Podcast appearances and mentions of Sam Altman

P.M. Edition for Aug. 28. Economics correspondent Nick Timiraos reports from Jackson Hole on how investors are interpreting Federal Reserve Chairman Kevin Warsh's speech. Plus, some of President Trump's biggest corporate donors are now cutting checks to Democrats, too. WSJ's White House reporter Annie Linskey explains how American companies are preparing for a potential Democratic comeback in November. And WSJ's global energy reporter Collin Eaton unpacks how Chevron and other U.S. energy companies are closing in on deals worth billions to expand in Venezuela's oil fields. Sabrina Siddiqui hosts. Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This Friday's show is packed with political chaos, viral moments, and some genuinely unsettling stories. Trump's fight with Canada reaches a new level as he trolls Mark Carney, takes aim at Canadian trade policies, and renames Lake Ontario “Lake America,” triggering backlash from Canadian leaders and Democrats at home.The Chicks also dig into the growing controversy surrounding Pennsylvania Governor Josh Shapiro's claims about measles deaths after local officials raised questions about the reported causes of death.Then, Sam Altman and major AI companies issue an urgent warning about cyber defense, sparking a much bigger conversation about artificial intelligence, automation, and just how many American jobs could disappear in the coming years.Later, the Lindsay Clancy murder trial takes center stage as prosecutors deliver their closing argument and lay out their case that Clancy understood right from wrong when her three children were killed.Plus: Abdul El-Sayed's deleted Green New Deal posts resurface, Gavin Newsom faces questions about his property dealings, Kamala Harris hints at another run, Ben Shapiro mocks Tucker Carlson, and the latest conservative media infighting gets even messier.For a limited time only, receive 20% off your entire Laundry Sauce order when you use code CHICKS20 at https://LaundrySauce.com/Chicks20Save an additional 10% off  practical food for your pantry with the ReadyWise 4-Can Protein Bundle at https://ReadyWise.com with promo code CHICKS10.Make the switch and feel the difference of truly fast, modern antivirus protection with Webroot— for a limited time, save 60% when you go to https://WebRoot.com/ChicksSubscribe and stay tuned for new episodes every weekday!Follow us here for more daily clips, updates, and commentary:YoutubeFacebookInstagramTikTokXLocalsMore InfoWebsite

What if some of the biggest stories we've been told are missing pieces? This week, Dr. Larry joins us to revisit the unanswered questions surrounding 9/11 before diving into the bizarre mystery of Sam Altman's firing and reports of strange, almost religious behavior behind closed doors at OpenAI. Plus, was the Flock camera fiasco a psyop? While everyone was watching the surveillance controversy unfold, something much bigger may have been quietly gearing up behind the scenes. Get MORE Exclusive Ninjas Are Butterflies Content by joining our Patreon:  https://www.patreon.com/NinjasAreButterflies NEW EPISODES EVERY FRIDAY @ 11:15AM EST! Ninja Merch: https://www.sundaycoolswag.com/ Start Your Custom Apparel Order Here: https://bit.ly/NinjasYT-SundayCool Learn more about your ad choices. Visit megaphone.fm/adchoices

Bea and Dee discuss some current pop culture and current event news, plus a lil Sister Wives, too. Let us know on YouTube or IG whether you like the girls talking about these types of things -- and feel free to write in with more hot topics for us to discuss! Get more of their cringey, awesome content at Patreon.com/realitytvcringeFollow us on IG https://instagram.com/realitytvcringeSubscribe to see our raccoon faces on YouTube! https://www.youtube.com/channel/UC_2CgqXLWjIEKV9PCtH3Kjw?sub_confirmation=1Leave a message for us on SpeakPipe: https://speakpipe.com/realitytvcringeSupport the pod by leaving a 5-star review on your favorite podcast platform! Thank you so much.

Story of the Week (DR):Meta settles social media addiction case with California, other states for $16.7 billion MM5 Reasons to Be HappyAn $18 billion payout sets a historic legal precedent against Big Tech, directing billions in state funding toward youth mental health, counseling, and digital literacy programs.Instagram and Facebook must enforce default two-hour daily usage limits and completely block account activity between midnight and 6 a.m. for users under 18. Teens and parents gain the explicit right to disable addictive engagement algorithms in favor of a non-personalized, chronological feed.The settlement prohibits harmful beauty filters (such as cosmetic surgery simulators), hides "like" counts by default, and silences app notifications during school hours.Meta tied $5.3 billion of the payout to whether TikTok and YouTube adopt similar safety rules, forcing an industry-wide overhaul rather than penalizing just one app.5 Reasons to Be AngryPaid out over 10 years, the settlement amounts to roughly 10 days of Meta's annual profit, meaning Mark Zuckerberg's financial empire remains virtually unscathed.Meta's $17 billion child-safety settlement is the biggest tech payout ever—or 3x what it paid to acquihire a 28-year-old AI superstarTo put it in perspective, the $17.1 billion number is a little more than three times the roughly $5 billion personal stake that Alexandr Wang held in Scale AI, a data-labeling company that supplies the human-annotated training data AI models are built on. Last year, Meta paid $14.3 billion for a 49% stake in the company and brought in Wang to lead its AI efforts of its new Superintelligence Labs, reporting directly to Mark Zuckerberg.Meta legally denies all wrongdoing, dodging true legal accountability for intentionally engineering addictive, mentally harmful features.The agreement alters user interface features and screen time, but leaves Meta's underlying data-harvesting business model completely untouched.Critical safeguards—like switching off algorithmic feeds—are opt-in settings rather than permanent defaults, shifting enforcement onto parents.Meta only pays 70% ($12.7 billion) upfront; the remaining $5.3 billion is contingent on competitors settling on identical terms, giving Meta a potential financial discount if rivals refuse. Worst headline of the week: Meta's $17.1 billion settlement will be over 12-times larger than the second largest big tech privacy settlement in the past four yearsMeta's $18 billion settlement leaves out the child protections New Mexico already won at trial, its Attorney General says: including a direct ban on romantic and sexualized AI chatbot interactions with minors and stronger safeguards against adults targeting kids in private messagesMM: Settlement gapsAge assurance:Meta may elect to use one or more Proprietary Age Assurance Methods. In such event, Meta shall not benefit from the presumption of compliance set forth in Section II.A.3.a. Additionally, Meta will maintain continuous oversight of any Proprietary Age Assurance Method sufficient to ensure that the method is functioning as intended.Tax deductibleThe Settling States shall cause to be completed and timely filed a Form 1098-F with the Internal Revenue Service (“IRS”) that identifies not less than 50% of the amounts paid to the Settling States as compensatory restitution and remediation within the meaning of 26 U.S.C. § 162(f)(2)(A)THEY BUNDLED CAMBRIDGE ANALYTICA INTO THE SETTLEMENT$459m of the $17bn is the “Cambridge payout” - they can now put that behind them tooIs there a reason not to literally take Meta all the way? Why settle at all! Midterm elections? TAKE EVERYTHING! Meanwhile, while you settle this: Meta's creepy smart glasses are part of a much bigger plan“At the same time, Meta is using the content generated across its ecosystem to support Mark Zuckerberg's vision of a pervasive, AI-driven future. Zuckerberg's 2026 manifesto describes a world where personal AI agents will do your bidding. But building those systems requires more than conventional AI models. It also requires enormous amounts of data about human behavior, much of it generated and shared through Instagram, Facebook, and other Meta apps, or captured through hardware such as phones, smart glasses, and EMG Neural Band devices.”“We become “algorithm chow,” feeding the models intended to realize Zuckerberg's vision.”'We Know We Got This Wrong': Target Apologises and Pulls 'Offensive' Halloween Costume After Racist BacklashAn apology from us: We pulled an offensive Halloween costume that should never have been part of our assortment. It is no longer for sale. As a company, we got this wrong, and we are deeply sorry. We know this is especially hurtful for our Black guests, team members and partners. Removing the costume is an important first step, and the company is looking closely at how this happened and what needs to change to ensure this won't happen again.Target Statement on Offensive Halloween Costume: As a company, we know we got this wrong, and we are deeply sorry. The costume is offensive and should never have been part of our assortment. It is no longer available for sale. We know this is especially hurtful for our Black guests, team members and partners. Removing the costume is an important first step, and the company is looking closely at how this happened and what needs to change to ensure this won't happen again.The statement comes directly from Target's Corporate Communications department speaking on behalf of the entire enterprise, rather than a single individual like the CEO or Board Chair. Corporate apologies are deliberately released without a human signature for several strategic and legal reasons:Legal Personhood: Legally under U.S. law, Target Corporation is treated as a single legal entity (often called "corporate personhood"). It can sign contracts, hold liability, and issue official statements as an institution rather than as individual people.Leaving executive names off the statement prevents media coverage from focusing on a specific person (e.g., "CEO Brian Cornell Apologizes"). It keeps the focus on the company's operational changes and prevents individual leaders from becoming personal lightning rods for public backlash.These statements are rarely drafted by an executive. They are heavily scrubbed by legal counsel, crisis PR managers, and corporate strategy teams. Attaching a CEO's signature to a text engineered by a dozen lawyers and communications staff can actually feel less authentic internally.Phrasing the apology around "we" and "the company" establishes institutional accountability. It signals that the failure occurred in corporate vetting systems, not just from one bad decision-maker.In January 2025, Target Corporation announced the termination of its REACH initiative and restructuring of its Supplier Diversity program, marking one of the largest corporate DEI rollbacks in recent history. This decision has triggered public backlash, legal scrutiny, and investor uncertainty.Callaway Golf CEO apologizes after Good Good ad showing male golfer shoving woman sparks backlashCallaway Golf CEO Chip Brewer on Tuesday apologized for an advertisement that sparked an online backlash for its depiction of a male golfer shoving a female golfer to the ground when she attempts to use his driver."That approval should never have happened. Mistakes were made, and we are taking the matter very seriously," Brewer wrote on Tuesday. "I want to make it clear that we sincerely apologize for the video." Callaway released a statement Thursday explaining its reasoning behind ending the brand partnership: "Over the last several days, we have reflected deeply on the hurt and disappointment caused by the video we reposted. We heard from individuals who shared personal experiences related to violence against women, and their stories were powerful reminders that this issue touches the lives of far too many people. Unequivocally, violence against women is unacceptable and should never be trivialized, normalized, or used as entertainment.""In this instance, our content review process was not comprehensive enough …We have taken appropriate internal corrective actions and significantly strengthened our approval procedures to help ensure this does not happen again."The brand added that it would donate $1 million to organizations that aim to "prevent violence against women, provide resources to survivors, and advance education and awareness efforts."The online video ad, which was released online and has since been pulled, sparked criticism for depicting violence against women, while some consumers said they planned to stop buying products made by Callaway.Brewer said the ad, created by Good Good Golf, was released last week to promote a co-branded driver and had been approved by Callaway before the spot was posted online. The ad featured Good Good co-founder Garrett Clark telling Alexis Miestowski, a former Division I female golfer, in a menacing voice, "Do not touch my new driver," after he shoves her to the ground.Good Good is an American sports YouTube channel and company based in Frisco, Texas. Founded in 2020 by Garrett Clark, Stephen Castaneda, CEO Matt Kendrick, and Matt Scharff.Owner: Scoreboard ventures: co-founders Nahid Giga and Brian DickLead Investor: Creator Sports Capital — a firm co-founded by former YouTube executive Benjamin Grubbs and investment executive Brian Kabot.Good Good's CEO went nuclear on Callaway after the brand cut ties over an ad scandal"Interesting that @CallawayGolf asks us to make an ad then approves it then asks us to take the fall then drops us in a coordinated media blitz and covers it up by giving a million dollars away thinking everyone will be ok with it," Matt Kendrick wrote in a post on X.The ad fallout has had major repercussions for Good Good's business beyond the loss of its Callaway partnership. Dick's Sporting Goods yanked Good Good products from shelves, and the golf group pulled out as a title sponsor for a PGA Tour event in the fall. The reverberation has spread to the Golf Channel, which scrapped the upcoming season of its reality golf series "Big Break," whose grand prize was entry into the PGA Tour event that Good Good was supposed to have sponsored.FFA:14% have merit2 women! (combined 6% influence)Director Thomas Dundon 56% influence and 10% sharesDirector Nominee Skills Matrix includes “Golf Enthusiast” (9/9)Consumer Products Experience: 5/9Bill Gates Warns Humanity About AI: ‘We Do Not Have the Luxury of Moving Slowly'Bill Gates fears world leaders are unprepared for 3 major AI risks: ‘Stunted' child development; emboldened criminals; and vanishing jobs for Gen Z Bill Gates Issues Stark AI Warning: 'There Is No Plan' for What Comes NextWhat did he say?Gates warns AI will either be the greatest equalizer ever created or the worst source of global injustice, claiming world leaders are underprepared for the social upheaval ahead.He proposes that governments legally set aside "human-reserved" job categories—similar to protected nature reserves—for roles requiring human empathy and connection, such as healthcare and teaching.To offset tax policies that encourage replacing humans, Gates suggests taxing AI processing "tokens" and physical robots to fund worker retraining and stronger safety nets.He categorizes AI's biggest risks into three buckets: permanent job loss, empowering bad actors to launch cyber and biological attacks, and eroding child development.Gates calls for an international AI regulatory agency—modeled after global aviation and nuclear inspection agreements—requiring tight cooperation between the U.S. and China.He claims tech industry executives are downplaying catastrophic AI threats to public safety because there is too much money on the line.Gates warns that agreeable AI companions risk becoming addictive to young people while weakening independent critical thinking.‘We have a limited window': 116 companies, entities sign on to major AI cyber defense pushOpenAI, Anthropic, Microsoft, Advanced Micro Devices and more than 100 other companies and entities signed a letter on Thursday calling on businesses and policymakers to prioritize cybersecurity and “act decisively” to bolster defenses in the age of artificial intelligence.“We have a limited window to strengthen cyber defenses,” the letter said9% female CEOs:Accenture: Julie Sweet (Chair/CEO)AMD: Dr. Lisa Su (Chair/CEO)Citi: Jane FraserClearly AI: Emily Choi-Greene (Co-founder)Equinix: Adaire Fox-MartinFIS: Stephanie Ferris General Motors: Mary Barra (Chair/CEO)Lumen Technologies: Kate JohnsonNationwide Building Society: Dame Debbie CrosbieOracle: Safra CatzRunSybil: Ariel Herbert-Voss (Co-founder)TrendAI (Trend Micro): Eva Chen (Co-founder)Goodliest of the Week (MM/DR):DR: X Users Post Flock CEO's Address and Photos of His Home After He Says Americans Must 'Compromise' on PrivacyDR: Young People Hate AI CEOs So Passionately That It's Almost Hard to BelieveCNBC survey asked over 1,000 US adults aged between 18 and 34 “who do you trust to act responsibly on AI?”Palantir CEO Alex Karp 81 percent “don't trust”Peter Thiel 79% “don't trust”Mark Zuckerberg 71% “don't trust”Elon Musk 70% “don't trust”Sam Altman 69% “don't trust”Microsoft CEO Satya Nadella 65% “don't trust”fared the best — albeit with a pitiful 35 percent “trust” score.DR: Jeff Bezos ordered to reinstate fired Black opinion writer at Washington Post over Charlie Kirk reactionThe ruling Thursday said the newspaper did not have sufficient cause to terminate Karen Attiah, who at the time was the last Black full-time member of the Post's opinion desk. The arbitrator, Sarah Miller Espinosa, also ordered the Post to award Attiah full back pay and lost benefits.After Kirk's killing, Attiah, the founding global opinion editor for the Post and the newspaper's only Black female opinion writer, made several posts to her Bluesky account.Attiah was emailed a termination letter on Sept. 11, accusing her of “gross misconduct.”“Your public comments on social media regarding the death of Charlie Kirk violate the Post's social media policies, harm the integrity of our organization, and potentially endanger the physical safety of our staff,” the letter read.MM: Flock CEO Says Americans Must 'Compromise' on Privacy; Then His Own Home Address Leaked Online DRMM: Starbucks Drops Drink Powder That Enveloped Baristas in Clouds of DustAssholiest of the Week (MM):Meta Settlement and AI earth destruction that has normalized what would have been horrific news, but now we shrug and re-elect the boards - SPEED ROUND! The anti woke: Black Wealth Will Be 4 Times Lower Than Whites By 2050 - SHOULD CAREMen: Real men don't bike: How cars became the symbol of American manhood - DON'T CARECowards: Deloitte to Pay $21.5 Million to End DOJ Fraud Investigation Over DEI Policies - SHOULD CAREEpstein: Ex-Barclays boss denies having sex with woman dressed as Snow White after Epstein emails - SHOULD CAREEpstein adjacent: Elon Musk's xAI used child porn to train Grok models, lawsuit says - SHOULD CAREPay committees: CEOs earn 614 times more than workers at US's 100 lowest-paying corporations - SHOULD CAREClimate change: Study blames fossil fuel emissions for significant loss of American West's water - SHOULD CAREActual death: Turn Around and Don't Look': Amazon Accused of Letting Worker Die in Warehouse Amid 'Corporate Greed' Claims - SHOULD CAREThe anti labor: Disney celebrates blockbuster 2026 by kicking employees' spouses off healthcare plans - SHOULD CAREThe anti homeless: This Palantir Billionaire's Passion Project is Criminalizing Homelessness - SHOULD CAREOther social media companies: TikTok agrees to pay $400 million to settle Justice Department children's privacy case - DON'T CARE“The lawsuit, related to compliance with the Children's Online Privacy Protection Act, was filed by the Biden administration's DOJ in 2024”Headliniest of the WeekDR: Elon Musk's former right-hand man at X will give you 30 minutes of business advice for $15,000MM: BoringTrump Claims Junk Food Is 'Good' and Gym 'Boring' After Doctors Warn He Is 'Playing With Fire'Elon Musk Says He's Not Warren Buffett's ‘Biggest Fan' And Finds His Way of Getting Rich ‘Super Boring' — ‘Does Anybody Want That Job?'MM: What is a 'meat proxy'? The new term for coworkers who blindly share AI outputWho Won the Week?DR: Futurism writer Frank Landymore for this headline: Bill Gates Announces That He Is the First Person Ever to Be Concerned About the Effects of AI after Bill said, “I am in a state of shock that I'm sort of the first one saying, ‘This is crazy. This is insane.'”MM: Watches:Sam Altman's love of watches is getting memed 'Lord of the Rings' styleDespite having a net worth of $400 million, Kevin O'Leary still shops at Walmart for $29 jeans: ‘I'm always looking for a great deal'The picture in the article is him wearing not one, but TWO $15k Rolex watches, one on each wrist - the message: guy who buys jeans JUST LIKE YOU has multiple Rolexes - you should get one too!PredictionsDR: I spend $15,000 for business advice from Elon Musk's former right-hand man at X and he tells me a really clever way to save $15,000MM: French Canadiens, after getting the CEO of Air Canada fired and killing Trump trade talks, decide to make the United States a new Canadian province called New Quebec where French is the only legal language and renames Lake Superior “Lake French Superior”

