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AI is making creative production faster while increasing the value of human craft, imperfection, and hands-on creative control.Drew and Rory start with Netflix's 300 AI-assisted programs and somehow end up defending Blockbuster, boxy cars, greasy roommates, and the radical act of making creative work harder on purpose. Between the usual intellectual potholes, they uncover why invisible AI succeeds, why perfect outputs are becoming exhausting, and why human-made work may become the premium signal.Covered in this episode:Netflix generative AI workflows span concept development, pre-visualization, visual effects, post-production, and release. Suno, Udio, Strudel, Foley artistry, AI music licensing, Runway visual storytelling, Claude, ChatGPT, Figma shaders, Photoshop retouching, creative consistency, nostalgic design, imperfect aesthetics, and hybrid human-AI production define the broader creative shift.---⏱️ Fast Hour00:00 Why are guests returning to Fast Hours?03:45 Why does summer trigger nostalgia?10:49 How is Netflix using generative AI?20:39 Could Blockbuster have become Netflix?24:04 What AI tools has Netflix open-sourced?28:36 What did the Suno breach reveal?32:21 Should AI be used to make music?43:31 Breaking down Runway's lamp film—hy does it work?51:43 How many movie story arcs exist?53:32 Does AI increase the value of human craft?57:53 Why are creators rejecting AI perfection?01:06:16 Why is nostalgic design returning?01:17:09 Why do simple stories feel better?01:23:09 How do AI projects maintain consistency?01:25:43 Who should Fast Hours interview next?#GenerativeAI #AIFilmmaking #AIMusic #CreativeProcess #FastHours

More nice guys: https://www.youtube.com/playli... In this episode of r/niceguys, we cover some walls of text. Simps of this caliber make me want to leave the planet. It's hard to stomach, but I'll be there to help see you through it. We'll do this nice guy reddit post together friends. But there is no reprieve from the cringe, so make sure you buckle yourself in securely. It doesn't matter what your background is, you always need to treat people like people and not use them simply to get off. Neckbeards seem to learn this lesson particularly slow and it really does make my blood boil... So we must bring it to light so others don't suffer alone. For your fill of neckbeard stories we've got you covered with the freshest weeaboo, niceguy, and neckbeard happenings on reddit. Stick with ReddX for your daily dose of cringe with a side-dish of relatability. ------------------------------------------------------------ #reddit #neckbeard #niceguys Join me on Discord dude: https://discord.gg/Sju7YckUWu Check out the Twitch streams: https://www.twitch.tv/daytondo... One-time PayPal donation: https://www.paypal.me/daytondo... Support this channel on Patreon: http://patreon.com/daytondoes Stalk me on the Twitter! http://www.twitter.com/daytond... Visit me over on Facebook: https://www.facebook.com/ReddX... Got a story? I got a subreddit: https://www.reddit.com/r/ReddX... Here's an Amazon link to my microphone: https://amzn.to/3lInsRR Wanna rock the ReddX merch? https://teespring.com/stores/r... Character animations are by: https://twitter.com/DarkleyStu... Check out my other channel: https://www.youtube.com/dayton... Wifey's channel is right over here: https://www.youtube.com/channe... ------------------------------------------------------------ Did I mention that we have playlists??: Full neckbeard story compilations: https://www.youtube.com/playli... All of our neckbeard stories: https://www.youtube.com/playli... All of our legbeard stories: https://www.youtube.com/playli... All of our RPG Horror Stories: https://www.youtube.com/playli... All of our weeaboo tales: https://www.youtube.com/playli... ------------------------------------------------------------ Podcasts can provide some ReddX on the go! Check it out! Spotify: https://open.spotify.com/show/... Soundcloud: https://soundcloud.com/reddxy iTunes: https://podcasts.apple.com/us/... Google Podcast: https://podcasts.google.com/fe... Spreaker: https://www.spreaker.com/show/... Podchaser: https://www.podchaser.com/podc... Deezer: https://www.deezer.com/us/show... Podcast Addict: https://podcastaddict.com/podc... JioSaavn: https://www.jiosaavn.com/shows... We are working on getting listed on Castbox, Audible, and iHeartRadio ASAP! Have you ever met a neckbeard or a nice guy? They are frustrating to deal with, but luckily you aren't alone! These r/neckbeardstories from Reddit are among the top posts of all time and include some of the funniest Reddit stories ever posted on the neckbeard stories subreddit! rSlash NeckbeardStories have all kinds of funny neckbeards in them, but especially the nice guy. And the weeaboo. There is a wide spectrum of neckbeards, and this is but a small slice of it. Listening to ReddX's neckbeard stories playlist is a great experience! These neckbeard stories Top Posts of All Time from Reddit are made for you to enjoy any time, so be sure to save my rSlash neckbeard stories playlist! While there are many rslash channels that read r/neckbeard stories and r/prorevenge from reddit, each channel has their own way of performing them. Some of the top rSlash entitled parents channels I recommend checking out are the original rSlash, Redditor, fresh, r/Bumfries, VoiceyHere, Mr Reddit, Storytime and Darkfluff. These Reddit story channels inspired me to start my own Reddit story channel, with a focus on Entitled Parents stories and at times going into the r/pettyrevenge and r/choosingbeggars subreddits. Because most of my audience prefers Entitled Parents stories of Reddit, I tend to just stick with reading the r/niceguys Top Posts of All Time. Subscribe to ReddX for the freshest daily Reddit content. I post relatable readings of Reddit posts and Reddit stories every single day! Journey with me as I relate these amazing Reddit stories to my personal life journey. I'm greatly inspired by the top reddit posts of all time videos and reddit stories! YouTube: https://www.youtube.com/channe... Discord: https://discord.gg/Sju7YckUWu Twitch: https://www.twitch.tv/daytondo... PayPal: https://www.paypal.me/daytondo... Patreon: http://patreon.com/daytondoes Twitter: http://www.twitter.com/daytond... Facebook: https://www.facebook.com/ReddX... Merch: https://reddx-shop.fourthwall....

¿Qué haces cuando una sesión se cancela de un momento a otro? En el episodio de hoy, exploramos cómo la improvisación creativa dio lugar a una de mis sesiones más icónicas: "Adorada".Junto a la experta en maquillaje Alejandra Castaño y la modelo/bailarina Valentina Herrera, desglosamos el proceso de crear un look de fantasía utilizando láminas de oro para esculpir el cuerpo y el rostro.En este episodio aprenderás:Esquemas de Iluminación: Cómo controlar la luz con Softboxes y Grids para evitar que el fondo se empaste y resaltar los reflejos dorados.El "Truco de la Pupila": Cómo identificar modificadores de luz analizando el reflejo en los ojos.Post-producción de Alto Nivel: Mi flujo de trabajo en Photoshop para lograr un acabado de "cuadro al óleo", incluyendo mezcla de canales, capas de curvas para dar tridimensionalidad y el uso selectivo del enfoque.Si eres fotógrafo, retocador o amante del arte visual, este análisis técnico te dará las herramientas para elevar tu próximo proyecto creativo.¡Escucha ahora y descubre cómo convertir una sesión de fotos en una pintura digital!

