Podcasts about Percy

The Paradox band members Eric Dangerfield, Donald Bryant, Christopher "Xelan" Bernard and Percy "PC3" Crews joins Ralph Sutton and Aaron Berg and they discuss how the band came together, Xelan getting force fed lava cakes, Percy breaking their guitar, Eric working as a caretaker, Percy getting his Amazon delivery van stolen, the origin of the band name The Paradox, how they went from viral videos to learning the industry, Xelan getting kicked out of a Blink 182 concert then the band going on to play a song with Travis Barker around a year later, performing with Jack White, a game of Blind Ranking of their least favorite trolled band names, every member of The Paradox's first concert, first drug and first sexual experiences, a surprise reveal of who they're touring with next and so much more! Air Date: 09/12/26To advertise your product or service on GaS Digital podcasts please go to TheADSide.com and click on "Advertisers" for more information!You can watch The SDR Show LIVE for FREE every Wednesday and Saturday at 9pm ET at GaSDigitalNetwork.com/LIVEOnce you're there you can sign up at GaSDigitalNetwork.com with promo code: SDR for discount on your subscription which will give you access to every SDR show ever recorded! On top of that you'll also have the same access to ALL the shows that GaS Digital Network has to offer!Follow the whole show on social media!The ParadoxInstagram: https://instagram.com/TheParadoxBandRalph SuttonTwitter: https://twitter.com/iamralphsuttonInstagram: https://www.instagram.com/iamralphsutton/Aaron BergTwitter: https://twitter.com/aaronbergcomedyInstagram: https://instagram.com/aaronbergcomedyShannon LeeTwitter: https://twitter.com/IMShannonLeeInstagram: https://instagram.com/ShannonLee6982The SDR ShowTwitter: https://twitter.com/theSDRshowSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Episode 158 - A Dot In The Sky (Fallout RPG)    The residents of Vault Theta are on high alert! Under strict orders from the Overseer, they are scanning the horizon for signs of...something. Something top secret! Shuttlecock faces a crisis of internal conflict, Victor self-medicates, and Percy proves that his eyes still work just as well as any robot!   Find Us on Bluesky @PretendWithDice, @MonkeyMagicEden, @Ajheretic666, @MarkusMalice87 & @unklchop You can also find us on Facebook, Instagram & Twitter/X @PretendWithDice Links to all of our online presences can be found at www.pretendingwithdice.com, including our Ko-fi page, Merch Store, Discord server and much much more!

Renee Percy Gets 30 Million Views a Month and STILL Isn't Famous Comedian and actress Renee Percy returns to Drinking During Business Hours for her second sit-down with hosts Sarah Halstead and Rich Chassler, and the timing could not be better  she is in the middle of a full-blown viral explosion, pulling over 30 million views a month on social media after 25 years of grinding in comedy. Renee gets real about what going viral actually means: why a Tonight Show spot doesn't move the needle like it used to, whether a follower count in Phoenix ever sells a ticket in Phoenix, and how she accidentally committed herself to touring Bangkok, Taipei, and São Paulo because that's where her fans actually live. She opens up about the slow build  the "overnight success" that took two decades, the body of work that justifies the break, and why comics are never satisfied. Sarah and Rich share the story of Renee's legendary last-minute wedding roast, she reveals the burger videos that made her hungry for fame (literally), the gang breaks down their red-hot weekly show Test Kitchen Comedy at the historic Starlight Cabaret in Studio City  complete with the building's Oil Can Harry's cop-alert boot-window history  and Renee previews her fourth year touring for the troops through Greece, Turkey, Portugal, and Norway, plus headlining dates in Arizona and Boise. All over bottles of Love Block Sauvignon Blanc, the wine from the woman who created Kim Crawford. Pour one and dive in. Guest Info Renee Percy is an award-winning actor, writer, and comedian who caught the acting bug at age 12 with a series-regular role, launching a career in Canadian television before making the move to the U.S. She has been seen on NBC, CBS, ABC, FOX, Nickelodeon, Disney, FX, and Comedy Central, and her special The Komic Sutra is available now on Amazon and Apple. Her viral videos on Instagram pull over 30 million views a month, she performs at every major comedy club, and she is heading into her fourth year touring overseas for the troops. Website: https://www.reneepercy.com/ Guest Social Links •      Instagram: https://www.instagram.com/reneepercycomedian/ •      TikTok: https://www.tiktok.com/@thereneepercy •      Facebook: https://www.facebook.com/ReneePercyComedian/ •      YouTube: https://www.youtube.com/channel/UC6kL_EkNsl3ZYl_86_OT9Nw •      Website: https://www.reneepercy.com/ Drink of the Podcast Love Block Sauvignon Blanc a crisp, vibrant white from Marlborough, New Zealand, made by Erica Crawford, the winemaker behind Kim Crawford before the brand was sold to a wine conglomerate. Named for the block of land the Crawfords fell in love with, it is a Sauvignon Blanc for people who loved the original and one of Sarah's all-time favorite wines from one of her favorite winemakers. Chapters 00:00   Intro: Welcome to Drinking During Business Hours 02:07   The Drink: Love Block Sauvignon Blanc 04:10   Welcome Back, Renee Percy 05:19   Still Not Famous: The Second Visit 06:45   There Is No Such Thing as a Big Break 10:15   Going Viral vs. The Tonight Show 14:54   Do Followers Really Sell Tickets? 21:24   A Play in New York (and Girls' Night) 22:27   Touring for the Troops: Greece, Turkey, Portugal, Norway 23:24   Headlining Dates: Arizona and Boise 25:12   Test Kitchen Comedy: All-New Material Every Week 28:47   The Wedding Roast Story 31:55   Roast Rules and Sarah Tiana's Tom Brady Playbook 33:55   Coming Up Together at Flappers Comedy Club 35:31   The Burger Videos and Beating the Algorithm 36:57   The Starlight Cabaret and Its Oil Can Harry's History 39:41   The Magic Number Seven (and a Little Cheating) 41:21   Where to Find Renee 42:18   Thank Yous and Outro Call to Action Enjoyed the episode? Like, subscribe, and share it with a comedy lover in your life. Rate and review the podcast on Apple Podcasts or your favorite platform every five-star review helps us reach more listeners. And don't forget to catch Renee Percy live on tour dates at reneepercy.com and stream her special The Komic Sutra on Amazon and Apple. If you're in L.A., come see Test Kitchen Comedy at the Starlight Cabaret in Studio City all-new material, 90 tight minutes, only 5 bucks. Special thanks to Doug Bass https://www.instagram.com/dougbasshole/ And Bass Hole Studios https://www.bassholepodcaststudio.com/  Producer Cori Fry podchicmedia@gmail.com Maximilian Riedel and Riedel glassware, and Erica Crawford of Loveblock Wines. Host Links FOLLOW US ON SOCIALS! Sarah IG @sarahhalstead https://www.instagram.com/sarahhalstead/?hl=en  FB @sarahjhalsteadcomic https://www.facebook.com/sarahjhalsteadcomic/ X @sarahjhalstead  https://twitter.com/sarahjhalstead  Website   @SarahHalstead | sarahjhalstead.com Rich IG @richchassler https://www.instagram.com/richchassler/ FB @chasslerfans https://www.facebook.com/Chasslerfans/ X @richchassler https://x.com/richchassler  Website  richardchassler.com

Send me a DM here (it doesn't let me respond), OR email me: imagineabetterworld2020@gmail.comFilmed in Broadstairs, Kent — Charles Dickens' old stomping ground — this episode continues the raw 2014 conversation between Miles Johnston and Max Spiers at the home linked to Max's family. Picking up from earlier discussion of Max's difficult life and triggers, the talk goes deeper into origins and the bigger picture he describes. Max recounts being born to a “high vibrational” mother and “low vibrational” father and arriving perfectly balanced — then immediately imbalanced. He describes a brief, intense birth phenomenon (half red, half yellow down the center line, photographed and reported as a “Harley Quinn child”) that vanished after three minutes. He frames his life's work as finding the center point between those polarities.He identifies as a fallen male fire dragon from Draco, one of four elemental dragon types corresponding to air, earth, water and fire. The conversation weaves DNA spirals, reptilian/R-complex strands, the need to climb out of the 3D loop, longer cycles beyond the usual precession talk, and why polarity, war and extreme sensation keep this dense reality intact. Peace and true balance, he says, would collapse the 3D construct that certain beings want to preserve for the pleasures of the flesh — and for power extracted from suffering.The discussion also covers the fleur-de-lis, Sirius A/B/C, Merovingian and Dagobert connections, and English royal charts as galactic origin markers (Sirius, Orion, Aldebaran) displayed in plain sight; the Grail as consciousness, DNA and state of mind rather than a physical cup; the end of a fourth cycle with “only two left fighting” and echoes of the Hunger Games, Mortal Kombat and MK; the void, Goetian entities, Crowley, Boleskine, an unclosed gate at Loch Ness, energy vampires, fear and deals; an older council, end times, the ouroboros/Möbius loop, double binds and why confusion keeps souls looping; the 39 Steps in Broadstairs, reversals and black sun symbolism; and personal lineage ties including the Black Prince, a Percy ancestor at Shrewsbury, Stewart and Diana bloodline connections, plus Canterbury as a soul-level birthplace.This is unscripted, wide-ranging and characteristic of the Bases series: bloodlines, interdimensional conflict, 3D as a maintained polarity game, and Max's claim of both participating in and trying to step off that game.

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Presenting... The Steam Rollers Adventure Podcast,     Season 4: "The Curse of the Glass Witch"   Episode 325, Chapter 44 "Doesn't Everybody Like The Plabe?" EARLY RELEASE (BRONZE+): 3+ weeks early! COMMERCIAL FREE! PUBLIC RELEASE: Thursday, September 10, 2026 Show Notes for the Episode... Matisse draws the wrong kind of attention when she's tasked with starting the show. Percy comes face to face with his zombie self! Holly the Faerie Witch finds herself trapped inside the White Temple. Fortunately, the Keepers gave her a map! Production... Executive Producer:            George Pecenica Producer:            Sholom West Patreon Sponsor:             Michael Cast...Storycrafter - Mike Rigg           Robbie, Boris, Margie, and Ben - Themselves     George Pecenica as Percy Alexander     Ray Volk as Martin Barnett     Jenn Avril as Connie Ross     Rupert Faullhurst as Nigel Osbert Wintermann     Dave Murtagh as Oliver Glass     and introducing Robin as Holly the Faerie Witch and Blake Azur as Jasper Remington Music Credits...          "Almost New, "Dark Times," "Hitman, "The Parting" by Kevin MacLeod (Incompetech.com) Licensed under Creative Commons: By Attribution 4.0 License http://creativecommons.org/licenses/by/4.0/ . Additional music: "The Steam Rollers Adventure Podcast Theme" performed by Floof* , "A Jaunty Day," "Robut Reviews," "A Jaunty Day in SRAPLand," "The Halo Temple," "The Halo Temple (Darker)," "The Saddest Music Ever," "The Temple" by RST Musek (* Floof is a fictional band. Find out more by following Whiskey Tango Furball on YouTube @WTFurball. RST Musek lyrics written by Michael J Rigg, music generated using SUNO.)

“We didn't get any of this for Jason because we don't know Jason. Rick doesn't know Jason.” Darien (she/they) and DJ (he/him) jump into the next Heroes of Olympus book by asking a very important question: Why is The Son of Neptune so much better than The Lost Hero?Other topics include superficial similarities between the first two HoO books, the scene on the cover NOT happening on page, more support for DJ's theory about how demigods get their gifts, how to successfully pull of a memory loss plot, Reyna and the Ace Experience™, examining Nico and Hazel's sibling relationship, Content Warning: This episode contains mentions of and conversations about amnesia, drowning, death, war, physical violence, murder, and racism. Spoilers for The Heroes of Olympus, The Sun and the Star, The Court of the Dead, Gwenpool, The West Coast Avengers, Kingdom Hearts: Birth by Sleep/Fragmentary Passage, Mort, Soul Music, The Trials of Apollo Bonus episode 7 Quizzes to Get to Know Yourself Better on Patreon! https://www.patreon.com/musesofmythologyAbout UsMuses of Mythology was created and co-hosted by Darien and DJ Smartt.Our music is Athens Festival by Martin Haene. Our cover art is by Ranpakoka. Find him on Instagram @Ranpakoka Love the podcast? Support us on Patreon and get instant access to bloopers, outtakes, and bonus episodes! Patreon.com/musesofmythologyGet you hands on podcast merch at Musesofmythology.com/merchFind us on Instagram. Find all of our episodes and episode transcripts at MusesOfMythology.com----------------------- Support the showNo portion of this episode may be used for large language learning models or generative AI training purposes or to create derivative works without express written permission from the creators and co-hosts Darien Smartt or Davis Smartt. 

