Podcasts about Ona

OPEN HEAVENSMATALA LE LAGI MO LE ASO GAFUA 20  IULAI 2026(tusia e Pastor EA Adeboye) Manatu Autu: O ki i le saolotoga 1 (The keys to freedom 1) Tauloto Tusi Paia: Salamo 72:12 “Auā e lavea‘i e ia o lē mativa i lona ‘alaga mai; ‘atoa ma lē ‘ua puapuagātia ma lē ‘ua leai sona fesoasoani.”Faitauga - Tusi Paia: Mareko 10:46-52E lē finagalo le Atua e iai se tagata i lalo o avega mamafa a satani. O le mafuaaga lea na fetalai ai Iesu, “Ia ‘outou ō mai ‘iā te a‘u, o ‘outou uma o ē tigāina ma mafatia i avega, o a‘u fo‘i e mālōlō ai ‘outou.” (Mataio‬ ‭11‬:‭28‬). E sili atu le mafai e le Atua ona gagau le amo o avega a le fili i soo se tagata (Isaia 10:27) peitai e tatau pea i tagata ona tautino e manaomia lona faasaolotoina. I tausaga e tele ua leva, na aumai e se tamaloa lana avā ia te au ma faapea, ‘Tamā, fesoasoani mai ia te au. O la'u avā o le taulaitu'. Na ou fesili i lana avā pe moni ae faafiti. Na ou fai iai afai o ia o se taulaitu, e mafai ona ou tatalo mo ia ona faasaolotoina lea. Peitai na finau pea e lē o ia o se taulaitu ma e lē manao e faia se galuega mo le faasa'olotoina. Ona ou tatalo lea e faapea, ‘afai e lē o oe o se taulaitu o le a e manuia pea, peitai afai o oe o se taulaitu, ou te saisaia soo se temoni o galue i totonu ia te oe, i le suafa o Iesu'. E tolu masinoa mulimuli ane, ua toe aumaia o ia ia te a'u ua fufula atoa le tino, ua faaluaina le tele o lona tino. O le temoni na ou saisaitia ua leaga i totonu o ia.O le laasaga muamua i soo se tagata o i lalo o avega a le tiapolo o le tautino lea e lea tagata o loo ia amoina se avega ma e fia saoloto. Seiloga lava e tautino e lea tagata, e lē mafai ona faasaolotoina. E faapena foi le tagata ua malie lava e tauave le ma'i, lagona nofo toatasi, pa, faanoanoaga poo le tigā, o le a faaauau ai pea ona nofo i lalo o avega a satani. I se taimi e lei leva atu, sa tale lava se tamaloa ma ua aumaia ia te a'u mo tatalo. Sa ou manatu ou te le fesili iai ae na o le tatalo, peitai ua ou faia ma masani le faia o fesili muamua. O lea na ou fesili iai, ‘lau susuga, o le a se mea ou te fesoasoani ai ia te oe?' E ui o loo manino e ma'i, ae na ou fia iloa poo le a le mea e manao iai, e pei ona fesili Iesu ia Patimaio i le faitauga mai le Tusi Paia o le asō. Na ou ofo ina ua fai mai ou te tatalo ia alu ese lemu lona tale. Le au pele e, o e i lalo o avega a satani i soo se vaega o lou olaga? Tautino e te manaomia le fesoasoani a le Atua ma alaga atu ia te ia ia gagau eseina vave ma ia atoatoa. E vave mai o ia e fesoasoani ia te oe i le suafa matautia o Iesu. O le laasaga muamua i le maua o le saolotoga mai avega a le tiapolo, o le tautino e te manaomia le fesoasoani, i le suafa o Iesu, Amene. 

OPEN HEAVENSMATALA LE LAGI MO LE ASO SA 19  IULAI 2026(tusia e Pastor EA Adeboye) Manatu Autu: Faasaolotoga mai avega o galuega ma aoaoga (Deliverance from career and academic burdens) Tauloto Tusi Paia: Faataoto  4:18“A o le ala o ē amiotonu, e tusa ia ma le malamalama o le ao, o lo‘o tupu pea lona malamalama e o‘o i le totonu o le la.”Faitauga - Tusi Paia: Luka 5:1-7I le faitauga mai le Tusi Paia o le asō, sa fagota Peteru i le po atoa ae leai se i'a na maua. E manatu sa fememeai, ma ou te malamalama lelei i le tulaga sa iai aua ou te fiafia e fagota. E masani ona ou alu e fagota e malolo ai mai galuega, e iai taimi e na o le lima minute ae maua le i'a. Ae iai foi taimi e atoa le itula e leai ma se i'a e maua. Sa leai se aoga o le tautiga o Peteru i lea po, e le faapea sa lē galue malosi, ae ona ua lē ō gatasi mea uma ma ia. Ao ou faiaoga i le Iunivesite, sa iai se faasalalauga o se avanoa faigaluega i se kamupani ma sa talosaga iai se polofesa. Na valaaulia mai mo se faatalatalanoaga, ma ina ua taunuu atu i le nofoaga e faia ai, ua ia iloa o le taitaifono o le komiti e faia le faatalatalanoaga o se alii talavou na aoga ia te ia e lei leva ona faauu. Ina ua iloa atu e le polofesa o ia, na faamalulu iai e sesē le potu o loo iai. Peitai na faailoa iai e le alii talavou o loo sa'o lelei le potu. Na lagona le maasiasi tele o le polofesa ona e lē o le tulaga lea e tatau ona iai i lona olaga galue. O nisi tagata e lē manuia i latou galuega ma aoaoga ona e lē o le paie, ae ona o loo latou tauaveina ni avega mamafa o le tetee mai le tiapolo e taofia i latou mai le ausia o tulaga manuia. O ia tagata e lē taitai manuia tusa poo le a le taumafai. Peitai a afio mai iai Iesu, Lē tauave avega, e liliuina o latou tulaga mo le lelei. E iai se alii talavou na sau ia te a'u mo tatalo. Fai mai e tetee a lona pule ia te ia ona o lona faatuatuaga kerisiano. Na oo ina fai mai lona pule, e lē taitai siitia lona tulaga pe afai e pule pea o ia. Ona o lea tulaga, na tumau pea le tulaga e aunoa ma se siitaga i le ofisa. Na ma tatalo ma folafola i le suafa o Iesu o soo se mauga o loo polokaina lona ala mo siitaga, ia liaieseina. E lei leva, ae faasee atu lona pule i seisi lala, ona maua lea o le siitaga a lea alii talavou. E lei leva se taimi ae toe faafoi mai lana pule i le lala lea e iai le alii talavou, e oo ane i le taimi lea, ua tutusa la tulaga ma lana pule sa iai muamua. E na o le tasi le folafolaga na faia i le suafa o Lē tauave avega, na liliuina lona tulaga mo le lelei. Le au pele e, o e tumau pea i le tulaga e tasi i lau galuega poo lau aoga? Ou te folafola atu i le asō o soo se avega o le tetee mai i le tupu ma siitia o lau galuega ma le aoaoga, ia tafiesea i le suafa o Iesu. TataloLe Alii e, faamolemole faasaoloto ia te a'u mai soo se mea o tetee mai i lo'u olaga, i le suafa o Iesu, Amene. 

OPEN HEAVENSMATALA LE LAGI MO LE ASO TOONAI 18  IULAI 2026(tusia e Pastor EA Adeboye) Manatu Autu: Faasaolotoga mai avega i le agaga (Deliverance from spiritual burdens) Tauloto Tusi Paia: Ioane 8:36 “O lenei pe ā tu‘u sa‘oloto ‘outou e le Atali‘i, ‘ona sa‘oloto fa‘amaoni ai lea o ‘outou.”Faitauga - Tusi Paia: Mareko 1:23-27A'o soifua si o'u tinā, sa ou alu i se tasi aso e asi, ma sa ave ifo ai se tamā ia te a'u faapea ou te tatalo ai. Na fai mai le tamā ia te a'u na te manaomia le fesoasoani peita'i ou te vaai atu ia te ia, e leai ma se mea o faaletonu. Ina ua ia iloa mai ou foliga le mautonu, na faapea mai ia te a'u, “Silasila mai,” sa tago o ia i totonu o ona lauulu ma aumai I fafo se mogamoga (tulou). Na ia faapea mai, “ E lē o a'u o se taulaitu. Ua na ona o'u fa'aali atu o le ituaiga malaia i le agaga o ia te a'u. Sa ia toe tu'u ona tamatama'ilima i totonu o ona lauulu ma toe aumai i fafo se isi ituaiga iniseti. Ona ia fai mai lea ou te faalogo toto'a a'o ia tuu mai lona ogalima latalata i lo'u taliga, ma ou faalogoina ai le leo o se uila afi o fa'aolaola. Ina ua maea nei mea uma, sa ou fai i le tamā lenei e tu'u lona ola iā Iesu, ma sa faapea ona ia faia. Ona o'u tagi atu lea i le lavea'i sili e afio mai ma fa'aali lona mana i le faafitauli o le tamā ona alu ai lea o le uso. I le lua vaiaso mulimuli ane, na o'u toe alu ai e vaai lo'u tinā ae toe alu ifo ai le tagata lenei vaai a'u. I le taimi lea, ua olioli lava auā ua fa'asa'olotoina atoatoa o ia. Ua pupula ona foliga ma aulelei. Ou te faatonu afai o e tauaveina soose ituaiga o avega i le agaga, ua fa'asa'olotoina oe i le suafa o Iesu. O avega fa'aleagaga e eseese ala e omai ai, o nisi o auala e aofia ai sauaga, saisaitiaga, faapologaina ma ma'i temoni. Ua ta'u mai ia i tatou i le faitauga mai le Tusi Paia o le asō le tala i se tagata na fa'ataugāina e se temoni. Ina ua ia vaai atu iā Iesu, i totonu o le malumalu na alaga atu le agaga leaga i totonu ia te ia faapea; “Aue, Iesu e, le Nasareta e! se a lau na ia te i matou? Ua e maliu mai ea ia fano i matou? Ua o'u iloa oe, o le Paia o le Atua.” Ona vavao atu lea o Iesu i le agaga leaga ma tuli ia te ia i fafo mai le tagata sa ulutinoina. Tatou te lē iloa po o le a le umi na i ai lea alii i le pologa; peita'i ina ua la fetaia'i ma Iesu, na siitia ai ma gausia le avega fa'aleagaga sa ia tauaveina. Le au pele e, o e tauamoina se avega fa'aleagaga? O lua tauivi ea ma ni saisaitiaga po o ni sauaga faatemoni? Ou te mana'o e te silafia o Iesu le tauaveina avega e mafai ona siitia lau avega mai ou tauau. Pau lau mea e fai o le faaaloalo i lana valaaulia o loo i le Mataio 11:28. Ou te tatalo ia siitia e le na te tauaveina avega uma, soose ituaiga avega o i lou olaga po o olaga o e pele ia te oe i le asō i le suafa mamana o Iesu. Tatalo. Tamā faamolemole faaumatia so'ose taupulepulega a le tiapolo e fa'ae'e se avega fa'aleagaga i o'u luga poo luga o lo'u aiga, i le suafa o Iesu. Amene.

Braškių derlius šiemet geras, bet dėl karštų orų baigtas doroti dviem savaitėm anksčiau nei įprastai. Šilauogių skynimas tik prasideda, tačiau dera tik trečdalis krūmų, nes likusius paveikė dideli šalčiai. Tokia padėtis ūkininko Vido Juodsnukio uogyne Kazlų -Rūdos savivaldybėje. Patyręs uogų augintojas aptaria ir kitus braškių ir šilauogių auginimo ypatumus šios vasaros permainingų orų sąlygomis.Vilkaviškio rajone Kiršų kaime iš molio ir šiaudų namą pasistatęs Andrius Milinkevičius kūrėsi iš senelių paveldėtoje žemėje. Etninės kultūros specialistas, 15 ha ūkininkas, dalį žemės skyrė pelkei atkurti. Pustrečio hektaro plote tyvuliuoja švendrais apaugęs prūdas, kuriame gausu žuvų, sugrįžę bebrai, ūdros, daug vandens paukščių, gausu vandens lelijų. Kaip pelkėje per pastarąjį dešimtmetį keičiasi bioįvairovė?Ignalinos rajono Mielagėnų Špitolėje kartais renkasi, repetuoja ir koncertuoja „Dainoriai“. Tai - vietos senjorų dainų ir muzikos mėgėjų kolektyvas. Su seniūnu Adu Trakymu aplankyta „Dainorių“ repeticija parodė kokia svarbi vietos gyventojams saviveikla, ką reiškia buvimas kartu. Kalbėję, groję ir dainave Ona, Stasė, Aldona, Alvydas, Mindaugas ir Romutis įsitikinę, kad tai padeda gyventi.Ved. Arvydas Urba

ADHD, Alcohol & Me: The Missing PieceFor a decade and a half, I was possibly solving the wrong problem.It was around 40 when I first started questioning my relationship with alcohol. I knew something had shifted. So I spent the best part of a decade playing with the rules — alcohol-free days, months off, even a year off at one point, then two. Stop-start, stop-start.Then at 56, I got diagnosed with ADHD. And that changed everything.In this episode, I'm talking about the thing nobody told me at the time: why the ADHD brain and alcohol are such a difficult match — and why this is true for so many of the women I speak to who are neurodivergent and struggling with drink.In this episode, I cover:The gap between questioning my drinking at 40 and understanding why at 56 — and the year and a half it took me to really land in that diagnosisWhy alcohol works so fast on an ADHD brain (and why that's exactly the problem) — the dopamine piece, in plain EnglishMasking: the decades of compensating, overworking and performing "fine" that so many late-diagnosed women will recogniseWhy "one glass" was never realistically going to be one glass, and why that was never about a lack of disciplineHow alcohol doesn't just numb an ADHD brain — it quietens it. And why that makes it feel like a solution long before it becomes a problemMy own teenage introduction to drinking, and the anxiety I didn't even know I was carryingThe vicious cycle of hangxiety, shame, obsessive replaying of the night before, and how alcohol makes every one of those symptoms worse, not betterWhy gray-area drinking with an undiagnosed or diagnosed ADHD brain is such a perfect stormThe running-on-a-stony-path metaphor — and why the right support is like finally putting your shoes onA few gentle questions to sit with if you suspect this might be part of your story tooA few lines I want you to sit with:"Alcohol doesn't just numb the ADHD brain — it quietens it. And that's exactly what makes it feel so helpful, long before it becomes harmful."Some questions to ask yourself:Do I reach for a drink to switch off a busy mind, more than to actually enjoy the drink itself?Have I spent my life feeling like I was too much and not enough at the same time — too much energy, not enough follow-through?Do I crash in the evenings after holding it all together, all day?None of these are a diagnosis. They might just be a doorway.I'm not here to diagnose anyone through a podcast. But if any of this lands, please don't let it get brushed off — by yourself, or by anyone else. Find someone who actually understands neurodivergence and the nervous system. You deserve better than being told you'll simply "grow out of it."Mentioned in this episode:The I Quit Wine Collective — a safe space for like-minded women on this journey. Come in, have a look around, say hello. There's an entry level with access to my 30-day break from alcohol, and the option to join the full Collective when you're ready.Take a look here:https://www.skool.com/i-quit-wine-iqw-collective-3336Email me here to share your story in confidence or enquire about 1:1 coaching:iqwwithsarah@gmail.com I'm rebuilding on Instagram after a break, please follow me & DM me to say hi. I'd love to hear what landed for you from this episode:https://www.instagram.com/iquitwine.withsarah/

