Podcasts about Luma

PODCAST LAS NOTICIAS CON CALLE DE 22 DE JULIO - Brutal ventaja para PR si sabemos aprovecha, Trump planifica tarifas de 100% para medicamentos genéricos - FT Apagones son más largos, aunque menos frecuentes - El Vocero Secuestrado desde anoche en caso Elvia - El Vocero Empresas tienen que crear su propia agua y reciclarla para poder operar en PR - El Vocero Pelea por si el daño brutal en Central Costa Sur fue culpa de LUMA o de Genera - El Nuevo Día Trump tumba billones por supuestos casos de corrupción tras desastres en USVI - El Nuevo Día Junta regaña a DACO por no haber hecho tecnología para empresarios acordada y en lío de Valerie - El Nuevo Día Trump dice que va a bombardear zona nuclear de Irán - Fox News China salvaje, forma montones de operativos navales en zona de otros países incluyendo Taiwán y Filipinas - Economist Encuentran avión estrellado en PR en los años 50 - Primera Hora Radican cargos contra uno del os cabilderos más influyentes en PR, Ariel de Codepola supuestamente agredió a un sujeto - Primera Hora • Muchos de ustedes se están preparando para volver a la rutina, comprando los materiales para la escuela, la universidad o hasta el trabajo.Para ayudarte T-Mobile trajo la oferta de back-to-school: un iPhone 17 Pro más un Apple Watch SE 3, ¡por la casa, sin trade-in!Arranca con equipo nuevo y beneficios que otros no te dancomo hotspot ilimitado, streaming incluido, internet y textos ilimitados cuando viajas sin costo adicional.También te puedes llevar el iPad A16 por solo $199 via créditos a tú factura más impuestos. Cámbiate en solo 15 minutos en el app de T-Life y regresabien conectado.Solo con T-Mobile, la mejor red móvil en Puerto Rico.Requiere plan de financiamiento y servicio elegible. Restricciones aplican.#Tmobile#incluyeauspicio Costa de PR bajo aviso de calor extremo - MetrNovo demanda a Lilly por supuestos anuncios engañosos - Semafor ChatGPT admite que su modelo se fue a lo loco a hackear a otra empresa sin ellos tener control sobre el sistema - BBC Vecinos muestran que planta de Guayama de carbón presuntamente ha contaminado hasta cuerpos de agua tras dragado presentar cenizas - El Nuevo Día Presidente de la AAA dice plan Pesquera no sirve - El Nuevo Día Guerra de Irán ya va por 37 billones y se esperan 75 más - Semafor Irán escala: Trump promete bombardear "Pickaxe Mountain". La guerra ya cuesta $37.5 mil millones.Petróleo: Brent sube a $91.10 (+2.11%) por el miedo a Hormuz.IA: Un modelo de OpenAI "se fue rogue" y hackeó a otra empresa de IA.Mercados: Wall Street cerró en verde; los chips empujaron al Nasdaq +1.29%.GOP: Reconciliación es un lío; Cámara y Senado ni se hablan (Punchbowl).Pharma: Novo Nordisk demanda a Lilly por sus anuncios de medicamentos de obesidad. LOS DATOS DEL DÍA (cierre martes 21 de julio) Brent$91.10/barril (+2.11%) Diésel (EEUU retail)~$3.80/gal (referencia, presión al alza por crudo) S&P 5007,509 (+0.89%) Dow Jones52,225 (+0.74%) Nasdaq25,837 (+1.29%) Bono 10 años4.63% (+3 pb) Euro/USD1.1413 (-0.01%) Gas natural$2.86/MMBtu (-0.11%) Hipoteca 30 años~6.63%

PODCAST LAS NOTICIAS CON CALLE DE 20 DE JULIO -  Reunión emergencia entre JGo y su equipo de Fortaleza durante el día de hoy - WUNO Avería en Costa sur por dos semanas deja en problemas sistema energético - Primera Hora Petróleo se trepó otra vez a un mes tras ataques y muertes de soldados - Oil Price Rusia disparó misiles balísticos como no había hecho desde el comienzo de la guerra en la capital - AlJazeera 71% de boricuas de la diáspora favorece la estadidad según encuesta, 68% de los hispanos en general - El Diario NY Alegan que Mamdani considera arrestar a Netanyahu cuando vaya a New York este año - NYPost MMM hoy voy pa Martins BBQEl mejor y más sabroso pollo asado a la varita de Puerto Rico. Cocinando diariamente comida fresca saludable y sabrosa con un montón de complementos para escoger, arroces, habichuelas, verduras, mofongo,tostones,....MMMM....Esto si es criolloMartins BBQ, TOMANDO todas las medidas de salud y sabor para mantener la mesa boricua al dia con opciones para llamar, recoger o delivery por UBER Eats, y DoorDash.MMM Hoy como en Martin's BBQAsado...Jugoso...Sabroso#martinsbbq#incluyeauspicioSe dobla la cantidad de fondos Medicaid - El Vocero Josué Colón responsabiliza a LUMA por fallas de Genera - El Vocero Yovngchimi pide le devuelvan la cadera de oro - El Vocero Cuesta 40 millones evitar la erosión para que caiga el Paseo Lineal de Puerta de Tierra - El Vocero Pablo José propone enmendar la Constitución para referendo revocatorio, segunda vuelta y elecciones por posiciones - Primera Hora Mujer perdió 1,300 billetes por ayudar a Keanu Reeves, sujeto muere por desafío de aguantar respiración bajo el agua, caen varios con rentas de casas de lujo con depósito inmediato - Primera Hora Contrato de generación temporera vuelve a la negociación - El Nuevo Día GENERA podría ser multada por no acabar de poner la generación temporera que lleva casi dos años de atraso - El Nuevo Día Todavía hay problemas de plomo en residencial en Vega Baja - El Nuevo Día Junta culpa a AAFAF por falta de arreglar sistema de energía por fondo rotatorio no tener reglamento, AAFAF culpa a LUMA - El Nuevo Día Sigue inoperante hospital de Vieques y muere ciclista por falta de llegar equipos - El Nuevo Día Cancelacion de destaques en venganza dice Rivera Schatz - El Nuevo Día Junta advierte que hay 20 millones asignados a alcaldes por Legislatura - Metro Mafia institucional en Hacienda no logró nada en PR, pero sí casos federales - Noticel El petróleo Brent rompió los $90 y la gasolina en EEUU regresó sobre $4/galónLOS DATOS DEL DÍA (cierre viernes 17 jul — los mercados de EEUU no abren fin de semana)Brent$88.10/barril (+4.6% vie) · rompió $90 el fin de semanaWTI~$82/barrilDiésel PR (retail)~$1.23–$1.32/litro (DACO, 18 jul)Gasolina PR (regular)~$1.05–$1.10/litroS&P 5007,457.69 (−1.0%)Dow Jones52,146.42 (−0.8%, −406 pts)Nasdaq25,520.24 (−1.4%)Bono 10 años4.55%Euro/USD1.1440Gas natural$2.91/MMBtuHipoteca 30 años6.55% (Freddie Mac)

Broecking, Maxi www.deutschlandfunk.de, Kultur heute

PODCAST LAS NOTICIAS CON CALLE DE 17 DE JULIO - Mega proyecto para arreglar en varias fases el super acueducto - El Nuevo Día500 mil de fianza a sujeto que iba a dejar morir o matar viejita en Las Piedras - El Vocero Se supone que al fin acabe el escaneo de furgones - El Nuevo Día Gas Natural de USA el gran ganador de guerra de Ormuz - Semáforo Trump jura que CHINA interviene en elecciones de USA y comete fraude - CNN Corrección podría mudarse por renta muy cara - El Nuevo Día Supremo no decide si va a resolver el caso de LUMA de arranque - El Nuevo Día Guerra de grandes ligas por pago de COBRA tras impuestos a la construcción de alcaldes - El Nuevo Día Siempre innovando y con los mejores beneficios, MCS Personal Directo te ofrece cubiertas accesibles para que cuides de tu salud y la de los tuyos.Con una amplia red de proveedores de más de 15,000 médicos de libre selección. Reembolso de hasta $40 mensuales por membresía a un gimnasio o por un entrenador personal debidamente certificado. Asistencia en el hogar para servicios de cerrajería, plomería y electricidad de hasta $350 por evento hasta 4 veces al año.¡Únete HOY a la gran familia de MCS!¡Salud que completa tu vida! Llama al 787.945.1259 y oriéntate.Endoso pagado#incluyeauspicio #MCSEmpezarán a cobrar el tren urbano otra vez - El. Vocero Educación dice que ha cumplido tanto con los padres de educación especial que merece que bajen multa de 11 mil diarios a mil - El Nuevo Día Demócratas inundados en dinero en comparación con republicanos para midterms - Punchbowl News Fin de semana sin IVU para escuelas arranca hoy - El Nuevo Día Buscan apoyo a proyecto de status - El Nuevo D´â Ahora Valerie Rodz dice que Domenech sí intervino para detener solicitud de propuestas - El Nuevo Día Le tendrán que dar a los fondos buitres de la deuda de la AEE expediente para ver si gastaron dinero que era para la deuda - El Nuevo DíaLOS DATOS DEL DÍA  Brent ~$84.93/barril · cerca de máximos de 1 mesDiésel/gasolina al alza siguiendo el crudo (dato PR sin confirmar)S&P 500 7,533.77 (−0.51%)Dow Jones 52,552.97 (−0.20%, −105.67 pts)Bono 10 años 4.59% (+0.04)Euro/USD 1.1433 (−0.27%)Gas natural Henry Hub sin confirmar; gas europeo €55/MWh (máx. desde marzo)Hipoteca 30 años 6.55%

#agencias #fortaleza #PNP Ex secretaria del DACO ahora habla de presiones por parte de Domenech. ¿Tenían que acusarla de discrimen para decir que Francisco Domenech presionó desde La Fortaleza para que escogieran otro proveedor para hacer trabajos en DACO? | JGo de vacaciones y un apagón deja sobre 300K sin energía. Zar, José Colón coge a LUMA en el embuste. ¡Conéctate, comenta y comparte! #periodismoindependiente #periodismodigital #periodismoinvestigativo Síguenos en nuestras redes sociales: tiktok.com: https://x.com/Bonita_Radio Facebook: / bonitaradio Instagram: / bonitaradio X: https://x.com/Bonita_Radio

#agencias #fortaleza #PNP Ex secretaria del DACO ahora habla de presiones por parte de Domenech. ¿Tenían que acusarla de discrimen para decir que Francisco Domenech presionó desde La Fortaleza para que escogieran otro proveedor para hacer trabajos en DACO? | JGo de vacaciones y un apagón deja sobre 300K sin energía. Zar, José Colón coge a LUMA en el embuste. ¡Conéctate, comenta y comparte! #periodismoindependiente #periodismodigital #periodismoinvestigativo Síguenos en nuestras redes sociales: tiktok.com: https://x.com/Bonita_Radio Facebook: / bonitaradio Instagram: / bonitaradio X: https://x.com/Bonita_Radio

PODCAST LAS NOTICIAS CON CALLE DE 16 DE JULIO - Gobierno dice que LUMA tiene que irse en el Supremo de PR - El Vocero 200 millones para rehabilitar el tren urbano - El Vocero Nuevo arancel de 25% a Brasil entra el 22 de julio; escalada comercial en curso.Los demócratas se rompen por Israel, sobre 100 votan contra ayudar a Israel - Semafor Bonistas logran aliado en Rivera Schatz, alega que la Junta solo quiere ofrecer poco para seguir quedándose en PR y no negociar pa guisar en PR - Noticel AAA dice que dará créditos por falta de servicio - El Vocero Trump tiene mensaje especial esta noche a las 9PM Un momento para WindMar Home — la empresa con más de 20 años protegiendo los hogares puertorriqueños.Solar para bajar tu factura. Techo para proteger tu inversión. Agua para que nunca te quedes sin — especialmente con las sequías que se aproximan. Y batería para total independencia energética.Todo bajo una misma empresa. Un solo llamado. Llama al 787-489-1155 o visita windmarhome.comWindMar Home — los que se preparan hoy , duermen tranquilos mañana.#incluyeauspicio #windmarhomeAlcaldes se enteran por los medios de racionamiento de agua, Comerío, Cidra, Canóvanas y Río Grande, San Lorenzo no tendrá, no anunciaron en Carolina - El Vocero EEUU atacó un petrolero y objetivos en el norte de Irán; Teherán respondió contra bases estadounidenses en Baréin, Kuwait y Jordania, y advierte que resistirá "hasta el final".Líderes de inteligencia artificial piden regulación de la inteligencia artificial - Axios Al fin aprueban ley para prohibir el escaneo obligatorio de furgones - El Vocero LePen está al frente en las encuestas de Francia - Reuters Se harán 3 casinos más en PR - El Vocero No hay jurisdicción federal en caso de Domenech y Sebastián hasta ahora - El Nuevo Día Huevos bajan demasiado de precio tras dumpeo federal - El Nuevo Día Albergue se va a quedar con perro que atacó a secretario de Recursos Naturales - El Nuevo Día Corrección no paga la renta de su sede y quieren contrato de 4 millones por quedarse en oficinas - El Nuevo Día Tres testigos dicen que Elvia sacó algo punzante de cartera - El Nuevo Día Sigue la guerra de Paulson v. Ghaffar en el tribunal de PR - El Nuevo Día Este weekend es el back to school sin IVU   LOS DATOS DEL DÍA (cierre / referencia 15-16 jul) Brent$84.95 · +12% en 3 sesiones  Gasolina EEUU (AAA)$3.89/gal · +9¢ semana  S&P 500 (fut.)~7,610 · -0.1%  Dow (fut.)+145 pts · +0.3%  Bono 10 años4.57% Euro/USD1.1431 · +0.1% Gas natural (Europa)€53.1/MWh  Hipoteca 30 años~6.65%

PODCAST LAS NOTICIAS CON CALLE DE 15 DE JULIO - Las primarias no le preocupan a JGo - El Vocero Rivera Schatz refiere a subsecretaria de la gobernación Itza García - El Vocero Bonistas la emprenden contra la Junta porque alegan esconden dinero para no pagar la deuda de la AEE - El Vocero USA envía barcos para confrontar a China en el Pacífico - WSJAhora mismo vuelven a atacar a Irán y cierran el estrecho de Hormuz - WSJProcurador del envejeciente la emprende contra la baby secretaria de la Familia - El Vocero Llega a PR la diarrea explosiva de cyclospora - Metro Adictos a la lotería, aumenta 7% la cantidad de billetes, 780 millones se juegan en PR - El Vocero     •    ¿Te ha pasado que llegas de viaje y se te arruina la ilusión tan pronto ves la factura del teléfono y tienes cargos adicionales?     •    Se suman más y más y más cargos adicionales por cada llamada, mensaje, búsqueda que hiciste.     •    Eso me llegó a pasar, hasta que me cambié a T-Mobile.     •    Los únicos que ofrecen SIN COSTO ADICIONAL internet y textos ilimitados en más de 215 destinos.     •    Ya no me tengo que preocupar cuando viajo, ni cuando regreso porque ya está incluido, sin cargos adicionales.     •    Viaja relax con T-Mobile, ¡Cámbiate hoy en T-Life o llama al 1800TMOBILE!#incluyeauspicio #tmobileDistrito Sports Hub en Centro de Convenciones con 20 millones de inversión - El Vocero Agricultores dicen que la sequía los está destruyendo - Primera Hora Gobernadora dice que LUMA no puede demandar al gobierno y pide al Supremo acoger el caso y resolverlo para sacar a LUMA - Metro Tres años de cárcel para Arriaga por abuso de menor de 12 años - Jay Fonseca PR Prohíben los jetskis en Salinas tras más casos de muerte de manatíes - Primera Hora ICE detiene operativos que incluyan detener carros cuando tras matar joven colombiano, Trump cambia decisión - WSJMoody's da buena nota pero con cuidado a San Juan para emitir deuda - El Nuevo Día EE.UU. golpea Irán por 4to día; Trump amenaza con volar plantas eléctricas y puentes. Brent en $86.82.LOS DATOS DEL DÍA (cierre martes 14 de julio)Brent$86.82/barril  +4.45%WTI~$80/barril (máximo de 4 semanas)Gasolina EE.UU. (prom.)$3.89/galónDiésel EE.UU. (retail)cerca de $5/galónS&P 5007,543.59  +0.38%Dow Jones52,508.27  +0.02%Bono 10 años4.583%Euro/USD~1.14 (últ. dato disp. 11 jul)Gas natural (Henry Hub)~$3.00/MMBtu (11 jul)

When is a brace the right choice? What can it realistically accomplish? And when might it actually hinder recovery? Caroline (Carrie) Adrian, BS, MSPT, PhD, helps us answer these questions and much more.We begin our two-part series on veterinary orthoses and bracing by focusing on the thoracic limb (front leg), trunk & pelvis/hip. We discuss the principles behind orthotic devices, common indications, clinical decision-making, and the importance of selecting the appropriate device for each patient.From shoulder instability to carpal hyperextension injuries, we explore how orthoses can improve function, protect healing tissues, reduce pain, and help dogs return to activity while avoiding common pitfalls.In This Episode:What is the difference between a brace, orthotic, and orthosis?Goals of orthotic management versus immobilizationConservative management +/- orthosis versus surgeryPatient selection: Which dogs are good candidates?The role of canine physical rehabilitation alongside bracingWhy custom fitting and follow-up evaluations matterThoracic Limb Topics CoveredShoulderMedial shoulder instability (MSI in dogs)The controversy surrounding hobbles and when they may—or may not—be appropriateElbowLimited indications for elbow orthosesPotential use in osteoarthritis to diminish the loadA lot of unknowns and potential for the elbowCarpus (Wrist)Carpal hyperextension injuriesWorking and sporting dogsPurpose of carpal wraps and performance supportTrunk Stability & Core SupportBenefits of trunk stabilization devicesSupports for hip dysplasia and Degenerative Myelopathy (DM) with video on our YouTube channelKey TakeawaysBraces are tools—not cures—and work best as part of a comprehensive rehabilitation plan.Correct diagnosis is essential before selecting an orthotic device.Proper fit and regular reassessment are critical to avoid complications such as skin irritation, pressure sores, or altered gait mechanics.Rehabilitation exercises remain an important component of recovery, even when a brace is being used.Coming Next: Part 2This conversation continues in our next episode, where we'll shift our focus to the pelvic limb (back leg), including:Trunk support and hip bracing reviewStifle (knee) injuries and cranial cruciate ligament diseaseMedial patellar luxationTarsal (hock, ankle) injuries and orthotic optionsAchilles tendon injuries and Graduated Flexion Orthoses (GFO)Functional bracing for recovery and long-term managementSkin management with orthosis useWhether you're a veterinary rehabilitation professional, veterinarian, technician, student, or devoted pet owner, Part 2 will continue exploring how orthotic devices can help improve mobility and quality of life for canine patients.Find Dr. Adrian at CanineIQ.net.Companies with products mentioned during this episode:DogLeggsHero BracesThera-PawWigglelessHipLignThanks for listening to PetAbility Podcast! If you enjoyed this episode, please subscribe, leave a review, and share it with colleagues and fellow animal rehabilitation enthusiasts.DisclaimerVitalVet.org, a platform for all things related to pet rehab - product information, education, and resources abound! MedcoVet (show sponsor)  Luma - advanced red-light therapy therapy that puts healing in the hands of the pet owner in the comfort of home! Use Promo Code PETPOD22  to receive discounts from our affiliates!Jope - science-backed supplements Ruff Ramp - a safe alternative to stairs Optimum Pet Vitality - education/coursework  Dr. Buzby's -Toe Grips to prevent slipping, Encore Mobility joint supplement, and Brain Boost cognitive supplement. Using this link donates 20% to PetAbility Calm & Cozy Cat Wrap - a must-have for anybody working with catsHedzUpPets Watercollars – save your dog from drowni...

Recorded on the ground at the Cannes Lions International Festival of Creativity, this Cannes special closes the current series of TellyCast before the summer break. Host Justin Crosby meets three guests working at the point where advertising, entertainment and technology now converge.Jason Day, Head of EMEA at Luma AI, explains how the company is unifying multiple video and image models into a single creative platform, why he believes the technology has moved ahead of consumer expectations, and how brands are building AI capability in-house rather than outsourcing it. He also discusses Luma Agents and the Moses drama series produced with Wonder Project and Amazon Prime.Will Scougal, EVP of Brand and Commercial Partnerships at ITV Studios' Studio 55, unpacks Double Date Island, the TikTok-first dating format built with Tinder and OMD. He sets out why ITV Studios is bringing broadcast-grade IP and creator craft to brands, and why production groups are still rare at Cannes.Emma Hardie Commercial and Brand Director at Aardman, marks 50 years of the studio with a look at how Shaun the Sheep, Wallace and Gromit and a forthcoming Pokémon series translate into brand partnerships, gaming, Roblox and live experiences, from a Japanese farmhouse recreation to Feathers McGraw tattoos in China.TellyCast returns in September, with the Digital Content Forum taking place in London on 5 November. Explore the back catalogue of more than 270 shows, plus recent content from the studio and events, on the TellyCast YouTube channel.

PODCAST LAS NOTICIAS CON CALLE DE 8 DE JULIO - Casi 700 agentes de la policía nuevos comienzan hoy - El VoceroGuerra por destaques - Noticel Trump declara fin del cese al fuego y se atacan Irán y USA, sube el petróleo 5% - CNBC Bebé de 18 meses declarado muerto en piscina estaba vivo en la morgue - Primera Hora 742 casos de hospitales por calor, aunque no son registradas muchas muertes como tal porque se reportan como ataques cardíacos o respiratorios, etc. - El Vocero Detienen racionamiento por ahora porque llovió ayer, mientras hay estado de emergencia - El VoceroAEE tiene déficit de 10 billones de dólares - El Nuevo Día Toa Vaca, Carraízo y Cidra bajo observación por falta de agua - El Nuevo Día Politank radica tarde informes por decreto contributivo - El Nuevo Día     •    ¿Te ha pasado que llegas de viaje y se te arruina la ilusión tan pronto ves la factura del teléfono y tienes cargos adicionales?     •    Se suman más y más y más cargos adicionales por cada llamada, mensaje, búsqueda que hiciste.     •    Eso me llegó a pasar, hasta que me cambié a T-Mobile.     •    Los únicos que ofrecen SIN COSTO ADICIONAL internet y textos ilimitados en más de 215 destinos.     •    Ya no me tengo que preocupar cuando viajo, ni cuando regreso porque ya está incluido, sin cargos adicionales.     •    Viaja relax con T-Mobile, ¡Cámbiate hoy en T-Life o llama al 1800TMOBILE!#incluyeauspicio #TmobileGobernadora le tira a LUMA por informar cuando hay apagones por causa de Genera - El Vocero Venezuela exporta 20% más petróleo que antes de sacar a Maduro - Bloomberg 17 asesinatos más que el año pasado - El Vocero Ucrania vuelve a dejar sin combustible a Rusia tras nuevos ataques en dos refinerías - BloombergUSA obliga a hospitales a meter mejor comida y más saludable - Axios Trump ordena cortar todo el comercio con Españaa - Economist  Casi 3700 muertes por terremotos de Venezuela - Noticel Seguros de hogares subió de 9% comparado con el año pasado - El Vocero Activan guardia nacional para fuegos forestales y llevar agua - Primera Hora Yovngchimi va a escribir letras más limpias - Primera Hora Fuera de control especies exóticas sueltas aquí - El Nuevo Día TrueNorth comparace a nombre de Smartmatic para llevarse contrato de contar los votos en la CEE según El Nuevo Día LOs Tirri vuelven a traer a Dairy Queen a PR - El Nuevo Día Piden salida de Graham Platner como candidato, ¿hasta dónde debe ser esa una decisión tras ganar proceso de primaria? - CNNLOS DATOS DEL DÍABrent$78.07/bbl ▲ +5.27%S&P 5007,503.85 ▼ -0.45%WTI$74.03/bbl ▲ +5.10%Dow Jones52,925.15 ▼ -0.25%Diésel EE.UU. (retail)$4.77/galBono 10 años4.53% (subiendo a 4.57%)Gas natural (Henry Hub)$3.30/MMBtu ▲ +1.07%Euro/USD1.1397Hipoteca 30 años6.63%Gasolina reg. EE.UU.$3.80/gal

