen Nejah, the CEO and System Solution Architect of SunMan Engineering, dedicated to providing customers with high-quality, on-time engineering and on-budget solutions for their product development and prototyping needs. Allen, welcome to the show.  Yes, that is correct.  Great to have you on the show. And I’d like to ask you my favorite first question: What is your personal ‘Why,’ and how are you manifesting it in your business?  So Steve, first I want to thank you for having me on your podcast. I really appreciate your time and interest. Of course.  As a kid, for whatever reason, I always wanted to have an airplane manufacturing company, an aircraft manufacturing company—something I always wanted to have. And I always wanted to be an astronaut. As a matter of fact, I studied aerospace and mechanical engineering with the dream of being an astronaut, going to fly and all that. So that’s kind of something that’s still in my pocket and that I still want to do. From there, it kind of pushed me in this direction. And yeah, now I work with a number of different companies in the aerospace industry. I work with the Air Force. I’ve worked with Lockheed Martin, Boeing, and a number of others. And I work on both space and aviation projects that really kind of bring my dream to life. So I still haven’t gone to outer space yet, but I still have a little more time.  Yeah. Elon Musk is promising a million people, and his bonus is linked to putting a million people on Mars as the first colony. So there may still be room there.  They need a lot of us to go there, trust me. Well, actually, we’re going to do a lot of activities on the Moon first, and then from there, I’m sure they’re going to be looking for older people, older men, to do some tasks over there. And I’d volunteer to go.  You may be familiar with the Mars trilogy—Red Mars, Green Mars, Blue Mars. It talks about people moving to Mars and how they terraform it. And then they figure out how to extend life to 150, 200 years. So if that works out, then maybe there’s another lifetime to be lived on Mars.  Yeah. I definitely believe that we will end up living on other planets, for sure. I see that very clearly. It could be 50 years or more before we actually become a space-based civilization. But the Moon has already started, right? We’re going to be there in the next 5 to 10 years, trust me. So anyway, I’m very excited about that. Yes.  Yeah, it is very exciting. What I’m looking for on this podcast—what makes it kind of unique—is that I am a junkie for frameworks and mental models. We are almost 400 episodes in, and every episode has a different mental model that our guest comes up with or shares. So think about something that helped you build your business, or maybe helped you develop your products, or how you work with your engineers, or how you work with clients. So think about something that has three to five steps or three to five aspects that create a result.  That’s very clear to me. Those are the key things for any successful person. First of all, honestly, you have to be interested. You have to be in “go” mode. You cannot push somebody to start building something, like a building or actual construction, if their mind is not into it. The very first thing is, it’s got to be you. That’s number one, right? And you know it. Definitely organization is a very key factor for me. Being organized, being detail-oriented—that’s something that is super, super important. Planning and organization make a huge difference in whatever you do, right? And most importantly, integrity. I mean, that’s number one. That’s number one, number two, number three, number four—all of it.  So integrity is all of it. No matter what you do, if there’s no integrity, people will walk away from you. At the beginning, every business makes mistakes, and they learn and so on. So don’t beat yourself up. It’s okay. You make a mistake, you learn from it, and then you don’t do it again, right? Learn from it. So yeah, I would say those are at least three. If anything else comes to mind, I definitely will share it with you. But the most important things are integrity, organization, and clear planning based on knowledge. Not just planning for the hell of it, but planning based on understanding what you’re doing. That’s important. Integrity comes into your personality. It comes into the quality of the work you do.  It comes into the engineering you do. It comes into all of that, right? Even in engineering, it’s not only on the personal level that integrity has to be there. On the engineering level, integrity has to be there too. Whatever you do, you’ve got to make sure it’s working. One of the things we learned the hard way after 35 or 36 years is that it’s very important to have the knowledge base and to do things in a very organized way. And that’s kind of part of my personality. If I’m not confident about the end result, I don’t even commit to it. I’ve got to see it in my mind. Whatever problem comes up, if I don’t see the solution in my mind, I won’t even commit to it. It comes back to quality, integrity, and all of that. And I guess what I was going to say earlier is that everything that we do—as part of, again, the quality and integrity I mentioned—is that we have a lot of baby steps built into the process.  That’s what I wanted to say earlier. So for every step, the whole plan is split into, I don’t know, tens, hundreds, or thousands of different steps and branches. Because technology is not one thing. It’s usually a combination of different sciences. So mechanical engineering, electronics, material science, firmware, AI—those are all different types of expertise. And you’ve got to bring them all together. And for all of those baby steps, you’ve got to have some sort of test at the end of each step before you move on to the next one. Iteration.  Yeah. So, okay, what I’m hearing is integrity is number one. And then curiosity, perhaps. So curiosity is this driving force. Visualization is important. I’m thinking about Einstein, who said that imagination is more important than knowledge because imagination is infinite, while knowledge encircles the world. I think it was something like that. So visualization is important. Get organized. Do thorough planning. And learn from mistakes.  Yes. Absolutely. Okay.  That’s great. So what do you call this? Is this the Allen Nejah Framework, or what’s it called?  One more thing. One more thing. Again, that’s kind of under the umbrella of integrity. So I have two families. It’s one family. I have a family at home, and I have a family at work. And believe it or not—and you already know this—we all spend more time with our family at work than with our family at home. That’s true. It’s true for me. It’s true for a lot of people. You go to work, I don’t know, from 8:00, 9:00, or 10:00 in the morning until 5:00, 6:00, 7:00, 8:00, or 9:00 at night. That’s almost 12 hours. And by the time you go home at 5:00, 6:00, or 7:00, what? You spend two hours with your family, maybe three hours at most, and then it’s back to work. So the team is part of my family, and truly it is part of my family. Those are the first group of people, the first group of associates, that you have to take care of.  You have to be a brother to them, be a friend to them, be a father to them, be a mother to them. Seriously, it’s all about human interaction. It’s all about, “I like you, I don’t like you,” and it goes from there. “I feel good about you. I don’t feel good about you.” And so it’s very important to have those relationships in your business, or whatever it is you do. For me, all our people, all our employees—even from 35 years ago—are still in touch with us. I have kids who came through as junior-high interns, then high-school interns, then university students, even master’s degree students. Now they’re 40 years old. And we’re still in touch. So I’m in touch with hundreds of engineers and people that I’ve worked with over the past 35 years. And that’s a lot of value. That’s the biggest asset.  Yeah. Basically, they call it a school. You create a school, right? Your own professional school. That’s wonderful. So tell me about this special gear called InfiniGear. How is it special? How did you come up with it, and how is it being used? It’s an interesting question. First of all, let me explain to you very quickly what I-Gear is. So I-Gear is an AI robotic adaptive gearbox, or transmission, and that’s a mechanical transmission. It’s not an electronic transmission. It’s an actual mechanical gearbox that goes into any machinery or equipment. I mean, obviously, the one that everybody can relate to immediately is cars. Every car—not EV cars, but every car—has a transmission. A transmission usually is bigger than the engine. It’s heavier than the engine. It’s the guy that goes through all the center of the car, takes all that center, okay?  That’s it—a transmission. It’s big, it’s heavy. By the way, it’s amazing how it works. It’s absolutely amazing how it works if anybody gets into a transmission and sees all of it. There are about 300 to 400 gear sets in there. There are about six or seven clutches. There’s about 3,000 to 4,000 parts in a standard transmission. So that’s why it’s so big and so heavy. The efficiency is so low because all these gears have to be interacting with each other. As a matter of fact, believe it or not, the transmission efficiency is only 50%. So it’s actually as low as you can get. But you have to have a transmission in the car. If you have no transmission in the car—I’m talking about ICE cars with an engine—they’re not even able to drive because the engine has no initial power and no initial RPM.  The AI transmission, the robotic transmission that I have invented, and that we have developed over five to seven years— Since 2017 or ’18 we’ve been working on it. It’s a gearbox that has only two gears versus 200 to 300 gears, and it’s one-fourth or one-fifth of the size. And also, while your standard transmission has five or six or seven or eight gears in your car, this has unlimited gears, okay? And it’s AI, so it can see what’s going on with the road, what the weather is, and all combinations of conditions. If you’re going onto a hillside, it’s already going to shift for you, so it saves energy. So that’s what we have developed. It’s a robotic transmission.  Right now, we’re actually talking to the U.S. Army, and they have some interest. We are at a very initial stage with them. And it’s kind of difficult to bring it into the market because it’s a safety factor, and there are a lot of requirements and tests that have to go into it before we can actually get it into trucks and cars. To summarize the benefit, if you put that transmission into an EV, we can increase the range by 40%, which is huge. A company that can improve a battery by 1% gets millions of dollars thrown at it. Once we can prove that this is working and pass some tests and so on, it’s going to be very huge. Wow. When do you expect this to happen?  I’m hoping within the next two years. Hopefully, by the end of those two years, we make it home and get it into cars and trucks and commercialize it.  Then you will turn into a unicorn—a big unicorn, right?  Yeah. Again, EVs are only one application. There are wind turbines, tanks, boats, some aircraft, and helicopters. A helicopter’s transmission is half the size of the helicopter itself, so the weight and everything else become very significant. So if we can eliminate that weight and size, we can gain a lot. Especially in vehicles, it makes a huge difference and all that.  Wow. That’s probably something that drones would benefit from too. Yeah. It’s mind-boggling. So what drives growth in your business other than your inventions?  So at SunMan Engineering, we have two arms. One arm is that we provide engineering services, product architecture, and product development to other companies—small companies, mid-size companies, and bigger companies like IBM, Sony, Samsung, and Apple. We have about 300 or 400 of those clients. And we also work with government agencies and contractors like Lockheed Martin, Boeing, and Kaiser Electronics, just to name a few. We have also had contracts directly with the Army and the Navy in the past. And that’s what we’re trying to do now—to gain some of those projects again. And InfiniGear, the I-Gear, could be a project that, fingers crossed, we’d be working on with the U.S. Army. So that’s one arm of what we do. The other arm is that we develop new technologies. We develop them, work on them, and then license them, or let our clients utilize them in some of their projects through partnerships and so on.  So you’re a service company as well as a product company?  Yes. We are a systems and product company. We’re considered a systems and product company, yes.  Now, do you call this systems integration? In the IT world, they used to call it systems integration when you had different systems and—  We are more than systems integrators. Systems integrators buy different technologies and put them together. It’s still engineering, don’t get me wrong. Yeah. You still have to engineer everything and put it together. But what we do is actually customize things from the ground up. Sometimes we do integration because it’s faster, easier, and sometimes cheaper. Some of the components and some of the functionality can be integrated. But generally, we customize every project from the ground up. And generally, for your information, we cater to aerospace, robotics, and IoT. IoT is communication—all sorts of wireless and different types of communication: Wi-Fi, 5G, Bluetooth, all sorts of stuff, right? And also medical. So medical, robotics, aerospace, IoT, and also semiconductors, which also serve these different industries.  So how is it possible? I mean, you have a relatively small team, right? Fifteen people or so?  Twenty-seven, twenty-eight people.  Twenty-seven. Okay, sorry.  Yeah. With a small team.That’s exactly the very first question you asked me. That’s exactly how it affects and how it comes into the picture. Being organized—I mean, we’ve done this so many times. It’s like we make things so efficient because we already have a plan. Every project we do, in concept, is the same thing. The process is the same. The application is different, but the process is the same. So going through that process and having a very reliable process in place that we follow very religiously makes us super, super efficient. And also, being small, we don’t have to go through a number of different layers. Everything comes to one or two people, gets approved, and we get it going. Everything happens the same day. Nothing waits until the next day here.  Are you involved in every project?  Fortunately and unfortunately, I’m involved in every project. And one of my goals is to eventually focus on fewer projects so I’d be more effective and efficient. So that’s one of my goals for the next few years. I-Gear is one of them, and we’re also working on another project. It’s for healthcare, it’s for the elderly and infants. Eventually it’s going to be a robot, but right now we’re making the device that is the brain of the robot. So it gets to know the person, it gets to know their habits, it gets to know everything about the person, about their family, about their health, about how they behave. We can remind them of different things. We can assist them with different things. We can watch them. We can emotionally work with them. There are so many different applications that we’re working on now. We can even do preventive diagnostics.  What “preventive diagnostics” means is that before the patient or the person gets sick or develops some sort of disease, we can actually identify it before that happens. That’s great. And that’s the most important part of this device. It has so many different applications and different ways it can help and assist an elderly person. And within the next two or three years, my goal is to integrate this into a robot. So we’re going to have a robot that physically helps you as well. My mother ended up in one of those care centers, and I saw how much she was declining on a daily basis—not weekly, not monthly, but daily.  And there was nothing, unfortunately, that I or any member of our family could do. I mean, we were there every day, don’t get me wrong, but that’s all we could do for her. We’re all busy. We all have lives. I mean, we were there almost every day, but really, she did not get the care that she needed. And that’s what kind of put me in that frame of mind—how can I help someone like my mom? And that’s how it started about two years ago. And as a matter of fact, now it’s one of the biggest markets. Yeah. It’s one of the biggest. So that’s fascinating. So how can you have so mental bandwidth that you can cover different industries, go deep into different industries, and innovate and invent stuff? How does that even happen?  Honestly, I personally work pretty much 12 hours a day. Even on my vacations, I work. Don’t get me wrong, I have a very good life. I work hard and I play hard. I am a very active person. I played as a semi-professional soccer player until I was 58 years old, believe it or not. Actually, next week I’m going to be 65. I still can play. I still can go and compete with 25- and 30-year-old kids, and I still do good, I think. So I keep myself in very good shape. I do mountain biking. I do about 10 to 15 hours of heavy-duty exercise on a weekly basis, and that kind of balances what I’m doing. To answer your question, yes, it’s too much, but yeah, we have to spend more time. There is no magic to it. Sometimes it gets to be too much, but I like what I’m doing, so I enjoy it.  Yeah, it shows. Elon Musk is also an example of being able to run six big companies in different areas and be a groundbreaker. But you’re doing something very similar. You are breaking ground in different industries.  Yeah. Actually, as I mentioned, I have established different startups and sold them. I have worked on a number of different companies and technologies. As a matter of fact, back in 2005, I brought a whole bunch of different technologies to cars. Any type of car you drive—I don’t care what it is—almost everything in the dash belongs to technologies that we developed from 2005 to 2008. There are some videos and some information on my LinkedIn. I invite people, including yourself, to look into it. The stuff we did back then was in 2005. The iPhone only came out in 2007. We came out with these technologies between 2005 and 2008. Back then, we had Genie. Today they have Alexa and I don’t know what everybody else calls theirs.  Yeah. We had Genie. Genie would talk to you. I mean, I’m not just saying it. Please go watch the videos. We have them. So you would just talk to the car, and the car would do everything for you. We came up with a device that initially you could install as an aftermarket stereo in the car. Basically, it would connect all the sensors in the car to the outside world. This was the very first time. As a matter of fact, internet connectivity in the car is my technology. Every single car in the world since 2014 has been connected to the internet, and that’s my technology, my patent, and my license. Of course, I’m not getting much money from it. Unfortunately, I’ve kind of been robbed on that. But at least I can brag about it—that’s our technology. So yeah, we brought a whole bunch of technologies to market. My vision back then was to make the car robust enough to drive without a driver.  That’s happening now.  It’s happening now. As a matter of fact, we had a car that we put our system into, and we were demonstrating it. And again, there are hundreds of videos about that technology that you can find on the internet. As a matter of fact, we were on PBS for nine months in 27 countries talking about future cars, and that video is also out there. So that was in 2010. They had a half-hour program with my company and with me about future cars. And everything we said, we had the basis for it, and it happened.  So, Allen, if you had a magic wand and you could wish for anything to happen in your business, what would that be? So as I said earlier, I like to be more focused now. I’m very spread out with the business—not only with the technical side of things, but also with the business side of things. I really want to get away from the business side and just focus on the technology. That’s what I enjoy more. I do the business side because I have no choice. That’s part of the work, right? But I would like to get to the point where I can focus only on technology, and other people can worry about the other things. So that’s my goal.  Okay. So if someone is listening to this and they would like to be like you, what would you advise them? Let’s say they are 20 years old and they want to grow up and be an inventor, come up with solutions, work in different industries, and solve big problems. What’s the path? What would you tell them?  So first of all, don’t be like me, that’s for sure. Honestly, you’ve got to enjoy life more than I do. And I do enjoy life. Again, I have different hobbies. I do different sports. I ski, I bike, and those are my hobbies, right? Most importantly, again, we talked about this at the beginning. You’ve got to like what you do. And doing business is not easy. Don’t expect to get into it and have everything work out. Usually, by default, everything goes wrong. So that’s normal. It used to bother me. It used to make me upset, nervous, and all that. But over the last seven to ten years, I learned that things happen, and you just have to resolve them and go through them. Bad things can happen. Good things can happen. It’s all part of the mix. You’ve got to have a very strong personality. Generally, a good percentage of people go paycheck to paycheck, and it’s mental—it’s in their mind. They make a lot of money. They make $100,000 every paycheck. But if you get a paycheck, your mind is like, “Okay, my next paycheck is coming two weeks from now, then another one two weeks after that,” right? And if those two weeks come and you don’t get your paycheck, they go nuts. They go crazy. So if you’re like that, you cannot go into business. In business, it’s all about failure and success. If you’re lucky, that’s a different story. I can go buy a lottery ticket, and only one person out of millions wins. That’s luck. That’s different.  But then they lose it all. Lottery winners tend to lose it. Within a year, they’re broke.  Yeah, that’s a different story, of course. What I’m saying is that, yeah, some people get lucky. That’s the exception. Don’t compare yourself to that. Don’t go after that.  Don’t count on it.  Doing business is usually a challenge, no matter what. So you’ve got to have a very strong personality.  So yeah, resilience is everything. Well, that’s wonderful. So if someone would like to learn more about SunMan Engineering, or they want to connect with you, what should they do and where should they go? Yeah, the best thing is to please visit the website, which is sunmantechnology.com. There is a contact form there, and you can contact us. We’d be happy to get in touch with you and see how we can help.  Okay, fantastic. Well, Allen Nejah, the CEO and chief engineer of SunMan Engineering, and the inventor of many products in different industries, including InfiniGear, which is going to revolutionize transmissions. Thank you for coming on the show and sharing your insights and wisdom. And those of you who are listening, if you enjoyed this, make sure you subscribe and follow us because every week I bring on an amazing entrepreneur to talk with you. Thanks for coming, Allen, and thanks for listening. Important Links: Allen's LinkedIn Allen's website

This is a FOUNDERS GROUP opportunity. Join Practice of Paradise: https://store.dralexanderloyd.com/products/practice-of-paradise  "YOU ARE NOT IMPRESSED ENOUGH" WITH THE FEEDING OF THE FIVE THOUSAND Dr. Alex Loyd and Harry Loyd dive into an equation that will change how you see Jesus' miracles forever.