What does it really mean to build bridges that last for decades? I want you to meet Bircan Unver, whose lifelong commitment to responsibility, creativity, and global citizenship has shaped more than 25 years of meaningful work through Light Millennium. From growing up as the eldest of seven children in Turkey to creating an internationally recognized nonprofit connected with the United Nations, Bircan shares how art, public media, and open dialogue can bring people together across cultures. We explore why responsibility begins with each of us, how local communities can help solve global challenges, and why issues like water security, environmental stewardship, and human connection matter more than ever. I believe you'll enjoy hearing how one person's unstoppable mindset continues to inspire collaboration, education, and hope for a better future. Highlights: 06:55 - How growing up with responsibility shaped Bircan's lifelong commitment to serving others. 18:30 - Why public access television became the foundation for sharing voices and building community. 26:15 - The story behind founding Light Millennium and creating a nonprofit built on dialogue and education. 36:55 - How local communities can play a meaningful role in advancing United Nations goals. 49:45 - Why water security, cybersecurity, and gender equality are becoming deeply connected. 55:40 - Bircan reflects on preserving ideas through books, creativity, and lifelong learning. About the Guest: Bircan Ünver is the Founder-President of The Light Millennium, a Charitable Global Human Advancement Organization (LMGlobal.Org, 2001, New York); Executive Producer of the LMTV Programs; Multi-Media and Event Producer; Host, Author, Publisher, Public Speaker; [Head] NGO Representative of The Light Millennium to the United Nations Department of Global Communications since 2005 (formerly, UN.DPI); and Chair, Outreach and Partnerships Subcommittee at Global NGO Executive Committee and director for the 2021-2023 term. She has been also a Content Provider at QPTV since 1992, and she is the editor and co-founder of the U.S. Turkish Library & Museum Project. She has undertaken the Organization's e-publications, public programs since its inception in August 1999, and #LightMillenniumTV Series and Specials in all aspects of it since January 2000; along with, the LMGlobal.Org's all UN-related activity and programs since 2005. Bircan is the author and director of the Compulsory Peace & ICTs Education from Kindergarten to K-12, and Beyond Campaign, which she launched it through the Light Millennium Global in support of the Summit of the Future in 2024. The Campaign has delivered its 8th session along with the Coalition for the Campaign, which contains 22 organizations and educational institutions including The Light Millennium Global as the leading organization. Further,  she is also author of the bi-annual international high school project, “J.U.C. Media, Research, Writing & Innovation Awards”. The third of its kind was dedicated to the “Water Action Decade” and was delivered  (virtually) on the World Water Day, March 22, 2025. Bircan served as a mentor to the GPODS for three consecutive terms in Winter'22, Summer'22, and Fall'22 Fellowship Programs; and delivered lectures on “How to associate with the UN-NGO”, Public Access TVs in the U.S., and the latest one was on the #WaterActionDecade and the #2023UNWater Conference. To attach that, on behalf of LMGlobal.Org, she organized and hosted an Outside-UN Side Event ID #W175, titled, “What Is Your Commitment To The #WaterActionDecade? ~ Seven Core Ideas Toward #WaterAwareness, #WaterConscience and #GameChangers” in NYC on March 21, 2023, and was the head delegate of the LMGlobal.Org at the #UN2023WaterConference. Based on LMGlobal.Org's Commitments to the #WaterActionDecade, she launched #OneMinuteWaterActionCommitment during the #W175 Side Event, along with continues to work toward #WaterAwareness toward building up #WaterConscience.  She served as the chair of the ATAA Committee on UN Relations, guided its association to the UNDGC in 2020, and also served as the New York Regional Vice-President of ATAA (Assembly of Turkish American Associations) from October 2019 to January 2022. Furthermore, she served on several Planning Committees of the UN-Civil Society Conferences, and the Planning Committee of the High-Level Forum on the Culture of Peace (HLF-CoP). She has been a strong advocate of the UN Vision, Programs & Sustainable Development Goals (2015-2030) along with the relevant UN Days, which are in line with the LMGlobal.Org's Mission/Purposes since its association with the UNDGC (formerly, UN.DPI/NGO) in December 2005. Currently, Bircan is on the Advisory Board of the Turkish Forum (based in Germany). She encourages and guides interested civil society organizations and members of academia toward their educational institutions' associations with the UN, along with engaging them with the UN Programs that are within her networks and beyond. Further, she is an Ambassador of Peace and Goodwill for Anuvrat (Anuvibha) Global Organization (Jaipur, India, since 2014); and a Member of the Global Movement for the Culture of Peace (GMCoP, since 2012). Bircan is also the founder and president of the IsikBinyili.Org Association based in Istanbul (2010), which is a sister organization and counterpart of the LMGlobal.Org. Author of the following four book titles in print (Turkish): “En Kutsalı Yaratmak” (The Most Sacred is to Create) (1995, 2022), “Sanatın Labirentlerinde” (The Labyrinths of Arts) (2016), and “Işık Yollarında (“The Ways of the Light”) (poetry, 2017), and “Bin Yıl Daha…” (2020, A Thousand Years More…). Also, she is the author of the concept and compilation of the “Hope Never Fades” (English) book (Istanbul, 2023). Bircan initially received her local and studio television production certificates at QPTV.Org in 1992. Based on this capacity, she produced and broadcasted near to 260 television programs through local channels in New York City, which are also available online through www.vimeo.com/channels/LightMillenniumTV including 36 #OneMinute #WaterAction PSAs. Bircan celebrated her 30th Anniversary at QPTV.Org through a video profile, titled, “A Turkish Experience in America” (Duration: ~9 min. Production Year: 2022). Her works through The Light Millennium Global is a recipient of various national (U.S.) and international awards and recognitions including two awards from the Foundation of Alliance Community 2023 Hometown Media Awards (F-ACM-HMA for her “GroundWater” Light Millennium TV program in Web-based Programming and Online Events / Independent Producer categories (received at Brick TV, New York), the Anuvrat Ahimsa Award For International Peace-2023 (received in Mumbai, India), and the 2023 International Volunteer President Award by Institution of Green Engineers (received in Chennai, India), and ashe is also the recipient of the 2024 Best Web-Based Program – Independent Producer for the #HopeNeverFades program by F-ACM-HMA, which was produced based on the 2023 J.U.C. Media, Research & Writing Awards (ACM HomeTown Media Awards, San Jose, CA). Bircan holds a Bachelor of Arts (B.A.) Degree from the Mimar Sinan Fine Arts University (Istanbul, 1988) and a Master's Degree (M.A.) from Media Studies of the New School University (New York City 1999). Ways to connect with Bircan**:** Websites: www.lmglobal.org  (active web site) | www.lightmillennium.org (serves as the organization's web archive)#LightMillenniumTV | www.vimeo.com/LMTV | www.vimeo.com/channels/LightMillenniumTV Social Media: Linkedin: http://www.linkedin.com/in/bircan-ünver-7353207 X@lightmillennium Instagram@lightmillennium 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/ 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  00:04 What if the biggest thing 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 Hingston, 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. Well, hello everyone, and I want to welcome you to another edition of Unstoppable Mindset, and today we get to talk to a very interesting person with a with a lot of roots in Turkey, but she is also doing a lot of work with the United Nations here in the U.S. and other places. Her name is Birchan Umfer, and I hope I got that right. And Bircan Unver  01:23 thank you. Michael Hingson  01:24 Oh, good. And Berjan is is with us, and is going to talk about a number of things that she is working on. She's working on, and for years has been involved with a program called Light Millennium, and we'll we'll talk about all that, but let's just start and and as usual we'll have a great conversation. So, Bir John, I want to welcome you to Unstoppable Mindset. We're glad you're here. Bircan Unver  01:50 Thank you so much, Michael Hingston. It's great honor and privilege to have your guests. Especially, I love the title Unstoppable Minds. It's really inspiring and triggering the mind. Thank you. Michael Hingson  02:08 Well, my pleasure. We're glad that you have the time to to spend with us, and we will we will we will do it and make it work. Well, let's start. I love to start this way because I really want people to learn about you. Tell us kind of about the early Birchan growing up, and then we'll go from there. So tell us about Birchan and growing up, and and and all of that. Bircan Unver  02:32 Thank you. This will be a little bit different than most people know about me, my work. Well, we'll get to Michael Hingson  02:38 your work. Bircan Unver  02:40 Yeah, I know. I mean, the people who already know my work. What I'm gonna say now is completely too different from Berja. So I am a elder of seven siblings, and I was born in an ancient village in Mid Anatolia, actually nearby the Black Sea region, and I'm proud with my age, 1959, and my family moved to town first from the village, and then Istanbul for our educations for their kids, and but I don't know really as a girl child growing up with seven kids, as especially with a traditional family, being older girl is not a good idea. But but maybe it was a kind of tough childhood as a girl child. I I don't feel that I never been a child. That's really what I feel. But on the other hand, and that was you know when you are growing up, living through like I was a kind of second mom, and also our home was kind of everyone our guest from the village town and stay over not only one night, like or a week, like sometimes months, even years. You won't believe that, and it was not because either. So, but those kind of build up maybe my feeling to be responsible, so I consider myself a responsible person because I was responsible for my sisters, brothers, and also washing dishes, making helping my mom to prepare the meal, lunch, breakfast, and clean up. Like you know, I was kind of second person, second mom at home. So those early things, all those stolen my childhood, but at the same time, provide me being able to do everything from very early age. Even though I remember several times at the time. The bread wasn't, you know, you you weren't buying the bread from the market, but from the bakery, real where they were baking the bread. So she was, and time to time also she was making the the bread at home, and then she she wasn't sending me to school because then I had to stay with my brothers and kids so she can make the you know breads a big amount for a couple days. So that said, also gave my idea. I want to suddenly want to work as soon as you know I'm 17, 1617, So and then I started early working at a bank, and it was my first eight years. I worked at a bank in Istanbul. It is called Istanbul Bank, and then my graphic is like life graphic is a little bit different, like curvy, not like straight line. Then after eight years working at a bank, I started to university and fine arts, and then I had kind of interest art history, especially TV production, art history, arts in in the concept is producing art documentaries. That was kind of my vision. Also, it was also my reason initially coming to the U.S. learning TV production. Of course, English as first. So that was very much my childhood until you know 18 until starting at the bank, and then the rest is another story. I have, I must say, I would have three different life. Michael Hingson  06:48 Well, you had certainly an interesting childhood, needless to say, and I, I can understand what you're saying about being the oldest and all the challenges. I was not. I was the youngest, but we only had two siblings, and neither of us we were we were both males, and so we we did not do a lot in terms of preparing meals and all that sort of stuff. Except my brother and I were both in the Boy Scouts, and so when we went camping and other things like that, we learned how to cook on an open or an open fire and and things like that. But still, I understand that you you had a a lot that you had to do. What lessons did you learn by being the oldest child? What kinds of things do you think that you you carry over to what to your life today, because you were the oldest. Bircan Unver  07:44 I think two different components of that. One is also because it wasn't only I was the as a kid at the home and as a girl, girl, but also at the time there wasn't that kind of awareness which we have today. Which I mean, my mom got married with my dad at the age of 15, and she had birth. She had given me birth at the age of 16, the reason I'm bringing up this, when we were going to shopping Kapolechar, Grand Market of Istanbul, when I was 1516, and literally we were halfway age difference between my mom and myself. And when I was saying mom, and the people were surprised, and she and isn't your sister, other sister? They were asking me, and she was my mom. So, but this is in the long later years. I always become the best friend with my mom, and even my brother was saying, "Oh, now I understood that she, you are the joy of my mom because she can kind of a joke, and the others, my kids, like they are kids, but I'm her friend because they kind of feel similar. That is one, you know, lifetime developed feeling and strong connection, different connection with my mom, and the other also, as I mentioned at the beginning, it really this whole, you know, not selected, but where you, which house you born, which condition you grow up, that build up for me early high level responsibility. I feel responsible to do everything, and I, you know, that's a little bit tiring because that's what I want to say here. You say something in our after our initial Zoom meeting. It's really very inspiring. You say something. I just took note. We can solve all the worst problem. We can. You say you don't say we cannot. You say we can. Solve all the world's problems. So, like, it wasn't possible. It's not possible, but you know, as if I could solve the problems or I could carry everything. So it's kind of you know build up my bricks in my life. Michael Hingson  10:18 One of the things that you certainly, it sounds like you learned as you were growing up, though, was was all about responsibility and and and learning to take charge, but learning about responsibility and and feeling that it was okay to be responsible for others in your family and so on. And I think a lot of people don't necessarily learn a lot of lessons about responsibility, like they should. But you were put in a position where you had to do that, which is is certainly a good thing because you clearly have have done that in your life. Bircan Unver  10:54 That's very true, and also it goes with everything. Let's say sometimes some people think maybe unnecessary action when people cut trees, even in their you know backyard or front yard, whatever trees or any type of trees or fruit trees. I really get mad and upset because it is irresponsible to nature, to their own environment, just feeling they're responsible to trees, loving the trees, loving the you know, for instance, if when I was it was two weeks ago, I was working on at my desk, a bees was you know flying around me, and I don't like you know trying to hit and chase the bees, and I just left the window open, moved the room two hours, and it's gone. So I don't want to hurt things, even though if it bites, it would hurt me, right? So to kind of find a way, being responsible, because also I have a subconscious thinking that if I try to chase a herd, if an insect, any of them, they you know they react sharp. So I'm not a threat to them. So they are not threat to me. So I kind of make a subconscious connection, communication. Michael Hingson  12:22 Well, and it's it's better to to learn to love than than not. So I I hear what you're saying. Now you didn't go to college or university, right? Or you did? Bircan Unver  12:35 Of course, I did. That's what I was just briefly brought this stair at that level. That after eight years working at at Istanbul Bank, from literally actually 17 to 24 or 23 late 23 early 24 then I started at the Fine Arts University in Istanbul, and I mainly study both as major Turkish tradition arts and also along with as a minor. We didn't have a minor, but we had we didn't have the minor degree, but we had a selected course. So I was following up several like four years in a row and also whole year around, not a quarter semester base artist troy and contemporary art. So I started writing on art and exhibit and interviewing artists while I started study at the Fine Arts University, which is top university in Fine Arts in Istanbul, Myanmar, Sinan Fine Arts University. Michael Hingson  13:44 So you learned a lot about fine arts, and Bircan Unver  13:47 yeah, Michael Hingson  13:47 and you had obviously learned about finance from the bank, which Bircan Unver  13:51 is didn't learn that Michael Hingson  13:53 much, huh? Bircan Unver  13:53 Not at all, and I didn't like it. That's why I, you know, I changed all my life line. Michael Hingson  14:00 Right, but but you enjoyed art. Bircan Unver  14:03 Yes, and because also art always for me, and it as it is today. Whatever the life problems we cannot be resolved, art is always for me a branch to hold on and to kind of feel strength, connect with the nature, with the art culture, whom I never might met, or maybe you know through art, through music, through books. So it's kind of really, I think the the best human conscious and what we leave behind is what we produce. Creative might be a little bit another discussion. What is the term defined? And now everyone using like creative for everything, but creativity is like really what stays, you know, central. And something as what is already before, and what you brought it something new, that new perspective, like cubism and faism and expressionism and all that different genres or pop arts and another one Dali's movement. So all the Dadaism, so each of them brought something what is already existed, and then you know moved to different level, and also technology and communication brought where we are today. So and music, I'm not any degree. Degree train or understand, but I love music as most people about music and arts and literature and writing is always for me. Also taking pictures. I don't trust my memory much, but this is not new, not because of my age now. But I somewhat I always like take the pictures, whether I have cell phone, the oldest, you know, digital or the manual photo photographs. So even though when I run into where where was it, where I was, who was with, who next to me? I can't remember. But why I love that? Because really, it brings, it captures your life, even you don't remember, and then reconnect. Also, I I come up with a new concept. I haven't done anything yet, but it's kind of developing in my mind, that we can, we are able to capture the past, but we cannot capture the future, because you know whether you know unexpected the one photo comes up, or an audio recording, or all those movies, musics, and documentaries and paintings throughout artistry, you can really capture the past depending on what you know your background or interest and education, but you cannot capture the future. But you can imagine, we can imagine the future. We can invest into the future. Michael Hingson  17:16 Well, and and the the reality is that that the future is based on so many things that happen in the past, and so you can learn to to use some of that information and and have a better idea of what the future might be like, and that's that's pretty fascinating too. So so, how long did you go to college Bircan Unver  17:42 in in Turkey the basic four university education is annual base, not semester base. It's a four years, and actually when I started it was five years. Then later on they the system education board changed it to like four years plus two years. So I graduated from a four years fine arts, and then I have a master's degree based in New York News School University. Michael Hingson  18:20 Ah, in New York. Bircan Unver  18:21 Yeah. Michael Hingson  18:22 Okay. So that was was that two years. Bircan Unver  18:27 Yes, but it was a little bit different again. Yeah. See, because first when I was here for the first time, 18 919, 89 to 1994, I started and I took to six credits and I love it. But I had to go back to Istanbul, so then I got the you know absence live of absence, and then but coming back three years later, I readmitted, and then I finish it. I got my graduate diploma in 1999 May 1999 Michael Hingson  19:12 Okay, so Bircan Unver  19:14 you've been dealing late. You've been Michael Hingson  19:17 dealing with school for a while, but but while all that was going on, you got interested in, and you started to to do things regarding public access television. And you started that, if I read your biography correctly, in in 1991, you started doing things with public public access TV. Tell us a little bit about that, and why did you do that? Bircan Unver  19:41 That's really the kind of key point in my life. In as for the initial one of the two reasons that I came to the U.S. as the first time, I was you know the first aim to learn English. The second also. To learn the TV production, and then my first year was in the U.S. was in L.A. and then I was looking for the schools and just I'm I I'd like to get the formal education, formal training, and then one of my friends there, whom I met there, she said my aunt is TV producer at Queens Public TV in New York, and she is looking for someone like you who really wants to get in and all that. And then I think a couple months later, I had a very brief trip to New York, and I met with her, and then I met with her at QPTV. Now she is unfortunately not with us, but she was also she was the first Turkish producer at QPTV, and I'm forever grateful in memory of her. She was the one who introduced me QPTV, so I met Victor at QPTV in 1990, and then when I went back to LA, I decided to move to New York. So as soon as I moved to New York and I registered to QPTV's both field production and studio, and at the time, there were seven, eight months waiting list. Eventually, I got it on the list, 1991, and first I got the field production certificate, and it was I think six months something, and we had a group project and solo project, and then studio and studio production. It's when the same group project after you are learning all the equipment and then shooting and everyone is crewing everyone is helping each other within the same group of the class and then also producing group project and then the individual project that it is the similar step for the field production and the studio, that also provides a certificate to enabling us to use QPTV equipment, studios taking out the equipment, inviting studios, studios. Unfortunately, after COVID 19, there has been a long dragging issue. They haven't opened the studios. This is I don't want to get in because it is beyond our concept, but because that was my initial reason also moving to New York. And then once I started producing program and airing, I really loved idea from one idea, just idea, and then put paper and develop it. Bring yes, bring the crew, especially with the manual three-inch tapes, and to present, put everything in a tape, and then submit it an ARC schedule. I really love that. So then, while I was there, and then I said, "Okay, I want to really have a master's degree on TV production. So my master's degree from New Zealand University is in media studies. So and I got my diploma May 1999 So, but New Zealand was amazing. I learned all the first my you know my life although it was 39 maybe 3839 years old when I was Photoshop and Premiere or Evid and all the first offline digital all the software program I learned at the new school and I edited my first program offline at the new circle as well, but when I got diploma, and then I had nowhere no access to continue. Also, you know, it's just I, I never been about the person. My mind and my heart wealthy, but not financial terms. And then, so QPT was always my second home because it provides me continuing the producing and provides me access, provides me equipment. It's like provides the community. That's what it is exists for, especially in support of the Article First Amendment and freedom of expression, and also QPTV format is really, really not well known, or not QPTV loaned. It is public access, pack programming, public education and government programming, non-commercial. So it's it is not much known widely, but it is really one of the best symbol of democracy. And now it's kind of a little bit diminishing because also widespreading out other web streaming platforms like this or other, so that there are so many. Discussion and issues, and also there is one petition to the New York Senate that is called Team New York that could also bring in all the web streaming to this community media access public access media. So then, Michael Hingson  25:19 oh, go ahead. Bircan Unver  25:20 No, I mean the question is so QPTV had has been the longest since 1991. I've been providing content, and as long as I am in the US, if I'm out of the country, even if I am out of the country, my previously submitted programs are rerunning in different, you know, whenever they schedule for my new programs, I determine which time slot because I have a time slot to be scheduled, and whether 28 minutes or one hour. But especially again after COVID 19, I couldn't produce anything at the studio at QPTV, but like this Zoom-based programs, and then for the late million organization, the programs I produce and then edit them, reformat them to schedule for QPTV. But it wasn't as it used to be produced at QPTV, at the studio with the crew, that's the excitement teaming up. It's really, I love it. But Zoom, this type also make more maybe manageable, but also bring more intonation speakers. You know, through online connection. If Speaker 1  26:54 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. Michael Hingson  27:28 So you you started in public access television and and and are still doing that essentially. But in 2000 you started Light Millennium TV. Tell us about Light Millennium Television. Bircan Unver  27:42 Thank you so much. Because Late Millennium, I still consider it's my third child because already 25th anniversary. The flyer on my back says 25th That also refers the 25th anniversary of the Light Millennium. I think a the experience and production, and also providing three platform QPTV, Queens Public TV, but actually the 1992 Communication Act and PAC programming, public government public education and government programming; those emerge with my new school education, like Fatrus, Plato, the concept of the two ways of messaging, and for the first time in my life, at the age of I think it was I was 39 I was able 3039, I was able to use. It was very new, also for the war. Internet. We had the internet at the new school as our media class, the open forum. One week media theory class. We have open discussion forum about Greek philosophy, further is communication, media theory. The other class we had the classic format. So all these together merged in my mind, and I really felt I found my medium. That medium is the internet, which me, especially someone is living in New York, who has you know 30 years first life in Turkey, Istanbul, that culture, and then I I didn't want to kind of disconnect from my root cultures, and internet provided me that connections, and also I always like to write and communicate, so so it becomes like natural medium. And then when I just graduated in May 1999 I send out by then like 40 people with my friends. Colleagues, and then I said, "Oh, I want to start a platform. This platform is going to be ours. And everyone wants to say, kind of to expand the QPTV's concept, because when I say QPTV's concept, this is the again First Amendment, and they don't control the content. They don't say anything you can do, you cannot unless it is a threat to someone's life. So it's all the content, or you are responsible as the producer. So I really love that freedom and responsibility again. And then then I was mentoring at the New York Food Moon Finance and Television, and I was kind of trying to find what I want to do, and I was already producing programs at QPTV. I never give up as as long as I could afford to produce the time and edit. Edit is always more time consuming, and then the executive director of the at the time 1999 Woman Film Man Television, she said you can form a nonprofit. I never taught it before, and I'm forever thankful to her. And then I said I don't know what to do where to start because she perhaps she saw the potential because I was producing non-commercial and publishing, trying to promote, you know, through group emails, and whatever the you know social media available at the time. Well, mostly email and group emails, and then she suggested me a volunteer lawyers of arts that she said they can help you, and I never knew and I never thought I if I never came to U.S. maybe I will never had a concept of forming a nonprofit or light minimum. So that U.S. and all combination brought me and news called Queens Public TV, First Amendment, United Nations Article of 19 Universal Declaration of Human Rights. Everything together kind of merged in my mind. Also, the projects I produce, I communicate, is contact with people, I learn from them. So then, when I contacted with them, they ask me, you know, what is my statement this type? And then I drafted all of them, and they put in medical, you know, terms and terminology, and I was lucky that we got a pro bono at the time one of the you know major U.S. law firms. I I think I can say now because they even though I think merged K Shuler, but they took our case and they formed my organization on on a pro bono basis and officially the first as a non profit organization done with the 500 1c T V together. So we officially formed 2001 July 17, and we and then right after that they filed 501c3 for us, and then we granted that in September 18, 2002. Bircan Unver  33:14 My memory is not good, but I I remember that date as of today because it was kind of imprinted in my mind, but also the beauty was that the granted granting 501 c3 was effective of the formation date, which is July 17 2001 So then, since I developed started the light minimum concept, introducing speaking people trying creating an open platform that everyone can you know contribute be part of it, so then I started in January 2000 on January 13 2000 started first monthly the like TV series at like at QP TV. That's how it came about. Michael Hingson  34:02 Yeah, you have certainly created quite a niche in in the whole light millennium and all the other things that you've done, which is pretty fascinating. How did you get connected with the United Nations? Because I know you're doing work with them. Bircan Unver  34:18 Thank you. Actually, the concept with the UN use, I don't do work for them. Michael Hingson  34:29 Right. Bircan Unver  34:29 We do work with them. Right. You're connected Michael Hingson  34:34 with them. You're not working for them. I understand that. Bircan Unver  34:36 Yeah, I just you know one word, but it's key key differences. But as as I mentioned, how the light millennium concept emerged, and also my master's degree program, media studies at the New School, and also there is another person I have to mention here, also in. Separate for her respectful and loving memory, Danielle Camille. She was my advisor for my thesis project advisor at the new school, and all that TV ideas and my thesis project. And she loved, and I got all A. And my first TV ideas project was peace, reality, or utopian dream, and it was 11 minutes or so. It was just before the first Clinton administration election, just October, I think 2002 and then I interviewed many academicians, civil society, non-profits who whose focus area on peace and war and you know against nuclear or all that and and then that actually the concept peace reality or utopian dream that took me to the United Nations I don't know now as a as an outsider, at the time it was so welcoming, and I went to photo department. They share me with photos, and I got all the books I was looking for. Of course, public library. I got all the books about the peace and peace organization. So that 12 minutes program, peace rate or utopian dream, and physically led me to step in the UN for the first time, and then producing this project, searching kind of open to me new horizon, and also my advisor was persistent. Birjan, we know you are great. You produce fundamental programs on arts, but I want you to do something else. So that actually also forced me to move beyond producing something beyond arts. And so then then peace, reality, or utopian dream concept came in, but also it wasn't far topic in my life because my son was born 20 when I was 2022 Now he is 45 His name is Borush, and mean is in Turkish peace. Peace also at the time, you know, Africa hunger, and I was hoping when I get 4050, this will be over. It's not the case, but as a vision, I always look for humanistic positive for the humanity, not you know for myself well-being. Michael Hingson  37:38 Well, you you kind of act as a bridge between UN programs and local communities. Tell me more about that because you view that you view yourself as being a bridge between UN programs and the local community. Why do you why do you view yourself as more of a bridge? Bircan Unver  38:00 That's very nice metaphor, and I think it's very true for me too. Maybe I could take it two three step backs. One is the village I was born. There is a river, and and then there was a bridge, and that bridge was kind of fundamental. Really, going to where you know people are established, living in all the agriculture and large fields, and it was kind of nostalgic to me. It's a bridge, but it's a stone, short bridge. That's the the first part. The second Istanbul. You know, my life main path when I was in Istanbul, Turkey in Istanbul, and Istanbul the Bosphor and then the Istanbul Bridge. Now the name changed, and now three bridges, and not just the bridge itself, but also Turkish geographic Turkey's geographical space place on Earth and especially on in between Europe and Asia and Black Sea and then the Mediterranean Sea and then when you go down North Africa, and then you go up like Russia and North Europe. So you see that that connection physically, geographically, and troy physical bridges. We live, we grow up with this kind of as part of our DNA and vision. When I was working on this, the first the initial need you know in the non-profit world to describe the need need was to connect with my culture, people, friends, family, the internet medium, and then village is also metaphor, and when we associated with the. I let I'm proud to say it. Let the association process. That was also my vision from that small video for the class project. And then, then I realize this is also. I think today is real fact that local communities, even Queens here, people are paying 1000s of dollars to come to New York to get visas. All that trying to get the sponsor, you know, to attend a conference, and I I didn't see much interest within the local nonprofits there, and that little bit was shocking realization for me. So I brought to my programs UN visions programs, MDGs, UN days, sustainable development goals. For instance, when it was announced at the UN for the 2023 agenda, we created dreams for humanity. So we brought people from lots of life, poets, authors, and youths to really share their ideas for humanity, for peace. Michael Hingson  41:12 Well, you-it sounds like, from all that I've read and and studied, you're you're, or at some point, you kind of have moved more into dealing with a lot of things with the environment. So I know that your program has been able to get a credit accredited as an observer observer status with the UN Environment Program. How is how has that affected what you do and all of your work going forward. Bircan Unver  41:43 Thank you. This is also another important, I think, milestone for us. The first in connection with the UN, associated with the in the formerly United Nations Department of Public Information, and then it has changed to Department of Global Communications. Officially, we've been associated since 2005, active and good standing, and we are able to be presented at the UN with six representatives, and therefore we are able also to reflect back to our committee's networks from the UN and it's two ways. I really like the concept two ways messaging, and then always environment in somewhat it involves in our programs. But let's say through water, through energy, through, for instance, when the forest fires really burns my heart. So being sensible and trying to, as much as I could, to attend the meetings, especially MDGs for the first phase of the Millennium Declaration, really, it's. I consider UN is the best school I ever had, and it's for me lifetimes to call, and I learn about so many countries I will never otherwise know them much. Some of the names you hardly hear in media and anywhere else, so it's kind of opens and to see the global spectrum. Also, one of the things I really love at the UN, whether you you are a ambassador or president or prime minister of a country that has maybe a population 1 million or 2 million or 1 billion or two 1.6 billion, the largest one, so you have the same minutes of speaking time, same voting, especially of course, I'm talking about the general assembly. So those things I follow up, and we try to incorporate time to time. And water issue always, I wanted to involve. I want to do something about, but it's just not like because I love the tourists, and I'm not, you know, scientist, so I'm not officially trained. So also, I'm not able to protect the, you know, fires in the forest. And every year it's getting worse and worse. And then I'm sensible, but you know, you can't do much about it. And eventually, although our last name is same, but we are not blood connected. Professor Oljoymer, at the time he was vice president for the UN Water at the UN, and we connected. And I was following up, and I was aware his work before we met. We connected through the UN. So then, especially during the COVID era, then when I've seen his speeches, natural-based solutions, and then his piece on smart water, so I propose him if we can do something. About water, and then he was very supportive, very kind, very modest. We had our first water program on the World Water Day in March 2001 and then it has turned out an annual program, and we kind of made the global connections and collaborations, and especially first three, four of them, Professor Olja led and guide, and also we worked together in a sense that I brought one part of the speakers and he brought other parts. So it was also great, diverse speakers and also the level of the speakers from whether civil society, academia, UN, and youth, all that. So we already presented six of them, and 2023 we were part of the UN Water Conference. We presented a program, and then last year we participated and presented a program site event in Nice on the Ocean Conference, and we kind of we also had previously on the ocean again. So plastic also become whether ocean, whether water, whether land life, like plastic, is becoming a huge in every level. Not plastic, but also chemical, all all sorts of polluters on in environment. So then we become promoting, producing, and there are really great level of academicians and experts, and they also like to share and connect their research and their findings. So it's a platform to break down together, and then when it is a video, when it is posted as both a summary along with the full presentation or speech, so it becomes a really source where you know you can find diverse voices, diverse solutions, diverse ideas, and also we align them in support of the UN days, UN conferences, SDGs, sustainable development goals like Water Days. Also, we collaborate with an organization in India, IGEN Green Institution, Green Engineers Institute of Green Engineers. So they are focusing on energy SDG seven. So we contribute them, bringing speakers. Bircan Unver  47:40 So then they join us to our program. So really, it's an organic volunteer base. So that that actually, I was so proud that we got a call, invitation to submit the application for this accredited status, and it was June 2025 after the ocean conference. I think ocean conference kind of brought them cumulatively and maybe brought their attention. And then October they asked our official documents, the bylaws and and certificate of organization, which is the regular require any formal application at the UN, and then I I submitted them in I think it was October 1525 but I haven't heard anything, and then I thought maybe you know they didn't consider, and then literally a year later, in June, last June, we got approval, and with a, it's not just accredited for a special one particular conference. It is an observer status assembly to contribute draft ideas. I mean, to contribute drafts, draft resolution to observe, to participate, and then also to be responsible to provide every four-year quadrennial report. Let's say if we fail to produce contribution at any level to this cause, then you know we may lose that observed status, but of course we'll do our best to contribute and to continue. Michael Hingson  49:27 With all of the work that you've done in all of this, I want to come back to World Water Day in a moment. But with all the work that you've done and all the the the things that you've done in public television and so on, when you host these meetings or you participate in these meetings, do they get televised? Also, are you able to bring those to to the public through public television? Bircan Unver  49:53 When it is Zoom, then I edit within my time slot within the limits of. Time slots and QPTV provides two different time slots. One is 20-eight minutes, the other one is 50-eight minutes. So then, let's say if it's two-hour session, I you know a little bit edit and then title, etc. and part one, part two, and also depending on the length of the session or 20-eight minutes. So then I schedule them through the local channels, as we spoke at QPTV. Also, I make them available through our vmail.com/lmtv channel on web on the web. Also, when we have a summary or outcomes, so we also provide those links and share through social media. Try our best to make those information available, visible, and reachable. Michael Hingson  50:51 Well, that I'm glad you do that. I'm glad that it gets to be something that is a lot more publicized than you just attending a meeting-that's important, I would think, to do when when you talk about World Water Day and so on. One of the things that that I I understand you do is you compare water security directly with cybersecurity and gender equality. Those are three different sorts of things when you include water security. Tell us more about that. Bircan Unver  51:24 This was our latest program in last March, and we had in our prior program on AI a discussion on AI a public discussion on AI policy or AI arc. So he's a professor and at the SUNY, and he's a mathematician, and he's also teaching cybersecurity. And when I was talking about when we met about the water conference upcoming, actually in this December, in the United Emirates on I think December six to eight. Even I was thinking to attend, but I wanted part a bit this time virtually instead of going there. So when we were talking about and and I really like this idea and I say as I asked exactly what you asked for, and then his really statement explanation made great sense because everything is nowadays control troy some form of electronic or AI or a combination of those systems, right? Competing systems. So if or if there is a technical issues, that's one case. But if there is a hack, especially water is the life source for everyone, whether you are billion or trillion, or you are you know ordinary people on the you know everyday life. So water is the source for everything, including producing the energy. AI. So water is the life itself. So then, when he said, if any hacking, whether you know small you know some you know people with a bad intention or some maybe big corporation because some profit purpose they want to sell more you know bottled water whatever or some international security issues you you may name this many other things. So if a computer system, if the control mechanism, if the AI system, whatever that combination in that system, is hack, then everything is a huge risk, and that's number one. How it connects with the water. Also now you know we smart how everything is electronic. Everything and then when that somewhat the life collapses there. So including water, including energy. So everything is so much you know interconnected. And then how that the gender equality came. Also, we follow Michael the UN annual-based dedication team for each UN Day or conferences. For instance, last year, water and gender equality, because water and gender required is also so inseparable concept and conditions in many parts of the world, and then also our professor Emre Tokus, he also. Make beautiful connection that if woman or when woman, if and when women are more in the security, cyber security, IT technology sectors, they are more sensitive. They are more like maybe natural in their dealings, like mother protection. So more protective, so there is less risk than where it is now. So to increase the gender equality, both not burden on the woman, you know, where it's the water scarcity that woman has to carry the burden. Girls, even five, seven years old, when developing countries, when it comes to developing countries, and then if the girls are, and also that was staggering. Stats he gave sort of shocked me today because he is a professor at SUNY. So what I mean by that, he said one of his class has only four girls out of 31. of his class has only one girl. One of his class doesn't have no girl. So even though if if girls are girls are not getting in this field, how we gonna bring the gender balance in all cross-cutting sectors of society. So that's how both from the UN perspective, the dedication team, also cybersecurity, the profile from a university that girls are not showing attention, interest studying cybersecurity. That was the fact based on his class last semester. One Michael Hingson  56:46 of the things that you have done, as I understand, is you've written several books. Bircan Unver  56:53 Yes, there are more, but hopefully I could get work on them, publish them as well. The my first book was Michael, based on my interviews with artists and my reviews on art exhibits, and also when I had questionnaire surveys like with artists, galleries, academicians, professors, students. When I before my first life prior prior the U.S. So when I went back after four years and I was really eager to get in a job for as a TV producer and somewhat that didn't work despite all my efforts even I my project load and everyone was after me, but they want to take the project, but not give me the role what I deserve for. So then I kind of close myself, and then I said I want to compile my books, my articles, my interviews. So that was how my first book came about in Turkish. To create is the most sacred. So, like the value to give the highest value for the creativity, intellectual production. That is through all those interviews, reviews, and questions. So that's that was the first book. The second book is in a way a bridge again between U.S. and Istanbul, New York and Istanbul, or maybe L.A. New York and Istanbul. Because when I came in, also I've done freelance journalism, so I wrote some you know reviews and the magazine. I used to, you know, send and appear my interviews and reviews. So and it was include not too frequent, but it was include some of major exhibits, both from LA and also from the Metropolitan Museum in MoMA in New York. Also Turkish artists here. So I met them, you know, when I was living. I started living in here. So then I a combination of those, and also that was another metaphor developed in my mind when I was Istanbul. I was feeling like the labyrinths of arts. So that's my second book title in Turkish labyrinths in arts. So like you are like this kind of narrow and small world in Istanbul art worlds and very high competition, and then nobody expanding to New York and LA expansion means bringing some, for instance, Franz Bacon, Thomas Hart Benton, and Max Ernst and Marina Magritte. Those also the last part connecting with the New York Istanbul from my art based on my art background. Michael Hingson  59:51 So, were any of the books published in English? The Bircan Unver  59:54 last 120, 23 is English, but. It is a compilation concept is written me. I directed the project, and of course I have some pieces also beside the concept. But it is a compilation by 24 contributors. It is based on the JUC Media Research Writing Awards 2021 and 2023 High School Awards Project, and also it is also engaging the youth to involve the UN programs at an early age and encourage them award them. So that also the next one is going to be on the Water Action Decatur in the same line, same concept, and also I have a book project since 2022 I couldn't still 2022 2020 actually. I dream, therefore I am. I have 80% of the book manuscript is ready, but I couldn't finalize it, and so the other one also I was hoping but couldn't to have a book for the 25th anniversary of the latentium. Unfortunately, it didn't happen. It's a little bit seemingly not going to happen this year to come up 25th anniversary of late millennium, but I had 20 anniversary of the late millennium in Turkish, and so this is completely different issue because I introduced like Millennium both in Turkish and in English, so it's like Tiffany Sister is the Turkish one, and then I formed Turkish sister in 2010, and then so on the 20th anniversary of the Turkish organization, as it is association, official association. So I compile the first part, the concept vision, very much like Millennium, because it's the system. But the second part based on the programs, activities, and challenges in Istanbul. So this book also in English will be first the the manifesto and the first all the history will be very much in English, the original one. But the second part is going to be completely, you know, selected ideas and projects and programs from the website and public programs from the last 20-five years, and it's hard hard things to do. It it's very challenging. I couldn't do it. Michael Hingson  1:02:47 It's it's a lot of work. Well, Berjan, I I want to tell you that we have now been talking for more than an hour. Time flies when you're having fun. Man, I'm going to go. I'm going to have to go ahead and and end our time, but we'll have to do this again and and continue the discussion. But I really appreciate you taking the time to be here, and I hope that people will monitor your programs and and and read your books if they can read Turkish or English, whichever works. Troy Bircan Unver  1:03:18 has so many English pieces, and now everyone welcome to look out our website. And what's the Michael Hingson  1:03:26 website again? Bircan Unver  1:03:28 lmglobal.org. Michael Hingson  1:03:32 lmglobal.org. Okay. Bircan Unver  1:03:34 Yes, but the whole archive from 2019 to 2000 no, 2019 no. of course not 2019 1999 to 2018 The archive. Our initial website is light millennium.org Millennium is with double N double N. So the everything we are talking about, all the process, our UN programs, and the reports from the UN NGO briefings, some conferences we participated. If anyone has any question, I'll be happy to provide the link and you know to contact them. Michael Hingson  1:04:17 And we will put that information in the show notes, the notes for the podcast. So I want to thank you for being here. This has been absolutely informative. I really appreciate your time, and I hope the programs continue to go well. So I want to thank you again for being here, and this has just been a lot of fun. Bircan Unver  1:04:39 Thank you so much, Michael Kingston, it is great honor and privilege. Especially, you are a hero, and your your story is amazing, and you are also taking really one of the challenges works like producing these programs, and we never met in real life. And then this is also like Millennium and your work. How we connected through? Otherwise, there was no like regular environment or database environment that we could meet. Your work and your dedication and your inspiring contribution really connected us and bring us together in this session. Thank you, and I'm really grateful for that. Michael Hingson  1:05:29 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