Send us Fan MailWilliam enters the forest in the dead of night after Fenrir senses that something is terribly wrong.In this episode of Werewolf the Podcast: A Serial (Killer) Drama, the medieval horror story takes William Marshal, Fenrir, Gervais and Percy deep into an ancient forest where they encounter Drear — a mysterious child who may actually be the spirit of a tree destroyed by the villagers.But Drear knows things no child should know.She can speak to the trees. She knows Fenrir is inside William. And she understands that the creature created by the necromancer Belphastus is not simply a demon.Something has been disturbed.Something ancient.Something that does not belong in this world.As William discovers the memory of the forest's first wound — the axe that destroyed an ancient tree and the men who took its wood to build their church — he begins to understand that Belphastus has accidentally opened a doorway into something far older and more dangerous than he intended.The forest remembers.And now something is coming.Werewolf the Podcast: The Spirit of the Woods is a dark fantasy and medieval supernatural horror story featuring werewolves, wolf souls, forest spirits, ancient trees, demons, necromancy and the terrifying mythology surrounding William Marshal and Fenrir.Then, from deep within the darkness:THUNK.The first tree has returned.Werewolf the Podcast: A Serial (Killer) Drama — Episode 277.Written by Fenrir Thorvaldsen and Gregory Alexander-Sharp. New episodes weekly—join the pack!Support the show • Books in the universe available on Amazon • Private Facebook group for Lunatics.Books by Fenrir ThorvaldsenAuthors' page on Amazon.https://amzn.to/3OJkzD0The Werewolf's Story by Fenrir Thorvaldsenhttps://amzn.to/4aX18xP Books by Gregory Alexander-SharpAuthors' page on Amazonhttps://amzn.to/4cTtf3CIl Lupo by Gregory Alexander-Sharphttps://amzn.to/4aZyCvABuy us a coffee at this link right here:https://www.buymeacoffee.com/WerewolfwilGrendel Press, our horror genre partnerThe best indie house publishers of horror in the blooming worldhttps://grendelpress.com/Grendel's very own cool Podcast.https://grendelpress.com/sinister-soup. Join the Lunatics at the Private Facebook Group.Facebook Grouphttps://www.facebook.com/groups/werewolfthepodcast/Greg's X profile: @SempaiGregFenrir's X profile: @FenThorvaldsenWerewolf the Podcast X profile: @AWerewolfsStoryWilShop at Dead_End_Society on Vinted.https://www.vinted.co.uk/member/3159606835Intro partnership with Grendel Press.https://grendelpress.com/ Outro partnership with Grendel Press.https://grendelpress.com/Support the show

Holly shares additional details of Percy Fawcett's life, including theories about his interest in spiritualism leading him to some odd conclusions.See omnystudio.com/listener for privacy information.

From his home in Hornbæk, northern Copenhagen-born, retired Danish pilot, airline captain, and businessman PERCY BECK RØRVIG recalls living in Manhattan at an early age, joining the Danish Air Force at 18, starting a 30-year long career at Scandinavian Airlines at 24, and piloting the CPH-JFK route for years. Percy calls New York his second home, having lived there for several periods. And he talks about the businesses he took up along the way, borrowing from lessons he learned as a pilot.----------For today's episode, Percy Beck Rørvig chose Alberto Giacometti's Three Men Walking II, from 1949 from the collection of The Metropolitan Museum of Art, New York. https://www.metmuseum.org/art/collection/search/489978 ----------Private Photograph----------This conversation with Christian D. Bruun occurred on June 28, 2026.----------We invite you to subscribe to Danish Originals for weekly episodes. You can also find us at:website: https://danishoriginals.com/ email: info@danishoriginals.com 

Bishop Tony Percy says Matthew's Gospel, chapter 18, presents Jesus' teaching on how Christian communities should live together, addressing how a community should respond to members who are backsliding: pray for them, speak the truth in love, and if needed, approach them again with another community member

The second part of Percy Fawcett's story delves into his fascination with a document known as Manuscript 512 and how it impacted his life. His obsession led to his disappearance; there has been endless speculation about what exactly happened. Research: Biello, David. “Ancient Amazon Actually Highly Urbanized.” Scientific American. August 28, 2008. “The Brazilian Indigenous People.” Survival International. https://www.survivalinternational.org/peoples/brazilian Britannica Editors. "Mato Grosso". Encyclopedia Britannica, 10 Jan. 2026, https://www.britannica.com/place/Mato-Grosso Canal-Soler, Jordi. “The man who died searching for the Lost City of Z.” National geographic. June 13, 2024. https://www.nationalgeographic.com/history/article/percy-fawcett-search-lost-city-of-z Fawcett, Lt-Col P.H. “Exploration Fawcett.” Hutchinson & Co. London. 1953. “Fawcett’s Bones Believed Found; Explorer Lost in Brazil Jungle in ’25.” New York Times. April 4, 1951. https://timesmachine.nytimes.com/timesmachine/1951/04/04/82103136.pdf?pdf_redirect=true&ip=0 “Fawcett Mystery Unsolved.” New York Times. Nov. 5, 1951. https://timesmachine.nytimes.com/timesmachine/1951/11/05/81775504.pdf?pdf_redirect=true&ip=0 Grann, David. “The Lost City of Z: A Tale of Deadly Obsession in the Amazon.” Doubleday. 2009. “Hidden City Is the Goal.” Los Angeles Times. Jan 12, 1925. https://www.newspapers.com/image/380427463/ Hutchison, Percy. “Hunting for Lost Explorers in the Jungles of Brazil.” New York Times. Jan. 26, 1930. https://timesmachine.nytimes.com/timesmachine/1930/01/26/96041140.pdf?pdf_redirect=true&ip=0 Moutinho, Sofia. “A Foundation of Trust.” Science. Nov. 6, 2025. https://www.science.org/content/article/unearth-their-past-amazonian-people-turn-language-white-men-understand “'Lost' report exposes Brazilian Indian genocide.” Survival International. April 25, 2013. https://www.survivalinternational.org/news/9191 “On Colonel Fawcett’s Train in Unknown Brazil by Air and River.” Illustrated London News. Sep 10, 1932. https://www.newspapers.com/image/1143308620/?match=2&terms=%22Vincenzo%20Petrullo%22&search-id=72603589-1171-4291-b93b-9c5eeffb7d90&search-rank=1 “Percy Fawcett.” Spike Island. https://www.spikeislandcork.ie/percy-fawcett/ “Lieutenant Colonel Percy Harrison Fawcett DSO, (MiD).” Tiegnmouth & Shaldon Remembers WW1. Teign Heritage. https://www.teignheritageworldwar.org.uk/index.php/lieutenant-colonel-percy-harrison-fawcett Pezzati, Alessandro. "The Lost Explorer." Expedition Magazine59, no. 2. September, 2017. https://www.penn.museum/sites/expedition/the-lost-explorer/ Potts, Mary Anne. “Finding Machu Picchu: A Look at Explorer Hiram Bingham, A Real-Life Indiana Jones.” National Geographic. May 26, 2010. https://www.nationalgeographic.com/adventure/article/machu-picchu-hiram-bingham “Remembering Col. Fawcett in WWI.” Torquay Museum. Nov. 4, 2021. https://torquaymuseum.org/news/view/remembering-col-fawcett-in-wwi Ribeiro, Taisa Alves and André Luiz Alves Moreno. “Towards an Archaeology of the Written Culture of Chapada Diamantina-BA: The Case of Manuscript 512.” Garimpus: Journal of Languages, Education and Culture in Chapada Diamantina. Vol. 2, no. 1. 2021. https://www.revistas.uneb.br/garimpus/article/view/8740 “Son of Lost Explorer Says Bones Are Not Fawcett's.” New York Times. Nov. 4, 1951. https://timesmachine.nytimes.com/timesmachine/1951/11/04/96221387.html?pageNumber=66 Squires, Cole. “TRANSCRIPTION/TRANSLATION NOTES (Manuscript 512).” Harvard. https://people.math.harvard.edu/~knill/teaching/mathe320_2021/exhibits/manuscript512/translation.pdf “Sustainable Mato Grosso.” Amazon Fund. https://www.amazonfund.gov.br/en/projeto/Sustainable-Mato-Grosso/ “Swindon Woman Awaits News of Colonel Fawcett.” Swindon Advertiser. April 13, 1932. https://www.newspapers.com/image/1209686028/?match=2&terms=%22percy%20fawcett%22&search-id=667a33c0-fac9-457e-bcf9-349a1d9b7e9f&search-rank=2 “Why do they hide?” Survival International. https://www.survivalinternational.org/articles/3104-why-do-they-hide See omnystudio.com/listener for privacy information.

Fawcett’s life has invited controversy and speculation, because he was a man who did a mix of great and shady things. Part one covers his early life, marriage, military service, and early visits to South America. Research: Biello, David. “Ancient Amazon Actually Highly Urbanized.” Scientific American. August 28, 2008. “The Brazilian Indigenous People.” Survival International. https://www.survivalinternational.org/peoples/brazilian Britannica Editors. "Mato Grosso". Encyclopedia Britannica, 10 Jan. 2026, https://www.britannica.com/place/Mato-Grosso Canal-Soler, Jordi. “The man who died searching for the Lost City of Z.” National geographic. June 13, 2024. https://www.nationalgeographic.com/history/article/percy-fawcett-search-lost-city-of-z Fawcett, Lt-Col P.H. “Exploration Fawcett.” Hutchinson & Co. London. 1953. “Fawcett’s Bones Believed Found; Explorer Lost in Brazil Jungle in ’25.” New York Times. April 4, 1951. https://timesmachine.nytimes.com/timesmachine/1951/04/04/82103136.pdf?pdf_redirect=true&ip=0 “Fawcett Mystery Unsolved.” New York Times. Nov. 5, 1951. https://timesmachine.nytimes.com/timesmachine/1951/11/05/81775504.pdf?pdf_redirect=true&ip=0 Grann, David. “The Lost City of Z: A Tale of Deadly Obsession in the Amazon.” Doubleday. 2009. “Hidden City Is the Goal.” Los Angeles Times. Jan 12, 1925. https://www.newspapers.com/image/380427463/ Hutchison, Percy. “Hunting for Lost Explorers in the Jungles of Brazil.” New York Times. Jan. 26, 1930. https://timesmachine.nytimes.com/timesmachine/1930/01/26/96041140.pdf?pdf_redirect=true&ip=0 Moutinho, Sofia. “A Foundation of Trust.” Science. Nov. 6, 2025. https://www.science.org/content/article/unearth-their-past-amazonian-people-turn-language-white-men-understand “'Lost' report exposes Brazilian Indian genocide.” Survival International. April 25, 2013. https://www.survivalinternational.org/news/9191 “On Colonel Fawcett’s Train in Unknown Brazil by Air and River.” Illustrated London News. Sep 10, 1932. https://www.newspapers.com/image/1143308620/?match=2&terms=%22Vincenzo%20Petrullo%22&search-id=72603589-1171-4291-b93b-9c5eeffb7d90&search-rank=1 “Percy Fawcett.” Spike Island. https://www.spikeislandcork.ie/percy-fawcett/ “Lieutenant Colonel Percy Harrison Fawcett DSO, (MiD).” Tiegnmouth & Shaldon Remembers WW1. Teign Heritage. https://www.teignheritageworldwar.org.uk/index.php/lieutenant-colonel-percy-harrison-fawcett Pezzati, Alessandro. "The Lost Explorer." Expedition Magazine59, no. 2. September, 2017. https://www.penn.museum/sites/expedition/the-lost-explorer/ Potts, Mary Anne. “Finding Machu Picchu: A Look at Explorer Hiram Bingham, A Real-Life Indiana Jones.” National Geographic. May 26, 2010. https://www.nationalgeographic.com/adventure/article/machu-picchu-hiram-bingham “Remembering Col. Fawcett in WWI.” Torquay Museum. Nov. 4, 2021. https://torquaymuseum.org/news/view/remembering-col-fawcett-in-wwi Ribeiro, Taisa Alves and André Luiz Alves Moreno. “Towards an Archaeology of the Written Culture of Chapada Diamantina-BA: The Case of Manuscript 512.” Garimpus: Journal of Languages, Education and Culture in Chapada Diamantina. Vol. 2, no. 1. 2021. https://www.revistas.uneb.br/garimpus/article/view/8740 “Son of Lost Explorer Says Bones Are Not Fawcett's.” New York Times. Nov. 4, 1951. https://timesmachine.nytimes.com/timesmachine/1951/11/04/96221387.html?pageNumber=66 Squires, Cole. “TRANSCRIPTION/TRANSLATION NOTES (Manuscript 512).” Harvard. https://people.math.harvard.edu/~knill/teaching/mathe320_2021/exhibits/manuscript512/translation.pdf “Sustainable Mato Grosso.” Amazon Fund. https://www.amazonfund.gov.br/en/projeto/Sustainable-Mato-Grosso/ “Swindon Woman Awaits News of Colonel Fawcett.” Swindon Advertiser. April 13, 1932. https://www.newspapers.com/image/1209686028/?match=2&terms=%22percy%20fawcett%22&search-id=667a33c0-fac9-457e-bcf9-349a1d9b7e9f&search-rank=2 “Why do they hide?” Survival International. https://www.survivalinternational.org/articles/3104-why-do-they-hide See omnystudio.com/listener for privacy information.

