Podcasts about snowflakes

ETP Red River Valley Today with guests the RRVDSS - Eric talks to staff from the Red River Valley Down Syndrome Society and the Reach Center with an update from the Center and all about their forthcoming Snowflakes and Dimaonds Gala. 

En la última tertulia del año traemos Carles Reina (ElevenLabs) como responsable de go-to-market y, además, como inversor: comenta que ha hecho decenas de “tickets” y que acaba de levantar su propio fondo, Baobab Ventures.A partir de ahí, la conversación entra fuerte en el negocio de ElevenLabs: explican que construyen modelos de voz “naturales” y operan en ~70 idiomas, y que encima han montado productos de agentes, doblaje, transcripción, etc. Carles da cifras muy concretas de tracción (alrededor de 400 personas y más de 300M de facturación, alcanzados “hace unas semanas”) y describe un motor enterprise muy agresivo (hablan de 150–170 contratos al mes y de un día especialmente “loco” superando 14M en enterprise). También hablan de por qué siguen levantando rondas aun generando caja: señal al mercado, liquidez para empleados vía secundario, y capacidad de invertir/comprar (incluidas GPUs). En ese bloque bromean bastante con los múltiplos (el “33x” como estándar) y con la posible burbuja en el sector. Luego hablan del tema más “cultural” y polémico: el doblaje y los derechos de voz. Sale Masumi un actor de doblaje conocido en España (que es la voz de Harry Potter y Anakin, y su vínculo con el sindicato) y se discute la línea roja de “no entrenar modelos con nuestras voces” frente a usos consentidos. Carles cuenta casos prácticos en Hollywood donde actores ceden permiso para usar su propia voz en postproducción cuando no pueden grabar, y aparece la idea que vertebra todo el debate: poder ver una peli con “la misma voz del actor” en otro idioma (por ejemplo, el ideal de oír a la misma actriz hablando en catalán o castellano sin perder identidad), frente a la realidad del consumo en España (acostumbrados al doblaje) y la alternativa de VO con subtítulos. En “actualidad/noticias”, el bloque más largo gira alrededor de una supuesta ola de consolidación en streaming y medios: comentan una operación de Netflix con Warner (centrada en activos digitales tipo HBO/HBO Max) y, como contrapeso, una oferta de Paramount por “todo” (y el lío político/regulatorio alrededor del antitrust). Ahí meten nombres y contexto político: hablan de Donald Trump opinando públicamente, de la familia Ellison (Oracle) detrás de Paramount, de tensiones por contenidos/editoriales, y de cómo eso mueve preferencias y narrativas; incluso lo cruzan con TikTok como parte del “ruido” de esos días. A nivel de análisis, lo conectan con el choque entre “calidad premium” (HBO/Warner) y “volumen/variedad algorítmica” (Netflix/TikTok) y con el riesgo de que la consolidación reduzca competencia y, por tanto, incentive menos calidad. También mencionan otras “noticias” tech/IA del momento dentro de la tertulia: preguntan por un anuncio de OpenAI con Disney y si cambia algo en la relación (Carles dice que no), y en otro punto comentan como titular que Amazon “por fin” habría invertido fuerte en OpenAI y lo enlazan con la guerra de infraestructura (chips/TPUs vs Nvidia y el rol del cloud). Por último, se abre el foco a inversión y mercado: cuentan que ElevenLabs tiene un “venture” y que invierten desde balance, y aparecen conversaciones típicas de ciclo: comparan múltiplos (Databricks vs Snowflake), especulan con una posible “edad dorada” de salidas a bolsa y, ya en tono de anécdota, comentan que “hoy” alguien anunció una ronda de 200M a 6B (sin entrar demasiado en detalles, pero usándolo como termómetro del hype). Sigue a los "tertulianos" en Twitter:• Bernat Farrero: @bernatfarrero• Jordi Romero: @jordiromero• César Migueláñez: @heycesrSOBRE ITNIG

Peter Tchaikovsky - The Nutcracker: Waltz of the SnowflakesSlovak Radio Symphony OrchestraOndrej Lenard, conductorMore info about today's track: Naxos 8.550515Courtesy of Naxos of America Inc.SubscribeYou can subscribe to this podcast in Apple Podcasts, or by using the Daily Download podcast RSS feed.Purchase this recordingAmazon

Scotty827 is back with Tylar to chat about all that's new in the world of Clash!  With Town Hall 18 over a month out, it's time to weigh in on how we're finding it!  Plus, we talk what's new in war, Tylar's promotion, and the air pushing trick!  Tylar talks his experiences with the Royal Champions new Snowflake equipment and we discuss new LL and war strategies at TH 18!  We catch up about CWL, changing rosters, and how hard LL is these days!  All that and everything Clashy!

In this episode: We discuss fast food (as always!!!), the film It's A Wonderful Life, and we play Would You Rather WINTER EDITION! (We apologize for the late episode)Please take a minute to leave us a rating and review on your favorite podcast app! This helps us in a big way and gets us one step closer to completing our goal of being the most popular podcast on the planet!

Fluent Fiction - Mandarin Chinese: Warm Hearts and Snowflakes: A Dongzhi Festival Tale Find the full episode transcript, vocabulary words, and more:fluentfiction.com/zh/episode/2025-12-18-23-34-02-zh Story Transcript:Zh: 大雪纷飞的冬至节，孤儿院里虽然寒冷，却充满了节日的温暖。En: On a snowy Dongzhi Festival, the orphanage, though cold, was filled with holiday warmth.Zh: 魏，是这里的一名志愿者，和孩子们一起给孤儿院挂上了彩色的灯笼和剪纸。En: Wei, a volunteer there, hung up colorful lanterns and paper cuttings with the children.Zh: 他有一个悲伤的过去，但他用心温暖了这里的每一个孩子。En: He had a sorrowful past, but he warmed the heart of every child there.Zh: 亮，是孤儿院最小的孩子之一，勇敢却又不易亲近。En: Liang was one of the youngest children in the orphanage, brave yet not easy to get close to.Zh: 他总是装作无所谓，但魏知道，亮渴望有人关心。En: He always pretended not to care, but Wei knew that Liang longed for someone to care.Zh: 那天，孩子们在院子里堆雪人，突发意外，亮从滑梯上摔了下来。En: That day, the children were building snowmen in the yard when an accident happened, and Liang fell from the slide.Zh: 他攥着自己的膝盖，脸色苍白，咬着嘴唇不让自己哭出声。En: He clutched his knee, his face pale, biting his lip to keep from crying out.Zh: 魏见状，立刻跑了过去，稳定亮的情绪。En: Seeing this, Wei immediately ran over to calm Liang's emotions.Zh: 他检查了一下发现伤势不轻。En: He checked and found the injury was not light.Zh: 孤儿院这时人手紧缺，医生还要晚些才能赶来。En: At that time, the orphanage was short-handed, and the doctor would take a while to arrive.Zh: 魏心里很着急，他知道必须尽快做出决定，是叫外部救援，还是让员工尽力而为。En: Wei was very anxious; he knew he had to make a decision quickly, whether to call for external help or let the staff do their best.Zh: 魏看到亮痛苦的神情，意识到不能再迟疑了。En: Wei saw the pain on Liang's face and realized he could not hesitate any longer.Zh: 他决定打电话给附近的诊所，请求医生马上过来。En: He decided to call a nearby clinic, asking a doctor to come immediately.Zh: 时间过得很慢，终于，医生赶到了，给亮做了检查并包扎好伤口。En: Time passed slowly, and finally, the doctor arrived, examined Liang, and bandaged his wound.Zh: 亮的痛苦明显缓解了很多，终于露出了一丝微笑。En: Liang's pain clearly eased, and he finally showed a slight smile.Zh: 他依偎在魏怀里，低声说：“谢谢你，魏叔叔。En: He nestled in Wei's arms and softly said, "Thank you, Uncle Wei."Zh: ”这件事后，魏意识到孤儿院的医疗条件需要改善。En: After this event, Wei realized that the orphanage's medical conditions needed improvement.Zh: 他向镇上的人们讲述这里孩子们的困境，大家纷纷伸出援手，不仅为孤儿院捐助医疗设备和药品，还有更多志愿者愿意加入其中。En: He spoke to the townsfolk about the children's plight, and everyone offered their help, not only donating medical equipment and medicines to the orphanage but also more volunteers willing to join.Zh: 在冬至节的那晚，孤儿院的孩子们聚在一起，吃着热腾腾的饺子，看着窗外的雪花。En: On the evening of the Dongzhi Festival, the children at the orphanage gathered together, eating steaming dumplings and watching the snowflakes outside the window.Zh: 他们的脸上洋溢着笑容，魏的心中充满了成就感与温暖。En: Their faces were filled with smiles, and Wei felt a sense of accomplishment and warmth in his heart.Zh: 从此，魏变得更加坚强主动，积极为孩子们创造更好的生活环境。En: From then on, Wei became more resilient and proactive, actively creating a better environment for the children.Zh: 而亮也不再躲避，他敞开了心扉，知道自己并不孤单，他的身边有爱护他的人。En: And Liang no longer hid; he opened his heart, knowing that he was not alone and had people who cared for him.Zh: 那个冬至夜，在老旧的孤儿院里，灯笼的光照亮了每一个角落，也温暖了每个人的心。En: That night of the Dongzhi Festival, in the old orphanage, the light of the lanterns illuminated every corner and warmed everyone's heart. Vocabulary Words:orphanage: 孤儿院volunteer: 志愿者lantern: 灯笼sorrowful: 悲伤injury: 伤势short-handed: 人手紧缺clinic: 诊所examine: 检查bandage: 包扎wound: 伤口plight: 困境nestle: 依偎accomplishment: 成就感resilient: 坚强proactive: 主动environment: 环境steaming: 热腾腾illuminate: 照亮decoration: 装饰calm emotions: 稳定情绪decision: 决定treatment: 治疗anxious: 着急aid: 援手diligent: 勤奋holidays: 节日anticipate: 期待ease: 缓解unite: 团结profound: 深刻

2026 wird wieder über Trends geredet. Wir drehen den Spieß um. In dieser Folge von AI or DIE sprechen Andreas Wiener und Christian Bühler (Five1) über Anti-Trends: Was Unternehmen nicht brauchenund welche Hausaufgaben jetzt wirklich entscheidend sind, um KI sinnvoll einzusetzen. Klartext statt Buzzwords: Data Governance, saubere Daten, echte Business-Cases und warum Tools allein noch nie ein Problem gelöst haben. Pflichtprogramm für Entscheider, Berater:innen und den gehobenen Mittelstand.

Step away from the noise of the world and burrow into a sanctuary of iridescent snow and absolute safety with this cozy guided sleep meditation. Welcome the sweet surrender of hibernation, where you are cozy and safe to rest. Sink into the warmth of your inner burrow as the 'Snowflakes of Hope' guide you into a deep and certain sleep. It's time to dream away.Original Script, Narration, Production, and Sound Design by Michelle Hotaling, Dreamaway Visions LLC 2025 All Rights Reserved✨YOUTUBE: www.youtube.com/michellessanctuary