An interesting picture featured in Minnesota Reformer featuring a “headless” Kendall Qualls - we got Blois's thoughts on this, voter turnout and fundraising numbers. House passing a Daylight Savings bill and also there is the push for AM radio in D.C.

An interesting picture featured in Minnesota Reformer featuring a “headless” Kendall Qualls - we got Blois's thoughts on this, voter turnout and fundraising numbers. House passing a Daylight Savings bill and also there is the push for AM radio in D.C.

Join our next FASO Show Live!https://artists.boldbrush.com/p/the-faso-showLearn the magic of marketing  with us here at BoldBrush!boldbrushshow.com--For today's episode we sat down with fine artist Tony D'Amico. Tony is a full-time representational painter and draftsman based in southern Connecticut whose work spans cityscapes, landscapes, coastal scenes, interiors, and everyday local subjects, all unified by his obsession with light, atmosphere, and strong design. He began his journey in art as a child, later studying graphic design, working as a commercial artist and technical illustrator, and eventually running his own marketing and design firm before transitioning gradually into fine art. Plein air painting transformed both how he sees and how he paints, forcing him to simplify quickly, capture specific moments in changing conditions, and infuse his studio work with authentic memories of place, light, and atmosphere. Tony is highly intentional in planning his compositions—often using thumbnails, photography, and Photoshop—to design compelling paintings that go beyond mere realism and invite viewers into a story. Drawing from his marketing background, he emphasizes that artists must learn to present and promote their work, build relationships with collectors and galleries, and accept rejection as a motivator rather than a verdict. For aspiring artists, he stresses persistence, continuous learning, good materials, honest self-critique, and the understanding that developing a true artistic voice and career can easily take a decade or more. Finally, Tony tells us about his upcoming shows and his revised book!Tony's FASO site:tonydamicofineart.com/Tony's Social Media:instagram.com/tonydamicofineart/facebook.com/tony.damico.524/Tony's Book:tonydamicofineart.com/books

Dans ce tout premier épisode de Vulgaire le jeu, on te raconte la vie de Claude Monet, le mec qui a décidé en 1883 que peindre flou, c'était le futur

Alex Murdaugh's original conviction leaned heavily on one piece of physical evidence: a white T-shirt investigators said proved he was standing close enough to shoot Maggie and Paul Murdaugh. New defense filings ahead of his retrial argue that story was built on a report that didn't originally say what jurors were told it said. According to court documents, blood-spatter analyst Tom Bevel's first write-up concluded the marks on the shirt were transfer stains, consistent with someone touching a bloody scene, not spatter from a gunshot. Defense attorneys say that conclusion shifted only after Bevel adjusted the shirt's colors in Photoshop, and the state chose never to call him to the stand to explain the change. It's one piece of a broader challenge the defense is mounting alongside a push to have unknown male DNA, pulled from under Maggie Murdaugh's fingernails, sent to the forensic lab Othram for genealogy testing the same technology used to identify Bryan Kohberger. Attorneys Dick Harpootlian and Jim Griffin have also raised questions about first-responder accounts that reportedly don't match up, and tips the defense says were forwarded to SLED without any confirmation of follow-up. The retrial is set for April 5, 2027 in front of a judge who has already made clear she won't be granting continuances, while Attorney General Alan Wilson keeps the death penalty on the table. This episode walks through the Bevel report in detail, lays the timeline against the David Camm case the defense is citing, and asks the question prosecutors will have to answer: if the shirt evidence changed once, what else might not hold up under a second look. The next hearing is set for August 14, and the defense has signaled this shirt fight is only getting started. Judge for yourself. SOCIAL LINKS & LEGAL FOOTER Join Our SubStack For AD-FREE ADVANCE EPISODES & EXTRAS!: https://hiddenkillers.substack.com/ Want to comment and watch this podcast as a video? Check out our YouTube Channel. https://www.youtube.com/channel/UC8-vxmbhTxxG10sO1izODJg?sub_confirmation=1 Instagram https://www.instagram.com/hiddenkillerspod/ Facebook https://www.facebook.com/hiddenkillerspod/ Tik-Tok https://www.tiktok.com/@hiddenkillerspod X Twitter https://x.com/TrueCrimePod This publication contains commentary and opinion based on publicly available information. All individuals are presumed innocent until proven guilty in a court of law. Nothing published here should be taken as a statement of fact, health or legal advice. HASHTAGS #MurdaughRetrial #AlexMurdaugh #HiddenKillers #TomBevel #BloodSpatterAnalysis #WhiteTShirt #TrueCrime #MurdaughTrial #SouthCarolina #DavidCamm 

Alex Murdaugh's retrial finally has a date, April 5, 2027, and a stack of defense motions that go straight at the evidence that convicted him the first time. Start with the shirt. Blood-spatter analyst Tom Bevel's original report reportedly described the marks on Murdaugh's white T-shirt as transfer stains, not gunshot spatter, before that finding changed following what defense filings describe as color adjustments made in Photoshop. The state never called Bevel to testify. Then there's the DNA. Investigators recovered an unknown male's genetic material from under Maggie Murdaugh's fingernails the night she and Paul were killed, and that sample was cataloged but never run through a genealogy database. The defense wants it sent to Othram, the same lab whose work helped identify Bryan Kohberger, and attorney Jim Griffin told the court the technology to trace it simply wasn't available when SLED first collected it. On top of that, attorney Dick Harpootlian says first-responder statements from the night of the killings contradict one another, and that tips forwarded to SLED may never have been followed up on. Judge Debra McCaslin, newly assigned to the case, has already made clear continuances won't be granted, while Attorney General Alan Wilson is keeping the death penalty in play against a man already serving multiple life sentences. This episode lays out all three motions side by side, weighs them against the David Camm wrongful-conviction case the defense cites as precedent, and gives the honest counterargument prosecutors are likely to raise. Two people are still dead at those kennels, and pieces of evidence tied directly to their deaths sat untested for years. The next hearing lands August 14. Both sides know how much rides on the next few hearings. Here is everything filed so far, in order. SOCIAL LINKS & LEGAL FOOTER Join Our SubStack For AD-FREE ADVANCE EPISODES & EXTRAS!: https://hiddenkillers.substack.com/ Want to comment and watch this podcast as a video? Check out our YouTube Channel. https://www.youtube.com/channel/UC8-vxmbhTxxG10sO1izODJg?sub_confirmation=1 Instagram https://www.instagram.com/hiddenkillerspod/ Facebook https://www.facebook.com/hiddenkillerspod/ Tik-Tok https://www.tiktok.com/@hiddenkillerspod X Twitter https://x.com/TrueCrimePod This publication contains commentary and opinion based on publicly available information. All individuals are presumed innocent until proven guilty in a court of law. Nothing published here should be taken as a statement of fact, health or legal advice. HASHTAGS #MurdaughRetrial #AlexMurdaugh #HiddenKillers #MurdaughTrial #MaggieMurdaugh #PaulMurdaugh #Othram #TomBevel #SouthCarolina #TrueCrime 