¿Estás buscando embarazo? Descubre cómo la alimentación puede ayudarte a preparar tu cuerpo antes de la concepción y qué aspectos son realmente importantes.Descárgate el plan posparto gratis desde aquí.Soy Paula Ripol, autora de Dar a luz con hipnoparto y fundadora de myBabymyBirth y mi misión es que consigas tener tu mejor parto ganando conocimiento para entender tus opciones y con herramientas para vivir tu embarazo y parto desde la calma. Síguenos en Instagram para ver vídeos y contenido sobre el parto. Suscríbete a nuestro canal de Youtube. Descubre nuestro recursos gratuitos.Descárgate ONA app gratis, tu contador de contracciones u olas con las relajaciones de hipnoparto. Adquiere el Pack Digital de Hipnoparto, nuestro curso de hipnoparto online que haces a tu ritmo.Descubre nuestros cursos grupales de HipnopartoSuscríbete a nuestro Pack Posparto, nuestro curso y acompañamiento ya desde el embarazo y cuarto trimestre

OPEN HEAVENSMATALA LE LAGI MO LE ASO SA 12 IULAI 2026(tusia e Pastor EA Adeboye) Manatu Autu: Galuega Mata'utia (Mighty Works) Tauloto Tusi Paia:Mareko 9:23 “Ona fetalai atu lea o Iesu ‘iā te ia, “‘Ai se mea ‘e te mafaia. Auā e mafaia mea uma lava i lē fa‘atuatua.”Faitauga - Tusi Paia: Mareko 6:1-6Ua faailoa mai e le tusi o Ieremia 32:19; ia I tatou, o le Atua Silisiliese e mata'utia i galuega. E finagalo le Atua e fai galuega Silisili. Paga lea, peita'i i le tusi faitau mai le Tusi Paia o le asō, ua lē mafai e Iesu ona faataunuu galuega mamana i totonu o lona lava nuu ona o le lē faatuatua o tagata. O le lē talitonu ma le masalosalo o le a lē mafai ai e se uso ona vaai i galuega mamana a le Atua i lona olaga. A i ai le faatuatua ma le talitonu o le a fa'aalia i le olaga o le uso galuega mata'utia a le Atua Silisili ese. E fiafia le Atua e fai galuega silisili ma na te sailia ni atalii ma ni afafine e galulue faatasi ma Ia. O loo saili mai o Ia mo ni tane ma ni fafine e faia galuega e sili atu i mea na faia e le Alii o Iesu Keriso a o i ai o Ia i le lalolagi. Peita'i e manaomia le faatuatua i le Alii o Iesu Keriso pe afai e te mana'o e mafai ona e faia galuega e sili atu i mea na Ia faia (Ioane 14:12). Le au pele e, e te lē manaomia sou auai atu i se aoga fa'afaifeau pe maua se tulaga faapitoa e faatino ai galuega tetele; pau le tulaga manaomia o lou faatuatua. Ina ua latalata i le taimi e afio a'e ai Iesu i le lagi, na ia poloa'i i ona so'o, e tāla'i atu le talalelei i le lalolagi uma ma ta'u atu iai latou, faailoga tetele e mulimuli atu iai latou. Na ia fetalai, ua iai latou le mana e tutuli ai temoni, tautalatala i gagana fou, fetagofi i latou i gata ma fa'ae'e o latou lima i luga o e mama'i (Mareko 16:15-18). Pau le mea e agava'a ai i latou e fai nei galuega uma o le faatuatua ia te Ia.Atalii ma le afafine o le Atua, e finagalo le Atua e faatino galuega silisili e ala ia te oe. E finagalo e fa'aaogā oe e fai ma ana uatogi o le taua e faaumatia ai galuega a le pouliuli (Ieremia 51:20). Peita'i e ao ona e faatuatua i le Atua e taunuu ai mea nei. E moni o Ia o le Atua e Pule aoao e mafaia ona fai soosemea e finagalo ai, peita'i e finagalo o Ia i le faatuatua ia mafaia ai mea uma mo oe (Mareko 9:23). Na e faatagaina le lē talitonu e faaseseina oe ma aveese oe mai galuega mamana na finagalo le Atua e faataunuu e auala ia te oe? Afai na e faia, ole atu mo lona alofa mutimutivale i le asō. Faatumu lou loto i lana upu auā o lou faalogo pea lava pea i le upu a le Atua e tupu ai lou faatuatua. Fai mai le tusi o Roma 10:17; e tupu le faatuatua i le taulogologo atu, o le taulogologo atu fo'i o i le Afioga a le Atua lea. E ao fo'i ona e sola ese mai soosemea e faavaivaia lou faatuatua. O Iesu Keriso e tumau ananafi, o le asō ma le faavavau (Eperu 13:8) ma o mea mata'utia ua ia faia mo isi, ma auala atu i isi, e mafai fo'i ona Ia faia mo oe ma ala atu ia te oe. Pau lava ia e faatuatua. Tula'i i luga ma galue. I le suafa o Iesu, Amene.

OPEN HEAVENSMATALA LE LAGI MO LE ASO TOONAI 11 IULAI 2026(tusia e Pastor EA Adeboye) Manatu Autu: Aua nei e manatu ua e matua tele e vivii ( Never outgrow praise ) Tauloto Tusi Paia:Eperu 13:15 “O lenei, o ‘iā tatou te avatu so‘o ai le taulaga o le vi‘iga i le Atua, o le fua lea o tatou laugutu, o lo‘o fa‘afetai atu i lona suafa.”Faitauga - Tusi Paia: Salamo 63:3-5O se tasi o auala e faatoilalo ai e le tiapolo le toatele o kerisiano faatuatua o le vaai maualalo lea i pese ma viiga i latou Ekalesia. O ia kerisiano faatuatua e lē fia auai i taimi o viiga pe faatali foi e o mai i le lotu pe a maea pese ma viiga. E manatu o le vivii i le Atua ma siva mo ia o mea a tamaiti poo ua matua tele faaleagaga e lē tatau ai ona toe siva ma vivii ia te ia. I luma o fofoga o le Atua, o tatou uma o lana fanau aua o le afe tausaga e tutusa ma le aso e tasi i ona luma ( 2 Peteru 3:8). O lona uiga o le silasila mai a le Atua, e leai seisi i le lalolagi i le asō ua atoa se aso i lona matua. O le viiga o se tasi o auupega malosi o loo i kerisiano. Fai mai le Salamo 22:3, ‘“A o oe, e pa‘ia oe; o lo‘o e ti‘eti‘e i vi‘iga a Isaraelu.” O lona uiga o lau viiga e tatai mai ai le mamalu o le Atua, a afio mai le Atua i se nofoaga, e lē afio fua mai. E afio mai ma meaalofa, faamalologa ma faamanuiaga. Ina ua faaaogaina e Iosefatu ma tagata o Iuta le viiga o se auupega, na toe fetauai lava o latou fili seia oo ina faaumatia e i latou lava (2 Nofoaiga Tupu 20:22-24). O nisi o taua, e pau le auala e manumalo ai o le viiga ma le siva malosi i luma o le Atua.Fai mai le Galuega 16:25-26 “O le tulua o po ma ao ‘ua tatalo ai ma pepese o Paulo ma Sila, i le Atua; ‘ua fa‘alogo fo‘i ‘iā te i lā‘ua e ‘ua noanoatia. ‘Ona fa‘afuase‘i mai lea o le mafui‘e tele, ‘ua lūlūina ai fa‘avae o le fale puipui; ‘ua matala mai ai uma faitoto‘a, ‘ua maunuunu ai fo‘i o latou noanoaga uma lava.”Fai mai le Tusi Paia, o Paulo ma Sila, na la avatu le taulaga o pese ma viiga i le Atua ao iai i le falepuipui. Na tali mai le Atua i le luluina o le mafuie, ua talaia uma faitotoa ma ua matalatala uma noanoataga o pagota. E leai seisi e vivii i le Atua ma le loto atoa ae tumau ona saisaitia. A e vivii i le Atua ma lou loto atoa, e tulai mai le Atua i lona malosi atoa e fesoasoani ia te oe ma faamanuia ia te oe. Le au pele e, e lē tatau ona e faatagaina e te oo i le tulaga e te manatu ai ua e matua tele e lē talafeagai ona e toe pese ma vivii. Na manatu Mekala o le vivii i le Atua o se tulaga maulalo tele i lona tulaga tau tupu, ma o le taui, na lē fanau i lona olaga atoa ( 2 Samuelu 6:16-23). E tatau ona e sau i luma o lou Tamā o se tasi o lana fanau ma vivii ia te ia ma lou loto atoa. I le Salamo 50:23, o loo fetalai le Atua, o lē faia le vi‘iga ma taulaga ia te ia, o lea tagata e āva ‘iā te ia; ma afai e āva ma viia le Atua i lou olaga, o lona matagofie o le a faailoa ia te oe ma mea uma i lou olaga. Ou te tatalo, ao e vivii i le Atua, o lona mamalu o le a faaalia i lou olaga i le suafa o Iesu. Aua nei e manatu ua e matua tele mo le viiga aua e taua ma pele i le finagalo o le Atua, i le suafa o Iesu, Amene. 

Notes Avui la Sílvia ens proposa un exercici per practicar adjectius: ella diu el començament d'una frase i l'Andreu l'ha de completar amb un adjectiu, el primer que li vingui al cap. Tot seguit, n'han de trobar el contrari. Entremig, comentaran matisos importants dels adjectius que vagin sortint. Episodi en directe Acompanya'ns el pròxim 23 de juliol a les 17 h a la llibreria Ona per al segon episodi amb públic! Podreu remenar llibres en català, protegir-vos de la calor, practicar el català i passar una bona estona amb nosaltres.

Besmele, işe başlamadan önce, işinin kolaylığa, hafifliğe ve müsamahaya dayanmakta olduğuna kulun dikkatini çekmektir. Böylece, sanki Cenâb-ı Hâkk, senin için zikrettiği kelimenin daha başında, onu, seni affedeceğine, sana lütûfta bulunacağına delil kılmıştır. Anlatıldığına göre Firavun, Tanrılık iddiasında bulunmazdan önce, bir saray yaptırttı. Ve sarayın dış kapısına da, besmelenin yazılmasını emretti. Ulûhiyyet iddiasına kalkışıp da, Hz. Musa (a.s.) peygamber olarak ona gelip, onu hak dine davet edince, onda doğruya ulaşma istidâdı görmedi. Bunun üzerine Hz. Musa (a.s.) şöyle dedi: "Ya Râbbî, onu ne kadar dine davet ettimse de, onda herhangi bir hayır görmedim." Bunun üzerine Cenâb-ı Hâkk şöyle buyurdu: "Ey Musa, belki de sen, onun küfrüne bakarak, onu helâk etmemi istiyorsun. Halbuki Ben, onun sarayının dış kapısının üzerine yazmış olduğu besmeleye bakıyorum." Buradaki incelik şudur: Kâfir de olsa, kim bu kelimeyi dış kapısının üzerine yazarsa, helâk olmaktan emin olur. Kim bu kelimeyi, ömrünün başından nihayetine kadar, kalbine yazarsa, onun durumu nasıl olur, var sen düşün! Cenâb-ı Hâkk kendisini Rahmân ve Rahîm diye adlandırdı. O halde, nasıl merhamet etmesin? Anlatıldığına göre, bir dilenci zengin bir kimsenin kapısında durarak, bir şeyler istemişti. Bunun üzerine kendisine çok cüz'î bir şey verildi. İkinci gün, elinde bir baltayla geldi ve kapıyı kırmaya başladı. Ona, "Ne yapıyorsun?" denilince, şöyle cevap verdi: "Ya kapının bahşedilene uygun veyahut da yapılan bağışın kapıya uygun olması gerekir." Ey Râbbimiz! Merhamet denizleri, senin râhmetine nisbetle, zerrenin senin Arşına olan nisbetinden daha küçüktür. Kitabının başında râhmetinin sıfatını kullarına bildirdin. Binâenaleyh, bizi râhmetin ve lütfundan mahrum bırakma. (Fahruddîn Er-Râzî, Tefsîr-i Kebîr Mefâtîhu'l-Ğayb, c.1, s.236)

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

 – Ona i Jordan Bardella jako premier mają być motorem napędowym dla Francji – tak deklarację Marine Le Pen ocenia na antenie Radia Wnet Mikołaj Murkociński. Choć liderka Zjednoczenia Narodowego usłyszała niedawno wyrok skazujący, niespodziewanie ogłosiła swój start w walce o Pałac Elizejski. W rozmowie z Łukaszem Jankowskim ekspert Radia Wnet ujawnia kulisy tej politycznej gry o najwyższą stawkę. 

