Podcasts about Memory

True crime has always been entertainment, but social media has turned tragedies like the Lindsay Clancy trial into monocultural moments. It's not enough to read the news, many people who are especially tuned-in are also spreading misinformation and conspiracy theories as part of participating in the larger fandom. On today's episode, host Kate Lindsay is joined by Leah Carroll, a true crime writer and author of the book Down City: A Daughter's Story of Love, Memory, and Murder, to discuss the impact of social media's obsession, and how Leah's own experience with family tragedy informs her perspective on true crime. This podcast is produced by Vic Whitley-Berry, Daisy Rosario, and Kate Lindsay. Hosted on Acast. See acast.com/privacy for more information.

True crime has always been entertainment, but social media has turned tragedies like the Lindsay Clancy trial into monocultural moments. It's not enough to read the news, many people who are especially tuned-in are also spreading misinformation and conspiracy theories as part of participating in the larger fandom. On today's episode, host Kate Lindsay is joined by Leah Carroll, a true crime writer and author of the book Down City: A Daughter's Story of Love, Memory, and Murder, to discuss the impact of social media's obsession, and how Leah's own experience with family tragedy informs her perspective on true crime. This podcast is produced by Vic Whitley-Berry, Daisy Rosario, and Kate Lindsay. Hosted on Acast. See acast.com/privacy for more information.

True crime has always been entertainment, but social media has turned tragedies like the Lindsay Clancy trial into monocultural moments. It's not enough to read the news, many people who are especially tuned-in are also spreading misinformation and conspiracy theories as part of participating in the larger fandom. On today's episode, host Kate Lindsay is joined by Leah Carroll, a true crime writer and author of the book Down City: A Daughter's Story of Love, Memory, and Murder, to discuss the impact of social media's obsession, and how Leah's own experience with family tragedy informs her perspective on true crime. This podcast is produced by Vic Whitley-Berry, Daisy Rosario, and Kate Lindsay.Need to set up your Slate Plus feed? If you subscribed through Slate.com, check out our FAQ at slate.com/podcastfaqs for easy instructions. Members subscribed via Apple Podcasts get automatic access—no setup required. Hosted on Acast. See acast.com/privacy for more information.

On this episode of Vitality Radio, Jared takes a deep dive into Lion's Mane, one of the most talked-about medicinal mushrooms for cognitive health, focus, memory, mood, and nervous system support. Jared explores the fascinating history of this unique mushroom, the science behind compounds like hericenones and erinacines, and how they may support nerve growth factor (NGF) and neuroplasticity. He reviews human clinical research on cognitive performance, mood, stress, and long-term brain health while helping listeners understand the differences between powders, extracts, capsules, gummies, fruiting body products, and mycelium-based supplements. Jared also shares his personal experience using Lion's Mane, discusses practical dosing strategies, and explains how to combine it with other supplements and lifestyle habits to support healthy brain function and overall vitality.Products:Lion's Mane: https://vitalitynutrition.com/collections/lions-mane Visit the podcast website here: VitalityRadio.comYou can follow @vitalitynutritionbountiful and @vitalityradio on Instagram, or Vitality Radio and Vitality Nutrition on Facebook. Join us also in the Vitality Radio Podcast Listener Community on Facebook. Shop the products that Jared mentions at vitalitynutrition.com. Let us know your thoughts about this episode using the hashtag #vitalityradio and please rate and review us on Apple Podcasts. Thank you!Just a reminder that this podcast is for educational purposes only. The FDA has not evaluated the podcast. The information is not intended to diagnose, treat, cure, or prevent any disease. The advice given is not intended to replace the advice of your medical professional.This podcast is produced by DrTalks.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://drtalks.com/podcast-service/

“We are in the middle of a labyrinth which suggests to us many fake corridors. What's the superpower of literature? Literature is like an antidote against propaganda. Propaganda explains the world easily in a two-dimensional way.  Literature gives you a more complex explanation. Literature tells personal stories.”Today, we have a conversation about time, memory, and the bittersweet geography of human sorrow. Georgi Gospodinovis widely considered one of the most daring voices in contemporary European literature. His acclaimed novel, The Physics of Sorrow, won the prestigious Jan Michalski Prize in 2016, blending ancient myth and quantum physics to chronicle the delicate realities of post-socialist Eastern Europe. Joining him is Angela Rodel, a brilliant linguist, musician, and translator whose profound artistic empathy carries the flowing cadences of the Bulgarian language into vivid English. Together, this extraordinary creative duo made history by winning the 2023 International Booker Prizefor Time Shelter—the first book written in Bulgarian to ever receive the honor.Time Shelter is a masterfully dark, funny, and prescient novel. It begins with an enigmatic psychiatrist opening a clinic that treats Alzheimer's patients by meticulously recreating past decades to match their internal clocks. But the experiment quickly escapes the clinic walls, triggering a pan-European crisis where entire nations hold democratic referendums to choose which era of the past they will retreat into. It is a book that holds up a mirror to our own world, exploring what happens when a civilization faces a deficit of meaning and tries to weaponize nostalgia.(0:00) The Trap of Nostalgia(2:13) The Art of Translation(5:44) The Pandemic of the Past(11:30) Reading from ‘Time Shelter'(14:28) Death and the Gardener(19:34) The Translator's Calling(26:05) Cultural Rhythms of the Bulgarian Language(30:00) The Nonlinear Approach to Storytelling(34:30) Separating Personal and Historical Pasts(42:55) Storytelling vs Propaganda(47:19) Bodies, Animals and the Loneliness of the Minotaur(56:00) Reading ' Eight Minutes and 19 Seconds'(1:00:28) What makes a good life? What has given your life meaning?(1:04:18)   Childhood, Memory and Imagination(1:10:38) Reflections on God and the Stories His Grandmother Told Him(1:17:20) Education and the Empathic Imagination(1:23:25) The Museum of Memory(1:26:15) The Importance of Hugging and Empathy(1:28:02) AI and the Future of HumanityEpisode Websitewww.creativeprocess.info/podInstagram:@creativeprocesspodcast

This is your daily horoscope for Thursday, August 27, and the most important aspects of the day:Mercury in Virgo conjunct Sun in Virgo (10am PT)Moon enters Pisces (12pm PT)Full Moon Lunar Eclipse in Pisces (9:18pm PT)Moon in Pisces opposite Mercury in Virgo (10:30pm PT)Moon in Pisces square Uranus in Gemini (10:30pm PT)Unlock More MagicGrimoire: Become a Better Witch in 12 WeeksBook a Reading with StephanieAccess Personalized Horoscopes + Join Stephanie's PatreonMake a DifferenceRevoke Stacy Turner's Medical License (Corrupt Coroner in Mississippi)Donate in Memory of Juliana NzitaHelp Honor Tasia FortuneSign the Petition + Demand Clemency for Jeffery Lee I Call Gov. Ivey + Demand Clemency 334-242-7100

Welcome back to Late Boomers! We're your hosts, Cathy Worthington and Merry Elkins . In this episode, we dive deep into the world of historical fiction with educator, novelist, and storyteller Dorothy Ward, whose acclaimed novel, Light Which Impresses, beautifully explores themes of identity, resilience, and the enduring strength of women through the lens of history.If you're fascinated by stories that connect the past to our present, or if you're finally ready to write your own narrative, this conversation will both inspire and motivate you.We're thrilled to welcome Dorothy Ward to discuss her journey from lifelong educator to published novelist at the age of 71! We explore why historical fiction is more relevant than ever, what inspired the unique structure of Light Which Impresses, and the meticulous research that brings her story to life. Dorothy Ward shares candid insights about recreating early 20th-century El Paso and the Mexican Revolution, crafting powerful women who defy expectations, and how her own background influenced the narrative.Whether you're a writer, a lover of history, or someone seeking encouragement to start something new in your own life, you'll find wisdom and practical advice throughout this episode.Key TakeawaysWhy Historical Fiction Matters: Dorothy Ward explains how stepping into the past through fiction helps us build empathy and understand today's challenges, especially around topics like migration and resilience (01:28).Inspirations Behind the Novel: The title of Light Which Impresses comes from a 100-year-old Kodak camera manual, a metaphor for memory and the double-edged power of truth (02:54).Unique Narrative Structure: The story weaves together interviews with the protagonist as an older woman and her youthful experiences against a backdrop of revolution, making history come alive and personal (05:47).Strong, Unconventional Female Characters: Inspired by real women of the Mexican Revolution, Dorothy Ward's protagonists break the mold and show the unheralded strength of women throughout history (09:08).The Research Process: Dorothy Ward reveals how she balanced exhaustive research walking tours, period photography, and vintage vehicles with compelling storytelling (17:30).Advice for Aspiring Writers: It's never too late to start! The most important step? Sitting down and writing, planning and talking about writing won't get your story on the page (29:02).Practical Writing Tips: Embrace rewriting, cut down the excess, and always read your work out loud to catch what doesn't sound right (30:50).If today's conversation sparked your curiosity or your creativity, we encourage you to pick up a copy of Light Which Impresses available at Amazon, Bookshop.org, or wherever you buy books. Connect with Dorothy Ward and learn more about her work at dorothypward.com.Don't forget to subscribe to Late Boomers wherever you get your podcasts and on our YouTube channel. Leave us a review and share this episode with friends who love history, literature, and inspiring new beginnings.Remember, it's never too late to rethink what's possible.Mentioned in this episode:Late Boomers is part of the eWomenPodcastNetwork. eWomenPodcastNetwork

