Podcasts about Manus

Alice Han and James Kynge look at why, for the first time in decades, China's new Five-Year Plan sets no numerical target for urban job creation. With unemployment at 5.1%, producer prices at a four-year high, and AI anxiety rippling through the labor market, what does it mean when Beijing, a government that treats jobs numbers as sacred, stops setting one? Then: Tencent is in talks to become the largest shareholder in Manus, the Chinese AI agent startup Meta tried to buy for $2 billion before Beijing forced the deal to unwind. Alice and James unpack why Chinese regulators intervened, what happened to Manus's founders, and what this all signals about Beijing's grip on its AI sector. Finally: Gen Z in China is skipping the megacities. Alice and James dig into why more young people are choosing Tier 3 and Tier 4 cities over Beijing and Shanghai, and whether it's a lifestyle choice or a symptom of a tougher economy. Subscribe to China Decode on Substack for weekly analysis, livestreams, and deep dives into the biggest story shaping the global economy: chinadecode.profgmedia.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

Links For The Occult Rejectshttps://linktr.ee/theoccultrejectsOccult Research Institutehttps://www.occultresearchinstitute.org/Substackhttps://substack.com/@theoccultrejects?r=7auau0&utm_campaign=profile&utm_medium=profile-pageCash Apphttps://cash.app/$theoccultrejectsVenmo@TheOccultRejectsBuy Me A Coffeebuymeacoffee.com/TheOccultRejectsPatreonhttps://www.patreon.com/TheOccultRejectsFull Bibliography for Part TwoCharcot, Hysteria, and the Medical TheaterJean-Martin Charcot. Lectures on the Diseases of the Nervous System.Jean-Martin Charcot. Clinical Lectures on Diseases of the Nervous System.Jean-Martin Charcot. Leçons sur les maladies du système nerveux faites à la Salpêtrière.Georges Didi-Huberman. Invention of Hysteria: Charcot and the Photographic Iconography of the Salpêtrière.Asti Hustvedt. Medical Muses: Hysteria in Nineteenth-Century Paris.Jan Goldstein. Console and Classify: The French Psychiatric Profession in the Nineteenth Century.Mark S. Micale. Approaching Hysteria: Disease and Its Interpretations.Elaine Showalter. The Female Malady: Women, Madness, and English Culture, 1830–1980.Henri F. Ellenberger. The Discovery of the Unconscious: The History and Evolution of Dynamic Psychiatry.Alan Gauld. A History of Hypnotism.The Nancy School and SuggestionAmbroise-Auguste Liébeault. Du sommeil et des états analogues, considérés surtout au point de vue de l'action du moral sur le physique.Hippolyte Bernheim. De la suggestion et de ses applications à la thérapeutique.Hippolyte Bernheim. Suggestive Therapeutics: A Treatise on the Nature and Uses of Hypnotism.Henri F. Ellenberger. The Discovery of the Unconscious.Alan Gauld. A History of Hypnotism.Adam Crabtree. From Mesmer to Freud: Magnetic Sleep and the Roots of Psychological Healing.Alison Winter. Mesmerized: Powers of Mind in Victorian Britain.Pierre Janet, Automatism, Dissociation, and TraumaPierre Janet. L'Automatisme psychologique.Pierre Janet. The Major Symptoms of Hysteria.Pierre Janet. The Mental State of Hystericals.Pierre Janet. Psychological Healing: A Historical and Clinical Study.Pierre Janet. Writings on fixed ideas, dissociation, hysteria, narrowed consciousness, and subconscious action.Henri F. Ellenberger. The Discovery of the Unconscious.Onno van der Hart, Ellert R. S. Nijenhuis, and Kathy Steele. The Haunted Self: Structural Dissociation and the Treatment of Chronic Traumatization.Adam Crabtree. From Mesmer to Freud.Alan Gauld. A History of Hypnotism.Ideomotor Effect, Table-Turning, and Automatic ActionMichel Eugène Chevreul. De la baguette divinatoire, du pendule explorateur et des tables tournantes.Michael Faraday. Writings and