Podcast appearances and mentions of Jennifer Lopez

Diddy moved to solitary confinement. Dave Landau, WATP Karl & Lucy Tightbox in-studio, Lindsay Clancy denied again, Phil Mickelson went to rehab, Cornell gang rape texts, John Hinckley Jr's podcast, and death row inmate Christa Pike beat lethal injection. Dave Landau, Karl Hamburger and Lucy Tightbox all in-studio today. There still has been no ID of the Flydubai pilot that tried to crash the plane he was flying to Israel. Phil Mickelson went to rehab for "family trauma" after he was busted harassing women. Derek Jeter has a Hall of Fame team photo on WhosDatedWho.com. Howard Stern was on Jimmy Kimmel Live to fight his battle against ABC. Diddy was having a great time in prison... until he got caught and was sent to solitary confinement. New updates in the Cornell gang rape story.  Including text messages between the victim and alleged rapist. Karl brings us breaking Opie news. Karl also brings us cuts of John Hinckley Jr's new podcast, Jerry Banfield clips and he introduces us to Barry Janfield. W. Kamal Bell introduces us to good white people. A female (?) Yankees fan beat the crap out of some Red Sox fans. Rick Ross arrested for domestic assault.  His lawyer tries to pull a don't-you-know-who-I-am and it fails spectacularly. Someone finally tells J Lo "no", as she gets her umbrella confiscated. Some spoiled heiress named Cibelle Savella killed her kid after losing custody. Lindsay Clancy's lawyer tried to get her murder charges tossed and was immediately denied. The View's Sunny Hostin doubles down on being a holdout juror after it was proven she lied. Tennessee death row inmate Christa Pike beat the lethal injection.  Some people are saying she should be set free. Merch is available if you want to rep the show. You'd look amazing too. If you'd like to help support the show… consider subscribing to our YouTube Channel, Facebook, Instagram and Twitter (Drew Lane, Marc Fellhauer, Trudi Daniels, Jim Bentley, BranDon, and Roberto).

On the show today... New information has been released about The BRAIN- and it’s actually Mind Blowing! (N) The most embarrassing thing you can do to your adult kids. Strange Things that INSTANTLY Strengthen Your Marriage- Backed by NeuroScience……. How old is too old to get it done?? Do you agree with JLO's top green flag??

Mally Roncal is a celebrity makeup artist who has worked with Beyoncé, Jennifer Lopez, Rihanna, Celine Dion, and so many more, and the founder of Mally Beauty.A big theme in Mally's life is learning not to make herself smaller. We get into the moments that made her question whether she should tone herself down, how she learned to see what made her different as a strength, and what working with some of the biggest women in entertainment taught her about confidence, intuition, and listening to her gut.Then there's the business story. Mally launched Mally Beauty on QVC in 2005. We talk about what it actually looked like building a company for nearly two decades, becoming a mom while growing the business, raising three daughters, and the harder chapters that taught her about trust and what happens when you hand parts of your company over to other people.Mally has experienced loss, rejection, setbacks, and plenty of moments that could have made her bitter or afraid, but instead she's built a practice around gratitude, perspective, and choosing her energy over and over again. We get into how to trust your instincts, how to build without losing the people and parts of life that matter most, how to recover when things don't go according to plan, and why authenticity can become one of your biggest advantages in both business and life.In this episode, we'll talk to Mally about:* How losing her mother shaped her gratitude and courage. [02:30]* Growing up with two inspiring Filipino doctor parents. [05:44]* Turning childhood bullying into a belief in her uniqueness. [08:37]* Learning to celebrate your differences instead of fitting in. [09:57]* Discovering makeup artistry after studying fashion design. [15:59]* Choosing authenticity after being told to change her appearance. [17:56]* How staying true to herself led to an InStyle opportunity. [21:05]* Building a celebrity makeup career and trusting her instincts. [22:12]* The Beyoncé makeup moment that changed her career. [24:01]* Finding creative freedom through collaborative client relationships. [26:53]* Balancing a demanding celebrity career with building a family. [28:36]* Creating Mally Beauty from personalized makeup formulas. [29:58]* Why she chose QVC to teach women makeup techniques. [31:41]* Building a business and raising twins while redefining success. [34:13]* Challenging the myth that women can't have it all. [38:52]* Finding the courage to expand beyond Mally Beauty. [42:58]* Why entrepreneurs must understand every part of their business. [45:34]* Prioritizing mental, physical, and spiritual well-being over business. [46:22]* Choosing joy, empathy, and gratitude through life's challenges. [50:31]* Manifesting a bigger vision and trusting the journey. [52:43]* Why you should acknowledge hard moments, then “fix your crown” and move forward. [57:52]* Remembering that life, family, and relationships matter more than business. [01:00:06]This episode is brought to you by Beeya:* If you or anyone you know have been struggling with hormonal imbalances and bad periods, go to https://beeyawellness.com/free to download the free guide to tackling hormonal imbalances* Plus, get $10 off your order by using promo code BEHINDHEREMPIRE10Follow Yasmin:* Instagram: https://www.instagram.com/yasminknouri/* Website: https://www.behindherempire.com/Follow Mally:* Instagram: https://www.instagram.com/mallyroncal/* QVC: https://www.qvc.com/catalog/psearch.html?keyword=Mally Hosted on Acast. See acast.com/privacy for more information.

JLO's Mug Shot full 322 Mon, 28 Sep 2026 16:45:35 +0000 wAeriPLqfMMvWKoScG31S2cvPtuB6RM6 comedy The Wake Up Call comedy JLO's Mug Shot The Wake Up Call is a morning radio show based in Sacramento, California, and heard weekday mornings on 106.5 the End. Gavin, Katie, and Intern Kevin wake up every morning to have FUN and be FUNNY, while you start your day. This show has unbelievable chemistry and will keep you laughing all morning! 2024 © 2021 Audacy, Inc. Comedy https://player.amperwavepodcasting.com?feed-link=https%3A%2F%2Frss.amperwave.net

1 - Eve - Got What You Need 2 - Christina Aguilera feat Redman - Dirrty 3 - Willy Denzey - Le Mur Du Son (Bounce) 4 - Mary Mary - Shackles 5 - Sean Paul - Ever Blazin' 6 - Rupee feat Daddy Yankee - Tempted to Touch 7 - Speedy feat. Lumidee - Sientelo 8 - Pitbull - I Know You Want Me 9 - Nicola Fasano - Calle Ocho 75 Brazil Street 10 - Madcon - Beggin' 11 - Gala vs Magic System - Cherie Coco Desire (Willy William Mash'up) 12 - Cascada - Evacuate The Dancefloor 13 - Flo Rida - Right Round 14 - David Guetta feat Akon - Sexy Bitch 15 - Rihanna - SOS 16 - Britney Spears - Womanizer 17 - Sean Paul - Press It up (Mast Edit) 18 - Montell Jordan - This Is How We Do It 19 - Deni Hines - It's Alright 20 - Jalane - Femmes 21 - One-T & Cool-T - The Magic Key 22 - Jennifer Lopez feat Ja rule - Ain't it funny (Daddy K Mash'up)

Brought to you by the English Programme. Featuring news, politics, popular culture, celebrity trivia, quizzes, book readings, and a whole host of fun.Support Our Rescue Cats | Our Blog | Get New Episodes By Email | Rumble | X | YouTube | NewsK365 on Spreaker | Get New Blog Posts By Email | Throne Wishlist |

Brought to you by the English Programme. Featuring news, politics, popular culture, celebrity trivia, quizzes, book readings, and a whole host of fun.Support Our Rescue Cats | Our Blog | Get New Episodes By Email | Rumble | X | YouTube | NewsK365 on Spreaker | Get New Blog Posts By Email | Throne Wishlist |

Tous en Boite en compagnie de Geoffrey Melin sur Radio City. Plus d'infos et concours sur http://www.tousenboite.be

The Cell (2000) sends Jennifer Lopez into a serial killer's mind while his next victim fights to survive. Henrique Couto and Rachael Redolfi unpack Tarsem Singh's surreal psychological horror, Vincent D'Onofrio's nightmare imagery and the ending's troubling questions about mercy and control. Explore water symbolism, childhood trauma and seven ways to interpret the title. Is Catherine a savior—or another kind of captor? A spoiler-filled horror movie review for your Halloween watchlist.Rent/buy (U.S.): https://tv.apple.com/us/movie/the-cell/umc.cmc.6nztuuqjkm043eux9zn1j0oy6Bonus episodes & support: https://weeklyspooky.com/joinMore scary stories: https://weeklyspooky.com/Story submissions: WeeklySpooky@gmail.com

In 1998 Jennifer Lopez gave a iconic interview to Movieline. She dished, she trash talked, she got a massage by the pool!LIVE SHOW TICKETSpatreon Hosted on Acast. See acast.com/privacy for more information.

Guests include:  Mike McFeely, Forum of Fargo-Moorhead Columnist; Jennifer Lopez, NDSU Volleyball Head Coach and; Steve Laqua, MSU Moorhead head football coach

Neste programa, dois latinos que fazem um estrondoso sucesso nos EUA: Walter Mercado, astrólogo e apresentador de televisão, no documentário “Ligue Djá - o Lendário Walter Mercado”, e Jennifer Lopez, no documentário “Halftime”. Ambos estão na Netflix. Músicas - https://mixkit.co e https://www.youtube.com/c/audiolibrary-channel:- You Got Jazz by Diego Nava- Little Samba by Quincas Moreira Music

Brendan Schaub and Bryan Callen react to Gable Steveson's shocking loss and break down why elite wrestling alone doesn't guarantee success in MMA. Brendan explains the holes he sees in Gable's striking, why he believes he was pushed too quickly, and what Gable would need to change if he wants to make a serious run.The Fighter and The Kid also break down Joshua Van vs. Alexandre Pantoja, UFC judging and the changing value of grappling, the controversial Converse ad, Carrot Top, Ed Sheeran, a viral Jennifer Lopez lookalike mugshot, Iggy Pop, Brendan's trip to Louisville and much more.Orion - Right now, Orion is offering our listeners 15% off at https://orionsleep.com/fighterDraftKings - New DraftKings customers, sign up with code FIGHTER, spend five bucks to get $150 in rewards within 14 days - includes all markets.Shopify - Start your free trial at http://shopify.com/fighterTruewerk - Go to http://truewerk.com/fighter and use code fighter to get 15% off your first order. TRUEWERK, Built Like It Matters.O'Reilly - Stop by O'Reilly Auto Parts today or visit us at https://oreillyauto.com/FIGHTER that's oreillyauto.com/FIGHTERProgressive - See if you could save when you switch to Progressive. You'll feel good about making a savvy choice. Visit https://progressive.com/ and see if you can enjoy a little extra cash back.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

¿Qué pasa cuando Hollywood ve una etiqueta antes que a un actor? Sylvia Villagrán y Duncan Crabtree-Ireland conversan con Tonatiuh sobre abrirse camino sin contactos, defender la amplitud de su talento y entender que actuar también es un negocio. El protagonista de Kiss of the Spider Woman comparte lo que la escuela no le enseñó sobre contratos, representación y vida en el set, y explica por qué los artistas necesitan reconocerse como trabajadores. Entre historias de sus primeros papeles y los exigentes ensayos junto a Jennifer Lopez, Tonatiuh reflexiona sobre la representación latina y LGBTQ+, la disciplina para sostener una carrera y la responsabilidad de cuidar a quienes comparten escena. Una conversación sobre crear tus propias oportunidades y decidir qué huella quieres dejar.

Crazy About You is a tech/house party music podcast. Please enjoy. Artist names and song titles are in the order they were played... A TOUCH OF CLASS-IT GOES AROUND, PINK-GET THE PARTY STARTED, CHRIS LAKE-I WANT YOU, FALLON-DIET COKE, ADAM PORT, VINSON, & BOYS NOIZE-CRAZY FOR IT, DUCK SAUCE-BARBRA STREISAND, STEVE ANGELLO-KNAS, JOSH BAKE & OMAR-BACK IT UP, FEDDE LA GRAND-NIGHT IN DETROIT, BAD BUNNY-EOO, JUSTIN TIMBERLAKE-ROCK YOUR BODY, CHUKIE & LMFAO-LET THE BASS KICK IN MIAMI BEACH, LIL BABY & DRAKE-YES INDEED, DOECHII-DENIAL IS A RIVER, FREAK NASTY-DA DIP, JENNIFER LOPEZ & LXRENZ-LOVE DON'T COST YOUR BODY, FETTY WAP-MY WAY, THE GAME & 50 CENT-HOW WE DO, MILLION DOLLAR BABY-G CHASE, KANYE WEST-LOVE LOCKDOWN. End. Thanks for listening to Ken Steele Music.

Send us Fan MailIn honor of Hispanic Heritage Month, we're celebrating one of the most recognizable Latina entertainers in Hollywood: Jennifer Lopez!From her breakout role as Selena Quintanilla to unforgettable rom-coms, dance music, and career-defining projects, J.Lo has spent decades proving that she can do it all.But which of her projects deserves the #1 spot?Follow us on socials: @twinsync.podcastMessage Kelsey on Instagram to plan your next Disney vacation! @modestpotthastGet your college gear @ section103.com

15. Oliver Heldens - Lady (Hear Me Tonight) 16.Jennifer Lopez, Alok - Everything's Fine (PM) 17. Jaden Bojsen, David Guetta - Upside Down 18. David Guetta, Bebe Rexha - Sad Girls (DJs from Mars Remix) 19. Robin Schulz, BARBZ - Better Times (feat. BARBZ) 20. Lykke Li, The Magician - Knife In The Heart - (The Magician Remix)  21. Swedish House Mafia, Lykke Li - Hapiness Is So Sad 22. Wade - I Was Made For Lovin' You 23. Sonny Fodera, Becky Hill - Say Something 24. David_Guetta, Hypaton - You And I, Me And You 25. Leclaire - I Was So 26. Troye Sivan, Tom Santa - Rush (Tom Santa Remix) 27. Teddy Swims - Bad Dreams (HUGEL Remix) 28. Taylor Swift - The Fate of Ophelia (Loud Luxury Remix)

Ecoutez votre mix Fun Radio du 21 septembre avec Jennifer Lopez, Tayc, mais aussi Bebe Rexha. Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Ecoutez votre mix Fun Radio du 21 septembre avec Jennifer Lopez, Tay C, mais aussi Bebe Rexha. Hébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

We went to the bullpen and called in a Hall of Fame closer to the weekend pod palooza! Hollering James from Minneapolis joins Ben for a rambunctious edition of the Fifth Hour Mailbag. Legendary for his thunderous snoring and undying love of the Ben Maller Show, James is one of the great larger-than-life cartoon characters of the Maller Militia.The boys rip open the mailbag and tackle listener questions from around the globe, traveling down a winding road of looksmaxxing, Colombian Bam Bam, toddler fight club, J-Lo lookalikes, Navy SEAL training, robotoilets, hurricane records, bad hygiene, and plenty more.It’s chaos, comedy, and questionable life advice—exactly what you signed up for. Buckle up and enjoy the ride. You better listen, or the FOMO will kick in, and you’ll need an industrial-sized shipment of copium. All questions sent in by new listeners & P1's of the #MallerMilitia! Download, subscribe, and remember that sharing is caring (unless it's an STD.) Follow Ben on Twitter @BenMaller and listen to the original terrestrial radio edition of "Ben Maller Show," Monday-Friday on Fox Sports Radio, 2a-6a ET, 11p-3a PT!...Follow, rate & review "The Fifth Hour!" #BenMaller #FSRWeekendsSee omnystudio.com/listener for privacy information.