Hotel Pacifico was created by Air Quotes Media with support from our presenting sponsor TELUS, as well as FortisBC.Former UK Conservative MP and newly minted Vancouver resident Andrew Percy returns to Hotel Pacifico. Mike, Geoff and Andrew discuss the

Tony Percy reflects on the theology of the body. Pope John Paul II's Theology of the Body develops this through the experiences of solitude, unity, nakedness and original sin, helping us understand the body as symbolic, spousal, beautiful and free, yet wounded and redeemed

We have all the latest transfer news as Liam Delap From Chelsea to Nottingham Forest is confirmed! Try Oxford Natural, Use Code FFTV For Up to 70% Off! https://oxfordnatural.com/fftv/ The latest Nottingham Forest transfer news has everyone talking after reliable reports, including a major reveal from Percy on X (Twitter), confirmed that a "here we go" deal is in place for Forest to sign Liam Delap from Chelsea. Wolfie breaks down all the details of this massive arrival on Forest Fan TV, diving straight into whether the young striker has what it takes to lead our frontline and make an immediate impact at the City Ground. With the fee reportedly sitting around £45 million, opinions are split across the fanbase on whether this is smart business or if a loan-to-buy arrangement would have been a safer gamble. We want to hear from the Forest faithful on this one—are you happy to see Delap pull on the Garibaldi, or does the £45m price tag make you nervous? Drop your thoughts, debates, and score predictions down in the comments section below, and make sure to hit that subscribe button for more daily Nottingham Forest fan reaction and transfer updates! #nffc #premierleague #chelsea Learn more about your ad choices. Visit podcastchoices.com/adchoices

Marvel's Midnight Universe is getting ready to open its doors, and this week we're going straight to two of the writers helping build it. Benjamin Percy and Phillip Kennedy Johnson join the AIPT Comics Podcast for an extended conversation about Midnight Fantastic Four and Midnight Spider-Man, two of the three series launching Marvel's new horror-infused universe on October 7. Along with Jonathan Hickman on Midnight X-Men, Percy and Johnson are helping to establish a world in which familiar Marvel characters are being rebuilt through body horror, cosmic terror, and some seriously disturbing new origins. Percy digs into the Lovecraftian nightmare behind his Fantastic Four, why their familiar powers are closer to curses, the influence of California's strange scientific and occult history, and just how grotesque Reed Richards' elasticity can become. Johnson takes us inside his radically different Peter Parker, the role Oscorp plays in his transformation, ScieTronc's horrifying designs, and why calling this version of Peter "Man-Spider" barely scratches the surface. The conversation also gets into the larger Midnight Universe, including how Percy, Johnson, and Hickman are coordinating their books, how carefully they're approaching other Marvel characters, plans for the universe to eventually expand, and yes, whether Hickman's beloved data pages are coming along for the ride. Visit our Patreon page to see the various tiers you can sign up for today to get in on the ground floor of AIPT Patreon. We hope to see you chatting with us on our Discord soon! NEWS Marvel November solicitations! Jean Grey returns! Marvel's ‘Incursions' one-shots revisit the road to ‘Secret Wars' this November Marvel teases ‘Origin III': Is Wolverine's untold past about to be revealed? Official press release Marvel's November 2026 solicitations reveal the post -‘ Avengers: Armageddon' era Marvel retells Venom's origin from the symbiote's perspective in ‘Venom: POV' Marvel's free ‘Midnight Universe' ashcan reveals creepy new details Marvel Comics sheds light on November 2026 variant series Momo-Tone covers Exclusive: Benjamin Percy and Raúl Fernández launch sci-fi horror series ‘Egg Hunt' Exclusive: Brain Poison launches with three new sci-fi comics in shared universe Garth Ennis and John McCrea get weird with psychedelic horror tale ‘The Snail' DC Comics Solicitations for November Our Top Books of the Week: Dave: Punisher Vs. Spider-Man #2 (Dan Abnett, Matteo Della Fonte) Thor #800 Chris:​​ Nights #20 (Wyatt Kennedy, Luigi Formisano) The Last Driver #1 (Sean Murphy, Simon Gough) Standout KAPOW moment of the week: Chris: Nights #20 (Wyatt Kennedy, Luigi Formisano)  Dave: Destination Kill #4 (Joe Palmer) TOP BOOKS FOR NEXT WEEK Chris: Minotaur #2 (Si Spurrier, Michael Dowling) Dave: Batman: Bad Seeds – Sunset #1 (Matt Fraction, G. Willow Wilson, Giuseppe) JUDGING BY THE COVER JR. Dave: Tomb of Apocalypse #1 (Pablo Villalobos) Chris: Next Level: One Shot #1 (Fernando Blanco Main Cover) Interview: Midnight Universe - Ben Percy (Midnight FF) and Phillip Kennedy Johnson (Midnight Spider-Man) - Out October 7, FOC Aug 31 You're both taking characters whose origins are among the most familiar in comics and rebuilding them through horror. What was the first thing each of you identified in the classic Fantastic Four and Spider-Man origins that could become genuinely frightening in the Midnight Universe? Since this is horror, are you inverting who is the hero? I.e. is Spider-Man the villain and hsi rogues the bad guys, same for FF, or is that giving too much away? Ben, the Fantastic Four have always been explorers pushing into the unknown, but here that curiosity seems potentially catastrophic. How much of Midnight Fantastic Four is about Reed Richards being unable to leave certain doors unopened, even when every instinct should tell him to stop? Phillip, you've described wanting Peter Parker's transformation to feel like something conceived by H.R. Giger and directed by David Cronenberg. Once Peter becomes this grotesque spider hybrid, how do you preserve the humanity and responsibility that make him recognizably Spider-Man? Both books seem fascinated with science going somewhere it absolutely should not go. How differently do Reed and Peter respond to the realization that scientific progress has created something horrifying, and do you see them as cautionary reflections of each other? The solicit for Midnight Fantastic Four #2 mentions revisiting and redefining the perils of the atomic age. Ben, what interested you about connecting the Fantastic Four to that particular period of scientific optimism, anxiety, and destruction? Phillip, Oscorp isn't simply responsible for Peter's transformation. They're apparently using what they learn from him to create more human-animal hybrids. Does that give this version of Spider-Man a different relationship with his rogues gallery, especially characters like the Lizard and Doctor Octopus? Kev Walker and ScieTronc have incredibly distinct visual identities. Were there moments when their designs or pages came back and actually changed your understanding of this universe, or pushed the horror further than what you'd originally scripted? Horror can become less frightening once readers understand its rules. With both of you planning potentially very long runs, how do you keep the Midnight Universe mysterious and unsettling after readers have spent 20, 30, or even 50 issues living inside it? I know your books haven't launched just yet, but it's hard not to be excited for your books to somehow connect, given Spidey and the FF are thoroughly linked in the 616. Have you dreamed up crossovers yet? Finally, the important Midnight Universe question: if Midnight Spider-Man and the Midnight Fantastic Four were trapped together in a horror movie, who dies first, who somehow survives, and who makes the catastrophically bad decision to say, “Let's split up”?