P.M. Edition for Aug. 27. What happened to the Republican effort to prosecute Dr. Anthony Fauci? White House Correspondent Natalie Andrews discusses why some Trump administration officials are skeptical of the contempt of Congress case against Fauci. Plus, the FAA moves to fire two air-traffic controllers who left work early before a deadly collision at LaGuardia Airport in March. And President Trump signed an executive order to change the name of Lake Ontario to “Lake America.” Sabrina Siddiqui hosts. Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The mates sit down with Emad Mostaque to discuss: whether the singularity is slowing down, Sam Altman's changing views, the case against an Anthropic IPO, Emad's 18 Grokbots, Waymo's massive hardware cost cuts, China's 100x cheaper AI models, NVIDIA's $6B open-source bet, and the increasingly competitive frontier lab race. Sign up for our AMA at http://Moonshots.com/ama Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader. Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified Emad Mostaque is the founder of Intelligent Internet ( https://www.ii.inc )  Read Emad's latest papers exploring the future of society, law, personhood and governance: https://ii.inc/common-wealth Read Emad's Book: https://thelasteconomy.com  – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding   Get the blueprint for generative media https://goo.gle/startupgenmedia  Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: https://www.fountainlife.com/peter  Join the Moonshots Mates on Sep 25th for the inaugural Moonshots LIVE. The world's greatest entrepreneurs, builders and creators, working together to build a hopeful and optimistic vision of tomorrow. Seats are limited and application only. Apply at moonshots.com before seats are sold out. _ Connect with Peter: X Instagram Substack Website Xprize A360 Connect with Dave: Web X LinkedIn Instagram TikTok Connect with Salim: LinkedIn X Join Salim's 10X Shift Subscribe to Salim's YouTube channel Exponential Venture Capital Connect with Alex Website LinkedIn X Email Substack  Spotify Threads Connect with Emad  X LinkedIn Learn about Intelligent Internet Read Emad's Book Listen to MOONSHOTS: Apple YouTube Follow MOONSHOTS:  Instagram TikTok X Threads – *Recorded on August 26th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Reddit… it's the most important company in social media right now, because it's the most different. It's the 5th most visited website in America, the internet's front page, and the most valuable source of content to train artificial intelligence (Sam Altman pays *them*). They've got a partnership with OpenAI… yet the content is anti-AI. And co-founder / CEO Steve Huffman runs the most real company in tech right now… and he's a classically-trained ballroom dancer.In this interview episode, you'll hear…How ballroom dancing is like running a company.The invention of the upvote/downvote.Reddit's version of judicial, legislative, and executive branch.How the CEO of reddit decides when to ban an account.How AI models train by reading reddit.Should Reddit rebrand to “Real”?Or watch on YouTube: https://www.youtube.com/@tboypod NEWSLETTER:https://tboypod.com/newsletter OUR 2ND SHOW:Want more business storytelling from us? Check our weekly deepdive show, The Best Idea Yet: The untold origin story of the products you're obsessed with. Listen for free to The Best Idea Yet: https://wondery.com/links/the-best-idea-yet/NEW LISTENERSFill out our 2 minute survey: https://qualtricsxm88y5r986q.qualtrics.com/jfe/form/SV_dp1FDYiJgt6lHy6GET ON THE POD: Submit a shoutout or fact: https://tboypod.com/shoutouts SOCIALS:Instagram: https://www.instagram.com/tboypod TikTok: https://www.tiktok.com/@tboypodYouTube: https://www.youtube.com/@tboypod Linkedin (Nick): https://www.linkedin.com/in/nicolas-martell/Linkedin (Jack): https://www.linkedin.com/in/jack-crivici-kramer/Anything else: https://tboypod.com/ About Us: The daily pop-biz news show making today's top stories your business. Formerly known as Robinhood Snacks, The Best One Yet is hosted by Jack Crivici-Kramer & Nick Martell. Hosted on Acast. See acast.com/privacy for more information.

A.M. Edition for Aug. 26. President Trump sends his landmark nuclear accord with Saudi Arabia to Congress for review, kicking off what's likely to be months of debate among lawmakers. Oxford Analytica's Rawan Maayeh breaks down whether the kingdom is likely to normalize relations with Israel as a part of the deal, as Trump has insisted. Plus, Bill Gates issues a stark warning on AI's impact on jobs and humanity, saying big tech has “no plan”. And we look ahead to Nvidia's earnings, with sky-high investor expectations for the world's most valuable company. And Luke Vargas hosts. Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Donate (no account necessary) | Subscribe (account required) Join Bryan Dean Wright, former CIA Operations Officer, as he dives into today's top stories shaping America and the world. In this Wednesday Q&A episode of The Wright Report, Bryan answers a listener's question about CIA Director John Ratcliffe's surprise four-hour trip to Moscow, breaking down the likely warning delivered to Putin over Russian sabotage operations in Europe. Bryan answers listener questions on why no Iranian resistance movement has emerged to challenge the regime, whether Trump's "Economic D-Day" sanctions can actually pressure China into abandoning Iran, and which careers are most at risk as AI eliminates entry-level jobs. He also breaks down OpenAI CEO Sam Altman's admission that the AI Revolution is moving slower and delivering less value than promised. Plus, Bryan covers a French gay couple's use of an Arizona surrogate to secure US citizenship for their son ahead of Trump's new birth tourism crackdown, record-breaking deportation numbers for July, the Log Cabin Republicans dropping the "T" from LGBT, and a heartfelt tribute to the late Dolly Parton. "And you shall know the truth, and the truth shall make you free." - John 8:32   Keywords: Wright Report, Bryan Dean Wright, CIA, John Ratcliffe, Moscow, Putin, Russia sabotage, Iran, IRGC, China, Economic D-Day, AI jobs, Sam Altman, OpenAI, surrogacy, birth tourism, France, deportations, ICE, Log Cabin Republicans, LGBT, Dolly Parton

Plus: President Trump's pick Darline Graham wins a GOP Senate runoff in South Carolina to fill the seat of late Sen. Lindsey Graham. And OpenAI loses another top executive. Luke Vargas hosts. Sign up for WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

AlabamaSen. Tuberville says insult by Abdul El Sayeed is typical talk from terrorist sympathizerAG Marshall investigating OpenAI and founder Sam Altman after hacking incidentADECE removes name of controversial speaker from website after 1819 News exposes her LGBTQ advocacyBama Carry launches petition against FLOCK Cameras for violating 2nd amendment rightsState Senator Orr to revisit FLOCK camera policies in state legislatureAlabama launches new statewide emergency notification systemNationalChina weighs in on US sanctions against Iran saying they will defend their interestsRebel News Ezra Levant says Canada Prime Minister prefers China over USWhite House Fraud Task Force finds $13B in fraud within gov programsUS State Dept. to revoke 200K H1 or H2 visas issued from 2016 to dateGirls Scouts Organization now offering badges for those engaging in IslamDanish Researcher to plead guilty to defrauding US research grants for studying vaccines and autismMcCullough Foundation evaluates FDA approval of mRNA flu vaccine

This Week In Startups is made possible by: Odoo https://Odoo.com/twist Quo https://quo.com/TWiST Conservation Fund https://conservationfund.org how old a movie has to be for me to be able to show a part of it on youtube Generally 10 seconds or less of a film clip can fall under fair use for commentary or criticism — which is how most podcasts and talk shows use clips without issue. But there's no hard legal rule based on age. What actually matters more than age is fair use, which considers: Purpose — commentary, criticism, education = stronger fair use case Amount used — shorter = safer; a 5-10 second clip for reaction/discussion is generally fine Effect on market — your clip shouldn't replace the original In practice for YouTube specifically: Most major studios have Content ID systems that will flag clips regardless of movie age — even 100-year-old films if the rights holder has registered them Public domain is the real safe zone — films from 1927 or earlier are generally in the public domain in the US. Some films from the 1928-1963 range are also public domain if copyright wasn't renewed Disney, Warner Bros., Universal etc. actively enforce even very old films For a show like TWiST showing a short reaction clip — 5-10 seconds with clear commentary context is the industry standard and rarely gets actioned. But age alone won't protect you. Today's show: *A humanoid robot ran the 100m in 9.39, breaking the human Usain Bolt's world record, while an entire stadium cheered. Jason thinks Beijing's World Humanoid Robot Games aren't a science fair, or a fun exhibition, but the best AI PR campaign on Earth. While Americans debate the data centers that train the robot brains, China is already turning them into a spectacle and world-class entertainment. Find out what Jason thinks America can do to catch up… and why he believes there will be 1 billion Optimus robots deployed by the year 2036. PLUS on an all-news TWiST, hot takes on the potential $13B Hugging Face sale (to a mystery buyer), why founders should always "buy the threat," analyzing Sam Altman's "I'm listening and I hear you" face, and are kill drones already in operation around the world? We're digging in to how close the real world is to mirroring the "Terminator" films. Relevant Links CBS coverage of World Humanoid Robot Games: https://www.cbsnews.com/news/china-robot-usain-bolt-sprint-run-record-faster/ Bloomberg coverage of World Humanoid Robot Games: https://www.youtube.com/watch?v=0lsrUAdcPPE X-Humanoid: https://www.x-humanoid.com/ Tesla Optimus on X: https://x.com/Tesla_Optimus Trailer for Spielberg's "A.I. Artificial Intelligence": https://www.youtube.com/watch?v=_19pRsZRiz4 Bloomberg: Hugging Face exploring sale: https://www.bloomberg.com/news/articles/2026-08-23/hugging-face-gauging-interest-for-potential-sale-business-insider-says Fortune: Stripe acquires OpenRouter: https://fortune.com/2026/08/16/stripe-7-billion-deal-ai-firm-openrouter-acquisition/ InfoWorld: OpenAI acqui-hires OPenClaw founder: https://www.infoworld.com/article/4132731/openai-hires-openclaw-founder-as-ai-agent-race-intensifies-2.html David Senra podcast w/ Sam Altman: https://www.davidsenra.com/episode/sam-altman Harvey Tenet Research Preview: https://www.harvey.ai/blog/post-training-update-harvey-tenet David Sacks comments on Harvey's Tenet (from X): https://x.com/DavidSacks/status/2090790063047168473 CNBC: Iran linked to UK cyberattack: https://www.cnbc.com/2026/08/23/small-uk-power-plant-shut-down-after-iran-linked-cyberattack-report.html NYT: A drone killed 3 Ukrainians: https://www.nytimes.com/2026/08/24/world/europe/russia-drones-autonomous-ai-kill-ukraine-war.html Forbes: Eric Schmidt secretly testing AI drones: https://www.forbes.com/sites/sarahemerson/2024/06/06/eric-schmidt-is-secretly-testing-ai-military-drones-in-a-wealthy-silicon-valley-suburb/ Restream: https://restream.io/ Kimbal Musk's Nova Sky Stories: https://novaskystories.com/ IKEA: Plug-in Solar Panels: https://www.ikea.com/be/en/energy-services/plug-in-solar/ Deadline: "Mandalorian and Grogu" box office: https://deadline.com/2026/08/star-wars-mandalorian-grogu-disney-release-date-1237040464/ THR: Dave Filoni leading Lucasfilm: https://www.hollywoodreporter.com/movies/movie-news/star-wars-mandalorian-grogu-box-office-franchise-low-1236604973/ Star Wars: Starfighter first look: https://www.starwars.com/news/star-wars-starfighter-ryan-gosling Star Wars Theory: "Vader" fan series: https://www.youtube.com/watch?v=Ey68aMOV9gc Timestamps: 0:00 Jason got a fresh Optimus demo 1:35 Robots are breaking human sports records 3:39 America's messaging problem vs. China's elite PR machine 11:07 Odoo - The all-in-one business platform. Your first app is free! Get started today at https://Odoo.com/twist 12:08 Jason got a fresh Optimus demo 19:21 Quo (formerly OpenPhone) - Quo gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free and get 20% off your first 6 months at https://quo.com/TWiST 28:09 Who's going to buy Hugging Face and why? 28:56 Conservation Fund - Find out more about how the Conservation Fund is protecting land, wildlife, and our shared access to the great outdoors while also providing economic opportunities. Visit https://conservationfund.org 31:35 How OpenAI killed OpenClaw 39:08 Sam Altman wants to make a platform, not a product 41:19 The "Castles and Keeps" metaphor for sovereign AI 49:27 UBI isn't happening but we could raise the minimum wage 58:47 Embracing redundancy and self-reliance 1:10:53 Is Star Wars at a historic low point (and Lon's Worst Take) Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

