Podcast appearances and mentions of Flo Rida

Send Mary and Kelsey a Message!Mary and Kelsey dive into the deep discography of global chart-topping sensation Pitull aka Mr. 305 aka Mr. Worldwide. They discuss how Pitbull has charmed the world with his signature catchphrases, iconic interpolations and guest features, and uplifting lyrics that have inspired arenas of women to don baldcaps and suits in his honor during his summer tour. Dale! Support the showInstagram: @whentheypoppedpodTikTok: @whentheypoppedEmail: whentheypoppedy2k@gmail.comWebsite: linktree.com/whentheypopped

Send us a textMeet Patricia--Venezuelan baker and owner of The Mama Dough, a sourdough microbakery at the Audubon Park Community Market. Over the past two years, Patricia's been baking delicious sourdough breads while gaining a loyal following of customers who line up at the market every Monday night to buy her loaves, bagels, croissants, cinnamon rolls, and mini baguettes.https://linktr.ee/helloapgdpod

01. Alice Deejay - Better Of Alone (Record Mix) 02. 666 - Supadupafly (Record Mix) 03. Klubbheads - Here We Go (Record Mix) 04. Blasterjaxx & Bd - Titan (Record Mix) 05. Flo Rida, Pitbull - Can't Believe It (Record Mix) 06. Loreen - Euphoria (Record Mix) 07. Hardwell - Dare You (Record Mix) 08. Macklemore - Thrift Shop (Record Mix) 09. Far East Movement - Turn Up the Love (Record Mix) 10. Axwell - Nobody Else (Record Mix) 11. Avicii - You Make Me (Record Mix) 12. Dimitri Vegas, Moguai, Like Mike - Body Talk (Record Mix) 13. Calvin Harris, Audiorockers, Matt Raiden - My Way (Record Mix) 14. Sebastian Ingrosso, Tommy Trash, John Martin - Reload (Record Mix) 15. Showtek - Booyah (Record Mix) 16. Tiesto, Kshmr, Vassy - Secrets (Record Mix) 17. Kygo, Conrad, Bassanova - Firestone (Record Mix) 18. Chocolate Puma, Tommie Sunshine - Scrub The Ground (Record Mix) 19. Afrojack, Martin Garrix - Turn Up The Speakers (Record Mix) 20. Zedd, Matthew Koma, Miriam Bryant - Find You (Record Mix) 21. Crystal Lake, Headhunterz - Say Goodbye (Record Mix) 22. Dvbbs - White Clouds (Record Mix) 23. Bassjackers, Luciana - Fireflies (Record Mix) 24. Kaptn - Ricky Ricardo (Record Mix) 25. Fedde Le Grand - So Much Love (Record Mix) 26. Freaks, Vandalism - The Creeps (Get on the Dancefloor) (Record Mix) 27. Martin Solveig - Hello (Record Mix) 28. Chris Brown, Benny Benassi - Beautiful People (Record Mix) 29. Global Deejays - Sound Of San Francisco (Record Mix) 30. Kid Cudi, Crookers - Day'n'Nite (Record Mix) 31. Junior Jack - E-Samba (Record Mix) 32. Camille Jones, Fedde Le Grand - The Creeps (Record Mix) 33. Nicky Romero, Vicetone, When We Are Wild - Let Me Feel (Record Mix) 34. Deadmau5, Rob Swire - Ghosts N Stuff (Record mix) 35. Pendulum - Hold Your Color (Record Mix)

Send us a textThis week we talk about how much money Disney makes daily and yearly. A trip to Disney got us thinking about how there is so many people world wide that goes to do Disney Parks daily and all the money generated. The numbers will astonish you. We then also talk about our top Disney movies since the subject of Disney has been brought up. There are alot of good movies and of course no so good movies. Check out what ONES we like and dislike......You can watch us on Youtube and listen on all major platforms......One Drink PodcastOne topic for One Drink. Topics are different and fun unlike the main media.Gods N GladiatorsCustom Clothing / Wall ArtDisclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.https://www.youtube.com/channel/UC-ytHeiGG6VND5GUmoWij-A

Florida is discussed by giving fun facts and then I give really interesting information about KeyLime pie over 200 more episodes giving fun mind-blowing facts about different locations around the World and their cuisine can be found on your favorite Podcast platform, including Spotify, IHeartRadio, Amazon Music and many more or you can simply click this link https://learn-about-world-cuisine.simplecast.com

Fáilte ar ais chuig eagrán nua de Ar An Lá Seo ar an 10ú lá de mí Aibreán, liomsa Lauren Ní Loingsigh. I 1981 thug an ghrúpa gallaher timpeall 10 milliún punt do shuíomh a bhí 41 acra timpeall Stephen's Green. I 2009 bhí clann timpeall an tír ábalta nach mór 500 euro gach mí a shábháil ar an teach de bharr gur thit praghsanna go mór I 75 bhliain. I 2012 bhí gnólacht ó Ros Cré ar Dragon's Den. Tháinig Graham Kenny agus a bean chéile suas le gnólacht chun fráma a chuir timpeall a chéad bhróga bábóg. Tháinig siad suas leis an smaoineamh I 2001. I 2014 tháinig an nuacht amach san Aonach Urmhumhan go raibh siad chun óstach a dhéanamh ar an Fleadh Cheoil I 2015. Is imeacht é a raibh seachtain ar fhad agus cheap na ndaoine a raibh ina chónaí sa bhaile go mbeadh níos mó ná 20,000 duine breise sa bhaile. Sin Flo Rida agus Kesha le Right Round – an t-amhrán is mó ar an lá seo I 2009. Ag lean ar aghaidh le nuacht cheoil ar an lá seo I 1985 thosaigh Madonna a chéad cheolchoirm I Meiriceá Thuaidh – chan sí trí oíche sa Paramount Theatre I Washington. D'oscail The Beastie Boys do Madonna ar an turas seo. I 2019 chuaigh Billie Eilish chuig barr na cairteacha sa Bhreatain lena chéad albam When We All Fall Asleep, Where Do We Go? Bhí sí an cailín is óige chun shroich uimhir a haon lena chéad albam sa Bhreatain. I 2020 ag na Grammys bhuaigh sí Albam den bhliain, agus Amhrán den bhliain lena amhrán Bad Guy – agus I bhfad níos mó. Agus ar deireadh breithlá daoine cáiliúla ar an lá seo rugadh aisteoir David Harbour I Nua Eabhrac I 1975 agus rugadh amhránaí Sophie Ellis Bextor sa Bhreatain ar an lá seo I 1979 agus seo chuid de a amhrán. Beidh mé ar ais libh amárach le heagrán nua de Ar An Lá Seo. Welcome back to another edition of Ar An Lá Seo on the 10th of April, with me Lauren Ní Loingsigh 1981: The gallaher group paid an estimated 10 million pounds for a 41 acre site adjoining stephens green in one of irelands biggest property deals. 2009: Families were able to save up to €500 a month on their household spending thanks to the biggest price drop in over 75 years. 2012 - A business that frames baby's first shoes based in Roscrea featured on RTE's 'Dragons' Den' Graham Kenny, a farmer all his life, set up a picture framing business, Framed Memories Forever, in 2001 with wife Cassandra, an artist and ballet teacher, as a source of off-farm income.  2014 - News broke that Nenagh was been chosen as the host town for the 2015 Munster Fleadh Cheoil. The week-long music event – the biggest of the provincial Fleadh gatherings, would attract as many as 20,000 visitors to Nenagh and its surrounds. It was the town's first time to host a Munster Fleadh.  That was Flo Rida and Kesha with Right Round– the biggest song on this day in 2009. Onto music news on this day In 1985, Madonna kicked off her very first North American tour by playing the first of three nights at the Paramount Theatre in Seattle, Washington. The Beastie Boys opened for Madonna on this 40-date Virgin Tour. In 2019, Billie Eilish was at No.1 on the UK chart with her debut studio album When We All Fall Asleep, Where Do We Go? It made Eilish the youngest female solo act to chart at No.1 in the UK. At the 2020 Grammy Awards, it won Album of the Year, Best Pop Vocal Album, while 'Bad Guy' from the album won Record of the Year. And finally celebrity birthdays on this day – actor David Harbour was born in New York in 1975 and singer Sophie Ellis Bextor was born in the UK in 1979 and this is one of her songs I'll be back with you tomorrow with another edition of Ar An Lá Seo.

Joining me today is Brian Dunne. Brian is the current drummer for Hall & Oates, Daryl Hall and has toured the world with them for almost 8 years. Brian is also the drummer on Live from Daryls House where he has recorded shows with Billy Gibbons, Sammy Hagar, Jason Mraz, Rob Thomas, Kenny Loggins, Darius Rucker, Joe Walsh, The Ojays, Cee Lo Green, Ben Folds, Joe Walsh and many more! if you havent seen this then it is a must watch! Brian has also performed / recorded with the likes of Patti Austin, Chuck Loeb, Ariana Grande, Cory Glover, Chaka Khan, Flo Rida, Ashanti, Sharon Jones, En Vogue, Carly Rae Jepson and again many more! He also has his own Production Facility (Back of the Bus Productions) where brian can record drums for anyone requiring live drums for their project. Huge thanks to Brian for great conversation and for giving up his time so freely! please check out Brian's website - www.briandunnedrums.com

C.C. Glitzer ist eine der bekanntesten Drag Queens in Florida – ein Bundesstaat, der Drag als Feindbild behandelt und queere Lebensrealitäten zunehmend kriminalisiert. Und doch tritt C.C. fast täglich auf, verzaubert ihr Publikum in Miami mit Shows voller Energie, Haltung und Humor. In dieser Folge spricht sie mit Thilo Mischke über den politischen Druck, der auf ihrer Community lastet, über Selbstzweifel, Leidenschaft und die Frage: Was gibt einem die Kraft, jeden Abend auf der Bühne zu stehen – in einer Gesellschaft, die einen nicht will? Thilo trifft C.C. in Miami – und lernt: Drag ist nicht nur Kunst und Performance, sondern auch Widerstand, Beruf und Lebensaufgabe. Es geht um Dollarscheine und Selbstachtung, um Applaus und Ausgrenzung. Um das Recht, sichtbar zu sein. Und um die ganz persönliche Entscheidung: Bleibe ich – oder breche ich alle Zelte ab? Hast du Fragen, Feedback oder Anmerkungen? Schreib uns eine Nachricht an [amr@pqpp2.de](mailto:amr@pqpp2.de) oder auf Instagram: https://www.instagram.com/allesmussraus_podcast/ und wenn du möchtest unterstütze unsere Arbeit auf Patreon: https://www.patreon.com/c/AllesMussRaus?l=de Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte: https://linktr.ee/allesmussrauspodcast Du möchtest in „Alles Muss Raus“ werben? Dann hier* entlang: https://podstars.de/kontakt/?utm_source=podcast&utm_campaign=shownotes_alles-muss-raus

Throughout history there are stories of weird things falling from the sky.  This week we have some of those stories on the show!Email us!  indarkplacespod@hotmail.comFacebook:https://www.facebook.com/indarkplacespodcastYouTube:https://www.youtube.com/channel/UCdrL6rsNSKeBA31NcU3reXARumble:https://rumble.com/user/InDarkPlacesOrder Jimmy's book, Mr. Haunted Origins, here:https://www.amazon.com/dp/B0D5752RN7/ref=sr_1_1?crid=2WMJ9MRBR2KMR&dib=eyJ2IjoiMSJ9.-DgjsjgRdJ4VXfE6OAQGtSlE0p-y-bhGXMMyAGBNvTzOAOevWbd2EdJ-ZTyob92w.WAhwJ4G8tSIUmcRMm41ex9oZFg0f9mfMn4KDKUCtYFc&dib_tag=se&keywords=mr+haunted+origins&qid=1716734152&s=books&sprefix=mr+haunted+origins%2Cstripbooks%2C122&sr=1-1Subscribe to classic episodes of The Haunted Chronicles!https://www.youtube.com/@thehauntedchronicles2013Patreon:https://www.patreon.com/indarkplacesThe ABCs Of Salvation:A.  ADMIT THAT YOU'RE A SINNER. This is where that godly sorrow leads to genuine repentance for sinning against the righteous God and there is a change of heart, we change our mind and God changes our hearts and regenerates us from the inside out.B.  BELIEVE IN YOUR HEART THAT JESUS CHRIST DIED FOR YOUR SINS, WAS BURIED, AND THAT GOD RAISED JESUS FROM THE DEAD. Believe in your heart that Jesus Christ died for your sins, was buried, and that God raised Jesus from the dead. This is trusting with all of your heart that Jesus Christ is who he said he was.C.  CALL UPON THE NAME OF THE LORD. This is trusting with all of your heart that Jesus Christ is who he said he was. Every single person who ever lived since Adam will bend their knee and confess with their mouth that Jesus Christ is Lord, the Lord of Lords and the King of Kings.

Send us a textReady for a podcast that serves up both laughs and shivers down your spine? We kick things off sharing our April Fool's Day experiences - from tiny clown car rental pranks to fake academic emergencies that had us completely fooled. There's something universally entertaining about those moments when we realize we've been had, especially by our loved ones.The conversation shifts to an unexpected place when we discuss the recently returned NASA astronauts who spent nine months in space instead of their planned week. What fascinates us most isn't just their extended stay, but their remarkable attitude about it. While most of us would lose our minds over a one-day flight delay, these extraordinary humans insist they weren't "stranded" at all. Their perspective challenges us to reconsider how we handle life's unexpected extensions and delays.We wrap up with a deep dive into breakfast habits and family morning routines. From microwave eggs (don't judge!) to chocolate chip pancakes to the healthiest options like oatmeal with berries, our morning meal preferences reveal surprising aspects of our personalities. Whether you're Team Breakfast Sandwich or devoted to your morning gruel, you'll find yourself nodding along to our breakfast debate. What's your non-negotiable breakfast item? Join the conversation and let us know!Mike Haggerty Buick GMCRight on the corner, right on the price! Head down to 93rd & Cicero & tell them the Noras sent you!Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.