Durante años, el Dr. Óscar Halaburda creyó que su trabajo era intervenir. En este episodio nos cuenta cómo su experiencia personal y su formación en hipnoparto transformaron por completo su manera de acompañar los nacimientos.Descárgate el plan posparto gratis desde aquí.Soy Paula Ripol, autora de Dar a luz con hipnoparto y fundadora de myBabymyBirth y mi misión es que consigas tener tu mejor parto ganando conocimiento para entender tus opciones y con herramientas para vivir tu embarazo y parto desde la calma. Síguenos en Instagram para ver vídeos y contenido sobre el parto. Suscríbete a nuestro canal de Youtube. Descubre nuestro recursos gratuitos.Descárgate ONA app gratis, tu contador de contracciones u olas con las relajaciones de hipnoparto. Adquiere el Pack Digital de Hipnoparto, nuestro curso de hipnoparto online que haces a tu ritmo.Descubre nuestros cursos grupales de HipnopartoSuscríbete a nuestro Pack Posparto, nuestro curso y acompañamiento ya desde el embarazo y cuarto trimestre

„Já se domnívám, že světu vládne ne ta moc, kterou vidíme, vlády, a tak dále, ale že světu vládne moc, která je za oponou, a tato moc také vyplývá z toho, že my na ní nemůžeme útočit, nemůžeme ji kritizovat. Ona nepředkládá žádné programy čili nemůže nic nesplnit. A tato kryptokracie má své nástroje, kterými ovládá ten svět, a Greta Thunbergová se právě na toto hodila,“ říká sociolog Petr Sak v rozhovoru pro pořad Kupředu do minulosti. 2. díl, 07.07.2026, www.RadioUniversum.cz

Notes A Catalunya hi ha gent de tot el món i de catalans n'hi ha repartits per tot arreu, però hi ha alguns països que tenen més connexions que d'altres, i aquest és el cas de Mèxic, que per raons històriques té molts vincles amb la cultura catalana. A l'episodi d'avui descobrirem alguns d'aquests enllaços juntament amb la Pamela, una comunicadora i gestora cultural que divulga fets i curiositats que entrellacen el seu país natal i el país que l'ha acollit. Som-hi! Susurros de México Segueix el perfil a Instagram: @susurrosdemexico L'expressió de la setmana "peti qui peti" ('tant sí com no', 'tant si plou com si neva', 'passi el que passi') "embolicar la troca" ('complicar les coses') Bonus La Pam explica com ho va fer per aprendre el català des de Mèxic, abans de venir a viure a Catalunya. Transcripció interactiva i vocabulari Fes-te membre d'Easy Catalan i tindràs accés a l'ajuda de vocabulari, la transcripció interactiva i el bonus de cada episodi: easycatalan.org/membership Transcripció Andreu: [0:16] Bon dia a tothom! Ja som al juliol i això vol dir que ja som a la segona meitat de l'any. Déu-n'hi-do, com de ràpid passen els mesos! En fi, des del gener han passat per aquí diverses persones convidades a parlar-nos dels seus projectes i de la seva relació amb el català. Vam tenir el Marc, ambaixador digital del Banc de Sang de Catalunya; el Kirill, creador de l'aplicació Wordbox per aprendre llengües; l'Enric Luzán, que fa la volta al món a peu i que, per cert, va rebre fa poc un premi com a millor creador de contingut en català de temàtica esportiva; també va venir la Fairlie, que treballa al Centre de Supercomputació de Barcelona, i l'Eloi i l'Arnau, del projecte Speak Catalan. La convidada d'avui és una persona de Mèxic, que ara viu a Catalunya, però que encara té un peu i mig cor, si més no, al seu país natal. Amb ella ens vam conèixer personalment l'any passat, a Barcelona, quan vam fer l'episodi en directe del pòdcast. Va venir al final de tot a xerrar amb la Sílvia i amb mi, es va presentar i ens va fer un petit regal amb alguns records de Mèxic. La conversa va ser breu, però de seguida ens va transmetre el seu amor pel seu país, així com pel país que l'ha acollit, Catalunya. Tant és així que va decidir crear un projecte de divulgació cultural sobre les connexions que hi ha entre aquests dos pobles. El projecte es diu Susurros de México, que podríem traduir el català com Xiuxiuejos de Mèxic, i que us animo a seguir a Instagram. Busqueu @susurrosdemexico, tot junt. Ara parlarem amb ella, però abans vull recordar que aquest juliol tornarem a fer un episodi del pòdcast en directe a Barcelona, a la llibreria Ona, i que hi esteu tots convidats. Ens faria molta il·lusió tornar a omplir la sala com ho vam fer l'any passat, així que reserveu-vos la data: dijous 23 de juliol a la tarda. Estigueu atents a les xarxes i a Discord per saber l'hora exacta i tots els detalls. Entrevista Andreu: [2:14] Bon dia, Pam! Pam: [2:16] Hola, bon dia! Andreu: [2:17] Bé, t'he dit Pam… o t'he de dir Pamela? Pam: [2:20] No, Pam em sembla fantàstic. Andreu: [2:22] Pam va bé, d'acord. Doncs, a veure, tu i jo ja ens coneixem, ens vam conèixer l'any passat, el 2024, a l'episodi en públic que vam fer… [2025.] Ai, 2025, perdona, sí, sí. 2025, a l'episodi amb públic, que vas venir a veure-ho i al final vam estar xarrant i ens vas donar alguns petits souvenirs o records de Mèxic. Pam: [2:43] Sí. Andreu: [2:44] Era un clauer, hi havia també unes llaminadures picants… Òbviament, picants. I això, i llavors, ens has anat compartint, des d'aleshores, contingut que fas tu a les xarxes, ara en parlarem, i ens vas proposar fa poc de venir aquí al pòdcast i parlar d'aquest contingut, o de les relacions entre Catalunya i Mèxic. Però abans de parlar del projecte, jo voldria coneixe't una mica més. Aleshores, per a més context, quan vas venir tu a viure a Catalunya i què t'hi va portar? Tenies alguna connexió familiar amb Catalunya? Pam: [3:19] (Bé), jo vaig venir a viure entre Mèxic i Catalunya des de 2024. Va ser una mica (lent), el procés, perquè vaig estar aquí tres mesos, després tres mesos a Mèxic, tres mesos aquí, tres mesos allà. Després ja vaig començar un procés de parella de fet, que és això el que em porta aquí a Catalunya, l'amor. Andreu: [3:37] D'acord. Pam: [3:37] I vaig estar ja més mesos aquí a Catalunya, però per a mi és com molt important sentir que tinc un peu a casa de Mèxic i un altre peu a casa de Catalunya, no? Andreu: [3:49] I encara estàs vivint entre un país i l'altre, o estàs més a Catalunya, ara?

OPEN HEAVENSMATALA LE LAGI MO LE ASO TOONAI 4 IULAI 2026(tusia e Pastor EA Adeboye) Manatu Autu: Manū O Ao (While It Is Day) Tauloto Tusi Paia: Ioane 11:9 “Ona tali atu lea o Iesu, “E lē ‘ua sefulu ‘ea ma le lua itūlā i le ao? ‘Āfai e savali se tasi i le ao, e lē tausuai o ia, auā e va‘ai o ia i le malamalama o lenei lalolagi.”Faitauga - Tusi Paia: Iosua 13:1-5 O le fa'amatalaina o nisi o galuega tetele a Iosua e maua i le tusi o Iosua 12. Ua fa'amamafa e le mataupu, tupu uma na fa'ato'ilalo e Iosua ma fanua na umia e Isaraelu. E moni o se lisi umi lava o manumalō, ma o so'o se uso na te ausia mea sa mafaia e Iosua, e mitamita i galuega faapea. Peita'i i le mataupu soso'o ane ai, o le faitauga fo'i lea o le Tusi Paia o le asō, na fetalai le Atua ia Iosua, e ui ua toeaina ia, o loo tele pea fanua e tatau ona umia. Ona muamua lea o le Atua e lisi fanua uma o totoe e le'i fa'ato'ilaloina ma faailoa ai ia Iosua o loo tele pea galuega e ao ona fai. Le au pele e, e i ai se taimi faatulagaina e tatau ai ona e faia galuega a lē na auina mai oe. I le tusi o Ioane 9:4; na fetalai Iesu “E tatau ona o'u faia galuega a le ua auina mai a'u, manū o ao; e o'o mai le po, e le mafaia e se tasi ona galue ai.” O tagata soifua uma, e i ai le ao ma le po. O le ao o le vaega o le olaga o se uso a'o talavou ma mataalia. I le ao, o le vaitau lea o loo i ai i se uso le malosi e lauga solo ai le talalelei a Keriso ma mafai ona anapogi ma tatalo poo le a lava le umi e mana'o ai. Peita'i a o'o mai le po e ono fa'aitiitia le malosi o le tagata. E le gata i lea, a o'o mai le po o nisi tagata, e maua i ma'i ma ua le mafai ona fa'aauau le galulue. O lona uiga afai o loo e maua le avanoa e fai ai le galuega a le Atua i le taimi lenei, fai ma lou malosi ma lou manatu atoa. Tusa pe afai ua tele tausaga o lou soifua, o le mea moni, o loo e soifua pea o lona uiga o loo tele pea galuega e mafai ona e faia mo le Atua, faapei ona ia fa'aali ia Iosua i le faitauga mai le Tusi Paia o le asō. E 24 itula o le aso. Pe a ma le afa o nei itula e fa'ailogaina i le i ai o le susulu o le la, ma i totonu o nei itula o le toatele o tagata e galulue ai i a latou lava fuafuaga. A mavae itula o le malamalama e oo mai le pogisa. Na fetalai Iesu i le tusi o Ioane 11:10; afai e savali se tasi i le po, e tautevateva o ia. O lona uiga o le taimi lenei e auauna ai i le Atua ma faia soose galuega na te tuuina mai i ou lima. E tatau ona e galue nei auā a o'o mai le po; e leai se isi, e aofia ai ma oe, e mafai ona galue. O lenei, galue a o i ai pea le ao. Aua le faatuai i le galuega a le Atua. Faamalōlō i e mama'i; lauga le talalelei, tuliese temoni, faufautua i le augatupulaga o soso'o mai ma fa'asusulu lou malamalama ia susulu atu i tagata uma ia o latou fa'amanūina ai lou Tama o i le lagi. Galue manū o ao. I le suafa o Iesu, Amene.

Künyesi Ebu Abdullâh'dır. Cüsseli, kalın pazulu, iki omzunun arası açık, kızıl ve kıvırcık saçlıydı. Resûlullâh (s.a.v.) zamanında İslâmiyeti kabul etti. Kabilesini de İslâma davet etti. Hudeybiye umresinden önce Müslüman oldu. Rıdvan Biati'ne katılanlardandı. Peygamber (s.a.v.)'den rivayette bulunmuştur. İbn Sad dedi ki: “Ona (isabetli görüşlerinden dolayı) 'Mugiratu'r-Re'y' derlerdi. Yemame Savaşına, Şam ve Irak fetihlerinde, Yermuk Savaşında ve Kadisiye Harbinde hazır bulundu. Yermük'te gözünden yaralandı. Eş-Şa'bî dedi ki: “Arabın dehâlarından idi”. Kabisa b. Cabir ise: “Mugire ile arkadaşlık ettim. Şayet Medine'nin seksen kapısı olsa ve onlardan ancak hile ile çıkılabilse, muhakkak ki Mugire hepsinden çıkardı.” Taberi dedi ki: “İçine düştüğü her durumdan mutlaka bir çıkış yolu bulurdu. İki seçenek arasında birini seçemeden kalmazdı. Hz. Ebubekir es-Sıddîk (r.a.) onu Nuceyr halkına göndermişti. Sonra Sad (r.a.)'ın elçisi olarak Rüstüm'e gitti.” Ömer (r.a.) onu Basra valisi olarak görevlendirmiştir. Bu dönemde Meysan, Hemedan ve birçok beldeyi fethetmiştir. Begavi dedi ki: “Mugire (r.a.) Basra'da ilk divan kuran kimsedir.” Hz. Osman (r.a.) onu görevinde bıraktı, sonra azletti. Hz. Osman (r.a.) şehit edilince Hakemeyn olayına katılana kadar savaştan uzak durdu. Bundan sonra Kûfe valisi olarak görevlendirildi. Kûfe'de, oranın emiri olduğu dönemde Hicri 50 yılında bir veba salgını yüzünden öldü. Ölümü yaklaştığı bir sırada şöylece duada bulundu: “Ey benim Allâhım, işte sağ elim ki onunla Peygamberin (s.a.v.)'e biat ettim ve yine Peygamberin (s.a.v.)'le senin yolunda mücahede yaptım.” (İbnu Hacer el-Askalânî, el-İsabe (Seçkin Sahabeler), s.375)

Cristina, una mamá que hizo el curso de hipnoparto y se leyó mi libro, comparte cómo pasó de un primer parto muy intervenido a vivir un segundo nacimiento en una casa de partos, sintiéndose protagonista de sus decisiones. Una historia que demuestra cómo la información, el acompañamiento y la confianza pueden transformar por completo la experiencia del parto.Descárgate el plan posparto gratis desde aquí.Soy Paula Ripol, autora de Dar a luz con hipnoparto y fundadora de myBabymyBirth y mi misión es que consigas tener tu mejor parto ganando conocimiento para entender tus opciones y con herramientas para vivir tu embarazo y parto desde la calma. Síguenos en Instagram para ver vídeos y contenido sobre el parto. Suscríbete a nuestro canal de Youtube. Descubre nuestro recursos gratuitos.Descárgate ONA app gratis, tu contador de contracciones u olas con las relajaciones de hipnoparto. Adquiere el Pack Digital de Hipnoparto, nuestro curso de hipnoparto online que haces a tu ritmo.Descubre nuestros cursos grupales de HipnopartoSuscríbete a nuestro Pack Posparto, nuestro curso y acompañamiento ya desde el embarazo y cuarto trimestre

„Ona jest taka grzeczna." „On nigdy nie sprawia problemów." „Zawsze się dostosuje." „Nie trzeba się nim zajmować."

İbn Arabî'nin verdiği dikkat çekici örneklerden biri de bazı ayetlerin insanlar üzerinde özel tesirler meydana getirmesidir. Ona göre kimi insanlar belirli ayetleri okuduklarında kendilerinde meydana gelen ruhsal değişimleri fark ederler. Daha sonra aynı ayeti tekrar okuduklarında aynı etkinin yeniden ortaya çıktığını görürler. Bu gözlem, İslam dünyasında yazının neden yalnızca okunmak için değil, seyredilmek için de üretildiğini açıklamaktadır.

At school, work, council offices or sporting events, you might see a red, black and yellow flag flying beside the Australian national flag. This is the Aboriginal flag, representing the Aboriginal people of Australia and their connection to land, community and stories. - Jeste li primijetili crveno-crno-žutu zastavu koja se često vijori uz australsku državnu zastavu? To je aboridžinska zastava. Ona predstavlja Aboridžine Australije i njihovu povezanost sa zemljom, zajednicom i pričama koje se prenose generacijama. Za mnoge ljude ona je mnogo više od zastave. Simbol je snage, opstanka i identiteta.