experimental reports on table-turning, unconscious muscular pressure, and involuntary movement.William Benjamin Carpenter. Principles of Mental Physiology.William Benjamin Carpenter. Essays and writings on unconscious cerebration and ideomotor action.Daniel M. Wegner. The Illusion of Conscious Will.Richard Wiseman. Paranormality: Why We See What Isn't There.Ray Hyman. Writings on ideomotor action, dowsing, psychical research, and anomalous experience.Spiritualism, Mediumship, Psychical Research, and Automatic WritingAlex Owen. The Darkened Room: Women, Power, and Spiritualism in Late Victorian England.Janet Oppenheim. The Other World: Spiritualism and Psychical Research in England, 1850–1914.Ann Braude. Radical Spirits: Spiritualism and Women's Rights in Nineteenth-Century America.Sofie Lachapelle. Investigating the Supernatural: From Spiritism and Occultism to Psychical Research and Metapsychics in France, 1853–1931.Frederic W. H. Myers. Human Personality and Its Survival of Bodily Death.The Society for Psychical Research. Early proceedings and reports on automatic writing, trance, mediumship, apparitions, and psychical phenomena.William James. Essays in Psychical Research.William James. The Varieties of Religious Experience.William James. The Principles of Psychology.Henri F. Ellenberger. The Discovery of the Unconscious.Adam Crabtree. From Mesmer to Freud.Freud, Breuer, Hypnosis, and the UnconsciousJosef Breuer and Sigmund Freud. Studies on Hysteria.Sigmund Freud. The Interpretation of Dreams.Sigmund Freud. Introductory Lectures on Psycho-Analysis.Sigmund Freud. “A Note on the Unconscious in Psycho-Analysis.”Sigmund Freud. “The Unconscious.”Sigmund Freud. “Remembering, Repeating and Working-Through.”Sigmund Freud. “The Dynamics of Transference.”Sigmund Freud. The Psychopathology of Everyday Life.Henri F. Ellenberger. The Discovery of the Unconscious.Mikkel Borch-Jacobsen. The Freudian Subject.Mikkel Borch-Jacobsen and Sonu Shamdasani. The Freud Files: An Inquiry into the History of Psychoanalysis.Frederick Crews. Freud: The Making of an Illusion.Élisabeth Roudinesco. Freud: In His Time and Ours.Frank J. Sulloway. Freud, Biologist of the Mind: Beyond the Psychoanalytic Legend.Occult Revival, Will, Imagination, and Esoteric PsychologyÉliphas Lévi. Dogme et Rituel de la Haute Magie.Éliphas Lévi. Transcendental Magic: Its Doctrine and Ritual.Éliphas Lévi. The Great Secret.Papus, Gérard Encausse. Traité méthodique de science occulte.Papus, Gérard Encausse. Elementary Treatise of Occult Science.Papus, Gérard Encausse. The Tarot of the Bohemians.Joscelyn Godwin. The Theosophical Enlightenment.Nicholas Goodrick-Clarke. The Western Esoteric Traditions: A Historical Introduction.Wouter J. Hanegraaff. Esotericism and the Academy: Rejected Knowledge in Western Culture.Alex Owen. The Place of Enchantment: British Occultism and the Culture of the Modern.Christopher McIntosh. Eliphas Lévi and the French Occult Revival.Crowley, Fortune, Spare, and Modern Magical PsychologyAleister Crowley. Magick: Liber ABA, Book 4.Aleister Crowley. Magick in Theory and Practice.Aleister Crowley. Liber O vel Manus et Sagittae.Aleister Crowley. The Equinox.Aleister Crowley. The Confessions of Aleister Crowley.Marco Pasi. Aleister Crowley and the Temptation of Politics.Dion Fortune, writing as Violet Firth. The Machinery of the Mind.Dion Fortune. Psychic Self-Defense.Dion Fortune. The Training and Work of an Initiate.Dion Fortune. Applied Magic.Dion Fortune. The Mystical Qabalah.Austin Osman Spare. The Book of Pleasure.Austin Osman Spare. The Focus of Life.Austin Osman Spare. A Book of Satyrs.Phil Baker. Austin Osman Spare: The Life and Legend of London's Lost Artist.Kenneth Grant. Images and Oracles of Austin Osman Spare.New Thought, Mind-Cure, Autosuggestion, and Personal MagnetismPhineas Parkhurst Quimby. The Quimby Manuscripts.Horatio W. Dresser. A History of the New Thought Movement.Catherine L. Albanese. A Republic of Mind and Spirit: A Cultural History of American Metaphysical Religion.Beryl Satter. Each Mind a Kingdom: American Women, Sexual Purity, and the New Thought Movement, 1875–1920.Robert C. Fuller. Mesmerism and the American Cure of Souls.