When we first dicsussed the Summer of Simulative AI in 2024 we knew it would be a brief summer, but it has recently come back with a vengeance with SimGym in April and now Simile AI's $2B Series B, backed by GreenOaks and Index Ventures with prominent backers like Fei-Fei Li and Andrej Karpathy, running tens of millions of simulations for Fortune 100 clients like CVS and 85–99% accuracy vs human focus groups. Time to catch up on why this Second Summer of simulation is working!From creating Smallville, the landmark 2023 paper on Generative Agents that showed AI characters could remember, plan, socialize, and develop emergent behaviors, to now building foundation models of human behavior, Joon Sung Park is trying to answer a much bigger question: what if we could simulate the world before making decisions in it? In this episode, the Simile co-founder and CEO joins us to unpack the path from generative agents to digital twins, why today's frontier models still fail to capture how humans actually behave, and what it would take to eventually simulate all 8 billion people on Earth.We go deep on Simile's approach to modeling human behavior: long-form interviews, observational and transaction data, randomized controlled trials, population-level and individual-level models, and post-training on the causal mechanisms behind why people make decisions. Joon explains how his research created digital twins that reproduced human behavior and attitudes 85% as accurately as people reproduced their own responses, why models optimized to be rational can be bad simulations of irrational humans, and why understanding “social physics” may require changing model weights rather than simply prompting frontier LLMs.We also explore the much larger ambition behind simulation: testing products and policies before deploying them, finding counterintuitive paths toward desired outcomes, modeling emergent behavior across entire societies, and potentially tackling problems like climate change, democratic instability, and UBI. Joon reflects on scaling laws for simulation, the economics of data-center-scale simulated worlds, the connection to Thomas Schelling and psychohistory, why simulation is surprisingly similar to painting, and whether we might already be living in one.We discuss:* How Smallville and Generative Agents led to Simile* Why Joon's team asked: “What if we can just recreate the world that we live in?”* Why useful personal agents require deep models of their users* Memory architectures, Markdown files, and the limits of prompting* “Social physics” and behavioral foundation models* Why web data captures what people say more than what they actually do* Interviews, transactions, observational data, and randomized controlled trials* Why predicting the future matters less than understanding how to shape it* How Simile creates representative simulated populations* Simulation versus prediction and the connection to Foundation's psychohistory* How to evaluate simulations instead of simply stacking LLM hallucinations* Creating digital twins of 1,000 real people and reaching 85% behavioral accuracy* Why frontier models can struggle to reproduce real human behavior* Why good simulations need to reproduce human biases and mistakes* Post-training models on randomized controlled trials* Population-level versus individual-level simulation* Scaling laws for human simulation* The long-term ambition to simulate all 8 billion people on Earth* Whether simulations could help solve climate change or detect collapsing democracy* Thomas Schelling and the history of agent-based modeling* Why future simulations could require an entire data center* Multi-agent simulations and what happens when simulated people interact* Replacing expensive human panels with synthetic populations* Why market research is only the starting point for simulation* Why Joon sees simulation as surprisingly similar to painting* Using simulation to study questions like UBI* Whether we are already living in a simulation* Why AGI and simulation may be the twin technologies of advanced civilizationsJoon Sung Park* LinkedIn: https://www.linkedin.com/in/joonspark* X: https://x.com/joon_s_pk* Website: https://www.joonsungpark.com* Simile: https://www.simile.comTimestamps00:00:00 Introduction and Joon's Path from Art to AI00:01:46 Smallville, Generative Agents, and the Origins of Simulation00:05:03 “Let's Just Create a World” and the Future of Personal Agents00:09:53 Social Physics and Behavioral Foundation Models00:14:08 Prediction vs. Simulation: How Do You Shape the Future?00:16:59 How Simile Models Real People and Populations00:25:35 Evaluating Simulations, Digital Twins, and 85% Accuracy00:30:23 Post-Training Models to Reproduce Human Behavior00:40:04 Scaling Laws and Simulating 8 Billion People00:43:10 From Schelling to Society-Scale Agent Simulations00:46:13 The Cost and Economics of Simulating the World00:52:05 Real-World Use Cases, Synthetic Populations, and the Market00:57:27 The Future of Simulation, Painting, and UBI01:04:23 Are We Already Living in a Simulation?01:06:08 Building Simile and HiringTranscriptIntroduction: Joon Sung Park, Simile, and the Story So FarVibhu [00:00:00]: Today, we have Joon in the podcast. Excited to kick this one off. Very exciting company. I wanna kick off and ask you the question, talk us through the story of your life. How have you gotten here?Joon [00:00:13]: Yeah, for sure. I'm really excited to be here. A story of my life. So I was born in Korea, and I lived there for a good 11 years or so of my life, and then my family moved to Boston. So we moved when I was 11, and my parents were doctors, so they were going through their postdoctoral studies. My dad was a surgeon, so he was doing his sabbatical years at the Boston Children's Hospital. So I grew up there, not too close to tech. I was very much a music and artsy, painting kind of guy.Vibhu [00:00:49]: Painting.Joon [00:00:49]: Exactly. I got into painting a little bit later, in high school, but that's what I used to do. And then I grew up mostly in the East Coast after Korea. So I lived a good number of years in New Hampshire, and then I went to college in Pennsylvania. And I got into more of this tech scene, in college. So I was originally trained to be an artist. I thought that would be my professional career. So it wasn't a hobby. It was like, “Hey, let's make a living out of this.” And then gradually, I got really interested in this idea of, hey, the greatest artist often creates their own medium, and the best medium that we had available today was in computation. So I decided to go deeper into that, and one thing led to another, and we can go deeper into this, but I decided that research was something that I gradually got interested in, and here I am.Smallville, Generative Agents, and the 2023 Breakout PaperSwyx [00:01:46]: So there's a lot that you packed into the research components. You had one of the best papers of 2023, which was the generative agents paper, commonly known as the Smallville paper.Swyx [00:01:58]: Feel free to call back to anything else that you mentioned, but most people would have heard of you from this. Do you have any statistics on how many people have, like, read it? arXiv gives you something, right? Some stats.Joon [00:02:10]: Yeah, it's a good question. How many people have read it, I'm not sure.Joon [00:02:14]: I know we do keep track of citations, and they are going up quite fast.Swyx [00:02:23]: Yeah, Google Scholar has 7,200 citations.Vibhu [00:02:25]: I feel like it made a bigger hit than that, and it was a pretty instrumental paper. It got cited so many times.Swyx [00:02:34]: It is frequently the answer when people ask, “What is the best paper you've read recently?” It's this one.Vibhu [00:02:39]: I thought the memory component was pretty underrated. It was a very good early memory system, and one of the biggest papers.Foundation Models and the Search for Killer ApplicationsJoon [00:02:47]: Yeah, so maybe I can talk a little bit about how this particular paper came together. So when I got into research, it was back in 2020 when I started my PhD program at Stanford, and that was the year, when we were about to get GPT-3 to be available. So we already had GPT-2, and you could sense that there was this new class of models that was just becoming available in the market, and the team got very intrigued. And the general consensus was, “Well, is this model going to be useful for anything?” “It's really strange that these models are not trained to do any particular task.” But we decided to take a bet. So a large group of scholars at Stanford, and it was led by one of my co-founders, Percy Liang, and we came togetherSwyx [00:03:35]: Who coined foundation models.Joon [00:03:36]: Who coined the term foundation models. We wrote this paper, where that term came from called Opportunities and Risks of Foundation Models. And during that process, really the thing that I started to think deeply about was, here is a model that is fundamentally new in our ecosystem. The reason why this was new was it wasn't, again, trained to do anything in particular, but its premise was it could do anything and everything. It was like a stem cell, if you were to take a biology analogy. And I got really interested in this idea that, well, if we were to really think about what are the killer applications that this particular technology would enable, what would that be? Many of my colleagues were using this for simple classification, simple generations. Interesting that these models can do that, but from an interaction perspective, not that interesting. We've known how to do that for many decades. And what we came down to was these models are trained on this very broad data from the web, right? So these are human behavioral data. It's social media, Wikipedia, all these data. So if you poke at the right angle, then you could see human behavior that would just pop out that's quite realistic, and we've never seen that before.The Time Machine Game and Recreating the WorldJoon [00:04:45]: So that got us really interested. The exercise that we decided to do, with this particular group of colleagues, Michael Bernstein, Percy Liang, and myself, who ended up becoming my co-founder at Simile, we sat down and we played this game that we call the time machine game.Joon [00:05:03]: Imagine we were to get on a time machine and fast-forward 10 years and look back. What would have been the single application that will have mattered that would be the most interesting and inspiring? And when we thought, “Well, what if we can just recreate the world that we live in?” it's really hard to get more ambitious than that. Like, let's just create a world.Joon [00:05:24]: And that's where we started. And initially, we had this paper that was a precursor to the generative agents paper called Social Simulacra.Swyx [00:05:32]: Before you go further, were there other candidates for the most ambitious thing in the time machine exercise? What was number two or number three?Personal Agents, User Models, and Why Simulation Came FirstJoon [00:05:44]: There is a close second that we were considering, which ended up becoming more of these automation tools, especially the vision around really personalized agents that would do things for you.Swyx [00:05:59]: That's also happening.Joon [00:06:00]: It's also happening. But it was interesting for us, right, in that the reason why, we decided to go with the idea of simulation, one, I was a huge science fiction nerd, and this idea of creating simulation, I was personally really just fascinated. I loved the idea. It's really cool to see, like, a game town like this and just see these agents live in it. But at the same time, my bet was if you were to create a really amazing personal assistant out of this technology, what you need first is an amazing model of your users. So I told a model, “Hey, can you go buy late dinner for me?” And it orders Hawaiian pizza, and I do not like pineapples on my pizza. Then it totally failed. The way for it to not make that mistake is only by having a deep understanding of who I am. And I gave a very simple and dumb example here, but you can imagine how this core understanding of people is instrumental. This is how, if we have our family and closest friends, they have a good mental model of who we are. That's the basis of our social connection. So our bet also was this technology around simulation, creating accurate representation of people ought to precede the more complex agents that would automate the world that we live in. So that was the bet. But that was a very close second, and I'm still very much fascinated by it. I think there's a lot of interesting work that's going around. My hot take here, though, is I don't think we've seen a true personal assistant that's useful, in ways that meet the ambition of that particular line of work. I think there are early applications that are interesting, and if you talk to even ChatGPT nowadays or Claude, they know a lot about us. So a lot of the generation it's doing, I do think it's much more tailored, but I think the ambition is quite large in that field, and I don't think we quite have all the right ingredients just yet.Swyx [00:08:01]: So OpenClaw and these personal agents, what do you want to see from them that they don't currently have?Memory, Markdown, and the Limits of PromptingJoon [00:08:09]: I do think it's slowly getting there, but I do generally want them to have much deeper understanding of the person. Right now, you look at the models. OpenClaw, what it's leveraging is a Markdown file, and I think it's quite clever, right? So if you look at the generative agents paper, this was the same intuition that we had, where initially when we were creating the memory architecture for the generative agents, and, like, this is, like, back in 2022, so we didn't really quite have the idea of even agentive architecture or the term agent. But the intuition that we shared with some of the work that's coming out today was we initially thought, “Well, do we want to make the memory into, let's say, knowledge graph? Do we want to train a bespoke model?” All of these things. And what we decided to do was, “No. Just forget about all this.” These language models are quite good at modeling text and understanding and reasoning about text. So just put everything in a Markdown file or a text file. You're done. I thought that was quite interesting that we could do that, and there's a lot of strength in doing that. But also, there are limitations. It's the way you retrieve and make sense of data that's extremely large, it takes a lot of work. So I think that technology is getting better. I also do, however, think, there are certain things you just cannot shape just by prompting the model. So to some degree, you do need to touch the parameters of the model itself. So there is this work that I do think does need to happen, and it is happening. The question is, how far can we take it? How do we source data, and how do you also create an ecosystem where people are continuously feeding data to this model so it's learning about you?Vibhu [00:09:50]: What's the intuition between why you need to do it in the model?Social Physics and Behavior Foundation ModelsJoon [00:09:53]: My intuition behind the actual when do you train or even post-train a model versus just prompt a model is if the model has to learn the underlying physics of the world that it's operating in. So it has to learn new social physics. The places where it doesn't have to train are the places where it already has the physics. We trust the physics. It already has the base statistics, but it's just trying to react to an environment. Then I think you can just prompt your way into getting the actions out of it. I don't think the models that are out in the open have yet learned the complete mapping of social physics of humanity. This is one of the core theses of Simile, right? And one of the core reasons why that is the case is if you look at the data that the model was trained on, these models were trained on the web data, like, whatever was available on the web. And these are really interesting data sets, but they are fundamentally the self-exposed attitudinal data with some behavior data that's sprinkled around here and there. And it has yet to learn the really deep behavioral nature of people, not just what people say they do online, but what they do in real life. And this is one of what I would consider to be the dark knowledge of humanity that we haven't quite captured. And it's these data that would also need to get factored into the model creation.Vibhu [00:11:21]: You call it behavior foundation model.Vibhu [00:11:23]: There's a good one-liner here, but outside of that, what type of data do you need? What are you changing on the model level? How do you go about modeling, doing a behavior foundation model?The Three Data Buckets: Interviews, Behavior, and CausalityJoon [00:11:35]: We think about data in three buckets. So one bucket is interview data. It's quite interesting. Rich qualitative data is interesting. It's not behavioral, but we would literally ask people, “Hey, tell me the story of your life.”Vibhu [00:11:53]: It's just what we're doing here exactly.Joon [00:11:54]: The question that you all asked at the beginning of this interview literally is the question we also ask. And we ask our participants to go a little bit deeper, than how far I went. Maybe I can give more of my life story in lieu of this. But the reason why that data is interesting is by learning about this very long-tail information about people, you get a lot of texture around this model, like, this person as a model. So even understanding their childhood memory or even their trauma, their first love, these things, quite informative in ways that's really hard to predict. So that's one. Then there are two tranches of what I would consider to be the behavioral data. One kind of behavioral data is observational. So these might be like transaction data, or these might be data that you can get by scraping the web, right? So you can imagine why these data sets would be interesting, right, because they give you the base statistics of people's behavior.Joon [00:12:55]: But then there is the last category of data, that I personally think is perhaps the most important, which is the data that describes the causal mechanism, the whys of people. Some of this is covered by the interview data, the qualitative, because people talk about why they made certain decisions. But really, where you get to see the most behavioral aspect of this is in randomized controlled trials, like RCTs. Imagine you have the same setup, but you have a few different variables that you are trying to tweak. Can you get realistic human behavior out of it in ways where, imagine you had this particular option. Imagine you're even trying to choose whether you're going to drink coffee or not. The day you drink coffee versus the day you didn't drink coffee, does your behavior change? That's a data set that describes a causal mechanism. This is quite important in modeling people. The reason why this is important is oftentimes when people come to us, or not just to us, but the reason why people are interested in simulation isn't because they want to predict the future. If you're trying to win against the stock market, predicting the future is interesting.Prediction vs. Simulation: Shaping the FutureJoon [00:14:08]: But most people, most decision-makers, what they want to know is, how can we shape the future? It doesn't really help you to hear that your sales are going to tank in two quarters. They're just gonna say, “Wow, that sucks.” What they want to know is, well, what do we need to do now to avoid that future? That's the causal mechanism. And this is also very hard data to come by, right, because the world is our ground truth, but it happens once. So in a very controlled setup where everything is equal except for one variable, this kind of data set rarely happens. So this is a reason why this data set is both hard to come by and quite important if you're trying to model human behavior.Swyx [00:14:50]: So behavior, I think, is the hardest data set to acquire. What is out there? What is even possible? You're not going to know a lot of details about my life. I don't even have data for myself on my own health or habits, and I just don't log everything. So how can you have that data?Joon [00:15:14]: So we run a lot of randomized controlled trials.Swyx [00:15:17]: But you put people in the lab, they watch them sleep, or what?Joon [00:15:20]: We do care a lot about the consent process. People know that we invite them to be a member of this community to both share data and have themselves represented in different forms. But we bring a lot of people to the lab, or virtual lab, where we design experiments that would pose them real behavioral decisions. And often in these experimental setups, what makes the difference between what is attitudinal versus behavioral is whether the stake in your decision is real. That's ultimately what makes it behavioral. So in these setups, we are inspired by our colleagues in social sciences, psychology, and so forth. So when they run studies, the techniques they utilize is imagine there's an online store that you're inviting people to come by. Then whatever they purchase in this experiment, they actually get that item delivered. Like, these are the things that make the stakes real. So we run a lot of these experiments, and we also do partner with firms. Right now, we also have customers who are quite excited to at least give us a glimpse of the behaviors that their users exhibit so that