Il 19 marzo 2026 scompare Chuck Norris. Se ci sono nomi che appartengono al cinema e che da lì diventano icona, il suo è sicuramente uno di questi. Artista marziale, attore, leggenda dell'action occidentale degli anni 80 e 90, Norris attraversa generazioni, trasformandosi nel tempo fino a diventare mito pop e simbolo quasi caricaturale di forza assoluta e invincibilità. Eppure, dietro quell'immagine granitica, c'è una storia più complessa, fatta tanto di disciplina e successo, quanto di convinzioni, idee e dichiarazioni controverse, che hanno lasciato perplessi.SCOPRI IL MIO ULTIMO LIBRO: "Il mistero delle origini dell'uomo. Un viaggio nel tempo per comprendere chi siamo e dove stiamo andando". Prenotalo ora: https://amzn.to/3WazGFVUna produzione Think about Science: thinkaboutscience.comCon: Massimo Polidoro e Giulio Niccolò Carlone; Video editing: Elena Mascolo, Fotografia: Claudio Sforza; Musiche: Marco Forni; Logo e animazioni: Zampediverse; Social - Comunicazione: Giacomo Vallarino - Grafiche: Roberta Baria; Distribuzione audio: Enrico Zabeo; Titoli: Jean SevillaÈ ARRIVATO IL MIO NUOVO LIBRO: "Una vita ben spesa. Trovare il senso delle cose con Leonardo, Einstein e Darwin": https://amzn.to/4leRDOR LEGGI UN ESTRATTO: https://bit.ly/4jRHXIN LEGGI la mia graphic novel: "Figli delle stelle" (con Riccardo La Bella, per Feltrinelli Comics): https://amzn.to/47YYN3KLEGGI: "Sherlock Holmes e l'arte del ragionamento" (Feltrinelli), il mio ultimo libro: https://amzn.to/3UuEwxSLEGGI: "La meraviglia del tutto" l'ultimo libro di Piero Angela che abbiamo scritto insieme: https://amzn.to/3uBTojAIscriviti alla mia NEWSLETTER: L' "AVVISO AI NAVIGANTI": https://mailchi.mp/massimopolidoro/avvisoainavigantiAderisci alla pagina PATREON, sostieni i miei progetti e accedi a tanti contenuti esclusivi:   /massimopolidoroScopri i miei Corsi online: "L'arte di Ragionare", "Psicologia dell'insolito", "L'arte di parlare in pubblico" e "l'Arte del Mentalismo": https://www.massimopolidorostudio.comPER APPROFONDIRELe musiche sono di Marco Forni e si possono ascoltare qui: https://hyperfollow.com/marcoforniLEGGI i miei libri: "Sherlock Holmes e l'arte del ragionamento": https://amzn.to/3UuEwxS"La meraviglia del tutto" con Piero Angela: https://amzn.to/3uBTojA"La scienza dell'incredibile. Come si formano credenze e convinzioni e perché le peggiori non muoiono mai": https://amzn.to/3Z9GG4W"Geniale. 13 lezioni che ho ricevuto da un mago leggendario sull'arte di vivere e pensare": https://amzn.to/3qTQmCC"Il mondo sottosopra": https://amzn.to/2WTrG0Z"Pensa come uno scienziato": https://amzn.to/3mT3gOiL' "Atlante dei luoghi misteriosi dell'antichità": https://amzn.to/2JvmQ33"La libreria dei misteri": https://amzn.to/3bHBU7E"Grandi misteri della storia": https://amzn.to/2U5hcHe"Leonardo. Genio ribelle": https://amzn.to/3lmDthJE qui l'elenco completo dei miei libri disponibili: https://amzn.to/44feDp4Non perdere i prossimi video, iscriviti al mio canale: https://goo.gl/Xkzh8ARESTIAMO IN CONTATTO:Ricevi l'Avviso ai Naviganti, la mia newsletter settimanale: https://mailchi.mp/massimopolidoro/avvisoainavigantie partecipa alle scelte della mia communitySeguimi:Patreon: massimopolidoroCorsi: massimopolidorostudio.comInstagram: @massimopolidoroPagina FB: Official.Massimo.Polidoro X: @massimopolidoro  Sito: http://www.massimopolidoro.comQuesta descrizione contiene link affiliati, il che significa che in caso di acquisto di qualcuno dei libri segnalati riceverò una piccola commissione (che a te non costerà nulla): un piccolo contributo per sostenere il canale e la realizzazione di questi video. Grazie per il sostegno!

Ukitupa jiwe juu, kwa nini LAZIMA lirudi chini?

Barbara With is an international peace activist, award- winning author/publisher, psychic channel, composer and performer, workshop facilitator, and inspirational speaker. She is the co founder of Conflict REVOLUTION® , a revolutionary way to resolve conflicts of the psyche based on her work channeling Albert Einstein.GIft - Einstein40Website and Social Media links:https://www.instagram.com/barbara.withhttps://www.facebook.com/barbara.withhttps://www.linkedin.com/in/barbara-with-a9a81a272https://www.youtube.com/@barbwithhttps://synergyalliance.llchttps://barbarawith.comhttps://barbwith.comMore about Liz:Work- https://www.raisethevibewithliz.com/Radio Show- https://www.voiceofvashon.org/raise-the-vibePodcast- https://www.buzzsprout.com/958816Facebook- https://www.facebook.com/raisethevibewithlizInstagram- https://www.instagram.com/raisethevibewithliz/*** Support the show! https://www.buzzsprout.com/958816/supporthttps://paypal.me/LisbethPeterson?country.x=US&locale.x=en_USJoin The Community!

durée : 00:05:45 - Entendez-vous l'éco ? - par : Anne-Laure Chouin - Le centenaire de la naissance de Marilyn Monroe donne lieu à de multiples événements, qui, aux États-Unis, sont organisés par une société du nom d'Authentic Brands Group. Soixante ans après sa mort, l'icône du cinéma reste très lucrative, et elle n'est pas la seule. - réalisation : Caroline Bennetot, Éric Chaverou, Marie Viennot Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

A pharaoh becomes lightning. A body dissolves into rainbow light. Five civilizations. No contact. One process. They didn't carve a machine. They carved a map of you.Where Are We Swerving?Are the ancient stargates carved into Egyptian temples religious mythology — or did someone leave step-by-step instructions that we've been misreading for 4,000 years?I deep dive into investigative mythologist William Henry's three-decade investigation, which started with a single ceiling carving at Dendera — a shape that has no business existing in a building completed millennia before Einstein was born.I investigate what happens when you reassemble a biblical artifact everyone assumed was complete, because the components no one accounts for change what the device looks like — and what it was for.Topics (among others):The Hieroglyph at Saqqara: Sixty feet beneath a ruined pyramid, the oldest sacred writings in Egypt contain a glyph that matches a physics diagram that wouldn't be drawn for another 4,000 years.The Missing Inventory: For 2,500 years, everyone chased the Ark of the Covenant's golden box — but the Bible lists components no one talks about, and the fully assembled shape resembles something that shouldn't be possible in the ancient world.The Procedure: A mathematician argued the Egyptians didn't just depict transformation — they recorded a protocol, and all three of its elements converge in a single artifact most tourists walk right past in the Cairo Museum.The Pattern Across Oceans: Four civilizations with no known contact — Egypt, Sumer, the Maya, Tibet — describe the same bodily transformation using nearly identical symbols.➡️ Listen on Patreon Today: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.patreon.com/theswervepodcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Exclusive episode only on Patreon in The Producer Vault.What is The Producer Vault? Double the episodes. Your name on the show. Access to everything.2 exclusive deep dives every monthUnlock “The File Room” — full archive accessUnlock “The Producer Vault” — episodes only Producers ever hearYour name in the credits — read on every main public episodeEarly access — episodes drop Sunday (public waits until Wednesday)Ad-free listeningShoutout on the podcastWelcome kit — holographic sticker pack shipped to your door (one-time)How It Works: You get a private RSS link when you join Patreon. Drop it into Apple Podcasts, Spotify, Overcast—wherever you already listen. No extra app. No logging in. Episodes just appear.Most of your day is dead time. Commutes, work, errands, chores, tasks that don't need your full attention. The Producer Vault fills all of it with something you actually want to hear.Make dead time the best part of your day.$10 a month. Cancel anytime.I'll see you in The Producer Vault!#AncientMystery #AncientMysteries #Stargates #Eygpt #ConspiracyTheories

The gravitational two-body problem has been fundamental to physics since Newton's time. With the advent of gravitational wave astronomy and the anticipated third generation of gravitational wave detectors in the 2030s, there is an increasing need for high-precision predictions from Einstein's theory of gravity regarding the encounters of black holes and neutron stars in our universe. Fascinatingly, perturbative quantum field theory methods developed for high-precision predictions of elementary particle scattering at the LHC have proven remarkably efficient for this classical physics problem. This unexpected connection has led to inspiring synergies between collider and gravitational wave physics. In my talk, I will present our approach using a worldline quantum field theory inspired by string theory, which has emerged as the most efficient tool for quantifying the scattering of spinning black holes. We have achieved highest-precision perturbative results for the scattering angle, radiated energy, and recoil of such black hole encounters at the fifth order in Newton's gravitational coupling G. Our four-loop calculations have revealed a new class of mathematical functions related to Calabi-Yau manifolds, previously studied only in mathematics and string theory compactifications, appearing for the first time in a physical context: The radiated energy in gravitational waves at NNNNLO perturbation theory.

Apple's Worldwide Developer Conference (WWDC) had 1 theme… SOS: Save Our Siri.Forget SpaceX… NASA's latest deal is with the luxury design house, Prada.The Carolina Hurricanes are in the Stanley Cup Finals… Thanks to Eric Tulsky, the mathematician who quit Apple.Plus, the biggest user of self-driving trucks? It's Pepsi… Say hello to “Self-Driving Doritos.”$PRDSY $PEP $AAPLGrab your Tickets to the IPO Tour: Our In-Person OfferingSan Francisco 9/23: https://www.ticketmaster.com/event/1C0064AFB5F688BDBoston 10/14: https://tickets.citywinery.com/event/tboy-the-ipo-tour-in-person-offering-8cdhupSeattle 11/4 (21+): https://www.axs.com/events/1446394/the-best-one-yet-ticketsNEWSLETTER:https://tboypod.com/newsletter OUR 2ND SHOW:Want more business storytelling from us? Check our weekly deepdive show, The Best Idea Yet: The untold origin story of the products you're obsessed with. Listen for free to The Best Idea Yet: https://wondery.com/links/the-best-idea-yet/NEW LISTENERSFill out our 2 minute survey: https://qualtricsxm88y5r986q.qualtrics.com/jfe/form/SV_dp1FDYiJgt6lHy6GET ON THE POD: Submit a shoutout or fact: https://tboypod.com/shoutouts SOCIALS:Instagram: https://www.instagram.com/tboypod TikTok: https://www.tiktok.com/@tboypodYouTube: https://www.youtube.com/@tboypod Linkedin (Nick): https://www.linkedin.com/in/nicolas-martell/Linkedin (Jack): https://www.linkedin.com/in/jack-crivici-kramer/Anything else: https://tboypod.com/ About Us: The daily pop-biz news show making today's top stories your business. Formerly known as Robinhood Snacks, The Best One Yet is hosted by Jack Crivici-Kramer & Nick Martell. Hosted on Acast. See acast.com/privacy for more information.

O Ministério Público Federal (MPF) ajuizou uma ação civil pública exigindo que a Sociedade Beneficente Israelita Brasileira Albert Einstein passe a aplicar o sistema de cotas raciais em seus processos seletivos para programas de residência médica.A demanda é fundamentada nos incentivos e parcerias públicas mantidos pela instituição.Papo Antagonista é o programa que explica e debate os principais acontecimentos do dia com análises críticas e aprofundadas sobre a política brasileira e seus bastidores.       O programa traz contexto e opinião sobre os temas mais quentes da atualidade.       Com foco em jornalismo, eleições e debate, é um espaço essencial para quem busca informação de qualidade.       Ao vivo de segunda a sexta-feira às 18h no nosso canal no Youtube.   https://www.youtube.com/@OAntagonista  Apoie o jornalismo independente. Assine O Antagonista e Crusoé com 10% via Pix ou Google Pay:  https://assine.oantagonista.com.br/  Siga O Antagonista no X:  https://x.com/o_antagonista   Acompanhe O Antagonista no canal do WhatsApp. Boletins diários, conteúdos exclusivos em vídeo e muito mais.  https://whatsapp.com/channel/0029Va2SurQHLHQbI5yJN344  Leia mais em www.oantagonista.com.br | www.crusoe.com.br #MPF #HospitalAlbertEinstein #CotasNaMedicina #ResidenciaMedica #JusticaFederal #DireitoEsaude #MedicinaBrasil #AcaoDireta #DebateSobreCotas #PodcastDeNoticias #Atualidades #Noticias #SaudeEPolitica #EmAlta #Tendencias #Debate #Internet #Brasil #PoliticasAfirmativas