Émile Coué. Self Mastery Through Conscious Autosuggestion.Émile Coué. How to Practice Suggestion and Autosuggestion.William Walker Atkinson. Thought Vibration; or, The Law of Attraction in the Thought World.William Walker Atkinson. Mind-Power: The Secret of Mental Magic.William Walker Atkinson. Practical Mental Influence.William Walker Atkinson. The Psychology of Salesmanship.William Walker Atkinson. Memory: How to Develop, Train and Use It.William Walker Atkinson. The Power of Concentration.William Walker Atkinson, under related New Thought and occult pseudonymous currents. Works on personal magnetism, suggestion, concentration, mental science, and occult psychology.Theosophy, Hypnotism, and Occult Warnings About InfluenceHelena Petrovna Blavatsky. The Key to Theosophy.Helena Petrovna Blavatsky. Collected Writings.Helena Petrovna Blavatsky. Writings and discussions touching mesmerism, hypnotism, psychic influence, occult dangers, and spiritual development.Annie Besant and C. W. Leadbeater. Thought-Forms.C. W. Leadbeater. The Astral Plane.C. W. Leadbeater. The Chakras.Joscelyn Godwin. The Theosophical Enlightenment.Nicholas Goodrick-Clarke. The Western Esoteric Traditions.Wouter J. Hanegraaff. Esotericism and the Academy.General Histories Useful Across Part TwoHenri F. Ellenberger. The Discovery of the Unconscious: The History and Evolution of Dynamic Psychiatry.Adam Crabtree. From Mesmer to Freud: Magnetic Sleep and the Roots of Psychological Healing.Adam Crabtree. Animal Magnetism, Early Hypnotism, and Psychical Research, 1766–1925: An Annotated Bibliography.Alan Gauld. A History of Hypnotism.Alison Winter. Mesmerized: Powers of Mind in Victorian Britain.Robert Darnton. Mesmerism and the End of the Enlightenment in France.Frank A. Pattie. Mesmer and Animal Magnetism: A Chapter in the History of Medicine.Peter Lamont. Extraordinary Beliefs: A Historical Approach to a Psychological Problem.Nicholas Goodrick-Clarke. The Western Esoteric Traditions.Wouter J. Hanegraaff. Esotericism and the Academy.Alex Owen. The Place of Enchantment.Also want to remind people about the website, if you're into reading we have tons of information by multiple contributors, and we got t-shirts up on the site if you're interested. Fun fact, the art is all based on the eyeball. 

En Más Platón y menos WhasApp  el filósofo Jose Carlos Ruiz y el humorista Manu Sánchez conversan sobre la vida desde una mirada filosófica 

Financial Times reported that Tencent is leading a deal to unwind Meta's $2 billion acquisition of Manus. The parties have not disclosed terms, and it is unclear whether Manus would return to independence, join a Tencent led consortium, or be split. The potential reversal aligns with Meta's recent portfolio adjustments, including the 2023 sale of Giphy and a shift toward AI infrastructure. Tencent's involvement reflects its cross border investment strategy built around minority stakes and partnerships. Regulators in the United States, Europe, the United Kingdom, and China continue to shape deal structures, though there is no indication a specific authority prompted this unwind. The transaction would require new arrangements for employees, customers, contracts, and intellectual property, with deal mechanics determining valuation and timeline.Learn more on this news by visiting us at: https://greyjournal.net/news/ Hosted on Acast. See acast.com/privacy for more information.

