Podcasts about Temporal

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.volts.wtf/subscribeTypically, AI data centers are large, inflexible loads that the grid has to build around, which is one reason utilities take so long to connect them. Emerald AI has designed a “digital brain” that can ramp down, move, or delay computing jobs in a data center on demand, making a data center a flexible asset to the grid. I talk with CEO Varun Sivaram about how the software works, what flexibility costs the compute, why it beats just installing batteries, whether utilities can enforce it, and what it would mean for clean energy.Chapters:00:00 – Introduction03:05 – Temporal, spatial, and resource flexibility06:26 – What Emerald Conductor touches on site08:35 – Who decides which workloads can flex10:55 – Who is liable when a job slows down13:45 – Who actually signs the contract14:49 – Larger and faster grid connections18:02 – Enforcing the flexibility promise19:05 – What broke in the demos, from bad nodes to slow telemetry26:41 – What flexing costs the compute jobs29:21 – Why not just use batteries, and the demand merit order35:44 – Training, inference, and substation-scale data centers40:23 – PJM, ERCOT, and legal enforceability44:50 – Renewables, gas, and consumer bills

Joe Rogan just delivered one of his most emotional and explosive statements yet about Dr. Anthony Fauci and the COVID vaccine controversy.During the discussion, Rogan claimed that he personally knows five women who became pregnant during the pandemic, received the COVID vaccine, and later suffered miscarriages. He then accused Fauci of knowing privately about potential concerns while continuing to publicly encourage vaccination.Rogan did not hold back:“I personally know 5 different people…”He went even further, calling Fauci a “sociopath” and urging people to examine Fauci's history going all the way back to the AIDS crisis and AZT.In this video, Professor Nez breaks down Rogan's remarks, the allegations surrounding Fauci, why this moment became so emotional, and what questions Americans should be asking now.Important: The statements regarding vaccines, miscarriage, and Dr. Fauci discussed in this video are claims and opinions attributed to Joe Rogan. Temporal association does not by itself establish that a vaccine caused a miscarriage, and this video is commentary rather than medical advice.

[Martes 18 de agosto, edición PM] La economía chilena se contrae un 0,2% en el segundo trimestre, mientras en plano judicial, se decreta prisión preventiva para Michael Clark y otros exdirectivos por el Caso Sartor —con el Anexo Capitán Yáber sin cupos—, mientras Franco Parisi y el PDG fichan defensa ante la indagatoria por presuntas irregularidades financieras y de firmas.

The fact that OpenAI has quickly adopted Temporal, a rapidly expanding AI ecosystem, and has even entered into a partnership with Crystal Palace FC shows that its business strategy is to pursue community-first innovation.For years, tech enterprises competed against each other on the grounds of innovative features. However, the competition has changed recently. Now the winners are those who build communities.In the recent episode of the Tech Transformed podcast, host Christina Stathopoulos, Founder of Dare to Data, is joined by Melissa Herrera, Senior Developer Advocate at Temporal, and Les Jackson, Staff Developer Advocate, to discuss the pivotal role of the community in technology. They further explore how Temporal's open-source philosophy fosters developer engagement, the impact of community feedback on product development, and the significance of partnerships, such as with OpenAI and Crystal Palace. The conversation emphasises the importance of authentic community relationships and the future direction of Temporal, highlighting the need for continuous integration and collaboration with developers.TakeawaysCommunity is a central part of Temporal's growth.Temporal's philosophy is rooted in open-source software.In-person community interactions are invaluable for developers.Feedback from the community directly shapes product direction.OpenAI's adoption of Temporal led to significant scaling.Partnerships should focus on community engagement, not just transactions.Temporal's collaboration with Crystal Palace merges tech and sports communities.Investing in community fosters trust and collaboration.Continuous integration with developer tools is essential for success.Authentic community relationships drive technology innovation.Chapters00:00 Introduction to Tech Transformed Podcast02:45 The Importance of Community in Technology05:13 Feedback from Developers: Shaping Product Direction07:51 OpenAI's Adoption of Temporal: A Case Study10:02 Unique Partnerships: Temporal and Crystal Palace15:12 Looking Ahead: Future of Temporal and Community Engagement19:38 Final Thoughts: Investing in CommunityTemporal, Enterprise AI, Developer Communities, Developer Advocacy, Open Source, OpenAI, AI Agents, AI Infrastructure, Durable Execution, AI Orchestration, Enterprise Software, Developer Experience, AI Workflows, AI Adoption, Community Led Growth, Developer Led Growth, Temporal SDK, Software Engineering, AI Engineering, Enterprise Technology, Crystal Palace, Tech Transformed

In this episode, Piergiorgio Lochner speaks with Arijana Lovrečić-Huzjan about giant cell arteritis and its neurological presentation.

Devocional para hoy:No te confundas. Jesús es el mismo ayer, lo es hoy y lo será mañana. ¡Que ninguna doctrina y tendencia cultural o religiosa de estos tiempos te alejen de la verdad de Dios!Busca, Hebreos 13:8-9Puedes ver el video aquí, https://vidawc.short.gy/De348VLee el articulo completo aquí, https://vidawc.short.gy/De348Escucha el audio aquí, https://vidawc.short.gy/De348ABuen DiaPr. Juan C Quintero#ETERNO, #FE, #CONFIAR, #ADORAR, #DIOS, #JESUS, #ESPIRITUSANTO, #DEVOCIONAL, #PASTOR, #IGLESIA, #VIDA, #BIBLIA, #PALABRADEDIOS, #BUENDIA, #TEMORES, #VIDAWORSHIPCENTER, #JUANCQUINTERO, #JCQPastor, #VidaWC, #BuenDiaTodosLosDiasConviértete en un supporter de este podcast: https://www.spreaker.com/podcast/buen-dia-todos-los-dias--3612971/support.

This episode is presented by Namespace.so, building high-performance cloud infrastructure for modern software development and AI-powered engineering. Engineering leaders from Cursor, Temporal, Tailscale, Legora, and Namespace discuss how AI agents are rapidly reshaping software development. From generating hundreds of PRs and debugging complex systems to running long-lived agents in the cloud, the conversation explores what's changing—and what isn't—as AI becomes part of everyday engineering. The group dives into reliability, security, context, observability, and managing fleets of agents, while examining why systems thinking and human judgment may matter more than ever as writing code itself gets easier. (Co-host)Namespace's Founder & CEO, Hugo Santos - https://www.linkedin.com/in/hugomgsantos/ Temporal Technologies's Director of Engineering, Yimin Chen - https://www.linkedin.com/in/ACwAAAwmUjcBTcOPTLnB5Cq6T7DPoQdcertQGMo Legora's Director, Platform Engineering, Greg Bell - https://www.linkedin.com/in/ACwAAABMP8oBhtLWLYNuzRM0MrQjHIoHYypmIGk Cursor's VP, Forward Deployed Engineering, Pauline Brunet - https://www.linkedin.com/in/ACwAAAXbWW8BYDDbSHlGjbN4CKkAGXaxsUJB0BE Tailscale's Director of Engineering, Rhea Ghosh - https://www.linkedin.com/in/ACwAAADSrI4Blak2OHN5pdkscC_T_2otRzXDvd4

Katy Milkman shares one technique that could keep you exercising for 55% longer.  --- Become an FSB member: https://get.fsb.org.uk/nudge/ Unlock the Nudge Vaults: https://www.nudgepodcast.com/vaults Katy's book: https://amzn.to/3RF63xA  Katy's podcast: https://www.schwab.com/learn/choiceology  Katy's newsletter: https://www.katymilkman.com/newsletter-milkman-delivers  Subscribe to my newsletter: https://www.nudgepodcast.com/mailing-list  Connect on LinkedIn: https://www.linkedin.com/in/phill-agnew/  --- Today's sources: Gallus, J. (2017). Fostering public good contributions with symbolic awards: A large-scale natural field experiment at Wikipedia. Management Science, 63(12), 3999–4015. Hershfield, H. E., Shu, S., & Benartzi, S. (2020). Temporal reframing and participation in a savings program: A field experiment. Marketing Science, 39(6), 1039-1051. Milkman, K. L., Minson, J. A., & Volpp, K. G. M. (2014). Holding the Hunger Games hostage at the gym: An evaluation of temptation bundling. Management Science, 60(2), 283–299. Rai, A., Sharif, M. A., Chang, E. H., Milkman, K. L., & Duckworth, A. L. (2023). A field experiment on subgoal framing to boost volunteering: The trade-off between goal granularity and flexibility. Journal of Applied Psychology, 108(4), 621–634. Woolley, K., & Fishbach, A. (2016). For the fun of it: Harnessing immediate rewards to increase persistence in long-term goals. Journal of Consumer Research, 42(6), 952–966.