We've been running a bit of an Agent Cloud series surveying all the top inference/compute/cloud providers, from Databricks to Daytona to Railway and, even further back, E2B, but we're excited to conclude this series returning to Modal, which has just raised a monster $355M Series C.The cloud was built for developers. But agents are now changing that.The old infra stack was designed for a human who could read docs, reason through YAML, and understand dashboards to figure out what they need when something broke. While this was painful for developers, it worked since they could fill in missing context in their heads.However, agents don't have that luxury. Now in this new era of agents, everything has to be tighter.They need a place to write code, run it, inspect the output, change the environment, debug failures, and try again. Fast iteration and feedback loops with all the necessary context are crucial for agents to operate properly. Furthermore, sandboxes are a clear representation of this shift as agents can easily spin up isolated environments. This programmatic infra even extends to research:Two years ago, we were one of the first to cover Modal with CEO Erik Bernhardsson and Alessio designed our favorite LS thumbnail of all time:At the time, Modal was just a teeny little company with a $17M Series A.Today, fresh off their $355M Series C, Modal is one of the clearest examples of the agent cloud future being built in real time: a cloud platform moving past traditional web app assumptions toward the workloads AI actually creates such as elastic inference, sandboxes, GPU burst, post-training, background agents, and infrastructure that agents themselves can operate.In this episode, Modal CTO Akshat Bubna joins swyx and Vibhu to unpack why AI applications don't fit traditional cloud assumptions, why Kubernetes was never designed for bursty compute-heavy workloads, and why Modal is now shifting from developer experience to agent experience.We go deep on Modal's AI infra stack: serverless functions, decorator-based infrastructure, elastic inference for custom models, GPU snapshotting, DeFlash, speculative decoding, Auto Endpoints, sandboxes, persistent storage, networked containers, private IPv6, RDMA, multi-node training, and Modal's capacity pool across 17 cloud providers. Akshat also explains why RL rollouts can require 100,000 sandboxes, why production agents need hard guardrails, why observability may matter more than reading code, and why AI has made infrastructure exciting again.We discuss:* Why Kubernetes wasn't built for bursty AI workloads* How Modal started as a better runtime before becoming an AI cloud* Why Modal added GPUs before ChatGPT* The shift from developer experience to agent experience* Why observability matters when agents are writing the code* Elastic inference for custom models across audio, video, robotics, and comp bio* GPU snapshotting, cold starts, and why inference workloads are so bursty* Why RL rollouts can require 100,000 sandboxes* DeFlash, speculative decoding, and frontier-level inference performance* Auto Endpoints and making optimized inference easier to deploy* What Modal adds beyond vLLM, SGLang, and raw GPU rental* Modal's 17-cloud capacity pool and supercloud strategy* Networked sandboxes, sidecars, private IPv6, and RDMA* Serverless multi-node training for post-training and research workloads* Auto-research, model-guided sweeps, and agents launching GPU experiments* Compute strategy, capacity planning, and batch tiers* Why production agents need specialized sandboxes and hard guardrails* Modal's take on managed agents, CI, Gitpod/Ona, Python, TypeScript, and Modal BenchAkshat Bubna* LinkedIn: https://www.linkedin.com/in/akshat-bubna-188885103* X: https://x.com/akshat_bModal* Website: https://modal.comTimestamps00:00:00 Introduction00:00:39 Modal's origin and why Kubernetes wasn't enough00:04:32 Developer Experience → Agent Experience00:06:21 Modal's AI cloud primitives00:09:14 Sandboxes, agent loops, and proto-Cognition00:12:12 Elastic inference, GPU snapshotting, and 100,000 sandboxes00:15:24 DeFlash, speculative decoding, and Auto Endpoints00:19:59 Production-grade inference beyond raw GPUs00:22:00 Background agents, Ramp Inspect, and the agent lifecycle00:24:08 Modal's 17-cloud supercloud strategy00:26:40 Networked sandboxes, private IPv6, and RDMA00:32:48 Multi-node training, post-training, and auto research00:37:36 Compute strategy, capacity planning, and batch tiers00:40:55 Open models, real-time AI, and production agent infra00:43:06 Hard guardrails, managed agents, and specialized sandboxes00:46:06 Why AI made infrastructure exciting again00:48:30 Model APIs, differentiated products, and agentic video00:51:50 CI, coding-agent infra, SDKs, and Modal Bench00:57:28 Closing ThoughtsTranscriptIntroduction: Modal, Series C, and the Art PartySwyx [00:00:00]: We're here with Akshat, CTO of Modal, together with Vibhu. Congrats on your Series C.Akshat [00:00:10]: Thank you.Swyx [00:00:11]: Your party yesterday was amazing.Akshat [00:00:15]: Yeah.Swyx [00:00:15]: From all the photos and all the swag.Akshat [00:00:17]: We had a bunch of art installations, which was fun, seeing, like, our products on pedestals next to, like, Rodin.Swyx [00:00:25]: Very nice. Very nice. When you started, it was not the GPU inference company. Maybe it was in your mind. Take us back to the origin story.Modal's Origin: A New Runtime Beyond KubernetesAkshat [00:00:39]: I first met Eric, who's the CEO, through an investor. Back then Eric was already thinking about building, a new runtime, and he got there thinking through why are workflow orchestration products so hard to use. It's because you have to run them on Kubernetes. Kubernetes is hard to manage. It's not built for burstiness and, custom images,Swyx [00:01:03]: YeahAkshat [00:01:03]: It has a terrible developer experience.Swyx [00:01:05]: And I'll, I'll interjectAkshat [00:01:06]: YeahSwyx [00:01:07]: For listeners, who are new, we interviewed Eric two years ago, and there's a bit more of the story there from Spotify and all those things.Swyx [00:01:14]: And I came across Eric through Data Council because he did that talk on the serverless container stack that you guys did, which was like, that was my first like, “Okay, I need to take Modal very seriously” moment.Akshat [00:01:26]: Yeah.Swyx [00:01:26]: But it was still very unclear, like, do I need all this for just my data pipelines?Akshat [00:01:33]: Yeah. initially what we were thinking about was if we build a better runtime, it's a very useful primitive in itself. It's There's a lot of things that, get solved by serverless functions, like you can do, ETL stuff, you can do job queues, you can do all this, like, bursty processing, which it turns out every company had needs for. but then we also were thinking about this as like, this is a primitive that we can build a whole collection of products on, which are very verticalized. So perhaps data engineering would've been the first one, but we were thinking about inference. Back then it was more classical inference, like computer vision stuff and running XGBoosts and whatnot. But we added GPUs to the product a year before ChatGPT came out.From Serverless Containers to GPU WorkloadsSwyx [00:02:19]: Nice.Akshat [00:02:19]: We just didn't think it would be that big of a deal.Swyx [00:02:22]: Yeah, just like add A100.Vibhu [00:02:23]: Was there any, like, early key problem that really sparked off why you built it?Akshat [00:02:28]: Yeah. Primarily it's just, none of the tooling that was out there was built for, one, a really great developer experience, and also there's a general trend of, a lot of the workloads that we were seeing were very. I wish there was a better word for it, but compute-heavy. Like, they need, one, like, need a lot more resources, so you need to burst up and down a lot, versus like Kubernetes designed for, like, slow scaling and, more for, like, web server use cases. And also there's just a lot more specialization in, like, what kinds of environments these workloads run in. Like, we had sometimes they need accelerators, sometimes they need different kinds of images, and this is just like a consistent thing that we saw across a lot of companies. That would be the next step.Software-Defined Infrastructure and Decorator-Based DXSwyx [00:03:13]: Yeah. Yeah. Be nice. I don't know how much this factored into the early story, but I wrote a post when I was at Temporal about infrastructure, software-defined infrastructure or something like that.Akshat [00:03:22]: Yeah, the self-provisioningSwyx [00:03:23]: Self-provisioning.Akshat [00:03:24]: Yeah.Swyx [00:03:24]: Yeah. I can't even remember my own post.Swyx [00:03:26]: And then you put me on the landing page.Akshat [00:03:28]: Yeah. We really like, the term and so we stole it.Swyx [00:03:32]: Because you had the insight that everything can just be in decorators co-located with the code, right?Akshat [00:03:37]: Yeah.Swyx [00:03:37]: Was that a big part of the originalAkshat [00:03:39]: YesSwyx [00:03:39]: Story or it was just like a DX layer?Akshat [00:03:41]: That was, really important because we really didn't want people to spend, so much time, writing YAML, and it seemed like you could really condense the surface area of what you're doing, put it in code so you can operate on it just like you operate on other code, and like build stuff that's more expressive and dynamic. and so yeah, that was always a very important part.Swyx [00:04:04]: Then the pushback is this is a DSL.Akshat [00:04:07]: Yeah.Swyx [00:04:07]: It's you're closed source. I am locked into Modal.Akshat [00:04:11]: Yeah. We never really got pushback for that because the nice thing about Modal is you can bring whatever code you have, and sure, the DSL is at the configuration layer for, what hardware you're using, how you're scaling things up, but you still own the code.Akshat [00:04:27]: And that's, that's been an important, part of our story, even as we do inference now.Swyx [00:04:32]: Yeah.Vibhu [00:04:32]: How much of do you think still stays the same today? Like if you were to build something today, DevX very important, but I feel like, a lot of this has been changed with just hook it up to an agent, have Claude Code, have Codex implement a tool. there's very agent native primitives that are different than if I'm doing this myself, right?Developer Experience → Agent ExperienceAkshat [00:04:54]: We've changed our SDK team to think about agent experience instead of, developer experience and we think that the same benefits that apply for DX also apply for AX, which is why would you have an agent read through hundreds of Kubernetes files and like write YAML that's not even typed when it can make a couple of changes in a decorator and it gets this self-provisioning runtime of, being able to see its changes live in action? yeah, it just seems from the customers we talk to, they find Modal is much faster for agents to use versus operating on a different substrate.Swyx [00:05:34]: Yeah, because like you, again, you co-locate the infrastructure requirements to the code that runs it.Akshat [00:05:38]: Yeah.Swyx [00:05:38]: Well, the negative thesis now is that nobody's looking at their code anymore, so there's no point.Akshat [00:05:44]: Yeah, people aren't looking at code. one thing we still see is really important is observability.Swyx [00:05:51]: Yeah.Akshat [00:05:51]: Like how good is your dashboard? And of course, like we have, we push a lot of it to the CLI so the agents can do their own investigation, but you still need humans to go interpret what's going on and, make judgment calls and whatnot. and that's I feel like, Maybe more important now than looking at the code itself.Swyx [00:06:11]: Yes, because like, you can try to treat the code as a black box and then use, see the observable action that comes out of it, and then just prompt a change.What Modal Is For: AI Cloud PrimitivesAkshat [00:06:21]: Yeah.Swyx [00:06:22]: So I think it takes a bit of restraint to not specialize, to say, “I want to ship a new primitive,” and then just be general purpose.Swyx [00:06:31]: People ask you, “What are you for?” You're like, “ I don't know. We can do this, we can do that.”Vibhu [00:06:36]: Well, I'd be curious to see, like, okay, if we were to ask you, like, what is Modal for even at a high level? There's a lot you guys do, sandboxes, GPUs, everything. How do you answer?Akshat [00:06:46]: Modal is a cloud platform that's built for, where we've built the primitives from scratch for AI applications. and right now it covers, inference, training, batch processing, and sandbox workloads.Akshat [00:07:00]: But we're building a lot moreSwyx [00:07:02]: I noticed you didn't say web server, so there is still a role for, like, the always-on large-scale Kubernetes type things.Akshat [00:07:09]: Yeah, absolutely. We're, we're not trying to compete with the renders of the world, because yeah, we think the differentiator for us is the, are the workloads that need specialized compute, need to scale up and down a lot. yeah, they're, they're, they're just shaped differently.Working Alongside Frontier StartupsVibhu [00:07:26]: I think you're building a lot of it alongside the startups, right? They're innovating quite a bit, even in your, like, latest blog post. Like, even in the series C, the customers that you mention here, the cognitions, technical ones, ramps and whatnot, they're, they're innovating with you, right? And that's not something AWS is doing directly with.Akshat [00:07:45]: Yeah, absolutely. I think, this is again classic. We're a small team. We can move really fast. our engineers are working with our customers and figuring it out. Yeah.Swyx [00:07:54]: So my first week at Cognition, I walked in, there was someone wearing a Modal shirt. I was like, “What are you doing here?” They're like, “Yeah, I just. I am embedded inside of Cog.”Akshat [00:08:05]: Yeah, I think that was Peyton. We sent him overSwyx [00:08:07]: Yeah.Akshat [00:08:07]: Because, the latency of communication was too high otherwise.Swyx [00:08:12]: Yeah, distributed node, you have to - you have to place one and collocate.Vibhu [00:08:16]: Yeah.Swyx [00:08:16]: So I had a, I had direct personal experience, right? So I worked on smol developer three years ago. it was inspired by Claude 1. I think you onboarded me at some point, like, just before, and I was like, “Oh, like, I need some bursty compute. Like, I was just gonna try using Modal.” And it was a, it was a pretty pleasant experience. apparently, I showed up in the board meeting, like the analytics.smol developer, Sandboxes, and Proto-CognitionAkshat [00:08:39]: Yeah, you blew up on Hacker News and,Swyx [00:08:41]: YeahAkshat [00:08:41]: We got a big traffic spike. I. I think the way you used smol developer was Modal functions for running stuff, which was. Like, the, that was a good use case. but then, yeah.Swyx [00:08:53]: Yeah. That - So to me, that was proto-cognition.Akshat [00:08:55]: Right.Swyx [00:08:56]: If only I had, like, stuck to it.Swyx [00:08:58]: Like, that was like, if - did you say draw the tech treeAkshat [00:09:00]: AbsolutelySwyx [00:09:00]: You're just like, “Yeah, like, probably this will happen.”Akshat [00:09:02]: Yeah. Like, he was so close. You were just rebuilding upon usSwyx [00:09:04]: I just didn't realize.Akshat [00:09:05]: But the funny story there is at the same time, we were talking to a bunch of customers who needed something like sandboxing.Swyx [00:09:14]: Yeah.Akshat [00:09:14]: This is like twenty-three.Swyx [00:09:15]: Yeah.Akshat [00:09:16]: So we builtSwyx [00:09:17]: You introduced a new API right after that.Akshat [00:09:18]: Yeah.Swyx [00:09:19]: Yes.Akshat [00:09:19]: Like, we built sandboxes in May of twenty-three before anyone was even knew this was gonna be a thing. And the first example we published was, we took smol developerSwyx [00:09:28]: Smol developerAkshat [00:09:28]: And put it in a loop, so the agent can iterate on itself.Swyx [00:09:33]: Loops are hot these days.Vibhu [00:09:34]: It's the looper.Akshat [00:09:34]: Yeah.Vibhu [00:09:35]: Loops in. When was this, twenty-three?Akshat [00:09:38]: Yeah.Vibhu [00:09:39]: A small check.Akshat [00:09:39]: Yeah.Swyx [00:09:39]: It's like twenty-three. so the. the, those for listeners, like, the problem was the models are not built for any of this, right?Swyx [00:09:46]: Like, you're just trying to like. They're not post-training to understand, like, looping and, like, self-correction and tool calling was there, but, like, also not that great.Akshat [00:09:55]: Yeah.Akshat [00:09:55]: I don't remember if you used tool calling in this one, but yeah, the models would just diverge after like ten iterations and not produce anything meaningful.Swyx [00:10:03]: Yeah. But like, then. So okay, like now talking to myself three years ago, the answerVibhu [00:10:08]: Of course they will get betterSwyx [00:10:09]: Collect all the failures, build benchmark, and then collect all the, examples, build the RL environmentAkshat [00:10:15]: RightSwyx [00:10:15]: Sell it for like ten billion dollars to Meta.Swyx [00:10:17]: And then also train a model and then sell that for sixty billion dollars to Elon. And this isAkshat [00:10:23]: Yeah, of courseSwyx [00:10:23]: The funny machine. Like, it's like, it's about the hardware.Akshat [00:10:28]: It's hard to have that inherent conviction that the stuff will get that much better.Swyx [00:10:33]: In retrospect, it's so f*****g obvious.Akshat [00:10:36]: Fair enough.Swyx [00:10:37]: Like, what else were we doing back then? I don't know. anyway. Yeah. So this. That was the start of your sandboxing journey, right? I feel like it didn't blow up until, like, last year.Akshat [00:10:49]: Yeah.Swyx [00:10:50]: So there was like a couple years of quietness.Akshat [00:10:52]: Exactly, yeah. We wereVibhu [00:10:53]: I think very underrated product value. Like, my experience with Modal, Charles, before he had joined Modal, met this guy at a hackathon, and he really insisted we wanted to run some small model, not hosted anywhere, and he's like, “ there's this cool company, Modal. They'll like spin up a GPU sandbox, we can throw it on there. They'll take a Hugging Face link.” And like there's so much value just right there, right? Like instant hosting, spin it up, spin it down. It'll stay cold, but we run the demo a few days later, it'll come back up and like all this stuff in retrospect, like it's still what we needed like today.Akshat [00:11:27]: Yeah, it's still needed today. workload shapes have changed a lot as, we run stuff for people with really massive production scale and, there it's it's not about scaling from zero to one, but it's how do we scale really elastically, from like thousand to fifteen hundred GPUs very quickly in a given region. It's the same shape problem.Elastic Inference, GPU Autoscaling, and Custom ModelsVibhu [00:11:50]: Okay. So you look at, say, Cursor Composer, right?Akshat [00:11:53]: Yeah.Vibhu [00:11:53]: They had a. “We'll do RL on a model every couple hours.” you guys have a whole version of RL inference gym and whatnot.Vibhu [00:12:01]: When you look at workloads like that, you're doing train runs where you need to scale up, scale down every hour thousands of GPUs, right? That's the example for we do need it, right?Akshat [00:12:12]: Yeah. Well, so I'll, I'll take a step back and, maybe talk about like how people use Modal today. because our biggest use case is, elastic inference. And the thing we first found product market fit, with was inference for custom models. So we stayed away from the LLM space, and we were serving companies like Suno for audio, Runway for video, robotics, comp bio companies that train their own model elsewhere. But Modal is the best black box that for deployment, scaling to however many GPUs you need as your traffic pattern changes. And we saw all of them like have a very unpredict- predict- predictable, traffic pattern. it's like diurnal. It's Some days, like the company will do a launch and, they'll need like, way more. And it's not just one model that they deploy. They-- all these companies deploy, lots of different models in different regions, and so the autoscaling problem becomes even harder because then you have to scale within a certain region, and those cycles are offset. So different times you scale up in different regions.Akshat [00:13:20]: So that's like our sortVibhu [00:13:22]: And thatAkshat [00:13:22]: YeahVibhu [00:13:22]: That in and of itself is a huge category. There's a bunch of inference providers which, provide this fireworks, does this as a service together, whatnot, Base10. that's carved into its own niche for language models, at least right now.Akshat [00:13:36]: Yeah. the thing that we have specialized in is the autoscaling aspect.Vibhu [00:13:41]: Yeah.Akshat [00:13:41]: Because we found that it's not universally true that everyone else can autoscale, and we've gone deeper into it on the tech side by, we've incorporated GPU snapshotting into the product so we can take the GPU state, like your torch.compile model, snapshot it, and the next cold start is way faster. And so going back to your question, it's That's why you need a lot of burstiness for inference. But then people also do a lot of demand training, like for RL stuff, your rollouts are bursty, as you said. People also do a lot of batch jobs. So we'll see, a lot of companies, before they have a training run, they'll need thousands of GPUs to run encoding or something like that. And I think those things are much more bursty than. I agree that agents are not that bursty. sandboxes are, except when you're doing RL. RL is justRL, Batch Jobs, and 100,000 SandboxesVibhu [00:14:28]: Or commerceAkshat [00:14:28]: Insanely bursty.Vibhu [00:14:29]: Yeah.Akshat [00:14:30]: Yeah. Like when you're doing, rollouts, you sometimes need a hundred thousand sandboxes in your sandboxes.Vibhu [00:14:37]: Yeah. I'm curious if you've seen early sparks of continual learning. There are some people, like our friends, ngram, recently announced thisAkshat [00:14:45]: YeahVibhu [00:14:45]: They're, they're trying to do training. That also seems like a different workload, right? If you're doing training twenty-four/seven per se, there's a very weird dynamic of how you're using GPUs between people and whatnot, but seems like something you guys would work for.Akshat [00:15:00]: As you said, we're, we're fortunate to work with a number of, customers at the frontier and grab some of our customers. and they are taking the primitives we have, and trying to use them in very interesting ways, like continual learning. It's possible as the stuff gets better, some of that will be part of, our offering as well if, more people need it. but we're, we're just waiting to seeVibhu [00:15:23]: YeahAkshat [00:15:23]: How it shakes out.Vibhu [00:15:24]: Is there a primitive that you added after sandboxing that was the next step in the story?LLM Inference, DeFlash, and Speculative DecodingAkshat [00:15:32]: I guess we've been going much deeper into LLM inferenceVibhu [00:15:35]: YeahAkshat [00:15:35]: Because we realized that some of the advantages we have with like autoscaling, again, especially in different regions and whatnot, are, not present elsewhere. and the place where we had a gap was we weren't, working on the model layer itself. Like we were a black box. And, we realized that, we can get to frontier-level model performance, with, by having great people who work on this. And, we've been open sourcing a lot of our work, in terms of, Recently, we, shared our work on DeFlash, which is a block-based, speculator, and we've open sourced, all of it. So, you can - By using open source DeFlash, you can get the same performance as you would with one of the proprietary providers. And the next thing we're thinking about hereVibhu [00:16:23]: I thought this wasAkshat [00:16:24]: YeahVibhu [00:16:24]: An interesting blog post as well, right? Like, I think in here you make a claim that. Not a claim, just that how effective speculative deco-decoding really just get to.Akshat [00:16:33]: Yeah.Vibhu [00:16:33]: Anything you wanna point out from this around, what people should know?Akshat [00:16:39]: Yeah, absolutely. the high-level summary is, it would help to describe what speculative decoding is.Vibhu [00:16:44]: Yes.Akshat [00:16:44]: I will, yes.Vibhu [00:16:45]: I think, likeAkshat [00:16:46]: YeahVibhu [00:16:46]: So we've covered like Eagle and all thisAkshat [00:16:47]: YeahVibhu [00:16:47]: Like Hydra and all those things, but it was like two years ago.Akshat [00:16:51]: Yeah.Vibhu [00:16:51]: I think it doesn't hurt, right?Akshat [00:16:52]: Yeah. Speculative decoding is you have a smaller model, called a draft model, predict tokens ahead of the bigger model, and then you have the bigger model, verify all of this, all the tokens are predicted. And the reason it's faster is if you're predicting, one token at once, you're bound by memory bandwidth. But if you can batch the verification of, the draft model, then you're much more efficient using compute, and it's faster, and as long as your draft model is producing a lot of tokens that can get accepted, which is called the accept length, you can get a speed up that's, multiple times of, the original model speed. and well, that's what we highlight here. It's Like people talk a lot about we made these kernels faster and whatnot, but improving kernel will only give you like few percentage points of improvement, and, increasing accept length, literally is a multiplicative decreaseVibhu [00:17:47]: Like two to four X.Akshat [00:17:48]: Yeah, exactly.Vibhu [00:17:48]: Without much head-on performance.Akshat [00:17:50]: Yeah. I think it may - you are running a second model, right? So it may be something more expensive in the compute,Vibhu [00:17:57]: I meant quality performanceAkshat [00:17:58]: Probably not by muchVibhu [00:17:58]: But yeah. I thinkAkshat [00:17:59]: So there's no drop in quality performanceVibhu [00:18:01]: YeahAkshat [00:18:01]: Because you're always. You're never accepting a token that the big modelVibhu [00:18:04]: It's strictly betterAkshat [00:18:05]: YeahVibhu [00:18:05]: Or it's same.Akshat [00:18:06]: Exactly.Vibhu [00:18:07]: Right. Yeah.Akshat [00:18:08]: And so we've been working a bunch on DeFlash, which is a block-based speculator. so it's instead of predicting, one token at a time, it's predicting a block. And we've been open sourcing our work with it. The next thing for us here is for helping people train speculators and custom models. it's it's something that traditionally is very forward-deployed engineering driven, support deployed, engineer driven, like you work with customers and help them do that. And our vision for. This is why we launched Auto Endpoints, is we want to make frontier-level performance available to everyone. And so, we mentioned this in the announcement, we teased it. The next thing we're, we're launching is, as you run an auto endpoint, we shadow trafficAuto Endpoints and Frontier-Level PerformanceVibhu [00:18:54]: Do you want to explain what auto endpoints are?Akshat [00:18:57]: Yeah.Vibhu [00:18:57]: I lovely, yeah.Akshat [00:18:58]: Yeah. So, this is, I guess, going back to your Modal is you touch the code, but, sometimes people don't wanna touch the code, and they wanna get started with an endpoint that works and has all the great performance and, scalability that Modal has. So we've made that easier with, a way to create an endpoint from our UI, from the CLI, that has all of our optimizations that we talked about, like the DeFlash stuff already baked in, and there's full transparency. So we give you the code, you can go run it yourself, and if you want, you can eject out into the full Modal experience, which we see as people get sophisticated, they do wanna tweak the models, they wanna, fine-tune stuff. You can still do all of that. It's it's not a black box. And yeah, the next thing, as we teased later in the post, is how do we give you value even beyond this in terms of having your draft models evolve as your data distribution evolves, again, without having to talk to a person and, yeah.Vibhu [00:19:59]: I guess just to understand it directly, you have the GPUs, you have an endpoint that's compatible, you serve open model. If someone was to do this themselves, what's the delta that you guys provide? So you do a lot of open source great work on effective inference. how does it compare to, say, I take the same model, 5.2 FP8, take shelf inference engine, vLLM, SGLang, get compute of similar capacity, similar cost. What's the delta that plugging into something this, like this offers outside of the benefit of, scaling?Production Inference Beyond Raw GPUsAkshat [00:20:34]: It's interesting because we've taken the approach of open sourcing our contributions and upstreaming them. we work closely with the SGLang team. We want the improvements that our team, comes up with to be, there in open source for others to use, even outside of Modal. The benefit to us is we have a team that has significant expertise in terms of if you do have something that is not there, our team can help you get that performance, first. the other thing is with these endpoints, we are way more elastic, as you said, than, anyone else, and you have true scaling to zero. you have true, burstiness, and in practice, that matters a lot more to people than just finding, the GPU and, running Modal code on something.Vibhu [00:21:20]: Yeah. And I will say it's not that straightforward to just. like what I said is easier said than done, right?Akshat [00:21:26]: Yeah.Vibhu [00:21:27]: It's I think still for the average person, still hard to just gut check using different. There's, there's quite a bit of combinations you can make there. the trade-offs aren't really known at face value.Akshat [00:21:40]: Yeah. it's it's not just that. I think it's it's that running production-grade inference is a hard infer problem.Vibhu [00:21:49]: YeahAkshat [00:21:49]: Even if you subtract out the autoscalingVibhu [00:21:50]: YeahAkshat [00:21:51]: Is controlling things like tail latency and, making sure every, request is delivered at least once and whatnot.The Model and Agent LifecycleVibhu [00:22:00]: There's a lot of innovation that you can do here. I think, it's very interesting that you're starting to encroach on, like as you become a full cloud, you're starting to encroach on other people's turf.Vibhu [00:22:09]: What will you not do?Akshat [00:22:13]: Well, we wanna follow our users and, make sure they get like a platform that has everything that works well together. so right now we're focused on the model lifecycle and the agent, lifecycle. so both like going from data prep to training to inference, and then also if I want to deploy a background agent, let's say, sandbox, do persistent storage, a whole bunch of other stuff.Vibhu [00:22:38]: We talked to Cole, who did, OpenInspect. Yeah.Akshat [00:22:42]: Yeah.Vibhu [00:22:42]: And RealInspect also is on Modal.Akshat [00:22:44]: Yeah. So Ramp Inspect was a great example of a background agent that was really successful because they, were able to use some of the primitives like snapshotting and fast scaling to just have something that feels really reactive and works well.Ramp Inspect and Background AgentsVibhu [00:23:02]: Yeah. That's the new CTO of, Ramp right there.Akshat [00:23:05]: Yeah, Rahul.Vibhu [00:23:08]: It was really fun. yeah, okay, I think, all very bullish. Like, one of my reflections was also I did not originally. So when I met you guysThe Inference Inflection: CPU, GPU, and Co-LocationVibhu [00:23:19]: You weren't that much in the GPU game, and now you're all about, inference. And one of the points that I hinged on for Jensen's keynote at GTC this year was, what we're calling like the inference inflection, right? That let's say in AI workloads or machine learning workloads, it used to be like, let's call it eight to one GPU to CPU, and now it's more like one to one, which is like a interesting. Like, - because of how much agents are blocked or call out to this, to CPU heavy stuff the actual, like, limiting factor, like, swings back and forth from GPU to CPU a lot more than it used to be all GPU and then occasional CPU.Akshat [00:24:01]: Yeah.Vibhu [00:24:02]: GPU, CPU. And now it's like just constantly, and you just have to locate everything.Seventeen Clouds and the Supercloud StrategyAkshat [00:24:08]: Yeah. And that's one of the things that, again, we see as, something appealing about Modal, which is we've built this capacity pool that spans, 17 cloud providers, so we're, we're very good at Running on various kinds of cloud capacity across the worldSwyx [00:24:24]: You don't have your own data centers?Akshat [00:24:25]: We don't have our own data centers. We just run across a lot of neo cloudsSwyx [00:24:29]: Yeah. AreAkshat [00:24:30]: Metal providers.Swyx [00:24:30]: Yeah. Question mark.Swyx [00:24:31]: Yeah. You're, you're running the math, and you're like, “What's the cutover point where you're like.”Akshat [00:24:36]: Yeah, it's a good question. part of it is we see our differentiator in the software layer, and, being capital light and focusing on the software helps us move really fast. so far it's worked out well because there are so many other people building data centers that we're able to work effectively with them, and again, focus on what makes us, special.Swyx [00:24:55]: Yeah.Swyx [00:24:56]: 17 gets you into, like, the local providers sometimes. LikeAkshat [00:25:00]: The,Swyx [00:25:01]: Which was the most interesting one?Akshat [00:25:02]: There are a lot more neo clouds than you expect, and they all have various degrees of, various levels of reliability. And, that's why it's something we've invested a lot of time in, is building our own reliability layer on top. so if the GPU falls off the bus or something happens, we user workloads are not affected, and that lets us use a lot more capacity than,Swyx [00:25:30]: YeahAkshat [00:25:30]: You as a user would be able to.Swyx [00:25:32]: It's a useful thing to have because like now everyone knows, like, what layer you are and, like, you optimize for being the super cloud of all clouds.Akshat [00:25:41]: Yeah. That's, that's, that's the idea. and so I guess when you mentioned colocation, that's, that's another interesting thing where, one thing we've seen is people come to us when they want, very specifically located, CPUs or GPUs, like they wantSwyx [00:25:57]: Oh, they pin it in likeAkshat [00:25:58]: YeahSwyx [00:25:58]: EU?Akshat [00:25:59]: Exactly. Or EU, US.Swyx [00:26:01]: Right. Data resiliencyAkshat [00:26:02]: AustraliaSwyx [00:26:02]: Locality thing or performance or what?Akshat [00:26:04]: It's either data locality or latency, yeah.Swyx [00:26:07]: Yeah.Akshat [00:26:07]: Like, you want your. They're running sandboxes and model. They want them to be right next to aSwyx [00:26:10]: Yeah, it's easy thenAkshat [00:26:11]: YeahSwyx [00:26:12]: To. That is important in all those things. and so, like, you've accidentally, I don't know if it's accident, but, like, you've built the perfect primitive for agents to express themselves. And then, like, it's almost very funny how every extra development just involves more file system, just involves more CPU.Akshat [00:26:30]: Yeah.Swyx [00:26:31]: Just like the things that you already have. I don't know much about, if there's any, like, networking usages that are interesting, but you've also done some good work on networking.Networking, Sidecars, Private IPv6, and SandboxesAkshat [00:26:40]: Yeah, that's exactly right. Like, we're just taking compute storage and networking and building stuff on that layer, for, again, the stuff people need.Swyx [00:26:49]: YeahAkshat [00:26:50]: We see a few interesting networking things coming up. one is people want networked sandboxes. so we haveSwyx [00:26:57]: For like a Docker cluster type thing.Akshat [00:26:59]: Yeah.Swyx [00:26:59]: Sorry, Docker Swarm. Oh, f**k. What is it called?Akshat [00:27:02]: Compose.Swyx [00:27:03]: Compose type thing.Akshat [00:27:04]: Yeah. So if you want Docker Compose, our sandboxes now support, this thing called sidecars. So you can. A sandbox is a pod of containers, and you can run multiple containers in, a sandbox. also useful because, going back to networking, people want a lot of control over, outbound networking from a sandbox.Swyx [00:27:23]: Yeah.Akshat [00:27:23]: Like, they might wanna run a middle proxy for, like, maybe logging stuff for RL or, controlling how egress can happen to a domain, injecting credentials. and yeah. So we've, we've had to build a lot of that stuff ourselves.Swyx [00:27:38]: Yeah.Akshat [00:27:39]: But then also sometimes people want, sandboxes spanning multiple nodes to talk to each other, which is an emerging thing we're seeing. We have support for that for a different reason, and yeah, we'll see if that becomes stable.Swyx [00:27:52]: Like, just an open socket. It's a. This is directly like mTLS.Akshat [00:27:56]: We do support that, which is you can, expose a tunnel inside a sandbox.Swyx [00:28:01]: Yeah.Akshat [00:28:01]: And then you can either expose it to public internet or it can be, you can add like a HTTP, auth layer above it. But we have this thing called I6PN, which we haven't talked about, which is this, like, overlay network using IPv6 addresses. so if Modal containers, within the same workspace, when this is enabled, can address each other using this private IPv6 address, and no one else can.Akshat [00:28:28]: So it's like private networking, for containers. We built it because we needed it as a primitive for our distributed training product. so we have this other feature, which is you can add a decorator to a function, and you get a cluster of GPUs. and they have RDMA networking. so you can run a distributed training job, that's truly serverless. and we did the overlay network for that. But then we've seen that people are using it for other reasons, and, I'm intrigued to yeah, what would people do with it.Swyx [00:28:59]: Build primitives and let people figure it out, right?Akshat [00:29:01]: Yeah, exactly.Swyx [00:29:02]: You put out a pretty interestingAkshat [00:29:03]: They're like, they read the docs webpage. Let me use thatSwyx [00:29:06]: YeahAkshat [00:29:06]: Something they never intended to work. This is literally not even in our docs page. People somehow found it, and they're using it.RDMA, Memory Movement, and Distributed TrainingSwyx [00:29:12]: Huh.Swyx [00:29:14]: The way you portrayed it with, like, RDMA versus TCP, like, very well laid out, but just the transfer speed change at scale for RL, like yeah, you have it, you have it built in. I'm sure someone found it. It's found it to be a lot more efficient before you made a thing out of it, right?Akshat [00:29:32]: Yeah. And not to split hairs, I guess the overlay network is the TCP overlay network.Akshat [00:29:39]: The reason we have that is you need that to do the key exchange for RDMA before you set up the RDMA network on top of that. but then people found the TCP part.Swyx [00:29:48]: Can I tell you, this is like a big aha moment for me becauseAkshat [00:29:51]: YeahSwyx [00:29:51]: So I review 2,200 submissions for the World's Fair.Akshat [00:29:56]: Yeah.Swyx [00:29:57]: And then I got this from John OsterhoutAkshat [00:29:58]: HuhSwyx [00:29:59]: Who I don't know if. Do John Osterhout by name?Akshat [00:30:01]: The name sounds familiar.Swyx [00:30:02]: He published a. He's a well-known professor, published a lot of interesting software design books, and this is the talk he chose to submit, is on RDMA at Inference. And I'm like, you wouldn't think that this guy, who is like operating systems guy, would care about RDMA.Akshat [00:30:20]: I, it makes sense to me because I,Swyx [00:30:24]: This is the cloud, right? YeahAkshat [00:30:25]: Like, the way you move around your KV cache and how efficiently you can do it, how efficiently you move, your weights from your training GPUs to your inference GPUs in RL is there's a lot of degrees of freedom, and it is a systems problemSwyx [00:30:41]: YeahAkshat [00:30:41]: Moving memory aroundSwyx [00:30:42]: YeahAkshat [00:30:43]: Scheduling.Swyx [00:30:44]: This shows you how primitive my understanding of networking stuff is.Swyx [00:30:46]: Is this like the domain of WireGuard as well?Akshat [00:30:50]: Not quite.Swyx [00:30:51]: It's adjacent?Swyx [00:30:53]: Explain everything.Akshat [00:30:54]: Sure.Swyx [00:30:56]: How do we move memory around GPUs?Akshat [00:30:58]: Well, so sorry. Yeah, that is memory. Sorry, I was talking more, and maybe I was talking like five minutes back, about the private IPv6, addressing that you've set up.Swyx [00:31:09]: Yeah.Akshat [00:31:09]: Is it like it's a VPN?Swyx [00:31:10]: Yeah, it is like a VPN, and yeah, WireGuard is, yeah, you're right. It is,Akshat [00:31:16]: Right. Yeah, you already moved on to new topicsSwyx [00:31:17]: A similarAkshat [00:31:18]: OkaySwyx [00:31:19]: In the same space, WireGuard is, encrypted and this is,Akshat [00:31:23]: And you don't need encryption.Swyx [00:31:23]: Yeah.Akshat [00:31:24]: Yeah.Swyx [00:31:24]: This is not encrypted. that's the main difference. This is TCP and we have eBPF programs that will reject or allow the TCP connection based on whether you're allowed to do it.Akshat [00:31:35]: Used to involve a full sidecar, but now you have eBPF in the Linux kernel.Swyx [00:31:39]: Yeah.Akshat [00:31:40]: Yeah. I don't know if this is a natural follow-on to the topic of like my skepticism on distributed training is that while, like, people spend a lot of money on, like, cables to hook up GPUs, and even that is not, like, fast enough, and that's the bottleneck, is your networking fast enough?Swyx [00:31:59]: Yeah. So I guess you're talking about fully distributed training like, Dialog or something which is like cross data centerAkshat [00:32:06]: That would be, yes.Swyx [00:32:07]: That's the extreme.Akshat [00:32:08]: Yeah.Swyx [00:32:08]: You're in the middle, and then other people would have like the Mellanox cables up in, like, their actual data center.Akshat [00:32:14]: When you run multi-node training on Modal, RDMA, I think Mellanox, is, or InfiniBand is like a, is all seen as RDMA. but it's a way to bypass the TCP networking stack and, transfer, stuff much faster, between one node, to the other. And we have I think like 3 terabit per second, internal networkingSwyx [00:32:40]: OkayAkshat [00:32:40]: Which is the standard that's needed.Swyx [00:32:42]: Okay. So I misunderstood whatAkshat [00:32:43]: 50Swyx [00:32:43]: What part of the stack you wereAkshat [00:32:44]: 50 gigs overSwyx [00:32:45]: YeahAkshat [00:32:45]: If you wentSwyx [00:32:45]: YeahAkshat [00:32:46]: RDMA.Swyx [00:32:46]: Okay.Swyx [00:32:48]: Yeah. I, very impressive work.Multi-Node Training, Post-Training, and Auto ResearchSwyx [00:32:52]: So effectively you're extending like the model philosophy to the training cluster, like, yeah.Akshat [00:32:59]: Yeah. And we're, we're not going for like large scale training runs. the thing that we've built multi-node training for is, we see a lot of, smaller scale post-training. like, people are post-training like medium sized fund models, so they can, get higher quality on inference. this is a perfect fit, for something like that.Swyx [00:33:21]: Yeah. That is my impression of how a lot of these labs explore branches in post-training and then eventually merge whatever they find in.Akshat [00:33:31]: Yeah. The other use case we've seen for multi-node training is even if you have a big cluster, your researchers are still doing small runsSwyx [00:33:38]: YesAkshat [00:33:39]: Having elasticity thereSwyx [00:33:40]: Right, sureAkshat [00:33:40]: Matters a lot more.Swyx [00:33:41]: Yeah. the, like, this is like the current limiting factor for auto research, which is like you need to give your model some GPUs in order for it to completely run.Akshat [00:33:51]: We have a blog post on auto resource and model is,Swyx [00:33:55]: YeahAkshat [00:33:56]: Yeah, like, turns out to be pretty good substrate for that.Swyx [00:33:59]: So my impression is auto research means many things, likeAkshat [00:34:01]: YeahSwyx [00:34:01]: Anything that Andrej coins. Right now it's still science fair, right? Like not like, I don't know how many people are doing this.Akshat [00:34:08]: We're having a golf.Swyx [00:34:08]: Yeah.Akshat [00:34:09]: I thought the same thing.Swyx [00:34:11]: Yeah, you would know.Akshat [00:34:12]: We, like, our internal both training and inference teams use this the general shape of this quite a bit. like we have this one internal repo called auto inference, which essentially we've automated our own forward-deployed engineering efforts using, this harness, which is, the agent will just spin up a sweep of different things. It'll even run like, NVIDIA inside profiler and it'll like tweak configs and it'll arrive the right thing. it'll change your GPUs both from H200 to B200, and works really well.Swyx [00:34:47]: Nice.Akshat [00:34:47]: So yeah.Swyx [00:34:48]: By the way, I enjoy that your forward-deployed engineering is so technical that you have to do these things.Swyx [00:34:52]: It's very different from forward-deployed engineering from other people.Akshat [00:34:54]: Yeah. For our forward-deployed engineering team is, essentially they're like applied inference researchers or applied training researchers.Swyx [00:35:02]: Someone told me like they have to be able to build, but they also have to be able to sell. do they have to sell or are they like they're good, they're just like post-sale type of thing?Akshat [00:35:09]: It does, being able to talk to a customer and engage effectively with themSwyx [00:35:13]: YeahAkshat [00:35:13]: Matters a lot.Swyx [00:35:14]: They want the same thing.Akshat [00:35:15]: Yeah.Swyx [00:35:15]: ?Akshat [00:35:15]: But it's it's not really a sales, thing. We pair them with-- We have solution architects as well that are more on the sales side.Swyx [00:35:23]: Okay. Let's spend a bit more time on auto research. This is a big focus for for this year. Where does this go? like, have people explored enough? Like, there's all these beautiful charts of like improve and then level off a bit and then you find the next thing. Is this one abstraction up from normal training? Is that how we think about it, or do you think about it differently? Like model level training versus high, like driven hyperparameter search.Auto Inference and Modal BenchAkshat [00:35:51]: Yeah, like,Swyx [00:35:51]: Someone, some people call it like neural architecture search or whatever, right? Like.Akshat [00:35:54]: Yeah, - So the stuff I've seen people do with it is nowhere on the architecture level. It's pretty much tweaking parameters, but it's it's a hyperparameter sweep that's guided by some model intuition, so it's like much more efficient than, whatever other, sweep you would have.Swyx [00:36:12]: Yeah, it's just, it's just a question of where you want to spend your compute?Akshat [00:36:16]: Right.Swyx [00:36:16]: ‘Cause yeah, you can just throw infinite amounts of money on this and somehow you'll bang out Shakespeare?Akshat [00:36:22]: Yeah, infinite monkey.Swyx [00:36:24]: Yeah, so like the very good for model. and I think it's also very important that agents can spin up other agents, can spin up their infrastructure. Like very good for you. how good is our LLMs at generating model code? Like the benefit of existing LLMs is that you are in the data.Akshat [00:36:42]: Yeah. They're, they're surprisingly good. I think like pre Cloud 4 they were not, and then now they're able to shot, stuff out of the box. But we're playing around with releasing like a Modal Bench for like the harderSwyx [00:36:55]: YeahAkshat [00:36:55]: Things, that the LLMs cannot do yet and maybeSwyx [00:36:59]: What's an example of that?Akshat [00:37:01]: I think the things that- Sometimes agents struggle with, without right guidance and a skill is, how to, use the rest of our observability. Like how to. Something is failing, like how do you look at the logs and then update the right thing? It's reasoning about that. But they're able to shot, likeSwyx [00:37:23]: Yeah. You can just add a skill to it?Compute Strategy and Capacity PlanningAkshat [00:37:26]: Yeah. So we have a Modal skill now that. Which is why we built this Modal Bench. It's to find things like that, so we can address them in our tool.Swyx [00:37:35]: Tune a skill. Yeah.Akshat [00:37:36]: Yeah.Swyx [00:37:36]: No. it's it's good. are you facing any shortages? like we talk a lot about GPU shortages, but also CPU, also memory.Swyx [00:37:44]: Yeah.Akshat [00:37:45]: We have had a lot of growth, which means that, there's - we've had to be much better aboutSwyx [00:37:53]: PlanningAkshat [00:37:54]: Proactive capacity planning.Swyx [00:37:55]: Yeah.Akshat [00:37:55]: So we have,Swyx [00:37:57]: Which by the way, like it's like a MBA's like dreamAkshat [00:38:00]: YesSwyx [00:38:00]: Is like just planning this stuff. I think last time you and I talked about something maybe about this.Akshat [00:38:03]: Yeah. we have a really competent team of people that we call, The role is called compute strategy. so yeah, if anyone listening here or wants to work on thatSwyx [00:38:13]: Compute strategy?Akshat [00:38:13]: Yeah.Swyx [00:38:14]: I think,Akshat [00:38:14]: I feel like,Swyx [00:38:15]: I think the normies call it FP&A or something.Akshat [00:38:18]: Well, it's more It's it's not FP&A. It's it's There's a lot of interesting financial questions of like what is the blend between one year and three-year reservations? how do we forecast our own capacity? how do we. especially since our capacity is very fungible across different GPU types and different regions, like you have to model a lot of it. and you also have to have an opinion on how the supply chain is gonna evolve, and then you have to like, take bets,Swyx [00:38:49]: YeahAkshat [00:38:49]: Based on that.Swyx [00:38:50]: Tokenomics.Akshat [00:38:50]: Yeah.Swyx [00:38:51]: This is like probably a not a real point, but, I was trying to think about like what other industries. I was trying to think about like, we cannot be first to like these kinds of problems.Akshat [00:38:59]: Yeah.Swyx [00:39:00]: And what other industries have had this? And I was like, airlines with fuel and like they have to hedge their fuel and like, I think for a long time Southwest because they made like a hero fuel bet, they like were like super low cost becauseAkshat [00:39:12]: OhSwyx [00:39:12]: Compared to everyone else.Akshat [00:39:14]: Yeah. I hadn't thought about that.Vibhu [00:39:16]: We're at a fun time too?Akshat [00:39:18]: Yeah. It's. A lot of the compute business in general, for us is also about being very good about capacity management. That is how you have great unit, economics. but also over time it's how you can unlock more value for customers. Like, one of the things we're building now is like a way for customers to get, If they don't care about latency, like get much cheaper pricing and they'll get results back in like next 24 hours or something, like a batch tier essentially.Batch Tiers and Latency-Insensitive WorkloadsSwyx [00:39:47]: Yeah.Akshat [00:39:47]: And those are levers we have because we control the whole stack and scheduling and whatnot to give people a sufficientSwyx [00:39:53]: Yeah. I feel like they're not as popular. Like those, like the Frontier Labs have all those APIs. They're not as popular as they should be.Akshat [00:40:00]: The demand that we see for something like that is not for LLMs. although sometimes people wanna run evals andSwyx [00:40:08]: OkayAkshat [00:40:08]: Synthetic data prep and there it makes sense.Swyx [00:40:10]: Okay.Akshat [00:40:11]: But it's from a lot of LLM companies, like people who are doing computational bio, like they have to run really big batch jobs and they don't care about when they get it back.Swyx [00:40:22]: Yeah. And like they have a reasonable. It's it's also like a cousin to the stopping problem of like, will this finish in time?Akshat [00:40:30]: Yeah. You can bound it.Swyx [00:40:33]: Yeah.Akshat [00:40:33]: Like you can give peopleSwyx [00:40:34]: YeahAkshat [00:40:34]: SLAs on it.Swyx [00:40:35]: Yeah. I think what's, what's interesting is like the next phase of model.Swyx [00:40:38]: Like what, do people expect from you, now that you're established and you're like well-known compute player among all these leading companies. You had an inference launch week, and we talked a little bit about the launches. like what else? Like what else should people know?What Modal Builds NextAkshat [00:40:55]: We are building primitives that make our users' lives much easier. So, I think for example, with LLM inference, thousands more companies are gonna post-train their own models and, deploy open source models for inference. so we're thinking a lot about what is the best product shape for that. And, that involves everything from our training gym to, then, endpoints that get frontier-level performance. again, but I haven't talked to anyone. It looks somewhat different on other verticals. Like, we're also seeing a lot of real-time, audio-video stuff in there, which is why like, we're working on things like regional routing, with fallbacks. So you can get GPUs that are as close to users as possible. so you get like low latency for video streaming and whatnot. And then on the agent side, it's,Akshat [00:41:52]: We're still working very closely with our customers because stuff is changing so fast in terms of what they need. And, I think beyond sandboxes and persistent file systems, there's a lot of other things people will need from this agent stack as they build production agents. So yeah, we're thinking about those other things that fit in there.Swyx [00:42:13]: I want to ask what the other things are.Akshat [00:42:15]: Yeah. I probably should share right now.Swyx [00:42:17]: I think-- I think, okay, so, I do think a lot about the principal components of cloud, and you do talk about compute storage networking.Akshat [00:42:25]: Yeah.Swyx [00:42:25]: Because so far for me, it's fine. so far for the. the first couple generations of cloud, it's fine. What's different, qualitatively different about agents that you need some new permission level? Like a lot of people, okay, and I'll just kinda spew tokens at you until it like hopefully sparks something.Akshat [00:42:43]: Yeah.Swyx [00:42:44]: Like the new level now is whatever Claude Code does, which is dangerously scope permissions or like allow list by command or like whatever, right? And sometimes they're like, “Well, okay, we have like this adaptive thinking mode where like, just trust me, bro. I will make the calls for you.” Is that it? like mediated permissions.Hard Guardrails vs. LLM-Mediated PermissionsVibhu [00:43:03]: Now you're looping it with a goal and letting it roll.Akshat [00:43:06]: Yeah, I'm, I'm skeptical of LLM media permission for stuff that is at the sandbox level because you do want hard boundaries.Swyx [00:43:16]: Yeah.Akshat [00:43:16]: Otherwise, someone can exfiltrate stuff.Swyx [00:43:20]: But likeAkshat [00:43:20]: YeahSwyx [00:43:20]: Maybe that's old school thinking. Maybe we're the dinosaurs.Swyx [00:43:23]: Maybe the AI OS or the LLM OS is really the kernel is a goddamn LLM.Swyx [00:43:30]: Like it makes you feel uncomfortable.Akshat [00:43:31]: Yeah, I'm, I'm toldSwyx [00:43:32]: But that's what trusting the LLM is. Like imagine a spherical cow perfect LLM.Akshat [00:43:36]: Right.Swyx [00:43:37]: That it.Akshat [00:43:39]: Maybe.Swyx [00:43:41]: I wanna test the boundaries, right?Akshat [00:43:42]: Yeah.Swyx [00:43:42]: Like, and I don't believe that, but I wanna see where I'm wrong ‘cause that's, that's the consensus.Akshat [00:43:49]: Yeah. I think you always need hard guardrails when you want, And you can pair those with softer guardrails, right? And that's gonna be a lot of mediated.Managed Agents and Specialized SandboxesSwyx [00:44:00]: There. I'll also get you a end with a couple of your commentary on like the ecosystem outside of Modal. Manage agents. Everyone has one. Gemini, OpenAI, Claude, very useful for you, but also like it is their way of starting to edge into your space.Akshat [00:44:17]: Yeah.Swyx [00:44:17]: What's going on?Akshat [00:44:19]: Yeah, we're, very excited to partner with Anthropic and some of the other foundation labs, will not name who we're also working with. the way we see it is the manage agent thing is a great place to start if you're starting out building an agent and, But then when you get to, building something more production grade, like you're a company that's like Ramp that's building their own, Ramp also runs their accounting agent on us, so their external-facing agent. You need a lot more control over, your compute primitive on things like, what sort - how do you persist different files that the agent has access to, and how do you snapshot and restore? How do you control the networking? maybe you want GPUs. When you get to that point, you kinda want, a specialized sandbox provider, that gives you those things, and that's the role that we are trying to play.Swyx [00:45:15]: YeahAkshat [00:45:16]: We don't really have an opinion on the harness, whether it runs - it's a cloud-managed agent, and you hook it up to Model Sandbox, or you run the harness in Model Sandbox. We'll see where people converge with that.Swyx [00:45:26]: Yeah. Do you any opinions on like the meta harnesses, or just another layer on top of these things?Akshat [00:45:31]: You mean like the OpenPipeSwyx [00:45:33]: OpenPipe is one. I think Vercel had one, which I can't remember the name of right now. Fredshot had one. and then, to me, most recently was Data Databricks that had Omnigen. All these are meta harness. Like it's kinda pseudo agent cloud type things.Akshat [00:45:50]: I personally have not played around with them.Swyx [00:45:53]: Yeah.Akshat [00:45:53]: Build agents with them.Swyx [00:45:54]: Everything's bullish Modal, as long as it consumes more infra.Akshat [00:45:57]: That's why we're focusing on the infra layer. It's somewhere where our, relative competence is and, also it's a hard problem to solve.Swyx [00:46:06]: Yeah. I will say like just generally reflecting on that, I don't know if - if there's other topics on Modal, but like just generally reflecting as an infra person, not as intense as you, but in that field, this has like been the most exciting time in infra. Like it was boring for a while, and you couldn't really get people excited about data infrastructure. Like Eric would get on Data Console, everyone just watched the video and like say, “Look at how many sandboxes I can spin up,” and no one gave a crap.Why Infrastructure Became Exciting AgainAkshat [00:46:39]: Yeah.Swyx [00:46:40]: And like now everyone gives a crap.Akshat [00:46:42]: That's true. It is a very exciting time, and I think a lot of that's driven by just the amount of scale all of this stuff needs.Swyx [00:46:50]: I think the, like a lot of your initiatives or a lot of your like product directions make sense in retrospect, which is like the best kind, but I wouldn't necessarily have thought about it myself, which.Akshat [00:47:00]: We need the predictions.Swyx [00:47:02]: I think there's a lot that you just don't even see, right? Like you have the batch, you have the voice, you have the multimodal, but what else?Akshat [00:47:10]: What else is coming up for usSwyx [00:47:11]: Yeah. Where do you see things going?Akshat [00:47:13]: Yeah. I, in generalBiotech, Robotics, and Non-LLM AI WorkloadsAkshat [00:47:15]: It's it's clear that there's there's a huge shift happening. I think one thing that's not as obvious to people because LLM inference gets talked about so much and is also we work a lot of companies that are, doing things like drug discovery and computational bio, like the Chai Discoveries of the world. Big things are probably gonna happen there. we work a lot of robotics companies that are putting robots in like active deployments and getting good results out of them.Swyx [00:47:45]: Is there Air Gap Modal? Is there a version that is like prem air gapped whatever?Akshat [00:47:50]: No. We,Swyx [00:47:51]: You should cloud only.Akshat [00:47:51]: Yeah.Swyx [00:47:52]: Yeah. Okay. But yeah, so what you're saying is like because you're focused on primitives and they're good primitives, you find use cases in all these kinds of things.Akshat [00:48:01]: Yeah.Swyx [00:48:01]: Probably diversifies you a little bit away from LMS all the time.Akshat [00:48:05]: Yeah, absolutely. We're, we'- our goal isn't to only serve the LLM inference market.Swyx [00:48:10]: There are a lot just on the website, the audio,Akshat [00:48:12]: Yeah. We said both onSwyx [00:48:14]: Computational bio images. Yeah, there's a lot here. There's QTA TTS, customizing. Oh, Chatterbox. there was customizing Whisper.Akshat [00:48:24]: Okay. Yeah.Swyx [00:48:25]: This screen reminds me of a fallen competitor, which Replicate.Model APIs vs. Differentiated AI ProductsSwyx [00:48:31]: What's your postmortem on what happened?Akshat [00:48:34]: This is one thing we've stayed away from is providing an API for models because I think providing model APIs is some of it ends up serving like a really hobbyist market, which is much less sticky.Swyx [00:48:50]: Yeah.Akshat [00:48:50]: And we've always wanted to build for companies that are building products and need more flexibility that's not just an API.Swyx [00:48:57]: Which you can build an API for a model and this is clearly what it is. But you - but what you're saying, you can wrap it into a more fully functioning back end that you run.Akshat [00:49:06]: Yeah. So all of our examples, it's not that spin up this model, here's an API token, use it. They're all code.Swyx [00:49:13]: Okay.Akshat [00:49:13]: And so the point is that this is just an example.Swyx [00:49:16]: Starter code.Akshat [00:49:17]: Yeah. But you can tweak it however you want.Swyx [00:49:20]: Yeah.Akshat [00:49:21]: And if you're like a company building a product, like, computational bio whatnot, yeah.Swyx [00:49:26]: I guess I'm trying to tease out for listenersAkshat [00:49:28]: YeahSwyx [00:49:28]: When does it stop becoming, oh, you're just an API call and you're just a wrapper on API to becoming what you call a product, right?Swyx [00:49:36]: Like, what is that layer? Like what-- Like, more lines of code, but like beyond that, what is the substance that people add that qualifies it to be something more?Akshat [00:49:46]: I think there's a little bit of like a selection effect of like a lot of the companies who do wanna get deeper into that level are probably building something that's more differentiated. And, I think, an example is like - with LLM inference, originally we, worked with companies that were building their own post-training frameworks or they were, - Ramp early in the day was training their own tokenizer and like swapping out the tokenizer in Llama and whatnot. I'm not saying that's, that successful, in that case. But a better example is like, let's say Suno. because Suno, does not use Modal for training.Swyx [00:50:26]: Mikey on the pod. Yeah.Akshat [00:50:27]: But they use Modal for all their inference and that's because they have like a custom-- They have completely custom model architecture and that means that they have to be at the code level and tweak things that are not, just an API.Swyx [00:50:41]: It's interesting as well, like we had, Ethan, most recently on the xAI Groq team make a prediction that like the next tier in video gen is not a better video model, it's a better model or agent that orchestrates video models.Video Agents and Production WorkflowsAkshat [00:50:56]: Oh, interesting.Vibhu [00:50:56]: Language model backbone that can use toolsAkshat [00:50:58]: RightVibhu [00:50:59]: And write code.Akshat [00:51:00]: Like, yes, I can make my second video or my second video from Groq, but I want my minute video.Akshat [00:51:06]: And I'm not going there through normal video gen.Swyx [00:51:10]: Yeah, that's interesting. I - So we have GPU sandboxes and recently have seen a few companies doing agents that do video manipulation or,Akshat [00:51:22]: Yeah. Give it FFmpeg and just do it.Swyx [00:51:23]: Run FFmpeg. But likeAkshat [00:51:25]: That's not enough.Swyx [00:51:25]: Yeah.Akshat [00:51:26]: You need to give it Adobe.Swyx [00:51:27]: Yeah, I hadn't put it together with like it would be a video production thing. in my mind these things were going more towards editingAkshat [00:51:36]: Yeah.Vibhu [00:51:36]: Well, shout out Mantis.Akshat [00:51:37]: I think about this a lot.Swyx [00:51:38]: .Akshat [00:51:41]: Yeah. Sorry.Vibhu [00:51:41]: Luma. Luma Agent is a version of this for video production, but it's a off.Swyx [00:51:46]: I was gonna get your quick takes, on some other stuff that happensGitpod/Ona, CI, and Runtime SandboxesSwyx [00:51:50]: In recent news and just-just see if you have anything interesting. Gitpod, very li