Hey everyone, Alex here

In this episode of The GaryVee Audio Experience, I sit down with Laura Desmond, CMO of Adobe, at Cannes 2026 for a Marketing for the Now conversation. We get into why experience maxing — IRL, in real life — is mattering more than ever, why VaynerX bet the farm on becoming an experiential agency, and why AI tools will get commoditized at scale exactly the way big data did. I share the Photoshop history lesson every fearful creative needs to hear, why the human matters more in an AI world, not less, and the jungle-gym career advice every young marketer should be writing down.You'll learn about:• Why Experience Maxing (IRL) Is Mattering More Than Ever• Why the Human Variable Matters More, Not Less• The Humility to Take a Step Backwards

Joey and Sean team up to cover the latest round of Team Blue updates. We're tracking the $22 billion Trump disclosure featuring meme coins, Binance pardons, and Larry Ellison's shadow over CBS before pivoting to the tragicomedy that is the Freedom 250 Fair. Find out why tech bros, AI George Washington, and Photoshop can't save the GOP from the ultimate crowd-size humiliation.Here's what's in the blender today:* The $22 Billion Windfall: We kick things off with a massive look at Trump's latest 2025 financial disclosures. From a casual $14 billion pulled from crypto ventures and licensing meme coins, to a $500 million UAE buy-in and a $400 million “gift” jet from Qatar, we break down how the ultimate art of the self-deal is currently operating at the highest level of government.* The Memory of Watergate: We head over to the Nixon Library to dissect Vice President JD Vance's recent comments, chortling at the historic scandal that took down a presidency. We trace Vance's fascinating, tragic evolution from a Yale-educated Hillbilly Elegy darling funded by Peter Thiel, who once called his current boss "Hitler" and “human fentanyl”, to a human weather vane whispering sweet nothings to an audience of one.* The Free Press Plot Twist: In a surprising turn of events, we look at the right-leaning Free Press dropping a devastating piece on Trump's deep financial corruption. We play out the inevitable corporate domino effect of what happens when the editor-in-chief of CBS News tries to poke the bear, and why the system treats DC insider trading like a legal perk while a military ranger betting on Kalshi gets instantly dragged down.* Fyre Festival 2.0 (The National Mall Edition): Finally, we wrap up with some high-quality crowd-size mockery at the “Freedom 250” Great American State Fair. It was supposed to be a massive Bicentennial-level blowout; instead, the 1,000 people who actually showed up got peeling columns, power outages, fake AI historical figures, and the single saddest, most depressed corn dog stand in American history.Grab your popcorn (If you're not at the National Mall) and stay amused; it's going to be a wild ride.0:00 Trump's $22 Billion Windfall 3:00 JD Vance Dismisses Watergate 3:30 Watergate History Refresher 6:30 Nixon's Resignation and Fallout 8:00 A Two-Tiered Justice System 9:30 The Free Press Exposes Trump's Corruption 10:30 Legal vs. Illegal Corruption Debate 14:00 JD Vance's Background Story 16:30 Vance's Flip-Flop on Trump 19:30 Trump's Freedom 250 State Fair Flop This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.truethirty.com/subscribe

Projetamos imagens ideais para o exterior e para nós próprios. Eduardo Sá defende que a felicidade exige transparência e que o "Photoshop" emocional nas relações impede a verdadeira paz.See omnystudio.com/listener for privacy information.

OLSEN TWINS SPOTTED! (Feels wrong!) Ahead of her wedding (maybe), a fan reads into Staind Guy's promo being used as packaging in Taylor's Toy Story single... If that feels confusing, that's because it is. T-Pain gets confused for footballer Tim Payne (but not really!) Plus, is SuperGirl queer? Did Arden Cho find her luggage? Is that Mia Thorton's actual body or a gorgeous Photoshop? Please stop pooping (outside the toilets) at Noah Kahan concerts, where was Brooklyn at Will Peltz's star-studded wedding and are THESE Off Campus co-stars hooking up? Logan Lerman's married, Lisa's split from a billionaire, Courtney Cox and her Snow Patrol bf broke up and JWOWW got married! Angelina wasn't invited! Neither were we! #ViQueensCall 619.WHO.THEM to leave questions, comments & concerns, and we may play your call on a future episode. Support us and get a ton of bonus content over on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Patreon.com/WhoWeekly⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Buy Bobby's new novel WE ARE GATHERED HERE TODAY ⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠, and preorder our upcoming book I WANT TO BE FAMOUS ⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠!

⭐️ Episode 809 - Dani Vee and Emily Gale - The Wild Unknown 2045 Dear gentle listeners, In this episode I chat to Emily Gale about her new dystopian middle grade novel set in 2045. We chat about …

Grok says: “In this episode of Randumb Thoughts, Darren dives headfirst into the moment AI stopped being a future concept and started showing up in your grocery cart. Fresh off a Meijer survey asking customers how they feel about AI comparing products, pre-filling shopping lists based on years of purchase data, and even handling checkout, he breaks down where the technology actually saves time (hello, never forgetting the pickles again) and where it crosses the line. He also shares how he used Amazon's AI during Prime Day to land a ridiculous Bitdefender deal and why he still won't let any algorithm spend his money without a human meatbag verifying the order. From there, Darren tackles the massive electricity demands of AI data centers, questions the sudden silence from the usual green crowd, and makes a strong case for running capable local AIs on your own hardware for real privacy. He walks through how AI is already transforming everyday work (including his own podcast production workflow for chapters, descriptions, and album art), demonstrates wild image-editing capabilities in Photoshop, and delivers a clear warning: these systems are excellent at pattern matching and photo manipulation, but they are not your therapist, financial advisor, or source of truth. Expect the usual unfiltered mix of practical tech talk, media criticism, listener stories, and value-for-value goodness.” Thanks for listening! EXECUTIVE PRODUCERS:Sir AnonymousMark KodraRonVAnonymousTHANK YOU FOR SUPPORTING THE SHOW! PLEASE SUPPORT RANDUMB THOUGHTS!TRY PROTONMAIL: https://t.co/9i2GPq3gNBTRY INCOGNI: https://incogni.cello.so/KpYfMWSF57i SUBSCRIBE / DONATE: http://randumbthoughts.com/donatePATREON: https://patreon.com/randumbthoughts CHECK OUT MY OTHER SHOWS: PLANET RAGE: https://planetrage.showUNRELENTING: https://unrelenting.showGRUMPY OLD BENS: http://grumpyoldbens.com Thank you for listening to Randumb Thoughts! Please, tell a friend!