10/7 WS scalda i motori per il debutto di SK Hynix: 148$ per ADR, raccoglie 26,5 mld dollari. Tutto quello che dovete sapere. La riscossa dei chip guida Wall Street insieme alla stabilizzazione del Brent: diplomazia Usa-Iran continua, negoziati tecnici. Hormuz paralizzata.Meta: produzione chip AI da settembre e nuovo modello Coding Muse Spark 1,1. OpenAI, Altman: con Gpt5.6 token più efficienti coding del 54%. La numero due lascia. Anthropic: Bernanke nel board di vigilanza. Treasury al 4,5%, nelle Task Force Fed Warsh sceglie Marc Andreessen e l'ex governatore BOE Mervyn King. ****Questo episodio è offerto da ⁠Scalable Capital ⁠ Apri un conto con Scalable Capital e inizia a ricevere il 2,5% di interessi* sui tuoi risparmi:  https://it.scalable.capital/broker-online?utm_medium=affiliate&utm_source=qualityclick&utm_campaign=broker&c_id=QC59486e7f67706c777b517d435049607362766c747c5aS7541p&utm_term=983 Messaggio pubblicitario. Tasso lordo annuo variabile sulla liquidità depositata nel conto deposito non vincolato, composto da tasso base collegato al Tasso di Deposito BCE e tasso bonus discrezionale. Liquidità allocata presso banche partner e fondi monetari riconosciuti. Foglio informativo e condizioni su scalable.capital. Investire comporta dei rischi Asia in rally: Nikkei +2% (Softbank +11%), Kospi +4% spinta da Sk e Smasung. Giappone: PPI ai massimi da tre mesi al 7,1%. Yen si rafforza. FT: Tencent punta a Manus (ex Facebook) Europa in verde, oggi Ecofin. Inflazione in Francia e Germania. Ubs promuove equity EU. Minute Bce: taglio più che assicurativo. Volkswagen: piano anti-crisi, 100mila licenziamenti. Stellantis, minimo storico: analisti scettici. Risiko, Messin (Intesa SP): unici in gradi di garantire indipendenza e  sicurezza nazionale degli asset strategici di questo paese. Learn more about your ad choices. Visit megaphone.fm/adchoices

This week on Sinica, in a special episode recorded at the Davos On Air booth at the World Economic Forum's Annual Meeting of the New Champions in Dalian, I sat down with Angela Huyue Zhang, professor of law at USC's Gould School of Law and author of High Wire: How China Regulates Big Tech and Governs Its Economy, and S. Alex Yang, professor of management science and operations at London Business School. Angela and Alex — who are also married, and who arrived at this collaboration from opposite ends of the academy — have developed what I think is one of the most useful new mental models for understanding China's political economy: the platform state. Their argument is that we should think of the Chinese state less as a central planner or owner and more as a platform company like NVIDIA or Apple, one that builds architecture, sets standards, and governs an ecosystem within which fiercely competitive private firms fight it out. Value accrues at the system level rather than as firm profit, and the payoff may decide who wins the race to put AI to work across an entire economy.5:37 – Three puzzles the framework is built to solve: profitless dominance in solar, EVs, and batteries; why the "grabbing hand" hasn't strangled Chinese innovation; and how China is attempting both zero-to-one invention and one-to-hundred scaling at once7:57 – The platform state thesis: why the Chinese government behaves like a platform company, how nurturing an ecosystem of private firms solves the information