In this wildly candid and captivating episode of Go Ask Allyson, host Allyson Sullivan recounts her ten most shocking, heartbreaking, and bizarre real estate deals in her 23-year career. Joined by producer Janine, Allyson walks us through everything from a client who fled to Mexico mid-sale, to a haunted property where the previous owner's spirit may not have left, to gut-wrenching landlord stories involving tragic tenant deaths and overwhelming cleanups.With humor, honesty, and a bit of “can you believe this?!” disbelief, Allyson pulls back the curtain on what really happens when deals go sideways. These stories are more than just real estate gone wrong — they're a rollercoaster of human drama, unexpected twists, and cautionary tales that will leave you both stunned and strangely entertained.Contact Allyson Sullivan:Email: AllysonSL@hotmail.comIG: @allysonsullivanrealtorWebsite: www.allysonsullivan.com

Send us a textMeet Cate--a gifted farmer with a seasonal booth at the Audubon Park Community Market and just one of the kindest people you'll ever meet. The name Open Hands Farm comes from the spirit of abundance and generosity; plus a willingness to let go and surrender to what life brings you. Cate is wise beyond her years with a sustainable agriculture degree, plus a lifelong interest in growing food. We talk about her farming journey through New Jersey, Pennsylvania, and Maine; and how her Farm Manager job in Ft. Meyers prepared her for running her own farm right here in the Greater Orlando (Longwood) area. https://linktr.ee/helloapgdpod

100% LIFESTYLE - Tous les jeudis : - De 19H à 20H sur RDL 103.5 FM en Centre Alsace - A l'écoute partout à cette heure sur le direct live sur www.rdl68.fr / rdl68.fr/playlist/100-lifestyle/ - En PODCAST sur SOUNDCLOUD chaque JEUDI à 21H : on.soundcloud.com/QPEjqQJ7u51dxPjv6 Dans ce numéro, Anne-Claire & Yann vous proposent : - En route pour l'aventure (voyage/Yann): Le voyage de Yann en Ecosse - La minute soignante (santé & bien-être/Anne-Claire): Quelques conseils pour un retour au sport après une blessure - Chanson Story (histoire d'un tube/Yann): "Hélène", Roch Voisine, 1989 - La question des auditeurs: Pourquoi les poils de chats se collent à nos vêtements ? - Mode & Beauté (Anne-Claire): Les tendances mode printemps - été 2025 MUSIQUES: "Galway girl", Ed Sheeran, 2017 "Hélène", Roch Voisine, 1989 "Amamé", Yuri Buenaventura, 2024 EXTRAITS: "Amazing Grace" à la cornemuse "Coming' thro' the rye", Bear McCreary, 2015 (BO de la série "Outlander) "Skye Boat song", Générique de la saison 1 de la série "Outlander" "Clean pease strae", Bear McCreary, 2015 (BO de la série "Outlander") "Good feeling", Flo Rida, 2011 "Tout le monde veut devenir un cat", Les Aristochats, 1994 "Et alors", Shy'm, 2012 Important: Je ne touche aucun droits d'auteur sur ces chansons. Les droits reviennent intégralement aux auteurs/compositeurs/interprètes. Diffusion: Jeudi 19H - 20H en direct sur RDL (103.5 FM dans le Centre Alsace) www.rdl68.fr Une production RDL 103.5 FM Tous droits réservés

Send us a textWhat happens when a small-town girl with zero fashion experience takes over a consignment shop during a financial crash… and ends up building a local style empire? Meet Jen Davis, the fearless force behind Second Time Around, who went from wrangling pigs on a Delray farm to curating designer treasures and surviving life's curveballs with humor, heart, and a whole lot of grit.In this colorful and candid episode of Mind Your Nest, host Jennifer Rosen uncovers the real story behind one of Delray Beach's most charming boutiques. From Chanel bags to eviction notices, unexpected threats, and a breast cancer battle—Jen's journey is anything but ordinary. If you've ever believed in second chances (or just love a good pair of Gucci loafers), this episode is your permission slip to reinvent your life—with style.Contact Jennifer Rosen:Email: jennifer@mindyournest.com

We will never not dance to our intro music, and honestly, this episode brings the same energy. Rachel and Dale are back—live from a $7M mansion in Lauderdale-by-the-Sea (shoutout to Courtney Ortiz and her Big Dock Energy). We kick things off with Dale's latest passion project: Dale's Dollars, a brilliantly chaotic plan to end poverty one dollar at a time. Shark Tank, are you listening?From nipple piercings and DIY speculums (don't ask) to haunted alleys in Charleston and daddy issues dirty martinis, we spiral into glorious chaos. We get real about acceptance in the South, Tesla shade, DMV scammers, and what happens when you say yes to everything on a girls' trip. Also: Roy, one of our producers, grabs the mic to reveal something very unexpected. Let's just say... we are never going to let this go!The math is not mathing! Do us a favor and hit that follow button because the math is not mathing. It's free and helps us! Pierced, proud, and probably haunted—this is Friends Without Benefits.Contact Rachel Sobel:Email: rachel@whineandcheezits.comWebsite: www.whineandcheezits.comFacebook:  Whine and Cheez - its by Rachel Sobel   Instagram: @whineandcheezitsTikTok: @rachel.sobel.writesContact Dale Mclean:Email: dance715@aol.comWebsite: dalethehost.comInstagram: @UptownDale

Flo Rida on Eurovision; Spock's strange new world aura detecting marketing; Fresno Nightcrawler cryptid pants; celebrity heists Spuds MacKenzie. Unlock the BONUS SCENE(S) at improv4humans.com and gain access to every episode of i4h, all ad-free, as well as TONS of exclusive new podcasts delving deeper into improv, the history of comedy, music and sci-fi.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

01. Calvin Harris, Ne-Yo - Let's Go (Record Mix) 02. Alesso, Nico & Vinz, Deniz Koyu - I Wanna Know (Record Mix) 03. Avicii - Street Dance (Record Mix) 04. Daft Punk, Deadmau5 - Harder, Faster, Stronger (Record Mix) 05. Tiesto, Oliver Heldens - Wombass (Record Mix) 06. Benny Blanco, Calvin Harris - I Found You (Record Mix) 07. Sidney Samson - Riverside (Record Mix) 08. Chocolate Puma - Listen To The Talk (Record Mix) 09. 4 Strings, Dave Darell - Take Me Away (Record Mix) 10. Dan Balan - Chica Bomb (Record Mix) 11. Dada Life - Rolling Stones T-Shirt (Record Mix) 12. Flo Rida, Sia - Wild Ones (Record Mix) 13. Fedde Le Grand, Niels Geusebroek - Falling (Record Mix) 14. Discobitch - C'est Beau La Bourgeoisie (Record Mix) 15. Armin Van Buuren, Mr Probz - Another You (Record Mix) 16. Don Diablo, Maluca - My Window (Record Mix) 17. Bassjackers, Kshmr, Sirah - Memories (Record Mix) 18. Tujamo, Danny Avila - Cream (Record Mix) 19. Antonio Giacca - Chemistry (Record Mix) 20. John Christian, Nicky Romero - Next Level (Record Mix) 21. Crystal Lake, Headhunterz - Say Goodbye (Record Mix) 22. Klaas - Flight To Paris (Record Mix) 23. Apashe, Splitbreed - Day Dream (Record Mix) 24. Lost Frequencies, Dimaro - Are You with Me (Record Mix) 25. Shm - Greyhound (Record Mix) 26. Moguai - ACIIID (Record Mix) 27. 2-Dutch - EVRBDY (Record Mix) 28. 3Lau, Bright Lights - How You Love Me (Record Mix) 29. Justice, Simian - We Are Your Friends (Record Mix) 30. Jasper Forks - River Flows In You (Record Mix) 31. Benny Benassi, Gary Go - Cinema (Record Mix) 32. Azealia Banks, Lazy Jay - 212 (Record Mix) 33. Avener, Dj Nil - Fade Out Lines (Record Mix) 34. Matt Nash - Know My Love (Record Mix) 35. Prodigy - Girls (Record Mix)

01. Calvin Harris, Ne-Yo - Let's Go (Record Mix) 02. Alesso, Nico & Vinz, Deniz Koyu - I Wanna Know (Record Mix) 03. Avicii - Street Dance (Record Mix) 04. Daft Punk, Deadmau5 - Harder, Faster, Stronger (Record Mix) 05. Tiesto, Oliver Heldens - Wombass (Record Mix) 06. Benny Blanco, Calvin Harris - I Found You (Record Mix) 07. Sidney Samson - Riverside (Record Mix) 08. Chocolate Puma - Listen To The Talk (Record Mix) 09. 4 Strings, Dave Darell - Take Me Away (Record Mix) 10. Dan Balan - Chica Bomb (Record Mix) 11. Dada Life - Rolling Stones T-Shirt (Record Mix) 12. Flo Rida, Sia - Wild Ones (Record Mix) 13. Fedde Le Grand, Niels Geusebroek - Falling (Record Mix) 14. Discobitch - C'est Beau La Bourgeoisie (Record Mix) 15. Armin Van Buuren, Mr Probz - Another You (Record Mix) 16. Don Diablo, Maluca - My Window (Record Mix) 17. Bassjackers, Kshmr, Sirah - Memories (Record Mix) 18. Tujamo, Danny Avila - Cream (Record Mix) 19. Antonio Giacca - Chemistry (Record Mix) 20. John Christian, Nicky Romero - Next Level (Record Mix) 21. Crystal Lake, Headhunterz - Say Goodbye (Record Mix) 22. Klaas - Flight To Paris (Record Mix) 23. Apashe, Splitbreed - Day Dream (Record Mix) 24. Lost Frequencies, Dimaro - Are You with Me (Record Mix) 25. Shm - Greyhound (Record Mix) 26. Moguai - ACIIID (Record Mix) 27. 2-Dutch - EVRBDY (Record Mix) 28. 3Lau, Bright Lights - How You Love Me (Record Mix) 29. Justice, Simian - We Are Your Friends (Record Mix) 30. Jasper Forks - River Flows In You (Record Mix) 31. Benny Benassi, Gary Go - Cinema (Record Mix) 32. Azealia Banks, Lazy Jay - 212 (Record Mix) 33. Avener, Dj Nil - Fade Out Lines (Record Mix) 34. Matt Nash - Know My Love (Record Mix) 35. Prodigy - Girls (Record Mix)

Fáilte ar ais chuig eagrán nua de Ar An Lá Seo ar an 10ú lá de mí Aibreán, liomsa Lauren Ní Loingsigh. I 1981 thug an ghrúpa gallaher timpeall 10 milliún punt do shuíomh a bhí 41 acra timpeall Stephen's Green. I 2009 bhí clann timpeall an tír ábalta nach mór 500 euro gach mí a shábháil ar an teach de bharr gur thit praghsanna go mór I 75 bhliain. I 1992 bhí picéad ag tarlú sa chontae ag 23 bainc ón Bank Of Ireland agus Ulster Bank. Sheas siad leis na comhghleacaí a bhí ag obair sa AIB a bhí ag agóidíocht ón mí roimhe. I 2009 tháinig nuacht iontach chuig an chontae mar dúradh go mbeadh gnólachtaí ag fáil na mílte euro timpeall Inis de bharr tionscnaíocht. Sin Flo Rida agus Kesha le Right Round – an t-amhrán is mó ar an lá seo I 2009. Ag lean ar aghaidh le nuacht cheoil ar an lá seo I 1985 thosaigh Madonna a chéad cheolchoirm I Meiriceá Thuaidh – chan sí trí oíche sa Paramount Theatre I Washington. D'oscail The Beastie Boys do Madonna ar an turas seo. I 2019 chuaigh Billie Eilish chuig barr na cairteacha sa Bhreatain lena chéad albam When We All Fall Asleep, Where Do We Go? Bhí sí an cailín is óige chun shroich uimhir a haon lena chéad albam sa Bhreatain. I 2020 ag na Grammys bhuaigh sí Albam den bhliain, agus Amhrán den bhliain lena amhrán Bad Guy – agus I bhfad níos mó. Agus ar deireadh breithlá daoine cáiliúla ar an lá seo rugadh aisteoir David Harbour I Nua Eabhrac I 1975 agus rugadh amhránaí Sophie Ellis Bextor sa Bhreatain ar an lá seo I 1979 agus seo chuid de a amhrán. Beidh mé ar ais libh amárach le heagrán nua de Ar An Lá Seo. Welcome back to another edition of Ar An Lá Seo on the 10th of April, with me Lauren Ní Loingsigh 1981: The gallaher group paid an estimated 10 million pounds for a 41 acre site adjoining stephens green in one of irelands biggest property deals. 2009: Families were able to save up to €500 a month on their household spending thanks to the biggest price drop in over 75 years. 1992: The bank dispute escalated in clare this week with pickets being placed on all 23 branches of the associated banks in the county as staff from the BOI and Ulster bank joined with their collegues in allied irish bank who were on the picket line for the last month. 2009: Businesses in the county recieved a massive boost with an announcemnt that hundreds of thousands of euro were to be ploughed into an initiative in ennis. That was Flo Rida and Kesha with Right Round– the biggest song on this day in 2009. Onto music news on this day In 1985, Madonna kicked off her very first North American tour by playing the first of three nights at the Paramount Theatre in Seattle, Washington. The Beastie Boys opened for Madonna on this 40-date Virgin Tour. In 2019, Billie Eilish was at No.1 on the UK chart with her debut studio album When We All Fall Asleep, Where Do We Go? It made Eilish the youngest female solo act to chart at No.1 in the UK. At the 2020 Grammy Awards, it won Album of the Year, Best Pop Vocal Album, while 'Bad Guy' from the album won Record of the Year. And finally celebrity birthdays on this day – actor David Harbour was born in New York in 1975 and singer Sophie Ellis Bextor was born in the UK in 1979 and this is one of her songs I'll be back with you tomorrow with another edition of Ar An Lá Seo.