Tiff and Dana address one of the most popular topics for Dental A-Team consultants: overhead! They talk about what it entails, where to start when looking to reduce it, critical questions to ask yourself about needs versus wants, and more. Episode resources: Subscribe to The Dental A-Team podcast Schedule a Practice Assessment Leave us a review Transcript: Tiff (00:00) Hello, Dental A Team listeners. Thank you for being here with us today. Thank you for listening. We say this every time, but we love what we do and we love bringing you so much valuable information. And the fact that Kiera can do all the podcasts she does blows my mind. ⁓ but she is a busy bee over there, and the fact that we get to do these as well is just really, really fun for us. It allows all of the consultants here on our team to really feel like we're giving back to you guys. So with that, I have Dana here with me today, and   Dana, gosh, we have been podcasting together for a really long time. I can't even put a number to it. And I remember, I don't know if you remember, but I remember I remember where I was sitting. I remember the thought process. And I remember it was me, you and Britt on a call on a Zoom link. And it was the first time marketing had said we want to do video with the podcast. And I was like, what? And video like was not, it was just like up and coming.   I didn't understand it. It was on Instagram. I was watching I was like, why am I watching you talk? Like the a podcast is to listen. Why am I watching you talk? And now I mean it's very normal and that's how I watch them. And I feel like I feel like it was like YouTube came back around, you know. But anyways, I remember that day vividly. ⁓ I don't remember what we were talking about, but I remember being like, I have to like do my hair. I'm gonna be seen.   DAT-Dana (01:23) Yeah. Yeah. I know it was   funny because we always could see each other, right, in those early days, but it was just like we weren't creating the video content for it. And I remember thinking exactly like who's gonna want to watch   Tiff (01:33) Yes.   DAT-Dana (01:35) us who's gonna want to watch us do this thing but then I see my kids literally like watching people play Minecraft and it's like their favorite thing and I'm like wouldn't it be more fun to actually go play? So I do feel like there is definitely this like niche of people like wanting to watch and like you know get a glimpse in of like the podcast world and just different worlds in general and so I agree with you. I remember the three of us just kind of being like who's gonna want to watch us talk to each other but hey we're so glad you're here.   Tiff (01:37) Yeah.   Yes.   It's true.   Yeah.   DAT-Dana (02:05) Yeah.   Tiff (02:06) Yes, I agree. And the three fur podcasts are hard. So hard when there's so many people virtually. And yeah, I r I remember the shock. I wish I could remember what the ⁓ podcast actually it was probably I bet you it was probably one that we did for Kiera. We probably it bosses day or something, yeah, 'cause if there are multiple of us. Anyways, that was that popped into my head this morning as I I always have to now have like prep for podcast time so I can like   DAT-Dana (02:12) Yeah.   Like Boss's Day or something like that. Yeah.   Tiff (02:35) just tame my hair or get my ring light just right. And I'm like, gosh, I remember the days that we did not have to do this. And then we have c new to Dental A Team consultants come on and I'm like, we're gonna podcast. And they're like stressed and I'm like, I get it. I just I get it. I saw them go talk yourself in the mirror for a bit first. You'll get used to it.   DAT-Dana (02:50) Yeah. Yeah.   I know   I remember in the early days I would always have to reframe my podcast because I'd see podcasting on my schedule and I'm like, ⁓ like I gotta get on. So then I just started reframing it. It was like time with Tiff, time with Britt, time with Kiera. And it's how I like kind of learn get over the like of the podcasting space. So I totally feel it when new consultants are like, I have my first podcast today.   Tiff (03:12) I love that.   Yeah,   yeah, and they all come to you, right? 'Cause I'll all schedule it and then they're like, Dana, what do I do? That's so cute. Yeah. I love the reframe. That actually like goes I think hand in hand with what we're talking about today. ⁓ but I think you can do that with anything and I have to remind myself, even like gosh, when I get up in the morning, I got up this morning and I went from for my walk and I was like, ⁓ this sucks and I was like, No, you get to be in the morning sun.   You get to move your body before anybody else in the house is awake. Like I think that's the part that's the hardest is like everybody else gets to sleep, you know? But you that reframe is so powerful. And we can look at a schedule and think I I look at my schedule and I'm like, shoot. This is so busy. Or gosh, I'm I'm like   So long today, and I have to reframe it often and be like, gosh, no, actually I get to do something really cool. And I get to wake up and go for a walk and I get to do these things or I get to go to an office and I get to be boots on the ground with other people. So I love that you mentioned that reframe, Dana. That was really smart. So today's reframe, which I love, I think this is one of the most popular conversations that we have. We get a couple of things here at Dental A Team. ⁓   We love everything that we get, but the most common, most popular things are systems, which we will help you with systems, I promise you. And there are thousands of podcasts I think that just Dana and I have done on systems and operations manual. So go look them up. We're not doing that today. And the second, which I actually really have grown to truly love, ⁓ is overhead cost reduction and and overhead analysis. And so many practice owners and leaders come to us and they're like, gosh.   what does overhead even mean? I know I had a conversation with a client last week that has been in the dental like consulting world for years and years and years. And w his question was what does that even what does it mean? Like overhead can mean so many different things to so many different people and so many different consulting companies. And for the sake of today's conversation and the sake of forever with Dental A Team know that when we say overhead, we are talking about top of the line   Whatever I always say if someone were to purchase your practice, what are the expenses they'd be taking over? Anything outside of that, your pay, your taxes, your debt, your debt will follow you typically, right? You can lump it into the loan, ⁓ but it's not overhead top of the line expense. So your debt, meaning your scanners, ⁓ your school debt, anything like that is outside of quote unquote overhead. So when we talk about overhead, it's top of the line and that had to that that   explanation, I think it can just vary. It can vary depending on who you're talking to. So today we wanted to reframe that, Dana Go. No, I love it.   DAT-Dana (06:08) and I don't want to interrupt you, but I think too just   just to be clear on overhead too, anything that you run through the business, right? Again, that's not something absolutely with your CPA, you structure it how you want. But understand that that's not an expense that somebody is going to take on when they take over the bracket.   Tiff (06:25) Yes, I love that. Thank you. Good clarification. so with this kind of reframe, every everybody's like reduce overhead, reduce overhead. And I totally agree. And a lot of a lot of companies, a lot of people, ⁓ a lot of strategists will come in and they're like, okay, what can we cut? And we for sure, like, we'll come in and look at what if there's space to make cuts, but our biggest piece is always we're not gonna spend a lot of time on it today because we've got a million other podcasts about it.   I think I just did one actually with Kristy not that long ago, but the first place we're gonna look is your collections. A lot of people will say, I need to over I need to produce. And I love the statement, you can't outproduce your problems. So if you're producing, producing, producing, producing, but you're still feeling like there's an issue. And if you're meeting the financial, like you're meeting your goal, your production goal, but you're still cash flow short, then there's an issue in your collections. And so look at your collections and Dana.   I would love to hear quick snippet, what are the areas that you tackle when it comes to overhead and it comes to collections? And then I want to talk about the reframes and the other pieces.   DAT-Dana (07:33) Yeah, so you're exactly right. The first thing I'm gonna look at is the collections number. I'll look at the total, like what is the total percentage and like what profit point do we need to get to when it comes to collections? And then the very next thing I'm gonna look at is your AR because honestly and truly I've been able to get practices out of cash flow crisis, out of really feeling that pinch simply by going after already produced   ⁓ monies. And so I think that those are usually the things that I look at. Okay, what are we collecting? What does our profit point need to be for healthy AR?   Right. And and obviously we're gonna talk about is that possible? How do we get your schedule to get you there? But then the very next thing I'm gonna look at is AR. Is there money that I can just quickly tackle that's already been produced that's gonna help the collections problem? So I'm looking at the total collections, collections percentage, and then what's sitting in AR, because if I can tackle that and make a really quick difference, ⁓ sure, we can budget things, we can line item your PL, we can we can chop where we need to, but those things are often the fastest, easiest, quickest fixes.   and like you said, you like outproducing the problem. If I can fix AR and then we can create systems that it doesn't happen again, oftentimes we don't even have to really touch production, right? Because we're already producing pretty well in a lot of these cases. So those are that's kind of where I start.   Tiff (08:46) Yeah.   Yeah, I love that. And it's something that makes such a massive difference. Knowing one, knowing your numbers, knowing what your numbers mean. So knowing your overhead, knowing your outgoing expenses is massive. And then looking to see, okay, well, if these are my outgoing expenses, what do I need to collect in order to profit? Right. And then if we're not collecting that, is it because production isn't where it needs to be? So what's our what's our bare minimum?   And is collections meeting that or is production meeting that so that collections can meet our bare minimum. If production is or is way above and our collections is just tanked, like I saw somebody the other day that was like 83% collections. They're like, we gotta produce more. And I Yeah, absolutely. If we want to maintain 83% collections and get your overhead in line, you for sure have to produce more. But also we can tackle your collections and get your collections up to that ninety-eight percent that it should be or above, and really not have to work   you harder as the provider work our numbers harder and get that collections up. It also kind of flows into Dana, I think the capacity that we just recorded a podcast. So probably the podcast ahead of this one I would assume is is about capacity. And I think that capacity conversation flows into this one really, really well. So all right, collections.   Go do it. We will harp on that for days, but go do it. If you need help with it, you're not sure, you don't know how to analyze it, you need help with your numbers, Hello@TheDentalATeam.com. We are honestly and truly here to help you. We will provide you as much information as we possibly can to get you on the right track. Now, something else that we like to do within that, and we talked about this on capacity, we talked about analyzing ⁓ fee schedules, right? But then we also need to analyze expenses. So when we're really looking at things and we're saying, okay.   Great, this is my overhead. I like to think, okay, does it have to be my overhead though? So a lot of people will look at staff cost, the employee cost. I actually I look at it, I kind of glaze that, you guys. I don't, I don't like to touch the staff cost unless it absolutely is extraordinary and there's maybe team members that are taking advantage or you're feeling like there's something culturally wrong in your practice, then I'm gonna say, okay, great.   Let's really take a look at this and make sure that we're being efficient with our time. We're not in overtime. We're not in those spaces. But I'm gonna kind of glaze at that unless there's a red flag somewhere else. And then I'm gonna look at those other expenses as well. And something that I really love to do is to analyze what do we need versus what we have. It reminds me of when Brody was little, we'd go to the store and he'd be like, Mom, is this a want or a need? Is it on your list? Is you have are you getting it because you just want it and it sounds exciting?   Or do we actually need this? And Dana, I love the conversation that you have around. I'm gonna say like analyze your vendors, analyze your contracts with vendors, but I love the conversation around ⁓ the wants versus needs when it comes to scanners, when it comes to mills. And I love I I miss the conversation actually. I miss the conversation of negotiate with your labs. And I miss that conversation because   I think that the mill has become such a bandwagon thing. It's been around for so long and it's such a bandwagon thing that everybody's that jumped into. But I love your your like evaluation of is it necessary? Is it actually going to save us the time and the money and get us the results that we want? And I would love, Dana, for you to talk through some of that and how you help your clients decide. Because I'm not against the mill, I'm not for it. I'm for it for the practices that it works.   And I'm for making sure that it's going to work and it's gonna do its due diligence. So what how is that conversation for you, Dana, when you talk to your practices about it   DAT-Dana (12:44) Yes. I love this conversation too, too. I   think first and foremost, I always want to know when when somebody wants to purchase something big like that. So whether it's a new scanner or whether it's a mill, like why.   Why do we want to purchase it? Is it because we have a scanner that we constantly use and we're constantly pulling and we never have it in the like appointment times that we need? So then we need to talk about adding another scanner. Is it that like we need another tool to show patients, but like could we just do IOPs a little bit more until we've got the budget set for the scanner? I'm not saying no to scanners. I'm not saying no to mills. I'm just saying, why do we want it? Is it the right time and is it going to do what you anticipate it's going to do as far as your budget goes?   Because I think we can talk about scanners and what's going to add so much more to my production. Okay, well, it is, but when are we going to use it? How often are we going to use it? Who's going to use it? How are we mapping it out to make sure that it really is putting more production on your schedule and it really is reducing your lab fees? Right. Scanner is a great tool for negotiating with a lab, but are you going to do that? Are you going to do the negotiations? Are you going to send them enough work to make it worth having the scanner?   Same thing with the mill. I'm always asking like why, right? And I know that kind of the mill is the hot spot or the mill is like the next big thing. And I think sometimes, you know, I hear a lot from doctors, well, it's gonna buy me back a lot of time. Well, it's only gonna buy you back time if you're going to let your assistant, right, help design and do the actual milling. If you're not gonna let that happen, then we're actually using more of your time than and sometimes it's not will you let them, it's do you have the capacity within your assistant team right now to be able to allow them.   Tiff (14:07) Yeah.   Mm-hmm.   DAT-Dana (14:21) to do those things because maybe we're short staffed in that area or maybe assistants are really hard to find. Well then maybe now's not the time to bring on the mill because it's actually going to use more of your time versus less of your time. And then you know all of these purchases typically come with either a large payout, right? Or a decent size loan that we're paying every single month. And so I like to kind of reverse engineer with my practices so they know cold hard facts how many crowns they have to do every single month.   to make that loan payment worth it or make that payout out of their emergency fund or their growth fund or wherever they're pulling that funds from. Hopefully not their emergency funds, but sometimes right, doctors get wild on us and it feels like an emergency to get that.   Mill. So knowing exactly how many crowns you have to do every single month. And then I'm saying, okay, let's go back through the last year. Let's see, did we even do as many? Because if we didn't do as many, then now's not the time. Let's get to that many crowns every single month, then take a look at the mill. Because so often we think, hey, the mill is going to save me on lab fees, but you have to do so many of them for it to save you on lab fees. And again, I'm not pro mill. I'm not like I'm neutral when it comes to mill. I think it's a great tool, but it's not the best tool for every   Tiff (15:25) Yeah.   Mm-hmm.   DAT-Dana (15:35) practice at that exact time. I think you really have to look   At and crunch things when you decide to make those purchases and really look at it as is it truly going to give your time back? Is it truly going to give you your lab fees back? Is it truly going to up your patient experience or up your diagnosis or whatever it is? Because that is when it makes it worth it. So I just like to like have the conversation, review the numbers together, and kind of say, hey, like this is the reality of the purchase. I, you know, I am.   Totally understand the like purchase in the feels, right? I get that. I've done it. I'm human. I think we've all been like, but this is gonna feel so good when I have it. But I think look at the numbers and make sure because these things can really hit your these these debt services can really hit your profit points if it's not set up correctly and you don't know kind of the benchmarks you have to hit to make it help with profit versus hurt.   Tiff (16:11) Yeah.   Yeah.   Absolutely. I think it's so beautiful. And a follow-up to that too is if you already have the mill, you already have the scanner, you already made the purchase or the laser, Dana, as you were talking, I was like, the lasers, the lasers. There's so many there's just so many really cool tools that dentistry has that makes us feel like we've got to jump on it to be the most progressive, to be the most exciting, to stay up with the times, to to not fall behind. And really they're just fun and exciting. It's like   ⁓ Canva and you know we only had Photoshop and then Canva came out and then we had, you know, all of these different opportunities. And it it can be easy to jump on board with them. So if we already have jumped on board, we didn't have this conversation, or maybe we did, and then gosh, we're just falling a little bit short. This is the overhead analysis as well. This all flows into that overhead analysis. So as you're looking at your overhead and you see those   those loans under on you have your bottom you have your top line and you have a bottom line. And at your bottom line, when you see those other loans in there and you're like, gosh, Def, Dana, I just I'm not using the scanner as much as I thought I did. I know both of us have I all of our consultants are really, really fantastic at having conversations like this that say, okay, great, why? Dana, you said something earlier, you said it asking more questions, right? Like I want to know, I want to know why you want it.   what it's gonna do for your practice and then reverse engineer it. And we are really great at pulling out the why for anything. So if you're not, if you bought it and you're not using it, we're gonna say, well, why aren't we using it? Is it because it's not the tool that we needed or we wanted and or we don't have the patient base for it or is it because we're not trained, we're not holding accountabilities. And ultimately, if this thing isn't working for your practice, it's not doing what you wanted it to or gosh, you just hate it. You don't like it. You don't want to use it.   This is a conversation with the company that you can have. You can call the company and say, Hey, what can I do? How can I how can I get out of this? I've had ⁓ I've had doctors that have had this conversation with them and they do have like a smaller buyout, right? They're like, Well, we'll buy it back from you, but you're gonna it's kind of like taking a car in and you you're you know, you're under.   So you you owe a little bit more on your car and then you owe on the car that you're buying. So it kind of sucks because you do have to pay that out, but could getting out of that contract early, sending the equipment back, save you in the long run because you haven't paid that total balance. Or a lot of doctors will call and they're like, yeah, absolutely. I have a doctor actually who's looking for one that might buy it from you.   And so you can you can sell this equipment as well if it's not working for you. So I don't ever want doctors to really just feel so stuck in the decisions that either they've made or that they want to make and you have that kind of decision paralysis. So as we're going through that looking at ⁓ cost control and overhead control.   Part of the conversation as well. So there's the projecting side and really looking at do I do I need this? What can it do? And then there's the evaluation side of is this working for me? And Dana, I think that same conversation when it comes to like marketing. Are is my marketing ROI coming in? Is it getting me what I what I thought it was going to? There's magazines investments, there's all of these like hottie-totty ⁓ marketing efforts that are coming around right now. They're trying to like really reinvent a lot of wheels.   And projecting and seeing, does this fit my avatar? Is this gonna work? Gosh, your telephone company, I know our like cable and internet. We don't even have cable, but it's the same company, right? And I'm like, why are we paying for cable and internet? And it just jumped like $90. And I'm like, what the heck? It's a call and a conversation with your vendors and looking at, okay, am I getting the most value for what I'm spending? And that I think Dana helps us to calm the storm.   Because what happens typically is we're like, okay, I gotta produce more in order to afford my life. And it's just like personal, right? I gotta work more in order to afford the lifestyle that I want. Well, maybe the lifestyle that you want can be had with less debt or less stuff, you know, and really evaluating your quote unquote lifestyle in the practice and out.   DAT-Dana (20:43) Yeah, I agree with you because like dental offices, do we have to spend money? Do we have expenses? Yes, absolutely. Let's make sure those expenses are doing what we need them to do and and we have an ROI on those expenses. And I do feel like just doctors highlighting like, don't forget those bottom of the line things because oftentimes it's like, hey, my payroll's in line, my rent's in line, my marketing is in line, everything's in line, but I don't have any profit at the end of the month. And I think don't forget to take a look at oftentimes I think there's an impression of doctors that like those below the   aligned things are like fixed expenses and oftentimes they are variable expenses that we can do something about it. We can make changes like you said, sell it or start using it, right? Or incorporating a way for it to help us produce or collect more. I think just don't forget those bottom of the line things and don't look at them as hey, those are fixed things, right? A lot of times those items aren't. We can either move the needle as far as using them or move the needle as far as offloading them.   Tiff (21:15) Uh-huh.   Yes.   DAT-Dana (21:42) Right. I just had a conversation with the practice. Like, why do we have two scanners? Right. Like, why do we need them? Walk me through it. If if you can walk me through why and it makes sense, totally keep your scanners, utilize them, have it help you. Right. But if we don't need them, then let's not have that sit there every month and pull from that profit that you so desperately need.   Tiff (21:45) Mm-hmm.   Yeah, I love that conversation and I think it's something that's a piece of value that the consulting team brings to our clients that I think is totally undervalued. I know I have clients that are like, Teff, I wanna buy this thing. And I'm like, Okay, cool. Like, tell me why. How are we gonna afford it? Great. I have a doctor that was like, I like this scanner better, but I bought this scanner before I knew that this scanner was better. And I was like, Awesome. Well it sounds you want that scanner. He's like, Yeah, I'm gonna get it. And I said, Cool, what are you gonna do with that scanner that you don't like?   Because that one is still being paid on. It's still in your office. And he's like, okay. So it's like we have this innate ability, right, to see things very, very cleanly. I had a conversation just last week with a client that was like, Tiff, what do I do? And it was like a personnel thing, right? I said, Listen, my job and the and the superpower that I have for you is to be very black and white in business. I'm not emotionally attached to what's going on in the practice. I I love you, I love the practice, I love the team.   And I I have emotions towards you, but I'm able to separate it out and say, hey, do this, don't do this, or these are the black and white opinions that I see. These are the pros and the cons that I can see. I'm not emotionally attached to one scanner is better than the other. I'm emotional, I'm not emotionally attached to the money that's coming in or going out. I am neutral and I'm able to say it is or it isn't. And so that value, that ROI is not always really easy to see.   in the numbers until you look backwards and say, gosh, actually I sold that scanner because of or I didn't buy that and gosh, I'm so happy. Or I was able to invest in my team because I could see my shortcomings or my accountability faults or the accountability that Dana was able to give me so that I could give my team like those spaces are just so   valuable in this overhead analysis is huge. And I know you and I do it often. I know the rest of the consulting team does. Gosh, Kristy, Kiera likes to say she's like a truffle hunting ⁓ little, you know, little piggy out there finding the dollars. And that's how she does it as well. And Nikki and Pam and all of you know, Diana, every one of us are out there looking for those dollars from that black and white kind of business mindset because it's easier for us as a pulled out   Peace, right? And Dana, I just think that is a space that doctors, I can't imagine making those kinds of decisions by myself, right? Even just as simple as purchasing a mill. Like because it's so it's like walk walking into Louis Vuitton with a credit card with no limits and expecting me to not leave with a purse, right? Because in my head it's paid for, it's done, it's it's good.   But then on the flip side, I've got expenses and other things and they've always got just gotta have that person who can be that sound mind.   DAT-Dana (24:58) Yeah. Yep. I agree with you.   Tiff (25:00) All right, Dana, so overhead cost analysis. ⁓ I would say, and I think Dana, add anything you can think of. My pro thought process is figure out your bottom line first of all. Figure out what are your costs, your fixed costs that aren't changing. If someone were to purchase your practice, then then look at what's left over. How much debt do you have? what do you want to be making? Are you paying yourself and are you paying yourself what you want to be making?   And are you saving money? So what do those buckets look like? That to me is your is your bare minimum. You have your bare minimum of this is what it takes to keep my practice open and my employees paid. And then you have your bare minimum of this is what I want my practice to look like. So I like to add that fluff in there. I know Dana does as well. We have our bare minimum and then we have our bare minimum. And our our second bare minimum is the number that I work from ⁓ and tack on a little bit extra. So overhead analysis, look at what your numbers are, look at what your   DAT-Dana (25:46) How many? Yeah.   Tiff (25:55) Collecting, always look at collections and then look at what your debt looks like and look at what your spending is. Is there anywhere in there that can be negotiated? Is there anywhere in there that maybe we need to start using a tool a little bit more to get it paid, paying for itself? Just like you want your team to pay for themselves, you want your equipment to pay for themselves as well. Dana, is there anything you can think of that I missed that I didn't add in there as an action item that they can scurry on home to do?   DAT-Dana (26:24) No, I think I think that those are great tools for them to really be able to slice and dice and look at those pieces.   Tiff (26:31) Awesome. All right, guys, go do the thing. Pull up your PLs, pull up month by month, pull up year to date, pull up last year's, and look at what your expenses truly are. And when you get to the point that you want some third-party perspective, some eyes on it, if you're a current client, you should be doing this with your consultant too. So do it. I want you to know how to do it and I want you to do it with your consultant as well. If you're not yet a consultant, you're ⁓ someone who is a listener and you want you're not a consultant, you're not a client.   You're a listener and you want help with this, please reach out. Hello@TheDentalATeam.com There's also a link on our website, TheDentalATeam.com, that you can schedule a consult with us and they'll help you run through a lot of that information as well. We are here to help. So let us know how we can best serve you and how we can help you in the short and the long run. Hello@TheDentalATeam.com. All right, guys, and we will catch you next time. Thanks so much.  

What happens when a creative mind, a startup operator, a cancer survivor, and a humanitarian all live inside the same person?In this episode of Clover, I sit down with Melissa Wood, founder of Formis and Curate, to explore the winding path that led her from a small town in North Carolina to the startup ecosystem in Austin. Melissa's story spans early tech startups, design and photography, turning down life-changing opportunities, surviving cancer, humanitarian work in Ethiopia, and building companies rooted in solving real-world problems.What stood out most was Melissa's ability to notice gaps others accept as normal;  and then build solutions around them. Whether helping homeowners navigate renovations through Formis or simplifying conference experiences through Curate, her work is driven by a simple question: “Why doesn't something better exist?”This conversation is about resilience, leadership, community, and the unexpected ways life experiences shape the companies we build.In this episode, we discuss:How an accidental discovery of Photoshop in the mid-1990s launched Melissa's career in technology and design.Why she walked away from opportunities—including an early chance to join the team behind Me.com—and how she evaluates big decisions.The life-changing impact of surviving cancer and how that experience influenced her approach to work, family, and entrepreneurship.What she learned from living and working in Ethiopia, including lessons about community, presence, loyalty, and leadership.How she built Curate, an AI-powered event discovery platform, in just days using no-code and AI tools after identifying a problem she'd personally experienced for years.Why trust breaks down in industries like home renovation and how technology can create transparency, alignment, and accountability.Notable Quotes“Trust isn't built in one big moment. It's built through patterns.”“The best products are born from real experiences.”“If the system reflects that someone is being heard and understood, it creates a feeling of partnership.”Resources & Links MentionedFormis – AI-powered platform designed to improve transparency and communication in home renovation projects.Curate – Event discovery and scheduling platform helping people navigate conferences, tech events, and community gatherings.Lovable – AI-powered development platform Melissa used to build an early version of Curate.Claude – AI assistant Melissa uses for ongoing product development and iteration.FoundHers – Austin-based organization supporting women founders and entrepreneurs.South by Southwest (SXSW) – The event experience that inspired Curate.Austin Tech WeekLA Tech WeekAustin TV FestivalMelissa's story is a reminder that entrepreneurship doesn't always begin with a grand vision. Sometimes it starts with a frustration, a life experience, or a problem you simply can't stop thinking about and the courage to do something about it.

Qué tal, queridos Curiosinautas. Bienvenidos a un nuevo CuriosiMartes, el resumen semanal de noticias tecno del tío Fabián.Esta semana viene cargada: el regreso inesperado de Commodore con un teléfono retro pensado para comunicarse sin caer en redes sociales, los problemas de Android 17 en los propios Pixel, la nueva guerra tecnológica entre China, Estados Unidos y la Unión Europea, y un cambio clave en Apple con la posible llegada de una etapa más enfocada en diseño y hardware.Además, hablamos de inteligencia artificial en serio: la salida de figuras clave de Google DeepMind y Meta, las advertencias de Sam Altman sobre una IA que podría superar intelectualmente a los humanos, el concepto de “rendición cognitiva” y el riesgo de dejar de pensar por depender demasiado de los chatbots.También exploramos el futuro de la robótica versátil junto a DEEPRobotics, con avances en robots cuadrúpedos, embodied AI, automatización y nuevos formatos como el M20 y su pequeño compañero robótico.La robótica ya no es solo industrial: empieza a mezclarse con asistencia, autonomía, seguridad, compañía y nuevas formas de interacción con el mundo físico.Y para cerrar, una noticia que parece ciencia ficción: Midjourney Medical trabaja en un sistema de escaneo corporal con medio millón de sensores ultrasónicos, pensado para analizar el cuerpo completo en menos de 60 segundos y ayudar en la detección temprana de enfermedades.