Jim Kwik on Memory, AI, and Why Natural Intelligence Beats Artificial Intelligence Your brain is quietly outsourcing itself to AI, and you won't notice until it's gone. This episode gives you the exact framework to use artificial intelligence as a tool for brain optimization instead of a crutch that erodes your memory, focus, and critical thinking. Watch this episode on YouTube for the full video experience: https://www.youtube.com/@DaveAspreyBPR Host Dave Asprey sits down with Jim Kwik, one of the world's leading experts in memory improvement, brain optimization, and accelerated learning. For more than 30 years, Jim has served as the brain coach to professional athletes, political leaders, business magnates, and Hollywood icons, with corporate clients including Google, Nike, SpaceX, and Harvard. He hosts the Kwik Brain podcast with over 100 million downloads, reaches 200,000 people annually through live keynotes, and just wrapped his 14th annual Beyond Biohacking Conference with 5,000 attendees in Austin. Jim overcame a childhood brain injury that left him labeled "learning disabled," and turned that struggle into a mission he calls "no brain left behind." They break down the MIT study showing that people who use AI to write and think score worse on memory and comprehension than those who rely on their own brains, and why that matters for anyone serious about longevity, human performance, and anti-aging. Jim introduces the concept of digital dementia and cognitive sovereignty, explaining how nootropics, neuroplasticity, and functional medicine can support your biology while AI still requires you to keep your own hardware sharp. They cover the MEDS Rx framework for brain optimization: meditation, exercise, diet, sleep optimization, and relationships, plus why mitochondria, metabolism, and inflammation from processed food directly impact your cognitive output. Jim also shares how his own kids use AI as a tutor rather than a replacement for thinking, and why sleep inertia and the first few minutes after waking set the tone for your entire day. This is essential listening for anyone serious about biohacking, hacking their own brain, longevity, neuroplasticity, brain optimization, supplements, and building a Smarter Not Harder approach to human performance in the age of AI. You'll Learn: Why the MIT study found AI users had weaker memory and comprehension than people who did the work themselves What digital dementia and digital deduction are, and how they quietly erode your cognitive muscles How to use AI as an augmented intelligence partner instead of a replacement for critical thinking The MEDS Rx framework for brain optimization: meditation, exercise, diet, sleep, and relationships Why the first few minutes after waking determine your focus and mood for the entire day How spaced repetition and AI-assisted learning can lock in new skills and behavior change faster The HUMAN framework for staying irreplaceable in a world run by algorithms Thank you to our sponsors! - KILLSwitch | If you're ready for the best sleep of your life, order now at https://www.switchsupplements.com/and use code DAVE for 20% off - Neuronic | Go to www.neuronic.online Code DAVE for $100 off - Our Place | Upgrade your kitchen with Our Place today. Visit fromourplace.com/DAVE and use code DAVE for 10% off sitewide. - LMNT | Check it out at drinklmnt.com/DAVE. You'll get a free 8 count sample pack with any purchase. Dave Asprey is a four-time New York Times bestselling author, founder of Bulletproof Coffee, and the father of biohacking. With over 1,000 interviews and 1 million monthly listeners, The Human Upgrade brings you the knowledge to take control of your biology, extend your longevity, and optimize every system in your body and mind. Each episode delivers cutting-edge insights inhealth, performance, neuroscience, supplements, nutrition, biohacking, emotional intelligence, and conscious living. New episodes are released every Tuesday, Thursday, Friday, and Sunday (BONUS). Dave asks the questions no one else will and gives you real tools to become stronger, smarter, and more resilient. Keywords: Jim Kwik, Limitless, Kwik Brain, digital dementia, cognitive sovereignty, human intelligence, artificial intelligence, MIT AI study, brain injury recovery, accelerated learning, memory improvement, speed reading, neuroplasticity, spaced repetition, memory palace, MEDS Rx framework, sleep inertia, attentional priming, metacognition, digital deduction, brain optimization, cognitive flexibility, cognitive anti-fragility, 40 Years of Zen, biohacking, Beyond Biohacking Conference, HUMAN framework, learning how to learn, GPS dependency, mental fatigue, burnout recovery, Limitless Daily Resources: • Learn More About Jim At: https://limitlessdaily.com/ • Follow Jim On Instagram At: https://www.instagram.com/jimkwik/ • Watch Jim On YouTube At: https://www.youtube.com/jimkwik • Get My 2026 Clean Nicotine Roadmap | Enroll for free at https://daveasprey.com/2026-clean-nicotine-roadmap/ • Dave Asprey's Latest News | Go to https://daveasprey.com/ to join Inside Track today. • Danger Coffee: https://dangercoffee.com/discount/dave15? • My Daily Supplements: SuppGrade Labs (15% Off) • Favorite Blue Light Blocking Glasses: TrueDark (15% Off) • Dave Asprey's BEYOND Conference: https://beyondconference.com • Dave Asprey's New Book – Heavily Meditated: https://daveasprey.com/heavily-meditated • Join My Substack (Live Access To Podcast Recordings): https://substack.daveasprey.com/ • Upgrade Labs: https://upgradelabs.com Timestamps: 00:00 – Trailer 00:55 – Intro 06:54 – AI as Tool, Not Crutch 13:00 – Protecting Cognitive Sovereignty 21:28 – Digital Dementia Explained 27:13 – AI-Enhanced Learning Techniques 32:18 – Speed Listening and Reading 40:38 – Rapid Tips by Age 46:59 – Building an AI Second Brain 53:04 – Burnout and Brain Optimization See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Detectives are baffled when two young girls are raped, murdered, and dumped in an abandoned house in Akron, Ohio. And a 26-year-old mother of three disappears on Christmas Eve in 1995, but the missing persons case goes cold when police can find few clues to her whereabouts.Hers: Start your free online visit at forhers.com/CCF for your personalized weight loss treatment options.Progressive: Multitask right now. Quote your car insurance at Progressive.com to join the over 28 million drivers who trust Progressive.Rosetta Stone - Cold Case Files listeners can get for 20% off their Rosetta Stone Sapphire subscription when you go to RosettaStone.com/coldcaseThrive Market: Go to ThriveMarket.com/coldcase for $30 off your first two orders!Vinted - See what's hiding in your closet. Download the Vinted app for free to start listing with no seller fees!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Hey Heal Squad! What better way to celebrate the back-to-school season than with one of TV's most iconic high schoolers: the one and only Jennie Garth, aka Kelly Taylor from Beverly Hills, 90210. Since leaving West Beverly, Jennie has built an incredible life and career…. starring in What I Like About You, competing on Dancing with the Stars, raising three daughters, writing her memoir I Choose Me, and creating a whole new chapter around what it really means to choose yourself. Today, Jennie opens up to Maria about the rock-bottom period after her divorce and the biggest mistake she says she made: isolating herself instead of letting people support her. She shares what actually helped her climb out, like  friendship, nature, therapy, creativity, and becoming determined to feel joy again. They also look back at the 90210 years, what it was like to spend her entire young adulthood on set, why leaving the show felt like a grief process, and how the cast eventually found their way back to one another later in life. Plus, Jennie gets candid about her health journey… from a shocking jet ski accident with Luke Perry to severe memory issues that led her to Dr. Amen and a brain scan. This one is part nostalgia, part healing, and a powerful reminder that sometimes choosing yourself starts with simply deciding you want to feel better, and staying persistent until you do. Enjoy! HEALERS & HEAL LINERS Isolation Makes Hard Times Harder: After her divorce, Jennie admits she isolated herself out of shame and now wishes she had let her friends support her sooner. Getting outside, hiking with friends, meeting new people and allowing laughter back into her life helped her begin climbing out of that period. Pay Attention to What Your Brain + Body Are Telling You: Jennie's severe memory issues became so concerning that she feared early-onset Alzheimer's or dementia. A brain scan revealed irregularities that Dr. Amen could be connected to a past head injury, while Jennie also believes then-unrecognized perimenopause was contributing. You Have to Be Persistent in Your Quest to Feel Better: Jennie says she became determined to feel joy again, trying different therapies, workshops, spending time in nature and eventually rediscovering creativity through designing a home. Her takeaway: change required consistency, figuring out what kind of life she actually wanted, and doing more of what made her feel alive. Join us at our Canyon Ranch 2026 Retreat: https://www.canyonranch.com/lenox/retreats/heal-retreat-maria-menounos HEAL SQUAD SOCIALS IG: https://www.instagram.com/healsquad/ TikTok: https://www.tiktok.com/@healsquadxmaria HEAL SQUAD RESOURCES: Heal Squad Website:https://www.healsquad.com/ Heal Squad x Patreon: https://www.patreon.com/HealSquad/membership Maria Menounos Website: https://www.mariamenounos.com My Curated Macy's Page: https://stylecrew.macys.com/@mariamenounos EMR-Tek Red Light: https://emr-tek.com/discount/Maria30 for 30% off Airbnb: https://www.airbnb.com/host GUEST RESOURCES: Follow Jennie on Instagram: https://www.instagram.com/jenniegarth/?hl=en More Info on I Choose Me Memoir, Podcast & More: https://jenniegarth.com/ Read Jennie's SubStack: https://substack.com/@itsjenniegarth Shop Me By Jennie Garth: https://jenniegarth.com/pages/me-by-jennie-garth ABOUT MARIA MENOUNOS: Emmy Award-winning journalist, TV personality, actress, 2x NYT best-selling author, former pro-wrestler and brain tumor survivor, Maria Menounos' passion is to see others heal and to get better in all areas of life. ABOUT HEAL SQUAD x MARIA MENOUNOS: A daily digital talk-show that brings you the world's leading healers, experts, and celebrities to share groundbreaking secrets and tips to getting better in all areas of life. DISCLAIMER: This Podcast and all related content (published or distributed by or on behalf of Maria Menounos or http://Mariamenounos.com and http://healsquad.com) is for informational purposes only and may include information that is general in nature and that is not specific to you. Any information or opinions provided by guest experts or hosts featured within website or on Company's Podcast are their own; not those of Maria Menounos or the Company. Accordingly, Maria Menounos and the Company cannot be responsible for any results or consequences or actions you may take based on such information or opinions. This podcast is presented for exploratory purposes only. Published content is not intended to be used for preventing, diagnosing, or treating a specific illness. If you have, or suspect you may have, a health-care emergency, please contact a qualified health care professional for treatment.