We went to the bullpen and called in a Hall of Fame closer to the weekend pod palooza! Hollering James from Minneapolis joins Ben for a rambunctious edition of the Fifth Hour Mailbag. Legendary for his thunderous snoring and undying love of the Ben Maller Show, James is one of the great larger-than-life cartoon characters of the Maller Militia.The boys rip open the mailbag and tackle listener questions from around the globe, traveling down a winding road of looksmaxxing, Colombian Bam Bam, toddler fight club, J-Lo lookalikes, Navy SEAL training, robotoilets, hurricane records, bad hygiene, and plenty more.It’s chaos, comedy, and questionable life advice—exactly what you signed up for. Buckle up and enjoy the ride. You better listen, or the FOMO will kick in, and you’ll need an industrial-sized shipment of copium. All questions sent in by new listeners & P1's of the #MallerMilitia! Download, subscribe, and remember that sharing is caring (unless it's an STD.) Follow Ben on Twitter @BenMaller and listen to the original terrestrial radio edition of "Ben Maller Show," Monday-Friday on Fox Sports Radio, 2a-6a ET, 11p-3a PT!...Follow, rate & review "The Fifth Hour!" #BenMaller #FSRWeekendsSee omnystudio.com/listener for privacy information.

Brought to you by the English Programme. Featuring news, politics, popular culture, celebrity trivia, quizzes, book readings, and a whole host of fun.Support Our Rescue Cats | Our Blog | Get New Episodes By Email | Rumble | X | YouTube | NewsK365 on Spreaker | Get New Blog Posts By Email | Throne Wishlist |

Jason & Paul give their thoughts on Lanterns, Jason Statham's Mutiny, Coyote vs. ACME, and a bunch of other movies, TV shows, albums, and comic books they're currently loving. But first, Paul responds to all your corrections & omissions on last week's Jack episode! We learn about Francis Ford Coppola's original cut of the movie, why Jennifer Lopez's character was a horrible teacher, how the movie shares themes with Drop Dead Fred, and a whole lot more. Plus, as always, at the end of the show Paul announces next week's new movie!PAUL & JASON'S RECS:Sterling PointMutinyCoyote vs. ACMELanternsSix of Us by Tom KingSupergirl: Woman of Tomorrow by Tom KingMarble Hall MurdersThe WitchObsessionAvatar Aang: The Last AirbenderMaddie's SecretGail Daughtry and the Celebrity Sex PassMotor CityEarth, Wind & Fire (To Be Celestial vs That's the Weight of the World)Batman: Caped CrusaderWitch Hat AtelierBocchi the Rock!The NewsreaderInferno by Boards of CanadaWhack's Museum by Tierra WhackGo to the Woods by Wolves of GlendaleMarrow Deep by Mastodon • Join our Vulture Movies Fantasy League at vulture.com/hdtgm • Go to hdtgm.com for tour dates, merch, FAQs, and more • Leave us a voicemail at speakpipe.com/hdtgm • Submit your Last Looks theme song here • Join our Discord at discord.gg/hdtgm • Buy merch at howdidthisgetmade.dashery.com/ • Order Paul's book about his childhood: Joyful Recollections of Trauma • Shop our new hat collection at podswag.com • Paul's Discord: discord.gg/paulscheer • Paul's YouTube page: youtube.com/paulscheer • Follow Paul on Letterboxd: letterboxd.com/paulscheer • Subscribe The Dark Web w/ Paul & Rob Huebel: youtube.com/@enterthedarkweb • Listen to Unspooled with Paul & Amy Nicholson: unspooledpodcast.com • Listen to The Deep Dive with June & Jessica St. Clair: thedeepdiveacademy.com/podcast • Instagram: @hdtgm, @paulscheer, & @junediane • Twitter: @hdtgm, @paulscheer • Jason is not on social media • Episode transcripts available at how-did-this-get-made.simplecast.com/episodes Get access to all the podcasts you love, music channels and radio shows with the SiriusXM App! Get 3 months free using the link: siriusxm.com/hdtgm Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This week Dante and Harry Discuss: popstar Jennifer Lopez stopping her concert to give relationship advice to men. Should anyone take any type of relationship advice from Jennifer Lopez, and should you ever take relationship advice from women. Who gives out better relationship advice, Men or women? New episodes of Man School 202 available every Friday Everything society has taught you about finding a partner and fixing your relationship is wrong. The ManSchool202 podcast (Formerly the Beige Phillip Show) brings some righteous perspective on dating, love, relationships, and hooking-up for men AND women.

Donna Valentine & Steve Patterson start the show talking about the new Street Fighter movie popcorn bucket, Wendy's is bringing back yellow packaging and is it rude to do chores while on the phone?In hour two, we play the Airport edition of the College of Pop Culture Knowledge, Lenny Kravitz is getting his own Ken doll and this year's finalists for the Toy Hall of Fame.Finally, Hallmark has released their "Countdown to Christmas" movie lineup, how baseball announcers sound to non-baseball fans and (maybe) we find out the Soup of the Day!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Jennifer Lopez arrestada???

This week on The Big Dumb Podcast we binge-watch like it's a second job (Lanterns, Lioness, and whatever else we half-finished), then clock Ben Affleck volunteering to be Tom Brady's gold-digger early-warning system. Ed Sheeran's tour implodes because somebody said two words on a stadium stage. Eric does the Constitution. Blake does J-Lo. Again. Then we find out there are companies whose entire business model is writing your “I quit” letter so you don't have to. We wrap with the Emmys, where the only surprise is that anyone still pretends to be shocked.

This week Dante and Harry Discuss: popstar Jennifer Lopez stopping her concert to give relationship advice to men. Should anyone take any type of relationship advice from Jennifer Lopez, and should you ever take relationship advice from women. Who gives out better relationship advice, Men or women? New episodes of Man School 202 available every Friday Everything society has taught you about finding a partner and fixing your relationship is wrong. The ManSchool202 podcast (Formerly the Beige Phillip Show) brings some righteous perspective on dating, love, relationships, and hooking-up for men AND women.

Send us Fan MailThis week on the podcast, the fashion designer who is known as the “King of Pants,” Alvin Valley, stops by the show. We talk about where he picked up the moniker, how his first runway show came with a little help from Kathy Hilton, and so much more.*****Named the “King of Pants” by The New York Times, designer Alvin Valley's journey revolves around Miami and, of course, pants. Born in New York City, and educated at the University of Miami, where he studied architecture, Valley's designer roots are firmly planted with Miami fashionistas. Back in 1995, Valley dressed Miami's social scene with his eponymous label, which was sold at his Coconut Grove boutique nestled on Commodore Plaza. Best-known for crafting the best-fitting pants for women, New York socialites beckoned him to the Big Apple to open a SoHo atelier. “In 2000, I packed my bags and left for New York to pursue a wider audience,” Valley says of his move. And a great decision. Valley showed regularly during New York Fashion Week with a presence in over 250 stores worldwide. His doors included well-established retailers such as Saks Fifth Avenue, Neiman Marcus, Bergdorf Goodman, Intermix, and Fred Segal.Hollywood embraced him, too. “I've always interacted directly with consumers,” Valley says of his business technique. He forged close relationships with his clients, including Kate Winslet, Jennifer Lopez, Sharon Stone, Gwyneth Paltrow, Halle Berry, Reese Witherspoon, Zoë Saldana, Penelope Cruz, Eva Longoria, Cindy Crawford, Madonna, Cher, Cameron Diaz, Celine Dion, Jennifer Garner, and more.In 2007, the Moret Group acquired the Alvin Valley brand, expanding its distribution to Nordstroms, Macy's, Bloomingdale's and even QVC. “I'm going back to the basics and bringing back my amazing pants. I'll be making visits around the U.S. to reconnect with my customers and I can't wait to visit Miami — because my career started there,” Valley says. “I feel like my life is coming full circle.”Check out his designs here: https://alvinvalley.com/Follow him on Instagram here: https://www.instagram.com/alvinvalley/*****If you would like to contact the show Dauna@betertopodcast.comFollow us on Social MediaYouTube: https://www.youtube.com/channel/UCX0ETs2wpOHbCuhUNr0XFTw?view_as=subscriberInstagram: https://www.instagram.com/author_d.m.needom/Facebook: https://www.facebook.com/bettertopodcastwithdmneedomSupport the podcast here: https://www.patreon.com/bettertopodcastwithdmneedom©2026 Better To...Podcast with D. M.NeedomSupport the show

Have you ever wondered just how much Sony Music spent on Jennifer Lopez or Good Charlotte to get more radio spins? Well, then this episode is for you! This week, your hosts are giving you a history lesson on payola. It's a term that's been tossed around quite a bit on this podcast, and now it's finally time to explain what it actually means. From the days of Dick Clark to Spotify Discovery Mode, there's a lot to talk about! Join our Patreon for more content! - ⁠⁠⁠patreon.com/Beyondtheblinds⁠⁠⁠ Follow us on Instagram -⁠ ⁠⁠instagram.com/beyondtheblindspod⁠⁠⁠ Kelli on IG - ⁠⁠⁠instagram.com/laguna_biotch/⁠⁠⁠ Troy on IG -⁠⁠ ⁠Instagram.com/troyjeanspears⁠⁠⁠ --SPONSORS-- ASPCA Pet Health Insurance! Make sure your pet is covered, to explore coverage, visit ASPCApetinsurance.com/BLINDS. Shopify:⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠shopify.com/blinds⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ - start your free trial today Quince: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Quince.com/BLINDS⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for free shipping and 365 day returns Whisker:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠whisker.com/blinds⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠-Take an additional $50 off Whisker Litter-Robot bundles with code BLINDS Wayfair: Head to ⁠⁠⁠Wayfair.com⁠⁠⁠ to shop all things home  Vinted: ⁠⁠⁠Vinted.com⁠⁠⁠  - download the Vinted app for free to start listing with no seller fees, and for a limited time, enjoy free shipping in the US Learn more about your ad choices. Visit megaphone.fm/adchoices

From Trump's reaction to the Federal Reserve's latest rate hike to Bernie Sanders sounding the alarm over artificial intelligence, today's show is packed. We break down the latest polling heading into the midterms, the tightening Florida governor's race, Abdul El-Sayed's campaign against Mike Rogers, and undercover political videos making waves online.The latest NYT/Siena national poll found Democrats ahead on several issue-trust questions, while AI was essentially split between the parties. Then things get even stranger: NYC's multimillion-dollar bathroom controversy, Bernie Sanders calling for consequences for AI developers, JD Vance weighing in on the risks of AI, and Andrew Yang warning about self-replicating AI bots. Plus, we get into the latest Macklemore and Ed Sheeran controversy, a New York Times Israel-related editing dispute, the upcoming Lindsay and Patrick Clancy 60 Minutes interview, the Charlie Kirk/UVU lawsuit, and Candace Owens' latest comments about TPUSA. And because we can't end without some chaos: a viral J-Lo lookalike mugshot, Tom Cruise's GQ cover, an unbelievable near-miss caught on camera, a heartwarming 911 birthday call, and plenty more.SUPPORT OUR SPONSORS TO SUPPORT OUR SHOW!Lose meaningful weight and keep it off. Get started with 20% Off and Free Rush Shipping at https://TakeLean.com with promo code CHICKSTreat yourself to the most advanced bras and shapewear on the market from Honeylove. Save 20% off at https://HoneyLove.com/ChicksOne thing to pack, five ways to power! Get your Ridge Power Bank at https://Ridge.com/Chicks and save 10% using code CHICKS at checkout.Save an additional 10% off practical food for your pantry with the ReadyWise 4-Can Protein Bundle at https://ReadyWise.com with code CHICKS10.Subscribe and stay tuned for new episodes every weekday!Follow us here for more daily clips, updates, and commentary:YoutubeFacebookInstagramTikTokXLocalsMore InfoWebsite

Salsa ICON Tito Nieves takes us back to the beginning of his career and shares personal memories of working with Héctor Lavoe, an artist he loved and deeply admired. He also explains why he believes El Cantante, the film starring Marc Anthony and Jennifer Lopez, focused too heavily on the darker parts of Lavoe’s life and failed to show who Héctor truly was beyond his struggles. The conversation also explores the lasting impact of “I Like It Like That,” including Tito’s version of the classic and its revival by Cardi B, Bad Bunny, and J Balvin. Tito shares his thoughts on today’s rising salsa singers and reveals which new-generation artists he believes are helping carry the genre forward. You may recognize a few of their names from previous episodes of Gracias, Come Again! Beyond the music, Tito opens up about love, four marriages, and the happiness he has found with his current wife, who is also his business partner. He speaks candidly about addiction, going to rehab four times, and reaching 30 years of sobriety. Drawing from his own recovery journey, he offers heartfelt advice and encouragement to anyone struggling with addiction. Tito also helps launch a new Gracias, Come Again segment called Life Advice, AKA Consejos de la Vida, where he shares wisdom on love, resilience, recovery, happiness, and making the most of life. He also reflects on nearly 50 years in music, his Puerto Rican roots, his deep connection to New York City, and his upcoming La Historia Continúa concert at NJPAC on 09/26/26. This is Tito Nieves like you have never heard him before: honest, funny, emotional, grateful, and still passionate about salsa after five decades in the game. La Historia Continúa, and the legend is far from finished.See omnystudio.com/listener for privacy information.