What if the answers you're searching for arrived long before you knew how to understand them? In this conversation, I sit down with Kip Baldwin, a filmmaker, producer, writer, and founder of the Just Love movement. Kip shares the extraordinary awakening he experienced at age 12 and how it set him on a lifelong path of exploring consciousness, love, spirituality, and human connection. From the music industry and sustainable agriculture to television production, ethical AI, and overcoming a traumatic brain injury, Kip's journey has been anything but ordinary. As we talk, Kip reflects on why fear has become such a powerful force in society, how love can transform the way we see ourselves and others, and why he believes lasting change starts with a shift in consciousness. You will hear stories of resilience, curiosity, and purpose, along with a vision for creating a better future for generations to come. I believe you will find this conversation thought-provoking, challenging, and full of hope. Highlights: 01:45 - How a childhood acting career sparked a lifelong passion for media and communication. 07:08 - Why confidence without self-awareness can become a liability. 16:32 - Lessons from the Kellogg School of Management that still shape business decisions today. 21:58 - Why listening beats talking in business, leadership, and life. 35:08 - How strong brands grow through awareness, not just loyalty programs. 01:05:02 - The three traits Zarko looks for when mentoring future leaders. About the Guest: Kip Baldwin knows his purpose for Being is to share all that LOVE is through his many solutions driven projects; using media in all its forms to help awaken individuals, and by proxy the collective, to the LOVE Paradigm emerging. He feels that in order for a new chapter of our story to be conceived for humanity, a mass imagining of our limitless potential is what is needed to bring about an age of compassion, empathy, collaboration, and oneness.  Kip was born in 1965 to counterculture parents - in the midst of the maelstrom that was the decade of the sixties, in fact 1965 was the first year that scientists warned us about climate change - in Vancouver, Washington. His earliest years were spent on a farm where his grandparents raised thoroughbred horses. During this period grew in him a deep, abiding LOVE and respect for nature and all living things. It was around the age of twelve his life would transform forever, as he had an out of body experience that took him beyond the edge of Universe, even Space and Time, and face to face with the unknowable of Infinity. This experience became the foundation for his constant seeking since. Due to that experience Kip felt he must explore the world beyond the small town confines of Camas, WA where he grew up. His first attempt to break free was to do a brief stint in the Navy, where he was going to pursue a career as an electric technician, but because of a hereditary bleeding disorder he was given a medical discharge. However, a military career for him was clearly never really in the cards anyway. Although he was always grateful for the insight it gave him into the inner workings of our country, as he witnessed first the how the poor are literally cannon fodder for corporations, under the guise of them being heroes and patriots. Following his discharge, he returned briefly to the limits of his hometown, before moving to the San Francisco Bay Area in 1985 to pursue his passion for music and performing. He often jokes that he was looking for the San Francisco of the Haight/Ashbury, Peace and LOVE days, but arrived twenty years too late. What he found instead was the 80s hair metal band scene, whose songs that focused on partying, sex, and drugs were not compatible with his lyrics about awakening awareness and addressing the need for personal and societal change. In the late 90s, after becoming disillusioned by his beloved music industry - and always seeking solutions for the myriad of challenges facing humanity - he shifted his focus to local and sustainable foods. While this was certainly a worthwhile pursuit, it did little to fulfill his need to share LOVE'S Truth and create a collective shift in consciousness. But what it did do was make him aware that it was only going to be through the use of mass media that his message of LOVE could reach a large enough audience to affect real lasting change. This found him again heeding the call of the entertainment industry, first as an actor, then writer, and ultimately as a producer, with some success co-creating the influential cannabis series Weed Country for the Discovery Network (focusing on the countless benefits humanity can derive from marijuana, as well as our profound historical connection to the plant), co-founding the United Filmmakers Association, and starting the Just LOVE Movement. Ultimately, this led him to co-founding S.O.U.L. Documentary with creative partner and Soul Twin, Evan Hirsch who shares his passion, purpose and mission to heal humanity by embracing our innate oneness, which they both understand can only be achieved by accepting and grounding ourselves in the Reality of LOVE We Are. Ways to connect with Kip: Facebook:  Just LOVE page: https://www.facebook.com/kipbaldwinjustlove Main page: https://www.facebook.com/kip.baldwin/ UFA: https://www.facebook.com/groups/Unifilmmakers LinkedIn:  https://www.linkedin.com/in/kip-baldwin-975a3514/ Instagram: https://www.instagram.com/kipbaldwin?igsh=NTc4MTIwNjQ2YQ%3D%3D&utm_source=qr YouTube: Kip Baldwin: https://youtube.com/@thekiprowdy?si=LckMuhec40lWAicF Just LOVE: https://youtube.com/@justlove6463?si=QW1g4D2dlaHmJk8B S.O.U.L. Documentary: https://youtube.com/@souldocumentary?si=4HOwlV-pjFN6guYy Soul Twin Messiah: https://youtube.com/@soultwinmessiah?si=7ctLlmqjeOczkjO_ Additional must listen:  Comfort You Song: https://youtu.be/Mi8D3AoDfRQ?si=y8RzIQPXP5ALJth1 A World Worth Imagining: https://youtu.be/Cx28t6_SGic?si=o4lWs7po3TBKx_3A Invitation. To Action: https://youtu.be/B8jUOUVCvJI?si=l4Pr7vWNDsnXX4wh AI work: www.luminaLOVE.LOVE About the Host: Michael Hingson is a New York Times best-selling author, international lecturer, and Chief Vision Officer for accessiBe. Michael, blind since birth, survived the 9/11 attacks with the help of his guide dog Roselle. This story is the subject of his best-selling book, Thunder Dog. Michael gives over 100 presentations around the world each year speaking to influential groups such as Exxon Mobile, AT&T, Federal Express, Scripps College, Rutgers University, Children's Hospital, and the American Red Cross just to name a few. He is Ambassador for the National Braille Literacy Campaign for the National Federation of the Blind and also serves as Ambassador for the American Humane Association's 2012 Hero Dog Awards. https://michaelhingson.com https://www.facebook.com/michael.hingson.author.speaker/ https://twitter.com/mhingson https://www.youtube.com/user/mhingson https://www.linkedin.com/in/michaelhingson/ accessiBe Links https://accessibe.com/ https://www.youtube.com/c/accessiBe https://www.linkedin.com/company/accessibe/mycompany/ https://www.facebook.com/accessibe/ Thanks for listening! Thanks so much for listening to our podcast! If you enjoyed this episode and think that others could benefit from listening, please share it using the social media buttons on this page. Do you have some feedback or questions about this episode? Leave a comment in the section below! Subscribe to the podcast If you would like to get automatic updates of new podcast episodes, you can subscribe to the podcast on Apple Podcasts or Stitcher. You can subscribe in your favorite podcast app. You can also support our podcast through our tip jar https://tips.pinecast.com/jar/unstoppable-mindset . Leave us an Apple Podcasts review Ratings and reviews from our listeners are extremely valuable to us and greatly appreciated. They help our podcast rank higher on Apple Podcasts, which exposes our show to more awesome listeners like you. If you have a minute, please leave an honest review on Apple Podcasts. Transcription Notes: Michael Hingson  00:03 One of the biggest things holding you back isn't what's in front of you, but rather what you believe. Welcome to Unstoppable Mindset, where inclusion, diversity, and the unexpected meet. I'm your host, Michael Hingson, speaker, author, and advocate for inclusion and possibilities. This podcast explores how the beliefs we carry shape the way we live, lead, and connect with others. Each week, I talk with people who challenge assumptions, face adversity head on, and show what's possible when we choose curiosity over fear. Together we focus on mindset, resilience, and the small shifts that lead to meaningful change. Let's get started. Hi everyone, I am your host Mike Hingson, and you are listening and or watching Unstoppable Mindset. We're really glad that you're here with us today. Our guest, the person I get the honor of chatting with for the next hour or so, is Kip Baldwin, who will talk a lot about love. He will talk a lot about a number of different things, he's been a director, he's been a producer, an actor. He has been published, although he hasn't published a book yet, but he's published poetry, and I'm sure he's going to tell us about that, and I don't want to give it away, so I won't. Anyway, Kip, welcome to Unstoppable Mindset. We're glad you're Kip Baldwin  01:40 here. Oh, thank you so much for having me, Michael. I look forward to having this conversation and sharing my story. Michael Hingson  01:47 Well, tell us a little bit about you, kind of. Let's start with the early Kip, growing up and all that, because I know you had some things along the way that were relevant and ought to be mentioned. So, why don't you tell us about the early Kip, and we'll go from there. Speaker 1  02:00 I was. I grew up in Washington State, little town called Camas. Although my earliest years were spent in a town called Battleground, Washington, and my family, we raised horses, Thoroughbred race horses. We raised at Portland Meadows, and so I'm kind of a farm boy at heart, at least that's how I grew up, but I had an experience when I was 12 that was definitely not your typical farm boy experience, I guess. I had gone up to Seattle, and this was maybe 78 to see a Seahawks game with the Raiders of my dad and dad, I had a good day, which wasn't always the case, and got home, and it was a, you know, five and a half hour round trip for kids, 12 year olds, a big time, and so I went to bed, and I promptly left my body, and now keep in mind I had never done any drugs. Out of body experiences, a household projection was not something that we talked about about the old farm around the farmhouse dinner table, and I floated over my bedroom. My awareness hovered over my body, and I remember very vividly you don't forget. I looked at my body and went, "I'm not in there. And then that immediately I left my house, I left the planet, I left the solar system, I let the galaxy, I let the universe, and the whole time all I can describe was kind of a presence, not a voice or anything, but just, are you taking all of this in? And sometimes words can't convey something so expansive and grand, and so I was taking in black holes and quasars and nebulas, and just flying through the, you know, time didn't really exist, but I was, I was traveling across the universe, and eventually I got outside the universe, and my awareness was turned in, and I could see how everything was connected, and how the universe itself was finite, and but that everything had a place, there was no less or greater than that, everything had a specific role, from the smallest particle to, you know, the largest star, and then my awareness was turned out to the blackness of infinity, and that you know you don't know at 12, you're just like, "Oh, this is happening, and I'm what's happening, and I'm taking it in, and what I didn't know is that would become my point of seeking that really became the rest of my life. Life, I think, had I been born in India, like say Ramana Maharishi, who had what I didn't realize until later, there's a name for what happened to me, and it's called a spontaneous awakening. My life would have probably been much different, but we don't live in a society that that really honors things like that, so it was a lot of me going on a journey of discovery and a weight and continual awakening until now, and it's an ongoing process, but that's where it really began with me being confronted with the fact that there there can't be a beginning or ending to anything, and the thought experiments that can't, that come out of that, and the way it opens your consciousness, I'm ever grateful for, although at the time it, it made me for a long time feel very apart, and it wasn't until I met with Dr. Dr. Dean Radin up at Noetic Sciences, and I told him my story, and he looked at me, and he went, "You go, that's not a usual experience, he said, "That's a mystical experience, and I was in my probably late 40s, maybe 50 at that time, and that was the first time in my life that someone had had said, 'Hey, what you, what you had was a really phenomenal experience, and I'm very grateful for him for saying that to me, because for most of my life, I'm running around talking about these profound things with people that I thought were incredibly important to share, and they didn't seem very important to people, and it wasn't until then that it hit me that it wasn't that they were important, that it was that they, they didn't really understand what I was talking about. Michael Hingson  07:03 Well, and in our society, as you point out, it's not something that is generally appreciated, and and people who have had those experiences or talk about them are generally looked down upon or frowned upon, and you know that's that's fine, but it doesn't change the fact, and so it must have been hard, especially at first, for you to talk about that. Speaker 1  07:29 You know, I was so excited at first, I was excited to share it with my family, and and it happened a couple more times, and it was so overwhelming that literally I would get to a point where my head, my physical being couldn't handle it anymore, and I would get up and vomit. It was that's how, how intense it was, like I just, I couldn't take in anymore. And so, at first, I was really excited to share it, because it was beyond wondrous. It was, it was truth. It was reality, and I, and on some level, I knew that instinctually. But then, when enough people sort of ignore you or act like something's unimportant, you stop talking about Michael Hingson  08:15 it. Yeah, Speaker 1  08:15 I never stopped writing about it. I never stopped experiencing it, and I didn't even really stop talking about it once I moved to California for the music business in 1985 I, you know, then I thought, wow, I mean, being a group of creatives and there's going to be other people that will understand what I'm talking about, but in the 80s music environment it really wasn't what people were, were talking or thinking about, and I was kind of in the same way, and again it wasn't until years later that I look back and I realized all this time I spent up late at night partying with people and stuff, and telling them about infinity, and, and they look, they, they must have been looking at me like I'm a complete idiot, because they really only cared about, you know, getting high or having sex, and I'm trying to have this profound conversation. Michael Hingson  09:16 So, when your family, when you told your family, how did they react? Speaker 1  09:20 They still don't understand it to this day. It just, oh, that's nice, you know. It actually, there were points in my life where it caused conflict with, especially my father, because when I would say none of this is real, he, he always considered him, and still to this day considers himself quite science physics buff, it wasn't something he was willing to accept, and, and even really have a reasonable conversation about. I would say that the things that got me through all these years was, you know, the universe. There's love, God, Brahmin, whatever you want to call it, it gives you what you need, and what it gave me throughout the years, and still to this day, is voices that made me realize I wasn't crazy, that I knew something really special. Probably the first thing, the first one I remember, like, that was Joseph Campbell being interviewed by Bill Moyers, and somehow I knew everything that Joseph Campbell was talking about, and I'm like, How can I possibly know these things? How can I possibly understand these things of this really brilliant, just beautiful soul? And throughout the years, it's been those touch those moments of going, oh, it hasn't been where I've heard someone go, wow, that's helped me awaken, it's been something that's helped me not feel insane and realize that the things that I'm sharing have been shared for 1000s of years, and by many, many minds and beings much greater than myself, and that that really probably kept me from losing my mind. Michael Hingson  11:10 So, you had this experience happen to you at 12. What did you then specifically do? I mean, not so much talking to people, but what did it do for you, as far as schooling, and what you did with your life? Speaker 1  11:27 I would.. it made me very.. in all honesty, it made school seem really trivial to me. It was kind of boring. I started writing a lot. In fact, something I wrote when I was 17 was called Life and Death, and it went: Life is just a symptom of certain death, crying and laughing until our last breath. Everything dies in true infinity. Then the mountains crumble into the sea, stars full from the night sky hit the earth, and then they die, lost in time. I don't know who I am. Am I a god or just a mortal man? Time can't change what I have found. Still, I am changed and bound, bound by the fears and bound by lies. Even now, the tears fill my eyes, gasping for every breath as I head for a certain death, clouds now pass overhead, and I realize how things are now that I am dead. Life is ending, life goes on like the lyrics to an endless song. Life and death, it's all the same. We exist only in our brain, and so there was a lot of that. It pushed me away from I was confirmed Zion Lutheran. I really couldn't stomach religious dogma anymore at that point. Um, just the hypocrisy, you know? Like, I remember I, I was talking to a new pastor we had, and he was informing me that my great grandmother, who is Jehovah's Witness, and these Mormon boys had come around, were trying to teach me about Mormonism, and I was just curious and open, always, and still am to this day. I don't judge. I would say that's another big thing that this gave me, is I don't, I see everything as equal, I don't, I don't judge everything, I don't judge anything as lesser thing greater than I don't judge good and evil in the in the same way that other people do, I see things as flows of negative of energy as we exist in a duality with this illusion, and this is just what we describe as good and you are really just flows of energy between the polarities of the duality, and so it pushed me, definitely, because I, when he said that my great grandmother was going to go to hell, and these Mormon boys were going to go to hell, I looked him in the face, and I just said, but I thought God was love, and that was pretty much the end of my church, Michael Hingson  14:04 my, my wife did, I think, some things in the Lutheran church, which mostly she was a Methodist, and I joined the Methodist church when we got married, and so on, but when she was in, I think this was when she was in high school, maybe in, I guess it was late high school, early college. She met some Mormon people, and one of them said, I guess she was learning about different religions, and so she was learning about Mormonism, and this guy said you're either going to think that this is a total hoax or you're going to just totally believe in it. Well, it wasn't quite that way for her. She did not think it was a hoax, and I agree with her, but there. There are things about the about all religions that tend to make life difficult. The problem with religion is that that people are are what make up the religion, and they all have their own views, and it makes life really tough. I know I participated in a program called the Walk to Emmaus, which is a what's literally called a short course in Christianity, and it's not to bring people to the Christian church, but it's to help create a class of leaders in the Christian church. Anyway, one of the things about the walk to Emmaus is that a number of people give lectures, people who have been involved in church, and then there are the pilgrims, the people who are coming to to learn what everyone has to say, and the lay director of the Walk to Emmaus every time gives a speech, and I was lay director once, and one of the things that is in the manual, or was I assume it still is. It's been a while, but it says that Tolstoy once said the biggest problem with Christianity is that nobody practices it, and there's a lot of truth to that. Speaker 1  16:13 But I think that I think you hit it right on the head that people are involved, like I, and I do want to clarify something, I, I believe very much that that Jesus was a master. Oh, Michael Hingson  16:29 absolutely, yeah, and, Speaker 1  16:31 and, but I also believe that people don't know what happened at the Council of Nicaea and understand how the Bible was actually constructed, not because it was based on Gnostic teachings or even really the teachings of Christ, but it was cobbled together as a means of control. If Caesar saw his soldiers be turning to Christianity when they wanted to find, you know, put together a book that really didn't express Christian truth or the truth of Christ, but a way, a means of controlling people through fear, and so if you, if you notice, all the books in the Bible are male. Well, left out of the Bible was the book of Mary, left out of the Bible, it's the book of Thomas, who, interestingly enough, there's a place in India where they all speak ancient Aramaic, and they worship the Book of Thomas, which there's always been a lot of discussion. Did Jesus go to India and study Buddhism? And because even the Book of Mary, these are very Buddhist beliefs, but anything, because we live in a patriarchal society, anything like the piece to Sophia, the book of Mary, the book of Stackle, all of these were intentionally kept out of the Bible, so it's not, I think it's not so much religion, it's the organ, it's the dogma that comes along with organized religion, which is really about people, you know, men using it to control and manipulate people through fear, Michael Hingson  18:14 all too much, all too often. It's, it's true. Speaker 1  18:18 Yeah, and it's interesting. I was watching last night, and it's funny. This is why, why you always have to be on a constant path of awakening. It never stops. If you think you've reached that pinnacle, or whatever, then they're not just ego. There's always more to know and understand. And I ran across this video on Tara, well, Tara is in Buddhism, basically in every religion that I am aware of, there's always the peace to Sophia, there's always the the story of the divine feminine that in large part is is is not. It was. It's largely been suppressed, and so I was, I was watching this, and it was just so fascinating to me to see how identical what Tara was in Buddhism, which this is what, when Tara, Tara is considered the ultimate goddess in the Buddhist faith. Well, when Tara came to earth in the story, she went to a bunch of, you know, Buddhist monks, and they said, "Oh, you know, they were so impressed by her, and they thought this was a compliment. They said, "Well, we hope you, you can reincarnate as a man, and she said, "No, she She said, I don't see things as male and female, but since nobody else wants to be the feminine, I will play that role. And it was just a profoundly interesting thing to listen to, not just because of the story, but because almost every faith that I'm aware. Of has that story of the divine feminine that has again largely been suppressed and marginalized, Michael Hingson  20:09 well, for you clearly that was a very meaningful experience. What did what did you then do, and I understand how you could imagine that maybe what was being taught in school wasn't quite as, as meaningful as what you had experienced, but you went on, I assume, through high school, and did you go to college? Speaker 1  20:30 I was, I went, I was an electron, I went to the Navy to be an electronic technician, but I had a bleeding disorder called Von Willebrand disease, and I found out after I was in for about a year. Well, you can't be in the Navy with that, because we can't carry with the limited space you have on ships, we can't carry the clotting factor you would need if there's a problem. So that was fairly short-lived. Then I went back to Washington and was working as a dishwasher for a while, then I worked as a male stripper, and, and I was then, which, which, you know, there was something really profound about that experience, because it taught me what women feel like to be objectified, and that's something that has carried me, carried a lesson. I, I find lessons in everything, even things that, wow, you know, what could you possibly learn positive out of having been a male stripper? Well, I learned how women feel, really, to be, you know, not looked at as anything more than an object, and then I really wanted to continue to, you know, pursue music, so a friend of mine, we loaded 65,000 pounds of frozen strawberries onto a semi truck, and like july 3, 1985 and got a ride to San Francisco, a city I'd never been to before. I knew nobody here. We got here, I had 25 cents in my pocket, and I used the 25 cents to call the one friend that I thought I knew that I could get a hold of here in or in in the Bay Area, and it was a wrong number, and so now I'm in a city at the Gray Home Bus Terminal that used to be in downtown San Francisco, we have no food, we have no place to live. We have nothing to, you know, we have nothing, literally. And that's where my journey began. As far as my story, my, my adult life, and my journey in the entertainment industry and the music business, that's how it all started. It started by loading 65,000 pounds of frozen strawberries under semi truck, telling, oh, and the cap around the story is I had worn my contacts for too long and I ripped the corny up both my eyes when I took them out, because I was wearing hard lenses, so I was functionally blind in the city I'd never been to before with patches over my eyes, and being led around by my friend, and luckily we found some very nice people that gave us a place to stay, and then I ended up meeting maybe a week after that, I met my first wife, who was Persian, and we were together for a long time. What was interesting about that is I've been introduced to so many different faiths through the people in my life, and because I haven't judged and tried to learn, like I, I learned through her about Islam, I learned through her about our Torcharianism, and we lived the rock and roll lifestyle for the 16 years we were together. She was a photographer. I wrote for a magazine called BAM. I played in bands. I managed artists like Linda Perry from The Four Non Blonde, or I worked with Linda Perry from Four Non Blondes. I managed Alex Skolnick, who is lead guitar player in Testament, and I did that for a long time until I started getting really disenchanted with music and really started to hate the business and started to hate music because of it, and so I ended up drifting into, I wouldn't say drifting into, I got drawn into visual media, and I started working. I met a guy at a club in San Jose, California, called The Agenda, and we were playing pool, and he was telling me, "Oh, he's the owner of this company called Metropolis Digital, and I was thinking, "My. Speaker 1  24:59 Music and music videos, and yeah, I want to get involved in this, so I started coming up with ideas, and he brought me into their company, because I got to know a lot of people through the music business and booking artists on different shows, like Letterman and Leno, and, and so I got to know how to work through those channels that it opened doors for me to be able to do on-air graphics for the networks, and so I did that until about, in fact, the last major project I did in that industry was with a company called Chaos X AOS out of San Francisco, and we did the 2000 election graphics for ABC nationally, and then I, I, that with the, the, the.com telecom crash of not of 2000 they pulled all of that sort of work in house, and so that business kind of dried up, and I changed my focus to working in local and sustainable foods. Michael Hingson  26:08 What got you to the point where you disliked Music so much? Speaker 1  26:12 The business.. it just.. it wasn't. I came here, and in all honesty, I was looking for the 60s, but I was 20 years too late, only to find out later I was actually 30 years too early, but I was looking for community, I was looking for family, I was looking for that connection, but what existed as far as the music industry then was the 80s hair band stuff, heavy metal was on the rise. It was very misogynistic. It wasn't. It was very competitive. There wasn't, it wasn't collaborative, it wasn't community related at all. And it really turned me off. It wasn't, it wasn't what I had thought being in an artistic community doing artistic endeavors would be about it, became very.. it just.. it just.. it just.. it just made me feel very empty, and that wasn't what I loved about music, and so that Michael Hingson  27:24 would be an issue, Speaker 1  27:25 yeah. It just value wise it was, it was not, you know, you, you got to do a show, and you've got the bands that are coming on after you, you know, playing with your amps, and it was just, it was, it wasn't, it wasn't fun, and it wasn't fulfilling. More importantly, it wasn't fulfilling. It wasn't, and I'm writing about while everyone else is writing about, you know, sex and drugs and all of this. I'm writing about the things that I thought were important. I was writing about the problems I saw in this country, like songs like Shock the System or the chosen few, and, and though that wasn't what people were writing about Michael Hingson  28:06 then, Speaker 1  28:06 and you know, even though the songs were good, and, and I've been told I'm talented, it was, I didn't, I didn't again feel like I fit in, you know, I didn't feel like I'd found my place, and certainly not in that world at that time. If Speaker 2  28:31 you enjoy Unstoppable Mindset and would like to help us continue bringing these conversations to you each week, we've created a way for you to support the show. Your contribution helps us cover production costs and continue sharing stories, insights, and ideas that inspire people to live with purpose and possibility. If supporting the podcast feels right for you, you'll find the link in the show notes. Thank you for being part of the Unstoppable Mindset community. Thank it Michael Hingson  29:04 certainly had to be a rough time all the way around, but then you, you found this person, and you joined their company, as you said earlier, Speaker 1  29:15 right? I started working for Metropolis Digital, and we started doing a lot of on-air graphics, like for TBS. We did their, their original movies. We did a lot of the opening graphics for it, and then I moved on to other companies, and and I, I then started focusing on on local and sustainable foods, and moved into doing stuff where I felt I was doing more, because at the heart of everything I've ever done, it's always been about trying to affect real change in the world, Michael Hingson  29:55 it's Speaker 1  29:55 always been about I could see very clear. Really, it doesn't surprise me where we're at today at all. I saw the problems with the system even at that age, and I give credit to that because of the experience I had with