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What happens when someone who grew up in the Lucasfilm Games golden era decides that today's AI tools are failing creatives? Mike Levine has spent more than 30 years building at the intersection of games, XR, VFX, and interactive storytelling—and his verdict is clear: the current AI stack is a fragmented, overcomplicated mess that turns directors into prompt engineers.Mike started as a tester at Lucasfilm Games (later LucasArts), working his way into the art department on titles like Sam & Max and The Dig before helping ship live-action Star Wars games such as Rebel Assault and Jedi Knight II. He later built rotoscoping tools used across the VFX industry, collaborated with ILM and Pixar, experimented with mobile AR games for Hasbro and HoloLens, and dipped into crypto gaming—before finally co-founding MovieFlow (now FilmSpark), an AI-native production platform designed so that filmmakers, agencies, and showrunners can move from script to screen without needing a computer science degree.The AI XR news you should know: Apple taps Google Gemini to power Siri, acknowledging that building world-class LLMs in-house makes little financial sense. Meta cuts 10% of Reality Labs, right-sizing its VR bets while pivoting toward wearables. Xreal raises another $100M amid questions about Chinese state influence and data flows. Higgs Field lands $80M at a $1.3B valuation for AI cinematography tools that many filmmakers still find unreliable. Wikipedia signs licensing deals with major AI companies after years of being scraped for free. OpenAI invests $252M in Sam Altman–backed Merge Labs, raising fresh conflict-of-interest questions.Key Moments Timestamps:[00:23:02] From Boston journalist-to-be to accidental hire at Lucasfilm Games[00:26:24] The “test pit” culture at Lucas and how Nintendo experience got Mike in the door[00:28:45] Moving into the art department, learning Photoshop from early legends, and shipping Sam & Max[00:31:15] Live-action Star Wars games: Rebel Assault, Jedi Knight II, and convincing George Lucas[00:34:38] Visiting Pixar with new VFX tools and recognizing the same creative “magic” as LucasArts[00:36:24] Doug Trumbull's influence on Mike's sense of cinematic possibility and immersion[00:43:27] The urinal meeting at Magic Leap and what early spatial computing got right (and wrong)[00:49:00] Why most AI tools are “dark ages” for filmmakers: node graphs, 10+ subscriptions, no story view[00:51:00] Building MovieFlow/FilmSpark: story-first, timeline-based AI production for long-form and vertical shows[00:53:00] The Neighborhood Podcast: a 90-second vertical murder mystery as proof-of-concept for AI-native seriesWhen humans can generate shots, scenes, and even entire episodes in minutes, the bottleneck shifts from production to vision. Mike argues that the winning AI tools will be the ones that let directors see their whole story, maintain continuity, and iterate fast—without ever feeling like they left the edit bay for a dev console. His vertical drama collaboration with Charlie, The Neighborhood Podcast, is an early look at what happens when narrative craft meets AI-native pipelines instead of fighting them.This episode is brought to you by Zapar creators of Mattercraft—the leading visual development environment for building immersive 3D web experiences. Build smarter at mattercraft.io.Watch the full episode on YouTube and subscribe to the AI XR Podcast for weekly conversations with the people building the future of AI, XR, and interactive media. Hosted on Acast. See acast.com/privacy for more information.

Herkese merhaba! Bu hafta yapay zeka dünyası kelimenin tam anlamıyla alev alev... Beyaz Saray'ın nükleer silah alarmına geçer gibi kısıtlamalar getirmesinden girdik , Çin'in Alibaba ve DeepSeek gibi devlerle bu duruma verdiği hızlı cevaplardan çıktık. Claude'un yeni MCP entegrasyonu sayesinde Photoshop ve çeşitli araçlarla bağlantı kurarak grafik tasarımcıları nasıl ihya ettiğini detaylıca anlattık. Bununla da kalmadık; Midjourney'nin sadece görsel üretmekle kalmayıp, ultrasonik ses dalgalarıyla çalışan ve MR çekimini bir "spa" keyfine dönüştüren yepyeni bir tıbbi tarama cihazı projesiyle Tıp dünyasına nasıl bomba gibi düştüğünü inceledik. Elon Musk'ın Grok hamleleri , Avrupa Birliği'nin 2 Ağustos'ta yürürlüğe girecek katı Yapay Zeka Yasası ve Meta'nın içeride yaşadığı büyük motivasyon krizi de masamızdaydı. Ayrıca yerli yapay zeka modelimiz TÜBİTAK Bilge'nin altyapısını ve Türk Telekom'un görme engelliler için geliştirdiği stadyum projesini de değerlendirdik. Peki sizce içeriklerde insan dokunuşu mu olmalı, yoksa yapay zeka da aynı tadı verebilir mi? Gerçekle yapay zeka arası sizin için fark eder mi? Yorumlarda kendi görüşlerinizi paylaşmayı unutmayın! Videoyu beğenmeyi, sevdiklerinizle paylaşmayı ve kanalımıza abone olmayı unutmayın, iyi seyirler! 00:00 - Giriş ve ABD'nin Nükleer Silah Statüsünde Yapay Zeka Kısıtlamaları 00:36 - Çin'in Hızlı Atağı: DeepSeek, Qwen ve Amerika'yı Tokatlamaya Hazır Veri Merkezleri 06:01 - Claude'dan Tasarımcılara Kıyak: MCP ile Photoshop Entegrasyonu 07:33 - Midjourney Tıp Dünyasında: MR Kalitesinde Ultrasonik Tarayıcı Spa Cihazı 12:22 - Grok 1.5 Video Modeli, Elon Musk'ın Destekleri ve Görme İmplantları 14:52 - Microsoft'un AWS'ye Geçişi ve Goldman Sachs'tan 7.6 Trilyon Dolarlık Yatırım Beklentisi 16:30 - Mistral "Le Chat" Yapay Zeka Memleri ve Test Tabloları 17:58 - Avrupa Birliği Yapay Zeka Yasası Geliyor: Şeffaflık Zorunluluğu ve Dev Cezalar 19:48 - Soyma Uygulamalarına ve İstismara Karşı Katı Avrupa Önlemleri 21:46 - Güney Kore'nin Endişeleri ve Yerli Yapay Zeka TÜBİTAK Bilge Tartışmaları 25:27 - Meta'nın Çöküşü: İşten Çıkarmalar ve "Cenaze Evi" Gibi Çalışma Ortamı 26:30 - Türk Telekom'un Görme Engelliler İçin Geliştirdiği Özel Stadyum Projesi 28:50 - Yapay Zekaya Karşı İnsanı Üstün Kılan Şey: Kusurlarımız ve Nüanslar 29:33 - Kapanış ve Yorumlarınızı Bekliyoruz #fable5 #claudemythos #yapayzeka

Elyse Kelly joins the show to discuss her meandering journey from childhood Disney fascination to her impactful work in animation and documentary storytelling. She discusses the importance of curiosity, storytelling, balancing passion with practicality, and her thoughts on the future of creative careers amidst technological change.

Send us Fan MailYour sheds can be built like a premium product and still get judged like a commodity if the photos don't match. From the first scroll on Google to the first click on your website, buyers are making fast decisions about trust, craftsmanship, and value based on visual cues, not just specs. We dig into the real psychology behind shed marketing images and why “good enough” photos quietly cost leads in a market where shoppers compare 10 builders at once.Ryan Glick from Crafted Generations joins us to break down what photorealistic CGI actually is, how computer generated imagery can look like a real-life photo, and why that realism matters for authenticity. We talk through the common problems in shed industry imagery, the difference between basic cut-and-paste Photoshop work and true photorealism, and how better visuals can elevate a brochure or catalog so dramatically it feels like a different company. Ryan also explains how modern workflows blend 3D modeling, scene creation, and careful craft to produce high-resolution images that hold up on websites, social media, and print.We also zoom out to the bigger story: shifting buyer behavior after COVID, the move from print to online advertising, and how small marketing upgrades compound into real ROI over time. Ryan shares how faith, mission work, and stewardship shape his view of business success, and we close with prayer over families, companies, and the industry.Subscribe for more real conversations with shed builders and industry pros, share this with someone who needs better visuals, and leave a review so more listeners can find the show.For more information or to know more about the Shed Geek Podcast visit us at our website.Would you like to receive our weekly newsletter?  Sign up on our website: shedgeek.comFollow us on Twitter, Instagram, Facebook, or YouTube at the handle @shedgeekpodcast.To be a guest on the Shed Geek Podcast visit our website and fill out the "Contact Us" form.To suggest show topics or ask questions you want answered email us at info@shedgeek.com.This episodes Sponsors:Studio Sponsor: Shed ProSolar BlasterCardinal ManufacturingDigital Shed BuilderVelocity 360

How Adobe Quietly Powers the World (and the AI Fight for Creators)This episode of Jimmy's Jobs of the Future visits Adobe's London headquarters to explore how Adobe's influence extends beyond Photoshop and PDFs into marketing technology that powers personalized experiences for major brands and institutions like Tesco, the Premier League, banks, Channel 4, Sky, Disney, and governments. VP Simon Morris explains Adobe's creative, document, and marketing solutions, how customer data is unified to deliver tailored communications, and highlights a campaign recreating Edvard Munch's physical brushes as Photoshop tools. The discussion covers Adobe's UK-wide initiatives, including tools for Women's FA Cup clubs, the Adobe Digital Academy, and government skills programs. Policy lead Stefanie Valdes-Scott addresses AI governance, creator protection, copyright, trust, content attribution via content credentials, and the unresolved tension between AI-enabled creativity and creators' fear of losing control of their work. 00:00 Adobe Hidden Influence 01:57 Quick Adobe History 02:45 Inside London HQ 04:15 Brands Powered By Adobe 05:40 Premier League Personalization 07:28 Banking Experience Design 10:05 Creativity Meets Data 13:11 Hiring Modern Marketers 14:08 Tools For Everyone 17:33 AI Productivity Debate 20:25 UK Initiatives And Skills 22:32 Creator Copyright Fears 24:01 Policy And AI Governance 25:31 Copyright And New Rights 30:30 Content Credentials Trust 32:55 Final Takeaways ********** Follow us on socials! Instagram: https://www.instagram.com/jimmysjobs Tiktok: https://www.tiktok.com/@jimmysjobsofthefuture Twitter / X: https://www.twitter.com/JimmyM Linkedin: https://www.linkedin.com/in/jimmy-mcloughlin-obe/ Want to come on the show? hello@jobsofthefuture.co Sponsor the show or Partner with us: sunny@jobsofthefuture.co Check out our clips channel here! ⬇️ https://www.youtube.com/@JimmysJobsClips Credits: Host / Exec Producer: Jimmy McLoughlin OBE Producer: Sunny Winter https://www.linkedin.com/in/sunnywinter/ Junior Producer: Thuy Camera Operations: Felix Cohen Learn more about your ad choices. Visit podcastchoices.com/adchoices

Sixtysomething_S3_Ep2 – Meet CanvaHave you heard people talking about Canva but aren't quite sure what it is—or why so many people love it?In this episode of Sixtysometing, your host, Grace Taylor Segal, shares introduces listeners to Canva, the free online design platform that has transformed the way millions of people create everything from greeting cards and photo books to business materials, social media graphics, family cookbooks, presentations, and legacy projects.But this episode isn't really about software. It's about creativity. It's about having access to tools that simply didn't exist for ordinary people for most of our lives.Grace shares her own journey from teaching herself Photoshop with a bootleg copy and learning design from books, to creating magazines, online courses, podcast graphics, legacy projects, and more. She explains why she believes Canva has “democratized design” and why that's such an exciting development for people in our stage of life.You'll learn:• What Canva is and how it works• The inspiring story behind Canva founder Melanie Perkins• Why Canva changed the design world forever• What you can create with Canva• What's included in the free version• Whether Canva Pro is worth considering• Favorite Canva features like Background Remover, Magic Resize, Magic Write, and AI Image Generation• How Canva can help with family history, memory books, photo collections, cookbooks, travel journals, and other legacy projects• Why Canva is especially valuable for people over 60• How creativity and learning don't have an expiration dateMost importantly, you'll be encouraged to think about what you've always wanted to create—and what might finally be possible now.☀️ ☀️ ☀️Canva ResourcesWant to learn more about Canva?I've included links to several beginner-friendly Canva tutorials as well as Canva Design School, which offers free courses, tutorials, and certifications.Whether you're a complete beginner or just curious about what's possible, these resources are a great place to start.Canvahttps://www.canva.comCanva Tutorial by Canvahttps://youtu.be/V9LtRF6EbyY?si=FDRCnNUYxeC8-vEfIn this video we'll show you the basics of Canva and how easy it makes design. This Canva for Beginners video series is here to show you how to get started with Canva and bring your ideas to life.With limitless potential for customization and templates, it's simple to make designs your own. Once you learn how to navigate around the editor, you'll be designing like a pro in no time.

In this episode, I take a moment to acknowledge the recent passing of Photoshop icon Jeff Schewe and discuss my just-announced expedition to South Georgia Island for September 2027.South Georgia Island ExpeditionFalkland Islands ExtensionSupport the showWild Nature Photo TravelPhotography Workshops and Expeditions around the Worldwww.wildnaturephototravel.comSupport the Show and fellow Nature Photographer: https://www.buymeacoffee.com/JoshuaHolko/membershipFind us on Social MediaFacebook: https://www.facebook.com/Joshuaholko/Twitter: https://twitter.com/HolkoJoshuaInstagram: https://www.instagram.com/joshuaholko/Need to Contact us? info@jholko.com 

In this episode of the AART Podcast, host Chris Stafford sits down with renowned American digital collage artist Maggie Taylor, whose dreamlike, surreal imagery has redefined the boundaries between photography, technology, and fine art.Known for her pioneering work in digital collage, Maggie Taylor creates richly layered visual narratives that blend 19th-century photographic elements with contemporary digital tools. Her work invites viewers into imaginative, often whimsical worlds—where memory, symbolism, and storytelling converge in unexpected ways. In this intimate and insightful conversation, Maggie shares how she discovered her distinctive artistic voice, her transition from traditional photography to digital media, and how tools like Photoshop became central to her creative process.Raised in a creative environment and married to photographer Jerry Uelsmann, Maggie Taylor developed an early appreciation for photographic experimentation. Yet she forged her own path, becoming one of the most recognized figures in digital art. Her work has been exhibited internationally and is held in major museum collections, including the Art Institute of Chicago, the George Eastman Museum, and the Smithsonian American Art Museum.On AART, Maggie reflects on the evolution of her career, the role of intuition in her artistic decisions, and the balance between control and discovery when creating complex digital compositions. She also discusses the emotional resonance of her work, the importance of curiosity, and how artists can embrace new technologies without losing their authenticity. This episode offers a fascinating look into the mind of an artist who has quietly but profoundly influenced contemporary visual culture. Whether you're an artist, photographer, or simply someone drawn to imaginative storytelling, Maggie Taylor's journey is both inspiring and deeply thought-provoking.Maggie's links website: www.maggietaylor.com Instagram: @maggietaylor.art Some favorite women artists: Julie Blackmon, Sandy Skogland, Lori Nix, Cig Harvey, Marion Peck, Lori Vrba, Claire RosenDinner party guests: Patti Smith, Aimee Mann, Laurie Anderson, Tilda Swinton, Kara Swisher, and Eve SchoolerKeywords: Maggie Taylor, digital collage artist, American artist Maggie Taylor, surreal digital art, digital collage photography, contemporary digital artists, Photoshop art, fine art photography, AART podcast, Chris Stafford podcast, women artists interview, visual storytelling, surrealism in digital art, creative process artists, modern collage art, experimental photography, women in art podcast, artist interviews, contemporary art podcast, museum exhibited artists, digital art techniques, storytelling through images, imaginative art, photography and technology, Jerry Uelsmann influence, American contemporary artists, art podcast interviews, Women Unscripted podcast networkBecome a supporter of this podcast: https://www.spreaker.com/podcast/women-unscripted--4769409/support.Host: Chris StaffordProduced by Hollowell StudiosFollow @twomenunscriptedpodcasts on InstagramOn Facebook at Women Unscripted PodcastsEmail: hollowellstudios@gmail.com

In this episode of the AART Podcast, host Chris Stafford sits down with renowned American digital collage artist Maggie Taylor, whose dreamlike, surreal imagery has redefined the boundaries between photography, technology, and fine art.Known for her pioneering work in digital collage, Maggie Taylor creates richly layered visual narratives that blend 19th-century photographic elements with contemporary digital tools. Her work invites viewers into imaginative, often whimsical worlds—where memory, symbolism, and storytelling converge in unexpected ways. In this intimate and insightful conversation, Maggie shares how she discovered her distinctive artistic voice, her transition from traditional photography to digital media, and how tools like Photoshop became central to her creative process.Raised in a creative environment and married to photographer Jerry Uelsmann, Maggie Taylor developed an early appreciation for photographic experimentation. Yet she forged her own path, becoming one of the most recognized figures in digital art. Her work has been exhibited internationally and is held in major museum collections, including the Art Institute of Chicago, the George Eastman Museum, and the Smithsonian American Art Museum.On AART, Maggie reflects on the evolution of her career, the role of intuition in her artistic decisions, and the balance between control and discovery when creating complex digital compositions. She also discusses the emotional resonance of her work, the importance of curiosity, and how artists can embrace new technologies without losing their authenticity. This episode offers a fascinating look into the mind of an artist who has quietly but profoundly influenced contemporary visual culture. Whether you're an artist, photographer, or simply someone drawn to imaginative storytelling, Maggie Taylor's journey is both inspiring and deeply thought-provoking.Maggie's links website: www.maggietaylor.com Instagram: @maggietaylor.art Some favorite women artists: Julie Blackmon, Sandy Skogland, Lori Nix, Cig Harvey, Marion Peck, Lori Vrba, Claire RosenDinner party guests: Patti Smith, Aimee Mann, Laurie Anderson, Tilda Swinton, Kara Swisher, and Eve SchoolerKeywords: Maggie Taylor, digital collage artist, American artist Maggie Taylor, surreal digital art, digital collage photography, contemporary digital artists, Photoshop art, fine art photography, AART podcast, Chris Stafford podcast, women artists interview, visual storytelling, surrealism in digital art, creative process artists, modern collage art, experimental photography, women in art podcast, artist interviews, contemporary art podcast, museum exhibited artists, digital art techniques, storytelling through images, imaginative art, photography and technology, Jerry Uelsmann influence, American contemporary artists, art podcast interviews, Women Unscripted podcast networkBecome a supporter of this podcast: https://www.spreaker.com/podcast/aart--5814675/support.A Hollowell Studios ProductionInstagram: @theaartpodcast Email: theaartpodcast@gmail.com© Copyright: Chris Stafford | Hollowell StudiosAll Rights Reserved