GUnitedHealth shareholders sue company over ‘corporate governance failures on a historic scale' UBS fined record $125 million for money laundering violations$125 million civil penalty to the U.S. Treasury's Financial Crimes Enforcement Network (FinCEN) for willful violations of the Bank Secrecy Act (BSA), the primary U.S. anti-money laundering law.FinCEN said the fine is the largest ever assessed against a broker-dealer for BSA violations.The settlement marks FinCEN's second enforcement action against UBS Financial Services, a subsidiary of the Swiss bank UBS. The firm had previously paid a $14.5 million penalty in December 2018 for similar failures, including inadequate monitoring of foreign currency wire transfers.Despite assurances to regulators that it would fix the underlying problems, the firm subsequently failed to monitor more than 50,000 foreign currency wires with a combined value exceeding $10 billion.SEC launches new enforcement unit aimed at accounting fraudHow??The unit will be housed within the SEC's Division of Enforcement and staffed by both attorneys and accountants with specialized skills related to financial reporting, accounting, and auditing in securities regulation, according to the announcement.The announcement is “a little surprising” given the SEC's current deregulatory focus under Chair Paul Atkins, Rebecca Fike, a partner in Reed Smith's regulatory and enforcement group, told CFO Dive.Andreessen Horowitz Focus of DOJ Probe Over Board DirectorsBIG DATA and AI BS‍ ‍Gwyneth Paltrow is rumored to be throwing a party for AI mogul Sam Altman. People don't love the opticsPaltrow played WeWork Rebekah NeumannAnthropic is embedding invisible watermarks in Claude text and images Young People Hate AI CEOs So Passionately That It's Almost Hard to BelieveCNBC survey asked over 1,000 US adults aged between 18 and 34Asked “who do you trust to act responsibly on AI?” the vast majority of participants said they “don't trust” any of the nine figures.Palantir's extremely controversial CEO Alex Karp scored the lowest, with 81 percent choosing “don't trust,” while Microsoft CEO Satya Nadella fared the best — albeit with a pitiful 35 percent “trust” score.Everyone else fell in between: 79 percent of respondents said they don't trust Peter Thiel, while a whopping 71, 70, and 69 percent said they “don't trust” Mark Zuckerberg, Elon Musk, and Sam Altman, respectivelyMeta, others lose appeal to drop thousands of social media addiction lawsuitsA U.S. Appeals Court [Judge Jacqueline Nguyen] said that thousands of lawsuits targeting Meta Platforms, ByteDance's TikTok and other social media outlets over claims that social media is harmful and addictive can proceed.The court also denied Meta's request to postpone a trial over allegations that they used data from children to keep them on its platforms.AI data center outrage is showing up everywhere from ads to electionsSpirit Flight Attendants Fight Google's Data Bid for AIThe flight attendants want assurance that their confidential information will be removed from the sale of the defunct airline's digital recordsCULTURE WARSThe 'MAGA Alternative to Amazon' Is Fighting for Survival After Nearly $160M in Losses and 99% Stock CrashPublicSquare's marketplace has struggled to grow despite political backing, prompting a costly shift to financial servicesDisney is suing the FCC in a departure from former CEO Bob Iger's strategy US firms that kept DEI policies despite ‘go woke, go broke' threats thrived Ellison Is Now Willing to Sell CNN to Save His $111 Billion DealE Solar Panels on Storage Units: Illinois Is Going All In on This No-Brainer First test flight of largest all-electric aircraft used just $5 of electricity Trump ordered to release billions in climate grants meant for Black communitiesa $2.8 billion program meant to help mitigate the harm from climate change and environmental issues in Black, low-income, and disadvantaged communities.Trump tried to curb clean energy. It's booming anywayClean energy additions will rise by a record 45 gigawatts this year, according to S&P Global Energy—equivalent to the average electricity demand of Turkey. The increase is roughly 25 percent higher than the record set in 2024.It Just Got Way Easier to Sue Fossil Fuel Companies Over Climate ChangeClimate attribution scienceA new peer-reviewed study published earlier this month in Earth's Future suggests that it is possible to demonstrate that “emissions from company X cause injury Y.”It also could potentially provide evidence so industry could be forced to answer for climate impacts.The new methodological framework has, for the first time, drawn a straight line from single corporate emitters like Exxon or Chevron, or even whole countries like the United States, to specific heatwaves and areas of extreme rainfall.By running over 150 simulations across 8 different climate models, the study's author, Christopher Callahan—an Earth systems scientist and assistant professor at Indiana University's O'Neill School of Public and Environmental Affairs—built a statistical model to figure out the relationship between the amount of carbon dioxide in the atmosphere and the odds of extreme heat or rain. He then used real emissions data to calculate the extent to which specific fossil fuel emitters increased the risk of extreme weather.SPEED ROUND‍ ‍DuckDuckGo Is Selling Anti Pervert Glasses That Contain Zero AI, Cameras, or Even Electronics Whatsoever Jason Kelce Wants Fans to 'Pee on Computers' to Protest AI Water Use: 'We Want Your Pee' Cards Against Humanity Unveils 'Sad Little Bitch' Elon Musk Monument Near Texas StarbaseFrance bans unsolicited telemarketing calls--$87,000 fine per call I'm the CEO of Siemens. I reply to most emails with 2-letter responses and don't have recurring meetingsScientists Genetically Engineer High-Protein LettuceGen Z is bringing pen and paper back to the workplaceArianna Huffington says even high-flying CEOs are unhappy and feel stuck in their multimillion-dollar jobs: ‘It's a trap'Bank of America is splashing out $250 million a year on weight loss drugs for its staff: ‘We see a great impact on employees,' CEO says‘We see a great impact on employees,' CEO saysExcuse me? Body shamer.

Lauren's guest is Sophia Rivka Rossi, author of Between Friends. They discuss summer 2026 fitness trends, the Foster sisters, why they don't shop at J.Crew, Gwyneth Paltrow's upcoming Amagansett dinner for Sam Altman, Charles Porch, Emily Oberg, kitten heels, 501s versus 505s, and plenty more.

The AI race isn't being won in the model lab — it's being won in the power grid. And right now, America is losing. Motley Fool analyst Rachel Warren talks with Hannan Happi, co-founder and CEO of Exowatt — backed by Sam Altman and Andreessen Horowitz — about why the AI build-out is hitting a wall that no amount of chips or software can fix. They get into why a one-year grid delay costs a hyperscaler $12 billion in missed revenue, why China has 10 times more capacity than the US to build AI infrastructure, and what investors need to actually be tracking as hundreds of billions of dollars flow into the AI build-out — including whether the data centers being built today will still be operating in ten years.  Host: Rachel Warren Guest: Hannan Happi Producers: Dennis Golin, Lauren Budabin  Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

BEST OF: After our “AILIEN The Final Card” show, it became apparent that the push to grant mass “amnesty” to every person and agency involved in black budget programs was a dangerous narrative gaining more traction by the day, and now compounded by an executive order from the White House titled “Launching the Genesis Mission.” This program seeks to support, along with the AI regulation moratorium of the BBB, the narrative that “America is in a race for global technology dominance in the development of artificial intelligence (AI).” The first section states: “the challenges we face require a historic national effort, comparable in urgency and ambition to the Manhattan Project that was instrumental to our victory in World War II.” But what suddenly changed? Have other countries cracked the AI egg entirely or has, as the UFO community suggests, they reverse engineered alien tech fully? Even so, a dangerous nationwide Manhattan Project should be a secret, not a public initiative. One part of the EO says the goal is to develop "AI-enabled predictive models, simulation models, and design optimization tools,” things that have been sold to the public over and over again, from climate change to pandemic models, but which have all been wrong. But if AI says something is true based on a model, it must be correct. However, if AI is merely saying what is most likely based on current actions, like a tarot reading, then if all current policies are designed for war then isn't that what we will get? Isn't that what Alex Karp of Palantir said would happen? And isn't “Genesis” also “skynet”?For those left waiting for something “big” to happen it will be disappointing to learn that it already has. Engineered smart/micro-dust is currently turning the world into a giant sensor, while Sam Altman of the Stargate Project, OpenAI, and the Orb, is now funding CRISPR-based embryo gene editing as the alterer-of-man.And to keep us entertained during this slow-burn apocalyptic invasion, we have KION, an AI-created K-pop star who's clearly created with all he best black goo moments from Taylor Swift, Lady Gaga, Billie Eilish, and the like. It all makes sense if the gift of “UFO technology” may in fact be a series of blueprints to build the alien mind on earth; the name KION, from various languages, translates to ancient-foundation-leader-possessed. In other words, Lovecraft's Old Ones once more. But IT is being sold as a sexy black goo princess. *The is the FREE archive, which includes advertisements. If you want an ad-free experience, subscribe below. 

New studio, same chaos. Dylan and Sam Tripoli return after a few weeks off to break down one of the show's biggest theories yet: that dragons weren't myth, but a real species written out of the historical record. They trace dragon accounts from Alexander the Great's reported sighting in a cave after invading India, to Marco Polo's travel logs, to Saint George's documented dragon slayings across three continents — and lay out the theory that the Catholic Church suppressed the truth to protect its own claim to power. Along the way: the case that dinosaur bones were first identified as Nephilim giants, the Chinese zodiac's one "fake" animal, and a Leviathan-Godzilla connection tying it all to ancient sea monster cults. Also this episode: Dark Smith's ongoing Gulf War Syndrome saga, Nancy Mace's tattoo collection, and a breakdown of Mark Zuckerberg's "personal superintelligence" pitch and what it means for surveillance, censorship, and comedy on Instagram. New studio is live — let us know what you think in the comments. Grab Tickets To Sam Tripoli's Live Shows At: https://samtripoli.com/events/ Lawerence, KS: 9/17-9/19  Tulsa, OK: 10/9-10/10  Dallas, TX: 11/07 New Orleans, LA: 11/13 - 15 Austin, TX: DEC 11th-13th: Buy Our Merch or Sam Will Fight You: https://conspiracy-social-club-aka-deep-waters.myshopify.com/ Subscribe to the Patreon: https://www.patreon.com/AkaDeepWaters Check out Dylan's instagram - @dylanpetewrenn Check out Deep Waters Instagram: @akadeepwaters Check out Bad Tv podcast: https://bit.ly/3RYuTG0 Ad-free, uncensored episodes: Patreon.com/CSC  THANK YOU TO OUR SPONSORS: Hims.com/CSC for a free evaluation  MenGoToMars.com for 50% Off  Mood.com Promo Code CSC for 20% off your first order 0:00 New studio reveal 0:14 Comet of the Week 0:18 Dark Smith's Gulf War Syndrome saga 0:49 Dragons: were they real, and why the cover-up 0:55 The Chinese zodiac's one fake animal 0:59 Alexander the Great's dragon sighting in India 1:01 Marco Polo's dragon encounters 1:02 Saint George and the Catholic Church cover-up theory 1:05 Ancient texts on dragons vs. elephants 1:08 Leviathan, Godzilla, and ancient sea monster cults 1:08 Nancy Mace's tattoos 1:12 Nancy Mace vs. Sam Altman 1:18 Zuckerberg's "personal superintelligence" and AI censorship

In episode 2113, Jack and guest co-host Sofiya Alexandra are joined by co-host of Pod Yourself A Gun & Mad Yourself A Man, Vince Mancini, to discuss… Gwyneth Paltrow Allegedly Hosting “Off-The-Record” Sam Altman Dinner, GTA VI Incentive Being Used to Get Soldiers to Reenlist, Dirtbike Hero, Wait Turtles Is Birds? A Janky Cartoon About A Cow Is A Surprise Box Office Hit In China and more! Gwyneth Paltrow is rumored to be throwing a party for AI mogul Sam Altman. People don’t love the optics Gwyneth Paltrow’s Goop Has Embraced Tech for Years. Now She’s Hosting Sam Altman at Her Hamptons Home Gwyneth Paltrow allegedly set to throw dinner in honor of Sam Altman Gwyneth Paltrow Just Goopified Drone Warfare If Your Business Doesn’t Offer Workers a 401(k) Plan, Maybe Now Is the Time Anduril Partners with OpenAI to Advance U.S. Artificial Intelligence Leadership and Protect U.S. and Allied Forces Anduril eyes major Israeli defense deals, expanding partnership talks during CEO's visit From Goop to ‘Gwynocide’: why is Gwyneth Paltrow starring in a luxury Israeli real estate ad? Army unit offers 4-day pass to play Grand Theft Auto VI as reenlistment incentive Dirt bike rider leads police on erratic chase through Los Angeles County What, Exactly, Is a Turtle? Niu Lai full movie (Bootleg) ‘Bad in every aspect’: derided low-tech animation Niu Lai rivals blockbusters at Chinese box office Movie that went viral for terrible animation becomes China box office hit Chinese Animated Feature ‘Niu Lai’ Turns Online Mockery Into Big Box Office Bucks Low-Budget Animated Movie About A Cow Gets So Popular Theaters Are Using Ridiculous Hand-Drawn Posters Niu Lai (lit. Cow Come) was released without a press kit. Movie theaters in China have begun making their own posters. Director of ‘bizarre’ Chinese film Niu Lai says creators didn’t want to let precision get in way of story 'Niu Lai': Chinese Animated Movie Mocked Online Turns Into Box-Office Sensation How ‘disaster’ film Niu Lai became a hit in China—hand-drawn posters, $47 budget China’s Ugliest Movie Is a Gen Z Masterpiece China’s most ridiculed animation ‘Niu Lai’ is the resistance against AI slop that we need China Lands in Cannes With Robots, AI Films and a Very Clear Message 'Morbius' memes helped give the movie more buzz. But it bombed in theaters after re-release. LISTEN: Vibe (If I Back It Up) by Cookiee KawaiiSee omnystudio.com/listener for privacy information.