Convertirse en madre o padre cambia por completo nuestras prioridades. Y muchas veces, en medio de las necesidades de nuestros hijos, nos olvidamos de las nuestras.En este episodio hablamos de un autocuidado realista, lejos de las imágenes perfectas de redes sociales. Porque cuidarte no siempre significa encontrar horas libres para ti, sino aprender a escuchar tus necesidades, bajar la exigencia y encontrar pequeñas formas de sostenerte en el día a día.Hablamos de culpa, descanso, alimentación, conexión, límites y de cómo nuestro bienestar influye directamente en la forma en que criamos y acompañamos a nuestros hijos.Porque cuidarte no es egoísta. Es una de las mejores maneras de cuidar a tu familia. ❤️

Ebû Hüreyre (r.a)'in bildirdiği hadîs-i şerifte: “Beni İsrail'e bir gün oruç farz kılındı. O gün de, Muharremin onuncu günü olan Aşûra günüdür. Siz o gün oruçlu olunuz. Çoluk çocuğunuza iyilik yapınız. Bir kimse Aşûre günü çoluk çocuğuna iyilik yapsa, onları sevindirse, Allâhü Teâlâ ona senenin diğer günlerini iyi eder. Aşûre günü oruç tutanın orucu, kırk yıllık günâhına keffâret olur. Aşûre gecesini ihyâ edip, sabahleyin de oruçlu olsa, ölüm acısını anlamayarak vefât eder.” buyuruldu. Hz. Alî (r.a)'in bildirdiği hadîs-i şerîfte: “Aşûre gecesini ihyâ edeni, Allâhü Teâlâ dilediği gibi ihyâ eder” buyuruldu. Büyük âlimlerden Muhammed bin Münteşir (r.âleyh): “Bir kimse Aşûra gününde çoluk çocuğuna mal ve para bakımından kolaylık yapsa, onlara iyi şeyler alsa, Allâhü Teâlâ o kimseye yılın diğer günlerinde kolaylık verir, rızkını genişletir. Ona asla darlık göstermez” dedi. Peygamberimiz (s.a.v.) “Aşure günü, peygamberlerin oruç tuttukları bir gündür. Siz de o gün oruç tutunuz!” buyurmuştur. (Musannef) Nebî (s.a.v.) aşura günü oruç tutmaya hem kendisi devam etti, hem de bunu müslümanlara emretti ve: “Aşure günü orucu bir yılın kefâretidir! Sağ olursam, gelecek yıl dokuzuncu gününü de, inşaallah oruçlu geçireceğim! “Dokuzuncu ve onuncu günü oruç tutup Yahûdilere muhâlefet ediniz!” buyurdu. Aşûre gününün üstünlüklerindendir ki, Allâhü Teâlâ o gün peygamberlerini düşmanlarından kurtardı. Fir'avun'u ve kavmini o gün helâk eyledi. Gökleri, yeri, Âdem (a.s.)'ı ve daha birçok şerefli şeyleri o gün yarattı. O gün oruç tutanlara büyük sevâb ve mükâfatlar hazırladı. O günde orucu, günâhlara keffâret eyledi. Bunun için Aşûre günü, iki bayram, Cum'a, Arefe ve bunlara benzer şerefli günler gibi oldu. Aşûre günü musîbet ve matem günü olsa idi, sahâbe ve tâbiîn (r.a.e) mâtem günü kabul ederlerdi. Çünkü onlar o zamana bizden daha yakîn idiler. Halbuki onlar Aşûre günü çoluk çocuğunu sevindirmek, giydirmek ve oruç tutmak gibi şeyler yaptılar. (Abdulkâdir Geylânî (k.s.), Gunyetü't-Tâlibîn, s.356)

OPEN HEAVENSMATALA LE LAGI MO LE ASO SA 21 IUNI 2026(tusia e Pastor EA Adeboye) Manatu Autu: Faaa'oa'o i lou Tamā oi le lagi (Emulate your heavenly Father) Tauloto Tusi Paia: Eperu 6:12 “‘ina ‘ia lē paiē, a ‘ia fa‘aa‘oa‘o i ē na maua i le fa‘atuatua ma le ‘onosa‘i mea na folafolaina.”Faitauga - Tusi Paia: Efeso 5:1-5I le tele o tausaga talu ai, na tatalo se faifeau ma fai i le Atua, afai e na te maua le sefulu pasene o mea o loo ia te a'u, ua malie foi lona loto. Na fai iai le Atua afai e na te faia galuega o loo ou faia, e mafai foi ona ia maua mea o loo ou maua. Ina ua fesili i le Atua poo a au mea na faia i le tuanai ma na faailoa iai e le Atua, na ou amata i le anapogi mo le 40 aso. Na fai le tamaloa lea i le Atua e tuu ia o ia aua e lei sauni e mulimuli i lea faataitaiga. Fanau a le Atua, o le ausia o ni taui i le olaga nei, e tatau ona e mulimuli i faataitaiga aua o le natura o  mea, e i'u ane lava e te faapei o olaga o i latou o loo e mulimuli ai. Ina ua aveolaina ae Elia i le lagi, na maua e Elisaia le faaluaina o le faauuga sa ia Elia, na ia aveina le ofu talaloa o Elia ma tāina ai le vaitafe i Ioritana. Ona ia ole atu i le Atua ia vaeluaina le vaitafe aua na ia vaeluaina mo Elia, ma na faataunuuina e le Atua. Na mulimuli Elisaia i faataitaiga a lona tamā. Na fai Paulo i le au faatuatua i Korinito e mulimuli ia te ia e pei ona ia mulimuli ia Keriso (1 Korinito 11:1). O le fesili, o ai o e mulimuli ai?  O ai o e faaa'oa'o iai? Fai mai le Efeso 5:1, e tatau ona tatou mulimuli o le Atua o lana fanau. Ao tatou mulimuli i le Atua, e iai foi tagata o le Atua i lo tatou siomaga e tatou te mulimuli ai. O le tauloto o le asō o loo faamalosi iai tatou e mulimuli iai latou na latou maua faamanuiaga o folafolaga e ala i le faatuatua ma le onosai. E iai faataitaiga ma faasologa o mea e te mulimuli ai o fanau a le Atua. Afai o mulimuli moni se tagata ia Iesu Keriso, e faasaoina oe pe a e mulimuli ai aua foi o le a ia taitaia oe i le Alii. O loo saunia e le Atua ni faataitaiga se tele i lana Upu ma aumaia iai tatou o tagata o le faatuatua e tatou te faataitai ma faaa'oa'o iai ao latou mulimuli ia Keriso. O le mulimuli i se tagata, e tatau ona e suesue lelei iai latou ma mataitū latou mea o loo faia. E lē mafai ona e faataitai i se tagata mai ni tamai ata o loo e matamata ai i luga o le initaneti, aua e tele mea ni mea e faatatau iai latou e te misia. Faitau i latou tusi, galue fua mo  i latou, suesue ma maitau mea ma faaiuga latou te faia i mataupu. Le au pele e, ao e faataitai i lou Tamā oi le lagi, ia avea oe o se faataitaiga lelei i nisi tagata.  Mulimuli ia Keriso ina ia mafai e i latou e fia faaa'oa'o ia te oe, ona latou maua le Alii. Ou te tatalo ao e faaa'a'o i lou Tamā oi le lagi, e na te faia oe o se amepasa matagofie, i le suafa o Iesu. Tatalo i le Atua e fesoasoani i tamā uma ia avea i latou ma faataitaiga lelei i isi tagata, i le suafa o Iesu, Amene.

OPEN HEAVENSMATALA LE LAGI MO LE ASO FARAILE 19 IUNI 2026(tusia e Pastor EA Adeboye) Manatu Autu: Vivii i le Atua e le aunoa (Always praise God) Tauloto Tusi Paia: Salamo 147:1 “Ia ‘outou vivi‘i atu i le ALI‘I. Auā e lelei ‘ona fai pesega i lo tatou Atua; auā e matagofie, e ono lava le vi‘iga.”Faitauga - Tusi Paia: Isaia 38:18-30I tausaga talu ai, o se tasi o ou afafine ua maua i le kanesa ma ua fautuaina e fomai e pau le fofō, o le aveesea o lea totoga, le vaega o loo iai lona leo. Ina ua maea le taotoga, na ma asiasi iai ma lo'u toalua, tatalo ma faamalosi iai, e mafaia mea uma i le Atua. Ona ua aveesea le vaega o lona tino e iai le leo, sa le mafai ona tautala mai ae pau fesootaiga e mafai ona faia o feau tusitusia mai le telefoni. E iai se aso ina ua ou fo'i mai sa'u malaga, ao ou oso i fafo o le taavale, na ou vaai atu i se tagata o taavalevale i le palapala. O lou afafine lena na aveesea le totoga o lona tino e iai le leo. Ina ua vaai mai ia te a'u, ua faapea mai, ‘o a'u lenei tamā, ua mafai ona ou toe tautala'. Sa matuā ou faafetai moni i le Atua mo le toe faafoisia o lona leo ma faataga o ia e usu pese e vivii ai i le Atua e faifai pea. Le au pele e, na avatu e le Atua le leo ia te oe ia faaaoga e vivii ai ia te ia. Afai o loo e soifua pea, e mafai ona faaaoga lou leo e vivii faifaipea ai ia te ia. E tatau i le Atua lau viiga, ma o se tasi lea o auala e maua ai tali o au tatalo. I le taimi o le nofoaiga tupu a Esekia, na ia tofia ositaulaga ma le au sa Levī e faia viiga i le Alii. O latou matafaioi, o le avatu o viiga faifai pea i lotoā o faleie o le Alii, ma o le mea muamua e vaaia e soo se tagata a'o ulufale atu i le faleie, o ositaulaga ma le au sā Levī o loo vivii i le Atua (2 Nofoaiga Tupu 31:2). E lei leva, ae afātia, ma ua gasegase Esekia. Sa matuā ma'i lava. Ua auina mai le Atua lana perofeta o Isaia e logo Esekia. Na matuā faanoanoa i le feau na oo mai, o lea sa liliu atu i le puipui o le fale, ma tagi atu i le Atua. Na ia faamanatu i le Atua, o ia sa savali i ona luma i le upu moni ma faia mea lelei i ona fofoga. Na faalogo le Atua i lana tatalo ma toe auina Isaia e logo o ia, e lē oti (Isaia 38:1-8). Na silafia e le tupu e fiafia le Atua pe a vivii atu, ma o lea na faapea atu i le Atua, o le tuugamau e lē mafai ona vivii ia te ia, na o ē o soifua, e pei ona tusia i le faitauga mai le Tusi Paia o le asō (Salamo 147:1). Le au pele e, tusa poo a mea o tutupu i lou siomaga, e tatau ona e vivii faifaipea i le Atua pe afai o loo e ola pea. A e vivii i le Atua, o loo e faaumatia fuafuaga a le tiapolo ma tapunia i latou e tulai e tauimasui (Salamo 149:67). Ia avea le viiga e fai ma au tali i soo se mea. O lou leo o loo iai e faaaogaina e pese ai viiga i le Atua, i le suafa o Iesu, Amene.  

Albánie není na prodej – zní z ulic balkánské země. Od června tam lidé vycházejí pravidelně do ulic na protest proti plánovanému projektu luxusních resortů zetě amerického prezidenta Jareda Kushnera. Vlnu nevole mimo jiné vzbudil také rozhovor s jeho manželkou Ivankou Trumpovou, ve kterém popisovala, jak ostrov Sazan objevili. „Ona přijela na ostrov, který není zapomenutý. Tedy možná pro Američany jo,” říká novinářka Magdaléna Fajtová.

Subscribe on Patreon and hear this week's full patron-exclusive episode here: https://www.patreon.com/deathpanelpod/posts/acap-06-philly-161158245 Beatrice speaks with Ona, Renya, and Zara from Philly Childcare Collective about their experiences engaging in mutual aid and survival work. Runtime 1:31:03 This is the sixth episode in a new series called All Care for All People (ACAP), as Artie describes in an introduction at the top of this episode. Over the coming weeks we will be speaking to people engaged in mutual aid survival programs, working across a variety of tactics, locations, and organizational structures, who are each stepping in, in different ways, to provide care where it is needed. MERCH STORE IS BACK! Patrons get a code for 10% off all orders. Find it at https://www.deathpanel.net/merch We're testing out a new Bookshop.org page (still under construction), where you can find books by past guests and book recommendations from the hosts. Find it here: https://bookshop.org/shop/deathpanel Show links: Get Health Communism here: https://bookshop.org/a/118130/9781839765179 Find Tracy's book Abolish Rent here: https://bookshop.org/a/118130/9798888902523

L'intelligenza artificiale entra in una nuova fase:non è più una semplice innovazione, ma una vera e propria infrastruttura strategica globale.In questa puntata analizziamo come miliardi di dollari stiano ridisegnando il futuro dell'AI attraverso data center, debito finanziario, nuove guerre tecnologiche e sfide geopolitiche.Approfondiamo inoltre il crescente peso dei costi computazionali per le aziende, la corsa all'autonomia infrastrutturale di Stati Uniti e Cina, i rischi informatici emergenti e le prime sentenze che ridefiniscono la responsabilità legale dei sistemi di intelligenza artificiale.Un episodio dedicato a imprenditori, manager e professionisti che vogliono comprendere le dinamiche che stanno trasformando il mercato e prepararsi ai cambiamenti che influenzeranno il business dei prossimi anni.  In questa puntata scoprirai:Come Big Tech stanno investendo centinaia di miliardi nelle infrastrutture AI.Perché il costo dei token sta cambiando i bilanci aziendali.Le nuove tensioni geopolitiche sui semiconduttori e sulla sovranità tecnologica.I rischi di cybersecurity e le implicazioni legali dell'AI generativa.Perché la governance e la supervisione umana saranno il vero vantaggio competitivo.Un appuntamento dedicato a imprenditori, manager e professionisti che vogliono comprendere come l'intelligenza artificiale stia trasformando il panorama economico e tecnologico mondiale. In collaborazione con Claudio Ricci, Amministratore unico di Recomb, una realtà specializzata nel fornire aggiornamenti personalizzati alle organizzazioni orientate all'innovazione sugli sviluppi dell'intelligenza artificiale, oltre a offrire corsi di aggiornamento professionale Per maggiori informazioni: info@recomb.aiFonti principali:Yahoo Finance – Data center di Anthropic e acquisizione di Ona da parte di OpenAI.Yahoo Finance – TechnologyReuters – Debito globale legato all'AI e grandi investimenti infrastrutturali.Reuters Business & TechnologyThe Wall Street Journal – Analisi sui costi dell'AI per le imprese e sui modelli di business del settore.TechCrunch – Report sulla spesa delle aziende per gli strumenti di intelligenza artificiale.TechCrunchTom's Hardware – Impatto ambientale e consumo di risorse dei nuovi data center AI.Tom's HardwareThe Information – Strategie industriali e accordi tra Big Tech per la produzione di chip AI.The InformationKorea Times – Google e Samsung collaborano sui chip AI di nuova generazione.Korea TimesBloomberg – Geopolitica dei semiconduttori e piano cinese per l'infrastruttura AI.CNBC – Crescita degli attacchi informatici contro le aziende tecnologiche.CNBC404 Media – Analisi dell'attacco alla supply chain che ha coinvolto repository Microsoft.404 MediaArs Technica – Sentenza sulla responsabilità legale delle AI per contenuti generati.Ars Technica

The celebration energy from last week isn't over — but this week adds a layer you're going to want to know about.The cards are highlighting:Why some information still hasn't fully come to light yet — and how to navigate thatThe most emotionally evolved version of you that this week is calling forwardMore celebrations, gatherings, and invitations — with one important heads upSomeone in your orbit who may be more guarded than they're letting onA decision coming that requires you to be neutral, grounded, and really honest with yourselfYour intuition is your superpower this week. The question is — are you listening to it?Get Joy's Free "Sign Magnet" 3 Day Mini Course HERE https://www.joyfulmedium.com/sign-magnetJoy's Website: www.joyfulmedium.comInstagram: @JoyfulMediumTikTok: @JoyfulMediumFacebook: @JoyfulMediumFacebook Group: Joy's Soul SpaYouTube: Psychic Medium Joy Giovanni 

