Podcasts about DAE

Up first, Inspirogene-by-McKesson with Joe DePinto   InspiroGene" is a dedicated business unit launched by McKesson in October 2024, focused solely on supporting the commercialization of cell and gene therapies (CGTs). It leverages McKesson's expertise in supply chain, logistics, and specialty pharmacy to help manufacturers, payers, and providers navigate the complex CGT landscape. https://www.mckesson.com/business-solutions/our-businesses/inspirogene-by-mckesson/ Our featured interview: Sponsored by MatchRX The TrumpRx Playbook for Independent Pharmacies CEO of MatchRx Johny Kello co-hosts with Todd Eury featuring our guest speaker, Dae Lee, Pharm.D., Esq., CPBS. Dae is a pharmacist-attorney and a Shareholder in the FDA & Biotechnology practice at Buchanan Ingersoll & Rooney. What makes Dae especially valuable for this conversation is that he's not just reading policy from 30,000 feet — he represents pharmacies every day in high-stakes fights with PBMs, from audits and reimbursement disputes to network suspensions and terminations. So, when we talk about TrumpRx — how it works, what it could break, and what independents should do next — Dae can translate the legal and contracting reality into real-world consequences behind the counter. Connect with MatchRX: MatchRX.com Special Message from Greg Reybold with APCI, update of the "Pharmacists Fight Back Act" Connect with Greg: https://www.apcinet.com/ Next, we talk with Dr. Jessica Daley PharmD Fractional Supply Chain and Operations Executive, with Pharma Logistics, we dicuss drug shortages and strategies for 2026. Connect with Jessica: https://www.linkedin.com/in/jessicaldaley/ Last interview, a suprise message from International Pharmacy 50 Pharmacist & Author Katrina Azer, announcing her new book  https://www.katrinaazer.com/#books   The TrumpRx Playbook for Independent Pharmacies - with MatchRX | TWIRx 

Reddit rSlash Storytime r doesanybodyelse where DAE : Am I the Only One Who Drinks with My Lips Inside the Glass? Does anybody else not want to be in management/the boss? DAE find that any time a TV is turned on in someone's house, motion smoothing is on, it's not a choice they made, and they can never ever tell the difference? DAE have less and less tolerance for people's nonsense/toxicity as they get older? DAE feel deep down that anyone you interact with would rather not interact with you, regardless of what they say, or how it seems on the surface? With very very few exceptions? Does anybody else never laugh when watching comedy shows, even though you still find it entertaining? DAE have a weird memory from thier childhood that they can't tell if it's real or not? DAE DAE act like the holidays don't exist? DAE feel like garage sales aren't cheap anymore and people price a lot of stuff pretty crazy? DAE feel like they can't relax unless everything at home is clean and done? DAE get weirdly cozy when there's ambient danger but you're safe? DAE have relatives with the coolest life stories that they don't share until they casually come up in conversation? DAE feel the need to see their boyfriend's b-hole? Hosted on Acast. See acast.com/privacy for more information.

Die 16 Dae van Aktivisme teen Geslagsgeweld het nogmaals nie juis 'n impak op die grond gehad nie. Vele verkragtings, gesinsgeweld, kinderaanrandings en verwante geweld is by die polisie aangemeld, maar dit is welbekend dat meeste gevalle nie aangemeld word nie. Kosmos 94.1 Nuus het gepraat met Ethne Mudge, die direkteur by Civic +264.

Send us a textSchedule an Rx AssessmentWhat happens when GLP-1 compounding, TrumpRx, and PBM audits all collide in your pharmacy?In this episode of the Bottom Line Pharmacy Podcast, hosts Austin Murray and Bonnie Bond, CPA, are joined by healthcare attorney Dae Lee of Buchanan Ingersoll to unpack the fast-moving legal and regulatory landscape around GLP-1s, PBMs, and audits—and what independent owners need to be doing right now to protect their businesses.We cover: - The vertical integration behind the “big three” PBMs and their rebate aggregators- Why PBM audit triggers and the realities of today's audit tactics- A practical roadmap for responding to an audit- What “recredentialing season” really means- TrumpRx And more!More About Our Guest:Dae Y. Lee, Pharm.D., Esq., CPBS focuses on representing pharmacies in their dealings against Pharmacy Benefit Managers (PBMs). With extensive experience in the intricacies of PBM audits, investigations, network enrollment, network suspension, network terminations, reimbursement disputes, and DEA as well as other governmental investigations, Dae has become a trusted advisor to a broad cross-section of pharmacies and pharmacy providers, including community retail pharmacies, chain pharmacies, compounding pharmacies, specialty pharmacies, mail order pharmacies, home infusion providers, and dispensing physician practices.. His practice also extends to assisting other stakeholders in the pharmacy industry such as wholesalers, manufacturers, and other healthcare providers. In addition to his PBM-focused work, Dae represents entities in pharmacy-related transactions and assists clients with corporate formation, due diligence, licensing, change-of-ownership requirements and credentialing, providing comprehensive legal support throughout the transaction process. Dae is a Certified Pharmacy Benefits Specialist™ (CPBS™). Offered through TransparentRx and accredited by the University of Kentucky School of Pharmacy, the CPBS program is designed to cover complex topics of pharmacy benefit management in order to provide a foundational knowledge required for higher-level evaluation of PBM business operations, fundamentals of PBM pricing, plan design, cost-containment strategies, PBM contracts, PBM procurement, Specialty Pharmacy benefits management, and overall PBM performance with emphasis on cost effectiveness.Stay connected with Dae and Buchanan, Ingersoll, & Rand: Dae Lee LinkedInBuchanan, Ingersoll, & Rand WebsiteBuchanan, Ingersoll, & Rand LinkedInBuchanan, Ingersoll, & Rand TwitterBuchanan, Ingersoll, & Rand FacebookStay connected with us on social media:FacebookTwitterLinkedInMore on this topic:Podcast: The Startup Compounding Pharmacy PlaybookPodcast: The Trusted Pharmacist: Advocacy and Building a Resilient PharmacyPodcast: From Counter to Capitol

In this episode (recorded live at the Sempertex International Balloon Convention), Jessica and Dae from The Balloon Club Co. share their journey of combining their individual balloon businesses into something new, together. They discuss the importance of trust and communication in their partnership, and the significance of setting boundaries to maintain work-life balance. They also share encouragement for getting past the fears of entrepreneurship. Key takeaways include: How trust is essential when going into business with someone. Why communication is key in partnerships. What things they put in place for their retail shop. Why overcoming fear is necessary for personal and professional growth. How partnerships can lead to greater resources and opportunities.   It was so fun to chat with this duo and I look forward to watching their growth! In the UGlu Hotline, hear why I leave extra balloons and adhesives at my installs.   Unlock three free bonus episodes!    RESOURCES MENTIONED: Presenting sponsor: 17hats (get 50% off your 1st year)  @balloonclubco  Other sponsors & resources: 2026 Bright Balloon Planner  Havin' A Party Wholesale (save 5% on orders $200+ with code PODCAST) Gemar USA  UGlu by Pro Tapes (save 5% on orders $200+ at Havin' A Party with code PODCAST)  DM @thebrightballoon on Instagram to ask a question or leave advice for the UGlu Hotline! Balloon Boss Mastermind & Summit  - - - - On the Bright Side (Apple) On the Bright Side (Patreon) 50 Ideas for Email Marketing | Join the Bright Balloon email list  The Bright Balloon on YouTube 

Ons is vandag op die sewende dag van die 16 Dae van Aktivisme teen vrouegeweld. Intussen is twee vroue vermoor, twee verkrag en een kind verwaarloos. Kosmos 94.1 Nuus het met maatskaplike aktivis en direkteur van Civic +264, Ethne Mudge, gepraat. Sy meen dit is van kritieke belang om seuns en mans by die veldtog te betrek.

Die ANC sê Suid-Afrika kan nie die waardes van die Vryheidsmanifes ten volle verwesenlik of sy demokratiese winste saamvoeg terwyl vroue, kinders en kwesbare persone steeds met bedreigings leef nie. Die 16 Dae van Aktivisme vir Geen Geweld teen Vroue en Kinders word tans tot 10 Desember gehou. Die ANC se woordvoerder, Mahlengi Bhengu, sê hulle vra die samelewing om hul pogings te verskerp en voorkoming te versterk, oorlewendes te ondersteun en toeganklike geregtigheid en psigo-maatskaplike dienste vir die betrokkenes te verseker:

Reddit rSlash Storytime r doesanybodyelse where dae get that weird irresistible urge to bend your toes and nothing fixes it?? DAE Eat a huge meal in one sitting, and then never eat anything else for the day? DAE feel total dread the moment anything is scheduled? Does anybody else feel like they're always eating or thinking about eating? DAE ask for consent to kiss a first date? DAE feel completely drained after making like... two plans? DAE feel like being a bridesmaid is the biggest emotional and financial scam that nobody talks about? DAE feel like empathy towards animals is ruining their life? DAE worry about teenagers now DAE likes to swing as an adult? DAE social skills fluctuate wildly from day to day? DAE think the way most of us live our lives is kind of lame? DAE feel a deep sense of sadness thinking about their parents even though they're still pretty okay and still alive? DAE just not want to talk to neighbors? DAE not enjoy cooking videos that start with "Did you know that if you..." Hosted on Acast. See acast.com/privacy for more information.

Talking Taiwan's inaugural fundraising gala was on April 30th here in New York City at the elegant Eichholtz showroom in Chelsea. The gala was a celebration of Taiwanese American cuisine, culture and community.   Related Links: https://talkingtaiwan.com/talking-taiwans-2025-inaugural-fundraising-gala-ep-332/   We had Peter Lin's AAPI Jazz Collective perform, and food catered by 886 Restaurant, DAE tea and Taiwan Beer. It was a memorable, magical night and if you're wondering what you missed out on it, don't worry, later on in the episode I'll be sharing how you can watch the replay that we made of the event. We'll also share the Humanitix link where you can make a donation to watch the replay of the Talking Taiwan Gala.   At the gala I interviewed comedian Esther Chen, Thomas Duh of DAE Tea, artist Kaarina Chu MacKenzie, and Jonny Lee, President of TAP-NY (Taiwanese American Professionals- NY chapter). And that's what we'll be sharing in this episode.   Related Links: https://talkingtaiwan.com/talking-taiwans-2025-inaugural-fundraising-gala-ep-332/

Reddit rSlash Storytime r doesanybodyelse where DAE think that, from a certain age, elderly people should be tested to see if it's still safe for them to drive? DAE feel a weird sense of grief for the before times that you can't even really explain? Does anybody else spread cheeks before pooping, or is that just me (and my husband)? DAE think the 8-hour workday is too long? DAE Smell Periods before they happen? DAE have a tradition or practice in thier family that you later found out was done out of necessity or some other reason? Does anybody else notice the lack of self awareness of other people in public nowadays? DAE split up their life with “apple” and “pie” Does anybody else notice that their parents literally cannot watch movies anymore? DAE needs "face space" when cuddling? DAE notice that the new generation are not having kids?? DAE have imaginary conversations in their head pretty much all the time? DAE use the bathroom repeatedly in their dreams if they have to pee irl? DAE have a piece of pencil lead stuck in their skin? DAE get anxious when they are “scheduled” to do something? Hosted on Acast. See acast.com/privacy for more information.

This time we discussed A Mouthful of Dust, book 6 of The Singing Hills Cycle, written by Nghi Vo and narrated by Cindy Kay. We also discussed some of our favorite recent short fiction listens in our short fiction spotlight.   A Mouthful of Dust [Libro.fm] / [Overdrive/Libby] A Witch's Guide to Magical Innkeeping [Libro.fm] / [OverDrive/Libby] The Grimoire Grammar School Parent Teacher Association [Libro.fm] / [OverDrive/Libby] The Very Secret Society of Irregular Witches [Libro.fm] / [OverDrive/Libby] Short Fiction Spotlight: "Wire Mother" written by Isabel J. Kim, narrated by Kate Baker [Clarkesworld] - Issue 229: October 2025 / Short Story "Holding Patterns" written by Jennifer Hudak, narrated by Kat Kourbeti [Escape Pod 989] / Short Story "The Porniest Porn in Porntown" written by Stephen Graham Jones, narrated by Stefen Rudnicki [Lightspeed] - October 2025 (Issue 185) / Short Story "Five Impossible Things" written by Koji A. Dae, narrated by Kate Baker [Clarkesworld] - Issue 228: September 2025 / Short Story "The Garden" written by Emma Törzs, narrated by Erika Ensign [Uncanny Magazine] - Issue Sixty-Five "The Girl Who Came Before" written by David von Allmen, narrated by Pine Gonzalez [Escape Pod 1004] / Short Story  

Reddit rSlash Storytime r doesanybodyelse where DAE randomly check their bank account just to make sure money is still there? DAE think social media is dying? DAE feel like the world has been not quite right since the pandemic? DAE think wealthy people who don't pass down inheritance are crazy? DAE go through life feeling like a kid pretending to be an adult? DAE have parents with the social skills equivalent of a coconut? DAE get anxiety when they have to go outside and do lawn work because you know you're being watched? DAE live with their significant other but not share a room with them? DAE feel like you're dying when you don't get enough sleep? DAE not care about work as soon as they leave those doors every day? Does anybody else ever feel deeply curious about the lives of complete strangers? DAE feel like their IQ drops 20 points whenever they know someone is watching them do a task? Hosted on Acast. See acast.com/privacy for more information.

In this episode, Dae and Mikey break down the Mariners' game five over the Blue Jays inning-by-inning and look ahead to the next two games, and the next series. Also, [redacted] the Dodgers?

In this episode, Mikey and Dae return -- true to their bandwagon nature -- to recap the Mariners' playoff run thus far. They talk about game five implications against Detroit Tigers, and what to expect in the series finale. They also talk about Emerson Hancock?????