Buckle up, because this episode is a wild ride you didn't know you needed! We're coming to you live (well, kinda) from Sea Ranch Lakes, where Dale gets recognized yet again — because apparently, you can't walk five feet without someone asking if he does bar mitzvahs (spoiler: he does... a LOT). We dive deep into jaw-dropping celebrity scandals — from Diddy to Elvis Presley's shocking relationship with Priscilla — and ask, why do some celebs get a free pass while others get canceled?And if you've ever been to a wedding where a screaming baby stole the show — oh, we've got thoughts. Plus, what the heck is Disco Foot (soccer + dance = chaos)? And in a heartfelt moment, we open up about surviving domestic abuse and why it's time to break the silence. Full of humor, real talk, and a few "did-they-just-say-that?" moments — this is an episode you cannot skip!Contact Rachel Sobel:Email: rachel@whineandcheezits.comWebsite: www.whineandcheezits.comFacebook:  Whine and Cheez - its by Rachel Sobel   Instagram: @whineandcheezitsTikTok: @rachel.sobel.writesContact Dale Mclean:Email: dance715@aol.comWebsite: dalethehost.comInstagram: @UptownDale

We are working with Amplify on the 2025 State of AI Engineering Survey to be presented at the AIE World's Fair in SF! Join the survey to shape the future of AI Eng!We first met Snipd over a year ago, and were immediately impressed by the design, but were doubtful about the behavior of snipping as the title behavior:Podcast apps are enormously sticky - Spotify spent almost $1b in podcast acquisitions and exclusive content just to get an 8% bump in market share among normies.However, after a disappointing Overcast 2.0 rewrite with no AI features in the last 3 years, I finally bit the bullet and switched to Snipd. It's 2025, your podcast app should be able to let you search transcripts of your podcasts. Snipd is the best implementation of this so far.And yet they keep shipping:What impressed us wasn't just how this tiny team of 4 was able to bootstrap a consumer AI app against massive titans and do so well; but also how seriously they think about learning through podcasts and improving retention of knowledge over time, aka “Duolingo for podcasts”. As an educational AI podcast, that's a mission we can get behind.Full Video PodFind us on YouTube! This was the first pod we've ever shot outdoors!Show Notes* How does Shazam work?* Flutter/FlutterFlow* wav2vec paper* Perplexity Online LLM* Google Search Grounding* Comparing Snipd transcription with our Bee episode* NIPS 2017 Flo Rida* Gustav Söderström - Background AudioTimestamps* [00:00:03] Takeaways from AI Engineer NYC* [00:00:17] Weather in New York.* [00:00:26] Swyx and Snipd.* [00:01:01] Kevin's AI summit experience.* [00:01:31] Zurich and AI.* [00:03:25] SigLIP authors join OpenAI.* [00:03:39] Zurich is very costly.* [00:04:06] The Snipd origin story.* [00:05:24] Introduction to machine learning.* [00:09:28] Snipd and user knowledge extraction.* [00:13:48] App's tech stack, Flutter, Python.* [00:15:11] How speakers are identified.* [00:18:29] The concept of "backgroundable" video.* [00:29:05] Voice cloning technology.* [00:31:03] Using AI agents.* [00:34:32] Snipd's future is multi-modal AI.* [00:36:37] Snipd and existing user behaviour.* [00:42:10] The app, summary, and timestamps.* [00:55:25] The future of AI and podcasting.* [1:14:55] Voice AITranscriptswyx [00:00:03]: Hey, I'm here in New York with Kevin Ben-Smith of Snipd. Welcome.Kevin [00:00:07]: Hi. Hi. Amazing to be here.swyx [00:00:09]: Yeah. This is our first ever, I think, outdoors podcast recording.Kevin [00:00:14]: It's quite a location for the first time, I have to say.swyx [00:00:18]: I was actually unsure because, you know, it's cold. It's like, I checked the temperature. It's like kind of one degree Celsius, but it's not that bad with the sun. No, it's quite nice. Yeah. Especially with our beautiful tea. With the tea. Yeah. Perfect. We're going to talk about Snips. I'm a Snips user. I'm a Snips user. I had to basically, you know, apart from Twitter, it's like the number one use app on my phone. Nice. When I wake up in the morning, I open Snips and I, you know, see what's new. And I think in terms of time spent or usage on my phone, I think it's number one or number two. Nice. Nice. So I really had to talk about it also because I think people interested in AI want to think about like, how can we, we're an AI podcast, we have to talk about the AI podcast app. But before we get there, we just finished. We just finished the AI Engineer Summit and you came for the two days. How was it?Kevin [00:01:07]: It was quite incredible. I mean, for me, the most valuable was just being in the same room with like-minded people who are building the future and who are seeing the future. You know, especially when it comes to AI agents, it's so often I have conversations with friends who are not in the AI world. And it's like so quickly it happens that you, it sounds like you're talking in science fiction. And it's just crazy talk. It was, you know, it's so refreshing to talk with so many other people who already see these things and yeah, be inspired then by them and not always feel like, like, okay, I think I'm just crazy. And like, this will never happen. It really is happening. And for me, it was very valuable. So day two, more relevant, more relevant for you than day one. Yeah. Day two. So day two was the engineering track. Yeah. That was definitely the most valuable for me. Like also as a producer. Practitioner myself, especially there were one or two talks that had to do with voice AI and AI agents with voice. Okay. So that was quite fascinating. Also spoke with the speakers afterwards. Yeah. And yeah, they were also very open and, and, you know, this, this sharing attitudes that's, I think in general, quite prevalent in the AI community. I also learned a lot, like really practical things that I can now take away with me. Yeah.swyx [00:02:25]: I mean, on my side, I, I think I watched only like half of the talks. Cause I was running around and I think people saw me like towards the end, I was kind of collapsing. I was on the floor, like, uh, towards the end because I, I needed to get, to get a rest, but yeah, I'm excited to watch the voice AI talks myself.Kevin [00:02:43]: Yeah. Yeah. Do that. And I mean, from my side, thanks a lot for organizing this conference for bringing everyone together. Do you have anything like this in Switzerland? The short answer is no. Um, I mean, I have to say the AI community in, especially Zurich, where. Yeah. Where we're, where we're based. Yeah. It is quite good. And it's growing, uh, especially driven by ETH, the, the technical university there and all of the big companies, they have AI teams there. Google, like Google has the biggest tech hub outside of the U S in Zurich. Yeah. Facebook is doing a lot in reality labs. Uh, Apple has a secret AI team, open AI and then SwapBit just announced that they're coming to Zurich. Yeah. Um, so there's a lot happening. Yeah.swyx [00:03:23]: So, yeah, uh, I think the most recent notable move, I think the entire vision team from Google. Uh, Lucas buyer, um, and, and all the other authors of Siglip left Google to join open AI, which I thought was like, it's like a big move for a whole team to move all at once at the same time. So I've been to Zurich and it just feels expensive. Like it's a great city. Yeah. It's great university, but I don't see it as like a business hub. Is it a business hub? I guess it is. Right.Kevin [00:03:51]: Like it's kind of, well, historically it's, uh, it's a finance hub, finance hub. Yeah. I mean, there are some, some large banks there, right? Especially UBS, uh, the, the largest wealth manager in the world, but it's really becoming more of a tech hub now with all of the big, uh, tech companies there.swyx [00:04:08]: I guess. Yeah. Yeah. And, but we, and research wise, it's all ETH. Yeah. There's some other things. Yeah. Yeah. Yeah.Kevin [00:04:13]: It's all driven by ETH. And then, uh, it's sister university EPFL, which is in Lausanne. Okay. Um, which they're also doing a lot, but, uh, it's, it's, it's really ETH. Uh, and otherwise, no, I mean, it's a beautiful, really beautiful city. I can recommend. To anyone. To come, uh, visit Zurich, uh, uh, let me know, happy to show you around and of course, you know, you, you have the nature so close, you have the mountains so close, you have so, so beautiful lakes. Yeah. Um, I think that's what makes it such a livable city. Yeah.swyx [00:04:42]: Um, and the cost is not, it's not cheap, but I mean, we're in New York city right now and, uh, I don't know, I paid $8 for a coffee this morning, so, uh, the coffee is cheaper in Zurich than the New York city. Okay. Okay. Let's talk about Snipt. What is Snipt and, you know, then we'll talk about your origin story, but I just, let's, let's get a crisp, what is Snipt? Yeah.Kevin [00:05:03]: I always see two definitions of Snipt, so I'll give you one really simple, straightforward one, and then a second more nuanced, um, which I think will be valuable for the rest of our conversation. So the most simple one is just to say, look, we're an AI powered podcast app. So if you listen to podcasts, we're now providing this AI enhanced experience. But if you look at the more nuanced, uh, podcast. Uh, perspective, it's actually, we, we've have a very big focus on people who like your audience who listened to podcasts to learn something new. Like your audience, you want, they want to learn about AI, what's happening, what's, what's, what's the latest research, what's going on. And we want to provide a, a spoken audio platform where you can do that most effectively. And AI is basically the way that we can achieve that. Yeah.swyx [00:05:53]: Means to an end. Yeah, exactly. When you started. Was it always meant to be AI or is it, was it more about the social sharing?Kevin [00:05:59]: So the first version that we ever released was like three and a half years ago. Okay. Yeah. So this was before ChatGPT. Before Whisper. Yeah. Before Whisper. Yeah. So I think a lot of the features that we now have in the app, they weren't really possible yet back then. But we already from the beginning, we always had the focus on knowledge. That's the reason why, you know, we in our team, why we listen to podcasts, but we did have a bit of a different approach. Like the idea in the very beginning was, so the name is Snips and you can create these, what we call Snips, which is basically a small snippet, like a clip from a, from a podcast. And we did envision sort of like a, like a social TikTok platform where some people would listen to full episodes and they would snip certain, like the best parts of it. And they would post that in a feed and other users would consume this feed of Snips. And use that as a discovery tool or just as a means to an end. And yeah, so you would have both people who create Snips and people who listen to Snips. So our big hypothesis in the beginning was, you know, it will be easy to get people to listen to these Snips, but super difficult to actually get them to create them. So we focused a lot of, a lot of our effort on making it as seamless and easy as possible to create a Snip. Yeah.swyx [00:07:17]: It's similar to TikTok. You need CapCut for there to be videos on TikTok. Exactly.Kevin [00:07:23]: And so for, for Snips, basically whenever you hear an amazing insight, a great moment, you can just triple tap your headphones. And our AI actually then saves the moment that you just listened to and summarizes it to create a note. And this is then basically a Snip. So yeah, we built, we built all of this, launched it. And what we found out was basically the exact opposite. So we saw that people use the Snips to discover podcasts, but they really, you know, they don't. You know, really love listening to long form podcasts, but they were creating Snips like crazy. And this was, this was definitely one of these aha moments when we realized like, hey, we should be really doubling down on the knowledge of learning of, yeah, helping you learn most effectively and helping you capture the knowledge that you listen to and actually do something with it. Because this is in general, you know, we, we live in this world where there's so much content and we consume and consume and consume. And it's so easy to just at the end of the podcast. You just start listening to the next podcast. And five minutes later, you've forgotten everything. 90%, 99% of what you've actually just learned. Yeah.swyx [00:08:31]: You don't know this, but, and most people don't know this, but this is my fourth podcast. My third podcast was a personal mixtape podcast where I Snipped manually sections of podcasts that I liked and added my own commentary on top of them and published them as small episodes. Nice. So those would be maybe five to 10 minute Snips. Yeah. And then I added something that I thought was a good story or like a good insight. And then I added my own commentary and published it as a separate podcast. It's cool. Is that still live? It's still live, but it's not active, but you can go back and find it. If you're, if, if you're curious enough, you'll see it. Nice. Yeah. You have to show me later. It was so manual because basically what my process would be, I hear something interesting. I note down the timestamp and I note down the URL of the podcast. I used to use Overcast. So it would just link to the Overcast page. And then. Put in my note taking app, go home. Whenever I feel like publishing, I will take one of those things and then download the MP3, clip out the MP3 and record my intro, outro and then publish it as a, as a podcast. But now Snips, I mean, I can just kind of double click or triple tap.Kevin [00:09:39]: I mean, those are very similar stories to what we hear from our users. You know, it's, it's normal that you're doing, you're doing something else while you're listening to a podcast. Yeah. A lot of our users, they're driving, they're working out, walking their dog. So in those moments when you hear something amazing, it's difficult to just write them down or, you know, you have to take out your phone. Some people take a screenshot, write down a timestamp, and then later on you have to go back and try to find it again. Of course you can't find it anymore because there's no search. There's no command F. And, um, these, these were all of the issues that, that, that we encountered also ourselves as users. And given that our background was in AI, we realized like, wait, hey, this is. This should not be the case. Like podcast apps today, they're still, they're basically repurposed music players, but we actually look at podcasts as one of the largest sources of knowledge in the world. And once you have that different angle of looking at it together with everything that AI is now enabling, you realize like, hey, this is not the way that we, that podcast apps should be. Yeah.swyx [00:10:41]: Yeah. I agree. You mentioned something that you said your background is in AI. Well, first of all, who's the team and what do you mean your background is in AI?Kevin [00:10:48]: Those are two very different things. I'm going to ask some questions. Yeah. Um, maybe starting with, with my backstory. Yeah. My backstory actually goes back, like, let's say 12 years ago or something like that. I moved to Zurich to study at ETH and actually I studied something completely different. I studied mathematics and economics basically with this specialization for quant finance. Same. Okay. Wow. All right. So yeah. And then as you know, all of these mathematical models for, um, asset pricing, derivative pricing, quantitative trading. And for me, the thing that, that fascinates me the most was the mathematical modeling behind it. Uh, mathematics, uh, statistics, but I was never really that passionate about the finance side of things.swyx [00:11:32]: Oh really? Oh, okay. Yeah. I mean, we're different there.Kevin [00:11:36]: I mean, one just, let's say symptom that I noticed now, like, like looking back during that time. Yeah. I think I never read an academic paper about the subject in my free time. And then it was towards the end of my studies. I was already working for a big bank. One of my best friends, he comes to me and says, Hey, I just took this course. You have to, you have to do this. You have to take this lecture. Okay. And I'm like, what, what, what is it about? It's called machine learning and I'm like, what, what, what kind of stupid name is that? Uh, so you sent me the slides and like over a weekend I went through all of the slides and I just, I just knew like freaking hell. Like this is it. I'm, I'm in love. Wow. Yeah. Okay. And that was then over the course of the next, I think like 12 months, I just really got into it. Started reading all about it, like reading blog posts, starting building my own models.swyx [00:12:26]: Was this course by a famous person, famous university? Was it like the Andrew Wayne Coursera thing? No.Kevin [00:12:31]: So this was a ETH course. So a professor at ETH. Did he teach in English by the way? Yeah. Okay.swyx [00:12:37]: So these slides are somewhere available. Yeah. Definitely. I mean, now they're quite outdated. Yeah. Sure. Well, I think, you know, reflecting on the finance thing for a bit. So I, I was, used to be a trader, uh, sell side and buy side. I was options trader first and then I was more like a quantitative hedge fund analyst. We never really use machine learning. It was more like a little bit of statistical modeling, but really like you, you fit, you know, your regression.Kevin [00:13:03]: No, I mean, that's, that's what it is. And, uh, or you, you solve partial differential equations and have then numerical methods to, to, to solve these. That's, that's for you. That's your degree. And that's, that's not really what you do at work. Right. Unless, well, I don't know what you do at work. In my job. No, no, we weren't solving the partial differential. Yeah.swyx [00:13:18]: You learn all this in school and then you don't use it.Kevin [00:13:20]: I mean, we, we, well, let's put it like that. Um, in some things, yeah, I mean, I did code algorithms that would do it, but it was basically like, it was the most basic algorithms and then you just like slightly improve them a little bit. Like you just tweak them here and there. Yeah. It wasn't like starting from scratch, like, Oh, here's this new partial differential equation. How do we know?swyx [00:13:43]: Yeah. Yeah. I mean, that's, that's real life, right? Most, most of it's kind of boring or you're, you're using established things because they're established because, uh, they tackle the most important topics. Um, yeah. Portfolio management was more interesting for me. Um, and, uh, we, we were sort of the first to combine like social data with, with quantitative trading. And I think, uh, I think now it's very common, but, um, yeah. Anyway, then you, you went, you went deep on machine learning and then what? You quit your job? Yeah. Yeah. Wow.Kevin [00:14:12]: I quit my job because, uh, um, I mean, I started using it at the bank as well. Like try, like, you know, I like desperately tried to find any kind of excuse to like use it here or there, but it just was clear to me, like, no, if I want to do this, um, like I just have to like make a real cut. So I quit my job and joined an early stage, uh, tech startup in Zurich where then built up the AI team over five years. Wow. Yeah. So yeah, we built various machine learning, uh, things for, for banks from like models for, for sales teams to identify which clients like which product to sell to them and with what reasons all the way to, we did a lot, a lot with bank transactions. One of the actually most fun projects for me was we had an, an NLP model that would take the booking text of a transaction, like a credit card transaction and pretty fired. Yeah. Because it had all of these, you know, like numbers in there and abbreviations and whatnot. And sometimes you look at it like, what, what is this? And it was just, you know, it would just change it to, I don't know, CVS. Yeah.swyx [00:15:15]: Yeah. But I mean, would you have hallucinations?Kevin [00:15:17]: No, no, no. The way that everything was set up, it wasn't like, it wasn't yet fully end to end generative, uh, neural network as what you would use today. Okay.swyx [00:15:30]: Awesome. And then when did you go like full time on Snips? Yeah.Kevin [00:15:33]: So basically that was, that was afterwards. I mean, how that started was the friend of mine who got me into machine learning, uh, him and I, uh, like he also got me interested into startups. He's had a big impact on my life. And the two of us were just a jam on, on like ideas for startups every now and then. And his background was also in AI data science. And we had a couple of ideas, but given that we were working full times, we were thinking about, uh, so we participated in Hack Zurich. That's, uh, Europe's biggest hackathon, um, or at least was at the time. And we said, Hey, this is just a weekend. Let's just try out an idea, like hack something together and see how it works. And the idea was that we'd be able to search through podcast episodes, like within a podcast. Yeah. So we did that. Long story short, uh, we managed to do it like to build something that we realized, Hey, this actually works. You can, you can find things again in podcasts. We had like a natural language search and we pitched it on stage. And we actually won the hackathon, which was cool. I mean, we, we also, I think we had a good, um, like a good, good pitch or a good example. So we, we used the famous Joe Rogan episode with Elon Musk where Elon Musk smokes a joint. Okay. Um, it's like a two and a half hour episode. So we were on stage and then we just searched for like smoking weed and it would find that exact moment. It will play it. And it just like, come on with Elon Musk, just like smoking. Oh, so it was video as well? No, it was actually completely based on audio. But we did have the video for the presentation. Yeah. Which