1. Condenan a 35 y 25 años de prisión a responsables del asesinato de dos mujeres transgénero en Humacao2. En pausa plan de racionamiento en Río Grande y Canóvanas tras las lluvias3. Gobernadora acusa a LUMA de crear caos con aviso falso de relevos de carga4. Gobernadora activa la Guardia Nacional para atender incendio entre Canóvanas y Loíza5. Politank radica informes tardíos luego de señalamientos en auditoría del DDEC6. En aumento los “fraudes de amor” contra los adultos mayores7. Choco Orta regresa al teatro local para el musical Buena Vista Social Club8. Estados Unidos bombardea Irán tras los ataques a tres barcos en el estrecho de Ormuz.9. 3.685 fallecidos y 17.907 personas sin hogar, según Gobierno de Delcy Rodríguez 10. Abelardo de la Espriella suspende el empalme con el Gobierno de Gustavo PetroEste es un programa independiente y sindicalizado. Esto significa que este programa se produce de manera independiente, pero se transmite de manera sindicalizada, o sea, por las emisoras y cadenas de radio que son más fuertes en sus respectivas regiones. También se transmite por sus plataformas digitales, aplicaciones para dispositivos móviles y redes sociales. Estas emisoras de radio son:1. Cadena WIAC - WYAC 930 AM Cabo Rojo- Mayagüez2. Cadena WIAC – WISA 1390 AM Isabela3. Cadena WIAC – WIAC 740 AM Área norte y zona metropolitana4. X61 – 610 AM en Patillas5. X61 – 94.3 FM Patillas y todo el sureste6. WPAB 550 AM - Ponce7. ECO 93.1 FM – En todo Puerto Rico8. WLRP 1460 AM Radio Raíces La voz del Pepino en San Sebastián9. WOQI 1020 AM – Radio Casa Pueblo desde Adjuntas 10. Mundo Latino PR.com, la emisora web de música tropical y comentarioUna vez sale del aire, el programa queda grabado y está disponible en las plataformas de podcasts tales como Spotify, Soundcloud, Apple Podcasts, Google Podcasts y otras plataformas https://anchor.fm/sandrarodriguezcottoTambién nos pueden seguir en:REDES SOCIALES: Facebook, X (Twitter), Instagram, Threads, LinkedIn, Tumblr, TikTokBLOG: En Blanco y Negro con Sandra http://enblancoynegromedia.blogspot.comSUSCRIPCIÓN: Substack, plataforma de suscripción de prensa independientehttps://substack.com/@sandrarodriguezcottoOTROS MEDIOS DIGITALES: ¡Ey! Boricua, Revista Seguros. Revista Crónicas y otrosEstas son algunas de las noticias que tenemos hoy En Blanco y Negro con Sandra.