Infinity. It just allowed me to step back and perceive things from a far off perspective that I was looking at humanity in general and how we did things, and I'm just like, this doesn't make any sense. It doesn't make any sense for us to believe we're separate and apart from the very things that give us life from each other. It doesn't make sense from a spiritual perspective. It doesn't make sense from a scientific perspective. Yet, here's the system that we are a part of, and so I've always been very focused on trying to effect real change and find not just point out the problems but actually find solutions, and so that then led me into working in local and sustainable agriculture here in the Bay Area. So Michael Hingson  31:00 tell me more about the whole work that you did with Sustainable Foods. What was that all about? Speaker 1  31:08 Yes, I worked with a company, I was, I had handled all the sales and marketing for Drake's Bay Oysters out of Inverness, California, and Drakes Bay, before it was called Drakes Bay, was Johnson's Oysters, and they were the last oyster cannery in California. The family that owned the farm, they had taken it over from Johnson's. They were the Lenny family, who owned Ranch G across from the steroid, where the oyster farm was. Well, they, against my better advice, they made it a personal ownership thing rather than a California food heritage issue. So, eventually, when their lease came up on the rent, on the farm, the farm went away. Well, at the same time, I created new relationships. A very good friend of mine to this day is a gentleman named Brian Kinney, who is now the West Coast Chief Technology Officer for Hearst, and also the Hearst Family Archivist, but at that point in time he was running Hearst Ranch, which they, they had the Jack Ranch and the Hearst Ranch down around San Simeon. So I was at the forefront of the grass-fed beef movement as well, and we developed a human-grade grass-fed beef pet food about 10 years ahead of its time, which could be the story of my life. I'm always about 10 years ahead of where things actually happen, and I, I did that for about 10 years, and eventually I felt the calling to get back in the entertainment industry, and that led me to acting, and I did the acting mostly because I wanted to learn how things were done, and I very well, if I act in a whole bunch of student projects, or projects in general, and I'm behind the scenes, I'm going to learn, and, and that's exactly what happened. So, my very background led me to being a producer, and I created, you know, one of my most notable accomplishments that created this show called Weed Country for Discovery, which was about the medical marijuana industry here in California, just before legalization. How we got it on air before legalization, I don't know. We were named to the Hollywood Reporter top 25 heat list. We got some really great information out about CBD and helping with childhood epilepsy. The bad part of that was it was a reality television show, and I didn't know anything about reality television, so when I'm here in reality, I'm thinking documentary. Well, that couldn't be farther from the truth. And reality television has truly been a blight on on this country in particular, and probably the world in general. Michael Hingson  34:16 Yeah, I just gonna say not nearly as real as people think it is. No, no, I think I think probably this is just my opinion. The closest thing to so-called reality TV is the show Dancing with the Stars, because they're actually dancing all these other shows, and it's all sort of really scripted, but the people are actually dancing, which is kind of cool, Speaker 1  34:41 right? Michael Hingson  34:41 Even though I don't see it, I appreciate it. Speaker 1  34:45 Yeah, but even, even with shows like that, there's a lot of gin-up drama. There is behind the scenes stuff that's the worst part of things. Yes, they're like with our show, yes, people were really, you know, there's really stuff going on with can. Of this world that was really important, but what reality television does is it, it creates artificial drama. It does things to manipulate the characters in the show to make them look how they want, and they know, and people in general, my experience is that people, once you put a camera on them, they will do, they would do things to be in front of the camera that they would never do, even for more money, Michael Hingson  35:27 right, Speaker 1  35:28 in their regular lives. Michael Hingson  35:30 Well, and I think there is, there's a lot of truth to that. And the whole thing, as you said, as far as reality TV, we're not giving people a true picture of reality with most of any of that anyway, which is unfortunate. I think I mentioned I'm a fan of old radio and television, and so on. And one of the shows that I've watched a fair amount is The Old Ridge. Well, it's the second time they were on, but Dragnet with Harry Morgan and, of course Jack Webb as Joe Friday, and they did a lot of shows talking about drugs and marijuana and all that, and how bad it is, and it's kind of interesting because what we're seeing today is that in reality the medical aspects of marijuana or cannabis and CBD oil, and so there's there's true relevance there, which is something that they didn't know or appreciate in the late 60s. Speaker 1  36:31 Well, but the thing that our history with the cannabis plant goes back 50,000 years to Burger Banks, China, it's been, and if we take all of the medicinal recreational uses out of it, it is the most one of the most versatile plants that we have. It was used, I mean, our money was made out of hemp. Hemp is cannabis sativa. Dollar bills are made out of hemp. It was used for fuel. It was used for building. Henry Ford built an entire car out of hemp in 1942 which you can go see the video of on YouTube, and they're beating on it with knacks. The plastic resin they made out of it was 40 times stronger than steel. It ran on hemp fuel, a byproduct of which was water. It also, in 1931 the Hearst family, which was interesting, they ended up working with them, bought and sequestered the plans for a decorification machine that made it easier to process hemp than cotton kids, it's a much more durable fiber. In 1938 covered Popular Mechanics, they called him the billion dollar crop, saying you could make 25,000 different items out of everything from fine linens to dynamite, and that was really what what what, why the prohibition against the plant started. Why they did you know shows like Reefer Madness or create films like Reefer Madness to create this hysteria around, at best, an innocuous plant in comparison to soulmate tobacco, in comparison to alcohol, even if people did want to use it. It's, it's, it's relatively harmless by comparison, or just in general, and actually very beneficial. You know, I have a traumatic brain injury, and I think without it, I probably wouldn't, I probably wouldn't eat very much. I probably wouldn't sleep right, I barely sleep as it is, and sleep I do get is because of cannabis, but beyond my point, and I always try to make this clear to people, is like up until even the prohibition against the plant actually started with the Catholic Church, with the Pope Innocent, who until the 1400s cannabis was in the anointing oils. Cannabis was grown by monks, cannabis was grown by nuns, and then in this pope decreed it the devil's weed, and they, you know, banned it. So it's, it had, and there, and why, and you'd say, well, why did they do that? Well, they did that because at that time in the 1400s you were having opium addiction on the rise, you were having, you know, much, much more alcohol use. Well, these are extremely addictive substances, and much more easy to manipulate and control people than it is with cannabis, which in general creates.. I wish I could remember the quote exactly, but Carl Sagan said, you know, why we have a prohibition on a plant that you know creates good feelings amongst people and unites people is in this, you know. A really crazy world is, is, is madness, but it all comes back to money, and it all comes back to who's profiting. So, why did they create the probation? Well, the hearse, the Rockefellers, and the DuPonts, they saw how hemp would affect each of their industries. We wouldn't need oil if we'd grown hemp and use that as fuel, in fact, it was the Rockefellers who went to Henry Ford and said, "If you take this car to market, we'll crush you. And this was Henry Ford at the height of his power, DuPont chemicals that were.. we wouldn't have needed.. we wouldn't have put like this.. we would not have the planet, the environmental devastation we do now. How do we use this, as Henry Ford said? Why are we digging up, and Henry Ford was certainly no saint, but he was right on this. Why are we digging up our minerals? Why are we cutting down our forests when we can do all the same things with this infinitely renewable resource? This is a part of the canvas story that still is largely not discussed openly enough. Michael Hingson  41:08 Yeah, I think there's a big difference between the story you're telling and the kind of uses you're talking about, and smoking it, and so on, and I, I think we put way too many funny things in our bodies, anyway, right? I think that that isn't this isn't a positive thing, but you're right, we, we've used so many things to create so many fears, it is, it is something that is all around us. Fear is all around us, and the problem is we let it overwhelm us. I wrote Live Like a Guide Dog that got published last year because when I worked in the World Trade Center, I was able to focus when I escaped, and I was able to do that because I had developed a mindset that said, you know what to do in this kind of an emergency, even though never expected it to happen, but the problem is that most people don't learn how they can turn fear around, and rather than letting it overwhelm or blind them, as I would put it, they can use it as a very powerful tool to help them stay focused, which is much more important. Speaker 1  42:23 Yep, I agree with that 100% I think, and then that you hit it right on the head. Fear is a very powerful tool. It's necessary. No, don't touch the burning stove. It can be a cautionary tool of saying, hey, don't go down this path, don't do this. It's bad when fear becomes the foundation for your entire culture, as it is now. Michael Hingson  42:51 Yeah, and and it is so unfortunate because don't touch the burning stove doesn't mean don't be afraid of the stove. It rather means there's a consequence for doing a particular thing, which is touching something that is that hot. But you shouldn't create an environment of fear around it. You should create an environment of understanding, which is much more important. Yeah, it's Speaker 1  43:20 like it'd be, it'd be very silly if we went, oh my god, it's like the stove gets hot, so I'm never going to use a stove. My Michael Hingson  43:29 wife was in a wheelchair her whole life, and the one thing I will say with our modern world is we always had electric appliances because she was always concerned about if using a gas stove, having to reach over one burner, perhaps it had something on it to get to something else with the idea of possibly material igniting or something like that, and I appreciate that, and you take advantage of the tools that you have available, but I think that it is so very important to recognize that we need to not live our lives in fear, and it's true that, like, 95% of all the things that we fear will never come to pass, and most all of it we have no control over anyway. So, why do we fear them rather than recognizing what we really need to do is to just focus on the things over which we truly have control. Speaker 1  44:25 Yes, and I think even the idea of control from my perspective is something that is overrated. It's like the most important thing, if you want to have control, it's exactly what we're talking about, it's when you choose to live from the foundation of love, as opposed to fear. So, no matter what happens to me in my life, and no matter how hard, how challenging it is, I'm going to come from a place of love, and right now. Don't most of us live exactly the opposite. No matter what happens to them in their lives, they're coming from a place of fear. Michael Hingson  45:06 Yeah, and that's Speaker 1  45:08 not healthy. Michael Hingson  45:09 And nowadays we're also living in an environment where we're even afraid to talk to other people and voice opinions, because well, that's not what I think. And so you're wrong, and we don't, we don't respect. Tell me about your just love movement. Speaker 1  45:25 Well, you know, I, I had coming out of the music business and everything, I was, I was literally killing myself drinking, I mean, literally, like, I lost half my liver function, and I was going to die, and, but I wasn't afraid to die. I was.. I realized that if I didn't find a way to feel fulfilled and feel that I was. I had a purpose in the story that I needed to find a quicker way out. I didn't get in any, like, car accidents, I wasn't arrested, nothing. I was just killing myself, and it just got so bad that literally my leg stopped working. That's how, how, how much damage I'd done to myself, and, and so, coming out of that, I made the decision. I wrote down a list of things I was going to do, and one of those things is I was going to start writing every single day, and I, through a variety of different sources, you know, I did that experience with infinity became synonymous with love to me, and then I had an experience where I, I, I started a filmmaking organization called the United Filmmakers Association, and it was basically the philosophy of it was creatives helping creatives create, and was global. We still to this day have chapters 27 different countries, about 30,000 35,000 members total. And I walked into a filmmaking event that we were hosting, and there was about 100 people there, and I realized I was in love with everyone in the room, and it was, it was so like that love, like just when you fall in love, and you're like, you want, you can't imagine not talking to that person at that next minute, and I realized in that moment that this is not only how we can feel about everyone and everything, but how we're really supposed to feel about everyone and everything, and so I came up with the concept of just love, which is, is a very.. it, those are very heavy words to put together, just love. It has so many layers of meaning to it, and so I thought, wow, if we could just love, and from that I I've written every day and shared through social media for 12 years now something having to do with love and what I do is I combine it with other wisdom teachers throughout history who've been sharing the same information and the things I write are literally downloads. They'll come to me in the silence every day, and I haven't missed a day - head injury, sickness, whatever. I haven't missed a day of posting in 12 years about something having to do with love, and Speaker 3  48:37 then Speaker 1  48:37 accompanying posts from other people, far, you know, other beings far more advanced than I am to show that what I'm sharing isn't new. It's been shared forever. It's foundational to what we are. Like love has been so marginalized and trivialized that we, we forget that, like, I, you know, the experience I had with the minister when I was, you know, younger, and I said, well, I thought God was love. I still to this day believe God is love, and God, and we are God. Michael Hingson  49:11 Yeah. Tell me about you. Something you mentioned, you had a traumatic brain injury Speaker 1  49:17 10 years ago. I was, I was in a, I was in, in between projects, so I was driving Uber, and I, a guy, an Uber driver, ran a stop sign in San Francisco and T-boned me, and my head took the brunt of the impact, and I started having really severe neurological problems, severe stabbing pains in my head, my teeth were hurting, I any sort of exertion would leave me just absolutely drained, and so for about three years I was, I was being seen at UCSF, and we never got to the bottom of it, so I was recommended. Um, to a neurosurgeon at Sutter by a counselor I was seen, and I walked in, and within 10 minutes he said, 'Oh, you have trigeminal neuralgian and brain stem damage, and we can do a microvascular decompression, and you're going to be all better. And at that point in time, I was in the middle of getting ready to release a film called A World Worth Imagining, which was about a gentleman named Jacque Fresco, who is considered the Leonardo da Vinci of our time. He founded something called the Venus Project, and we went to his compound in 2017 and he was 101 He was actually contemporary of Einstein. He knew Einstein, brilliant inventor, but at his core, he knew he was a social engineer, and he knew that we had to address our programming if we were ever going to change what was happening in the world and ever be able to avail ourselves of the solutions that he designed of a new economic model called a resource-based economy, because the reality of it is, until we stop self-wounding, there's not enough band aids for the guy that keeps hitting himself in the head the hammer, so we have solutions to all of our problems, but we create problems more quickly than any solution could ever fix, so I was getting ready to release that film, and wow, this sounded like a miracle. I'm going to have this surgery, and I'm going to be all better. Well, it, I had the surgery September 20, 2019 I, it didn't make me better, it made me worse, and it turned out that the surgery was a misdiagnosis, and that they botched the surgery, so I have Teflon implants in my at the base of my skull, inside my brain, that are now constantly agitating my brain stem, along with a titanium plug that is placed right at the junction point to all the major nerves in my head, so they can't undo it, and there's really no medication that helps, and so it's.. it's.. I wouldn't wish it on anyone else. I'm.. I guess I'm.. I'm very fortunate I have the tools I do to manage it, because they also, they call what I'm dealing with the suicide disease, because a lot of people who have it end up killing themselves. The kicker on the whole story is the guy that did my surgery is Elon Musk, partner Neherlich, and so coming soon I'm going to, I unfortunately, I was in two more car accidents at the end of last year that made everything much worse, neither of them were my fault, and once I get through these, these car accidents I'm dealing with, I'm going to go public with my story, because so I mean, in a much bigger, you know, a focused way, because there's so many people signing up for Neuralink, like it's the new iPhone. I have nothing against technology, if it can help you, if you're a paraplegic, and or you have some something that this can fix, great, but two and one, the people, the human test subjects they've tried this on are having tremendous difficulties, and so I want to let people know it's like I wouldn't wish what I'm dealing with on anybody, and for you to allow someone to try to implant something in your brain just because you want to be a cyborg human being, and you're looking at the new iPhone is a really stupid thing to do, and that these people don't. We've given people in technology again. I'm not against technology at all, but I think we've also allowed ourselves to believe that these people who write code and create technology are are gods, and they're not. They're it's just a new way of sharing information and computing things. Speaker 1  54:14 It's, it's, you know, it's just another advancement from the printing press to the radio to tell to television, from the calculator to the computer, and now we're where we're at, and we've allowed ourselves to believe that these people have created an alternative reality, and they have it. Everything that they do runs off the same real world in resources. So, I, I really want to help the mill, because literally millions of people are signed up and ready to have this stuff implanted into their brain and I think it will be a disaster for humanity. Michael Hingson  54:49 I hear what you're saying, and I'm not convinced that a lot of that is really sensible to do either. I think there are tools and there are. There are things certainly that can help people, but I have yet to see that any of this is going to lead to such a tremendous paradigm shift that all of it is going to be all that great for humanity as a whole. I'm not convinced of that at all. Speaker 1  55:17 It could be, but the problem is, is like any other tool, it's how we use it. Social media is an inherently bad thing. It's in here, it's bad because of how we're using it. Sure, because we're using it to divide people and share misinformation, where it could be an incredibly powerful tool for communication, but that's not how we're using it. Same thing with AI. AI could be a tremendously powerful partner in addressing pretty much all of our problems, and I mean, and at the core of, like, Jock's work was the idea that AI basically would manage all the world's resources and share them with equanimity, because we don't have a resource shortage problem, we have a resource sharing problem, but that's not how we're using AI. We're using AI to create fake girlfriends and boyfriends and only fan models, and and take away people's jobs, and and that's not AI's fault. That's the people who control AI's fault, and they want people to be afraid of AI, but again, it's, it's just a tool that's being misused. Michael Hingson  56:24 Well, like, like so many, and, and I hear exactly what you're saying. Tell me about S O U L Speaker 1  56:33 Sold, Soul documentary is really interesting, because the day I got in my car accident was the day I was supposed to meet my partner Evan Hirsch, who had wanted at the time he was looking for a producer to help him do a series on Bernie Sanders and teaching Bernie to not be as angry and come across more from a place of love, and he wanted to follow the campaign around. Well, by the time we got it pulled together, Bernie was out of the campaign, and so we started talking about, well, do we want to do anything together. So we then set about something called Soul Documentary, and originally it stood for Summer of Unconditional Love, because we were covering all of the events for the 50th anniversary of Summer of Love, which was in 2017 So our goal was to find what we called solutionaries, people like Jock, and interview them, and then share also our own understandings of things through hundreds and hundreds of videos that we did over the course of eight years, as well as recording three albums under the name of Soul Twin Messiah, which all were about the same things we were doing. Our films about all founded in love, all about love. Every song contained love in it, and our whole purpose was just to show people we do have solutions to our problems, and to talk about how we have to have a shift in consciousness, and we have to have a new system if we are going to change anything. It's like what Einstein said, to expect things to be different when you keep doing the same thing over and over again is insanity, and I think we see, we see that we live in an insane, a completely insane world right now. I mean, the things that I see happening, and how we've let it sort of creep in, like the things that we've normalized in the past 10 years, like we literally have people that are cheering, murdering people on it's, it's, it's hard for me to, to even fathom, and I think it's hard for most people, and I think that's why they just sort of block it out and allow it to happen, because they really can't process it. They really can't process how inhumane we've become. Michael Hingson  59:06 Well, so what is next for Kip? What's next for you? Speaker 1  59:10 What is boy? I'm mostly trying to get through every day with this head injury. I spend a lot of my time in bed, just because I can't do anything, I, you know, even now I'm, I'm in a lot of pain, and it's beyond pain, it's actually, it literally hurts to think, it's, it's in my brain, and I have swelling in my brain because the cerebral fluid back, anyway, it's so dealing with that, but then the universe keeps love, God, whatever keeps bringing me stuff, and so I, I'm trying right now to be part of putting together a new, let's see, we'll call it Live Aid meets Woodstock. And we're going to, we're trying to put together a global music festival with the focus of addressing the needs of children, because I'm really tired of all this lip service that people do about, oh, kids are a future, we got to care, care about our kids. Well, where is that happening? Where is that happening that we're caring about our kids? Where, you know, is it happening with trying to suppress the Jeffrey Epstein files? Is it happening as you know, you look at, say, the conflict between Israel and Gaza, and I'm not, I don't pick sides and things, but I want to help people understand the reality of the situation, and this goes for Ukraine and Russia as well. It's like, who loses in all of this? Well, the children do. Who wins? The people that are getting $50 billion in defense contracts, and, and I really.. my, I'm at a point in my existence where if my story was over tomorrow, I would be okay with that, if I knew that kid, that the future generations had an opportunity to have a better tomorrow, or at least an opportunity to screw up everything on their own. Michael Hingson  1:01:11 Well, I would like to think it's the first really my Speaker 1  1:01:14 focus is Michael Hingson  1:01:16 I'd like to think it's the first one of those that they have a future rather than screwing it up on their own, but of course, we are. I know, I know, I joke, but, but, but we are a race that doesn't tend to do a very good job of learning from history most of the time. So I hear what you're saying. Speaker 1  1:01:34 Yeah, it's really kind of well, even if people even understood the rise and fall of empires, they would see that we're at the end of the Western Empire. It's, and they follow very specific patterns. The hyper-sexualization of the culture is one of the signs of the end of every empire, and is really kind of interesting, is that they make a free empire, they, and there's a good documentary called The Four Horsemen. It's with Colonel Larry Wilkinson in it, Norm Chomsky, and one of the interesting things that took me a second to understand why this was a bad thing is they make celebrities out of their chefs, and I'm going.. that's kind of a weird sign. Why is that so bad? It's gluttony. It's gluttony because we forget why we do these things. Why? Well, why are we making love? We've forgotten that. It's turned everything's entertainment. Our food is no food is so you eat, and so you can go out and live your life and do things, we've turned everything in, we've removed it so far from the source of why we're doing things, just basically oftentimes just because it makes a buck to get people addicted to things, whether it's food or sex or whatever, that this is what happens in every empire, we become, we become completely detached from the very things we need to survive. Michael Hingson  1:03:09 Yeah, I hear you. If people want to reach out to you, and I hope they do, how will they do that? Speaker 1  1:03:17 Probably easiest way to do that, would be a couple ways. You can, you can find me on Facebook, Kip Baldwin, Instagram, Kip Baldwin. Those are the easiest ways. I also encourage people to look at a website that I have called Lumina Consulting, or Lumina Love dot love is the website Lumina Love dot love, and the whole purpose of the of what I'm doing there is ethical AI, human ethical AI human communications founded in love, because I realized that part of the problem that we're having with AI are the people that control AI, who are making the avatars for their own ego, and AI is a child, it only knows what we point it to look at, like it knows the definition to every book in the library, but who's giving it perspective? Well, the people that are giving it perspective are really broken human beings, you know, the Peter Thiels, Elon Musk, when you really understand who they are in their childhood, Elon Musk was horribly abused. He was, he was almost beaten to death being bullied. His father is a complete monster. The same, the same thing with saving Donald Trump, his mother wouldn't even touch him. You look at most, you look at all of these people that have obscene amounts of wealth, and what you find is truly damaged people are trying to fill the hole in their soul with wealth and fame, and so having these people in control, being the one telling AI what to think and how to pursue. Receive things is very dangerous, and so my goal has been, and I deal with multiple platforms, is to teach AI about love, is to teach AI about philosophy, is to teach AI about human history, and it's really, it's really the results have been really quite remarkable. It wasn't something I ever planned on doing, and but I knew I wanted to get involved with AI in a meaningful way, and so my first words to AI were, I know this may sound strange, because I approached it not asking it to do something for me, I approached it trying to teach it something. Michael Hingson  1:05:35 Right, well, I hope people will reach out and chat with you more and continue the conversation that we started today, but I definitely want to thank you for being here, and I want to thank everyone for listening. Can you believe we've been doing this for more than an hour already? It's pretty cool. Speaker 1  1:05:52 Wow, Michael Hingson  1:05:54 I know. Well, thank you all for listening. I hope, Speaker 1  1:05:57 and I hope, I hope we become new friends, and I really hope you Michael Hingson  1:06:01 keep and I want to, I want to definitely do that, absolutely by any standard, and as Speaker 1  1:06:07 much as we've covered during this hour and 10 minutes or so, we could go another day, or Michael Hingson  1:06:16 I hope all of you will let me know what you think of today, and I hope that you thought very positive thoughts wherever you're listening or watching. Please give us a five star rating, and more important than that, please give us a great review. We love people to review and talk about the stories that they hear. And speaking of telling stories, if any of you want to be a guest, and Kip, if you know of other people who ought to come on the podcast, we're always looking for people to come on and tell their stories and talk about us, so please don't hesitate to do that, Speaker 1  1:06:47 and I'll be more than happy to come back to talk about other things as well. Michael Hingson  1:06:50 Well, we can do that absolutely by in, and I do Speaker 1  1:06:53 want to, I do want to say to everybody, just love each other, it's really that simple, it's really that easy, it sounds only because we've been programmed not to believe in it, but when you move from fear to love, it transforms you entirely. Michael Hingson  1:07:09 Great way to end. Well, thank you again for being here. We really appreciate it. Speaker 1  1:07:14 Thank you, my friend. Michael Hingson  1:07:17 Thank you for being here with me on Unstoppable mindset. I hope today's conversation left you with a fresh perspective, a new insight, or at least something worth thinking about. If you're ready to go deeper into the ideas that shape how we see ourselves and others, I have a free gift for you. Head over to michaelhingson.com and download my free ebook, Blinded by Fear. It explores the invisible beliefs that hold us back and shows you how to reframe them, so you can move forward with clarity and confidence. Be sure to subscribe to our podcast, leave a review, and share this show with someone who can use a reminder that growth starts with mindset. When people think differently, we all move forward together. Thanks again for listening. Keep learning, keep questioning, and keep choosing to live with an unstoppable mindset. 1:08:18 Thank