En el capítulo de hoy de Un verano en el Expreso de Medianoche, Noemí López nos acompaña para adentrarnos en el inquietante mundo de las distorsiones temporales. ¿Puede el tiempo comportarse de una manera diferente a la que conocemos? Hablamos de personas que aseguran haber perdido horas, trayectos realizados en tiempos imposibles, lugares que parecen pertenecer a otra época y experiencias en las que pasado y presente parecen mezclarse durante unos instantes. ¿Son simples alteraciones de nuestra percepción o existen momentos en los que el tiempo realmente puede distorsionarse? Historias, testimonios y muchas preguntas en un viaje hacia uno de los grandes misterios de nuestra existencia: el tiempo. Porque ya sabes que, también en verano, el misterio no tiene vacaciones. APOYA A EXPRESO DE MEDIANOCHE Accede a todos nuestros contenidos exclusivos y ayúdanos a seguir viajando por el misterio: https://www.ivoox.vip/premium?affiliate-code=6b635ba6a54f97bbd521a44d5dd7cd77 DIPLOMA DE OYENTE DISTINGUIDO 2026 Forma parte oficialmente de nuestra comunidad y consigue tu diploma personalizado: https://www.expresodemedianoche.com/diploma-oyente-distinguido/ ¿VIAJAS CON NOSOTROS AL MISTERIO? Tu opinión también forma parte del programa. Cuéntanos qué te ha parecido este episodio, comparte tus teorías y déjanos tu comentario. Te leemos. Dirección y presentación: José Paredes MEDIANOCHE PRODUCCIONES Porque nos une el misterio. Teléfono y WhatsApp: +34 600 088 391 Correo electrónico: contacto@expresodemedianoche.com Web oficial: https://www.expresodemedianoche.com/ YouTube — Expreso Live: https://www.youtube.com/channel/UCV9PdMmFZKQz5v71zyz7T8Q Instagram: https://www.instagram.com/expresomedia/ TikTok: https://www.tiktok.com/@expresomedia Discord: https://discord.gg/FAmktKTUSw Twitter: https://twitter.com/expresomedia Facebook: https://www.facebook.com/Expresomedia Telegram: https://t.me/expresodemedianoche Este contenido ha sido generado total o parcialmente por inteligencia artificial ¿Quieres anunciarte en este podcast? Hazlo con advoices.com/podcast/ivoox/160341 Este contenido ha sido generado total o parcialmente por inteligencia artificial. Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

Crossing to the occult? Why not translating the TLM to the vernacular? All religions leading to God? All this and more on Open Line Friday with Colin Donovan.

Confira nesta edição do JR 24 Horas: Um temporal com ventos de até 132 km por hora provocou falta de energia e paralisou o sistema de trens da região metropolitana de Porto Alegre. O tempo virou após às nove horas da noite. Quase 400 mil residências seguem sem energia elétrica. Mais cedo, um tornado atingiu a cidade de Pedro Osório, no sul gaúcho.  

El frente de tormenta avanza sobre la capital provincial con lluvias intensas, viento y un brusco descenso de temperatura. Ya se registraron la caída de un cartel comercial y de varios árboles que provocaron complicaciones en la vía pública.

El intenso fenómeno provocó anegamientos en distintos sectores de la ciudad, ingreso de agua en viviendas y cortes de energía. El intendente Fabio Villa destacó que el sistema de drenaje respondió de manera eficiente y confirmó que la situación ya fue normalizada.

En Perspectiva Interior - Salto: ¿Cómo está el sector productivo a 15 días del temporal? by En Perspectiva

Tres incendios forestales siguen activos en México Temporal deja muertos, comunidades aisladas y miles sin luz en ChileHace 169 años comenzó el alumbrado público en la Ciudad de MéxicoMás información en nuestro podcast#grc

Ceuta está colapsada por la llegada masiva de miles de migrantes. No hay todavía una cifra oficial de todos los que han conseguido cruzar la frontera, lo que sí esta confirmado es que, al menos, 15 personas han muerto intentando llegar a nado. La Comunidad de Madrid ha puesto a la venta, en menos de 24 horas, el ático que había comprado como oficina temporal. El objetivo es destinar lo recaudado a los afectados por los incendios.

Confira os destaques do Jornal da Manhã desta quinta-feira (30): O senador Cleitinho Azevedo confirmou que será candidato ao governo de Minas Gerais pelo Republicanos, contrariando uma nota divulgada pelo próprio partido. Durante o anúncio, também apresentou o ex-prefeito Luís Eduardo Falcão como pré-candidato a vice. Reportagem: Rodrigo Costa. O presidente Lula sancionou a lei que cria o chamado "Pix Pensão Alimentícia", mecanismo que permite a cobrança automática da pensão diretamente da conta do pagador. A medida busca agilizar o cumprimento das decisões judiciais sobre o benefício. Reportagem: Thaís Sprovieri. A defesa de Jair Bolsonaro afirmou que desconhecia o uso de um vídeo produzido com inteligência artificial exibido na convenção do PL. Os advogados tentam evitar possíveis consequências no STF, enquanto o episódio também pode gerar impactos na candidatura de Flávio Bolsonaro. Reportagem: Janaína Camelo. Ronaldo Caiado e Gilberto Kassab criticaram a convenção do PL que oficializou a candidatura de Flávio Bolsonaro à Presidência. Segundo eles, o evento foi marcado por ataques políticos, poucas propostas e desviou o debate sobre o futuro do país. Reportagem: Marco Viana. Fortes rajadas de vento provocaram a morte de duas pessoas e deixaram mais de 680 mil imóveis sem energia no Rio de Janeiro. A tempestade também interrompeu a circulação de trens e do metrô em diferentes regiões do estado. Reportagem: Rodrigo Viga. Pesquisa PoderData/Aya mostra empate técnico entre Lula e Flávio Bolsonaro em um eventual segundo turno da eleição presidencial. O presidente aparece com 46% das intenções de voto, contra 43% do senador, dentro da margem de erro, mantendo o cenário de polarização. O Aeroporto de Congonhas retomou as operações após os fortes ventos que atingiram São Paulo. Ao todo, 30 voos foram cancelados ou tiveram horários alterados em razão das condições climáticas. Reportagem: David de Tarso. O Irã deve receber nas próximas semanas um lote de até 400 lançadores portáteis de mísseis antiaéreos fabricados na China. O acordo busca reforçar as defesas do país após meses de conflito com Estados Unidos e Israel. Reportagem: Luca Bassani. A Rússia realizou um novo bombardeio em larga escala contra a Ucrânia, deixando ao menos oito mortos e 12 feridos. Os ataques atingiram diversas cidades e regiões do país, incluindo Kiev e Lviv. Reportagem: Luca Bassani. Essas e outras notícias você acompanha no Jornal da Manhã. Learn more about your ad choices. Visit megaphone.fm/adchoices

Los fuegos en las provincias de Madrid y Ávila ya están estabilizados, es decir, que las llamas no siguen avanzando. Mientras, en la provincia de Zamora, un incendio que se originó ayer por la tarde ha obligado a evacuar al menos 12 municipios. Y otro incendio que preocupa es el de Vall D'Uxió, que ha afrontado una noche crítica con más de 400 efectivos tratando de controlarlo. La crónica política hoy estará marcada por el ático de lujo adquirido por la CAM, cuya compra no se hizo pública ni aparece en el portal de transparencia autonómico. Esta vivienda ubicada en Chamberí, según Isabel Díaz Ayuso, se utilizará de manera temporal para tener reuniones mientras duran las obras de Puerta del Sol, que es donde se encuentra su sede normalmente.