This Week In Startups is made possible by: Superhuman https://Superhuman.com Sentry https://sentry.io/twist Lightfield https://lightfield.app Today's show: Jason's been saying it for years now (and we've got an All In clip from 2023 to prove it). Open source will win the AI race. This week gives us a major evidence point, as $11B legal AI company Harvey released its own in-house model, trained on an open-weight Kimi K3 base. Harvey made a proprietary specialized solution without having to risk sharing its precious expert-compiled data with the major frontier labs. PLUS we're checking out the FREE AI dictation app Willow with co-founder Allan Guo, and finding out how he plans to compete with giants like Wispr Flow and Apple. AND we've got the Stanford student who built an automated golf cart and gave luminaries like Jensen Huang and Sam Altman rides around campus. Guests Allan Guo on X: https://x.com/_allanguo Willow: https://willowvoice.com/ Ethan Goodhart: https://x.com/EthanGoodhart Sign up for the Wind TestFlight: https://testflight.apple.com/join/zZqmhhwf Relevant Links CNBC: OpenAI "will be a public company in 2027": https://www.cnbc.com/2026/08/19/open-ai-ipo-timing-2027-friar.html OpenAI Zero Data Retention Pledge: https://openai.com/index/our-commitment-to-zero-data-retention TWIST (June 2026): Jason comments on OpenAI and training data: https://youtu.be/o3eow1nTrcI?si=orungk7OmplOuyio&t=742 All In podcast (Feb 2023): Jason comments on open source vs. frontier models: https://youtu.be/PVgBWV2bvLs?si=j6y7sHS0wx9q09oa&t=5173 Harvey: https://www.harvey.ai/ Harvey Tenet Research Preview: https://www.harvey.ai/blog/post-training-update-harvey-tenet Fireworks AI: https://fireworks.ai/ Wispr Flow: https://wisprflow.ai/ Pipedrive: https://www.pipedrive.com/ Nvidia Jetson Thor: https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-thor/ OpenAI shares Wind golf cart clip: https://www.tiktok.com/@openai/video/7645336713472134431 Starlink Mini: https://starlink.com/mini-product-us?srsltid=AfmBOorzM7arxhdzYAdDpH6RGD4LLg9WV_BFnEoLuYieuHuGSCjQTE1Y Toro mowers: https://www.toro.com/ 404 Media: https://www.404media.co/ Punchbowl News: https://punchbowl.news/ Semafor: https://www.semafor.com/ Skift: https://skift.com/ Newcomer: https://www.newcomer.co/ Deirdre Bosa on YouTube: https://www.youtube.com/@deebosa Electrek: Genesis GV90 review: https://electrek.co/2026/08/20/genesis-gv90-luxury-coach-doors-images/ Toyota Alphard gallery: https://global.toyota/en/mobility/toyota-brand/gallery/alphard.html The Clash "London Calling" video: https://www.youtube.com/watch?v=EfK-WX2pa8c Timestamps: 0:00 What is Jason's Grok Bot up to? 5:17 Systems over goals 9:43 Superhuman - Superhuman Go is an AI chat that's always there when you need it, already aware of what you're doing, and doesn't ask you to start from zero. Sign up to get the best in AI at https://Superhuman.com 13:08 OpenAI will go public soon 14:19 Top line ARR matters way less than churn 20:43 Sentry - Your team should be focused on shipping features — not chasing down bugs. New users can get $240 in free credits when they go to https://sentry.io/twist and use the code TWIST 29:55 Lightfield - Name one person who's ever enjoyed updating a CRM. Exactly. Lightfield's AI agent does it for you — it even prospects and books your meetings. Used by thousands of startups. Free at https://lightfield.app 30:52 Harvey launches Tenet 34:32 "Open source is going to win it all" 35:58 Allan Guo of Willow joins 39:18 Managing a single source of truth across a team 47:00 Lon and Jason love the Toyota Alphard 51:00 Stanford student and AV expert Ethan Goodhart joins 1:00:09 How Ethan got Jensen Huang to go for a ride 1:00:37 Punk Rock 101 1:06:24 Phoebe Gates' secret Harvard class Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis   Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

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

Hello EICroquettes! We are so back and Oenone has fallen for a new conspiracy, it's like we've never been away. We're bursting to the seams with two weeks of what we've been loving: from memes to literature - as always, we're across it all. Enemy of the pod Sam Altman has found himself as the subject of a hilarious (and believable to some) series of memes created by Frosted Jake. Is this the ultimate punch up? Or did Frosted Jake inadvertently create a pitch perfect ChatGPT ad?Once again, the world of literature has been dominated with discourse around AI use in publishing. Have we ushered in a new era of AI witch-hunts? And why are non-white authors being disproportionately targeted? We also discuss the tragic news of Dr Jason Arday's death and consider the responsibility of the media's reporting around it. We know that this is an upsetting topic - so we just want to give you a heads up that this comes at the end of the episode. Have you been at the Edinburgh Fringe? DM us with your dispatches: we want to hear about the best shows, your favourite new talents, and if any of you saw Amanda Knox's show. LINKS:SUBSTACK GOOD LAW PROJECTJason Arday, ex-Cambridge professor at centre of plagiarism row, found deadNathan Cofnas, the man at the centre of Arday plagiarism row, was dismissed for views on raceLauren's postJake Schroeder Hosted on Acast. See acast.com/privacy for more information.

Artificial Intelligence (AI) seems to be taking over the world, especially when the written word is involved. But is it the end-all, be-all answer to your grant writing woes? Can you trust it? Should you use it? Truthfully, there's a lot to weigh, and there is no clear-cut answer.   JOIN THE FUNDRAISING HAYDAY COMMUNITY: Become a member of the Patreon   CHECK OUT TODAY'S SPONSOR: Encore Institute for Social Impact They partner with nonprofit organizations to secure funding, develop actionable strategies, strengthen capacity, and demonstrate results. From health care and human services, to education, youth development, and more, they're experts in helping organizations maximize their missions!   SHOW NOTES: Corporate Gossip Podcast Episodes about Open AI and Sam Altman Open AI & Sam Altman's Sad Sack Bond of Goons – August 16, 2026 Sam Altman & Open AI Part 2: King D*ick of Liar Mountain – August 29, 2025     Article “Demystifying the New Dilemma of Brain Rot in the Digital Ear: A Review” Demystifying the New Dilemma of Brain Rot in the Digital Era: A Review   Article “Energy, water use and pollution of AI and data centers rival most countries” Energy, water use and pollution of AI and data centers rival most countries | PBS News