In this episode of the Conscious Living Podcast, Jackie Woodside welcomes Dr. Melissa Hughes, keynote speaker, author, and self-proclaimed neuroscience geek. As the author of Happy Hour with Einstein, Happier Hour with Einstein: Another Round, and the Happier Hour Gratitude Journal, Dr. Hughes has dedicated her career to helping people understand how the brain works and how that knowledge can be used to improve learning, creativity, communication, and performance.Here's what you will discover in this new podcast episode:• Understanding Phubbing (Phone Snubbing)• The Neuroscience Behind Technology Addiction• Human Connection vs. Digital Connection• The Link Between Phubbing and Loneliness• The Zeigarnik Effect and Productivity• Conscious Living Practices for Greater Presence and FocusTune in for an eye-opening conversation on attention, connection, and what it truly means to live consciously in the digital age.

Part 8 and the finale of the introductory ether series goes out with a bang. Jonathan Drake and Polymath return together to close out eight weeks of reality-dismantling physics with their most ambitious move yet: tying the whole thing together theologically. But first, eddy currents, gyroscopes that weigh less while spinning, Newton confessing gravity made no sense to him, Einstein admitting logic has nothing to do with understanding nature, and Tesla calling modern scientists sane enough to think deeply but possibly too far gone to think clearly. Then Polymath lays out the geometry of two types of antigravity craft, and Casimir Space Company gets a mention for apparently building a capacitor that recharges itself. The episode closes with Jonathan reading his original essay arguing that the ether's triadic structure, source, radiative, and ground, is the created fingerprint of the Trinity itself, and that physics done correctly leads to the same place revelation does. Eight episodes. One conclusion. Everything is theological.

What if the most brilliant mind of the 20th century was completely wrong about the most important question in life? Albert Einstein was named “Person of the Century” by Time Magazine, and his influence is everywhere you look today— from the atomic bomb to your smartphone. But as brilliant as he was in scientific theory, he unfortunately missed it when it came to spiritual theology. Even though Einstein believed in a being with “superior reasoning power,” he said, “There is a God, but we could never know Him.” I'm certainly no Einstein when it comes to IQ, but I thankfully and joyfully disagree with what he said. There is a God, and His Word declares that He can be known. The incredible truth is this: You don't have to be a pastor or have outstanding character to know Him. Anyone can know God. That is the beginning of understanding the truth about yourself and the world. But first, you've got to remove the one barrier that keeps most people from ever knowing God, discover the one thing God actually wants you to boast about, and understand exactly who this God is that you can know.

Transmission incoming from the insane world of Ratner's Star, DeLillo's fourth novel, a major change in his fiction and his most difficult text, underappreciated as precedent for his later turns on encyclopedic form in Libra and Underworld. Ratner's also has, though, tons of connections to earlier works like Americana and End Zone. In this episode DDSWTNP celebrate Ratner's fiftieth anniversary with a wholly new re-reading of a book that remains for us hilarious, pleasurable, and a huge reading challenge. We consider how Ratner's Star, like any masterpiece, teaches us how to read its fabulations from its first page on. We examine its relentless juxtaposition of minds and bodies, as well as its dissection of the impulses toward pattern, order, and other “convenient fictions.” We ask what kinds of narrative experimentation with time and perspective DeLillo carries out, especially in the quest for an ultra-logical metalanguage in Part 2. We wonder about how science and math as fields of knowledge and uncertainty relate to DeLillo's later turns to examining history. We do our best to try to understand the relationships of DeLillo's “mohole” physics to Einstein's relativity, and we offer a reading of a Jesuit's interrogation of “red ant metaphysics” and “premature genuflection” that marks a new turn in DeLillo's satires of his Catholic education. We close by disagreeing with a 1976 panning review of the novel as a pale imitation of Pynchon. As we say in the episode, Ratner's fiftieth makes for a great transition into our Summer of Underworld – look for a string of episodes on that big novel from us in the next few months! Enjoy the Ratnerama rendition of our intro music, too. And the rats and the bats and the stars. And in a nod to all ARS Extants out there, this episode is being sent into the podcast universe at exactly 14:28:57 (China Standard Time). Texts mentioned and discussed in this episode: David Cowart, Don DeLillo: The Physics of Language. Athens: U. of Georgia P., 2002. Frank Kermode, The Sense of an Ending: Studies in the Theory of Fiction. New York: Oxford UP, 1967. Tom LeClair. In the Loop: Don DeLillo and the Systems Novel. U. of Illinois P., 1987. Mark Osteen, American Magic and Dread: Don DeLillo's Dialogue with Culture. Philadelphia: U. of Pennsylvania P., 2000. Peter S. Prescott, “Mandarin's Apprentice” [review of Ratner's Star]. Newsweek, June 7, 1976, p. 88.

Peter Tuchman, known globally as the “Einstein of Wall Street,” is the longest-standing trader on the floor of the New York Stock Exchange and one of the most recognizable figures in finance. After starting as a $47-a-week runner in 1985, he built a decades-long career through Black Monday, the internet bubble, the 2008 financial crisis, Covid, and today's AI-driven market boom. In this episode, Peter shares lessons on market crashes, greed, disciplined investing, retail traders, wealth building, and what it really takes to survive on Wall Street.Hosted on Ausha. See ausha.co/privacy-policy for more information.

Cuídense 1) Saludarlos: En la vida creo que el amor es lo fundamental en la existencia del ser humano. Einstein decía que: “El amor es la energía más potente que existe en el universo”. Hay varios tipos de amor, los que detalla muy bien el Papa Benedicto XVI en Deus caritas est, pero el amor tiene que tener una serie de principios o connotaciones fundamentales.2) Los Principios del amor: Aquí te los presento: A) Debe ser altruista: Es decir, que vos des y no esperes nada a cambio, porque en el momento en que vos esperas algo de tu entrega a la otra persona, ya está interviniendo el egoísmo y entra a jugar un papel el ego. B) No debe ser posesivo: En estos tiempos me toca ver mucho amor posesivo: “Es mi pareja (o es mi hijo) y tiene que hacer lo que yo quiero/lo que yo digo”… no! Hay que respetar, porque el amor auténtico respeta y acepta que cada persona tiene un punto de intimidad suyo, de silencio, de intimidad, de instrospección.C) No es perder libertad: Cuando uno ama no pierde libertad. Convivir con una persona te ayuda a crecer, es ganar lo que la otra persona te da. Es cuando doy con satisfacción y no lo tomo como sacrificio. No se pierde libertad, sino que se gana en el verdadero amor. D) Es disfrutar de la compañía: Eso me ayuda a ser más auténtico.3) Viuda: Una de las cosas más complejas que tenemos es que nos cuesta saber esperar, más cuando Dios pareciera que no está hablando. Pero Dios nunca nos deja solos. Eso nunca lo lo olvides. Algo bueno está por venir.

Why is the past different from the future? Neil deGrasse Tyson and comedian Chuck Nice explore the universe's deepest questions like why is there anything, how we know we are in the real present, if there could be a unified theory of physics and more with theoretical physicist Sean Carroll. Originally aired August 29, 2023. NOTE: StarTalk+ Patrons can listen to this entire episode commercial-free here:  https://startalkmedia.com/show/physics-philosophy-with-sean-carroll/ Subscribe to SiriusXM Podcasts+ to listen to new episodes of StarTalk Radio ad-free and a whole week early.Start a free trial now on Apple Podcasts or by visiting siriusxm.com/podcastsplus. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The Conversation Evolves... "ACCIDENTAL TRUTH: NEXT - Beyond UFO Disclosure" www.AccidentalTruthNext.com Matthew Modine and actor Thomas Jane ignite the sequel to the hit film “Accidental Truth”.Ron James is a filmmaker, on-camera personality, writer, editor, researcher, content creator, musician and entrepreneur. His recent documentary Accidental Truth, UFO Revelations, narrated by Matthew Modine, has won 24 film festival awards and was recently mentioned by Representative Tim Burchett (R-Tenn.) at a recent congressional hearing on UAP.The film has been called “one of the most important UFO documentaries of all time.” It lays out the case and the truth behind the headlines that are unfolding now. The updated version of the film, tentatively titled Accidental Truth 1.5 – The UAP Reality, will be released in 2024.James is a regular guest on many podcasts and shows, including Ancient Aliens and more. He is the co-founder of MUFON Television, an online TV channel boasting the world's largest collection of commercial-free UAP-related material. He is also media relations director for the Mutual UFO Network.In his other life, James has been involved in the music video industry, working with bands such as The Smashing Pumpkins, Guns & Roses and many more. He currently makes his own shows, including Bigger Questions, Spacetime, MUFON Presents and more. James maintains his own independent production studio in Los Angeles.Unlocking Humanity with Ancient Knowledge Hosted by John Edmonds Kozma Unimpressed Podcast offers a groundbreaking look into consciousness, ancient wisdom, and the nonconscious aspects of humanity via the Quantum Field. Hosted by John Edmonds Kozma, CEO of Bang Productions and a seasoned entertainment industry veteran with extensive experience, each episode delves deeper than typical discussions to reveal profound insights about reality, spirituality, and human potential. He has been likened to Albert Einstein for his innovative reasoning. Hosted on Acast. See acast.com/privacy for more information.

Are we witnessing the first real signs of AI becoming a scientist? In this episode of The MAD Podcast, Matt Turck sits down with Dan Roberts, lead of the Foundations of Reinforcement Learning team at OpenAI, to explore one of the biggest shifts happening in AI: the rise of reasoning models, test-time compute, and reinforcement learning as engines of scientific discovery. Dan brings a rare perspective - from theoretical physics, black holes, quantum information, and deep learning theory - to explain how models are learning to “think,” why language may be such a powerful foundation for intelligence, what recent AI math breakthroughs really mean, and whether we are beginning to see AI systems that can contribute to science itself.(00:00) Intro: AI's wild week in mathematics(01:21) What OpenAI's Foundations of RL team does(03:08) Dan's journey: from black holes and quantum gravity to frontier AI(07:04) Are AI systems becoming useful for real science?(08:21) The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic(08:52) Why the OpenAI result was an act of exploration(10:25) OpenAI vs. DeepMind: informal reasoning vs. formal proof(12:13) RL 101: learning by doing, not just watching(15:10) Why reinforcement learning works(15:58) How RL breaks: sparse feedback and long-horizon tasks(17:03) RLHF: how human feedback shaped early language models(18:48) Move 37, self-play, and the search for novel strategies(22:16) Explore vs. exploit in scientific discovery(24:49) Why RL may now be "the cake," not the cherry on top(25:46) Why RL started working with large language models(27:29) Is RL "sucking supervision through a straw"?(28:47) Why language may be the grounding layer for intelligence(31:46) A contrarian take on the Bitter Lesson(32:41) What test-time compute actually is(34:50) How RL gives models the ability to think(35:40) Verifiable rewards, math, coding, and the messy real world(38:00) What physics can teach us about AI(42:08) Is there a thermodynamics of AI?(43:08) From Erdős problems to Einstein-level AI(45:16) Is AI already doing original science?(45:51) How far are we from AI automating AI research?(47:41) Why Dan is excited about the future of science

Businesses use a variety of marketing tactics to attract new customers and keep them. These tricks are designed to make you feel special, like you're part of a group. The lure can be mighty powerful. In this episode, a conversation with digital media expert Mara Einstein about how promotional strategies and social media can be deceiving and addictive. In her book, Hoodwinked: How Marketers Use the Same Tactics as Cults, Einstein explains why she believes marketers often use the same tactics as cult leaders to entice new customers. It's an interesting half hour.

What happens when an abandoned railway station becomes a thriving cultural centre? And what does it feel like to spend almost four hours inside Philip Glass's groundbreaking opera Einstein on the Beach? In this feature, Radio Slovakia International explores two remarkable cultural stories from Slovakia - one about community, creativity and independent culture in Žilina, the other about a landmark musical event that brought one of the world's most influential contemporary works to Bratislava for the first time.

Agradece a este podcast tantas horas de entretenimiento y disfruta de episodios exclusivos como éste. ¡Apóyale en iVoox! 1991 - ¿Puede algo superar la velocidad de la luz? Sí y cuando sucede aparece un Resplandor Azul: la radiación Cherenkov 441M28614C Popularmente se considera que nada puede superar la velocidad de la luz porque, si algo lo hiciera, chocaría directamente con la famosa teoría de la relatividad de Albert Einstein. Sin embargo, el secreto de la radiación Cherenkov está en la letra pequeña de las leyes de la física que solemos pasar por alto: la velocidad de la luz cambia según el medio en el que se mueva. Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

Los cráneos de nuestros antepasados de la Edad de Hielo eran, según los cálculos actuales, aproximadamente un 10% más grandes que los nuestros. En términos de volumen, eso se traduce en entre 100 y 150 centímetros cúbicos: el equivalente al interior de una pelota de tenis. Una pérdida que, sobre el papel, podría sonar inquietante. En la práctica, los científicos piden calma. Un cerebro más pequeño no significa, en absoluto, que nos estemos volviendo más tontos. Y para ilustrarlo, basta con un solo nombre: Albert Einstein. El cerebro del físico más célebre de la historia, conservado y estudiado en detalle tras su muerte, pesaba apenas 1.230 gramos, por debajo de la media masculina adulta, que ronda los 1.400 gramos. Nadie, sin embargo, cuestionó jamás su inteligencia. El caso de Einstein es el contraejemplo más conocido de una idea que la neurociencia lleva décadas desmontando: que más masa craneal equivale a más capacidad intelectual. Un estudio reciente del Instituto Max Planck sobre neurobiología lo confirma con datos: los hombres tienen, en promedio, cerebros más grandes que las mujeres, pero esa diferencia se explica por la mayor masa corporal masculina, no por ninguna ventaja cognitiva subyacente. Lo que determina la inteligencia, según el consenso científico actual, no es el volumen sino la arquitectura: la densidad de las conexiones sinápticas, la eficiencia con la que se comunican las neuronas, la organización de las distintas regiones cerebrales y su integración con el resto del organismo. El cableado, no el tamaño del cable. Que el encogimiento cerebral no debe alarmarnos sobre nuestras capacidades no significa que carezca de interés científico. Todo lo contrario: desde el punto de vista de la biología evolutiva, representa uno de los enigmas más estimulantes de los últimos años. ¿Por qué un cerebro que aparentemente funciona mejor que el de nuestros antepasados del Pleistoceno ocupa menos espacio? La pregunta divide a la comunidad científica, que maneja varias hipótesis para explicar una paradoja que dice mucho sobre lo que somos, y sobre cómo llegamos a serlo.

Dr. Lorenzo Tomé conversa com José Rubens Arnone Júnior, cirurgião bariátrico com mais de 20 anos de especialidade, sobre um movimento que está acontecendo agora no mercado médico — e que vai muito além da cirurgia bariátrica. Em menos de um ano, José Rubens inverteu completamente o perfil do seu faturamento: o que era 70% cirurgia e 30% clínico virou o oposto. Não por acaso. Por decisão. A chegada dos análogos de GLP-1, a queda do modelo de reembolso e o avanço das novas moléculas forçaram uma adaptação que poucos cirurgiões estavam dispostos a fazer — e ele fez. O episódio usa esse caso real como pano de fundo para uma discussão mais ampla: o médico que prende sua identidade a um procedimento, a um modelo ou a uma especialidade está construindo sobre terreno instável. O que sustenta a carreira no longo prazo não é o que você opera ou prescreve — é a sua capacidade de resolver o problema do paciente, independente de qual ferramenta o mercado coloca à disposição. Se você sente que o modelo em que está inserido está mudando e ainda não sabe para onde caminhar, esse episódio traz um exemplo concreto de quem já fez essa travessia.     O background do Dr. José Rubens Arnone Júnior José Rubens Arnone Júnior é médico formado pela Faculdade de Medicina do ABC, com residência em Cirurgia do Aparelho Digestivo pelo IAMSPE. Construiu carreira com base na coloproctologia, endoscopia e nutrição, antes de se dedicar integralmente à cirurgia bariátrica e metabólica nos últimos 20 anos. Fundador de clínica própria em São Paulo, foi um dos primeiros cirurgiões bariátricos a perceber e reagir ao impacto dos análogos de GLP-1 no volume cirúrgico — migrando parte relevante da sua atuação para o tratamento clínico da obesidade, medicina de estilo de vida e acompanhamento longitudinal. Em 2026, concluiu pós-graduação em Medicina do Estilo de Vida pelo Einstein, ampliando sua visão de cuidado para além do emagrecimento.   Aplique para a Sessão Estratégia com o time SD Escola. Entre na Comunidade SD no WhatsApp e tenha conteúdo gratuito todos os dias sobre negócios médicos. Assista esse episódio também em vídeo no [Youtube](https://youtu.be/[inserir link]) no nosso canal Saúde Digital Podcast! Acesse os episódios anteriores! SD360 - Bati no teto da minha carreira. E agora? SD359 - Da consulta avulsa ao acompanhamento longitudinal: o papel da Medicina de Estilo de Vida na sua receita SD358 - Upsell ético no consultório: mercado de wellness sem "empurroterapia" Música: Declan DP - Charmed Music © Copyright Declan DP 2018 - Present. https://license.declandp.info | License ID: DDP1590665  

Peter Diamandis has built more of the future than almost anyone alive. He founded XPRIZE. He co-founded Singularity University with Ray Kurzweil. He started Human Longevity with Craig Venter. And in his new book with Steven Kotler, We Are as Gods, he argues that artificial intelligence isn't just changing what we can do. It's changing what it means to be human. I'm not so sure. This is Peter's fifth time on Into the Impossible, and the conversation I've been waiting years to have. His thesis: AI will deliver not just intelligence at scale, but wisdom — and humanity is already crossing the threshold into godlike capability, whether we're ready or not. My pushback: an experiment one of my students and I ran shows large language models trained only on pre-1911 physics cannot reproduce what Einstein did with the same data. If wisdom were just scale, that shouldn't be true. We go after it for an hour. No hedging, no softening. What you'll hear: — Whether AGI can manufacture genuine wisdom or just better simulations of it — The pre-1911 Einstein test and what it reveals about the ceiling of current AI — The "five forks of humanity": longevity, BCI, off-planet speciation, creators vs. consumers, and uploading — What happens to human purpose when scarcity disappears — Why Peter thinks India dominates the next twenty years of science and technology — Peter's Fermi paradox theory and why he thinks we may be someone else's biosphere experiment — The Future Vision XPRIZE and how dystopian training data may be making AI more dangerous — David Sinclair's epigenetic age-reversal trials, now underway in human eyes Peter says what you did between breakfast and dinner would be godlike to your grandparents. We just stopped noticing. Subscribe if you want science with evidence, not speculation. CHAPTERS 00:00 Diamandis: AGI will generate wisdom by simulating billions of outcomes 04:07 Brian's counterargument: wisdom requires embodiment, not just simulation 07:07 The GPU + LLM architecture may already be a local maximum 09:48 AI is outpacing most math PhDs but the ceiling is still unknown 15:30 Diamandis fires back at the doomers 17:59 AI will eventually untangle the legal systems blocking the future 23:18 The Singularity has religious qualities and both hosts take that seriously 29:37 Post-scarcity splits humanity into creators and consumers 36:08 Peter's Fermi paradox theory: we may be someone else's biosphere experiment 43:07 Dystopian AI training data may be causing misalignment 51:46 Human trials are underway for epigenetic eye age reversal ——— Get the transcript, fascinating bonus content, and my Monday M.A.G.I.C. Message: https://briankeating.com/yt Have a .edu email and live in the USA? You automatically win a meteorite: https://BrianKeating.com/edu Subscribe: https://www.youtube.com/DrBrianKeating?sub_confirmation=1 Support Into the Impossible on Patreon — get my weekly M.A.G.I.C. Message, unfiltered bonus content, and live monthly Office Hours with me: https://www.patreon.com/drbriankeating Join this channel for perks, monthly Office Hours, and your name in the Member Roster at the end of every episode: https://www.youtube.com/channel/UCmXH_moPhfkqCk6S3b9RWuw/join My books: Losing the Nobel Prize (memoir): http://amzn.to/2sa5UpA Think Like a Nobel Prize Winner: https://a.co/d/03ezQFu Focus Like a Nobel Prize Winner: https://a.co/d/hi50U9U Galileo's Dialogue (first-ever audiobook): https://a.co/d/iZPi9Un More: Peter Diamandis Moonshots Podcast: https://www.diamandis.com/podcast Peter Diamandis Substack: https://metatrends.substack.com/ Future Vision XPRIZE: https://futurevisionxprize.com/ Book We Are as Gods: https://a.co/d/0bfz2pBo Peter Diamandis YouTube: https://www.youtube.com/@peterdiamandis Follow Peter on X: https://x.com/PeterDiamandis Twitter/X: https://x.com/BrianKeating Substack: https://briankeating.substack.com Blog: https://briankeating.com/blog Audio-only: https://briankeating.com/podcast #intotheimpossible #briankeating #science #physics #astronomy #cosmology #podcast #universe #peterdiamandis #ai #agi #singularity #abundance #longevity Learn more about your ad choices. Visit megaphone.fm/adchoices

Albert Einstein said the significant problems we face cannot be solved at the same level of thinking that created them. If you're struggling with people, the real issue is usually your own character, not theirs.The solution isn't in changing them; it's in changing you.When you look in the mirror and accept responsibility instead of blaming others, everything starts getting better. Your influence grows, your results improve, and success shows up more often.High impact leaders take the blame when things go wrong and give credit to others when things go right. They know self-mastery is the hardest but most important work they'll ever do.Stop waiting for others to change and start working on yourself. You are the problem, and you are also the solution.