OPEN HEAVENSMATALA LE LAGI MO LE ASO TO'ONAI 13 IUNI 2026(tusia e Pastor EA Adeboye) Manatu Autu: Mativa e lē tutusa ma le amio Atua (Poverty is not equal to godliness) Tauloto Tusi Paia: 3 Ioane 2 “Le pele e, ‘ia e manuia i mea uma, ma ‘ia e mālōlō, fa‘apei ‘ona manuia o lou agaga.”Faitauga - Tusi Paia: 2 Tupu 4:1-7I le fitusefulu, ina ua fa'aolaina lo'u olaga, sa talitonu le toatele o kerisiano o le mativa o se tasi lea ta'iala mo le avea o se atalii poo le afafine moni o le Atua. Sa malosi tele lenei talitonuga ma ina ua fai meaalofa mai se tasi ia te a'u i se Mercedes-Benz, sa ou teuina i totonu o lo'u fale taavale e lē fa'aaogaina mo ni masina seia o'o ina fetalai le Alii ia te a'u, o lo o o'u taofiofia faamanuiaga a le tagata na foaiina le taavale mo a'u I lo'u lē fa'aaogaina o le foa'i. Sa ou fefe nei faapea tagata ua toe fo'i i tua lo'u olaga pe afai e vaai mai ia te a'u i lenei taavale taugata. Ona o le fetalaiga a le Alii ia te a'u, na o'u filifili ai ou te tietie ma fa'aaogā le taavale, tau lava o le faa tasi, ma ou te manatua sa matua'i lagona lo'u mā i lea aso. Ina ua uma lea aso, sa ou faapea atu i le Alii, “Le Alii e, ua o'u tietie i le taavale, e mafai ona o'u faatauina ese loa?” Na finagalo i ai le Alii ma sa ou faatauina ese loa. E le'i umi ae aumai e se isi se taavale limousine ono faitotoa mo a'u. Ina ua o'u vaai atu i le taavale sa ou faapea, “Le Alii e, e te silafia e tusa pe latou te tuuina lo'u tino maliu i totonu o lenei taavale e toe oso mai lava I fafo.” O le tele lea o lo matou manatu o le mativa e tutusa lelei ma le amioatua I na aso, ma ona o lea na faasesēina ai I matou e le tiapolo. Na siitia e le tiapolo tagata e pulea kamupani ma fale gaosimea seia o'o ina alofaina kerisiano e tagata amio leaga o loo faagaioia tamāoaiga eseese i le lalolagi. E leai se mea amioatua faatatau i le mativa, ua i'u ai le toatele o tagata i Seoli, faapei lava ona faia e le mauoa. O le mativa ua mafua ai ona filifili le toatele o tupulaga talavou e lē mulimuli i ala o latou matua kerisiano ona o aafiaga leaga a'o tutupu a'e. Ua mafua ai ona ula tagata o le lalolagi i le Atua mata'utia auā ua o latou manatu ua valea kerisiano ona o lo latou naunau i lenei Atua. I le faitauga mai le Tusi Paia o le asō, o se tasi o le ‘auso'o o Elisaia, na oti i le mativa ae tu'u se tofi o aitalafu mo lona aiga. A na lē sulu lana avā iā Elisaia ma maua ai le upu a le Alii na liliuina lo latou mativa i le tamāoaiga, sēmanū e ola a'e ona atalii e toalua i se olaga pologa ma inoino i le Atua e ui o lo la tamā o se tagata sa amioatua. E lē mativa le Atua (Hakai 2:8), o lona uiga o le mativa e lē mai le Atua. E avatu e le Atua i lana fanau le malosi e maua ai le tamāoaiga (Teuterenome 8:18;) ma o lona finagalo ia manuia i latou faapei ona manuia o latou agaga (3 Ioane 1:2). Le au pele e, tete'e le mativa! e lē o le finagalo lenā o le Atua mo lou olaga. E leai se amioatua i le mativa, i le suafa o Iesu, Amene.

SpaceX startet mit einem ordentlichen Pop in den Handel. Tausende Mitarbeiter werden zu Millionären, Founders Fund und Andreessen Horowitz vermelden Rekord-Returns. Anthropic launcht Fable 5 und das Mythos-Modell für Testpartner. OpenAI plant laut Wall Street Journal drastische Preissenkungen für den User-Krieg mit Anthropic. China plant $300 Mrd. für nationalen KI-Ausbau über fünf Jahre. Xiaomi MiMo Code schlägt Claude Code in den gängigen Benchmarks. OpenAI übernimmt das Kieler Startup ONA, Mistral kauft das Linzer Emmi AI für eine Industrie-KI-Plattform und verhandelt selbst eine $20-Mrd.-Bewertung. Dario Amodei mit neuem Essay zur AI-Exponential-Politik. Oracle Earnings, Prometheus von Jeff Bezos bei $41 Mrd. Die Trump-Familie hat $2,3 Mrd. mit Krypto eingestrichen. Palantir verliert vor dem Zürcher Handelsgericht gegen die Zeitschrift Republik. Neura Robotics raised $1,4 Mrd. mit Tether als Lead. Landgericht München: Google haftet für seine AI-Overviews.  Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) SpaceX-IPO (00:08:04) Mitarbeiter-Millionäre (00:11:51) OpenAI/Anthropic-IPO-Outlook (00:15:31) Elon-Puppe vor der Nasdaq (00:16:13) Anthropic Fable 5 & Mythos 5 (00:19:54) OpenAI Preiskrieg (00:27:27) Token-Wert pro Abo (00:30:30) Messi für ChatGPT (00:34:48) China $300 Mrd. KI-Plan (00:37:31) Xiaomi MiMo Code (00:39:46) OpenAI kauft ONA (00:42:54) Anthropic: AI Exponential Policy (00:46:53) Oracle Earnings (00:48:07) Mistral kauft Emmi AI (00:49:08) Prometheus von Bezos (00:50:48) Trump Phone (00:51:22) Waymo Premier (00:55:40) Google Trade-Worker (00:57:08) Anthropic Claude Corps (00:58:37) Trump-Krypto-Scam (00:59:35) The Platform Group (01:03:48) Palantir vs. Republik (01:05:48) Mistral $20 Mrd. Runde (01:07:07) Neura Robotics Series C (01:10:47) NYT: China und Robotik (01:13:19) Google haftet für AI-Overviews Shownotes SpaceX-IPO zieht $70 Mrd. an Retail-Orders - bloomberg.com Founders Fund + Andreessen: Rekord-Returns aus SpaceX-IPO - bloomberg.com SpaceX Proteste - xcancel.com Anthropic launcht Claude Fable 5 & Mythos 5 - wired.com OpenAI plant drastische Preissenkungen für User-Krieg mit Anthropic - wsj.com Bitte manuell prüfen (petergostev-Post) - xcancel.com SemiAnalysis - xcancel.com China plant $295 Mrd. für nationalen KI-Ausbau - bloomberg.com ONA: Kieler KI-Startup raised - linkedin.com Anthropic: Policy on the AI Exponential - anthropic.com Oracle Q4 Earnings - cnbc.com Mistral übernimmt Emmi AI für Industrie-KI-Plattform - handelsblatt.com Prometheus: Bezos' Industrial-AI-Startup - axios.com Teardown: Trump Phone ist HTC U24 Pro in Gold - de.ifixit.com Waymo launcht Loyalty-Programm mit 10% Cashback - techcrunch.com Google launcht Trade-Worker-Initiative für KI - axios.com Daniela Amodei startet Anthropics Claude Corps - apnews.com Xiaomi MiMo Code schlägt Claude Code bei 200-Step-Tasks - venturebeat.com Trump-Crypto-Playbook: Family wins, Investors don't - reuters.com The Platform Group - manager-magazin.de Einstweilige Verfügung: The Platform Group vs. Manager Magazin - lhr-law.de Palantir - ft.com Mistral verhandelt $20 Mrd. Bewertung - bloomberg.com Bitte manuell prüfen (dreger-Post) - linkedin.com Neura Robotics schließt Rekord-Series-C - neura-robotics.com Chinas Humanoid-Robot-Schub - nytimes.com Deutsches Gericht: Google haftbar für AI-Overviews - thenextweb.com

OPEN HEAVENSMATALA LE LAGI MO LE ASO TOFI 11 IUNI 2026(tusia e Pastor EA Adeboye) Manatu Autu: E lē taofia le Atua e le alofa (Love should not hinder God) Tauloto Tusi Paia: Mataio 16:23 “Ona fāliu atu lea o Iesu, ‘ua fa‘apea atu ‘iā Peteru, “Satani e, ‘inā alu ia oe i o‘u tua, ‘ua fai oe ma mea ‘ou te tausuai ai; auā e lē o mea a le Atua ‘e te loto i ai, a o mea a tagata.”Faitauga - Tusi Paia: 1 Samuelu 17:26-31Ia Tesema 2018, sa ou malaga atu e auai i se tasi o matou polokalame faa evagalia e masani ona ou auai ai. O le leaga ia o auala peitai ou te lei faatagaina e avea ma faalavelave ia te au aua ua ou masani i le leaga o auala. Peitai ua sili atu ona leaga auala i lea tausaga, ma e oo atu i le aso lona tolu o le polokalame, ua matua vaivai atoa lou tino, ma e oo atu i le kerisimasi, ua ou taoto. Ina ua oo i le taimi ou te toe foi ai i le Redemption city, sa matuā vaivai lou tino, ua lē mafai ona ou toe malaga i le auala. O lea na saunia se helikopa ou te malaga ai. Ina ua taunuu le helikopa, ua lolofi atu iai le motu o tagata, ma ua faigata ona ou alu atu iai. Na o atu le matou aufaigaluega ma avatu au i le helikopa, peitai ua faigata ona tuua le nofoaga, ona o loo pipii iai le toatele o tagata, ma iu ina ta'e le tiaoata o le vaalele. I le viiga o le Atua, na ou sao mai i lea tulaga ma taunuu ma le saogalemu i le fale. E iai taimi, o tagata e alolofa ia te oe, e manatu o loo latou faia ni mea mo lou lelei, peitai, e te tigaina ma leaga atu ai, i latou mea o loo faia, ae lē mo sou lelei. O tagata na lolofi atu i le helikopa e pei ona ou faamatalaina, e lei faapea na naunau ou te lavea ai. Na ō atu ona o le alolofa ia te a'u, ae latou te lei iloa o latou mea na faia semanu e ono aafia tele ai a'u. I le faitauga o le Tusi Paia o le asō, sa taumafai Eliapo e puipui ia Tavita aua o ia o le uso matua. E lei aoaoina Tavita o se fitafita ae o lea ua ia lui i le fitafita ua lava le tomai i taua. Ana o oe o Eliapo, e te ono faia mea uma e taofia ai Tavita mai le tau ma Koliata. Peitai e ui e lelei lona manatu, o ana gaoioiga semanu e taofia Tavita mai le faataunuuina o le faamoemoega o lona olaga.Le au pele e, e tatau ona e faaeteete ia e iloa pe afai o loo gaioioi mai  lou aiga i se tulaga e taofia ai lou faataunuuina o le faamoemoega o lou olaga. I le Mataio 16:21-23, o Peteru lea faatoa maea folafola o Iesu o le alo o le Atua, ua ia amata ona tetee atu i lona matai ,i le taimi na amata talanoa ai i lona maliu. E mautinoa e alofa ia Iesu, peitai, toeitiiti lava avea o ia, ma maa faalavelave i le Alii i le ausia ai, o lona faamoemoega i le lalolagi. Ou te tatalo e fesoasoani atu le Atua e iloa poo gaoioiga a e pele ia te oe o loo taofia le finagalo o le Atua mo lou olaga. Tau ina ia foai atu le malosi ma le loto toa e te lē talia ai a latou upu ma taga e taofia oe mai le faia o lona finagalo, i le suafa o Iesu. TataloTamā, faamolemole fesoasoani mai ia te a'u ia ou iloa pe afai e lē manatu lo'u aiga i lou finagalo e tusa ma lo'u olaga, i le suafa o Iesu, Amene. 

Dragi prijatelji, jubilarna 400. epizoda podkasta pod zaštitom Međunarodnog PEN centra, "Dobar loš zao", je tu! U prvom delu emisije, koja je protekla u radnoj i svečanoj atmosferi, Nenad Kulačin i Marko Vidojković bavili su se Sisolinijevim tivatskim lažima, evropskom antiperspektivom Srbije, patrijarhom iz kanalizacije i kosovskim izborima. Gošća je suspendovana profesorka sociologije u Jovinoj gimnaziji u Novom Sadu, politička zatvorenica i jedna od dobitnica ovogodišnje nagrade "Borka Pavićević" za javni gest, Marija Vasić. Ona je govorila o situaciji u gimnaziji, strategijama da se borba (koju sigurno dobijamo) izdrži, ali i malim šansama da za naših života dođe do istinske promene u srpskom društvu. Ovo ni izdaleka nije sve. Profesorka Vasić je govorila i o svojim zatvorskim cimerkama, pravu studenata da budu nacionalisti i opozicije da se kandiduje na izborima, a zapaženu ulogu su i ovaj put imala pitanja sa Patreona. U Magarećem kutku ćete imati priliku da čujete Konjdiloma kako laže. Da bi DLZ opstao, pretplatite se na patreon.com/ucutatinecemo a možete poslati i jubilejsku poklon-donaciju na PayPal ucutatinecemo@gmail.com. Na isti mejl možete poručiti DLZ merch, kao što je hit majica "DLZ ČALE".