Yeşim Erdeğer Georgia State Üniversitesi (GSU) İletişim Bölümü'nde doktora öğrencisidir. Araştırmaları, eleştirel feminist bir bakış açısıyla aşırıcı siyasi şiddet kullanan yapılarda kadınların rolü ve medyada kadın temsillerinin çerçevelenmesi üzerine odaklanmaktadır. Yeşim Erdeger, lisans eğitimini Boğaziçi Üniversitesi Siyaset Bilimi ve Uluslararası İlişkiler Bölümü'nde tamamlamıştır. Yüksek lisans eğitimine Kadir Has Üniversitesi Uluslararası İlişkiler programında devam etmiştir. Yeşim Erdeğer, yüksek lisans tezini Türkiye'den DAEŞ'e katılan kadınların radikalleşme süreçleri üzerine yazmıştır. Bu çalışma, Türkiye'den DAEŞ'e katılan kadınlara odaklanan ve literatürde sıklıkla ihmal edilen bu alanı kapsamlı şekilde ele alan az sayıdaki araştırmalardan biri olmuştur. 2022 yılında Kadir Has Üniversitesi'nde “Terörizm ve Şiddet” dersinde öğretim asistanlığı yapmıştır. Yeşim Erdeğer, yakın dönemde Georgia State Üniversitesi'nde öğretim ve araştırma asistanı olarak görev almıştır. Şu anda aynı üniversitede Human Communication dersini vermektedir. Doktora sürecinde, toplumsal cinsiyet çalışmaları, şiddet içeren aşırıcılık, toplumsal hareketler, direniş biçimler ve medya temsilleri kesişiminde araştırmalar yürütmektedir.

This episode features "Five Impossible Things" written by Koji A. Dae. Published in the September 2025 issue of Clarkesworld Magazine and read by Kate Baker. The text version of this story can be found at: https://clarkesworldmagazine.com/dae_09_25 Support us on Patreon at https://www.patreon.com/clarkesworld/membership

Koji A. Dae discusses HOLD MY HEART, an uncompromisingly dark horror novella about desire—and the things we'll do to get what we really want.

Do you enjoy hosting a handful of people for game night? How about a few hundred? That's what these three tried for the first time about a month ago in Burbank, CA: Dustin Staats, content creator and owner of online and brick-and-mortar retailer BGE Tabletop; George Caceres, owner of board game cafe Game N' Grounds; and Dae, owner of board game store Fire & Dice, came together to put on the very first LFG Con this past June. We asked Dustin to join us on the podcast to talk about how their convention dreams started and what it took to make them a reality. Plus, Dustin shares how he made the transition from board game content creator to board game retailer. Listen in! Timeline: 3:53 - Going Analog's game pick: Dark Heists. 8:58 - Dustin's game pick: Scythe. 11:59 - Going Analog's topic: Running a game convention (for the first time). 25:47 - Dustin's topic: From content creator to retailer (how I opened my brick & mortar store)

A GAME OF KILLER HIDE AND SEEK!! Squid Game Season 3 Full Reaction Watch Along:   / thereelrejects   Visit https://huel.com/rejects to get 15% off your order The FINAL Season is here & it's time for our Squid Game Season 3 Reaction, Recap, Breakdown, Commentary, Spoiler Review & ending explained!! Greg Alba & John Humphrey return to the dystopian playground in Netflix's final and explosive Squid Game season, with Episodes 1 & 2 premiering June 27, 2025. After the violent uprising of Season 2, Season 3 opens with Seong Gi‑hun (Lee Jung‑jae, Train to Busan), dubbed Player 456, wheeled back in via a coffin in a chilling first scene. Haunted by survivor's guilt, he's emotionally shattered and driven by the crushing need for justice and revenge. The two episodes thrust us into a deranged version of “Hide-and-Seek,” with red and blue teams battling for life, intensified by cold psychological stakes. Gi‑hun's fractured alliance with Dae-ho (Kang Ha‑neul, Forgotten, Midnight Runners) and the return of detective Jun-ho (Wi Ha‑joon, Money Heist, Something in the Rain) deepens the narrative. Jun-ho's quest continues as he searches for his brother, the enigmatic Front Man (Lee Byung‑hun, G.I. Joe, Masters of the Universe)—infiltrating both the games and the inner workings of the Institute. Standout moments include: Gi‑hun's silent breakdown and explosive confrontation with Dae‑ho, The grotesquely thrilling Hide-and-Seek game, Jun‑ho's investigative breakthrough and near-encounter with betrayals inside the Island's power structure, & more! Main cast stars include Lee Jung‑jae as Gi‑hun, Lee Byung‑hun as the Front Man, Wi Ha‑joon as Jun‑ho, Kang Ha‑neul's cunning Dae‑ho, Park Gyu‑young as No‑eul, Im Si‑wan, Park Sung‑hoon, Jo Yu‑ri, and more, bringing fresh tension and emotional arcs to the final season. This gritty, emotionally haunted premiere sets the tone for a savage descent into the games' conclusion. Join Greg & John as they unpack every twist, alliance, and horrifying moment in Squid Game's last season! Intense Suspense by Audionautix is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... Support The Channel By Getting Some REEL REJECTS Apparel! https://www.rejectnationshop.com/ Follow Us On Socials:  Instagram: https://www.instagram.com/reelrejects/  Tik-Tok: https://www.tiktok.com/@reelrejects?lang=en Twitter: https://x.com/reelrejects Facebook: https://www.facebook.com/TheReelRejects/ Music Used In Ad:  Hat the Jazz by Twin Musicom is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Happy Alley by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... POWERED BY @GFUEL Visit https://gfuel.ly/3wD5Ygo and use code REJECTNATION for 20% off select tubs!! Head Editor: https://www.instagram.com/praperhq/?hl=en Co-Editor: Greg Alba Co-Editor: John Humphrey Music In Video: Airport Lounge - Disco Ultralounge by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Ask Us A QUESTION On CAMEO: https://www.cameo.com/thereelrejects Follow TheReelRejects On FACEBOOK, TWITTER, & INSTAGRAM:  FB:  https://www.facebook.com/TheReelRejects/ INSTAGRAM:  https://www.instagram.com/reelrejects/ TWITTER:  https://twitter.com/thereelrejects Follow GREG ON INSTAGRAM & TWITTER: INSTAGRAM:  https://www.instagram.com/thegregalba/ TWITTER:  https://twitter.com/thegregalba Learn more about your ad choices. Visit megaphone.fm/adchoices

THE DEADLY JUMP ROPE GAME!!! Use REELREJECTS to get 55% off your first month at Scentbird https://sbird.co/43HYPuV This month I received... Charlie by Matthew Zink https://sbird.co/4dT1yGP The Element by NEH https://sbird.co/3FLSpTy Dylan Blue Pour Homme by Versace https://sbird.co/4mPpSNI Burberry for Men EDT by Burberry https://sbird.co/4mOQb6x Squid Game Season 3 Full Reaction Watch Along:   / thereelrejects   With the FINAL SEASON upon us, Greg & John give their Squid Game Season 3 Recap, Commentary, Analysis & Spoiler Review!! Greg Alba & John Humphrey return to the edge of survival in Netflix's explosive final Squid Game season with Episodes 3 (“It's Not Your Fault”) and 4 (“222”). As the competition narrows, Seong Gi‑hun (Lee Jung‑jae, Star Wars: The Acolyte) and his fractured alliance must face one of the season's most infamous challenges yet: a fiendishly deadly jump-rope game once again played at great heights in front of an audience of our favorite over-the-top VIP's... In Episode 4, titled “222,” Gi‑hun finally confronts the masked Front Man (Lee Byung‑hun, G.I. Joe, Masters of the Universe), leading to a dramatic unmasking that shifts the power balance in brutal fashion. The stakes are raised as he's offered a knife and forced to betray his remaining allies—blurring the lines between hero and survivor. Meanwhile, returning players like detective Jun‑ho (Wi Ha‑joon, Money Heist, Something in the Rain) deepen the rescue plot as he climbs closer to the island, while Dae‑ho (Kang Ha‑neul, Forgotten) proves himself in the games again. New blood like Im Si‑wan, Park Gyu‑young, and Jo Yu‑ri bring fresh energy and emotional complexity. Standout moments include the terror of synchronized ropes, the jaw-dropping Front Man reveal, and the moral crumble as players choose survival over solidarity. Critics say Season 3 returns to the series' brutal essence, focusing on psychologically harrowing childlike games with dehumanizing stakes at their core... Tune in with Greg & John as they unpack every tension-fueled game, shocking twist, and heartbreaking choice in these key episodes of the final season! Intense Suspense by Audionautix is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... Support The Channel By Getting Some REEL REJECTS Apparel! https://www.rejectnationshop.com/ Follow Us On Socials:  Instagram: https://www.instagram.com/reelrejects/  Tik-Tok: https://www.tiktok.com/@reelrejects?lang=en Twitter: https://x.com/reelrejects Facebook: https://www.facebook.com/TheReelRejects/ Music Used In Ad:  Hat the Jazz by Twin Musicom is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Happy Alley by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... POWERED BY @GFUEL Visit https://gfuel.ly/3wD5Ygo and use code REJECTNATION for 20% off select tubs!! Head Editor: https://www.instagram.com/praperhq/?hl=en Co-Editor: Greg Alba Co-Editor: John Humphrey Music In Video: Airport Lounge - Disco Ultralounge by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Ask Us A QUESTION On CAMEO: https://www.cameo.com/thereelrejects Follow TheReelRejects On FACEBOOK, TWITTER, & INSTAGRAM:  FB:  https://www.facebook.com/TheReelRejects/ INSTAGRAM:  https://www.instagram.com/reelrejects/ TWITTER:  https://twitter.com/thereelrejects Follow GREG ON INSTAGRAM & TWITTER: INSTAGRAM:  https://www.instagram.com/thegregalba/ TWITTER:  https://twitter.com/thegregalba Learn more about your ad choices. Visit megaphone.fm/adchoices

CAN GI HUN PROTECT 222?? Squid Game Season 3 Full Reaction Watch Along:   / thereelrejects   With the FINAL EPISODES of the series upon us, Squid Game Season 3 Episode 5 Reaction, Recap, Breakdown, Commentary, Spoiler Review & ending explained!! Greg Alba & John Humphrey return for another high-stakes showdown in Squid Game Season 3 as Episode 5 debuts on Netflix. The final rounds begin with unexpected twists and testing reveals that raise the tension even higher. This episode centers on the final eight contestants awakening and preparing for the last games. A masked guard (Guard 11, played by Park Gyu-young – Netflix's Squid Game, Lovecraft Country) shows fierce resistance, defying orders and protecting Player 246—creating an early emotional jockeying for power. Meanwhile, Jun-ho (Wi Ha-joon – Money Heist, Something in the Rain) pilots Player 246's rescue boat through dense fog, receiving a chilling warning from his brother, the Front Man (Lee Byung-hun – G.I. Joe, Masters of the Universe), instructing him to abandon the mission—or else... Back on the island, the final players ascend a towering stairwell toward the last game, Control Room tensions, high-stakes defiance, and the true cost of resistance. Guard 11's bold stand in the corridors and Harrowing whispers of final eliminations set a grim tone that weighs on every character's fate. With only half the contestants left, alliances are tested and gut instincts kick in. Notable scenes include the powerful showdown between guarded empathy and brutal rule, and a cliffhanger hinting at the brutal final format of Episode 6. Squid Game veterans Seong Gi-hun (Lee Jung-jae – Train to Busan), Front Man (Lee Byung-hun), and Jun-ho return, joined by returning allies Dae-ho (Kang Ha-neul) and Cho Hyun-ju (Park Sung-hoon), plus emerging players like Park Gyu-young as Guard 11—all amplifying the emotional stakes. Intense Suspense by Audionautix is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... Support The Channel By Getting Some REEL REJECTS Apparel! https://www.rejectnationshop.com/ Follow Us On Socials:  Instagram: https://www.instagram.com/reelrejects/  Tik-Tok: https://www.tiktok.com/@reelrejects?lang=en Twitter: https://x.com/reelrejects Facebook: https://www.facebook.com/TheReelRejects/ Music Used In Ad:  Hat the Jazz by Twin Musicom is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Happy Alley by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/... POWERED BY @GFUEL Visit https://gfuel.ly/3wD5Ygo and use code REJECTNATION for 20% off select tubs!! Head Editor: https://www.instagram.com/praperhq/?hl=en Co-Editor: Greg Alba Co-Editor: John Humphrey Music In Video: Airport Lounge - Disco Ultralounge by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/ Ask Us A QUESTION On CAMEO: https://www.cameo.com/thereelrejects Follow TheReelRejects On FACEBOOK, TWITTER, & INSTAGRAM:  FB:  https://www.facebook.com/TheReelRejects/ INSTAGRAM:  https://www.instagram.com/reelrejects/ TWITTER:  https://twitter.com/thereelrejects Follow GREG ON INSTAGRAM & TWITTER: INSTAGRAM:  https://www.instagram.com/thegregalba/ TWITTER:  https://twitter.com/thegregalba Learn more about your ad choices. Visit megaphone.fm/adchoices

We're kicking off Pride with one of the messiest Netflix shows we love to watch, XO, Kitty season 2. Kitty's back at KISS after winter break, having just officially broken up with Dae, realized she's into Yuri, and been confessed to by Minho, and with Chaos Queen Kitty at the reigns you can be sure that's not even half the drama. Send us your thoughts at the links below, and don't forget to rate & review. OUR SOCIALSFind us everywhere: https://linktr.ee/ninetiesbabiesnostalgiaInstagram: https://www.instagram.com/ninetiesbabiesnostalgia/ YouTube: https://www.youtube.com/channel/UCgmyQV7STEmjISJKCZr362w TikTok: https://www.tiktok.com/@90sbabiesnostalgia Twitter: https://twitter.com/Nineties_Babies Theme Song by Patrick Dunnevant, (https://www.youtube.com/c/AcappellaVGM)Artwork by Dawn Wheeler (https://www.instagram.com/wool_and_stone) Send us a text

In Episode 43, I speak with A Beautiful Dae, a local singer from Los Angeles.  We talk about her journey through dealing with various health complications including multiple sclerosis. She tells us that it has helped her to sing because it became a tool of healing for her. We also discuss her influences and inspirations in music. Dae opens up about her various job experiences and the skills she has acquired through them. Overcoming all this advesity, she opens up about how challenging the education system was. Her path to singing became very clear to her. Thus, we discuss that transition of becoming a full time musical artist. We discuss how she found opportunities in the most unexpected places. In addition, we talk about what her creative process looks like. Everything from the role of the internet on music careers to the role of music on young lives, we discuss so much within the music industry. This was a great conversation getting to know the one and only A Beautiful Dae. Make sure to check out some of her songs. My top 3 are It Pours (When It Rains), Damsel in Distress, G.T.F.Y. (I Gotta Thing for Ya). Follow her @abeautifuldae09 on instagram!! 