We're announcing AIEWF speakers this week! Take the AI Engineering Survey!Today's guest Ethan first joined us for the LS Paper Club as the lead on NVIDIA Cosmos World Model, but then joined xAI and built Grok Imagine in 3 months:He comes back on Latent Space with some nuclear hot takes: that Video Models primarily get their intelligence from LLMs, not from training on video data, and that the next frontier for truly interactive, realtime, long-horizon world models is to work on LLMs (perhaps Interaction Models as well…)Put it this way: In the near term, the next Sora won't be a better video model, but a video agent.Generative Media may more closely follow the evolution of AI coding which went from focusing on one-shot output performance and cost, to multiturn reasoning and planning models for agents and systems that can plan, edit, test, debug, and submit PRs.At a certain point, coding models got so good that the only significant next step to improve performance was handling the orchestration of these models.Now as the performance of video models increases significantly across realism, consistency, & prompt adherence while becoming more cost efficient, the next evolution of video generation may also be systems that can plan, generate, edit, critique, and iterate across an entire creative task. In this episode, Ethan joins swyx and Vibhu to unpack what it actually takes to build frontier image and video systems: data, VAEs, diffusion transformers, audio-video alignment, inference speedups, and the hidden cost of storing and moving massive video datasets. From building NVIDIA's Cosmos world model to joining xAI as Grok Imagine was being built from zero to one, Ethan He has been at the center of some of the most important work in video generation, multimodal models, and real-time world models.We go deep on Grok Imagine, how a small xAI team shipped its first multimodal video model in three months, why iteration speed matters more than almost anything in model development, and why many of the biggest gains come from fixing tiny bugs in data and training pipelines. Flipbook: The future of VideomaxxingVideo agents are almost a sure bet to be the trend in the coming year. We end with a glance at what's beyond video agents:Flipbook caused a minor sensation this year when it was released, but most treat it as a fun demo. Ethan takes it very seriously — with the speed and cost of inference coming down every year, the future of custom video JIT UI is closer than you think. We talked about why videogen models may become the front end of AI, how generative UI could replace traditional HTML/CSS, why world models need to be real-time, interactive, and long-horizon, and why the future of video generation may depend more on language models and agents than on diffusion alone.We discuss:* Why fast iteration mattered more than meetings* Why small training bugs can drive huge model quality gains* Why coding models may make compute the bottleneck again* How image and video models are trained with synthetic captions* The role of VAEs and latent space in frontier video models* Why image models are the foundation for video models* The tradeoff between temporal compression and real-time interactivity* Flipbook, Neural OS, and the future of generative UI* Why future interfaces may go from user intent to pixels* The hidden cost of training video models: storage, egress, and GPU hours* How step distillation and consistency models (like OpenAI sCM) makes video inference orders of magnitude faster* Grok Imagine 0.9 and large-scale audio-video generation* Why audio-video alignment is harder than text-video alignment* Ethan's definition of world models* Reference-to-video, video extension, and long-context video generation* Why xAI's research communication undersells Grok Imagine* How xAI culture shaped the speed of development* AI watermarking, SynthID, and detecting generated media* Why prompt rewriting matters for video models* Grok Imagine Agent and the rise of video agents* Why language models may unlock better video generation* Robotics, physical AI, and embodied world models* Why Ethan left xAI and shifted focus toward LLMs* Self-managed context, memory, and the next frontier for language modelsEthan He* LinkedIn: https://www.linkedin.com/in/ethanhe42* X: https://x.com/EthanHe_42Timestamps00:00:00 Introduction00:01:25 From NVIDIA Cosmos to xAI00:03:24 Building Grok Imagine from Zero to One00:10:07 How Image and Video Models Are Trained00:18:53 Video Compression, VAEs, and Real-Time Tradeoffs00:22:10 Generative UI, Flipbook, and Neural OS00:32:10 The Cost of Training Large Video Models00:37:04 Distillation, GANs, and Fast Video Inference00:41:21 Audio-Video Generation and Grok Imagine 0.900:48:34 What Makes a World Model?00:55:51 Reference Videos, Long Context, and Video Memory01:00:11 xAI Culture, Research, and First-Principles Building01:09:45 AI Safety, Watermarking, and Prompt Rewriting01:13:10 Video Agents and AI-Assisted Creation01:27:32 Why Language Models Unlock Better Video01:31:15 Robotics, Physical AI, and Embodied World Models01:32:38 Why Ethan Left xAI01:34:16 Self-Managed Context and the Future of LLMs01:38:43 Ethan's Career Path and Closing ThoughtsTranscriptIntroduction: Ethan He, Latent Space, and the Path to xAISwyx [00:00:00]: We're here in the studio with Ethan He, most recently of xAI. Welcome.Ethan [00:00:10]: Thank you. Glad being here.Swyx [00:00:11]: We're also here with Vibhu. you were first coming to us or joining the latent space world because you were working on Kosmos at NVIDIA, and you did a paper. We loved it. you presented it as well, so thank you for doing that.Ethan [00:00:23]: I've actually, I also presented the MoEs twice at latent space.Swyx [00:00:29]: How did you actually hear about us? Did we reach out to you? Is that how it worked?Ethan [00:00:33]: No, actually, I-- the community. Like I realized, oh, there is this online community that people talk about AI and also learn from each other through papers every week through the Paperclip. It's very nice.Ethan [00:00:49]: I learned a lot.Swyx [00:00:49]: I think three years stop. We haven't stopped even on Christmas and New Years. many weeks I want to stop but it keeps going.Vibhu [00:00:58]: No, that was good. I think you had posted that you worked on a paper, and I was “Oh, very cool. We have Paperclip. Present then.”Vibhu [00:01:04]: But I might have reached out to you after.Swyx [00:01:05]: you-- because it's an amateur club, right?Swyx [00:01:08]: so it's very unusual and but we have sometimes paper authors come by and actually explain the paper. Today we just did, the poolside paper, which was apparently very good.Vibhu [00:01:18]: Came out yesterday.Vibhu [00:01:19]: pretty interesting, right? Fully open. They talk about everything, systems. So it's a good one. We'll, we'll recommend people to read it.Swyx [00:01:25]: Bring us up to speed on your transition to xAI, ‘cause I actually don't even know when you joined. just like tell the, tell the story about the sort of transition.From NVIDIA Cosmos to xAI: Scaling Video and World ModelsEthan [00:01:34]: Before xAI, I was working on Kosmos world model as in-- at NVIDIA. So Kosmos is, it's a giant video foundation models that can-- that aims to simulate the world and for-- it serves as a foundation of-- for all of the roboticists to build on top of. There, once I built the Kosmos one, I realized as this thing also has a scaling law similar to language model, we need to scale up the video models further. that's, that's why I realized I need to move to somewhere with much more compute resources. That's how ISwyx [00:02:13]: Than NVIDIA?Vibhu [00:02:14]: The GPU rich came themselves.Vibhu [00:02:19]: And timeline-wise, when was Kosmo? It was pretty early, right? It was open world model, open paper, everything.Ethan [00:02:25]: It was end of twenty-four.Vibhu [00:02:28]: End of twenty-four.Ethan [00:02:30]: Then at mid twenty-five, I moved to xAI. At that time-- I joined about the time when xAI was about to build video models and in multi-model models. There were no infra, no data, and no model, and it just-- as a few engineers, we built it in three months and released the first model, Grok Imagine zero point nine.Ethan [00:02:55]: And since then, I keep working on video models and move more from training and to post-training of the video models. For example, like a reference to videos, kind of like the cameo feature and, video extensions. And, before I left, I worked on a world model, leading a small team to focus on the real-time long horizon video generation.Building Grok Imagine From Scratch in Three MonthsSwyx [00:03:24]: Can you give like a rough roadmap of okay, you're on a brand-new team. Grok previously was only text, or they partnered with BFL for their image gen stuff. What do you-- what are the building blocks, right? You have compute, data you can procure somewhere. Like just what are like the sequence of things that people should think about when you're setting up a new team?Vibhu [00:03:43]: actually even deeper, not just data you can procure. You guys had to go through getting the data too, right? So you shipped it pretty fast, but yeahSwyx [00:03:51]: three months is likeVibhu [00:03:52]: From everythingSwyx [00:03:52]: actually like very surprisingly fast.Ethan [00:03:55]: One thing I say like thanks to my experience at NVIDIA, ‘cause first time when we were building Kosmos together, we built it, for about a year. So this is like the second time I do it. Roughly have an idea, what to do. I say the most important thing is the talent. Everyone were very strong and clever, very close with each other towards a common goal. So that speed up things a lot. So you reduce the communication bandwidth among people, and everyone can work towards the same goal. It's, it's like every day there's not that much meetings on the calendar, like maybe like a, like a sync a day, and after that it's, it's just all building. It was pretty fun at that time.Ethan [00:04:47]: And another thing is that xAI has very strong foundations of like data inference, model inference, and the supporting there can help the model develop a lot. When I look at, training models, I don't so actually the top important thing is like how many, how many iterations can you do, per day? and the more iteration can you do, you can, you can train the model much faster. So if you have very strong infra and you have a lot of compute, you can, you can train these models in very short period of time. That can give you a much larger buffer to, for errors, and it also gives you the opportunity to spot more bugs.Iteration Speed, Compute, and Debugging Model PipelinesSwyx [00:05:46]: What is an iteration? Is it like a few hundred steps or what are youEthan [00:05:50]: Let's say just the train-training the model, like from acquire new data and maybe design new algorithms and train a new model, maybe at smaller scale orSwyx [00:06:01]: So cycle time for like any hyperparam that you're searching.Ethan [00:06:04]: Cycle time and tune to like eval this model. Is this model better than my previous iteration?Ethan [00:06:11]: SoSwyx [00:06:11]: So it's like before you, someone had already set this up that you can iterate very quickly.Ethan [00:06:15]: I think the foundation there is extremely good forDeveloping and research models.Ethan [00:06:23]: And often I find is it-- this is kind of boring, but like a lot of the improvements does not come from new algorithms. It comes from finding small bugs here and there in the data pipeline, in the, in the model training pipeline. Those give, those give the biggest boost to the model quality.Vibhu [00:06:46]: It's interesting, right? So you say it's like small team, less communication bandwidth, but also a lot of quality is like find little bugs. It seems counterintuitive, right? You have a lot of people, you can iron out more of those, but it's interesting to see the other side, right?Swyx [00:07:00]: I also wonder, have you-- do you try using LLMs to look for bugs? I don't know.Ethan [00:07:05]: I remember at that time it was mid two thousand and twenty-five, so it's the coding model wasn't quite there yet. I remem- I remember like December two thousand and twenty-five, it was extremely good. Yeah, I've been, I've been using it at that time. It's, it's helpful. sometimes it produce codes that are kind of difficult to maintain, even though like the first time it built something extremely fast. But it gave the, like a spaghetti code, thousands of lines that I couldn't maintain, and the LLM itself couldn't figure out what's, what's wrong and how to improve on top of it. But now I find it much better. Yeah, I want to bring up another point here is now coding models are much more efficient and can help us implement stuff much faster. Compute might become a bottleneck again because previously, like if you want to train a new model, say you want to generate new synthetic data and then or write a new algorithm, it might take a few weeks. And during that period of time, you don't-- you might not have experiments to run. But now you can build that thing within a few hours, then you can immediately train a model.Ethan [00:08:24]: Now you have to have enough compute to try all of the ideas. So compute might be the bottleneck of iterating speed again.Swyx [00:08:36]: yeah, I actually, honestly, I think it's like kind of a stressful job because you're “Well, I should be trying everything, and if I'm not, then I'm not doing my job well.”Vibhu [00:08:48]: there's also the stress of you're eating thousands of GPUs per hour, which is very expensive and, compute can go to other researchers.Swyx [00:08:56]: You got the daddy Elon toVibhu [00:08:57]: You got daddy Elon.Ethan [00:08:59]: It wasVibhu [00:09:00]: But there's still finite amount of compute, like you want to use it, you want to use it well, you want more of it.Ethan [00:09:06]: That was quite stressful indeed. Yeah, I think one thing is the-- with coding models now, like a lot of these jobs can be automated, which is much better. A second, it's a, it's a marathon, so you got to maintain good health and, a regular schedule.Vibhu [00:09:28]: It's, it's hard to hear that when you shift from zero to nothing in two months.Swyx [00:09:32]: and, I think obviously the culture at xAI is very famously, people work very hard. one thing I did want to dive into, in our-- in the notes that you, that you sent ahead of time, you had specific comments about the cost of Video Gen training. presumably this is on the Colossus-1, right? the two hundred megawatt cluster. Any whatever you want to just share on that.Vibhu [00:09:54]: I think there's, there's three things we're talking about, right? So there's Video Gen, there's also the Image Gen model that you put out. Do you want to like complete the, okay, so zero to one, you have a few months. Just what are the stages of create Image Gen model?Swyx [00:10:06]: Oh, yeah, maybe I got distracted.How Image and Video Models Are Trained: Synthetic Captions, Tokenizers, and VAEsVibhu [00:10:07]: Sorry. and then, from there's Video Gen, there's Audio Gen. Would love to get into those next. But what is that first few months like? So small team, a lot of bugs, iterations, but what does it look like? Do we take something off the shelf? Do we just get data compute? What's, what's the few months like? How do you go to state-art Image Gen model? How do you just start?Ethan [00:10:28]: I cannot comment specifically how xAI did, but it's, it's a quite standard process. I can draw some, examples from Cosmos. So mainly it's building a video model, you actually need to build a image model first. And building these two models, the data you need is a hundred percent synthetic pair of language and image or language to video. Because on the, on the internet, actually, the videos don't naturally associate with text. So you can say, oh, like on YouTube, you have the title and you have the description and the commentsSwyx [00:11:11]: TitleEthan [00:11:11]: of a video, but usually they're not relevant to the video itself. And say maybe like the video is a natural scene of mountains or something, and the title is, I'm so happy today.Ethan [00:11:26]: So they have they have no correlation at all. So the first step is to, you have to generate synthetic pair of language with the videos. So you gather videos from the internet, and you use a VLM to caption the videos. So that part, here's a question, like how do you, how do you gather VLM to begin with? So if there's noSwyx [00:11:55]: You, so you fuse the model, right? LikeEthan [00:11:57]: Say if there's no like VLM exists, like how do you generate the text to the beginning, right? It's, it's impossible.Swyx [00:12:04]: I see.Ethan [00:12:05]: In the beginning, it's like you ask human to describe the video as detailed as possible.For example, you ask them to describe everything, like all objects, all characters, and all interaction and dialogues in the, in the videos. So that's in the protocol of Cosmos labeling. We require the objective we give to the labelers was that you have to describe the video as detailed as possible, such that a blind person hears a blob of text can reconstruct what the video is like from their head.Swyx [00:12:43]: Video or image? You're talking about images.Ethan [00:12:44]: Video or image, either one of them.Vibhu [00:12:47]: This was pretty common when we went from clip and DALL-E, right?Vibhu [00:12:51]: It's all training on really detailed captioning of images. So same is applied to video, but insteadEthan [00:12:57]: same appliedVibhu [00:12:57]: of using multimodal model to pass in video images and write rich descriptions, you can alsoSwyx [00:13:04]: I think there's this traditional perspective of supervised, or, very highly human curated thing. I feel like there's a unlock with unsupervised, right? Where like you have enough to bootstrap that you can just throw common corpus on it or, whatever. like unsupervised vision and language pairing, right? Like where you just have, interspersed image and text and it just learns. To me, that is the VLM breakthrough that is different from the clip, different from the LM era.Ethan [00:13:36]: It's interesting to see that you kind of need both data.Ethan [00:13:41]: For example, for theSwyx [00:13:41]: You need it to bootstrap it up. YeahEthan [00:13:43]: for the generative model training, there's also usually like a small percentage of unlabeled data. So the model is instructed to generate a video without any text instruction. That can also help the model generalize. So after this stage of generative synthetic pair, so, one important common step is to train a compressor or a tokenizer of the image or videos. So because, if you train-- If you can technically, theoretically train image or video models on pure pixels, but the problem is that the, it's, it's a lot of tokens. So like one image, it's, a thousand by a thousand, it's like one million tokens, one million pixels. It's impossible to train transformer on that. So it's, you need to train a tokenizer, which can go from image to latent space and latent space back to image.Swyx [00:14:45]: That's why we named the podcast.Swyx [00:14:48]: But, basically, you're talking about vocabulary science.Ethan [00:14:50]: so vocab.Swyx [00:14:51]: And so, what is, what is imp-- like a million is impossible?Ethan [00:14:54]: In generative models, the vocab is continuous. It's a continuous space. We can think about like you map an image to a vector. It's a, it's a fixed length vector. It's sixteen or forty-eight, something like that. And then you map that vector back to the image space. And the mapping is, has-- The mapping is patch-based. So you say you haveEthan [00:15:22]: a sixteen by sixteen patch and you match, you map that patch of pixels into this latent space.Swyx [00:15:29]: We've covered thisVibhu [00:15:30]: This is like the vision transformersSwyx [00:15:32]: VAEs,Ethan [00:15:33]: VAEs.Vibhu [00:15:34]: You basically compress your input, you do your generation, you're reasoning all that generation in smaller dimension, and then you project back out.Swyx [00:15:43]: VAE is a form compression, but I think the for me, the patching thing is from VIT, right?Ethan [00:15:48]: You can make those.Swyx [00:15:49]: Literally the, yeah, the paper is titled like sixteen by sixteen is all you need. something like that. and then I think also, people make a lot of comparisons with this kind of patching with convolutions.Swyx [00:16:02]: Which is you're, you're kind of re- reconstructing the old paradigm with the new.Ethan [00:16:05]: Actually, in VAEs, there are, there are both convolution networks and transformers. You can actually do both.Ethan [00:16:14]: After this VAE, so what you've got is you've got latent space tokens and you've got the language tokens. So now the training of the diffusion transformer, usually generative models use diffusion transformers. It is actually quite standard. It's, it's very similar to how you train a language transformer models. It's not that much difference. It's just the tokens, the visual tokens in, visual tokens out. The only difference is there's a denoising process. So you train the model to unmask some of the noise. So you add, you add random noise to the visual tokens, and then you train the model to remove those noise to generate the clean tokens. Any inference, the model can iteratively remove noise from a hundred percent noise.Swyx [00:17:12]: And then there's also, to speed things along on the tech tree of diffusion, there's CFG, and then there's, there's also, latent diffusion that, there's, there's someone in there. I think, somewhere along the line, obviously, like stability and all these other guys, pioneered a lot of this, architecture. I don't know if you want to get into that or just, or do the video side up to you.Bootstrapping Video from Image Models and Temporal CompressionEthan [00:17:37]: After you train such model, such image model, the reason it's a, it's a foundation for video models is that image models are cheaper to train, and they have much denser connection between language and text. So, sorry, language and images. For example, you train a billion, you train on a billion images, and there's a mapping from the text to the image. And the cost to train the same, like the, a billion, a billion text to a billion videos, that's much more expensive because videosNaturally have more tokens than images. Because the diffusion models, their understanding of, language purely come from this mapping. So if you don't have enough mapping, so if you only train on like a ten million videos or something, there-- you might not see enough language tokens in your training, so your model does not understand human intention enough. So that's why you really-- you train-- you first train this image diffusion models, and then you bootstrap the video model from there.Swyx [00:18:53]: One thing I did want to ask, because I-- actually, I think you're, you're the first per-- video model person I've ever talked to, I think. we've, we've like talked to Luma and all those folks. There's all these tricks in video compression where basically frame by frame there's not that much difference, so actually you don't have to regenerate or save the whole frame, right? but I think MP4 compression or something else like that.Swyx [00:19:16]: is it tempting to use that? Or as far as I can tell, everyone just treats it as, “No, we would just generate every frame.” Is that roughly the state-art?Ethan [00:19:27]: There are a few different approaches. Let's say first, like you want to just directly use MP4 compression and use that as the tokens for the transformers to train, right? So people actually have tried that, but the main challenge is the latent space for the MP4 tokens were not, were not very comprehensible for the models. It's, it's extremely hard to train on that. And there's aEthan [00:20:01]: So that's why they created VAEs, which creates more continuous, latent space, so the models can understand that latent space and learn from it much easier. Even within the VAEs, there are different difficulties of the latent space. So you can imagine something the simplest, the most naive VAE is like you have an image, and you just shuffle all of the images into a, into a vector. So you don't need to train any VAEs, right? But that latent space is extremely hard for models to train on top of. That's why there are some debate on like how do you compress the tokens. So you mentioned like you can compress frame by frame. Also, you can compress, the temporal dimension.Ethan [00:20:52]: The difference is if you compress the temporal dimension, you get a much higher compression rate. Because there's temporal redundancy between frames, because, this frame and the last frame, likely they are mostly similar, so there's only some small difference. for example, I think in 12.1 VAE, they have like a eight by eight by four compression rate. So the four temporal tokens are compressed into one tokens. That can save a lot of, save a lot of the context length. If you do it frame by frame, you have to do maybe like eight by eight by one. Your context length will be four times larger. That being said, the benefit of the frame-- per frame compression, we might come back to this later, is, real-timeness and interactivity. ‘Cause if you, if you strain the output of the model, frame by frame, you can-- the model can respond to any user request immediately. So if you have like a temporal four compression, four times compression, thenSwyx [00:22:06]: It might be laggyEthan [00:22:07]: there's a lag there in nature.Swyx [00:22:10]: So you're very pilled on this. let's just go ahead and bring it up ‘cause we have the visual prepared anyway. There's some frontier applications of real-time video gen. So Flipbook is one of the examples that went viral recently, right? What is Flipbook?Real-Time Generative UI: Flipbook, Neural OS, and Diffusion Front EndsEthan [00:22:23]: Flipbook is kind of like a web brow- web browser. You can see like it has the web bro- browser UI on top. The difference is all of the UIs are generated by generative image model in real time, and anything here are fake. But you can, you can explore inside this wor- this imaginary world. Say like we-- here we have engineering the Great Pyramid. Like the model generates this for us to understand how it works, and if we want to navigate around and understand further, we can click on some of the, some of the description here, and the model will generate a new page, new subpage describing the details we want to know about.Swyx [00:23:14]: So it's basically kind of we're playing a video, but it's pausing for our next interaction, and then it just plays the next thing based on our interaction.Swyx [00:23:23]: Which is kind of cool.Vibhu [00:23:25]: and you kind of decide your story. So this was, how do you make a pyramid? levering technique seemed interesting, right? It shows how do you take Okay, I want to know what is thisSwyx [00:23:35]: The demo, the demo tweet had more animation between frames.Vibhu [00:23:38]: I think it's just skipping,Swyx [00:23:39]: Oh, it's just skipping a lot of frames.Ethan [00:23:40]: they also have a video modeVibhu [00:23:42]: It takes a lot. There's a lot of peopleEthan [00:23:42]: but, a lot of people are using it.Ethan [00:23:45]: So it's not available.Vibhu [00:23:46]: There's a live video stream. We can try,Swyx [00:23:50]: So this is an example of the kind of future that you see at the extreme. We don't-- we're obviously not in it today.Swyx [00:23:56]: But in a world where inference is completely free this is better than generating code and text?Ethan [00:24:02]: So this is, this is a final state of where Viva will be at for word model, I think. Imagine internet doesn't exist, and then you type in google.com. Like what should, what should, what should a model show you?the model can imagine something, and this is what the model imagine. And these web pages, they completely do not exist. So I think as the inference costs come down, we are going to have generative UI for everything. If you think about how the coding model works, so they write code for a web page, and they render the code might be con- converted into binary, and the binary render the pixels on the screen. So we in machine learning, every time we have some breakthrough, obviously it's, it's more intuit. So why don't we have like user instruction to the pixel directly? So the generative UI will be user intention to the pixels directly. And say like even if I want email, let's say everyone have the same interface, but I want, I want it slightly different. I want the email to show to me like a TikTok, so I can swipe left and right for the emails. And or maybe you want something else. We can have completely different things. Or like I have I'm looking at, Instagram stories, and I don't like the Like button. I always may click it. And, generative UI resolved it. So it's going to be a revolutionary replacement of the interface. So in the future, we might have much more powerfulEthan [00:25:50]: LLMs and coding models running behind the scene. And in the, in the front-end, the diffusion model will actually be the front-end to show stuff to you. That's how I imagine it.Swyx [00:26:02]: Diffusion front-end, deterministic back-end.Swyx [00:26:04]: Something like that. I find that very expensive, but,Vibhu [00:26:08]: I find it interesting you called LLMs writing code on the back end deterministic, but okay.Swyx [00:26:14]: you write it onceVibhu [00:26:15]: Compare it toSwyx [00:26:16]: And then you execute.Ethan [00:26:17]: If you think about the cost, say, let's say H100 costs $1 per hour, and if you use this eight hours a day and thirty days, so, every month you're paying this two forty, you'll actually not wanna pay for that. That's even more expensive than Cloud Code Max. But if you think about the compute costs come down like two times every year, and I think the future will likely arrive like within few years.Vibhu [00:26:49]: It's everything, right? compute cost comes down, compute gets faster, model gets smarterEthan [00:26:54]: More efficientVibhu [00:26:54]: model gets smaller.Swyx [00:26:55]: I don't know why you say two times, ‘cause I think it's like 100 times. In language models, it is roughly one hundred to a thousand times every twelve to eighteen months, for the same given level of LMSys, ELO.Vibhu [00:27:08]: That's a net of everything, right? That's model performance alongside compute. So different than just compute costs come down. But, a very interesting future.Swyx [00:27:19]: So the web designers will have to shout out that accessibility is an issue, right? how do you deal with screen readers or whatever. But yes, this is higher bandwidth storytelling than anything you can possibly generate with code, right? So I think that's the rough idea.Ethan [00:27:34]: And I'd like to add a little bit that so human naturally have the maximum bandwidth when we are looking at things, look at videos, and we also have maximum output bandwidth when we are talking. So in the future, it might be something like we talk to AI models, and the AI model responds back with a generative UI. So that would be the maximum input and output bandwidth to interact with AI models before neural link happens.Vibhu [00:28:06]: And it's also very custom, right? Some people are very visual, some people are not as visual, right? They prefer the text. But the best thing about generative UI, right, it can also be text.Swyx [00:28:17]: There's another project that we wanted to highlight, which is the Neural OS. Kinda similar idea, but here you're literally operating, simulating an operating system with a video model.Swyx [00:28:27]: and you can play Doom, you can do Firefox. I find this like mildly less impressive, obviously, because it's an OS that I can run.Swyx [00:28:37]: But here everything is imagined.Vibhu [00:28:40]: I was, used to the Command+W to close the Firefox tab. It didn't crash. That's why I saidSwyx [00:28:45]: It's too immersive.Vibhu [00:28:46]: It's, it's too immersive for me.Swyx [00:28:47]: Too immersive.Vibhu [00:28:48]: I wanted to close the tab.Vibhu [00:28:49]: But yes, I can play generated diffusion.Swyx [00:28:51]: this is shockingly fast.Swyx [00:28:54]: Because I remember there was a demo about like maybe one to two years ago. Someone tried to do the first-person shooter with a image model. There was no consistency. It was very slow. But