174. Bu mektûb, hâce Muhammed Eşref-i Kâbilîye yazılmışdır. Bu yolun şaşkınları, uzaklık görünen yakınlık ve ayrılık sanılan vuslat ararlar. Yazılan rü'yânın cin te'sîri ile olduğu bildirilmekdedir: “Kıymetli kardeşimin güzel mektûbu geldi. Fakîrleri sevdiğinizi ve bu yüksek insanlara sığındığınızı bildirdiği için, bizleri çok sevindirdi. (Kişi sevdiği ile berâberdir) hadîs-i şerîfi, büyük müjdedir. Fekat, bu yolun âşıkları, bu kadarla doymazlar. Yakınlık görünen uzaklıkla sevinmezler. Uzak görünen bir yakınlık ve ayrılık görünen bir kavuşmak ararlar. İşin gecikdirilmesine, sonraya bırakılmasına râzı olmazlar. Tenbelliği, gericiliği çirkin bilirler. Kıymetli dakîkaları, yaldızlı pislikler için elden kaçırmazlar. Ömür sermâyesini, sonu gelmez hayâller arkasında geçirmezler. Yüksekleri bırakıp, alçaklara bakmazlar. Beğenileni verip, gadab olunanı, kızılanı almazlar. Tatlı yağlı yemeklere aldanmazlar. İnce, süslü elbise için, Allahü teâlâya kulluk zevkıni vermezler. Hükümdârlık koltuğu gibi olan kulluğu, pislik gibi olan dünyâ bağlılığı ile kirletmekden utanırlar. Allahü teâlânın mülkünde, memleketinde, Lât ve Uzzâ putlarını Ona ortak yapmakdan hayâ ederler. Kardeşim! Bu makâmda, hâlis din isterler! Zümer sûresinin üçüncü âyetinde meâlen, (Biliniz ki, Allahü teâlâ, ancak hâlis dîni beğenir) buyuruldu. Ortaklık tozunu bile kondurmak istemezler. Zümer sûresinin altmışbeşinci âyetinde meâlen, (Eğer Allah'a ortak koşarsan bilmiş ol ki yaptıkların boşa gidecek ve mutlaka hüsrana uğrayanlardan olacaksın!) buyuruldu. Bir ân, kendinizi düşününüz! Eğer, ortak katılmamış bir dîniniz varsa, size müjdeler olsun! Eğer böyle değilse, başınıza belâ gelmeden önce çâresine başvurunuz! Yazdığınız rü'yâ, cin görünmesidir. Onun boş işleridir. Cinnin böyle, bozuk işleri, tâliblerde çok görülmekdedir. Buna hiç üzülmeyiniz! Nisâ sûresinin yetmişbeşinci âyetinde meâlen, (Şeytânın aldatması, elbette zayıftır) buyuruldu. Eğer yine gelirse, (Kelime-i temcîd) okuyunuz! Ya'nî, (Lâ havle ve lâ kuvvete illâ billahil'aliyyil'azîm) deyiniz! Bunu okumak, cinleri dağıtır, kovar. Doğru yolda bulunanlara ve Muhammed Mustafânın izinde gidenlere selâm olsun “aleyhi ve alâ âlihissalevâtü vetteslîmâtü etemmühâ ve ekmelühâ” Yüce Allah, Kur'ânda, Hazret-i Nûh'un ağzından şöyle buyuruyor "Yâ Rabbî! Beni, ana-babamı, imân etmiş olarak evime girenleri mü'min erkek ve kadınları affeyle..." (Nûh sûresi, âyet: 28). Yine Yüce Allah, Hazret-i İbrahim'in ağzından şöyle buyurmuştur: "Ey Rabbimiz! Hesab görüleceği gün, beni, ana babamı ve mü'minleri affeyle." (Ibrahim sûresi, âyet: 41) Rabbenağfirlî duasını bellet çocuğuna… Öldükten sonra onun sırtından geçinirsin, kurnaz ol. Abdullah ibni Mesut'un karısı kocasını şikayete peygamberimize geldi. Bütün gece namaz kılıyor benim kocam dedi peygamberimiz aleyhisselam dedi ki ben onla konuşacağım. Abdullah gecenin üçte birinde ibadet yap üçte birinde dinlen üçte birinde ailenle ilgilen. İslam bir denge dinidir bütün aşılıcılıklardan bizi men eder iki aşırı kavim bize bir örnektir Yahudiler ve hristiyanlar. Örnek olarak bacaklarını acmazsan yürüyemezsin ama bacaklarını gereğinden fazla açarsan yine yürüyemezsin düşersin Allah her şeyi dengede yapmamızı istiyor. Tövbe yapacaksın ama nasuh tövbesi yapacaksın. Nasuh tövbesi mutlak butlan gibidir. Tam bir geriye dönüş temizliğe dönüş Yani siz bir dinsizden merhamet mi ararsınız ben size bir ateistim merhamet kapasitesini yaşanmış bir olayla anlatacağım: Bir kardeşim anlattı 11:12 yaşlarında okulda sınıfına girerken parmağını kapıya kaptırıyor ve parmak kesilince kanamaya başlıyor. Çocuğun da en sevdiği öğretmen ateist ve eşcinsel hem ateist hem eşcinsel. Yani zebaniler ellerindeki listeye baktığında kafaları karışacak ya hem ateist hem eşcinsel cehenneme atacağız da ya Rabbi hangisini atacağız kafaları karışacak. Öğretmene gidiyor diyor ki hocam parmağım kanıyor yardım eder misiniz? Öğretmeni şöyle cevap veriyor “ayy minik bir kedi miyav dedi, git bir bardak su iç geçer.

31.Sohbet“Yapılan öfke, Allah için olursa iyi sayılır. Başka sebeplerle duyulan öfke iyi sayılmaz. İman sahibi, hiddetini Allah'ın emri olmadan göstermez. Nefsi için hiçbir hiddete kapılmaz. İslâm dininin zaferi için hiddet eder; fakat nefsin arzusunu yerine getirmek için sertleşmez. İman sahibi, dinî emirlerin biri zedelenecek olursa sonsuz hiddete kapılır; onun hiddeti şiddetlidir. Evi elinden alınan bir kaplan, belki onun kadar hiddete gelemez. Şüphesiz, Allah Teâlâ da öfkelenir. İman sahibinin öfkesi, ilâhi öfkeye benzer. İmanı bütün olan Yaratan'ın darıldığı şeylere darılır, hoşlandığı şeylerden hoşlanır, sevinç duyar. Aslında nefsin için olan, fakat dışta Allah için olduğu görülen hiddeti etme. Sonra münafık olursun. Münafık olmasan bile benzersin. Allah için olan şey devamlı, ömürlü olur. Başkası için yapılacak hiddet az zaman durur, sonra geçer. Varlığını Hak yoluna vakfeden kimselerle ol. Onların kuvveti ile kuvvet bul. Görüşlerini onların görüşlerine uydur. Bunları yaparsan Yaratan, onları övdüğü gibi seni de över. Seni meleklere metheder. Daha başka tabirle, seninle övünür. Her şey zıddından ve sevmediği şeyden kaçar. Kuvvetler çeşitlidir. O zıtlar arasında kudsî kuvvetler ve onun karşısında kudsî olmayan kuvvetler vardır; sana düşen ilâhî kuvveti alıp aksini bir yana atmak. Varlığını Hak varlığı ile doldur. O kudsî varlığı yitirirsen, hiçbir şey bulman kabil değildir. Görürsün. Sonra yine O'nu görürsün. O'nun dışında varlık görmek mümkün olmaz. Yeter ki, varlığını temizlemen kabil ola. Neler görmezsin ki? Ancak temizlik şarttır. Bir padişahın katına dış pisliği ile girilmediği gibi mukaddes varlığa da derûnî kirle girmek mümkün değildir. İçin boşalmış, orayı aç kurtlar doldurmuş. Seni neylerler? Ruhunda bir inkılâp yap, temizle. Ancak bundan sonra şahın katına girebilirsin. Hak yakınlığı dehşet verir. Şayet bir dehşet duymuyorsan, sakın O'nun yakınlığından dem vurma, sonra yalancı olduğunu yüzüne vururlar. Kulların işiyle gönlünü eğlendirmektesin. Onların sana gelip el öpmelerini bekliyorsun. Onlar gelip bir şeyler versinler diye kapıda bekliyorsun. İstediğini yerine getirmedikleri zaman üzüntü duymaktasın. Övülünce yüzün gülüyor. Kötülüğünü söyleyen olursa yüzün buruşuyor. O büyükler Hak varlığında sakin olurlarsa, imanları artar. Kullara güvenir, onların geçici metalarına koşarlarsa perişan olurlar, imanları kuvvetten düşer. Ama onlar hiçbir zaman yaratılmışlara dayanamazlar. Yaratan'larına güvenirler, O'na tevekkül ederler. İstinat noktaları Hak'tır. O'ndan korkarlar. Bir şey bekleyecek olurlarsa yine O'ndan beklerler. Çünkü er geç gidecekleri yer orasıdır. Tevhid ehlidirler. Şirk yolunu bilmezler bile. Düşkün oldukları hâl budur. Tevhidleri kalplerinde yer etmiştir. Halkla sohbet eder, iyi geçinirler. Kendilerine karşı bir cahillik eden olsa onunla bir olmazlar. Hak Teâlâ onların bu vasfını şöyle anlattı: “Cahiller onlara söz attıkları zaman, selâm derler.” (el-Furkân, 25/63) Sus; cahillere yumuşak davran. Cahil kişinin yanlış hâli seni üzmesin. Onların tabiatında mevcut olan huysuzluk yüzünü buruşturmasın. Nefis ve şahsî arzularının sapık tezahürü seni üzmesin. Ama bir günah işledikleri zaman da susma, konuş. Hatalı işlere karşı susmak yasaktır. O zaman konuşmak ibadet sayılır. Gücün yeterse, iyiliği yaptır. Kötülüğe mâni ol. Bu babta kusurlu olma. O kapı bir hayır kapısıdır. Kendin için bir ganimet bil, içeri girmeye bak. Dünyanın ömrü nedir? Nimeti ne kadar sürer? Bir gün mevcut olan güzel hâli, ikinci gün oluyor mu ki? İman sahibi bunları iç âleminde sezer. Dünya çirkin huyludur. Elinde karası bulunur. Her sözü zehir taşır. Tadı hemen gider. Ve bir daha dönmez. Hiçbir vaadinin aslı çıkmaz. Ahdine vefa etmez. Ona güvenip üstünde köşkler kurmak, su üstünde ev yapmaya benzer. İman sahibi dünyayı tutmaz. Onda yerli olmayı aklına koymaz. Bu sebeple derecesini artırır. Hak irfanına sahib olur. Mahlûk şeyleri sevmez. Bu yüzden öbür âlemi de istemez.

CELÝ ROZHOVOR V DÉLCE 54 MIN. JEN NA ⁠HTTPS://HEROHERO.CO/CESTMIR⁠⁠⁠⁠ A ⁠HTTPS://FORENDORS.CZ/CESTMIR „Neumím moc hovořit ve frázích,“ říká spisovatelka a moderátorka Halina Pawlowská, když mluví o tom, proč se z jejích bonmotů, knih, časopisů i televizních pořadů stal fenomén, který lidem zůstává v hlavě i po letech. Sama říká, že v jejích textech není „vata“, protože se k věcem dostává přes příhody, názor a pointu. A právě pointy podle ní stály i za slavnými radami z Banánových rybiček. „Nejtěžší v té radě je si říct ideově, co chci říct. A pak už hledám slova,“ vysvětluje. V rozhovoru se vrací k začátkům, k FAMU, k televizi i k tomu, že věci v jejím životě podle ní často vznikaly přirozeně. „Mě nic nehnalo,“ říká. „Dost mi to všechno šlo,“ dodává se smíchem, když mluví o práci, která se postupně rozrostla do 42 knih, televize, rozhlasu i časopisů. Mluví ale i o dětství, ve kterém ji matka nikdy nechválila. „Ona mě vždycky kritizovala a pochybovala o mě,“ říká Pawlowská a dodává, že doma se vlastně nechválí dodnes. Silně do rozhovoru vstupuje i její ukrajinská rodinná historie. „U nás byla hlavní téma svoboda Ukrajiny,“ říká a popisuje, že otec v Rusku vždy viděl obrovské nebezpečí. Když dnes slyší, jak část společnosti mluví o Ukrajincích, bolí ji to. „Někdy se stydím za to, co slyším,“ říká. Pawlowská mluví také o vážných zdravotních problémech, po kterých si musela připomenout, že má zvládnout žít. Popisuje, jak měla plicní kolaps a od té doby si život víc dávkuje, i když přiznává, že pořád nerada říká ne. „Teď je to pomaloučku, polehoučku,“ shrnuje svůj současný režim. Do rozhovoru ale výrazně vstupuje i smrt. Pawlowská říká, že v životě viděla tři své blízké lidi umírat - rodiče a manžela. Otec zemřel doma, manžel také, s maminkou byla hospitalizovaná na pokoji v nemocnici. „Byla jsem překvapená z toho, jak je ta smrt jednoduchá,“ říká. I proto dnes má ze samoty a umírání obavy. Na otázku, jestli vztah s manželem vydržel díky práci, ale odpovídá jednoduše: „Já myslím, že jsme spolu vydrželi, protože to byla láska.“ A mluví také o sexismu, který dřív neuměla pojmenovat. „Sundejte si kabát, ať vidíme, jaký máte talent,“ cituje větu, která se jí zaryla do paměti a dodává, že zpětně ji štve, co všechno musela vydržet. Přesto se i z bolestných situací často staly příběhy. „Potom jsem z toho většinou napsala nějakou povídku,“ říká. Proč se Halina Pawlowská bojí samoty víc než popularity? Jak se z ponížení, strachu a smutku stává humor? Co jí nemoc změnila v pohledu na život a proč by dnes byla podle svých slov mnohem větší feministka? Poslechněte si celý rozhovor.

Marshall Softball All-American Sydni Burko joins me on this episode of The ThunderCast for a conversation about one of the greatest individual seasons in program history, her decision to come home and transfer to Marshall, and why the future of Herd Softball may be even brighter than its present. In 2026, Burko was named the Sun Belt Conference Player of the Year and Sun Belt Conference Newcomer of the Year while earning All-American honors and setting Marshall's single-season home run record with 24 home runs. She led the Sun Belt in home runs, OPS, and slugging percentage while finishing among the conference leaders in RBI, hits, and batting average. But this conversation isn't just about statistics. We talk about why a player who grew up just down the road from Marshall chose to come home, what made this year's team so special, playing for fellow Ona native Morgan Zerkle, and the culture that's helping transform Marshall Softball into one of the premier programs in the Sun Belt. Sydni also shares her thoughts on the future of the program, the returning talent that has Marshall fans excited, and why this team feels like it still has unfinished business heading into next season. And of course, we wrap things up with some fun rapid-fire questions covering teammates, music, food, Marshall traditions, and more. If you're a Marshall Softball fan, this is a conversation you won't want to miss. There is a lot of excitement throughout the Herd Universe right now, and after listening to Sydni talk about where this program is headed, you'll understand why. Topics Include: Why Sydni transferred to Marshall Coming home to West Virginia Setting Marshall's single-season home run record Sun Belt Player of the Year & Newcomer of the Year Marshall Softball's team culture Playing for Morgan Zerkle Returning talent for 2027 The future of Marshall Softball Rapid Fire Questions 2026 Stats ⚾ 24 Home Runs (#1 Sun Belt) ⚾ 1.342 OPS (#1 Sun Belt) ⚾ .854 Slugging Percentage (#1 Sun Belt) ⚾ 48 RBI (#3 Sun Belt) ⚾ 66 Hits (#4 Sun Belt) ⚾ .386 Batting Average (#5 Sun Belt) #GoHerd #MarshallSoftball #MarshallAthletics #ThunderCast #SydniBurko #SunBelt #CollegeSoftball #NCAAsoftball