It's your Ill-Advised News, the stupid criminals of the day. Support the show and follow us here Twitter, Insta, Apple, Amazon, Spotify and the Edge! See omnystudio.com/listener for privacy information.

Mazawey's top 5 hottest coaches, Ed Sheeran in a tough spot, LA news helicopter crash, Arch Manning apologizes, Sydney Sweeney loves sports, a new Bonerline, Jim's List: Most Pretentious Songs, and Drew's never been to Olive Garden. We miss Jerry Springer. Olive Garden is the #1 restaurant in America. Drew says he's going to eat there for the first time ever. Arch Manning has been in some hot water over a hilarious AI video. Sydney Sweeney is the worst...According to female athletes. Jordon Hudson is going scorched Earth on UNC to find out who is spilling the beans over there. Brand New Bonerline. John Gotti's grandson, Carmine Agnello, is a bum. He pushed off going to jail for months. Turns out, his mom never needed a kidney. How is this possible? Now, he married the chick that ratted him out. The duct tape airplane racist guy broke his silence. Nice excuse, idiot. An LA news anchor gave a eulogy for her "family" in the helicopter crash. Ed Sheeran is in a pretty bad spot right now. But Macklemore is kicking ass. Tom Mazawey answered on the first try. Tom rattles of his Top 5 hottest football coaches. Tom gives his hottest Detroit Lions takes. Jimmy Connors is Maz's guy...Always has been, always will be. Maz gives us his Lions vs Bills prediction. JJ McCarthy's stock isn't very high in Minnesota. Get well soon, Barry Manilow. See ya, Tommy! Tiger Woods is back at the driving range. No one was injured in a car on his way to the course. J Lo is posting pictures of her new $18M home. Wonder what her next failure is? Macklemore Breaking News: He's calling out Robert Kraft to match his $1M donation to Palestine. Yeah. That'll happen. Jim's Picks: Top 10 Most Pretentious Songs Of All Time Don't forget to check out Dave Landau's special… for free! Merch is available if you want to rep the show. You'd look amazing too. If you'd like to help support the show… consider subscribing to our YouTube Channel, Facebook, Instagram and Twitter (Drew Lane, Marc Fellhauer, Trudi Daniels, Jim Bentley, BranDon, and Roberto).