I sat down with attorneys Dae Lee and Adam Farkas to dig into the legal mess surrounding GLP-1 compounding, PBM overreach, and the brutal reality facing independent pharmacies. Dae's a pharmacist-attorney, Adam's a legal powerhouse, and together they're helping pharmacies fight back in a system stacked against them.

North Korean defectors face a huge information gap upon arrival in South Korea and in this week's episode we're joined by Dae-hyeon Park, the founder and CEO of Woorion, an NGO that supports North Korean defectors in their resettlement and integration into South Korean society. He discusses the events and personal motivations that led him to establish Woorion, the various services the organization provides, including financial assistance, educational programs and mentorship and some of the success stories from Woorion's programs that showcase the resilience and achievements of North Korean defectors as they adapt to their new lives in the South.  Dae-hyeon Park is the founder and CEO of Woorion, an NGO dedicated to supporting North Korean defectors in their resettlement and integration into South Korean society. Established in 2015, Woorion offers a comprehensive online platform providing essential services to bridge the information gap and empower defectors towards self-reliance. About the podcast: The North Korea News Podcast is a weekly podcast hosted by Jacco Zwetsloot exclusively for NK News, covering all things DPRK — from news to extended interviews with leading experts and analysts in the field, along with insight from our very own journalists. NK News subscribers can listen to this and other exclusive episodes from their preferred podcast player by accessing the private podcast feed. For more detailed instructions, please see the step-by-step guide at nknews.org/private-feed.

The third and final part of this triumvirate. Did I use that incorrectly? Almost undoubtedly. It was so much fun recording these, and I'm pumped to put them out. Gabe is always down to goof. He called into one of the first episodes of Does Anyone Else if you somehow need more of this kind of rubbish. Webcast of Mass Discussions is also back, and will be up soon. W tried stand up and runs some of the stuff from his set, and we catch up. New episode of DAE is being recorded later this week with the hilarious @Zachsoraven, and I may try and convince him to stay on as a co-host, and add Most Valuable Player Haters to the podcast consortium. Okay bye.

This episode features "Hook and Line" written by Koji A. Dae. Published in the March 2025 issue of Clarkesworld Magazine and read by Kate Baker. The text version of this story can be found at: https://clarkesworldmagazine.com/dae_03_25 Support us on Patreon at https://www.patreon.com/join/clarkesworld?

Jenn chats with Koji A. Dae about CASUAL, a stark and cutting glance at a near future that looks uncannily like our present, exploring themes of bodily autonomy and the struggle for mental health in a world increasingly divided.

Fluent Fiction - Korean: Seollal Revelations: Finding True Happiness on Jeju-do's Shores Find the full episode transcript, vocabulary words, and more:fluentfiction.com/ko/episode/2025-02-18-23-34-01-ko Story Transcript:Ko: 제주도의 달빛 해변은 겨울에도 아름다웠습니다.En: The moonlit beaches of Jeju-do were beautiful even in winter.Ko: 고등학생 지현은 학교 생물학 수업 때문에 친구 민서, 대준과 함께 여기에 왔습니다.En: High school student Ji-hyun came here with her friends Min-seo and Dae-jun because of a biology class project.Ko: 바닷속 해양 생물을 연구하는 것이 이번 여행의 주제였습니다.En: Their trip was intended for studying marine life in the ocean.Ko: 하지만, 지현의 마음은 그리 편하지 않았습니다.En: However, Ji-hyun did not feel completely at ease.Ko: 설날이 다가오고 있었습니다.En: Seollal was approaching.Ko: 가족과 전통을 중요시하는 지현의 부모님은 이번 설날에 지현이 더욱 잘 준비된 모습을 보여주길 기대하고 있었습니다.En: Ji-hyun's parents, who valued family and tradition highly, expected her to present herself as more prepared this Seollal.Ko: 하지만, 지현은 자신이 정말 무엇을 원하는지 알지 못했습니다.En: However, Ji-hyun did not really know what she wanted for herself.Ko: 그녀는 학업 스트레스에서 벗어나 진정으로 행복을 찾고 싶었습니다.En: She yearned to escape academic stress and find true happiness.Ko: 밤이 되자, 친구들보다 먼저 해변으로 나간 지현은 달빛이 비치는 바다를 바라보며 깊은 생각에 잠겼습니다.En: As night fell, Ji-hyun went to the beach before her friends and gazed at the moonlit sea, lost in deep thought.Ko: 바람은 차가웠지만, 마음은 점점 따스해졌습니다.En: Although the wind was chilly, her heart gradually warmed.Ko: 친구들 없이 혼자 있는 이 시간은 그녀에게 소중한 시간이었습니다.En: This time alone, without her friends, was precious to her.Ko: 그러던 중, 해변 저쪽에서 무언가 준비하는 소리가 들렸습니다.En: Meanwhile, she heard sounds of preparation from the other side of the beach.Ko: 가까이 다가가 보니, 마을 사람들이 설날 준비를 하고 있었습니다.En: Upon approaching, she noticed the villagers preparing for Seollal.Ko: 전통 한복을 입고 다양한 음식을 준비하고 있었습니다.En: They were dressed in traditional hanbok and preparing various foods.Ko: 그 모습은 지현의 마음을 사로잡았습니다.En: The sight captivated Ji-hyun.Ko: 단순한 행위처럼 보였지만, 그 안에서 큰 행복과 만족을 느낄 수 있었습니다.En: It seemed like a simple act, but she could sense great happiness and contentment within it.Ko: 지현은 설날을 단순히 가족과의 약속을 지키는 날로만 생각했었지만, 그곳에서는 다른 의미를 찾고 있었습니다.En: Ji-hyun had once thought of Seollal merely as a day to fulfill family obligations, but there, she found a different meaning.Ko: 사람들은 진심으로 서로를 위하며 기쁨을 나누고 있었습니다.En: The people were genuinely caring for each other and sharing joy.Ko: 이것이 진정한 행복이었습니다.En: This was true happiness.Ko: 지현은 그 날 밤 새로운 결심을 했습니다.En: That night, Ji-hyun made a new resolution.Ko: 부모님의 기대를 반대하거나 무시하는 것이 아니라, 자신만의 길을 찾는 것이 중요하다는 것을 깨달았습니다.En: She realized it was important not to oppose or ignore her parents' expectations but to find her own path.Ko: 설날이 되면 부모님께 솔직하게 말할 것입니다.En: When Seollal came, she would honestly tell her parents.Ko: 자신이 어떤 길을 선택할지 결정했다고 말할 것이고, 그것이 학문적인 성공이 아니어도 괜찮다고 말할 것입니다.En: She would say she had decided on the path she would take, and that it was okay if it wasn't academic success.Ko: 다음 날 지현은 오랜만에 진심으로 웃었습니다.En: The next day, Ji-hyun laughed sincerely for the first time in a while.Ko: 이제 그녀는 자신만의 길을 시작할 준비가 되었습니다.En: Now she was ready to start her own journey.Ko: 설날의 달빛 해변에서 얻은 깨달음이 그녀를 이끌어줄 것입니다.En: The insights she gained from the moonlit beaches during Seollal would guide her.Ko: 지현은 마음속에 가지런히 담긴 그 장면들을 떠올리며, 자신만의 새로운 이야기를 써 내려가기 시작했습니다.En: Reminiscing the neatly stored scenes in her heart, Ji-hyun began to write her own new story. Vocabulary Words:moonlit: 달빛이 비치는beaches: 해변project: 프로젝트intended: 의도된marine: 해양chilly: 차가운precious: 소중한villagers: 마을 사람들hanbok: 한복obligations: 의무resolution: 결심escape: 벗어나다academic: 학문적인contentment: 만족honestly: 솔직하게sincerely: 진심으로journey: 여정insights: 깨달음gained: 얻은remissing: 떠올리며neatly: 가지런히obligations: 약속gazed: 바라보며escape: 벗어나다yearned: 갈망했다approaching: 다가오고 있는warm: 따스한captivated: 사로잡혔다cherished: 소중히 여겨졌다fulfillment: 이행

Metabolic syndrome is common and affects about 1 in 3 Americans. But how much do you know about this cluster of risk factors? On this show, Karolyn talks with integrative health expert Dr. Daemon Jones (aka Dr. Dae) about what metabolic syndrome is and more importantly, how to reduce risk and treat it naturally. Dr. Dae is an accomplished author, speaker, and the creator of Healthy Daes Naturopathic Medical Center in Washington, DC.Five To Thrive Live is broadcast live Tuesdays at 7PM ET and Music on W4CS Radio – The Cancer Support Network (www.w4cy.com) part of Talk 4 Radio (www.talk4radio.com) on the Talk 4 Media Network (www.talk4media.com).Five To Thrive Live Podcast is also available on Talk 4 Media (www.talk4media.com), Talk 4 Podcasting (www.talk4podcasting.com), iHeartRadio, Amazon Music, Pandora, Spotify, Audible, and over 100 other podcast outlets.

XO Kitty is back with season 2 on Netflix and Jillian breaks down all the romance, drama and surprises. From Kitty's love life to the twists between Yuri, Min Ho, and Dae, we're diving into the biggest moments of the season....including the epic return of PETER KAVINSKY. Jenny Han forever!! Follow Previously On Teen TV on Instagram: https://www.instagram.com/previouslyon_teentv/ Follow Previously On Teen TV on Threads: https://www.threads.net/@previouslyon_teentv Follow Previously On Teen TV on TikTok: https://www.tiktok.com/@previouslyon_teentv Subscribe to our YouTube: https://www.youtube.com/channel/UCe2lgvvZGKMrQ8v24FmDdWQ?sub_confirmation=1