we can get a little bit deeper understanding of how people behave in these different platforms.How Customers Use Simile: Populations, Queries, and ExperimentsVibhu [00:16:39]: I think on the customer side, they have a lot of data about their users, who has bought. They have the action data.Vibhu [00:16:47]: Can you walk us through an example of what someone comes to you for? What questions would they want solved? Do you customize a model for them? Do you have something off the shelf? What does that look like?Joon [00:16:59]: Today, when people leverage our models, it's often to better understand the population of their interest. So usually, the start of the relationship, we come together and hear about what population they want us to model, right? So it might be that if you're a CPG company that's selling to all of the US, then maybe it's fairly straightforward. You want to model the gen pop of the US. But at the same time, if there is a vertical or if there's a market that they're trying to go into, imagine, they want to better understand, let's say, people in their 20s and 30s living in California. That's a much more specific population. So we hear about this population, and we go recruit these people, with consent, and with incentives, and we collect some of their data and create a model of these people. Then what our product allows you to do is query them. So it can take as input a filter that is a description of the population that you want to talk to, just like the one I just mentioned, and an environment. The environment can literally be survey questions, behavioral experiments, It can be A/B testing. Oftentimes, the core use cases are things like concept testing, to start with. But also, people sometimes want to do focus groups or one of the fun use cases that we also serve is even modeling things like earnings calls for public companies.Joon [00:18:21]: So these are the use cases that we often start with.Swyx [00:18:23]: Concept testing, is that an established term? I've never heard of concept testing.Concept Testing, Gallup, and PoliticsJoon [00:18:27]: Yeah. So it has to do with they have, let's say, different messaging, different products, different ideas.Swyx [00:18:32]: It's like a marketing exercise.Swyx [00:18:33]: Okay, got it. Got it. Politics?Joon [00:18:36]: We do, have a strategic partnership with Gallup, and of course, Gallup is deep into policy space and so forth. Right now, we have not worked deeply with politics, like that area just yet, however.Swyx [00:18:49]: I'm curious if there is demand or if they really would have different needs that somehow fundamentally don't mix with your existing, users or people.Joon [00:19:00]: I think there's certainly demand.Joon [00:19:02]: But we are very much mindful of how this technology gets adopted and the societal impact that we'll end up having with this technology. And I do see politics as an area where a company has to be particularly thoughtful about the way they operate and make impact. So this is where we also want to make sure that we form enough of guardrail and perspective on how to leverage this technology before we go on to serve markets like the politics.Swyx [00:19:29]: I'll give people an example. one of my favorite shows is The West Wing. I don't know if people have watched.Swyx [00:19:34]: One of the key storylines is, like, the president has, multiple sclerosis, but they haven't. they need to figure out how to disclose it. So they run a poll with a fake governor and ask people to respond on the poll,Counterfactuals, Polling, and When Simulation Is UsefulSwyx [00:19:47]: They try to make decisions based on the results of that poll on, like, how well they'll be received, like where, how should we play this?Swyx [00:19:54]: And I'm like, well, I think those counterfactual things, I would use a simulation for this if I could trust it.Joon [00:20:01]: For sure.Joon [00:20:02]: In that show, how'd it go?Swyx [00:20:04]: In that show, it was, like a foregone conclusion. They were like, “We know it's bad. We just don't know how bad.” And then the poll came back. It was like, “It's really bad.” And then they just did it anyway.Joon [00:20:14]: Part of it is to show, right? So you're, you're looking at the ideaSwyx [00:20:17]: Maximizing drama.Joon [00:20:18]: How bad could it be? Oh, it's horrible.Swyx [00:20:20]: And to some extent, I think that is part of the trick of the, or the challenge or with being a customer of yours, which is that if I know it's. if I roughly know and can intuitSwyx [00:20:35]: What the effect is going to be, do I need you? What sensitivity of it, of effect do I need in order to make a decision, right? So for example, if I, my approval rating is 50%Swyx [00:20:48]: And I, they have this negative piece, news item comes out, and it drops to 30.Swyx [00:20:52]: If it drops to 20, if it drops to 40, do I care? No. It, I know it drops. It's negative. So when do I care about simulations?Joon [00:21:01]: You do something that's clearly bad, that's not popular, and people don't like you, like, yeah, it's likeSwyx [00:21:05]: You don't need a simulation.Joon [00:21:07]: Yeah. Well, so there are a couple of things. one is, there are use cases where, like every day, developers, designers, policymakers, marketers, every single day, they create assets. They create new products. And turns out, it's many of the decisions in hindsight is obvious. Yes, of course this is bad, but we still run those studies because understanding the magnitude and understanding how acute something is quite difficult, even if, we feel like, of course, like this makes sense. this is the reason why we make so many mistakes. Like, every time somebody goes online and say something that has huge backlash, you look at that and like, “What an idiot.” However, it's tough. That's one. There's also another aspect here, which is, again, this is the reason why simulation is different from prediction. In simulation, in the ideal case scenario. So what simulation is trying to show is it's trying to show each step of the way or each step that we need to take to get to a certain outcome, right? So in the most advanced simulations, sometimes the next step that we're suggesting might be quite counterintuitive. The analogy that I sometimes give, and I ground it in a more realistic example, but, I, as I mentioned, I'm a huge fan of science fiction, and I don't know how, many of the audience members have read, like, things like the Foundation series by Asimov.Simulation as a Path, Not Just a PredictionSwyx [00:22:37]: Oh, yeah. We've mentioned psychohistory a number of times.Joon [00:22:39]: Okay, fantastic. So I might be, talking to the right crew. If you read Foundation series, literally the first act is there's a group of scientists who have found out that, “Oh, our galactic empire is going to collapse, and we're going to have 30,000 years of unrest.” And they run psychohistory, the simulator that tries to teach them, “Okay, how can we keep this unrest to a 1,000 years?” And they plan this out, and the first step of that plan is to get the scientists who say, “Okay, this is coming,” exiled into this random place in this, galax- galaxy.Swyx [00:23:18]: Terminus.Joon [00:23:19]: Exactly. And that's so counterintuitive. Like, what a strange move that you literally sent the group of scientists who was raising voice around this potential collapse of galactic empire into nowhere. How is that the right first move? Well, it turns out in this particular simulation, that was the move.Joon [00:23:40]: It's these things, right? And the reason why these reasoning is possible is because you're showing the step function or each step that results in a particular outcome. So really what simulation allows you to do in its highest form is you give it not a problem or question, like what would people answer to the survey? That's not what we do. What we tell it is, “Here is a goal that we have. In the context of foundation, we want to keep the unrest to a 1,000 years. What is the path that we need to take now to get to that particular future?” And that's what simulation allows you to do. Now, translating that into real market, imagine you're a automobile company and you're about to release a, EV, and you're trying to understand, well, how do we market EV, to make sure that our stock price goes up? But what if the answer comes down that, well, you can market your EV in XYZ way, but that might change people's perception around the cars that's not EV and make your overall sales to go down. Not very intuitive, especially all you're trying to optimize is EV salesss, and that's the only thing that you're tracking, then that might result in a completely wrong solution, or at least different solution than what you would have expected, whether it's right or wrong.Joon [00:24:57]: That's the power of simulation.Swyx [00:24:58]: For listeners, we covered a similar topic with Mikhail Parakhin from Shopify, where they are working on SimGym. I don't know if he ever talked to you about it. it's very similar.Joon [00:25:07]: ISwyx [00:25:07]: The goal is increased conversion, but then the journey is very unusual.Joon [00:25:12]: Journey is unusual.Swyx [00:25:12]: Yeah. The-- He's trying to look for interventions on a shopping trajectory, which is similar to what you're saying. Like, it's not about the attitudinal, is your word for it.Swyx [00:25:24]: It's about behavior.Joon [00:25:25]: It's about behavior.Swyx [00:25:25]: And that's exactly the difference, right? It's, like, not about the near-term direction about-- but it's more about, like, how do you affect multiple turns of interactions.Vibhu [00:25:35]: You had a good quote at the start about this as well. It's not about people wanting to know the outcome. It's about how they can change it, change the way to get there, something like that. But I wanna take it back to how do we know this is grounded? LikeGrounding and Evaluating Digital TwinsVibhu [00:25:47]: How do you run evals? How do you test that simulations come through? if I was to do the same thing that you described with, say, your favorite LLM, Opus, GPT-5.6, have some agent to map out these thingsVibhu [00:26:02]: How different are the answers we would get if I give it the same goal, the same objective, make a decent system? You're saying that you need to change the model weight. You have your own solution to this. But how far off are we, and how do you check if it's grounded? you have some interesting stuff on your site that points to how you run real evals, but if you could take us through that side. I think that's one of the big concerns that people have. They're like, “LLMs hallucinate.”Vibhu [00:26:27]: “You're just hallucinating layer after layer,” right?Joon [00:26:30]: The way we do this, and this is the paper that we worked on after the generative agents paper that really became the, at least for Simile and also the field of simulation and synthetic panels, really became the foundation. Yeah, this is the paper. the paper is called Generative Agent Simulations of 1000 People. Here's what we've done. For this paper, we brought 1,000 people that's representatively sampled from the US to a virtual lab. And what we have done was we spent two hours collecting fairly wide-ranging data. In this particular study, we focused a lot on this interview data, that was, whose script was taken from this project called American Voices Project. And then we would also pair that with a lot of behavior data and so forth, whatever we can collect within two hours. And then we would send these people away for a couple of weeks. And during that time, I would use this data to create their digital twins. And I would bring the humans, participants back after 2 weeks and have them complete a battery of surveys, experiments, behavior studies. So we have the list here, which included things like behavioral economics games. We would run literally, like, Big Five personality test, General Social Survey. We would also go ahead and run the randomized controlled trials that were published on PNAS. And we would have their digital twins predict how the source individuals would have acted in these studies and surveys. And this is where we could replicate people's behaviors and attitudes 85 percent as accurately as people would replicate their own. So that was the first really paper that gave this validated results that we can model individuals in an accurate way. And what we ended up finding now, of course, in AI space, so this paper came out at the end of 2024. AI space, a year and a half, 2 years, that's a lifetime.85% Accuracy and Why Frontier Models Miss Human BehaviorSwyx [00:28:24]: Yeah. Just, for listeners who are not seeing the YouTube, I just wanna say, like, the headline figure is 85 percent accuracy, like, which is a big improvement over all the otherSwyx [00:28:34]: Methods that you showed.Joon [00:28:36]: But the part that was particularly striking to us, especially as we improved this technology even further, was the generative AI models like ChatGPT, Claude that's coming out, it does give you the right foundation. However, what they do not consider is the true attitudinal and behavioral aspect of people, especially in the population that you care about. So what these models are really good at today is they're trying to become the super rational, objective machines, right? So you go get their data from places like Mercor, Scale. You talk to professional programmers, scientists to create model that's amazing at reasoning. That's what they do. Simile doesn't care about any of this. The models that we're talking about here, what we're trying to create are models that are as dumb as I am, right? So if I make some mistakes, the model has to make the same mistake.Swyx [00:29:34]: Oh, that's very hard.Joon [00:29:35]: That's very hard.Swyx [00:29:36]: You're solving Murphy's paradox.Joon [00:29:37]: That's exactly. And this is a completely different data and training objective. This is also where we see quite a bit of discrepancy in the performance in human behavior prediction between the frontier models, Simile's model, and the models being created in this space, where in some cases, the model performance of frontier models go all the way down to 20, 30 percent, especially if you go into that more niche population on topics that our customers would care about. On more gen pop, it might be around 50 to 60 percent. So it's not very robust. Like, you wouldn't want to make your decision off of these and these findings. If you can bring that up to 85 percent, that is ultimately what people end up getting very excited about.Swyx [00:30:20]: Yeah. Do we wanna keep going on the paper, routes?Joon [00:30:23]: Yeah, for sure. So the last one, was an interesting one. So this, paper was the follow-up paper that we had, to the 1000 agents paper, where the idea was now can we augment the models even further and post-train a model based on a lot of randomized controlled trials? So this was an interesting one. The data is always the most interesting part of modeling in many ways. The data that we got here was there's this, there's this platform called Open Science Framework. So some, the audience might be familiar with this. And there has been, especially in the social sciences over the past 5 years or so, there has been this concern around replicability of studies. And so it was a bit of a crisis, the scientists acknowledged, where we rerun the study and we don't see the same finding.Post-Training on RCTs and Replication StudiesVibhu [00:31:12]: Oof.Joon [00:31:12]: It's tough. And the reason why it's there-- that was often the case was there's this survival bias where the papers that get published often need to maintain what we call the value of less than 0.05 in the experiments that we ran. That suggests that only-- there's only 5% chance that the results that we saw is false positive. But the tricky part was all the papers that were not published, and there's still a 5% chance that whatever we publish is totally just randomly generated. Like, there's a 5% chance that, hey, this effect is not real, but it just happened to be real because of the sampling bias. So because of that, what scientists started to do was they started to register their studies. So before running an experiment, they would go to this platform and say, “Here is the data. Here is the population that we're collecting, and here's the hypotheses.” And they would just say, “Here is our hypothesis.” Like, “This is what we believe.” And you cannot retroactively change those hypotheses. This is what gives us more scientific statistical confidence that whatever effect that you ended up seeing is true. So that ended up creating this really interesting platform where there's one platform that has now contains tens of thousands of real-world experiments and hypotheses. And a lot of these are really high-quality, like, professionally designed behavior studies and random- randomized controlled trials. So we got the data and the studies from this platform and used that to make a point. And this particular, model is not, something that we're serving commercially because this was a part of the open science. But this particular data set, helped us make a point that by collecting a lot of these randomized controlled trials, that are really well-designed, we can make significant improvement in model's capability to predict human behaviors. So that's what this paper was about.Vibhu [00:33:10]: Is this stuff done on a individual level? Like, do I need to tune the model per individual, per company? Is there foundation model changes and then some slight post-training? Anything you can share there?Population-Level vs. Individual-Level ModelsJoon [00:33:21]: So this particular model was trained. the data we had at the level of individuals, but this particular model was trained. We experimented with both. And this is what we end up doing at Simile too. We always train 2, distinct model. One is what we call the population-level model. The other is what we call the individual-level model. And both take very similar input, which is the description of a subpopulation or individual and a stimuli. In this particular work, we've done the same. Here, the results that we are reporting are much more geared towards individuals because we do think that is a harder task in many ways, but that's what we have done.Vibhu [00:34:02]: You seen anything on the questions that humans can solve that models can't solve? So likeHuman Biases, Mundane Choices, and What Models MissVibhu [00:34:09]: Currently, it's, I live 5 minutes walk away from a car wash. It's a 10-minute drive. Should I walk or drive?Joon [00:34:16]: Huh.Vibhu [00:34:16]: The model will say, “Oh, walk to the car wash.” And, you don't have your car.Vibhu [00:34:20]: Is anything like this a problem in simulation? You would assume, like, very simple for human to think about, but if the model is saying you should walk to the car wash, anything here?Joon [00:34:32]: It's less, what can we solve, but I think it's more about what biases or mistakes do people make that models miss. Like, imagine that you are, like the. When I was still at Stanford, I lived in Palo Alto. So it's about, I would say, 40-minute walk from the campus. You ask the model, “Okay, let's go home. What can I, what can I do?” It would likely call an Uber or, give me, the bus time. But for the longest time, I really liked walking back. And the reason why I wanted to do that was not for efficiency. It really helped me think. And I like to walk for, half an hour or 40 minutes or so a day, where I just get to, just think about ideas, research, just get lost in my thoughts. That's very human activity. Unless the model has seen that and understands the importance of that activity, it would miss these kinds of features. So that I think, is fundamentally what we're trying to model. Like, what is fundamentally human might not be the most efficient thing to do, might not be the right thing to do, but things that make us who we are.Swyx [00:35:43]: I'm curious if, there are some data sets that you really want that would materially help you. One version of this may be interesting, which is more valuable to you to acquire as a data set, all of LinkedIn, all of Twitter, all of Facebook?What Data Matters: Social Media, Transactions, and FacebookJoon [00:35:57]: It's a little bit hard to rank, in part because, there's, there's this product saying where no feedback is wrong because it teaches you something about your users. Doesn't matter what feedback.Joon [00:36:11]: I think it's a little bit like that.Swyx [00:36:12]: So just whatever is bigger.Vibhu [00:36:13]: What about a different domain? Say it was. What about all of Amazon data?Joon [00:36:17]: Oh, yeah.Vibhu [00:36:18]: Shopping data, right?Joon [00:36:18]: Shopping data. So Amazon data is interesting in that it's very much behavioral, although, like, what people do on social media, you could squint and say that is also behavioral. But the transaction data is always interesting. It is also most commonly available, however.Joon [00:36:33]: If we were to look at purely social media, like if you really, if I were, if I had to really pick, Facebook likely is interesting because I do think it is most a default version of people. Because you go to LinkedIn, it's very much professional environment. So people put up their, they have their guards up, right? And that still is interesting because that is true human attitude and behavior, but it is not your base state. you go to Twitter- Twitter, people have their own crazy personas, or depending on who you are. Like, my Twitter profile and, persona is