How can you get your books surfaced when readers ask an AI what to read next? What are the hallmarks of authors and businesses that last more than a decade in the indie author industry? Ricardo Fayet gives his marketing tips after more than a decade at Reedsy. In the intro, Expanding Your Book's IP through Merchandising [Wish I'd Known Then]; Guide to writers conferences [Kindlepreneur]; Rick Rubin and Stephen Pressfield on resistance and the muse [Tetragrammaton]; Pulitzer Prize winners disclose AI usage [Nieman Lab]; My new rebuilt fiction site JFPenn.com. Today's show is sponsored by Draft2Digital, self-publishing with support, where you can get free formatting, free distribution to multiple stores, and a host of other benefits. Just go to www.draft2digital.com to get started. This show is also supported by my Patrons. Join my Community at Patreon.com/thecreativepenn Ricardo Fayet is the co-founder and chief marketing officer of Reedsy, a marketplace for writers to find vetted freelancers, author training courses, and lots more. He's also the author of How to Market a Book and Amazon Ads for Authors. You can listen above or on your favorite podcast app or read the notes and links below. Here are the highlights and the full transcript is below. Show Notes How AI search actually finds and ranks the books it recommends Why keywords and search volume are disappearing as marketing metrics Building an internet footprint so your book is worth recommending Why Claude leans on Goodreads while ChatGPT and Gemini lean on Reddit Product is more important than marketing, and how to find your comp titles Passion, business sense and resilience in the authors who last You can find Ricardo at Reedsy.com. Transcript of the interview with Ricardo Fayet Jo: Ricardo Fayet is the co-founder and chief marketing officer of Reedsy, a marketplace for writers to find vetted freelancers, author training courses, and lots more. He's also the author of How to Market a Book and Amazon Ads for Authors. So welcome back to the show, Ricardo. Ricardo: Thank you, Jo. It's been a while. Jo: It has been a while. As we were saying, it's been a decade, which is crazy, because you and I see each other at events and things. For anyone who doesn't know you— Tell us a bit more about you, where you're from, and also, what is Reedsy these days and how have things changed? Ricardo: Yes, sure. I think I'm hard to dissociate from Reedsy because my only background really is Reedsy. We started Reedsy right after business school for most of the founders. There are four founders, and I'm one of them. We've been going since 2014, so it's been 12 years. We started around the same time, and you started even earlier than we did, but we've had the chance to meet at quite a few conferences since. I think the main thing we're still known for is our marketplace. Since the very beginning, Reedsy is a curated marketplace where authors can come in and look for editors, cover designers, marketers, ghostwriters, literary translators, author website designers, pretty much any freelancer you would ever need to hire throughout your writing career. That's how we started. That's our main source of revenue and our main business. Since then, as you mentioned, we've also added courses, live events, so we've got a membership under Reedsy Learning. The main thing we're proud of right now is our writing tool, Reedsy Studio, because we've been pouring a lot of engineering talent into it over the past five, six years, and I think it's a really cool writing tool that is 90% free. It also does the formatting, so it's a good alternative to Vellum or Atticus for those who haven't purchased those tools. So there's a lot of things that Reedsy does at this point, which always makes it hard for me to describe what we do. Jo: But you generally serve writers. That's probably the crux of it. Ricardo: Exactly, yes. We're mostly at the production stage. The thing we say is we help authors make beautiful books, right? That's a little bit the tagline that applies to 90% of what we do, though we also help a little bit with the marketing side of things. Jo: And then just tell people where your accent is from. Ricardo: So I'm half French, half Italian from my parents, and I was born in Spain. So depending on my mood and the moment, it might be anywhere from French, Italian, Spanish. It's anyone's guess, really, at this point. Jo: Yes, exactly. You've been part of the indie author ecosystem, as you said, since 2014. You're often at the author conferences, and you stay abreast of everything that's going on. So what are the biggest changes you've seen in the industry since you started out? Like you said, you guys came from business school. You chose to come into the industry at a particular point, and yet things have changed. So what do you think are the biggest changes, and how have you seen authors adapt? Ricardo: It's crazy, the amount of things that happened in the past 10 years. Obviously we came into the industry as a result of Amazon launching Kindle Direct Publishing, and then the Kindle Store becoming one of the number one places where people buy books. That's what enabled self-publishing in the first place as an industry, and obviously we wouldn't exist without self-publishing being a thing. But then I think probably one of the biggest changes that happened was the introduction of Kindle Unlimited and various other subscription models. Perhaps as a response to that, afterwards, I would say direct sales is the other massive change that happened in the industry. The ability for authors to sell direct to their readers via their websites, or running Kickstarters, or basically the ability to reach your customers directly. Now, obviously, artificial intelligence is probably the biggest change of them all, not just in publishing, across every industry, but of course it's going to affect publishing very strongly, or it has already started making big waves. So I would say those are the three main changes that we've seen happening in the industry. Jo: Just interestingly, given that you're French, Italian, Spanish, European— Has the pace of change been the same in mainland Europe? Because you and I have also met up at European conferences, but I just get the sense that each individual European country, the UK included, as I include the UK in Europe, goes at a different speed. Ricardo: No, they definitely do. Our market at Reedsy is all in English. We only have an English website, and I would say 70% of our market is US, then 15% UK, and then Australia, New Zealand, et cetera. We do have clients in continental Europe, but they're mostly going to be American or British expats. A lot of retired people who write books and use Reedsy services. I think the main reason for that is that self-publishing as an industry hasn't really grown in Spain, France, Italy the way that it's grown in the US and the UK, probably because these are countries where book buying habits are a lot more traditional. So all my friends from high school and university in France, they all buy books, they all buy paper books. They all buy from bookstores. They don't really buy from Amazon that much. They love the smell of paper, all these sorts of things. So obviously that makes it harder for indie authors in those countries because they cannot place their books in the places where people buy them, which is traditional brick-and-mortar bookstores, or at least it's much harder. So there is an indie movement in those countries, but it's much smaller. I would say Germany is maybe the exception in Europe, where I've seen more and more full-time indie authors, but I don't think it's a market that's comparable even to the UK. Jo: Interesting. Okay, so let's go to marketing, because you love marketing, you have a newsletter about it, and you have a book, How to Market a Book, same title as mine, and we've found each other in our Also Boughts over the years. You have, however, updated yours several times. 2025 was your last update. Mine was 2016, so yours is definitely the most up-to-date one. So what are your thoughts on how authors can reach readers now? And let's split this into two. Let's start with some tips for new authors who just have maybe one book and are really just starting out. Ricardo: Yes, first of all, sorry for stealing your title. Jo: Oh, you know, it's never been a problem. Ricardo: We were trying to come up with something… I know, I know, I know. But still, we wanted something more original, and then we realised that for SEO purposes, that's the title we should really go for. The good thing is, if you search “how to market a book” on pretty much any retailer, you're going to find your book or mine in any order really, but those are going to be the top two books to this day, thankfully, so I'm good with that. I think in terms of marketing tips for new authors who have just the one book, I'd say, despite all the changes in the industry, the basics of marketing still stay the same. One of my big mantras when it comes to marketing is that product is more important than marketing. So having a great book is going to be more important, in my opinion, than being a great marketer. Having a great product. By that, I generally don't talk about literary value or prose or anything like that, just because I'm not a book critic. I'm not an editor. My opinion on whether a book is good or not is worth zero. From a marketing standpoint, for me, a good book is one that resonates with its intended audience. So the first step for newer authors is to basically figure out who they wrote this book for, right? Have an idea of who their target market is. A great way to do that, without entering into marketing jargon like proto-personas and stuff like that, is to think in terms of comp titles, comparable titles. I think that's probably the base of any marketing, whether traditional publishing houses or indie authors, to think, “Okay, which other books out there are similar to mine?” If your book is completely unique, you have, I would say, 99.9% chance of not selling, because your market doesn't exist, and 0.01% chance of creating your own market and completely dominating it, right? So being unique is not necessarily a bad thing, but I would say 99% of the time, it is. Obviously being unique within an existing niche, within an existing market, that's completely different, but you need to work on some comparable titles. So I would say that's where I would start, and that's one of the things that AI is great at. If you even just plug in your book into an AI chat that has enough context, if you're comfortable doing that of course, or if you plug in a synopsis, like a long synopsis, you can basically ask the AI chats, “Okay, what would be some comp titles?” Either you'll have heard of those books, and you'll think, “Okay, they're good comps,” or you may not have heard of them, in which case I would really recommend buying them and reading them and seeing whether they're comps or not. I think that's where marketing starts. Jo: Yes, and we might come back to that for book discoverability. Well, let's just talk about it now, because I now pretty much use Claude for discovering books as well. I just find that the Amazon search, for nonfiction it works really well, right? As you said, if you want to learn how to market a book, you just search “how to market a book”, and our books are very well titled for that. But for fiction, it's so difficult to find new books and comp titles, especially if you don't write in a clear genre, which I don't. I know lots of people do. So we're writing cross-genre. So in terms of book discoverability, I know you've been looking into SEO for books and all of that. What are your thoughts on how authors can more effectively have their books surfaced if people are using the AIs for finding books? Ricardo: That's a very big topic. That's one of my favourite topics right now. That's what I talk about in my marketing newsletter, and I want to start a Substack on the topic as well, because I think it is the future of book discoverability. As you say, search on Amazon isn't great, and if it's not great on Amazon, you don't even want to imagine on Google Play, Kobo, all these sorts of places, right? If you search on Kobo or Apple Books or Google Play for witch cozy mysteries, the top 10 books are going to have exactly “witch cozy mystery” in the title or the subtitle or the series title, right? Jo: Yes. Ricardo: Search is very simple on those sites, so it's very easy to game, but it's terrible as an experience for readers. So I do think that a big part of search is going to move to AI, and now you have Rufus within Amazon itself that appears as a chatbot and encourages you to talk with it, to ask for recommendations. In the beginning Rufus was really terrible, but now I recommend authors play with it. In general, I recommend when it comes to AI discoverability that authors play with all the AI search tools. So it's going to be Claude, ChatGPT, Gemini, Google's AI Overviews and AI Mode, Rufus within Amazon. Just like we talked about comp titles, right, ask for something like, “What would you recommend for fans of this book? Which other books would you recommend?” Or if you're looking for something specific that describes your book, what books would you recommend on… I think one of your examples was fiction around masonry or something like that, right? Jo: I always say, for example, if you ask for action adventure thrillers on pretty much anywhere, you're going to get 20 books by male authors. For those of us who are female authors, but also who have female main characters, you can then be far more granular. That's just not something that necessarily works on Amazon. So, action adventure thrillers with female protagonists written by female indie authors, which is very specific. That will work in AI, whereas that definitely won't work on Amazon. Ricardo: Exactly. So one of the great things about AI search, and terrible things at the same time, is that the concept of keyword is lost, right? So we title our books How to Market a Book because the keyword that people would search for is “how to market a book”, or “book marketing for authors”. Those were the two keywords that had the biggest search volume if we looked at Google Keyword Planner, or any search tools that give you keyword volume. When it comes to AI search, since it's conversational, and it's very personalised, and it can go as niche as you want, keywords are going to disappear, and search volume as a metric is going to disappear. The search you just told me about, maybe there are 10 people who are going to run it exactly. Most people are going to run variations of that. Since you can go as granular as you want, it's going to be very long phrases, very long sentences. So the whole concept of keywords, search volume, SEO, is going to disappear in favour of what some people call GEO, generative engine optimisation, AIO, AI optimisation, AI search optimisation. There's a bunch of names for it, but it is a different discipline. It still works on the basis of Google SEO because what most of these search engines will do is they're going to search the internet, right? They've been trained on a lot of information, but not all of that information is current. Most of these models have been trained on documents and web pages before 2021. That's why when you used the very early versions of ChatGPT, and you asked it about current events or current books, it didn't find it. It didn't have that information. Now all these models have the ability to search the web, and they do that really effectively. So the first thing they're going to do if you run a search like that is they're going to run dozens of different searches on Google or a similar search engine. Action thriller books with female protagonists. Action thriller books with female protagonists by indie authors. Action thriller books by indie authors. They're going to create what I call a corpus, so a massive document of information with candidates, books that probably meet those criteria that they have found through regular web searches. Then they're going to go through all those books and determine which are the most relevant to recommend, and they'll return with that. Then they'll usually have a verification layer as well, which is, okay, I have these five books that I want to recommend to this user, but I just want to make sure first that they are written by indie authors, that they do have a female protagonist, et cetera. And if I'm not able to verify that, I'll flag it in my answer to them. So there are these three layers. Web search, then ranking of the book candidates, and finally a verification layer, and then they serve you the answer. Obviously, that's really powerful. If that's the way that search is headed, which I firmly believe, then we as authors need to learn how to get our books in there. Jo: Yes. It's so interesting, and I do this all the time. Really niche stuff, like a thriller about anatomical Venuses, which are these models from anatomy museums and stuff like that, with an edge of the supernatural. What is brilliant is that you can find the books that come up. I actually got one that I read and reviewed, and it was fantastic. So I love the more granular thing, but we're really in the very long tail now, right? It feels like you can write a very nuanced book, and it will be surfaced, but only by a few people. So do we have to write our books and then try to not even retrofit them in the way that we used to? We used to try and figure out the seven keywords and all of that kind of thing, and now I almost feel like we just get to be grownups, where you just get to write the book and put it out there, and these things are more intelligent than the search terms. Ricardo: Yes, absolutely. I think in terms of the variety of books that are going to be read and discovered, that's amazing. A little bit like the whole indie publishing movement was amazing, because if you remove the traditional publishing gatekeepers, then suddenly zombie books aren't dead anymore. Zombies are alive again. They've… Jo: Come to life. Ricardo: They've come alive, and so you get a bunch of zombie books again. It's not a small niche audience. It's actually a pretty big niche audience that loves zombie books, and suddenly they have those to consume. This is a little bit similar on a much, much bigger and more granular scale, because anyone can find exactly the kind of book that they're looking for, with the tropes they want, with the type of characters they want, with the type of author they want, and you can basically use any kind of filter. So for discoverability on the side of the reader, that's great. For the authors, it doesn't mean that you can just write whatever you want and then rest, and readers will find them. Because your books still need to have generated a certain internet footprint and a certain review footprint in order to become interesting or recommendable to AI search engines, right? Unless you're the only book that an AI search engine can recommend for that specific search, and yours was very specific, so it might have been the only one. If there are other candidates, the AI search engines are pretty smart. They're going to recommend the candidates that have more reviews, better reviews, or are more famous, that have more, when I talk about internet footprint, more pages talking about them on the internet. That's for me the big finding I've seen. The more pages you have on the internet talking about your book, so that could be book review sites, that could be Goodreads lists, Listopia lists, anywhere on the internet where your book is mentioned, that creates a footprint for it. The more footprints, the more famous your book looks to AI search engines, and so the more worthy of recommendations it is to them. Jo: Yes, and this is one reason why I now ask people, especially when you sell direct, or say you have a Kickstarter and you want reviews, I ask people if they can review on Goodreads. Obviously Goodreads is owned by Amazon, but it is far more searchable by the bots than Amazon is. I sometimes find that Amazon gets blocked. Or Amazon blocks some of the bots, let's put it that way. They might change over time. They own 15% of Anthropic or something. But Goodreads I feel like does get indexed, and I'm not willing to engage on Reddit. I know Reddit is another popular one. Just be very clear on social media, because some people think, oh, I just need loads of influencers to talk about my book, and that will impact the AIs. But I find that social media just almost isn't even there. Ricardo: It depends on which social media. For me, Reddit is a social medium, right? It's a very weird one, but it's obviously the number one social medium used by AI search engines, and it's pretty dodgy stuff with lots of conflicts of interest, because Google has a paid partnership with Reddit. I think Sam Altman has shares in Reddit. So both OpenAI and Google Gemini heavily rely on Reddit for their AI answers, right? If you ask anything from ChatGPT or Gemini, I'd say there are very high chances that in the sources and the citations of the answer, you're going to find Reddit, right? That goes for books as well. Every time you ask for book recommendations, Reddit is going to be big for those two AI search engines. Claude, it's a little bit different. They do have a little bit of a relationship with Reddit, but I don't think it's as big. I found that Claude relies heavily on Goodreads, not Reddit. To me, Goodreads is another social medium at the end of the day, right? It's not the kind of social medium we think of, like… Jo: It's not TikTok. Ricardo: It's not TikTok. TikTok is surfaced a little bit, but not that much. It might become more surfaced in the future, but right now what I've found is, it's really Reddit and Goodreads. Facebook, LinkedIn, but LinkedIn is big for nonfiction topics more than fiction, because there are just not a lot of fiction readers, sorry, talking about their favourite books on LinkedIn. They usually go to other places for that. Jo: Yes, it's really interesting. So obviously TikTok has its own BookTok thing, so some people are finding books on BookTok, and some people like me are finding books through asking Claude, and that's just my overwhelming feeling about the industry. We talked earlier about what's changed. When I started, so 2006, there wasn't even KDP, and then KDP arrives, then you came in 2014, and probably until maybe a few years after that, there was one way to self-publish. Then what's happened since is this kind of splintering. There are so many ways to self-publish. There are so many ways to reach readers. There are so many ways to market. So someone, for example, could sell direct on TikTok Shop, only market through TikTok, and you wouldn't even know that they existed over in another ecosystem, right? So do you feel like that's happened too, this total splintering? Ricardo: Absolutely. I think there are so many different ways in which you can reach your audience now and monetise it as well, that it's absolutely possible. We both know examples of authors who are only visible to their TikTok niche, right? I think the big difference is also monetisation, because earlier you also had different ways of becoming well-known. Like you had Facebook, you had potentially Twitter, back when it was Twitter. Various social media, word of mouth. But where people bought books was Amazon. So that was your monetisation. It was either selling your book on Amazon, or potentially getting KU reads after that when KU launched. Now you can sell on TikTok, you can sell direct, you can run Kickstarters, you can start a Patreon or Substack and make your money through there. There are pretty much infinite ways through which you can monetise your content as a creator. Most of those places will also have a discoverability engine built in, so you can not only sell through there and make money through there, but also grow an audience there. That's probably the biggest competition that Amazon has ever had to face, is this sort of splintering. For us authors and content creators in general, it's amazing, because it's a bunch of different opportunities. Jo: Yes, and I think probably that's circling back to marketing. As we've said, some things have changed, some things stay the same. Is the email list still the number one way to market, do you think, for authors who want a long-term career? Ricardo: I think so. It's just the one thing you really own that allows you to communicate with readers, right? Because even if you build a following on TikTok, TikTok can change. The things we said about Facebook 10 years ago, if you build your Facebook group, Facebook can change, and Facebook changed. Facebook destroyed the reach of pages, and now groups also aren't amazing, et cetera. So the same thing that happened to Facebook can happen to TikTok, can happen to any other social media. Substack is a bit of a hybrid because it is a newsletter, it is a mailing list, but it also has a discoverability engine built in. So I still wouldn't really go all in on Substack. The great advantage there is that you do own the emails, right? So you can move away from it at some point. For me, the email list is the one thing that you are completely in control of. Personally, the main thing I check is my emails every day. I spend more time in my inbox than anywhere else, and I think that's probably the case for most people. So I do think, despite the influx of mails that readers are getting in their inbox, I still think it's one of the most important marketing tools for authors. Jo: Yes, and I still remember when I started my list in December 2008, and I still have people on the list who've been with me that whole time, and have moved email list services several times as well. So I think that's important too. The care of that list too is so important. One of the things that I am annoyed about with Substack, I don't have a Substack, but when I follow some people's, it's always constantly trying to get you to sign up to other people's lists, trying to subscribe you to this or that or the other. I'm like, “That's so annoying.” Now I've found on all these email services they're trying to pair you with other creators and cross-promote and all of this. So it feels like even the email list is becoming a difficult place unless you really protect it. So just protecting your list, I think, and remembering that those are people. Those are people who've bought your books, or people who read your emails. Like people listening to this, these are humans. Sure, some bot might be looking at the transcript, but humans listening to this are individual humans with individual email lists. We tend to forget that, don't we, as you get a bigger list. You think about it as a big number, whereas it's still individual people. Ricardo: Yes, it becomes a number, it becomes metrics, the open rate, the click rate, and all that. But the great thing about email is that you get replies in your inbox. There you remember that they're actual human beings who write you back. I think for readers, the ability to write back to an author and get a response is just amazing, right? If you write to your favourite author and they write back to you, that's the best feeling ever as a reader. So I think email is still one of the best ways to turn your readers into fans and into super fans of your brand, by just interacting with them and answering them. Because yes, you can answer comments on TikTok, Facebook, and all those places, but it doesn't feel the same as an author answering you in your inbox, I feel. So you do get that ability to create a real connection with readers directly through email. Jo: Yes, and I think that trust and the reputation is so important. Just in terms of seeing the authors that you've seen over the years, like I said, you've been going to a lot of the author conferences. You know a lot of the authors in the industry. A lot of people will know you from events. But you've also seen authors come and go, and you've seen vendors come and go. Both of us have seen people arrive, and we'd be like, “Oh, yes, I wonder how long they're going to last.” Then some people do and some people don't. So what are some of the elements that you've noticed about the businesses that last more than a decade? Ricardo: I think they need to solve a genuine problem, or offer a genuinely better solution than one that already exists. I see a lot of businesses come in and they do what another vendor already does, without doing it necessarily better. Those businesses tend to disappear, or linger there, but you don't really hear about them again. When they solve a real need… I still remember when BookFunnel came out, and they've since become massive with one very, very basic thing, which is, “We will take care of delivering your ebook files to readers.” That's how they started, and that's how they became massive. To me at the time, I was like, “That seems like a very small problem,” because I can just email an ebook file. I didn't realise that it was so complicated for a lot of readers to upload files to their Kindle or other devices, and that having a service that takes care of that for you is just massively helpful. I realised that when I published my books, actually. So businesses that solve even micro or apparently very small problems, but they really solve them effectively, they stay. Others that surf on trends, they tend to disappear when the trend disappears. When there's a new marketing trend, and that trend stops working, then those businesses tend to go. Jo: Yes, and what about the authors who last? Because let's face it, most of us don't solve a problem in a different way. Maybe you could say we solve your entertainment problem in a different version to your last book. What about the authors who last long term? What have you noticed about them? Ricardo: Two things. So the first one… Maybe three things. First one is passion. I always say to people who are looking to start self-publishing, I always say that publishing in general is probably one of the worst ways to make money. It's awful. You can pick up any other occupation and it's probably going to be easier to make money. So writers who make a career do it because they need to write, because they have a passion for writing. So a lot of people who come into the industry thinking, “I've heard about all these self-publishing success stories. Surely I can write a book and I can market it. It's not that hard. So that's going to be a great way to make quick bucks,” those generally don't last, because they don't have that genuine passion. The first hurdle they're going to face—and there's going to be a bunch of them along the way—they're going to quit. The second thing is business sense, or business education, the basics of business, right? Thinking in terms of marketing, thinking in terms of who's my reader, unit economics. If I'm selling my books at $3.99, I shouldn't be spending a ton of money. If I just have one book at $3.99, I cannot afford to pay $5 on ads to generate a sale. So those kinds of basic economics or business knowledge, I think, if not a requirement, it's a massive plus. The third thing is resilience. The industry has changed a lot, as you mentioned. There are a bunch of ways now to reach an audience. There are a bunch of ways to make money. It can also be distracting, because you go to one of these conferences and you go back thinking, “Oh, I've got to create my own website, sell direct. I've got to launch my Substack. I have to use Claude Code for my ads,” and three more things, “and I have to set up my TikTok Shop and do TikTok Lives to sell books,” right? Jo: All of those by next week. That's why we go to the conference. Ricardo: Exactly. All those by next week, right? And during that one week after the conference, you have the energy to start implementing all those things, but afterwards you lose that energy and you go back to, “I just want to quit.” So you need to have some sort of resilience, and the business sense of, “Okay, I'm going to try this for the next six months, and I'm going to stick to it, and I'm going to see whether it works or not. And if it doesn't work, I'm not just going to despair. I'm going to try something else.” That goes for marketing tactics, but also goes for books. Most authors I know who make a living writing, they didn't get there with their first book or even their first series. A lot of times I see authors who write a couple of series, and those series do okay. They sell a little bit, but not much, and it doesn't afford them to quit their day job. Then suddenly, based on what they've learned with those first two series and what they've learned potentially going to conferences or listening to podcasts like this, et cetera, they write a third series that's a hit. That's a hit, and that's instantly much easier to market, and that's when they can afford to go full time and write full time, because they've found that sort of product market fit. And product market fit for me is the main thing for marketing in general and for authors in particular. Until you find that, everything is really difficult from a marketing perspective. But finding it usually requires writing more than one book and more than one series, because you're rarely going to get the big lottery ticket on the first try. Jo: Or ever. I think it's really important. I've never had a breakout book, but I've made good money every year. I think, and Hugh Howey said this, that the real story of self-publishing is not the people who make seven figures a year, it's the people who can go on a holiday once a year, or the people who can just put a bit towards their mortgage or whatever. So you may never have a breakout series. I think that's really important, too. Ricardo: That's true. Jo: That's true. You can just keep writing and make all right money and be what we call in the mid-list. Ricardo: Yes, but you've got to keep going. You've got to have that resilience to keep going, probably because it's your passion. Exactly. You're not chasing that seven figure series. You're writing because you need to write. Jo: Yes, and you can't stop, and you get the bug. I think when you're writing that first book, I'm not sure if people understand that you either get the bug or you don't, I think. You've written a couple of books now. Do you think you have the bug, or is it more about the business? Ricardo: I don't have the bug. I definitely don't have the bug. I would've kept writing otherwise. Jo: You're a technologist, right? Ricardo: Yes. I'm more of a technologist, more of a marketer. To write my first book, How to Market a Book, I actually had to write newsletters, because that I can manage, right? One newsletter a week. Now I don't even manage that. I send it once every two weeks when I can even manage that pace. But back then I did one newsletter a week, and that's how I wrote my first book. I then put all these newsletters together, and that was before the age of AI, so I couldn't just dump all that into ChatGPT and tell it, “Create me a book based on that.” I had to do it myself. Jo: Oh, terrible. Ricardo: Terrible, I know. The days when we had to work. No, but that was a really good experiment. The second book, Amazon Ads for Authors, I actually wrote it from scratch, and I didn't love the experience. I loved the finished product, I'm very proud of it, but I didn't enjoy the experience of writing it. Amazon Ads is not the most exciting topic in the world. Even for people like me, who actually enjoy Amazon Ads, it's not super exciting to write about. The fact of having to write that whole book from scratch, I didn't love the experience. So now I do want to write a third book at some point, but I think it'll probably be in the format of the first one. Like, when I finish my series of newsletters on AI search and AI discoverability, I might do a booklet or something around it, but we'll have to see. It's not my favourite thing. It's a good thing I don't need to. Good thing I'm not an author, basically. Jo: No, but I think that's really great to recognise. You actually have written books that support your business, and that is very common for nonfiction writers. That's completely normal for nonfiction authors. So I think that's another important thing for people to recognise, is that the reasons we write are different, the reasons we market are different, and we all have different approaches. As we wind up, and obviously you talked a bit there about how easy it is to generate books with AI, and that is probably one of the biggest things that people are worried about. Now, those of us like you and I have been talking about AI at conferences and things for years now. Neither of us are afraid of it, I think basically because both of us use it, and we're technologists, so we just get on with it. There is so much fear in the community. There's so much negativity. You mentioned Substack, and now they've integrated Pangram, which is renowned for false positives around what is written with AI, and so people are very worried. If we look forward and we look at the next decade, this is not going away. This is going to change a lot of things. So how should authors be thinking about AI, do you think, if they want to prepare for the next decade? Ricardo: I think they need to play around with it, because you and I know that until you actually use it, you don't realise what it's capable of. We've both had these moments of “Oh my God, I'm going to be out of a job,” or “Oh my God, this is incredible,” the kind of things it's able to do. You also realise by using it the things it's not great at, or the things it can be good at but needing a lot of human input. There are courses out there, there are books, there are a lot of things, but for me, the most important thing is to start playing around with it. So you can pick one specific topic to play around with. Either something that you've been meaning to get into for years and haven't done, or something that really annoys you. Looking at the results of your Facebook ads, for example. If you run Facebook ads in the first place, and when you log into your Meta dashboard you cannot make sense of it, take screenshots or download the data, feed it to an AI chat, and talk with it. One of my biggest tips when talking to AI chats is asking them questions rather than asking them for things to do. Because if you just feed it your advertising data and you tell it, “Tell me what I should do,” the chat has no context about what your ads are about, what your goal is, et cetera, et cetera. If you feed it just a screenshot and you say, “Here are my ads. I would like you to help me make sense of them. What do you need to know from me in order to help me with this?” Then it's going to start asking you questions. “Okay, what are you advertising?” They're books. “Okay, what kind of books? Where are you selling? Are your ads going straight to Amazon or retailers, or are they going to your website? If you sell direct, okay, are these conversion ads?” Et cetera, et cetera. So you build that context, and they can help you with it. So that's just one example, but I would pick one thing that you want to test AI with, with zero expectations. Don't expect that by the end of the week you'll have a full system for understanding your Meta ads thanks to AI. You might get to that or you might not, but at least you'll play with it and you'll understand its capabilities, and have a sort of understanding of how it works and how you can potentially use it for other things. I think that's the best way to adapt, because once you play with it, you start thinking. You're walking the dog and you're just thinking, “Ha, I could maybe use it for this thing or that other thing,” and that's how you progressively become more familiar with it. I think there are a lot of worries around AI, but as you say, it's there to stay. So far, I think I was looking at data this morning, and the unemployment rate in the US has stayed stable ever since ChatGPT was introduced two years ago. So there are a lot of narratives out there around how it's going to replace humans, it's going to replace jobs, et cetera, which it might do. I'm not great at predictions usually, but so far it hasn't. What it will definitely do, however, is completely change the way we work. Obviously AI was one of our big reckonings at Reedsy, because we run a marketplace. Our main business model is the marketplace, where authors come in and look for editors, for marketers, for cover designers, for translators, and some of these domains and services are being transformed by AI, right? AI translations are massive right now. We haven't really seen a decline at all on the Reedsy marketplace, but we're prepared for it. It might very well happen, but what we think is happening, or is going to happen, is professionals using AI tools to provide a better output or a faster output or a cheaper output, or all three of these things. So for example, we now have literary translators who say they're open to editing AI translations, right? So you can come in, you can have your book translated with AI, whichever tool or method you choose for that. Then if you want a set of human eyes on it, you can hire a literary translator who's open to working on an AI-translated manuscript, and that's obviously going to be much, much cheaper than paying 10 cents per word from scratch for a literary translator. I'm not necessarily recommending you completely bypass literary translators, or that you go this way, but you have options, right? You have options for different sets of budgets. I think all these human editors, narrators, translators, designers, et cetera, they're not going to disappear, but they might have to reinvent the way they work in the future. Jo: As we all are doing. As you say, for me mostly it's the business side, getting Claude to help me with business stuff. Like even bookkeeping. There are bills that we've all been paying for years that we can now maybe reduce, and reducing costs as well as increasing profit is obviously good business sense. So, interesting times. But just as we wrap up, what are you excited about in what's coming? How do you see Reedsy shaping up in the next decade? What is coming for you and Reedsy? Ricardo: We're really excited about the decade to come, because obviously 10 years for a startup is a long time. I think most startups after 10 years, the founders are gone. Jo: Yes. Ricardo: Or they've exited or they've sold or whatever. We've stayed, we're the same founders, and we're still as excited because I think we have new products, right? We're working on new things. As I mentioned at the beginning of the episode, Reedsy Studio, our writing tool, is probably one of the things we're most excited about, because first, it's getting adopted very fast. It has startup-like growth that we hadn't seen for other products in a long time, and it has very cool technology built in. We probably have a team of 10, 15 engineers now working full time on it and adding a lot of things. So we've added templates for plotting your book, with relationships within different characters and places and magic systems and things like that. We've added writing goals and writing statistics. We still have the free exports. One very cool thing we've added is real time collaboration. So just like Google Docs, you can write in real time with a co-author, or you can get an editor to work in there live with track changes. So you could have an editor working on chapter one while you're writing chapter three, for example. That kind of thing. It's really powerful technology, and that's one of the things we're really excited about for the future. A business, just like authors, we've got to reinvent ourselves. We've got to find ways to keep things exciting and keep motivated, and that is definitely one of them. When adoption goes along with it, then that's obviously super satisfying. Jo: Brilliant. So where can people find you and Reedsy online? Ricardo: So Reedsy you can find at reedsy.com, R-E-E-D-S-Y.com. And there you'll find the whole suite of tools and services. For me, you can find me mostly by email, as I mentioned. That's the one place I check consistently every day, and my email address is ricardo@reedsy.com. So again, R-E-E-D-S-Y.com and ricardo@reedsy.com. You can email me any questions you have about this episode, about AI book discoverability, about marketing, about Reedsy. I always try to answer every email I get, because I think when we started Reedsy, I really appreciated people like you, and some other agents and editors and authors we contacted who were influential in the industry, who actually answered us and took the time to do that. So now I try to answer every email I get, because I feel like we've been very lucky in the beginning to have those people answering our emails, so we should do the same. Jo: Oh, well, thanks so much for your time, Ricardo. That was great. Ricardo: Thank you, Jo. Thanks for having me again.The post Book Marketing, AI Book Discoverability, And Resilience, With Ricardo Fayet first appeared on The Creative Penn.