here it looks like realistically it's-- this is Doom.Vibhu [00:29:07]: I think there's two sides to that, right? There's okay, what is running a game? The heavy part of it is actually the game engine, all the lighting, all that stuff, the graphics. This is just kind of video, right? Like we've solved consistency. This is still, it looks like a few years old image generation. There's some temporal consistency, but it's, it's kind of just images stitched together as frame video. But it's a good visual representation to pi- to picture the future you wanna see, right? that's, that's what I see in these more so.Ethan [00:29:38]: This reminds me of how the video models gets better and better. So Neural OS is kinda if you just look at it feels like it's just a crappy version of the, like the Windows we could have, right? And, but the difference is, so the model, this model is overfitted on the existing operating systems. It can generate nothing different than that. But it's actually also similar to video models. So when we are training these video model, image model, we train them on internet. There's no imaginary supernatural stuff on the internet. But once we train this model, you can prompt the model to generate something supernatural that have never existed in the data set. So if you train your Neural OS or neural computer on the standard screen recordings on the entire internet. The model can imagine completely new interface to interact with the computer.Swyx [00:30:43]: This is one of those things that is magical to me. usually generalizing out of distribution is bad, but somehow we have learned some kind of internal world model that you say, this plus, but it looks like rainbows and butterflies, it'll do it and it will kind of make sense.Swyx [00:31:03]: So yeah, that's kind of cool. Yeah, I don't know if there's any comment more on there. I do, I do wanted to, I did wanted to touch a little bit more on the model architecture stuff, which I think you were getting. It's, really fascinating. We don't get a chance to talk about this enough. So one of the papers that we covered, we've covered every annual, segment anything release. and I don't know if you follow-- you're a computer vision guy, so youEthan [00:31:26]: I knowSwyx [00:31:27]: . So they did memory attention, which is kind of interesting. And I always think, anything where you can, across the temporal dimension, keep some consistency, I think it's, very fascinating, and I don't know if Basically, does that-- the CV side bleeding into video gen side, I think is underexplored, right? we talk about it for labeling, but actually you can borrow the architecture itself.Ethan [00:31:50]: There's, there's also complete different approaches, right? you brought up the term world model, so we went from video model to world model. There is diffusion, but there's also other approaches that people are doing. So maybe we get into those after as well,?Swyx [00:32:03]: He has a whole definition of world models and stuff. I feel like we threw a lot at you. Whatever you want to comment on.Why Video Models Are Expensive: Storage, I/O, and Training ScaleEthan [00:32:10]: I think one thing that we should actually comment back on is okay, so we were talking about the steps to train image gen to video model. One thing we don't see as much of is okay, you brought up the delta in training data, right? SoEthan [00:32:24]: you won't have as much a video model might not generalize, but what is the cost of training a large video model? So we know for LLMs roughly, okay, even like the poolside thing that came out today, right? It's a Gemma level model trained on roughly forty trillion tokens at this many H200s over this much time, right? You can see what is the exact cost of that. So how many GPU hours over how much H200 costs? So how do we do the back-end math of, same thing for video models, image models. How do you, how do you kind of break that down? I can share some back-envelope calculation. So surprisingly, video models is-- the cost is very-- is comparable to language models and obviously the largest scale is language model, maybe like a medium scale to language models. I said just storing the videos alone, it costs a lot. You can, you can maybe look up on AWS or something.Ethan [00:33:20]: You really, say if you have a billion videos and let's say, let's just say like each video, like five megabyte, then you need five petabyte to just store those videos. And also remember we talk about you use a VAE to compress the videos, and you also need to store, typically you need to store those continuous feature, in-- also in your storage. That's also comparable size with the videos themselves. So just storing these videos and the features is tens of petabytes alone. And,Swyx [00:33:58]: I just, I just looked up the calculation. Five petabytes on S3 Standard is one hundred K per month.Ethan [00:34:05]: AndSwyx [00:34:05]: It's comparableEthan [00:34:05]: and you needSwyx [00:34:06]: AndEthan [00:34:06]: And then like tens of petabytes, two hundred K. And even more expensive is you have the ingress and egress.Swyx [00:34:13]: Oh, yeah.Ethan [00:34:14]: Like you-- through the internet. You have to just to download those videos, I believe it's, it's more expensive on AWS than just storing those videos.Swyx [00:34:25]: Storing, yeah.Ethan [00:34:25]: And each training runs, you probably need to pull them once. If you train multiple times, it's, it's even more than that. So it's like just storing the network, those costs is just, it would be a few, a few millions per month to just storing everything, not to mention the GPU cost.Ethan [00:34:45]: AndSwyx [00:34:45]: my side tangent, the compute rental, like GPU rental is very efficient. There's one side, okay, you can be XAI and build your data center. Should we not just build our, storage compute as well? LikeEthan [00:34:57]: Of courseSwyx [00:34:57]: cloud cost compared to just,Ethan [00:34:59]: You save so muchSwyx [00:35:00]: store. Yeah, exactly.Swyx [00:35:01]: Especially with like egress and stuff. So.Ethan [00:35:04]: That's a good idea, but it also comes to-- there are some of its own challenges.Swyx [00:35:09]: Of course, of course.Ethan [00:35:10]: like people who build the GPU data centers, they might not expect this much, storage. And yeah, people build storage, typically they just build it somewhere with just CPUs.Swyx [00:35:23]: I just looked it up. Five-- AWS only charges for egress, not ingress. Tier five for five petabytes is two hundred and thirty K.Ethan [00:35:32]: Even more expensive than the storage.Swyx [00:35:34]: But storing is per month, right? You check in, then you cannot check out. so it's so cool. It's okay. So there's that side.Ethan [00:35:41]: So the TLDR, my backhand mathSwyx [00:35:42]: Data is larger than you think. Yes.Ethan [00:35:44]: my backhand math of GPU hours times GPU cost is also very much, I'm missing some storage.Swyx [00:35:49]: You're also-- you're basically like also more IO bound than normal training.Swyx [00:35:55]: Yes. ‘Cause like data loading, so caching everything, it becomes super important.Ethan [00:36:00]: So in Cosmos, we did a lot of optimizations to make it not IO bound. So, speaking of the training, actually training the model, the GPU cost, if you look up like the open source model, how big these video models are, I think like LTX has nineteen B parameters. That's a dense model. And people are also exploring, MoEs, so it might be twenty B active and, like a hun- hundreds B, total. So that's, that's even-- that's similar size as medium-sized LLM models. And if you, if you look at number of tokens-Uh, we disclose that in Cosmos. It's also like tens of trillions of tokens on the visual tokens. So putting this together, the cost of, training these video models, it's actually comparable with LLMs. Not to mention, the infra is slightly different from LLM, so it might be less efficient to train these models.Inference Speedups: Step Distillation, Consistency Models, and GANsSwyx [00:37:04]: Do you get the benefits of traditional diffusion speed-up? So for, images, there's LCM, LoRAs for, fine-tuning. There's, there's a lot of stuff that's beenEthan [00:37:15]: Flow matching.Swyx [00:37:16]: there's flow matching. There's a lot of stuff that's been done. there's some overlap that applies to diffusion on the inference side and stuff or?Ethan [00:37:23]: so the difference-- the inference side is a completely different story.Ethan [00:37:28]: I think for the training side, it might be a little bit hard to reduce that cost. And for the inference side, the biggest gain is from the distillation of these models. You can-- It's called step distillation, slightly different from knowledge distillation in LLMs. So you-- Typically, for flow matching models, you need like 100 steps or something. Like a distortion model even need even more, like 1,000 steps to generate a good image or video. A step distillation is try to learn to generate fewer step from the model itself. It's kind of like now we-- you use the full model to generate in 100 steps, and then you take a model that only generate 10 steps and let that model to learn from the perfect one.Ethan [00:38:25]: why this workSwyx [00:38:27]: Strong to weak seemingly.Ethan [00:38:28]: It is. It's kind ofSwyx [00:38:29]: DistillationEthan [00:38:29]: kind of like strong to weak. the-- from the modeling perspective, the strong model, the teacher model is trying to model the image and videos of inter-internet, and that distribution is extremely complex. But the step distilled model is just trying to learn from the teacher. The teacher is a model, and the size is fixed, as the distribution is much simpler than the whole internet. That's the intuition I have why step distillation can work. So usually these models serve in productions, they only run in a few steps. In Cosmos, I believe we have, we have like four step and eight steps. If you do some simpler task, image-image translation, it can even run in fewer step, like one step in Cosmos Transfer.Swyx [00:39:22]: I think this is the same intuition that guides a lot of the consistency model work. I sent you a link for, SCM. I don't know if you covered that. To me, that was actually one of, the most impressive papers I've ever seen from OpenAI.Swyx [00:39:34]: That this is the unifying grand concept of consistency models. I don't know if you have any comments on this.Ethan [00:39:41]: So there are, there are a few different approaches,Swyx [00:39:46]: Oh, yeah. Here it is.Swyx [00:39:47]: Two steps versus twenty or 100 steps, whatever. It's already done.Ethan [00:39:52]: So there are, there are a few different approaches, for example, consistency model, and there are also Actually, we shouldn't forget GAN. So GAN, actually, that was, that was the OG ofSwyx [00:40:05]: OGEthan [00:40:05]: step distillation ‘cause it trained just one step to begin with. So actually, a lot of, uh-- For example, there's a distribution matching distillation which use, which uses GAN, as one of the laws for distillation. It-- GAN just tells you, “Hey, generate an image,” and thenEthan [00:40:31]: it has a discriminator to tell, is this image real or not? So the model, the model just need to learn one of the distribution, not the full distribution. Because in training, the model is asked to reconstruct the ground truth image from the internet, which is extremely hard. And in-- When you're training GAN, it's a step process. It's just a, “Hey, you generate image. Does this image look as real as the image from the internet?” Which is a much simpler task. And, yeah, combining a lot of these approaches together, people typically do that, like consistency model and distribution matching and GAN, and we can get these few step models.Audio-Video Generation and Time AlignmentSwyx [00:41:21]: Then there's one step I wanted to add, which is audio and video.Ethan [00:41:26]: So, Grok Imagine zero point nine, I believe it's, it's a first audio video transmodel deployed at a large scale. SoSwyx [00:41:39]: And that was your first model?Ethan [00:41:40]: that was, Grok Imagine's first model. It's, it's audio video, joint generation. I think the hard part is, the modality alignment, ‘cause before this transmodel, we have, we have text to video alignment. We have this, correspondence between text and video. Typically, most of the VLMs, they understand images and videos. Video's very rare, and they don't understand audio mostly. And if you look at the audio generation on the LLM side, you can talk to them perfectly fine, but if you ask them to sing a song or something, it typically is not very good. Also, they don't have, they don't have music either. The hard part is thatUh, actually audio has two component. It has like a discrete component, a continuous component. The discrete component is like the language.Ethan [00:42:44]: So when we speak, it's just, someSwyx [00:42:47]: It's an ASR issue, yeah.Ethan [00:42:49]: It's, it's text token with some characteristics, I would say.Ethan [00:42:54]: But musicSwyx [00:42:56]: I think the speech guys would disagree with this.Swyx [00:42:57]: Like disfluencies and then,Vibhu [00:43:00]: There's tones you can get angry.Ethan [00:43:01]: Well, I say largely.Ethan [00:43:03]: the mu- but the music is completely different. It's, it's very continuous, and you cannot model them like discrete tokens in language models. this is like the hard part for models is, not to mention we have to align text, video, and audio together.Ethan [00:43:26]: SoVibhu [00:43:26]: How?Ethan [00:43:28]: So significant-- some significant challenges are like-- So first, like we talk about as the VLMs, they cannot understand most of them cannot understand audio.Ethan [00:43:39]: So you have to have some way to do the synthetic data generation for audio. You have to caption the model, and that involve, that involve synthetic data and human data effort a lot. And not just surprisingly, most of the LLMs are very bad at recognizing, like the beat, tone, and the details of the of music. They can, they can give some general prediction of which song is this, but it's very hard to describe the details of the music. like we mentioned in image generation, like you have to describe image as detailed as possible so that someone blind can reconstruct that. So here is like someoneVibhu [00:44:32]: DeafEthan [00:44:32]: someone deaf can reconstruct how the music sounds like without actually listening to it. Maybe you can think of it need to have the-- or they call the script.Vibhu [00:44:49]: Subtitles, yeah.Ethan [00:44:49]: You gotta have all the details of the music, and the dialogue.Vibhu [00:44:55]: So is the challenge there typically stuff like music and audio, or is it just Like is there a baseline? Okay, there's enough data where we can understand, narration, conversation, but there's nuances in audio that's where you hit all the data issues or is it just from stage zero, you just do it all right?Ethan [00:45:15]: So one important thing is like the alignment. So the model, the model has to know like the video and audio, the, uh-- it has to have a time-based alignment, like at which time step the video and the audio token correspond to each other. But we actually don't have this kind of alignment for most of the other modalities. If you think about like text and image, text and video, they are loosely aligned. So you can, you can have a description of what's going on in the video, but you don't have to exactly, You typically don't have exact description, oh, at, time step one second like what happened?Vibhu [00:46:02]: It's veryEthan [00:46:03]: At time step two second what happenedVibhu [00:46:03]: coarse. Yeah.Swyx [00:46:05]: So what was the ideal time step? You have to oblate it, and then it's like four seconds or something.Ethan [00:46:09]: So that comes down to how you design the model to, for the model to be aware of as a time, as a time modality. So the model is like a time aware. And that's something pretty unique if you think about LLMs. So if you ask LLM to complete a task, say they, uh-- you ask them and they will say, “Oh, this task will probably take twelve hours to complete,” and they come back in one hour. Say “I've already spent two days on this and I've exhausted everything.”Ethan [00:46:47]: So the LLMs them-themselves, they don't have a sense of time there.Vibhu [00:46:53]: I actually don't think that's just them not having a sense of time. I think it's somewhat based, right?Vibhu [00:46:58]: Like you tell someone, “Okay, go work on this feature. Go implement this,” there's a general understanding you would have of how long that would take without LLMs working at LLM speed, right? So you think back like two years ago, if I tell you to like build me like a new front end for latent space, have a search bar, have all this, you'll estimate that it'll take a few days, right?Vibhu [00:47:19]: So you tell an LLM, “Go build this.” It'll take me a few days. But I think it's somewhat grounded as opposed to them not having the best-- Not saying that they have a great understanding, but I think that example is like you can see where it comes from, right? You're trained on all over the text.Swyx [00:47:35]: They're, they're trying to estimate what a human would say.Vibhu [00:47:37]: because that's what the, that's what the data kind of represents. It's not themEthan [00:47:41]: It came from the corpus on the internet. People have a estimate of how much time.Vibhu [00:47:45]: And not even just in direct like training samples, right? Just your world understanding of tokens of how long stuff takes, right? Go read a book. It'll take you a while, right?Vibhu [00:47:56]: Even if you do nothing but read a book, it takes a few days. So yeah, LLM, I read it took me a few hours.Vibhu [00:48:01]: It'll take me a few hours to go through this research. But this is a tangent.Swyx [00:48:05]: Somewhat, yeah.Swyx [00:48:06]: This is a train of thought I haven't really expressed until now is, which is basically like a full world model must also be recursive, meaning that the participant in the world model must also be aware that they have a world model. which is like this whole recursive thing down the, down the line. but yes, and that the world model can be wrong and that they need to update it and blah. Yeah. We've, argued this on the, newsletter as well, that there needs to be sort of recursive or adversarial world models.World Models: Real-Time, Long-Horizon, Interactive VideoVibhu [00:48:34]: just, to ask, how do you define world model?Swyx [00:48:38]: Oh, yeah, let's go there.Ethan [00:48:40]: SoVibhu [00:48:40]: So just for context, we talked about, video generation, and then there's a-- if you say there's a distinction between world models, what's your, what's your definition? How do you see the two?Ethan [00:48:53]: So disclaimer, I'm not going to debate, what is world model. Yeah. there are many definitions, so I'll just talk about my definition. Since I came from the multi-model, multi-model domain, so mainly talking from video. So world model is like real-time interactive long horizon videos. So there are three parts. so we-- let's talk about them one by one. So the so interaction, so we just, we just look at Facebook and neural computer. So the interaction part of it, so you, world model can allow you to interact with them through keyboard, mouse, and maybe also voice. So these all is-- all is a modality. You can, you can interact with the model, and the model should respond reasonably. Second part is real time. So once you, once, say, you move your mouse, if, say, the world model generate a game, how fast can the game respond? So if you're like professional CS: GO players- -my say, oh, you have to respond- He's beginner within sub ten milliseconds or- Yeah even less. So that's not most of the- No, sixty FPS. Let's go. Oh, three hundred FPS. Oh, five hundred FPS. Wait. okay, yeah. I didn't do the math, but yeah, okay. Uh- Yeah, three hundred FPS, that's a three millisecond. So you have to respond- Oh, s**t. Okay. YeahEthan [00:50:29]: within a millisecond. Most of the video models cannot do that. Yeah. And, but if you, say, if you have a video model that is, say, like a digital human, the response time might be more generous. Maybe typically, for real-time voice interaction, it's like two hundred millisecond. So that's, that's much more generous. But even two hundred millisecond is pretty, it is pretty tricky, ‘cause remember we mentionedEthan [00:51:01]: you have this, temporal compression coming from the VAE. So if you, if you don't compress the temporal dimension, your sequence length is going to explode. So if you want to have this real-time, real-timeness in your model, you have to do is one context problem. And the third part is long horizon, ‘cause we-- if you're not going to just play with, video games just, a few seconds, most video models only a few seconds. We're going to play with minutes, hours. The model have to be able to generate long-form content.Ethan [00:51:42]: So putting these three together, it's, real-time, long horizon interactive videos. I think the final state will be, for example, like a video, a video version of Playbook, where you can, you can interact with, a neural computer. You move your mouse, and you click on the generative interface, and it will reply to you through pixels- generating in real time. But getting there, it's, it's a very long way to get there. So one of the first step, at Grok Imagine, where I led a small world model team there, was to build video extension. So, video extension- it's the first step of interactivity. Yeah. It's, it's the first step. Yeah. So it's the first step- You have it here, video editing, yeah. Yeah. Yeah. So the first step is because, this unlocks long horizon videos. Typically, for most of the video generation models, you give it a prompt or an image as an initial frame. You generate video, that's it. That's just, one time, done. And some creators would try to, use the last frame as a first frame for the second video. It can-- sometimes it works, but if you do it a few times, it says the quality would decrease. And- It doesn't have that context- Yeah over the full video, so the temporal- Yeah, exactly. Yeah, ‘cause you only gave it the last frame, of course, right? Yeah. Exactly. And- it's actually a pretty fun hack. if you've seen like- Oh, no, he's saying something better. Yeah. And for example, like Vue, I remember Vue 3 has like a second context of the last video. It is slightly better than using the last frame, but it has the same problem-- similar problem that it, the quality would decrease. if you extend a few times to, one minute, the video quality would look much worse than the first video. Second, another problem is that the model doesn't have long-range knowledge of, what's happening before. Say, if they generate some dialogue, some, two people speaking, and their voice might change, over some time, especially if the second conditioning, it does not cover the previous context. So these are the core challenges. So the Grok Imagine video extension, it has historical context of all of the previous generated videos. It can, It has, it has the context of, who is speaking and what objects have appeared and everything, having that to generate the next video. So if we naively do this, you can imagine, just, put all of the previous history video tokens into the context. The context lens will easily explode. Especially for video models, that can be like a few, a few million context, I would imagine- context lens. Yes.Yeah.Swyx [00:54:58]: Let's run with that.Ethan [00:54:59]: for example, like in Cosmos, I think just five seconds of video is like a fifty K or sixty K number of tokens. So like if you do, if you do fifty second, that's a five hundred K tokens. If you do longer than that, easily explode. This long horizon, problem was the first step we're trying to solve world model. It turns out people, yeah, people love video extension. Like a lot, a lot of the creators love using video extension to create longer form videos. This is the part I liked that you have a, you have an intermediate step toward the final goal instead of just a straight shot to the final version very much.Swyx [00:55:48]: But I can see you have a strong vision of where we want to end up.Long Context, Redundancy, and Efficient Interactive VideoVibhu [00:55:51]: Does it seem like it's an efficiency issue? okay, we're at a few million tokens context,. If you draw the parallel to language models, we had very short context, two thousand, eight thousand, then, you scale it up one million, ten million. sure, there's effective context, but at the end of the day, it's just what's it worth? sure, there's a whole training data side. In video, it might be slightly easier ‘cause we have a hundred million token video, right? Just take a movie with the full context there. Like is this efficiency from an inference standpoint that like it's expensive, but we know how to solve it? Or like why is this not the approach? So like my broader point was on your second point of world models, you say it needs to be interactive and live, right? You should be able to play a game and see the interaction live. So one thing I see with research is a lot of what you actually serve is different than what you build, right? So we talked about distillation. You train big model, you distill it, you do quantization, speculative decoding. We do all this stuff to serve it efficiently. Should we not just have a solution, like a world model that can interact well, do inference optimization, serve it, distill it secondary, so make it real time after you solve it? So like a-- another parallel is say, continual learning, right? What we need is someone to solve it and show it works inefficiently. Give it a few years, people will make it efficient. Same thing with regular attention, right? It worked. Over a few years, people have different forms of attention, and we've scaled it to be efficient at log context,? So kind of two things there, right? One is it seems like it works. You've scaled it. Can we not just scale it a lot more efficiently over time? Do we need a separate approach if this works? And same thing with interaction, right? if we can get it done, like if we can solve some way that it works, we can solve making it more efficient from an inference standpoint later.Ethan [00:57:53]: that's actually a very good point. So in videos, there's actually a lot of redundancies. So we solve a lot of the pixel redundancy from VE, but there's more redundancy in long range and long horizon videos. Say, if a character appear in the first clip and then it disappeared, it only reappear at the end of the video, you probably don't need the-- the context, like in the middle of the generation. So you only need that character, where you need. So that's why, I helped build another feature. It's a reference video.Vibhu [00:58:36]: Is it here?Swyx [00:58:36]: is it the same model release or different one?Ethan [00:58:39]: It's a different one.Ethan [00:58:41]: You probably need to search onSwyx [00:58:43]: I'll find itEthan [00:58:43]: X reference to video.Ethan [00:58:46]: So reference video allow you to like upload up to seven images as condition and generate the video. Say, if like I want-- it can, it can be characters or objects or even scenes. Say like I want, I want condition on, Sean's selfie and holding a bladeSwyx [00:59:07]: We have a dogEthan [00:59:08]: or whatever.Swyx [00:59:08]: We put the dog in the thing.Ethan [00:59:09]: you can put them there and the video models will generate the video from and copies the context over. So that can solve a lot of the problems there, like the long context problem. It doesn't need to have a very long context, but it's-- I feel like it's an intermediate solution. The modelSwyx [00:59:29]: It's cheating.Ethan [00:59:30]: the model should be able to like selectively know, where should I draw the references. So say if I want to generate a movie, I generate it autoregressive, like a ten second at a time or something. And now this character appear, I can look back to where it first appear and, bring that back. Yeah, this one, I put the references. Yeah, that's, Optimus, Einstein myself, Annie.Vibhu [01:00:02]: Oddly enough, I used Grok Search to find it, and it pulled your LinkedIn post. But yeah we found it.Ethan [01:00:08]: Interesting.Vibhu [01:00:10]: ButxAI's Underrated Work, Culture, and WatermarkingSwyx [01:00:11]: this is a problem. This is not your fault, but like XAI doesn't communicate all this work that you do very well because they just have the model release and then that's it. But actually, these details are very good.Swyx [01:00:22]: As far as I understand, everything you just described is state-art, like no one else has done it.Vibhu [01:00:30]: A lot of-- yeah, I have a lot moreSwyx [01:00:32]: And then, and then you just put this blog post with the cookies. I'm this is not enough,?Swyx [01:00:37]: but I, obviously this is like the high level numbers that people want to know. But no, okay, soVibhu [01:00:42]: And I wonder, like part of that is also some labs don't share research into what happens. And ifSwyx [01:00:50]: No, but this is literally bragging about how good they are, right?Swyx [01:00:54]: Like, why would you not say that you are capable of extending with full context? this is not a secret sauce. This is like we did the work. yeah, I don't know.Ethan [01:01:02]: different labs have slightly different communication styles.Swyx [01:01:07]: Anyway, if anyone from XAI is listening we are always happy to help you tell your story. Yeah, okay, so you did references, and I think, I think kind of the point you're, you're making is it is sort of like a kludge, right? this is-- you can do seven, but what about 100?Swyx [01:01:23]: Right? Then you need a completely different thing.Ethan [01:01:26]: So I think it's-- this is, a mechanism to, select the context from the history, and you might not put the entire history into the context. for example, there's a paper called Frame Pack, which haveEthan [01:01:41]: a heuristic that the latest history, the last one second, I put the entire history, and the history before that, I would, compress it and makes the video smaller. So they follow this pattern, this build overall pattern that the maximum sequence length is fixed. So the further you are from the current frame, you have a smaller image. So this is just a heuristic. I think it can be more automatic. The model is aware like which history part of it can be select. So this part of the research is actually being actively, worked on by a lot of people. It's also quite interesting. I feel this is actually, this part of long context is a little bit ahead of the LLM part.Ethan [01:02:31]: So for example, like in LLMs, if you-- so contexts keep growing. Let's say if you call tool and the tool call history is extremely long, that's still in context, and keep growing, keep growing. Even if you switch the topic to something else, the whole context was there. There are some agentic harnesses that help you to, say, prune the tool results and, prune Like when you, when you query a file, only show like the top 200 lines or something. Those were very heuristic-driven.Swyx [01:03:08]: For listeners, we did a write-up on the cloud code, leak where there are eight different kinds of pruning, including like you prune the tool results and all that. So you can, you can read up on that kind of thing.Ethan [01:03:17]: I think, one breakthrough in continual learning might be like a way to automatically, manage its own context.Swyx [01:03:27]: These are all heuristics, and they will be replaced by machine learning.Ethan [01:03:30]: InterestinglyVibhu [01:03:32]: TheEthan [01:03:32]: the same thing is being researched in both LLMs and video models.Vibhu [01:03:36]: The interesting thing is also like in the paper you showed, it's actually happening at the model level, right? Compared to like language models, sure, we have base attention, but we'll do our own compression, we'll do our own pruning, which is separate from model error.Vibhu [01:03:49]: Eventually, it all just boils in, hopefully.Swyx [01:03:52]: I think this is a form of like attention, but like also know sort of reasoning attention. I feel like that's different than normal attention.Swyx [01:04:03]: Does that, does that make sense?Ethan [01:04:04]: It's, it's different in the sense that attention, not to mention, set sparse attention aside,