OPEN HEAVENSMATALA LE LAGI MO LE ASO SA 31 ME 2026(tusia e Pastor EA Adeboye) Manatu Autu: Faalagolago tau o le Leoleo Mamoe Lelei  (Depend Only On The Good Shepherd) Tauloto Tusi Paia: Ioane 10:10 “O le gaoi, e leai se tasi mea e sau ai na ‘ona ia gaoi, ma fasi, ma fa‘aumatia; ‘ua ‘ou sau ‘ina ‘ia latou maua le ola, ‘ia maua atili ai lava.”Faitauga - Tusi Paia: Salamo 37:3-7Na folo e se tagata se tapui (mea faataulaitu) sa faapea e avea ai ia ma mauoa, peita'i na tumau pea le mativa, e le'i mauoa. E le gata i lea, na logoina ia o le a maliu pe a mavae le fitu tausaga ona o le tapui ua ia folo. Ina ua toe lua vaiaso na totoe e ola ai ma ua sioa atu le oti i ona fofoga, na tamoe mai i le RCCG. Ina ua ia faamatala mai ia i matou lona puapuaga na o matou ta'u i ai, o lo matou Atua o le lavea'i sili. Na ia ofo lona ola mo Keriso, ma ina ua o matou faia se tatalo puupuu mo ia, na ia pua'i mai i fafo le tapui sa ia foloina (tulou). Na toaga mai i le lotu mo le lua vaiaso, olioli ona o le fa'asa'olotoga na faia e le Atua mo ia. Ona faafuase'i lea ona le toe sau i le lotu. Ina ua o matou asiasi atu ia te ia na faapea mai, “Na ta'u mai e le tagata taulasea fai vai na faia le tapui, ia te a'u, na sesē lo'u foloina o le tapui.” Na ia toe folo se isi tapui, ma o le taimi la lea, na matua'i mauoa lava ia. Na ta'u e le taulasea ia te ia o le a soifua pea mo ni tausaga se fitu e fa'aaogā ma fiafia i ana oa ma ina ua lata ina uma le taimi (fitu tausaga) na faafuasei ona maua sana togafiti poto. Na ia filifili e alu e nofomau i Lonetona ma lona manatu, o temoni na o Aferika e mafai ai ona galulue. Peita'i o le tala faanoanoa na maliu I luga o le vaalele. O lo'u tamā i le Alii, Pa Josiah Akindayomi e masani ona fai mai, “O le a tausia oe e lou tamā i soosemea o ia te ia. Afai o ia te ia le leaga, o le leaga lena na te fa'aaogā e tausi ai oe, afai o ia te ia lelei, o le lelei fo'i e te maua mai ia te ia.” O le tiapolo e leai ma se mea lelei o i ai; afai e te alu i ai i soosemea e te mana'o ai, ia e mautinoa poo le a lava na te avatu ia te oe, e leaga. Peita'i o Iesu, o ia o le leoleo mamoe lelei; soosemea na te aumai e mautinoa lava e lelei. E tusa ai ma le Tusi Paia faitau o le asō, o le faamoemoe ma le faalagolago i le Atua lou auala i lona agalelei. O i latou e faamoemoe iā Iesu o le a maua le mana e avea ai ma atalii o le Atua (Ioane 1:12). O le a ia i latou le pule i le malosi uma o le fili ma e leai se mea e afaina ai i latou (Luka 10:19). E leai se auupega a le fili e fa'asagatau ia te i latou e manumalō (Isaia 54:17) ma latou te aai i mea lelei o le laueleele (Isaia 1:19).Le au pele e, e te faamoemoe ea tau lava o le leoleo mamoe lelei? O i latou e faamoemoe ia te ia e faapei o le mauga o Siona. Poo le a lava le tulaga e o'o i ai, e lē fa'agae'etia i latou. Ia e fiafia lava oe i le Alii ona foaiina lea e ia ia te oe o mea e mana'o i ai lou loto (Salamo 37:4). I le suafa o Iesu, Amene.

171. Mektup Bu mektûb, molla Tâhir-i Bedahşîye yazılmışdır."Âlemlerin rabbi olan Allahü teâlâya hamd olsun. Peygamberlerin efendisine salât ve selâm olsun. Onun temiz Âline ve Eshâbının hepsine iyi düâlar olsun! "sallallahü teâlâ aleyhi ve alâ Âlihi ve Eshâbihi ecma'în".Biz fakîrlerin, Allahü teâlâya karşı aşağı, küçüklük düşüncesi içinde olmamız, herşeyi Ondan beklememiz, kalbi kırık, hep yalvarıcı ve Ona sığınıcı olmamız, kulluk vazîfelerini yapmamız, islâmiyyetin dışına taşmamamız ve sünnet-i seniyyeye sıkı sarılmamız lâzımdır. Hayrlı işler yaparken niyyetlerimizi düzeltmeliyiz. Kalblerimizi, dünyaya düşkün olmakdan kurtarmalıyız. Her uzvumuz islâmiyyete teslîm olmalıdır. Ayblarımızı görüp, günahlarımızın çokluğunu düşünüp, Allahü teâlânın intikâm almasından korkmalıyız. İyiliklerimizi az görmeli, günahlarımızı az olsa da, çok bilmeliyiz. Şöhret sahibi olmakdan, insanlar arasında iyi tanınmakdan çok korkmalı, titremeliyiz. Peygamberimiz "sallallahü aleyhi ve sellem", (Din veyâ dünyâ işlerinde iyi tanınarak parmakla gösterilmek, bir kimseye zarar olarak yetişir. Bu zarardan ancak Allahü teâlânın koruduğu kurtulabilir) buyurdu. İnsân, niyyeti ve işleri, ne kadar hâlis ve iyi olsa da, kendini kusûrlu ve kabâhatli bilmelidir. Tesavvuf yolunda, ele geçen ni'metlere, hållere, zevklere güvenmemeli, ne kadar doğru ve islâmiyyete uygun olsalar da, bunlara özenmemelidir. Dîne yapdığı hizmetlere, islâmiyyeti kuvvetlendirmesine ve insanların doğru yola gelmelerine sebeb olmasına güvenmemeli ve bunlarla övünmemelidir. Bu güzel işleri, kâfirler ve fâcirler de yapabilir. Resûlullah "sallallahü aleyhi ve sellem", (Çok olur ki, Allahü teâlâ bu dînini fâcir kimse ile kuvvetlendirir) buyurdu.Dînini öğrenmek, Allahü teâlânın rızâsına kavuşmak için gelenleri, arslan ve kaplan gibi zararlı bilmeli, bunun kendi harâblığına sebeb olmaması için çok korkmalıdır. Talebe gelince, kendinde sevinç duyarsa, bunu küfr ve şirk bilmelidir. Hemen tevbe, istigfår ederek bu sevinci gidermelidir. Onun yerine korku ve üzüntü yerleşinceye kadar uğraşmalıdır. Hele, talebenin malında gözü olmakdan, ondan fâide beklemekden çok sakınmalıdır. Böyle olursa, talebe istifade edemez ve pîrin harâb olmasına sebeb olur. Çünki bu yolda, yalnız hâlis din isterler. Zümer sûresinin üçüncü âyetinde meâlen, (Bilinmeli ki halis dindarlık yalnız Allah için olanıdır...) buyuruldu. Allahü teâlânın katında şirke hiçbir süretle yol yokdur. Kalbe gelen her sıkıntı ve karartı, tevbe, istigfâr ve pişmanlık ile ve Allahü teâlâya sığınarak, kolayca giderilebilir. Fekat, bu alçak dünyâ için gelen karartı, leke, kalbi büsbütün karartır, harâb eder. Bunu temizlemek çok güç olur. Resûlullahın "sallallahü aleyhi ve sellem", (Dünyaya düşkün olmak, günahların başıdır) hadîs-i şerîfi çok doğrudur. Allahü teâlâ, bizi ve sizi, dünyaya düşkün olmakdan kurtarsın! Dünyaya düşkün olanları sevmekden ve onlarla arkadaşlık etmekden, düşüp kalkmakdan korusun! Çünki o, öldürücü zehrdir ve iyi olmaz bir hastalıkdır ve büyük belâdır ve bulaşıcı hastalıkdır. Akıllı kardeşim şeyh Hamîd yanınıza gelmekdedir. Ondan işiteceğiniz yeni, tâze haberlerin kıymetini biliniz. Gerisini, buluşunca bildiririm."

Notes Fer-se petons, que hi hagi un bar a cada cantonada, dir "ja quedarem" i no acabar quedant mai... Fent classes amb alguns de vosaltres ens hem adonat de coses que us sorprenen quan veniu aquí. Per nosaltres formen part del dia a dia, però potser no són tan normals. En aquest episodi en comentem unes quantes. Som-hi! Vine al Campus d'Estiu aquest juliol i practica el català amb nosaltres! Campus Complet: inclou les activitats de conversa, el dinar i les activitats culturals Campus Bàsic: inclou només les activitats de conversa i el dinar (es pot complementar amb algunes activitats culturals individuals) Transcripció interactiva i vocabulari Fes-te membre d'Easy Catalan i tindràs accés a l'ajuda de vocabulari, la transcripció interactiva i el bonus de cada episodi: easycatalan.org/membership Bonus La conversa segueix amb algunes cosetes més que poden sorprendre a més d'un de vosaltres. Transcripció Andreu: [0:15] Bon dia, Sílvia! Sílvia: [0:16] Bon dia, Andreu! Com estàs? Andreu: [0:18] Molt bé. Avui que gravem és el dia després de Sant Jordi i… bé, aquest any no hem fet res especial, no?, per Sant Jordi. No hem fet cap concurs ni cap cosa, però… Sílvia: [0:29] No hem fet res especial. Però ja hi ha moltes coses especials que hem fet, perquè vam fer un vídeo molt interessant, un any que vam anar al Sant Jordi a Barcelona, que ens va quedar molt bonic, la veritat. Andreu: [0:40] Sí, i vam tenir sort també el temps, perquè recordo quan estàvem gravant el final del vídeo, dient que el temps havia aguantat i just mentre jo estava dient això, va començar a ploure. Sílvia: [0:55] Però vam tenir el temps literal de posar-nos a sota del balcó més pròxim abans de que caigués un aiguat…Te'n recordes? Perquè va ser com un xàfec, de cop, es van mullar tots els llibres de les parades, vull dir, tothom va quedar xop… i va ser com: "Mira, doncs per nosaltres no ha anat tan malament el dia". Andreu: [1:19] No. I ahir no va ploure, però com a mínim aquí a Barcelona, el que sí que va passar és que hi havia molt de pol·len o aquestes volves que fan els plataners. Sílvia: [1:30] Ah, sí! És típic. Andreu: [1:31] I que piquen molt, piquen a la gola i als ulls, i n'hi havia moltíssimes. Sílvia: [1:35] Sí. A més, de plataners n'hi ha a totes les ciutats, vull dir… és un arbre que es posava molt, abans. Andreu: [1:41] Sí. Que sempre m'he preguntat: "Per què es diu plataner si no fa plàtans?" Sílvia: [1:45] No ho sé, noi. Andreu: [1:48] En fi, ja ho investigarem. I com vau celebrar vosaltres Sant Jordi? Vau fer alguna cosa especial? Sílvia: [1:54] No, nosaltres el vam… entre cometes, celebrar el diumenge anterior, perquè van fer una fireta molt petitona al poble i vam comprar llibres i flors i... sí, el vam celebrar el diumenge. I llavors ahir va ser un dia de feina normal i corrent. Però bé. Andreu: [2:13] Clar, és que és això, que Sant Jordi és un dia laborable, és un dia feiner. Sílvia: [2:17] Sí, sí, totalment. Andreu: [2:18] Jo em vaig escapar un moment a la tarda per anar a veure l'ambient i comprar un llibre i després altre cop a la feina. Sílvia: [2:26] Clar. És el que toca. Andreu: [2:27] Però bé, dèiem que aquest any no hem fet res especial amb la comunitat, no?, que altres anys hem fet algun concurs o alguna cosa, però la comunitat no ha estat pas parada, aquestes últimes setmanes. Hem fet unes quantes activitats presencials. Per exemple, vam anar a una sessió de micro obert a Les Cosines, no?, una sessió de stand-up, amb el Joe, de la comunitat. Un altre dia vam anar al bar del Tradicionàrius amb la Neia i el Chris a jugar a l'Scrabble en català. Una altra nit vam anar al cine amb la Gaïd, el Silvestre i el Sigurd, i fa poc, bé, el dia de Sant Jordi, o sigui, ahir, hi va haver uns quants membres de la comunitat que es van trobar per anar a la Manifestació per la Llengua que van fer a Barcelona. O sigui, el Mike, la Fairlie i el Sigurd. Sílvia: [3:17] Molt bé, molt bé. Ja veieu que és una comunitat activa, no només escrivint a Discord, sinó que també es queda presencialment. Andreu: [3:26] I encara hi ha una activitat presencial molt important i molt xula que estem preparant, que és el pròxim Campus d'Estiu. Sílvia: [3:33] És divertidíssim, de veritat. No és perquè ho organitzem nosaltres, és que és la veritat. Vull dir, jo m'ho passo pipa durant aquella setmana, coneixent les persones que venen al Campus, passant tantes estones plegats, explicant-nos vivències i històries de la nostra vida, coneixent-nos els uns als altres… i millorant, perquè és que, de veritat, és una passada veure com evoluciona el nivell de les persones des de que arriben el dilluns fins que s'acaba el Campus el diumenge. Andreu: [4:04] És veritat. El dilluns encara… aquell dia la gent encara està una mica tímida i no vol parlar, perquè clar, costa arrencar, però després acabem la setmana, que tots xerrant allà… Sílvia: [4:15] Sí, sí. A més a més, la gent ja no se'n vol anar. No? Que el diumenge dius: "Adeu, adeu!", però no, és com que ja no vols, no? Ja no vols deixar-los, sí. Andreu: [4:24] Sí, aquesta ja serà la quarta vegada que fem el Campus. Sílvia: [4:27] Sí. Andreu: [4:27] És fort, eh?, dir-ho. Sílvia: [4:28] És molt fort, Andreu. Andreu: [4:30] Per mi, ja és com un dels grans esdeveniments de l'any. Sílvia: [4:34] Sí, totalment. Andreu: [4:35] Vull dir, és aquella setmana que és a finals de juliol, ja està marcada, sé que està reservada aquella setmana per fer el Campus. Sílvia: [4:43] Sí, oi tant. Penseu que és del dia 20 al dia 26 de juliol, tota la setmana sencera. Si entreu a la pàgina web, que és campus.easycatalan.org, hi trobareu tota la informació amb totes les activitats que farem, perquè és que no només fem activitats de parlar, sinó que ens en anem a visitar llocs. Per exemple, aquest any anirem a Tarragona, o farem tallers, farem un taller de trencadís de ceràmica. I moltes altres coses. Teniu tot tot tot tot ben explicat allà. Andreu: [5:12] I un altre pòdcast en directe, a la llibreria Ona. Sílvia: [5:15] Ai, sí, un altre. A veure com anirà, Andreu. Andreu: [5:18] Home, esperem que bé. Sílvia: [5:19] Bé, bé. Andreu: [5:20] No, anirà superbé! Doncs això, si voleu participar al Campus d'Estiu aquest any, entreu a campus.easycatalan.org i allà veureu que hi ha dues modalitats. La modalitat de Campus Complet, que ho inclou absolutament tot: les activitats de conversa, el dinar i les visites o activitats de la tarda, i el Campus Bàsic, que només inclou les activitats de conversa i el dinar. I, per tant, amb aquesta opció tindríeu les tardes lliures per, si voleu... Sílvia: [5:50] Descansar una mica. Andreu: [5:51] Descansar, dormir, el que vulgueu. Doncs això, teniu també l'enllaç a la descripció de l'episodi.