Authors Zhuofan Li, Daniel Dohan, and Corey M. Abramson discuss the article, "Temporal Misalignment and Unequal Agency: What Terminal Cancer Patients Teach Us about Time and Inequality," published in the August 2026 issue of American Sociological Review.

Tertulia y análisis con Mariano Alonso, Isabel García Pagán y Arturo Puente

Hey baby, I hear the blues a-callin'.Temporal causality loops and Season 5, Episode 18See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

El presidente de la Sociedad Nacional de Agricultura (SNA), Antonio Walker, analizó las consecuencias económicas que tuvieron las últimas lluvias que afectaron a gran parte del país, especialmente el norte, advirtiendo que el daño suma "cientos de millones de dólares"."Yo no tengo recuerdo, y llevo 40 años trabajando en el campo, de haber tenido una concentración de lluvia en tan poco tiempo como esta (de los últimos días)", sostuvo el exministro de Agricultura de Sebastián Piñera."Tenemos un Niño que se está portando muy mal. Tenemos una isoterma muy alta y llovió a 2.800 metros de altura anoche. Este es un Niño que va a causar mucho daño. Están anunciadas precipitaciones para septiembre, octubre y noviembre. Entonces esto sigue, no ha terminado", aseveró.Por otro lado, Walker abordó los nuevos aranceles del 12,5% fijados por el gobierno de Estados Unidos a más de 60 economías, entre las que se incluye a Chile, por su presunta importación de bienes creados mediante trabajo forzoso. Walker destacó que Estados Unidos es el segundo socio comercial de Chile, sin embargo, "de Trump se puede esperar cualquier cosa; medidas muy unilaterales, una política exterior muy errática".El Diario de Cooperativa, con Verónica Franco y Rodrigo Vergara.Escucha más episodios en Cooperativapodcast.cl

El pasado viernes 24 de julio debía finalizar el fin del llamado TPS, el Estatus de Protección Temporal del que gozan los haitianos en Estados Unidos desde el terremoto de 2010. Su revocacion, ordenada por Donald Trump para Haití y tambien para una decena de paises, deja a mas de 300 mil haitianos en el limbo. Este Estatus de Protección Temporal permite a los ciudadanos de paises afectados por catástrofes naturales o conflictos armados residir o trabajar en Estados Unidos. Haití goza de este estatus desde 2010, tras el devastador seísmo que sacudió la isla. A finales de junio, la Corte Suprema del país autorizó al Gobierno de Donald Trump a revocar este permiso, lo que dejará a su suerte a 330.000 haitianos como explica Paul Christian Nanphy, de la red Acción Familiar. "Estamos viviendo un momento muy crítico ya que creemos en la reflexión de las causas de migración, el por qué la gente sale de países como Haití, Venezuela, El Salvador, Honduras, Nicaragua y otros muchos más. Actualmente, deportar a cualquier persona a Haití, El Salvador o Venezuela es forzarla a arriesgar su vida", afirma Christian Nanphy. Estos haitianos podrian ser deportados en cualquier momento,  cuando la violencia de las pandillas persiste en el pais. Los grupos armados controlan el 90 % de Puerto Príncipe, la capital, y se expanden a otras zonas. El miembro de Acción Familiar asevera que simplemente las imágenes de la vida cotidiana de las personas en Haití son prueba suficiente del riesgo que vive la población en el país caribeño. "Cualquier deportación pone su vida en riesgo, ya que los grupos armados saben quién viene y de dónde viene, lo que la convierte en potencial víctima de secuestro", pone de ejemplo Christian Nanphy como uno de los peligros para los posibles haitianos expulsados de Estados Unidos. La revocacion de este estatus tambien afecta a ciudadanos de Venezuela, Nicaragua, Ucrania, Siria y otra decena de países. Christian Nanphy considera "preciso y necesario encontrar una solución para las personas que ya están aquí (EE.UU) trabajando y pagando impuestos legalmente puedan seguir viviendo y contribuyendo a la economía estadounidense".  La situacion en Haiti es muy critica. Según el último informe de la Oficina de las Naciones Unidas para los Asuntos Humanitarios,en Haití, 5,7 millones de personas —casi la mitad de la población— padecen hambre aguda.

El pasado viernes 24 de julio debía finalizar el fin del llamado TPS, el Estatus de Protección Temporal del que gozan los haitianos en Estados Unidos desde el terremoto de 2010. Su revocacion, ordenada por Donald Trump para Haití y tambien para una decena de paises, deja a mas de 300 mil haitianos en el limbo. Este Estatus de Protección Temporal permite a los ciudadanos de paises afectados por catástrofes naturales o conflictos armados residir o trabajar en Estados Unidos. Haití goza de este estatus desde 2010, tras el devastador seísmo que sacudió la isla. A finales de junio, la Corte Suprema del país autorizó al Gobierno de Donald Trump a revocar este permiso, lo que dejará a su suerte a 330.000 haitianos como explica Paul Christian Nanphy, de la red Acción Familiar. "Estamos viviendo un momento muy crítico ya que creemos en la reflexión de las causas de migración, el por qué la gente sale de países como Haití, Venezuela, El Salvador, Honduras, Nicaragua y otros muchos más. Actualmente, deportar a cualquier persona a Haití, El Salvador o Venezuela es forzarla a arriesgar su vida", afirma Christian Nanphy. Estos haitianos podrian ser deportados en cualquier momento,  cuando la violencia de las pandillas persiste en el pais. Los grupos armados controlan el 90 % de Puerto Príncipe, la capital, y se expanden a otras zonas. El miembro de Acción Familiar asevera que simplemente las imágenes de la vida cotidiana de las personas en Haití son prueba suficiente del riesgo que vive la población en el país caribeño. "Cualquier deportación pone su vida en riesgo, ya que los grupos armados saben quién viene y de dónde viene, lo que la convierte en potencial víctima de secuestro", pone de ejemplo Christian Nanphy como uno de los peligros para los posibles haitianos expulsados de Estados Unidos. La revocacion de este estatus tambien afecta a ciudadanos de Venezuela, Nicaragua, Ucrania, Siria y otra decena de países. Christian Nanphy considera "preciso y necesario encontrar una solución para las personas que ya están aquí (EE.UU) trabajando y pagando impuestos legalmente puedan seguir viviendo y contribuyendo a la economía estadounidense".  La situacion en Haiti es muy critica. Según el último informe de la Oficina de las Naciones Unidas para los Asuntos Humanitarios,en Haití, 5,7 millones de personas —casi la mitad de la población— padecen hambre aguda.

Confira na edição do Jornal da Record desta sexta-feira (24): 9 entre 10 motoristas de aplicativo estão endividados e não contribuem para a aposentadoria. Com cheia dos rios, o risco de inundação volta a assustar Porto Alegre (RS), dois anos depois da grande enchente. Temporal com ventos fortes provoca estragos e mata uma pessoa no interior de São Paulo. Bahia se torna o estado com mais mortes de motociclistas nas estradas federais. Navio chinês ataca embarcações filipinas com canhões d'água.

The boys react to the world going crazy for The Odyssey, not so crazy for Avengers: Doomsday and Angus going crazy for Tenet explainer YouTube. Join our Patreon where you can hear twice as much Hey Fam and become a member of our lit Discord. Hosted on Acast. See acast.com/privacy for more information.

¿Te pasa que te sentás a resolver algo simple y, sin darte cuenta, pasaron dos horas? El TDAH no afecta solo la atención: afecta la forma en que tu cerebro percibe el tiempo. A esto Barkley lo llamó "ceguera temporal" o "miopía de futuro", y en este episodio te explicamos exactamente cómo funciona y qué hacer al respecto.Descubrirás:✅ Qué es la ceguera temporal según Barkley y cómo se divide en cuatro procesos: percepción, ritmo, memoria prospectiva y valor motivacional del futuro.✅ Los cinco patrones que vemos en consulta en INECAP —como "el tiempo elástico" o "la activación por urgencia"— y por qué no son falta de voluntad, sino disfunción ejecutiva.✅ Siete estrategias concretas para reorganizar tu relación con el tiempo, empezando por la más simple: registrar tu estimación versus tu duración real.