Fluent Fiction - Dutch: A Heartwarming Christmas on Ice: Love Under Falling Snowflakes Find the full episode transcript, vocabulary words, and more:fluentfiction.com/nl/episode/2025-12-17-23-34-02-nl Story Transcript:Nl: Onder de glinsterende kerstlichten van de stad, bevond de drukke ijsbaan zich in het hart van de feestelijkheden.En: Under the shimmering Christmas lights of the city, the bustling ice rink was at the heart of the festivities.Nl: Bram stond zenuwachtig op zijn schaatsen.En: Bram stood nervously on his skates.Nl: Sneeuwvlokken dwarrelden zachtjes naar beneden en de muziek van kerstmuziek vulde de frisse winterlucht.En: Snowflakes gently drifted down, and the music of Christmas carols filled the crisp winter air.Nl: Terwijl hij naar Sanne keek, die gracieus over het ijs gleed, voelde hij een lichte duizeligheid over zich heen komen.En: As he watched Sanne, who glided gracefully across the ice, he felt a slight dizziness come over him.Nl: "Het gaat goed," fluisterde Bram tegen zichzelf.En: "It's going well," Bram whispered to himself.Nl: Hij wilde zijn eerste date met Sanne niet verpesten.En: He didn't want to ruin his first date with Sanne.Nl: Sanne, in haar glanzende roze jas, had een vastberaden blik in haar ogen.En: Sanne, in her shiny pink coat, had a determined look in her eyes.Nl: Ze wilde indruk maken op Bram, maar diep van binnen voelde ze de vlinders in haar buik.En: She wanted to impress Bram, but deep down she felt butterflies in her stomach.Nl: Op dat moment probeerde Sanne een gedurfde draai.En: At that moment, Sanne attempted a daring spin.Nl: Haar schaatsen gleden snel over het ijs, maar halverwege verloor ze haar evenwicht en viel.En: Her skates glided swiftly over the ice, but halfway through she lost her balance and fell.Nl: Omstanders keken geschrokken op, maar Sanne lachte het weg terwijl ze overeind krabbelde.En: Onlookers looked on in surprise, but Sanne laughed it off as she scrambled upright.Nl: Ondanks haar overmoed toverde haar glimlach een geruststellend gevoel.En: Despite her daring move, her smile offered a reassuring feeling.Nl: Bram schaatste naar haar toe, zich zorgen makend, terwijl zijn hoofd begon te bonzen van de koorts die hij verdoezelde.En: Bram skated over to her, worried, while his head started pounding from the fever he was hiding.Nl: "Gaat het, Sanne?"En: "Are you okay, Sanne?"Nl: vroeg hij, terwijl hij zijn hand uitstak.En: he asked, extending his hand.Nl: Zijn stem klonk zwak.En: His voice sounded weak.Nl: Precies op dat moment kwam Marieke aanlopen.En: Just then, Marieke walked over.Nl: Haar ogen scanden de ijsbaan en vonden haar broer.En: Her eyes scanned the ice rink and found her brother.Nl: "Bram!En: "Bram!Nl: Het gaat niet goed met je," riep ze.En: You're not doing well," she called out.Nl: Ze merkte de bleekheid op zijn gezicht en de kleine rimpel van zorgen op zijn voorhoofd.En: She noticed the paleness on his face and the small wrinkle of concern on his forehead.Nl: Met tegenzin gaf Bram toe: "Ja, ik voel me niet zo lekker."En: Reluctantly, Bram admitted, "Yes, I'm not feeling too well."Nl: Hij wilde niet dat de dag in het water viel.En: He didn't want the day to be ruined.Nl: Hij wilde samen met Sanne genieten, ondanks alles.En: He wanted to enjoy the time with Sanne, despite everything.Nl: Marieke legde haar arm om hem heen en keek streng.En: Marieke put her arm around him and looked sternly.Nl: "Laten we wat warme chocolademelk gaan halen," stelde ze voor, haar toon zachter.En: "Let's go get some hot chocolate," she suggested, her tone softer.Nl: Ze begreep zijn verlangen naar een goede dag, maar ook de noodzaak van rust.En: She understood his desire for a good day, but also the necessity of rest.Nl: In het gezellige café naast de ijsbaan, zaten ze rond een tafeltje met stomende bekers chocola voor zich.En: In the cozy café next to the ice rink, they sat around a small table with steaming cups of chocolate in front of them.Nl: De warmte van de chocolademelk deed Bram goed en Sanne voelde haar vingers weer tintelen na de val.En: The warmth of the hot chocolate did Bram good, and Sanne felt her fingers tingle again after the fall.Nl: Hoewel niet alles volgens plan was gegaan, straalde een lichte tevredenheid in hun ogen.En: Although not everything had gone according to plan, a light sense of satisfaction shone in their eyes.Nl: Bram keek naar Sanne, zijn stem eerlijk: "Bedankt dat je vandaag met me wilde doorbrengen.En: Bram looked at Sanne, his voice sincere: "Thank you for spending today with me.Nl: Sorry dat ik niet helemaal eerlijk was over hoe ik me voelde."En: Sorry that I wasn't completely honest about how I was feeling."Nl: Sanne glimlachte naar hem, haar ogen glinsterend van begrip.En: Sanne smiled at him, her eyes glistening with understanding.Nl: "Je hoeft niets te verbergen voor mij, Bram.En: "You don't have to hide anything from me, Bram.Nl: Ik vind je leuk om wie je bent, niet om wat je doet."En: I like you for who you are, not for what you do."Nl: Marieke keek tevreden toe hoe haar broer zijn les had geleerd - eerlijkheid en zorg voor jezelf waren belangrijk.En: Marieke watched on with satisfaction as her brother learned his lesson - honesty and taking care of yourself were important.Nl: En Sanne had ingezien dat ware charme niet in indrukwekkende trucs zit, maar in oprechte connecties.En: And Sanne realized that true charm doesn't lie in impressive tricks, but in genuine connections.Nl: Die nacht, onder de lichtjes van de reusachtige kerstboom, was het hun gelach dat de winterlucht vulde.En: That night, under the lights of the gigantic Christmas tree, it was their laughter that filled the winter air.Nl: De kerstgeest lag niet in de perfectie, maar in de eenvoudige warmte van verbintenis.En: The Christmas spirit wasn't in perfection, but in the simple warmth of connection.Nl: Het was een kerst om nooit te vergeten.En: It was a Christmas to never forget. Vocabulary Words:shimmering: glinsterendebustling: drukkeice rink: ijsbaannervously: zenuwachtigdrifted: dwarreldencrisp: frissedizziness: duizeligheidwhispered: fluisterdedetermine: vastberadenbutterflies: vlindersattempted: probeerdedaring: gedurfdespin: draaionlookers: omstandersscrambled: krabbeldepounding: begenbonefever: koortspaleness: bleekheidreluctantly: met tegenzindesire: verlangennecessity: noodzaaktingle: tintelensincere: eerlijkglistening: glinsterendlesson: lesgenuine: oprechtecharm: charmegigantic: reusachtigeperfection: perfectieconnection: verbintenis

Im heutigen Podcast zeige ich dir am Beispiel von Microsoft und Snowflake den größten Widerspruch der Börse, nämlich steigende Gewinne bei gleichzeitigem Absturz des Aktienkurses. Die Ursache ist eine viel zu hohe Anfangsbewertung. Du erfährst, warum Meinungen über gute Firmen nichts bringen und wie dir klare Charttechnik mit fallenden Hochs und Tiefs zeigt, wann der Markt eine Aktie abstraft. Vereinbare jetzt dein kostenfreies Strategiegespräch: https://jensrabe.de/Q4Termin25 Trage dich hier in meinen täglichen kostenfreien Newsletter ein https://jensrabe.de/Q4NewsYT25

In this episode of SUGTalks, Craig is joined by Russell Smith, Vice President of ERP Transformation Technology at AstraZeneca.Together, they unpack SAP's newly announced partnership with Snowflake and what it really means for SAP customers in practice. Russell shares why AstraZeneca was involved early, how the collaboration supports large-scale S/4HANA transformation, and where zero-copy data sharing can remove complexity and accelerate timelines.The conversation explores semantically rich data, real-time analytics, AI readiness, and the cultural shift required to bring analytics and AI to the data rather than moving data between platforms. Russell also reflects on governance, data trust, and why strong foundations matter before scaling AI across the enterprise.To learn more about the UKISUG referral scheme, visit: https://www.sapusers.org/community-referral-scheme

In this episode of the Grow Your B2B SaaS podcast, host Joran welcomes back Jacco van der Kooij, founder of Winning by Design, to unpack how AI-native SaaS companies are changing the rules of growth, pricing, and go-to-market in 2026. The conversation covers why real-time user-level data is becoming the defining competitive advantage, the pitfalls and promise of usage-based pricing for AI products, the existential challenge of inference costs for freemium models, and the enduring importance of subscriptions with smart hybrid elements. It also dives into how AI will replace the majority of sales tasks, the 30 percent of human expertise that remains essential, and why advocacy and community-driven growth loops will shape pipeline generation. From early-stage foundations to scaling to $10 million ARR, Jacco breaks down what founders need to get right now to thrive in the years ahead.Key Timecodes(0:00) - B2B SaaS podcast intro, AI native SaaS, pricing, GTM strategy 2026(1:01) - Jacco van der Kooij intro, Winning by Design(1:14) - 2026 success factors: real-time data, PLG, cohort analytics(2:31) - AI native buyer journey, user-led growth, usage patterns(3:48) - SaaS pricing: usage-based vs subscription, outcome-based pricing(4:23) - AI inference costs, freemium risk, monetization challenges(5:05) - Freemium in AI tools, limits, value gating(5:23) - Consumption-based pricing vs subscription, hybrid pricing(6:12) - Hybrid pricing example, membership + per-resolution fees(7:03) - Efficient growth, GTM efficiency, LTV:CAC, retention, outcomes(8:36) - AI for customer insights, demand gen, lookalike users(9:36) - Ad: B2B SaaS affiliate referral platform, AI-powered recruitment(9:47) - AI and jobs: replace vs enable, workforce impact(11:19) - GTM with AI: 70% sales tasks automated, CRM, scheduling, summaries(12:56) - Trust, human expertise, advocacy, risk mitigation(13:59) - Rebuilding GTM 2026: automation, expert touchpoints, events(15:00) - Growth loop: usage patterns, word of mouth, advocacy pipeline(16:26) - Community-led growth: user conferences, LinkedIn sharing, Clay example(17:02) - SDR strategy: activate users, customer success advocacy(17:11) - Early-stage advice: real-time data system, analytics(17:25) - Data stack recommendation: Snowflake, realtime data lake(17:32) - Scaling to $10M ARR: team alignment, closed-loop GTM(18:04) - Shared system understanding: recurring revenue, training(19:01) - Growth Institute by Winning by Design: courses, community, case studies(19:39) - Where to find: winningbydesign.com, Growth Institute(19:45) - Closing thoughts, optimism, AI era(19:54) - Outro: like, subscribe, sponsor, guest/topic requests(20:17) - Reditus mention, B2B SaaS affiliate program

Fluent Fiction - Dutch: Snowflakes and Startups: An App-Raising Christmas Encounter Find the full episode transcript, vocabulary words, and more:fluentfiction.com/nl/episode/2025-12-16-08-38-20-nl Story Transcript:Nl: De eerste sneeuwvlokken dwarrelden neer op de stad terwijl het startup incubatorgebouw zich vulde met enthousiaste stemmen en glinsterende kerstdecoraties.En: The first snowflakes gently fell on the city as the startup incubator building filled with enthusiastic voices and glistening Christmas decorations.Nl: Binnen was het warm en uitnodigend, met lange tafels vol laptops en ondernemers die probeerden hun dromen te realiseren.En: Inside, it was warm and inviting, with long tables full of laptops and entrepreneurs trying to realize their dreams.Nl: Sven zat ietwat nerveus achter zijn laptop, zijn vingers rustend op het toetsenbord.En: Sven sat somewhat nervously behind his laptop, his fingers resting on the keyboard.Nl: Zijn app-idee, dat technologie toegankelijk maakte voor iedereen, was klaar voor de presentatie.En: His app idea, which made technology accessible to everyone, was ready for the presentation.Nl: Toch voelde hij een knoop in zijn maag.En: Still, he felt a knot in his stomach.Nl: Vorige samenwerkingen waren niet goed afgelopen, en hij twijfelde of hij anderen kon vertrouwen.En: Previous collaborations had not ended well, and he doubted whether he could trust others.Nl: Aan de andere kant van de zaal stond Merel.En: On the other side of the hall stood Merel.Nl: Ze was in gesprek met een groepje mensen.En: She was talking to a small group of people.Nl: Haar lach klonk helder en enthousiast.En: Her laugh was clear and enthusiastic.Nl: Ze had een neus voor beloftevolle projecten en zocht iets waar ze haar marketingvaardigheden in kon steken.En: She had a knack for promising projects and was looking for something to invest her marketing skills into.Nl: Toen ze Sven zag, voelde ze nieuwsgierigheid.En: When she saw Sven, she felt curiosity.Nl: Zijn rustige houding intrigeerde haar.En: His calm demeanor intrigued her.Nl: De presentaties begonnen, en één voor één stapten de deelnemers naar voren om hun ideeën te presenteren.En: The presentations began, and one by one, the participants stepped forward to present their ideas.Nl: Toen Sven aan de beurt was, was zijn stem in het begin wat onvast.En: When it was Sven's turn, his voice was a bit unsteady at first.Nl: Maar naarmate hij sprak over zijn visie, kreeg hij meer vertrouwen.En: But as he spoke about his vision, he gained more confidence.Nl: Hij legde uit hoe zijn app mensen zou helpen, en zijn passie werd duidelijk.En: He explained how his app would help people, and his passion became evident.Nl: Merel luisterde aandachtig.En: Merel listened attentively.Nl: Ze merkte dat zijn concept veel potentie had, maar ook dat hij moeite had om een publiek te boeien.En: She noticed that his concept had a lot of potential but also that he struggled to engage an audience.Nl: Het zou aan marketing niet ontbreken.En: It would not lack marketing.Nl: Na verloop van tijd stak ze haar hand op.En: Eventually, she raised her hand.Nl: “Hoe denkt u dat mensen deze app zullen ontdekken?” vroeg ze met een vriendelijke, maar doordringende blik.En: “How do you think people will discover this app?” she asked with a friendly but penetrating look.Nl: Sven aarzelde even.En: Sven hesitated for a moment.Nl: Hij wist dat marketing zijn zwakke punt was.En: He knew marketing was his weak point.Nl: “Ik hoop dat het product voor zichzelf zal spreken,” antwoordde hij uiteindelijk.En: “I hope the product will speak for itself,” he finally replied.Nl: Merel liep naar hem toe nadat de presentatie was afgelopen.En: Merel walked over to him after the presentation was over.Nl: "Je idee is geweldig," zei ze oprecht, "maar zonder een manier om het onder de aandacht te brengen, missen mensen misschien de kans om het te zien."En: "Your idea is great," she said sincerely, "but without a way to bring it to people's attention, they might miss the chance to see it."Nl: Sven keek Merel in de ogen en zag geen oordeel, maar oprechte interesse en steun.En: Sven looked Merel in the eyes and saw no judgment, but genuine interest and support.Nl: Hij wist dat ze gelijk had.En: He knew she was right.Nl: "Wil je me helpen?" vroeg hij, zijn traditionele aarzeling even terzijde schuivend.En: "Will you help me?" he asked, putting aside his usual hesitation for a moment.Nl: Ze glimlachte.En: She smiled.Nl: “Alleen als jij openstaat voor samenwerking.En: "Only if you're open to collaboration.Nl: Ik denk dat we iets moois kunnen maken.”En: I think we can create something beautiful."Nl: De dagen verstreken, en terwijl de kerstversiering in de straten steeds uitbundiger werd, begonnen Sven en Merel samen te werken.En: The days passed, and as the Christmas decorations in the streets became more exuberant, Sven and Merel began working together.Nl: Ze combineerden zijn technische kennis met haar creativiteit.En: They combined his technical knowledge with her creativity.Nl: Hun gezamenlijke inspanningen begonnen vruchten af te werpen, en de app kreeg vorm.En: Their joint efforts began to bear fruit, and the app took shape.Nl: Op een koude winteravond, tijdens een kerstborrel in de incubator, stonden ze samen: Sven minder geïntimideerd en Merel vol vertrouwen in hun gezamenlijke project.En: On a cold winter evening, during a Christmas party at the incubator, they stood together: Sven less intimidated and Merel full of confidence in their joint project.Nl: “In het nieuwe jaar gaan we investeerders zoeken,” zei Sven, nu vastberaden.En: “In the new year, we're going to look for investors,” said Sven, now determined.Nl: Merel knikte.En: Merel nodded.Nl: “En tot die tijd maken we er iets geweldigs van.”En: “And until then, we'll make something great out of it.”Nl: Het was het begin van een nieuwe samenwerking, en misschien wel meer.En: It was the beginning of a new partnership, and maybe even more.Nl: Sven en Merel hadden niet alleen een balans gevonden tussen hun vaardigheden, maar ook een nieuw begin met elkaar.En: Sven and Merel had not only found a balance between their skills but also a new beginning with each other. Vocabulary Words:snowflakes: sneeuwvlokkenstartup: startupincubator: incubatorenthusiastic: enthousiasteglistening: glinsterendeentrepreneurs: ondernemersnervously: nerveuscollaborations: samenwerkingentrust: vertrouwendemeanor: houdingintrigued: intrigeerdeattentively: aandachtigpotential: potentiestruggled: moeite hadpenetrating: doordringendehesitated: aarzeldegenuine: oprechteexuberant: uitbundigercreativity: creativiteitefforts: inspanningenintimidated: geïntimideerddetermined: vastberadeninvestors: investeerdersboerenkoel: exuberantstake: stekenjudgment: oordeelknack: neusinviting: uitnodigendresting: rustendknot: knoop