deficit that cripples command-and-control, and why over-entry, involution, and consolidation are a repeated pattern — from EVs to the 140-plus humanoid robot companies operating today16:13 – The aha moment: how a paper on the legal infrastructure of physical AI became the platform state idea over the Zhang-Yang dinner table, and whether this is a new species of political economy or the East Asian developmental state in new clothes20:44 – State conditions: why state capacity and domestic scale are the two preconditions for the model, and why an ambitious Vietnam — which has the top-down capacity — may still find the Chinese playbook impossible to replicate23:39 – Profitless dominance by design: harvesting versus extracting, the Uber analogy, overshooting as a control-theory strategy for nudging sectors, and how the anti-involution campaign and the 60-day supplier payment mandate show the state moderating the very competition it engineered30:33 – Organized chaos: from the bike-sharing graveyards of the O2O wars to today's disciplined market, the exit of more than 400 EV makers since 2018, and why the survivors of China's "Premier League" of competition are now turning profitable32:59 – The 3Gs playbook: growing markets by solving the cold-start problem, from Liuzhou's EV test drives to Beijing's green license plates, and how subsidy is only one lever among many38:36 – Governing the ecosystem like Apple runs its App Store: why Beijing regulates generative AI with a light touch but physical AI is a different species entirely, law as the sixth layer of the AI stack, why robotaxis scale faster in China than in the U.S., and the state-convened standard-setting that's driving down humanoid robot costs46:54 – Two flywheels: the familiar data-and-cost flywheel and the deeper state capacity flywheel, and how the National AI Fund's small but voting stake in DeepSeek aligns a complementor with the domestic stack — tilting the ecosystem toward Chinese chips53:28 – Guarding the moat: automotive data rules and Tesla's stalled FSD ambitions, the unwound Manus sale, China's own small yard and high fence, and the closing provocation — that America could build the smartest frontier models and still lose the diffusion race to "artificial good-enough intelligence." Plus: the case for coopetition, and what policymakers should (and shouldn't) borrow from the platform stateLinks from the episodeAngela's paper on law as the sixth layer of China's AI stack:The Sixth Layer: The Legal Infrastructure for Physical Artificial Intelligence in China (SSRN)Three Project Syndicate op-eds on the platform state idea:The Rise of the Chinese Platform State by S. Alex Yang & Angela Huyue ZhangAre Government Stakes the Key to AI Sovereignty? by Angela Huyue ZhangOvercapacity Is China's Biggest AI Advantage by Angela Huyue ZhangTwo Management Science papers on commercial platforms:Crowd-Judging on Two-Sided Platforms: An Analysis of In-Group BiasImproving Dispute Resolution in Two-Sided Platforms: The Case of Review BlackmailSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In questa puntata di Marketing Garage Gianluca Testa intervista Alessandro Aresu, consigliere scientifico di Limes, esperto di geopolitica, mercati asiatici, semiconduttori e intelligenza artificiale, autore di “La Cina ha vinto” e “Geopolitica dell'intelligenza artificiale”.Per anni ci siamo raccontati una frase semplice: “Gli Stati Uniti innovano, la Cina copia, l'Europa regola.”