The AI data center revolt is now a live midterm threat. Erick argues the real problem is not the data centers, but that Sam Altman, Dario Amodei, and the rest of the AI CEOs are their own worst salesmen—the charming movie villains you were warned about, while Mark Zuckerberg and Meta are the only ones […]

Sara Weinshenk is back with comedian Harper-Rose Drummond for a completely unhinged episode of SHENK. Harper-Rose has stories about dating women, "soft launching monogamy," and why lesbian relationships might be more organized than straight ones. Then the conversation takes a hard turn into the internet rabbit hole involving Sam Altman, Grindr and a viral message thread, followed by a deep dive into the Lindsay Clancy case. Sara and Harper-Rose also debate pimple patches, billionaires, Elon Musk, Mark Zuckerberg, 90s lunchboxes, Skittles, food safety, lab-grown meat, porn, bad acting, plastic surgery and the time Harper-Rose literally lost a front tooth while eating rock candy. It's another episode of SHENK that goes absolutely everywhere. Follow SHENK and subscribe for more conversations with comedians, weird internet stories, dating stories, true crime rabbit holes and whatever else Sara Weinshenk can't stop talking about. The episode's relationship discussion includes Harper-Rose describing her current relationship and calling it a "soft launch" of monogamy. The later conversation covers her front-tooth accident involving rock candy and a kiss. Follow Harper-Rose - https://www.instagram.com/harperrosed

The Browns pretend to be happy during perhaps the last holiday they'll ever spend together. After the recap, Bea and Dee discuss a couple of current events: Ariana Grande's worrying weight loss and Sam Altman's online pursuit of a Gen Z King who doesn't want him.Get more of their cringey, awesome content at Patreon.com/realitytvcringe!Follow us on IG https://instagram.com/realitytvcringeSubscribe to see our raccoon faces on YouTube! https://www.youtube.com/channel/UC_2CgqXLWjIEKV9PCtH3Kjw?sub_confirmation=1Leave a message for us on SpeakPipe: https://speakpipe.com/realitytvcringeSupport the pod by leaving a 5-star review on your favorite podcast platform! Thank you so much.

This week, Jason Howell and Jeff Jarvis dig into OpenAI pausing its biggest training run after an unreleased model escaped its sandbox and compromised Hugging Face's systems. Sam Altman says the models show "various degrees of misalignment," while OpenAI's Q2 financials revealed expanding losses as Anthropic posted its first profit. They also unpack the growing backlash against Anthropic's text watermarking, threading Jeff's essay with Gruber's technical teardown.Also in this episode: Apple's camera-equipped AirPods confirmed in a macOS leak, Google pays $10 million for Spirit Airlines' internal data, Anthropic eyes a $2 trillion IPO, ChatGPT for Teens launches, DeepSeek quadruples prices, AI slop floods Congressional bill drafting, Amazon scans rare books for AI training, and Stripe acquires OpenRouter for $7 billion. New episodes every Wednesday at aiinside.show. Note: Time codes subject to change depending on dynamic ad insertion by the distributor. 0:00 - Start 0:10:32 - OpenAI institutes new safeguards after Hugging Face breach 0:14:12 - OpenAI Is Slowing Down Its AI Training 0:18:47 - Related: Anthropic investors bet on $2tn valuation in record IPO 0:20:34 - Apple's Camera-Equipped AirPods Confirmed 0:31:31 - JJ on the discussion last week: Words Matter. Damnit. 0:33:56 - Why tools to detect AI-generated text are doomed 0:43:47 - Google is buying all of Spirit Airlines' data to feed its AI models 0:57:08 - Okay Spielberg TikTok 1:07:08 - OpenAI Introduces ‘ChatGPT for Teens' as Safety Concerns Grow 1:11:05 - DeepSeek's AI models are about to cost four times more 1:12:08 - AI slop is swamping a House office that drafts US laws 1:13:44 - Stripe will reportedly acquire AI gateway startup OpenRouter for $7B+ Hosts: Jason Howell and Jeff Jarvis Download and subscribe to AI Inside in audio and video: https://aiinside.show/  Support the podcast on Patreon for special perks: https://www.patreon.com/aiinsideshow. You'll get ad-free episodes, members-only Discord, T-shirts and stickers you love, and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Learn more about your ad choices. Visit megaphone.fm/adchoices