Fluent Fiction - French: From Snowflakes to Startups: Élise's Eco-Friendly Journey Find the full episode transcript, vocabulary words, and more:fluentfiction.com/fr/episode/2025-12-16-08-38-20-fr Story Transcript:Fr: C'était une froide soirée d'hiver.En: It was a cold winter evening.Fr: Le vent faisait tournoyer délicatement des flocons de neige devant les grandes fenêtres du Startup Incubator.En: The wind delicately swirled snowflakes in front of the large windows of the Startup Incubator.Fr: À l'intérieur, la chaleur et la lumière des guirlandes de Noël créaient une ambiance accueillante.En: Inside, the warmth and the light from the Christmas garlands created a welcoming atmosphere.Fr: Des stands improvisés accueillaient de jeunes entrepreneurs.En: Improvised stands welcomed young entrepreneurs.Fr: Élise était l'une d'entre eux.En: Élise was one of them.Fr: Élise avait consacré toute son énergie à son projet : une ligne de produits éco-responsables.En: Élise had devoted all her energy to her project: a line of eco-friendly products.Fr: Elle rêvait de changer le monde, un produit à la fois.En: She dreamed of changing the world, one product at a time.Fr: Mais pour réaliser son rêve, elle avait besoin d'investissements.En: But to realize her dream, she needed investments.Fr: Ce soir, elle espérait le convaincre.En: This evening, she hoped to convince someone.Fr: Elle savait que Vincent, un investisseur expérimenté à la recherche d'idées novatrices, serait présent.En: She knew that Vincent, an experienced investor looking for innovative ideas, would be present.Fr: Vincent était déjà dans la salle.En: Vincent was already inside the room.Fr: Avec son flair pour identifier les projets prometteurs, il était attentif aux présentations.En: With his knack for identifying promising projects, he paid close attention to the presentations.Fr: À ses côtés, Clara, sa partenaire d'affaires, regardait chaque pitch avec un œil critique.En: By his side, Clara, his business partner, watched each pitch with a critical eye.Fr: Élise prit une profonde inspiration avant d'approcher Vincent.En: Élise took a deep breath before approaching Vincent.Fr: Elle savait que Clara était sceptique envers de nombreux projets comme le sien.En: She knew that Clara was skeptical of many projects like hers.Fr: Mais Élise décida de suivre son instinct.En: But Élise decided to follow her instincts.Fr: Elle s'approcha de Vincent, le cœur battant.En: She approached Vincent, her heart pounding.Fr: "Bonsoir, Vincent," dit-elle avec un sourire chaleureux.En: "Good evening, Vincent," she said with a warm smile.Fr: "Je m'appelle Élise.En: "My name is Élise.Fr: J'aimerais vous parler de mon projet."En: I'd like to talk to you about my project."Fr: Vincent était captivé par la passion dans le regard d'Élise.En: Vincent was captivated by the passion in Élise's eyes.Fr: Elle lui parlait avec cœur de l'importance de préserver la planète pour les générations futures.En: She spoke to him sincerely about the importance of preserving the planet for future generations.Fr: Elle décrivait avec enthousiasme sa gamme de produits, expliquant comment ils pourraient réduire les déchets et encourager un mode de vie durable.En: She described her product line enthusiastically, explaining how it could reduce waste and encourage a sustainable lifestyle.Fr: Clara écoutait en arrière-plan, les bras croisés.En: Clara listened in the background, arms crossed.Fr: Elle semblait peu convaincue.En: She seemed unconvinced.Fr: Mais Vincent, lui, sentit une étincelle d'excitation.En: But Vincent felt a spark of excitement.Fr: Les idées d'Élise résonnaient en lui.En: Élise's ideas resonated with him.Fr: Il voyait en elles non seulement une opportunité d'affaires, mais aussi un projet qui avait du sens.En: He saw in them not only a business opportunity but also a project with meaningful purpose.Fr: Après la présentation d'Élise, Vincent s'éloigna avec Clara pour discuter.En: After Élise's presentation, Vincent stepped aside with Clara to discuss.Fr: Clara exprima ses doutes.En: Clara expressed her doubts.Fr: "C'est un risque," dit-elle.En: "It's a risk," she said.Fr: "Mais quelque part en lui, Vincent savait que cela valait la peine de prendre un risque pour le bien de la planète et de soutenir un esprit aussi passionné qu'Élise.En: But somewhere inside him, Vincent knew that it was worth taking a risk for the good of the planet and to support a spirit as passionate as Élise.Fr: Plus tard dans la soirée, Vincent fit part de sa décision à Élise.En: Later in the evening, Vincent shared his decision with Élise.Fr: "Je veux soutenir ton projet," dit-il.En: "I want to support your project," he said.Fr: "Mais Clara a raison sur certains points.En: "But Clara is right on some points.Fr: Nous devrons intégrer ses conseils pour solidifier le projet."En: We will need to integrate her advice to strengthen the project."Fr: Élise était ravie, et elle accepta avec gratitude.En: Élise was thrilled, and she accepted with gratitude.Fr: Elle se sentit plus confiante que jamais.En: She felt more confident than ever.Fr: C'est ainsi que commença leur collaboration.En: That's how their collaboration began.Fr: Avec le soutien de Vincent, Élise put lancer son projet à une plus grande échelle.En: With Vincent's support, Élise was able to launch her project on a larger scale.Fr: Et, au-delà du succès professionnel, une amitié particulière se développa entre Vincent et Élise, en semant peut-être les graines d'une future relation.En: And beyond professional success, a special friendship developed between Vincent and Élise, perhaps sowing the seeds of a future relationship.Fr: Dans la chaleur de l'incubateur, alors que la neige continuait de tomber dehors, Élise avait pris un grand pas vers la réalisation de ses rêves.En: In the warmth of the incubator, as the snow continued to fall outside, Élise had taken a big step towards realizing her dreams.Fr: Vincent, quant à lui, apprenait à écouter son cœur, autant qu'à suivre ses calculs d'investisseur.En: Vincent, meanwhile, was learning to listen to his heart, as much as to follow his investor's calculations.Fr: Une simple soirée d'hiver pleine de magie de Noël avait changé leur vie.En: A simple winter evening full of Christmas magic had changed their lives. Vocabulary Words:evening: la soiréesnowflakes: les flocons de neigewindows: les fenêtresgarlands: les guirlandesentrepreneurs: les entrepreneursenergy: l'énergieinvestments: les investissementsinvestor: l'investisseuridea: l'idéeknack: le flairpartner: la partenairebreath: la respirationinstinct: l'instinctheart: le cœurlook: le regardwaste: les déchetslifestyle: le mode de viebackground: l'arrière-planspark: l'étincelleopportunity: l'opportunitépurpose: le sensrisk: le risqueadvice: les conseilsgratitude: la gratitudestep: le pasdreams: les rêvescalculations: les calculsmagic: la magieproject: le projetsuccess: le succès

Join host Jason Pereira on 'FinTech Impact' as he discusses the foundational elements of AI, specifically data, with Anand Pandya, head of Financial Services for Hakkoda, an IBM company. In this episode, they dive deep into the evolution of data management, the challenges organizations face in maintaining high-quality data, and the importance of clean data for successful AI implementation. Learn about the history of data waves, the pivotal role of cloud platforms like Snowflake, and how big companies can avoid common pitfalls in the AI landscape. Don't miss this insightful conversation packed with expert insights and practical advice for the future of data in financial services. Hosted on Acast. See acast.com/privacy for more information.

Snow begins high in the clouds when tiny water droplets freeze around dust particles. As more water vapor freezes onto these particles, they grow into crystals. The temperature and humidity shape each crystal into a unique snowflake. Most snowflakes have six sides because of the way water molecules connect. When many crystals stick together, they become the soft flakes we see falling from the sky. Discover the science behind winter's most magical creation.

Part Two of my chat with Jessica. Part One is here: https://pscrb.fm/rss/p/traffic.megaphone.fm/PHTE6587632258.mp3?updated=1765138058 Jessica can be contacted by people through Substack or at uisceawakening@gmail.com Here's her Substack:Uisce Awakening | Substack   And YouTube channel:https://youtube.com/@uisceawakening?si=Ijk7k_XRoZAqKA0E  Show Notes: Boggart and the Banshee episode Bunny Horror: Ghostly Rabbits and Witchy Hares: https://podcasts.apple.com/gb/podcast/bunny-horror-ghostly-rabbits-and-witchy-hares/id1588119563?i=1000739101148 Isobel Gowdie's chant to turn into a hare: I shall go into a hare,With sorrow and sych and meickle care;And I shall go in the Devil's name,Ay while I come home again. To change back: Hare, hare, God send thee care.I am in a hare's likeness now,But I shall be in a woman's likeness even now. (Pitcairn, 1833) The Tale of Taliesin in The Mabinogionhttps://sacred-texts.com/neu/celt/mab/mab32.htm Image: Etching of a hare by Curt Meyer Eberhardt (1895-1977) ⭐️ JOIN THE MODERN FAIRY SIGHTINGS COMMUNITY ⭐️ ⁠https://www.patreon.com/c/themodernfairysightingspodcast/membership⁠ If you're looking for exclusive bonus material, monthly zoom chats with like-minded folks, access to the Discord chat channels, quiet meditation gatherings and meeting other members, join us at: ⁠ https://www.patreon.com/c/themodernfairysightingspodcast/membership⁠S U P P O R T If you'd prefer to support the Modern Fairy Sightings with a one off donation, you can ‘buy me a coffee' and I'd be very grateful

TW: Suicide, racism.Kia ora, team! We're here again with ANOTHER tattoo episode! Who are we? Tattoo artists with a podcast?This episode we go over questions from one of our dear listeners as well as other tattoo artists on Reddit. Listen in as we get deep with questions about why we don't tattoo certain people, how we get out of ruts in our career, and why some apprentices are just downright snowflakes.Check out our tattoo studio:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.CaliLousTattoos.com⁠⁠⁠orwww.instagram.com/CaliLousTattoos and our YouTube Channel:⁠@tattoohomewreckers266⁠Please share your thoughts with us and if you have any questions, you know where to find us!