¡Con lo pelu alante! ¡Gustavo Cáez “Muñiz” con los deportes!¡Prepárate para casi tres horas de manicomio puro! Un episodio tan cargado de noticias que, si lo escuchas sentado en el inodoro, puedes salir con una experiencia religiosa. Si no nos crees pregúntale a Super Estaca. A él le gusta esa pendejada.La FIFA 2026 manda para su casa a Estados Unidos y a México. Como era de esperarse, no faltan los actos racistas que le recuerdan al planeta que algunos fanáticos tienen menos evolución que un microondas inverter. La FIFA, mientras tanto, hace lo que mejor sabe hacer: mirar para otro lado hasta que llegue el próximo cheque.“La Maldad” vuelve al desierto justo cuando al “Voodoo Ranger” le toca cargar la cruz durante el fin de semana del 4 de Julio. Gustavo desata una crisis humanitaria al repartir cervezas tan calientes que la gente juraba que venían directamente de la caldera del diablo. Bueno, Texas. ¿Qué más pueden esperar?Y para completar el menú del disparate, un grupo de supremacistas blancos enmascarados decide salir a marchar en plena celebración de los 250 años de independencia de Estados Unidos, demostrando una vez más que el patriotismo mal mezclado con ignorancia produce efectos secundarios permanentes como si te estuvieras masturbando con Bengay. Así de mal están ellos.La economía sigue haciendo cosplay del Titanic mientras las decisiones de Donald Trump continúan generando controversia y sacudiendo mercados. En Puerto Rico, la histórica Hacienda Juanita cierra sus puertas. Cuba vuelve a quedarse sin luz , porque al parecer allí los apagones ya son patrimonio nacional. Y esta vez no se le puede hechar la culpa a LUMA. Y en Venezuela algunos hasta se ponen exigentes con la ayuda recibida después de los terremotos, como si el sufrimiento ahora incluyera menú a la carta con símbolo de Plaza Las Americas. ¡Ni eso!En el mundo del entretenimiento, Marvel sigue coleccionando decisiones que tienen a muchos fanáticos preguntándose si Avengers: Doomsday terminará siendo una película o un documental sobre cómo quemar cientos de millones de dólares y mandarte al Capestrano por depresión severa. Mientras tanto, Sony decide seguir empujando el futuro completamente digital de los videojuegos y logra unir a internet entero en una sola oración: “¡Váyanse pal' carajo!”Y por increíble que parezca… esto apenas calienta motores.Porque cuando uno cree que la humanidad ya tocó fondo, siempre aparece alguien con una pala. Y como la realidad insiste en escribir mejores comedias que cualquier libretista, los Güanimes hacen lo único responsable: sentarse frente a un micrófono, reírse del desastre… y arrastrarte con ellos. En adición de rezarle al Divino Creador.Con las participaciones deMío: El Huevo FelizGustavo “El Carnepuerco” CáezAlberto “Súper Servo” ReyesGustavito “Eñ Gusti” CáezGiancarlo “La Maldad” Martínez Consigue ya la mercancía oficial de SE RASCÓ ASÍ visitando nuestro Güanime Store:

1.  Comisión cameral evalúa medidas para regular a los vendedores ambulantesen las carreteras2.  José Huertas Torres enfrenta 25 cargos por obras no realizadas en laquebrada Margarita3.  Reportan fuga de químico de incendios en la Base Ramey de Aguadilla4.  Sin luz y sin agua. Trabajos de LUMA y la AAA provocarán interrupcionesla semana que viene5.  ¿Por qué renunció el fiscal federal Stephen Muldrow?6.  JSF aprueba reasignar $116 millones para pagar deudas por servicios deEducación Especial7.  Empleado de Hacienda se declara culpable por sobornos y pérdida de $5millones8.  Habla en exclusiva el presidente de Cuba, Miguel Díaz Canel, con laprensa en PR sobre crisis actual con EEUU9.  ICE confirma que realiza operativos contra indocumentados en los 50estados10.            Terremotos dejan 2,594muertos en Venezuela, rescatan hombre que estuvo 8 días bajo tierra,11.            Suben a 27 los muertospor masivo ataque ruso contra KievEste es un programa independiente y sindicalizado. Esto significa que este programa se produce de manera independiente, pero se transmite de manera sindicalizada, o sea, por las emisoras y cadenas de radio que son más fuertes en sus respectivas regiones. También se transmite por sus plataformas digitales, aplicaciones para dispositivos móviles y redes sociales.  Estas emisoras de radio son:1.    Cadena WIAC - WYAC 930 AM Cabo Rojo- Mayagüez2.    Cadena WIAC – WISA 1390 AM Isabela3.    Cadena WIAC – WIAC 740 AM Área norte y zona metropolitana4.    X61 – 610 AM en Patillas5.    X61 – 94.3 FM Patillas y todo el sureste6.    WPAB 550 AM - Ponce7.    ECO 93.1 FM – En todo Puerto Rico8.    WLRP 1460 AM Radio Raíces La voz del Pepino en San Sebastián9.    WOQI 1020 AM – Radio Casa Pueblo desde Adjuntas 10. Mundo Latino PR.com, la emisora web de música tropical y comentario Una vez sale del aire, el programa queda grabado y está disponible en las plataformas de podcasts tales como Spotify, Soundcloud, Apple Podcasts, Google Podcasts y otras plataformas https://anchor.fm/sandrarodriguezcotto También nos pueden seguir en:REDES SOCIALES:  Facebook, X (Twitter), Instagram, Threads, LinkedIn, Tumblr, TikTok BLOG:  En Blanco y Negro con Sandra http://enblancoynegromedia.blogspot.com  SUSCRIPCIÓN: Substack, plataforma de suscripción de prensa independientehttps://substack.com/@sandrarodriguezcotto OTROS MEDIOS DIGITALES: ¡Ey! Boricua, Revista Seguros. Revista Crónicas y otrosEstas son algunas de las noticias que tenemos hoy En Blanco y Negro con Sandra. 

PODCAST LAS NOTICIAS CON CALLE DE 1 DE JULIO - Rivera Schatz y gobernadora siguen en guerra, ahora por destaques y Politank Anthonieska comienza selección de jurado y Elvia sigue hoy Autorizan aumento de la luz por aumento de costo de combustible Comienzan hoy aumentos del agua y la luz, 2% del agua y 4.9% de la luz - El Vocero Junta ofrece a bonistas 3 billones para transar deuda de la AEE - El Vocero Trump ha hecho 2.2 billones desde que llegó a la presidencia - NYTHasta el 10 de Julio la amnistía de multas de tránsito - Primera HoraSalud reabre planta de la AAA de Loíza y Canóvanas - Metro   ¿Te ha pasado que llegas de viaje y se te arruina la ilusión tan pronto ves la factura del teléfono y tienes cargos adicionales? Se suman más y más y más cargos adicionales por cada llamada, mensaje, búsqueda que hiciste.     •    Eso me llegó a pasar, hasta que me cambié a T-Mobile.     •    Los únicos que ofrecen SIN COSTO ADICIONAL internet y textos ilimitados en más de 215 destinos.     •    Ya no me tengo que preocupar cuando viajo, ni cuando regreso porque ya está incluido, sin cargos adicionales.     •    Viaja relax con T-Mobile, ¡Cámbiate hoy en T-Life o llama al 1800TMOBILE!#tmobile#incluyeauspicioVuelve Kamala para el 2028 según reuniones recientes con Mamdani - Axios Trump le suelta garra a Claude de Anthropic y Fable 5 sale - Bloomberg Supremo de PR plantea si entra o no a decidir sobre LUMA y su contrato - Noticel Moscú bajo ataque de Ucrania, no tiene ni combustible y apunto de perder Crimea - Reuters USA e IRán negocian en Doha - Reuters Guerra de billboards para favorerecer a Miguel Romero - Jay Fonseca PR LOS DATOS DEL DÍA (cierre 30 de junio)Brent$74.28/barril (+1.99% en el día; tendencia a la baja)Diésel EEUU$4.67/galón retail · ~$3.28 al por mayorS&P 500+0.8% (+14% en el trimestre)Dow+0.26% → 52,319 (récord)Bono 10 años4.44%Euro/USD1.139Gas natural$3.26/MMBtu (+2.34%)Hipoteca 30 años6.49%

Yoko Li speaks with Luma's Head of Applied Research Matt Tancik and Phota Labs cofounder and CTO Zach Xia about how AI is changing creativity, photography, and the tools people use to make art. The conversation explores the evolving relationship between artists and AI, from image generation and personalization to creative workflows, controllability, and agentic design tools.  They discuss personalization, photography, creative software, model design, evaluation, and why the future of creative tools may depend less on generating content and more on helping people express ideas they couldn't easily realize before. Along the way, they explore AI agents, interfaces, and how creators are already using these tools in unexpected ways.   Resources: Follow Matt on LinkedIn: https://www.linkedin.com/in/matthewtancik/ Follow Zach on LinkedIn: https://www.linkedin.com/in/zhihao-zach-xia/ Follow Yoko Li on X: https://x.com/stuffyokodraws Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

El socio de Luna Sevilla Asesores patrimoniales selecciona los fondos de: Buy and hold bonds, Loreto Premium Renta Variable Mixta, Invesco Develop Small and Mid Cap Equity, Goldman Sachs Emerging Markets ex China

LUMA contraataca. La empresa intensifica su ofensiva legal y política mientras aumenta la presión sobre su contrato, sus reclamos económicos y el futuro del sistema eléctrico de Puerto Rico.En este PPPLIVE! analizamos qué busca LUMA, por qué está elevando la pelea, quiénes están detrás de su nueva estrategia legal y qué consecuencias podría tener para el Gobierno, la Junta de Supervisión Fiscal y los abonados.Nos sentamos con Frank Torres Viada uno de los abogados picapleitos de LUMA ENERGY.¿Es una defensa legítima de su contrato o una maniobra para obligar al país a pagar más? Conectamos los puntos, explicamos el juego de poder y discutimos lo que puede pasar ahora.Háblamos también sobre el proyecto nacerSuscríbete, activa las notificaciones y acompáñanos en vivo.#PPPLIVE #LUMA #PuertoRico #EnergíaEléctrica #GobiernoPR #PuestosPalProblema

A customer discovered 11,000 AI agents running in their environment - and most weren't even built by developers. In this episode of 10X Growth Strategies, host Preethy Padmanabhan talks to Ankur Shah (CEO, Straiker) and Nick Shevelyov (CEO, vCSO.ai) on how AI is reshaping cybersecurity for enterprises and startups alike.   In this episode, we discuss: The two sides of AI and cybersecurity: using AI to improve security, and securing the AI itself Why LLMs and AI agents can be socially engineered just like humans and why that's a fundamentally new attack surface The discovery of 11,000 "citizen agents" inside a single enterprise, built without developer oversight Why visibility, governance, and guardrails are the new foundation of AI security What "YOLO mode" is, and why human-in-the-loop approval matters for high-risk agent actions How CISOs are thinking about traceability, accountability, and blast radius when deploying agentic AI Why distribution and trust are now the hardest problems in cybersecurity How MYTHOS and AI-discovered vulnerabilities are changing patching cycles and concentration risk Founder advice on building enduring companies in a crowded, fast-moving cybersecurity market Whether you're a founder, a CISO, or an investor trying to understand where AI and cybersecurity intersect - this conversation is for you. 10X Growth Strategies is a community founded by Preethy Padmanabhan, started as a podcast five years ago and now grown into a community of over 7,500 founders, investors, and executives across Luma and LinkedIn. The community hosts monthly events on timely topics in tech, AI, and entrepreneurship. Chapters: 00:00:10 - 00:00:55 - Introduction & Community Milestone 00:00:56 - 00:01:43 - Sponsor & Partner Shout-Outs 00:01:44 - 00:02:52 - Audience Check: Founders vs. Investors 00:02:53 - 00:03:38 - Meet the Speakers: Ankur Shah (Straiker) 00:03:39 - 00:05:01 - Meet the Speakers: Nick Shevelyov (vCSO AI) 00:05:02 - 00:06:44 - How AI is Changing Cybersecurity 00:06:45 - 00:08:36 - Why AI Agents are Hard to Secure 00:08:37 - 00:26:26 - Variables vs. Invariables in Cyber Strategy 00:26:27 - 00:28:40 - Audience Q&A: Standing Out in a Crowded Market 00:28:41 - 00:31:00 - Audience Q&A: Is Your Data Safe with ChatGPT & Claude? 00:31:01 - 00:33:19 - Closing Advice for Founders Connect: LinkedIn: www.linkedin.com/in/preepadu Website: https://grow10x.podbean.com/ Luma: https://lu.ma/10xgrowthstrategies

#pnp #jueces #supremo Ex Jueces Supremo también representan interés de LUMA ante tribunales. | Artillería pesada en bufete que defiende a LUMA incluye ex Fiscal Federal | Gobernadora insiste en que Francisco Domenech tiene toda su confianza y secretaria de Justicia le pasa la papa caliente al FEI. ¿Por qué será? ¡Conéctate, comenta y comparte! #periodismoindependiente #periodismodigital #periodismoinvestigativo Síguenos en nuestras redes sociales: tiktok.com: https://x.com/Bonita_Radio Facebook: / bonitaradio Instagram: / bonitaradio X: https://x.com/Bonita_Radio

1.  Alcaldesa de Loíza Julia Nazario habla En Blanco y Negro sobre eldesprecio del gobierno central y la AAA a su pueblo. Dice que TRS la ayudó2.  Se la pasa insultando a independentistas, pero juega a la república.Senador PNP Carmelo Rios nombrado Embajador Honorario del Caribe Unido3.  Traigo prueba de que en el Departamento de Salud organizan eventopolítico en horario laboral para ratificar delegados del PNP, en horariolaboral4.  Video muestra empleados municipales de Aibonito le caen encima a golpesa un señor mayor que es vendedor ambulante5.  Gobernadora nomina como juez al exjuez y secretario de correcciónFrancisco Quiñones.6.  Jenniffer González defiende a Domenech y atribuye pesquisa del Senado auna futura primaria en el PNP7.  Justicia envía al PFEI caso contra exsecretario del DDEC por supuestosdelitos8.  Escala batalla legal entre LUMA y Gobierno tras nueva contrademanda9.  El presidente de Irán afirma que no habrá negociación sobre el programade misiles balísticos10.            Estados Unidos sancionaa 5 empresas cubanas y familiar de Raúl Castro11.            El Tribunal Supremoaprueba la demanda de ExxonMobil por la confiscación de propiedades en Cubarealizadas por Fidel Castro. La petrolera estadounidense reclamaba 1.000millones de dólares a dos empresas públicas energéticas cubanas por laexpropiación de una refinería y más de 100 estaciones de servicio en los añossesenta  Este es un programa independiente y sindicalizado. Esto significa que este programa se produce de manera independiente, pero se transmite de manera sindicalizada, o sea, por las emisoras y cadenas de radio que son más fuertes en sus respectivas regiones. También se transmite por sus plataformas digitales, aplicaciones para dispositivos móviles y redes sociales.  Estas emisoras de radio son:1.    Cadena WIAC - WYAC 930 AM Cabo Rojo- Mayagüez2.    Cadena WIAC – WISA 1390 AM Isabela3.    Cadena WIAC – WIAC 740 AM Área norte y zona metropolitana4.    X61 – 610 AM en Patillas5.    X61 – 94.3 FM Patillas y todo el sureste6.    WPAB 550 AM - Ponce7.    ECO 93.1 FM – En todo Puerto Rico8.    WLRP 1460 AM Radio Raíces La voz del Pepino en San Sebastián9.    WOQI 1020 AM – Radio Casa Pueblo desde Adjuntas 10. Mundo Latino PR.com, la emisora web de música tropical y comentario Una vez sale del aire, el programa queda grabado y está disponible en las plataformas de podcasts tales como Spotify, Soundcloud, Apple Podcasts, Google Podcasts y otras plataformas https://anchor.fm/sandrarodriguezcotto También nos pueden seguir en:REDES SOCIALES:  Facebook, X (Twitter), Instagram, Threads, LinkedIn, Tumblr, TikTok BLOG:  En Blanco y Negro con Sandra http://enblancoynegromedia.blogspot.com  SUSCRIPCIÓN: Substack, plataforma de suscripción de prensa independientehttps://substack.com/@sandrarodriguezcotto OTROS MEDIOS DIGITALES: ¡Ey! Boricua, Revista Seguros. Revista Crónicas y otrosEstas son algunas de las noticias que tenemos hoy En Blanco y Negro con Sandra.  

#pnp #jueces #supremo Ex Jueces Supremo también representan interés de LUMA ante tribunales. | Artillería pesada en bufete que defiende a LUMA incluye ex Fiscal Federal | Gobernadora insiste en que Francisco Domenech tiene toda su confianza y secretaria de Justicia le pasa la papa caliente al FEI. ¿Por qué será? ¡Conéctate, comenta y comparte! #periodismoindependiente #periodismodigital #periodismoinvestigativo Síguenos en nuestras redes sociales: tiktok.com: https://x.com/Bonita_Radio Facebook: / bonitaradio Instagram: / bonitaradio X: https://x.com/Bonita_Radio

What happens when veterinary professionals take healthcare directly into the communities that need it most?In this episode of PetAbility Podcast, we're joined by Marilyn Jerome, LVT, MS who shares her experience helping establish and operate low-cost wellness clinics throughout all five boroughs of New York City while working with the ASPCA. These clinics provided essential preventive and wellness care—including vaccines, spay/neuter services, nail trims, and more—to thousands of pets whose families might otherwise have gone without veterinary care.Marilyn takes us behind the scenes to explain how these large-scale community clinics worked, who they served, and why veterinary nurses were at the heart of their success. From patient flow and anesthesia support to client education and compassionate care, this conversation highlights the incredible impact veterinary technicians and nurses make every day—especially in underserved communities.Whether you're a veterinary professional, shelter worker, or pet owner who believes every animal deserves access to care, this episode offers an inspiring look at one model that has improved countless lives.In This Episode You'll Learn How the ASPCA's free and deeply discounted wellness clinics  operated  What services were offered and why preventive care matters  How families qualified for affordable veterinary services  The essential role veterinary nurses and technicians played before, during, and after each clinic  The logistical challenges of providing high-volume veterinary care  Lessons learned from serving diverse communities across New York City's five boroughs  Why improving access to veterinary care strengthens both animal welfare, the human-animal bond, and society at-large Marilyn's advice for veterinary professionals interested in community medicine and outreach Why This Conversation MattersPreventive veterinary care is one of the most effective ways to keep pets healthy—but for many families, access remains a significant challenge. Community wellness clinics help bridge that gap by providing affordable services that prevent disease, reduce suffering, and keep pets with the people who love them.As Marilyn explains, none of this happens without skilled veterinary nurses who coordinate patient care, educate families, assist veterinarians, and keep high-volume clinics running safely and efficiently.This episode is a reminder that expanding access to veterinary care isn't just about medicine—it's about compassion, teamwork, and meeting people where they are.Enjoyed this episode?Please subscribe, leave a review, and share this episode with fellow veterinary professionals, animal welfare advocates, and pet lovers. Your support helps us continue bringing conversations that improve mobility, recovery, and quality of life for pets everywhere.PetAbility Podcast — Helping pets live healthier, happier, and more mobile lives.DisclaimerVitalVet.org, a platform for all things related to pet rehab - product information, education, and resources abound! MedcoVet (show sponsor)  Luma - advanced red-light therapy therapy that puts healing in the hands of the pet owner in the comfort of home! Use Promo Code PETPOD22  to receive discounts from our affiliates!Jope - science-backed supplements Ruff Ramp - a safe alternative to stairs Optimum Pet Vitality - education/coursework  Dr. Buzby's -Toe Grips to prevent slipping, Encore Mobility joint supplement, and Brain Boost cognitive supplement. Using this link donates 20% to PetAbility Calm & Cozy Cat Wrap - a must-have for anybody working with catsHedzUpPets Watercollars – save your dog from drowni...