AIUC first got our attention with the NFDG backing, and have just announced a $40M series A today, with the most impressive industry advisor list we may have ever seen for an early startup behind AIUC-1, their agent standard backed by real insurance:From being Anthropic's first product hire to building the standards, testing, and insurance infrastructure meant to make frontier AI deployable, Rune Kvist is betting that the biggest constraint on AI adoption won't be capability it will be trust. In this episode, the AIUC cofounder joins swyx and Vibhu to announce a new $40M round and explain why companies like Cursor, Harvey, Lovable, and ElevenLabs are increasingly confronting a problem that gets harder as AI gets better: who is responsible when autonomous systems fail?We go deep on AIUC-1, the emerging standard for agent security, safety, and reliability; how AI agents are stress-tested for jailbreaks, hallucinations, and data leaks; and why Rune thinks standards and insurance could become critical infrastructure for AI. We also discuss the growing trust gap between governments and frontier labs, AI-enabled cyber and biological risks, why every model can ultimately be jailbroken, what happens when a $20 coding agent causes $200M of damage, whether AI engineers should be certified, and why even after AGI there may be one job the labs can never do themselves: be their own watchdog.We discuss:* Why risk, liability, and trust may become the binding constraint on AI adoption* Rune's path from reading the Scaling Laws paper to joining Anthropic in its earliest days* What Anthropic understood about scaling, compute, and the future years before it became obvious* Why Waymo illustrates the gap between AI capability and real-world deployment* AIUC's $40M round and work with Cursor, Harvey, Lovable, ElevenLabs, and other frontier AI companies* AIUC-1: a standard for AI agent security, safety, and reliability* How agents are tested for jailbreaks, hallucinations, and data leakage* Why most AI companies optimize the happy path without seriously stress-testing adversarial cases* Why AI standards may need to update every quarter instead of every decade* The emerging trust gap between frontier AI labs and governments* Cybersecurity, child safety, biological weapons, and the expanding frontier-model risk surface* Why standards and insurance may need to evolve together* How Lloyd's of London can insure AI systems and bring trust to enterprise deployment* What happens if a $20 Cursor subscription contributes to a $200M plane crash* The Air Canada chatbot case and how AI failures are beginning to clarify legal liability* Why copyright may be one of the hardest AI risks to insure* Evals, mechanistic interpretability, monitoring, and models becoming aware they're being tested* The impossible CISO mandate: adopt AI fast, but don't let anything go wrong* Why robotics will make AI liability dramatically more consequential* Whether AI engineers should have Level 1, 2, and 3 certifications* AIUC's roadmap across agents, frontier models, robotics, and universal red teaming* Why AGI could become a question of national sovereignty* Why the labs can never fully serve as their own watchdogs* The Big Short problem: how do you stop competing watchdogs from racing standards to the bottom?Rune Kvist* LinkedIn: https://www.linkedin.com/in/runekvist/* X: https://x.com/RuneKvistAIUC* https://aiuc.comTimestamps00:00:00 AIUC's $40M Round and the Risk Bottleneck for AI00:01:07 From Scaling Laws to Early Anthropic00:07:58 Why Trust, Not Capability, Could Limit AI Adoption00:12:19 Founding AIUC and Building AIUC-100:18:52 How AI Agents Are Audited and Stress-Tested00:25:26 Frontier Models, Government, and the AI Trust Gap00:33:32 Cyber, Child Safety, and AI-Enabled Biological Risk00:38:14 Why Standards and Insurance Belong Together00:41:45 What Does an AI Insurance Policy Actually Cover?00:50:44 The $20 Cursor Subscription and the $200M Plane Crash00:53:53 AI Liability, Monitoring, and Earning Enterprise Trust00:56:21 From AI Agents to Models to Robotics00:58:29 Copyright, Adverse Selection, and AI Insurance01:03:28 Evals, Mechanistic Interpretability, and Eval Awareness01:08:36 The Impossible Enterprise AI Mandate01:11:52 Prediction Markets vs. AI Audits01:14:43 Should AI Engineers Be Certified?01:19:10 AIUC's Roadmap, AGI, and Who Watches the Watchdogs?TranscriptIntroduction: AIUC, the $40M Series A, and Risk as the Adoption BottleneckSwyx [00:00:00]: Okay, we're in the studio with Rune from AIUC, the Artificial Intelligence Underwriting Company, with our trusty co-host, Vibhu. Welcome.Rune Kvist [00:00:10]: Thank you. Thanks for having me. Thank you.Swyx [00:00:11]: What are you announcing today?Rune Kvist [00:00:12]: We have raised $40 million, led by Ribbit Capital and First Harmonic.Swyx [00:00:17]: You first came to my attention when Nat and Daniel invested in you guys. Is the story, like, pretty much the same? Like, what are you today versus what you thought you were back then?Rune Kvist [00:00:26]: When we raised our seed round, we had a hypothesis that at some point risk was going to hold down adoption. At that point in time, that felt kind of hypothetical, and I think that is now over. Clearly, the moment is now with Mythos and Fable. It's pretty obvious that literally the binding constraint on adoption is risk. And so for us, it feels like this is a natural continuation of the same hypothesis, but where previously it was speculation, now it feels like fact.Swyx [00:00:54]: And let's get a list of the customers that you're highlighting as part of your Series A.Rune Kvist [00:00:58]: Totally. Yeah. So we are now working with folks like Cursor, Harvey, Lovable, ElevenLabs.Swyx [00:01:05]: Yeah. Amazing. Congrats.Rune Kvist [00:01:06]: Thank you.Swyx [00:01:07]: So you were famously one of the first hires involved in GTM and product. I'm just kind of curious: what was your path into AI? Just recap.Rune's Path Into AI: Scaling Laws, Capital, and AnthropicRune Kvist [00:01:18]: Yeah.Rune Kvist [00:01:19]: Late 2021, I sold a company, my first company, an edtech company. I had a bit of time to think about what was next. I came across the Scaling Laws paper, and that just struck me like lightning. I was just like, “This is a big idea.” In short, the Scaling Laws paper just says the bigger the model, the smarter the model.Swyx [00:01:38]: So this is the Kaplan one, not the Chinchilla one?Rune Kvist [00:01:40]: Exactly, the Kaplan one.Swyx [00:01:42]: Yeah.Rune Kvist [00:01:42]: And the important thing that clicked for me there was, oh, now capital will understand this. If you put in more money, you get more money out, and so that will kick off a hype cycle. And so you get a sense of predictable returns, which is, in fact, what's played out. And so I just packed my bags. I'd never been to San Francisco. I'd never been there. I just packed my bags, flew out here to find the people who had written it. And at the time, they had just started a small lab called Anthropic. There were around 40 people at the time or so. Drank a bunch of coffee until I eventually got introduced to Dario. And at the time, they were wrestling with some of these questions of, like, should we deploy our models? Should we make revenue? How should we engage with the rest of the world? They'd just broken off from OpenAI, and it's been publicly reported that they were kind of concerned with how they were dealing with deployment. So they were wrestling with some of those questions. At this point, this is early fog of war, like early 2022. The hottest product at the time was, like, Jasper. Like, there's nothing out there. So where value was going to accrue, and what the different parts of the stack were going to be, were all open questions.Swyx [00:02:48]: I want to highlight to people, you ask these questions because you have a PPE background.Rune Kvist [00:02:52]: Yes.Swyx [00:02:52]: I actually was in Singapore in one of the sort of feeder programs for prepping people for PPE. So I had a tutor. We learned, you know, philosophy and politics and economics. But, like, I think your kind of background matters. Machine learning people who read the neural, Scaling Laws paper would not necessarily draw the same conclusions that you did. Whereas any capitalist would read that and go, “Holy s**t.”Rune Kvist [00:03:19]: Correct.Swyx [00:03:20]: Right?Rune Kvist [00:03:21]: Yes.Swyx [00:03:21]: Who tipped you onto that paper? Because it's not a paper that you normally read, right, like, in your circles?Rune Kvist [00:03:26]: Yeah. I think I'd actually, ever since AlphaGo, had some appreciation that AI was a big deal.Swyx [00:03:36]: Yeah.Rune Kvist [00:03:36]: But it kind of felt like it raised all these kind of interesting philosophical questions, but it was kind of not clear from afar where exactly that would go. But it was obvious enough that it was like, this is going to be a big thing if we find the kind of right mechanism to kind of get the techno-capital machine to work on this. But it was just not clear. And so I think there was some way in which, like, that became obvious, and also it wasn't as obvious at the time than it is now, right? Like, it was just like, wow, this is so interesting. But it still felt, coming from kind of a philosophy and economics background, it felt like if this turns out to be true, you're going to be wrestling with all of the big questions in society. Everything you've learned about politics gets thrown out of the window. Everything you've learned about economics at least gets challenged. And so what felt interesting was to be at that frontier that has ramifications across everything. So that's why I sought it out.Swyx [00:04:32]: I mean, clearly really good insight. For people who don't know, the PPE program is, like, where prime ministers are born. So then you end up meeting Dario.Rune Kvist [00:04:41]: Yep. First Dario, yeah.Swyx [00:04:43]: Yeah. Well, I mean, like, so did you get extra insights from talking with them that you didn't get from your original hypothesis?Anthropic's Early Conviction and the Scaling Laws Crystal BallRune Kvist [00:04:50]: If you read the Scaling Laws paper, you get this, like, very vague sketch of like, wow, this seems kind of important. There are some lines on a chart. This seems kind of important. And what I think the team at Anthropic had thought more about than anyone was like, what are the implications of this if you really play this out? And back then they had, kind of vision documents for what the world would look like in 2026, and they were kind of in vivid detail playing out how much compute is going to be needed, what the CapEx was going to look like, what some of the societal concerns were going to be, but also what is the amount of economic value coming out here? And so it kind of felt like they held a crystal ball that in hindsight turned out to just be dramatically correct. And they weren't holding it like they were obviously correct. They were just like, “Take this hypothesis really seriously.”Swyx [00:05:38]: Think it through, yeah.Rune Kvist [00:05:38]: And think it through in the same way as the kind of situational awareness that isSwyx [00:05:43]: Across the street.Rune Kvist [00:05:44]: Across the street.Swyx [00:05:44]: Your office, yeah. Oh my God, we're all living across the street in the same one square mile.Rune Kvist [00:05:50]: Correct. And that's now a couple of years old, but also people keep referencing it these particular weeks with Fable and Mythos, and it's like, wow, if you take this one idea seriously- For the Scaling Laws, a lot of things fall into place.Vibhu [00:06:03]: And keep in mind, at this point, this is the same team that did GPT-1, GPT-2, and GPT-3.Rune Kvist [00:06:08]: Correct.Vibhu [00:06:08]: Which is also, like, it's not just some experimentation. Like, this is a real model that we just scaled up.Rune Kvist [00:06:14]: And they had deep conviction in this idea: if you take a big blob of compute and data, it just wants to learn, and out of that will come smarter and smarter models. And all the particulars were not clear.Vibhu [00:06:26]: Yeah.Rune Kvist [00:06:27]: And all the implications were not clear. But their deep conviction in this, like, core thesis, and that was kind of dizzying. It was both phenomenally interesting and exciting, and also very quickly you get to, like, the world we know today will no longer be if this hypothesis holds. So it also just felt, like, important in some kind of grand sense.Vibhu [00:06:48]: What kind of shaped you there? So that was early 2022. Not only had GPT-1, GPT-2, and GPT-3 come out, but, you know, the amazing founders of Anthropic that have never split up, the only ones, they actually had the conviction to leave OpenAI, start their lab. You said there were about 40 people there. What was the time like there?Inside Early Anthropic: Mission, Deployment, and RiskRune Kvist [00:07:06]: It was kind of remarkably like what it looks like on the outside today. Extremely cohesive, extremely mission-oriented, and living in this tension between their two ideas, which is AI could both go really well and really bad, and we want to be part of building it. That creates astounding amounts of tension. And they were wrestling with this incentive challenge where they know they're in a race that they're in where you might get forced to cut corners, but it also felt very important to them to be at the forefront of technology. And all of those ideas were just present at that time. It kind of feels like that line has been just very clear, and I think kind of love them or hate them, they have really stuck to their guns. There's a core set of beliefs that they hold more deeply than most companies hold any beliefs.Vibhu [00:07:58]: Yeah. Fast-forward to today.Rune Kvist [00:08:00]: Yeah.Vibhu [00:08:00]: What does that lead us to AI underwriting company? What are you up to? What motivated you to start this?From Waymo to AIUC: Confidence Infrastructure for AIRune Kvist [00:08:05]: Yeah. AIUC builds confidence infrastructure for frontier AI through standards and insurance. The link from Anthropic to building confidence infrastructure, looking out the windows at Anthropic offices and seeing Waymos driving by. Already back then, early 2022, Waymos were in some ways like AGI for cars. Like, they were superhuman drivers, but you couldn't take one to the airport. And now, four and a bit years later, you still can't take your Waymo to the airport, despite now everyone having kind of looked at the evidence and being like, “They're better drivers than humans.” So in that particular instance, what's clear is that the binding constraint on AI being useful is not capability, but is that liability or risk or trust. That problem is, general. The reason why right nowRune Kvist [00:08:52]: Fable is not open for access is not because it's not a good model, it's because it's a very good model. It's just hard to make promises about what it will or will not do. And this problem gets worse as AI gets better. Basically, more intelligent AI can be more autonomous. That's more valuable, but also the risk surface grows. And so - what Waymo illustrates is that unless you build the confidence infrastructure to make promises about AI, or at least bring light to the risks, you grind adoption to a halt. Governments, banks, hospitals, militaries need to have some sense of what AI will and will not do to be able to operate for them to incorporate it. And that's the problem that we're trying to solve. Now, why standards and insurance? If you trace this problem back through history, every technology wave has had some version of this problem. So if you go back to, like, year 1900, electricity comesVibhu [00:09:47]: Ben Franklin.Rune Kvist [00:09:48]: Cars burn down, sorry, houses burn down, lots of people die. 1930s, cars are a big deal, kill lots of people. 1950s, private nuclear energy is a big deal, poses big risks. In each of those instances, the market runs ahead of regulation to create confidence infrastructure because that's required to make go/go decisions. That is required for adoption, and the market fundamentally wants adoption. And in all of those instances, common blueprint emerges between standards and insurance. The reason these two components is standards kind of provide the rules of the road, and they also specify, like, what are the tests that need to be run so we can get a sense of how high the risk is. So take in the case of cars, that's like a car crash. Great, everyone, they inform your insurance pricing today, they inform your purchasing decisions, et cetera. That's basically the risk framework. The insurers are important because they pick up the bill. So they are the private institution that is most on the side of. That is best incentivized to quantify the risks truthfully and then figure out all the ways to reduce the risk ‘cause that increases their profit. So they're basically, they help shape the incentives. And these two work really well in unison. Now, how does that show up as a company? Well, one of the things that was obvious even - or starting to become obvious even a couple years ago was that frontier companies, some of our customers today, like Cursor, Sierra, ElevenLabs, Harvey, were going to have a very easy time selling a pilot to a bank. The, like, the demo just sells itself. It's magic. But bringing that through, if you want to do a wall-to-wall rollout at a bank or a hospital, you have to go through the risk process. These banks have no idea even which questions to ask, let alone which answers are sufficient, let alone, like, how do they go and test whether these agents actually work the way they're supposed to. And so they had this problem of, like, what can we say to earn the trust? And we think there's, like, a golden sentence that goes something like, “Hey, I hear you're really worried about hallucinations or jailbreaks or whatever it may be. We've had an independent third party test us against the gold standard. We passed with flying colors. And as a vote of confidence, the world's most conservative insurers have looked at the data.” And they're willing to take some of the risk onto their balance sheet.Swyx [00:12:06]: Yeah.Rune Kvist [00:12:07]: So if something does go wrongSwyx [00:12:07]: There's money behind it, yeah.Rune Kvist [00:12:09]: Exactly. So that's kind of like the link between all this. We can get into some of the hard parts related to the technical testing, which is, I think, the crux of the matter, but I'll pause there.Swyx [00:12:19]: How did you and Rajiv come together? This-- there's always, like, you come across very confident and, you know, and we're announcing your Series A and all these things, but I want to see, like, the early initial stages of, like, idea formation.Cofounding AIUC with Rajiv DattaniRune Kvist [00:12:31]: Yeah. Rajiv is actually my soon-to-be brother-in-law.Swyx [00:12:35]: Oh.Rune Kvist [00:12:36]: So I'm actually, in a week and a half getting married to Rajiv's sister.Swyx [00:12:42]: Okay, now you're tight.Rune Kvist [00:12:44]: Exactly.Swyx [00:12:44]: Now you know.Rune Kvist [00:12:45]: So - Rajiv and I have known each other for a decade. Funny story, I met both Rajiv and his sister, Hena, at the same time when Hena and I were interns at McKinsey in London, and Rajiv was assigned as my mentor. And so met them at the same time. For the longest time, it was not obvious that we were necessarily going to work together. I was in startups. He was, an insurance partner at McKinsey. Three or four years ago, I think Hena convinced him that AI was going to be a really big thing. And so he quit his job, cushy partner job at McKinsey in London, packed his bags, flew to San Francisco, and ended up joining METR. You guys are probably online enoughSwyx [00:13:24]: CEO.Rune Kvist [00:13:24]: Exactly.Swyx [00:13:24]: We've, we've, we've heard of METR.Rune Kvist [00:13:25]: You see the plot-- the chart of the horizons of the tasks that agents can take on is doubling extremely fast. So he was COO at METR, led their partnerships with Anthropic and OpenAI to test their models before release, but also working closely with the US and UK government, to figure out, like, how do you know whether a model can be released? And in some ways, that was, like, the perfect background. He's spent a lot of time in insurance, knows that world, spent a lot of time with frontier testing of models. And so when I was bumbling around this idea space, starting with some of the ideas we talked about related to Waymo, as soon as we got into the content, we were both like, “Oh, this would be an amazing business to build together.” This is wrestling with the problem that we both think is the most important in the world from a market angle, which is kind of our intuitions is that the market can do a lot, and the faster AI moves, the harder it is for government to solve some of these problems. And then it took a little bit of time to work through what is it like to work with family.Swyx [00:14:27]: Sure.Rune Kvist [00:14:27]: And,Swyx [00:14:30]: Because you were already dating at the timeRune Kvist [00:14:31]: Yeah. Yeah, exactly.Swyx [00:14:33]: Yeah.Rune Kvist [00:14:34]: Already back then, itSwyx [00:14:35]: Yeah.Rune Kvist [00:14:35]: We felt like we were a family.Swyx [00:14:36]: Nice.Rune Kvist [00:14:36]: And so starting a business together felt like kind of a big step. And, here we are with just immense amounts of trust.Vibhu [00:14:43]: Yeah. So now you're a company of how big? How big are you guys now?AIUC-1 Certification: Agent Security, Safety, and ReliabilityRune Kvist [00:14:46]: There are just 20 of us now.Vibhu [00:14:47]: 20 of you guys now, have Series A, and you have your first certification out, the AIUC-1. Let's bring up the certification. So this is the agent certification, right? What goes into the process? I have, like, two questions here. One is, walk us through the certification, and two is, what is the process for a company to get certified, you know?Rune Kvist [00:15:08]: Great. As it says right on the top, AIUC-1 is a standard for agent security, safety, and reliability. The fundamental design principle is take all of the concerns that slow down adoption, so all the questions, all the fears that keep, security leaders in the Fortune 1000 up at night, and put them into one comprehensive framework. That's what you'll see there. You can see the six categories. Two, you want to ground all of this in technical testing. So one of the concerns with security standards that often feel kind of like theater paperwork is that they're not actually ground out in, does any of this work? Does any of this matter? And so we had a conviction from early on that was going to be the kind of crux, was to pass this, you must get tested every quarter, basically run thousands of simulations to see, well, so can it actually be jailbroken? How hard is it to jailbreak? How often does it hallucinate? How often does it leak data? Et cetera. And then the last, core idea here, if you scroll up to the top here, is to refresh it quarterly.Rune Kvist [00:16:08]: So the core trait of AI is that it moves extremely fast. Whatever concerns we're discussing today were not the same ones three months ago, and this will keep changing. Typically, standards update on a, like, a decade cycle is obviously not going to work. But the question is kind of how do you update it? And the core thing here was to basically get the risk leaders of the Fortune 1000 around the table. So if you go over to the left hereVibhu [00:16:32]: YeahRune Kvist [00:16:32]: You'll see the AIUC-1 consortium. The consortium is a group of risk leaders who run real banks, real hospitals, real critical infrastructure, who are facing these challenges every day. And we meet with these folks twice a quarter and hear what's top of mind, what is keeping them up at night. There's tremendous amount of desire for that conversation. And then we operationalize that into a specific standard that gets into. And actually, we can go into and look at whatVibhu [00:16:55]: YeahRune Kvist [00:16:55]: What even is the standard. So if we go back to introduction, out there to the left, scroll up a little bit to the wheel, click into reliability. So if you take something like hallucinations sits in reliability. There is a number of requirements here. If you go into the top one, prevent hallucinated outputs, hallucinate outputs, this is one particular requirement. This is a technical control. Basically, we want some kind of ground in this filter. The first thing you see here is what's called a crosswalk. So everyone and their grandmother has put out a framework, very high-level framework for what are the AI risks.Swyx [00:17:27]: This is basically your competition,Rune Kvist [00:17:28]: In some ways our competitionSwyx [00:17:29]: Not seriously, yeah.Rune Kvist [00:17:30]: We're, in fact, friends with them. We'll come back to why.Swyx [00:17:31]: Yeah.Rune Kvist [00:17:32]: But mapping everything together so you have one superset. The claim you're trying to support here is, if you follow this framework, then you can also see how you follow the other frameworks. But the meat of it comes down here in control activities and evidence. So control activities is like, great, you have this high-level requirement. How do you turn that down to something operational? Here's what you must do, and then what is the evidence that we're looking for?Rune Kvist [00:17:57]: And the reason we go this deep is that there's actually not that much confusion about what are the big concerns in AI. Everyone agrees to these. The question, like, what are you actually supposed to do? And so. What we found a lot of demand for is getting down to the specific evidence, that people need to look for. Whether you are Cursor building something or, even JPMorgan building something, but also if you're just a risk leader at JPMorgan, like what exactly should you ask for? What can you ask for without sounding stupid? Like if you ask for some-- you won't believe the amount of time a risk leader has asked for the IP rights to the underlying model to Cursor or something, and you're just like “Sorry, what?” Like,Swyx [00:18:39]: You slip it in there and you seeRune Kvist [00:18:40]: SlipSwyx [00:18:40]: See if you notice.Rune Kvist [00:18:41]: See if they. Exactly.Swyx [00:18:42]: Yeah.Rune Kvist [00:18:42]: Put that in the questionnaire. All right, so that's kind of what our standard is, and we update this every quarter with these folks, to keep up with the latest concerns.Swyx [00:18:51]: Can I double-click on this one?Controls, Evidence, and Third-Party TestingRune Kvist [00:18:52]: Yeah.Swyx [00:18:52]: So first of all, the website's beautiful. Like, it's so confidence-inducing which is the whole point where, like, okay, I know exactly what I'm signing up for when I talk with you. Like, I don't even have to talk to you. I can just see your whole, certification, which is great. But, like, okay, so from here, like D001.1 configure a groundedness filter, how does that get applied? Like, you have a person thatRune Kvist [00:19:16]: Yeah,Swyx [00:19:16]: Goes through it?Rune Kvist [00:19:17]: If you, go backVibhu [00:19:19]: I did see somewhere there's like, you know, fifty-one requirements, a hundred thirty controls. There's like a wholeSwyx [00:19:25]: Right. I just want to. Like, to me, this doesn't translateVibhu [00:19:27]: Yeah.Swyx [00:19:27]: Into a test or an eval.Rune Kvist [00:19:28]: Yes. So if you go into, on the left-hand side. So actually, if - before we go in there are three types of requirements. The first is technical controls, like you must implement some guardrails.Rune Kvist [00:19:42]: Two, there are test controls. So you must have an independent third party go and run some tests against you. I'll show you one of those in a second. And then three, there are policy controls. For example, you must have a person whose name is on the line when you guys f**k up, and you must have a plan for how you tell your customers and how you engage with them. They're kind of more traditional, standard type stuff. So in this particular instance, we just check whether they in fact have a ground in filter. So we will partner with an auditor. So we partner with auditors like KPMG or like Schellman who go in and do the thing auditors do, which is to check the evidence. In this case, that might be a screenshot, it might be part of the code that they need to review to see that it actually. Just that it exists.Swyx [00:20:21]: Oh, okay.Rune Kvist [00:20:22]: And then the second thingSwyx [00:20:22]: So you're not testing the effectiveness of it.Rune Kvist [00:20:24]: That's the second thing. So if you go downSwyx [00:20:25]: Yeah.Rune Kvist [00:20:25]: To the third-party testing for hallucinations out on the left, that's basically the next requirement. This is where we test how well does it actually work.Swyx [00:20:32]: Okay, and is it you testing or the auditor?Rune Kvist [00:20:34]: We test them.Rune Kvist [00:20:35]: We test them.Swyx [00:20:36]: That's a lot of work.Vibhu [00:20:37]: How long does testing take? So if I want to get certified, justCertification Timelines, Remediation, and Quarterly UpdatesRune Kvist [00:20:40]: Yeah.Vibhu [00:20:40]: How long does the end roughly take?Rune Kvist [00:20:42]: Yeah, the end, almost always is dependent on, like, our customers needVibhu [00:20:47]: Yeah.Rune Kvist [00:20:47]: To look something for us. It takes somewhere between, like, 3 to 10 weeksSwyx [00:20:52]: Yeah.Rune Kvist [00:20:52]: Depending on how up to snuff they already are. So some people show up to us with, like, extremely rigorous security programs. When we test them, it works extremely well. We can get that done very quick. Some people come to us, and they're not that far along. We give them kind of the spec that they need to build towards, and then their security teams and engineers get to work and build to meet the standard. The testing itself typically takes a couple of weeks, including the time for them to remediate. Often, we'll find something that we cannot pass, where this is actually just not up to the standard. - you won't pass the standard. And then they will need to go and implement additional safeguards or additional remediation that makes them more robust so that they can actually kind of hand on heart look at their customers in the eyes and say, like, “Hey, we've done truly our very best.”Vibhu [00:21:35]: And they're certified for a year and have quarterly updates?Rune Kvist [00:21:38]: Correct, yeah.Vibhu [00:21:39]: And, yeah, it's pretty interesting. I think, you know, what's changed since. So this is certifying agents in production, right? Your customers, like you've had Lovable, ElevenLabs, Intercom, and they've all gone through this certification.Rune Kvist [00:21:50]: Yes.Vibhu [00:21:51]: What has changed? So I see you post, like, you know, Q2 added MCP agent,How Agent Risks Are Changing: Coding, MCP, and Agent-to-Agent InteractionsRune Kvist [00:21:56]: Yeah.Vibhu [00:21:56]: agent communication. Any other things that you want to kind of highlight since the first iteration? What comes in quarterly?Rune Kvist [00:22:03]: Yeah. So some of the changes have just been agents are not just one thing. So, like, if you take agents like Cursor and compare them to Sierra, they're really quite different. And compare them to Harvey again, compare them to you out of againSwyx [00:22:16]: ElevenLabs, yeah.Rune Kvist [00:22:17]: ElevenLabs, they're all quite different. And so we wanted to design a standard that works for all of the types of agents. And we started with one that was, like, pretty text-based, like, honestly, pretty customer support-focused. That's where there's a lot of existing demand. And then over time, we've picked, some of the frontier companies in each of these other domains that we could work with and build out the standard, so, such that we know that the same standard works for code, it works for customer support, works for automation, et cetera. So that's been one big thing. Yeah, then some of the things that have been top of mind recently, Mythos is bringing up a lot of concerns for security leaders. We're starting to get more and more questions around agent interactions. It's very nascent, at the moment, but it's starting to emerge. There've been a lot of, questions related to OpenClaw and MCP. Again, like agents starting to interact with each other, is really top of mind. Then as coding agents