Fluent Fiction - Spanish: Snowflakes and Serendipity: Finding Connection in Madrid Find the full episode transcript, vocabulary words, and more:fluentfiction.com/es/episode/2025-12-15-23-34-02-es Story Transcript:Es: En el corazón de Madrid, el mercado navideño resplandecía bajo un cielo gris.En: In the heart of Madrid, the Christmas market glittered under a gray sky.Es: Las luces parpadeaban como estrellas y el aroma a castañas asadas flotaba en el aire helado.En: The lights flickered like stars, and the smell of roasted chestnuts floated in the icy air.Es: Elena paseaba entre los puestos, observando los adornos y juguetes.En: Elena strolled among the stalls, observing the ornaments and toys.Es: A pesar del bullicio a su alrededor, sentía una soledad persistente.En: Despite the bustle around her, she felt a persistent loneliness.Es: Elena era una artista en busca de inspiración.En: Elena was an artist in search of inspiration.Es: Pasaba por los puestos, tocando las figuritas de madera y las bufandas tejidas a mano.En: She passed by the stalls, touching the wooden figurines and the hand-knitted scarves.Es: Sin querer, chocó con Diego, un arquitecto que recientemente se había mudado a la ciudad.En: Unintentionally, she bumped into Diego, an architect who had recently moved to the city.Es: Diego ofreció una sonrisa, sus ojos reflejando una calidez inesperada.En: Diego offered a smile, his eyes reflecting unexpected warmth.Es: —Lo siento, no te vi —se disculpó Elena, un poco nerviosa.En: "Sorry, I didn't see you," Elena apologized, a little nervous.Es: —Tranquila —respondió Diego—.En: "No worries," Diego replied.Es: Yo también estaba distraído con tanto color.En: "I was also distracted by all the colors."Es: Ambos intercambiaron miradas, un poco tímidos, pero con una chispa de curiosidad.En: They exchanged glances, a little shy, but with a spark of curiosity.Es: Continuaron caminando juntos, observando la alegría que los rodeaba.En: They continued walking together, observing the joy surrounding them.Es: Diego, aunque acostumbrado a diseñar estructuras, admiraba la espontaneidad del arte.En: Diego, though accustomed to designing structures, admired the spontaneity of art.Es: Después de dar varias vueltas por el mercado, se detuvieron en un puesto de chocolate caliente.En: After several laps around the market, they stopped at a hot chocolate stall.Es: Carmen, la amiga optimista de Elena, había insistido en que Elena saliera más.En: Carmen, Elena's optimistic friend, had insisted that Elena go out more.Es: Elena sabía que su amiga solo quería verla feliz.En: Elena knew her friend only wanted to see her happy.Es: Mientras sostenían sus tazas humeantes, Diego miró a Elena y dijo: —Esta ciudad es hermosa, pero aún me siento desconectado a veces.En: While holding their steaming cups, Diego looked at Elena and said, "This city is beautiful, but sometimes I still feel disconnected.Es: No conozco a mucha gente.En: I don't know many people."Es: Elena asintió.En: Elena nodded.Es: —Yo busco algo más, una conexión verdadera.En: "I'm looking for something more, a true connection.Es: Todo lo que hago, lo hago por mi arte, pero a veces siento que falta algo.En: Everything I do, I do for my art, but sometimes I feel something is missing."Es: De repente, empezó a nevar.En: Suddenly, it began to snow.Es: Los copos caían suavemente, cubriendo el mercado con un manto blanco.En: The flakes fell softly, covering the market with a white blanket.Es: En ese momento mágico, Elena y Diego hablaron del dolor de su pasado.En: In that magical moment, Elena and Diego spoke of the pain in their pasts.Es: Diego compartió sus decepciones, el miedo a confiar.En: Diego shared his disappointments, the fear of trusting.Es: Elena habló de su corazón cerrado, temerosa de volver a sentir.En: Elena talked of her closed heart, afraid to feel again.Es: —A veces, abrirse es el primer paso —dijo Diego.En: "Sometimes, opening up is the first step," Diego said.Es: —Sí, y estoy lista para intentarlo —respondió Elena.En: "Yes, and I'm ready to try," Elena replied.Es: Tomada de una inspiración repentina, Elena decidió pintar un mural, un homenaje a la nueva amistad y potencial comienzo.En: Taken by sudden inspiration, Elena decided to paint a mural, a tribute to their new friendship and potential beginning.Es: —Quiero crear algo especial —explicó—.En: "I want to create something special," she explained.Es: Algo que mezcle nuestra historia.En: "Something that blends our story."Es: Diego sonrió.En: Diego smiled.Es: —Te ayudaré a diseñarlo.En: "I'll help you design it."Es: Con la nieve cayendo a su alrededor, se sintieron más unidos, listos para un nuevo capítulo.En: With the snow falling around them, they felt more connected, ready for a new chapter.Es: Elena, antes reservada, ahora encontraba confianza al compartir sus sueños.En: Elena, once reserved, now found confidence in sharing her dreams.Es: Diego, sintiéndose finalmente acogido, encontraba su lugar en la ciudad.En: Diego, finally feeling welcomed, found his place in the city.Es: La pintura del mural se convirtió en un proyecto de unión.En: The painting of the mural became a unifying project.Es: Representaba luces navideñas, copos de nieve y la esperanza de nuevos comienzos.En: It depicted Christmas lights, snowflakes, and the hope of new beginnings.Es: Con cada pincelada, Elena y Diego entrelazaron sus vidas, descubriendo que la conexión y la inspiración siempre habían estado al alcance.En: With each brushstroke, Elena and Diego intertwined their lives, discovering that connection and inspiration had always been within reach.Es: En el frío del invierno madrileño, dos almas solitarias encontraron calor en una amistad naciente que prometía florecer con el tiempo.En: In the cold of a Madrid winter, two lonely souls found warmth in a budding friendship that promised to flourish over time.Es: Y así, entre luces y risas, el mercado navideño había obrado su milagro.En: And so, among lights and laughter, the Christmas market had worked its miracle. Vocabulary Words:the heart: el corazónthe market: el mercadoto glitter: resplandecerthe sky: el cieloto flicker: parpadearthe hustle: el bulliciopersistent: persistenteloneliness: la soledadthe sculptor: el escultorthe stall: el puestothe ornament: el adornoto stroll: pasearthe architect: el arquitectoto bump into: chocar conthe glance: la miradathe curiosity: la curiosidadto observe: observarthe inspiration: la inspiraciónto knit: tejerto apologize: disculparseto smile: sonreírthe warmth: la calidezthe scarf: la bufandato distract: distraerthe connection: la conexiónto design: diseñarthe snowflake: el copo de nieveto trust: confiarto share: compartirthe mural: el mural

Snowflake VP of Product Management Chris Child joins Tristan Handy to unpack Snowflake's AI roadmap and what it means for data teams. They discuss the evolution from Snowpark to Cortex and Snowflake Intelligence, how to govern agents with row- and column-level controls, and why Snowflake is investing in Apache Iceberg and the Open Semantic Interchange initiative (dbt Labs recently open sourced MetricsFlow, the technology that powers the dbt Semantic Layer, to align with the goals of OSI). Chris also shares a vision for the next five years of data engineering: fewer bespoke pipelines, more standardization and semantics, and a bigger focus on business context and data products. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.

Episode 502: I will discuss my memories of Hardrock, Coco, and Joe, Suzy Snowflake, and The Frosty the Snowman Cartoons that aired on WGN-TV Channel 9 in Chicago. Also, I read a menu from Al Farber's Steak Room in Chicago.

Episode 502: I will discuss my memories of Hardrock, Coco, and Joe, Suzy Snowflake, and The Frosty the Snowman Cartoons that aired on WGN-TV Channel 9 in Chicago. Also, I read a menu from Al Farber's Steak Room in Chicago.

Tabnine (https://www.tabnine.com/) Eran on LinkedIn (https://www.linkedin.com/in/eranyahav/) Alice for Snowflake (https://alice.dev/alice-snowflake/) Mike on X (https://x.com/dominucco) Coder on X (https://x.com/coderradioshow) Show Discord (https://discord.gg/k8e7gKUpEp) Alice & Custom Dev (https://alice.dev)

Benedikt turns a year older. Benedicte moves forward despite the curveballs.Benedikt took a week off work to celebrate his 40th birthday. He spent his birthday week with a few parties with family and friends, and seeing two concerts. On the work front, he and the team built a Snowflake integration. And with the ETL infrastructure now in place, this potentially opens doors for other integrations.Despite another major extended family upheaval, Benedicte carries on by going on morning walks and focusing on her projects. She recently shipped the new Framer plugin version, made demos, and is planning to get the documentation for the plugin.Benedikt and Benedicte talk about books, how fast the internet is breaking nowadays, and more.Mentioned on the show:Surrounded by Idiots – a book by Thomas EriksonAntifragile – a book by Nassim Nicholas TalebNonviolent Communication – a book by B. Marshall Rosenberg