very much, initially was I was very much an academic. “Hey, I'm here to share my studies.” Now, I share, things that's related to Simile. But Facebook is one of those more private space where people just connect with their friends. In that way, I do think it shows you a little bit more about who that person is. So if I had to pick, I'd likely pick, Facebook.Swyx [00:37:30]: Yeah. And you're interested in, like, the whole person and their background and philosophy. I, is it too clinical or too machine learning-oriented to just say this is just ways to inject variance and biases? The broad question, is, like, is this any better than a randomized, like, combinatorial explosion version? So we have a link to the TencentBillion Personas, Synthetic Demographics, and Bespoke DataSwyx [00:37:54]: Billion persona paper, where they did not do any of the groundwork that you are doing.Swyx [00:37:59]: They just did like a cross matrix of here's all the professions in the world, here's all the people, possible backgrounds in the world, do a dot product across all of them, and that's it. That's your prompt for a billion people.Swyx [00:38:12]: This will do something. I don't know if it'll do what you do, but it gets you some way, some percent of the way there.Joon [00:38:18]: So this was an interesting paper. Like, what I admired about this paper when it came out was the scale. And you do gradually want to be able to simulate really large societies and interactions. So the scale is definitely admirable. it is relying heavily on the known statistics that went into training the model. So to the extent that you believe that statistics is correct, this is not a bad way to go about this. But the thesis here, and this is something that we also have seen in the market, like if this works, then we have solved simulation.Joon [00:38:54]: It,Swyx [00:38:55]: Because I survey, like, okay, 5% of the US population is in construction.Swyx [00:39:01]: The other 5% is in medicine, whatever, right? And then you just keep going down the list, and then you do the other side. 5% has, like, the big 5 personalitySwyx [00:39:08]: Of, like, neurotic or whatever. That's it.Joon [00:39:11]: That's it. So if you believe that the underlying data set and the platform that we're leveraging has all the right statistics, then this will have solved it. you're at that point merely retrieving the knowledge that is already embedded in the model, in the model parameters. That's not, unfortunately, what we see, where there is such detailed and also niche knowledge about people that if you just take one example, it might feel very mundane, but it's quite rich when you put together, that you do need to do a lot of bespoke data collection to better understand people. And this is also, I think what makes this particular, job fun, which you want to deeply understand people, and the process of deeply understanding them requires a lot of attention to the details. And you do need to pay attention to and pay respect to the daily lives that people lead.Scaling Simulation: From Thousands to SocietiesVibhu [00:40:04]: I wanna talk about scaling simulation.Vibhu [00:40:07]: So what can't we simulate, what can we simulate, and how does scaling affect this? So how big are the models? What if we go from, 8B, like, couple 100 billionVibhu [00:40:18]: Like billion000 parameters, billion000? Do we get scaling? Any interesting emergence? Like, at a certain scale, at a certain amount of training, you uncover anything unusual and any learnings from that?Joon [00:40:31]: What we are seeing is at Simile, so we do post-train our own model. The thing that we're seeing is the early glimpse of scaling law in simulations. The more data about humans and more compute you ingest, you start to get predictive and predictable gains of the model performance in simulating it, simulating people.Vibhu [00:40:51]: Ooh. We need a scaling law curve.Joon [00:40:52]: It's scaling law. Whenever you find it's a beautiful thing. And we're starting to see the glimpse of it, which is quite exciting. But if you talk about the ambition of simulation as a whole, it's not merely about building a model. It's about building a model, then creating the agents that become the individuals in a much larger ecosystem. So they're creating this multi-agent simulation. Down the line, you want these multi-agent simulation to also live in a very rich environment, right? What we are really trying to get to at that point is, hey, can we create. All right, let's do a time machine game again, and 5 years, 10 years into the future, can we create a simulation of 8 billion people living on Earth? I think that's quite interesting. And that really is the vision. And once you get to that state, the questions that you can help answer for the society also start to change from my perspective. The answers are fundamentally about emergence of the emergent behavior of society and large groups of people.Joon [00:41:53]: So the questions that I get excited by, and maybe this is a stodgy- a bit. I have my, academic side of me.Joon [00:42:01]: And for me, it's questions like, can we help solve climate change? If you look at climate change as a problem space, this is what we, like social scientists would often call it the wicked problems, problem where you have many actors with competing incentives for trying to make a very complex decision and coordinating that coordination decision. Very difficult to really solve in real life, which is also the reason why we couldn't solve it. Can simulation help us solve that? Another one is, can we understand the signals for collapsing democracy, or can we understand or can we uncover the origin story of the monetary system? These are societal questions that we never really had a good way of answering. If we can create simulations of our society, you have to believe that these are the problems that we can solve. So that's really the ambition of this field. And, I also think, yes, I think there's a Nobel Prize to be won there, which wouldn't be surprising. And I think there's some amazing societal impact that we can have to help people make better decisions.Climate Change, Democracy, and Societal SimulationSwyx [00:43:04]: Nobel Prize in economics?Joon [00:43:06]: In economics.Swyx [00:43:06]: Oh, I see. I see. Rooting for you to write that paper.Joon [00:43:10]: One of these days. But, one of the scholars that I was deeply inspired by, When I was coming into the space of simulation, is this scholar, named Thomas Schelling.Schelling, Agent-Based Models, and the Nobel PrizeSwyx [00:43:23]: Schelling point?Joon [00:43:24]: So the canonical example of the work that he's done was he was one of the creators of agent-based modeling. So this was, like, in the 1970s and 80s. It's very early days, but this was truly one of the first exemplars of simulations. And one of the canonical model from that time, and of course many of these simulations are trying to tackle the societal problems that's most relevant for their era, it was called the model of segregation. So racial segregation was a big topic, that, we cared about. And what they've done was they created this grid world where they had red dots and blue dots. And these dots were, back in the day, like, they were the agents, and they had a simple rule that governed their behavior. If certain percentage of your neighbors are of different color and if that goes above certain threshold, then you move to a new location at random.Joon [00:44:21]: One of the striking finding of this paper or this agent-based model was for the longest time, people thought the segregation within society was caused by explicit and overt racism.Joon [00:44:34]: But if you look at this model, people's preference towards living with people of the same color, that preference can be very minute.Joon [00:44:42]: But the very small difference causes the society to segregate completely over time. This was very counterintuitive for a lot of people. And this particular work ended up informing housing policies. Mixed income housing, got really inspired by this work. And Thomas Schelling ends up winning the Nobel Prize for having laid the groundwork for very early versions of simulations. The opportunity that I do see here in the more scientific terms, is agent-based models for the longest, had impact in the 1980s, 90s, to some extent, early 2000s, but it has now gotten forgotten by the community a little bit. Because as you can imagine, red dots and blue dots is not really a rich description of people.Joon [00:45:31]: But with the emergence of things like generative AI and, in particular, generative agents, we do have an opportunity to create these agent-based models that are high fidelity enough to help us make really complex decisions. And that's the opportunity that I see. If that truly works, then yes, that is the work that will result in a Nobel Prize.Swyx [00:45:53]: Yeah. For what it's worth, and I grew up in Singapore. 80% of Singapore is in public housing, and public housing has, enforced racial quotas for exactly that reason, which is very interesting. okay, so we talk about scaling, we talk about all these, the agent possible applications.Cost, Reuse, and the Economics of SimulationSwyx [00:46:13]: I'm scared about the cost. if you even-- let's just keep it to the US, about 8 billion people.Swyx [00:46:21]: But, how much does it cost to model so many hundreds of millions of people?Joon [00:46:26]: Oftentimes today, we don't start at that scale, this stage of the, of industry and simulation as technology. But we can get our users extremely rich and meaningful insights even by modeling thousands, tens of thousands of people. And today what we do is every week we are collecting data on the scale of tens of thousands people's data, and we have panel partnerships that gets us to tens of millions of people globally. So that's what we do today.Swyx [00:46:55]: And just as a side note once you've collected one person for one studySwyx [00:46:59]: Can you reuse that same person for all the subsequent studies?Joon [00:47:03]: That's exactly right.Swyx [00:47:03]: Okay.Joon [00:47:04]: The beauty of this model and these agents is the fact that they are domain-agnostic.Joon [00:47:08]: That what you're really trying to understand is what is the fundamental nature of these people? What's their social physics? And there are a lot of, a lot of, people that does change over time. Like, even, like, even things like, how many times have you gone have you been to, like, CVS the past week? that will change. But there's so many traits about people that are also known to never change. Like, your risk tolerance doesn't really change over time. It's very consistent. So it's these things that we're trying to learn. But the scale we are operating is right now hundreds or, tens of thousands to hundreds of thousands. And in many of the core use cases that we are deployed in, and this is more than enough population, to cover those. Really, at that point, what you care about is less the number of people, but more do you have the right subpopulation of interest covered? And this is also the reason why people want a larger sample. It's not because they want, stronger statistical guarantees. It's more that can they filter down to any population of their interest. However, you can also imagine in 10 years, if we truly believe that the compute is going to scale, that we'll have much more availability for compute, and our ambition for simulation is also going to scale accordingly, there's definitely a reason for us to create an entire data center worth of simulations.Joon [00:48:35]: Or in my hunch here is I do think in the next some number of years, we will start creating simulations that will cost as much as training a foundation model. But perhaps it's going to be so valuable to the society that it would be a no-brainer. Right now, even today, like, we are training bunch of new foundation model just so we can say we trained one and we spent tens of millions. But if we can create a simulation at the level of society that would solve climate change, I would run that today. I would raise the money right now just to run that.Multi-Agent Simulation and Social InfluenceSwyx [00:49:10]: Amazing. the follow-up question is, does it also compound if you let the simulations talk to each other?Swyx [00:49:18]: Or do they already do that today? They don't, right, as far as I understand?Joon [00:49:22]: It depends on what simulation you're trying to run.Joon [00:49:24]: In the multi-agent simulation setup, the agents do talk to each other.Swyx [00:49:28]: Right, which is exactly Smallville, right?Joon [00:49:29]: That's right.Swyx [00:49:30]: But a lot of times, for example, in commerce, you're just by yourself, so there's no point talking. which is way cheaper.Vibhu [00:49:37]: But they use all these levels, right? Like, you decide what you will buy based on what other people around you buy and talk about, right?Swyx [00:49:43]: It depends.Vibhu [00:49:44]: It depends.Swyx [00:49:45]: Again, I'm, I'm coming at this from a cost point of view. I'm like, “Oh my God.” LikeVibhu [00:49:48]: I thinkSwyx [00:49:49]: If there is, like, some combinatorial thing of, like, thousands of people talking to thousands of people, then that one million X's might cost.Vibhu [00:49:56]: I have a very different view as the cost point aside. Like, running these studies in reality is a lot more expensive, right? Running any study like this is you gotta have people do it, you gotta sign people up. It's very expensive and sometimes, like, not feasible to run the study.Vibhu [00:50:14]: But the outcome or the decisions you make are very expensive on them, right? So spend X million on something that, the overall process costs 100 million might as well, right? There's, there's a lot of value to be had there. It's a small cost, but I'm excited on the cost side.Joon [00:50:33]: To some extent, and when you deploy technology, you often want to deploy in a way where you can replace existing budget or you can make things more efficient, and that is the best way to deploy. However, the way you capture the long-term value of the technology is making the argument that, no, it's the upside, that by making this better decision using simulation, you have saved yourself or made yourself hundreds of millions or even billions of dollars, and that's a case to be made.Vibhu [00:51:06]: Random tangent question. So if you're doing a lot of inference, a lot of model multi-agent stuff, are you at the point where it makes sense to, train a model that' very sparse? You're expecting to do multi-million dollar runs. Are you thinking about this in model architecture standpoint or inference efficiency, or, you're still at the research phase of it works, we're not super there yet?Joon [00:51:34]: Efficiency, we do think quite a bit about. this is technology that is deployed now in some of the largest enterprise companies in the world, and we do process significant number of queries, that are trying to, simulate the populations in the world. So efficiency is a consistent thing. we don't want to over-optimize too early, so I wouldn't say, like, this is the higher bid Right now, but this is definitely something that we think pretty carefully about.Swyx [00:52:05]: Yeah. Are there other case studies? So we, you talked about CVS, talked about Gallup, Deloitte, Wealthfront.Efficiency, Enterprise Use, and Real-World Case StudiesJoon [00:52:12]: Wealthfront is an interesting one, because one of the things they were trying to do, they were one of the first customers that wanted to do product testing that goes beyond just asking people what they think about, let's say, behavior experiments and so forth. So there, really what we had to do was reason about multimodal input, so images, but also you can also imagine, like, these agents traversing through Figma mockups or websites. So some of the things that our agents can also do is it can be given a domain, like, or, like, a website URL and go use it for a while. It's these things. And Wealthfront was one of the first, customers, that was very excited about this possibility.Vibhu [00:52:53]: What have people been asking? Like, is there any demand that we have not covered? Like, UI testing, right?Vibhu [00:52:59]: I wanna try a new. I wanna ship a new feature, test the UI, simulate how people will do it. Any interesting things that you're seeing demand for?Product Testing, Websites, and Synthetic PanelsJoon [00:53:08]: Today, a lot of the demand does come from like, the places where people have historically used human panels, we can now replace with agents, and these synthetic populations. And this is not replacing human panel. in many ways, the simulation that Simile is building is grounded. So the way that I think about this is we are trying to represent humanity at scale. And in that way, the use cases are what we would expect, but it's the scale of deployment that surprises me.Joon [00:53:44]: Turns out there are so many decisions that people make every day in these organizations, groups, and we want to be able to say, “We listen to people. We have consulted our users.” But in reality, that is rarely the case because getting to people and asking them many questions, it's difficult. It's both costly, time-consuming, but most importantly, people are just not available. If I had to answer 1000 survey questions for this one particular, vendor, even if I wanted to do that, like, I would never do it. And that's very much the case. What simulation can do is ensure that the voices of people are always represented in rooms where the decisions for them is made, right? So all the stakeholders of this particular product launch, ideally they're consulted. That's what this technology really is trying to enable.Market Size, TAM, and Human Decision-MakingSwyx [00:54:39]: In my mind, that means it skews towards more consumer focus, right? Like, anything with a wide enough customer base where you do benefit from the diversity that you represent. What are some rough statistics, just for people who are not familiar with this market in general, what's the market size that. I'm sure you have some, like, rough numbers. market size is, like, a vague questionSwyx [00:55:01]: But, like, how much do people spend?Joon [00:55:03]: So market research is a $100 billion industry.Joon [00:55:06]: But the thing about simulation is not a tool for market research. Simulation is a tool for human decision-making. So the question around what is a TAM here is quite tricky, right? Because it's easy to say, “Well, market research TAM is roughly 100 million or 100 billion.” so is it a TAM? And not really, right? Because in many ways, you're trying to inform all human decision-making. You're trying to inform every decision that are made about humans for humans. What is a TAM for that? It's really unclear. And I'll be honest. Like, I have a scientific background, I have a research background, so I didn't come into the field calculating, oh, what is the TAM for human decision-making? But I just had to assume, well, if we can inform every decision that is made about human for human, that has to be big.Swyx [00:55:58]: Some- something valuable.Joon [00:55:59]: Exactly.Swyx [00:55:59]: To some extent, you are a unicorn founder now, and you have to care as a CEO. But, like, I do think, like, yeah, when you go into these boardrooms with people that you're quoting millions of dollars of contracts for, like, you have to say, “Well, here's what you spend on humans-”Swyx [00:56:15]: “. And here's what we save you, and it's 85% similar.”Joon [00:56:19]: And certainly, the value case, is something that we care deeply about. Like, what is the value that we provide to the users and the decision-makers? But this is also where, like, as a founder, I think valuation only tells one very superficial aspect of the story, and I try not to think too much about valuation, in general, because that's not what also motivates a team or certainly doesn't. I'm, I-- Again, the interesting thing about researchers is we are happy living in academia, getting paid next to. we get paid okay. we don't get paid that much, as a researcher here in academia, but it's the impact and it's the, it's the value that we can provide to the individuals and the society that really drives us. And in that way, ultimately what drives us is the impact. Does the simulation we provide have a real impact in people's decision-making in ways that progresses our society forward? If the answer is yes, then yes. that has to be great business, and we see that in numbers, and we do care deeply about that upside story, but that's the heart of it.Where Simulation Goes NextVibhu [00:57:27]: Do you have any timeline predictions? So we talked about scaling laws of simulations.Vibhu [00:57:33]: You brought up, okay, maybe one day we can simulate how to solve climate change.Vibhu [00:57:38]: Where are we now?Vibhu [00:57:40]: If that's not the end state, what is an end state, and what does progress look like?Joon [00:57:45]: So what I sometimes tell people is simulation as industry, it feels a lot like where GPT-3.5, GPT-4 was, for the AGI saga, which is we have now technology that is powerful enough to do real damage on the verticals that we are tackling. At the same time, there's a lot of progress that is yet to come. And that's, I think, where this is. So the way I see it, I do think there will continue to be breakthroughs both in data, in algorithms, and there will be much more aggressive scaling that will also happen over the next few years. But I think that's roughly where we are.Swyx [00:58:27]: I think that was about the ro