1. Policía identifica turistas vinculados a presunta agresión sexual múltiple en Condado2. Abuso del gobierno central con el municipio de Loiza. Siguen sin agua. ¬Parece otra forma de discrimen racial3. Gobierno pagará $90.4 millones en deuda acumulada a más de 5,850 maestros4. Puerto Rico cae siete puestos en el Índice de Competitividad Mundial5. LUMA recibe visita del Departamento de Energía Federal6. Senado confirma a Carlos Ríos Pierluisi secretario DDEC7. Sobre 70 organizaciones boricuas fueron ante el Comité de Descolonización de la ONU a denunciar el daño ambiental en proyectos como Esencia y otros, además de denunciar el coloniaje8. Andy Burnham se prepara para asumir el poder mientras un emocionado Keir Starmer se retira como primer ministro del Reino Unido9. Estados Unidos levanta parcialmente las sanciones petroleras contra Irán pero Trump dice que EEUU tiene “control total” del estrecho de Ormuz10. Messi se convierte en el máximo goleador en solitario del Mundial de Fútbol 18 golesEste es un programa independiente y sindicalizado. Esto significa que este programa se produce de manera independiente, pero se transmite de manera sindicalizada, o sea, por las emisoras y cadenas de radio que son más fuertes en sus respectivas regiones. También se transmite por sus plataformas digitales, aplicaciones para dispositivos móviles y redes sociales. Estas emisoras de radio son:1. Cadena WIAC - WYAC 930 AM Cabo Rojo- Mayagüez2. Cadena WIAC – WISA 1390 AM Isabela3. Cadena WIAC – WIAC 740 AM Área norte y zona metropolitana4. X61 – 610 AM en Patillas5. X61 – 94.3 FM Patillas y todo el sureste6. WPAB 550 AM - Ponce7. ECO 93.1 FM – En todo Puerto Rico8. WLRP 1460 AM Radio Raíces La voz del Pepino en San Sebastián9. WOQI 1020 AM – Radio Casa Pueblo desde Adjuntas 10. Mundo Latino PR.com, la emisora web de música tropical y comentarioUna vez sale del aire, el programa queda grabado y está disponible en las plataformas de podcasts tales como Spotify, Soundcloud, Apple Podcasts, Google Podcasts y otras plataformas https://anchor.fm/sandrarodriguezcottoTambién nos pueden seguir en:REDES SOCIALES: Facebook, X (Twitter), Instagram, Threads, LinkedIn, Tumblr, TikTokBLOG: En Blanco y Negro con Sandra http://enblancoynegromedia.blogspot.comSUSCRIPCIÓN: Substack, plataforma de suscripción de prensa independientehttps://substack.com/@sandrarodriguezcottoOTROS MEDIOS DIGITALES: ¡Ey! Boricua, Revista Seguros. Revista Crónicas y otrosEstas son algunas de las noticias que tenemos hoy En Blanco y Negro con Sandra.

Terence Kawaja is a media and technology investment banker and the founder and CEO of LUMA Partners, specialising in digital media, advertising, and M&A advisory. With over three decades of experience, he has advised on hundreds of high-value transactions and is one of the most influential voices in adtech and media investment.In the first of our ‘Audience with' interviews from this year's Cannes Festival, NDA's editor-in-chief Justin Pearse gets Kawaja's latest takes on live events, AI and the evolution of the media marketplace…  

PODCAST LAS NOTICIAS CON CALLE DE 22 DE JUNIO - Apelativo deja que PR tome decisión de LUMA y no sea el tribunal federal No hay agua en 8 municipios y plantean racionamiento de agua - El Vocero Ponen detente a los aumentos salariales sin procesos - El Nuevo Día La Junta dice que nos han ahorrado 76 billones en deuda que no vamos a tener que pagar - El Vocero Muere Allan Greenspan Trump mañana va a pedir prohibir el voto por correo y exigir ID para votar en USA - Punchbowl News Bomberos dicen que no han sido afectados por falta de agua - El Vocero Renunció primer ministro de Inglaterra MMM hoy voy pa Martins BBQEl mejor y más sabroso pollo asado a la varita de Puerto Rico. Cocinando diariamente comida fresca saludable y sabrosa con un montón de complementos para escoger, arroces, habichuelas, verduras, mofongo,tostones,....MMMM....Esto si es criolloMartins BBQ, TOMANDO todas las medidas de salud y sabor para mantener la mesa boricua al dia con opciones para llamar, recoger o delivery por UBER Eats, y DoorDash.MMM Hoy como en Martin's BBQAsado...Jugoso...Sabroso#martinsbbq#incluyeauspicio Alegan agresión sexual de dos jovencitas de 22 años por parte de 5 españoles en el apartamento y los españoles se fueron a España - El Vocero Gana el Bukele Trump en Colombia, pierde la izquierda soviética pero por casi nada - Noticel Advierten de calor extremo hoy - Metro Vuelven a pedir la libertad e independencia para PR en la ONU - El Nuevo día Senado investigará a Domenech - El Nuevo Día Gobernadora contratará empleados transitorios - El Nuevo Día Vega Baja también abre su parque acuático - Primera Hora  LOS DATOS DEL DÍA Brent: $80.59/barril (+0.9%) vie 19 jun Diésel: ~$3.40/galón ref. EIA 2026 S&P 500: 7,500.58 (+1.08%) jue 18 jun Dow: 51,564.70 (+0.14%) Nasdaq: 26,517.93 (+1.91%) Bono 10Y del Tesoro: 4.46% Euro/USD: 1.147 Gas natural: ~$3.35/MMBtu ref. EIA 2S26 Tasa hipotecaria 30Y: 6.47% (bajó de 6.52%)*Acciones cerraron el jueves 18: el viernes 19 fue feriado (Juneteenth) y Wall Street no abrió.

PODCAST LAS NOTICIAS CON CALLE DE 19 DE JUNIO - San Francisco Domenech acusa de corrupto San Sebastián Martir Detienen a famoso baloncelista por ley 54 Ucrania logra atacar Moscú con drones No hay agua suficiente para Esencia dice AAA - Noticel No hay dinero para agentes y oficiales, pero sí para empleados de confianza en seguridad Pública, duplican nómina - Noticel AAA tenía montones de equipos para planta Sergio Cuevas pero no lo han instalado, solo una bomba funciona - El Vocero Senado federal pendiente a escándalo de San Francisco de Domenech v. San Sebastián Martir Gobernadora quiere que LUMA se quede por un año mientras la cambian, dice que le toca a la corte decidir cómo - El Vocero Siempre innovando y con los mejores beneficios, MCS Personal Directo te ofrece cubiertas accesibles para que cuides de tu salud y la de los tuyos.Con una amplia red de proveedores de más de 15,000 médicos de libre selección. Reembolso de hasta $40 mensuales por membresía a un gimnasio o por un entrenador personal debidamente certificado. Asistencia en el hogar para servicios de cerrajería, plomería y electricidad de hasta $350 por evento hasta 4 veces al año.¡Únete HOY a la gran familia de MCS!¡Salud que completa tu vida! Llama al 787.945.1259 y oriéntate.Endoso pagado#mcs#incluyeauspicio Convocan a protestar contra la Junta el 30 de junio cuando se cumplen 10 años - El Vocero 15 meses de cárcel para constructor de casa de suegros de la gobernadora- Jay Fonseca PR Comienza proceso para llenar 175 plazas vacantes de jefes de la policía Juncos hará hotel, mientras dice que necesita poder incentivar la construcción de vivienda - Primera HoraRivera Schatz pide la renuncia De Francisco Domenech Clases comienzan el 6 de agosto - El Nuevo Día Vendieron La Mallorquina, pero proceso de compra y sacar a la dueña anterior todavía no termina - El Nuevo Día En su primera reunión, Kevin Warsh dejó las tasas en 3.5% Apple va a subir precios de productos - Bloomberg Trump destruye al Senado federal retirando a jefe de inteligencia y obligando a que voten sobre proyecto de ID para poder votar y prohibir el voto por correo - Axios Bernie Sanders va contra el Ai, mientras Anthropic en guerra con Casa Blanca - Bloomberg Baja dramática en el preciod el petróleo - OilPrice LOS DATOS DEL DÍA• Brent: ~$78.00/barril (5ta sesión a la baja, mínimo desde marzo)• Diésel (EIA, retail EE.UU.): $5.06/galón · Gasolina EE.UU.: $3.999 (bajó de $4)• S&P 500: 7,420 (−1.2%)• Dow: 51,493 (−1.0%, −507 pts)• Bono 10Y del Tesoro: ~4.45% (el 2Y saltó a 4.20%, el mayor brinco en más de un año)• Euro/USD: 1.151• Gas natural (Henry Hub): $3.25/MMBtu• Tasa hipotecaria 30Y: 6.62%

PODCAST LAS NOTICIAS CON CALLE DE 18 DE JUNIO - Hoy llega el día del jefe de la AAA ante el SenadoRivera Schatz presenta medida para investigar a Domenech otra vez Solo han llegado 37% del 100% de los fondos prometidos a Educación Especial - El Vocero Hoy hay vista del Senado federal y la gobernadora se fue para allá - Primera Hora Investigarán si hay o no algo ilegal en declaraciones de Sebastián Negrón - El Nuevo DíaJefe de Ética dice que le quitaron jurisdicción de investigar mal uso de carros y que ahora le toca a ASG - WSKNLe quitan 25% del presupuesto a oficina de Verónica Ferraiuoli - El Nuevo Día LUMA pide aumentar en 9% el costo de Genera y su combustible - El Nuevo Día “La gobernadora quería a JJ Investments para hacerle los anuncios a OGPe” - Informe de presunta corrupción - El Nuevo Día Lefranc Fortuño aguanta la info que le pide el Senado sobre Opus Miramar y la intervención de Politank - El Nuevo Día 30 millones de dólares para 107 familias que no tienen hogar ahora mismo con fondos federales - Primera Hora DACO dice que ahora está vigilando el costo de acarreo de cisternas de agua - Primera Hora Messi metió 3 goles, Mbappé 2 Si tu compañía de teléfono te está dando razones para irte, T-Mobile te da hasta $1,200 por línea para que no lo pienses más.• Porque ahora puedes traer tu número y el teléfono que ya tienes, cambiarte a T-Mobile y recibir hasta $1,200 por línea al activarte en su mejor plan.• sea, no tienes que dejar tu teléfono. Te quedas con tu equipo, haces el switch y puedes recibir hasta $1,200 por línea.• Además, te activas con beneficios que otros no te dan, como hotspot ilimitado, streaming incluido con Netflix, Hulu y Apple TV, y conexión en más de 215 destinos con internet de alta velocidad y textos ilimitados sin pagar extra.• Estamos hablando de más valor, más beneficios y una mejor experiencia móvil.• Todo conectado a la mejor red móvil en Puerto Rico.• Así que, si tu compañía actual ya no te convence, este puede ser el momento de hacer el cambio.• Porque esto no pasa todos los días. T-Mobile te paga hasta $1,200 por línea por quedarte con tu teléfono, con más beneficios, más valor y todo conectado a la mejor red móvil en Puerto Rico.• La señal está clara. Cámbiate hoy a T-Mobile.#tmobile#incluyeauspicio 300 billones para Irán el fondo de inversión - Reuters Aliados de Israel disparan contra Trump y el acuerdo de Irán - Axios Alguien prendió 7 fuegos en San Germán - Metro LOS DATOS DEL DÍA Brent$78.67/barril (−0.4%) Diésel (ULSD wholesale)bajando con el crudo (~$2.40/gal aprox.) S&P 5007,548.60 (−0.6%) Dow Jones52,003 (+0.6%, récord) Bono 10Y del Tesoro4.43% Euro/USD1.16 Gas natural$3.25/MMBtu Tasa hipotecaria 30Y6.52%

First-year Foster MBA  (Class of '27) Tejash Bagri explains how he turned a stalled application into an interview by building a go-to-market prototype before reaching out — and what that says about standing out when every candidate has the same AI tools. A practical case study for anyone in a competitive recruiting process. Tejash was part of the core organizing team for Foster's inaugural AI Spark Day and leads the school's AI and Data Analytics Society. Before his MBA, he worked as chief of staff for a group of organizations in a startup environment, where he built AI-driven workflows for research, marketing, and hiring. He reached the final sixteen of Foster's Dempsey Startup Competition and is building a product focused on AI literacy in the classroom. What you'll learn How to use a prototype to get past a resume screen when everyone's resume looks optimized Why AI fluency only matters once it sits on top of real functional or industry expertise Why you should identify the two or three areas where you're genuinely above average — and build from there A staged model for AI maturity, and where most people stall Where to keep the human visibly in control during a live interview Resources mentioned Luma and Meetup (for finding local industry events) Lovable, Replit, Databricks, Claude Code (build/prototyping tools) Company 10-K filings as interview-prep research Ethan Mollick's "jagged edge" framing of AI capability

1. Los chats no son la enfermedad: son la radiografía de la decadencia gubernamental. Ni el chat de los Brothers con Rosselló ni el actual choque entre Domenech y Negrón Reichard son anomalías. Son evidencia de una cultura política donde las decisiones de gobierno se negocian en chats privados, lejos de la transparencia que exige la función pública. 2. Hay gente que opina sin leer, dice secretaria de Justicia sobre controversia DDEC3. Justicia se desmarca de la controversia en OGPe: alega su opinión solo abordó permisos.4. Encuentran artefacto explosivo en residencia abandonada en Coamo5. LUMA dice que no pidió aumento en tarifa, pero van a aumentar la luz6. AEP gasta miles de dólares en agua y luz en edificios que se supone están abandonados, según estudio OIG7. Denuncia aprobación de proyecto que debilita veda electoral 8. “Humillación”: Trump combate la acusación de que su acuerdo con Irán es peor que el de Obama9. El principal enviado de Irán afirma que el acuerdo de paz con Estados Unidos depende de la retirada de Israel del Líbano10. Guterres: Haití vive la "crisis más severa" de A. LatinaEste es un programa independiente y sindicalizado. Esto significa que este programa se produce de manera independiente, pero se transmite de manera sindicalizada, o sea, por las emisoras y cadenas de radio que son más fuertes en sus respectivas regiones. También se transmite por sus plataformas digitales, aplicaciones para dispositivos móviles y redes sociales. Estas emisoras de radio son:1. Cadena WIAC - WYAC 930 AM Cabo Rojo- Mayagüez2. Cadena WIAC – WISA 1390 AM Isabela3. Cadena WIAC – WIAC 740 AM Área norte y zona metropolitana4. WLRP 1460 AM Radio Raíces La voz del Pepino en San Sebastián5. X61 – 610 AM en Patillas6. X61 – 94.3 FM Patillas y todo el sureste7. WPAB 550 AM - Ponce8. ECO 93.1 FM – En todo Puerto Rico9. WOQI 1020 AM – Radio Casa Pueblo desde Adjuntas 10. Mundo Latino PR.com, la emisora web de música tropical y comentarioUna vez sale del aire, el programa queda grabado y está disponible en las plataformas de podcasts tales como Spotify, Soundcloud, Apple Podcasts, Google Podcasts y otras plataformas https://anchor.fm/sandrarodriguezcottoTambién nos pueden seguir en:REDES SOCIALES: Facebook, X (Twitter), Instagram, Threads, LinkedIn, Tumblr, TikTokBLOG: En Blanco y Negro con Sandra http://enblancoynegromedia.blogspot.comSUSCRIPCIÓN: Substack, plataforma de suscripción de prensa independientehttps://substack.com/@sandrarodriguezcottoOTROS MEDIOS DIGITALES: ¡Ey! Boricua, Revista Seguros. Revista Crónicas y otrosEstas son algunas de las noticias que tenemos hoy En Blanco y Negro con Sandra.

PODCAST LAS NOTICIAS CON CALLE DE 16 DE JUNIO - Rivera Schatz dispara contra secretaria de Justicia y FEI tras querella de Sebastián Negrón Baja sustancialmente la demanda de petróleo y la compra de casas en China - Bloomberg Sebastián va contra Domenech al FEI, Ética y Thomás Rivera Schatz Hoy llega el agua a 60% de la gente del Superacueducto dice AAA - El Nuevo Día LUMA dice que hace falta un billón para conectar la generación de energía que se plantea realizar - El Nuevo Día Mañana es la vista del Senado sobre el agua y la AAA - El Nuevo Día Aprueban medida para que padres de influencers menores tengan que separar ingresos - El Nuevo Día Opus Miramar jura que no hizo nada ilegal - El Nuevo Día Arrestan 5 por presunto intento terrorista en evento de Trump y UFC con Drones - NYPost Se venden más carros eléctricos por montones, casi 75% de aumento de carros chinos - Semafor Llego la temporada de huracanes y es vital tomar medidas para asegurarnuestra tranquilidad.Si tienes dudas, llamános al 787-641-7171 Todos tienen una manera diferente de prepararse para un huracán.Lo importante es que lo hagan.Auspiciado por Universal, en nuestro servicio está la diferencia.#universalinsurance#incluyeauspicio Baja el petróleo a 78 - Oil PriceIrán jura que ganó la guerra - FT Economist dice que ahora Trump y su gente van por Cuba, pero que no deben hacerlo por la fuerza Fox compra Roku, conservadores se siguen quedando con los medios Ballroom de Trump en Casa Blanca cuesta 600 millones - Washington Post Federales investigan al gobernador y esposa de Gavin Newsom en California - Washington Post  LOS DATOS DEL DÍA Brent:$82.97/barril (−0.24%) Diésel (proy. EIA 2026):~$3.40/galón (presión al alza por Hormuz) S&P 500:7,554.29 (+1.65%) Dow:51,671.03 (+0.92%) Nasdaq:+3.0% (lunes) Bono 10Y:~4.43% Euro/USD:1.16 Gas natural:~$3.34/MMBtu Hipoteca 30Y:6.6%

Dave sits down with Eoin Clancy, VP of Growth at AirOps, to talk about what's working in B2B marketing right now. They get into the rise of the content engineer role, how to use AI to produce high-quality content without creating AI slop, and why webinars have become AirOps' top growth channel in 2026. Eoin breaks down the three signs that content is AI slop, how AirOps runs their webinar funnel end-to-end, and how they follow up with attendees without ever pushing for a demo.Timestamps(00:00) - - Intro and episode overview (04:15) - - What AirOps does and the content engineer role (09:49) - - Why good SEO principles haven't changed in the AI era (14:13) - - AirOps' growth story: 10x revenue in 12 months (17:40) - - The challenge of using AI without creating slop (20:48) - - Three signs your content is AI slop (24:47) - - How to capture and maintain your brand's tone of voice (27:41) - - Why subject matter expertise is the best content ingredient (36:49) - - Why webinars are AirOps' #1 growth channel in 2026 (42:43) - - How AirOps plans topics and sources webinar guests (44:05) - - The webinar tech stack: Luma, HubSpot, Zoom, and Clay (44:34) - - Personalized follow-up strategy and signal scoring (49:07) - - How to build internal buy-in for a long-game content strategy (54:14) - - How to fill a webinar without gating anything Join 50,0000 people who get Dave's Newsletter here: https://www.exitfive.com/newsletterLearn more about Exit Five's private marketing community: https://www.exitfive.com/***Brought to you by:Optimizely - A no-code AI platform where autonomous agents execute marketing work across webpages, email, SEO, and campaigns. Learn how to deploy agents on your marketing team at Agents in the Mix. Learn more at optimizely.com/exitfive. Vector - A contact-level ads platform that lets you build audiences from actual people on your site, clicking your ads, and checking out your competitors. Learn more at vector.co, and get their new MCP server by clicking here. Customer.io - An AI powered customer engagement platform that help marketers turn first-party data into engaging customer experiences across email, SMS, and push. Learn more at customer.io/exitfive.Join us in Stowe, Vermont for Drive 2026 - three days away from your desk to learn what's working in B2B marketing from the people who are actually doing it. Grab your ticket at exitfive.com/drive.***Thanks to my friends at hatch.fm for producing this episode and handling all of the Exit Five podcast production.They give you unlimited podcast editing and strategy for your B2B podcast.Get unlimited podcast editing and on-demand strategy for one low monthly cost. Just upload your episode, and they take care of the rest.Visit hatch.fm to learn more

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durée : 00:01:29 - Le 6/9 de l'été - par : Marion L'Hour - 80 secondes pour vous inviter à naviguer et même à vous perdre entre abstraction et réalité. Grace l'artiste allemand Gerhard Richter à qui la fondation Luma consacre une exposition. Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

PODCAST LAS NOTICIAS CON CALLE DE 5 DE JUNIO - Zelensky pide negociaciones directas entre Ucrania y Rusia por actuales lineas de batalla dando a entender que percibe que está ganando la guerra - Economist Anthropic vuelve a pedir detente de inteligencia artificial tras lograr sucesores hagan su propio submodelo - SemaforNSA Susa Mythos aunque está en lista prohibida - Axios Las reservas de petróleo de EEUU cayeron a su nivel más bajo desde 2004 y Goldman advierte que el diésel podría bajar a 20 días de suministro para agostoHezbollah rechaza pacto de cese al fuego con Israel y Líbano - Economist Menos personas sin hogar en PR - El Vocero Senador Dalmau pide investigar examen de peritos electricistas, Colegio dice que quieren suspenderlo - El Vocero Circuito cuestiona si LUMA tiene legitimación sobre Stay de PROMESA en la AEE, bonistas piden levantar el stay para que paguemos la deuda - El Vocero Educación todavía no ha pagado a centros de educación especial aunque se prometió a hacerlo - El Vocero DACO disque pendiente a los aumentos de precios de la comida y alimentos expirados - El Vocero 4 jinetes boricuas en el Belmont Stakes Space X se queda fuera del S&P por no cumplir con requisitos - Reuters Jueza permite que Digimedia enmiende demanda contra Hacienda, mientras Hacienda se opuso - El Nuevo Día Demandaron a Trump por quitarle fondos a FEMA para energía renovable a entidades, hoy hay vista en Boston - El Nuevo Día Jefe de incentivos dice que se tenían que ir en entrevista con Tax NotesProyecto plantea que AEELA sea voluntario, pero lo derrotaron - El Nuevo Día La Junta dice que sí a reforma de permisos de la gobernadora - El Nuevo Día EEUU sanciona a Díaz-Canel y la cúpula cubana; Visa, Mastercard y Meliá se van - Semafor Fuera de control la basura en Cuba - El Nuevo Día Congreso aprueba ayuda a Ucrania desafiando a Trump con votos republicanos - WSJ#universalinsurance #incluyeauspicio LOS DATOS DEL DÍA Brent$96.50/barril (−1%) WTI$92.86/barril (−0.2%) Diésel mayorista EEUU~$3.45/galón (inventarios en mínimo desde 2003) S&P 500~7,590 (futuros −0.4%, racha en riesgo) Dow49,445 (+0.6%) Bono 10Y del Tesoro4.47% Euro/USD~1.07 Gas natural$3.30/MMBtu (máximo en 4 meses) Tasa hipotecaria 30Y~7.20%NotiCel publicó hoy que el salario mínimo de PR sigue bajo el nivel federal de pobreza.La Fed TIENE que subir tasas por el petróleoLa defensa de Anthonieska presentó una moción urgente alegando que declaraciones juradas confidenciales del sumario fiscal se filtraron y se manejaron frente a cámaras en un programa de redes sociales, lo que para ellos viola los derechos de su representada, y pidieron que el Inspector General investigue quién dentro del Estado las filtró. Aparte, anunciaron que irán por tercera vez al Tribunal Supremo insistiendo en que ella no está en condiciones mentales para ser procesada, algo que ya le negaron dos veces. Y mientras todo eso queda en suspenso, el reloj corre: el término de los 120 días vence el 7 de julio y el juicio está pautado para el 23 de junio, pero esa fecha está en veremos. - Bárbara Figueroa 

La controversia en el Departamento de Desarrollo Económico y Comercio continúa escalando luego de que otro exfuncionario afirmara que las alegadas intervenciones de La Fortaleza fueron más allá de la OGPe. Mientras tanto, LUMA acudió de emergencia al Tribunal de Apelaciones en Boston para intentar evitar que el pleito sobre su contrato regrese a los tribunales de Puerto Rico.En medio de estas controversias, el alcalde de Bayamón, Ramón Luis Rivera, aseguró que Jenniffer González es una figura políticamente sólida y que es reelegible. Sin embargo, las renuncias, las denuncias de interferencia política y los conflictos con LUMA continúan alimentando preguntas sobre el funcionamiento interno de la administración.¿Quién está tomando realmente las decisiones dentro del gobierno de Puerto Rico?#ElResaltadorDeLaRealidad #PuertoRico #JennifferGonzalez #FranciscoDomenech #DDEC #LUMA #PoliticaPR #PNP #NoticiasPR #GobiernoPR #SebastianNegron #LaFortaleza #AnalisisPolitico #ActualidadPR #PuertoRicoNews

PODCAST LAS NOTICIAS CON CALLE DE 4 DE JUNIO - Jefe de seguridad nacional dice que evalúan fraude en sistema de energía de PR - El Nuevo Día Cambiar minoridad a 18 años vuelve a estar en portada - El VoceroSi tienes un billete de 2 puede que tengas mucho, pero mucho dinero - Primera Hora Estados advierten que requisitos de trabajar par Medicaid trae serios problemas - Axios  Alarma con la carne, llega el parásito come carne a vacas de Estados Unidos - WSJ En déficit la AAA, tienen que usar fondo de emergencias para mejoras - El Vocero Hoy pelean DACO y LUMA en Boston sobre fallo de pagar por los enseres - El Vocero Autorizan contrato para que la AEE use generación temporera de 10 años con Gas Natural  de Power Expectations - El Vocero Bancos se oponen a medida que elimina truco de comprar deuda barata y espetártela cara - El Vocero Asignación de millones para Ferraouili es defendida por… ella misma - El Nuevo Día Alegan intervenciones indebidas continuas desde Fortaleza en contratos - El Nuevo Día Ni la ropa de Elvia ni la de Anthonieska es la misma recuperada de la escena - El Nuevo Día Siempre innovando y con los mejores beneficios, MCS Personal Directo te ofrece cubiertas accesibles para que cuides de tu salud y la de los tuyos.Con una amplia red de proveedores de más de 15,000 médicos de libre selección. Reembolso de hasta $40 mensuales por membresía a un gimnasio o por un entrenador personal debidamente certificado. Asistencia en el hogar para servicios de cerrajería, plomería y electricidad de hasta $350 por evento hasta 4 veces al año.¡Únete HOY a la gran familia de MCS!¡Salud que completa tu vida! Llama al 787.945.1259 y oriéntate.Endoso pagado#mcs#incluyeauspicio Cese al fuego entre Israel y Líbano otra vez - CNBCHay fondos para comprar casa - Primera Hora Republicanos votaron a favor de parar guerra de Irán - Reuters En problemas famoso dominicano congresista aliado de PR - Gothamist CUBA se quedó fuera de Visa y Mastercard por sanciones a GAESA - Cuba Debate  Venezuela subiendo exportaciones 22% — Bloomberg  LOS DATOS DEL DÍABrent: $96.97/barril (-0.86%)Diésel (promedio nacional EEUU): $5.35/galónS&P 500: 7,553.68 (-0.74%)Dow: 50,687.07 (-1.21%, -620.72 pts)Bono 10Y del Tesoro: 4.49% (subió desde 4.43%)Euro/USD: 1.16Gas natural (Henry Hub): $3.21/MMBtu • • Tasa hipotecaria 30Y: 6.52%

Addy and Joey recap AI on the Lot's biggest announcements: Amazon MGM's Gen AI Creators Fund, their new AI production platform Project Nara, and the backlash that drove Jorge Gutierrez out of the program. Plus, new agentic tools from Drumina and Luma. ...