Dive into what's next for enterprise AI in the latest episode of Tech-Driven Business. Mustansir Saifuddin welcomes SAP expert Andrea Haupfear for an in-depth conversation on how SAP is helping organizations turn AI from hype into measurable business value. If you're navigating transformation across finance, supply chain, or operations, this episode is a must-listen. Andrea breaks down what makes enterprise AI different—why trusted data, business context, and governance are non-negotiable—and how SAP is embedding AI directly into business processes to improve speed, accuracy, and ROI. Tune in for a real-world example and practical guidance on how organizations can start small, prioritize high-impact use cases, and prepare for what's coming next with Agentic AI. Andrea Haupfear is a Business Process Architect with over a decade of experience driving digital transformation through artificial intelligence and advanced analytics. She specializes in designing and implementing AI-powered solutions that enhance operational efficiency, decision-making, and adaptability across diverse business environments. Andrea is recognized for her strategic leadership in translating complex technologies into scalable, real-world applications, making her a trusted advisor in navigating change and unlocking value through innovation. Connect with Us: LinkedIn: Andrea Haupfear Mustansir Saifuddin Innovative Solution Partners X:  @Mmsaifuddin YouTube or learn more about our sponsor Innovative Solution Partners to schedule a free consultation.    Episode Transcript [00:00:00] Mustansir Saifuddin: Welcome to Tech Driven Business, brought to you by Innovative Solution Partners. I'm honored to have Andrea Haupfear of SAP. Join me today to break down how SAP is helping organizations leverage AI to drive efficiency, reduce risk and deliver measurable ROI. We'll also look ahead at what's next and how you and your team can prepare as AI moves from experimental to essential for enterprises to thrive. [00:00:35] Hello Andrea. How are you? [00:00:37] Andrea Haupfear: I'm good. How are you? [00:00:40] Mustansir Saifuddin: Doing well, doing well. I'm so excited to have you on our show. So thank you for coming on. Today we would like to talk about the latest SAP's AI journey and the business transformation. And what it really means for SAP customers. How does it sound? [00:00:57] Andrea Haupfear: Sure. No, it sounds great. This is one of my passions that I love to talk about, and so you know, happy and excited to actually share a little bit about what we're doing with AI at SAP and what we've seen in the field with our customers. So, super excited and it's a pleasure being here. [00:01:14] So thank you again for inviting me here. [00:01:17] Mustansir Saifuddin: Awesome. Awesome. Let's get into it, we know we are at an inflection point, right? AI is moving so fast and it's actually turning from experimental to essential, right? For in a lot of different cases. So let's focus in how is SAP's AI strategy fundamentally different from consumer AI? And why does it really matter for enterprises? [00:01:39] Andrea Haupfear: Yeah, absolutely. So a couple of things that I wanna kind of touch on here. So oftentimes, and you mentioned this, right, we, we've used, we've used AI in our personal and daily lives for, you know, the last decade plus, right? I mean, when you think about AI, a lot of people think about Siri or Alexa or ChatGPT, right? [00:02:01] And you know, when I personally think about AI you've got your broad and creative tasks. What we've done in our personal lives, you know, everything from creating a grocery list to, editing a, a photo, right? A family photo. But from a business perspective you know, an enterprise AI, it really has to change those business outcomes. [00:02:26] And really when you think about this, think about, you know, everything from could be closing the books faster or. A faster on time delivery rate or reducing risk in my supply chain. And how do we ultimately do it with the highest level of governance, auditability, cost control. And so SAP's approach is really built around that flywheel of applications, data and that additional layer of artificial intelligence on top of it. [00:02:58] So there's, there's that aspect to it, but then also thinking about it in a couple of other ways of how we're doing this. Is, you know, yes, we're embedding it where your business or where the work happens. So making it easier for our end users to be able to leverage artificial intelligent capabilities and even machine learning capabilities, not just [00:03:23] from a digital assistant or a chat perspective, but how do we integrate it and infuse it within their specific business, day-to-day business processes to make their lives that much easier? But then also thinking about it from a strategic perspective, how can I obtain that high level of ROI by leveraging artificial intelligence. [00:03:47] So we're seeing it in a couple of different flavors from our customers. And then also what we're developing from a, from a product perspective as well. So we're thinking about it from a couple of different angles. [00:04:00] Additionally, thinking about it from a AI operating system for our developers and for our consultants, leveraging the AI foundation on the business technology platform. [00:04:13] So think about what used to be our developers would have to generate thousands upon thousands of lines of code. Now that's no longer the case, right? It can take them you know, a, a minute or so now to develop the, these applications and these lines of code to where it's, it's easier for them to go about their day-to-day jobs and their, their tasks where now they don't have to spend days upon days trying to develop these different applications and agents. [00:04:45] It also lets you and I just mentioned around agents, it also lets you create and govern custom agents to read and write back to SAP and non SAP systems. Thinking about this automation and accountability, not just getting those pointed answers, right? And then last but not least, kind of how I think about this is, yes, you've got your trust. [00:05:09] Think about trust not only in the data from looking at it in your SAP systems, but also think about non SAP systems. Think about your third party applications that you're going in and looking at the data, whether it's geographic information customer sentiment information, or it could even be, asset related sensor information, right? So bringing in that data as well as looking at it from your SAP business data context but then also looking at it with responsibility. So SAP has that responsible AI program in place really aligned to the UN UNESCO principles and the ISO 4 2 0 0 1 certification to really prioritize [00:05:57] those ethics and compliance and human oversight within our, our AI applications such as, you know, AI core and our digital assistant juul. So really taking it from a full spectrum approach and looking at it at the holistic level and how we can bring in artificial intelligence within these, these areas. [00:06:20] Mustansir Saifuddin: I love the way you kind of package it all together, from an overall perspective, especially, you know, the two things that really stuck out to me was. Again, coming from a business side, what is in it for a customer, right? What is the real value? [00:06:35] And you touched upon two things, embedding it. So a person who is currently doing a job and they're used to doing it manually. Now you can. Embed these ai component to their daily work streams, right? And how they can, you know, utilize that. And the second part I really loved it is you talked about ROI really what is the return I'm getting on this investment, right? And then lastly, you talked about data. So let's, let's talk about that. You know, here's the uncomfortable truth. AI is only as good as the data it learns from. We all know that. We all talk about it. And we have always heard this term garbage and garbage out, but what that sort really mean when we are talking SAP AI, making recommendations to customers and we are talking the effect in terms of millions in revenues or supply chain decisions. How would you like to address that? What is, what is SAP's approach on that? [00:07:33] Andrea Haupfear: Yeah, so a couple of things and you know, I've heard that term many times and coming and being an ex consultant. It's, it's definitely right. You're only as good as, as I've heard, you know, as the data that you have. So my thought on this is really when you have an AI agent that recommends, say for example, expediting a shipment or reclassifying a receivable, the truth that it relies on, [00:08:00] is your master data. [00:08:01] It is your transactional history and any sort of process constraints that lie in between. So ultimately, when I think about this, it's not just your, your master data. It's a, it's a multitude of things that ultimately will help the AI model in the end. In the end game to take those three pillars and turn garbage in into good decisions out. [00:08:27] The other piece that, how I think about this are semantics and not necessarily just schemas. So think about when we have some of our solutions such as Business Data Cloud, which carries those semantics and lineage into your AI workloads. So say for example, the customer, the plants, or an open po, it means the same thing everywhere. [00:08:51] And that's really critical for explainability and audit purposes. That's another way how I think about this. And then also just looking at this from a context perspective. So I also think about, you have to train a model when at first go, right? And be able to provide it some context, some instruction, some understanding that says, this is where this particular business process lies. [00:09:17] This is how the process should look and feel. What does good look like? And that's ultimately what we explain and tell our customers is we need to train our model to understand what does good look like, and this is where you have that context, rich retrieval and not just kind of that blind prompting that just says, go do this. [00:09:36] But the model will try to establish what it thinks good looks like, which may not necessarily mean what you think good looks like. This is where SAP HANA Cloud will bring in that vector engine, so those semantic retrievals and documents and notes and images. [00:09:53] Think about a knowledge graph. So it brings in those specific facts and relationships from your ERP, but then also thinking about a rag model as well, reducing those hallucinations and making those citations explainable. So why did the model or an agent be able to go through the process that it did? [00:10:16] Well, that's because there's multiple steps and instructions that the model has to take in order to provide an accurate response. Those are some of the things in, in which we leverage today with our customers and really making it so that way it's, yes, they may not always have the best data, but let's provide additional context to really help, again, make those good decisions coming out. [00:10:41] Mustansir Saifuddin: I liked the way you tied it together, right? We talk about business semantics being so important, BDC, the business data cloud. How is that coming into play in this conversation? And then coming from business semantics into a context. A context really is required for the answers to make sense and be business relevant. [00:11:03] So I really love the way you kind of connected together. Let's zoom in. Let's pick an industry. And there are so many examples that manufacturing, retail, financial services. Can you walk us through one compelling use case where SAP AI is really creating these breakthrough value? [00:11:21] What was the business problem? And how did AI solve it differently? [00:11:26] Andrea Haupfear: Yeah, absolutely. Mentioned at the beginning, SAP is investing heavily within artificial intelligence and machine learning capabilities, not just from an embedded AI perspective, but also think about it from a tailored AI perspective. So I mentioned [00:11:41] Business Data Cloud, being able to pull information and data not only from your internal SAP systems, but also external and third party information. And I wanna give you an example in a use case real world use case of a dairy co-op out of Wisconsin that is actually doing this today [00:12:00] from a very innovative approach. [00:12:02] Their challenge was around their performance at the subcontracting level. Ultimately these guys have a dairy co-op with their local farmers or farm base. They bring in the milk to not only from an internal manufacturing perspective to process out milk cheese, butter whey, et cetera cream, but they also subcontract it out as well. [00:12:28] And so this is really where they wanted to be able to get a better understanding, not just insights perspective on their data at their subcontractors from a yield output perspective. How much dairy, how much cheese was being was an output or yield, but what was going in and then going in versus going out. [00:12:50] And so ultimately what they wanted to be able to do was, yes, be able to look at the yield perspective from an insights, but they wanted to be able to leverage and infuse artificial intelligence from this process to ultimately help with their reduce of shrink. And contributing to a 1% KPI, which ultimately makes up to you and I roughly 10 to $15 million. [00:13:16] Okay. So just to kind of put it in perspective here of how much we're talking about. And so what they did was, yes, we have the insights from an analytics perspective, they wanted to be able to make it easier for their dairy supply chain planners to be able to, in real time through natural language processing, be able to chat with a digital assistant to gain insights around, Hey, what is my yield output for specific plant? [00:13:42] Tell me my highest and lowest plants that had the yield output. Tell me un understanding from a scrapping perspective how much waste is going out. So they wanted to be able to look at these specific metrics and be able to get a better understanding, hey, which particular plant is performing the best versus the worst. [00:14:03] So that way they can help to be able to retain and possibly improve some of these plant relationships going forward. Additionally as kind of that part two, what they wanted to be able to do is they receive manual yield output reports on a weekly basis from these subcontractors. It's typically in a PDF format, Excel, PDF format, and oftentimes these can be miskeyed into their S4 system. [00:14:35] And what they wanted to be able to do is be able to have an a little bit more of an automated process. Of, yes, not only uploading these reports that they, they have to manually key in today, but they wanted to be able to provide some intelligence behind it. And so this is where we've put in outlier detection on these attachments to where now I can see, okay, was there a miskey or an oversight that says, okay, you know, this should have been 2,622 versus 6,222. It can detect those mis keys in real time to say, Hey. For my supply chain planner, this doesn't necessarily look right. It's way outta whack compared to what was previously entered in, in the previous weeks. [00:15:24] You should triple check this, right? So it's, it's being able to provide a little bit more of, think of like big brother watching over you before it actually goes and hits into their ERP system. This is ultimately contributing to their supply chain process and has a direct impact on their KPI metrics that they're leveraging. [00:15:44] In this case, it's it's within shrink, so really getting a, a better handle on that. [00:15:50] Mustansir Saifuddin: No, I think the, the way you explained it, it is a great example 'cause now I can see not only does it apply to this particular industry, but it can cut across multiple industries. [00:16:00] Right. Because the example talked about production at a plant level. At the same time, the supply chain mishaps that can happen. [00:16:08] And usually a human eye can take so much [00:16:11] or can detect so much, but you can't try and put it together in a way that you guide your, your workforce to look at anomalies that can really help you steer the ship in the right direction quickly and efficiently. So that's great. [00:16:26] That really leads into my, my next question is, all of this is great, right? This is happening right now, we can see like the example you use, [00:16:35] right? It is in action. It is in motion, and customers are seeing value. Let's fast forward, where is SAP's AI development heading? You know, let's take a time horizon, 18 to 24 months. What capabilities should organizations be preparing for? Because it is all about future proofing ourselves, right? And how should they architect the solutions today to be ready for that feature, you know, coming up so quickly? [00:17:02] Andrea Haupfear: Yeah, absolutely. So a couple things that that come to mind. So number one and we've all been hearing kind of the next and elitist buzzword is around agents and agentic AI. So really how. I think about agents is how do we provide some of those tasks that, you know, may not necessarily whether they're they're still important, but, you know, maybe take up a lot of our time [00:17:29] but being able to provide and have a AI model behind that. To really free up some of the workload and provide some of our end users more on the strategic front. Freeing up some of that time. So I think in my humbled opinion, Agentic AI but Agentic AI at scale. So a lot of our customers are looking at what we have and this is where we're embedding. [00:17:54] Within our SAP applications agents within each one of our lines of business, but also custom agents. So this is something that is going to be released here in the next next several months, is looking at I have my embedded agents, but if I have very specific and unique, maybe differentiated business processes, how can I be able to integrate and infuse custom agents or an agent within this particular process? [00:18:23] And so this is really where I think is gonna we're really gonna see a lot of value coming in from our customers that says, yes, I can use agents in a multitude of different ways. Second is thinking about as an organization, we're becoming more dynamic and, and open source for data and how we can process it in a business context. [00:18:47] So thinking about, yes, I mentioned the Business Data Cloud, but also you know, strong partnerships. That was just announced with Snowflake as well. Right? So bringing in, yes, not only our internal data, but also our external data as well. How can we take that data and be able to normalize it? As far as from an architect's perspective, here are a couple points that I was kind of thinking about in my mind as we were going through this. [00:19:13] Was around keeping the core clean, right? So making sure that, yes, we're using our, our business technology platform various extensions and agents and skills from from JUUL studio and avoiding really those those drastic upgrades. And also kind of how I'm thinking about this is adopting that data product mindset. [00:19:40] So looking at, and I mentioned this as well, like Business Data Cloud, from looking at semantics and lineage, but also looking at retrieval methods. So vector engines and knowledge graphs. But then also thinking about it from a process perspective and [00:20:00] designing agent guardrails. So making sure that you have a much more standardization of an understanding of those roles and permissions. [00:20:10] Understanding human in the loop checkpoints at what point should be automated versus, okay, we need to have a set of eyes on this to actually be able to say, yep, this looks correct. I think that that's extremely important. [00:20:25] Mustansir Saifuddin: Yeah, for sure. And I think a couple of things that really stuck out for me. One is very near and dear to me, is the data part. And you talked about the partnership with Snowflake coming out recently, and I think it's important, especially when we talk about data for an organization. It's not just SAP data, it's like the overall, right? [00:20:42] You know, this, what does it really make up my organization? So [00:20:45] great approach from SAP, how it's trying to bring in like a business context around it, right? You have information within your ERP, outside of your ERP and then using the BTP platform. and the BDC platform to kind of bring it all together. So I think great segue, especially when we talk about agents and you know, we've all been talking about agents you know, for quite some time now, but now we can see the real value, how we can customize it and bring it together from a data perspective. So great conversation. On a personal note, how are you staying up, you know, on top of all these changes taking place in technology and business? What is your secret sauce? [00:21:26] Andrea Haupfear: Yeah, no, it's tough 'cause it's changing daily, weekly, right. And so being able to stay, have it stay top of mind. This is something that is part of, yes, not only my passion and what I do day in and day out, right, but also looking and getting, keeping educated not only from a process perspective by virtue of, you know, our internal processes, what we have in our products and our product offering, but also external with our clients. [00:21:54] To say, okay, what are they doing today with their processes? And then how can we leverage AI within that? So yes, not only from an internal knowledge sharing perspective, from a functional and technical perspective, but also external as well. And then thinking about external blogs, news sources, those are just kind of some of the things that I try to stay up to date. [00:22:16] You know, as best as I can. [00:22:18] Mustansir Saifuddin: No, I hear you on that. It is, it is a constant learning and I think that's the key, right? Educating [00:22:23] and educating and educating and be able to find your sources. I think that's the key. Great conversation. I know we are at time, what would you take out of this conversation that we just had and want to leave a particular takeaway for our listeners and folks who are interested in this topic? [00:22:42] Andrea Haupfear: Sure. Absolutely. So AI is not just like, and, and I meant we mentioned this earlier on, right? AI is not just in our personal lives, but it's also in our workplace and it's very, very real. We are seeing our companies and our customers take advantage of infusing AI into their business processes and receiving the high ROI in their processes. [00:23:05] The key is to start small. Strategically and identify which areas will have AI and will have that high ROI, but then also have the highest value when it comes from an impact perspective. We see this to where we run this as, as ultimately an ideation sessions with our customers and from the takeaway out of those sessions is they can start to craft an internal roadmap that will lead them to AI success. [00:23:38] And ultimately our organization can help them get there along the way, even whether they're just dipping their toe in the AI pool or some, some customers that we deal with already have strong partnerships with large language model providers or they're partnering with universities, things like that. [00:23:57] The end goal in net net is that [00:24:00] our organization can help to not only help identify those high value AI use cases, but also investing in you to create those. We offer a free proof of concept in as much as eight weeks. You mentioned this, you know how frequently this is changing. [00:24:18] AI is changing. Right? And this is where we can develop these proof of concepts to where you, our customers can be able to realize those value in a very quick and short amount of time. And so that's ultimately where I wanna leave the audience with is that we're, we're seeing AI not just in our personal lives, but also in the workplace. [00:24:39] And we're actually showing them and, having them realize it in real time. So you guys can, can feel free to reach out to me. I think we'll have my contact information at the end of the podcast here. But you know, happy to have further conversations with you and your organization. [00:24:55] I wanna thank you again personally for inviting me to the podcast and to discuss a, a very, very close and passionate topic for me. [00:25:04] Mustansir Saifuddin: It's a pleasure to have you, Andrea, and really, I think it was a great conversation. You touched upon so many different things and I think that was the purpose of this, was to kind of bring light to exactly what's going on in, you know, we talk about AI in general, but what is really happening at the inter-enterprise level [00:25:21] and what is the real value when folks are looking at, from a business perspective. How to increase ROI in this new technology and what does really mean in terms of increasing business revenue and across the board improving efficiencies. Right? So it's all together. But thank you so much for coming on our show. [00:25:42] Andrea Haupfear: Absolutely. Thank you for having me. [00:25:44] Mustansir Saifuddin: Thanks for listening to Drug Driven Business, brought to you by Innovative Solution Partners. SAP is helping customers move from AI experimentation to enterprise value by embedding AI where work happens, grounding it in trusted data and business context. And ensuring governance, auditability, and control. [00:26:10] Andrea's Key takeaway? Start small. Focus on the highest ROI use cases and build a clear roadmap because when AI is tied to real processes and real outcomes, SAP customers can unlock faster decisions, lower risk, and measurable impact. We would love to hear from you. Continue the conversation by connecting with me on LinkedIn or X. [00:26:36] Learn more about innovative solution partners and schedule a free consultation by visiting isolutionpartners.com. Never miss a podcast by subscribing to our YouTube channel. Information is in the show notes.        