Dèy by acclaimed writer Edwidge Danticat is multigenerational story of family, resilience, and hope in the wake of an unexpected tragedy. Edwidge joins us to talk about evolving ideas of the American Dream, the Haitian diaspora, ghost stories and expanding canon with host Miwa Messer. This episode of Poured Over was hosted by Miwa Messer and mixed by Harry Liang. New episodes land Tuesdays and Thursdays (with occasional Saturdays) here and on your favorite podcast app.   Featured Books: Dèy by Edwidge Danticat Breath, Eyes, Memory by Edwidge Danticat Brother, I'm Dying by Edwidge Danticat Claire of the Sea Light by Edwidge Danticat Everything Inside by Edwidge Danticat Wave by Sonali Deraniyagala The Art of Death by Edwidge Danticat The Body Keeps the Score by Bessel van der Kolk My Brother by Jamaica Kincaid Annie John by Jamaica Kincaid Bridge of San Luis Rey by Thornton Wilder Love, Anger, Madness: A Haitian Triptych by Marie Vieux-Chauvet Paule Marshall: A Writer's Life by Mary Helen Washington Pride and Prejudice by Jane Austen Moderation by Elaine Castillo Windward Heights by Maryse Condé Wuthering Heights by Emily Brontë Wide Sargasso Sea by Jean Rhys Jane Eyre by Charlotte Brontë Krik? Krack! by Edwidge Danticat

This is your daily horoscope for Wednesday, August 26, and the most important aspects of the day:Moon in Aquarius opposite Jupiter in Leo (2:30am PT)Moon in Aquarius trine Venus in Libra (3pm PT)Unlock More MagicGrimoire: Become a Better Witch in 12 WeeksBook a Reading with StephanieAccess Personalized Horoscopes + Join Stephanie's PatreonMake a DifferenceRevoke Stacy Turner's Medical License (Corrupt Coroner in Mississippi)Donate in Memory of Juliana NzitaHelp Honor Tasia FortuneSign the Petition + Demand Clemency for Jeffery Lee I Call Gov. Ivey + Demand Clemency 334-242-7100

“We are in the middle of a labyrinth which suggests to us many fake corridors. What's the superpower of literature? Literature is like an antidote against propaganda. Propaganda explains the world easily in a two-dimensional way.  Literature gives you a more complex explanation. Literature tells personal stories.”Today, we have a conversation about time, memory, and the bittersweet geography of human sorrow. Georgi Gospodinovis widely considered one of the most daring voices in contemporary European literature. His acclaimed novel, The Physics of Sorrow, won the prestigious Jan Michalski Prize in 2016, blending ancient myth and quantum physics to chronicle the delicate realities of post-socialist Eastern Europe. Joining him is Angela Rodel, a brilliant linguist, musician, and translator whose profound artistic empathy carries the flowing cadences of the Bulgarian language into vivid English. Together, this extraordinary creative duo made history by winning the 2023 International Booker Prizefor Time Shelter—the first book written in Bulgarian to ever receive the honor.Time Shelter is a masterfully dark, funny, and prescient novel. It begins with an enigmatic psychiatrist opening a clinic that treats Alzheimer's patients by meticulously recreating past decades to match their internal clocks. But the experiment quickly escapes the clinic walls, triggering a pan-European crisis where entire nations hold democratic referendums to choose which era of the past they will retreat into. It is a book that holds up a mirror to our own world, exploring what happens when a civilization faces a deficit of meaning and tries to weaponize nostalgia.(0:00) The Trap of Nostalgia(2:13) The Art of Translation(5:44) The Pandemic of the Past(11:30) Reading from ‘Time Shelter'(14:28) Death and the Gardener(19:34) The Translator's Calling(26:05) Cultural Rhythms of the Bulgarian Language(30:00) The Nonlinear Approach to Storytelling(34:30) Separating Personal and Historical Pasts(42:55) Storytelling vs Propaganda(47:19) Bodies, Animals and the Loneliness of the Minotaur(56:00) Reading ' Eight Minutes and 19 Seconds'(1:00:28) What makes a good life? What has given your life meaning?(1:04:18)   Childhood, Memory and Imagination(1:10:38) Reflections on God and the Stories His Grandmother Told Him(1:17:20) Education and the Empathic Imagination(1:23:25) The Museum of Memory(1:26:15) The Importance of Hugging and Empathy(1:28:02) AI and the Future of HumanityEpisode Websitewww.creativeprocess.info/podInstagram:@creativeprocesspodcast

“We are in the middle of a labyrinth which suggests to us many fake corridors. What's the superpower of literature? Literature is like an antidote against propaganda. Propaganda explains the world easily in a two-dimensional way.  Literature gives you a more complex explanation. Literature tells personal stories.”Today, we have a conversation about time, memory, and the bittersweet geography of human sorrow. Georgi Gospodinovis widely considered one of the most daring voices in contemporary European literature. His acclaimed novel, The Physics of Sorrow, won the prestigious Jan Michalski Prize in 2016, blending ancient myth and quantum physics to chronicle the delicate realities of post-socialist Eastern Europe. Joining him is Angela Rodel, a brilliant linguist, musician, and translator whose profound artistic empathy carries the flowing cadences of the Bulgarian language into vivid English. Together, this extraordinary creative duo made history by winning the 2023 International Booker Prizefor Time Shelter—the first book written in Bulgarian to ever receive the honor.Time Shelter is a masterfully dark, funny, and prescient novel. It begins with an enigmatic psychiatrist opening a clinic that treats Alzheimer's patients by meticulously recreating past decades to match their internal clocks. But the experiment quickly escapes the clinic walls, triggering a pan-European crisis where entire nations hold democratic referendums to choose which era of the past they will retreat into. It is a book that holds up a mirror to our own world, exploring what happens when a civilization faces a deficit of meaning and tries to weaponize nostalgia.(0:00) The Trap of Nostalgia(2:13) The Art of Translation(5:44) The Pandemic of the Past(11:30) Reading from ‘Time Shelter'(14:28) Death and the Gardener(19:34) The Translator's Calling(26:05) Cultural Rhythms of the Bulgarian Language(30:00) The Nonlinear Approach to Storytelling(34:30) Separating Personal and Historical Pasts(42:55) Storytelling vs Propaganda(47:19) Bodies, Animals and the Loneliness of the Minotaur(56:00) Reading ' Eight Minutes and 19 Seconds'(1:00:28) What makes a good life? What has given your life meaning?(1:04:18)   Childhood, Memory and Imagination(1:10:38) Reflections on God and the Stories His Grandmother Told Him(1:17:20) Education and the Empathic Imagination(1:23:25) The Museum of Memory(1:26:15) The Importance of Hugging and Empathy(1:28:02) AI and the Future of HumanityEpisode Websitewww.creativeprocess.info/podInstagram:@creativeprocesspodcast

In this episode of the Kwik Brain podcast, I break down the default mode network, the system your brain activates when you are no longer focused on a demanding task. I explain why zoning out is not always a bad thing, how this network helps retrieve memories and form new connections, and why your brain needs a balance between focus and unfocus to perform at its best.You'll learn:✅ Why sleep is not the only type of rest your brain needs✅ What the default mode network is and when it becomes active✅ How mind wandering helps your brain connect memories and ideas✅ Why unfocused time can improve creativity and self-awareness✅ How to use positive constructive daydreaming✅ Why free walking can improve fluency, flexibility, and original thinking✅ How an overactive default mode network can lead to rumination and anxiety✅ How meditation, deep breathing, and awe can quiet repetitive thought patterns✅ Why optimal brain performance requires both focus and unfocusAfter this episode, you will stop treating every quiet moment as wasted time and start building intentional mental downtime into your day, so your brain has the space to recover, connect ideas, and create better solutions.

During this Black August, US White Nationalists have continued to compile victories in the federal court, from Donald Trump's White Nationalist Department of Justice dropping charges against Oath Keepers January 6, 2021 insurrectionists to his illegal White House ballroom project being endorsed through inaction by Supreme Court Chief Justice John Roberts.Internationally, the US federal government continues to alienate former allies such as Canada, strong arm African governments like Liberia and support authoritarian and genocidal regimes from North Korea to Israel, all while further attempting to suppress internal critics, from sailors aboard the USS Abraham Lincoln to military media watchdogs like Stars and Stripes.Still, from within the fracturing US polity, both resistance and victory against would-be fascist overlords continues to rise. A US Senate primary victory in Florida and wins in other smaller federal and state races continue to unsettle both soft white nationalist Democratic establishment formations and an increasingly unhinged and embattled White Nationalist Party.Their reactions are well-warranted: A swelling number of people are taking and preparing to take action, independent of establishment politicians, mass media pundits, political operatives and precariously-perched managerial classes.From within Africana Governance formations, hope for creating better lives through collective effort is finding footing, fed by increasing numbers of awakened, informed, and engaged actors.This week, In Class With Carr places the concept of hope as an Africana Way of Knowing formed out of the Momentum of Memory in the context of US and global events.We start today's class with Tequila Johnson.Are you a member of Knarrative? If not, we invite you to join our community today by signing up at: https://www.knarrative.com. As a Knarrative subscriber, you'll gain immediate access to Knubia, our growing community of teachers, learners, thinkers, doers, artists, and creators. Together, we're making a generational commitment to our collective interests, work, and responsibilities. Join us at https://www.knarrative.com and download the Knubia app through your app store or by visiting https://community.knarrative.com.To shop Go to:TheGlobalMajorityMore from us:Follow on X: https://x.com/knarrative_https://x.com/inclasswithcarrFollow on Instagram IG / knarrative IG/ inclasswithcarr Follow Dr. Carr: https://www.drgregcarr.comhttps://x.com/AfricanaCarrFollow Karen Hunter: https://karenhuntershow.comhttps://x.com/karenhunter IG / karenhuntershowSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Melissa Swift shares strategies for navigating the chaos of the modern workplace more effectively. — YOU'LL LEARN — 1) The four trends making work feel more intense and chaotic 2) How to hone in on what makes you effective 3) Two critical questions to ask in the face of chaos Subscribe or visit AwesomeAtYourJob.com/ep1176 for clickable versions of the links below. — ABOUT MELISSA — Melissa Swift is a leading voice on how organizations, teams, and individuals can succeed in an ever-more challenging world of work. As founder and CEO of Anthrome Insight, she is a practicing consultant and keynote speaker. She has held consulting leadership roles at Capgemini, Mercer, Korn Ferry, and Deloitte. She is also the author of Work Here Now: Think Like a Human and Build a Powerhouse Workplace (Wiley, 2023).Her quarterly columns in MIT Sloan Management Review often rank among their most-read articles. Swift speaks regularly at events, including the MIT CIO Symposium, and has been quoted on the subject in The New York Times, The Wall Street Journal, NPR, Newsweek, The Economist, The Washington Post, Axios, and more.Throughout her career, Swift has pioneered techniques to reshape organizations for digital and workforce transformation, leading breakthrough projects across industries ranging from manufacturing to professional services to biotech to consumer goods. She earned her B.A. from Harvard University and her MBA from Columbia Business School.• Book: Effective: How to Do Great Work in a Fast-Changing World• LinkedIn: Melissa Swift• Website: AnthromeInsight.com— RESOURCES MENTIONED IN THE SHOW — • Database: O*ONET• Study: “Work intensification: Towards mapping the study field and defining a research agenda” by Ana Heloísa da Costa Lemos, Waleska Yone Yamakawa Zavatti Campos, and Marcelo Quintão• Book: The Warmth of Other Suns: The Epic Story of America's Great Migration by Isabel Wilkerson• Past episode: 314: How to Feel Less Busy With Laura Vanderkam• Past episode: 366: Mastering Conversations through Compassionate Curiosity with Kwame Christian• Past episode: 417: Managing Infinite Expectations with Laura Vanderkam• Past episode: 798: How to Have Difficult Conversations about Race with Kwame Christian• Past episode: 981: Using AI to Enhance Your Reading, Notes, Memory, and Decisions with Kwame Christian• Past episode: 1150: How to Reclaim Your Schedule and Own Your Time with Laura Vanderkam— THANK YOU SPONSORS! — • Shopify. Sign up for your free trial at Shopify.com/awesomepod• Vinted. Download the Vinted app for free to start selling with no seller fees!• Fitnexa. Get $10 off the SomniPods3 with the link and code AWESOMESee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