Brasil proíbe foie gras após classificar técnica como maus-tratos. Começa a valer lei que autoriza venda de spray de pimenta para mulheres; veja regras. STF autoriza investigação contra ministro do STJ Marco Buzzi em caso de venda de sentenças. Temporal com ventos de 70 km/h causa estragos, derruba árvores e deixa Ribeirão Preto (SP) parcialmente sem energia, telefonia e internet. Frente fria mantém chuva no Sudeste e no Paraná; temporais voltam ao Sul no domingo.

Eternal Hope for Temporal Pain by Orchard Hills Bible Church

Durante el debate sobre el manejo comunicacional y la coordinación del Gobierno por los efectos de la lluvia en el Norte Chico, la presidenta del Partido Socialista manifestó que "me preocupa un poco el tono complaciente del Gobierno, de bajar un poco el perfil. Más allá de las declaraciones desafortunadas de algunos ministros, o de la ausencia del ministro de Defensa, que me parece del todo inexplicable".Por su parte, el presidente del Partido Comunista, Lautaro Carmona, apuntó a que la magnitud del desastre superó las capacidades de anticipación de las autoridades pese a las advertencias previas. "Un temporal como situación crítica muy advertido, con mucho tiempo, finalmente pilló por sorpresa o pasó por sobre las capacidades que tenían las autoridades para orientar y evitar estas muertes y esta cantidad de damnificados".Desde el oficialismo, el diputado Eduardo Cretton (UDI) matizó las críticas al llamar a priorizar la respuesta a la emergencia por sobre la disputa política. "La crítica política es legítima, pero tenemos que centrarnos hoy día, como lo ha señalado el Presidente de la República, en enfrentar la emergencia. Y para eso, en Chile la verdad es que tenemos que dejar de lado por un momento los colores políticos y centrarnos en el bienestar de las personas", planteó.El Primer Café. Conduce: Cecilia Rovaretti.Descubre más contenidos como este en Cooperativapodcast.cl

El delegado presidencial provincial de Huasco (Región de Atacama), Juan Donoso, realizó un balance de los efectos del sistema frontal en la zona, confirmando un fallecido, más de 21 mil aislados y cortes en diversas rutas producto de socavones.En conversación con El Diario de Cooperativa, la autoridad regional informó que este martes "nos encontramos con un nuevo pulso de precipitaciones y la verdad es que la lluvia no nos da tregua. Actualmente tenemos alrededor de 21.724 personas aisladas entre todas las comunas producto de las constantes crecidas y quebradas que se activan".Respecto al corte de rutas, Donoso explicó que la Ruta 5 Norte se mantiene habilitada desde Vallenar hasta Copiapó. Sin embargo, en el tramo entre Vallenar y la Región de Coquimbo existen "varios cortes y socavones que se produjeron dada la última lluvia y no está con conexión todavía".El Diario de Cooperativa. Conducen: Verónica Franco y Rodrigo Vergara.Encuentra más episodios en Cooperativapodcast.cl

El director ejecutivo de Rumbo Colectivo alertó sobre la urgencia de una planificación urbana adaptada a la crisis climática, e hizo un enérgico llamado a terminar con la construcción desregulada en zonas de riesgo. Para ello, según Leighton, el país debe replicar el exitoso modelo de exigencia de la normativa antisísmica enfocado en resistir los embates de los nuevos e intensos fenómenos hidrometeorológicos.Luis Ruz, de Democracia y Comunidad, coincidió en que el cambio climático es una realidad instalada: "una de las discusiones que no hemos hecho con profundidad es cómo somos capaces de adaptarnos a esta nueva realidad, en lo que significa no solamente la planificación urbana o cómo se construye, sino también cómo hacemos la adaptabilidad urbana", señaló.Álvaro Pezoa, de Ideas Republicanas, planteó que la respuesta a la crisis climática debe centrarse en la búsqueda de un "justo equilibrio" que ordene el cuidado medioambiental al bienestar y la dignidad de las personas, sin asfixiar la actividad económica. Pezoa advirtió que la planificación urbana y la regulación de suelos en Chile son hoy "muy débiles, menguadas y escasas", sustentadas en leyes antiguas que requieren una modernización urgente.El Primer Café. Conduce: Cecilia Rovaretti.Encuentra más contenidos como este en Cooperativapodcast.cl

Justa deportiva deja derrama de 66 mil mdp en la CDMXEdomex lidera Semana Nacional de Salud PúblicaTemporal en Chile deja tres muertos y 500 viviendas dañadasMás información en nuestro Podcast#grc

Protección Civil alerta por lluvias intensas en tres estadosGrupo Carso compra 30% del Bloque 30 en el Golfo de MéxicoTemporal deja más de 590 mil usuarios sin luz en ChileMás información en nuestro Podcast#grc

A primera hora de este viernes, el Presidente José Antonio Kast realizó en El Diario de Cooperativa un balance del sistema frontal que afecta a gran parte del país. En medio de la emergencia, el Mandatario inició hoy un viaje por tierra con destino a las regiones de Maule y Biobío, debido a que las severas condiciones climáticas impidieron su traslado por vía aérea.El Jefe de Estado detalló que liderará reuniones operativas con los gabinetes regionales y alcaldes de las zonas más damnificadas, con el fin de evaluar la respuesta estatal frente al desborde de cauces, voladuras de techumbres e inundaciones.Frente al temor manifestado por diversos alcaldes de comunas rezagadas o previamente golpeadas por catástrofes —como los incendios forestales del verano— sobre la llegada tardía de la ayuda estatal, Kast dio garantías de que el financiamiento centralizado se encuentra completamente disponible. El Mandatario explicó que la estrategia implementada junto a los comités locales marcó un cambio administrativo radical mediante la firma —el pasado lunes— del Decreto N° 1212 del Ministerio del Interior, que declaró Emergencia Preventiva en 10 regiones.El Diario de Cooperativa. Conduce: Rodrigo Vergara.Encuentra más contenidos como este en Cooperativapodcast.cl

Louis de Grange, biministro de Obras Públicas, Transportes y Telecomunicaciones, descartó que liderar ambas carteras afecte la capacidad de respuesta del Ejecutivo para enfrentar el sistema frontal que mantiene bajo alerta a 10 regiones del país, asegurando que las funciones de estos ministerios "no son excluyentes", sino "complementarias".Consultado sobre cómo dividirá su tiempo ante las contingencias de infraestructura, conectividad y telecomunicaciones, la autoridad defendió la solidez de sus equipos de trabajo y la ventaja de coordinar de manera unificada los servicios, afirmando que "la sinergia que genera esta coordinación conjunta es más virtuosa".Respecto a la coordinación del Ejecutivo por el fenómeno meteorológico, de Grange señaló que las prioridades del despliegue de las autoridades están orientadas a resguardar la conectividad terrestre, asegurar la infraestructura hídrica y vigilar el comportamiento de los principales cursos fluviales del centro y sur de Chile.Finalmente, la autoridad recordó que uno de los flancos más complejos en contingencias climáticas radica en la continuidad de los servicios de telefonía e internet. De Grange advirtió que la estabilidad de estos sistemas depende directamente del suministro eléctrico, el cual suele verse interrumpido por caídas de árboles y postes debido a los fuertes vientos.El Diario de Cooperativa. Conducen: Verónica Franco y Rodrigo Vergara.Encuentra más episodios en Cooperativapodcast.cl

