Podcasts about Roblox

If you've been asking yourself, why does my child melt down over everything, you're not alone. Learn why emotional outbursts are often signs of nervous system overload—not bad behavior. Dr. Roseann Capanna-Hodge shares her Regulation First Parenting™ approach to help families create lasting calm and connection.Every parent has experienced it—that moment when asking your child to put on a shirt, turn off Roblox, or brush their teeth suddenly leads to tears, yelling, or total shutdown. It feels confusing because the reaction seems so much bigger than the situation.The good news? The meltdown isn't usually about the shirt, the game, or the transition. It's often the final drop in an already overflowing stress cup.Once you understand what's happening in your child's nervous system, everything starts to make more sense—and your parenting becomes far more effective.Why Does My Child Melt Down Over Everything?When your child's reaction feels completely out of proportion, it's natural to assume they're being defiant. But it's important to remember that behavior is communication.A meltdown often signals that your child's nervous system has become overwhelmed long before the explosion happened. School stress, lack of sleep, sensory overload, anxiety, social demands, or difficult transitions can all quietly fill their "stress cup."Key takeaways:Behavior is the symptom—not the root problem.Small triggers often become the "last straw."Neurotypical children dysregulate too, though neurodivergent kids may experience it more often.Imagine your child happily playing a game all afternoon. The request to stop isn't what caused the meltdown—it simply overflowed an already full nervous system.

Market update for Monday August 3, 2026Check out the Public app for incredible investing tools and to support the show (LINK)Follow us on Instagram (@TheRundownDaily) for bonus content and instant reactions.In today's episode, Zaid covers:Why the U.S. government stepped in to support the Japanese yenAstraZeneca's in talk over $400 billion merger with Bristol Myers SquibbFerguson Enterprises joining the S&P 500 Roblox's had worst day even after earnings Fun Fact: Spider-Man: Brand New Day nearly broke the all-time box-office opening record

2,5% Zinsen p.a. auf ein unbegrenztes Guthaben mit bis zu fünfmal der gesetzlichen Einlagensicherung*. Auch für Kinder. Das gibt's bei Scalable Capital. Mehr Infos hier.Trump stoppt Iran-Angriff. Amazon, Microsoft & Alphabet legen 1.500 Mrd. $ zu. Roblox, Reddit & Universal Music crashen über 20%. Novo Nordisk fällt wegen Studien-Flop. Schaeffler kappt Prognose. Alimentation Couche-Tard will Zabka.Perimeter Solutions (WKN: A40PUQ) hat quasi ein Monopol auf Löschmittel aus der Luft. Dahinter steckt TransDigm-Gründer Nick Howley. Starke Marktstellung, aber das Feuergeschäft stagniert trotz Brandsaison.CATL (WKN: A418NB) baut nicht nur E-Auto-Batterien. Back-Up-Batterien für KI-Rechenzentren boomen, Umsatz mit Speichern fast verdoppelt. Dazu Natrium-Batterien und über 150 Beteiligungen. Erwartetes KGV liegt bei 20.Diesen Podcast vom 03.08.2026, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung. *Veränderlicher Zins auf unbegrenztes Guthaben. Konditionen sowie Guthabenverteilung auf scalable.capital/tagesgeld. Learn more about your ad choices. Visit megaphone.fm/adchoices

In der heutigen #kassensturz Folge, unseren wöchentlichen Marketing & eCommerce News, geht es unter anderem um folgende Themen:bevh Zahlenhttps://bevh.org/daten-studienSHEIN: Börsenprospekt offenbart Zahlenhttps://de.fashionnetwork.com/news/Shein-was-aus-dem-borsenprospekt-in-hongkong-hervorgeht,1856068.htmlhttps://www.theinformation.com/briefings/sheins-hong-kong-ipo-filing-reveals-damage-done-end-de-minimis-rulehttps://momentumworks.substack.com/p/what-does-sheins-ipo-prospectus-actuallyhttps://chinesellers.substack.com/p/sheins-ipo-prospectus-reveals-forhttps://excitingcommerce.de/2026/07/30/der-shein-marktplatz-entwickelt-sich-besser-als-gedacht/TikTok Shop testet eigenes Prime-Abohttps://www.businessinsider.com/tiktok-is-testing-an-amazon-prime-style-membership-program-2026-7Temu verliert Millionen Nutzer in Polenhttps://chinesellers.substack.com/p/sheins-ipo-prospectus-reveals-forGoogle wegen Datentransfer nach China verklagthttps://topclassactions.com/lawsuit-settlements/lawsuit-news/google-hit-with-class-action-alleging-user-data-shared-with-temu-baidu/Finanzinvestoren greifen nach Ströerhttps://www.manager-magazin.de/unternehmen/dienstleister/stroeer-zwei-finanzinvestoren-wollen-kontrolle-beim-werberiesen-a-d21927d2-a8e3-4dac-ac14-c87539fac7d9MyMuesli-Gründer übernimmt wieder als CEOhttps://www.businessinsider.de/gruenderszene/mymuesli-gruender-kehrt-als-ceo-zurueck-wollen-wieder-pionier-werden/Myspace plant sein Comebackhttps://tech.yahoo.com/social-media/articles/myspace-owners-plan-comeback-173025561.htmlMeta baut Facebook im TikTok-Stil umwqk/sbb7729.htmlCreator bekommen ihre eigenen Awardshttps://www.criticschoice.com/the-critics-choice-association-announces-inaugural-critics-choice-creator-awards/EU gibt grünes Licht für Hugo-Boss-Übernahmehttps://www.tagesschau.de/inland/regional/badenwuerttemberg/swr-eu-kommission-gibt-gruenes-licht-fuer-moegliche-uebernahme-von-hugo-boss-100.htmlChatGPT und Roblox unter strengeren EU-Regelnhttps://www.it-boltwise.de/eu-plant-strengere-dsa-aufsicht-fuer-chatgpt-und-roblox-als-vlops.htmlOpenAI erweitert ChatGPT AdsEarnings Corner: Meta, Amazon & Reddit-> jeweils die offiziellen Shareholder StatementsMehr Informationen zu Billbee⁠⁠⁠⁠> Billbee 60 Tage lang kostenlos testen!⁠⁠⁠⁠Billbee bietet eine umfangreiche, aber einfach zu bedienende Auftragsabwicklung, Artikelverwaltung und Automatisierungslösung für Multichannel-Händler:innen.Im Vordergrund steht dabei die kanalübergreifende und zeitsparende Arbeit innerhalb nur eines cloudbasierten Tools.Dank der über 120 verschiedenen Schnittstellen und Partner aus allen E-Commerce relevanten Bereichen, können Online-Händler:innen ihr Business einfach und effektiv abwickeln. Zu den Anbindungen zählen u.a.MarktplätzeShopsystemeVersanddienstleister Buchhaltungssoftwares Zahlungsdienstleister … sowie Cloudspeicher, Fulfillment-Dienstleister und weitere!Durch die schnelle und intuitive Einrichtung, für die keine IT-Kenntnisse notwendig sind, ist der Start mit Billbee kinderleicht. Alle Funktionen sind dabei ab Start der Testphase bereits inklusive.Ein starker Fokus liegt darauf, dass Billbee von der Komplexität und von der Preisgestaltung besonders für Kleinst- und Kleinunternehmen attraktiv ist, ohne dass dabei die notwendige Skalierungsfähigkeit für größere Unternehmen auf der Strecke bleibt.LinkedIn-Beitrag von Melanie Bondza> ⁠⁠⁠⁠⁠⁠⁠⁠⁠Zum LinkedIn-Beitrag⁠⁠⁠⁠⁠⁠⁠⁠⁠Max & Kristina auf LinkedIn>⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠Max Rottenaicher⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠>⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠Kristina Mertens⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠CreditsLogo Design: Naim SolisIntro & Jingles: Kurt WoischytzkyFotos: Stefan GrauIntro-Video: Tim Solle