What happens when words are no longer enough to explain a life? Composer and jazz artist Ray Seol joins Dave Carter for a deeply personal conversation about immigration, language, music, memory, and the unlikely journey that led him to search for meaning through sound. At the heart of the conversation is Professor Seol's extraordinary relationship […]

What if everything you believe about why you are 'you' is wrong? My guest today has spent his career studying the brain at Johns Hopkins — and a few years ago, he was told he had six to twelve months to live. Today, we're talking about what he's learned on both sides of that line. We're going to get into why 'nature versus nurture' is, in his words, scientifically lazy — and what's actually shaping your personality, your preferences, even who you're attracted to. We're going to talk about a discovery about sexual sensation in the body that's only a few years old. And we're going to talk about what facing death taught him about time, gratitude, and identity that no textbook ever could. Stick around — this one gets personal fast   Connect With David Linden: Web: https://davidlinden.org Facebook: https://www.facebook.com/davidlindenauthor   Follow Dr. JC Doornick and the Makes Sense Academy:► Makes Sense Substack - https://drjcdoornick.substack.com ► Instagram: / drjcdoornick ► Substack: / drjcdoornick ►Facebook:  / makessensepodcast ►YouTube:  / drjcdoornick     MAKES SENSE PODCAST Welcome to the Makes Sense with Dr. JC Doornick Podcast. This podcast explores topics that expand human consciousness and enhance performance. On the Makes Sense Podcast, we acknowledge that it's who you are that determines how well what you do works, and that perception is subjective and an acquired taste. When you change the way you look at things, the things you look at begin to change. Welcome to the uprising of the sleepwalking masses. Welcome to the Makes Sense with Dr. JC Doornick Podcast.   SUBSCRIBE/RATE/REVIEW & SHARE our new podcast. FOLLOW Podcast: You will find a "Follow" button in the top right. This will enable the podcast software to alert you when a new episode launches each week. Apple: https://podcasts.apple.com/ca/podcast/makes-sense-with-dr-jc-doornick/id1730954168 Spotify: https://open.spotify.com/show/1WHfKWDDReMtrGFz4kkZs9?si=003780ca147c4aec   Podcast Affiliates: Kwik Learning: Many people ask me where I get all these topics, which I've been covering for almost 15 years. I have learned to read nearly four times faster and retain information 10 times better with Kwik Learning. Learn how to learn and earn with Jim Kwik. Get his program at a special discount here: https://jimkwik.com/dragon OUR SPONSORS: Operly - Take Back Control of Your Work Day and Get Rid of All Your AI Apps - Welcome to the new world of Time Freedom and Unlimited Scaling and Success with Operly -  https://go.getoperly.ai/video?ref=jean-claude-claude-d-2a95 Blue Blinds Bakery - Handcrafted with all-natural ingredients - www.blueblindsbakery.com     DAVID LINDEN TIMESTAMP 00:00 - Cold Open and Meeting Dr. David Linden 03:08 - Facing Cancer: David's Diagnosis and JC's Own News 06:00 - Why "Unique" Needed to Be Written 09:49 - The Third Factor: Why Identical Twins Differ 13:30 - The Heritability Spectrum: Earwax to Accent 17:11 - Intelligence, Addiction and Personal Responsibility 22:32 - Why Healthy People Still Get Cancer 24:58 - When Individuality Begins: Life Before Birth 29:39 - Cilantro, Taste and the "Anti-Panda" Diet 32:54 - Diet Advice and the Truth About Supplements 36:32 - Certainty, Curiosity and the Scientist's Mindset 39:24 - Science Evolving: Being Wrong and Staying Humble 44:25 - Open Questions: Sexuality and Revising "Unique" 47:35 - Lightning Round: Myths, Memory and a Favorite Book 52:39 - ending: New Book, Where to Find David and Sign-Off  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Links For The Occult Rejectshttps://linktr.ee/theoccultrejectsOccult Research Institutehttps://www.occultresearchinstitute.org/Substackhttps://substack.com/@theoccultrejects?r=7auau0&utm_campaign=profile&utm_medium=profile-pageCash Apphttps://cash.app/$theoccultrejectsVenmo@TheOccultRejectsBuy Me A Coffeebuymeacoffee.com/TheOccultRejectsPatreonhttps://www.patreon.com/TheOccultRejectsBibliographyRepetition, Fluency, and BeliefBacon, Frederick T. “Credibility of Repeated Statements: Memory for Trivia.” Journal of Experimental Psychology: Human Learning and Memory 5, no. 3 (1979): 241–252.Begg, Ian Maynard, Ann Anas, and Suzanne Farinacci. “Dissociation of Processes in Belief: Source Recollection, Statement Familiarity, and the Illusion of Truth.” Journal of Experimental Psychology: General 121, no. 4 (1992): 446–458.Dechêne, Alice, Christoph Stahl, Jochim Hansen, and Michaela Wänke. “The Truth About the Truth: A Meta-Analytic Review of the Truth Effect.” Personality and Social Psychology Review 14, no. 2 (2010): 238–257.Fazio, Lisa K., Nadia M. Brashier, B. Keith Payne, and Elizabeth J. Marsh. “Knowledge Does Not Protect Against Illusory Truth.” Journal of Experimental Psychology: General 144, no. 5 (2015): 993–1002.Hasher, Lynn, David Goldstein, and Thomas Toppino. “Frequency and the Conference of Referential Validity.” Journal of Verbal Learning and Verbal Behavior 16, no. 1 (1977): 107–112.Reber, Rolf, and Norbert Schwarz. “Effects of Perceptual Fluency on Judgments of Truth.” Consciousness and Cognition 8, no. 3 (1999): 338–342.Unkelbach, Christian. “Reversing the Truth Effect: Learning the Interpretation of Processing Fluency in Judgments of Truth.” Journal of Experimental Psychology: Learning, Memory, and Cognition 33, no. 1 (2007): 219–230.Zajonc, Robert B. “Attitudinal Effects of Mere Exposure.” Journal of Personality and Social Psychology 9, no. 2, part 2 (1968): 1–27.Memory, Spacing, and RetrievalCepeda, Nicholas J., Harold Pashler, Edward Vul, John T. Wixted, and Doug Rohrer. “Distributed Practice in Verbal Recall Tasks: A Review and Quantitative Synthesis.” Psychological Bulletin 132, no. 3 (2006): 354–380.Ebbinghaus, Hermann. Memory: A Contribution to Experimental Psychology. Translated by Henry A. Ruger and Clara E. Bussenius. New York: Teachers College, Columbia University, 1913. Originally published 1885.Karpicke, Jeffrey D., and Henry L. Roediger III. “Repeated Retrieval During Learning Is the Key to Long-Term Retention.” Journal of Memory and Language 57, no. 2 (2007): 151–162.Roediger, Henry L. III, and Jeffrey D. Karpicke. “Test-Enhanced Learning: Taking Memory Tests Improves Long-Term Retention.” Psychological Science 17, no. 3 (2006): 249–255.Tulving, Endel, and Donald M. Thomson. “Encoding Specificity and Retrieval Processes in Episodic Memory.” Psychological Review 80, no. 5 (1973): 352–373.Whitehouse, Harvey. Modes of Religiosity: A Cognitive Theory of Religious Transmission. Walnut Creek, CA: AltaMira Press, 2004.Semantic Satiation and Verbal TransformationBalota, David A., and Sarah Black. “Semantic Satiation in Healthy Young and Older Adults.” Memory & Cognition 25, no. 2 (1997): 190–202.Jakobovits, Leon A. Effects of Repeated Stimulation on Cognitive Aspects of Behavior: Some Experiments on the Phenomenon of Semantic Satiation. PhD diss., McGill University, 1962.Kounios, John, et al. “On the Locus of the Semantic Satiation Effect: Evidence from Event-Related Brain Potentials.” Memory & Cognition 28, no. 8 (2000): 1366–1377.Pilotti, Maura, John S. Antrobus, and Monica Duff. “The Effect of Presemantic Acoustic Adaptation on Semantic ‘Satiation.'” Memory & Cognition 25, no. 3 (1997): 305–312.Ströberg, Kim, Lau M. Andersen, and Stefan Wiens. “Electrocortical N400 Effects of Semantic Satiation.” Frontiers in Psychology 8 (2017): 2117.Warren, Richard M. “Illusory Changes of Distinct Speech upon Repetition—The Verbal Transformation Effect.” British Journal of Psychology 52, no. 3 (1961): 249–258.Warren, Richard M. “Illusory Changes in Repeated Words: Differences between Young Adults and the Aged.” American Journal of Psychology 74, no. 4 (1961): 506–516.Speech, Song, and Musical RepetitionDeutsch, Diana. “The Speech-to-Song Illusion.” Journal of the Acoustical Society of America 134, no. 5 (2013): 4241.Deutsch, Diana, Trevor Henthorn, and Rachael Lapidis. “Illusory Transformation from Speech to Song.” Journal of the Acoustical Society of America 129, no. 4 (2011): 2245–2252.Jakubowski, Kelly, Sebastian Finkel, Lauren Stewart, and Daniel Müllensiefen. “Dissecting an Earworm: Melodic Features and Song Popularity Predict Involuntary Musical Imagery.” Psychology of Aesthetics, Creativity, and the Arts 11, no. 2 (2017): 122–135.Margulis, Elizabeth Hellmuth. On Repeat: How Music Plays the Mind. New York: Oxford University Press, 2014.Marjieh, Raja, Pol van Rijn, Ilia Sucholutsky, Harin Lee, Thomas L. Griffiths, and Nori Jacoby. “A Rational Analysis of the Speech-to-Song Illusion.” Preprint, 2024.Vickhoff, Björn, Helge Malmgren, Rickard Åström, Gunnar Nyberg, Seth-Reino Ekström, Mathias Engwall, Johan Snygg, Michael Nilsson, and Rebecka Jörnsten. “Music Structure Determines Heart Rate Variability of Singers.” Frontiers in Psychology 4 (2013): 334.Breath, Vocalization, and Autonomic PhysiologyBernardi, Luciano, Peter Sleight, Gianfranco Bandinelli, Simone Cencetti, Lino Fattorini, Jacek Wdowczyc-Szulc, and Andrea Lagi. “Effect of Rosary Prayer and Yoga Mantras on Autonomic Cardiovascular Rhythms: Comparative Study.” BMJ 323, no. 7327 (2001): 1446–1449.Lehrer, Paul M., and Richard Gevirtz. “Heart Rate Variability Biofeedback: How and Why Does It Work?” Frontiers in Psychology 5 (2014): 756.Shaffer, Fred, and J. P. Ginsberg. “An Overview of Heart Rate Variability Metrics and Norms.” Frontiers in Public Health 5 (2017): 258.Zaccaro, Andrea, Andrea Piarulli, Marco Laurino, Erika Garbella, Danilo Menicucci, Bruno Neri, and Angelo Gemignani. “How Breath-Control Can Change Your Life: A Systematic Review on Psycho-Physiological Correlates of Slow Breathing.” Frontiers in Human Neuroscience 12 (2018): 353.Meditation, Chanting, and NeuroscienceFox, Kieran C. R., Matthew L. Dixon, Savannah Nijeboer, Manesh Girn, James L. Floman, Michael Lifshitz, Melissa Ellamil, Peter Sedlmeier, and Kalina Christoff. “Functional Neuroanatomy of Meditation: A Review and Meta-Analysis of 78 Functional Neuroimaging Investigations.” Neuroscience & Biobehavioral Reviews 65 (2016): 208–228.Kalyani, B. G., G. Venkatasubramanian, R. Arasappa, N. P. Rao, S. V. Kalmady, R. Behere, H. Rao, M. Vasudev, and B. N. Gangadhar. “Neurohemodynamic Correlates of ‘OM' Chanting: A Pilot Functional Magnetic Resonance Imaging Study.” International Journal of Yoga 4, no. 1 (2011): 3–6.Travis, Fred, and Jonathan Shear. “Focused Attention, Open Monitoring and Automatic Self-Transcending: Categories to Organize Meditations from Vedic, Buddhist and Chinese Traditions.” Consciousness and Cognition 19, no. 4 (2010): 1110–1118.Ritual, Attention, and Embodied PracticeBell, Catherine. Ritual Theory, Ritual Practice. New York: Oxford University Press, 1992.Hobson, Nicholas M., Juliana Schroeder, Jane L. Risen, Dimitris Xygalatas, and Michael Inzlicht. “The Psychology of Rituals: An Integrative Review and Process-Based Framework.” Personality and Social Psychology Review 22, no. 3 (2018): 260–284.McCauley, Robert N., and E. Thomas Lawson. Bringing Ritual to Mind: Psychological Foundations of Cultural Forms. Cambridge: Cambridge University Press, 2002.Rappaport, Roy A. Ritual and Religion in the Making of Humanity. Cambridge: Cambridge University Press, 1999.Xygalatas, Dimitris. Ritual: How Seemingly Senseless Acts Make Life Worth Living. New York: Little, Brown Spark, 2022.Also want to remind people about the website, if you're into reading we have tons of information by multiple contributors, and we got t-shirts up on the site if you're interested. Fun fact, the art is all based on the eyeball. 