Anna Davlantes, WGN Radio's investigative correspondent, joins Bob Sirott to share what happened this week in Chicago history. Stories include the anniversary of Chicago’s parking meter deal, the retiring of Mike Ditka’s jersey, the debut of “Suzy Snowflake,” and more.

Fluent Fiction - Danish: A Heartfelt Christmas Quest: Søren's Magical Snowflake Find the full episode transcript, vocabulary words, and more:fluentfiction.com/da/episode/2025-12-09-23-34-01-da Story Transcript:Da: Sneen dalede sagte ned over Nyhavn, mens julelysene glimtede mellem de farverige gavlhuse.En: The snow fell gently over Nyhavn, while the Christmas lights twinkled between the colorful gabled houses.Da: Der var en særlig julestemning, der fyldte de brostensbelagte gader.En: There was a special Christmas spirit filling the cobblestone streets.Da: Søren gik langsomt med hænderne dybt i lommerne.En: Søren walked slowly with his hands deep in his pockets.Da: Han havde en mission: at finde den perfekte gave til sin kone.En: He had a mission: to find the perfect gift for his wife.Da: Kirsten gik ved siden af ham, fuld af energi.En: Kirsten walked beside him, full of energy.Da: "Se her, Søren!"En: "Look here, Søren!"Da: udbrød hun ivrigt, mens hun pegede på en bod med håndlavede stearinlys.En: she exclaimed eagerly, pointing at a stall with handmade candles.Da: "De er smukke og dufter af gran!En: "They're beautiful and smell like fir!Da: Perfekt til jul."En: Perfect for Christmas."Da: Mikkel, der gik lidt efter dem, rystede på hovedet.En: Mikkel, who walked a little behind them, shook his head.Da: "Husk budgettet, Søren.En: "Remember the budget, Søren.Da: Vi skal ikke bruge for meget på en ting," sagde han fornuftigt.En: We shouldn't spend too much on one thing," he said sensibly.Da: Søren kiggede rundt på markedet.En: Søren looked around the market.Da: Overalt var der juleting – nisser, gløgg og julepynt i alle former og farver.En: Everywhere were Christmas items—gnomes, mulled wine, and ornaments of all shapes and colors.Da: Det var lidt overvældende.En: It was a bit overwhelming.Da: "Det skal være noget særligt," mumlede han for sig selv og tænkte på sin kone.En: "It has to be something special," he muttered to himself, thinking of his wife.Da: Sammen gik de tre venner videre gennem markedet.En: Together, the three friends continued through the market.Da: Kirsten blev ved med at komme med forslag.En: Kirsten kept making suggestions.Da: "Hvad med en uldplaid?En: "What about a wool blanket?Da: Eller disse smukke keramikskåle?"En: Or these beautiful ceramic bowls?"Da: Søren smilte, men tvivlede.En: Søren smiled but was unsure.Da: Pludselig stoppede han op.En: Suddenly, he stopped.Da: Der, midt på en bod, hang en håndlavet juleornament.En: There, in the middle of a stall, hung a handmade Christmas ornament.Da: Det var formet som et snefnug og glimtede i lyset.En: It was shaped like a snowflake and sparkled in the light.Da: Søren tog det op og drejede det i hænderne.En: Søren picked it up and turned it in his hands.Da: "Det er lige os," tænkte han.En: "This is just us," he thought.Da: Men prisen var høj.En: But the price was high.Da: For høj.En: Too high.Da: Med et tungt suk satte han det tilbage.En: With a heavy sigh, he put it back.Da: "Jeg tror ikke, jeg har råd til det," sagde han til Mikkel og Kirsten.En: "I don't think I can afford it," he said to Mikkel and Kirsten.Da: Kirsten så på Mikkel, og de begge nikkede stille.En: Kirsten looked at Mikkel, and they both nodded quietly.Da: "Vi kan hjælpe," sagde Mikkel.En: "We can help," said Mikkel.Da: "Vi kan skillinge sammen."En: "We can chip in together."Da: Søren blev overrasket.En: Søren was surprised.Da: "Det kan I ikke gøre," protesterede han.En: "You can't do that," he protested.Da: Men de insisterede.En: But they insisted.Da: "Det er jul, Søren," sagde Kirsten.En: "It's Christmas, Søren," said Kirsten.Da: "Og gaver fra hjertet betyder mere end noget andet."En: "And gifts from the heart mean more than anything else."Da: Søren følte en varme brede sig i brystet.En: Søren felt a warmth spread in his chest.Da: Øjeblikket var særligt.En: The moment was special.Da: Med vennernes hjælp købte Søren snefnugget.En: With his friends' help, Søren bought the snowflake.Da: Det skinnede i lyset fra julelysene.En: It shone in the light of the Christmas lights.Da: På vejen hjem følte Søren sig lettet og fyldt med taknemmelighed.En: On the way home, Søren felt relieved and filled with gratitude.Da: Han indså, at det bedste ved julen var ikke gaverne, men venskabet og kærligheden bag dem.En: He realized that the best part of Christmas was not the presents, but the friendship and love behind them.Da: Og at selv det mindste snefnug kan øge kærligheden, når det kommer fra hjertet.En: And that even the smallest snowflake can amplify love when it comes from the heart. Vocabulary Words:gently: sagtegables: gavlhusecobblestone: brostensbelagtemission: missionstall: bodhandmade: håndlavedecandles: stearinlysfir: gransensible: fornuftigtmulled wine: gløggornaments: julepyntoverwhelming: overvældendewool blanket: uldplaidCeramic: keramikskålesnowflake: snefnugsparkled: glimtedeafford: rådheavy sigh: tungt sukchip in: skillinge sammenprotested: protesteredeinsisted: insisteredewarmth: varmegratitude: taknemmelighedrealized: indsåamplify: øgefriendship: venskabetlove: kærlighedenspecial: særligtenergetic: energirelieved: lettet

Episode 166 is on the scene and Jody is joined by our good buddy Boo Carlisle who is filling in for Julian this week as co-host. Robert Pressley competed in the highest level of NASCAR for over two decades winning at Daytona, Darlington, Dover among other facilities in both the NASCAR Craftsman Truck Series and the O'Reilly Auto Parts Series. Robert is taking on a new venture as Race Control for the IHRA Stock Car Series that is debuting in 2026 for an 8 race schedule. Robert joins us to tell us about how he got involved in this series, what to expect on race days and what they are looking to accomplish. He also tells us about his days being the promoter at Kingsport Speedway and the lessons he learned doing so and how he will apply that in what the IHRA is looking to bring to the table. He also discusses the rules and the vision for the series. This news has taken the racing world by storm and we give you some insight from one of it's key players. Boo and Jody discuss the recent Snowball Derby that was completed shortly before this show went on the air. They discuss Stephen Nasse finally winning this event after 15 years and Ty Majeski's protest following his black flag on the last restart. The boys also reveal if they stayed up till 3:30 Sunday morning to watch the Snowflake and discuss all the weather issues. The guys also discuss the ARCA Menards East Series coming to Hickory, the upcoming Christmas Clash at Carteret County and some breaking news concerning the STAR Super Stock Tour and where they will be opening up the season in 2026. All this and more this week on DLN!

We review the results from SentinelOne (S) and Snowflake (SNOW) and predict which stock is more likely to record profits first. We also take a critics-eye view of the Netflix-Warner Bros. deal amid Paramount's hostile counter offer. Rick Munarriz, Sanmeet Deo, and Tim Beyers: - Review last week's results from SentinelOne and Snowflake. - Predict which of the two will reach GAAP profitability first. - Give a critics choice take on the Netflix-Warner Bros deal, including some thoughts on Paramount's just-launched hostile takeover. Companies discussed: S, SNOW, NFLX, WBD, PSKY Host: Tim Beyers Guests: Rick Munarriz, Sanmeet Deo Producer: Anand Chokkavelu Engineer: Dan Boyd Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

Come sit with me for a quiet moment while we make these big paper-bag snowflakes together ❄️ it's simple, cozy, and just the kind of slow holiday craft that feels good for the soul. :) ♥ Happy Holidays! I hope this season brings you warmth, ease, and a few gentle moments just for you.Amazon Storefront https://www.amazon.com/shop/gentlewhisperingAmazon Mp3 https://www.amazon.com/s/ref=ntt_srch_drd_B01BAXDICM?ie=UTF8&field-keywords=GentleWhispering&index=digital-music&search-type=ss YouTube Mp3 https://music.youtube.com/channel/UCAYaoy-i0_bTnd9yzzDMkhw Spotify Mp3 https://play.spotify.com/artist/3gkB9Cdx4UuWQxjhelyd87?play=true&utm_source=open.spotify.com&utm_medium=open iTunes Mp3 https://itunes.apple.com/us/artist/gentlewhispering/id1077570705#see-all/top-songshttps://itunes.apple.com/us/artist/maria-gentlewhispering/id1048320316PayPal (Donations, if you feel you need to give back) https://www.paypal.me/GentleWhisperingEmail: MariaGentlewhispering@gmail.com#ASMR #GentleWhispering

I speak to Jessica in Oxfordshire who has had a number of encounters including a brownie. Her story begins with meeting a handsome Otherworldly man, dressed completely in green in her local woods who she feels turned out to be Gwyn ap Nudd. It sent her on a journey to discover her ancestry as connected to one of the 'Families of the 'Old North'. The quest entirely transformed the way she lives her life. This is part one of two episodes. ⭐️ JOIN THE MODERN FAIRY SIGHTINGS COMMUNITY ⭐️ https://www.patreon.com/c/themodernfairysightingspodcast/membership If you're looking for exclusive bonus material, monthly zoom chats with like-minded folks, access to the Discord chat channels, quiet meditation gatherings and meeting other members, join us at: https://www.patreon.com/c/themodernfairysightingspodcast/membership S U P P O R T If you'd prefer to support the Modern Fairy Sightings with a one off donation, you can ‘buy me a coffee' and I'd be very grateful

Please enjoy our annual children's Christmas production: The Secret Of Snowflake County.