Percy, Daisy, and Aris are over the moon about this series.  Find out why.Titles: The Wolf King and The Night PrinceAuthor: Lauren PalphreymanReviewed by: Percy, Daisy, Aris Created by the Podcast Team at the Harris County Public Library.www.hcpl.netPodcast Team Members include: Beth Krippel, John Harbaugh, Mary Mink, Dylan Smith, Sadina Shawver, Alinda Mac, John Schaffer, Jennifer Finch, Katelyn Helberg, Darcy Casavant, Darla Pruitt and Nancy Hu 

Jack Graham and John Pedersen interview the talented photographer Bruce Percy and talk about his work, his style and share viewpoints on elevating your creative game.

Bishop Tony Percy reflects on Jesus saying he will build his Church on a rock: You are Peter and on this rock I will build my Church. The Church survived and thrived for so long because of fidelity to the truth and adaptability to change

"89 is such a hoax, dude." Chris Cote is mad at gas stations, and it's not for the reason you think. He also once put green gas in his car because he was distracted. Amin is mad at dogs again and especially mad at Ethan's dog, who is named Percy, NOT Malachi. Plus, Hall of Fame quarterback Drew Brees joins the show to discuss the emotions of his enshrinement, how close he came to signing with the Miami Dolphins, and when the last time he went to the movies was. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Bishop Tony Percy says that we're passing through a time of intense spiritual crisis, i.e., a crisis of truth and a crisis of love, and we might also add, a crisis of hope. Mercy and forgiveness are in short supply, yet forgiveness is at the heart of our relationships because we are weak, and we are sinful.

This week we return from our summer holidays (having avoided the wildfires in France) with Pam narrating the life of Captain John Smith. A man from Lancashire who became both a key part of the British settling of the East Coast of America, and a Disney Character.From humble orphan origins, John embarked on the life of an adventurer which encompassed pretty much everything you could imagine. So strap in for a tale of Crusades, duels, slavery, disasters, double-dealing, slanders, pirates, exploration, life or death struggles and cartography!With special guest appearances from Pocahontas and (potentially) a pug called Percy.Guest Host: Pamela Loetterle Hosted on Acast. See acast.com/privacy for more information.

This episode is a recording of our book club. The book we discuss is Why Die? The Extraordinary Percy Cerutty, 'Maker of Champions' by Graem Sims (Author).Percy Cerutty was an Australian athletics coach who transformed distance running in the 1950s and 1960s. Based at his rugged Portsea training camp, he developed the Stotan philosophy, blending Stoic discipline, Spartan toughness, natural diets, sand-hill running, weight training and intellectual growth. Best known for coaching Herb Elliott to world records and Olympic gold, Cerutty inspired athletes to pursue physical excellence and personal mastery. Our discussion is led by Dr David Turner, a Senior Lecturer in Sports Coaching at Anglia Ruskin University in the United Kingdom, and we are also joined by Andrew Gunn the author of Percy Cerutty: Life Lessons From A Remarkable Coach by Andrew Gunn.I scribbled down these 3 self-reflective questions:· Where in my life could I benefit from choosing growth over comfort?· What is one challenge I have already overcome that shows I am capable of reinvention?· How do I personally measure success: by outward achievement, or by how far I have come from where I started? If you would like to send us any feedback or if you know a great coach, who has a unique story to share, then we would love to hear from you, please contact us at paul@thegreatcoachespodcast.com and if you would like to receive our newsletter with 5 ideas to help you improve your leadership, then sign up at: https://thegreatcoaches.beehiiv.com/subscribe Hosted on Acast. See acast.com/privacy for more information.

Episode 156 - Every Tool's A Hammer (Fallout RPG)    After returning home to Vault Theta, our explorers take the opportunity to rest and consider what they've just been through. The Overseer is deep in discussion with the Ghoul family that the explorers found along the coast, attended by Shuttlecock; Victor looks to personalise the Laser weapon he "borrowed" from Harry, and Percy & Sally set to building a set of armour, to protect from future dangers...Dangers which may be closer than they think!   Find Us on Bluesky @PretendWithDice, @MonkeyMagicEden, @Ajheretic666, @MarkusMalice87 & @unklchop You can also find us on Facebook, Instagram & Twitter/X @PretendWithDice Links to all of our online presences can be found at www.pretendingwithdice.com, including our Ko-fi page, Merch Store, Discord server and much much more!

Existe um caminho certo para chegar à liderança? E como uma instituição financeira se prepara para atender clientes com uma visão cada vez mais global?No novo episódio do Mind Asset, recebemos Percy Moreira, CEO do Itaú USA e Head do Itaú Private Bank Internacional, para uma conversa sobre carreira, liderança, gestão de equipes globais e expansão internacional do Itaú.Ao longo da conversa, Percy compartilha aprendizados da sua trajetória, apresenta sua visão sobre a expansão das operações do Itaú nos Estados Unidos e mostra por que investir internacionalmente pode contribuir para a diversificação do patrimônio e para a construção de portfólios mais resilientes.

TODAY ON THE ROBERT SCOTT BELL SHOW: Polypharmacy Death Risk, Dr. Shonna Calica, Annalisa Percy RN, Global Natural Health Solutions, Hormonal Homeopathic Care, Cyclospora Skinny Trend, Medical Reform Failure, Jennifer Margulis, Anna Bazarnaya, Writing Under The Tuscan Sun, Lepidium Bonariense, and MORE! https://robertscottbell.com/polypharmacy-death-risk-dr-shonna-calica-annalisa-percy-rn-hormonal-homeopathic-care-cyclospora-skinny-trend-medical-reform-failure-jennifer-margulis-anna-bazarnaya-lepidium-bonariense-and-m/ Purpose and Character The use of copyrighted material on the website is for non-commercial, educational purposes, and is intended to provide benefit to the public through information, critique, teaching, scholarship, or research. Nature of Copyrighted Material Weensure that the copyrighted material used is for supplementary and illustrative purposes and that it contributes significantly to the user's understanding of the content in a non-detrimental way to the commercial value of the original content. Amount and Substantiality Our website uses only the necessary amount of copyrighted material to achieve the intended purpose and does not substitute for the original market of the copyrighted works. Effect on Market Value The use of copyrighted material on our website does not in any way diminish or affect the market value of the original work. We believe that our use constitutes a 'fair use' of any such copyrighted material as provided for in section 107 of the U.S. Copyright Law. If you believe that any content on the website violates your copyright, please contact us providing the necessary information, and we will take appropriate action to address your concern.

Mary and Doug blether about Dr Percy Calder and his work on Tuberculin milk. Learn more about your ad choices. Visit megaphone.fm/adchoices

Wrath of the Triple Goddess, ch. 26 to 30 This week on Unwise Girls, we discuss Deltarune, the tragedy of our GOAT, a fix to some of our previous problems, Percy's journey to learn that women are people, more overt magical school allusions, the sad state of being a woman who is a mother, and the superpower of neurodivergence. Come back next week for Wrath of the Triple Goddess, ch. 31 to 35! Check out our Patreon! (https://www.patreon.com/unwisegirls) Follow the show (bsky.app/profile/unwisegirls.bsky.social) Join our Discord! (https://discord.gg/XnhhwzKQ8d) Hosted by Jacqueline (https://twitter.com/swampduchess) and Jane (https://twitter.com/janeyshivers). Edited by Jacqueline. Cover art by Vera (https://twitter.com/Innsmouth_Inn). Intro/outro: "Super Mariocean" by spacepony (https://ocremix.org/remix/OCR01147) This podcast is powered by Pinecast.

Episode 149. The boys are back! In this episode Corwin waits for Supergirl to come straight to demand, then becomes astonished at No Way Home's box office numbers. Meanwhile, Scott talks about his trip to Alaska, then admits after 149 episodes he still does not know who Slayback is. They then play catch up and are up to date on Percy's run of Deadpool. In Past-O-Vision they continue reading The Last Ronin. For Merc File, Corwin takes the wheel for once and breaks down Guy Garner. And as always Robot Chicken Hulk wraps the show up with a PSA. Note: This episode was recorded before Brand New Day and the SDCC MUC Panel. Second note, episode 150 the boys will be covering the anime series Steins;gate and Steins;gate 0 and the movie.   0:22:56 Movie Talk 0:32:07 Anime Talk 0:34:29 Corwin's One Piece Progress 0:39:11 Jeff Meets Daredevil (2026) #1 0:44:10 Wade Wilson: Deadpool (2026) #3 0:47:34 Wade Wilson: Deadpool (2026) #4 0:55:20 Wade Wilson: Deadpool (2026) #5 1:01:17 Wade Wilson: Deadpool (2026) #6 Past-O-Vision 1:07:38 TMNT: The Last Ronin (2020) #2 1:17:57 Merc File: Guy Gardner   [MwaP RSS] Subscribe [RSS All] Subscribe [Google Podcasts] Subscribe [Apple Podcasts] Subscribe   Music by Jenki Girls of Los Angeles Email: HipsterDaken@gmail.com Website: http://www.EarthsMightiestPodcast.comFacebook Group: https://www.facebook.com/MercWithaPodcast/ Episodes #1-26 can be found @ Cultural Wormhole.com The Merc Report has now joined the EMP family of podcasts and has now become The Merc With a Podcast! -EXPLICIT CONTENT

With Sarah on foreign shores, Alex heads to the Old Vic rehearsal room to chat to stage and screen legend Roger Allam. Known for his TV and stage appearances in the likes of The Thick of It, Les Misérables and Frank and Percy, Allam is back on stage this summer in How The Other Half Loves at the Old Vic. And, apparently, he played a certain body part in an Ayckbourn radio play. Allam also touches on the topic of amplification and seeing his greats at the Old Vic when he was young. Hosted on Acast. See acast.com/privacy for more information.

Hello, this one goes out to Preston, Kaden, and all the farmers out there, but specifically those two, cause theyre the coolest farmers.   This week started where all weeks start, talking about porridge, and Percy, mainly Percy. We attempted to talk about The World Cup, which went terribly. Played Hypothetical Trivia(which, if you didn't know, was created by Carrington), and laughed way too hard about David murdering Goliath; it was for a good cause, right? RIGHT?!?!?! After that, we got a special guest, and you'll never guess who it was. That's right!! ANOTHER FRICKEN ASTRAL TRAVELER!! I swear the lore in this world is getting more convoluted than the MCU. Thank you all for listening; this thing does take a decent amount of energy(shocking, I know), so seeing everyone still listening is actually a huge deal for us, or at least for me; the boys don't love you as I do. Muah!!! See you next time!!   Email: hotcrossbunspod@gmail.com Instagram/TikTok: @hotcrossbunspod

Have you heard the story of Henry Hugh Manvers Percy? This 19th century member of the Percy family won a Victoria Cross for his actions in the Battle of Inkerman, one of the crucial fights during the Crimean War, and his story is told in the book 'A Bearskin's Crimea' by Algernon Percy, newly re-released in an expanded an illustrated edition.We are joined by the author on this episode of the Alnwick Castle Podcast, where he explains who Henry Percy was, some of his actions in the Crimea, and the origins of the Victoria Cross, among many other things. If you are interested in this period of history, this episode and the book are definitely for you; and if you have not heard anything about the Crimean War beyond names like Florence Nightingale, Mary Seacole or the Charge of the Light Bridge, well, we hope this episode and the book are for you too!You can get a copy of 'A Bearskin's Crimea' now. Buy directly from Alnwick Castle at alnwickcastle.com/shop , or you can also order it online through Waterstones.And don't forget to look out for Henry Percy's sword on display in the State Rooms next time you visit Alnwick Castle!