had a, had of course an amazing effect. Yeah. Like this gave us a lot of activation energy, but it wasn't actually about winning the hackathon. Yeah. But the interesting thing that happened was after we pitched on stage, several of the other participants, like a lot of them came up to us and started saying like, Hey, can I use this? Like I have this issue. And like some also came up and told us about other problems that they have, like very adjacent to this with a podcast. Where's like, like this. Like, could, could I use this for that as well? And that was basically the, the moment where I realized, Hey, it's actually not just us who are having these issues with, with podcasts and getting to the, making the most out of this knowledge. Yeah. The other people. Yeah. That was now, I guess like four years ago or something like that. And then, yeah, we decided to quit our jobs and start, start this whole snip thing. Yeah. How big is the team now? We're just four people. Yeah. Just four people. Yeah. Like four. We're all technical. Yeah. Basically two on the, the backend side. So one of my co-founders is this person who got me into machine learning and startups. And we won the hackathon together. So we have two people for the backend side with the AI and all of the other backend things. And two for the front end side, building the app.swyx [00:18:18]: Which is mostly Android and iOS. Yeah.Kevin [00:18:21]: It's iOS and Android. We also have a watch app for, for Apple, but yeah, it's mostly iOS. Yeah.swyx [00:18:27]: The watch thing, it was very funny because in the, in the Latent Space discord, you know, most of us have been slowly adopting snips. You came to me like a year ago and you introduced snip to me. I was like, I don't know. I'm, you know, I'm very sticky to overcast and then slowly we switch. Why watch?Kevin [00:18:43]: So it goes back to a lot of our users, they do something else while, while listening to a podcast, right? Yeah. And one of the, us giving them the ability to then capture this knowledge, even though they're doing something else at the same time is one of the killer features. Yeah. Maybe I can actually, maybe at some point I should maybe give a bit more of an overview of what the, all of the features that we have. Sure. So this is one of the killer features and for one big use case that people use this for is for running. Yeah. So if you're a big runner, a big jogger or cycling, like really, really cycling competitively and a lot of the people, they don't want to take their phone with them when they go running. So you load everything onto the watch. So you can download episodes. I mean, if you, if you have an Apple watch that has internet access, like with a SIM card, you can also directly stream. That's also possible. Yeah. So of course it's a, it's basically very limited to just listening and snipping. And then you can see all of your snips later on your phone. Let me tell you this error I just got.swyx [00:19:47]: Error playing episode. Substack, the host of this podcast, does not allow this podcast to be played on an Apple watch. Yeah.Kevin [00:19:52]: That's a very beautiful thing. So we found out that all of the podcasts hosted on Substack, you cannot play them on an Apple watch. Why is this restriction? What? Like, don't ask me. We try to reach out to Substack. We try to reach out to some of the bigger podcasters who are hosting the podcast on Substack to also let them know. Substack doesn't seem to care. This is not specific to our app. You can also check out the Apple podcast app. Yeah. It's the same problem. It's just that we actually have identified it. And we tell the user what's going on.swyx [00:20:25]: I would say we host our podcast on Substack, but they're not very serious about their podcasting tools. I've told them before, I've been very upfront with them. So I don't feel like I'm shitting on them in any way. And it's kind of sad because otherwise it's a perfect creative platform. But the way that they treat podcasting as an afterthought, I think it's really disappointing.Kevin [00:20:45]: Maybe given that you mentioned all these features, maybe I can give a bit of a better overview of the features that we have. Let's do that. Let's do that. So I think we're mostly in our minds. Maybe for some of the listeners.swyx [00:20:55]: I mean, I'll tell you my version. Yeah. They can correct me, right? So first of all, I think the main job is for it to be a podcast listening app. It should be basically a complete superset of what you normally get on Overcast or Apple Podcasts or anything like that. You pull your show list from ListenNotes. How do you find shows? You've got to type in anything and you find them, right?Kevin [00:21:18]: Yeah. We have a search engine that is powered by ListenNotes. Yeah. But I mean, in the meantime, we have a huge database of like 99% of all podcasts out there ourselves. Yeah.swyx [00:21:27]: What I noticed, the default experience is you do not auto-download shows. And that's one very big difference for you guys versus other apps, where like, you know, if I'm subscribed to a thing, it auto-downloads and I already have the MP3 downloaded overnight. For me, I have to actively put it onto my queue, then it auto-downloads. And actually, I initially didn't like that. I think I maybe told you that I was like, oh, it's like a feature that I don't like. Like, because it means that I have to choose to listen to it in order to download and not to... It's like opt-in. There's a difference between opt-in and opt-out. So I opt-in to every episode that I listen to. And then, like, you know, you open it and depends on whether or not you have the AI stuff enabled. But the default experience is no AI stuff enabled. You can listen to it. You can see the snips, the number of snips and where people snip during the episode, which roughly correlates to interest level. And obviously, you can snip there. I think that's the default experience. I think snipping is really cool. Like, I use it to share a lot on Discord. I think we have tons and tons of just people sharing snips and stuff. Tweeting stuff is also like a nice, pleasant experience. But like the real features come when you actually turn on the AI stuff. And so the reason I got snipped, because I got fed up with Overcast not implementing any AI features at all. Instead, they spent two years rewriting their app to be a little bit faster. And I'm like, like, it's 2025. I should have a podcast that has transcripts that I can search. Very, very basic thing. Overcast will basically never have it.Kevin [00:22:49]: Yeah, I think that was a good, like, basic overview. Maybe I can add a bit to it with the AI features that we have. So one thing that we do every time a new podcast comes out, we transcribe the episode. We do speaker diarization. We identify the speaker names. Each guest, we extract a mini bio of the guest, try to find a picture of the guest online, add it. We break the podcast down into chapters, as in AI generated chapters. That one. That one's very handy. With a quick description per title and quick description per each chapter. We identify all books that get mentioned on a podcast. You can tell I don't use that one. It depends on the podcast. There are some podcasts where the guests often recommend like an amazing book. So later on, you can you can find that again.swyx [00:23:42]: So you literally search for the word book or I just read blah, blah, blah.Kevin [00:23:46]: No, I mean, it's all LLM based. Yeah. So basically, we have we have an LLM that goes through the entire transcript and identifies if a user mentions a book, then we use perplexity API together with various other LLM orchestration to go out there on the Internet, find everything that there is to know about the book, find the cover, find who or what the author is, get a quick description of it for the author. We then check on which other episodes the author appeared on.swyx [00:24:15]: Yeah, that is killer.Kevin [00:24:17]: Because that for me, if. If there's an interesting book, the first thing I do is I actually listen to a podcast episode with a with a writer because he usually gives a really great overview already on a podcast.swyx [00:24:28]: Sometimes the podcast is with the person as a guest. Sometimes his podcast is about the person without him there. Do you pick up both?Kevin [00:24:37]: So, yes, we pick up both in like our latest models. But actually what we show you in the app, the goal is to currently only show you the guest to separate that. In the future, we want to show the other things more.swyx [00:24:47]: For what it's worth, I don't mind. Yeah, I don't think like if I like if I like somebody, I'll just learn about them regardless of whether they're there or not.Kevin [00:24:55]: Yeah, I mean, yes and no. We we we have seen there are some personalities where this can break down. So, for example, the first version that we released with this feature, it picked up much more often a person, even if it was not a guest. Yeah. For example, the best examples for me is Sam Altman and Elon Musk. Like they're just mentioned on every second podcast and it has like they're not on there. And if you're interested in it, you can go to Elon Musk. And actually like learning from them. Yeah, I see. And yeah, we updated our our algorithms, improved that a lot. And now it's gotten much better to only pick it up if they're a guest. And yeah, so this this is maybe to come back to the features, two more important features like we have the ability to chat with an episode. Yes. Of course, you can do the old style of searching through a transcript with a keyword search. But I think for me, this is this is how you used to do search and extracting knowledge in the in the past. Old school. And the A.I. Web. Way is is basically an LLM. So you can ask the LLM, hey, when do they talk about topic X? If you're interested in only a certain part of the episode, you can ask them for four to give a quick overview of the episode. Key takeaways afterwards also to create a note for you. So this is really like very open, open ended. And yeah. And then finally, the snipping feature that we mentioned just to reiterate. Yeah. I mean, here the the feature is that whenever you hear an amazing idea, you can trip. It's up your headphones or click a button in the app and the A.I. summarizes the insight you just heard and saves that together with the original transcript and audio in your knowledge library. I also noticed that you you skip dynamic content. So dynamic content, we do not skip it automatically. Oh, sorry. You detect. But we detect it. Yeah. I mean, that's one of the thing that most people don't don't actually know that like the way that ads get inserted into podcasts or into most podcasts is actually that every time you listen. To a podcast, you actually get access to a different audio file and on the server, a different ad is inserted into the MP3 file automatically. Yeah. Based on IP. Exactly. And that's what that means is if we transcribe an episode and have a transcript with timestamps like words, word specific timestamps, if you suddenly get a different audio file, like the whole time says I messed up and that's like a huge issue. And for that, we actually had to build another algorithm that would dynamically on the floor. I re sync the audio that you're listening to the transcript that we have. Yeah. Which is a fascinating problem in and of itself.swyx [00:27:24]: You sync by matching up the sound waves? Or like, or do you sync by matching up words like you basically do partial transcription?Kevin [00:27:33]: We are not matching up words. It's happening on the basically a bytes level matching. Yeah. Okay.swyx [00:27:40]: It relies on this. It relies on the exact match at some point.Kevin [00:27:46]: So it's actually. We're actually not doing exact matches, but we're doing fuzzy matches to identify the moment. It's basically, we basically built Shazam for podcasts. Just as a little side project to solve this issue.swyx [00:28:02]: Actually, fun fact, apparently the Shazam algorithm is open. They published the paper, it's talked about it. I haven't really dived into the paper. I thought it was kind of interesting that basically no one else has built Shazam.Kevin [00:28:16]: Yeah, I mean, well, the one thing is the algorithm. If you now talk about Shazam, the other thing is also having the database behind it and having the user mindset that if they have this problem, they come to you, right?swyx [00:28:29]: Yeah, I'm very interested in the tech stack. There's a big data pipeline. Could you share what is the tech stack?Kevin [00:28:35]: What are the most interesting or challenging pieces of it? So the general tech stack is our entire backend is, or 90% of our backend is written in Python. Okay. Hosting everything on Google Cloud Platform. And our front end is written with, well, we're using the Flutter framework. So it's written in Dart and then compiled natively. So we have one code base that handles both Android and iOS. You think that was a good decision? It's something that a lot of people are exploring. So up until now, yes. Okay. Look, it has its pros and cons. Some of the, you know, for example, earlier, I mentioned we have a Apple Watch app. Yeah. I mean, there's no Flutter for that, right? So that you build native. And then of course you have to sort of like sync these things together. I mean, I'm not the front end engineer, so I'm not just relaying this information, but our front end engineers are very happy with it. It's enabled us to be quite fast and be on both platforms from the very beginning. And when I talk with people and they hear that we are using Flutter, usually they think like, ah, it's not performant. It's super junk, janky and everything. And then they use it. They use our app and they're always super surprised. Or if they've already used our app, I couldn't tell them. They're like, what? Yeah. Um, so there is actually a lot that you can do with it.swyx [00:29:51]: The danger, the concern, there's a few concerns, right? One, it's Google. So when were they, when are they going to abandon it? Two, you know, they're optimized for Android first. So iOS is like a second, second thought, or like you can feel that it is not a native iOS app. Uh, but you guys put a lot of care into it. And then maybe three, from my point of view, JavaScript, as a JavaScript guy, React Native was supposed to be there. And I think that it hasn't really fulfilled that dream. Um, maybe Expo is trying to do that, but, um, again, it is not, does not feel as productive as Flutter. And I've, I spent a week on Flutter and dot, and I'm an investor in Flutter flow, which is the local, uh, Flutter, Flutter startup. That's doing very, very well. I think a lot of people are still Flutter skeptics. Yeah. Wait. So are you moving away from Flutter?Kevin [00:30:41]: I don't know. We don't have plans to do that. Yeah.swyx [00:30:43]: You're just saying about that. What? Yeah. Watch out. Okay. Let's go back to the stack.Kevin [00:30:47]: You know, that was just to give you a bit of an overview. I think the more interesting things are, of course, on the AI side. So we, like, as I mentioned earlier, when we started out, it was before chat GPT for the chat GPT moment before there was the GPT 3.5 turbo, uh, API. So in the beginning, we actually were running everything ourselves, open source models, try to fine tune them. They worked. There was us, but let's, let's be honest. They weren't. What was the sort of? Before Whisper, the transcription. Yeah, we were using wave to work like, um, there was a Google one, right? No, it was a Facebook, Facebook one. That was actually one of the papers. Like when that came out for me, that was one of the reasons why I said we, we should try something to start a startup in the audio space. For me, it was a bit like before that I had been following the NLP space, uh, quite closely. And as, as I mentioned earlier, we, we did some stuff at the startup as well, that I was working up. But before, and wave to work was the first paper that I had at least seen where the whole transformer architecture moved over to audio and bit more general way of saying it is like, it was the first time that I saw the transformer architecture being applied to continuous data instead of discrete tokens. Okay. And it worked amazingly. Ah, and like the transformer architecture plus self-supervised learning, like these two things moved over. And then for me, it was like, Hey, this is now going to take off similarly. It's the text space has taken off. And with these two things in place, even if some features that we want to build are not possible yet, they will be possible in the near term, uh, with this, uh, trajectory. So that was a little side, side note. No, it's in the meantime. Yeah. We're using whisper. We're still hosting some of the models ourselves. So for example, the whole transcription speaker diarization pipeline, uh,swyx [00:32:38]: You need it to be as cheap as possible.Kevin [00:32:40]: Yeah, exactly. I mean, we're doing this at scale where we have a lot of audio.swyx [00:32:44]: We're what numbers can you disclose? Like what, what are just to give people an idea because it's a lot. So we have more than a million podcasts that we've already processed when you say a million. So processing is basically, you have some kind of list of podcasts that you will auto process and others where a paying pay member can choose to press the button and transcribe it. Right. Is that the rough idea? Yeah, exactly.Kevin [00:33:08]: Yeah. And if, when you press that button or we also transcribe it. Yeah. So first we do the, we do the transcription. We do the. The, the speaker diarization. So basically you identify speech blocks that belong to the same speaker. This is then all orchestrated within, within LLM to identify which speech speech block belongs to which speaker together with, you know, we identify, as I mentioned earlier, we identify the guest name and the bio. So all of that comes together with an LLM to actually then assign assigned speaker names to, to each block. Yeah. And then most of the rest of the, the pipeline we've now used, we've now migrated to LLM. So we use mainly open AI, Google models, so the Gemini models and the open AI models, and we use some perplexity basically for those things where we need, where we need web search. Yeah. That's something I'm still hoping, especially open AI will also provide us an API. Oh, why? Well, basically for us as a consumer, the more providers there are.swyx [00:34:07]: The more downtime.Kevin [00:34:08]: The more competition and it will lead to better, better results. And, um, lower costs over time. I don't, I don't see perplexity as expensive. If you use the web search, the price is like $5 per a thousand queries. Okay. Which is affordable. But, uh, if you compare that to just a normal LLM call, um, it's, it's, uh, much more expensive. Have you tried Exa? We've, uh, looked into it, but we haven't really tried it. Um, I mean, we, we started with perplexity and, uh, it works, it works well. And if I remember. Correctly, Exa is also a bit more expensive.swyx [00:34:45]: I don't know. I don't know. They seem to focus on the search thing as a search API, whereas perplexity, maybe more consumer-y business that is higher, higher margin. Like I'll put it like perplexity is trying to be a product, Exa is trying to be infrastructure. Yeah. So that, that'll be my distinction there. And then the other thing I will mention is Google has a search grounding feature. Yeah. Which you, which you might want. Yeah.Kevin [00:35:07]: Yeah. We've, uh, we've also tried that out. Um, not as good. So we, we didn't, we didn't go into. Too much detail in like really comparing it, like quality wise, because we actually already had the perplexity one and it, and it's, and it's working. Yeah. Um, I think also there, the price is actually higher than perplexity. Yeah. Really? Yeah.swyx [00:35:26]: Google should cut their prices.Kevin [00:35:29]: Maybe it was the same price. I don't want to say something incorrect, but it wasn't cheaper. It wasn't like compelling. And then, then there was no reason to switch. So, I mean, maybe like in general, like for us, given that we do work with a lot of content, price is actually something that we do look at. Like for us, it's not just about taking the best model for every task, but it's really getting the best, like identifying what kind of intelligence level you need and then getting the best price for that to be able to really scale this and, and provide us, um, yeah, let our users use these features with as many podcasts as possible. Yeah.swyx [00:36:03]: I wanted to double, double click on diarization. Yeah. Uh, it's something that I don't think people do very well. So you know, I'm, I'm a, I'm a B user. I don't have it right now. And, and they were supposed to speak, but they dropped out last minute. Um, but, uh, we've had them on the podcast before and it's not great yet. Do you use just PI Anode, the default stuff, or do you find any tricks for diarization?Kevin [00:36:27]: So we do use the, the open source packages, but we have tweaked it a bit here and there. For example, if you mentioned the BAI guys, I actually listened to the podcast episode was super nice. Thank you. And when you started talking about speaker diarization, and I just have to think about, uh, I don't know.Kevin [00:36:49]: Is it possible? I don't know. I don't know. F**k this. Yeah, no, I don't know.Kevin [00:36:55]: Yeah. We are the best. This is a.swyx [00:37:07]: I don't know. This is the best. I don't know. This is the best. Yeah. Yeah. Yeah. You're doing good.Kevin [00:37:12]: So, so yeah. This is great. This is good. Yeah. No, so that of course helps us. Another thing that helps us is that we know certain structural aspects of the podcast. For example, how often does someone speak? Like if someone, like let's say there's a one hour episode and someone speaks for 30 seconds, that person is most probably not the guest