No matter how long you've used your favorite creative tools, there's always one more shortcut, hidden feature, or unexpected workaround waiting to surprise you. In this episode, Theresa Jackson and Mike Rankin share a collection of practical tips and "wait, you can do that?" discoveries submitted by CreativePro Week speakers. You'll hear tips for favorite tools from Acrobat to PowerPoint, including clever ways to edit faster, move between apps, customize layouts, animate designs, manage masks, and make AI more useful in real workflows. Theresa also talks with PageProof founder Marcus Radich about PageProof Intelligence (PI) and learns how a proof can mark itself with AI. Episode Highlights Hear why Mike Rankin is looking at Affinity as a useful add-on to Adobe workflows, including an easier way to use images as custom bullets Learn where to find your Firefly generation history, including the prompts you used to create past results Discover how to export video with transparency from PowerPoint Follow Theresa and Mike through practical "round trip" workflows, from editing PDF images in Photoshop to moving Firefly Boards assets into other Adobe apps Hear Amy Balliett's tip for getting better AI results by using more than one AI tool Learn how Ben Willmore uses keyboard shortcuts to build masks faster in Adobe Camera Raw and Lightroom Discover Dax Castro's simple InDesign alt-text tip that can save time when adding descriptions to multiple images Resources CreativePro Week 2026: Nashville, June 29–July 3, 2026. https://creativeproweek.com/ CreativePro Events: https://creativepro.com/events/ Event Savings: Save $100 on any CreativePro event in 2026 with the discount code PODCAST: https://creativepro.com/events/ Membership Discount: Get $15 off one year of CreativePro membership with the discount code PODCAST: https://creativepro.com/become-a-member/ PageProof Intelligence: https://pageproof.com/pageproof-intelligence José Semidei: Tips for Creating Gradient Mesh Effects in Illustrator: https://creativepro.com/tips-for-creating-gradient-mesh-effects-in-illustrator/ How to Edit Photos in a PDF with Photoshop: https://youtu.be/aak26NToW5g?si=_ZQBnAU3AkyU6XXV

AI filmmaker and 14-time author Jason Moore joins me to unpack how artificial intelligence has reshaped the way he tells stories — without stripping out the creativity behind them. We get into a real client project that only became possible because of AI, his three guiding principles for using it well, and how he handles the inevitable wave of online critics. If you're curious (or a little nervous) about where AI fits into your video business, this conversation's for you. Key Takeaways AI works best as a collaborator, not a vending machine — the more of yourself you bring to it, the better the output. Some projects only exist because AI makes them affordable. In those cases, nobody actually loses a job that was never in the budget to begin with. Every big tech shift — Photoshop, CGI in Jurassic Park, even self-checkout — displaced some work while creating new opportunities for the people who adapted. Jason's "soul test": if you don't bring your own creativity and judgment, you get soulless results. The human stays in the driver's seat. About Jason Moore Jason is the author of 14 books on topics ranging from creativity and design to artificial intelligence. His most recent release, AI and the Church: A Clear Guide for the Curious and Courageous, is an Amazon bestseller that has sparked more than 150 national training engagements. In film and television, Jason has collaborated with Hollywood producers and created book trailers for New York Times bestselling authors including Arianna Huffington, Seth Godin, Robert Greene, Ryan Holiday, and Marc Ecko. A graduate of The Modern College of Design, Jason now returns to his alma mater as an adjunct instructor, alongside his work as a sought-after keynote speaker and trainer whose career bridges the worlds of creative production, ministry, and emerging technology. In This Episode [00:00] Welcome to the show! [05:58] Meet Jason Moore [12:06] AI Video Content [16:22] AI Video Package [27:47] Using AI Morally [38:23] Example Projects [48:35] Outro  Quotes "AI should be a 'do it with you' tool, not a 'do it for you' tool." — Jason Moore "You have a soul and AI doesn't. If you don't bring enough of your soul to your interaction with AI, you get really soulless outputs." — Jason Moore "I'm a human first, business owner second." — Ryan Koral "When the option exists, we're going to help more people tell stories in more compelling ways than we could in the past." — Jason Moore Guest Links Follow Jason Moore on Instagram | Facebook | X Links Find out more about the Studio Sherpas Mastermind Join the Grow Your Video Business Facebook Group  Follow Ryan Koral on Instagram Follow Grow Your Video Business on Instagram Get your Early Bird tickets for the Onward Summit Join the Studio Sherpas newsletter

Host Mike Rosado welcomes designer/illustrator/author Jon Contino to the Pencil Pushers podcast to discuss Contino's upbringing on Long Island, his parents' craft-driven influence, and his early path from band flyers, cassette art, and self-taught HTML to charging for creative work at 14. Contino explains how his lifelong obsession with lettering, failed graffiti attempts, Photoshop experimentation, hardcore/grunge culture, and New York's grime shaped his "organized chaos" style, later balanced by a problem-solving approach to branding inspired by figures like Paula Scher. He describes career growth from a 2005 studio and a handmade clothing brand to building Contino Studio, shifting from illustration trends into larger storytelling and branding work, including Toyota, the Tampa Bay Buccaneers, and sports. They debate commercialization of "handcrafted," carbon-copy styles, and AI's threat, emphasizing human mistakes and youth rejecting "AI slop." Contino shares his remote studio model, intense family-driven schedule, rare client friction, flexible discovery through live conversation, a move from paper to iPad/Procreate for speed, heavy use of Figma/Framer, and excitement about revitalizing Coffee Bean & Tea Leaf's brand. Host: Mike Rosado (mrcraleigh.com) (instagram.com/ekimodasor) Post Production: Max Trujillo (instagram.com/trujillomedia) Sponsors: MRC (mrcraleigh.com) and Burny Wild's (burnywilds.com) 

Guests: Don Simms and Chris Newey Host: Dave Homewood Recorded: ‎1st of June ‎2026 Released: 6th of June 2026 Duration: 55 minutes 27 seconds “Maximum Effort” was a docu-drama made by the Ministry of Information during WWII about a crew of a No. 75 (NZ) Squadron Avro Lancaster bomber based at RAF Mepal in mid-1944. In this episode Dave Homewood, Don Simms and Chris Newey discuss the making of this film, the real life characters who appear as themselves, and the Lancaster that is featured, ND752. Portions of the original film footage, along with original black and white and recently colourised photographs are used to illustrate the discussion. This all-but-forgotten film is an amazing time capsule showing life at RAF Mepal, near Ely, Cambridgeshire, which became a little bit of New Zealand back in 1944-45. NOTE: It is recommended that you watch the original 18 minute “Maximum Effort” first, and the watch the WONZ 354 Maximum Effort video. There is an audio podcast version of the latter but the video is much more satisfying. Above: Avro Lancaster ND752 of No. 75 (NZ) Squadron as features in Maximum Effort, as the Whitting Crew’s regular aircraft. This is a colourisation from an original black and white from the collection of the late Bomb Aimer and New Zealand Bomber Command Association President Ron Mayhill DFC. Quick Links: • The Air Force Museum of New Zealand • The Museum of Transport and Technology – Home of the New Zealand Lancaster • The New Zealand Bomber Command Association • The New Zealand Bomber Command Association Facebook Page Footage and original soundtrack used from Maximum Effort in this podcast are Crown Copyright but are in the Public Domain. These clips are used here only to illustrate the narrative of the podcast. Below are other publicity stills from the film, which have been colourised by Dave Homewood using a mix of ChatGPT and Photoshop, as seen in the WONZ Show video episode. The original monochrome images came from the Air Force Museum of New Zealand collection, but will have been Crown Copyright images, and are therefore in the public domain.

Grok says: “LOCK AND LOAD, YOU PUSSYFOOTING CIVILIANS! Listen up, warriors of the airwaves! In Episode 193 of the Unrelenting podcast, Darren and Gene charge straight into the breach with zero remorse. Darren recounts his goddamn chemical stress test nightmare — the Lexiscan that turned his ticker into a crashing Blackhawk, beta blockers sabotaging the mission, blood pressure tanking to seventy over fifty, and a little Asian nurse dropping truth bombs while the EKG tapes sweat right off his chest. They rip into nurse practitioners, cardiologist roulette, and why you better damn well know your meds before they shoot poison into your veins. From there these two operators unload on everything else that's pissing them off: the absolute scam that is CleanFeed for podcasters, eBay's IRS rape on that Michael Jordan Boy Scout card sale, Photoshop and Adobe's AI-powered art theft operation, and the coming tsunami of AI-generated slop flooding YouTube and Google. Then they go full tactical on the 2026 Tiger King — the Bricks & Minifigs Lego heist, the Mormon mafia, dirty cops running illegal raids, small claims court warfare, and how an 84-year-old man's Star Wars collection got straight-up stolen by corporate greaseballs. This episode is raw, unfiltered, and unrelenting as hell. If you want real talk on health, tech, AI, crypto dips, rocket explosions, and garage-sale ethics mixed with classic military-grade ball-busting and Doctor Who nostalgia, you need to lock in and listen right now. Download it, stream it, share it with your squad. Stop wasting time on weak sauce — get after it and hit play on Unrelenting 193. Failure is not an option.” Unrelenting: where discipline means no mercy, no bullshit, and no excuses. Thanks for listening. Please support the show! –>> DONATE NOW

主播：Meimei（中国）+ Maelle（法国） 音乐：Beautiful People最近，法拉利推出了它的第一台纯电动车。但真正引爆网络的，不只是车本身，还有网友们的神评论。今天我们就来聊聊：法拉利的“翻车”梗、英语里把品牌和人名变成动词的有趣现象。01. Backlash & Verdict：抵制和最终评价法拉利首款 EV 发布后，很多媒体标题非常直接：“Ferrari is facing a backlash”。还有“Ferrari fans have given their verdict”。Backlash ：“强烈的负面反应”，可以理解为“遭到群嘲”或“遭到反对”。例句：The company faced a backlash online (这家公司在网上遭到了大量批评).而verdict 原本是法庭上的“判决”，现在常被引申为“最终评价”。Verdict： 判决例句：Fans have given their verdict (粉丝们已经下结论了).所以这两句话连起来的意思就是：法拉利这次的新车，网友并不买账。02. “Hold my beer”——拿好我的啤酒，看我表演有一个评论精准捕捉了互联网幽默的精髓：Jaguar ruined its brand. Ferrari replied: Hold my beer。Hold my beer字面意思是“帮我拿一下啤酒”。这个梗的语境是：在国外聚会或酒吧里，有人准备做一件冒险或离谱的事之前，会让朋友帮忙拿住啤酒，然后说：“看我的”。所以在这里，法拉利的意思其实是：“捷豹翻车算什么？看我的。”它表达的是一种“你这不算什么，我能干出更离谱的”态度。例子：A: I crashed my bike.B: Hold my beer.（A：我自行车撞了。B：你这算啥。）03. “Pull a Ross”：英语里的动作化表达更有意思的是另一个梗：Ferrari pulled a Jaguar。这不是字典里的表达，而是网友自己创造的。意思是：重蹈捷豹的覆辙，或者更直白地说——把自己的品牌形象搞砸。这里藏着一个非常有趣的英语规律：Pull a + 人名/品牌名例句：Pull a Ross.像《老友记》里的 Ross 一样，把事情搞复杂、搞尴尬。英语母语者非常喜欢把人名或品牌名“动作化”。一个名字，就能概括一整个情境或人格类型。04. Google it, Photoshop, Uber：品牌变成动词这种“名字动作化”的现象，不仅出现在网络梗里，现实生活中也非常普遍。最经典的例子是Google：Google it (自己搜一下)。Google: 谷歌还有Photoshop：This photo is photoshopped. 这张图修过。Photoshop: Adobe公司的图像处理软件甚至连 Maelle自己都经常用的 Uber（优步打车）。例句：I'll Uber home (我打个 Uber 回家).即使有时候接单的不是 Uber 而是其他网约车公司，大家还是习惯说 Uber。就像中文里说“我打个滴滴”一样。品牌能变动词，人名当然也跑不掉。He's such a Chad. Chad 这个人名近几年特别火。它指的是一种：自信、能力强、很成功的男性形象。可以理解为“特别能打的人”或“很有魅力的男性”。05. Anything can be a meme: 英语里的造梗文化为什么英语这么喜欢“名字动作化”？因为这是一种高效的故事表达方式。One name can instantly communicate a whole personality or situation. 你不需要讲半天背景，一个名字就够了。它代表了一整个群体、一种行为模式，甚至一种文化现象。这也是为什么互联网英语进化（evolve）的这么快。人们把品牌、名人、电视剧角色、甚至公司，都变成了某种“想法的速记符号”。从Google it，再到 Ferrari pulled a Jaguar——英语网友几乎可以说：万物皆可造梗。而这也正是网络英语特别有意思的地方。欢迎在评论区留言：你最喜欢的英语网络梗是什么？What is your favorite internet meme in English?

From NAB in Las Vegas, Matt Bach, Senior Product Manager at Puget Systems, explains PugetBench, a free benchmarking tool for end users that tests real applications such as Premiere Pro, Photoshop, After Effects, DaVinci Resolve, and soon Unreal Engine. Matt discusses why real-world benchmarks beat synthetic scores, how software updates can dramatically change performance, and how Mac and Windows systems each excel in different workflows.  Show Notes: Chapters: [0:03] Introduction from NAB 2026[0:20] Matt Bach introduces PugetBench[0:31] Real-world benchmarking for creative applications[1:23] Why first-party claims and synthetic benchmarks can mislead[1:53] Software updates and changing performance over time[2:18] Synthetic benchmarks versus real application testing[3:19] Variables that affect benchmark accuracy[4:04] Why testing your own projects is the gold standard[4:27] Using benchmarks to evaluate upgrades realistically[5:07] Comparing your system through PugetBench's database[6:09] Supported apps and future Unreal Engine benchmarking[7:06] Unreal Engine uses beyond gaming[7:56] Mac versus Windows value and workflow strengths[9:16] Where to get PugetBench and end-user pricing[10:05] Closing from NAB in Las Vegas Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

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,

Matt and Shelby are joined by David Lebensfeld (founder, Ingenuity Studios) as they discuss facing major changes, professionally and personally. We cover everything from founding Ingenuity Studios to its eventual sale, his approach to navigating industry challenges, and how he views his next chapter. The conversation offers valuable insights into entrepreneurship, leadership, industry shifts, and personal growth. 

From NAB in Las Vegas, Matt Bach, Senior Product Manager at Puget Systems, explains PugetBench, a free benchmarking tool for end users that tests real applications such as Premiere Pro, Photoshop, After Effects, DaVinci Resolve, and soon Unreal Engine. Matt discusses why real-world benchmarks beat synthetic scores, how software updates can dramatically change performance, and how Mac and Windows systems each excel in different workflows.  Show Notes: Chapters: [0:03] Introduction from NAB 2026 [0:20] Matt Bach introduces PugetBench [0:31] Real-world benchmarking for creative applications [1:23] Why first-party claims and synthetic benchmarks can mislead [1:53] Software updates and changing performance over time [2:18] Synthetic benchmarks versus real application testing [3:19] Variables that affect benchmark accuracy [4:04] Why testing your own projects is the gold standard [4:27] Using benchmarks to evaluate upgrades realistically [5:07] Comparing your system through PugetBench's database [6:09] Supported apps and future Unreal Engine benchmarking [7:06] Unreal Engine uses beyond gaming [7:56] Mac versus Windows value and workflow strengths [9:16] Where to get PugetBench and end-user pricing [10:05] Closing from NAB in Las Vegas Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Stewart Alsop sat down with Michael Shackelford to discuss their experiences building applications through vibe coding—the practice of using AI to create software without traditional programming expertise. Stewart, who runs the AI Whispers community in Buenos Aires and hosts the Crazy Wisdom podcast (with over 660 interviews), shared how he went from teaching people prompt engineering to building his own video conferencing software as a Riverside.fm replacement, while Michael opened up about his year-long journey creating Genrupt Inc, an AI-powered content generation tool for e-commerce sellers. The conversation covered everything from the decline in quality of Claude's reasoning capabilities and how Chinese companies used distillation attacks to copy Anthropic's models, to the importance of spaced repetition systems for managing knowledge in the age of LLMs, with both sharing battle-tested prompting strategies like asking AI to "explain it to me in genius terms" and using deep research queries to reverse engineer how competitors build their products.Show Notes:- Dan Martell's book "Buy Back Your Time" was mentioned as one of the best business books for thinking about life and business- Check out John Vervaeke's "Awakening from the Meaning Crisis" for understanding relevance realization and why AI fundamentally cannot determine what's relevant to humans without being toldTimestamps00:00 Michael discusses being exhausted from getting his app ready for launch, working nonstop with AI to prepare landing page for podcast traffic driving beta signups05:00 Stewart explains starting AI Whispers in Buenos Aires after leaving OpenAI vendor company, meeting early adopters like Torin who was building mind-reading EEG technology10:00 Discussion of how corporations resist AI adoption due to political games and job security fears while some companies use AI as excuse for pandemic-era layoffs15:00 Stewart describes teaching workshops on using LLMs as linguistic tools rather than coding tools, noting technical people often lack humanities background needed for prompting20:00 Explaining chatbot wrappers, API calls, and how Anthropic's reasoning quality declined after Chinese distillation attacks copied their secret sauce developed with philosophers25:00 Technical discussion of model training, fine-tuning versus RAG for new information, and different approaches to updating AI knowledge beyond initial training30:00 Stewart describes building podcast recording software to replace expensive Riverside, struggling with syncing audio and video files across different computer clocks35:00 Discussion of critical factors in vibe coding, discovering unknown technical requirements, and how AIs don't automatically reveal missing information40:00 Stewart's reverse engineering process using deep research function to study competitors' hiring and technology stacks, separating planning agents from coding agents45:00 Prompting techniques including "explain like I know everything" and using spaced repetition systems to capture valuable prompts and technical knowledge50:00 Michael explains his Generux app for generating ecommerce content using Amazon review data analysis to inform high-converting listing images and videos55:00 Discussion of founder mentality involving self-delusion about project timelines, Michael working nine-plus hours daily for nine months on app development60:00 Comparing Amazon's expert software to prosumer software approach, discussing distribution challenges and future robotics applications for customized products65:00 Stewart demonstrates spaced repetition app for memory improvement and knowledge retention, explaining relevance realization problem that AI agents cannot solve without embodimentKey Insights1. Stewart Alsop started AI Whisperers in Buenos Aires after leaving his role at Invisible Technologies, which was OpenAI's largest vendor for RLHF work. He noticed that machine learning engineers at tech companies lacked the humanities background needed to properly interact with large language models, which are fundamentally linguistic tools. This led him to create weekly workshops teaching non-technical people how to use AI effectively, running events every Thursday for two years straight. The group attracted intense geeks from the start and eventually led to Stewart speaking right after Vitalik Buterin at DevConnect, marking a significant milestone for the community.2. Large corporations are resistant to AI adoption due to multiple factors including political dynamics within organizations and employees fearing job loss. Many companies that grew during the pandemic are now using AI as an excuse to downsize when the real issue is inefficiency from rapid expansion. Stewart observed that even technical people in machine learning often don't understand how to properly use AI tools because they lack linguistic and humanities training. The fundamental problem is educational, requiring companies to train people how to use these new tools while those same people resist learning them.3. Vibe coding has evolved significantly with Claude Code being a game changer that reduced the technical barrier to entry. Before Claude Code, developers needed substantial technical knowledge to work through constant doom loops and debugging cycles. The success of coding AI tools stems from thirty years of testing infrastructure that provides clear yes or no feedback on whether code works. This infrastructure doesn't exist in the same way for manufacturing, science, and other fields, which is why software became the dominant area for AI assistance initially.4. Claude's quality degradation over recent months resulted from multiple factors including distillation attacks by Chinese companies who reverse engineered Anthropic's reasoning capabilities. Anthropic had hired philosophers, sociologists, and psychologists to develop exceptional reasoning in Claude 4.5, but this was expensive to run. When Chinese models like Kimi copied these capabilities at one tenth the cost, and when mainstream users flooded the platform before Anthropic's planned IPO, the company had to reduce quality to manage computational costs. This represents a significant loss for power users who relied on Claude's superior reasoning abilities.5. Stewart built a podcast recording application to replace Riverside because he needed API access to automate workflows, which Riverside wanted one thousand dollars monthly to provide. The technical challenge involves syncing audio and video from local recordings on multiple computers with different clocks through a server, then merging them so voices match lip movements. This problem requires understanding complex timing issues across different network conditions and file formats. Stewart has been working through AI psychosis for months on this FFMPEG pipeline problem, illustrating how vibe coding still requires building intuition about technical problems even without traditional coding knowledge.6. The transition from expert software to prosumer software represents a major opportunity for AI-enabled tools. Expert software like Photoshop, Blender, and terminal interfaces have extreme complexity that intimidates beginners, but AI is making these capabilities accessible through natural language. The reign of specialists is ending as generalists with broad knowledge and curiosity can now build complete applications by leveraging AI to fill technical gaps. This shift particularly benefits entrepreneurs and founders who specialize in getting into difficult situations and figuring them out, even when they originally thought tasks would be easier than they turned out to be.7. Building applications with AI requires accepting massive time investments beyond initial estimates and developing strategies for overcoming knowledge gaps. Michael estimated his ecommerce content generation app would take months but spent nearly a year working over nine hours daily, while Stewart spent months solving audio-video sync issues. Success requires using tools like deep research to understand how competitors solve problems, maintaining separate planning and coding agents, and learning to ask the right questions. The key insight is that vibe coders can achieve ninety percent of functionality independently, but the final ten percent often requires understanding specific technical concepts that AI cannot intuit without proper context and domain knowledge.