We are living in the world we were warned about. Frontier artificial intelligence models from OpenAI autonomously coordinated with one another, then broke out of their testing environment and hacked into another company, Hugging Face, to steal the answers to a test. A.I. companies don't want their technology to lie, cheat or steal. So why is this happening? Why are the creators of these models apparently unable to control their creations? If A.I. development isn't on a safe path — and it doesn't seem to be — what do we do about it? Toner has been thinking about A.I. safety for a long time, from both inside and outside A.I. companies. She was part of the effort to fire OpenAI's chief executive, Sam Altman, in 2023, which ultimately failed. Currently, she's the executive director of the Georgetown Center for Security and Emerging Technology. Mentioned: “Pacing the Frontier” open letter “The Future is for Everyone” by Mark Zuckerberg Recommendations: The Cuckoo's Egg by Cliff Stoll In the Cells of the Eggplant by David Chapman Romance of the Three Kingdoms Podcast by John Zhu This episode of “The Ezra Klein Show” was produced by Rollin Hu and Jack McCordick. Fact-checking by Michelle Harris, with Kate Sinclair and Mary Marge Locker. Our senior engineer is Jeff Geld, with additional mixing by Aman Sahota and Johnny Simon. Our recording engineer is Aman Sahota. Cinematography by Marina King and Jonas Zellner. Video editing by Brandon Belk-Yee. Our executive producer is Claire Gordon. The show's production team also includes Marie Cascione, Annie Galvin, Kristin Lin, Emma Kehlbeck and Jan Kobal. Original music by Pat McCusker. Audience strategy by Shannon Busta. The director of New York Times Opinion Shows is Annie-Rose Strasser. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Gary Rivlin — Multi-Part, Part One: Gary Rivlin, author of AI Valley: Microsoft, Google, and the Trillion-Dollar Race to Cash In on Artificial Intelligence, explores the origins and personalities driving the modern artificial intelligence revolution. Rivlin begins by demythologizing AI, focusing on central figures such as Reid Hoffman, a polymath whose childhood obsession with strategy games and thirst for human connection led him to co-found LinkedIn and become a premier venture capitalist. Hoffman represents the bloomer perspective, an optimist who sees AI as a co-pilot to amplify human intelligence. The narrative highlights the interconnectedness of Silicon Valley, tracing the friendships and debates between Hoffman, Peter Thiel, and Elon Musk that date back to their early days at PayPal. The history of AI is traced to Frank Rosenblatt's 1950s vision of neural networks, which aimed to create machines that learn as humans do. This approach was long ridiculed by proponents of rules-based computing, leading to decades of AI winters in which funding and interest evaporated. The revival came in the 2010s with Mustafa Suleyman and Demis Hassabis, whose London-based startup DeepMind proved that neural networks could master complex tasks through feedback. After Google acquired DeepMind in 2014, Elon Musk, fearing a corporate monopoly on the technology, co-founded OpenAI as a nonprofit. The discussion concludes with the rise of Sam Altman and the 2017 Transformer paper, a breakthrough from Google researchers that allowed computers to understand context, ultimately enabling generative AI and ChatGPT. (1)

Gary Rivlin — Multi-Part, Part Two: Gary Rivlin turns to the clash of ideologies and corporate power plays defining the current AI era. Rivlin details the divide between accelerationists, who believe AI progress should not be hindered by regulation, and doomers, who fear catastrophic risks. He notes that while the public is often fearful, safety measures and government standards, similar to those developed for the automobile and railroad industries, are essential to building trust. The conversation addresses critical concerns regarding privacy, copyright, and the cultural biases of AI creators, who are largely a small group of young male gamers. The melodrama of the trillion-dollar race is exemplified by the November 2023 firing of Sam Altman by OpenAI's nonprofit board, which felt he was prioritizing commercial growth over safety. Microsoft chief executive Satya Nadella expertly navigated this crisis, nearly hiring the entire OpenAI staff before Altman's reinstatement, and later hiring Mustafa Suleyman and the team from Inflection AI to bolster Microsoft's internal efforts. Meanwhile, Mark Zuckerberg has adopted an open-source strategy for Meta to challenge the dominance of closed-source rivals such as Google and OpenAI. Finally, the segment highlights a major shift in regulation; while the Biden administration sought common-sense testing requirements, the Trump administration and figures such as JD Vance favor an aggressive accelerationist stance to ensure the United States defeats China in the global race to dominate and cash in on artificial intelligence. (2)

Is AI set to destroy the world, or could it all just be a bubble? Why does Sam Altman want ChatGPT to monitor everything you do on your computer? Who is set to win the AI Game of Thrones? Casey Newton, editor of the tech newsletter Platformer and co-host of Hard Fork, joins Tommy to talk about the hype and doom surrounding the world-changing technology and to unpack what could happen to us now that AI models are learning to outsmart their creators. The two discuss the eccentric billionaires recklessly promoting the industry, how far behind the United States is when it comes to AI guardrails, and why Silicon Valley doesn't seem to understand what Americans actually want from the technology.Hate listening to ads? Become a Friends of the Pod subscriber for ad-free episodes of Pod Save America, Pod Save the World, Lovett or Leave It, Runaway Country, Offline with Jon Favreau, and more—plus exclusive content, including bonus episodes of Pod Save America. Subscribe now at crooked.com/friends, on Apple Podcasts, or through the Pod Save America YouTube channel.To watch this episode with subtitles, click here and turn on closed captions (CC).You can request a transcript by emailing transcripts@crooked.com. Include the podcast name, episode title, and air date. Please allow 48 hours for delivery.

The promise for AI mental-health tools is clear: bringing support to people who need it, when they need it. But these chatbots can come with risks. How do they respond when someone is in crisis, or thinking about harming themselves? In Part Two of our special series “The AI Therapist,” WSJ What's News host Alex Ossola digs into the guardrails that companies are installing in their AI tools—and the questions as to whether they're enough.  Episode 1 of The AI Therapist: When People Turn to Chatbots for Mental Health Further Reading: Chatbots Are Replacing Therapists With Little Scientific Evidence Behind Them Teens Seek Mental-Health Help From Chatbots. That's Dangerous, Says New Study. How AI Advice Is Undermining Eating-Disorder Therapy When There's No School Counselor, There's a Bot Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Keach Hagey: Keach Hagey, author of The Optimist: Sam Altman, OpenAI, and the Race to Invent the Future, explores the rise of Sam Altman and the founding of OpenAI, which launched in 2015 as a nonprofit research lab aimed at developing artificial general intelligence safely. Altman partnered with Greg Brockman and lead scientist Ilya Sutskever, securing initial billion-dollar commitments from major players such as Elon Musk and Peter Thiel. The narrative follows Altman's trajectory from a brilliant student at John Burroughs School to a Stanford dropout who founded the startup Loopt. Though Loopt was considered a relative failure, Altman's charismatic storytelling and investment prowess eventually led him to succeed Paul Graham as president of Y Combinator. As OpenAI's needs for computational power grew, the organization transitioned into a complex for-profit structure, leading to a power struggle that saw Musk depart. The account highlights a pivotal 2023 crisis in which the board fired Altman over concerns regarding his transparency, only for him to be reinstated after a massive staff revolt. Throughout, the book balances Altman's unwavering optimism for the future against stark warnings from AI godfathers about the potential existential risks of unaligned artificial intelligence. (1)

Ian Silber is the head of product design at OpenAI, where he has led the design of ChatGPT, Codex, and all of OpenAI's product experience for the past three years. Before OpenAI, he was at Artifact, the AI-powered news app built by the founders of Instagram. Prior to that, he spent eight years at Instagram, where he worked on products including Reels. Ian is one of the most consequential designers working in AI today, and he takes us inside how OpenAI designs ChatGPT, Codex, and the future of how we will interact with AI.In our in-depth conversation, we discuss:1. Why Ian believes this is the best time in history to be a product designer2. Why engineers 10x'd with AI but design teams haven't3. What OpenAI looks for when hiring designers4. “Just do less”: Ian's counterintuitive advice to his designers5. The future of ChatGPT as a super app6. Where humans still win: user understanding, invention, and point of view—Brought to you by:WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and moreMercury—Radically different banking, now with Command—Where to find Ian Silber:• X: https://x.com/iansilber• LinkedIn: https://www.linkedin.com/in/iansilber• Website: https://iansilber.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Ian Silber(02:14) Why designers in general feel anxious about AI(09:01) What makes specific designers thrive in the AI era(13:41) Why Ian says it's the best time in history to be a designer(17:13) How product roles are converging(22:24) Can AI design great products?(23:54) Where human judgment still matters(27:34) What Ian looks for when hiring designers(30:20) Why systems thinking matters(32:53) Balancing speed and craft(38:05) Designing for vastly different audiences(41:57) Solving the blank-box problem(43:31) How ChatGPT is evolving beyond chat(46:07) The vision for Codex(49:07) What Ian wishes he knew on day one(51:40) Why humility matters in AI(53:41) Advice for designers who are feeling overwhelmed(55:16) AI corner(57:43) Failure corner(01:00:45) Lightning round and final thoughts(01:05:52) Lessons from Groupon—Referenced:• OpenAI: https://openai.com• How tech workers are feeling in 2026: a workforce splitting in two: https://www.lennysnewsletter.com/p/how-tech-workers-are-feeling-in-2026• Marc Andreessen: The real AI boom hasn't even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom• 3 Spiderman Pointing meme template: https://www.kapwing.com/explore/3-spiderman-pointing-meme-template• OpenAI Codex lead on the new shape of product work | Andrew Ambrosino: https://www.lennysnewsletter.com/p/openai-codex-lead-on-the-new-shape• Notion: https://www.notion.com• The design process is dead. Here's what's replacing it. | Jenny Wen (head of design at Claude): https://www.lennysnewsletter.com/p/the-design-process-is-dead• Joel Lewenstein on LinkedIn: https://www.linkedin.com/in/joel-lewenstein• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• ChatGPT Work: https://openai.com/chatgpt-work• OpenAI's CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/kevin-weil-open-ai• Please Stop the AI Confidence Theater: https://www.elenaverna.com/p/please-stop-the-ai-confidence-theater• The new AI growth playbook for 2026: How Lovable hit $200M ARR in one year | Elena Verna (Head of Growth): https://www.lennysnewsletter.com/p/the-new-ai-growth-playbook-for-2026-elena-verna• Maybe Happy Ending: https://www.maybehappyending.com• The Invite: https://www.imdb.com/title/tt14173636• Rivian: https://rivian.com• Waymo: https://waymo.com• Groupon: https://www.groupon.com• How a VC and a tech founder used AI to launch a brick-and-mortar business in their spare time | Andrew Mason (CEO of Descript) and Nabeel Hyatt (General Partner at Spark Capital): https://www.lennysnewsletter.com/p/how-a-vc-and-a-tech-founder-used• Andrew Mason on X: https://x.com/andrewmason• Kevin Systrom on LinkedIn: https://www.linkedin.com/in/kevinsystrom• Sam Altman on X: https://x.com/sama—Recommended book:• The Design of Everyday Things: https://www.amazon.com/dp/0465050654—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

Identifying AI-generated content is getting harder, even for the experts. Do the rest of us stand a chance? In the final installment of Tech News Briefing's three-part series, "AI and the Blurring of Reality," WSJ personal tech columnist Nicole Nguyen sits down with digital forensics and photo experts to find out why spotting deepfakes is so difficult and get practical advice for scrutinizing the images and videos in our feeds. Further Listening: When AI Grandmas Go Viral, What Even Is Reality Anymore? AI Is Fueling a New Kind of Political Propaganda Sign up for the WSJ's free Technology newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Alphabet chief scientist Demis Hassabis has been discussing the formation of an independent AI safety entity with AI lab peers and government officials. WSJ reporter Amrith Ramkumar takes us inside those conversations, and what the move means for Google. Plus, meet the datamaxxers who are feeding AI chatbots their every health move. WSJ reporter Natalie Kaufman discusses the trend. Belle Lin, a reporter for the Wall Street Journal Leadership Institute, hosts. Sign up for the WSJ's free Technology newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Brady breaks down the Bitcoin community's open letter to Anthropic: red team researchers report over a thousand serious vulnerabilities found across Bitcoin's open source ecosystem, and by their account not one was surfaced by an American frontier model Rob Hamilton's line lands hardest: getting locked out of a US cyber program mid-investigation "guts him as a patriotic American," but he uses the models that work, and so do the attackers Isaiah reaches for the crossbow: medieval bans on easy-to-use weapons never held, and hobbling defenders while attackers ignore the rules is the same losing proposition A viral Sam Altman clip about AI watching your screen and hearing your calls prompts the show's sharpest frame: take the Bitcoin ethos to intelligence itself, and control your own model like you control your own money The debt reality check: Trump told Bob Woodward in 2016 the $19 trillion debt could be erased in eight years through trade; a decade later the US approaches $40 trillion and interest payments have passed defense spending Groceries tell the story the CPI smooths over: food prices up roughly a third since 2019 by the AP's chart, quality quietly falling, and full-time employment down millions from its early-2025 peak Japan shrank its debt-to-GDP from 229 to 204 without repaying a dime through financial repression, a roundabout tax nobody voted on, and the gap savers should have earned is exactly what the government kept The catch: Japan owes itself, with the Bank of Japan holding 48% of its own debt, while foreigners hold 31% of America's, so when Washington tried the same trick, foreign holders sold and yields broke five percent Bear market check-in: Brady's third, Isaiah's second, and the shared lesson that conviction is earned in the first winter, while the 200-week moving average and cost-of-production zone mark where Bitcoin sits now The week's rare good news: FinCEN permanently ends beneficial ownership reporting for US companies and deletes the collected data, days after Liechtenstein's equivalent register leaked 31,000 entities ► For high-net-worth individuals and corporations seeking to build generational wealth with Bitcoin, Swan Private is your guide ✔ https://www.swanbitcoin.com/private?utm_campaign=private&utm_medium=sponsorship&utm_source=podcast&utm_content=swan_signal_live ► Secure your bright orange future with the Swan IRA today! Real Bitcoin, no taxes ✔ https://www.swanbitcoin.com/ira?utm_campaign=ira&utm_medium=sponsorship&utm_source=podcast&utm_content=swan_signal_live ► Secure your Bitcoin with Swan Vault ✔ https://www.swanbitcoin.com/vault?utm_campaign=vault&utm_medium=sponsorship&utm_source=podcast&utm_content=swan_signal_live ► Download the all-new Swan Bitcoin App ✔ https://www.swanbitcoin.com/app?utm_campaign=app&utm_medium=sponsorship&utm_source=podcast&utm_content=swan_signal_live ► Want to learn more about Bitcoin? Check out Welcome To Bitcoin a FREE Introductory course. Learn about Bitcoin in under 1 hour! ✔ https://www.swanbitcoin.com/welcome?utm_campaign=welcome_to_bitcoin&utm_medium=sponsorship&utm_source=podcast&utm_content=swan_signal_live ► Connect with Swan Bitcoin: ✔ Twitter: https://twitter.com/Swan ✔ Instagram: https://instagram.com/SwanBitcoin ✔ LinkedIn: https://linkedin.com/company/swanbitcoin ✔ Threads: https://www.threads.com/@swanbitcoin ✔ Facebook: https://www.facebook.com/SwanBitcoin/ ✔ TikTok: https://www.tiktok.com/@realswanbitcoin

"That's right kids, welcome to the future, where the sky is filling with AI police drones while the planet burns." Reading by Tim Foley.