The EU just fined Google €890M for making it hard to steer users to cheaper web stores — another crack in the 30% wall, and genuinely good news for every developer. That's the lead of a quieter, summer-holiday news week, with Felix flying solo while Matej and Jakub are at ChinaJoy.Felix Braberg walks two stories and a charts tour. First, the European Commission fined Google €890M (split €460M + €430M) under the Digital Markets Act for antitrust practices — preventing developers from freely informing users about cheaper offers and steering them to web stores or third-party channels. Google has 60 days to comply or face periodic penalties of up to 5% of worldwide turnover (~$403B), and it's another blow in the slow unwinding of the 30% app-store tax that companies like FastSpring exist to route around. Second, a Seeking Alpha analysis argues the market keeps underestimating AppLovin: the stock came under pressure in 2026 (swept up in the "SaaS apocalypse" sell-off after the CloudX agentic-buying launch), but the fundamentals are strong, the gaming runway is bigger than assumed, and as the dominant mediation player (AppLovin Max), it holds a structural advantage. Then the US charts: Smash Fest (Flow Games, Turkey) is now #1 in free downloads — beating Roblox — followed by Meow Doku and Vita Mahjong (same studio), with the standout story being that a copycat of Smash Fest (Royal Smash by Cypher Games) has itself cracked the top six out of ~70 clones. Plus Level Devil sold and scaling under new ownership, EA Sports FC still strong post-World Cup, and Turkey vs China duking it out for chart dominance.The through-line of a quiet week: the 30% tax keeps cracking, AppLovin keeps winning, and the copycat economy is faster and more brutal than ever.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⏱️ TIMESTAMPS00:00 Solo news week — Matej and Jakub at ChinaJoy00:40 Google fined €890M under the Digital Markets Act04:00 Why it's another crack in the 30% wall05:00 AppLovin: why the market keeps underestimating it07:30 US charts — Smash Fest beats Roblox08:30 The copycat that cracked the top six10:00 Level Devil sold, EA Sports FC, and Turkey vs China---------------------------------------This is no BS gaming podcast 2.5 gamers session. Sharing actionable insights, dropping knowledge from our day-to-day User Acquisition, Game Design, and Ad monetization jobs. We are definitely not discussing the latest industry news, but having so much fun! Let's not forget this is a 4 a.m. conference discussion vibe, so let's not take it too seriously.Panelists: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jakub Remia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠r,⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Felix Braberg, Matej Lancaric⁠Join our slack channel here: https://join.slack.com/t/two-and-half-gamers/shared_invite/zt-3bckldvr8-8PXvzciMWdheOzED9hq0SA---------------------------------------Matej LancaricUser Acquisition & Creatives Consultant⁠https://lancaric.meFelix BrabergAd monetization consultant⁠https://www.felixbraberg.comJakub RemiarGame design consultant⁠https://www.linkedin.com/in/jakubremiar---------------------------------------Please share the podcast with your industry friends, dogs & cats. Especially cats! They love it!Hit the Subscribe button on YouTube, Spotify, and Apple!Please share feedback and comments - matej@lancaric.me---------------------------------------If you are interested in getting UA tips every week on Monday, visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠lancaric.substack.com⁠⁠⁠⁠⁠⁠ & sign up for the Brutally Honest newsletter by Matej LancaricDo you have UA questions nobody can answer? Ask ⁠⁠⁠⁠⁠⁠⁠⁠Matej AI⁠⁠⁠⁠⁠⁠ - the First UA AI in the gaming industry! https://lancaric.me/matej-ai

Clair Obscur znów zgarnia nagrody, Castlevaniachwali się brakiem AI podczas gdy Roblox pozwala tworzyć gry promptem ztelefonu, a wściekli fani PlayStation planują tygodniowy blackout. 

In deze aflevering neem ik je mee in mijn persoonlijke zoektocht naar balans in een wereld die soms overweldigend voelt. Ik deel mijn eerlijke gedachten over waarom sommige gebeurtenissen me ogenschijnlijk niet meer raken – is dat apathie, of is het zelfbescherming?Ik sta uitgebreid stil bij een thema dat me nauw aan het hart ligt: het opvoeden van onze kinderen in een digitale wereld. Waarom ik er bewust voor kies om mijn kinderen zo lang mogelijk weg te houden bij social media, en hoe ik probeer hen te begeleiden bij technologieën als Roblox en AI, zonder de verbinding te verliezen.Van het belang van eerlijkheid naar jezelf tot de uitdagingen van het 'anders leren vasthouden' van je opgroeiende kinderen; het is een gesprek over de grijstinten in het leven. Want niet alles is zwart-wit, en soms is 'vallen en opstaan' – mét een flinke dosis liefde – het enige wat we kunnen doen.#opvoeding #digitalewereld #socialmedia #ouderschap #technologie #bewustleven #kinderen #kimyilic #kikdepodcast #veiligonline

In der heutigen Folge sprechen die Finanzjournalisten Lea Oetjen und Holger Zschäpitz über Freud und Leid bei Amazon und Apple, die enttäuschenden Zahlen von Coinbase und den historischen Fall von Adidas. Außerdem geht es um Microsoft, Roblox, Reddit, Monolithic Power Systems, AXT, Marvell Technology, Live Nation Entertainment, Western Union, Infineon, Siemens Energy, Siemens, Hochtief, Siltronic, Nemetschek, TeamViewer, SAP, IREN, Nebius, Sandisk, Micron Technology, SK Hynix, Bloom Energy, CoreWeave, Core Scientific, Nvidia, AMD, Broadcom, Adobe, Arm Holdings, Lam Research, Schneider Electric, Ahold Delhaize und Walmart. Mit dem Code „AAAFRIENDS“ sparst du 50 Prozent auf dein Ticket – aber nur unter folgendem Link. https://veranstaltung.businessinsider.de/event/financesummit26/summary?rp=c6dc55d6-6f4f-4fb4-b75f-3f3501d84859 Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Hier könnt ihr den AAA-Newsletter abonnieren: https://www.welt.de/newsletter/article232797673/Alles-auf-Aktien-Der-taegliche-Boersen-Newsletter-fuer-WELTplus-Abonnenten.html Und – ganz neu: AAA gibt es jetzt auch auf Instagram: https://www.instagram.com/alles_auf_aktien/ Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien Anzeige: Eight Sleep: Der Pod 5 reguliert die Temperatur im Bett automatisch, trackt Schlaf- und Gesundheitswerte ohne Wearable und kann so zu besserem Schlaf beitragen. Mit dem Code ALLESAUFAKTIEN erhaltet ihr auf https://www.eightsleep.com/allesaufaktien bis zu 350 Euro Rabatt. Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

Roblox is one of the biggest gaming platforms in the world... but is it just a fun game for kids, or is there more parents need to know?This week on Co-op Chronicles, Blacklabel, Geisha, and Azzi dive into the world of Roblox from both a gamer's and a parent's perspective. We explore why millions of kids love the platform, the creativity it inspires, and the real dangers that can exist behind the screen.Blacklabel also shares a personal story about his oldest daughter being scammed in Adopt Me, and how that experience changed the way he thinks about online gaming and internet safety.This isn't an episode about fear.It's an episode about understanding the games our kids love, recognizing the risks, and having the conversations that matter.Whether you're a parent, a gamer, or just curious about Roblox, this is a conversation worth having.

In today's MadTech Daily, we cover ChatGPT and Roblox facing the EU's toughest platform rules, Elon Musk settling X's ad group lawsuit, and Meta's shares falling amid investor concerns over rising AI spending.

Werbung | Handelsblatt mit 50% Rabatt: Sichert euch jetzt für 12 Monate vollen Zugriff auf alle digitalen Inhalte des Handelsblatts mit 50% Rabatt. Alle Infos zum Angebot findet ihr unter: www.handelsblatt.com/rabatt50 Die Wall Street startet freundlich in den Freitag, mit dem Nasdaq aber unter den Tageshochs. Nach der kräftigen Erholung vom Donnerstag setzen Anleger weiter auf eine Stabilisierung der KI-Aktien. Auslöser ist zum einen die Entspannung rund um den Hedgefonds Situational Awareness, dessen Portfoliotransaktionen zuletzt als wesentlicher Treiber der massiven Verkäufe im KI-Sektor galten, zum anderen eine überzeugende Zahlenflut aus dem Technologiesektor. Im Mittelpunkt steht Amazon. Der Konzern steigerte den Umsatz um 20 Prozent, das Cloud-Geschäft AWS wuchs um beeindruckende 37 Prozent, das stärkste Wachstum seit 18 Quartalen, und die operative Marge erreichte außergewöhnlich hohe 39,4 Prozent. Gleichzeitig zeigt sich jedoch die Kehrseite des KI-Booms: Der freie Cashflow rutschte auf minus 9 Milliarden US-Dollar, während die Investitionen in KI-Infrastruktur auf rund 220 Milliarden US-Dollar erhöht werden. Apple legte zwar bessere Quartalszahlen als erwartet vor, belastete die Börse jedoch mit einem schwächeren Ausblick. Vor allem das Dienstleistungsgeschäft sowie das China-Geschäft blieben hinter den Erwartungen zurück, während das Management für das laufende Quartal auf Lieferengpässe und Währungseffekte verwies. Makroseitig richtet sich der Blick heute auf den Arbeitskostenindex, den Einkaufsmanagerindex aus Chicago sowie das endgültige Verbrauchervertrauen der Universität Michigan. International sorgen die überraschend restriktiven Signale der Bank of Japan, schwache chinesische Einkaufsmanagerindizes und eine leicht über den Erwartungen liegende Kerninflation in der Eurozone für zusätzliche Aufmerksamkeit. Unter den weiteren Unternehmenszahlen überzeugen Chevron, Reddit, Eaton, MasTec und DexCom mit starken Ergebnissen und teils angehobenen Prognosen. Coinbase und Roblox enttäuschen dagegen mit schwächeren Geschäftszahlen und einem verhaltenen Ausblick. Ein Podcast - featured by Handelsblatt. ► Erhalte einen exklusiven 15% Rabatt auf Saily eSIM Datentarife! Lade die Saily-App herunter und benutze den Code wallstreet beim Bezahlen: https://saily.com/wallstreet * ► Entdecke den exklusiven NordVPN Deal! Jetzt risikofrei testen mit einer 30-Tage-Geld-zurück-Garantie: https://nordvpn.com/wallstreet * ► Direkt an der Börse handeln mit tradegate.direct: https://bit.ly/WallStreet_Juni * +++ Alle Rabattcodes und Infos zu unseren Werbepartnern findet ihr hier: https://linktr.ee/wallstreet_podcast +++ Impressum: https://www.360wallstreet.de/impressum *Werbung