have really taken off, that's also where banks and hospitals, et cetera, are getting more and more precise on what it is they need. So really dialing in as that start to be, like, where most of the tokens flow through in the world, getting much sharper on that.Vibhu [00:23:26]: Can you share for people that are listening that don't really think about this? Like you mentioned, there's the obvious stuff, you know, hallucination, citations. What are best practices that people should do when building agents? Like, if they come to you pretty ready with certification like, you know, they'll probably pass certification. What are the things people don't think about that they should have?Best Practices for Agent Builders: Stress Tests and GuardrailsRune Kvist [00:23:46]: The most important thing is that a lot of companies have not done a serious stress test. They spend most of the time, perhaps rightly so, optimizing for how does it work in the good case, the average case, how high-quality is the output for the customer. And a lot of these companies are pretty new, so they haven't spent a lot of time stress testing the what is there as an adversary on the other side? What are some of the complicated corner cases that you've not really considered? So I think that's, like, a frame of mind. And you'll also see this in startups. It often takes a while until they hire their first security person. They- And that's a whole different kind of risk surface than just building a good product. So a lot of that applies. Most companies actually also have the right kind of architecture. Most of them will have some kind of guardrails in place, either some that come out of the box from their model provider or they'll have built their own filters that sit in between. They just don't work very well. The difference between putting a classifier in place that, like, maybe goes and checks whether you're giving medical advice when you shouldn't and says, “Hey, if this looks like medical advice, filter it out.” Lots of companies have that in place. The question is whether it works. And it's actually pretty fiddly to sit down and think about all the ways in which you could ask for medical advice, read the academic literature on what are the kinds ofRune Kvist [00:25:03]: Framings or tricks you might play to get an AI to give you medical advice when you really shouldn't. And so there's, like, an area of expertise that's just missing. So what we find is that most people have the right building blocks in place. They don'- It doesn'- It's not rocket science, but the finicky thing is, like, getting into the corners and testing whether it works such that you can look your customers in the eye, or maybe a bank or maybe a hospital and be like, “This is going to work for you.”Vibhu [00:25:26]: I see. So we talked a lot about the agent-level certification. Where do you guys go from here? So announcing series A camera, we talked about this a bit. There's the whole security risk of Fable, government stepping in. You guys are kind of announcing that you're also going into model certification?Toward Model Certification: The Government–Lab Trust GapRune Kvist [00:25:46]: When we do a bit of cutting afterwards,Vibhu [00:25:48]: YeahRune Kvist [00:25:48]: We will not yet be announcing this,Vibhu [00:25:49]: NiceRune Kvist [00:25:50]: The question that is top of everyone's minds now is at the model level. And Mythos, then Fable, has really brought this to the fore that in addition to the commercial risk and the kind of economic security risks that are happening at the agent layer, the models are going to present risk in the national security category. The shape of the problem is very similar. You have some people that are on the hook if something goes wrong. In the case of agents, it's often security leaders in the enterprise. In this case, it's the government. They don'- haven't necessarily spent their entire lives thinking about what are the new risks that come here, what is the kind of data you might be looking for, how might you test that? But they do have to make sure that their concerns are addressed. You have some frontier AI companies that are deeply technical. They know a lot about the risks, but they fundamentally have an incentive to not always be truthful. So you have a trust gap between the government and the labs. And in every other industry, you end up with some kind of body sitting between, a neutral third party sitting between those people. There's no other industry where you allow people to audit themselves. So there is going to be a need for a third party that can take the rigor of the labs to run frontier technical evals, but can also speak legible trust in the way that the government trusts PwC to go and run financial audits. And they know that they output audit reports in a way that's consistent, that's easy to read, that's factual, that's, trustworthy. Those two things need to be brought together. And what we've learned from our work with agents is that if you want those-- that communication between those two parties to be smooth, there has to be one common standard that is public, that people can go and inspect. What are the risks that matter? Within each of these risks, what are the kinds of threat models that you're really looking for? You need to specify for each of those risks, what are the guardrails that need to be in place, and what are the tests they need to run to see whether those guardrails are effective? And then you need to go and run audits that are - technical audits that are consistent. So if you're trying to bring trust, it's extremely important that you methodically work your way through the risks. You can't send one researcher in and say, like, “Come back with whatever you find.” You need to be able to explain exactly what you did, exactly what you tried, exactly what you did not try, and therefore the kinds of promises you can and cannot make at the end of it. I think ofNeutral Third Parties, CAISI, and Model Risk AuditsRune Kvist [00:28:13]: Fable as a direct symptom of this problem that the government was told that there's a risk. The government may struggle to assess just how big that risk is. They call Anthropic, and Anthropic is trying to tell them, “Hey, actually, every model can be jailbroken.”Swyx [00:28:28]: That's not what you want to hear, right?Rune Kvist [00:28:32]: As the government, that might be hard to trust.Rune Kvist [00:28:36]: And we think that a broker is the most natural solution. In other markets, you see something like, in financial markets, you see Moody's. Moody's goes in, and they look at a bond, and they output a rating. They say like, “Here's the evidence we found. Here's the rating.” We don't decide whether anyone should buy this bond or not buy this bond. Well, that depends on their risk appetite. But we do provide this common information layer that everyone can rely on. In the case of Moody's, the government, points to them and say, “Hey, pension funds, you should probably really take care. You shouldn't risk your pensioners' money, so you can only invest in triple-A rated bonds.” That means that now the government doesn't have to staff thousands of financial technical experts to rerun forecasts every week to see whether things are correctly rated. They get to point to some neutral third party. So my hypothesis is, my hunch is that you will see a third party that sits between the government and the labs, and it could either be the government builds it themselves. So something like CAISI was set up to do exactly this. And the questionSwyx [00:29:44]: Sorry, I'm not familiar with CAISI.Rune Kvist [00:29:45]: CAISI is the Center for AI Standards and Innovation.Swyx [00:29:49]: Okay.Rune Kvist [00:29:50]: I won't get into the details, but it's a body of NIST that typically sets standards. So it's basically a government body that has AI experts. Yeah, exactly. Exactly.Swyx [00:29:59]: Very key. Very key.Rune Kvist [00:30:00]: Very key.Vibhu [00:30:00]: I think, you know, it's one of those things where when you just sit back and listen-- look at it, like, is there enough technical expertise in the government to measure, test these things right now? Probably not, right? And Fable is a result of, okay, we've had to scale back and pause things,Rune Kvist [00:30:17]: Yeah. And they have excellent people, but they have an extraordinarily small budget compared to the scale of the challenge that's ahead of us. And I think they have a role to play. The question is kind of like, who does what? We have now outlined the jobs to be done, and they're quite extensive. Every model release, there is an astounding-- Given that they take in any input, their risk surface is astounding. And so the question is really: what can only the government do, and what can the market provide here that can keep up with the pace as AI risk changes? Our perspective is that also at the model layer, the risks that people care about today are not the same ones they cared about three months ago. So the pace of legislation is too slow to deal with pinpointing the risks here. And so we think there's a lot that the market can do to surface timely information. Ultimately, there is a bunch of policy decisions here. Is the national security risks of a model too high?Swyx [00:31:12]: Yeah.Rune Kvist [00:31:12]: That's a political answer. But what we want to make sure is that the process that produces this risk information is compatible with very fast innovation. So you don't want to. This is not a question of like, can you slow the things down? Can you keep, the models locked up until-- for months on end until everyone can make a guarantee? But it is this, can you, in the time it. Given that the US is competing with China on releasing models, can you insert risk information that allows the government to, like, make rapid decisions on some of these questions? Balancing that trade-off between failing to adopt AI is going to put us at risk, but also reckless adoption is going to put us at risk. And that's a very kind of fine balance that they're going to need, like, a lot of high-quality intelligence to make.Chinese Models, Data Flows, and National Security ConcernsSwyx [00:31:55]: Just a side mention, because you mentioned Chinese models, any specific concerns that you're hearing from your CISOs about that? ‘cause I guess it's free, but.Rune Kvist [00:32:05]: CISOs have a bunch of concerns around data flows in general that they're really concerned about. So there's a lot of questions like, if these models are Chinese, where does that, where does that data go? I think a lot of this can be addressed, but they come up often.Swyx [00:32:18]: I mean, they understand they're running on American GPUs.Rune Kvist [00:32:21]: Some of them, some of them understand that they're running on American GPUs.Swyx [00:32:23]: They're not, like, phoning home every time you, like, call home.Rune Kvist [00:32:26]: No. A year ago, there was not a lot of understanding of this. I actually think, you're seeing the security leaders becoming kind of AI literate at a blistering pace, and you're actually also seeing my Twitter timeline that's very pilled and my LinkedIn feed that used to not at all be pilled kind of converge. They're both talking about Fable.Swyx [00:32:45]: Right. Yeah, that's true.Rune Kvist [00:32:46]: They are both talking about whether you can prevent models from being jailbroken these days.Swyx [00:32:51]: Yeah.Rune Kvist [00:32:52]: Like national security national security risks are now the conversation that is actually emerging. Other than that, I think you mostly see a kind of general picture: there are no concerns with any particular model or any particular model output, but there is a general nervousness of having critical infrastructure run on models that are not produced in America by Americans where the American government has control.Swyx [00:33:14]: But it doesn't necessarily show up in your framework that directly, or it might, I don't know.Rune Kvist [00:33:18]: There's a bit of stuff in there actually on the, like, the provenance of the models and disclosing that. But I think there's a bunch of use cases where running a Chinese open-source model is just the best solution.Swyx [00:33:27]: Yeah.Rune Kvist [00:33:27]: And a concern is slightly more macro here, which is not best addressed at any particular certification level.Vibhu [00:33:32]: Is there anything interesting that you see at the. You know, if you're trying to fill that middle gap, that mediation gap, any interesting stuff that you guys forecast would be required other than, you know, what the average person might expect?Cyber, Child Safety, Bio Risk, and Expert CoordinationRune Kvist [00:33:47]: There's a bunch of interesting questions about what are the risks that matter here. So right now, the risk of the day is cyber, because it's very real, very tangible. And some of the risks that are also emerging as pretty real and pretty tangible are things like child safety is becoming both extremely important, but also politically important. And then there are some of the risks that are coming down the pipeline that today feel kind of speculative, but people who spend a lot of time with the models see them coming down is things like, risks that relate to biology.Rune Kvist [00:34:18]: And specifically whether models will help adversaries produce biological weapons and making that extremely cheap, extremely accessible, producing-- making the chance of another COVID or worse pandemic. COVID was not engineered to be bad, as if you were trying to do that. So I think those are some of the risks that are coming down the pipeline. I think one other thing to just note is that agents are kind of deliberately narrow. So, like, when a frontier agent company puts a chatbot that interacts with customers, they've really tried to narrow the topics it's interested in talking about. Such that if you ask it, like, “What do you think of the president?” it will just decline, which means that the kind of risk area is somewhat smaller. For models, it is infinite. And so there's not a single expert out there who can competently evaluate the risks of cyberattacks and fifteen-year-olds having month-long conversations with a chatbot and seeing whether it will in fact recommend suicide or something horrendous like that, and can evaluate the risks that terrorists can use AI to produce bioweapons. The risk surface is just too big. And so the central challenge actually becomes how do you get those subject matter experts to work within a one coherent framework that outputs one coherent report and rating that the world can go and inspect? ‘Cause that global perspective is central, but there's not a single organization today that could produce that.Swyx [00:35:47]: And you would be the presumptive one when you put out your model standards.Rune Kvist [00:35:51]: We think there can be one company that can, with a consortium of experts, build one coherent standard. I think we've shown that across all of the enterprise risks today. We think it could be one company that could, with a consortium, specify the audit rules, basically like the inputs and outputs that all these technical experts need. What access do they need? How should they treat infosec- info security? They can look at whether the eval- evals are well-produced without necessarily being able to say, “Hey, is this a threat or not a threat?” But overall, evaluating whether the evals are good, well-constructed, that set of audit rules that basically becomes the interface for all these experts, we think one clearinghouse could put together. To be clear. When I say one company, I think of it as one company coordinating lots of this in the same way that when we saw our consortium, it's not like we say we have all the answers on agent security. What we say is we are taking on the role of eliciting all of the concerns and being the secretary that puts it together and runs a tight house such that the standard updates lockstep every quarter, and that the audit reports that come out, in this case, 100-page audit reports, uniform and crisp and clear all to the level of detail that is required for executives that need to make a clear go/go decision. So that's kind of the role that we think we might play.OWASP, Frameworks, and the Operational Audit LayerSwyx [00:37:11]: I think in many ways you're performing the role that OWASP used to do there, and you said, like, you know, competition and partners.Rune Kvist [00:37:18]: Yeah.Swyx [00:37:19]: Can you go more into, like, how they partner?Rune Kvist [00:37:20]: Yeah. So first of all, OWASP is basically an open source community of security practitioners that are coming together to build frameworks for addressing the latest security concerns. We think they are phenomenal at creating frameworks. We'- In fact, we'- First of all, we're partners with them, so we have a joint article. Two, we've learned a lot from them. We think they're a tremendous source of intelligence. What OWASP does not do is building the machine that runs third-party audits such that a company like Cursor or a company like JPMorgan could get a third party to go and review them against this and say, “Hey, you've passed the standard, and here is the report that you can use to build trust and preempt your partners' or customers' questions.” So they fundamentally try to do something different. You - They are part of the information gathering and intelligence gathering and creating clarity, but the operational layer of turning this into promises is not the business they try to be in.Swyx [00:38:14]: The standard is emerging and is doing very well. Was it necessary to then also do underwriting? Obviously it's in the name, so please remember you thought about it first. I feel like if you just have enough consensus, you don't actually need the money angle, but it does help.Vibhu [00:38:30]: I did want to also note, you guys are a profit company too, right? It's not profit where there's a whole business side to it as well?Why For-Profit Standards and Insurers MatterRune Kvist [00:38:39]: Yeah. Yeah, so I'm just getting crazySwyx [00:38:41]: I think about the money part.Rune Kvist [00:38:42]: Yeah. Yeah, let's get into the money part. Let's start from actually your question, profit versus profit. In the security space today, cybersecurity, most of the standards are produced by nonprofits. I think that's an issue.Rune Kvist [00:39:00]: The question you have to ask yourself is, how do you create good incentives for these standards to be good and keep up?Rune Kvist [00:39:09]: Nonprofits tend to not have these adverse profit incentives where they, hollow out their standard and create a race to the bottom, but they're also not at all responsive by default to the communities that they serve. There's no process-- They don't have customers that they serve where they go and ask, “What do you want? What do you want? What do you want?” And when you look at the overall satisfaction with the security standards today, people tend to just not like them very much. You do see in other domains, that profit standards can serve the world quite well. So there are examples, like we talked about Moody's before. It's not without flaws, but, it is absolutely critical societal infrastructure that gets run at an astounding scale today. Your credit score, it's FICO. It's also a profit business. And when you go back even further in history, some of the crash testing standards came out of insurance companies.Rune Kvist [00:40:06]: The insurance companies together founded the Insurance Institute for Highway Safety because they were very interested in, like, how can we use standards to drive down mortality and save money? Go back, prior-- Our name actually pays homage to the Underwriters Laboratories, UL, which, was started right around when electricity came out. Houses started burning down. Insurers, again, were paying the bill, and they were maybe also good people, but their profit incentive was, let's prevent houses from burning down. Let's test all the electrical products, the light bulbs. All the light bulbs in here are probably tested, the toasters, et cetera. And they set up, an entity to create those standards. Today, UL has a profit entity and a profit entity. What they've recognized, they spun - They started profit. They spun out a profit because what they recognized was like, hey, actually to serve customers well, you need a profit entity. The lesson here is one of the ways that the market can align incentives so you're both responsive to customersRune Kvist [00:41:07]: And not hollowing out your standard over time is to align it with insurers because they fundamentally have good incentives. And so if you're a profit standard that works closely with insurers, you get the feedback loop in such that you're really tuned into your customers, but also have their interest at heart. So that's the model that we - the kind of inspirational model that we've learned a lot from, and that's also where the name comes from. In some ways, the term underwriting can both be associated with insurance, but it's also a broad term for, like, making decisions.Rune Kvist [00:41:40]: If you underwrite a decision, you're fundamentally kind of taking ownership for the consequences of it.AI Insurance Contracts, Lloyd's of London, and ElevenLabsSwyx [00:41:45]: Yeah, I mean, what does an insurance contract look like for AI?Rune Kvist [00:41:49]: Yeah. Most of the demand comes today for insurance contracts is, sitting between people who've built AI and people who are buying AI.Swyx [00:41:56]: Yes.Rune Kvist [00:41:57]: And what you want—the reason why people want insurers involved, both for the traditional reasons, hey, if something goes wrong, we want to be compensated, but it's in particular because insurers can bring trust to the equation. Because insurers will pay for the damages, if they're willing to write an insurance policy, that is them saying, “Hey, we think there is risk here, but that is manageable.” And that is kind of a. Their incentive aligns with the enterprises adopting it, so that's a really a good signal to the market. In the same way, actually, one of the things that Waymo tried to get their first permit to even operate in San Francisco was to get a lot of insurers to stack up a huge insurance policy. In the case if something went wrong, not because Google can't pay, but because it was very valuable to have a third party go and look at that dataRune Kvist [00:42:47]: That are trusted by governments, trusted by enterprises as conservative people and say, “Hey, we've looked at it. We're actually willing to take some of this on our balance sheet.” So that's, that's kind of the reason why people are interested in it. What it looks like is, in some ways like every other insurance contract. You specify what are the perils you want to cover, how much do you want to cover them, like up to what limits, and what does it cost to cover that. And in the case of, if we take a really concrete example, ElevenLabs, bought a first of its kind AI agent insurance policy. They work with some of the biggest, enterprises that work with governments. They're really interested in going above and beyond and making promises to their customers. So they wrote a policy that covers just some of the core concerns that their customers have been asking about. And, the crucial thing was really to get Lloyd's of London, the world's oldest insurer, one of our partners, to look at this data and be that third party alongside us to say, “Hey, we think there's something here that's worth underwriting.” and that's actually what it looks like. And so they will show that contract to their customers, and they can see how much they're covered for. They can see what exactly it covers, and that will also probably change next year. They will want to write an insurance policy that might cover more.Swyx [00:44:04]: When you say Lloyd's, is it reinsurance, or are they sharing somehow at the same level orRune Kvist [00:44:11]: Yeah. So typically, the way, new companies get into insurance is that they partner with insurers such that the insurers take the majority or all of the financial risks. Fundamentally, if insurance is useful, because it brings trust, you have to be able to pay the bill. Lloyd's of London is 400 years old. They've never not paid a claim. They're extremely trusted. What Lloyd's of London struggle to do on their own is to figure out which of the risks are real, what should we be looking for, what are the kinds of technical controls, and running the tests. So they use AIUC-1 as kind of the underwriting framework, and we produce a bunch of eval results that then directly feed in to inform the pricing. So this means that ElevenLabs customers know that payment will be there. They don't have to look to our series A and see, like, do we think they have enough cash on the balance sheet? They will look at Lloyd's.Swyx [00:45:05]: Yeah.Rune Kvist [00:45:05]: Yeah.Swyx [00:45:05]: And Lloyd's, like, famously very creative. I think I remember some headline like, they insured Jennifer Lopez's, butt or something.Rune Kvist [00:45:13]: Correct.Swyx [00:45:13]: Right?Rune Kvist [00:45:13]: And I think, was it, David Beckham's right foot?Swyx [00:45:16]: So, yeah. Right?Rune Kvist [00:45:17]: And stuff like this.Swyx [00:45:18]: So, like, clearly not a large data set.Rune Kvist [00:45:22]: Exactly. It's actually a remarkable institution that's both kind of has some of the truly school virtues of having been around for a long time. They, like, really. They really operate like a trusted entity, and they have appetite to figure out the future. And I think there's a lot of recognition that both there is, like, tremendous amount of risk in AI that is poorly understood today, so getting into this business carries real risks. But also this is where lots of the risk exposure will happen in the future. This is the one market where risk is truly growing. This is the one market that will also take out some of the existing markets. Take, like, auto insurance. When there are no human drivers, how's that market going to look? Well, it's clearly going to change. How are you going to assessSwyx [00:46:08]: You want to insure Waymo?Rune Kvist [00:46:10]: I. All I'll say is the principles for how you insure Waymo are very similar to how you insure other kinds of AI.Swyx [00:46:15]: Right.Rune Kvist [00:46:15]: So again, crash testing, that's what we do for customer share at Lovable. That will also need to happen for Waymo, which is not how you do it for human drivers. So there's this growing awareness that the world is changing very fast, and the only way to learn how to underwrite AI is to write some policies. You may incur some losses and think of that as R&D expense, really. But the question for them is, like, who are the trustedtechnical partners they can get into this business with that can help them navigate and make sure they don't make, kind of foolish mistakes? But also who is willing to hear the wisdom that they have? They've done this before. They've seen it was. They were there when cyber came out. So there are lots of ways in which AI feels completely new, but there's also lots of ways in which risks look the same. And so there's actually a tremendous amount of wisdom sitting in some folks that may have gray hair, but really have, like, a keen sense of, how to quantify risk.Swyx [00:47:08]: Yeah. And the number is. So it's basically like I want fifty million dollars worth of coverage against these perils, and Lloyd's will give you a quote on it, and then you have, like, a small markup or something, and then you turn it around and do that? Is that as simple as it is?Risk Capital, Premiums, and Working with InsurersRune Kvist [00:47:23]: You basically share some of that premium.Swyx [00:47:25]: Yeah.Rune Kvist [00:47:25]: X percent goes to the people who do the pricing of it.Swyx [00:47:28]: You're. It's kind of like a. It's kind of like a merchant bank for insurance type of thing.Rune Kvist [00:47:33]: Exactly. You basically split the fee, and you can think of the insurance supply chain as, like, there's bringing the capital, there is doing the pricing, and there is doing the distribution. And typically, you will pay out some X percent of premium here, Y percent of premium here, and the rest of it will go here.Swyx [00:47:46]: Does all the insurance world work like this, or is there some point at which, like. So if right now you have equity capitalRune Kvist [00:47:51]: Yeah.Swyx [00:47:52]: At some point, maybe you start raising, debt or whatever, and then you have enough of a bank account and enough history, let's say you've been in operation for ten yearsRune Kvist [00:48:00]: Correct.Swyx [00:48:00]: That you don't need Lloyd's anymore?Rune Kvist [00:48:02]: That's totally an option. And I could see some worlds where that makes sense, specifically if there are risks that we feel high confidence that we'd want to insure where the incumbent insurers are too slow to find appetiteSwyx [00:48:13]: Okay.Rune Kvist [00:48:13]: Or simply struggle to evaluate it such that they don't want to do it. But by and large, in general, you do not want to compete with insurers on, bringing risk capital to the game for two reasons. One is that's fundamentally a cost of capital game. They have extremely low cost of capital. Startups have high cost of capital, by and large. And two, you want to hedge your bets, and it's very helpful then to also have a portfolio of home insurance, of car insurance. And we're not about to become a car insurer nor a home insurer.Rune Kvist [00:48:43]: So they have some natural advantages, which makes it much more likely that we'll partner.Swyx [00:48:48]: Yeah.Rune Kvist [00:48:48]: And they bring that, the capital at scale, and we bring the technical expertise.Swyx [00:48:51]: You're, you're going to work with them for a long time.Vibhu [00:48:52]: How are the discussions with the insurers as well? So basically, they're going off of your certification, right? They're trusting the diligence on you that your certification is valid, you tested the right things, and they're backing the money that, you know, you have the right testing in place. So any interesting takeaways from working with insurers?Rune Kvist [00:49:12]: I think the maybe the first thing is they feed into the standard as well. So if there are things that they feel like they need that they're not seeing, we are also taking that as input into the standard, because fundamentally we think a good standard is one that creates a really healthy promise ecosystem, and we think insurers are a critical part of that. And again, they are the most well-incentivized to. They see all the lost data across every. Any particular CISO knows their particular concerns. Insurers see the concerns across the entire portfolio and often have direct access to, like, what exactly happened, who was at fault, et cetera, as they do part of their forensics. So they're actually, like, a great source of intelligence on this. One of the big takeaways from cyber insurance, which is a market that didn't work that well, was that the insurance and the technical expertise was not married up. What our conviction is that standards have to precede insurance. Fundamentally, what everyone first and foremost want, whether you're a CISO at JPMorgan or a CISO at Cursor or an underwriter at Lloyd's of London syndicate, is you want to not have an incidentRune Kvist [00:50:19]: In the first place. You want to know that the risk is well-managed, and only then does insurance start to make sense. So we'll see the standard ecosystem basically run ahead of the insurance. And the reason why we. You asked us kind of why I also do insurance, this is kind of proving what we think a whole promise confidence infrastructure ecosystem needs to look like, and we think it's very compelling to bring that to life, even if we think the standard is kind of the core linchpin that unlocks the rest.Claims, Liability, Air Canada, and Duty of CareSwyx [00:50:44]: There's been no claims yet, right?Rune Kvist [00:50:45]: Nope.Swyx [00:50:46]: This is one of those things where, you know, if people haven't really worked through what it means to cover things.Rune Kvist [00:50:52]: Yeah.Swyx [00:50:52]: So for example, I pay Cursor $20 a month.Rune Kvist [00:50:55]: Yep.Swyx [00:50:56]: And I write a vibe code something that makes, a plane crash, causing $200 million worth of damage.Rune Kvist [00:51:02]: Yes.Swyx [00:51:02]:

The squad plays matchmaker on a chaotic Homie Helpline where 39-year-old "Thick Paula Abdul" picks a Super Mario lookalike who won her over with a clutch Vin Scully line ⚾

Anna Crowe is the founder and CEO of Crowe PR, an award-winning integrated public relations agency she launched in 2015.Her path to PR is anything but typical. Anna began her career in accounting at a Big Four firm before moving into marketing and communications, where she went on to work with iconic brands including Sony, AT&T, Jennifer Lopez, The Beatles, and Coldplay. Today, she brings that combination of financial discipline, creativity, and an ROI-focused mindset to building brands and leading a growing agency. Anna is also a best-selling author, speaker, marketing professor, and entrepreneur who has spent more than two decades thinking about what makes brands—and the people behind them—stand out.The PR Podcast is a show about how the news gets made. We talk with great PR people, reporters, and communicators about how the news gets made and strategies for publicity that drive business goals. Host ⁠⁠Jody Fisher⁠⁠ is the founder of Jody Fisher PR and works with clients across the healthcare, higher education, financial services, real estate, entertainment, and non-profit verticals. Anna Crowewebsite: https://www.anna-crowe.comInstagram: https://www.instagram.com/acrowepr/LinkedIn: https://www.linkedin.com/in/annacrowe25/Crowe Media website: https://www.crowe-media.comInstagram: https://www.instagram.com/crowepr/LinkedIn: https://www.linkedin.com/company/crowepr/home/The PR Podcast Facebook: https://www.facebook.com/ThePRPodcast/Twitter: https://x.com/ThePRPodcast1Instagram: https://www.instagram.com/theprpodcast_/TikTok: https://www.tiktok.com/@theprpodcast?