and not the host. It's probably some ad, like some speaker from an ad. So we have like certain of these heuristics that we can use and we leverage to improve things. And in the past, we've also changed the clustering algorithm. So basically how a lot of the speaker diarization works is you basically create an embedding for the speech that's happening. And then you try to somehow cluster these embeddings and then find out this is all one speaker. This is all another speaker. And there we've also tweaked a couple of things where we again used heuristics that we could apply from knowing how podcasts function. And that's also actually why I was feeling so much with the BAI guys, because like all of these heuristics, like for them, it's probably almost impossible to use any heuristics because it can just be any situation, anything.Kevin [00:38:34]: So that's one thing that we do. Yeah, another thing is that we actually combine it with LLM. So the transcript, LLMs and the speaker diarization, like bringing all of these together to recalibrate some of the switching points. Like when does the speaker stop? When does the next one start?swyx [00:38:51]: The LLMs can add errors as well. You know, I wouldn't feel safe using them to be so precise.Kevin [00:38:58]: I mean, at the end of the day, like also just to not give a wrong impression, like the speaker diarization is also not perfect that we're doing, right? I basically don't really notice it.swyx [00:39:08]: Like I use it for search.Kevin [00:39:09]: Yeah, it's not perfect yet, but it's gotten quite good. Like, especially if you compare, if you look at some of the, like if you take a latest episode and you compare it to an episode that came out a year ago, we've improved it quite a bit.swyx [00:39:23]: Well, it's beautifully presented. Oh, I love that I can click on the transcript and it goes to the timestamp. So simple, but you know, it should exist. Yeah, I agree. I agree. So this, I'm loading a two hour episode of Detect Me Right Home, where there's a lot of different guests calling in and you've identified the guest name. And yeah, so these are all LLM based. Yeah, it's really nice.Kevin [00:39:49]: Yeah, like the speaker names.swyx [00:39:50]: I would say that, you know, obviously I'm a power user of all these tools. You have done a better job than Descript. Okay, wow. Descript is so much funding. They had their open AI invested in them and they still suck. So I don't know, like, you know, keep going. You're doing great. Yeah, thanks. Thanks.Kevin [00:40:12]: I mean, I would, I would say that, especially for anyone listening who's interested in building a consumer app with AI, I think the, like, especially if your background is in AI and you love working with AI and doing all of that, I think the most important thing is just to keep reminding yourself of what's actually the job to be done here. Like, what does actually the consumer want? Like, for example, you now were just delighted by the ability to click on this word and it jumps there. Yeah. Like, this is not, this is not rocket science. This is, like, you don't have to be, like, I don't know, Android Kapathi to come up with that and build that, right? And I think that's, that's something that's super important to keep in mind.swyx [00:40:52]: Yeah, yeah. Amazing. I mean, there's so many features, right? It's, it's so packed. There's quotes that you pick up. There's summarization. Oh, by the way, I'm going to use this as my official feature request. I want to customize what, how it's summarized. I want to, I want to have a custom prompt. Yeah. Because your summarization is good, but, you know, I have different preferences, right? Like, you know.Kevin [00:41:14]: So one thing that you can already do today, I completely get your feature request. And I think it just.swyx [00:41:18]: I'm sure people have asked it.Kevin [00:41:19]: I mean, maybe just in general as a, as a, how I see the future, you know, like in the future, I think all, everything will be personalized. Yeah, yeah. Like, not, this is not specific to us. Yeah. And today we're still in a, in a phase where the cost of LLMs, at least if you're working with, like, such long context windows. As us, I mean, there's a lot of tokens in, if you take an entire podcast, so you still have to take that cost into consideration. So if for every single user, we regenerate it entirely, it gets expensive. But in the future, this, you know, cost will continue to go down and then it will just be personalized. So that being said, you can already today, if you go to the player screen. Okay. And open up the chat. Yeah. You can go to the, to the chat. Yes. And just ask for a summary in your style.swyx [00:42:13]: Yeah. Okay. I mean, I, I listen to consume, you know? Yeah. Yeah. I, I've never really used this feature. I don't know. I think that's, that's me being a slow adopter. No, no. I mean, that's. It has, when does the conversation start? Okay.Kevin [00:42:26]: I mean, you can just type anything. I think what you're, what you're describing, I mean, maybe that is also an interesting topic to talk about. Yes. Where, like, basically I told you, like, look, we have this chat. You can just ask for it. Yeah. And this is, this is how ChatGPT works today. But if you're building a consumer app, you have to move beyond the chat box. People do not want to always type out what they want. So your feature request was, even though theoretically it's already possible, what you are actually asking for is, hey, I just want to open up the app and it should just be there in a nicely formatted way. Beautiful way such that I can read it or consume it without any issues. Interesting. And I think that's in general where a lot of the, the. Opportunities lie currently in the market. If you want to build a consumer app, taking the capability and the intelligence, but finding out what the actual user interface is the best way how a user can engage with this intelligence in a natural way.swyx [00:43:24]: Is this something I've been thinking about as kind of like AI that's not in your face? Because right now, you know, we like to say like, oh, use Notion has Notion AI. And we have the little thing there. And there's, or like some other. Any other platform has like the sparkle magic wand emoji, like that's our AI feature. Use this. And it's like really in your face. A lot of people don't like it. You know, it should just kind of become invisible, kind of like an invisible AI.Kevin [00:43:49]: 100%. I mean, the, the way I see it as AI is, is the electricity of, of the future. And like no one, like, like we don't talk about, I don't know, this, this microphone uses electricity, this phone, you don't think about it that way. It's just in there, right? It's not an electricity enabled product. No, it's just a product. Yeah. It will be the same with AI. I mean, now. It's still a, something that you use to market your product. I mean, we do, we do the same, right? Because it's still something that people realize, ah, they're doing something new, but at some point, no, it'll just be a podcast app and it will be normal that it has all of this AI in there.swyx [00:44:24]: I noticed you do something interesting in your chat where you source the timestamps. Yeah. Is that part of this prompt? Is there a separate pipeline that adds source sources?Kevin [00:44:33]: This is, uh, actually part of the prompt. Um, so this is all prompt engine. Engineering, um, uh, you should be able to click on it. Yeah, I clicked on it. Um, this is all prompt engineering with how to provide the, the context, you know, we, because we provide all of the transcript, how to provide the context and then, yeah, I get them all to respond in a correct way with a certain format and then rendering that on the front end. This is one of the examples where I would say it's so easy to create like a quick demo of this. I mean, you can just go to chat to be deep, paste this thing in and say like, yeah, do this. Okay. Like 15 minutes and you're done. Yeah. But getting this to like then production level that it actually works 99% of the time. Okay. This is then where, where the difference lies. Yeah. So, um, for this specific feature, like we actually also have like countless regexes that they're just there to correct certain things that the LLM is doing because it doesn't always adhere to the format correctly. And then it looks super ugly on the front end. So yeah, we have certain regexes that correct that. And maybe you'd ask like, why don't you use an LLM for that? Because that's sort of the, again, the AI native way, like who uses regexes anymore. But with the chat for user experience, it's very important that you have the streaming because otherwise you need to wait so long until your message has arrived. So we're streaming live the, like, just like ChatGPT, right? You get the answer and it's streaming the text. So if you're streaming the text and something is like incorrect. It's currently not easy to just like pipe, like stream this into another stream, stream this into another stream and get the stream back, which corrects it, that would be amazing. I don't know, maybe you can answer that. Do you know of any?swyx [00:46:19]: There's no API that does this. Yeah. Like you cannot stream in. If you own the models, you can, uh, you know, whatever token sequence has, has been emitted, start loading that into the next one. If you fully own the models, uh, I don't, it's probably not worth it. That's what you do. It's better. Yeah. I think. Yeah. Most engineers who are new to AI research and benchmarking actually don't know how much regexing there is that goes on in normal benchmarks. It's just like this ugly list of like a hundred different, you know, matches for some criteria that you're looking for. No, it's very cool. I think it's, it's, it's an example of like real world engineering. Yeah. Do you have a tooling that you're proud of that you've developed for yourself?Kevin [00:47:02]: Is it just a test script or is it, you know? I think it's a bit more, I guess the term that has come up is, uh, vibe coding, uh, vibe coding, some, no, sorry, that's actually something else in this case, but, uh, no, no, yes, um, vibe evals was a term that in one of the talks actually on, on, um, I think it might've been the first, the first or the first day at the conference, someone brought that up. Yeah. Uh, because yeah, a lot of the talks were about evals, right. Which is so important. And yeah, I think for us, it's a bit more vibe. Evals, you know, that's also part of, you know, being a startup, we can take risks, like we can take the cost of maybe sometimes it failing a little bit or being a little bit off and our users know that and they appreciate that in return, like we're moving fast and iterating and building, building amazing things, but you know, a Spotify or something like that, half of our features will probably be in a six month review through legal or I don't know what, uh, before they could sell them out.swyx [00:48:04]: Let's just say Spotify is not very good at podcasting. Um, I have a documented, uh, dislike for, for their podcast features, just overall, really, really well integrated any other like sort of LLM focused engineering challenges or problems that you, that you want to highlight.Kevin [00:48:20]: I think it's not unique to us, but it goes again in the direction of handling the uncertainty of LLMs. So for example, with last year, at the end of the year, we did sort of a snipped wrapped. And one of the things we thought it would be fun to, just to do something with, uh, with an LLM and something with the snips that, that a user has. And, uh, three, let's say unique LLM features were that we assigned a personality to you based on the, the snips that, that you have. It was, I mean, it was just all, I guess, a bit of a fun, playful way. I'm going to look up mine. I forgot mine already.swyx [00:48:57]: Um, yeah, I don't know whether it's actually still in the, in the, we all took screenshots of it.Kevin [00:49:01]: Ah, we posted it in the, in the discord. And the, the second one, it was, uh, we had a learning scorecard where we identified the topics that you snipped on the most, and you got like a little score for that. And the third one was a, a quote that stood out. And the quote is actually a very good example of where we would run that for user. And most of the time it was an interesting quote, but every now and then it was like a super boring quotes that you think like, like how, like, why did you select that? Like, come on for there. The solution was actually just to say, Hey, give me five. So it extracted five quotes as a candidate, and then we piped it into a different model as a judge, LLM as a judge, and there we use a, um, a much better model because with the, the initial model, again, as, as I mentioned also earlier, we do have to look at the, like the, the costs because it's like, we have so much text that goes into it. So we, there we use a bit more cheaper model, but then the judge can be like a really good model to then just choose one out of five. This is a practical example.swyx [00:50:03]: I can't find it. Bad search in discord. Yeah. Um, so, so you do recommend having a much smarter model as a judge, uh, and that works for you. Yeah. Yeah. Interesting. I think this year I'm very interested in LM as a judge being more developed as a concept, I think for things like, you know, snips, raps, like it's, it's fine. Like, you know, it's, it's, it's, it's entertaining. There's no right answer.Kevin [00:50:29]: I mean, we also have it. Um, we also use the same concept for our books feature where we identify the, the mention. Books. Yeah. Because there it's the same thing, like 90% of the time it, it works perfectly out of the box one shot and every now and then it just, uh, starts identifying books that were not really mentioned or that are not books or made, yeah, starting to make up books. And, uh, they are basically, we have the same thing of like another LLM challenging it. Um, yeah. And actually with the speakers, we do the same now that I think about it. Yeah. Um, so I'm, I think it's a, it's a great technique. Interesting.swyx [00:51:05]: You run a lot of calls.Kevin [00:51:07]: Yeah.swyx [00:51:08]: Okay. You know, you mentioned costs. You move from self hosting a lot of models to the, to the, you know, big lab models, open AI, uh, and Google, uh, non-topic.Kevin [00:51:18]: Um, no, we love Claude. Like in my opinion, Claude is the, the best one when it comes to the way it formulates things. The personality. Yeah. The personality. Okay. I actually really love it. But yeah, the cost is. It's still high.swyx [00:51:36]: So you cannot, you tried Haiku, but you're, you're like, you have to have Sonnet.Kevin [00:51:40]: Uh, like basically we like with Haiku, we haven't experimented too much. We obviously work a lot with 3.5 Sonnet. Uh, also, you know, coding. Yeah. For coding, like in cursor, just in general, also brainstorming. We use it a lot. Um, I think it's a great brainstorm partner, but yeah, with, uh, with, with a lot of things that we've done done, we opted for different models.swyx [00:52:00]: What I'm trying to drive at is how much cheaper can you get if you go from cloud to cloud? Closed models to open models. And maybe it's like 0% cheaper, maybe it's 5% cheaper, or maybe it's like 50% cheaper. Do you have a sense?Kevin [00:52:13]: It's very difficult to, to judge that. I don't really have a sense, but I can, I can give you a couple of thoughts that have gone through our minds over the time, because obviously we do realize like, given that we, we have a couple of tasks where there are just so many tokens going in, um, at some point it will make sense to, to offload some of that. Uh, to an open source model, but going back to like, we're, we're a startup, right? Like we're not an AI lab or whatever, like for us, actually the most important thing is to iterate fast because we need to learn from our users, improve that. And yeah, just this velocity of this, these iterations. And for that, the closed models hosted by open AI, Google is, uh, and swapping, they're just unbeatable because you just, it's just an API call. Yeah. Um, so you don't need to worry about. Yeah. So much complexity behind that. So this is, I would say the biggest reason why we're not doing more in this space, but there are other thoughts, uh, also for the future. Like I see two different, like we basically have two different usage patterns of LLMs where one is this, this pre-processing of a podcast episode, like this initial processing, like the transcription, speaker diarization, chapterization. We do that once. And this, this usage pattern it's, it's quite predictable. Because we know how many podcasts get released when, um, so we can sort of have a certain capacity and we can, we, we're running that 24 seven, it's one big queue running 24 seven.swyx [00:53:44]: What's the queue job runner? Uh, is it a Django, just like the Python one?Kevin [00:53:49]: No, that, that's just our own, like our database and the backend talking to the database, picking up jobs, finding it back. I'm just curious in orchestration and queues. I mean, we, we of course have like, uh, a lot of other orchestration where we're, we're, where we use, uh, the Google pub sub, uh, thing, but okay. So we have this, this, this usage pattern of like very predictable, uh, usage, and we can max out the, the usage. And then there's this other pattern where it's, for example, the snippet where it's like a user, it's a user action that triggers an LLM call and it has to be real time. And there can be moments where it's by usage and there can be moments when there's very little usage for that. There. So that's, that's basically where these LLM API calls are just perfect because you don't need to worry about scaling this up, scaling this down, um, handling, handling these issues. Serverless versus serverful.swyx [00:54:44]: Yeah, exactly. Okay.Kevin [00:54:45]: Like I see them a bit, like I see open AI and all of these other providers, I see them a bit as the, like as the Amazon, sorry, AWS of, of AI. So it's a bit similar how like back before AWS, you would have to have your, your servers and buy new servers or get rid of servers. And then with AWS, it just became so much easier to just ramp stuff up and down. Yeah. And this is like the taking it even, even, uh, to the next level for AI. Yeah.swyx [00:55:18]: I am a big believer in this. Basically it's, you know, intelligence on demand. Yeah. We're probably not using it enough in our daily lives to do things. I should, we should be able to spin up a hundred things at once and go through things and then, you know, stop. And I feel like we're still trying to figure out how to use LLMs in our lives effectively. Yeah. Yeah.Kevin [00:55:38]: 100%. I think that goes back to the whole, like that, that's for me where the big opportunity is for, if you want to do a startup, um, it's not about, but you can let the big labs handleswyx [00:55:48]: the challenge of more intelligence, but, um, it's the... Existing intelligence. How do you integrate? How do you actually incorporate it into your life? AI engineering. Okay, cool. Cool. Cool. Cool. Um, the one, one other thing I wanted to touch on was multimodality in frontier models. Dwarcash had a interesting application of Gemini recently where he just fed raw audio in and got diarized transcription out or timestamps out. And I think that will come. So basically what we're saying here is another wave of transformers eating things because right now models are pretty much single modality things. You know, you have whisper, you have a pipeline and everything. Yeah. You can't just say, Oh, no, no, no, we only fit like the raw, the raw files. Do you think that will be realistic for you? I 100% agree. Okay.Kevin [00:56:38]: Basically everything that we talked about earlier with like the speaker diarization and heuristics and everything, I completely agree. Like in the, in the future that would just be put everything into a big multimodal LLM. Okay. And it will output, uh, everything that you want. Yeah. So I've also experimented with that. Like just... With, with Gemini 2? With Gemini 2.0 Flash. Yeah. Just for fun. Yeah. Yeah. Because the big difference right now is still like the cost difference of doing speaker diarization this way or doing transcription this way is a huge difference to the pipeline that we've built up. Huh. Okay.swyx [00:57:15]: I need to figure out what, what that cost is because in my mind 2.0 Flash is so cheap. Yeah. But maybe not cheap enough for you.Kevin [00:57:23]: Uh, no, I mean, if you compare it to, yeah, whisper and speaker diarization and especially self-hosting it and... Yeah. Yeah. Yeah.swyx [00:57:30]: Yeah.Kevin [00:57:30]: Okay. But we will get there, right? Like this is just a question of time.swyx [00:57:33]: And, um, at some point, as soon as that happens, we'll be the first ones to switch. Yeah. Awesome. Anything else that you're like sort of eyeing on the horizon as like, we are thinking about this feature, we're thinking about incorporating this new functionality of AI into our, into our app? Yeah.Kevin [00:57:50]: I mean, we, there's so many areas that we're thinking about, like our challenge is a bit more... Choosing. Yeah. Choosing. Yeah. So, I mean, I think for me, like looking into like the next couple of years, like the big areas that interest us a lot, basically four areas, like one is content. Um, right now it's, it's podcasts. I mean, you did mention, I think you mentioned like you can also upload audio books and YouTube videos. YouTube. I actually use the YouTube one a fair amount. But in the future, we, we want to also have audio books natively in the app. And, uh, we want to enable AI generated content. Like just think of, take deep research and notebook analysis. Like put these together. That should be, that should be in our app. The second area is discovery. I think in general. Yeah.swyx [00:58:38]: I noticed that you don't have, so you