Die Wall Street startet freundlich in den Freitag, mit dem Nasdaq aber unter den Tageshochs. Nach der kräftigen Erholung vom Donnerstag setzen Anleger weiter auf eine Stabilisierung der KI-Aktien. Auslöser ist zum einen die Entspannung rund um den Hedgefonds Situational Awareness, dessen Portfoliotransaktionen zuletzt als wesentlicher Treiber der massiven Verkäufe im KI-Sektor galten, zum anderen eine überzeugende Zahlenflut aus dem Technologiesektor. Im Mittelpunkt steht Amazon. Der Konzern steigerte den Umsatz um 20 Prozent, das Cloud-Geschäft AWS wuchs um beeindruckende 37 Prozent, das stärkste Wachstum seit 18 Quartalen, und die operative Marge erreichte außergewöhnlich hohe 39,4 Prozent. Gleichzeitig zeigt sich jedoch die Kehrseite des KI-Booms: Der freie Cashflow rutschte auf minus 9 Milliarden US-Dollar, während die Investitionen in KI-Infrastruktur auf rund 220 Milliarden US-Dollar erhöht werden. Apple legte zwar bessere Quartalszahlen als erwartet vor, belastete die Börse jedoch mit einem schwächeren Ausblick. Vor allem das Dienstleistungsgeschäft sowie das China-Geschäft blieben hinter den Erwartungen zurück, während das Management für das laufende Quartal auf Lieferengpässe und Währungseffekte verwies. Makroseitig richtet sich der Blick heute auf den Arbeitskostenindex, den Einkaufsmanagerindex aus Chicago sowie das endgültige Verbrauchervertrauen der Universität Michigan. International sorgen die überraschend restriktiven Signale der Bank of Japan, schwache chinesische Einkaufsmanagerindizes und eine leicht über den Erwartungen liegende Kerninflation in der Eurozone für zusätzliche Aufmerksamkeit. Unter den weiteren Unternehmenszahlen überzeugen Chevron, Reddit, Eaton, MasTec und DexCom mit starken Ergebnissen und teils angehobenen Prognosen. Coinbase und Roblox enttäuschen dagegen mit schwächeren Geschäftszahlen und einem verhaltenen Ausblick. Abonniere den Podcast, um keine Folge zu verpassen! ____ Folge uns, um auf dem Laufenden zu bleiben: • X: http://fal.cn/SQtwitter • LinkedIn: http://fal.cn/SQlinkedin • Instagram: http://fal.cn/SQInstagram

Microsoft surged 15% on its fastest cloud growth since 2022, while Meta slid 10% defending its AI spending. Aschenbrenner's hedge fund unwound positions after the AI rout, the EU targeted ChatGPT under the DSA, and airlines let AI set fares. Microsoft's Shares Surge on Fastest Cloud Growth Since 2022 (Bloomberg) Meta Falls After Defending AI Bets to Skeptical Investors (Bloomberg) AI investor Leopold Aschenbrenner forced to unwind all public stock positions after steep losses, sources say (CNBC) Source: the European Commission plans to designate OpenAI's ChatGPT and Roblox as "very large online platforms" under the DSA as soon as August (Bloomberg) Airlines are using AI to adjust seat prices more quickly, capturing more revenue while narrowing the pricing gaps that once let travelers find bargain fares (Bloomberg) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

Het is zomer en traditiegetrouw een luwe periode als het gaat om de verschijning van nieuwe games. Zo kun je op het strand liggen (een favoriete bezigheid van Donner), genieten van een drankje op het terras óf je onderdompelen in een nieuwe game. Daarom deelt Jochem Visser met Joe van Burik en Donner Bakker zijn lijstje met games waar je weinig over hoort, maar die het spelen zeker waard zijn in deze Mini-Game Round-Up van All in the Game. Jochems lijstje: Thick as Thieves Mörk Borg Heresy Supreme Sultan's Game Travelling by Night (update) Vragen? Mail ons! Op allinthegame@bnr.nl Over All in the GameAll in the Game is de podcast over games voor iedereen. Wanneer er iets speelt in de wereld van games, hoor je dat hier: spannende ontwikkelingen, boeiende onderzoeken en natuurlijk de nieuwste releases om te spelen op je PlayStation, Xbox, pc of welk platform dan ook. Onder leiding van BNR's techredacteur Joe van Burik hoor je gesprekken met andere gamekenners, zoals beursnerd Jochem Visser, techredacteurs Niels Kooloos en Daniël Mol én popcultuurkenners Donner Bakker en Sam van Zuilen. Ook hoogleraar computerwetenschappen Felienne Hermans en universiteit docent Laura van der Lubbe schuiven geregeld aan, en je hoort bijdragen van audioproducers André Dortmont, Ivo Klokman en Jeanne Heeremans. Elke week zijn er minimaal twee afleveringen van All in the Game. Of nog meer, wanneer er veel speelt in de wereld van games. Soms met impressies en analyses over actuele ontwikkelingen en nieuwe games. Andere keren kun je luisteren naar interviews met makers van bijzondere games, van Grand Theft Auto (GTA) tot Baldur's Gate 3 - zowel Nederlandse als internationale ontwikkelaars. Of we praten met e-sport-atleten, onderzoekers en andere experts in de wereld van videogames. In deze podcast kijken we verder dan alleen wat een game leuk maakt: we bespreken juist ook in de culturele, maatschappelijke, economische en technologische impact ervan. Jaarlijks gaat er immers zo'n 200 miljard euro om in de wereldwijde game-industrie, dat is al (vele jaren zelfs) daadwerkelijk meer dan de muziek- en filmindustrie bij elkaar opgeteld. Zo hoor je bij All in the Game niet alleen wat je moet spelen - en op welk nieuwe (game)platform - maar kun je daar nog bewuster mee bezig zijn, over praten en natuurlijk van genieten. Of het nou gaat om Super Mario of Sonic the Hedgehog, Fortnite of Roblox, voetbalgames van EA Sports FC of de FIFA, Call of Duty of Battlefield, League of Legends of Dota,of goude oude titels zoals Tetris, Rollercoaster Tycoon, The Sims of zelfs Snake. En we hebben ook aandacht voor liefhebberijen die dicht op games zitten, zoals Dungeons & Dragons, Lego en de films, series en strips rond reeksen zoals Star Wars en Marvel. Het komt allemaal aan bod in All in the Game. All in the Game werd als podcast al in 2022 opgenomen in het archief van Het Nederlands instituut voor Beeld & Geluid in Hilversum - als eerste podcast van BNR Nieuwsradio en één van de eerste gamepodcasts van allemaal. Gezamenlijk met talloze Nederlandse televisieprogramma’s, radioshows, games, websites, webvideo’s en podcast vormt dit materiaal de Nederlandse mediageschiedenis. Over Joe van BurikJoe van Burik is presentator, podcastmaker en techredacteur bij BNR Nieuwsradio. Je hoort hem bijna dagelijks in de Tech Update met het laatste nieuws over digitale technologie, en gaat daar in De Grote Tech Show (samen met Ben van der Burg) elke woensdag dieper op in met gasten uit de techwereld. Daarnaast maakt hij onder meer de podcast All in the Game, voor iedereen die meer wil horen over videogames.See omnystudio.com/listener for privacy information.