В 94-м выпуске подкаста Javaswag поговорили с Николаем Шипяковым, Java-разработчиком, который провел всю свою карьеру в финтехе и суровом энтерпрайзе. В этом эпизоде мы проследили эволюцию энтерпрайз-решений: от тяжеловесных вендорских платформ вроде IBM WebSphere и IBM BPM, где бизнес-логика «рисовалась кубиками», до современных подходов со Spring, Kotlin и Camunda. Николай поделился историей о том, как на хакатоне зародилась идея создать собственный Kotlin DSL для описания бизнес-правил, который успешно заменил неповоротливые решения и прослужил долгие годы. Мы также разобрали архитектурные кейсы, обсудили, как подружить синхронные REST-вызовы с асинхронными процессами в Camunda при помощи Kafka и Kotlin Flow. В завершение выпуска поговорили о выборе оркестраторов (Camunda 7, 8, Temporal), внутренней кухне организации ИТ-конференций и обсудили непопулярное мнение о том, почему gRPC зачастую переоценен в энтерпрайзе. Шоуноты 00:00:22 Приветствие 00:01:43 с .NET на Java и первый крупный проект для Альфа-Банка 00:04:43 Каким был энтерпрайз в десятых годах 00:09:04 Переход в Тинькофф (Т-Банк) в 2015 году: 00:16:53 Смена технологического стека: отказ от решений IBM в пользу оркестратора Camunda в связке со Spring и Kotlin 00:23:33 Что такое Camunda простыми словами: почему этот инструмент удобно использовать как надежную стейт-машину для сложных распределенных транзакций 00:27:11 Идея с хакатона: создание кастомного Kotlin DSL для удобного описания бизнес-правил (вместо визуальных редакторов для бизнеса), который стал успешным внутренним продуктом 00:33:01 Преимущества подхода “Contract/Code First”: тестирование, контроль версий в Git и трейсинг процессов, написанных на Kotlin DSL 00:47:40 Внутренняя мобильность в Т-Банке: почему разработчику полезно менять проекты и как найти команду сильных сеньоров внутри одной компании 00:53:42 Разбор архитектурного кейса: как объединить асинхронный процесс Camunda и синхронный REST-контроллер с использованием топиков Kafka и Kotlin Flow 01:01:17 Очереди в энтерпрайзе: в каких случаях стоит использовать Kafka, а когда для обработки задач подойдет PostgreSQL 01:05:46 О важности observability (наблюдаемости): история инцидента со 100% загрузкой CPU в базе данных из-за отвалившейся репликации PostgreSQL 01:09:02 Переход в стартап и проблема выбора: почему старушка Camunda 7 до сих пор актуальнее, чем Temporal или платная Camunda 8 с закрытой архитектурой 01:20:18 Организация собственной технической Java-конференции от компании: сбор программы, уникальные доклады и почему платные билеты улучшают отношение аудитории 01:32:18 Непопулярные мнения от гостя: почему группа Ария без Кипелова звучит отлично, и почему технология gRPC часто применяется в энтерпрайзе не по делу 01:39:23 О важности софт-скиллов

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

Other accoutrements worn by some punks included: BDSM fashions, fishnet stockings (sometimes ripped), spike bands and other studded or spiked jewelry, safety pins (in clothes and as body piercings), silver bracelets and heavy eyeliner worn by both men and women.Archie Comics' Sonic The Hedgehog #5200:00 Intro04:10 The Discovery Zone Part 117:29 The Discovery Zone Part 224:37 The Discovery Zone Part 335:29 First Contact (Princess Sally)49:38 Sonicgrams52:00 Outro-----Gotta Talk Fast is an oral review of Archie Comics' Sonic the Hedgehog. Way past cool.LINKS: https://gottatalkfast.com/

In this episode, we're joined by Cornelia Davis, Developer Advocate at Temporal and a longtime software architect who has spent decades helping shape modern cloud-native systems.We explore how programming has evolved from assembly language to cloud-native architectures, and why AI is forcing us to rethink software development once again. Cornelia argues that natural language is becoming a new programming abstraction, while durable execution may be the missing layer that makes AI agents reliable in production.The conversation dives into probabilistic software, long-running AI agents, MCP tasks, human-in-the-loop workflows, durable timers, distributed systems, and why developers may no longer need to think about infrastructure the way they once did.Cornelia Davis: https://www.linkedin.com/in/corneliadavisDemetrios: https://www.linkedin.com/in/dpbrinkmTemporal: https://temporal.ioTimestamps[00:00] AI Programming Abstractions[00:52] Abstraction Evolution in Programming[04:05] Text to SQL Evolution[10:08] Compensations for Natural Language[12:13] Durable MCP in AI[18:34] Streaming Session Explanation[21:31] Batch Processes with Tasks[29:29] Complexity Relocation in Systems[33:10] Complexity Relocation in Dev[36:36] Programming Model Shifts

World-leading behaviour change expert Katy Milkman details how to change your habits.  --- Become an FSB member: https://get.fsb.org.uk/nudge/ Unlock the Nudge Vaults: https://www.nudgepodcast.com/vaults Katy's book: https://amzn.to/3RF63xA  Katy's podcast: https://www.schwab.com/learn/choiceology  Katy's newsletter: https://www.katymilkman.com/newsletter-milkman-delivers  Subscribe to my newsletter: https://www.nudgepodcast.com/mailing-list  Connect on LinkedIn: https://www.linkedin.com/in/phill-agnew/  --- Today's sources: Beshears, J.Beshears, J., Dai, H., Milkman, K. L., & Benartzi, S. (2021). Using fresh starts to nudge increased retirement savings. Organizational Behavior and Human Decision Processes, 167, 72–87. Dai, H., Milkman, K. L., & Riis, J. (2014). The fresh start effect: Temporal landmarks motivate aspirational behavior. Management Science, 60(10), 2563–2582. Eskreis-Winkler, L., Fishbach, A., & Duckworth, A. L. (2018). Dear Abby: Should I give advice or receive it? Psychological Science, 29(11), 1797–1806. Eskreis-Winkler, L., Milkman, K. L., Gromet, D. M., & Duckworth, A. L. (2019). A large-scale field experiment shows giving advice improves academic outcomes for the advisor. Proceedings of the National Academy of Sciences, 116(30), 14808–14810. Schroeder, S. A. (2007). We can do better — Improving the health of the American people. New England Journal of Medicine, 357(12), 1221–1228.