Slow news week so Phil took off to Flo Rida! It's just Tommy and Nicky this week. They do chat this weeks figure news, they talk Wrestlemania figure reveal predictions, and with Nicky heading to Big Event this weekend they decide on what Cesaro figure Nick should get signed. Of course they chat it up about Weekly Purchases too!Become a Patreon at patreon.com/figcave

Hocus Focus Mix met Blu Cantrell, Daddy Yankee, Format B, Au_Ra, CamelPhat, Esmee Denters, Fake Blood, Felix da housecat, Alexandra Burke & Flo Rida

01. Leonid Agutin - Ostrov02. IOWA - Mama 03. Misha Miller, Alex Velea - Bam Bam04. TROMAE - Alors Dans 2505. Don Omar & Lucenzo - Danza Kuduro06. CC CATCH - Heaven & Hell 2507. D.BILAN, MARI - It's My Life08. ARTIK ASTI - Ochen Ochen 2509. Yulianna Karaulova - Ty ne takoj10. SEREBRO - Ya tebya ne otdam 11. Noch 2512. Alan Walker, Ina Wroldsen – Barcelona13. Galvanize 2514. My Humps15. Love Is Gone16. Sky 2517. Lick18. Flo Rida ft. Ke$ha - Right Round20. Hey Mama Azkaban 21. Bob Sinclar ft Dollarman, Big Ali & Makedah - Rock This Party22. Technologic Groove23. Lykke Li - I Follow Rivers24. Reflex - Non Stop25. Sigma Boy26. Bearwolf - GODZILLA27. Maks Korzh - Shantazh28. Goluboi Wagon29. Jah Khalib - Protivoyadie

Send us a textMeet Mabel--Marketing Director for Small Food Group, a collection of restaurants run by Michelin and James Beard-recognized Chef Sean "Sonny" Nguyen; three of which are in Audubon Park's East End Market. We discuss their two newest restaurants--Rion's Ocean Room and Gyukatsu Rose; along with Domu's appearance on a the “Real Orlando” episode of Netflix's ‘Somebody Feed Phil'. After leaving New York City for better weather in Orlando, Mabel worked with the Orlando Museum of Art prior to joining the Small Food Group team. Her roots with Bento Group, along with her longstanding friendship with Sonny, brought her to our neighborhood and we're so grateful for all that she and her team does!https://www.instagram.com/smallfoodgrouphttps://linktr.ee/helloapgdpod

Bears wasted a whole year of Caleb Williams, Ant Herron talks Chiefs' run game issues & Flo Rida is coming to a White Sox game (Hour 2) full 2610 Fri, 07 Mar 2025 21:14:10 +0000 0lWLQcDd5rPuUQBsFg2wfoH5XeE2rhoM sports Spiegel & Holmes Show sports Bears wasted a whole year of Caleb Williams, Ant Herron talks Chiefs' run game issues & Flo Rida is coming to a White Sox game (Hour 2) Matt Spiegel and Laurence Holmes bring you Chicago sports talk with great opinions, guests and fun. Join Spiegel and Holmes as they discuss the Bears, Blackhawks, Bulls, Cubs and White Sox and delve into the biggest sports storylines of the day. Recurring guests include Bears cornerback Jaylon Johnson, former Bears coach Dave Wannstedt, former Bears center Olin Kreutz, Cubs manager Craig Counsell, Cubs second baseman Nico Hoerner and MLB Network personality Jon Morosi. Catch the show live Monday through Friday (2 p.m. - 6 p.m. CT) on 670 The Score, the exclusive audio home of the Cubs and the Bulls, or on the Audacy app. 2024 © 2021 Audacy, Inc. Sports