Ma questa frase oggi è ancora vera? Secondo Aresu, no. La nuova formula è molto più dura e realistica: gli Stati Uniti attraggono, la Cina scala, l'Europa rallenta.Durante l'intervista abbiamo provato a capire cosa ci siamo persi negli ultimi decenni: l'ascesa industriale dell'Asia, il ruolo della Cina come potenza manifatturiera e tecnologica, la centralità di Taiwan nei semiconduttori, il dominio di Nvidia nell'AI e la difficoltà europea nel costruire una vera autonomia tecnologica:

Sau khi « mượn » đô la trong tay các quỹ đầu tư Mỹ làm bệ phóng cho các công ty khởi nghiệp để phát triển công nghệ, Trung Quốc « qua cầu rút ván », áp dụng chính sách bảo hộ để kiểm soát những lĩnh vực mũi nhọn chiến lược. Bắc Kinh không chỉ giỏi đánh cắp bí quyết công nghiệp và công nghệ của Hoa Kỳ mà còn sao chép cả những công cụ pháp lý của Washington để giành lấy thế thượng phong.  Vụ Bắc Kinh hủy thương vụ của đại tập đoàn công nghệ Mỹ Meta mua lại Manus, một công ty khởi nghiệp rất có triển vọng trong công nghệ trí tuệ nhân tạo của Trung Quốc là trường hợp tiêu biểu, để lộ rõ những nước cờ của Trung Quốc.  RFI Việt ngữ mời chuyên gia về luật tài chính, nhà nghiên cứu về Trung Quốc Isabelle Feng, phó chủ tịch trung tâm nghiên cứu Á Châu Asia Centre, Paris, phân tích về chiến lược phát triển công nghệ cao của Bắc Kinh, về những tính toán của Trung Quốc trong cuộc tranh hùng với Mỹ trên mặt trận high tech và trí tuệ nhân tạo.   Một tháng sau khi công bố những biện pháp giới hạn đầu tư của các doanh nghiệp Trung Quốc ở hải ngoại, Bắc Kinh kể từ ngày 01/07/2026 có quyền hủy một chương trình hợp tác giữa một nhà đầu tư nước ngoài với một công ty Trung Quốc, nếu như dự án đó bị coi là « nhạy cảm » và « đe doạ đến an ninh quốc gia ». Giống như Hoa Kỳ, Trung Quốc cũng viện lý do « an ninh quốc gia » để siết chặt kiểm soát các dự án đầu tư ra nước ngoài, đặc biệt là trong các lĩnh vực trí tuệ nhân tạo (AI), công nghệ bán dẫn hay những công nghệ xanh. Luật chơi mới cho phép các giới chức Trung Quốc « kiểm soát lưu lượng vốn và cả các nguồn lực lao động ». Hai tháng trước khi quy định mới của Trung Quốc giới hạn đầu tư ra nước ngoài có hiệu lực, Meta và Manus đã là những nạn nhân đầu tiên của chính sách này. Cuối tháng Tư vừa qua, vài tuần trước khi tổng thống Hoa Kỳ Donald Trump đến Bắc Kinh và vào lúc thế giới tập trung vào chiến tranh Trung Đông, vào eo biển Hormuz bị Iran phong tỏa, vào nguy cơ nổ ra một cuộc khủng hoảng dầu hỏa và năng tượng toàn cầu, thì tại Bắc Kinh, cơ quan chức năng đã hủy một thương vụ vốn đã hoàn tất gần nửa năm trước đó giữa tập đoàn công nghệ Meta của Hoa Kỳ và Manus đang hoạt động tại Singapore. Một công ty khởi nghiệp và « gã khổng lồ » Meta Manus hiện được coi là con chim đầu đàn về trí tuệ thông minh, trụ sở ban đầu đặt tại Vũ Hán. Nhưng để có thể thu hút đầu tư của Mỹ và cũng là để lách luật COINS Act 2025 của Hoa Kỳ ( Luật cho phép Hoa Kỳ kiểm soát các khoản đầu tư của doanh nghiệp và nhà đầu tư Mỹ ra nước ngoài, đặc biệt là vào các lĩnh vực công nghệ nhạy cảm ở các « quốc gia đáng quan ngại » như Trung Quốc), hai sáng lập viên đã ngừng hoạt động tại Hoa Lục, sang Singapore hành nghề, dưới danh nghĩa là một công ty khởi nghiệp Singapore. Điều đó không cấm cản các sáng lập viên của Manus bị triệu tập về Trung