Text the Show or Leave a VoicemailToday we continue our interview with Pete and Michelle Tucker. Pete was a motorcycle cop in Canada who had a catastrophic motorcycle accident that took his left leg and put him in a coma. If you haven't heard part one, it's really necessary for you to back and listen to Episode 148. This episode will pick up with the Pete in the hospital recovering from the multiple injuries and the traumatic amputation, slowly working through the system to win back his job as a cop on the street. You need to hear Pete and Michelle talking about the losses and struggles, because they are a fantastic example of a police couple who, together, survived the worst day possible.Music is by Mini VandalsHey Chaplain podcast episode 148.5Tags:Police, Accidents, Amputation, Career, Coma, Confidence, Hospital, Humor, Injury, Loss, Medical, Memory, Motorcycles, Spouse, Niagara Falls, Ontario, CanadaSupport the showThanks for Listening!  And, as always, pray for peace in our city.Subscribe/Follow here:Apple Podcasts: https://podcasts.apple.com/us/podcast/hey-chaplain/id1570155168Spotify: https://open.spotify.com/show/2CGK9A3BmbFEUEnx3fYZOYEmail us at: heychaplain44@gmail.comYou can help keep the show ad-free by buying me a virtual coffee!https://www.buymeacoffee.com/heychaplain

This is your daily horoscope for Tuesday, August 25, and the most important aspects of the day:Moon enters Aquarius (2am PT)Mercury in Leo conjunct South Node in Leo (2am PT)Mercury enters Virgo (4am PT)Moon in Aquarius conjunct Pluto in Aquarius (9am PT)Moon in Aquarius sextile Neptune in Aries (9:30am PT)Mercury in Virgo trine Chiron in Taurus (12pm PT)Moon in Aquarius trine Uranus in Gemini (1pm PT)Unlock More MagicGrimoire: Become a Better Witch in 12 WeeksBook a Reading with StephanieAccess Personalized Horoscopes + Join Stephanie's PatreonMake a DifferenceRevoke Stacy Turner's Medical License (Corrupt Coroner in Mississippi)Donate in Memory of Juliana NzitaHelp Honor Tasia FortuneSign the Petition + Demand Clemency for Jeffery Lee I Call Gov. Ivey + Demand Clemency 334-242-7100

All the hottest rhythmic and urban music songs from all your favorite artists!

All the hottest rhythmic and urban music songs from all your favorite artists!

All the hottest rhythmic and urban music songs from all your favorite artists!

After 43 years of marriage, Doug Lawrence lost his beloved wife and entered a season that changed his understanding of grief, mental health and purpose. In this deeply personal conversation, Doug explains why telling his wife's story became part of his healing, how unresolved losses can accumulate and why asking for help should never be mistaken for weakness. He also discusses how mentors, counselors, family members and trusted friends can support someone through grief—while emphasizing that mentoring should never replace professional mental-health care. CJ shares how losing his father affected every member of his family differently, including how his mother continues to carry the loss of her husband. Together, CJ and Doug explore the memories, dates and ordinary moments that can bring grief back without warning. This conversation is about more than learning to live after loss. It is about preserving love, finding safe people with whom to tell the truth and understanding that nobody should have to walk through grief entirely alone. Doug Lawrence is a grief mentor, author and founder of TalentC. His book, Grief: The Silent Pandemic, examines the emotional and social realities of grief and the importance of connection throughout the healing journey. In this episode: • Why grief does not follow a fixed timeline • How different family members experience the same loss differently • Why storytelling became part of Doug's healing • How unresolved losses can affect future grief • The role of memory and family rituals • Why men need safe spaces to discuss emotional pain • How mentoring can support—but not replace—professional care • Why it is okay to ask for help Connect with Doug Lawrence: Website: https://www.talentc.ca LinkedIn: https://www.linkedin.com/in/douglawrence-mentor Grief: The Silent Pandemic is available through Amazon and other major booksellers. ISBN: 9781941680186. Listener note: This episode discusses bereavement, mental-health struggles and emotional crisis. It is intended for education and personal reflection and is not a substitute for care from a qualified mental-health professional. If you or someone you know is struggling or in crisis, call or text 988 in the United States or Canada. If there is immediate danger, contact local emergency services. The CJ Moneyway Show Transformational Conversations. Built For Purpose. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jeremy Zakis, Part Two: Zakis reports on springtime in New South Wales, beginning with magpie breeding and swooping season—the start of nesting and defensive "dive-bombing" behavior, contrasted with the birds' remarkable memory and facial recognition that allow them to remember friendly locals. He notes the arrival of docile currawongs peacefully sharing garden space and pet biscuits with local magpies and dogs. The conversation turns to protecting ecosystems amid housing demands: addressing Australia's housing shortage by re-zoning and building dense apartment blocks in existing suburbs rather than clearing native bushlands and koala habitats. Finally, Zakis examines the Ashescricket re-evaluation—how England's tactical victory over Pakistan under new captain Joe Root signals a return to conservative cricket, forcing Australia to rethink its youthful Ashes strategy. (2)

This is your daily horoscope for Monday, August 24, and the most important aspects of the day:Moon Void in CapricornUnlock More MagicGrimoire: Become a Better Witch in 12 WeeksBook a Reading with StephanieAccess Personalized Horoscopes + Join Stephanie's PatreonMake a DifferenceRevoke Stacy Turner's Medical License (Corrupt Coroner in Mississippi)Donate in Memory of Juliana NzitaHelp Honor Tasia FortuneSign the Petition + Demand Clemency for Jeffery Lee I Call Gov. Ivey + Demand Clemency 334-242-7100