Actor and comedian David Koechner (Anchorman, The Office) joins TigerBelly for the first time. We chat the Larry David cut, Comedy Store Obamas, makeshift tampons, SNL stories, 50-year-old grunts, Roblox weridos, and the Canadian comedy scene.Download the Bilt app and join the membership for where you live, at joinbilt.com/belly.For simple, online access to personalized and affordable care for Hair Loss, Weight Loss, and more, visit www.hims.com/BELLY See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On this special episode of Have a Seat, Chris Hansen Chris brings you the Roblox session from CrimeCon Las Vegas. There, Hansen was joined by victim turned online safety advocate, Schlep; Louisiana Attorney General Liz Murrill and sexual assault attorney Martin Gould to educate attendees of the dangers lurking on the gaming platform Roblox.  Dangerous Games: A Chris Hansen Investigation: Watchtrublu.comhttps://www.youtube.com/@RealSchlephttps://gghlaw.com/https://www.ag.state.la.us/About This episode is brought to you by: Home Title Lock: Go to https://hometitlelock.com/chrishansen and use promo code HANSEN to get a FREE title history report and a FREE TRIAL of their Triple Lock Protection! For details visit https://hometitlelock.com/warranty AquaTru: Head to https://AquaTru.com & use code HANSEN for 20% off your purifier and a 30-day best-tasting water guarantee Learn more about your ad choices. Visit megaphone.fm/adchoices

Protecting Kids From Online Grooming and Sextortion with Laura Parker of The Exodus Road   Andy Murphy hosts the Secure Family Podcast. Today he interviews Laura Parker, CEO and co-founder of The Exodus Road, a global nonprofit fighting human trafficking. She explains how exploitation has moved online, enabling predators to groom and extort many children quickly through platforms like Instagram, Roblox, and apps with disappearing messages.   They discuss the signs of grooming like "love bombing." Laura emphasizes frequent micro-conversations, building trust so kids report problems without fear, and steps after an image is shared. Take control of your data with DeleteMe. Because they sponsor the podcast you can get 20% off a privacy plan from DeleteMe with promo code: DAD.  Protect your senior parents from scams with this free video series. It will share why older Americans are being targeted as well as break down today's scams so you know the red flags to spot. Watch Part 1 on YouTube now. Connect

Your weekly guide to the music biz and how it all works. This week, Stu and Joe comb their Emo fringes, use a tie as a belt, and pout about this week's music industry news:→ A surprising percentage of Americans are actually MORE interested in music if it was made using AI – according to a new survey.→ In last week's episode, we talked about a data breach at Suno that seemed to have given the game away on what music it trained its models on. But there's been a development…→ Spotify has a brand new daily music videos chart. Is it now officially The New MTV? And does this mean full-length music videos haven't been killed off by TikTok after all? → The UK has a new prime minister, he's a New Order stan, and one of his first moves was focused on helping grassroots music venues and clubs…→ What's the latest big music trend in Mexico? It's erm, emo…→ Live Nation wants YOU to become a festival promoter. But happily for your stress levels and financial standing, this is just for pretend on Roblox.→ AND FINALLY… KPop Shark Heroes!And in the special post-show lock-in section just for our ⁠⁠Patreon Superfans⁠⁠, Stu and Joe prop themselves up at the bar – in this week's bonus material: Stuart has a new favourite music wearable: a Game Boy-inspired digital music player on Kickstarter. It's time for a Little Grandad Update!Discogs and crazy vinyl prices: which 00's band has the highest-priced record sold on Discogs so far this year?https://www.discogs.com/digs/collecting/the-most-valuable-records-sold-on-discogs-in-2026-so-far/===================================As ever, we welcome your feedback, emails and – in particular – any questions you might have about how the music biz works!Email us: ⁠⁠⁠⁠⁠thepriceofmusicpodcast@gmail.com⁠⁠⁠⁠⁠See you next week!Stuart and Joe======TPOM online: ⁠http://tpom.uk/⁠Support The Price of Music on Patreon:⁠⁠⁠⁠⁠https://www.patreon.com/ThePriceofMusic⁠⁠⁠Follow Stuart on X - @stuartdredgeFollow The Price of Music on X - @PriceofMusicpodFor sponsorship opportunities, please email - ⁠⁠⁠joe@musically.com⁠

This Week on True Crime News The Podcast: A missing teen isn't deemed endangered until it's too late. When teenager Ashley Buzbee left her home with a man she met online gaming, cops classified her as a runaway. Weeks later Tyler Thomas led police to her remains but maintains his innocence in her slaying.Alison Triessl joins host Ana Garcia.

Send us Fan MailNintendo says customers received exactly what they paid for and are not entitled to any portion of the company's potential tariff refund. Is Nintendo legally correct, morally wrong—or both?Xbox is also testing free, ad-supported cloud gaming that allows players to stream games they already own without a Game Pass subscription. We explain why the current offer may actually benefit players, while establishing the lines Microsoft cannot be allowed to cross.Also in this episode:• A Florida man allegedly used malware-infected Steam games to steal cryptocurrency from gamers. • Pokémon card stores are being targeted in smash-and-grab robberies across the United States and Australia. • A West Virginia lawmaker and teacher faces a federal charge involving the alleged exploitation of a minor after communication that began through Roblox. • KFC launches Simpsons and Evangelion menus. • McDonald's introduces Honey Brown Butter breakfast sandwiches. • Starbucks prepares 5 Orange Cream drinks. • OMEA and the After End Demo are recognized as our Games of the Week.Join NickMoses05 and the MoFam for gaming news, strong opinions, food madness, and debates that go beyond the headlines.Support the show

In this episode, we pull back the curtain on one of the most disturbing and fast-growing threats in the digital landscape: 764 and the wider network known as "The Com". Operating at the intersection of Nihilistic Violent Extremism (NVE), cyberstalking, and severe online child exploitation, 764 is not a traditional political or religious terrorist group. Instead, it functions as a decentralized, clout-driven subculture that targets vulnerable minors through mainstream gaming and social platforms, coercing them into horrifying acts of self-harm, abuse, and violence. Through investigative insights and expert analysis, this episode explores how these networks operate, why law enforcement agencies worldwide are designating them as terrorist organizations, and what parents, educators, and platforms must do to protect youth.

Megyn Kelly discusses the latest developments in the Nolan Wells case, Wells' best friend speaking out and revealing the last moment he saw Wells, new details about how Wells' family found out he was missing, fact-checking a Democratic politician getting all the facts of the Nolan Wells story wrong, the politician spreading racial lies about the circumstances, and more. Then Chris Hansen, investigative journalist and host of "Takedown," joins to discuss why Nolan Wells' best friend speaking out appears credible, the different scenarios which could explain what happened to Wells after his friends left, why it's good the police aren't getting ahead of the case in the media, his years on NBC's "To Catch a Predator," behind-the-scenes stories from his predator investigations, why he calls the children's game Roblox "a playground for predators," the risks kids face while engaging with adult strangers, the disturbing online group of criminals known as "764," some of his most shocking predator confrontations, his calm interview strategy when faced with these criminals, practical steps parents can take to protect their children online, the dangers of social media and our new digital environment, and more.   More from Chris Hansen- watchtrublu.com   ARMRA: go to https://tryarmra.com/MEGYN to get 30% off your first subscription order Supersure Insurance: Upgrade your business insurance to a year-round SuperAgency at https://Supersure.com/Megyn American Financing: Call American Financing today to find out how customers are saving an average of $800/mo. NMLS #182334 https://nmlsconsumeraccess.org. APR for rates in the 5s start at 6.327% for well qualified borrowers. Call 800-852-2010 for details about credit, costs and terms. Visit https://AmericanFinancing.net/MegynKelly . Average savings based on borrowers who save over $199.99 Birch Gold: Text MK to 989898 and get your free info kit on gold     Follow The Megyn Kelly Show on all social platforms: YouTube: https://www.youtube.com/MegynKelly Twitter: http://Twitter.com/MegynKellyShow Instagram: http://Instagram.com/MegynKellyShow Facebook: http://Facebook.com/MegynKellyShow Find out more information at:https://www.devilmaycaremedia.com/megynkellyshow Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Shams and Fernando bring on their buddy Jon Shafer (former Lead Designer on Civ V) from Conifer Games to cut through the noise and break down the actual state of PC gaming post-Steam Next Fest! Spoiler alert: that 2010s indie golden age everyone misses? It's dead and buried. Jon's been obsessively tracking Steam data (while juggling his double PC setup optimized for Steam demos), and the new reality is, well to be honest, brutal. To survive today, developers either need to pump out a game in two months or bleed over it for up to 14 years - there is zero in-between. Welcome to the "go short or go long" meta. The trio also look into the wildest trends currently hijacking the platform such as the unapologetic explosions of co-op "friend slop," the massive wave of players jumping between Roblox and Steam, and why traditional buying habits are out while cult-level fandom is in. In short - the dev scene might be an absolute bloodbath right now, but for players? We might just be sitting in a brand-new golden age. Thanks for listening! The BBC article Designer Notes Podcast