PODCAST LAS NOTICIAS CON CALLE DE 2 DE JUNIO - LUMA se canta pelao y sin dinero para poder operar - WUNO Siguen investigaciones por casos de PUA y federales presionan al gobierno para meterle mano - El Vocero 14 mil personas sin agua en PR alrededor de la isla admite la AAA - El Vocero Jueza vuelve a fallar contra LUMA y a favor de que el caso siga en tribunales estatales - El Vocero JGo dice que cuadró presupuesto, le debe 94 millones a Educación Especial - El Vocero A declararse culpable CDobleta - El Vocero Secretaria de la familia subió sueldos a empleados de confianza nos dice Luis Javier - El Vocero PPD demanda a Justicia para que entreguen info ddd casos archivados - El Vocero Gracias a exención de cabotaje han entrado 2 millones de barriles desde USA con barcos extranjeros - El Vocero DEA arresta a enfermera por robo y manipulación de fentanilo - El Nuevo Día Comisión total al jefe de la AAA - El Nuevo Día Norwegian reduce cruceros desde PR por falta de puertos dicen - El Nuevo Día Calor extremo y polvo del Sahara afectando salud de boricuas - WAPA.tvUSA hace movimientos para invadir CUBA - USS Nimitz entró al Caribe acompañado de destructores y cruceros; el buque anfibio USS Kearsarge está frente a Virginia. Drones y aviones de reconocimiento llevan meses circulando Cuba. El comandante de Southcom se reunió con militares cubanos Trump insulta a Netanyahu de Israel tras invasión de Líbano - Axios Rusia lanza cientos de drones hacia Ucrania, prohíben exportar jetfuel - Moscow Times Gobierno asegura estar listo pa huracanes, pero FEMA tiene menos recursos que antes - Metro LUMA arranca el año fiscal con déficit de $117 millones - El Nuevo Día Trump pierde otra en capitolio federal, le dicen que no a su fondo de 1.8 billones para darle a supuestas víctimas de Biden - Punchbowl Alphabet dueños de Google salen al mercado pa buscar 80 billones cash para Ai - Bloomberg #universalinsurance #incluyeauspicio LOS DATOS DEL DÍABrent: $94.58/barril (-0.42%)Diésel retail US: $5.52/galón (semana del 25 may)S&P 500: 7,599.96 (+0.26%) — récordDow Jones: 51,078.88 (+0.09%) — récordBono 10Y del Tesoro: 4.45%Euro/USD: 1.165Gas natural (Henry Hub): $3.37/MMBtuHipoteca 30Y (Freddie Mac): 6.53%

What if the cause of a dog's chronic pain, gait abnormalities, weakness, or unexplained mobility challenges isn't orthopedic at all?In this episode of PetAbility Podcast, hosts Chris Cranston, MPT, CCRP, and Cathy Symon, CVT, CCRP, CHPT, explore the often-overlooked condition known as Tethered Cord Syndrome (TCS) with pet physical therapist and rehabilitation expert Amie Hesbach. TCS occurs when the spinal cord is abnormally restricted, creating tension on the nervous system that can affect movement, comfort, and overall quality of life.Because the symptoms can mimic a variety of orthopedic, neurologic, and behavioral (think anxiety!) conditions, many affected dogs may go undiagnosed for years. Amie shares her insights into recognizing the subtle signs of TCS, the challenges of obtaining an accurate diagnosis, and the treatment and rehabilitation options available to help these dogs live more comfortable, functional lives.Whether you're a veterinarian, rehabilitation professional, trainer, or devoted dog owner, this conversation will help you better understand a condition that may be hiding in plain sight.In This EpisodeWhat Tethered Cord Syndrome is and how it affects the canine nervous systemWhy TCS is frequently overlooked or misdiagnosedCommon signs and symptoms that should raise concernConditions that TCS can mimicHow TCS is diagnosed and why diagnosis can be challengingCurrent treatment options and the role of rehabilitationPractical advice for owners seeking answers for dogs with chronic mobility issuesThe importance of advocacy, awareness, and early recognitionKey TakeawayTethered Cord Syndrome may be uncommon, but awareness matters. By recognizing the signs early and pursuing appropriate diagnostic evaluation, owners and professionals can help affected dogs receive the care and support they need to achieve their best possible quality of life.You may reach out directly to Amie by email at AmieHesbach@gmail.com or via her website: EmpowerPhysio.DisclaimerVitalVet.org, a platform for all things related to pet rehab - product information, education, and resources abound! MedcoVet (show sponsor)  Luma - advanced red-light therapy therapy that puts healing in the hands of the pet owner in the comfort of home! Use Promo Code PETPOD22  to receive discounts from our affiliates!Jope - science-backed supplements Ruff Ramp - a safe alternative to stairs Optimum Pet Vitality - education/coursework  Dr. Buzby's -Toe Grips to prevent slipping, Encore Mobility joint supplement, and Brain Boost cognitive supplement. Using this link donates 20% to PetAbility Calm & Cozy Cat Wrap - a must-have for anybody working with catsHedzUpPets Watercollars – save your dog from drowni...