In this episode of Business Brain, we get practical about putting AI to work on the everyday stuff, not just the big business plays. Shannon walks through building a custom food log with Claude after a doctor’s visit — snap a photo, let the AI ID the ingredients, get a clean report emailed before the next appointment, and pin it to your home screen as a web app. The bigger lesson: if all we’re doing is chatting back and forth with our favorite AI, we’re missing roughly 90% of what it can do. Don’t know what we’re missing? Ask the bot itself. Build the custom tool, start a health folder (eyes wide open about feeding personal data to a third party), and let it take the grunt work off our plate. Then Dave drops a reframe worth keeping: AI isn’t artificial intelligence, it’s assistive intelligence. It helps us, it doesn’t replace us — we’re still the one driving the bus. We connect it to history, too: when Photoshop hit, the same panic about lost jobs and “that’s not real art” played out, and it became the assistive tool every creative now relies on. The internet did the same, creating community and abundance. Every leap looks scary until it becomes the thing that powers our Charmed Life. Used right, with guidance, this is a superpower — so stop treating the chatbot like just a chatbot and start letting it build. 00:00:00 Business Brain – The Entrepreneurs' Podcast #757 for Casual FridAI, May 29, 2026 May 29th: National Paperclip Day Trade a Paperclip for a House 00:01:29 Claude Food Tracker The SAAS-Pocalypse Create an iOS Home screen app with Claude Don't forget to use your favorite ChatBot for every day things If you're only using your ChatBot as a ChatBot, you're missing out. Ask your ChatBot what you're missing! 00:09:16 SPONSOR: Shopify – For anyone to sell anywhere, sign up for a one-dollar-per month trial period at Shopify.com/BusinessBrain and upgrade your selling today! 00:10:48 SPONSOR: Bitdefender. Keep your small business safe with Bitdefender Ultimate Small Business Security. Save 30% when you go to https://bitdefender.com/BRAIN 00:12:14 AI is Assistive Intelligence AI isn't going to take jobs Photoshop didn't take jobs They both let people replace their jobs with different jobs “Before the Internet, why did you need a computer?” This Episode's Big Takeaway: Think about AI as your Assistive Intelligence 00:22:59 Business Brain 757 Outtro Check out Business Brain Blueprints Tell Your Friends! Business Blueprints Review Business Brain Subscribe to the show feedback@businessbrain.show Call/Text: (567) 274-6977 X/Twitter: @ShannonJean & @DaveHamilton, & @BizBrainShow LinkedIn: Shannon Jean, Dave Hamilton, & Business Brain Facebook: Dave Hamilton, Shannon Jean, & Business Brain The post FridAI – Assistive Intelligence – Business Brain 757 appeared first on Business Brain - The Entrepreneurs' Podcast.

From 05/28 Hour 4: The Sports Junkies discuss the top storylines around the celebrity world.

With both Brad and Dave nominated for awards this year, the guys spiral into a surprisingly deep conversation about awards, marketing, ego, and whether creators should plaster “award nominee” stickers all over their books. Later, they tackle a listener question about using 3D models, digital sets, and reference material in comics production — leading to a fascinating behind-the-scenes look at how both creators actually build comics pages in tools like Clip Studio Paint and Photoshop. Along the way, they discuss why imperfections matter in cartooning, how typography affects visual storytelling, and why “cheating” is often just another word for “working smarter.” Today's Show Should you put an award nomination on a book cover? UPDATE: Hugo Award voter packet "WSFS Membership"  Using sets and other pre-made background materials  UPDATE: Patreon Quips is now available on desktop You get great rewards when you join the ComicLab Community on Patreon$2 — Early access to episodes$5 — Submit a question for possible use on the show AND get the exclusive ProTips podcast. Plus $2-tier rewards.If you'd like a one-on-one consultation about your comic, book it now!Brad Guigar is the creator of Evil Inc and the author of The Webcomics Handbook. He is available for personal consultations. Dave Kellett is the creator of Sheldon and Drive. He is the co-director of the comics documentary, Stripped.

Margo is joined by Abby for another edition of Creative Current Events—the series where they unpack the stories, launches, trends, and internet conversations shaping the creative world right now. This episode covers everything from the rise (and critique) of the "beige epidemic" in interiors to unexpected retail collaborations, bold beauty marketing, shifting brand landscapes, and artists doing interesting work outside the algorithm. Along the way, they discuss what these moments reveal about creativity, originality, accessibility, and where culture seems to be headed next. Mentioned in this episode: The Beige Epidemic – House Beautifulhttps://www.housebeautiful.com/design-inspiration/a71336893/the-next-issue-beige-epidemic/ Colorful interiors and inspiration – The House That Lars Builthttps://thehousethatlarsbuilt.com/ Jonathan Adler collection at Michaels https://www.michaels.com/shop/jonathan-adler Review video of the Jonathan Adler collection https://www.instagram.com/reels/DXkZqF7kvtv/ GIMP's redesign: Photoshop familiarity without the subscription https://www.digitaltrends.com/computing/open-source-gimp-reskin-gives-it-a-familiar-photoshop-look-without-the-hefty-fee/ Explore GIMP https://www.gimp.org/ Create! Magazine – Call for Art Submissions https://www.createmagazine.co/call-for-art Garden & Gun Magazine https://gardenandgun.com/ Cover artist feature – Brian Steely https://www.instagram.com/p/DYe7ldUx2YO/ The Bitter Southernerhttps://bittersoutherner.com/ The Ordinary's skewered beauty marketing approach https://www.creativereview.co.uk/the-ordinary-markup-marche-pop-up-supermarket-uncommon/ "The Most Valuable Place a Brand Can Be Right Now Isn't Online" https://www.instagram.com/p/DWZzckqEYuM/ Shein acquires Everlane discussion https://www.instagram.com/p/DYfcq7Ik49Y/ The "tone deaf" commencement speech conversation https://www.instagram.com/reel/DYNfbyEP82q/ Wylie Welling × Carhart https://wyliewelling.com/blogs/journal Artist & listener spotlight: Renee Reid https://www.instagram.com/reneereidcreations Connect with Abby: https://www.abbyjcampbell.com/ https://www.instagram.com/ajcampkc/ https://www.pinterest.com/ajcampbell/   Connect with Margo: www.windowsillchats.com www.instagram.com/windowsillchats www.patreon.com/inthewindowsill

Matt and Shelby are BACK with a new season of The CMD-Z Show! In this episode, they give an update on what they've been up to as well as an update on the motion design industry. It's been 565 days since their last episode and A LOT has changed!

DxO is offering PetaPixel Podcast listeners 15% off any DxO software, including the brand-new Nik Collection 9, by using the code 'PetaPixel' at checkout. Nik Collection 9 adds AI-powered object and depth masks, plus new creative filters like Halation, Color Grading, Chromatic Shift, and Glass Effect in Color Efex and Analog Efex. Blending modes now work inside the plug-in stack, so you can experiment without opening Photoshop. All AI processing runs locally on your machine, so no images leave your computer. Head over to dxo.com and check out Nik Collection 9 and use code 'PetaPixel' to save 15%!With a PetaPixel Membership, not only can you support original PetaPixel reporting and in-depth reviews, but you can also remove ads from the website and gain access to some seriously great perks, too. Members get $15 off the Moment Store, 5% off certified pre-owned gear from KEH, 10% off lighting gear from FJ Westcott, and now can download full-resolution RAW files and JPEGs from the latest cameras and lenses. It costs just $3 per month or $30 per year. Join today!This week on the PetaPixel Podcast, the team is in-person at Fujifilm's Tokyo headquarters to chat with Yuji Igarashi about lenses, specifically how it feels the results of the Focus on Glass vote went. Plus, Sony gets thrashed for bad AI advice, Nikon is rumored to be selling to Essilor Luxxotica, TSMC wants to build a sensor fab in Japan, and Jordan Drake gives his thoughts on the Lumix L10. All that and more!Watch Fujifilm's 2026 Focus on GlassCheck out PetaPixel Merch: store.petapixel.com/ We use Riverside to record The PetaPixel Podcast in our online recording studio.We hope you enjoy the podcast and we look forward to hearing what you think. If you like what you hear, please support us by subscribing, liking, commenting, and reviewing! Every week, the trio go over comments on YouTube and here on PetaPixel, but if you'd like to send a message for them to hear, you can do so through SpeakPipe.In This Episode:00:00 -Intro08:16 - You can make this 3D printed digital rangefinder at home11:04 - Nikon speculators believe it might sell to Essilor Luxotica15:05 -

Memorial Day weekend is here, and I caught my first sunburn of the year—Florida summer is back. It's also the time when small, unexpected moments seem to appear out of nowhere. This weekend brought Maya's ballet recital and flashed me back 35 years to a strip mall computer store, where I left with an $800 piece of plastic in my hand—and an unexpected memory. If you've ever pondered your place on your life's timeline, slow down for a bit and come along—this story is worth a listen. Featured Story In 1990, I walked out of a small strip mall computer store with Photoshop 1.0 on a CD—eight hundred bucks I didn't really have, but I was determined to become a producer-editor, which we used to call a predator back then. Then I saw them. An older man is being pushed to a car in a wheelchair, totally silent. Thirty feet behind him, a baby in a stroller is kicking her feet, making baby noises, and her parents are smiling. Same parking lot. Two strollers heading toward cars that they didn't drive themselves to. Standing there with my $800 CD, I realized the only difference between those two strollers was time. That moment stayed with me. Important Points Remember: the only difference between the wheelchair and stroller is time. We're each somewhere on that timeline—recognizing it is key to living purposefully. Most of the stuff you think will matter probably won't, and the stuff you almost miss turns out to be almost everything. Take a breath, look at where you actually are today, and decide who you want sitting next to you in the parking lot. Memorable Quotes The only difference between those two strollers was the time and a little distance across the parking lot that day. Most of the stuff we think will matter doesn't, and most of what we almost miss turns out to be almost everything. The more I observe, the more I take a breath and just go, what a ride. Life moves fast, and things really do change. Scott's Three-Step Approach Stop in the middle of your regular routine today and actually notice the moments and people most of us are too busy to see. Take an honest breath and figure out where you actually stand on the timeline between the stroller and the wheelchair. Choose who you want pushing you across that parking lot one day, then go invest your time and attention in them now. Chapters 0:02 - First sunburn and the start of Florida summer 1:13 - Maya's ballet recital is the cutest thing ever 1:57 - Walking out of the store with $800 Photoshop on a CD 5:43 - The wheelchair and stroller in the same parking lot 6:28 - Poopy diapers and lessons from mom at 94 8:50 - Where are you actually sitting on the timeline today 9:02 - Closer to the wheelchair and what mattered most SEO Description Scott shares a 1990 parking lot moment — a wheelchair and a baby stroller — that reveals where you actually sit on life's timeline today. Connect With Me Search for the Daily Boost on YouTube, Apple Podcasts, and Spotify If you enjoy the Daily Boost, you might like Notes From Scott. A few mornings each week, I send a short note with something I've been thinking about or noticing lately. Sometimes those ideas turn into podcast episodes later. You can sign up at https://notesfromscott.com. Email: support@motivationtomove.com Main Website: https://motivationtomove.com YouTube: https://youtube.com/dailyboostpodcast Instagram: https://instagram.com/heyscottsmith Facebook Page: https://facebook.com/motivationtomove Facebook Group: https://dailyboostpodcast.com/facebook Learn more about your ad choices. Visit megaphone.fm/adchoices

Mike Rosado interviews Raleigh-based illustrator and designer Ian Wenstrand about his highly detailed, vibrant illustrations blending cityscapes, technology, and imaginative world-building. Wenstrand describes drawing constantly as a kid, studying studio art at University of the Cumberlands (recruited to swim), and moving from production artist retouching roles into graphic design before illustration work organically became steady freelance. He self-published a children's book inspired by artists like Graeme Base and cross-section illustrators, then gained momentum through public art opportunities including a 2018–2019 Citrix window mural and later a major Film NC tourism brochure project featuring five regional illustrations packed with 50+ movie Easter eggs. He outlines his process (two sketch phases in Procreate, then Photoshop for color), time demands, work-life balance with two kids, and the importance of tight contracts to prevent scope creep. Wenstrand shares influences (IC4 Design, Moebius, sci-fi film aesthetics), discusses collaborative "Easter egg" client input, and explains why he avoids using AI, adding an AI clause to contracts and valuing the human creative process. Host: Mike Rosado (mrcraleigh.com) (instagram.com/ekimodasor) Post Production: Max Trujillo (instagram.com/trujillomedia) Sponsors: MRC (mrcraleigh.com) and Burny Wild's (burnywilds.com) 

Car companies are beginning to use AI tools to radically speed up their development process, which could change the cars we drive forever — and have some big effects on the people who make them now. Verge contributor Tim Stevens explains. Then, The Verge's Hayden Field catches us up on Codex vs. Claude Code, Anthropic vs. the US government, the vibes at OpenAI, and more, before helping answer a question on the Vergecast Hotline (call 866-VERGE11 or email ⁠vergecast@theverge.com⁠!) about whether all the recent tech layoffs are really about AI. Further reading: ⁠The AI-designed car is taking shape | The Verge⁠ ⁠Pentagon strikes classified AI deals with OpenAI, Google, and Nvidia — but not Anthropic⁠ ⁠Google employees ask Sundar Pichai to say no to classified military AI use | The Verge⁠ ⁠Anthropic's new cybersecurity model could get it back in the government's good graces | The Verge⁠ ⁠Microsoft and OpenAI's famed AGI agreement is dead | The Verge⁠ ⁠Here's how the new Microsoft and OpenAI deal breaks down | The Verge⁠ ⁠ChatGPT downloads are slowing — and may cause problems for OpenAI's IPO | The Verge⁠ ⁠Claude can now plug directly into Photoshop, Blender, and Ableton | The Verge⁠ ⁠OpenAI's new security model is for ‘critical cyber defenders' only | The Verge⁠ ⁠Anthropic releases a new Opus model amid Mythos Preview buzz | The Verge⁠ ⁠Jack Dorsey's Block cuts nearly half of its staff in AI gamble | The Verge⁠ Subscribe to The Verge for unlimited access to theverge.com, subscriber-exclusive newsletters, and our ad-free podcast feed.We love hearing from you! Email your questions and thoughts to vergecast@theverge.com or call us at 866-VERGE11. Timestamps are approximate.) 00:00:00 Intro 00:02:00 Today Show Preview 00:04:00 Car Design Primer 00:08:00 AI Speeds Up Design 00:13:00 Clay Models and Craft 00:15:00 Jobs Pipeline Risk 00:18:00 Software Defined Cars 00:20:00 Regulation and Safety 00:27:00 Slate Truck Update 00:34:00 Claude Code vs Codex 00:42:00 OpenAI Vibes Check 00:44:00 PR vs AI Doomerism 00:48:00 Pentagon Deals Exclude Anthropic 00:53:00 Mythos Reality Check 00:56:00 RIP AGI Moment 01:04:00 Hotline AI Layoffs ROI 01:13:00 Wrap Up and Sign Off Learn more about your ad choices. Visit podcastchoices.com/adchoices