Thursday, July 23, 2026 Today, a modeling scout who connected women to Epstein has been found dead in France; Donald Trump has just approved a deal with Saudi Arabia to let them build nuclear reactors; Arizona held its primary elections and we'll go over the results; West Virginia Republican House member Elliott Pritt has been charged with soliciting a minor; the Justice Department is quietly investigating Florida Republican Rep. Cory Mills; plus Allison delivers your Good News. Thank You, Smalls For a limited time, get 60% off your first order, plus free shipping and free treats for life, when you head to Smalls.com/DAILYBEANS Thank You, HomeServe For 50% less your first year, go to HomeServe.com/dailybeans. Void in Florida. The Daily Beans is proud to partner with Miles Taylor and our friends at DEFIANCE.org For a limited time, members of the Daily Beans community can receive a FREE 3-month full membership to DEFIANCE.org and gain access to one of the fastest-growing pro-democracy movements in America. Join here: https://www.defiance.org/beans Join The Daily Beans and give a gift today to ensure The Trevor Project can continue its crucial work in the face of continued challenges. Donate to The Trevor Project - Daily Beans Podcast The Latest Breakdown→ Epstein Survivor Recounts Meeting With Todd Blanche StoriesDaniel Siad, Model Scout Who Connected Women to Epstein, Is Found Dead in France | The New York Times DOJ is quietly investigating Cory Mills | MS NOW House Speaker calls on GOP Del. Elliot Pritt to resign after arrest for soliciting 15-year-old girl | West Virginia Watch Arizona primary takeaways: Trump's picks prevail and a House Democrat survives | Washington Post Trump Approves Landmark Nuclear Deal With Saudi Arabia in Big Win for Kingdom | WSJGood TroubleVolunteer with Powered By People and Help save Texas from Ken Paxton! Check your voter registration and deadlines → Voter Registration Deadlines - Vote.org →Help save Texas from Ken Paxton! →Urge Democrats to Oppose and Stop Trump's Crypto Corruption | Indivisible Guide →Defiance.org/beans →Show up for our Libraries - action.ala.org →Stand With Minnesota →ICE List  →iceout.org Good NewsSan Diego Humane Society, Humane Pennsylvania Adopt Memphis and Maddie http://PacificWildlifeCare.org dana-goldbergs-southwest-funnyfest Oct 9 -Email Dana@DanaGoldberg.com for sponsorship informationTickets for Dana Goldberg: Outrageous - Sep 23 - Den Theater - Chicago  →Share your Good News & Good Trouble - The Daily Beans →Beans Talk audio -beans-talk.simplecast.com →Email Dana LGBTQ Owned eating establishments in your area - hello@mswmedia.com Subject: “Dana's Project” Subscribe to the MSW YouTube Channel - MSW Media - YouTube Our Donation Links The Trevor Project - trevorproject.org/beans Blue Wave California - https://secure.actblue.com/donate/msw-bwc Donate to Public Citizen - https://citizen.org/beans/ Donate to It Gets Better / The Daily Beans Fundraiser Pathways to Citizenship link to MATCH Allison's Donationhttps://crm.bloomerang.co/HostedDonation?ApiKey=pub_86ff5236-dd26-11ec-b5ee-066e3d38bc77&WidgetId=6388736 Join Dana and The Daily Beans in support of Human Rights Campaign http://onecau.se/_ekes71National Security Counselors - Donate, ActBlue.com/donate/msw-bwc, WhistleblowerAid.org/beans Dr. Allison Gill - The Breakdown | Allison Gill, Mueller, She Wrote @muellershewrote.com - Bluesky, MSW & The Daily Beans Podcast @muellershewrote - Instagram, MSW Media - YouTube →Federal workers - email AG - fedoath@pm.me Dana Goldberg - Dana is on Patreon! At Dana's Dugout, @dgcomedy - Bluesky, @dgcomedy - IG, Dana Goldberg - Facebook,  DanaGoldberg.com More from MSW Media - Shows - MSW Media, Cleanup On Aisle 45 pod, The Breakdown | Allison Gill Reminder - you can see the pod pics if you become a Patron. The good news pics are at the bottom of the show notes of each Patreon episode! That's just one of the perks of subscribing! patreon.com/muellershewrote Listener Survey:http://survey.podtrac.com/start-survey.aspx?pubid=BffJOlI7qQcF&ver=shortFollow the Podcast on Apple:https://apple.co/3XNx7ckWant to support the show and get it ad-free and early?https://patreon.com/thedailybeanshttps://dailybeans.supercast.com/https://apple.co/3UKzKt0 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

If you are looking for a review of the odyssey, you wont find it here, but we have other exciting news. Like Disney cuts Pixar staff, even after making a billion dollars. Or Is Nintendo justified in telling consumers to stuff it after tariff refunds? PlayStation ain't budging on ditching discs, and some sales numbers back them up. But hey, at least we got a trailer for Avengers Doomsday!

P.M. Edition for July 22. WSJ special writer Theo Francis explains how startup founders, hedge-fund managers and Silicon Valley insiders are using IRAs to supercharge their wealth. Plus, trade uncertainty comes roaring back. WSJ trade and economic policy reporter Gavin Bade explains the Trump administration's new front on tariffs. And Journal reporter Sam Federman explains how the New York Mets turned baseball's highest payroll into its biggest waste of money. Danny Lewis 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.

Your weekly guide to the music biz and how it all works. This week, Stu and Joe are back from two weeks' holiday in Rhyl – and immediately hop into a golf cart along with Ronaldo and Ronaldinho to go through this week's music biz news:→ More than 50%(!) of all new music being uploaded to streaming services is now AI-generated. How might the music industry respond to this? With... a system of labels (not the record kind…)→ Stu's Big Number is 1.124 billion... but which mega-song does it relate to? (If you're a parent, you'll know it only too well…)→ Someone's leaked the code of Suno, the biggest AI-music service, and they claim they know what it trained its models on...→ The latest startup hoping to help artists make some money directly from their biggest fans is Lume, and it's got Lorde's backing→ Lorde has also been giving a right Royals bashing to Meta and Spotify... but why?→ Michael Jackson biopic ‘Michael' got a mixed response from critics (OK, they thought it was rubbish). But at the box-office it's a huge hit: to the tune of ONE BILLION dollars…→ The Rolling Stones (collective age of their three founder members: 243) are now on Roblox, the platform famously used by children. But is this a surprisingly good fit?And in the special post-show lock-in section just for our ⁠⁠Patreon Superfans⁠⁠, Stu and Joe prop themselves up at the bar – in this week's bonus material: → Following the last episode featuring plastic bottles being turned into Ed Sheeran Records – could Ed Sheeran records be turned back into plastic bottles?→ A recap on the World Cup half-time extravaganza: Madonna! Ronaldo/Ronaldinho! Muppets! Bieber! Vuvuzelas! BTS!→ Stuart rhapsodises about seeing the Beta Band live, including some epic four-man bongo wigouts→ Good overlooked deep-cut World Cup songs, including  Chin Up by The Rhythm Method (https://www.youtube.com/watch?v=8KqmUtU1QEM)===================================As ever, we welcome your feedback, emails and – in particular – any questions you might have about how the music biz works!Email us: ⁠⁠⁠⁠⁠thepriceofmusicpodcast@gmail.com⁠⁠⁠⁠⁠See you next week!Stuart and Joe======TPOM online: ⁠http://tpom.uk/⁠Support The Price of Music on Patreon:⁠⁠⁠⁠⁠https://www.patreon.com/ThePriceofMusic⁠⁠⁠Follow Stuart on X - @stuartdredgeFollow The Price of Music on X - @PriceofMusicpodFor sponsorship opportunities, please email - ⁠⁠⁠joe@musically.com⁠

After raising prices on many of its products a few weeks ago, Apple has raised prices again, this time on services like iCloud and Apple Music. Is it too much? How much will iPhone prices go up? We share our thoughts, plus plenty more in this episode. Watch on YouTube! - Notnerd.com and Notpicks.com INTRO (00:00) MAIN TOPIC: Apple raises more prices (03:30) Apple raises prices for Apple Music and Apple One subscriptions Apple faces imminent iPhone price hikes amid chip shortage DAVE'S PRO-TIP OF THE WEEK: Back up before beta-ing. (13:15) JUST THE HEADLINES: (18:05) Robot decapitated in world's first-ever humanoid UFC fight Kalshi flags Trump's teleprompter operator after making more than $100K betting on Kalshi markets France orders ISPs to block access to Polymarket Amazon Web Services customers receive bills for up to $1.5 Trillion after global glitch Spotify is now an AI chatbot, too Roblox is shutting down its video chat service Astronauts take first X-rays in space WITHIN REACH! Dave is up 10-6, Round 19, Nate goes first (20:20) TAKES: Unauthorized AI biographies are all over Amazon (28:50) NY school to introduce first humanoid robot in US classroom — and vows 'Sally' will never replace teachers (30:45) BONUS ODD TAKE: Moist Towelette Online Museum (32:40) PICKS OF THE WEEK:  Dave:  SMALLRIG SSD Magnetic Phone Mount Bracket SSD Holder with Magsafe, 45-70mm（1.77''-2.76'' Wide Clamping, 1/4"-20 Threads and Cold Shoe, for Samsung T3/T5, for SanDisk, for Crucial, for iPhone - 5157 (39:15) Nate: Umisleep Soft Sleep Mask, Blackout Eye Mask for Side Sleepers, Comfortable Sleep Mask for Women Men, Satin Eye Masks for Sleep with Wide Band, Sleeping Mask, Blindfold, Black (44:50)