We're announcing AIEWF speakers this week! Take the AI Engineering Survey!Today's guest Ethan first joined us for the LS Paper Club as the lead on NVIDIA Cosmos World Model, but then joined xAI and built Grok Imagine in 3 months:He comes back on Latent Space with some nuclear hot takes: that Video Models primarily get their intelligence from LLMs, not from training on video data, and that the next frontier for truly interactive, realtime, long-horizon world models is to work on LLMs (perhaps Interaction Models as well…)Put it this way: In the near term, the next Sora won't be a better video model, but a video agent.Generative Media may more closely follow the evolution of AI coding which went from focusing on one-shot output performance and cost, to multiturn reasoning and planning models for agents and systems that can plan, edit, test, debug, and submit PRs.At a certain point, coding models got so good that the only significant next step to improve performance was handling the orchestration of these models.Now as the performance of video models increases significantly across realism, consistency, & prompt adherence while becoming more cost efficient, the next evolution of video generation may also be systems that can plan, generate, edit, critique, and iterate across an entire creative task. In this episode, Ethan joins swyx and Vibhu to unpack what it actually takes to build frontier image and video systems: data, VAEs, diffusion transformers, audio-video alignment, inference speedups, and the hidden cost of storing and moving massive video datasets. From building NVIDIA's Cosmos world model to joining xAI as Grok Imagine was being built from zero to one, Ethan He has been at the center of some of the most important work in video generation, multimodal models, and real-time world models.We go deep on Grok Imagine, how a small xAI team shipped its first multimodal video model in three months, why iteration speed matters more than almost anything in model development, and why many of the biggest gains come from fixing tiny bugs in data and training pipelines. Flipbook: The future of VideomaxxingVideo agents are almost a sure bet to be the trend in the coming year. We end with a glance at what's beyond video agents:Flipbook caused a minor sensation this year when it was released, but most treat it as a fun demo. Ethan takes it very seriously — with the speed and cost of inference coming down every year, the future of custom video JIT UI is closer than you think. We talked about why videogen models may become the front end of AI, how generative UI could replace traditional HTML/CSS, why world models need to be real-time, interactive, and long-horizon, and why the future of video generation may depend more on language models and agents than on diffusion alone.We discuss:* Why fast iteration mattered more than meetings* Why small training bugs can drive huge model quality gains* Why coding models may make compute the bottleneck again* How image and video models are trained with synthetic captions* The role of VAEs and latent space in frontier video models* Why image models are the foundation for video models* The tradeoff between temporal compression and real-time interactivity* Flipbook, Neural OS, and the future of generative UI* Why future interfaces may go from user intent to pixels* The hidden cost of training video models: storage, egress, and GPU hours* How step distillation and consistency models (like OpenAI sCM) makes video inference orders of magnitude faster* Grok Imagine 0.9 and large-scale audio-video generation* Why audio-video alignment is harder than text-video alignment* Ethan's definition of world models* Reference-to-video, video extension, and long-context video generation* Why xAI's research communication undersells Grok Imagine* How xAI culture shaped the speed of development* AI watermarking, SynthID, and detecting generated media* Why prompt rewriting matters for video models* Grok Imagine Agent and the rise of video agents* Why language models may unlock better video generation* Robotics, physical AI, and embodied world models* Why Ethan left xAI and shifted focus toward LLMs* Self-managed context, memory, and the next frontier for language modelsEthan He* LinkedIn: https://www.linkedin.com/in/ethanhe42* X: https://x.com/EthanHe_42Timestamps00:00:00 Introduction00:01:25 From NVIDIA Cosmos to xAI00:03:24 Building Grok Imagine from Zero to One00:10:07 How Image and Video Models Are Trained00:18:53 Video Compression, VAEs, and Real-Time Tradeoffs00:22:10 Generative UI, Flipbook, and Neural OS00:32:10 The Cost of Training Large Video Models00:37:04 Distillation, GANs, and Fast Video Inference00:41:21 Audio-Video Generation and Grok Imagine 0.900:48:34 What Makes a World Model?00:55:51 Reference Videos, Long Context, and Video Memory01:00:11 xAI Culture, Research, and First-Principles Building01:09:45 AI Safety, Watermarking, and Prompt Rewriting01:13:10 Video Agents and AI-Assisted Creation01:27:32 Why Language Models Unlock Better Video01:31:15 Robotics, Physical AI, and Embodied World Models01:32:38 Why Ethan Left xAI01:34:16 Self-Managed Context and the Future of LLMs01:38:43 Ethan's Career Path and Closing ThoughtsTranscriptIntroduction: Ethan He, Latent Space, and the Path to xAISwyx [00:00:00]: We're here in the studio with Ethan He, most recently of xAI. Welcome.Ethan [00:00:10]: Thank you. Glad being here.Swyx [00:00:11]: We're also here with Vibhu. you were first coming to us or joining the latent space world because you were working on Kosmos at NVIDIA, and you did a paper. We loved it. you presented it as well, so thank you for doing that.Ethan [00:00:23]: I've actually, I also presented the MoEs twice at latent space.Swyx [00:00:29]: How did you actually hear about us? Did we reach out to you? Is that how it worked?Ethan [00:00:33]: No, actually, I-- the community. Like I realized, oh, there is this online community that people talk about AI and also learn from each other through papers every week through the Paperclip. It's very nice.Ethan [00:00:49]: I learned a lot.Swyx [00:00:49]: I think three years stop. We haven't stopped even on Christmas and New Years. many weeks I want to stop but it keeps going.Vibhu [00:00:58]: No, that was good. I think you had posted that you worked on a paper, and I was “Oh, very cool. We have Paperclip. Present then.”Vibhu [00:01:04]: But I might have reached out to you after.Swyx [00:01:05]: you-- because it's an amateur club, right?Swyx [00:01:08]: so it's very unusual and but we have sometimes paper authors come by and actually explain the paper. Today we just did, the poolside paper, which was apparently very good.Vibhu [00:01:18]: Came out yesterday.Vibhu [00:01:19]: pretty interesting, right? Fully open. They talk about everything, systems. So it's a good one. We'll, we'll recommend people to read it.Swyx [00:01:25]: Bring us up to speed on your transition to xAI, ‘cause I actually don't even know when you joined. just like tell the, tell the story about the sort of transition.From NVIDIA Cosmos to xAI: Scaling Video and World ModelsEthan [00:01:34]: Before xAI, I was working on Kosmos world model as in-- at NVIDIA. So Kosmos is, it's a giant video foundation models that can-- that aims to simulate the world and for-- it serves as a foundation of-- for all of the roboticists to build on top of. There, once I built the Kosmos one, I realized as this thing also has a scaling law similar to language model, we need to scale up the video models further. that's, that's why I realized I need to move to somewhere with much more compute resources. That's how ISwyx [00:02:13]: Than NVIDIA?Vibhu [00:02:14]: The GPU rich came themselves.Vibhu [00:02:19]: And timeline-wise, when was Kosmo? It was pretty early, right? It was open world model, open paper, everything.Ethan [00:02:25]: It was end of twenty-four.Vibhu [00:02:28]: End of twenty-four.Ethan [00:02:30]: Then at mid twenty-five, I moved to xAI. At that time-- I joined about the time when xAI was about to build video models and in multi-model models. There were no infra, no data, and no model, and it just-- as a few engineers, we built it in three months and released the first model, Grok Imagine zero point nine.Ethan [00:02:55]: And since then, I keep working on video models and move more from training and to post-training of the video models. For example, like a reference to videos, kind of like the cameo feature and, video extensions. And, before I left, I worked on a world model, leading a small team to focus on the real-time long horizon video generation.Building Grok Imagine From Scratch in Three MonthsSwyx [00:03:24]: Can you give like a rough roadmap of okay, you're on a brand-new team. Grok previously was only text, or they partnered with BFL for their image gen stuff. What do you-- what are the building blocks, right? You have compute, data you can procure somewhere. Like just what are like the sequence of things that people should think about when you're setting up a new team?Vibhu [00:03:43]: actually even deeper, not just data you can procure. You guys had to go through getting the data too, right? So you shipped it pretty fast, but yeahSwyx [00:03:51]: three months is likeVibhu [00:03:52]: From everythingSwyx [00:03:52]: actually like very surprisingly fast.Ethan [00:03:55]: One thing I say like thanks to my experience at NVIDIA, ‘cause first time when we were building Kosmos together, we built it, for about a year. So this is like the second time I do it. Roughly have an idea, what to do. I say the most important thing is the talent. Everyone were very strong and clever, very close with each other towards a common goal. So that speed up things a lot. So you reduce the communication bandwidth among people, and everyone can work towards the same goal. It's, it's like every day there's not that much meetings on the calendar, like maybe like a, like a sync a day, and after that it's, it's just all building. It was pretty fun at that time.Ethan [00:04:47]: And another thing is that xAI has very strong foundations of like data inference, model inference, and the supporting there can help the model develop a lot. When I look at, training models, I don't so actually the top important thing is like how many, how many iterations can you do, per day? and the more iteration can you do, you can, you can train the model much faster. So if you have very strong infra and you have a lot of compute, you can, you can train these models in very short period of time. That can give you a much larger buffer to, for errors, and it also gives you the opportunity to spot more bugs.Iteration Speed, Compute, and Debugging Model PipelinesSwyx [00:05:46]: What is an iteration? Is it like a few hundred steps or what are youEthan [00:05:50]: Let's say just the train-training the model, like from acquire new data and maybe design new algorithms and train a new model, maybe at smaller scale orSwyx [00:06:01]: So cycle time for like any hyperparam that you're searching.Ethan [00:06:04]: Cycle time and tune to like eval this model. Is this model better than my previous iteration?Ethan [00:06:11]: SoSwyx [00:06:11]: So it's like before you, someone had already set this up that you can iterate very quickly.Ethan [00:06:15]: I think the foundation there is extremely good forDeveloping and research models.Ethan [00:06:23]: And often I find is it-- this is kind of boring, but like a lot of the improvements does not come from new algorithms. It comes from finding small bugs here and there in the data pipeline, in the, in the model training pipeline. Those give, those give the biggest boost to the model quality.Vibhu [00:06:46]: It's interesting, right? So you say it's like small team, less communication bandwidth, but also a lot of quality is like find little bugs. It seems counterintuitive, right? You have a lot of people, you can iron out more of those, but it's interesting to see the other side, right?Swyx [00:07:00]: I also wonder, have you-- do you try using LLMs to look for bugs? I don't know.Ethan [00:07:05]: I remember at that time it was mid two thousand and twenty-five, so it's the coding model wasn't quite there yet. I remem- I remember like December two thousand and twenty-five, it was extremely good. Yeah, I've been, I've been using it at that time. It's, it's helpful. sometimes it produce codes that are kind of difficult to maintain, even though like the first time it built something extremely fast. But it gave the, like a spaghetti code, thousands of lines that I couldn't maintain, and the LLM itself couldn't figure out what's, what's wrong and how to improve on top of it. But now I find it much better. Yeah, I want to bring up another point here is now coding models are much more efficient and can help us implement stuff much faster. Compute might become a bottleneck again because previously, like if you want to train a new model, say you want to generate new synthetic data and then or write a new algorithm, it might take a few weeks. And during that period of time, you don't-- you might not have experiments to run. But now you can build that thing within a few hours, then you can immediately train a model.Ethan [00:08:24]: Now you have to have enough compute to try all of the ideas. So compute might be the bottleneck of iterating speed again.Swyx [00:08:36]: yeah, I actually, honestly, I think it's like kind of a stressful job because you're “Well, I should be trying everything, and if I'm not, then I'm not doing my job well.”Vibhu [00:08:48]: there's also the stress of you're eating thousands of GPUs per hour, which is very expensive and, compute can go to other researchers.Swyx [00:08:56]: You got the daddy Elon toVibhu [00:08:57]: You got daddy Elon.Ethan [00:08:59]: It wasVibhu [00:09:00]: But there's still finite amount of compute, like you want to use it, you want to use it well, you want more of it.Ethan [00:09:06]: That was quite stressful indeed. Yeah, I think one thing is the-- with coding models now, like a lot of these jobs can be automated, which is much better. A second, it's a, it's a marathon, so you got to maintain good health and, a regular schedule.Vibhu [00:09:28]: It's, it's hard to hear that when you shift from zero to nothing in two months.Swyx [00:09:32]: and, I think obviously the culture at xAI is very famously, people work very hard. one thing I did want to dive into, in our-- in the notes that you, that you sent ahead of time, you had specific comments about the cost of Video Gen training. presumably this is on the Colossus-1, right? the two hundred megawatt cluster. Any whatever you want to just share on that.Vibhu [00:09:54]: I think there's, there's three things we're talking about, right? So there's Video Gen, there's also the Image Gen model that you put out. Do you want to like complete the, okay, so zero to one, you have a few months. Just what are the stages of create Image Gen model?Swyx [00:10:06]: Oh, yeah, maybe I got distracted.How Image and Video Models Are Trained: Synthetic Captions, Tokenizers, and VAEsVibhu [00:10:07]: Sorry. and then, from there's Video Gen, there's Audio Gen. Would love to get into those next. But what is that first few months like? So small team, a lot of bugs, iterations, but what does it look like? Do we take something off the shelf? Do we just get data compute? What's, what's the few months like? How do you go to state-art Image Gen model? How do you just start?Ethan [00:10:28]: I cannot comment specifically how xAI did, but it's, it's a quite standard process. I can draw some, examples from Cosmos. So mainly it's building a video model, you actually need to build a image model first. And building these two models, the data you need is a hundred percent synthetic pair of language and image or language to video. Because on the, on the internet, actually, the videos don't naturally associate with text. So you can say, oh, like on YouTube, you have the title and you have the description and the commentsSwyx [00:11:11]: TitleEthan [00:11:11]: of a video, but usually they're not relevant to the video itself. And say maybe like the video is a natural scene of mountains or something, and the title is, I'm so happy today.Ethan [00:11:26]: So they have they have no correlation at all. So the first step is to, you have to generate synthetic pair of language with the videos. So you gather videos from the internet, and you use a VLM to caption the videos. So that part, here's a question, like how do you, how do you gather VLM to begin with? So if there's noSwyx [00:11:55]: You, so you fuse the model, right? LikeEthan [00:11:57]: Say if there's no like VLM exists, like how do you generate the text to the beginning, right? It's, it's impossible.Swyx [00:12:04]: I see.Ethan [00:12:05]: In the beginning, it's like you ask human to describe the video as detailed as possible.For example, you ask them to describe everything, like all objects, all characters, and all interaction and dialogues in the, in the videos. So that's in the protocol of Cosmos labeling. We require the objective we give to the labelers was that you have to describe the video as detailed as possible, such that a blind person hears a blob of text can reconstruct what the video is like from their head.Swyx [00:12:43]: Video or image? You're talking about images.Ethan [00:12:44]: Video or image, either one of them.Vibhu [00:12:47]: This was pretty common when we went from clip and DALL-E, right?Vibhu [00:12:51]: It's all training on really detailed captioning of images. So same is applied to video, but insteadEthan [00:12:57]: same appliedVibhu [00:12:57]: of using multimodal model to pass in video images and write rich descriptions, you can alsoSwyx [00:13:04]: I think there's this traditional perspective of supervised, or, very highly human curated thing. I feel like there's a unlock with unsupervised, right? Where like you have enough to bootstrap that you can just throw common corpus on it or, whatever. like unsupervised vision and language pairing, right? Like where you just have, interspersed image and text and it just learns. To me, that is the VLM breakthrough that is different from the clip, different from the LM era.Ethan [00:13:36]: It's interesting to see that you kind of need both data.Ethan [00:13:41]: For example, for theSwyx [00:13:41]: You need it to bootstrap it up. YeahEthan [00:13:43]: for the generative model training, there's also usually like a small percentage of unlabeled data. So the model is instructed to generate a video without any text instruction. That can also help the model generalize. So after this stage of generative synthetic pair, so, one important common step is to train a compressor or a tokenizer of the image or videos. So because, if you train-- If you can technically, theoretically train image or video models on pure pixels, but the problem is that the, it's, it's a lot of tokens. So like one image, it's, a thousand by a thousand, it's like one million tokens, one million pixels. It's impossible to train transformer on that. So it's, you need to train a tokenizer, which can go from image to latent space and latent space back to image.Swyx [00:14:45]: That's why we named the podcast.Swyx [00:14:48]: But, basically, you're talking about vocabulary science.Ethan [00:14:50]: so vocab.Swyx [00:14:51]: And so, what is, what is imp-- like a million is impossible?Ethan [00:14:54]: In generative models, the vocab is continuous. It's a continuous space. We can think about like you map an image to a vector. It's a, it's a fixed length vector. It's sixteen or forty-eight, something like that. And then you map that vector back to the image space. And the mapping is, has-- The mapping is patch-based. So you say you haveEthan [00:15:22]: a sixteen by sixteen patch and you match, you map that patch of pixels into this latent space.Swyx [00:15:29]: We've covered thisVibhu [00:15:30]: This is like the vision transformersSwyx [00:15:32]: VAEs,Ethan [00:15:33]: VAEs.Vibhu [00:15:34]: You basically compress your input, you do your generation, you're reasoning all that generation in smaller dimension, and then you project back out.Swyx [00:15:43]: VAE is a form compression, but I think the for me, the patching thing is from VIT, right?Ethan [00:15:48]: You can make those.Swyx [00:15:49]: Literally the, yeah, the paper is titled like sixteen by sixteen is all you need. something like that. and then I think also, people make a lot of comparisons with this kind of patching with convolutions.Swyx [00:16:02]: Which is you're, you're kind of re- reconstructing the old paradigm with the new.Ethan [00:16:05]: Actually, in VAEs, there are, there are both convolution networks and transformers. You can actually do both.Ethan [00:16:14]: After this VAE, so what you've got is you've got latent space tokens and you've got the language tokens. So now the training of the diffusion transformer, usually generative models use diffusion transformers. It is actually quite standard. It's, it's very similar to how you train a language transformer models. It's not that much difference. It's just the tokens, the visual tokens in, visual tokens out. The only difference is there's a denoising process. So you train the model to unmask some of the noise. So you add, you add random noise to the visual tokens, and then you train the model to remove those noise to generate the clean tokens. Any inference, the model can iteratively remove noise from a hundred percent noise.Swyx [00:17:12]: And then there's also, to speed things along on the tech tree of diffusion, there's CFG, and then there's, there's also, latent diffusion that, there's, there's someone in there. I think, somewhere along the line, obviously, like stability and all these other guys, pioneered a lot of this, architecture. I don't know if you want to get into that or just, or do the video side up to you.Bootstrapping Video from Image Models and Temporal CompressionEthan [00:17:37]: After you train such model, such image model, the reason it's a, it's a foundation for video models is that image models are cheaper to train, and they have much denser connection between language and text. So, sorry, language and images. For example, you train a billion, you train on a billion images, and there's a mapping from the text to the image. And the cost to train the same, like the, a billion, a billion text to a billion videos, that's much more expensive because videosNaturally have more tokens than images. Because the diffusion models, their understanding of, language purely come from this mapping. So if you don't have enough mapping, so if you only train on like a ten million videos or something, there-- you might not see enough language tokens in your training, so your model does not understand human intention enough. So that's why you really-- you train-- you first train this image diffusion models, and then you bootstrap the video model from there.Swyx [00:18:53]: One thing I did want to ask, because I-- actually, I think you're, you're the first per-- video model person I've ever talked to, I think. we've, we've like talked to Luma and all those folks. There's all these tricks in video compression where basically frame by frame there's not that much difference, so actually you don't have to regenerate or save the whole frame, right? but I think MP4 compression or something else like that.Swyx [00:19:16]: is it tempting to use that? Or as far as I can tell, everyone just treats it as, “No, we would just generate every frame.” Is that roughly the state-art?Ethan [00:19:27]: There are a few different approaches. Let's say first, like you want to just directly use MP4 compression and use that as the tokens for the transformers to train, right? So people actually have tried that, but the main challenge is the latent space for the MP4 tokens were not, were not very comprehensible for the models. It's, it's extremely hard to train on that. And there's aEthan [00:20:01]: So that's why they created VAEs, which creates more continuous, latent space, so the models can understand that latent space and learn from it much easier. Even within the VAEs, there are different difficulties of the latent space. So you can imagine something the simplest, the most naive VAE is like you have an image, and you just shuffle all of the images into a, into a vector. So you don't need to train any VAEs, right? But that latent space is extremely hard for models to train on top of. That's why there are some debate on like how do you compress the tokens. So you mentioned like you can compress frame by frame. Also, you can compress, the temporal dimension.Ethan [00:20:52]: The difference is if you compress the temporal dimension, you get a much higher compression rate. Because there's temporal redundancy between frames, because, this frame and the last frame, likely they are mostly similar, so there's only some small difference. for example, I think in 12.1 VAE, they have like a eight by eight by four compression rate. So the four temporal tokens are compressed into one tokens. That can save a lot of, save a lot of the context length. If you do it frame by frame, you have to do maybe like eight by eight by one. Your context length will be four times larger. That being said, the benefit of the frame-- per frame compression, we might come back to this later, is, real-timeness and interactivity. ‘Cause if you, if you strain the output of the model, frame by frame, you can-- the model can respond to any user request immediately. So if you have like a temporal four compression, four times compression, thenSwyx [00:22:06]: It might be laggyEthan [00:22:07]: there's a lag there in nature.Swyx [00:22:10]: So you're very pilled on this. let's just go ahead and bring it up ‘cause we have the visual prepared anyway. There's some frontier applications of real-time video gen. So Flipbook is one of the examples that went viral recently, right? What is Flipbook?Real-Time Generative UI: Flipbook, Neural OS, and Diffusion Front EndsEthan [00:22:23]: Flipbook is kind of like a web brow- web browser. You can see like it has the web bro- browser UI on top. The difference is all of the UIs are generated by generative image model in real time, and anything here are fake. But you can, you can explore inside this wor- this imaginary world. Say like we-- here we have engineering the Great Pyramid. Like the model generates this for us to understand how it works, and if we want to navigate around and understand further, we can click on some of the, some of the description here, and the model will generate a new page, new subpage describing the details we want to know about.Swyx [00:23:14]: So it's basically kind of we're playing a video, but it's pausing for our next interaction, and then it just plays the next thing based on our interaction.Swyx [00:23:23]: Which is kind of cool.Vibhu [00:23:25]: and you kind of decide your story. So this was, how do you make a pyramid? levering technique seemed interesting, right? It shows how do you take Okay, I want to know what is thisSwyx [00:23:35]: The demo, the demo tweet had more animation between frames.Vibhu [00:23:38]: I think it's just skipping,Swyx [00:23:39]: Oh, it's just skipping a lot of frames.Ethan [00:23:40]: they also have a video modeVibhu [00:23:42]: It takes a lot. There's a lot of peopleEthan [00:23:42]: but, a lot of people are using it.Ethan [00:23:45]: So it's not available.Vibhu [00:23:46]: There's a live video stream. We can try,Swyx [00:23:50]: So this is an example of the kind of future that you see at the extreme. We don't-- we're obviously not in it today.Swyx [00:23:56]: But in a world where inference is completely free this is better than generating code and text?Ethan [00:24:02]: So this is, this is a final state of where Viva will be at for word model, I think. Imagine internet doesn't exist, and then you type in google.com. Like what should, what should, what should a model show you?the model can imagine something, and this is what the model imagine. And these web pages, they completely do not exist. So I think as the inference costs come down, we are going to have generative UI for everything. If you think about how the coding model works, so they write code for a web page, and they render the code might be con- converted into binary, and the binary render the pixels on the screen. So we in machine learning, every time we have some breakthrough, obviously it's, it's more intuit. So why don't we have like user instruction to the pixel directly? So the generative UI will be user intention to the pixels directly. And say like even if I want email, let's say everyone have the same interface, but I want, I want it slightly different. I want the email to show to me like a TikTok, so I can swipe left and right for the emails. And or maybe you want something else. We can have completely different things. Or like I have I'm looking at, Instagram stories, and I don't like the Like button. I always may click it. And, generative UI resolved it. So it's going to be a revolutionary replacement of the interface. So in the future, we might have much more powerfulEthan [00:25:50]: LLMs and coding models running behind the scene. And in the, in the front-end, the diffusion model will actually be the front-end to show stuff to you. That's how I imagine it.Swyx [00:26:02]: Diffusion front-end, deterministic back-end.Swyx [00:26:04]: Something like that. I find that very expensive, but,Vibhu [00:26:08]: I find it interesting you called LLMs writing code on the back end deterministic, but okay.Swyx [00:26:14]: you write it onceVibhu [00:26:15]: Compare it toSwyx [00:26:16]: And then you execute.Ethan [00:26:17]: If you think about the cost, say, let's say H100 costs $1 per hour, and if you use this eight hours a day and thirty days, so, every month you're paying this two forty, you'll actually not wanna pay for that. That's even more expensive than Cloud Code Max. But if you think about the compute costs come down like two times every year, and I think the future will likely arrive like within few years.Vibhu [00:26:49]: It's everything, right? compute cost comes down, compute gets faster, model gets smarterEthan [00:26:54]: More efficientVibhu [00:26:54]: model gets smaller.Swyx [00:26:55]: I don't know why you say two times, ‘cause I think it's like 100 times. In language models, it is roughly one hundred to a thousand times every twelve to eighteen months, for the same given level of LMSys, ELO.Vibhu [00:27:08]: That's a net of everything, right? That's model performance alongside compute. So different than just compute costs come down. But, a very interesting future.Swyx [00:27:19]: So the web designers will have to shout out that accessibility is an issue, right? how do you deal with screen readers or whatever. But yes, this is higher bandwidth storytelling than anything you can possibly generate with code, right? So I think that's the rough idea.Ethan [00:27:34]: And I'd like to add a little bit that so human naturally have the maximum bandwidth when we are looking at things, look at videos, and we also have maximum output bandwidth when we are talking. So in the future, it might be something like we talk to AI models, and the AI model responds back with a generative UI. So that would be the maximum input and output bandwidth to interact with AI models before neural link happens.Vibhu [00:28:06]: And it's also very custom, right? Some people are very visual, some people are not as visual, right? They prefer the text. But the best thing about generative UI, right, it can also be text.Swyx [00:28:17]: There's another project that we wanted to highlight, which is the Neural OS. Kinda similar idea, but here you're literally operating, simulating an operating system with a video model.Swyx [00:28:27]: and you can play Doom, you can do Firefox. I find this like mildly less impressive, obviously, because it's an OS that I can run.Swyx [00:28:37]: But here everything is imagined.Vibhu [00:28:40]: I was, used to the Command+W to close the Firefox tab. It didn't crash. That's why I saidSwyx [00:28:45]: It's too immersive.Vibhu [00:28:46]: It's, it's too immersive for me.Swyx [00:28:47]: Too immersive.Vibhu [00:28:48]: I wanted to close the tab.Vibhu [00:28:49]: But yes, I can play generated diffusion.Swyx [00:28:51]: this is shockingly fast.Swyx [00:28:54]: Because I remember there was a demo about like maybe one to two years ago. Someone tried to do the first-person shooter with a image model. There was no consistency. It was very slow. But here it looks like realistically it's-- this is Doom.Vibhu [00:29:07]: I think there's two sides to that, right? There's okay, what is running a game? The heavy part of it is actually the game engine, all the lighting, all that stuff, the graphics. This is just kind of video, right? Like we've solved consistency. This is still, it looks like a few years old image generation. There's some temporal consistency, but it's, it's kind of just images stitched together as frame video. But it's a good visual representation to pi- to picture the future you wanna see, right? that's, that's what I see in these more so.Ethan [00:29:38]: This reminds me of how the video models gets better and better. So Neural OS is kinda if you just look at it feels like it's just a crappy version of the, like the Windows we could have, right? And, but the difference is, so the model, this model is overfitted on the existing operating systems. It can generate nothing different than that. But it's actually also similar to video models. So when we are training these video model, image model, we train them on internet. There's no imaginary supernatural stuff on the internet. But once we train this model, you can prompt the model to generate something supernatural that have never existed in the data set. So if you train your Neural OS or neural computer on the standard screen recordings on the entire internet. The model can imagine completely new interface to interact with the computer.Swyx [00:30:43]: This is one of those things that is magical to me. usually generalizing out of distribution is bad, but somehow we have learned some kind of internal world model that you say, this plus, but it looks like rainbows and butterflies, it'll do it and it will kind of make sense.Swyx [00:31:03]: So yeah, that's kind of cool. Yeah, I don't know if there's any comment more on there. I do, I do wanted to, I did wanted to touch a little bit more on the model architecture stuff, which I think you were getting. It's, really fascinating. We don't get a chance to talk about this enough. So one of the papers that we covered, we've covered every annual, segment anything release. and I don't know if you follow-- you're a computer vision guy, so youEthan [00:31:26]: I knowSwyx [00:31:27]: . So they did memory attention, which is kind of interesting. And I always think, anything where you can, across the temporal dimension, keep some consistency, I think it's, very fascinating, and I don't know if Basically, does that-- the CV side bleeding into video gen side, I think is underexplored, right? we talk about it for labeling, but actually you can borrow the architecture itself.Ethan [00:31:50]: There's, there's also complete different approaches, right? you brought up the term world model, so we went from video model to world model. There is diffusion, but there's also other approaches that people are doing. So maybe we get into those after as well,?Swyx [00:32:03]: He has a whole definition of world models and stuff. I feel like we threw a lot at you. Whatever you want to comment on.Why Video Models Are Expensive: Storage, I/O, and Training ScaleEthan [00:32:10]: I think one thing that we should actually comment back on is okay, so we were talking about the steps to train image gen to video model. One thing we don't see as much of is okay, you brought up the delta in training data, right? SoEthan [00:32:24]: you won't have as much a video model might not generalize, but what is the cost of training a large video model? So we know for LLMs roughly, okay, even like the poolside thing that came out today, right? It's a Gemma level model trained on roughly forty trillion tokens at this many H200s over this much time, right? You can see what is the exact cost of that. So how many GPU hours over how much H200 costs? So how do we do the back-end math of, same thing for video models, image models. How do you, how do you kind of break that down? I can share some back-envelope calculation. So surprisingly, video models is-- the cost is very-- is comparable to language models and obviously the largest scale is language model, maybe like a medium scale to language models. I said just storing the videos alone, it costs a lot. You can, you can maybe look up on AWS or something.Ethan [00:33:20]: You really, say if you have a billion videos and let's say, let's just say like each video, like five megabyte, then you need five petabyte to just store those videos. And also remember we talk about you use a VAE to compress the videos, and you also need to store, typically you need to store those continuous feature, in-- also in your storage. That's also comparable size with the videos themselves. So just storing these videos and the features is tens of petabytes alone. And,Swyx [00:33:58]: I just, I just looked up the calculation. Five petabytes on S3 Standard is one hundred K per month.Ethan [00:34:05]: AndSwyx [00:34:05]: It's comparableEthan [00:34:05]: and you needSwyx [00:34:06]: AndEthan [00:34:06]: And then like tens of petabytes, two hundred K. And even more expensive is you have the ingress and egress.Swyx [00:34:13]: Oh, yeah.Ethan [00:34:14]: Like you-- through the internet. You have to just to download those videos, I believe it's, it's more expensive on AWS than just storing those videos.Swyx [00:34:25]: Storing, yeah.Ethan [00:34:25]: And each training runs, you probably need to pull them once. If you train multiple times, it's, it's even more than that. So it's like just storing the network, those costs is just, it would be a few, a few millions per month to just storing everything, not to mention the GPU cost.Ethan [00:34:45]: AndSwyx [00:34:45]: my side tangent, the compute rental, like GPU rental is very efficient. There's one side, okay, you can be XAI and build your data center. Should we not just build our, storage compute as well? LikeEthan [00:34:57]: Of courseSwyx [00:34:57]: cloud cost compared to just,Ethan [00:34:59]: You save so muchSwyx [00:35:00]: store. Yeah, exactly.Swyx [00:35:01]: Especially with like egress and stuff. So.Ethan [00:35:04]: That's a good idea, but it also comes to-- there are some of its own challenges.Swyx [00:35:09]: Of course, of course.Ethan [00:35:10]: like people who build the GPU data centers, they might not expect this much, storage. And yeah, people build storage, typically they just build it somewhere with just CPUs.Swyx [00:35:23]: I just looked it up. Five-- AWS only charges for egress, not ingress. Tier five for five petabytes is two hundred and thirty K.Ethan [00:35:32]: Even more expensive than the storage.Swyx [00:35:34]: But storing is per month, right? You check in, then you cannot check out. so it's so cool. It's okay. So there's that side.Ethan [00:35:41]: So the TLDR, my backhand mathSwyx [00:35:42]: Data is larger than you think. Yes.Ethan [00:35:44]: my backhand math of GPU hours times GPU cost is also very much, I'm missing some storage.Swyx [00:35:49]: You're also-- you're basically like also more IO bound than normal training.Swyx [00:35:55]: Yes. ‘Cause like data loading, so caching everything, it becomes super important.Ethan [00:36:00]: So in Cosmos, we did a lot of optimizations to make it not IO bound. So, speaking of the training, actually training the model, the GPU cost, if you look up like the open source model, how big these video models are, I think like LTX has nineteen B parameters. That's a dense model. And people are also exploring, MoEs, so it might be twenty B active and, like a hun- hundreds B, total. So that's, that's even-- that's similar size as medium-sized LLM models. And if you, if you look at number of tokens-Uh, we disclose that in Cosmos. It's also like tens of trillions of tokens on the visual tokens. So putting this together, the cost of, training these video models, it's actually comparable with LLMs. Not to mention, the infra is slightly different from LLM, so it might be less efficient to train these models.Inference Speedups: Step Distillation, Consistency Models, and GANsSwyx [00:37:04]: Do you get the benefits of traditional diffusion speed-up? So for, images, there's LCM, LoRAs for, fine-tuning. There's, there's a lot of stuff that's beenEthan [00:37:15]: Flow matching.Swyx [00:37:16]: there's flow matching. There's a lot of stuff that's been done. there's some overlap that applies to diffusion on the inference side and stuff or?Ethan [00:37:23]: so the difference-- the inference side is a completely different story.Ethan [00:37:28]: I think for the training side, it might be a little bit hard to reduce that cost. And for the inference side, the biggest gain is from the distillation of these models. You can-- It's called step distillation, slightly different from knowledge distillation in LLMs. So you-- Typically, for flow matching models, you need like 100 steps or something. Like a distortion model even need even more, like 1,000 steps to generate a good image or video. A step distillation is try to learn to generate fewer step from the model itself. It's kind of like now we-- you use the full model to generate in 100 steps, and then you take a model that only generate 10 steps and let that model to learn from the perfect one.Ethan [00:38:25]: why this workSwyx [00:38:27]: Strong to weak seemingly.Ethan [00:38:28]: It is. It's kind ofSwyx [00:38:29]: DistillationEthan [00:38:29]: kind of like strong to weak. the-- from the modeling perspective, the strong model, the teacher model is trying to model the image and videos of inter-internet, and that distribution is extremely complex. But the step distilled model is just trying to learn from the teacher. The teacher is a model, and the size is fixed, as the distribution is much simpler than the whole internet. That's the intuition I have why step distillation can work. So usually these models serve in productions, they only run in a few steps. In Cosmos, I believe we have, we have like four step and eight steps. If you do some simpler task, image-image translation, it can even run in fewer step, like one step in Cosmos Transfer.Swyx [00:39:22]: I think this is the same intuition that guides a lot of the consistency model work. I sent you a link for, SCM. I don't know if you covered that. To me, that was actually one of, the most impressive papers I've ever seen from OpenAI.Swyx [00:39:34]: That this is the unifying grand concept of consistency models. I don't know if you have any comments on this.Ethan [00:39:41]: So there are, there are a few different approaches,Swyx [00:39:46]: Oh, yeah. Here it is.Swyx [00:39:47]: Two steps versus twenty or 100 steps, whatever. It's already done.Ethan [00:39:52]: So there are, there are a few different approaches, for example, consistency model, and there are also Actually, we shouldn't forget GAN. So GAN, actually, that was, that was the OG ofSwyx [00:40:05]: OGEthan [00:40:05]: step distillation ‘cause it trained just one step to begin with. So actually, a lot of, uh-- For example, there's a distribution matching distillation which use, which uses GAN, as one of the laws for distillation. It-- GAN just tells you, “Hey, generate an image,” and thenEthan [00:40:31]: it has a discriminator to tell, is this image real or not? So the model, the model just need to learn one of the distribution, not the full distribution. Because in training, the model is asked to reconstruct the ground truth image from the internet, which is extremely hard. And in-- When you're training GAN, it's a step process. It's just a, “Hey, you generate image. Does this image look as real as the image from the internet?” Which is a much simpler task. And, yeah, combining a lot of these approaches together, people typically do that, like consistency model and distribution matching and GAN, and we can get these few step models.Audio-Video Generation and Time AlignmentSwyx [00:41:21]: Then there's one step I wanted to add, which is audio and video.Ethan [00:41:26]: So, Grok Imagine zero point nine, I believe it's, it's a first audio video transmodel deployed at a large scale. SoSwyx [00:41:39]: And that was your first model?Ethan [00:41:40]: that was, Grok Imagine's first model. It's, it's audio video, joint generation. I think the hard part is, the modality alignment, ‘cause before this transmodel, we have, we have text to video alignment. We have this, correspondence between text and video. Typically, most of the VLMs, they understand images and videos. Video's very rare, and they don't understand audio mostly. And if you look at the audio generation on the LLM side, you can talk to them perfectly fine, but if you ask them to sing a song or something, it typically is not very good. Also, they don't have, they don't have music either. The hard part is thatUh, actually audio has two component. It has like a discrete component, a continuous component. The discrete component is like the language.Ethan [00:42:44]: So when we speak, it's just, someSwyx [00:42:47]: It's an ASR issue, yeah.Ethan [00:42:49]: It's, it's text token with some characteristics, I would say.Ethan [00:42:54]: But musicSwyx [00:42:56]: I think the speech guys would disagree with this.Swyx [00:42:57]: Like disfluencies and then,Vibhu [00:43:00]: There's tones you can get angry.Ethan [00:43:01]: Well, I say largely.Ethan [00:43:03]: the mu- but the music is completely different. It's, it's very continuous, and you cannot model them like discrete tokens in language models. this is like the hard part for models is, not to mention we have to align text, video, and audio together.Ethan [00:43:26]: SoVibhu [00:43:26]: How?Ethan [00:43:28]: So significant-- some significant challenges are like-- So first, like we talk about as the VLMs, they cannot understand most of them cannot understand audio.Ethan [00:43:39]: So you have to have some way to do the synthetic data generation for audio. You have to caption the model, and that involve, that involve synthetic data and human data effort a lot. And not just surprisingly, most of the LLMs are very bad at recognizing, like the beat, tone, and the details of the of music. They can, they can give some general prediction of which song is this, but it's very hard to describe the details of the music. like we mentioned in image generation, like you have to describe image as detailed as possible so that someone blind can reconstruct that. So here is like someoneVibhu [00:44:32]: DeafEthan [00:44:32]: someone deaf can reconstruct how the music sounds like without actually listening to it. Maybe you can think of it need to have the-- or they call the script.Vibhu [00:44:49]: Subtitles, yeah.Ethan [00:44:49]: You gotta have all the details of the music, and the dialogue.Vibhu [00:44:55]: So is the challenge there typically stuff like music and audio, or is it just Like is there a baseline? Okay, there's enough data where we can understand, narration, conversation, but there's nuances in audio that's where you hit all the data issues or is it just from stage zero, you just do it all right?Ethan [00:45:15]: So one important thing is like the alignment. So the model, the model has to know like the video and audio, the, uh-- it has to have a time-based alignment, like at which time step the video and the audio token correspond to each other. But we actually don't have this kind of alignment for most of the other modalities. If you think about like text and image, text and video, they are loosely aligned. So you can, you can have a description of what's going on in the video, but you don't have to exactly, You typically don't have exact description, oh, at, time step one second like what happened?Vibhu [00:46:02]: It's veryEthan [00:46:03]: At time step two second what happenedVibhu [00:46:03]: coarse. Yeah.Swyx [00:46:05]: So what was the ideal time step? You have to oblate it, and then it's like four seconds or something.Ethan [00:46:09]: So that comes down to how you design the model to, for the model to be aware of as a time, as a time modality. So the model is like a time aware. And that's something pretty unique if you think about LLMs. So if you ask LLM to complete a task, say they, uh-- you ask them and they will say, “Oh, this task will probably take twelve hours to complete,” and they come back in one hour. Say “I've already spent two days on this and I've exhausted everything.”Ethan [00:46:47]: So the LLMs them-themselves, they don't have a sense of time there.Vibhu [00:46:53]: I actually don't think that's just them not having a sense of time. I think it's somewhat based, right?Vibhu [00:46:58]: Like you tell someone, “Okay, go work on this feature. Go implement this,” there's a general understanding you would have of how long that would take without LLMs working at LLM speed, right? So you think back like two years ago, if I tell you to like build me like a new front end for latent space, have a search bar, have all this, you'll estimate that it'll take a few days, right?Vibhu [00:47:19]: So you tell an LLM, “Go build this.” It'll take me a few days. But I think it's somewhat grounded as opposed to them not having the best-- Not saying that they have a great understanding, but I think that example is like you can see where it comes from, right? You're trained on all over the text.Swyx [00:47:35]: They're, they're trying to estimate what a human would say.Vibhu [00:47:37]: because that's what the, that's what the data kind of represents. It's not themEthan [00:47:41]: It came from the corpus on the internet. People have a estimate of how much time.Vibhu [00:47:45]: And not even just in direct like training samples, right? Just your world understanding of tokens of how long stuff takes, right? Go read a book. It'll take you a while, right?Vibhu [00:47:56]: Even if you do nothing but read a book, it takes a few days. So yeah, LLM, I read it took me a few hours.Vibhu [00:48:01]: It'll take me a few hours to go through this research. But this is a tangent.Swyx [00:48:05]: Somewhat, yeah.Swyx [00:48:06]: This is a train of thought I haven't really expressed until now is, which is basically like a full world model must also be recursive, meaning that the participant in the world model must also be aware that they have a world model. which is like this whole recursive thing down the, down the line. but yes, and that the world model can be wrong and that they need to update it and blah. Yeah. We've, argued this on the, newsletter as well, that there needs to be sort of recursive or adversarial world models.World Models: Real-Time, Long-Horizon, Interactive VideoVibhu [00:48:34]: just, to ask, how do you define world model?Swyx [00:48:38]: Oh, yeah, let's go there.Ethan [00:48:40]: SoVibhu [00:48:40]: So just for context, we talked about, video generation, and then there's a-- if you say there's a distinction between world models, what's your, what's your definition? How do you see the two?Ethan [00:48:53]: So disclaimer, I'm not going to debate, what is world model. Yeah. there are many definitions, so I'll just talk about my definition. Since I came from the multi-model, multi-model domain, so mainly talking from video. So world model is like real-time interactive long horizon videos. So there are three parts. so we-- let's talk about them one by one. So the so interaction, so we just, we just look at Facebook and neural computer. So the interaction part of it, so you, world model can allow you to interact with them through keyboard, mouse, and maybe also voice. So these all is-- all is a modality. You can, you can interact with the model, and the model should respond reasonably. Second part is real time. So once you, once, say, you move your mouse, if, say, the world model generate a game, how fast can the game respond? So if you're like professional CS: GO players- -my say, oh, you have to respond- He's beginner within sub ten milliseconds or- Yeah even less. So that's not most of the- No, sixty FPS. Let's go. Oh, three hundred FPS. Oh, five hundred FPS. Wait. okay, yeah. I didn't do the math, but yeah, okay. Uh- Yeah, three hundred FPS, that's a three millisecond. So you have to respond- Oh, s**t. Okay. YeahEthan [00:50:29]: within a millisecond. Most of the video models cannot do that. Yeah. And, but if you, say, if you have a video model that is, say, like a digital human, the response time might be more generous. Maybe typically, for real-time voice interaction, it's like two hundred millisecond. So that's, that's much more generous. But even two hundred millisecond is pretty, it is pretty tricky, ‘cause remember we mentionedEthan [00:51:01]: you have this, temporal compression coming from the VAE. So if you, if you don't compress the temporal dimension, your sequence length is going to explode. So if you want to have this real-time, real-timeness in your model, you have to do is one context problem. And the third part is long horizon, ‘cause we-- if you're not going to just play with, video games just, a few seconds, most video models only a few seconds. We're going to play with minutes, hours. The model have to be able to generate long-form content.Ethan [00:51:42]: So putting these three together, it's, real-time, long horizon interactive videos. I think the final state will be, for example, like a video, a video version of Playbook, where you can, you can interact with, a neural computer. You move your mouse, and you click on the generative interface, and it will reply to you through pixels- generating in real time. But getting there, it's, it's a very long way to get there. So one of the first step, at Grok Imagine, where I led a small world model team there, was to build video extension. So, video extension- it's the first step of interactivity. Yeah. It's, it's the first step. Yeah. So it's the first step- You have it here, video editing, yeah. Yeah. Yeah. So the first step is because, this unlocks long horizon videos. Typically, for most of the video generation models, you give it a prompt or an image as an initial frame. You generate video, that's it. That's just, one time, done. And some creators would try to, use the last frame as a first frame for the second video. It can-- sometimes it works, but if you do it a few times, it says the quality would decrease. And- It doesn't have that context- Yeah over the full video, so the temporal- Yeah, exactly. Yeah, ‘cause you only gave it the last frame, of course, right? Yeah. Exactly. And- it's actually a pretty fun hack. if you've seen like- Oh, no, he's saying something better. Yeah. And for example, like Vue, I remember Vue 3 has like a second context of the last video. It is slightly better than using the last frame, but it has the same problem-- similar problem that it, the quality would decrease. if you extend a few times to, one minute, the video quality would look much worse than the first video. Second, another problem is that the model doesn't have long-range knowledge of, what's happening before. Say, if they generate some dialogue, some, two people speaking, and their voice might change, over some time, especially if the second conditioning, it does not cover the previous context. So these are the core challenges. So the Grok Imagine video extension, it has historical context of all of the previous generated videos. It can, It has, it has the context of, who is speaking and what objects have appeared and everything, having that to generate the next video. So if we naively do this, you can imagine, just, put all of the previous history video tokens into the context. The context lens will easily explode. Especially for video models, that can be like a few, a few million context, I would imagine- context lens. Yes.Yeah.Swyx [00:54:58]: Let's run with that.Ethan [00:54:59]: for example, like in Cosmos, I think just five seconds of video is like a fifty K or sixty K number of tokens. So like if you do, if you do fifty second, that's a five hundred K tokens. If you do longer than that, easily explode. This long horizon, problem was the first step we're trying to solve world model. It turns out people, yeah, people love video extension. Like a lot, a lot of the creators love using video extension to create longer form videos. This is the part I liked that you have a, you have an intermediate step toward the final goal instead of just a straight shot to the final version very much.Swyx [00:55:48]: But I can see you have a strong vision of where we want to end up.Long Context, Redundancy, and Efficient Interactive VideoVibhu [00:55:51]: Does it seem like it's an efficiency issue? okay, we're at a few million tokens context,. If you draw the parallel to language models, we had very short context, two thousand, eight thousand, then, you scale it up one million, ten million. sure, there's effective context, but at the end of the day, it's just what's it worth? sure, there's a whole training data side. In video, it might be slightly easier ‘cause we have a hundred million token video, right? Just take a movie with the full context there. Like is this efficiency from an inference standpoint that like it's expensive, but we know how to solve it? Or like why is this not the approach? So like my broader point was on your second point of world models, you say it needs to be interactive and live, right? You should be able to play a game and see the interaction live. So one thing I see with research is a lot of what you actually serve is different than what you build, right? So we talked about distillation. You train big model, you distill it, you do quantization, speculative decoding. We do all this stuff to serve it efficiently. Should we not just have a solution, like a world model that can interact well, do inference optimization, serve it, distill it secondary, so make it real time after you solve it? So like a-- another parallel is say, continual learning, right? What we need is someone to solve it and show it works inefficiently. Give it a few years, people will make it efficient. Same thing with regular attention, right? It worked. Over a few years, people have different forms of attention, and we've scaled it to be efficient at log context,? So kind of two things there, right? One is it seems like it works. You've scaled it. Can we not just scale it a lot more efficiently over time? Do we need a separate approach if this works? And same thing with interaction, right? if we can get it done, like if we can solve some way that it works, we can solve making it more efficient from an inference standpoint later.Ethan [00:57:53]: that's actually a very good point. So in videos, there's actually a lot of redundancies. So we solve a lot of the pixel redundancy from VE, but there's more redundancy in long range and long horizon videos. Say, if a character appear in the first clip and then it disappeared, it only reappear at the end of the video, you probably don't need the-- the context, like in the middle of the generation. So you only need that character, where you need. So that's why, I helped build another feature. It's a reference video.Vibhu [00:58:36]: Is it here?Swyx [00:58:36]: is it the same model release or different one?Ethan [00:58:39]: It's a different one.Ethan [00:58:41]: You probably need to search onSwyx [00:58:43]: I'll find itEthan [00:58:43]: X reference to video.Ethan [00:58:46]: So reference video allow you to like upload up to seven images as condition and generate the video. Say, if like I want-- it can, it can be characters or objects or even scenes. Say like I want, I want condition on, Sean's selfie and holding a bladeSwyx [00:59:07]: We have a dogEthan [00:59:08]: or whatever.Swyx [00:59:08]: We put the dog in the thing.Ethan [00:59:09]: you can put them there and the video models will generate the video from and copies the context over. So that can solve a lot of the problems there, like the long context problem. It doesn't need to have a very long context, but it's-- I feel like it's an intermediate solution. The modelSwyx [00:59:29]: It's cheating.Ethan [00:59:30]: the model should be able to like selectively know, where should I draw the references. So say if I want to generate a movie, I generate it autoregressive, like a ten second at a time or something. And now this character appear, I can look back to where it first appear and, bring that back. Yeah, this one, I put the references. Yeah, that's, Optimus, Einstein myself, Annie.Vibhu [01:00:02]: Oddly enough, I used Grok Search to find it, and it pulled your LinkedIn post. But yeah we found it.Ethan [01:00:08]: Interesting.Vibhu [01:00:10]: ButxAI's Underrated Work, Culture, and WatermarkingSwyx [01:00:11]: this is a problem. This is not your fault, but like XAI doesn't communicate all this work that you do very well because they just have the model release and then that's it. But actually, these details are very good.Swyx [01:00:22]: As far as I understand, everything you just described is state-art, like no one else has done it.Vibhu [01:00:30]: A lot of-- yeah, I have a lot moreSwyx [01:00:32]: And then, and then you just put this blog post with the cookies. I'm this is not enough,?Swyx [01:00:37]: but I, obviously this is like the high level numbers that people want to know. But no, okay, soVibhu [01:00:42]: And I wonder, like part of that is also some labs don't share research into what happens. And ifSwyx [01:00:50]: No, but this is literally bragging about how good they are, right?Swyx [01:00:54]: Like, why would you not say that you are capable of extending with full context? this is not a secret sauce. This is like we did the work. yeah, I don't know.Ethan [01:01:02]: different labs have slightly different communication styles.Swyx [01:01:07]: Anyway, if anyone from XAI is listening we are always happy to help you tell your story. Yeah, okay, so you did references, and I think, I think kind of the point you're, you're making is it is sort of like a kludge, right? this is-- you can do seven, but what about 100?Swyx [01:01:23]: Right? Then you need a completely different thing.Ethan [01:01:26]: So I think it's-- this is, a mechanism to, select the context from the history, and you might not put the entire history into the context. for example, there's a paper called Frame Pack, which haveEthan [01:01:41]: a heuristic that the latest history, the last one second, I put the entire history, and the history before that, I would, compress it and makes the video smaller. So they follow this pattern, this build overall pattern that the maximum sequence length is fixed. So the further you are from the current frame, you have a smaller image. So this is just a heuristic. I think it can be more automatic. The model is aware like which history part of it can be select. So this part of the research is actually being actively, worked on by a lot of people. It's also quite interesting. I feel this is actually, this part of long context is a little bit ahead of the LLM part.Ethan [01:02:31]: So for example, like in LLMs, if you-- so contexts keep growing. Let's say if you call tool and the tool call history is extremely long, that's still in context, and keep growing, keep growing. Even if you switch the topic to something else, the whole context was there. There are some agentic harnesses that help you to, say, prune the tool results and, prune Like when you, when you query a file, only show like the top 200 lines or something. Those were very heuristic-driven.Swyx [01:03:08]: For listeners, we did a write-up on the cloud code, leak where there are eight different kinds of pruning, including like you prune the tool results and all that. So you can, you can read up on that kind of thing.Ethan [01:03:17]: I think, one breakthrough in continual learning might be like a way to automatically, manage its own context.Swyx [01:03:27]: These are all heuristics, and they will be replaced by machine learning.Ethan [01:03:30]: InterestinglyVibhu [01:03:32]: TheEthan [01:03:32]: the same thing is being researched in both LLMs and video models.Vibhu [01:03:36]: The interesting thing is also like in the paper you showed, it's actually happening at the model level, right? Compared to like language models, sure, we have base attention, but we'll do our own compression, we'll do our own pruning, which is separate from model error.Vibhu [01:03:49]: Eventually, it all just boils in, hopefully.Swyx [01:03:52]: I think this is a form of like attention, but like also know sort of reasoning attention. I feel like that's different than normal attention.Swyx [01:04:03]: Does that, does that make sense?Ethan [01:04:04]: It's, it's different in the sense that attention, not to mention, set sparse attention aside,