No programa de hoje, Renato e Cristiane Cardoso compartilharam o pedido de ajuda de uma aluna. Na oportunidade, ela disse que ama muito o esposo, com quem está casada há cinco anos. Contudo, ela não tem conseguido demonstrar isso a ele e, pior, até a relação íntima está difícil para ela. Os dois têm dois filhos e a aluna salientou que não quer perder o casamento. Uma outra visãoNa sequência, eles leram o agradecimento de uma aluna chamada Graziele. Ela disse que gostaria de agradecer a Deus pelo livro Namoro Blindado, pois, por meio dele conseguiu se livrar de um amor platônico de 20 anos. Isso porque só leu até a página 38, o que corresponde a dois capítulos. Hoje, enxerga o amor de uma forma inteligente. Ela imaginava que a vida dela fosse ser um romance como nos filmes. Ainda hoje, Talita, de 22 anos, disse que morou com um rapaz por um ano e eles têm uma filha que já está com três anos de idade. Os dois estão separados e a aluna gostaria de recuperar o relacionamento. Porém, ele não quer compromisso sério e só quer ficar. Talita por sua vez, quer constituir uma família. A aluna está sofrendo e não sabe o que fazer. Terapia do AmorPor fim, confira depoimentos de quem foi transformado através das palestras da Terapia do Amor. Participe todas as quintas-feiras, às 20h, no Templo de Salomão, no Brás, em São Paulo. Para mais locais e endereços, acesse terapiadoamor.tv ou ligue para (11) 3573-3535.Inclusive, nesta quinta-feira (14) acontecerá, às 18h, a Hora dos Solteiros no Templo. Esteja presente. Bem-vindos à Escola do Amor Responde, confrontando os mitos e a desinformação nos relacionamentos. Onde casais e solteiros aprendem o Amor Inteligente. Renato e Cristiane Cardoso, apresentadores da Escola do Amor, na Record TV, e autores de Casamento Blindado e Namoro Blindado, tiram dúvidas e respondem perguntas dos alunos. Participe pelo site EscoladoAmorResponde.com. Ouça todos os podcasts no iTunes: rna.to/EdARiTunes

Povodom Dana majki razgovarali smo sa Amelom Ademi, mladom bosanskom majkom sa istoka Melbournea. Ona uspješno spaja tri velike i zahtjevne životne uloge - majčinstvo, profesiju i aktivizam u bosanskohercegovačkoj zajednici. Kao majka troje djece i dugogodišnja aktivistica, Amela Ademi svakodnevno balansira između porodičnih obaveza, društvenog angažmana i borbe za vrijednosti u koje vjeruje.

Bu bölümde seyahat etmekle yurt dışında yaşamak arasındaki farkı konuşuyoruz. Bir ülkeyi turist olarak görmek gerçekten onu tanımak mı? İnsan hangi deneyimde daha çok değişiyor? Kendi deneyimlerimiz üzerinden “gezmek” ve “orada yaşamak” arasındaki çizgiyi tartışıyoruz. Interactive Transcript and Vocab Helper Support Easy Turkish and get interactive transcripts and live vocabulary for all our episodes: easyturkish.fm/membership Show Notes Sponsor Find your ideal Turkish teacher on italki: https://go.italki.com/turkish5 Use the code EASYTURKISH5 for 5€ off on your first lesson (of at least 10€) Podcast'te bahsi geçen videoyu buradan izleyebilirsiniz

OPEN HEAVENSMATALA LE LAGI MO LE ASO SA 10 ME 2026(tusia e Pastor EA Adeboye) Manatu Autu: Faamanuiaga e aunoa ma le tigā (Blessings without sorrow)Tauloto Tusi Paia: Faataoto 10:22 “O le fa‘amanuia a le ALI‘I, o lea e fa‘atamao‘āiga ai; na te lē fa‘aopoopo i ai se tigā.”Faitauga - Tusi Paia: Ioane 10:10Toatele tagata e manana'o e mauoa i soose tau, ma ona o lea, e taumafai ai pea le tiapolo e fa'aosoosoina i latou e fai so'ose ituaiga amioga agasala. O nisi o i latou e i'u lava ina maua le tamāoaiga o mananao ai, peita'i o lea ituaiga tamāoaiga e masani ona maua faatasi ma le tele o le tigā. Ua na o manuia o le Atua, e maua e aunoa ma le faavauvau e pei ona o tatou vaaia i le fuaiupu tauloto o le asō.O le tiapolo e lē taitai mana'o e maua e se isi se mea lelei. E mafai ona faafoliga le fili peiseaī e mana'o i le aupito sili ona lelei mo se uso, peita'i o ia o se faamatua o taufaasesē ma e le mafai ona ia avatu i se tagata se mea lelei. Pau le mana'o o le fili, e fiafia e gaoi soosemea ua tuuina e le Atua i lana fanau. Ua faailoa mai le tusi o Ioane 10:10 fuafuaga moni a le fili mo soose tagata, o le gaoi, fasioti ma faaumatia. A e paū atu i mailei a le tiapolo e fai le agasala, ua e faatagaina le fili e gaoi oe, fasioti ma faaumatia oe.I tausaga ua mavae na fai mai ai se tamaita'i o la'u vasega, ia te a'u, “Tamā ua ou maua se taulealea talavou e mana'o e faaipoipo ia te a'u.” Sa o'u fa'amālō ia te ia ae fai mai, “Leai! E i ai le faafitauli.” Ona ia faamatala lea faapea na faailoa atu e lona tamā na ia foaiina ia i se tiapolo, le agaga o le gataifale, ma afai ae fai sona toalua o le a oti o ia. Na fai atu fo'i lona tamā afai e le o ia e oti, poo ai lava le tagata e faaipoipo I ai o le a oti i le aso tonu o le faaipoipoga. Ona faapea mai lea o le tamaita'i ia te a'u, “O lea la ua fai mai le taulealea lenei ma te faaipoipo ma ou te manatu o le finagalo lea o le Atua ia ou faaipoipo atu ia te ia. Peita'i ou te lē mana'o ou te tali Ioe ia te ia ona ou te lē mana'o e fasiotia le taulealea e le tiapolo poo le agaga o le gataifale. O le a se mea e tatau ona ou fai?” Sa ou ata ma fai atu i le tamaita'i, “Ou te iloa le Tamā o agaga uma.” Ona ou tatalo lea o se tatalo faigofie i le suafa o Iesu ma fai atu i le tamaita'i, e alu e talia le talosaga a le taulealea. Lua tausaga mulimuliane a o ou i totonu o se falesa i Yaba Lagos, ae savali atu le tamaita'i lenei ia te a'u o loo ia sapai se pepe i ona lima ma fai mai, “Susuga e, e te manatua a'u?” Sa ou tali, “Ioe!” Sa o'u fesili ia te ia poo fea lana tane ma sa ia faasino i se taulealea aulelei. Pe ana lē sulufa'i lea tamaita'i ia Iesu, semanu e ola ai lava I saisaitiaga o le pologa o le fasiotia o tane uma e faailoa lo latou manana'o ia te ia.Le au pele e, o faamanuiaga a Satani e omai faatasi lava ma loli pusa sasa'a o le faavauvau. Peita'i a faamanuia oe e le Atua na te avatu manuia e faatamāoaiga a'i, na te lē faaopoopo I ai se tigā, I le suafa o Iesu, Amene.

OPEN HEAVENSMATALA LE LAGI MO LE ASO TOONAI 9 ME 2026(tusia e Pastor EA Adeboye) Manatu Autu: Mealilo o le soifua umi 6 (Secrets to longevity 6)Tauloto Tusi Paia: Esoto 16:30“Ona mālōlō lea o le nu‘u i le aso fitu.”Faitauga - Tusi Paia: Kenese 2:1-3 Ina ua avea a'u ma Ta'ita'i aoao o le Ekalesia RCCG, sa mamafa tele ia te a'u le tupu ma ola o le lotu, sa ou anapogi ma tatalo e lē aunoa ma lauga i le mea e gata ai, ma ua ou le malolo ai pe tafao. Na o'u faia lenei faiga mo ni tausaga seia o'o ina faafuasei ona o'u maitauina pe a ou lauga, e uma loa le sefululima minute e te'i a ua matuā leai a so'u leo. E ui sa ou tausisia ituaiga fautuaga uma e fo'ia ai le faafitauli, o se tasi o nei fesoasoani o le inu o le ti e ave i ai le honey, e le'i te'a ai na tumau pea. O le tasi aso na sau ai se tinā matua na ia maitauina le tulaga ua tupu ma fai mai ia te a'u, “Susuga e, ua e aafia i le fa'ama'i a faiaoga.” Sa o'u fai I le tinā lenei, ou te le'i faalogo muamua i lea faamai ma sa ia tali mai. “Ua e a'oa'o, pea lava pea, ma ua e lē tuua se avanoa e faamalolō ai lou siufofoga. O lena ua lē fiafia le leo.” Sa ou fesili i le tina pe faafefea ona fo'ia le faafitauli ma sa ia faapea mai, “Faamalolō lou siufofoga mo aso e sefululima.” E faafefea ona o'u faia?” Sa o'u fesili ae tali mai le tinā. “E mafai lava ona e a'oa'o e aunoa ma le leai o sou leo mo le sefululima minute; ae a le mafai loa ona e o'o i le lima minute; e tatau ona e faia loa le mea lea o'u te fai atu ai.” O lea la, mo le taimi muamua talu ona avea a'u ma ta'ita'i o le ekalesia, sa ou alu ai ou te malolo. Sa ou malaga i Siamani ma ou nofo i se fale sa i ai se potu faaafu (sauna). Fai mai lē e ona le fale sa ou nofo ai, e mafanafana ai le tino atoa mai totonu i fafo, ma a ou ulufale e tatau ona ou toe ulufafo pe a uma le sefululima minute pe a umi, aua o le ā matua'i sisina lo'u afu. Sa ou alu i totonu o le potu mafanafana ma e uma ifo le lima minute e leai ma se afu. Uma le sefulu minute e leai lava se afu. O le uma o le sefululima minute faatoa ou faalogoina sina afu itiiti. E fasefulu lima minute o o'u i totonu o le potu fa'aafu faatoa sau se afu. Ua leva ona lē tausia lelei lo'u tino ua lē toe galue lelei ai. Mai lea aso, ua ou iloa ai afai ou te fia ola umi ma fa'aaogaina a'u i le galuega a le Atua ua tuuina mai ia te a'u e tatau ona lava la'u malolo.Le au pele e, afai e te mana'o e umi lou soifua e tatau ona fa'aavanoa sou taimi e te malolō lelei ai. O loo tau mai i le faitauga mai le Tusi Paia o le asō, na malolo le Atua ina ua maea ona Ia faia le foafoaga ma o se faataitaiga lea mo kerisiano uma. E mata'utia ma ogaoga le galue mamafa e lē malolo auā e mafai ona e maliu ona o le tino vaivai ma le lēlavā. ‘Aua e te faapologaina lou tagata ona o le faataunuuina o lou valaauina mai le Atua. Faaavanoa le taimi e te malolo lelei ai ona e maua pea lea o le malosi e mafai ai pea ona e tamo'e i lau tausinioga. I le suafa o Iesu, Amene.

Morning news, the GOP pillow fight on KOIN tv, Asante in trouble, the ONA apparently can not COUNT. Bryan Riley from National Taxpayers Union says the president can do THIS to really get more cars built here...

No programa da Escola do Amor Responde de hoje, Renato Cardoso compartilhou com os alunos uma matéria especial sobre como foi a Celebração dos Casamentos 2026, que aconteceu no dia 30 de maio, no Templo de Salomão, em São Paulo, bem como em todo o País e também em outros países do mundo. Inclusive, entre os noivos, dezenas deles se conheceram por meio do aplicativo Quero Te Conhecer, exclusivo para os participantes das palestras da Terapia do Amor.Marido vivendo uma ilusãoNa sequência, uma aluna – que não quis se identificar – comentou que está em um casamento há dez anos, no qual houve muita traição por parte do marido. Eles têm um filho de seis anos de idade. O marido é um bom pai, porém, não quer mais trabalhar. A aluna comentou que ele está viciado em jogos de azar e que é ela quem tem que prover o sustento da casa. Isso tem a deixado cansada. Todas as vezes que ela fala para ele trabalhar, ele sempre arruma uma desculpa e diz que não compensa.Quando a aluna o conheceu, ele trabalhava em dois empregos, mas isso mudou. Ela não sabe mais o que fazer por causa disso. A aluna confessou que não sente mais atração pelo marido, nem amor. Ela já pensou em se separar, mas o filho é muito apegado ao pai.Ciúme doentioLogo em seguida, outra aluna comentou que conheceu o marido, logo passaram a morar juntos e, depois, se casaram no civil. Após algum tempo da oficialização, ele começou a proibi-la de sair de casa sozinha, pois acha que ela está o traindo. Ele tem ciúmes dela até com a família, incluindo a filha mais velha da aluna, que já é casada.Ela largou tudo, como academia e idas a lojas, entre outras atividades. Ela instalou até aplicativos de rastreamento no celular dela e, mesmo assim, ele não acredita que ela está no local informado. A aluna perguntou o que fazer nessa situação.Bem-vindos à Escola do Amor Responde, confrontando os mitos e a desinformação nos relacionamentos. Onde casais e solteiros aprendem o Amor Inteligente. Renato e Cristiane Cardoso, apresentadores da Escola do Amor, na Record TV, e autores de Casamento Blindado e Namoro Blindado, tiram dúvidas e respondem perguntas dos alunos. Participe pelo site EscoladoAmorResponde.com. Ouça todos os podcasts no iTunes: rna.to/EdARiTunes

Sudbina najznačajnijeg međunarodnog pozorišnog festivala u regionu, Bitefa, postala je jedna od najvažnijih tema debate o političkoj kontroli kulture u Srbiji. Prošlogodišnji presedan, kada se festival po prvi put u istoriji nije desio u planiranom obliku, otvorio je pitanje opstanka ove institucije pod pritiskom cenzure i kadrovskih rešenja koja stručna javnost ocenjuje kao nepodobna. O tome kakva je trenutna situacija i da li postoji nada za relevantnost 60. Bitefa, u Radar Forumu sa teatrologom i profesorom FDU Ivanom Medenicom razgovarala je Jelena Knežević, asistentkinja na FDU, producentkinja i bivša dugogodišnja izvršna direktorka festivala. Ivan Medenica podseća da je prošle godine selekcija reditelja Miloša Lolića bila cenzurisana iz političkih razloga, konkretno zbog govora reditelja Mila Raua, što je dovelo do povlačenja celog tima. Iako je došlo do delimične promene Upravnog odbora, Medenica ističe skandaloznu činjenicu da su zadržana dva člana koja su prošle godine glasala za cenzuru, dok novi predsednik, Spasoje Milovanović, prema njegovim rečima, nema reference za kustoske prakse niti međunarodnu saradnju na svetskom nivou. U novoj strukturi rukovođenja festivalom, Jelena Knežević prepoznaje promenu koja prevazilazi puku administraciju. Ona ukazuje na to da je institucija odbora, iako formalno demokratska, u aktuelnom režimu postala sredstvo za kontrolu onih manifestacija koje se smatraju „rizičnim“. Prema njenim rečima, kontrola se više ne sprovodi samo preko jedne osobe, upravnika, već kroz kolektivna tela koja deluju kao pojačanje u nadzoru i naglašava da je situacija ove godine, na sopstveno iznenađenje, možda i gora. Više na radar.rs