Shakings Coming (1) (audio) David Eells – 6-24-26 IT WILL SHAKE THE WORLD! Lynne Johnson 5-27-26 IAM, King Yeshuya wants you, My people to know that all will erupt soon in Iran. President Trump is playing a waiting game with the radicalized left in the IRGC for there are many factions vying for control. Trump is ensuring that when the United States military strikes Iran, the United States will have very few casualties. Trump doesn't want American casualties, therefore the United States is intending to use all intelligence being fathered to ensure few American casualties. When the U.S. Military strikes, there will be no doubt that the IRGC, in its radical form, is no longer in existence. Once assured of the success of this campaign, Trump will have the military pull back to the general areas away from Iran. Very shortly after the United States military pulls back from Iran, then Israel will strike. First, Damascus, Syria (a weapon depot) destroying it. Next, Israel will move against Iran's nuclear facilities along with their weapon depots. These strikes will effectively end Iran's nuclear program. Once this is concluded, then very shortly look for the First Event of MY Judgments (again these events of Mine, King Yeshuya, are not those of Tribulation, which are far worse, for a much longer time frame), the California earthquake which will shake the world as this earthquake is massive in size and in effect. I AM, King Yeshuya tells you this again so that you MY children, MY Believers are warned to plan, to prepare for what is soon to occur. IAM always warns ahead through MY prophets and messengers. Listen to My Words, heed My Warnings for they are to help protect you and your families. Continue MY children to come to ME in prayer, stay in MY Word, stay focused, stay calm. Come directly to ME, King Yeshuya with your queries. I AM will gladly answer you. IAM loves you MY children. Your King Yeshuya, the King of Kings and Lord of Lords, the Alpha and Omega, the Beginning and the End, the Most High, Commander of heaven's hosts and armies, the Lion of Judah, the Prince of Peace. Scriptures: Psalm 20:7 NKJV “Some trust in chariots and some in horses, but we will remember and trust in the name of the Lord our God.” Isaiah 43:2 NKJV “When you pass through the waters, I will be with you; and through the rivers, they will not overwhelm you. When you walk through fire, you will not be scorched, nor will the flame burn you.” Ezekiel 7:7 NKJV “Doom has come to you, you who dwell in the land; the time has come, a day of trouble is near, and not of rejoicing in the mountains.” Isaiah 17:1 NIV “A prophecy against Damascus: “See, Damascus will no longer be a city but will become a heap of ruins.” Isaiah 13:9 NKJV “Behold, the day of the Lord comes, cruel with both wrath and fierce anger, to lay the land desolate; and He will destroy its sinners from it.” Isaiah 13:6 NKJV “Wait, for the day of the Lord is at hand! It will come as destruction from the Almighty.” John 14:29 NKJV “And now I told you before it comes, that when it does come to pass, you may believe.” Lamentations 3:25 NKJV “The Lord is good to those who wait for Him, to the soul who seeks Him.”   FAMINE WILL EXTEND WORLDWIDE Lynne Johnson – 5-9-26 I AM, King Yeshuya, would like MY people to know that it is soon for the “Iranian Conflict” to conclude. It will end as IAM has stated; the United States will deploy missiles, which will effectively end the IRGC Regime's control over Iran. Then the United States will pull back their military, leaving destroyers, aircraft carriers, and such in the area. Shortly after the United States military is pulled back, Israel will strike Damascus, the other weapon depots in Syria, then strike Iran's nuclear facilities and weapon depots. Israel will present the truth with proof that Iran fully intended to finish the building of nuclear bombs to destroy Israel. There will be the usual outcry, but no one will “lift a hand” against Israel, for all of the surrounding Arab nations know the truth. They also know that they were not safe from Iran's nuclear attacks. Again MY children, this is your marker to know that you only have a short time to finish getting your food, to prepare for what is coming, MY First Event – Judgment upon California. Do not put off procuring your food, your other necessities. Use cash as much as possible and by going to different stores. Do not discuss storing food with ANY OTHERS as IAM has clearly stated unless you have spoken directly with ME, King Yeshuya, the King of Kings and Lord of Lords to find out who you are able to trust. Ensure that you get your answer from ME, BEFORE you talk with others. If you choose not to listen to ME here, you and your family will suffer harm. People will become desperate quickly for food – any food that they are able to find. They do not wish to share, and they will harm others to get food. Those who have not done so recently or at all, are to read Jeremiah – ALL OF IT! You will see what hunger does to people. There will be few people who you will be able to trust now, so be discreet and come to ME, King Yeshuya to find out who you can SAFELY SHARE YOUR FOOD WITH. You must also accept MY answer as final. IAM alone sees the hearts, minds, thoughts and intentions of ALL people! You do not. You must also understand that the famine will extend worldwide. It will not be located only in specific cities, areas, or countries. With the famine, there will be deaths and then pestilences due to these deaths. IAM will give you more specific detail on this soon. FOR NOW YOUR JOB IS TO PREPARE. COME DIRECTLY TO ME WITH YOUR QUESTIONS AS I AM WILL GLADLY ANSWER YOU. MY BELOVED CHILDREN, STAY IN PRAYER TO ME, STAY IN MY WORD, STAY FOCUSED, STAY CALM. Your King Yeshuya, the King of Kings and Lord of Lords, the Most High, the Alpha and Omega, the Beginning and the End, the Lion of Judah, the Prince of Peace Scriptures: Isaiah 17:1 NKJV “The burden against Damascus. “Behold, Damascus will cease from being a city, and it will be a ruinous heap.” Luke 21:11 NKJV “And there will be great earthquakes in various places, and famines and pestilences; and there will be fearful sights and great signs from heaven.” Psalm 9:8 NKJV “He shall judge the world in righteousness, and He shall administer judgment for the people in uprightness.” Ecclesiastes 8:6 NKJV “Because for every matter there is a time and judgment, though the misery of man increases greatly.” Psalm 76:8 NKJV “You caused judgment to be heard from heaven; the earth feared and was still.” Deuteronomy 8:6 NKJV “Observe the commands of the LORD your God, walking in obedience to Him and revering Him.” Proverbs 15:11 NKJV “Hell and Destruction are before the Lord; so how much more the hearts of the sons of men.” Psalm 112:5 NKJV “A good man deals graciously and lends; he will guide his affairs with discretion.” Deuteronomy 32:24 NKJV “They shall be wasted with hunger, devoured by pestilence and bitter destruction; I will also send against them the teeth of beasts, with the poison of serpents of the dust.” Romans 12:12 NKJV “Rejoicing in hope, patient in tribulation, continuing steadfastly in prayer,”   GOLDEN DOME MR POOL X - *GOLDEN DOME went fully operational on June 14, 2026.** Not announced. Not disclosed. ACTIVATED. Posted By: Lymerick 6-23-26 www.rumormill.news/269653   Mr. Pool @MrPool_QQ

E aí, tudo bem por aqui?Profa Ju chegando. Sejam todos bem-vindos, semanacomeçando e mais um episódio do nosso podcast Falar Português Brasileiro para você aprender mais um pouquinho de português, o podcast que te acompanha enquanto você caminha, lava a louça, dirige, passeia com o cachorro, organiza a casa ou simplesmente tira alguns minutos do dia para estudar português.Vamos continuar falando sobre os verbos? Contudo, diferente dos episódios anteriores, vou contar uma história. Será uma história diferente. Uma história sobre o encontro entre os “eus”. O “eu” do futuro com o “eu” de agora. Na verdade, não será bem “eu”, é um outro “eu”. O eu do futuro.Lembram da Maria, a Maria já passou por aqui em uma das nossas narrativas. No Brasil somos todas Marias. Vamos lá?Eu quero que você imagine o futuro. Não aquele futuro dos filmes norteamericanos cheios de carros voadores e cidades metálicas saindo fumaça por todas as esquinas com bueiros.

Georg Northoff is Canada Research Chair in Mind, Brain, Imaging, and Neuroethics at the University of Ottawa's Institute of Mental Health Research, a practising psychiatrist, neuroscientist, and philosopher, and one of the founders of neurophilosophy. Over two decades his work has reframed the brain's resting spontaneous activity — the Default Mode Network — as the primary architect of consciousness and selfhood.He is the author of The Spontaneous Brain, alongside more accessible introductions including NeuroWaves: Brain, Time, and Consciousness (2023) and NeuroPsychoAnalysis (2023).________________In this conversation, I sit down with Georg to explore his spatial-temporal neuroscience — a framework that replaces the mind-body problem with the world-brain relationship. We begin with AI consciousness, move into the Default Mode Network and why depression is a brain running too slowly, his non-dual awareness study with meditators, his critique of Heidegger as still anthropocentric, and Whitehead's process ontology. A conversation that starts with ChatGPT and ends near the edge of what it means to exist.________________

Jesus' followers are “peculiar” people. Following the path that He has blazed for you means your walk will be “out of step” with a sinful world. Jesus shakes you out of the customary ways of thinking, speaking, and “doing,” inviting us to follow Him. A journey that, unsurprisingly, goes through valleys of rejection and suffering, after all “a student is not above his teacher….it's enough for the student to be like his teacher.” Temporal troubles are certain, but so are eternal blessings for you who are in the care of a Loving Father to whose eye is on the sparrow and to whom “even the hairs of your head are all numbered.”

Brugada encabezó la entrega de mejoras del Vaso ReguladorEl Salado  Irán se retiró de las negociaciones que mantenía con EE. UUEn torneo mundialista Paraguay presume su herencia guaraní  Más información en nuestro podcast#grc