We're back, and we're causing chaos—again! Dale's very strong opinions on group fajita orders have officially ignited a social media war (even Chili's got involved). Should you have to ask permission before ordering the sizzling dish of doom? The results may shock you. Then, we break down the most controversial Super Bowl halftime show in years—was Kendrick Lamar's performance a masterpiece or a misunderstood mess? And why is Taylor Swift getting booed just for existing?!But wait—there's more! Dale finally binge-watches Secret Lives of Mormon Wives and discovers their shocking soda obsession, we declare war over Smarties (candy gold or trash?), and Florida snowbirds are officially on notice. From eyebrow emergencies to unexpected reality TV obsessions, this episode is unfiltered, hilarious, and 100% unhinged!Contact Rachel Sobel:Email: rachel@whineandcheezits.comWebsite: www.whineandcheezits.comFacebook:  Whine and Cheez - its by Rachel Sobel   Instagram: @whineandcheezitsTikTok: @rachel.sobel.writesContact Dale Mclean:Email: dance715@aol.comWebsite: dalethehost.comInstagram: @UptownDale

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01. Hardwell, Chris Jones - Young Again (Record Mix) 02. Avicii - Silhouettes (Record Mix) 03. David Guetta, Showtek - Your Love.. (Record Mix) 04. Zedd, Matthew Koma, Miriam Bryant - Find You (Record Mix) 05. The Naked & The Famous - Young Blood (Record Mix) 06. Ivan Gough, Feenixpawl, Georgi Kay, Axwell - In My Mind (Record Mix) 07. Nicky Romero, Vicetone, When We Are Wild - Let Me Feel (Record Mix) 08. Klaas - Flight To Paris (Record Mix) 09. Abel Ramos, Albert Neve - Flat Beat (Record Mix) 10. Kid Cudi, Crookers - Day'n'Nite (Record Mix) 11. Calvin Harris, Camelphat - I'm Not Alone (Record Mix) 12. Flo Rida, Pitbull - Can't Believe It (Record Mix) 13. Jasper Forks - River Flows In You (Record Mix) 14. Avener, Dj Nil - Fade Out Lines (Record Mix) 15. Oliver Heldens, Shaun Frank, Delaney Jane - Shades of Grey (Record Mix) 16. Bastille, Audien - Pompeii (Record Mix) 17. Serge Devant - Addicted (Record Mix) 18. Olav Basoski, Mitchie One - Waterman (Record Mix) 19. Ph Electro - Englishman (Record Mix) 20. Filterfunk - SOS (Message In A Bottle) (Record Mix) 21. Azealia Banks, Lazy Jay - 212 (Record Mix) 22. Fedde Le Grand - So Much Love (Record Mix) 23. Dada Life - Rolling Stones T-Shirt (Record Mix) 24. Bob Sinclar - Rock This Party (Record Mix) 25. Blasterjaxx & Bd - Titan (Record Mix) 26. Kygo, Conrad, Bassanova - Firestone (Record Mix) 27. Kygo, Conrad, Bassanova - Firestone (Record Mix) 28. Don Diablo, Maluca - My Window (Record Mix) 29. Martin Solveig - Hello (Record Mix) 30. Bassjackers, Kshmr, Sirah - Memories (Record Mix) 31. Quintino, Kenneth G - Blowfish (Record Mix) 32. Deadmau5 - Professional Griefers (Record mix) 33. Crystal Lake, Headhunterz - Say Goodbye (Record Mix) 34. Tujamo, Danny Avila - Cream (Record Mix) 35. Dimitri Vegas, Like Mike, Vinai - Louder (Record Mix) 36. JAY HARDWAY - Electric Elephants (Record Mix) 37. LOST FREQUENCIES/DIMARO - Are You with Me (Record Mix) 38. PENDULUM - Blood Sugar (Record Mix)

 This episode interviews Laura Sherman, VP of operations for Guest Services, a company managing food and lodging in national parks since 1917. Sherman discusses the company's journey towards sustainability, driven by their partnership with the National Park Service and a growing awareness of climate change, focusing on the Flamingo Lodge in the Everglades, which was rebuilt using shipping containers to minimize its impact. The conversation touches on the challenges and rewards of sustainable practices, emphasizing the long-term benefits and the need for both strategic planning and small, manageable steps for other companies to transition. The podcast aims to inspire listeners to adopt sustainable solutions for both environmental and economic benefits, highlighting that this is not a trend but an industry shift. Key Takeaways: Guest Services' Historical Roots in Sustainability:Guest Services was founded in 1917 and evolved from a food service provider for soldiers to managing contracts in national and state parks. Their involvement with the National Park Service 30-40 years ago instilled a commitment to conservation and preservation.The Flamingo Lodge: A Model for Sustainable Accommodation:Located in Everglades National Park, the lodge was rebuilt after being destroyed by hurricanes.It's constructed from elevated shipping containers to minimize environmental impact and provide resilience against future storms. The lodge highlights the importance of stewardship in protecting fragile ecosystems like the Everglades.Offers glamping options alongside traditional camping and RV spots.Provides educational opportunities through partnerships with park rangers and interpretive programs.Benefits of Sustainable Practices:Attracts environmentally conscious guests who favor properties with sustainable initiatives.Improves operational efficiencies and reduces long-term operating costs.Prepares businesses for increasing regulatory compliance related to environmental protection.Future Trends in Sustainable Hospitality:The industry will move forward as people adapt.People moving towards energy efficiencies using geothermal heating systems.Getting rid of styrofoam, plastics, and straws. *Regulatory compliance will be evident.The industry is moving towards bulk amenities. *Colorado has eliminated single use plastics.Quote: “You've got to set your goals. You've got to set that path and that journey that you want to follow. Because if you just start off and go blindly, it's going to backfire. How do you anticipate getting there and work towards that goal?” 

In hour two, Hoch and Crowder discuss words that don't rhyme but flow together, and Flo Rida has a strange way of trying to rhyme Wisconsin. In Cat Talk Hoch reads the prop bet for the USA vs Canada in the 4 Nations Finals tomorrow night in Boston. Also, have you ever ordered something with double ginger or somebody that deconstructs their food? We find out Jimmy has been to a hibachi restaurant and what he orders there. Tyler Herro of the future with the Heat without Jimmy Butler and if there is growth. Hoch tells us about his trip to Bud's Chicken & Seafood. Peter Berger a Miami firefighter with COPD who has been honored by the American Lung Association joins the show to talk about his charity event Fight For Air Climb Miami on March 9 at Loan Depot Park to donate go to climbmiami.org.

This episode of the Someone You Should Know Podcast features a musician who has spent decades creating and sharing music with purpose. For 20 years, he served as a Pastor and Youth Minister in the Presbyterian Church, always guided by a simple but powerful goal: to craft music that welcomes all, respects different perspectives, and delivers a message of hope. His latest album, Shades of Light, debuted on January 24th, and it's a testament to his mission—filled with heartfelt lyrics, uplifting melodies, and a spirit of inclusivity. We'll showcase some incredible tracks from the album, so tune in for an inspiring conversation and great music. Don't miss it!  He's Ken Holt and he's Someone You Should Know. Click here to buy the Rik Anthony a cold one.Show Links:Click here to go to Ken's WebsiteClick here to go to Ken's  FacebookClick here to go to Ken's InstagramClick here to go to Ken's YouTube ChannelClick here to go to Ken's Spotify pageClick here to check out Ken's band The PromiseAll music used with permission from the artistSomeone You Should Know 2025 // CatGotYourTongueStudios 2025Feedback: Send us a text.How to Contact Us:Official Website: https://Someoneyoushouldknowpodcast.comGmail: Someoneyoushouldknowpodcast@gmail.comTwitter: @RIKANTHONY1Facebook: https://www.facebook.com/rikanthonyInstagram: https://www.instagram.com/someoneyoushouldknowpodcast/LinkedIn: https://www.linkedin.com/in/rik-anthony2019/TikTok: @SomeoneYouShouldKnow2023YouTube: https://www.youtube.com/@someoneyoushouldknowpodcastThank you for listening!Theme music "Welcome to the Show" by Kevin MacLeod was used per the standard license agreement.

Top 40 Remixes to power you through your workout on this weeks episode of Funk Factory Radio with Tomas Tomas1 | Billie Eilish | BIRDS OF A FEATHER (Cosmic Dawn Extended Remix) 2 | Chappell Roan | Good Luck, Babe! (DJ Dark Remix)3 | Tate McRae | 2 Hands (Don Diablo Extended Mix) 4 | David Guetta, Alphaville & Ava Max | Forever Young (Don Diablo Remix)5 | Rihanna | Where Have You Been (2Crimes Remix)6 | Teddy Swims | Bad Dreams (Kaymata Remix)7 | Ace Of Base | All That She Wants (Esox Remix)8 | Taio Cruz | Hangover (Pete Summers & Kareem Remix)9 | Kevin Rudolf x BVRNOUT | Let It Rock10 | Pitbull & Bon Jovi | Now Or Never 11 | Sabrina Carpenter | Taste (Finlay C Remix)12 | Flo Rida x DJibouti x Kilhoffer | Low (DJibouti & Kilhoffer Remix) 13 | Nelly vs. Marshall Jefferson | Hot In Herre vs. Move Your Body (LXRENZ Remix)14 | The Pussycat Dolls | Buttons (LOOZBONE Remix)15 | ROSÉ & Bruno Mars | APT. (WIN WIN Private Mix)16 | Kesha | Die Young (TAIGA Remix)17 | Deorro & Chris Brown | Five More Hours (Mave & Cody Dunstall Remix)18 | Jennifer Lopez feat. Pitbull | On The Floor (Tiger Toast Remix)19 | David Guetta feat. Sia | Titanium (ASUNDER Remix)20 | Drake | Hotline Bling (Kicksave Disco Remix) (Clean)21 | Sabrina Carpenter | Espresso (Sgt Slick's Discotizer ReCut)

This week, we're taking you on a hilarious and heartfelt ride through the chaos of modern life. From teenagers freaking out over TikTok's sudden disappearance to the unbelievable YouTuber adoption scandal that left us outraged, we're diving into the stories you'll be thinking about long after you hit play.We also discovered Florida's Supermarket Sweetheart, Publix, is getting into the club biz.: Clublix is happening and we don't know how to feel about it. Plus, you'll hear about ski trip mishaps, Brightline encounters, and the ultimate guide to avoiding Gen Z's photo critiques. It's the kind of episode that feels like a conversation with friends—full of laughs, shocks, and moments that make you say, “Wait, what?!”Contact Rachel Sobel:Email: rachel@whineandcheezits.comWebsite: www.whineandcheezits.comFacebook:  Whine and Cheez - its by Rachel Sobel   Instagram: @whineandcheezitsTikTok: @rachel.sobel.writesContact Dale Mclean:Email: dance715@aol.comWebsite: dalethehost.comInstagram: @UptownDale

01. David Guetta - One Love (Record Mix) 02. Dj Antoine, Beat Shakers - Ma Cherie (Record Mix) 03. Tiesto - Red Lights (Record Mix) 04. Will.I.Am, Britney Spears - Scream Shout (Record Mix) 05. Romero, Nervo - Like Home (Record Mix) 06. Afrojack, Jewelz & Sparks - One More Day (Record Mix) 07. Junior Caldera, Sophie Ellis-Bextor - Can't Fight This Feeling (Record Mix) 08. Rodrigezz, Rene - We Let It Burn (Record Mix) 09. Will.I.Am & Ss - Better Than Yesterday (Record Mix) 10. Sander Van Doorn, Martin Garrix, Dvbbs - Gold Skies (Record Mix) 11. Arno Cost - Cyan (Record Mix) 12. Nicky Romero - Toulouse (Record Mix) 13. Eric Prydz, Wildvibes - Pjanoo (Record Mix) 14. Diplo, Sleepy Tom - Be Right There (Record Mix) 15. Deadmau5, Gartner - Animal Rights (Record Mix) 16. Antonio Giacca - Going Crazy (Record Mix) 17. Azealia Banks, Lazy Jay - 212 (Record Mix) 18. Tim Berg - Seek Bromance (Record Mix) 19. Lmfao - Sexy & I Know It (Record Mix) 20. Filterfunk - SOS (Message In A Bottle) (Record Mix) 21. Martin Solveig - Madan (Record Mix) 22. Bastille, Audien - Pompeii (Record Mix) 23. Flo Rida, Pitbull - Can't Believe It (Record Mix) 24. Duke Dumont - Won't Look Back (Record Mix) 25. Sidney Samson - Riverside (Record Mix) 26. Serge Devant - Take Me With You (Record Mix) 27. Chocolate Puma - Listen To The Talk (Record Mix) 28. Alesso, Onerepublic - If I Lose Myself (Record Mix) 29. Hardwell, Chris Jones - Young Again (Record Mix) 30. Deorro - For President (Record Mix) 31. Armin Van Buuren - We Are Here To Make Some Noise (Record Mix) 32. W&W - Bigfoot (Record Mix) 33. Tjr, Vinai, Bingo Players - Knock Your Generation (Record Mix) 34. Dada Life - Feed the Dada (Record Mix) 35. Dyro - Wolv 36. Andrew Bennett - Babylon 37. Nero, Sub Focus - Promises (Record Mix)

This week on Kankakee Podcast News, we cover the firing of Kankakee School District 111's assistant superintendent, updates on the Gotion lithium battery plant expansion in Manteno, and a key ruling in the Harris murder trial. Plus, Bradley 315 Fest announces its star-studded lineup, and Stefari Coffee House makes its return to Downtown Kankakee. Tune in for the latest local headlines! Send us a textSupport the show