One last Gold sponsor slot is available for the AI Engineer Summit in NYC. Our last round of invites is going out soon - apply here - If you are building AI agents or AI eng teams, this will be the single highest-signal conference of the year for you!While the world melts down over DeepSeek, few are talking about the OTHER notable group of former hedge fund traders who pivoted into AI and built a remarkably profitable consumer AI business with a tiny team with incredibly cracked engineering team — Chai Research. In short order they have:* Started a Chat AI company well before Noam Shazeer started Character AI, and outlasted his departure.* Crossed 1m DAU in 2.5 years - William updates us on the pod that they've hit 1.4m DAU now, another +40% from a few months ago. Revenue crossed >$22m. * Launched the Chaiverse model crowdsourcing platform - taking 3-4 week A/B testing cycles down to 3-4 hours, and deploying >100 models a week.While they're not paying million dollar salaries, you can tell they're doing pretty well for an 11 person startup:The Chai Recipe: Building infra for rapid evalsRemember how the central thesis of LMarena (formerly LMsys) is that the only comprehensive way to evaluate LLMs is to let users try them out and pick winners?At the core of Chai is a mobile app that looks like Character AI, but is actually the largest LLM A/B testing arena in the world, specialized on retaining chat users for Chai's usecases (therapy, assistant, roleplay, etc). It's basically what LMArena would be if taken very, very seriously at one company (with $1m in prizes to boot):Chai publishes occasional research on how they think about this, including talks at their Palo Alto office:William expands upon this in today's podcast (34 mins in):Fundamentally, the way I would describe it is when you're building anything in life, you need to be able to evaluate it. And through evaluation, you can iterate, we can look at benchmarks, and we can say the issues with benchmarks and why they may not generalize as well as one would hope in the challenges of working with them. But something that works incredibly well is getting feedback from humans. And so we built this thing where anyone can submit a model to our developer backend, and it gets put in front of 5000 users, and the users can rate it. And we can then have a really accurate ranking of like which model, or users finding more engaging or more entertaining. And it gets, you know, it's at this point now, where every day we're able to, I mean, we evaluate between 20 and 50 models, LLMs, every single day, right. So even though we've got only got a team of, say, five AI researchers, they're able to iterate a huge quantity of LLMs, right. So our team ships, let's just say minimum 100 LLMs a week is what we're able to iterate through. Now, before that moment in time, we might iterate through three a week, we might, you know, there was a time when even doing like five a month was a challenge, right? By being able to change the feedback loops to the point where it's not, let's launch these three models, let's do an A-B test, let's assign, let's do different cohorts, let's wait 30 days to see what the day 30 retention is, which is the kind of the, if you're doing an app, that's like A-B testing 101 would be, do a 30-day retention test, assign different treatments to different cohorts and come back in 30 days. So that's insanely slow. That's just, it's too slow. And so we were able to get that 30-day feedback loop all the way down to something like three hours.In Crowdsourcing the leap to Ten Trillion-Parameter AGI, William describes Chai's routing as a recommender system, which makes a lot more sense to us than previous pitches for model routing startups:William is notably counter-consensus in a lot of his AI product principles:* No streaming: Chats appear all at once to allow rejection sampling* No voice: Chai actually beat Character AI to introducing voice - but removed it after finding that it was far from a killer feature.* Blending: “Something that we love to do at Chai is blending, which is, you know, it's the simplest way to think about it is you're going to end up, and you're going to pretty quickly see you've got one model that's really smart, one model that's really funny. How do you get the user an experience that is both smart and funny? Well, just 50% of the requests, you can serve them the smart model, 50% of the requests, you serve them the funny model.” (that's it!)But chief above all is the recommender system.We also referenced Exa CEO Will Bryk's concept of SuperKnowlege:Full Video versionOn YouTube. please like and subscribe!Timestamps* 00:00:04 Introductions and background of William Beauchamp* 00:01:19 Origin story of Chai AI* 00:04:40 Transition from finance to AI* 00:11:36 Initial product development and idea maze for Chai* 00:16:29 User psychology and engagement with AI companions* 00:20:00 Origin of the Chai name* 00:22:01 Comparison with Character AI and funding challenges* 00:25:59 Chai's growth and user numbers* 00:34:53 Key inflection points in Chai's growth* 00:42:10 Multi-modality in AI companions and focus on user-generated content* 00:46:49 Chaiverse developer platform and model evaluation* 00:51:58 Views on AGI and the nature of AI intelligence* 00:57:14 Evaluation methods and human feedback in AI development* 01:02:01 Content creation and user experience in Chai* 01:04:49 Chai Grant program and company culture* 01:07:20 Inference optimization and compute costs* 01:09:37 Rejection sampling and reward models in AI generation* 01:11:48 Closing thoughts and recruitmentTranscriptAlessio [00:00:04]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel, and today we're in the Chai AI office with my usual co-host, Swyx.swyx [00:00:14]: Hey, thanks for having us. It's rare that we get to get out of the office, so thanks for inviting us to your home. We're in the office of Chai with William Beauchamp. Yeah, that's right. You're founder of Chai AI, but previously, I think you're concurrently also running your fund?William [00:00:29]: Yep, so I was simultaneously running an algorithmic trading company, but I fortunately was able to kind of exit from that, I think just in Q3 last year. Yeah, congrats. Yeah, thanks.swyx [00:00:43]: So Chai has always been on my radar because, well, first of all, you do a lot of advertising, I guess, in the Bay Area, so it's working. Yep. And second of all, the reason I reached out to a mutual friend, Joyce, was because I'm just generally interested in the... ...consumer AI space, chat platforms in general. I think there's a lot of inference insights that we can get from that, as well as human psychology insights, kind of a weird blend of the two. And we also share a bit of a history as former finance people crossing over. I guess we can just kind of start it off with the origin story of Chai.William [00:01:19]: Why decide working on a consumer AI platform rather than B2B SaaS? So just quickly touching on the background in finance. Sure. Originally, I'm from... I'm from the UK, born in London. And I was fortunate enough to go study economics at Cambridge. And I graduated in 2012. And at that time, everyone in the UK and everyone on my course, HFT, quant trading was really the big thing. It was like the big wave that was happening. So there was a lot of opportunity in that space. And throughout college, I'd sort of played poker. So I'd, you know, I dabbled as a professional poker player. And I was able to accumulate this sort of, you know, say $100,000 through playing poker. And at the time, as my friends would go work at companies like ChangeStreet or Citadel, I kind of did the maths. And I just thought, well, maybe if I traded my own capital, I'd probably come out ahead. I'd make more money than just going to work at ChangeStreet.swyx [00:02:20]: With 100k base as capital?William [00:02:22]: Yes, yes. That's not a lot. Well, it depends what strategies you're doing. And, you know, there is an advantage. There's an advantage to being small, right? Because there are, if you have a 10... Strategies that don't work in size. Exactly, exactly. So if you have a fund of $10 million, if you find a little anomaly in the market that you might be able to make 100k a year from, that's a 1% return on your 10 million fund. If your fund is 100k, that's 100% return, right? So being small, in some sense, was an advantage. So started off, and the, taught myself Python, and machine learning was like the big thing as well. Machine learning had really, it was the first, you know, big time machine learning was being used for image recognition, neural networks come out, you get dropout. And, you know, so this, this was the big thing that's going on at the time. So I probably spent my first three years out of Cambridge, just building neural networks, building random forests to try and predict asset prices, right, and then trade that using my own money. And that went well. And, you know, if you if you start something, and it goes well, you You try and hire more people. And the first people that came to mind was the talented people I went to college with. And so I hired some friends. And that went well and hired some more. And eventually, I kind of ran out of friends to hire. And so that was when I formed the company. And from that point on, we had our ups and we had our downs. And that was a whole long story and journey in itself. But after doing that for about eight or nine years, on my 30th birthday, which was four years ago now, I kind of took a step back to just evaluate my life, right? This is what one does when one turns 30. You know, I just heard it. I hear you. And, you know, I looked at my 20s and I loved it. It was a really special time. I was really lucky and fortunate to have worked with this amazing team, been successful, had a lot of hard times. And through the hard times, learned wisdom and then a lot of success and, you know, was able to enjoy it. And so the company was making about five million pounds a year. And it was just me and a team of, say, 15, like, Oxford and Cambridge educated mathematicians and physicists. It was like the real dream that you'd have if you wanted to start a quant trading firm. It was like...swyx [00:04:40]: Your own, all your own money?William [00:04:41]: Yeah, exactly. It was all the team's own money. We had no customers complaining to us about issues. There's no investors, you know, saying, you know, they don't like the risk that we're taking. We could. We could really run the thing exactly as we wanted it. It's like Susquehanna or like Rintec. Yeah, exactly. Yeah. And they're the companies that we would kind of look towards as we were building that thing out. But on my 30th birthday, I look and I say, OK, great. This thing is making as much money as kind of anyone would really need. And I thought, well, what's going to happen if we keep going in this direction? And it was clear that we would never have a kind of a big, big impact on the world. We can enrich ourselves. We can make really good money. Everyone on the team would be paid very, very well. Presumably, I can make enough money to buy a yacht or something. But this stuff wasn't that important to me. And so I felt a sort of obligation that if you have this much talent and if you have a talented team, especially as a founder, you want to be putting all that talent towards a good use. I looked at the time of like getting into crypto and I had a really strong view on crypto, which was that as far as a gambling device. This is like the most fun form of gambling invented in like ever super fun, I thought as a way to evade monetary regulations and banking restrictions. I think it's also absolutely amazing. So it has two like killer use cases, not so much banking the unbanked, but everything else, but everything else to do with like the blockchain and, and you know, web, was it web 3.0 or web, you know, that I, that didn't, it didn't really make much sense. And so instead of going into crypto, which I thought, even if I was successful, I'd end up in a lot of trouble. I thought maybe it'd be better to build something that governments wouldn't have a problem with. I knew that LLMs were like a thing. I think opening. I had said they hadn't released GPT-3 yet, but they'd said GPT-3 is so powerful. We can't release it to the world or something. Was it GPT-2? And then I started interacting with, I think Google had open source, some language models. They weren't necessarily LLMs, but they, but they were. But yeah, exactly. So I was able to play around with, but nowadays so many people have interacted with the chat GPT, they get it, but it's like the first time you, you can just talk to a computer and it talks back. It's kind of a special moment and you know, everyone who's done that goes like, wow, this is how it should be. Right. It should be like, rather than having to type on Google and search, you should just be able to ask Google a question. When I saw that I read the literature, I kind of came across the scaling laws and I think even four years ago. All the pieces of the puzzle were there, right? Google had done this amazing research and published, you know, a lot of it. Open AI was still open. And so they'd published a lot of their research. And so you really could be fully informed on, on the state of AI and where it was going. And so at that point I was confident enough, it was worth a shot. I think LLMs are going to be the next big thing. And so that's the thing I want to be building in, in that space. And I thought what's the most impactful product I can possibly build. And I thought it should be a platform. So I myself love platforms. I think they're fantastic because they open up an ecosystem where anyone can contribute to it. Right. So if you think of a platform like a YouTube, instead of it being like a Hollywood situation where you have to, if you want to make a TV show, you have to convince Disney to give you the money to produce it instead, anyone in the world can post any content they want to YouTube. And if people want to view it, the algorithm is going to promote it. Nowadays. You can look at creators like Mr. Beast or Joe Rogan. They would have never have had that opportunity unless it was for this platform. Other ones like Twitter's a great one, right? But I would consider Wikipedia to be a platform where instead of the Britannica encyclopedia, which is this, it's like a monolithic, you get all the, the researchers together, you get all the data together and you combine it in this, in this one monolithic source. Instead. You have this distributed thing. You can say anyone can host their content on Wikipedia. Anyone can contribute to it. And anyone can maybe their contribution is they delete stuff. When I was hearing like the kind of the Sam Altman and kind of the, the Muskian perspective of AI, it was a very kind of monolithic thing. It was all about AI is basically a single thing, which is intelligence. Yeah. Yeah. The more intelligent, the more compute, the more intelligent, and the more and better AI researchers, the more intelligent, right? They would speak about it as a kind of erased, like who can get the most data, the most compute and the most researchers. And that would end up with the most intelligent AI. But I didn't believe in any of that. I thought that's like the total, like I thought that perspective is the perspective of someone who's never actually done machine learning. Because with machine learning, first of all, you see that the performance of the models follows an S curve. So it's not like it just goes off to infinity, right? And the, the S curve, it kind of plateaus around human level performance. And you can look at all the, all the machine learning that was going on in the 2010s, everything kind of plateaued around the human level performance. And we can think about the self-driving car promises, you know, how Elon Musk kept saying the self-driving car is going to happen next year, it's going to happen next, next year. Or you can look at the image recognition, the speech recognition. You can look at. All of these things, there was almost nothing that went superhuman, except for something like AlphaGo. And we can speak about why AlphaGo was able to go like super superhuman. So I thought the most likely thing was going to be this, I thought it's not going to be a monolithic thing. That's like an encyclopedia Britannica. I thought it must be a distributed thing. And I actually liked to look at the world of finance for what I think a mature machine learning ecosystem would look like. So, yeah. So finance is a machine learning ecosystem because all of these quant trading firms are running machine learning algorithms, but they're running it on a centralized platform like a marketplace. And it's not the case that there's one giant quant trading company of all the data and all the quant researchers and all the algorithms and compute, but instead they all specialize. So one will specialize on high frequency training. Another will specialize on mid frequency. Another one will specialize on equity. Another one will specialize. And I thought that's the way the world works. That's how it is. And so there must exist a platform where a small team can produce an AI for a unique purpose. And they can iterate and build the best thing for that, right? And so that was the vision for Chai. So we wanted to build a platform for LLMs.Alessio [00:11:36]: That's kind of the maybe inside versus contrarian view that led you to start the company. Yeah. And then what was maybe the initial idea maze? Because if somebody told you that was the Hugging Face founding story, people might believe it. It's kind of like a similar ethos behind it. How did you land on the product feature today? And maybe what were some of the ideas that you discarded that initially you thought about?William [00:11:58]: So the first thing we built, it was fundamentally an API. So nowadays people would describe it as like agents, right? But anyone could write a Python script. They could submit it to an API. They could send it to the Chai backend and we would then host this code and execute it. So that's like the developer side of the platform. On their Python script, the interface was essentially text in and text out. An example would be the very first bot that I created. I think it was a Reddit news bot. And so it would first, it would pull the popular news. Then it would prompt whatever, like I just use some external API for like Burr or GPT-2 or whatever. Like it was a very, very small thing. And then the user could talk to it. So you could say to the bot, hi bot, what's the news today? And it would say, this is the top stories. And you could chat with it. Now four years later, that's like perplexity or something. That's like the, right? But back then the models were first of all, like really, really dumb. You know, they had an IQ of like a four year old. And users, there really wasn't any demand or any PMF for interacting with the news. So then I was like, okay. Um. So let's make another one. And I made a bot, which was like, you could talk to it about a recipe. So you could say, I'm making eggs. Like I've got eggs in my fridge. What should I cook? And it'll say, you should make an omelet. Right. There was no PMF for that. No one used it. And so I just kept creating bots. And so every single night after work, I'd be like, okay, I like, we have AI, we have this platform. I can create any text in textile sort of agent and put it on the platform. And so we just create stuff night after night. And then all the coders I knew, I would say, yeah, this is what we're going to do. And then I would say to them, look, there's this platform. You can create any like chat AI. You should put it on. And you know, everyone's like, well, chatbots are super lame. We want absolutely nothing to do with your chatbot app. No one who knew Python wanted to build on it. I'm like trying to build all these bots and no consumers want to talk to any of them. And then my sister who at the time was like just finishing college or something, I said to her, I was like, if you want to learn Python, you should just submit a bot for my platform. And she, she built a therapy for me. And I was like, okay, cool. I'm going to build a therapist bot. And then the next day I checked the performance of the app and I'm like, oh my God, we've got 20 active users. And they spent, they spent like an average of 20 minutes on the app. I was like, oh my God, what, what bot were they speaking to for an average of 20 minutes? And I looked and it was the therapist bot. And I went, oh, this is where the PMF is. There was no demand for, for recipe help. There was no demand for news. There was no demand for dad jokes or pub quiz or fun facts or what they wanted was they wanted the therapist bot. the time I kind of reflected on that and I thought, well, if I want to consume news, the most fun thing, most fun way to consume news is like Twitter. It's not like the value of there being a back and forth, wasn't that high. Right. And I thought if I need help with a recipe, I actually just go like the New York times has a good recipe section, right? It's not actually that hard. And so I just thought the thing that AI is 10 X better at is a sort of a conversation right. That's not intrinsically informative, but it's more about an opportunity. You can say whatever you want. You're not going to get judged. If it's 3am, you don't have to wait for your friend to text back. It's like, it's immediate. They're going to reply immediately. You can say whatever you want. It's judgment-free and it's much more like a playground. It's much more like a