En el PPP de hoy:• Seguimos analizando todo lo que sabemos hasta ahora sobre el revolú en el DDEC.• Miguel Romero demanda a la AAA por la crisis del agua en el área metropolitana y deja caer comentarios que tienen a medio mundo preguntándose si está preparando una candidatura a la gobernación.• Además, un tribunal ordena el embargo de cuentas relacionadas a Elo Molina, añadiendo otro capítulo a una saga que sigue creciendo.En el chit chat:despidos en LUMA,el ambiente político post Mensaje de Estado,y los últimos rumores de Fortaleza.

- La Junta defiende a LUMA en tribunal federal de Boston Alcalde de San Juan va contra JGo al tribunal por la AAA - El Vocero Hoy senado decide si va o no al tribunal a obligar a entregar info de Familia y el caso de Baby - El Vocero No se gradúan suficientes para mantener una industria aeroespacial - El Vocero Regresa Luis Raúl como Ai - El Vocero Mañana detienen servicios de educación especial que llevan esperando pagos desde diciembre - Los Datos Wanda Vázquez dice que no pidió escoltas contrario a lo que dice la policía - El Nuevo DíaJefe de WIPR se va para tratar ser alcalde de Luquillo - El Nuevo Día DDEC dice que está todo en orden cuando llega nuevo jefe - El Nuevo DíaSacan directivos de Phoenix Fund - El Nuevo Día Abre nuevo hotel en Barranquitas - Primera Hora Trump tiene los peores números de popularidad desde que la encuesta se hace - Economist Noruega quiere entrar a acuerdo nuclear con Francia - ReutersBaja a 91 el petróleo - Oil Price Guerra por publicidad del gobierno es lo que hay detrás de contratos entre DDEC y OGPe - CPI #incluyeauspicio #UniversalLOS DATOS DEL DÍA• Brent: $96.30/barril (+2.13%)• Diésel wholesale: $3.60/galón• S&P 500: 7,520.36 (+0.02%) — cierre récord• Dow Jones: 50,644.28 (+0.36%) — cierre récord• Bono 10Y Tesoro: 4.48% (subiendo a 4.50% hoy)• Euro/USD: 1.1636• Gas natural (Henry Hub): $3.12/MMBtu (+3.6%)• Tasa hipotecaria 30Y: 6.51% — máximo en 9 meses

PODCAST LAS NOTICIAS CON CALLE DE 26 DE MAYO - Vuelven a atacarse Irán y USA, dice el FT que Irán huele a debilidad de TrumpJGo v. Rivera Schatz hoy se reúnen los titanes Miguel Romero lanza anuncio de casi campaña - El Vocero Aumentan asesinatos en 25 más que el año pasado y esclarecimiento en 40% - El Vocero Bonistas se quejan de demandas contra LUMA y quieren paralizar sacarlos - El Vocero Fiscalía no quiere separar caso de CDobleta de los demás acusados - El Vocero 5 muertes en las cárceles y 18 en lo que va de año - El Nuevo Día Proponen amnistía para entregar armas gratis - El Nuevo Día Gobierno de PR no va a intervenir para que le devuelvan los fondos de energía solar - El Nuevo DíaEsperando contratos temporeros de energía de Power Expectations - Metro MMM hoy voy pa Martins BBQEl mejor y más sabroso pollo asado a la varita de Puerto Rico. Cocinando diariamente comida fresca saludable y sabrosa con un montón de complementos para escoger, arroces, habichuelas, verduras, mofongo,tostones,....MMMM....Esto si es criolloMartins BBQ, TOMANDO todas las medidas de salud y sabor para mantener la mesa boricua al dia con opciones para llamar, recoger o delivery por UBER Eats, y DoorDash.MMM Hoy como en Martin's BBQAsado...Jugoso...Sabroso#martinsbbq#incluyeauspicio Enfermero demanda para recuperar armas luego de caso Viqueira - El Nuevo Día Admiten Empleados de tribunales piden trabajar remoto y jornada reducida por costo de vida - Metro Trump ata acuerdos para Israel de otros países para finalizar acuerdo de Irán - Reuters Equipo de Irán estará en México para la copa mundial luego de Trump negarle que vivan en USA - Reuters El Papa se presenta contra la inteligencia artificial - Reuters China no deja viajar a talento top de Ai - Bloomberg Israel vuelve a atacar a Hezbollah en Líbano - NYT Texas decide la fuerza MAGA y de Trump entre Paxton y Cornyn - NYTIceland considera meterse a la Unión Europea ante amenazas de Trump contra Groenlandia - NYTBono Tesoro 30Y cerró el viernes en 5.06%, cerca del máximo post-2007 de 5.18%. Hipoteca 30Y subió de menos de 6% a 6.65% en tres meses (Freddie Mac reportó 6.51% esta semana).LOS DATOS DEL DÍABrent: $98.11/barril (+0.89%)Diésel mayorista EEUU: $3.74/galón (retail nacional ~$5.60)S&P 500: 7,473.47 (+0.37%)Dow Jones: 50,579.70 (+0.58%)Bono Tesoro 10Y: 4.51%EUR/USD: 1.1633Gas natural (Henry Hub): $2.95/MMBtu (+1.48%)Hipoteca fija 30Y: 6.51% • • Oro: $4,572.80/oz (+1.15%) · Bono Tesoro 30Y: 5.06%

In this episode, I sit down with Teri DeLucca for a candid conversation about what really happens behind the scenes in the speaking industry, from getting your first speaking engagements to negotiating fees, navigating “pay-to-play” conferences, and building the confidence to take bigger stages.Teri shares how she went from feeling intimidated and unsure if she belonged on stage to becoming an in-demand speaker traveling across the country. We talk openly about the realities many speakers face but few discuss publicly: speaking for free, undercharging, the gender pay gap in speaking fees, networking with other speakers, and learning to see speaking not as performance — but as service.We also dive into Teri's new AI platform, Luma, a human-centered AI “thinking partner” designed to support educators and leaders with communication, stress management, organizational culture, and decision-making. Plus, she shares exciting news about becoming a finalist for a grant funded through the Bill & Melinda Gates Foundation focused on women and AI innovation.If you've ever wondered:How speakers actually get bookedWhen to speak for free (and when not to)How to raise your speaking fees with confidenceWhat event organizers don't tell speakersHow AI is changing leadership and workOr whether you really have what it takes to speak……this conversation is for you.About Our Guest: Dr. Teri DeLucca is a developmental psychologist and the founder of Impact Early Education, which equips leaders with strategies that improve outcomes for children, teams, and businesses. She holds a dual PhD and previously worked as a research scientist specializing in teacher-child interactions and early intervention in neurocognitive and social-emotional development. Dr. DeLucca has successfully operated schools, reducing staff turnover, strengthening school culture, and driving sustainable growth. In addition to her work in education, she speaks nationally to corporate organizations and women's groups on personal leadership, communication, resilience, and coaching strategies. She is a published author, award-winning researcher, speaker, and recognized leader in the industry.About Us: The Speaking Your Brand podcast is hosted by Carol Cox. At Speaking Your Brand, we help women entrepreneurs and professionals clarify their brand message and story, create their signature talks, and develop their thought leadership platforms. Our mission is to get more women in positions of influence and power because it's through women's stories, voices, and visibility that we challenge the status quo and change existing systems. Check out our coaching programs at https://www.speakingyourbrand.com. Links:Show notes at https://www.speakingyourbrand.com/474/  Teri's website: https://impactearlyed.com/ Discover your Speaker Archetype by taking our free quiz at https://www.speakingyourbrand.com/quiz/Enroll in our Thought Leader Academy: https://www.speakingyourbrand.com/academy/ Connect on LinkedIn:Carol Cox = https://www.linkedin.com/in/carolcoxTeri DeLucca (guest) = https://www.linkedin.com/in/dr-teri-delucca-46b296200/  Related Podcast Episodes:Episode 338: Escaping the Expert Trap: From Academic Presenter to Sought-After Speaker with Teri DeLucca

PODCAST LAS NOTICIAS CON CALLE DE 22 DE MAYO - Trump destruye a la estadidad para PR - Fox News Dan concesiones en La Parguera en vez de demoler propiedades - El Vocero Salud y ASSMCA explican los casos como el de baby - El Vocero Línea aérea de España decide que no va a seguir volando a Cuba por ahora - El Vocero Muere Ismael Guadalupe, un verdadero patriota - El Nuevo Día Vienen cambios a sistema judicial - El Nuevo Día OGP pide 115 millones para pagarle a educación especial - El Nuevo Día SpaceX radica el IPO más grande de la historia - WSJOmán negocia con Irán un sistema permanente de peaje en el Estrecho de Hormuz- Bloomberg Beijing prohibió la importación de algunos chips de NvidiaMensaje de la gobernadora: Segundo Mensaje de Situación: $33,570 millones, salida de LUMA y 3,000 MW - Primera HoraRepublicanos empiezan a dejar de apoyar a Trump en cuanto a costo de vida - Reuters Siempre innovando y con los mejores beneficios, MCS Personal Directo te ofrece cubiertas accesibles para que cuides de tu salud y la de los tuyos.Con una amplia red de proveedores de más de 15,000 médicos de libre selección. Reembolso de hasta $40 mensuales por membresía a un gimnasio o por un entrenador personal debidamente certificado. Asistencia en el hogar para servicios de cerrajería, plomería y electricidad de hasta $350 por evento hasta 4 veces al año.¡Únete HOY a la gran familia de MCS!¡Salud que completa tu vida! Llama al 787.945.1259 y oriéntate.Endoso pagadoApuestas actuales dicen quién gana senado federal: Republicanos 53% / Demócratas 47%LOS DATOS DEL DÍA▸ Brent crudo: $107.20/barril (+2.1%)▸ Diésel al detal EE.UU. (AAA): $5.66/galón▸ Diésel mayorista nacional: $3.93/galón▸ S&P 500: -0.45%▸ Dow Jones: -0.48%▸ Nasdaq: -0.50% | Russell 2000: +2.56%▸ Bono 10Y del Tesoro: 4.57%▸ Euro/USD: 1.1627▸ Gas natural Henry Hub: $3.02/MMBtu (+0.62%)▸ Tasa hipotecaria 30Y: 6.63%#mcs#incluyeauspicio 

PODCAST LAS NOTICIAS CON CALLE DE 20 DE MAYO - Jefe de OGPe que se fue alegan lo fueron por traqueteo y hay guerra por agencias de publicidad - Primera Hora No hay acuerdo para los hermanos de Georgie Navarro para declararse culpables por fraude de Covid - Primera Hora Trump barre Kentucky: cae Massie, su "peor crítico republicano" - Punchbowl News Plantean eliminar el IVU en comida preparada ante la inflación - El Vocero Le deben 100 millones a maestros por carrera magisterial - El Vocero Estudiantes de Automeca ayudarían a inspecciones de autos con DACO - Primera Hora COR3 pedirá a alcaldes que hagan obras porque no encuentran empresas que puedan dar los servicios - El Nuevo Día Dicen que hoy acusarán a Raúl Castro - Axios •    Si tu compañía de teléfono te está dando razones para irte, T-Mobile te da hasta $1,200 por línea para que no lo pienses más.•    Porque ahora puedes traer tu número y el teléfono que ya tienes, cambiarte a T-Mobile y recibir hasta $1,200 por línea al activarte en su mejor plan.•    sea, no tienes que dejar tu teléfono. Te quedas con tu equipo, haces el switch y puedes recibir hasta $1,200 por línea.•    Además, te activas con beneficios que otros no te dan, como hotspot ilimitado, streaming incluido con Netflix, Hulu y Apple TV, y conexión en más de 215 destinos con internet de alta velocidad y textos ilimitados sin pagar extra.•    Estamos hablando de más valor, más beneficios y una mejor experiencia móvil.•    Todo conectado a la mejor red móvil en Puerto Rico.•    Así que, si tu compañía actual ya no te convence, este puede ser el momento de hacer el cambio.•    Porque esto no pasa todos los días. T-Mobile te paga hasta $1,200 por línea por quedarte con tu teléfono, con más beneficios, más valor y todo conectado a la mejor red móvil en Puerto Rico.•    La señal está clara. Cámbiate hoy a T-Mobile.Viene o no viene el cable submarino, ya está en la AAPP - El Nuevo Día Hormuz cumple casi 3 meses cerrado y la inflación llegó al punto de quiebre — la gasolina, el diésel y las hipotecas siguen subiendo - Economist JGo da el Mensaje de Estado este jueves con presupuesto de $33,570 millones, mientras LUMA pelea por subir el cargo fijo residencial de $4 a más de $40.Gobiernos extranjeros botan bonos del Tesoro — notas de 10 años se van a 4.62% y empuja hipotecas a 6.66% Xi recibe a Putin en Beijing y le pide a EE. UU. "urgencia máxima" para acabar la guerra en Medio Oriente.Gobernadora pide ir en una sola voz a pedir más para Medicaid, pero Rivera Schatz iba a parte - El Nuevo Día Trump saca demanda a cambio de que el IRS nunca lo pueda investigar, ni a él ni a sus hijos  - WAPA.tv Buscan la estadídad para PR sin proyecto de estadidad - El Nuevo Día Alcalde de Cataña molesto se va de conferencia cuando le cuestionan sobre sus gastos y personas vinculadas - Jay Fonseca Demandan a Phoenix Fund por 285 millones - El Nuevo Día Cooper Vision detiene expansión, dicen que solo por ahora  - El Nuevo Día Noticel dice que no tiene dispensa ética la jefa de Compras, aunque ella afirmó que sí Gobernadora veta medida para obligar a que todas las compras del gobierno tengan que estar publicadas - El Vocero Plantean cambiar la zona marítimo terrestre en el Senado, proyecto ya fue aprobado enlace Cámara - Noticel Propane Educación federal que casos de discapacidad estudiantil pasen a Salud o Trabajo - Noticel Negociado de Energía volverá a evaluar tarifa base de energía tras impugnaciones - Metro • Brent: $111.22/barril (−0.79%)• Diésel retail EE. UU.: $5.596/galón (semana del 18 mayo)• S&P 500: 7,353.61 (−0.67%) — tercera sesión consecutiva de pérdidas• Dow Jones: 49,363.88 (−0.65%, −322 pts)• Bono 10Y del Tesoro: 4.62%• Euro/USD: 1.1612 (−0.39%)• Gas natural (Henry Hub): $3.13/MMBtu (alta de 7 semanas)• Hipoteca 30Y: 6.66% (subiendo por la guerra en Irán)#tmobile#incluyeauspicio 

PODCAST LAS NOTICIAS CON CALLE DE 13 DE MAYO - 102 billetes el barril del WTI y 108 billetes el Brent - Oil PriceOperativo en dos residenciales, en Virgilio Dávila y las Gardenias, diligencian 3 órdenes de allanamiento y 4 arrestos - TelemundoPR Venezuela dice que NO a la estadidad dice Delcy Rodríguez - Primera Hora Trump planifica discutir si sigue vendiéndole armas a Taiwán o no en cumbre de China - Financial Times No viene cambio en vivienda de residenciales aunque cambie regla federal de solo poder vivir allí 2 años - El Vocero Arturo Deliz se defiende tras referirse a Justicia al cooperador que denunció todo el esquema - Jay Fonseca Premium Junta va a tener que aclarar metodología en la que consigue el dinero y que no - El Vocero Zar de energía sigue diciendo que LUMA se va a finales de este año - El Vocero Legislatura vuelve a citar a componente fiscal del gobierno - El Vocero Proponen mayoridad sea a los 18 años en PR en vez de 21 como es ahora - El Vocero CESCO va a tener licencia de los carros además de la de conducir - El Nuevo DíaPR está cortito por 400 millones en recaudos en comparación dice Junta - Metro  República Dominicana recibirá deportados de otros países desde USA - Metro Mi gente, me acaba de llegar una noticia de última hora. T-Mobile acaba delanzar un incentivo de hasta $1,200 por línea para los que se quieren cambiar decompañía.Sí, escuchaste bien. Te pueden pagar hasta $1,200 por línea cuando traes tunúmero y el teléfono que ya tienes de tu compañía actual.Esto aplica al cambiarte a T-Mobile y activarte en su mejor plan, ExperienceBeyond, con beneficios que otras compañías no te dan. Estamos hablando de hotspot ilimitado, streaming incluido de Netflix, Hulu yApple TV, y conexión en más de 215 destinos con internet de alta velocidad ytextos ilimitados sin pagar extra.Así que si tu compañía te ha dado razones para irte, T-Mobile te está dandohasta $1,200 por línea para que hagas el switch hoy mismo. Y recuerda, T-Mobile es la mejor red móvil en Puerto Rico según Ookla. La señal está clara. Trae tu número y tu teléfono, cámbiate a T-Mobile y llévatehasta $1,200 por cada línea.Empresas de hijos de Trump piden 400 millones para mina en Kazakhstan, ya tenían 1.6 billones Regresan a PR los clonadores de tarjetas - Primera Hora No hay suficientes muelles en PR para mercancía tras orden de Guardia Costera - El Nuevo Día Zar de Energía dice que la semana que viene tendrán barcazas de energía desde San Juan - El Nuevo Día Presupuesto final será presentado el viernes entre Junta y gobierno de JGO - El Nuevo Día Siguen operativos para evitar que se propague el hantavirus - El País Trump aterriza en Beijing para cumbre con Xi JinpingInflación EEUU sube a 3.8% en abrilTrump perdiendo el control del partido republicano tras Thune descartar quitar erudita federal, Johnson dice que no a proyecto de Vivienda, no va el proyecto de ballroom de Trump y Carolina del Sur irse contra redibujar distritos en Gerrymandering - Punchbowl News Inflación de tech con el "memory crunch" global y los costos para el consumidor con precios de chips → laptops, celulares, neveras inteligentes más caras → otra capa de inflación Brent:~$110.43/barril (intradía martes)WTI futures:$101.19 (-1.0%)S&P 500:7,400.96 (-0.16%)Dow Jones:49,760.56 (+0.11%)Nasdaq:26,088.20 (-0.71%)Bono 10Y Tesoro:4.439%Tasa hipotecaria 30Y:6.37% (Freddie semanal) / 6.46% (diario)CPI EEUU abril:+3.8% interanual, +0.6% mensualGasolina EEUU prom.:$4.50+/galón (+44% año/año)Gas regular PR (mayorista):~$1.20–$1.23/litro#tmobile#incluyeauspicio

PODCAST LAS NOTICIAS CON CALLE DE 11 DE MAYO -  7 asesinatos en el weekend Escándalo contra ex jefa de OCIF de multar por destruir al ex de su BFF - Jay Fonseca PR Genera pide acelerar gasificación de sistema energético - El Nuevo Día Narcos vuelven al Caribe tras casos de Venezuela y operativos de Trump - El Vocero No hay agua en San Juan por culpa de los anteriores - El Nuevo Día Se reúnen hoy senadores PPD con fiscal de justicia en caso de Suzzanne Roig - Primera Hora JGo no sabe cuándo daría mensaje de Estado - El Nuevo Día UPRM extiende semestre tras huelga y protestas - El Nuevo Día Por qué no hay casos federales de corrupción radicándose en PR, fiscales federales nos dicen - El Nuevo Día Sube agricultura como parte de economía en casi 6%, pero es solo 1% de la economía - El Vocero Empresas de petróleo del mundo hacen más dinero que nunca - El Vocero MMM hoy voy pa Martins BBQEl mejor y más sabroso pollo asado a la varita de Puerto Rico. Cocinando diariamente comida fresca saludable y sabrosa con un montón de complementos para escoger, arroces, habichuelas, verduras, mofongo,tostones,....MMMM....Esto si es criolloMartins BBQ, TOMANDO todas las medidas de salud y sabor para mantener la mesa boricua al dia con opciones para llamar, recoger o delivery por UBER Eats, y DoorDash.MMM Hoy como en Martin's BBQAsado...Jugoso...SabrosoPermiten casa de reptiles, pero no va a ser suficiente para evitar epidemia de invasores - El Nuevo Día No se puede depender de FEMA, advierten que hace falta seguro privado nacional - El Nuevo DíaContrato de LUMA y su posible cancelación será en tribunal de PR - El Vocero Se atrasa de nuevo el presupuesto del gobierno de PR - El Vocero Brote de norovirus y hantavirus pone en preocupación a población tras llegada de cruceros - El Vocero Se curan o no se curan las enfermedades crónicas - El Nuevo Día 3 muertes en la cueva del indio incluyendo un buzo Alcalde de Toa Baja anuncia resort municipal en canales de agua de Levittown - Primera Hora Gerrymandering vuelve a destruir a demócratas y le da break a republicanos - El Nuevo Día Arranca el "Cheque Para Ti": $554 millones antes de fin de mesLa llegada de Trump a Pekín el jueves es la noticia de la semana - FTTrump dice que no a propuesta de Irán y subieron dramáticamente los precios del petróleo otra vez LOS DATOS DEL DÍABrent crude: $103.80/barril (+2.5%) — sube otra vez tras rechazo de Trump a propuesta iraníDiésel mayorista PR (DACO): ~$1.20–$1.36/galón mayorista (precios al consumidor siguen presionados)S&P 500: 7,398.93 (+0.84% el viernes — récord histórico)Dow Jones: 49,609.16 (+0.02%)Nasdaq: 26,247.08 (+1.71%)Bono 10Y del Tesoro: 4.38%Euro/USD: ~1.08Gas natural Henry Hub: $2.78/MMBtu (TTF Europa: €44.21/MWh)Tasa hipotecaria 30Y: 6.33%–6.45%Apuestas - ¿Demócratas ganan la Cámara en 2026?▸ Odds: ~83% Sí (Polymarket), 80% (Kalshi) ▸ Cambio 24h: bajó algo tras decisiones SCOTUS sobre redistribución▸ Por qué importa: Si los demócratas toman la Cámara, cambia el balance para PR (estatus, fondos federales, Junta Fiscal).#martinsbbq#incluyeauspicio