Hello! Please feel free to text me here but you will have to type your first and last name, email and phone number in your message for me to be able to respond. I look forward to connecting! Sincerely, Dr. BawaWhat is squirting? Is it all just hype, or is there more to it? In this episode, I am breaking down everything you need to know about female ejaculation, from why it happens to the techniques that can help you make a woman squirt, I am here to help you explore one of the most fascinating and intimate aspects of female pleasure.Whether you are curious about experiencing it yourself or want to unlock this for your partner, I am answering all your burning questions and sharing tips to take your intimate experiences to a whole new level. This is one episode you will not want to miss.To schedule a virtual or in-office consultation with Dr. Bawa: https://www.bawamedical.com/contact/To learn more about Dr. Sex Fairy supplements:https://shop.bawamedical.com/collections/supplements To watch Dr. Sex Fairy in video format: https://www.youtube.com/@drsexfairy To learn more about sexual wellness: https://www.bawamedical.com/sexual-health/ TikTok: https://www.tiktok.com/@drsexfairy Instagram: https://www.instagram.com/therealdrsexfairy/ Facebook: https://www.facebook.com/doctorsexfairy

This episode of Friends Without Benefits dives headfirst into life's quirkiest moments with Rachel and Dale leading the charge. They share hilarious listener confessions, from awkward encounters at weddings to navigating secret relationships and even the bizarre concept of a “listening affair.” The duo also highlights the exclusivity of Sea Ranch Lakes, South Florida's hidden gem, featuring private beach clubs, gated communities, and multimillion-dollar waterfront homes. Along the way, they debate pop culture trends, including the absurdity of a $6.4M banana art piece, and dive into spicy relationship dynamics, from dirty texts gone wrong to the controversy of discussing “body counts.” With its mix of humor, chaos, and unfiltered honesty, this episode is a rollercoaster of real talk and laughter.Contact Rachel Sobel:Email: rachel@whineandcheezits.comWebsite: www.whineandcheezits.comFacebook:  Whine and Cheez - its by Rachel Sobel   Instagram: @whineandcheezitsTikTok: @rachel.sobel.writesContact Dale Mclean:Email: dance715@aol.comWebsite: dalethehost.comInstagram: @UptownDale

Happy New Year! To start 2025 with the bang, take a listen to our newest mixing podcast. Our very own DJ Jon Divine curated some of the hottest remixes and new music for you to dance, chill or workout to. Enjoy!Tracklist:00:00:00 Cash Cash & Taylor Dayne - Tell It To My Heart (Intro Clean)00:02:53 Jason Derulo vs MK - In My Head x 17 (Adam b Edit) [Intro Clean]00:04:06 Travis Scott & Drake vs Kernkraft 400 & The Shooters - Sicko Zombie (DJ Roller Mash Up.) [Intro Clean]00:06:29 Flo Rida ft. David Guetta - Club Can't Handle Me - Ovano & Beatz Freq Remix00:08:59 Fisher & Arco x Calvin Harris & Dua Lipa - One Kiss (DJ Arman Aveiru 'Ocean' Edit) [Intro Clean]00:11:14 AC Slater vs Fisher - Bass Face x Losing It (BONZON Mashup) [Intro Clean]00:14:14 Icona Pop ft. Charli XCX - I Love It - Audiorokk Feel It Edit (Clean)00:16:43 Andruss x Sam Collins x Adam Port, Keinemusik, Stryv, Malachiii - PAPI x Move (Sebastian Bronk Mashup) [Intro Clean]00:19:13 The Wanted x Eric Prydz x Freejak - Glad You Came (Cream 'Pjanoo' Edit) [Intro Clean]00:21:41 Natasha Bedingfield x Henry Hacking x Spice Girls - These Words x Wannabe x Groove (Sebastian Bronk Mashup) [Intro Clean]00:23:27 Rihanna - Don't Stop The Music (Challeask Remix) [Intro Clean]00:25:12 Adele x DubVision - Set Fire To The Rain (Andrew Marks "I'll Be There" Edit) [Intro Clean]00:28:00 Princess Superstar vs Luke Alexander - Perfect x Move Your Feet (Tiger Toast Bootleg / Clean)00:31:12 LMFAO & Lil Jon vs Tujamo, NOME. & Charlie Ray - Shots (DJ OD Samirs Theme VIP Edit) Clean00:33:13 Alesso & Nate Smith - I Like It (Alesso & Sentinel Remix) [Intro Clean]00:36:12 Tiesto & Deorro Ft. Kesha - We R Who We R (David S Savage Mash Up) [Intro Clean]00:38:29 Jess Glynne vs. Sam Feldt, Thomas Nan - Hold My Hand (Kastra "Better" Edit) [Intro Clean]00:41:59 Outkast - The Way You Move (Henry Fong Remix) [Intro Clean]00:43:58 Dom Dolla - Girl$ (Clean) (Extended) (HD)00:47:19 Cajmere - Percolator (Alex Miura & E-Spin RMX / Short Edit)00:49:27 N.O.R.E. ft Nina Sky & Daddy Yankee - Oye Mi Canto (GioMetrik & Odaya Remix) (Clean)00:52:42 Afrojack & Steve Aoki vs GUZ - No Beef (JD Live Tech House Bootleg) Clean CK Cut00:53:55 Steve Aoki & Willy William ft. Sean Paul, El Alfa, Sfera Ebbasta & Play-N-Skillz - Mambo - DJcity Clap Intro

Send us a text  Walk the red carpet in glitz and glamour with Dipperz and Danity Kane! This week, Sarah and Lauren recount the sordid and scandalous story of the creation of one of the quintessential girl groups of the early 2000's. Appearing on the TV show Making the Band gave these young, talented and ambitious performers a chance at stardom, but at what cost? Danity Kane was active between 2005 and 2020 and included Aubrey O'Day, Dawn Richard, Shannon Bex, Wanita "D. Woods" Woodgett, and Aundrea Fimbres. FEATURING: a whole lot of Di**y hate, a surprising analysis of some favorite holiday songs, low-rise jeans and layered tank tops, a physiological discussion of Frosty the Snowman's "balls", linguistic implications in the song Low by Flo Rida, and a taste of the sparkling wit you need to launch you into the new year in style!  BONUS: poetry! Support the pod: www.patreon.com/dipperzEmail us! dipperzpod@gmailInstagram! @dipperz_podcast

Send us a textMeet Brittany--Owner of The Owl's Attic, Orlando's #1 vintage shop with locations in the East End Market and Audubon Park's east plaza on Corrine Drive. Since 2011, she and her husband, Augie, have been growing the business by curating a stylish collection of rare finds in clothing, accessories, home goods, and collectibles. When you visit their shop, prepare to be transported back in time.https://theowlsattic.comhttps://linktr.ee/helloapgdpod

01. Diplo, Sleepy Tom - Be Right There (Record Mix) 02. Alesso, Nico & Vinz, Deniz Koyu - I Wanna Know (Record Mix) 03. Zedd - Spectrum (Record Mix) 04. Avicii - Last Dance (Record Mix) 05. Chemical Brothers - Hey Boy Hey Girl (Record Mix) 06. Example - Wont Go Quietly (Record Mix) 07. Duck Sauce - Barbra Streisand (Record Mix) 08. Chris Brown, Benny Benassi - Beautiful People (Record Mix) 09. Calvin Harris, Ellie Goulding - I Need Your Love (Record Mix) 10. Far East Movement, Chew Fu - Like A G6 (Record Mix) 11. Oliver Heldens - Melody (Record Mix) 12. Chocolate Puma, Kris Kiss, Shystie Roya - Step Back (Get Down) (Record Mix) 13. Camille Jones, Fedde Le Grand - The Creeps (Record Mix) 14. Deadmau5 - Professional Griefers (Record mix) 15. Lmfao, Chuckie - Let the Bass Kick in Miami Bitch (Record Mix) 16. Armand Van Helden - I Want Your Soul (Record Mix) 17. Tiesto, Don Diablo - Chemicals (Record Mix) 18. Bassjackers, Luciana - Fireflies (Record Mix) 19. Flo Rida, Pitbull - Can't Believe It (Record Mix) 20. Sidney Samson - Riverside (Record Mix) 21. Azealia Banks, Lazy Jay - 212 (Record Mix) 22. Outwork - Elektro (Record Mix) 23. Armin Van Buuren - We Are Here To Make Some Noise (Record Mix) 24. Showteck, Mc Ambush - 90's By Nature (Record Mix) 25. Ton!C - Big Fat (Record Mix) 26. Dj Snake, Mercer, Jermaine Dupri - Let's Get Ill (Record Mix) 27. Moquai - Champs (Record Mix) 28. Martin Garrix, Brooks - Byte (Record Mix) 29. Dimitri Vegas, Like Mike, Ummet Ozcan - The Hum (Record Mix) 30. Nws - Flute (Record Mix) 31. Steve Angello - Knas (Record Mix) 32. Hardwell - Eclipse (Record Mix) 33. Kshmr, Marnik - Bazaar (Record Mix) 34. Dj Kuba, Ne!Tan - Party On! 35. Dj Kuba, Ne!Tan - Party On! 36. Tujamo, Plastik Funk - Dr Who 37. Prodigy - Omen (Record Mix)

Join Cindy Lawrence, Ann Griffith, and special guest Brian Trigalet as they hit the road to Lakeland, Florida, for a riveting conversation on the evolution of vehicle inspections. From the days of scribbled notes on greasy paper to cutting-edge video updates sent straight to your phone, this episode dives deep into how transparency, trust, and technology are transforming the auto repair experience. Laugh along as they recount quirky stories from the shop, explore the pros and cons of digital advancements, and debate whether kiosks and gadgets will ever replace the personal touch of a seasoned advisor. Tune in for insights, laughs, and a glimpse into the future of automotive care. Don't miss this joyride on "On The Drive"!Join our Journey:Share this episode with a friendClick the plus to follow us on your podcast app and get automatic downloads of each episodeRate and Review us on Apple Podcasts Email us at Cindy@OnTheDriveTraining.comLinkedIn:   Connect on LinkedinFacebook:  Join us on FacebookHost:Cindy Lawrence713.299.2435Cindy@OnTheDriveTraining.comAtYourServcie-Drive.comIf You Need Fixed Ops Training…You Need Cindy!

We Raid the Algorithm to listen to Ben Roethlisberger hype up the Steelers, a twist on Mariah Carey's All I Want for Christmas Is You, and a mashup of Low by Flo Rida and Little Drummer Boy.

What a journey it's been—from recording in bars with unexpected swinger encounters to lounging in a $14.5 million mansion on the water. In this laugh-out-loud episode, we reflect on how far we've come while tackling your wildest Instagram polls and confessions. Should you tell someone their partner's cheating? How often do you really change your toothbrush? And what's up with butter-stuffed dates being called “healthy”? Don't miss this step-up in our podcast glow-up—subscribe now and join the fun!Contact Rachel Sobel:Email: rachel@whineandcheezits.comWebsite: www.whineandcheezits.comFacebook:  Whine and Cheez - its by Rachel Sobel   Instagram: @whineandcheezitsTikTok: @rachel.sobel.writesContact Dale Mclean:Email: dance715@aol.comWebsite: dalethehost.comInstagram: @UptownDale

01. Example - Changed The Way You Kiss Me (Record Mix) 02. Tiesto, Hardwell - Zero 76 (Record Mix) 03. Zedd - Spectrum (Record Mix) 04. Faithless - Insomnia (Record Mix) 05. Diplo, Sleepy Tom - Be Right There (Record Mix) 06. Alesso, Nico & Vinz, Deniz Koyu - I Wanna Know (Record Mix) 07. Lmfao - Sexy & I Know It (Record Mix) 08. Matt Nash - Know My Love (Record Mix) 09. Moquai - Champs (Record Mix) 10. Sidney Samson - Riverside (Record Mix) 11. Bag Raiders - Shooting Stars (Record Mix) 12. Gadjo - So Many Times (Record Mix) 13. Duck Sauce - Big Bad Wolf (Record Mix) 14. Flo Rida, Pitbull - Can't Believe It (Record Mix) 15. Oliver Heldens, Shaun Frank, Delaney Jane - Shades Of Grey (Record Mix) 16. Azealia Banks, Lazy Jay - 212 (Record Mix) 17. Avicii - Street Dance (Record Mix) 18. Outwork - Elektro (Record Mix) 19. Icona Pop - I Love It (Record Mix) 20. Serge Devant - Take Me With You (Record Mix) 21. Axwell - Nobody Else (Record Mix) 22. Christopher S - Keep On Rockin' (Record Mix) 23. Fedde Le Grand - So Much Love (Record Mix) 24. Freaks, Vandalism - The Creeps (Get On The Dancefloor) (Record Mix) 25. Daft Pank - Around The World (Record Mix) 26. Alex Gaudino, Shena - Watch Out (Record Mix) 27. Dj Dimixer - Lamantine (Record Mix) 28. Junior Jack - Stupidisco (Record Mix) 29. Chocolate Puma, Kris Kiss, Shystie Roya - Step Back (Get Down) (Record Mix) 30. Camille Jones, Fedde Le Grand - The Creeps (Record Mix) 31. Armand Van Helden - I Want Your Soul (Record Mix) 32. Deadmau5 - Professional Griefers (Record Mix) 33. Bodyrox - Yeah Yeah (Record Mix) 34. Prodigy - Smack My Bitch Up (Record Mix)

Send us a textIn this episode, Joey Pinz talks with Adam Hartley about the latest strategies for marketing and sales in the Managed Service Provider (MSP) industry. Adam shares insights from his upcoming session on effective growth strategies for MSPs, emphasizing the importance of innovation and collaboration. They discuss ways MSPs can differentiate themselves in a competitive market by leveraging modern marketing techniques, client engagement, and relationship-building skills.

Cody & Andrew share all the things they're grateful for this year including THIS WEEK'S RELEASE OF WICKED, the Delta Sky Lounge, Sabrina Carpenter's bangs, Flo Rida on the Disney Channel, and Cooper Koch's full frontal scene!!! Check out our holiday deals!!! Skylight: Frame your memories... digitally! Get $20 off your purchase at SkylightFrame.com/petty Lume Deodorant: Wanna smell fresh? Get 15% off all products with code "Tactful" at LumeDeodorant.com Quince: Upgrade your wardrobe! Go to Quince.com/pettiness for free shipping on your order AND 365-day returns!

Ep 574 features Lindsey, a supervisor in the Employment Relations Unit at Cobb County 911 out of GA.  Sponsored by INdigital - Facebook | LinkedIn | Twitter | Web Episode topics – Lindsey's transition from EMS to fire rescue and then to police dispatch Differences in protocols and communication styles between fire, EMS, and police departments Intense relief and euphoria from successfully resolving challenging calls Memorable and unusual call scenarios, including 'Florida man' incidents and a call involving an emu If you have any comments or questions or would like to be a guest on the show, please email me at wttpodcast@gmail.com.