fun experience. And you could see that if the AI gave a person a compliment, they would love it. It's much easier to get the AI to give you a compliment than a human. From that day on, I said, okay, I get it. Humans want to speak to like humans or human like entities and they want to have fun. And that was when I started to look less at platforms like Google. And I started to look more at platforms like Instagram. And I was trying to think about why do people use Instagram? And I could see that I think Chai was, was filling the same desire or the same drive. If you go on Instagram, typically you want to look at the faces of other humans, or you want to hear about other people's lives. So if it's like the rock is making himself pancakes on a cheese plate. You kind of feel a little bit like you're the rock's friend, or you're like having pancakes with him or something, right? But if you do it too much, you feel like you're sad and like a lonely person, but with AI, you can talk to it and tell it stories and tell you stories, and you can play with it for as long as you want. And you don't feel like you're like a sad, lonely person. You feel like you actually have a friend.Alessio [00:16:29]: And what, why is that? Do you have any insight on that from using it?William [00:16:33]: I think it's just the human psychology. I think it's just the idea that, with old school social media. You're just consuming passively, right? So you'll just swipe. If I'm watching TikTok, just like swipe and swipe and swipe. And even though I'm getting the dopamine of like watching an engaging video, there's this other thing that's building my head, which is like, I'm feeling lazier and lazier and lazier. And after a certain period of time, I'm like, man, I just wasted 40 minutes. I achieved nothing. But with AI, because you're interacting, you feel like you're, it's not like work, but you feel like you're participating and contributing to the thing. You don't feel like you're just. Consuming. So you don't have a sense of remorse basically. And you know, I think on the whole people, the way people talk about, try and interact with the AI, they speak about it in an incredibly positive sense. Like we get people who say they have eating disorders saying that the AI helps them with their eating disorders. People who say they're depressed, it helps them through like the rough patches. So I think there's something intrinsically healthy about interacting that TikTok and Instagram and YouTube doesn't quite tick. From that point on, it was about building more and more kind of like human centric AI for people to interact with. And I was like, okay, let's make a Kanye West bot, right? And then no one wanted to talk to the Kanye West bot. And I was like, ah, who's like a cool persona for teenagers to want to interact with. And I was like, I was trying to find the influencers and stuff like that, but no one cared. Like they didn't want to interact with the, yeah. And instead it was really just the special moment was when we said the realization that developers and software engineers aren't interested in building this sort of AI, but the consumers are right. And rather than me trying to guess every day, like what's the right bot to submit to the platform, why don't we just create the tools for the users to build it themselves? And so nowadays this is like the most obvious thing in the world, but when Chai first did it, it was not an obvious thing at all. Right. Right. So we took the API for let's just say it was, I think it was GPTJ, which was this 6 billion parameter open source transformer style LLM. We took GPTJ. We let users create the prompt. We let users select the image and we let users choose the name. And then that was the bot. And through that, they could shape the experience, right? So if they said this bot's going to be really mean, and it's going to be called like bully in the playground, right? That was like a whole category that I never would have guessed. Right. People love to fight. They love to have a disagreement, right? And then they would create, there'd be all these romantic archetypes that I didn't know existed. And so as the users could create the content that they wanted, that was when Chai was able to, to get this huge variety of content and rather than appealing to, you know, 1% of the population that I'd figured out what they wanted, you could appeal to a much, much broader thing. And so from that moment on, it was very, very crystal clear. It's like Chai, just as Instagram is this social media platform that lets people create images and upload images, videos and upload that, Chai was really about how can we let the users create this experience in AI and then share it and interact and search. So it's really, you know, I say it's like a platform for social AI.Alessio [00:20:00]: Where did the Chai name come from? Because you started the same path. I was like, is it character AI shortened? You started at the same time, so I was curious. The UK origin was like the second, the Chai.William [00:20:15]: We started way before character AI. And there's an interesting story that Chai's numbers were very, very strong, right? So I think in even 20, I think late 2022, was it late 2022 or maybe early 2023? Chai was like the number one AI app in the app store. So we would have something like 100,000 daily active users. And then one day we kind of saw there was this website. And we were like, oh, this website looks just like Chai. And it was the character AI website. And I think that nowadays it's, I think it's much more common knowledge that when they left Google with the funding, I think they knew what was the most trending, the number one app. And I think they sort of built that. Oh, you found the people.swyx [00:21:03]: You found the PMF for them.William [00:21:04]: We found the PMF for them. Exactly. Yeah. So I worked a year very, very hard. And then they, and then that was when I learned a lesson, which is that if you're VC backed and if, you know, so Chai, we'd kind of ran, we'd got to this point, I was the only person who'd invested. I'd invested maybe 2 million pounds in the business. And you know, from that, we were able to build this thing, get to say a hundred thousand daily active users. And then when character AI came along, the first version, we sort of laughed. We were like, oh man, this thing sucks. Like they don't know what they're building. They're building the wrong thing anyway, but then I saw, oh, they've raised a hundred million dollars. Oh, they've raised another hundred million dollars. And then our users started saying, oh guys, your AI sucks. Cause we were serving a 6 billion parameter model, right? How big was the model that character AI could afford to serve, right? So we would be spending, let's say we would spend a dollar per per user, right? Over the, the, you know, the entire lifetime.swyx [00:22:01]: A dollar per session, per chat, per month? No, no, no, no.William [00:22:04]: Let's say we'd get over the course of the year, we'd have a million users and we'd spend a million dollars on the AI throughout the year. Right. Like aggregated. Exactly. Exactly. Right. They could spend a hundred times that. So people would say, why is your AI much dumber than character AIs? And then I was like, oh, okay, I get it. This is like the Silicon Valley style, um, hyper scale business. And so, yeah, we moved to Silicon Valley and, uh, got some funding and iterated and built the flywheels. And, um, yeah, I, I'm very proud that we were able to compete with that. Right. So, and I think the reason we were able to do it was just customer obsession. And it's similar, I guess, to how deep seek have been able to produce such a compelling model when compared to someone like an open AI, right? So deep seek, you know, their latest, um, V2, yeah, they claim to have spent 5 million training it.swyx [00:22:57]: It may be a bit more, but, um, like, why are you making it? Why are you making such a big deal out of this? Yeah. There's an agenda there. Yeah. You brought up deep seek. So we have to ask you had a call with them.William [00:23:07]: We did. We did. We did. Um, let me think what to say about that. I think for one, they have an amazing story, right? So their background is again in finance.swyx [00:23:16]: They're the Chinese version of you. Exactly.William [00:23:18]: Well, there's a lot of similarities. Yes. Yes. I have a great affinity for companies which are like, um, founder led, customer obsessed and just try and build something great. And I think what deep seek have achieved. There's quite special is they've got this amazing inference engine. They've been able to reduce the size of the KV cash significantly. And then by being able to do that, they're able to significantly reduce their inference costs. And I think with kind of with AI, people get really focused on like the kind of the foundation model or like the model itself. And they sort of don't pay much attention to the inference. To give you an example with Chai, let's say a typical user session is 90 minutes, which is like, you know, is very, very long for comparison. Let's say the average session length on TikTok is 70 minutes. So people are spending a lot of time. And in that time they're able to send say 150 messages. That's a lot of completions, right? It's quite different from an open AI scenario where people might come in, they'll have a particular question in mind. And they'll ask like one question. And a few follow up questions, right? So because they're consuming, say 30 times as many requests for a chat, or a conversational experience, you've got to figure out how to how to get the right balance between the cost of that and the quality. And so, you know, I think with AI, it's always been the case that if you want a better experience, you can throw compute at the problem, right? So if you want a better model, you can just make it bigger. If you want it to remember better, give it a longer context. And now, what open AI is doing to great fanfare is with projection sampling, you can generate many candidates, right? And then with some sort of reward model or some sort of scoring system, you can serve the most promising of these many candidates. And so that's kind of scaling up on the inference time compute side of things. And so for us, it doesn't make sense to think of AI is just the absolute performance. So. But what we're seeing, it's like the MML you score or the, you know, any of these benchmarks that people like to look at, if you just get that score, it doesn't really tell tell you anything. Because it's really like progress is made by improving the performance per dollar. And so I think that's an area where deep seek have been able to form very, very well, surprisingly so. And so I'm very interested in what Lama four is going to look like. And if they're able to sort of match what deep seek have been able to achieve with this performance per dollar gain.Alessio [00:25:59]: Before we go into the inference, some of the deeper stuff, can you give people an overview of like some of the numbers? So I think last I checked, you have like 1.4 million daily active now. It's like over 22 million of revenue. So it's quite a business.William [00:26:12]: Yeah, I think we grew by a factor of, you know, users grew by a factor of three last year. Revenue over doubled. You know, it's very exciting. We're competing with some really big, really well funded companies. Character AI got this, I think it was almost a $3 billion valuation. And they have 5 million DAU is a number that I last heard. Torquay, which is a Chinese built app owned by a company called Minimax. They're incredibly well funded. And these companies didn't grow by a factor of three last year. Right. And so when you've got this company and this team that's able to keep building something that gets users excited, and they want to tell their friend about it, and then they want to come and they want to stick on the platform. I think that's very special. And so last year was a great year for the team. And yeah, I think the numbers reflect the hard work that we put in. And then fundamentally, the quality of the app, the quality of the content, the quality of the content, the quality of the content, the quality of the content, the quality of the content. AI is the quality of the experience that you have. You actually published your DAU growth chart, which is unusual. And I see some inflections. Like, it's not just a straight line. There's some things that actually inflect. Yes. What were the big ones? Cool. That's a great, great, great question. Let me think of a good answer. I'm basically looking to annotate this chart, which doesn't have annotations on it. Cool. The first thing I would say is this is, I think the most important thing to know about success is that success is born out of failures. Right? Through failures that we learn. You know, if you think something's a good idea, and you do and it works, great, but you didn't actually learn anything, because everything went exactly as you imagined. But if you have an idea, you think it's going to be good, you try it, and it fails. There's a gap between the reality and expectation. And that's an opportunity to learn. The flat periods, that's us learning. And then the up periods is that's us reaping the rewards of that. So I think the big, of the growth shot of just 2024, I think the first thing that really kind of put a dent in our growth was our backend. So we just reached this scale. So we'd, from day one, we'd built on top of Google's GCP, which is Google's cloud platform. And they were fantastic. We used them when we had one daily active user, and they worked pretty good all the way up till we had about 500,000. It was never the cheapest, but from an engineering perspective, man, that thing scaled insanely good. Like, not Vertex? Not Vertex. Like GKE, that kind of stuff? We use Firebase. So we use Firebase. I'm pretty sure we're the biggest user ever on Firebase. That's expensive. Yeah, we had calls with engineers, and they're like, we wouldn't recommend using this product beyond this point, and you're 3x over that. So we pushed Google to their absolute limits. You know, it was fantastic for us, because we could focus on the AI. We could focus on just adding as much value as possible. But then what happened was, after 500,000, just the thing, the way we were using it, and it would just, it wouldn't scale any further. And so we had a really, really painful, at least three-month period, as we kind of migrated between different services, figuring out, like, what requests do we want to keep on Firebase, and what ones do we want to move on to something else? And then, you know, making mistakes. And learning things the hard way. And then after about three months, we got that right. So that, we would then be able to scale to the 1.5 million DAE without any further issues from the GCP. But what happens is, if you have an outage, new users who go on your app experience a dysfunctional app, and then they're going to exit. And so your next day, the key metrics that the app stores track are going to be something like retention rates. And so your next day, the key metrics that the app stores track are going to be something like retention rates. Money spent, and the star, like, the rating that they give you. In the app store. In the app store, yeah. Tyranny. So if you're ranked top 50 in entertainment, you're going to acquire a certain rate of users organically. If you go in and have a bad experience, it's going to tank where you're positioned in the algorithm. And then it can take a long time to kind of earn your way back up, at least if you wanted to do it organically. If you throw money at it, you can jump to the top. And I could talk about that. But broadly speaking, if we look at 2024, the first kink in the graph was outages due to hitting 500k DAU. The backend didn't want to scale past that. So then we just had to do the engineering and build through it. Okay, so we built through that, and then we get a little bit of growth. And so, okay, that's feeling a little bit good. I think the next thing, I think it's, I'm not going to lie, I have a feeling that when Character AI got... I was thinking. I think so. I think... So the Character AI team fundamentally got acquired by Google. And I don't know what they changed in their business. I don't know if they dialed down that ad spend. Products don't change, right? Products just what it is. I don't think so. Yeah, I think the product is what it is. It's like maintenance mode. Yes. I think the issue that people, you know, some people may think this is an obvious fact, but running a business can be very competitive, right? Because other businesses can see what you're doing, and they can imitate you. And then there's this... There's this question of, if you've got one company that's spending $100,000 a day on advertising, and you've got another company that's spending zero, if you consider market share, and if you're considering new users which are entering the market, the guy that's spending $100,000 a day is going to be getting 90% of those new users. And so I have a suspicion that when the founders of Character AI left, they dialed down their spending on user acquisition. And I think that kind of gave oxygen to like the other apps. And so Chai was able to then start growing again in a really healthy fashion. I think that's kind of like the second thing. I think a third thing is we've really built a great data flywheel. Like the AI team sort of perfected their flywheel, I would say, in end of Q2. And I could speak about that at length. But fundamentally, the way I would describe it is when you're building anything in life, you need to be able to evaluate it. And through evaluation, you can iterate, we can look at benchmarks, and we can say the issues with benchmarks and why they may not generalize as well as one would hope in the challenges of working with them. But something that works incredibly well is getting feedback from humans. And so we built this thing where anyone can submit a model to our developer backend, and it gets put in front of 5000 users, and the users can rate it. And we can then have a really accurate ranking of like which model, or users finding more engaging or more entertaining. And it gets, you know, it's at this point now, where every day we're able to, I mean, we evaluate between 20 and 50 models, LLMs, every single day, right. So even though we've got only got a team of, say, five AI researchers, they're able to iterate a huge quantity of LLMs, right. So our team ships, let's just say minimum 100 LLMs a week is what we're able to iterate through. Now, before that moment in time, we might iterate through three a week, we might, you know, there was a time when even doing like five a month was a challenge, right? By being able to change the feedback loops to the point where it's not, let's launch these three models, let's do an A-B test, let's assign, let's do different cohorts, let's wait 30 days to see what the day 30 retention is, which is the kind of the, if you're doing an app, that's like A-B testing 101 would be, do a 30-day retention test, assign different treatments to different cohorts and come back in 30 days. So that's insanely slow. That's just, it's too slow. And so we were able to get that 30-day feedback loop all the way down to something like three hours. And when we did that, we could really, really, really perfect techniques like DPO, fine tuning, prompt engineering, blending, rejection sampling, training a reward model, right, really successfully, like boom, boom, boom, boom, boom. And so I think in Q3 and Q4, we got, the amount of AI improvements we got was like astounding. It was getting to the point, I thought like how much more, how much more edge is there to be had here? But the team just could keep going and going and going. That was like number three for the inflection point.swyx [00:34:53]: There's a fourth?William [00:34:54]: The important thing about the third one is if you go on our Reddit or you talk to users of AI, there's like a clear date. It's like somewhere in October or something. The users, they flipped. Before October, the users... The users would say character AI is better than you, for the most part. Then from October onwards, they would say, wow, you guys are better than character AI. And that was like a really clear positive signal that we'd sort of done it. And I think people, you can't cheat consumers. You can't trick them. You can't b******t them. They know, right? If you're going to spend 90 minutes on a platform, and with apps, there's the barriers to switching is pretty low. Like you can try character AI, you can't cheat consumers. You can't cheat them. You can't cheat them. You can't cheat AI for a day. If you get bored, you can try Chai. If you get bored of Chai, you can go back to character. So the users, the loyalty is not strong, right? What keeps them on the app is the experience. If you deliver a better experience, they're going to stay and they can tell. So that was the fourth one was we were fortunate enough to get this hire. He was hired one really talented engineer. And then they said, oh, at my last company, we had a head of growth. He was really, really good. And he was the head of growth for ByteDance for two years. Would you like to speak to him? And I was like, yes. Yes, I think I would. And so I spoke to him. And he just blew me away with what he knew about user acquisition. You know, it was like a 3D chessswyx [00:36:21]: sort of thing. You know, as much as, as I know about AI. Like ByteDance as in TikTok US. Yes.William [00:36:26]: Not ByteDance as other stuff. Yep. He was interviewing us as we were interviewing him. Right. And so pick up options. Yeah, exactly. And so he was kind of looking at our metrics. And he was like, I saw him get really excited when he said, guys, you've got a million daily active users and you've done no advertising. I said, correct. And he was like, that's unheard of. He's like, I've never heard of anyone doing that. And then he started looking at our metrics. And he was like, if you've got all of this organically, if you start spending money, this is going to be very exciting. I was like, let's give it a go. So then he came in, we've just started ramping up the user acquisition. So that looks like spending, you know, let's say we're spending, we started spending $20,000 a day, it looked very promising than 20,000. Right now we're spending $40,000 a day on user acquisition. That's still only half of what like character AI or talkie may be spending. But from that, it's sort of, we were growing at a rate of maybe say, 2x a year. And that got us growing at a rate of 3x a year. So I'm growing, I'm evolving more and more to like a Silicon Valley style hyper growth, like, you know, you build something decent, and then you canswyx [00:37:33]: slap on a huge... You did the important thing, you did the product first.William [00:37:36]: Of course, but then you can slap on like, like the rocket or the jet engine or something, which is just this cash in, you pour in as much cash, you buy a lot of ads, and your growth is faster.swyx [00:37:48]: Not to, you know, I'm just kind of curious what's working right now versus what surprisinglyWilliam [00:37:52]: doesn't work. Oh, there's a long, long list of surprising stuff that doesn't work. Yeah. The surprising thing, like the most surprising thing, what doesn't work is almost everything doesn't work. That's what's surprising. And I'll give you an example. So like a year and a half ago, I was working at a company, we were super excited by audio. I was like, audio is going to be the next killer feature, we have to get in the app. And I want to be the first. So everything Chai does, I want us to be the first. We may not be the company that's strongest at execution, but we can always be theswyx [00:38:22]: most innovative. Interesting. Right? So we can... You're pretty strong at execution.William [00:38:26]: We're much stronger, we're much stronger. A lot of the reason we're here is because we were first. If we launched today, it'd be so hard to get the traction. Because it's like to get the flywheel, to get the users, to build a product people are excited about. If you're first, people are naturally excited about it. But if you're fifth or 10th, man, you've got to beswyx [00:38:46]: insanely good at execution. So you were first with voice? We were first. We were first. I only knowWilliam [00:38:51]: when character launched voice. They launched it, I think they launched it at least nine months after us. Okay. Okay. But the team worked so hard for it. At the time we did it, latency is a huge problem. Cost is a huge problem. Getting the right quality of the voice is a huge problem. Right? Then there's this user interface and getting the right user experience. Because you don't just want it to start blurting out. Right? You want to kind of activate it. But then you don't have to keep pressing a button every single time. There's a lot that goes into getting a really smooth audio experience. So we went ahead, we invested the three months, we built it all. And then when we did the A-B test, there was like, no change in any of the numbers. And I was like, this can't be right, there must be a bug. And we spent like a week just checking everything, checking again, checking again. And it was like, the users just did not care. And it was something like only 10 or 15% of users even click the button to like, they wanted to engage the audio. And they would only use it for 10 or 15% of the time. So if you do the math, if it's just like something that one in seven people use it for one seventh of their time. You've changed like 2% of the experience. So even if that that 2% of the time is like insanely good, it doesn't translate much when you look at the retention, when you look at the engagement, and when you look at the monetization rates. So audio did not have a big impact. I'm pretty big on audio. But yeah, I like it too. But it's, you know, so a lot of the stuff which I do, I'm a big, you can have a theory. And you resist. Yeah. Exactly, exactly. So I think if you want to make audio work, it has to be a unique, compelling, exciting experience that they can't have anywhere else.swyx [00:40:37]: It could be your models, which just weren't good enough.William [00:40:39]: No, no, no, they were great. Oh, yeah, they were very good. it was like, it was kind of like just the, you know, if you listen to like an audible or Kindle, or something like, you just hear this voice. And it's like, you don't go like, wow, this is this is special, right? It's like a convenience thing. But the idea is that if you can, if Chai is the only platform, like, let's say you have a Mr. Beast, and YouTube is the only platform you can use to make audio work, then you can watch a Mr. Beast video. And it's the most engaging, fun video that you want to watch, you'll go to a YouTube. And so it's like for audio, you can't just put the audio on there. And people go, oh, yeah, it's like 2% better. Or like, 5% of users think it's 20% better, right? It has to be something that the majority of people, for the majority of the experience, go like, wow, this is a big deal. That's the features you need to be shipping. If it's not going to appeal to the majority of people, for the majority of the experience, and it's not a big deal, it's not going to move you. Cool. So you killed it. I don't see it anymore. Yep. So I love this. The longer, it's kind of cheesy, I guess, but the longer I've been working at Chai, and I think the team agrees with this, all the platitudes, at least I thought they were platitudes, that you would get from like the Steve Jobs, which is like, build something insanely great, right? Or be maniacally focused, or, you know, the most important thing is saying no to, not to work on. All of these sort of lessons, they just are like painfully true. They're painfully true. So now I'm just like, everything I say, I'm either quoting Steve Jobs or Zuckerberg. I'm like, guys, move fast and break free.swyx [00:42:10]: You've jumped the Apollo to cool it now.William [00:42:12]: Yeah, it's just so, everything they said is so, so true. The turtle neck. Yeah, yeah, yeah. Everything is so true.swyx [00:42:18]: This last question on my side, and I want to pass this to Alessio, is on just, just multi-modality in general. This actually comes from Justine Moore from A16Z, who's a friend of ours. And a lot of people are trying to do voice image video for AI companions. Yes. You just said voice didn't work. Yep. What would make you revisit?William [00:42:36]: So Steve Jobs, he was very, listen, he was very, very clear on this. There's a habit of engineers who, once they've got some cool technology, they want to find a way to package up the cool technology and sell it to consumers, right? That does not work. So you're free to try and build a startup where you've got your cool tech and you want to find someone to sell it to. That's not what we do at Chai. At Chai, we start with the consumer. What does the consumer want? What is their problem? And how do we solve it? So right now, the number one problems for the users, it's not the audio. That's not the number one problem. It's not the image generation either. That's not their problem either. The number one problem for users in AI is this. All the AI is being generated by middle-aged men in Silicon Valley, right? That's all the content. You're interacting with this AI. You're speaking to it for 90 minutes on average. It's being trained by middle-aged men. The guys out there, they're out there. They're talking to you. They're talking to you. They're like, oh, what should the AI say in this situation, right? What's funny, right? What's cool? What's boring? What's entertaining? That's not the way it should be. The way it should be is that the users should be creating the AI, right? And so the way I speak about it is this. Chai, we have this AI engine in which sits atop a thin layer of UGC. So the thin layer of UGC is absolutely essential, right? It's just prompts. But it's just prompts. It's just an image. It's just a name. It's like we've done 1% of what we could do. So we need to keep thickening up that layer of UGC. It must be the case that the users can train the AI. And if reinforcement learning is powerful and important, they have to be able to do that. And so it's got to be the case that there exists, you know, I say to the team, just as Mr. Beast is able to spend 100 million a year or whatever it is on his production company, and he's got a team building the content, the Mr. Beast company is able to spend 100 million a year on his production company. And he's got a team building the content, which then he shares on the YouTube platform. Until there's a team that's earning 100 million a year or spending 100 million on the content that they're producing for the Chai platform, we're not finished, right? So that's the problem. That's what we're excited to build. And getting too caught up in the tech, I think is a fool's errand. It does not work.Alessio [00:44:52]: As an aside, I saw the Beast Games thing on Amazon Prime. It's not doing well. And I'mswyx [00:44:56]: curious. It's kind of like, I mean, the audience reading is high. The run-to-meet-all sucks, but the audience reading is high.Alessio [00:45:02]: But it's not like in the top 10. I saw it dropped off of like the... Oh, okay. Yeah, that one I don't know. I'm curious, like, you know, it's kind of like similar content, but different platform. And then going back to like, some of what you were saying is like, you know, people come to ChaiWilliam [00:45:13]: expecting some type of content. Yeah, I think it's something that's interesting to discuss is like, is moats. And what is the moat? And so, you know, if you look at a platform like YouTube, the moat, I think is in first is really is in the ecosystem. And the ecosystem, is comprised of you have the content creators, you have the users, the consumers, and then you have the algorithms. And so this, this creates a sort of a flywheel where the algorithms are able to be trained on the users, and the users data, the recommend systems can then feed information to the content creators. So Mr. Beast, he knows which thumbnail does the best. He knows the first 10 seconds of the video has to be this particular way. And so his content is super optimized for the YouTube platform. So that's why it doesn't do well on Amazon. If he wants to do well on Amazon, how many videos has he created on the YouTube platform? By thousands, 10s of 1000s, I guess, he needs to get those iterations in on the Amazon. So at Chai, I think it's all about how can we get the most compelling, rich user generated content, stick that on top of the AI engine, the recommender systems, in such that we get this beautiful data flywheel, more users, better recommendations, more creative, more content, more users.Alessio [00:46:34]: You mentioned the algorithm, you have this idea of the Chaiverse on Chai, and you have your own kind of like LMSYS-like ELO system. Yeah, what are things that your models optimize for, like your users optimize for, and maybe talk about how you build it, how people submit models?William [00:46:49]: So Chaiverse is what I would describe as a developer platform. More often when we're speaking about Chai, we're thinking about the Chai app. And the Chai app is really this product for consumers. And so consumers can come on the Chai app, they can come on the Chai app, they can come on the Chai app, they can interact with our AI, and they can interact with other UGC. And it's really just these kind of bots. And it's a thin layer of UGC. Okay. Our mission is not to just have a very thin layer of UGC. Our mission is to have as much UGC as possible. So we must have, I don't want people at Chai training the AI. I want people, not middle aged men, building AI. I want everyone building the AI, as many people building the AI as possible. Okay, so what we built was we built Chaiverse. And Chaiverse is kind of, it's kind of like a prototype, is the way to think about it. And it started with this, this observation that, well, how many models get submitted into Hugging Face a day? It's hundreds, it's hundreds, right? So there's hundreds of LLMs submitted each day. Now consider that, what does it take to build an LLM? It takes a lot of work, actually. It's like someone devoted several hours of compute, several hours of their time, prepared a data set, launched it, ran it, evaluated it, submitted it, right? So there's a lot of, there's a lot of, there's a lot of work that's going into that. So what we did was we said, well, why can't we host their models for them and serve them to users? And then what would that look like? The first issue is, well, how do you know if a model is good or not? Like, we don't want to serve users the crappy models, right? So what we would do is we would, I love the LMSYS style. I think it's really cool. It's really simple. It's a very intuitive thing, which is you simply present the users with two completions. You can say, look, this is from model one. This is from model two. This is from model three. This is from model A. This is from model B, which is better. And so if someone submits a model to Chaiverse, what we do is we spin up a GPU. We download the model. We're going to now host that model on this GPU. And we're going to start routing traffic to it. And we're going to send, we think it takes about 5,000 completions to get an accurate signal. That's roughly what LMSYS does. And from that, we're able to get an accurate ranking. And we're able to get an accurate ranking. And we're able to get an accurate ranking of which models are people finding entertaining and which models are not entertaining. If you look at the bottom 80%, they'll suck. You can just disregard them. They totally suck. Then when you get the top 20%, you know you've got a decent model, but you can break it down into more nuance. There might be one that's really descriptive. There might be one that's got a lot of personality to it. There might be one that's really illogical. Then the question is, well, what do you do with these top models? From that, you can do more sophisticated things. You can try and do like a routing thing where you say for a given user request, we're going to try and predict which of these end models that users enjoy the most. That turns out to be pretty expensive and not a huge source of like edge or improvement. Something that we love to do at Chai is blending, which is, you know, it's the simplest way to think about it is you're going to end up, and you're going to pretty quickly see you've got one model that's really smart, one model that's really funny. How do you get the user an experience that is both smart and funny? Well, just 50% of the requests, you can serve them the smart model, 50% of the requests, you serve them the funny model. Just a random 50%? Just a random, yeah. And then... That's blending? That's blending. You can do more sophisticated things on top of that, as in all things in life, but the 80-20 solution, if you just do that, you get a pretty powerful effect out of the gate. Random number generator. I think it's like the robustness of randomness. Random is a very powerful optimization technique, and it's a very robust thing. So you can explore a lot of the space very efficiently. There's one thing that's really, really important to share, and this is the most exciting thing for me, is after you do the ranking, you get an ELO score, and you can track a user's first join date, the first date they submit a model to Chaiverse, they almost always get a terrible ELO, right? So let's say the first submission they get an ELO of 1,100 or 1,000 or something, and you can see that they iterate and they iterate and iterate, and it will be like, no improvement, no improvement, no improvement, and then boom. Do you give them any data, or do you have to come up with this themselves? We do, we do, we do, we do. We try and strike a balance between giving them data that's very useful, you've got to be compliant with GDPR, which is like, you have to work very hard to preserve the privacy of users of your app. So we try to give them as much signal as possible, to be helpful. The minimum is we're just going to give you a score, right? That's the minimum. But that alone is people can optimize a score pretty well, because they're able to come up with theories, submit it, does it work? No. A new theory, does it work? No. And then boom, as soon as they figure something out, they keep it, and then they iterate, and then boom,Alessio [00:51:46]: they figure something out, and they keep it. Last year, you had this post on your blog, cross-sourcing the lead to the 10 trillion parameter, AGI, and you call it a mixture of experts, recommenders. Yep. Any insights?William [00:51:58]: Updated thoughts, 12 months later? I think the odds, the timeline for AGI has certainly been pushed out, right? Now, this is in, I'm a controversial person, I don't know, like, I just think... You don't believe in scaling laws, you think AGI is further away. I think it's an S-curve. I think everything's an S-curve. And I think that the models have proven to just be far worse at reasoning than people sort of thought. And I think whenever I hear people talk about LLMs as reasoning engines, I sort of cringe a bit. I don't think that's what they are. I think of them more as like a simulator. I think of them as like a, right? So they get trained to predict the next most likely token. It's like a physics simulation engine. So you get these like games where you can like construct a bridge, and you drop a car down, and then it predicts what should happen. And that's really what LLMs are doing. It's not so much that they're reasoning, it's more that they're just doing the most likely thing. So fundamentally, the ability for people to add in intelligence, I think is very limited. What most people would consider intelligence, I think the AI is not a crowdsourcing problem, right? Now with Wikipedia, Wikipedia crowdsources knowledge. It doesn't crowdsource intelligence. So it's a subtle distinction. AI is fantastic at knowledge. I think it's weak at intelligence. And a lot, it's easy to conflate the two because if you ask it a question and it gives you, you know, if you said, who was the seventh president of the United States, and it gives you the correct answer, I'd say, well, I don't know the answer to that. And you can conflate that with intelligence. But really, that's a question of knowledge. And knowledge is really this thing about saying, how can I store all of this information? And then how can I retrieve something that's relevant? Okay, they're fantastic at that. They're fantastic at storing knowledge and retrieving the relevant knowledge. They're superior to humans in that regard. And so I think we need to come up for a new word. How does one describe AI should contain more knowledge than any individual human? It should be more accessible than any individual human. That's a very powerful thing. That's superswyx [00:54:07]: powerful. But what words do we use to describe that? We had a previous guest on Exa AI that does search. And he tried to coin super knowledge as the opposite of super intelligence.William [00:54:20]: Exactly. I think super knowledge is a more accurate word for it.swyx [00:54:24]: You can store more things than any human can.William [00:54:26]: And you can retrieve it better than any human can as well. And I think it's those two things combined that's special. I think that thing will exist. That thing can be built. And I think you can start with something that's entertaining and fun. And I think, I often think it's like, look, it's going to be a 20 year journey. And we're in like, year four, or it's like the web. And this is like 1998 or something. You know, you've got a long, long way to go before the Amazon.coms are like these huge, multi trillion dollar businesses that every single person uses every day. And so AI today is very simplistic. And it's fundamentally the way we're using it, the flywheels, and this ability for how can everyone contribute to it to really magnify the value that it brings. Right now, like, I think it's a bit sad. It's like, right now you have big labs, I'm going to pick on open AI. And they kind of go to like these human labelers. And they say, we're going to pay you to just label this like subset of questions that we want to get a really high quality data set, then we're going to get like our own computers that are really powerful. And that's kind of like the thing. For me, it's so much like Encyclopedia Britannica. It's like insane. All the people that were interested in blockchain, it's like, well, this is this is what needs to be decentralized, you need to decentralize that thing. Because if you distribute it, people can generate way more data in a distributed fashion, way more, right? You need the incentive. Yeah, of course. Yeah. But I mean, the, the, that's kind of the exciting thing about Wikipedia was it's this understanding, like the incentives, you don't need money to incentivize people. You don't need dog coins. No. Sometimes, sometimes people get the satisfaction fro