Everything has changed this summer and Every Year After is officially going for it. Jillian is joined by Claire to break down Episode 4, “Anatomy of a Romance,” as the series reaches one of the book's most anticipated scenes and takes the story into completely unexpected territory.They discuss Percy's mission to swim across the lake, the anatomy textbook moment that finally pushes Percy and Sam across the friendship line, and Sam immediately getting in his own way. Plus, Charlie reveals the heartbreaking truth about what happened after his father died, Percy confronts Sam about years of mixed signals, and Sue causes chaos from beyond the grave by leaving The Tavern to Percy.Jillian and Claire also rank their Top 5 “Everything Has Changed This Summer” moments, unpack Percy's struggle to reconnect with the fearless girl she used to be, and celebrate the wine-fueled Barry's Bay girls' night that ends with breaking and entering, shocking confessions, and a trip to jail. With kisses, breakups, family resentment, and one truly unhinged will reading, this episode brings the drama in every possible timeline.00:00 Intro to pod02:08 Ep 4 "Anatomy of a Romance"03:03 Recap of Ep 407:33 Top 5 Everything Has Changed Moments09:02 Percy swims lake16:40 Truth after dad's death21:56 Anatomy textbook scene26:05 Sam ends it34:37 Percy's Tavern41:36 McMansions43:16 ChantalThank you to Matt Buechele (@mattbooshell) for creating our new theme song. You can listen to "Sunscreen" on Spotify: https://open.spotify.com/artist/1gFHHF3QyQxjbbKXV3qLu9Buy our merch: ⁠https://www.etsy.com/shop/PreviouslyOnTeenTV⁠Follow Previously On Teen TV on Instagram: ⁠⁠https://www.instagram.com/previouslyon_teentv/Follow Previously On Teen TV on TikTok: ⁠⁠https://www.tiktok.com/@previouslyon_teentv⁠⁠Subscribe to our YouTube: ⁠⁠https://www.youtube.com/channel/UCe2lgvvZGKMrQ8v24FmDdWQ?sub_confirmation=1⁠

Send us Fan MailAnimated fantasy gets thrown into a lot of different categories, but The Legend of Vox Machina stands out from the crowd. We break down Season 1, talking about its over-the-top action, surprisingly brutal violence, crude humor, and the emotional moments that make it all work. We also discuss how well the series captures the feeling of a real D&D campaign, from the established party dynamic to the moments where you can almost see the dice rolls behind the action. And yes, Scanlan absolutely steals the show.We also dive into the Critical Role roots of the series, Percy's revenge story in Whitestone, the Briarwoods, cursed weapons, vampire lore, and big moments like Pike's return. Whether you're a longtime fan or watching for the first time, there's plenty here to enjoy if you love fantasy, tabletop games, or character-driven adventures.If you enjoyed the conversation, subscribe, share the episode with a fellow fantasy fan, and leave us a five star review to help more people discover the show.Twitter handles:Project Geekology: https://twitter.com/pgeekologyAnthony's Twitter: https://twitter.com/odysseyswowDakota's Twitter: https://twitter.com/geekritique_dakInstagram:https://instagram.com/projectgeekology?igshid=1v0sits7ipq9yYouTube:https://www.youtube.com/@projectgeekologyGeekritique (Dakota):https://www.youtube.com/channel/UCBwciIqOoHwIx_uXtYTSEbASupport the show

"Percy...all beans with a little frank but he gets the job done."Hey Little Paulsters! Your hosts, Jeff Macanovich and Jaime Cavazos, welcome Beast back to drink some beers and watch the first half of WWF Survivor Series 1997. Notwithstanding that, the old men kick off the show by (once again) yelling at the cloud that is modern professional wrestling, Beast airs some fantasy football grievances and the guys add a radio morning show to the canon.The guys enjoyed beers from Miller Brewing Company, Lagunitas Brewing Company, Grupo Modelo, Buffalo Creek Brewing, New Holland Brewing and Garage Beer.New episodes drop every other Tuesday morning and follow the show @WorkTheArmPod, on Twitter, Instagram, Blue Sky and (I guess) Threads.Check out our merch from the mind of Starman here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠T-Shirts by Starman's Podcasting Buddies | TeePublic⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Grab something with the Work The Arm logo here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠T-Shirts by WorkTheArm | TeePublic⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Wind and Water, Hearth and Home, All beneath the blue sky dome,When the crying gulls have flown, Wind and Water, bring me homeCW: ThalassophobiaDeath/dyingViolenceShipwreckFireThunder/lightningMentions/Discussions of: Harm to animals, Drowning, Poison, AlcoholSFX: Knives being sharpened, Cannon fire, Created by Lou Sutcliffe and Daisy McNamaraTranscript is available HERE: https://cytochromehear.wordpress.com/home/eelers-choice/eelers-choice-episode-12/Daisy's book: https://daisymcnamara.com#gospelofhavennovelWriter, composer and sound designer - Lou SutcliffeProducer and dialogue editor - Daisy McNamara.Directed by Lou Sutcliffe and Daisy McNamara.Script editing was by Ken Cumberlidge.Our executive producer was Pongo.Nama Fishercliff - Lindsey C. Prin Whitchanter - Caroline Orejuela. Merry Whitechanter - Tanja Milojevic. Blethin Stormsinger - David Ault. Pugill Flenserly - B. Narr. Aderyn Tanner - Leon Egan. Spartina Sawbones - Interiority. Acaster Selvage - Rhys Lawton. Moryana Whitechanter - Erika Sanderson. Beyin Ossificer - Kale Brown. Ned Sharktackle - Meg Molloy-Tuten.Opochtli Pulpodore - Diego HerreraMeredith Redeland - J.E. Haywood. Selachia - Hera Alexander Elasmo - Jamie Petronis.Lir Fishercliff - William WellmanSistra - Jessica Law. Bone Creature - Fay Roberts. Ran Stormsinger - Rae LundbergWith additional voices by Lauren Oakley and Jessica LawOur theme for this episode, “When I Am Gone” was written by Lou Sutcliffe and sung by Diego Herrera, Elijah Harper, Derrick Valen, Jessica Law and Lou Sutcliffe.We would like to thank the following crowdfund backers for their support: Sarah Vincent, Susan Hance, Aimleo17, MerelyMatt, Aarlone, Mike Fielding, Michael Hudson, KyokoNyan, Siobhan Thomas, Audrey Martin, Ella Watts, Robin Johnson, Nepenthe Wang, Francesca Mylod-Ford, Alexandra Pal, Pine Gonzalez, Rowan Ash, Rowan van Grinsven, Jon Ware, Kale Brown, Sue R, Reuben Eadon, Ruth Beebe, Percy, Kim Khavelund, Hannah Brown, Nicole Hislop, Jack McDonald, Josh Burgess, Rowan Blue, Felix Cosm, Just Jenah, Bee Allen, Naem D. Chouinard, Anja Myers, Niamh Lynn-Devere, Devin from the Dead West, Ben Hamlin, Mark Nixon, Leon Egan, Tom Borowski, Pen Toll, Liz Lynch, Helen Sears, Annette McArdle, Scott Paladin, Jack Fulmin, Elizabeth Bonnell, Candace Brednow, Sera Darland, Libby Thomas, Corrie P, Aliyah Ingman, Amy Crossway, Jem Hawes, Doodles v. de Castro, Katherine Nickerson, Nishka Corey and Reag Coster.A production of Cytochrome Hear and Eelsong StudiosOur Social Media: The Website Formerly Known As Twitter: https://twitter.com/eelerschoiceTumblr: https://www.tumblr.com/eelerschoice Bluesky: https://bsky.app/profile/eelerschoice.bsky.socialWebsite: https://cytochromehear.wordpress.com/home/eelers-choice/ Hosted on Acast. See acast.com/privacy for more information.

Things are heating up in Barry's Bay and someone's gonna get burned! In this episode of Previously On, Jillian and Claire break down Every Year After Episode 3, “Playing With Fire,” as the past and present begin mirroring each other in increasingly complicated ways.In honor of the episode title, we're counting down the Top 5 “We're Playing With Fire” moments including Percy and Sam sharing a bed, the jealousy-fueled bonfire kiss, and Percy getting dressed up for a totally casual 6 p.m. pierogi-making date.We also discuss Charlie and Chantal's roadside detour where we discover these two have more in common than they think. And we break down the surprise ending where Percy learns she's been named in Sue's will, and she'll have to stick around for the reading...THE DRAMA!00:00 Reenactment "Sam got hot"00:53 Ice cream lick03:41 Intro to pod04:59 Ep 3 Recap06:15 Top 5 Playing with Fire Moments06:33 Sam and Percy09:32 Sharing bed18:38 Charlie and Delilah23:07 Percy bonfire kiss31:33 Almost kiss39:14 Will reading42:01 Passport probsThank you to Matt Buechele (@mattbooshell) for creating our new theme song. You can listen to "Sunscreen" on Spotify: https://open.spotify.com/artist/1gFHHF3QyQxjbbKXV3qLu9Buy our merch: ⁠https://www.etsy.com/shop/PreviouslyOnTeenTV⁠Follow Previously On Teen TV on Instagram: ⁠⁠https://www.instagram.com/previouslyon_teentv/Follow Previously On Teen TV on TikTok: ⁠⁠https://www.tiktok.com/@previouslyon_teentv⁠⁠Subscribe to our YouTube: ⁠⁠https://www.youtube.com/channel/UCe2lgvvZGKMrQ8v24FmDdWQ?sub_confirmation=1⁠

Percy es un pingüino alegre, divertido y lleno de ocurrencias. Pero mientras él disfruta haciendo reír a todos. Sus compañeros lo consideran demasiado inquieto y deciden dejarlo de lado. Un hermoso cuento que nos recuerda que cada persona tiene cualidades únicas y que nuestras diferencias también enriquecen a quienes nos rodean.

Dan Bardell is live to react to Jacob Tanswell's reports on "The Athletic" that Chelsea's Alejandro Garnacho and Nicolas Jackson are of interest to Aston Villa.Dan also reacts to John Percy's report in "The Telegraph" that there may be further sales. Sponsored by Luke 1977.com. Use code 'TVV20' at checkout for 20% off.

Tasting Notes Include: Forcing Tiny Tony to Grow Up Fast, Percival being Immortal, but not Invulnerable, Archie being a General in the War for Good and Evil, Percival can teleport, but his clothes can't, Powers get turned on their users, Percy gets got by the Devil, A Comet is coming to crash into Riverdale and also the World.   So Sorry about how long it took to get these episodes out. Life is dark and full of terrors. Say hi on Social Media because we love to hear from you!   Our Socials: @Riverdale Runs on Bluesky and riverdale_runs on Insta Our Email: arrtipod@gmail.com

The verdict is in!  Check out if this was good spice or bad writing.  Both?  Neither? Title: For Whom the Belle TollsAuthor: Jaysea LynnReviewed by: Percy, Daisy, Aris Created by the Podcast Team at the Harris County Public Library.www.hcpl.netPodcast Team Members include: Beth Krippel, John Harbaugh, Mary Mink, Dylan Smith, Sadina Shawver, Alinda Mac, John Schaffer, Jennifer Finch, Katelyn Helberg, Darcy Casavant, Darla Pruitt and Nancy Hu 

Guess who's baaaaack??? It's us (hiiiii). We've returned from our hiatus and what better way to celebrate than to turn our focus to that ol' party animal Percival (middle name redacted) Weasley? Did that textbook middle child really get a fair representation in the series? What is the narrative purpose of the series of events surrounding Percy's return in Book 7? And which Wilson is headed to an ashram? Support the showSupport FFH on Patreon: patreon.com/thefoxandthefoxhoundFollow us!IG: @thefoxandthefoxhoundTikTok: @thefoxandthefoxhound

Presented by Everett 3 on 3 Seattle basketball reporter Percy Allen joins the Iconic Sonics Podcast for a conversation that spans the past, present and future of hoops in the Pacific Northwest. We look back at the 2008 NBA Draft, the final draft in SuperSonics history, and revisit the selection of Russell Westbrook with the fourth overall pick. Percy also shares his perspective on the Sonics leaving Seattle 18 years ago, what that moment was like to cover and how the city has continued to rally around basketball ever since. We also dive into the latest around the Seattle Storm, the local basketball scene and where Seattle hoops stands today. This episode is presented by Everett 3 on 3, one of the Northwest's premier basketball tournaments. Grab your friends, build your squad and sign up to compete! Follow us on social: Instagram: @iconic_sonics X: @iconic_sonics TikTok: @iconic_sonics  

TODAY ON THE ROBERT SCOTT BELL SHOW: The Case Against Scientific Retraction, Annalisa Percy, Global Natural Health Solutions, Eating disorders, Natural Medicine is Powerful, From Healing to Harm, Morley Robbins, Cu-re, Root Cause Protocol, Guarea Trichiloides, and MORE! https://robertscottbell.com/the-case-against-scientific-retraction-annalisa-percy-jama-natural-medicine-is-powerful-from-healing-to-harm-morley-robbins-cu-re-root-cause-protocol-guarea-trichiloides-and-more/ Purpose and Character The use of copyrighted material on the website is for non-commercial, educational purposes, and is intended to provide benefit to the public through information, critique, teaching, scholarship, or research. Nature of Copyrighted Material Weensure that the copyrighted material used is for supplementary and illustrative purposes and that it contributes significantly to the user's understanding of the content in a non-detrimental way to the commercial value of the original content. Amount and Substantiality Our website uses only the necessary amount of copyrighted material to achieve the intended purpose and does not substitute for the original market of the copyrighted works. Effect on Market Value The use of copyrighted material on our website does not in any way diminish or affect the market value of the original work. We believe that our use constitutes a 'fair use' of any such copyrighted material as provided for in section 107 of the U.S. Copyright Law. If you believe that any content on the website violates your copyright, please contact us providing the necessary information, and we will take appropriate action to address your concern.

Mary & Blake recap and give reaction to Outlander Season 8 Episode 9, "Pharos." In this episode, we discuss why Lord John Grey finally gets the emotional spotlight, why the Jamie and Lord John chess scene may be the best payoff of Season 8, and why "Pharos" works as both a literal lighthouse clue and a symbolic title for the episode. We also get into Richardson's reveal as a time traveler, Claire letting him go, Lord John shooting him anyway, Percy's betrayal, William's two-fathers reckoning, Bree giving birth, Claire writing "our story," and whether this episode actually works as the penultimate chapter of the entire series. Plus, Mary brings the heat on Under The Tuscan Sun, cannoli, cribbage, Kelly Clarkson, mouth farts, and why Lord John walking away from Percy may be his Miss Independent moment. In this episode, you'll hear: Why "Pharos" is a strong episode title How Diana Gabaldon's writing shapes the Lord John material Why the chess scene between Jamie and Lord John works so well Whether Percy's betrayal and death hit hard enough Why Richardson's plan feels underbuilt Claire's hope that history can still change Lord John as the emotional engine of the episode William's complicated love for both Jamie and Lord John Whether "Pharos" gives enough momentum going into the finale Support the show and get bonus content at JoinTheNerdClan.com. Follow Mary & Blake at MaryandBlake.com, YouTube, Facebook, and Instagram. Slàinte Mhath.