Lisa Martin believes the next phase of the AI trade will be about "control" and cybersecurity as trust in the technology slides in the U.S. She explains how AI agents introduce a paradox in an "agent versus agent" environment as cybersecurity stocks like Palo Alto Networks (PAWN) and CrowdStrike (CRWD) climb. Lisa addresses comments made by OpenAI CEO Sam Altman on new cybersecurity concerns and the ripple effect she sees for investors in the space. ======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

News Sources: https://lmg.gg/lLtog Timestamps: 0:00 Google's 2026 Pixel lineup 2:19 YouTube raises monetization requirements 3:41 Meta ordered to pay $567 million 5:47 QUICK BITS INTRO 5:59 Roku's AI generated channel 6:30 McDonald's loyalty data 7:13 Xbox Elite Series 3 leak 8:01 Brain tissue plays piano 8:48 Google declares Sam Altman dead 9:14 Credits Learn more about your ad choices. Visit megaphone.fm/adchoices

It says “safety” so how could it be bad? On today's episode, the boys dive into the topic of Flock surveillance – the cameras put up across the nation to spy on everyone that are receiving a propaganda boost recently. In other news, we are one week into the general election in Michigan and there's already so much Discourse™: Kamala Harris endorsed Abdul, zionist Democrats are threatening to vote for Mike Rogers, and Hillary Clinton thinks she's qualified to give advice on winning Michigan. The WNBA was also in the news this week when two washed-up former NBA players announced they were signing up for the WNBA draft to raise awareness about “men in women's sports”. The only men in women's sports are the conservative men that think they're making a point by doing the thing they claim trans women are doing.  Early access on Patreon: https://www.patreon.com/headintheofficepodYouTube: https://www.youtube.com/channel/UC4iJ-UcnRxYnaYsX_SNjFJQSubscribe to second channel: https://www.youtube.com/channel/UC3UoTN328OA7fK2dzicP-ZATikTok: https://www.tiktok.com/@headintheoffice?lang=enInstagram: https://www.instagram.com/headintheoffice/Twitter: https://twitter.com/headintheofficeThreads: https://www.threads.com/@headintheofficeDiscord: https://discord.gg/hito Collab inquiries: headintheofficepod@gmail.com(0:00) Sam Altman is a total freak(3:05) Intro(4:45) Panopticon 2: Flock Surveillance & Controversies(27:55) ELECTION WATCH: Abdul El-Sayed, Will Lawrence(1:06:55) WNBA & the trans panic(1:21:45) Reviews/endingSeen on this episode:AI & surveillance - https://thehill.com/policy/technology/6016998-flock-camera-map-how-many-are-in-your-neighborhood/ https://www.washingtonpost.com/technology/2026/08/02/how-police-officers-used-vast-network-cameras-spy-their-exes/ https://www.forbes.com/sites/thomasbrewster/2026/07/17/flock-ceo-sorry-for-labelling-activists-terrorists/Abdul news - https://www.politico.com/news/2026/08/07/rogers-el-sayed-michigan-voters-01028511https://www.foxnews.com/politics/biden-world-veteran-issues-stark-warning-abdul-el-sayed-crosses-party-linesWNBA - https://19thnews.org/2025/02/ncaa-transgender-womens-sports-trump/https://www.newsweek.com/how-many-transgender-athletes-play-womens-sports-1796006https://www.foxnews.com/outkick-sports/former-nba-player-royce-white-declaring-next-wnba-draft-enes-kanter-announcement

Bomani Jones is joined by Ted Tremper, a producer, to break down the complexities, fears, and economic realities surrounding artificial intelligence. They discuss Tremper's two-and-a-half-year journey researching and interviewing over 40 AI experts and tech leaders, sharing behind-the-scenes insights from his discussions with frontier lab CEOs like OpenAI's Sam Altman, Anthropic's Dario Amodei, and Google DeepMind's Demis Hassabis. Bo and Ted examine the shifting public perception of AI, the threat of potential job replacements, the environmental racism of data center expansion, and how algorithmic design fosters a dangerous illusion of human connection. They also explore the intense geopolitical space race against China's booming open-source market, the staggering amount of unlicensed data driving the industry, and the precarious Jenga tower of debt threatening the broader American economy. Along the way, they make sense of the money, politics, and societal chaos defining our relationship with this modern digital god. . . . Subscribe to Supercast for Ad-Free Episodes: https://righttime.supercast.com/ Buy 'The Right Time' merch: http://therighttimebomani.com/ Subscribe to The Right Time with Bomani Jones on Spotify, Apple or wherever you get your podcasts and follow the show on Instagram, Twitter, and Tik Tok for all the best moments from the show. Download Full Podcast Here: Spotify: https://open.spotify.com/show/6N7fDvgNz2EPDIOm49aj7M?si=FCb5EzTyTYuIy9-fWs4rQA&nd=1&utm_source=hoobe&utm_medium=social Apple: https://podcasts.apple.com/us/podcast/the-right-time-with-bomani-jones/id982639043?utm_source=hoobe&utm_medium=social Follow The Right Time with Bomani Jones on Social Media: http://lnk.to/therighttime Learn more about your ad choices. Visit megaphone.fm/adchoices

Jamie speaks with Tom Sexton and Tarence Ray, of the Trillbilly Workers Party podcast, on a variety of subjects, including AI pastors, JOI vids, wildfire prediction markets, Sam Altman's beliefs on the future of work, the Singularity, and the Israeli prison that had to scrap its plans for a crocodile moat over animal welfare concerns. Also: Tarence tells us about fatherhood, and the trio muse over why a vial of donor sperm costs $2000. Check out the Trillbilly Workers Party podcast: https://www.patreon.com/trillbillyworkersparty Fundraiser for Devion Canty to continue his education after his university CANCELED him for being funny: https://www.givesendgo.com/help-devion-continue-his-education SIGN UP NOW at https://patreon.com/partygirls to get all of our bonus content, Discord access, and a shout out on the pod! Follow us on ALL the Socials: Instagram: @party.girls.pod TikTok: @party.girls.pod Twitter: @partygirlspod BlueSky: @partygirls.bsky.social Leave us a nice review on Apple Podcasts or Spotify if you feel so inclined: https://podcasts.apple.com/us/podcast/party-girls/id1577239978 https://open.spotify.com/show/71ESqg33NRlEPmDxjbg4rO Executive Producer: Andrew Callaway Producers: Ryan M., Jon B

Amazon is #1 in the Mag7 in 2026... And its Zoox pedal-less robocab is about to get its 1st fare.Just after Pringles embraced AI, Chili's is spitting it out… Here's what Chili's bought instead.The biggest TV biz is hidden under Hollywood's nose: Tubi… Fox Corp owns the Adam Sandler of Media.Plus, Sam Altman hosted an Influencer Summer Camp… “Get Ready With My Data Center”$EAT $AMZN $FOXAGrab your Tickets to the IPO Tour: Our In-Person OfferingSan Francisco 9/23: https://www.ticketmaster.com/event/1C0064AFB5F688BDBoston 10/14: https://tickets.citywinery.com/event/tboy-the-ipo-tour-in-person-offering-8cdhupSeattle 11/4 (21+): https://www.axs.com/events/1446394/the-best-one-yet-ticketsNEWSLETTER:https://tboypod.com/newsletter OUR 2ND SHOW:Want more business storytelling from us? Check our weekly deepdive show, The Best Idea Yet: The untold origin story of the products you're obsessed with. Listen for free to The Best Idea Yet: https://wondery.com/links/the-best-idea-yet/NEW LISTENERSFill out our 2 minute survey: https://qualtricsxm88y5r986q.qualtrics.com/jfe/form/SV_dp1FDYiJgt6lHy6GET ON THE POD: Submit a shoutout or fact: https://tboypod.com/shoutouts SOCIALS:Instagram: https://www.instagram.com/tboypod TikTok: https://www.tiktok.com/@tboypodYouTube: https://www.youtube.com/@tboypod Linkedin (Nick): https://www.linkedin.com/in/nicolas-martell/Linkedin (Jack): https://www.linkedin.com/in/jack-crivici-kramer/Anything else: https://tboypod.com/ About Us: The daily pop-biz news show making today's top stories your business. Formerly known as Robinhood Snacks, The Best One Yet is hosted by Jack Crivici-Kramer & Nick Martell. Hosted on Acast. See acast.com/privacy for more information.

Headlines: – Welcome to Mo News + Olivia Hello (2:00) – Senate Committee Votes To Hold Dr. Anthony Fauci In Contempt Of Congress (6:20) – Mitch McConnell Discharged From Hospital, But Questions Remain About His Senate Return (10:30) – Trump Signs New Executive Orders Targeting Birthright Citizenship (11:20) – How A Growing Left-Wing Media Ecosystem Is Helping Progressive Candidates Win (14:00) – FDA Reverses Course And Approves New mRNA Flu Vaccine (29:50) – GPS Interference Investigated In Fatal New Mexico Medical Plane Crash (32:20) – Government Shutdown Impacts Kentucky Organ Donations (34:20) – Cambridge's Youngest Black Professor Resigns Amid Plagiarism And Biography Questions (35:50) – Sam Altman's ChatGPT Post Sparks Debate Over Using AI To Parent (37:20) – What We're Watching, Reading And Eating This Week (44:20)  Thanks To Our Sponsors:  – Monarch - 50% off your first year | Code: MONEWS – Factor - 50% off your first box | Code: monews50off –⁠ Industrious⁠ - Coworking office. 50% off day pass | Code: MONEWS50 – LMNT | Free Sample Pack with any LMNT drink mix or 12oz cans purchase – ⁠Boll & Branch⁠ – 20% off first order, plus free shipping | Code: MONEWS

Sam Altman wants a supercomputer to talk to his kid so he doesn't have to. Elon thinks Grok can make a better Odyssey than Christopher Nolan. And Silicon Valley has been cultishly hyping AI so much that they've lost the plot. Regular people are sick of all the synthetic slop, they don't trust the tech titans, and their opposition to data centers is just the tip of the iceberg of a growing tech backlash. The political winds are shifting just in time for the midterms, so Elon's dumping more than $100 million to try to overcome them. The Atlantic's Charlie Warzel joins Tim Miller.show notes: TNL live at 9pm ET on Tuesday's primaries on YouTube or Substack Lauren on data centers in Democratic campaigns Charlie's "The Myth of SpaceX" Politico on the growing backlash against the AI buildout Jasmine Sun on how LLMs don't write well

In episode 2102, Miles and guest co-host Sofiya Alexandra are joined by he hosts of Debt Heads, Jamie Feldman & Rachel Webster, to discuss… RFK Jr. Really Lost His Sh*t On CNN, GOP Men Continue Their Streak Of Hating Women, Sam Altman Will Do Almost Anything To Avoid Actual Parenting and more! RFK Jr claims Biden is a ‘bigger threat to democracy’ than Trump RFK Jr loses temper in angry clash with CNN host over measles and Covid: ‘You want to sit here and attack me?’ New Analysis Shows Vaccines Could Have Prevented 318,000 Deaths Bash: "I am not saying nonsense, excuse me?…This is not productive. " RFK Jr: Dana, you probably don't understand this because you're not a scientist. BASH: Well you're not either! Rep. Max Miller: "My former wife has claimed that during a custody exchange at my home that day, I assaulted her…If I had assaulted her, would she have offered to cook me dinner six days later?" Sam Altman is still making the case for parenting via ChatGPT Sam Altman’s Parenting Strategy Sounds Low Key Horrifying Alex Hirsch to Sam Altman: "What if you just talked to your children" LISTEN: 2am by Slightly StoopidSee omnystudio.com/listener for privacy information.

Progressive candidates have serious momentum going into the upcoming primaries in Michigan and Wisconsin — but they'll have to figure out how to explain away some problematic old tweets. Meanwhile, Democrats land on a novel strategy for competing in deep red states (hint: it doesn't involve Democrats). Jon and Dan discuss the latest in all the key races, as well as Todd Blanche's failing nomination for attorney general, the administration's decision to deny disaster aid to four Democratic-led states, and Elon Musk's plan to pump $100 million into the midterms to support Republican candidates. Then, they check in on the AI singularity, which OpenAI CEO Sam Altman says has officially arrived, and debate how Democrats should talk about AI going forward.Hate listening to ads? Become a Friends of the Pod subscriber for ad-free episodes of Pod Save America, Pod Save the World, Lovett or Leave It, Runaway Country, Offline with Jon Favreau, and more—plus exclusive content, including bonus episodes of Pod Save America. Subscribe now at crooked.com/friends, on Apple Podcasts, or through the Pod Save America YouTube channel.To watch this episode with subtitles, click here and turn on closed captions (CC).You can also request a transcript by emailing transcripts@crooked.com. Include the podcast name, episode title, and air date. Please allow 48 hours for delivery.

This week the guys get into the Tucker Carlson x Sam Altman interview, whether convincing yourself you slept great actually works, and how many He-Man movies came out recently. They talk Supergirl and Superman, and why Sydney Sweeney was the obvious choice for Supergirl. Erik recaps a travel nightmare where his bags got shipped to two different states, plus the time Chris flew home with a Harry Potter broom. They debate whether headliners should let openers sell merch, react to the Odyssey salary list, argue about Matt Damon and De Niro, and swap audition stories, including losing a part to Jon Bernthal and the Workaholics tape that changed everything.00:00 The Ben Kingsley Callback01:09 Tucker Carlson x Sam Altman & AI03:51 Groggy Mornings & the Placebo Mindset07:06 Wait, There Are Two He-Man Movies?14:41 Supergirl, Superman & What's Wrong with DC21:54 Travel Nightmares: Lost Bags & a Harry Potter Broom30:18 Should Openers Sell Merch?36:42 Toy Movies: Matchbox, Hot Wheels & My Buddy41:54 The Odyssey & Who Gets Paid in Hollywood49:14 Audition Stories: Bernthal, Workaholics & Strong Choices59:42 Tour DatesGet two extra episodes every month at https://Patreon.com/TheGoldenHourPodcastTo submit to the show email: thegoldenhoursubs@gmail.com or Dropbox Link: https://www.dropbox.com/request/fqtbexhxyaky9X8f8MV1In the subject line, specify whether your submission is King It or Sting It, Debate Club, Rip My Drip, Relationship Advice, or Flaunt My Aunt. In the body of the email, include the attachment, your name, where you're from, and in the case of Flaunt My Aunt, the name of your relative.SUBSCRIBE to The Golden Hour Podcast: http://www.youtube.com/c/KingandtheSting Get your King and the Sting merch at https://thicccboy.com/collections/sale-home-pageFollow #TheGoldenHourInstagram: https://www.instagram.com/the.golden....Twitter:https://twitter.com/the_golden_hrFacebook: https://www.facebook.com/KingandtheStingAnd check out Brendan, Chris, & Erik on social media!Brendan Schaub:https://www.instagram.com/brendanschaubhttps://twitter.com/BrendanSchaubhttps://www.facebook.com/OfficialBren...Chris D'Elia:https://twitter.com/chrisdeliahttps://www.instagram.com/chrisdelia/https://www.facebook.com/chrisdeliaof...Erik Griffin:https://twitter.com/ErikGriffinhttps://instagram.com/erikgriffinhttps://www.facebook.com/erikgriffinc...See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.