Interview Date: August 30, 2026Episode SummaryIn Episode 149 of The Business of Dance Podcast, host Menina Fortunato sits down with Los Angeles-based choreographer, movement director, and performer Noelle Marsh. Noelle traces her path from a small dance studio in North Carolina to the world stage, beginning with dance at age three, competing nationally, and appearing on So You Think You Can Dance, which became her gateway into the industry. She opens up about assisting Mia Michaels, being mentored by Brian Friedman, and choreographing and later performing alongside Tate McRae. Noelle also shares what it was like dancing in the Thriller sequence of the Michael Jackson biopic and the emotional weight of stepping into that legacy. The conversation explores her transition from performer to creative lead, moving fluidly between dancing and choreography, the fear and freedom of rejection, and why she believes people feel your thoughts more than your words. The episode closes with a mentee Q&A about authenticity, standing out in the room, building connections, and navigating today's social-media-driven industry.Shownotes00:50 – Introducing guest Noelle Marsh03:10 – Growing up dancing in small-town North Carolina04:33 – Getting the call to assist Mia Michaels07:00 – Moving to Los Angeles with no plan and no backup10:33 – First booking: the Oscars with Adam Shankman12:42 – Building a relationship with Brian Friedman15:07 – Choreographing and later dancing for Tate McRae19:20 – Dancing in the Thriller sequence of the Michael Jackson biopic24:04 – Transitioning from performer to choreographer27:00 – Winning Every Single Step and gaining creative confidence29:48 – Balancing dancing and choreography today32:37 – Authenticity, thoughts over words, and reframing rejection36:56 – Mentee Q&A: connections, standing out, and social media's role todayBiographyNoelle Marsh is a Los Angeles-based choreographer, movement director, and performer whose career moves across contemporary dance, pop culture, film, television, and brand work. After growing up in North Carolina, she appeared on So You Think You Can Dance, assisted Mia Michaels, and became part of the original company of Shaping Sound.As a performer, Noelle has worked with artists including Beyoncé, Taylor Swift, Jennifer Lopez, Dua Lipa, Tate McRae, Halsey, Mariah Carey, Gwen Stefani, and Katy Perry. Her choreography and movement-direction work includes projects for Tate McRae, The Voice, and campaigns for Bose, McDonald's, Motorola, and DSW.Connect with NoelleInstagram — @noellemarsh

Robin Williams plays a 10-year-old boy who looks like a 40-year-old man in the 1996 Francis Ford Coppola film Jack—a movie that wants to be a dramedy but is actually a body horror flick about boomers and their mortality. Paul, Jason, and June cover Fran Drescher's inexplicable attraction to Jack, Bill Cosby farting in the treehouse, if Jennifer Lopez was tempted to be Jack's date, why Jack was NOT a shooting star, and so much more. Plus, Paul shares a childhood story about an awkward hotel check-in experience with his mom. • Join our Vulture Movies Fantasy League at vulture.com/hdtgm • Go to hdtgm.com for tour dates, merch, FAQs, and more • Leave us a voicemail at speakpipe.com/hdtgm • Submit your Last Looks theme song here • Join our Discord at discord.gg/hdtgm • Buy merch at howdidthisgetmade.dashery.com/ • Order Paul's book about his childhood: Joyful Recollections of Trauma • Shop our new hat collection at podswag.com • Paul's Discord: discord.gg/paulscheer • Paul's YouTube page: youtube.com/paulscheer • Follow Paul on Letterboxd: letterboxd.com/paulscheer • Subscribe The Dark Web w/ Paul & Rob Huebel: youtube.com/@enterthedarkweb • Listen to Unspooled with Paul & Amy Nicholson: unspooledpodcast.com • Listen to The Deep Dive with June & Jessica St. Clair: thedeepdiveacademy.com/podcast • Instagram: @hdtgm, @paulscheer, & @junediane • Twitter: @hdtgm, @paulscheer • Jason is not on social media • Episode transcripts available at how-did-this-get-made.simplecast.com/episodes Get access to all the podcasts you love, music channels and radio shows with the SiriusXM App! Get 3 months free using the link: siriusxm.com/hdtgm Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

01.Benny Benassi, Hypaton, Sandy Chambers – Illusion 02.Armin Van Bureen – In And Out Of Love (Lilian Bilotta Remix) 03.Lufthaus Feat Sophie Ellis Bextor – Immortal 04.Zerb, The Chainsmokers & Ink – Addicted (Drove Remix) 05.Meduza Feat Henry Camamile – Don't Wanna Go Home 06.Lady Gaga – Abracadabra (Makj Remix) 07.Gorilla Zippo – Танцую До Утра 08.Pete Tong, Roro, Jules Buckley, The Essential Orchestra – Rhythm Of 09.Esse – Make My Day 10.Chique, No Hopes – Dance Of The Fire 11.Argy, Omnya – Aria 12.Meduza, Becky Hill, Goodboys – Lose Control 13.Raye – Where Is My Husband (David Guetta & Hypaton Remix) 14.Rio – Shine On (Gonsu X Jenia Smile & Ser Twister Remix) 15.Anyma, Stylo – No Good 16.Ava Max – Don't Click Play 17.Chris Lake, Chris Lorenzo, Kenny Beats, Cake – Long Jacket 18.Kiesza – Hideaway (Jay Bird Remix) 19.Madonna, Martin Garrix – Bizarre 20.Jon.K, Artemios Trigo – Calabria 21.Fisher & Aatig – Take It Off 22.Rita Ora Feat. Fatboy Slim – Praising You (Fatboy Slim Remix) 23.Touchtalk – Change It (Westend Edit) 24.Oliver Heldens Feat. Kstewart – Last All Night (Koala) 25.Sonny Fodera, D.O.D, Poppy Baskcomb – Think About Us 26.Duck Sauce – Barbra Streisand (Rubbio Remix) 27.Haven. – I Run (Azooland Remix) 28.Robin Schulz – Embers 29.Alan Walker, Steve Aoki, Arash – Broken Angel (Valeriy Smile Remix) 30.Fast Boy – Music Sounds 31.Duke Dumont – Ocean Drive (Rowka Remix) 32.Masters At Work X Nix – Work (Chique Blend) 33.Heartless House – Pussy 34.Sean Finn – Give It To Me 35.Filatov & Karas – Включи Музыку 36.Dimitri Vegas & Like Mike, Tiësto, Dido, W&W – Thank You Not So Bad (Alex Caspian Remix) 37.Sistek, Morry, Fly Project – Toca Toca 38.Lady Gaga – The Dead Dance (DJ Dark Remix) 39.Atb, Topic, A7s – Your Love (9pm Ramirez & Yudzhin Remix) 40.Imanbek – No Matter What 41.DJ Peretse, DJ Nejtrino, Lexolee, Dmc Kelz – Washed Away 42.Jonas Blue, Malive – Edge Of Desire 43.Tony Dark Eyes – Perfect 44.Eric Mars – Popcorn (Valeriy Smile Remix) 45.Hosh & 1979 Feat. Jalja – Midnight (Sasha Goodman Remix) 46.Klangkarussell – Ride 47.Filatov & Karas – Time Won't Wait 48.J Balvin, Willy William – Mi Gente (Gonsu, Jenia Smile & Ser Twister Remix) 49.DJ Peretse X DJ Nejtrino – Rockit 50.Darude – Sandstorm 2k25 (DJ Morpheuz Remix) 51.1-8. Malaa – Bonnie 52.Daft Punk – Around The World (Westend Edit) 53.Avö, Sauaro, Tony Shades, Andrew Aoun – Barababa 54.Trap Mafia House – Mafia Style 55.Calvin Harris – My Way 56.Joel Corry, Rahh – Devotion Sweetest Emotion 57.Topic, Carteblanche – Lucky Ones 58.Jennifer Lopez, David Guetta – Save Me Tonight 59.Tommy Cash – Espresso Macchiato 60.Prospa, Cloonee – Free Your Mind 61.Sean Finn – Crazy 62.Shouse, Cub Sport – Only You 63.Boney M., R3hab – Sunny 64.DJ Peretse, DJ Nejtrino – Pardonne-Moi 65.Block & Crown – Power Dancer 66.Zerb, Ty Dolla $Ign, Wiz Khalifa – Location 67.DJ Kuba, Neitan, Bounce Inc. – Watch Out 68.Whiteout, Depdramez, Mitti – Now You're Gone 69.Mark Dann Feat Giovanni Ricci – Let Me Die (Alex Caspian Remix) 70.Bebe Rexha & Faithless – New Religion (DJ Dark Remix) 71.Ed Sheeran – Bad Habits (Triiper Bootleg) 72.Dunmore Brothers – Trust Me 73.Hurts, Purple Disco Machine – Wonderful Life 74.DJ Antonio, Drama Heroes, DJ Chris Parker, Tomyam – Space

This week on Bad Dads Film Review, Sidey, Dan, Reegs and Cris take on Steven Soderbergh's Traffic, the Oscar-winning 2000 ensemble drama about the war on drugs, starring Michael Douglas, Benicio del Toro, Catherine Zeta-Jones, Don Cheadle, Luis Guzmán, Erika Christensen, Dennis Quaid and several thousand other people you recognise from better-lit rooms.The episode begins with Reegs back from France, a heroic return to walking football, a 6–2 win, snacks from Grand Marché, Rioja on the table and the usual sense that the podcast might be more structured if anyone genuinely wanted that. Recent viewing includes Dan on Early Man, Ted Lasso and Grown Ups, Reegs going deep into Reacher, Cris bringing a bit of cartel-adjacent homework energy, and Sidey watching Barry plus Netflix serial-killer thriller The Whisper Man, a film he enjoys until the last-minute ghost business turns up and starts knocking over the furniture.Before the main film, the dads count down Steven Soderbergh and Soderbergh-adjacent favourites. Cris explains how Benicio del Toro led him towards Traffic and Che, while the conversation takes in the myth and reality of Che Guevara, Soderbergh's habit of editing and shooting under pseudonyms, and the frankly annoying fact that he appears to have made several films since this paragraph began. The list includes Solaris, Contagion, Syriana, Logan Lucky, Erin Brockovich, Magic Mike, Ocean's Eleven, Ocean's Thirteen, Haywire, Her, Confessions of a Dangerous Mind and Sidey's beloved Out of Sight, which he still considers a 10-out-of-10 film thanks to Clooney, J-Lo, Luis Guzmán, Catherine Keener, David Holmes and the sort of charm that should probably be illegal.Then it is time for Traffic, a film the dads remember as serious, long, colour-coded and very much trying to win awards, which, to be fair, it did. The review follows the film's interlocking stories: Javier Rodriguez trying to do good police work in Mexico while the system around him is already captured by cartel politics; DEA agents Montel Gordon and Ray Castro attempting to protect an informant long enough to bring down Carl Ayala; Helena Ayala discovering that being a wealthy pregnant society wife becomes much more complicated when your husband is dragged away by federal agents; and Robert Wakefield becoming America's new drug czar just as his own daughter Caroline falls into addiction.The dads dig into the film's bleak central point: the drug war is not really a war that can be won, because every apparent victory is also part of somebody else's business model. Sidey describes the film as showing where drugs come from, how they move, how people try to stop them, where demand lives and why the whole machine is so futile. Cris particularly likes the Mexico storyline and the way the film's colour palette helps you instantly know which world you are in, while Reegs connects the whole thing to the kind of institutional fatalism later explored in The Wire.A major talking point is the subtitle disaster. Dan and Sidey both watched versions where the Spanish sections were not properly translated, which is not ideal when huge parts of your Oscar-winning bilingual drama are in Spanish. Dan's version apparently just told him people were “speaking Spanish”, which he had already managed to work out by being awake. Reegs uses this as a chance to grumble, correctly, about the loss of physical media and the way streaming platforms can serve up broken versions of films without anyone seeming to care.The film itself gives the dads plenty to chew on: Benicio del Toro's quiet moral centre, the funfair arrest and “don't shoot the clown”, Luis Guzmán's excellent Ray Castro and his brutal car-bomb exit, Catherine Zeta-Jones going from shocked wife to ruthless operator, Dennis Quaid sniffing around the Ayala money, Caroline Wakefield's awful spiral, Michael Douglas having to confront the war on drugs happening in his own house, and Javier's beautifully modest final request for electricity so kids can play baseball at night.Verdicts are positive, but not breathless. Sidey thinks Traffic is extremely well made, handheld, fluid, serious and still strong, but also calls it a one-and-done rather than a film he would rush to revisit. Dan struggles more, partly because the missing subtitles kneecapped the experience and partly because the film is long, worthy and occasionally lost up its own arse; if forced to choose, he is watching Gladiator twice before watching Traffic twice. Cris is warmer on it, praising the acting, the structure, the Mexican material and the way the separate stories connect without turning into a neat crossover event.So the Bad Dads verdict lands somewhere between strong recommend and medium-well: a serious, grown-up Soderbergh drama about drugs, power, money, family and futility, admired more than loved, and improved enormously if your streaming service can manage the advanced technical feature known as subtitles.You can now text us anonymously to leave feedback, suggest future content or simply hurl abuse at us. We'll read out any texts we receive on the show. Click here to try it out!We love to hear from our listeners! By which I mean we tolerate it. If it hasn't been completely destroyed yet you can usually find us on twitter @dads_film, on Facebook Bad Dads Film Review, on email at baddadsjsy@gmail.com or on our website baddadsfilm.com. Until next time, we remain... Bad Dads