What if one of the most important health crises affecting men today wasn't being caused by aging, but by the environment we live in? In this eye-opening solo episode, Darin Olien investigates the alarming decline in testosterone levels, fertility, and reproductive health among men worldwide. Drawing on decades of research, epidemiological studies, environmental science, endocrinology, and public health data, Darin examines the growing evidence connecting endocrine-disrupting chemicals, microplastics, sleep deprivation, chronic stress, poor lifestyle habits, and environmental toxins to declining testosterone levels across generations. From BPA, phthalates, atrazine, PFAS, and microplastics to sleep quality, circadian rhythms, cholesterol metabolism, cortisol regulation, and natural testosterone-supporting strategies, this episode explores what may be one of the most underreported public health issues of our time—and what men can do to take control of their health today.     What You'll Learn Why testosterone levels have been declining for decades The startling research on global sperm count decline How endocrine-disrupting chemicals interfere with hormone production Why BPA and phthalates may disrupt testosterone synthesis The role of atrazine, PFAS, and environmental toxins How chronic stress diverts resources away from testosterone production Why sleep may be the most important testosterone intervention The connection between cholesterol and hormone production How microplastics are being found throughout the human body The surprising relationship between statins and testosterone levels Natural lifestyle strategies that support healthy hormone production Practical steps to reduce environmental exposure and improve health     Chapters 00:00:00 – Welcome to SuperLife 00:00:33 – Sponsor: Fatty15 and cellular health 00:04:17 – The testosterone collapse explained 00:04:51 – Testosterone levels have been declining for decades 00:06:03 – Global sperm count decline and accelerating trends 00:07:02 – Why treating symptoms misses the root cause 00:07:27 – The hidden public health crisis 00:08:03 – Why low testosterone isn't just about aging 00:09:12 – Why hormone health affects longevity 00:09:53 – Low testosterone and increased mortality risk 00:10:35 – Testosterone's role in metabolism and cardiovascular health 00:11:27 – Endocrine-disrupting chemicals and hormone disruption 00:12:44 – BPA and its effects on testosterone production 00:13:59 – Phthalates and their impact on hormone pathways 00:16:00 – Glyphosate, atrazine, and pesticide exposure 00:17:07 – PFAS and reproductive health concerns 00:17:55 – Environmental toxins and population-wide effects 00:18:11 – Sponsor: Shakeology 00:20:02 – Cholesterol and hormone production 00:20:53 – Chronic stress and cortisol dominance 00:21:45 – Actionable solutions begin 00:21:56 – Why sleep is essential for testosterone production 00:23:07 – How sleep deprivation rapidly lowers testosterone 00:23:21 – Light pollution and circadian disruption 00:23:41 – Foods and nutrients needed for hormone health 00:24:23 – Microplastics and testicular tissue 00:24:53 – Statins and unintended hormonal consequences 00:25:39 – A practical testosterone sovereignty protocol 00:25:48 – Water filtration and reducing toxic exposure 00:26:13 – Eliminating plastics and fragrance chemicals 00:26:35 – Why organic food matters 00:26:45 – Sunlight and vitamin D 00:27:05 – Magnesium, omega-3s, and iodine 00:27:26 – Pine pollen and natural androgen support 00:28:01 – Tongkat Ali and ashwagandha 00:28:48 – Strength training and lifestyle interventions 00:29:10 – Habits that naturally support testosterone 00:29:27 – Darin's approach to healthy aging 00:29:37 – Plants, herbs, and common sense 00:29:51 – Reclaiming your health and sovereignty 00:30:00 – Final thoughts and closing message     Thank You to Our Sponsors Fatty15: Get an additional 15% off their 90-day subscription Starter Kit by going to fatty15.com/DARIN and using code DARIN at checkout. Shakeology: Get 15% off with code DARINO1BODI at Shakeology.com.     Join the SuperLife Patreon: This is where Darin now shares the deeper work: - weekly voice notes - ingredient trackers - wellness challenges - extended conversations - community accountability - sovereignty practices Join now for only $7.49/month at https://patreon.com/darinolien     Find More from Darin Olien: Website: darinolien.com Instagram: @darinolien Book: Fatal Conveniences Platform & Products: superlife.com New Show: Roadmap to Happiness     Key Takeaway "The testosterone crisis may be about far more than aging. It may be a reflection of the modern environment itself—one increasingly saturated with endocrine-disrupting chemicals, chronic stress, poor sleep, circadian disruption, and toxic exposures. While many of these forces feel outside our control, the encouraging reality is that many of the most powerful interventions remain accessible: improving sleep, reducing toxic load, eating whole foods, getting sunlight, managing stress, exercising regularly, and reclaiming responsibility for our health. The goal isn't fear. The goal is awareness—and action."     Bibliography/Sources: The Decline — Primary Research Levine, H., Jørgensen, N., Martino-Andrade, A., et al. (2022). Temporal trends in sperm count: A systematic review and meta-regression analysis of samples collected globally in the 20th and 21st centuries. Human Reproduction Update, 29(2), 157–176. https://doi.org/10.1093/humupd/dmac035 Lokeshwar, S. D., Patel, P., Fantus, R. J., et al. (2021). Decline in testosterone levels in men aged 15–40: Results from the National Health and Nutrition Examination Survey (NHANES), 1999–2016. World Journal of Urology, 39(2), 447–452. https://doi.org/10.1007/s00345-020-03227-1 Spital Clinic. (2026, March). Declining testosterone levels by generation. https://www.spitalclinic.com Travison, T. G., Araujo, A. B., O'Donnell, A. B., Kupelian, V., & McKinlay, J. B. (2007). A population-level decline in serum testosterone levels in American men. The Journal of Clinical Endocrinology & Metabolism, 92(1), 196–202. https://doi.org/10.1210/jc.2006-1375 Low Testosterone — Mortality & Disease Risk Muraleedharan, V., Marsh, H., Kapoor, D., Channer, K. S., & Jones, T. H. (2013). Testosterone deficiency is associated with increased risk of mortality and testosterone replacement improves survival in men with type 2 diabetes. European Journal of Endocrinology, 169(6), 725–733. https://doi.org/10.1530/EJE-13-0321 Shores, M. M., et al. (2006). Low testosterone associated with increased all-cause and cardiovascular mortality. Archives of Internal Medicine, 166(15), 1660–1665. https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/410754 Yeap, B. B., Marriott, R. J., Dwivedi, G., et al. (2024). Associations of testosterone and related hormones with all-cause and cardiovascular mortality and incident cardiovascular disease in men. Annals of Internal Medicine. https://doi.org/10.7326/M23-2781 Endocrine Disrupting Chemicals Associations between endocrine-disrupting chemical exposure and fertility outcomes: A decade of human epidemiological evidence. (2024). PubMed Central (PMC12299029). https://pmc.ncbi.nlm.nih.gov/articles/PMC12299029/ Hayes, T. B., Haston, K., Tsui, M., et al. (2002). Herbicides: Feminization of male frogs in the wild. Nature, 419, 895–896. https://doi.org/10.1038/419895a Mechanisms of testicular disruption from exposure to BPA and phthalates. (2020). Journal of Clinical Medicine, 9(2), 471. https://pmc.ncbi.nlm.nih.gov/articles/PMC7074154/ Meeker, J. D., Calafat, A. M., & Hauser, R. (2014). Urinary phthalate metabolites and their biotransformation products: Predictors and temporal variability among men and women. Journal of Exposure Science & Environmental Epidemiology. https://www.sciencedaily.com/releases/2014/08/140814124330.htm Zhao, Q., et al. (2023). Male reproductive toxicity of microplastics: Head and tail of the sperm. Science of the Total Environment, 872, 162181. https://doi.org/10.1016/j.scitotenv.2023.162181 Zhong, B., et al. (2024). Mixed EDC exposure associated with reductions in testosterone and free androgen index. Scientific Reports. https://doi.org/10.1038/s41598-024-76972-z Cortisol, Stress & the HPG Axis Bielohuby, M., et al. (2012). Swiss military cadets prolonged stress study. Psychoneuroendocrinology. Preprints.org. (2025). Sleep deprivation: A modifiable cause. https://doi.org/10.20944/preprints202505.0580.v1 SiPhox Health. (n.d.). Summary of Journal of Clinical Endocrinology & Metabolism data. https://www.siphoxhealth.com Viau, V. (2002). Functional cross-talk between the hypothalamic-pituitary-gonadal and -adrenal axes. Journal of Neuroendocrinology, 14(6), 506–513. https://doi.org/10.1046/j.1365-2826.2002.00798.x Sleep & Testosterone Leproult, R., & Van Cauter, E. (2011). Effect of 1 week of sleep restriction on testosterone levels in young healthy men. JAMA, 305(21), 2173–2174. https://jamanetwork.com/journals/jama/fullarticle/1029127 Reiter, R. J., et al. (2021). Melatonin and male reproductive health: Relationship to oxidative stress, mitochondrial function, and Leydig cell protection. Endocrine. Tan, D. X., Hardeland, R., Manchester, L. C., et al. (2023). Melatonin as a pleiotropic antioxidant hormone. Journal of Pineal Research. Nutrition — Zinc, Vitamin D, Cholesterol Corona, G., et al. (2010). Statin therapy and testosterone levels in men: A systematic review. The Journal of Sexual Medicine. Daniell, H. W. (2002). Hypogonadism in men consuming sustained-action oral opioids. The Journal of Pain, 3(5), 377–384. https://doi.org/10.1054/jpai.2002.126790 Pilz, S., Frisch, S., Koertke, H., et al. (2011). Effect of vitamin D supplementation on testosterone levels in men. Hormone and Metabolic Research, 43(3), 223–225. https://doi.org/10.1055/s-0030-1269854 Prasad, A. S., Mantzoros, C. S., Beck, F. W., Hess, J. W., & Brewer, G. J. (1996). Zinc status and serum testosterone levels of healthy adults. Nutrition, 12(5), 344–348. https://doi.org/10.1016/S0899-9007(96)80058-X Natural Testosterone Support — Botanical Evidence Pine pollen impacts testosterone-related symptoms in men. (2024). ACMCR Case Reports, 14(5), 1–9. Chinnappan, S. M., George, A., et al. (2021). Effect of Eurycoma longifolia standardised extract Physta on testosterone levels in ageing males: A randomised, double-blind, placebo-controlled multicentre study. Food & Nutrition Research, 65. https://doi.org/10.29219/fnr.v65.5647 Lazarev, A., & Bezuglov, E. (2021). Testosterone boosters intake in athletes: Current evidence and further directions. Endocrines, 2(2), 109–120. https://doi.org/10.3390/endocrines2020011 Leisegang, K., et al. (2022). Eurycoma longifolia (Tongkat Ali) improves serum total testosterone in men. Food & Nutrition Research. https://pubmed.ncbi.nlm.nih.gov/36013514/ Leitão, A. E., et al. (2021). 6-month double-blind RCT: Eurycoma longifolia 200mg + concurrent training. Maturitas. https://doi.org/10.1016/j.maturitas.2020.10.005 Lopresti, A. L., Smith, S. J., et al. (2019). An investigation into the stress-relieving and pharmacological actions of an ashwagandha extract. Medicine, 98(37), e17186. https://doi.org/10.1097/MD.0000000000017186 Pandit, S., Biswas, S., Jana, U., De, R. K., Mukhopadhyay, S. C., & Biswas, T. K. (2016). Clinical evaluation of purified shilajit on testosterone levels in healthy volunteers. Andrologia, 48(5), 570–575. https://doi.org/10.1111/and.12482 Saden-Krehula, M., Tajic, M., & Kolbah, D. (1971). Testosterone, epitestosterone and androstenedione in the pollen of Scotch pine Pinus sylvestris L. Experientia, 27(1), 108–109. https://doi.org/10.1007/BF02137731 Wankhede, S., Langade, D., Joshi, K., et al. (2015). Examining the effect of Withania somnifera supplementation on muscle strength and recovery: A randomized controlled trial. Journal of the International Society of Sports Nutrition, 12, 43. https://doi.org/10.1186/s12970-015-0104-9