Quốc và bị cấm rời khỏi Hoa Lục, trong khi đợi « kết quả điều tra ». Bắc Kinh đang điều tra xem việc Manus bị đại tập đoàn công nghệ Mỹ Meta mua lại có là một mối đe dọa đối với an ninh quốc gia hay không. Vì sao quyết định hủy thương vụ Manus bán cho Meta lại là một trường hợp tiêu biểu cho cuộc chiến Mỹ- Trung và đâu là những bài học có thể rút ra từ vụ này về chính sách đầu tư của Bắc Kinh, về cung cách hoạt động của Trung Quốc về tiến trình khởi nghiệp và cất cánh của các công ty Trung Quốc trong lĩnh vực công nghệ ? Trung Quốc mượn vốn của Mỹ để phát triển RFI : Thân chào Isabelle Feng, báo chí Mỹ như Wall Street Journal hay Bloomberg, New York Times đã chú ý nhiều đến cuộc « liên hôn » ngắn ngủi giữa Meta, công ty mẹ của những Facebook, Whatsapp, Intagram với Manus, một công ty khởi nghiệp ban đầu là từ Vũ Hán. Manus phát triển AI thế hệ mới, với những chức năng như là dùng AI để mua vé xe lửa hay tìm nhà cho thuê … Meta đã chi ra 2 tỷ đô la để thâu tóm Manus. Thủ tục sáp nhập này đã hoàn tất vào cuối năm 2025 và đôi bên đã chính thức hợp tác với nhau từ đó đến nay. Cho dù Manus đang hoạt động với danh nghĩa một công ty Singapore, Trung Quốc vẫn có thẩm quyền hủy giao dịch giữa Meta và Manus. Chúng ta có thể thấy gì từ trường hợp này ?   Isabelle Feng : « Nghiên cứu từ nhiều năm nay về trường hợp của Meta và Manus, tôi có những nhận xét như sau : Manus cũng như rất nhiều các hãng công nghệ khác của Trung Quốc khởi nghiệp nhờ vốn đầu tư của tư nhân bởi vì họ không được nhà nước tài trợ, không được các ngân hàng nhà nước giúp đỡ. Vốn của tư nhân ở đây chủ yếu là vốn từ các tổ hợp đầu tư liên doanh. Cho đến năm 2020, phần lớn những tổ hợp liên doanh này có vốn của Mỹ. Trong trường hợp của tập đoàn ô tô điện Trung Quốc BYD chẳng hạn, ban đầu họ đã phát triển nhờ vốn của một quỹ mang tên là Wang Chuanfu  nhưng đến năm 2008 thì bắt đầu mở cửa cho các nhà đầu tư nước ngoài dưới dạng một joint venture. Tương tự như vậy, từ Tencent, Alibaba đến ByteDance… cũng đã khởi nghiệp với vốn của các quỹ đầu tư ngoại quốc, trong đó có vốn của các nhà đầu tư Mỹ. Nhưng đến khi những công ty khởi nghiệp đó thành công, các cổ đông bán lại cổ phần để thu lại vốn. Khi đó đến lượt các ngân hàng của nhà nước Trung Quốc can thiệp. Alibaba năm 2014 tham gia sàn chứng khoán Hoa Kỳ, nhưng kỳ thực thì ngay cả ông khổng lồ này cũng do nhà nước Trung Quốc kiểm soát ». RFI : Nói cách khác, công nghệ của Trung Quốc cất cánh một phần cũng nhờ các quỹ đầu tư của Hoa Kỳ. Bản chất các nhà đầu tư là bỏ vốn vào những thị trường, những lĩnh vực dễ sinh lời, có mức lãi cao và chóng thu hồi vốn. Riêng Manus thì đã được thành lập trong bối cảnh mà Mỹ và Trung Quốc đã lao vào một cuộc chiến thương mại, và nhất là công nghệ. Isabelle Feng : « Manus là một ca rất thú vị : Được 2 kỹ sư sáng lập năm 2022, trụ sở tại Vũ Hán. Đó cũng là thời điểm quan hệ Mỹ và Trung Quốc đã xấu đi. Cho nên Manus chỉ có thể trông cậy vào vốn đầu tư của tư nhân Trung Quốc. Nhưng rồi để nhanh chóng phát triển, Manus cần vốn của cả các tổ hợp liên doanh tức là phải có vốn của nước ngoài -trong lĩnh vực AI, mỗi dự án đầu tư cần cả tỷ đô la. Chúng ta biết nguồn vốn mạnh nhất là từ Mỹ. Washington nhân danh an ninh quốc gia đã cấm các nhà đầu tư Hoa Kỳ bỏ vốn vào những lĩnh vực nhạy cảm của Trung Quốc. Để lách điều khoản này, Manus trong một sớm một chiều đã đóng cửa cơ sở tại Vũ Hán để