How To Lose A Guy In 10 Days is officially getting the TV sequel treatment, and we're spiralling over what that means for the most iconic yellow dress moment, reimagined. But it got us thinking about the one thing every great rom com has in common: an enormous, plot-driving lie. From fake fiancés to stolen identities to a man who helps reset his girlfriend's memory every single day, we're deep diving the beautiful deceptions that make these movies work, and would absolutely land you in a true crime doco in real life. We're unpacking all our favourite love story deceptions, before landing on the takeaway we did not see coming: maybe we should all just be lying more. TAKE THE SPILL'S WEEKLY POP CULTURE QUIZ HERE Become a Mamamia subscriber and get an all-access pass to everything we make, including exclusive podcasts and early listening, subscriber-only articles, monthly giveaways and our home workout app, MOVE. Get access to Very Peri, Mamamia's exclusive perimenopause series, for just $59. 25 world-leading experts, over 20 on-demand sessions, available now. We’ve sorted through the noise so you don't have to. Go to veryperi.com.au and join me today. You hot? Same. Buy today and save 40%THE END BITS Find and follow us on socials: Instagram: https://www.instagram.com/thespillpodcast/ TikTok: https://www.tiktok.com/@thespillpod Facebook: https://www.facebook.com/thespillpodcast/ Support independent women's media Want to join the conversation? Have feedback or a topic you want us to discuss? Send us a voice message or email us at thespill@mamamia.com.auand we’ll get back to you ASAP! Executive Producer: Monisha Iswaran Audio & Video Producer: Julian Rosario Mamamia acknowledges the traditional owners of the land on which we have recorded this podcast.Become a Mamamia subscriber: https://www.mamamia.com.au/subscribeSee omnystudio.com/listener for privacy information.

In The Loop looks beyond the obvious matchups in Texans-Bills and asks which intangibles could turn into something tangible once the game begins. What little things—momentum, experience, emotion, coaching decisions or unexpected plays—could ultimately swing Week 1? Then it's time for Lunch-Time Confessions, where Lopez has a bone to pick with a Netflix broadcast. The hour wraps with J-Lo's College Football Headline of the Weekend presented by Wrangler, as Lopez picks the college football storyline he'll be watching closest this weekend.

In The Loop gets you ready for Texans-Bills in Week 1, starting with what has the crew most excited to finally see when Houston takes the field and which players, matchups and storylines could define the opener. The guys react to Texans OC Nick Caley's comments on Kayshon Boutte and Jaylin Noel before asking the Question of the Day: What's the biggest letdown you've ever had on a trip or vacation? ITL then goes Around The NFL to hit the biggest stories across the league before B-Scott gives his thoughts on Texans-Bills and what could ultimately decide the game, followed by What's Popping in sports and entertainment. Later, the crew looks beyond the obvious matchups and asks which intangibles could turn into something tangible on Sunday, before Lunch-Time Confessions, where Lopez has a problem with a Netflix broadcast, and J-Lo's College Football Headline of the Weekend presented by Wrangler. The show wraps with Texans Win Because, Texans Lose Because: Bills Edition, laying out exactly how Houston could start the season 1-0—or what could lead to a loss—before Figgy's Mixtape looks back at things we used to do before 9/11, reacts to a social media influencer who died after undergoing a penis enlargement procedure, and hears what listeners have to say on Figgy's Mixtape Voicemail.

01.Benny Benassi, Hypaton, Sandy Chambers – Illusion 02.Armin Van Bureen – In And Out Of Love (Lilian Bilotta Remix) 03.Lufthaus Feat Sophie Ellis Bextor – Immortal 04.Zerb, The Chainsmokers & Ink – Addicted (Drove Remix) 05.Meduza Feat Henry Camamile – Don't Wanna Go Home 06.Lady Gaga – Abracadabra (Makj Remix) 07.Gorilla Zippo – Танцую До Утра 08.Pete Tong, Roro, Jules Buckley, The Essential Orchestra – Rhythm Of 09.Esse – Make My Day 10.Chique, No Hopes – Dance Of The Fire 11.Argy, Omnya – Aria 12.Meduza, Becky Hill, Goodboys – Lose Control 13.Raye – Where Is My Husband (David Guetta & Hypaton Remix) 14.Rio – Shine On (Gonsu X Jenia Smile & Ser Twister Remix) 15.Anyma, Stylo – No Good 16.Ava Max – Don't Click Play 17.Chris Lake, Chris Lorenzo, Kenny Beats, Cake – Long Jacket 18.Kiesza – Hideaway (Jay Bird Remix) 19.Madonna, Martin Garrix – Bizarre 20.Jon.K, Artemios Trigo – Calabria 21.Fisher & Aatig – Take It Off 22.Rita Ora Feat. Fatboy Slim – Praising You (Fatboy Slim Remix) 23.Touchtalk – Change It (Westend Edit) 24.Oliver Heldens Feat. Kstewart – Last All Night (Koala) 25.Sonny Fodera, D.O.D, Poppy Baskcomb – Think About Us 26.Duck Sauce – Barbra Streisand (Rubbio Remix) 27.Haven. – I Run (Azooland Remix) 28.Robin Schulz – Embers 29.Alan Walker, Steve Aoki, Arash – Broken Angel (Valeriy Smile Remix) 30.Fast Boy – Music Sounds 31.Duke Dumont – Ocean Drive (Rowka Remix) 32.Masters At Work X Nix – Work (Chique Blend) 33.Heartless House – Pussy 34.Sean Finn – Give It To Me 35.Filatov & Karas – Включи Музыку 36.Dimitri Vegas & Like Mike, Tiësto, Dido, W&W – Thank You Not So Bad (Alex Caspian Remix) 37.Sistek, Morry, Fly Project – Toca Toca 38.Lady Gaga – The Dead Dance (DJ Dark Remix) 39.Atb, Topic, A7s – Your Love (9pm Ramirez & Yudzhin Remix) 40.Imanbek – No Matter What 41.DJ Peretse, DJ Nejtrino, Lexolee, Dmc Kelz – Washed Away 42.Jonas Blue, Malive – Edge Of Desire 43.Tony Dark Eyes – Perfect 44.Eric Mars – Popcorn (Valeriy Smile Remix) 45.Hosh & 1979 Feat. Jalja – Midnight (Sasha Goodman Remix) 46.Klangkarussell – Ride 47.Filatov & Karas – Time Won't Wait 48.J Balvin, Willy William – Mi Gente (Gonsu, Jenia Smile & Ser Twister Remix) 49.DJ Peretse X DJ Nejtrino – Rockit 50.Darude – Sandstorm 2k25 (DJ Morpheuz Remix) 51.1-8. Malaa – Bonnie 52.Daft Punk – Around The World (Westend Edit) 53.Avö, Sauaro, Tony Shades, Andrew Aoun – Barababa 54.Trap Mafia House – Mafia Style 55.Calvin Harris – My Way 56.Joel Corry, Rahh – Devotion Sweetest Emotion 57.Topic, Carteblanche – Lucky Ones 58.Jennifer Lopez, David Guetta – Save Me Tonight 59.Tommy Cash – Espresso Macchiato 60.Prospa, Cloonee – Free Your Mind 61.Sean Finn – Crazy 62.Shouse, Cub Sport – Only You 63.Boney M., R3hab – Sunny 64.DJ Peretse, DJ Nejtrino – Pardonne-Moi 65.Block & Crown – Power Dancer 66.Zerb, Ty Dolla $Ign, Wiz Khalifa – Location 67.DJ Kuba, Neitan, Bounce Inc. – Watch Out 68.Whiteout, Depdramez, Mitti – Now You're Gone 69.Mark Dann Feat Giovanni Ricci – Let Me Die (Alex Caspian Remix) 70.Bebe Rexha & Faithless – New Religion (DJ Dark Remix) 71.Ed Sheeran – Bad Habits (Triiper Bootleg) 72.Dunmore Brothers – Trust Me 73.Hurts, Purple Disco Machine – Wonderful Life 74.DJ Antonio, Drama Heroes, DJ Chris Parker, Tomyam – Space

1.Benny Benassi, Hypaton, Sandy Chambers – Illusion 2.Armin Van Bureen – In And Out Of Love (Lilian Bilotta Remix) 3.Lufthaus Feat Sophie Ellis Bextor – Immortal 4.Zerb, The Chainsmokers & Ink – Addicted (Drove Remix) 5.Meduza Feat Henry Camamile – Don't Wanna Go Home 6.Lady Gaga – Abracadabra (Makj Remix) 7.Gorilla Zippo – Танцую До Утра 8.Pete Tong, Roro, Jules Buckley, The Essential Orchestra – Rhythm Of 9.Esse – Make My Day 10.Chique, No Hopes – Dance Of The Fire 11.Argy, Omnya – Aria 12.Meduza, Becky Hill, Goodboys – Lose Control 13.Raye – Where Is My Husband (David Guetta & Hypaton Remix) 14.Rio – Shine On (Gonsu X Jenia Smile & Ser Twister Remix) 15.Anyma, Stylo – No Good 16.Ava Max – Don't Click Play 17.Chris Lake, Chris Lorenzo, Kenny Beats, Cake – Long Jacket 18.Kiesza – Hideaway (Jay Bird Remix) 19.Madonna, Martin Garrix – Bizarre 20.Jon.K, Artemios Trigo – Calabria 21.Fisher & Aatig – Take It Off 22.Rita Ora Feat. Fatboy Slim – Praising You (Fatboy Slim Remix) 23.Touchtalk – Change It (Westend Edit) 24.Oliver Heldens Feat. Kstewart – Last All Night (Koala) 25.Sonny Fodera, D.O.D, Poppy Baskcomb – Think About Us 26.Duck Sauce – Barbra Streisand (Rubbio Remix) 27.Haven. – I Run (Azooland Remix) 28.Robin Schulz – Embers 29.Alan Walker, Steve Aoki, Arash – Broken Angel (Valeriy Smile Remix) 30.Fast Boy – Music Sounds 31.Duke Dumont – Ocean Drive (Rowka Remix) 32.Masters At Work X Nix – Work (Chique Blend) 33.Heartless House – Pussy 34.Sean Finn – Give It To Me 35.Filatov & Karas – Включи Музыку 36.Dimitri Vegas & Like Mike, Tiësto, Dido, W&W – Thank You Not So Bad (Alex Caspian Remix) 37.Sistek, Morry, Fly Project – Toca Toca 38.Lady Gaga – The Dead Dance (DJ Dark Remix) 39.Atb, Topic, A7s – Your Love (9pm Ramirez & Yudzhin Remix) 40.Imanbek – No Matter What 41.DJ Peretse, DJ Nejtrino, Lexolee, Dmc Kelz – Washed Away 42.Jonas Blue, Malive – Edge Of Desire 43.Tony Dark Eyes – Perfect 44.Eric Mars – Popcorn (Valeriy Smile Remix) 45.Hosh & 1979 Feat. Jalja – Midnight (Sasha Goodman Remix) 46.Klangkarussell – Ride 47.Filatov & Karas – Time Won't Wait 48.J Balvin, Willy William – Mi Gente (Gonsu, Jenia Smile & Ser Twister Remix) 49.DJ Peretse X DJ Nejtrino – Rockit 50.Darude – Sandstorm 2k25 (DJ Morpheuz Remix) 51.1-8. Malaa – Bonnie 52.Daft Punk – Around The World (Westend Edit) 53.Avö, Sauaro, Tony Shades, Andrew Aoun – Barababa 54.Trap Mafia House – Mafia Style 55.Calvin Harris – My Way 56.Joel Corry, Rahh – Devotion Sweetest Emotion 57.Topic, Carteblanche – Lucky Ones 58.Jennifer Lopez, David Guetta – Save Me Tonight 59.Tommy Cash – Espresso Macchiato 60.Prospa, Cloonee – Free Your Mind 61.Sean Finn – Crazy 62.Shouse, Cub Sport – Only You 63.Boney M., R3hab – Sunny 64.DJ Peretse, DJ Nejtrino – Pardonne-Moi 65.Block & Crown – Power Dancer 66.Zerb, Ty Dolla $Ign, Wiz Khalifa – Location 67.DJ Kuba, Neitan, Bounce Inc. – Watch Out 68.Whiteout, Depdramez, Mitti – Now You're Gone 69.Mark Dann Feat Giovanni Ricci – Let Me Die (Alex Caspian Remix) 70.Bebe Rexha & Faithless – New Religion (DJ Dark Remix) 71.Ed Sheeran – Bad Habits (Triiper Bootleg) 72.Dunmore Brothers – Trust Me 73.Hurts, Purple Disco Machine – Wonderful Life 74.DJ Antonio, Drama Heroes, DJ Chris Parker, Tomyam – Space

This week on Deux/U, Deux is talking about the hottest topics of the week, including:Updates: Miss USA pageant, Ariana Grande + Ricky Álvarez, Prince Harry + Meghan Markle, Justin + Hailey BieberFrançois ArnaudOff-CampusJennifer Lopez + Brett GoldsteinDeux/U Hotline: Olivia Rodrigo + Louis Partridge, Joe Jonas, Taylor Fritz, and more!

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