¡Emprendeduros! En este episodio Rodrigo nos da una actualización de mercado donde habla del estatus del mercado, del cosumo, del mercado de empleos y del codigo rojo de OpenAI. Nos da los reportes de ingresos de Crowdstrike, American Eagle, Salesforce, Snowflake, Kroger, Dollar General y Dollar Tree. Después habla de la linea de pobreza y del altruismo pero bien hecho. Finalmente contesta unas preguntas de los Emprendeduros.

Frank on LinkedIn (https://www.linkedin.com/in/franckpachot/) MongoDB (https://www.mongodb.com/) Alice for Snowflake (https://alice.dev/alice-snowflake/) Mike on X (https://x.com/dominucco) Coder on X (https://x.com/coderradioshow) Show Discord (https://discord.gg/k8e7gKUpEp) Alice & Custom Dev (https://alice.dev) Mike's Recent Omakub Blog Post (https://dominickm.com/omakhub-review/)

-The Minnesota corruption saga grows so large it might qualify as its own GDP, and Rob gleefully predicts the political downfall of Walz, Ellison, and possibly Ilhan Omar. -Kaitlin Bennett joins on the Newsmax hotline, recounting her campus adventures where college students flee debates faster than they flee Thanksgiving history lessons. Today's podcast is sponsored by : BIRCH GOLD - Protect and grow your retirement savings with gold. Text ROB to 98 98 98 for your FREE information kit!WEBROOT : Live a better digital life with Webroot Total Protection. Rob Carson Show listeners get 60% off at http://webroot.com/Newsmax  To call in and speak with Rob Carson live on the show, dial 1-800-922-6680 between the hours of 12 Noon and 3:00 pm Eastern Time Monday through Friday…E-mail Rob Carson at : RobCarsonShow@gmail.com Musical parodies provided by Jim Gossett (http://patreon.com/JimGossettComedy) Listen to Newsmax LIVE and see our entire podcast lineup at http://Newsmax.com/Listen Make the switch to NEWSMAX today! Get your 15 day free trial of NEWSMAX+ at http://NewsmaxPlus.com Looking for NEWSMAX caps, tees, mugs & more? Check out the Newsmax merchandise shop at : http://nws.mx/shop Follow NEWSMAX on Social Media:  -Facebook: http://nws.mx/FB  -X/Twitter: http://nws.mx/twitter -Instagram: http://nws.mx/IG -YouTube: https://youtube.com/NewsmaxTV -Rumble: https://rumble.com/c/NewsmaxTV -TRUTH Social: https://truthsocial.com/@NEWSMAX -GETTR: https://gettr.com/user/newsmax -Threads: http://threads.net/@NEWSMAX  -Telegram: http://t.me/newsmax  -BlueSky: https://bsky.app/profile/newsmax.com -Parler: http://app.parler.com/newsmax Learn more about your ad choices. Visit megaphone.fm/adchoices

With the AI trade in the spotlight, Carl Quintanilla and Jim Cramer discussed Nvidia CEO Jensen Huang's Wednesday visit to Washington, DC — which included a meeting with President Trump. Hear what Huang said at a separate event about the U.S.-China battle over AI. The anchors reacted to Al bubble-related comments Anthropic CEO Dario Amodei made to Andrew Ross Sorkin at The New York Times DealBook Summit. David Faber called in with breaking news about the battle to acquire Warner Bros. Discovery — his sources say Netflix is the leading bidder. Meta shares rally: CEO Mark Zuckerberg reportedly plans deep cuts to the company's metaverse group. On the earnings front: Salesforce shares rise while Snowflake melts.  Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, we explore Anthropic's move to hire lawyers ahead of a potential IPO and what this means for its next stage of growth. We also break down the $200M Snowflake partnership and how bringing Anthropic's LLMs to enterprise data stacks could reshape adoption.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustle------------See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Varun Puri, CEO and cofounder of Yoodli, joins the show to talk about using AI role play to transform how people practice for high stakes conversations, from sales calls to job interviews to tough manager chats. He breaks down how Yoodli went from a consumer public speaking tool to a serious enterprise platform used by teams at Google, Snowflake, Databricks, and more, all while staying anchored in one mission, helping humans communicate with confidence. We dig into product led growth, honest feedback loops, and why real human communication will matter even more as AI makes information instant.Key takeaways• Why Yoodli started with public speaking anxiety and grew into an AI role play simulator for any important conversation, not just conference talks or pitch decks• How watching real user behavior inside companies like Google pulled the team into enterprise without abandoning their consumer product• A simple approach to product feedback, talk to end users constantly, then prioritize changes by business impact, renewal risk, and how many people benefit• What it really takes to move from consumer to enterprise, new roles, new processes, and a very different mindset around reliability, security, and expectations• Why Varun draws clear ethical lines, using AI to coach and prepare people, not to replace human judgment in hiring, promotion, or high trust decisionsTimestamped highlights[00:35] What Yoodli actually does today, from solo practice to training sales and go to market teams inside large enterprises[01:43] The original vision, helping people who are scared of public speaking, and the insight that interviews, sales calls, and manager talks are all just role plays[03:37] How the team listens to end users, the channels they rely on, and why the consumer product is still their testing ground for new ideas and experiments[05:20] Following users into the enterprise, why it was an addition and not a full pivot, and how product led growth inside companies like Google works in practice[07:42] The early shock of selling to enterprises, learning about new roles, SLAs, InfoSec, and bringing in leaders from Tableau and Salesforce to build a real B2B engine[11:10] Two paths for AI in sales, tools that try to replace humans versus tools that make humans better, and why Varun has drawn a hard line on what Yoodli will not do[15:26] A future where information is commoditized and instant, and why communication and presence become the real edge for top performers in that world[20:48] Designing for trust and adoption, how Yoodli keeps practice private by default, when data is shared, and why control has to sit with the end userA line worth saving“In a world where AI makes everyone smarter and faster, the thing that will be at the biggest premium is how you communicate as a human with other humans.”Practical ideas you can use• Keep a consumer like surface in your product so you can experiment faster than your enterprise roadmap would ever allow• Treat feedback from large customers like a queue you rank by renewal risk, strategic value, and number of users helped, not as a list you must clear• Look for product led growth signals inside your user base, if thousands of people in one company are using you, someone there probably wants a team level solution• Draw explicit boundaries for your AI product, write down what you will not automate, so you can build trust with users and buyers over the long termCall to actionIf you care about the future of sales, interviewing, and communication in an AI rich world, this conversation is worth a listen. Follow the show, leave a quick rating, and share this episode with a founder, product leader, or sales leader who is thinking about AI in their workflow. And if you want feedback on your own speaking, check out what Varun and his team are building at Yoodli.

Initial jobless claims and Challenger layoff data come ahead of the open after ADP's weak report yesterday raised rate cut odds. Salesforce and Snowflake results are also in focus.Important DisclosuresThis material is intended for general informational purposes only. This should not be considered an individualized recommendation or personalized investment advice. The investment strategies mentioned may not be suitable for everyone. Each investor needs to review an investment strategy for his or her own particular situation before making any investment decisions.The Schwab Center for Financial Research is a division of Charles Schwab & Co., Inc.All names and market data shown above are for illustrative purposes only and are not a recommendation, offer to sell, or a solicitation of an offer to buy any security. Supporting documentation for any claims or statistical information is available upon request.Past performance is no guarantee of future results.Diversification and rebalancing strategies do not ensure a profit and do not protect against losses in declining markets.Indexes are unmanaged, do not incur management fees, costs, and expenses and cannot be invested in directly. For more information on indexes, please see schwab.com/indexdefinitions.The policy analysis provided by the Charles Schwab & Co., Inc., does not constitute and should not be interpreted as an endorsement of any political party.Fixed income securities are subject to increased loss of principal during periods of rising interest rates. Fixed income investments are subject to various other risks including changes in credit quality, market valuations, liquidity, prepayments, early redemption, corporate events, tax ramifications, and other factors.All expressions of opinion are subject to change without notice in reaction to shifting market, economic or political conditions. Data contained herein from third party providers is obtained from what are considered reliable sources. However, its accuracy, completeness or reliability cannot be guaranteed.Investing involves risk, including loss of principal, and for some products and strategies, loss of more than your initial investment.The Schwab Center for Financial Research is a division of Charles Schwab & Co., Inc.Apple Podcasts and the Apple logo are trademarks of Apple Inc., registered in the U.S. and other countries.Google Podcasts and the Google Podcasts logo are trademarks of Google LLC.Spotify and the Spotify logo are registered trademarks of Spotify AB.(0131-1225) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Fluent Fiction - Danish: Snowflakes and Healing: A Christmas Reunion in Adversity Find the full episode transcript, vocabulary words, and more:fluentfiction.com/da/episode/2025-12-04-08-38-20-da Story Transcript:Da: Snefnug dalede stille udenfor vinduet, dækkende verden i et hvidt tæppe.En: Snowflakes drifted quietly outside the window, covering the world in a white blanket.Da: Inde på hospitalet var der en lidt anden stemning.En: Inside the hospital, there was a slightly different mood.Da: Rummet var koldt og sterilt, men små papirfnug og et lille plastikjuletræ i hjørnet gav et hint af højtidsstemning.En: The room was cold and sterile, but small paper snowflakes and a little plastic Christmas tree in the corner gave a hint of holiday spirit.Da: Mikkel lå i sengen, pakket ind i et blødt tæppe.En: Mikkel lay in the bed, wrapped in a soft blanket.Da: Han havde netop gennemgået en mindre operation, og kroppen krævede hvile.En: He had just undergone a minor operation, and his body needed rest.Da: Han kiggede ud af vinduet, mens tankerne kredsede om den forestående jul.En: He looked out the window, while his thoughts circled around the upcoming Christmas.Da: Det var en tid for familie, men Mikkel ønskede ikke at være en byrde.En: It was a time for family, but Mikkel didn't want to be a burden.Da: Han sukkede dybt.En: He sighed deeply.Da: Døren åbnede sig stille, og der trådte Astrid ind med et smil på læben.En: The door opened quietly, and Astrid stepped in with a smile on her face.Da: "Hej storebror," sagde hun glad.En: "Hi big brother," she said happily.Da: "Hvordan har du det?"En: "How are you feeling?"Da: Mikkel prøvede at smile, men bekymringerne vejede tungt.En: Mikkel tried to smile, but the worries weighed heavily.Da: "Du behøvede ikke komme, Astrid," sagde han.En: "You didn't need to come, Astrid," he said.Da: "Jeg klarer mig."En: "I can manage."Da: Astrid satte sig ved siden af hans seng.En: Astrid sat down next to his bed.Da: "Julen handler om at være sammen," svarede hun.En: "Christmas is about being together," she replied.Da: "Og jeg vil ikke lade dig være alene her."En: "And I won't let you be alone here."Da: Mikkel trak vejret dybt.En: Mikkel took a deep breath.Da: Han mindedes tidligere juleaftener, fyldt med latter, julemad og duften af nybagte småkager.En: He remembered past Christmas Eves filled with laughter, Christmas food, and the smell of freshly baked cookies.Da: De varme minder bragte et svagt smil til hans læber.En: The warm memories brought a faint smile to his lips.Da: "Kan du huske dengang, vi byggede en snemand i mors have?"En: "Do you remember the time we built a snowman in mom's garden?"Da: spurgte Astrid pludseligt.En: Astrid suddenly asked.Da: "Den havde gulerodsnæse og fars gamle hat."En: "It had a carrot nose and dad's old hat."Da: Mikkel lo svagt, minderne om den skæve snemand fik ham til at føle sig varmere.En: Mikkel laughed softly, memories of the crooked snowman made him feel warmer.Da: "Ja, det var en god dag," indrømmede han.En: "Yes, that was a good day," he admitted.Da: Astrid trak en lille pakke op af tasken.En: Astrid pulled a small package out of her bag.Da: "Jeg har noget til dig," sagde hun.En: "I have something for you," she said.Da: Mikkel åbnede pakken og så en smuk, håndlavet ornament.En: Mikkel opened the package and saw a beautiful, handmade ornament.Da: "Den er til vores juletræ, for vores familie," forklarede hun.En: "It's for our Christmas tree, for our family," she explained.Da: Hans hjerte blev fyldt med varme, og øjnene blev våde.En: His heart filled with warmth, and his eyes became wet.Da: Den lille gestus betød alverden for ham.En: The small gesture meant the world to him.Da: "Tak, Astrid," sagde han blødt, vel vidende at kærligheden i deres familie altid vil være der.En: "Thank you, Astrid," he said softly, knowing that the love in their family would always be there.Da: For første gang i lang tid følte Mikkel sig ikke alene.En: For the first time in a long time, Mikkel didn't feel alone.Da: Han så på sin søster og nikkede.En: He looked at his sister and nodded.Da: Måske var det okay at tage imod hjælp og værdsætte de mennesker, der var omkring ham.En: Maybe it was okay to accept help and appreciate the people around him.Da: "Skal vi tage hjem og fejre jul sammen?"En: "Shall we go home and celebrate Christmas together?"Da: spurgte Astrid, mens hun rejste sig op.En: Astrid asked as she stood up.Da: Mikkel tog hendes hånd og smilede.En: Mikkel took her hand and smiled.Da: "Det lyder som en plan," sagde han.En: "That sounds like a plan," he said.Da: Før han vidste af det, trådte de ud i sneen, hånd i hånd, klar til at fejre julen med deres familie.En: Before he knew it, they stepped out into the snow, hand in hand, ready to celebrate Christmas with their family.Da: Mikkel havde lært, at nogle gange betyder familie mest, og at man er stærkest, når man er sammen.En: Mikkel had learned that sometimes family means the most and that you are strongest when you are together. Vocabulary Words:drifted: daledesterile: steriltslightly: lidtoperation: operationburden: byrdesigh: sukkedeworries: bekymringerweight: vejedemanage: klareappreciate: værdsættegesture: gestusornament: ornamenthints: hintupcoming: foreståendememories: minderplan: plancelebrate: fejrehospital: hospitaletlaughed: loscenic: skævecrisply: sprødttogether: sammenspirit: åndencrooked: skævsmile: smilnod: nikkesoftly: blødtslightly: lidtwrapping: indpakningstepped: trådte