Episode Description:This is a From the Archive episode with Arianna Huffington.Arianna Huffington returns to the show for a conversation about sleep, success, reinvention, and the cultural delusion that burnout is the price of achievement.James begins by asking practical sleep questions: Is nine hours too much? Can sleep be split into two four-hour blocks? Arianna explains that for most people, seven to nine hours is the real range, and that sleep should leave a person fully recharged, not limping through the day waiting for a second shift of rest.From there, James rewinds to Arianna's career. Before The Huffington Post, before Thrive Global, before The Sleep Revolution, Arianna had already spent decades writing, appearing on television, entering politics, changing positions, and reinventing herself. She credits her mother with giving her the belief that failure was not the opposite of success, but a stepping stone toward it.One of the central stories is Arianna's second book being rejected by 36 publishers. Out of money and unsure whether she should remain a writer, she walked into a bank in London and asked for a loan. The manager gave it to her. That small act kept her on the path.James and Arianna then talk about The Huffington Post: its rough launch, brutal early reviews, the team behind it, the importance of creating a platform, and the thrill of giving unknown people a chance to be heard. Arianna tells one of her favorite stories about a homeless teenager whose writing on HuffPost helped lead to Harvard discovering him.The conversation then turns to the 2007 collapse that changed Arianna's relationship with sleep. Arianna says the problem was not just personal overwork. It was a collective belief that sleep deprivation is required for success. But James pushes her on the personal side too, and Arianna acknowledges perfectionism: building a company, raising daughters, trying to be a perfect mother, and working through the night after college-tour days with her daughter.Arianna's answer is not a rigid sleep doctrine. It is a series of small steps. Build a transition. Remove devices from the bedroom. Lower the lights. Take a bath or shower. Read a physical book. Use gratitude as the closing scene of the day. If you wake up at 3 a.m., meditate instead of spiraling.The episode closes with joy. For Arianna, sleep is not only about health and productivity. It is about being present enough to experience life while it is happening.Editorial Note:This is a From the Archive episode. References to Arianna's role at The Huffington Post, HuffPost's size and global expansion, her contract, sleep resources, and digital products reflect the original recording period.This episode discusses sleep, medication, insomnia, health, and wellbeing. It should not be treated as medical advice. Anyone dealing with chronic insomnia, sleep medication dependence, depression, narcolepsy, or other health concerns should speak with a qualified clinician.What You'll Learn:Why Arianna says sleep deprivation is not a requirement for achievement.How her 2007 collapse changed her view of success, productivity, and wellbeing.Why most people need seven to nine hours of sleep.Why she sees failure as a stepping stone, not the opposite of success.How her mother shaped her courage, optimism, and relationship to fear.Why The Huffington Post was built as both a journalistic enterprise and a platform for voices.How brutal early reviews tested the HuffPost team.Why Arianna believes teams matter most during hard times.How perfectionism contributed to her burnout.Why sleep affects health, productivity, decision-making, creativity, and joy.Why dreams matter for memory, insight, and new ideas.How to start a sleep transition with small microsteps.Why removing devices from the bedroom is one of the first practical changes.How gratitude can become the “closing scene” of the day.Why waking up in the middle of the night is not the problem—the stress spiral is.How meditation can help turn middle-of-the-night waking into rest.Why being exhausted makes people miss the moment.Timestamped Chapters:[03:02] Arianna Huffington ReturnsJames introduces Arianna and The Sleep Revolution, and they start with the practical question of how much sleep is enough.[03:51] Can You Split Sleep Into Two Blocks?James asks about sleeping four hours in the afternoon and four at night; Arianna explains why waking up fully recharged matters.[05:16] The Secret Origins of Arianna HuffingtonJames moves from sleep to Arianna's long career of writing, media, politics, public life, and reinvention.[06:20] Failure as a Stepping StoneArianna credits her mother with teaching her to aim high and see failure as part of the path.[08:06] Rejected by 36 PublishersArianna remembers running out of money in London, walking into Barclays Bank, and receiving the loan that helped her stay a writer.[09:52] The Huffington Post BeginsArianna explains HuffPost as both a journalism operation and a platform for known and unknown voices.[11:28] The Magic of the InternetArianna tells the story of a homeless teenager whose HuffPost piece helped bring him to Harvard's attention.[11:48] When the Launch Reviews Were BrutalJames asks whether Arianna ever worried HuffPost would fail, and she remembers harsh early criticism.[12:42] Everything Is Rigged in Your FavorArianna describes the spiritual belief that helped her move through fear, uncertainty, and dark periods.[13:18] Moving Continents After HeartbreakArianna explains how leaving a relationship in London led to her life in America, her daughters, her career, and The Huffington Post.[14:19] Life After Selling HuffPostJames asks how Arianna's life changed after the sale, and she explains why the company still felt new because it kept evolving.[15:20] The Collapse That Changed EverythingArianna connects her 2007 collapse from exhaustion to the wellness work that eventually became The Sleep Revolution.[16:32] The Collective Delusion About SleepArianna explains why modern culture wrongly treats sleep deprivation as essential to achievement.[18:02] Perfectionism, Work, and MotherhoodJames pushes on the personal side of Arianna's burnout, and she identifies the pressure to be perfect at work and at home.[20:16] Why Sleep MattersArianna lays out the benefits of sleep across health, productivity, decision-making, creativity, and emotional life.[21:53] What the Brain Does While We SleepArianna explains why sleep is not passive downtime, but a period of active cleanup and restoration.[23:21] Sleep and ProductivityArianna argues that sacrificing sleep for work backfires because it reduces judgment, creativity, engagement, and performance.[25:08] Sleep as a Performance EnhancerJames brings up willpower and negotiation, and Arianna adds the example of athletes using sleep to improve performance.[26:49] First Understand the CrisisArianna explains why people need to change their minds about sleep before they can change their habits.[27:30] Dreams, Memory, and InsightArianna talks about dreams and recommends writing them down when you wake up.[28:32] Sleeping Pills and Better AlternativesJames asks about medication, and Arianna points to behavioral approaches and sleep preparation.[29:50] The Sleep TransitionArianna explains the importance of beginning somewhere, even with just five or ten minutes.[30:57] Escort Your Devices Out of the BedroomArianna recommends turning off phones, laptops, and tablets before bed and creating a clean boundary between day and sleep.[31:24] Bath, Books, Temperature, and GratitudeArianna describes her wind-down routine: water, dedicated sleep clothes, lower lights, a cool room, physical books, and three things she is grateful for.[33:42] The 3 A.M. Anxiety SpiralJames shares his method for postponing middle-of-the-night anxieties until the afternoon.[34:14] Meditation in the Middle of the NightArianna says waking up is not the problem and explains why meditation helps her return to sleep.[36:28] Sleep, Wellbeing, and JoyJames asks whether Arianna feels happy, and she says sleep helps her bring more joy into everything she does.[37:49] Don't Miss the MomentArianna defines joy as being fully engaged and grateful, and shares her mother's reminder that this moment is all we have.Additional Resources:Arianna Huffington Official WebsiteThe Sleep Revolution — Penguin Random HouseThrive — Arianna HuffingtonThrive Global — Arianna HuffingtonArianna Huffington's TED Talk: “How to succeed? Get more sleep”Pulitzer Prize: David Wood of The Huffington PostThe Female Woman — Google BooksSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We like to think of memory as a record of the past. But that's not really what it is. Memory doesn't keep the past — it can also remake it. It stitches fragments into stories, and those stories — true or not — are what we end up calling our life, and sometimes, our collective history. Today's episode is a rerun of an interview that originally published last year with Charan Ranganath, a neuroscientist and author of a book called Why We Remember. The two discuss the strange alchemy of remembering and how the stories our minds create end up creating us. Host: Sean Illing (@SeanIlling) Guest: Charan Ranganath, neuroscientist and author of Why We Remember We would love to hear from you. To tell us what you thought of this episode, email us at thegrayarea@vox.com or leave us a voicemail at 1-800-214-5749. Your comments and questions help us make a better show. And you can watch new episodes of The Gray Area on YouTube. Listen to The Gray Area ad-free by becoming a Vox Member: vox.com/members Learn more about your ad choices. Visit podcastchoices.com/adchoices

Scientists warn the El Niño event developing in the Pacific could be the strongest in living memory, pushing up global temperatures and increasing the risk of extreme weather. Effects are already being felt around the world - the Indian government is having to import sugar to bolster local supplies. We visit the West Bank town of Kadim to see how the Israeli government is expanding settlements ahead of October elections. The former Pakistani President Imran Khan is taken to hospital and then returned to prison, confusing his family and followers. And what is Meghan going to do in the UK when she returns with Prince Harry in a couple of weeks' time? The Global News Podcast brings you the breaking news you need to hear, as it happens. Listen for the latest headlines and current affairs from around the world. Politics, economics, climate, business, technology, health – we cover it all with expert analysis and insight. Get the news that matters, delivered twice a day on weekdays and daily at weekends, plus special bonus episodes reacting to urgent breaking stories. Follow or subscribe now and never miss a moment. Get in touch: globalpodcast@bbc.co.uk Photo: A woman walks during heavy rainfall in Yangon, Myanmar, 12th August. Credit: EPA/Shutterstock

Weather experts describe the developing climate system as an unprecedented event. Temperatures in the Pacific Ocean could climb more than three degrees above normal.Also in the programme: the Facebook whistleblower Frances Haugen speaks to Newshour about the legal case against Facebook's parent company for improperly collecting and using children's personal data; and dramatising the colourful life of the British economist John Maynard Keynes.(Photo: Mexico says mass bird deaths likely caused by El Nino's hotter waters. Credit: Mexican Government/Handout via Reuters)

Who is ____?, a little game of “guess who” on a Friday morning How much are these white rappers worth? Headlines

This is your daily horoscope for Sunday, August 23, and the most important aspects of the day:Moon in Capricorn opposite Mars in Cancer (6am PT)Sun in Virgo trine Chiron in Taurus (12:30pm PT)Moon in Capricorn square Saturn in Aries (6pm PT)Moon in Capricorn square Venus in Libra (11:30pm PT)Unlock More MagicGrimoire: Become a Better Witch in 12 WeeksBook a Reading with StephanieAccess Personalized Horoscopes + Join Stephanie's PatreonMake a DifferenceRevoke Stacy Turner's Medical License (Corrupt Coroner in Mississippi)Donate in Memory of Juliana NzitaHelp Honor Tasia FortuneSign the Petition + Demand Clemency for Jeffery Lee I Call Gov. Ivey + Demand Clemency 334-242-7100