Are you looking to save time, make money, and start winning with less risk? Then head to https://www.ovtlyr.com.Learn more about OVTLYR: https://youtu.be/TUCbD5KovlcThe market still looks bullish on the surface... but underneath? The cracks are starting to show. Breadth is weakening, bond yields are climbing, and more stocks are quietly flipping to sell signals. The question isn't whether the market can keep going higher... it's whether you're buying at the right time or showing up after everyone else already has.This conversation dives into one of the biggest mistakes traders make—chasing the hottest sectors after they've already exploded higher. Using OVTLYR's new Sector Intelligence Map, the discussion breaks down how to identify industries that are just beginning to gain momentum instead of becoming the last buyer before the crowd heads for the exits. There's also a fascinating look at why buying the rip often beats buying the dip, and how market cycles repeat themselves over and over.One of the biggest takeaways has nothing to do with predicting the future. It's about stacking probabilities in your favor. Instead of chasing headlines or following the herd, the episode explains how sector rotation, buy signal participation, and disciplined risk management can help traders stay ahead of the crowd while avoiding the emotional trap of buying at peak greed.There's also a complete market update covering SPY, QQQ, market breadth, bond yields, equal-weight performance, active portfolio management, Roblox, Coca-Cola, Apple, GameStop, Box, and how professional traders stick to their plan—even during frustrating drawdowns.✅ SPY, QQQ, market breadth, and bond yield analysis✅ OVTLYR Sector Intelligence Map and sector rotation strategies✅ Why buying the rip beats buying the dip✅ Portfolio updates with Apple, Roblox, GameStop, Box, and Coca-Cola✅ Trading psychology, risk management, and avoiding the herd mentalityIf you've ever bought a stock right before it started falling... or wondered how professionals spot strong sectors before everyone else does... this episode is packed with lessons you can apply immediately.Subscribe to OVTLYR for disciplined trading strategies that actually make sense.

Watch or listen to episode 327 of the Digital and Social Media Sports Podcast, in which Neil chatted with Joe Farren, Innovation Consultant, Future Sport Co. Joe Farren has sat in a lot of seats: six years at Hawk-Eye, leading the innovation unit at Manchester City, and now running his own consultancy, Future Sport Co. We get into the Man City Roblox playbook that drove 55 MILLION unique players (and 6,000 new members in four hours), why 3D player tracking data could one day rival media rights, and the fan behaviors that outlast every tech hype cycle. Loaded with case studies and real numbers. 106 minute duration. Listen on Apple, Spotify and YouTube

Are you looking to save time, make money, and start winning with less risk? Then head to https://www.ovtlyr.com.Learn more about OVTLYR: https://youtu.be/TUCbD5KovlcEveryone loves talking about winning trades... but almost nobody talks about what happens in between. The drawdowns. The losing streaks. The moments where it feels like your strategy has completely stopped working. That's where most traders quit... and that's exactly why most traders never make it.This conversation dives deep into what professional investing actually looks like. Why stop losses exist to protect your capital instead of limiting your profits. Why one big winner can completely erase dozens of small losses. And how proper position sizing can keep you in the game long enough for your edge to finally play out. There's also a fascinating comparison between trading and gold mining that perfectly explains why consistency always beats chasing the next hot stock.One of the biggest takeaways from this episode is learning to trust the probabilities instead of your emotions. The discussion breaks down Monte Carlo simulations, expectancy, and why even winning strategies experience painful losing streaks. Professional traders don't expect to win every trade... they expect to follow their process until the statistics eventually work in their favor.There's also a complete portfolio update covering Robinhood's emergency exit, Apple, GameStop, Roblox, Coca-Cola, market breadth, SPY support levels, order blocks, earnings season, and why managing risk is far more important than predicting what the market will do next.✅ SPY support, market breadth, and order block analysis✅ Robinhood emergency exit and real portfolio updates✅ Position sizing, stop losses, and professional risk management✅ Monte Carlo simulations, expectancy, and trading probabilities✅ Trading psychology, discipline, and why one big winner changes everythingIf you've ever wondered why successful traders stay calm during losing streaks... or why the best investors care more about probabilities than predictions... this episode will completely change how you think about trading.Subscribe to OVTLYR for disciplined trading strategies that actually make sense.

A single DM can turn into a case file, and most families never see it coming. We sit down with Cape Coral Police Department Special Victims Unit Detectives Trish Gould and Hailey DiGiovanni to talk plainly about internet crimes against children, what they're seeing right now, and why the digital world moves faster than a kid's judgment.We get specific about how these situations start on everyday platforms like Snapchat, Instagram, TikTok, YouTube, and even games like Roblox. We also explain the behind-the-scenes pipeline many parents don't know exists: social platforms can flag suspected minor activity and send reports through the National Center for Missing and Exploited Children, which then routes cyber tips to local law enforcement. If your child thinks a disappearing message means “no consequences,” this conversation is the reality check.We also dig into "sextortion" and how it often begins with consensual sharing before threats, pressure, and fear take over, including scenarios tied to teen relationships. Then we shift to what helps: open, ongoing talks; knowing passcodes; checking devices regularly; reviewing hidden folders and recently deleted content; and using iPhone Screen Time to spot high-use apps. 

Emma Witkowski is a highly accomplished digital media executive, strategic investor, and the Vice President of Media Solutions at WildBrain, a global leader in kids and family entertainment. In her role, she drives advertising sales and monetization strategy across WildBrain's massive digital ecosystem—including YouTube, FAST channels, AVOD, and immersive gaming integrations on Roblox and Fortnite—for timeless properties like Teletubbies, Strawberry Shortcake, and Inspector Gadget.Key Career MilestonesThe Media Solutions Leader: Based in Los Angeles, Emma brings over two decades of heavy-hitting experience in digital strategy, investment planning, and advertising ecosystem engineering.

Thank you to Cash App for sponsoring this episode! #ad - Download Cash App Today: https://capl.onelink.me/vFut/7ehn3u8l #CashAppPod. Cash App is a financial services platform, not a bank. Banking services provided by Cash App's bank partner(s). Prepaid debit cards issued by Sutton Bank, Member FDIC. Cash App Visa® Debit Flex Cards issued by Sutton Bank, Member FDIC, and The Bancorp Bank, N.A., pursuant to a license from Visa U.S.A. Inc. See terms and conditions for the Sutton prepaid card, Sutton debit flex card, and Bancorp debit flex card. Cash App Green features, Savings, Direct deposit, Round ups, Overdraft coverage and Discounts provided by Cash App, a Block, Inc. brand. Visit cash.app/legal/podcast for full disclosures. CHECK OUT THE PATREON! - https://www.patreon.com/ThePogcastPod On this episode of the Pogcast we talk through whether Veritas should split his video into 2 parts and what makes a good YouTube title and thumbnail. We also talk through the recent Blackout event in Escape From Tarkov, the Kappa changes, and the recently revealed season 1 modifiers. Check it out! Timestamps 00:00:00 - Intro Banter 00:10:24 - YouTube Duscission 00:29:39 - Cash App! 00:32:09 - YouTube Thumbnails 00:54:02 - Roblox is Insane 01:11:16 - Crazy Unban Request 01:26:20 - Tarkov Blackout Event 01:46:16 - Tarkov Kappa Changes 01:55:11 - Tarkov Season 1 Modifiers Check out JesseKazam Twitch: http://Twitch.tv/jessekazam YouTube: https://www.youtube.com/jessekazam Twitter: http://Twitter.com/jessekazam Discord: https://discord.gg/jessekazam Check out Veritas Twitch: http://Twitch.tv/Veritas YouTube: https://www.youtube.com/@VeritasGames Twitter: http://twitter.com/veriitasgames Spotify: https://open.spotify.com/artist/2S6iwClVoSNnpOcCzyMeUj Learn more about your ad choices. Visit podcastchoices.com/adchoices

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

Seja apoiador do X do Controle⁠⁠Compre seus jogos na Nuuvem! MARCAÇÕES DE TEMPO00:00 - Abertura e reações ao fim dos discos no PlayStation07:46 - Mudanças em breve no X do Controle16:17 - Asha Sharma e Xbox viram alvos de teoria da conspiração da Fox News28:59 - Xbox demite equipe de relações com indies da América Latina34:51 - Warframe vai explorar outro sistema solar em nova expansão44:59 - Roblox anuncia ferramenta de criação de jogos com IA generativa51:00 - Rapidinhas e encerramentoCRÉDITOSApresentação: PH Lutti Lippe e Guilherme DiasRoteiro: PH Lutti LippeEdição: Guilherme DiasThumbnail: Lucas G. FerreiraSiga o XdC: ⁠YouTube ⁠⁠⁠⁠| ⁠Instagram⁠ | ⁠Bluesky⁠ | ⁠Threads⁠ | ⁠⁠⁠⁠Tik Tok⁠⁠⁠⁠⁠⁠⁠⁠Nossas plataformas e redes⁠⁠⁠⁠Contato: ⁠contato@xdocontrole.com⁠Contato para anunciantes e parcerias: ⁠comercialxdc@gmail.com⁠