The Carrington Event was a massive geomagnetic storm that happened in 1859. It led to expanded understanding of solar phenomena. Research: “Great Aurora of 1859. Art. XLII – The Great Auroral Exhibition of August 28th to September 4th, 1859.” American Journal of Science. Ser. 2. Vol. 28. July-November 1859. Cardenas, Freddy Moreno et al. “The Grand Aurorae Borealis Seen in Colombia in 1859.” Preprint submitted to Advances in Space Research. August 21, 2015. Cliver, E.W. “The 1859 space weather event: Then and now.” Advances in Space Research. 38 (2006) 119-129. Cliver, E.W. and L. Svalgaard. “The 1859 Solar-Terrestrial Disturbance and the Current Limits of Extreme Space Weather Activity.” Solar Physics. (2004) 224: 407–422. Cliver, Edward W. and William F. Dietrich. “The 1859 space weather event revisited: limits of extreme activity.” J. Space Weather Space Clim. 3 (2013) A31 DOI:10.1051/swsc/2013053 Dobrijevic, Daisy and Andrew May. “The Carrington Event: History's greatest solar storm.” Space.com. 5/20/2022. https://www.space.com/the-carrington-event Giegengack, Robert. “The Carrington Coronal Mass Ejection of 1859.” Proceedings of the American Philosophical Society , DECEMBER 2015, Vol. 159, No. 4. Via JSTOR.https://www.jstor.org/stable/26159195 Green, James L, and Scott Boardsen. “Duration and extent of the great auroral storm of 1859.” Advances in space research : the official journal of the Committee on Space Research (COSPAR) vol. 38,2 (2006): 130-135. doi:10.1016/j.asr.2005.08.054 Green, James L. et al. “Eyewitness Reports of the Great Auroral Storm of 1859.” Submitted to Advances in Space Research. NASA Technical Reports Server (NTRS) 20050210157. 8/5/2005. Haeberle, Tom. “The Carrington Affair!” Amateur Astronomers Association Eyepiece. 9/1/2018. https://aaa.org/2018/09/01/the-carrington-affair/ Hayakawa, Hisashi et al. “Temporal and Spatial Evolutions of a Large Sunspot Group and Great Auroral Storms Around the Carrington Event in 1859.” Space Weather. 8/29/2019. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019SW002269 Hodgson, R. “On a Curious Appearance Seen in the Sun.” Monthly notices of the Royal Astronomical Society vol. 19-20 (1858-1860). https://academic.oup.com/mnras/article/20/1/15/983497 Hodžić, Jasna. “The Carrington Event of 1859 Disrupted Telegraph Lines. A ‘Miyake Event’ Would Be Far Worse.” JSTOR Daily. 9/7/2023. https://daily.jstor.org/the-carrington-event-of-1859-disrupted-telegraph-lines/ Howard, R.A. (2006). A Historical Perspective on Coronal Mass Ejections. In Solar Eruptions and Energetic Particles (eds N. Gopalswamy, R. Mewaldt and J. Torsti). https://doi.org/10.1029/165GM03 Josefowicz, Diane. “The British Magnetic Scheme (1839-1851): People and Institutions.” Victorian Web. https://victorianweb.org/science/geomagnetism/magneticcrusade.html Kaminski, Isabella. “'The fate of nations and the fall of kingdoms': History's epic theories of what causes aurora.” BBC. 11/16/2025. https://www.bbc.com/future/article/20251114-historys-epic-theories-of-what-causes-aurora Kimball, D.S. “A Study of the Aurora of 1859.” Scientific Report No. 6. NSF Grant No. Y/22.6/327. April 1960. Klein, Christopher. “A Perfect Solar Superstorm: The 1859 Carrington Event.” History. 1/29/2025. https://www.history.com/articles/a-perfect-solar-superstorm-the-1859-carrington-event Marinus Anthony van der Sluijs, Hisashi Hayakawa. “A candidate auroral report in the Bamboo Annals, indicating a possible extreme space weather event in the early 10th century BCE.” Advances in Space Research. Volume 72, Issue 12. 2023. https://doi.org/10.1016/j.asr.2022.01.01 Mills, Virginia. “A message from Alexander von Humboldt.” The Royal Society. 9/23/2019. https://royalsociety.org/blog/2019/09/a-message-from-alexander-von-humboldt/ Muller, C. “The Carrington solar flares of 1859: consequences on life.” Origins of life and evolution of the biosphere : the journal of the International Society for the Study of the Origin of Life vol. 44,3 (2014): 185-95. doi:10.1007/s11084-014-9368-3 Phillips, Tony. “A Warning from History: The Carrington Event Was Not Unique.” Space Weather Archive. 9/1/2020. https://spaceweatherarchive.com/2020/08/30/a-warning-from-history-the-carrington-event-was-not-unique/ Phillips, Tony. “Near Miss: The Solar Superstorm of July 2012.” NASA. 12/22/2014. https://science.nasa.gov/science-research/planetary-science/23jul_superstorm/ C. Carrington, Description of a Singular Appearance seen in the Sun on September 1, 1859, Monthly Notices of the Royal Astronomical Society, Volume 20, Issue 1, November 1859, Pages 13–15, https://doi.org/10.1093/mnras/20.1.13 Starmans, Barbara J. “Carrington Solar Flare of 1859.” The Social Historian. 11/27/2016. https://www.thesocialhistorian.com/carrington-solar-flare-of-1859/ Thompson, D. (2009) The Carrington Event and the Electric Telegraph in Victoria in Museums Victoria Collections https://collections.museumsvictoria.com.au/articles/2880 See omnystudio.com/listener for privacy information.