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

Welcome to the Friday insight. This is part two for the ongoing "Conceptualization and Rating" series on the Friday Insight. Find the first part in last week's insight episode. Starting out with Chess is tough on the brain. Here are the key conceptualization skills you need to finally reach 1000. Mentioned in this episode: Don't Move Until You See It training tools The New Mantra Technique article For more articles like this, head to https://dontmoveuntilyousee.it/articles And to learn more about the 10-minute stretch feature and the Don't Move membership, head to https://dontmoveuntilyousee.it/join

Lou Holtz shares a lesson on leadership, standards, and why maintaining what you built is how you lose it. In this direct talk, he reveals the four things every person needs, the three rules he's used with his teams and his children, and the insecurity he had to admit to in his own marriage. This episode will challenge you to stop protecting and start growing.Source: Lou Holtz on LeadershipHosted by Sean CroxtonFollow me on InstagramSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This is your daily horoscope for Saturday, August 22, and the most important aspects of the day:Moon in Sagittarius trine Mercury in Leo (1:30am PT)Moon in Sagittarius trine Sun in Leo (1:30pm PT)Moon enters Capricorn (2pm PT)Sun in Leo conjunct South Node in Leo (3pm PT)Sun enters Virgo (7pm PT)Moon in Capricorn square Neptune in Aries (10pm PT)Unlock More MagicGrimoire: Become a Better Witch in 12 WeeksBook a Reading with StephanieAccess Personalized Horoscopes + Join Stephanie's PatreonMake a DifferenceRevoke Stacy Turner's Medical License (Corrupt Coroner in Mississippi)Donate in Memory of Juliana NzitaHelp Honor Tasia FortuneSign the Petition + Demand Clemency for Jeffery Lee I Call Gov. Ivey + Demand Clemency 334-242-7100

This is your daily horoscope for Friday, August 21, and the most important aspects of the day:Moon in Sagittarius trine Jupiter in Leo (12:30am PT)Venus in Libra opposite Saturn in Aries (6am PT) Moon in Sagittarius trine Saturn in Aries (6am PT)Moon in Sagittarius sextile Venus in Libra (6am PT)Unlock More MagicGrimoire: Become a Better Witch in 12 WeeksBook a Reading with StephanieAccess Personalized Horoscopes + Join Stephanie's PatreonMake a DifferenceRevoke Stacy Turner's Medical License (Corrupt Coroner in Mississippi)Donate in Memory of Juliana Nzita Help Honor Tasia FortuneSign the Petition + Demand Clemency for Jeffery Lee I Call Gov. Ivey + Demand Clemency 334-242-7100

“We are in the middle of a labyrinth which suggests to us many fake corridors. What's the superpower of literature? Literature is like an antidote against propaganda. Propaganda explains the world easily in a two-dimensional way.  Literature gives you a more complex explanation. Literature tells personal stories.”Today, we have a conversation about time, memory, and the bittersweet geography of human sorrow. Georgi Gospodinovis widely considered one of the most daring voices in contemporary European literature. His acclaimed novel, The Physics of Sorrow, won the prestigious Jan Michalski Prize in 2016, blending ancient myth and quantum physics to chronicle the delicate realities of post-socialist Eastern Europe. Joining him is Angela Rodel, a brilliant linguist, musician, and translator whose profound artistic empathy carries the flowing cadences of the Bulgarian language into vivid English. Together, this extraordinary creative duo made history by winning the 2023 International Booker Prizefor Time Shelter—the first book written in Bulgarian to ever receive the honor.Time Shelter is a masterfully dark, funny, and prescient novel. It begins with an enigmatic psychiatrist opening a clinic that treats Alzheimer's patients by meticulously recreating past decades to match their internal clocks. But the experiment quickly escapes the clinic walls, triggering a pan-European crisis where entire nations hold democratic referendums to choose which era of the past they will retreat into. It is a book that holds up a mirror to our own world, exploring what happens when a civilization faces a deficit of meaning and tries to weaponize nostalgia.(0:00) The Trap of Nostalgia(2:13) The Art of Translation(5:44) The Pandemic of the Past(11:30) Reading from ‘Time Shelter'(14:28) Death and the Gardener(19:34) The Translator's Calling(26:05) Cultural Rhythms of the Bulgarian Language(30:00) The Nonlinear Approach to Storytelling(34:30) Separating Personal and Historical Pasts(42:55) Storytelling vs Propaganda(47:19) Bodies, Animals and the Loneliness of the Minotaur(56:00) Reading ' Eight Minutes and 19 Seconds'(1:00:28) What makes a good life? What has given your life meaning?(1:04:18)   Childhood, Memory and Imagination(1:10:38) Reflections on God and the Stories His Grandmother Told Him(1:17:20) Education and the Empathic Imagination(1:23:25) The Museum of Memory(1:26:15) The Importance of Hugging and Empathy(1:28:02) AI and the Future of HumanityEpisode Websitewww.creativeprocess.info/podInstagram:@creativeprocesspodcast

NOTE: For Ad-Free Episodes, 100+hrs of Bonus Content and More - Visit our Patreon at https://www.patreon.com/thewheelweavespodcastFind us on our Instagram, YouTube & Website, and join the conversation on Discord!In this episode Dani and Brett discuss PERSPECTIVES 27-30 of Chapter 37 of A Memory of Light!We would like to thank and welcome Christopher Turansky, Joe, Powerbank, Ethan, and Jesse Eisenheim to The Wheel Weaves Patreon Team! Thank you so much for your generosity and support!!We would like to acknowledge and thank our Executive Producers Brandy and Aaron Kirkwood, Sean McGuire, Janes, LightBlindedFool, Big C, Deyvis Ferreira, Green Man, Bennett Williamson, Hannah Green, Noralia, Helena Jacobsen, Matthew Mendoza, Sims, Cyndi, Manethraen, Kevin wallbank, Andrew Scarponi, Mr. Boddy's Body, and HoneyBunchesOfJason!The Wheel Weaves is hosted and edited by Dani and Brett, produced by Dani and Brett with Passionsocks, Cody Fouts, Mozyme, Jamie Young, Jared Berg, Matt Truss, Antoine Benoit, MKM, Colby T, Gabby Young, Ricat, Chris G., Saverio Bartolini, Mag621, Courtney B, and Tina Gruene; with music by Audionautix.Don't forget to leave us that 5 star review if you enjoy the show for a chance to win exclusive merchandise!Check out https://www.thewheelweavespodcast.com for everything The Wheel Weaves!Become a supporter of this podcast: https://www.spreaker.com/podcast/the-wheel-weaves-podcast-a-wheel-of-time-podcast--5482260/support.

Topics covered in this episode: Python 3.12.14, 3.11.16, 3.10.21 - security releases Codeberg's AI-code ban tests its role as a GitHub alternative Brett Cannon: what's missing for reproducible builds on PyPI nothing records the source code a distribution came from. direct_url.json captures it when you install from a repo or archive, so the fix is putting the same info in sdist/wheel metadata. recording the build tools. Wheels can already do this via PEP 770 SBOMs in .dist-info/sboms/ - sdists can't, since they're a tarball plus a precalculated PKG-INFO with nowhere to hang extra metadata. Either "don't use sdists" or an sdist v2. Extra extra extra, hear all about it Extras Joke Watch on YouTube Sponsored by Logfire from Pydantic pythonbytes.fm/logfire This episode is brought to you by Pydantic Logfire. It's observability for AI apps from the team behind Pydantic - agents, LLMs, APIs, database, and infrastructure in a single trace, queried with Postgres-compatible SQL. Your coding agent can query it too, through their MCP server. I'll tell you more later. Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Calvin #1: Python 3.12.14, 3.11.16, 3.10.21 - security releases https://blog.python.org/2026/08/python-31214-31116-31021/ Source-only security releases for the three branches now in security-fix-only mode; release team blamed the European solar eclipse for the timing. tarfile hardening. Multiple path-traversal bypasses of the data filter closed, including a symlink escape that bypassed the CVE-2025-4330 fix; extract() now applies the filter to link targets too. Four fresh CVEs: CVE-2026-2297 (SourcelessFileLoader not using io.open_code() for .pyc), CVE-2026-4224 (expat crash on deeply nested content models), CVE-2026-3644 (control chars in http.cookies.Morsel), plus the completed CVE-2021-4189 fix in ftplib.ftpcp. Quadratic-complexity DoS cleanup across the stdlib: HTMLParser, configparser regexes, unicodedata.normalize(), csv.Sniffer.sniff(), and ElementTree XPath index predicates. Header/injection fixes: CR/LF rejected in HTTPConnection.set_tunnel(), control chars blocked in wsgiref.handlers status, and webbrowser now rejects leading dashes (plus a %action prefix bypass). http.client now caps chunked trailer lines and 1xx interim responses at 100 each - a hostile server could previously hang the client forever despite a socket timeout. Memory-safety odds and ends: stale pointers in lzma/bz2/zlib decompressors after MemoryError, a bz2 stack overflow on reuse-after-error, and bundled libexpat bumped to 2.8.3. If you're still on 3.10, 3.11, or 3.12 - and you extract tarballs from anywhere you don't fully control - this one's not optional. Michael #2: Codeberg's AI-code ban tests its role as a GitHub alternative Armin's article “Codeberg Divides” Armin Ronacher argues that Codeberg's new terms, which prohibit projects mostly written with generative AI, create a vague and difficult-to-enforce boundary. His larger concern is that a democratically governed host can still be unpredictable or ideologically narrow, weakening Codeberg's potential as a broad European alternative to GitHub. The strongest question for Python developers is whether repository hosting should judge legal open source by how code was produced, or focus on behavior and resource abuse. “Mostly generated” is hard to measure in modern codebases where developers mix handwritten code, completions, agents, and generated refactors. Ronacher suggests clearer alternatives: ban all LLM involvement, or target autonomous repository spam, abusive resource use, and low-quality generated contributions directly. Codeberg is free to choose a values-driven community, but that may conflict with being predictable, neutral infrastructure and a serious GitHub competitor. Worth discussing: can open-source communities set meaningful AI boundaries without driving maintainers and projects into opposing camps? Very first search for these terms lands on this page. Codeberg looked like a viable alternative. … Unfortunately, the latest update to its terms of service seems to mark a first step in changing one part I moved there for, namely the “freedom” part. Sponsor: Logfire from Pydantic Your AI agent failed at 2am. Was it the model? A tool call? The database? Most observability tools can't tell you, because they only see part of your stack. Pydantic Logfire sees all of it. One trace across your agents, LLMs, APIs, and database. Down to the infrastructure: services, Kubernetes, and hosts. It's built on OpenTelemetry, with SDKs for Python, TypeScript, and Rust, and it works with any OTel-compatible language. Every prompt, token count, and cost, right next to your vector searches and API calls. You query everything with Postgres-compatible SQL. And so can your coding agent, through the Logfire MCP server. Stop guessing. Read the trace. Pydantic Logfire. AI, it's still just engineering. Visit pythonbytes.fm/logfire today and sign up today. Get 10M records free every month, no card required. You can even click “Onboard with your coding agent” to copy a prompt to have claude or codex integrate Logfire into your app. Thanks to Pydantic for supporting the show. Calvin #3: Brett Cannon: what's missing for reproducible builds on PyPI Framing came out of his 2026 Python Packaging Council nomination - the secure-supply-chain gap he found is that Python has no defined way to do reproducible builds at all. Design goal is zero friction: producers uploading to PyPI shouldn't have to do anything. The work lands on build backends and installers. Gap #1: nothing records the source code a distribution came from. direct_url.json captures it when you install from a repo or archive, so the fix is putting the same info in sdist/wheel metadata. Gap #2: recording the build tools. Wheels can already do this via PEP 770 SBOMs in .dist-info/sboms/ - sdists can't, since they're a tarball plus a precalculated PKG-INFO with nowhere to hang extra metadata. Either "don't use sdists" or an sdist v2. The replay mechanism already exists: [build-system] in pyproject.toml is a defined entry point, so if backends recorded their own environment, you could reinstall and re-run the build. Payoff idea: trusted third parties report successful reproductions back to PyPI, which displays "independently reproduced by X" - surfaced in the index API so installers could prefer reproduced files. Explicitly framed as a perk, not a requirement - roughly SLSA build level 1, no shaming projects that don't opt in. Verbal kicker option: "And don't think pure-Python wheels are off the hook. Something built that wheel, and if that something was compromised, so is your wheel. SolarWinds was a build-process attack." Michael #4: Extra extra extra, hear all about it Python 3.14.7 Upgraded the MCP servers to 2026-07-28 v2 protocols (talk python, python bytes) Got agentsview running synced via postgres Talk Python courses, teams trial offering Talk Python courses, government procurement offering Lean TDD audio book is out Extras Calvin: uv now prefers post-quantum key exchange - https://github.com/astral-sh/uv/releases/tag/0.12.4 Joke: Beware of dog