Co Host Ryan Hurd (https://mountaintoppodcast.com/luciddreaming) My first-time guest is a dream researcher and educator with dreamstudies.org. What if you had a sandbox for practicing with women...with zero real-life consequences? And what if you didn't have to find ANY new time in your busy schedule for it? I mean it sounds crazy, but if you could open up those hours of built-in "downtime" in human existence when you're asleep to get better with women, what would the ramifications be? I mean, it's not like you'd be too busy to get to it. After all, you're asleep. What we're talking about here is learning the art (and science) of lucid dreaming, and harnessing the skill to go anywhere, meet anyone, and do anything...all while you're asleep. So what is lucid dreaming, anyway? How do you learn it? And what exactly can you be capable of in your dream world? Obviously, the potential for practicing skills with women in a "sandbox" with zero real-world impact should be intriguing to any man. But how does what happens in your dreams actually translate to real-world results with women? And what are some of the unexpected positive consequences? What else can lucid dreaming be used to get better at? Can you build neighborhoods and sort of an entire Roblox or Second Life kind of existence in your dream world that you can return to again and again...even with the same women? What are some of the most outlandish ways lucid dreaming can improve your overall quality of life? And is flying better than sex? Hey, if you're asleep almost a third of your life, why not maximize it to your advantage? Get the free report Flip The Switch: 5 Ways To Get Better With Women Right Now (the 6th one should be "fall asleep"!) when you go to: https://mountaintoppodcast.com === HELP US SEND THE MESSAGE TO GREAT MEN EVERYWHERE === This show is built on the "Big Four": Confidence, Masculinity, Liking Women, and Good Character. Better men get better women. If you love what you hear, please rate the show on the service you subscribed to it on (takes one second) and leave a review.

Connor Pugs tells a Storytime about This Roblox Animator Needs To Be STOPPED.. (i'm sick)Today, I tell a story about this gen alpha kid who is also a roblox animator, and there is nothing wrong with roblox animations in general, but in this case, this roblox animator is sick and twisted and needs to be stopped..

Are you looking to save time, make money, and start winning with less risk? Then head to https://www.ovtlyr.com.Learn more about OVTLYR: https://youtu.be/TUCbD5KovlcNobody likes talking about losing money... but every serious trader eventually has to face it. Drawdowns are part of the game. The question isn't whether they'll happen... it's what you'll do when they do.This conversation gets into the reality of professional trading. Why even traders who make hundreds of percent in a year still struggle emotionally through drawdowns. Why chasing losses almost always makes things worse. And why the traders who survive aren't the ones who never lose... they're the ones who know exactly how much they're willing to lose before they ever enter a trade.There's a powerful lesson throughout this episode that goes far beyond the charts. Great trading isn't about predicting every move. It's about controlling your emotions, sticking to your rules, reducing risk whenever possible, and trusting a system even when results aren't going your way. The market doesn't owe anyone a win... but discipline gives you a chance to still be standing when the big winners finally arrive.There's also a full portfolio walkthrough covering real trades, Apple option rolls, GameStop, Roblox, Robinhood, Coca-Cola, and Box, plus a deep discussion on position sizing, risk management, trading psychology, and lessons from professional trader Lance Breitstein on handling drawdowns without letting emotions take over.✅ How professional traders handle drawdowns without panicking✅ Trading psychology, emotional discipline, and risk management✅ Apple option rolling strategy and reducing portfolio risk✅ Real trade management with GameStop, Roblox, Robinhood, Box, and more✅ Building a trading plan that survives losing streaksIf you've ever questioned your strategy after a losing streak... or wondered why trading feels more psychological than technical... this episode will probably change the way you think about the markets.Video Link: https://www.youtube.com/watch?v=o7DfwJTC_Ow&t=14sSubscribe to OVTLYR for disciplined trading strategies that actually make sense.

Did you hear that #Roblox has agreed to pay over $12 million to the state of Nevada rather than face litigation over child safety concerns? What should you glean from that fact? Come visit Plugged In for insights on this blocky gaming situation. PluggedIn Facebook Page Read our Blog! If you've enjoyed listening to Plugged In Reviews, please give us your feedback.

Meet Louis and Ryoji, two eleven-year-old boys from Japan. What's on their minds when it comes to media? Manga, Anime, One Piece, the Japanese rock band Mrs. Greenapple and an obsession with Phonk music. They connect with the big global 6: Netflix, Minecraft, TikTok, YouTube, ChatGPT, and Roblox. But they also express fears about a loss of privacy online, the stress of preparing for school tests, becoming a YouTuber, and the existential threat of A.I. I hope you enjoy the episode.Sherri

Today from SDPB - South Dakota is receiving over $8 million dollars in a settlement with the video game Roblox, Rapid City Council approves an effort to expand heavy industrial zoning and more.

Level up your leadership: https://forms.gle/nqRTUvgFrtdYuCbr6 Does hyper-scaling your game studio actually destroy the soul of your product? When outside capital flooded into WonderWorks Studio following Roblox's IPO, founder Zach Letter did what every investor screamed for: he scaled his three-person team to nearly 100 employees, built a massive physical studio, and hired a traditional AAA C-suite. The result was a toxic corporate culture, a mountain of high-maintenance work-for-hire contracts, and the near-death of their original IP. In this episode, Ben sits down with Zach Letter to deconstruct the grueling reality behind those decisions. Zach shares the timeline of cutting his studio back down to a core group of 12 people, bootstrapping a high-stakes licensing deal with Paramount on raw grit, and shipping a chart-topping SpongeBob Tower Defense game on their final weeks of runway. What You'll Learn in This Episode: What structural traps await small, agile teams when transitioning to high-overhead venture capital models. Why relying on traditional AAA corporate leadership frameworks can severely decouple your studio from fast-moving UGC algorithms and audiences. How to leverage hyper-focused community feedback and competitive gap analysis to disrupt saturated game genres. How to design high-stimulus, free-to-play reward loops that prioritize long-term player commitment over short-term FOMO mechanics. If you're a leader in game dev who is struggling to balance studio growth with creative control, or considering a high-risk pivot into licensed IP and UGC platforms, this episode is for you. Learn more about our guest:

Do influencer parents trade in their kids' privacy for the hope of financial security?Kids are everywhere on the Internet – and not just playing on Roblox. They're the stars of many family influencing pages that document kids' lives: from the intimate details of their births, to starting school, to going through puberty. That can come with a host of problems – but also a ton of money. So what happens when parents trade their kids' privacy for the hope of financial security? And how does that content play into feedback loops about what family life should look like?Brittany gets into it with Fortesa Latifi, senior writer at Yahoo! and author of Like, Follow, Subscribe: Influencer Kids and the Cost of Childhood Online.(00:00) The cost of a childhood online(02:48) How Mommy blogging transformed into family influencing(07:39) Just how much do family influencers make?(10:37) Online exploitation risks(16:36) How influencing distorts family life(24:59) Should kids be influencers?For more episodes on parenting, kids, and modern life, check out:The fear & shame of modern parentingAre children a marginalized group?The real meaning of "6 7"Support Public Media. Join NPR Plus.Follow Brittany on Instagram: @bmluseSee pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