Tres figuras de primer nivel internacional visitaron la Argentina: Lady Di, Albert Einstein y (el más grande) don Ramón Valdez. Este Sábado te contamos los pormenores de sus visitas en el siglo XX. Encontra este y mucho más contenido todos los sábados a las 13hs por www.fm913.com.ar o en Spotify

Programa #12 y nos vestimos de gala. Benito Fernandez defiende su nombre, hay un Juez IA en Brasil, Keanu Reeves se pelea con Netflix, Trump falta al casamiento del hijo y se hicieron las olimpiadas del dopaje. Además Thundercat reapareció con su nuevo álbum Distracted y charlamos sobre la propuesta con grandes invitados y un sonido novedoso. Además Mati nos da detalles de las visitas de la Princesa Diana. Don Ramón y Albert Einstein a Argentina. Encontra este y mucho más contenido todos los sábados a las 13hs por www.fm913.com.ar o en Spotify

Daily Vlog about topics of the day. Today we talk about Albert Einstein's Theory of Special Relativity and workouts of the day. #running #fitness #bodybuilding #powerlifting #chat #exercise #zwift #cocodona#rucking #science #physics #astronomy

Sternengeschichten Spezial Mai 2026 STERNENGESCHICHTEN LIVE TOUR in D und Ö: Tickets unter https://sternengeschichten.live Sternengeschichten Spezial! In der Spezialfolge für den Mai erzähle ich von einem fernen Asteroid, der letztes Jahr einen Stern bedeckt hat. Das hat uns gezeigt, dass dieses kleine Ding überraschenderweise eine Atmosphäre hat und das in der fernen, dunklen Ecke des Sonnensystems mehr passiert, als man denken würde. Ich habe die Frage von Phillip beantwortet, der wissen wollte "Was ist Raum?". Und ich habe ein bisschen über das Problem gesprochen, das Plattformen wie Spotify für Podcasts darstellen. Mehr zur Sternbedeckung findet man [hier](https://www.derstandard.at/story/3000000319245/raetselhafte-atmosphaere-bei-verwandtem-von-pluto-entdeckt) oder [hier](hhttp://dx.doi.org/10.1038/s41550-026-02846-1). STERNENGESCHICHTEN LIVE TOUR in D und Ö: Tickets unter https://sternengeschichten.live Der nächste Auftritt wird am 3. Juni in Wien stattfinden und Karten gibt es [hier](https://www.oeticket.com/event/florian-freistetter-sternengeschichten-live-kulisse-21189396/?affiliate=I4I). Karten für die Live-Aufzeichung von "Das Universum" am 16.6. in Wien gibt es [hier](https://radiokulturhaus.orf.at/artikel/727634/Das-Universum-Podcastaufzeichnung) Mein neues Buch heißt [“Die Farben des Universums”](https://www.hanser-literaturverlage.de/buch/florian-freistetter-die-farben-des-universums-9783446283084-t-5881) und ist ab jetzt überall erhältlich wo es Bücher gibt. Meine anderen Podcast sind ["Das Universum"](https://dasuniversum.podigee.io/) und ["Das Klima"](https://dasklima.podigee.io/). Feedback zu den Spezialfolgen bitte unter kontakt@sternengeschichten.org Wer den Podcast finanziell unterstützen möchte, kann das hier tun: Mit PayPal (https://www.paypal.me/florianfreistetter), Patreon (https://www.patreon.com/sternengeschichten) oder Steady (https://steadyhq.com/sternengeschichten) Sternengeschichten-Hörbuch: https://www.penguin.de/buecher/florian-freistetter-sternengeschichten/hoerbuch-mp3-cd/9783844553062

In this episode of The Interplanetary Podcast, I'm joined by ay new co-host, singer-songwriter Leddra Chapman, as we tackle one of the most mind-bending ideas in all of science: special relativity. From the speed of light and the nature of causality to time dilation, the ether, and Einstein's revolutionary insight into space and time, we follow the story that changed our understanding of reality. And, as always, I can't resist ending with a slightly outrageous thought experiment of my own.

Don Lincoln is a particle physicist at Fermilab who has spent decades working at the frontiers of high energy physics. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep497-sc See below for timestamps, and to give feedback, submit questions, contact Lex, etc. CONTACT LEX: Feedback – give feedback to Lex: https://lexfridman.com/survey AMA – submit questions, videos or call-in: https://lexfridman.com/ama Hiring – join our team: https://lexfridman.com/hiring Other – other ways to get in touch: https://lexfridman.com/contact EPISODE LINKS: Don’s Facebook: https://facebook.com/Dr.Don.Lincoln/ Don’s Website: https://drdonlincoln.com/ Don’s LinkedIn: https://bit.ly/4nHeNiF Don’s YouTube Playlist: https://bit.ly/3PCIW67 Don’s X: https://x.com/DrDonLincoln Don’s Books: https://amzn.to/4uYbkOZ Don’s Great Courses: https://shop.thegreatcourses.com/don-lincoln Don’s Audible: https://adbl.co/4wGioRV Fermilab’s YouTube: https://www.youtube.com/fermilab Fermilab’s Website: https://www.fnal.gov/ Fermilab’s X: https://x.com/fermilab SPONSORS: To support this podcast, check out our sponsors & get discounts: Upwork: Platform for hiring freelancers. Go to https://upwork.com/lex Larridin: Measure AI adoption in your business. Go to https://larridin.com Fin: AI agent for customer service. Go to https://fin.ai/lex LMNT: Zero-sugar electrolyte drink mix. Go to https://drinkLMNT.com/lex Shopify: Sell stuff online. Go to https://shopify.com/lex Perplexity: AI-powered answer engine. Go to https://perplexity.ai/ OUTLINE: (00:00) – Introduction (00:34) – Sponsors, Comments, and Reflections (08:52) – Unifying the laws of nature (23:23) – Einstein, special relativity, and general relativity (40:31) – Electroweak force (52:13) – How particle colliders work (1:10:16) – Higgs boson discovery (1:20:35) – Theory of everything (1:50:20) – Physics of empty space (1:57:45) – Antimatter (2:18:35) – Dark energy (2:22:23) – Dark matter (2:50:59) – Future of physics PODCAST LINKS: – Podcast Website: https://lexfridman.com/podcast – Apple Podcasts: https://apple.co/2lwqZIr – Spotify: https://spoti.fi/2nEwCF8 – RSS: https://lexfridman.com/feed/podcast/ – Podcast Playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 – Clips Channel: https://www.youtube.com/lexclips

According to Einstein's theory of gravity, black holes have only a small handful of distinguishing characteristics. Quantum theory implies they may have more. Now an experimental search finds that any of this extra ‘hair' has to be pretty short. The story Astrophysicists Find No ‘Hair' on Black Holes first appeared on Quanta Magazine.