This is your daily horoscope for Thursday, August 20, and the most important aspects of the day:Moon enters Sagittarius (1:30am PT)Moon in Sagittarius sextile Pluto in Aquarius (9am PT)Moon in Sagittarius trine Neptune in Aries (9:30am PT)Moon in Sagittarius opposite Uranus in Gemini (12:30pm PT)Unlock More MagicGrimoire: Become a Better Witch in 12 WeeksBook a Reading with StephanieAccess Personalized Horoscopes + Join Stephanie's PatreonMake a DifferenceRevoke Stacy Turner's Medical License (Corrupt Coroner in Mississippi)Donate in Memory of Juliana NzitaHelp Honor Tasia FortuneSign the Petition + Demand Clemency for Jeffery Lee I Call Gov. Ivey + Demand Clemency 334-242-7100

Your morning starts shaping your brain long before you answer your first email or take your first sip of coffee.In this episode of the Kwik Brain podcast, I walk you through the morning routine I use to support my brain's natural chemistry, boost mental energy, and create focus that lasts throughout the day.Most people think productivity begins when they sit down to work. But your brain is already deciding how alert, focused, and resilient you'll be based on what you do in the first 30 minutes after waking up.I break down the simple science behind hydration, sunlight, movement, breathwork, gratitude, journaling, visualization, and curiosity, and explain why each habit helps prepare your brain to learn faster, think more clearly, and perform at a higher level. You'll also learn how to direct your attention intentionally instead of letting distractions control your day.These aren't complicated routines that require hours. They're practical habits you can start using tomorrow morning to build momentum before the rest of the world demands your attention.In this episode, you'll learn:✅ Why your brain needs hydration immediately after waking up✅ How morning sunlight boosts alertness and improves sleep later that night✅ Why movement increases blood flow and primes your brain for learning✅ How journaling creates mental clarity and reduces overwhelm✅ Why gratitude rewires your brain for resilience and optimism✅ How curiosity activates your brain's learning centers✅ Why visualization helps your brain focus on what matters most✅ Simple breathing exercises to improve focus and calm your nervous system✅ How to create a morning routine that works with your brain instead of against itYour mornings don't have to feel rushed or reactive.A few intentional minutes can completely change how your brain performs for the rest of the day.

Padraic Scanlan — Multi-Part, Part One: Padraic Scanlan explores the deep-seated historical and economic causes of the Great Irish Famine, beginning with the haunting folk memory of Queen Victoria's visit to Skibbereen, a village that became an icon of social collapse and starvation. While the crisis was triggered by the failure of potato crops, Scanlan emphasizes that the vulnerability of the Irish population was manufactured through centuries of British conquest and colonial land management. By the nineteenth century, a tiny oligarchy owned the vast majority of Irish land, with 4,000 people controlling 80 percent of the island. The rural economy rested on a fragile three-legged stool consisting of the potato, the pig, and turf for fuel. The potato served as the glue of this system, allowing landlords to maintain a low-wage, capital-poor labor force that could survive on small, high-yield plots. The economic landscape was further constrained by the conacre system, short-term and expensive leases for tiny parcels of land that discouraged any improvements, as visible prosperity might prompt a rent increase. This precarious existence was justified by influential Victorian economists such as Thomas Malthus, who argued that famine was a dreadful resource of nature necessary to check population growth and compel the uncivilized poor to work. When the novel pathogen Phytophthora infestans arrived from the Americas in the early 1840s, it decimated the genetically uniform potato monocrop. The blight not only killed the growing tubers but also rotted stored supplies, leaving the two million people who relied exclusively on the potato with no buffer against catastrophe. (1)

- Apple Opens Advanced Manufacturing Center in Houston, TX - Apple Gives Politicos Tour of Houston's AMC - White House Not Into Apple Buying Memory from Chinese Firms - Report: Apple Builds China-Specific LLM Powered by Alibaba, Baidu - Sales Begin for Ads in Apple Maps - Recent macOS Security Updates Address Issue Under Active Exploit - Apple Updates Refurbished Store Offerings - Apple TV Teams with Cuarón on Horror/Thriller Series - Vince Gilligan Says Filming on Second Season of "Pluribus" Starts Soon - Sponsored by Coveron: Save up to 76% off with code macos at coveron.com/macos - Sponsored by Copilot Money: Get a two month free trial with Offer Code MACOSKEN at copilot.money/macosken - Catch Ken on Mastodon - @macosken@mastodon.social - Send Ken an email: info@macosken.com - Chat with us on Patreon for as little as $1 a month. Support the show at Patreon.com/macosken

Storage stocks lead the semi rally as Trump administration officials look to steer Apple away from Chinese chips. The traders debate the health of the AI trade amid new commentary from leaders of OpenAI and Anthropic. Then, Vanda's Jens Nordvig explains how prolonged dollar weakness could send gold prices surging. Plus, the countdown to Meta's child safety trial, Nike stumbles to 12-year lows and how to trade home improvement stocks into earnings. Fast Money Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What connections may exist between childhood GATE programs, intelligence experimentation, MK-Ultra and claims of ritualized trauma?Today, Robert Kalil welcomes Chris Mathieu, founder and host of Forbidden Knowledge News and the Forbidden Knowledge Network, for a deep and uncensored conversation about controversial programs and the hidden systems that may operate behind them.Chris has built an independent media network dedicated to investigating suppressed history, unexplained phenomena, covert operations, consciousness, technology and subjects frequently ignored by mainstream media. In this episode, Rob and Chris examine reports surrounding gifted-and-talented education programs, trauma-based conditioning, MK-Ultra, SRA testimony and the possibility that vulnerable individuals have been monitored or selected from an early age.Topics may include:• The origins and purpose of GATE programs• Gifted children and unusual screening procedures• MK-Ultra and trauma-based conditioning• Claims involving SRA and organized abuse• Intelligence agencies and behavioral experimentation• Memory fragmentation and recovered memories• Manipulation of consciousness• Suppressed testimony and institutional protection• Independent media and censorship• Chris Mathieu's work with Forbidden Knowledge NewsThese subjects include disputed allegations and personal testimony. This program is presented for discussion, investigation and educational purposes. Viewers should research the evidence and reach their own conclusions.We go deep. You decide.Typical Skeptic Podcast #2777Live at 4:00 PM EasternChris Mathieu / Forbidden Knowledge News:https://www.youtube.com/@ForbiddenKnowledgeNewshttps://forbiddenknowledge.news/

Carl Quintanilla and Jim Cramer led off the show with tech as a market bright spot: Sandisk, Western Digital and Micron rallied after The Wall Street Journal reported Commerce Secretary Lutnick urged Apple not to buy Chinese memory chips. The anchors discussed Anthropic amid reports its revenue has skyrocketed as the AI startup prepares to go public. President Trump's comments on the Iran war also in the spotlight — from his warning to Oman to him urging Americans to accept higher gas prices. Also in focus: The beaten-down names Cramer believes you should buy now, Nvidia's $21 billion SpaceX stake, OpenAI's president on recent executive departures, Disney's CEO on the company's stock slump, Situational Awareness meltdown fallout.    Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Cramer says investors should go for this stock if they want exposure to memory. Become an Investing Club member to go behind the scenes with Jim Cramer and Jeff Marks every day as they talk candidly about the market's biggest headlines, analyst calls and holdings in the Charitable Trust – and see up close how they decide when, and if, to take action on stocks. Sign up here:  cnbc.com/morningtake CNBC Investing Club Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.