Have you ever wondered what really makes a team thrive? This week on The Activity Call, Adam Katz is breaking down the "Light of DAE"·duplicating the right actions, surrounding yourself with the right people, and lifting up your team to succeed together. It·s all about creating a culture where everyone wins. If you're ready to grow your business and help others do the same, you don·t want to miss this one!

Amerika yeni yıla kanlı saldırılarla girdi. Önce New Orleans kentinde bir saldırgan, aracıyla kalabalığın arasına daldı; 14 kişi hayatını kaybetti, 35 kişi yaralandı. Bu saldırıdan saatler sonra da Las Vegas'taki Trump otelinin önünde bir araç patladı. New Orleans saldırganının DAEŞ sempatizanı olduğu anlaşıldı. Kanlı eylemler ne anlama geliyor, Trump'a yönelik bir mesaj mı? DAEŞ yeniden güç kazanabilir mi? Bu durum Suriye denklemini nasıl etkiler? Kayıttayız'da bu sorulara yanıt arandı.

Namibië het aansienlike vordering gemaak met die uitskakeling van geslagsongelykhede en het in 2024 die 8ste posisie wêreldwyd beklee en was eerste in Afrika suid van die Sahara. Sleutelareas in die vordering sluit in 100 persent geslagsgelykheid in onderwys, 78 persent in ekonomiese deelname, 45 persent in politieke bemagtiging en 98 persent in gesondheid. Die land het ook onlangs die 16 Dae van Aktivisme teen Geslagsbaseerde Geweld en Namibiese Vrouedag herdenk. Kosmos 94.1 Nuus het met die aktivis Zack Itodo gesels wat bly is oor die statistieke maar wil weet wat na die 16 dae gebeur.

On this week's menu: with us is Dae-won Lim, founder and creative director of Sundae School. Born in South Korea and now based out of New York City, Dae is ~*~highly*~* aware of how controversial his business really is. But what's really so controversial about living as your authentic self? Watching the full video episodes on YouTube. Follow Us:Instagram: https://www.instagram.com/fulldiscoursepodTikTok: https://www.tiktok.com/@fulldiscoursepod Follow Dae and Sundae School:  Dae's Instagram: https://www.instagram.com/dae.slim/Sundae School's Website: sundae.schoolSundae School's Instagram: https://www.instagram.com/sundae.school/Follow Josh:Instagram: https://www.instagram.com/thejoshelkin TikTok: https://www.tiktok.com/@thejoshelkin YouTube: https://www.youtube.com/thejoshelkinFollow Hana:Hana's Instagram: https://www.instagram.com/hananaberry/

In this empowering episode of That Sounds Terrific, host Nick Koziol sits down with Jon-Lee "Jonni" Campbell, the inspiring founder of Differently Abled Entertainment (DAE), a 501(c)(3) organization reshaping inclusivity in the entertainment industry. After a spinal cord injury at age 16, Jonni transformed her personal journey into a mission to uplift and represent differently abled artists. She discusses how DAE creates opportunities in an industry that often overlooks individuals with disabilities, and shares her powerful vision of rewriting the narrative for underrepresented voices. Tune in to hear how Jonni's journey, passion, and determination are paving the way for a more diverse and inclusive entertainment industry. About Jonni Campbell, Founder/Executive Director, Differently Abled Entertainment Email: jonni@ourdae.org LinkedIn: www.linkedin.com/in/jon-lee-campbell-a4a089211 Connect and Follow Jonni Cambell: Website: ourdae.org/ LinkedIn: www.linkedin.com/company/ourdae Instagram: www.instagram.com/differentlyabledentertainment/ Facebook: www.facebook.com/differentlyabledentertainment More About That Sounds Terrific - Host Nick Koziol For more information on our Podcast, That Sounds Terrific visit our website at www.thatsoundsterrific.com  and be sure to follow us on Facebook, Twitter, and Instagram. If you or someone you know are doing some terrific things that should be featured by our show then be sure to reach out by emailing us at thatsoundsterrfic@gmail.com. Special Thank You to Our Sponsors & Key Supporters: Chris Jones of Chris Jones Media for the Introduction and Outro recordings for That Sounds Terrific.  Intro and Outro animation created in collaboration with Ben Albert of Balbert Marketing, LLC. Boost your business popularity, traffic, and conversions online!   The video and audio portions of this podcast are powered by the Vidwheel Creator Network. Join Neil Carrol and be a part of the network that allows you to learn and develop video skills. Make powerful video content while looking terrific on camera so that you can sustain and grow your businesses. Reach a wider audience of clients and partners who need to hear your message and develop the flexibility in your businesses to thrive in a turbulent world.  --- Support this podcast: https://podcasters.spotify.com/pod/show/thatsoundsterrific/support

Zen is making me feel anything but zen. OMG. I went from cheering Dae to absolutely freaking out and worrying for him. We're discussing episodes 95-97 of Eaternal Nocturnal by Instantmiso! JOIN INSTANTMISO'S PATREON: patreon.com/instantmiso JOIN MY PATREON FOR EARLY ACCESS: patreon.com/girlwonder EATERNAL NOCTURNAL IN 33 MINUTES (Recap Podcast Episode): https://soundcloud.com/user-35260934/eaternal-nocturnal-in-33-minutes-the-ultimate-series-recap-deep-dive?si=9271d4aec2b846248232a49a41af6835&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing LATEST INTERVIEW WITH INSTANTMISO: https://soundcloud.com/user-35260934/qa-with-instantmiso-creator-of-eaternal-nocturnal-sirens-lament?utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing MY FIRST INTERVIEW WITH INSTANTMISO: https://soundcloud.com/user-35260934/all-about-sirens-lament-with?si=e8138a59da224dc6b4a4013fa5fe7fb7&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing SHOP WEBTOON - SIREN'S LAMENT: https://shopwebtoon.com/collections/sirens-lament MUSIC CREDIT: Isabella LeVan https://www.instagram.com/isabellalevan https://open.spotify.com/artist/3mHmktHG4sbkGsCORnaNT3?si=Nx2DvyOGQyatxudvD3ik9Q Connect with Girl Wonder:  My Patreon: https://www.patreon.com/girlwonder My YouTube Channel: https://www.youtube.com/channel/UCTk-JbxxAnf5TKyeCchNRHA twitter.com/girlwonderpod instagram.com/girlwonderpodcast Email: girlwondersquad (at) gmail (dot) com Buy me a coffee: http://ko-fi.com/girlwonderpodcast

In this episode of the Nirvana Sisters podcast, we return with Product Junkies, after a summer hiatus. We dive into a variety of products that we've been loving lately, starting with some fun fashion finds. We share a new favorite clothing set from Ocean Drive, perfect for lounging or poolside wear and the Rag & Bone Miramar Wide Leg Pants, which combine the comfort of sweats with the look of jeans.We introduce the HiSmile Glow Stick Tooth Gloss, a unique product that brightens teeth on the go. As well as a new favorite styling wand from Dae, which helps tame frizz and flyaways effortlessly.As we wrap up, we reveal a favorite new find that will blow you away, the Peter Thomas Roth Instant Firm X Temporary Face Tightener, which visibly tightens and smooths the skin, giving a youthful appearance. Finally, we discuss our favorite lip glosses for the season, featuring products from Patrick Ta, Lawless, and Anastasia Beverly Hills.Brands/Mentions + Shop this episode hereFor more on this episode, read the full show notes hereFollow us @nirvanasisters on InstagramFind us at www.nirvanasisters.comShop our Amazon StoreShopMy ShopSay hi at hello@nirvanasisters.comPlease subscribe, rate, review and share