Lords: Chall RT-55J https://samarantes.neocities.org/ https://metroidconstruction.com/hack.php?id=878 Topics: Remembering the Dynowarz Instagram private server, and social media thoughts every Mastodon user had already Why don't CPUs do analog arithmetic? Leaves, by Ursula LeGuin https://www.poetryfoundation.org/poems/148293/leaves-5bd9e153d78b2 Microtopics: DogTroid, the first Metroid ROM hack to star a dog. Self-finishing games. Sparkling water: it's like water but a lot more interesting. Caffeine Free Diet Pepsi. What sodas foam the most in response to a mento. Foam persistence. Foaminess reactions of a mento on various vintagesn of Diet Coke. Jolt Cola: all the sugar, twice the caffeine, three times the foam. A can of soda that's safe to open in a bathroom stall. Artisanal Coca Cola cans on Etsy that finally allow you to open a can of soda in a bathroom stall without anyone realizing you're drinking a Coke on the toilet. Flushable soda cans: as flushable as a flushable wipe. Why do toilets have pee traps when the pee deserves to be free? The second worst game in your NES collection. Desert Chrome title screens. Playing as a little spaceman until you enter the dinosaur mech. Shooting some alien brain or maybe a heart. 8bitnintendo.science How to pick what video games to buy in the late 1980s. How Metroid improved on the maze-with-keys genre. Nanosaur. A velociraptor with a techno-backpack. A game that is exhilarating and scary and endless when you're a child turning out to be a twenty minute trifle when you're an adult. Trespasser (1998) Simulation dinosaur emotions but you can't find a good balance so you just permanently lock them all to angry. Installing a violent action game about dinosaurs in the elementary school computer lab because dinosaurs are technically educational. Revisiting games that perplexed you as a child. Playing bad video games because no matter how bad they are they're still better than going outside and talking to people. The one where Kirby eats a car. The Roblox-like games you can find by logging into third party Minecraft servers. Starting your own Pixelfed server. Following the only person you know on Mastodon. Bluesky's recommendation algorithms recommendeding you nothing but bots. Inventing Internet forums from first principles. When your brain makes up garbage and you need a void to shove it into. Doing your part to make AI worse. CSS Crimes. How to find people to follow on Cohost. Signing up for a social media site and looking around and realizing you doing know anyone here. Mining and reposting. The ongoing maintenance requirements of running a Mastodon server. Ways you can interact with your family that only work if you have an iOS developer in the family. Off-box SQL database backup. Hypothetical IRC servers that support chat logs. Hardware random number generation. The pot of boiling water every Intel CPU draws thermal noise from for random number generation. The most commonly used analog computers in 2026. The market forces that led to semi-modular synthesizers being available for $300. Using your analog CPU to run a million instances of Lunar Lander at once. A rustic summer retreat ranch in the hills of Napa Valley, California. What makes us perceive the gradient of identities over the course of someone's life as a single identity. The most ephemeral thing possible. Musing for a few sentences and then thinking "hmm, I could put some line breaks in here and then publish it." Musing about the nature of identity, with line breaks. Topic Slingers. Topics: throw them around a lil bit. They love it. A lot of people don't know that.

There is a lot going on right now regarding the safety of kids online.In the United States, the majority of state legislatures have passed age verification laws requiring a variety of websites to more rigorously verify the age of their visitors. In the United Kingdom, Canada, Norway, Spain, and Germany, lawmakers are considering bans on social media access for anyone under the age of 16—Australia passed its ban in 2025. In schools across the world, smartphones have been removed from classrooms, hallways, and cafeterias. And online, some of the most popular apps and video games with children, such as Discord and Roblox, have implemented default restrictions on what young users can find and who they reach.But all this activity comes after rising crises at home, as an increasing number of behavioral researchers connect increased social media use with increased rates of depression, isolation, and suicidal thoughts. So, until real, societal change takes place, what is a concerned parent to do?That's what we're trying to answer today.Today, on the Lock and Code podcast with host David Ruiz, we bring back Anna Brading, editor-in-chief of Malwarebytes Labs and director of content and, perhaps most importantly, mother of three. With a long career in cybersecurity—and an equally long time spent reading, writing, and assigning some of the cybersecurity world's most pressing headlines—Brading has a unique perspective on what is most dangerous to her children online.Brading's list of priorities is long, and includes improper image use, “online nastiness,” and Roblox, but she has a few rules and guidelines to help. She sets a one-hour-a-day video game limit on the weekends, restricts YouTube to a communal and monitored activity, and requests that no one share photos of her children online without her express permission. Importantly, she also reminds parents to trust their guts.“If the norm now is mental health issues or online grooming or non-consensual porn or constant comparison, then I'm okay without my kids fitting in. I would say be radical, buck the trend, don't do what everybody else is doing. Say no to things you don't feel comfortable with.”Tune in today.You can also find us on Apple Podcasts, Spotify, and whatever preferred podcast platform you use.For all our cybersecurity coverage, visit Malwarebytes Labs at malwarebytes.com/blog.Show notes and credits:Intro Music: “Spellbound” by Kevin MacLeod (incompetech.com)Licensed under Creative Commons: By Attribution 4.0 Licensehttp://creativecommons.org/licenses/by/4.0/Outro Music: “Good God” by Wowa (unminus.com)Listen up—Malwarebytes doesn't just talk cybersecurity, we provide it.Protect yourself from online attacks that threaten your identity, your files, your system, and your financial well-being with our exclusive offer for Malwarebytes Premium for Lock and Code listeners.

Download MP3 | Watch Video Episode Full Timestamps: https://docs.google.com/document/d/e/2PACX-1vRojR7jDLDhzQ9r8xrLymUOUfwfe28YSPTzQFsmuZ9iS3DrzGZsb8E_Bg-YzxagkQhT6ozDunn4KsFC/pub Watch full episodes: https://www.youtube.com/@CastleSuperBeastArchive NEW CASTLE SUPER BEAST "LEGACY" SHIRT & DESKMAT AVAILABLE NOW: https://www.orchideight.com/collections/castle-super-beast Go to http://buyraycon.com/superbeast to get 20% off The Everyday Earbuds Classics. Take control of your income. Start your free trial at http://shopify.com/superbeast Go to http://brooklynbedding.com/ and use promo code SUPERBEAST to get 30% off Docket: Physical disc production ending in January 2028 for new games releasing on PlayStation consoles Saying they're killing physical media like a week after deleting purchased movies off of accounts is an absolutely hysterical optics decision to make And the same day you announce the closure of the Vita and PS3 digital stores. PlayStation Has Clearly Learned Nothing From Helldivers 2, As Marvel Tokon Is Being Blocked In 132 Countries. Any country that doesn't have PSN won't be able to play the PC version Sony: switch out lever gates with ease on the FlexStrike wireless fight stick…MightyKeef - Reverse the disc-less decision, fuck nigga. Chinese game Love and Deepspace canceled a new love interest after furious fans mailed cow poo to the developers. The studio has now promised it will never add another romance option to the game again and issued a massive apology JoJo's Bizarre Adventure: Steel Ball Run 2nd Stage | Official Trailer: Streaming every friday starting Sptember 25th from 2nd and 3rd stage, 11 episodes in total, Jojo Fridays are (kinda) backl Avatar Aang: The Last Airbender | Official Movie Trailer | Paramount+ | Avatar Young Ladies Don't Play Fighting Games | Official Trailer | Crunchyroll Former Xbox president Sarah Bond, former Roblox chief product officer Manuel Bronstein, and Take-Two CEO Strauss Zelnick have been linked with a secret society called 'Dialog' organised by controversial billionaire and conservative activist Peter Thiel.  

In January 2026, 17-year-old Hailey Buzbee disappeared after leaving her home in Fishers, Indiana, in the middle of the night. When she failed to return, her family launched a desperate search to find her. As investigators retraced Hailey's final movements, they uncovered a trail of online messages and hidden communications that would ultimately lead them across state lines in pursuit of the truth.Hailey's Law PDFGoFundMeFacebook PageHailey's Army For ChildrenChange PetitionResources Via Child Rescue CoalitionNCMEC's Online Safety ToolsThis episode is sponsored by:Wayfair: ready to upgrade your home for way less? Head to wayfair.com right now to shop all things home and get your space ready for less. Square: get up to $200 off Square hardware when you sign up at square.com/go/tckr! #squarepodWhatnot: download Whatnot today and get $20 Off and free shipping on your first purchaseCashapp: new Cash App customers can earn $10 if they use code CASHAPP10 in their profile at signup and send $5 to a friend within 14 days. Terms apply.Check out my foundation: Higher Hope Foundation: https://www.higherhope.org/Watch my documentaries:530 Days: https://www.youtube.com/watch?v=CjUWkmOjNLkApartment 801: https://bit.ly/2RJ9XXr True Crime with Kendall Rae podcast:Apple Podcasts: https://apple.co/3rks84oSpotify: https://spoti.fi/3jC66prShop my Merch! https://kendallrae.shopCheck out my other podcasts:Mile Higher (True Crime) @milehigherpodYouTube: https://bit.ly/2ROzJcwInstagram: http://instagram.com/milehigherpodThe Sesh (Current events, a little true crime, pop culture, and commentary) https://bit.ly/3Mtoz4X @the_seshpodcastInstagram: https://bit.ly/3a9t6Xr*Follow My Social!* @KendallRaeOnytInstagram: http://instagram.com/kendallraeonytFacebook: https://bit.ly/3kar4NKTrue Crime TikTok: https://bit.ly/3VDbc77Personal TikTok: https://bit.ly/41hmRKgREQUESTS: General case suggestion form: https://zfrmz.com/yg9cuiWjUe2QY3hSC2V0Form for people directly related/close to the victim: https://zfrmz.com/HGu2hZso42aHxARt1i67Join my discord to chat with other viewers about this video, it's free! https://discord.com/invite/an4stY9BCNC O N T A C T:For Business Inquiries - kendallrae@night.coSend me mail: Kendall Rae 8547 E Arapahoe Rd Ste J #233 Greenwood Village, CO 80112