In der heutigen Folge sprechen die Finanzjournalisten Anja Ettel und Holger Zschäpitz über das Microsoft-Barometer und seine Folgen, das Inditex-Luxusproblem und gute Stimmung bei Salesforce. Außerdem geht es um Eli Lilly, AbbVie, Johnson & Johnson, Novo Nordisk, AstraZeneca, Abbott Laboratories, UnitedHealth Group, Bristol Myers Squibb, Dexcom, Align Technology, ResMed, Hims & Hers, JD Health International, iRhythm Technologies, Pro Medicus, Oscar Health, Xtrackers MSCI World Health Care (WKN: A113FD), Amundi S&P World Health Care Screened (WKN: A3DSTC), Franklin Future of Health and Wellness (WKN A3EFKW), Global X Telemedicine & Digital Health (WKN A2QKQ1), Xtrackers MSCI Genomic Healthcare Innovation (WKN: DBX0R2), Agilent, Roche, Vertex, Microsoft, Meta, Alphabet, Amazon, Nvidia, Salesforce, SAP, Snowflake, Inditex, H&M, Next, LVMH, Hermès, Aumovio, TKMS, Hellofresh, Gerresheimer, Ottobock, Tonies, PSI Software, Verbio, LPKF, Stratec, Thyssenkrupp Nucera, Procredit, Amadeus Fire, Bayer, BASF, Corteva, Syngenta, Formycon und PNE. Die aktuelle "Alles auf Aktien"-Umfrage findet Ihr unter: https://www.umfrageonline.com/c/mh9uebwm Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts und AAA-Newsletter.[ Hier bei WELT.](https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html.) [Hier] (https://open.spotify.com/playlist/6zxjyJpTMunyYCY6F7vHK1?si=8f6cTnkEQnmSrlMU8Vo6uQ) findest Du die Samstagsfolgen Klassiker-Playlist auf Spotify! Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? [**Hier findest du alle Infos & Rabatte!**](https://linktr.ee/alles_auf_aktien) Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

Writer and producer Joseph Lidster visits the podcast for a fun chat about Dark Shadows and his experiences as writer and co-producer on the Big Finish range of Dark Shadows audio dramas! In addition to taking up the DS producing reins at Big Finish, Joe wrote dramatic readings and audio plays such as London's Burning, The Fall of the House of Trask, and Snowflake, and co-wrote The Crimson Pearl and the full-cast serial Bloodlust. If you love the Big Finish DS audio dramas, you won't want to miss this one!Terror at Collinwood and Shilling Shockers shirts, stickers, mugs, and merch at the Penny Dreadful XIII TeePublic shopHelp support the podcast by donating at Buy Me a CoffeeJoin the Terror at Collinwood Facebook PagePenny Dreadful's Shilling Shockers Etsy shopBig Finish – home of Dark Shadows audio dramas - WEBSITE LINKGeorge Kalogridis YouTube ChannelSurfing the Shadows surf rock cover of Robert Cobert's Dark Shadows theme by Johnny D & The MoonlightersTaC logos by Eric Marshall

A big day of tech earnings, including results from Salesforce, Snowflake, C3.AI and UiPath. BD8 Capital's Barbara Doran and Charles Schwab's Kevin Gordon break down the market action and react to the key earnings. C3.AI CEO Stephen Ehikian joins to break down the company's quarter and broader trends in the industry. UiPath CEO Daniel Dines talks enterprise spending levels after his company's earnings. Fortune Brands CEO Nicholas Fink on the health of the consumer and where they are spending in their home. Plus, Jensen Huang heads to Capitol Hill to lobby for export control changes.  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Umesh Sachdev, cofounder and CEO of Uniphore, joins Shripati Acharya for a deeply insightful and very real conversation about what it actually takes to build and scale enterprise AI. Whether you are a founder, a product leader or someone thinking seriously about enterprise AI, this episode will give you clarity on business AI you won't find elsewhere.What you'll take away:• A clearer understanding of what Uniphore does as an end-to-end enterprise AI and data platform• Why so many AI pilots “fail” at first and how that failure can actually be meaningful progress• How enterprises are achieving predictable outcomes using unitary agents, workflow orchestration, guardrails and fine-tuned SLMs• The inside story of Uniphore's strategic raise and why some of the world's biggest AI and data companies chose to back them⭐Episode Timestamps00:00 Introduction03:00 – What Uniphore Actually Does 05:47 – Why Enterprise AI Struggles to Scale Beyond Pilots10:08 – The Determinism Problem: Why AI Gives Different Answers Each Time12:32 – Unitary Agents and Workflow Orchestration for Predictable AI14:00 – Small Language Models vs Large LLMs for Enterprise Use Cases15:25 – Why Guardrails and Governance Matter in Real Deployments16:39 – One Big Agent Fails but Ten Small Agents Work Better20:40 – Why AI Pilots Fail and Why That Is a Good Thing22:20 – Converting Experiments into Enterprise-Scale Adoption24:26 – 35,000 Invoices a Week with Only Four Humans: ROI Case Study26:25 – What Enterprises Really Look for in AI Systems28:45 – Lessons from Building Across India and the US32:51 – Why Founders Must Be Close to Their Biggest Market34:44 – Structuring Teams Across Geographies for Global Scale38:10 – The Journey of Building Uniphore Over Seventeen Years42:36 – Hard Lessons Learned Along the Way46:45 – Why NVIDIA, Snowflake, AMD and Databricks Invested51:17 – How the Strategic Round Came Together52:22 – Closing NoteIf this conversation resonates with you, drop your biggest takeaway in the comments and subscribe for more in-depth founder and VC discussions.#EnterpriseAI #Uniphore #ArtificialIntelligence #AIAgents #SmallLanguageModels #AIInnovation #AIinBusiness #FounderInsights #StartupLessons #TechLeadership #GlobalScale #FutureOfWork #PrimeVenturePartnersPodcast

Crypto turned around yesterday but Marvell Technology earnings appeared to disappoint. Today brings Salesforce results and ADP jobs data, along with Macy's and Snowflake.Important DisclosuresThis material is intended for general informational purposes only. This should not be considered an individualized recommendation or personalized investment advice. The investment strategies mentioned may not be suitable for everyone. Each investor needs to review an investment strategy for his or her own particular situation before making any investment decisions.The Schwab Center for Financial Research is a division of Charles Schwab & Co., Inc.All names and market data shown above are for illustrative purposes only and are not a recommendation, offer to sell, or a solicitation of an offer to buy any security. Supporting documentation for any claims or statistical information is available upon request.Past performance is no guarantee of future results.Diversification and rebalancing strategies do not ensure a profit and do not protect against losses in declining markets.Indexes are unmanaged, do not incur management fees, costs, and expenses and cannot be invested in directly. For more information on indexes, please see schwab.com/indexdefinitions.The policy analysis provided by the Charles Schwab & Co., Inc., does not constitute and should not be interpreted as an endorsement of any political party.Fixed income securities are subject to increased loss of principal during periods of rising interest rates. Fixed income investments are subject to various other risks including changes in credit quality, market valuations, liquidity, prepayments, early redemption, corporate events, tax ramifications, and other factors.All expressions of opinion are subject to change without notice in reaction to shifting market, economic or political conditions. Data contained herein from third party providers is obtained from what are considered reliable sources. However, its accuracy, completeness or reliability cannot be guaranteed.Investing involves risk, including loss of principal, and for some products and strategies, loss of more than your initial investment.The Schwab Center for Financial Research is a division of Charles Schwab & Co., Inc.Apple Podcasts and the Apple logo are trademarks of Apple Inc., registered in the U.S. and other countries.Google Podcasts and the Google Podcasts logo are trademarks of Google LLC.Spotify and the Spotify logo are registered trademarks of Spotify AB.(0131-1225) Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Snowflake (SNOW) shares have rallied nearly 50% this year, outperforming its peers in the cybersecurity sector. Rick Ducat examines the chart ahead of earnings and Tom White places an example trade.======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – / schwabnetwork Follow us on Facebook – / schwabnetwork Follow us on LinkedIn - / schwab-network About Schwab Network - https://schwabnetwork.com/about

Chris and Daniel unpack how AI-driven document processing has rapidly evolved well beyond traditional OCR with many technical advances that fly under the radar. They explore the progression from document structure models to language-vision models, all the way to the newest innovations like Deepseek-OCR. The discussion highlights the pros and cons of these various approaches focusing on practical implementation and usage.Featuring:Chris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XSponsors:Shopify – The commerce platform trusted by millions. From idea to checkout, Shopify gives you everything you need to launch and scale your business—no matter your level of experience. Build beautiful storefronts, market with built-in AI tools, and tap into the platform powering 10% of all U.S. eCommerce. Start your one-dollar trial at shopify.com/practicalaiFabi.ai - The all-in-one data analysis platform for modern teams. From ad hoc queries to advanced analytics, Fabi lets you explore data wherever it lives—spreadsheets, Postgres, Snowflake, Airtable and more. Built-in Python and AI assistance help you move fast, then publish interactive dashboards or automate insights delivered straight to Slack, email, spreadsheets or wherever you need to share it. Learn more and get started for free at fabi.aiFramer – Design and publish without limits with Framer, the free all-in-one design platform. Unlimited projects, no tool switching, and professional sites—no Figma imports or HTML hassles required. Start creating for free at framer.com/design with code `PRACTICALAI` for a free month of Framer Pro.Upcoming Events: Register for upcoming webinars here!

I speak to Robert in Slovakia who shares his family's encounter with a 'Magical Grandpa' encounter when he was seven years old.When a local woman at his school shared her own mystical encounters, it seemed to offer him an opportunity to understand the world in a very different way ⭐️ JOIN THE MODERN FAIRY SIGHTINGS COMMUNITY ⭐️ https://www.patreon.com/c/themodernfairysightingspodcast/membership If you're looking for exclusive bonus material, monthly zoom chats with like-minded folks, access to the Discord chat channels, quiet meditation gatherings and meeting other members, join us at: https://www.patreon.com/c/themodernfairysightingspodcast/membership S U P P O R T If you'd prefer to support the Modern Fairy Sightings with a one off donation, you can ‘buy me a coffee' and I'd be very grateful

John McMahon is widely regarded as one of the greatest enterprise-software sales leaders of all time. He's the only person to have served as Chief Revenue Officer at five public software companies: PTC, GeoTel, Ariba, BladeLogic and BMC Software. He helped scale BladeLogic from a startup into a public company — ultimately leading to its ~$880M sale to BMC — and drove GeoTel into a multi-billion dollar acquisition. Today he sits on the boards of top names such as Snowflake and MongoDB, while also mentoring and influencing a who's-who of modern SaaS sales leaders. AGENDA: 03:33 The Art and Science of Sales: Insights from a Veteran 04:29 Adapting Sales Strategies in the Age of AI and PLG 07:47 The Ultimate Framework to do Deal Qualification 14:13 How to Drive Urgency and Maintain Sales Process 20:06 How to Hire the Best Sales Reps 25:11 Step-by-Step Guide to Training Sales Reps 45:22 The Mindset of the Best Sales Reps 54:55 Single Most Important Skill to Win in Sales  

This week I had the pleasure of talking all things housewives with my friend Carlos J. Harris! Check out the visual on YouTube! We talked the recent Potomac/Atl arrests, Salt Lake City (the ladies are TAKING IT) and the girls down in the P (they are doing their jobs!) Let's GO! Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.