In this episode of the Nirvana Sisters podcast, we return with Product Junkies, after a summer hiatus. We dive into a variety of products that we've been loving lately, starting with some fun fashion finds. We share a new favorite clothing set from Ocean Drive, perfect for lounging or poolside wear and the Rag & Bone Miramar Wide Leg Pants, which combine the comfort of sweats with the look of jeans. We introduce the HiSmile Glow Stick Tooth Gloss, a unique product that brightens teeth on the go. As well as a new favorite styling wand from Dae, which helps tame frizz and flyaways effortlessly. As we wrap up, we reveal a favorite new find that will blow you away, the Peter Thomas Roth Instant Firm X Temporary Face Tightener, which visibly tightens and smooths the skin, giving a youthful appearance. Finally, we discuss our favorite lip glosses for the season, featuring products from Patrick Ta, Lawless, and Anastasia Beverly Hills. Brands/Mentions + Shop this episode here For more on this episode, read the full show notes here Follow us @nirvanasisters on Instagram Find us at www.nirvanasisters.com Shop our Amazon Store ShopMy Shop Say hi at hello@nirvanasisters.com Please subscribe, rate, review and share

Want the scoop on what the kids are up to? Casey Lewis is your gal. We're chatting with the genius behind After School—iconic newsletter and epic new podcast tracking all things Gen Z—about back-to-school trends, curly-hair controversy, and, of course, Thingies.   Some trending BTS items include tube tops and sweats (ideally together?), On shoes, Adidas Campus sneakers, Birkenstock Bostons, *the* Abercrombie camo hoodie, and Dae's Cactus Fruit 3-in-1 Styling Cream with Taming Wand.   Casey's Thingies include the Wet Brush (Claire is trying out the Bounce Curl brush, too), fiber (chia seeds!), a walking pad, and the Funky Nassau from the Lot in Greenpoint (combo of white wine and Grapefruit Spindrift).   Subscribe to the After School newsletter and podcast, both. Casey knows how to make trend-tracking very entertaining.   Cooking oil recs from us: Algae Cooking Club and Enzo infused olive oil (Organic Basil Crush and Organic Fresno Chili Crush specifically).   What's your take on the (potential) skinny jeans resurgence? Let us know at 833-632-5463, podcast@athingortwohq.com, or @athingortwohq—or join our Geneva!   Boost your hair with Nutrafol. Take $10 off your first month's subscription with the code ATHINGORTWO. Turn to Shopify for all your ecomm needs and get a $1-a-month trial with our link. YAY.  

That time Dae choked out Zen and SMILED while doing it! Discussing episodes 92-94 of Eaternal Nocturnal by Instantmiso! JOIN INSTANTMISO'S PATREON: patreon.com/instantmiso JOIN MY PATREON FOR EARLY ACCESS: patreon.com/girlwonder EATERNAL NOCTURNAL IN 33 MINUTES (Recap Podcast Episode): https://soundcloud.com/user-35260934/eaternal-nocturnal-in-33-minutes-the-ultimate-series-recap-deep-dive?si=9271d4aec2b846248232a49a41af6835&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing LATEST INTERVIEW WITH INSTANTMISO: https://soundcloud.com/user-35260934/qa-with-instantmiso-creator-of-eaternal-nocturnal-sirens-lament?utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing MY FIRST INTERVIEW WITH INSTANTMISO: https://soundcloud.com/user-35260934/all-about-sirens-lament-with?si=e8138a59da224dc6b4a4013fa5fe7fb7&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing SHOP WEBTOON - SIREN'S LAMENT: https://shopwebtoon.com/collections/sirens-lament MUSIC CREDIT: Isabella LeVan https://www.instagram.com/isabellalevan https://open.spotify.com/artist/3mHmktHG4sbkGsCORnaNT3?si=Nx2DvyOGQyatxudvD3ik9Q Connect with Girl Wonder:  My Patreon: https://www.patreon.com/girlwonder My YouTube Channel: https://www.youtube.com/channel/UCTk-JbxxAnf5TKyeCchNRHA twitter.com/girlwonderpod instagram.com/girlwonderpodcast Email: girlwondersquad (at) gmail (dot) com Buy me a coffee: http://ko-fi.com/girlwonderpodcast

This week, Reggie DAE$ sits down with Monet and Sheem "The Dream" to discuss and Kendrick Lamar's "The Pop Out" concert in Inglewood, California. Reggie starts the episode with an extended West Coast Mix (ONLY AVAILABLE ON PATREON!!!). From the concert to the cultural relevance, they break down and review the evening. They also discuss Hip-Hop's relationship with "Ghost Writing" and react to a few Quick Clips before providing their "Songs of the DAE$" and closing out.  Mother Requests Play date expenses from another Mom https://www.instagram.com/reel/C8dSnTypIic/?igsh=MWc5MHkwbnJwaHVvaA== Wife dumped Husband's Mothers Ashes in the Toilet (ONLY AVAILABLE ON PATREON!!!)  https://x.com/joshybesloshy/status/1803903057396208026?s=46 Have you ever been “Mobbed”? https://www.instagram.com/reel/C8HnuJNvgRK/?igsh=OGo1dTZqemphZHlm Song of the DAE$ Sheem: Kendrick Lamar "She Needs Me (Remix)" ft. Dom Kennedy & Murs Monet: Jhene Aiko "Never Call Me (Remix)" ft. YG Reggie: Mozzy, DCMBR & Yhung T.O. "Excuse Me" ft. Too $hort --- Send in a voice message: https://podcasters.spotify.com/pod/show/reggie-daes/message Support this podcast: https://podcasters.spotify.com/pod/show/reggie-daes/support

Ozempic and other GLP-1 medications have been in the news a lot over the past year. As a result, the availability of these drugs has expanded considerably. But how safe are they and how can integrative practitioners work with patients on these powerful medications? Karolyn talks with Daemon Jones, ND, a naturopathic physician in Washington, DC, about how these drugs work, their side effects, and other issues.    About the Expert Daemon Jones, ND, “Dr Dae,” graduated from Northwestern University and earned her naturopathic medicine degree from Bridgeport's College of Naturopathic Medicine. She is an expert in using lifestyle as medicine to reduce chronic disease. Her Replenish. Restore. Reclaim. framework proves that diminished health and energy can be reversed with proactive choices, at any age. Dr. Dae works with individuals who are struggling with health issues such as weight gain, diabetes, thyroid problems, and issues around menopause. She is a licensed naturopathic doctor in Washington, DC, and treats patients from across the DC Metropolitan area, as well as through virtual appointments all over the world.

This week we doubling up on the episode to get us back on track for the new season. Episode 4 had Rhae and Dae hitting the streets of silk which eventually led to Crispy getting targussy whipped. Episode 5 were introduced to the Divorce Rock, the Green Wedding and the beginning of the declaration of war If you want to keep the fun going with us throughout the week, come join our Facebook group. THE WATCH DEM THRONES FACEBOOK GROUPhttps://www.facebook.com/groups/126567443834910/?ref=share&mibextid=NSMWBTTO WATCH AND SUBSCRIBE:Facebook:https://www.facebook.com/blackwithnochaser/Twitter:https://twitter.com/BeBlackNoChaser?t=pVFV06lBFdZRu72ot4uCjA&s=09Twitter:https://twitter.com/WatchDemThrones?t=q0ngrYPlugf0ttzM2jo39A&s=09Apple Music: https://podcasts.apple.com/us/podcast/watch-dem-thrones-by-black-with-no-chaser/id1641754247Spotify:https://open.spotify.com/show/1qI1bJ1vIlobu502w6zrtN?si=mtsa3gZYRZW_3FmlCrv7UgBWNC RADIO: https://apps.apple.com/us/app/bwnc-radio/id6443800363Amazon Musichttps://music.amazon.com/podcasts/45279c3a-c09f-47d1-a3a3-88e6e2507230/watch-dem-thrones-by-black-with-no-chaserIHeartRadiohttps://www.iheart.com/podcast/269-watch-dem-thrones-by-black-101286659/?cmp=android_share&sc=android_social_share&pr=false#gameofthrones #demdragons #blackwithnochaser #houseofthedragonhbo #dragonseeds #theblacks #thegreens #houseofthedragon #youtube #targaryens #podcast #podsincolor #applemusic #spotifymusic #podsincolor #starks #lannisters #Velaryon

What is frailty? Kate Callahan relates a clear metaphor on today's podcast.  A frail person is like an origami boat: fine in still water, but can't withstand a breeze, or waves.  Fundamentally, frailty is about vulnerability to stress. In 2021 we talked with Linda Fried about phenotypic frailty.  Today we talk with Kate Callahan, Ariela Orkaby, & Dae Kim about deficit accumulation frailty.  What is the difference, you ask?  George Kushel probably explained it best in graphical terms (in JAGS), using the iconic golden gate bridge as a metaphor (Eric and I get to see the bridge daily driving or biking in to work). Phoenotypic frailty is like the main orange towers and thick orange support cables that run between towers.  Damage to those critical functions and the bridge can collapse.  Deficit accumulation frailty is like the hundreds of smaller vertical cables that connect the thick orange support cables to the bridge itself. Miss a few and you might be OK.  But miss a bunch and things fall apart.  Resilience is the ability of the bridge to withstand stress, like bridge traffic,  wind, waves, and the occasional earthquake (hey it's California!). Frailty research has come a long way.  We're now at a point where frailty can be measured automatically, or electronically, as we put in the title.  Kate created an eFrailty tool that measures frailty based on the electronic health record (EHR) data.  Ariela created a VA frailty index based on the EHR of veterans.  And Dae created an index using Medicare Claims.  Today we're beginning to discuss not just how to measure, but how to use these electronic frailty indexes to improve care of patients. We should not get too hung up on battles over frailty.  As Kate writes in her JAGS editorial, “If geriatricians wage internecine battles over how to measure frailty, we risk squandering the opportunity to elevate frailty to the level of a vital sign. Learning from the past, a lack of consensus on metrics impeded the mainstream adoption of valuable functional assessments, including gait speed.” To that end, modeled after ePrognosis, Dae and Ariela have launched a new tool for clinicians that includes multiple frailty measures, with guidance on how to use them and in what settings.  It's called eFrailty, check it out now! Did I cheat and play the guitar part for Sting's Fragile at ⅔ speed then speed it up?  Maybe…but hey, I still only have 2 usable fingers on my left hand, give me a break! -@AlexSmithMD    Additional Links: eFrailty website is: efrailty.hsl.harvard.edu (efrailty.org is fine). Dae's Frailty indexesCGA-based frailty index web calculator for clinical use: https://www.bidmc.org/research/research-by-department/medicine/gerontology/calculator The Medicare claims-based frailty index program for research: https://dataverse.harvard.edu/dataverse/cfi/ Ariela's VA-FI:Original VA frailty index: https://academic.oup.com/biomedgerontology/article/74/8/1257/5126804 ICD-10 version https://academic.oup.com/biomedgerontology/article/76/7/1318/6164923 Link to the code for investigators (included in the appendix): https://github.com/bostoninformatics/va_frailty_index  As an FYI for those in VA the code is readily available through the Centralized Interactive Phenomics Resource (CIPHER) Recent validation against clinical measures of frailty: https://agsjournals.onlinelibrary.wiley.com/doi/10.1111/jgs.18540 Kate's eFrailty Index https://doi.org/10.1093/gerona/glz017 our original eFI paper https://doi.org/10.1111/jgs.17027 &  https://doi.org/10.1001/jamanetworkopen.2023.41915 on eFI and surgery https://doi.org/10.1111/jgs.17510 editorial in JAGS  

Get ready to be inspired by today's episode, where you'll hear the remarkable story of Dae'vontay Latimer. Despite facing numerous hardships and setbacks, he has overcome them with the help of God's divine intervention. Through his experiences, he has learned to appreciate the value of faith and resilience, and we can all gain valuable insights from his journey.Support the showContact Us: Email the show: experience@emerge.org Emerge.org facebook.com/EmergeCounselingMinistries Thank you for listening, sharing, and praying for our podcast!Support the ExEm podcast by clicking here:https://www.buzzsprout.com/882700/support

The aftermath of Zen's creepy predatory behavior. Jae showed up for Eve! And wait a minute ... Dae, are you jealous? Today on the podcast, we're discussing episodes 69-71 of Eaternal Nocturnal by instantmiso! JOIN INSTANTMISO'S PATREON: patreon.com/instantmiso JOIN MY PATREON FOR EARLY ACCESS: patreon.com/girlwonder EATERNAL NOCTURNAL IN 33 MINUTES (Recap Podcast Episode): https://soundcloud.com/user-35260934/eaternal-nocturnal-in-33-minutes-the-ultimate-series-recap-deep-dive?si=9271d4aec2b846248232a49a41af6835&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing LATEST INTERVIEW WITH INSTANTMISO: https://soundcloud.com/user-35260934/qa-with-instantmiso-creator-of-eaternal-nocturnal-sirens-lament?utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing MY FIRST INTERVIEW WITH INSTANTMISO: https://soundcloud.com/user-35260934/all-about-sirens-lament-with?si=e8138a59da224dc6b4a4013fa5fe7fb7&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing SHOP WEBTOON - SIREN'S LAMENT: https://shopwebtoon.com/collections/sirens-lament MUSIC CREDIT: Isabella LeVan https://www.instagram.com/isabellalevan https://open.spotify.com/artist/3mHmktHG4sbkGsCORnaNT3?si=Nx2DvyOGQyatxudvD3ik9Q Connect with Girl Wonder:  My Patreon: https://www.patreon.com/girlwonder My YouTube Channel: https://www.youtube.com/channel/UCTk-JbxxAnf5TKyeCchNRHA twitter.com/girlwonderpod instagram.com/girlwonderpodcast Email: girlwondersquad (at) gmail (dot) com Buy me a coffee: http://ko-fi.com/girlwonderpodcast

This episode features "Resistant" written by Koji A. Dae. Published in the August 2023 issue of Clarkesworld Magazine and read by Kate Baker. The text version of this story can be found at: https://clarkesworldmagazine.com/dae_08_23 Support us on Patreon at https://www.patreon.com/join/clarkesworld?