đăng ký hoạt động tại Singapore. Với danh nghĩa là một công ty khởi nghiệp của Singapore, Manus đã thu hút chú ý của các quỹ đầu tư – trong đó có Benchmark Capital. Qua Benchmark, Manus đã được Meta chú ý ». Sự "bất an" trong các công cụ pháp lý của Trung Quốc RFI : Phải chăng một trong những lý do khiến Manus bị Bắc Kinh chú ý đến là do công ty khởi nghiệp này đang nổi lên như diều gặp gió với công nghê AI thế hệ mới ? Trường hợp của Manus đã gây bất ngờ tương tự như hiệu ứng DeepSeek. Tháng 1/2026, một công ty còn ít được biết đến cho ra đời « phiên bản Trung Quốc của ChatGPT », được cho là « thông minh hơn » « gọn nhẹ hơn » « rẻ hơn » và « hiệu quả hơn » những công cụ của Mỹ. Chính vì thế mà Bắc Kinh muốn tránh để một công ty quý giá như Manus vào tay Hoa Kỳ Isabelle Feng : « Qua việc Bắc Kinh hủy thương vụ liên quan đến Meta và Manus, chúng ta có thể đưa ra những nhận xét như sau : Một là Trung Quốc muốn khẳng định các doanh nghiệp, các kỹ sư Trung Quốc bất luận hoạt động ở nơi nào đều vẫn thuộc quyền kiểm soát của chính quyền Trung Quốc. Nghịch lý ở đây là Trung Quốc đang rất cần thu hút vốn đầu tư trực tiếp nước ngoài, nhưng khi hủy hợp đồng của tập đoàn Mỹ Meta mua lại Manus rõ ràng là họ đang khẳng định chỉ có Bắc Kinh mới làm chủ cuộc chơi. Điểm thứ nhì cần lưu ý : Hủy một quyết định, một hợp đồng đã có hiệu lực từ sáu tháng trước nhắm vào một tập đoàn Trung Quốc hoạt động ở Singapore, đây là lần đầu tiên Bắc Kinh áp dụng một cách triệt để nguyên tắc ngoài lãnh thổ, trong lúc không có bất kỳ một lý do nào cho thấy thương vụ giữa Manus và Meta vi phạm luật pháp của Trung Quốc.Điều đó càng để lộ rõ cái mà chúng ta có thể gọi là khía cạnh ‘bất an' trong các công cụ pháp lý của Trung Quốc đối với các doanh nghiệp nước ngoài. Bài học thứ ba có thể rút ra từ trường hợp của Meta và Manus là cuộc chạy đua phát triển trí tuệ nhân tạo đòi hỏi rất nhiều đầu tư – mỗi dự án có thể cần đến cả tỷ đô la và để thu hút đầu tư và phát triển AI, Hoa Kỳ trông cậy từ 80 đến 90 % vào đầu tư tư nhân. Tại Trung Quốc, đầu tư của nhà nước chiếm hơn 50 %. Nửa còn lại là vốn của tư nhân, của các quỹ tài chính liên doanh. Câu hỏi còn lại là sau vụ của Manus, là một nhà đầu tư ngoại quốc còn mấy ai dám bỏ vốn  vào AI Trung Quốc ? ». RFI : Nói như vậy nạn nhân đầu tiên từ những quy định hạn chế đầu tư của Trung Quốc ra nước ngoài chính là các công ty khởi nghiệp Trung Quốc, bởi vì như vừa nói  công nghệ mới của Trung Quốc đã phát triển nhờ vào các quỹ đầu tư của Hoa Kỳ. Ngoài ra vào lúc mà cuộc đọ sức giữa hai siêu cường kinh tế thế giới gia tăng cường độ, Bắc Kinh càng lúc càng chứng tỏ khả năng đáp trả đích đáng Hoa Kỳ khi cần, điển hình là thông báo hôm 22/06/2026 đưa một loạt doanh nghiệp Mỹ vào danh sách trừng phạt. Biện pháp này nhằm trả đũa Lầu Năm Góc hơn một chục ngày trước đó đã đưa nhiều tập đoàn lớn của Trung Quốc vào danh sách với lý do «nghi ngờ » các thực thể này hợp tác với quan đội Trung Quốc. Thưa Isabelle Feng ,bà đánh giá thế nào về quyết định này từ phía Bắc Kinh ? Isabelle Feng : « Mỗi lần Mỹ ban hành lệnh trừng phạt các công ty Trung Quốc, lập tức Bắc Kinh phản công. Nếu nhìn kỹ vào danh sách của đôi bên lần này, chúng ta thấy có một sự bất tương xứng. Mỹ nhắm vào những tên tuổi như Alibaba hay BYD... Những công ty này hoàn toàn không nằm trong lĩnh vực nhạy cảm : Alibaba là một nhà phân phối hàng trên mạng, còn hãng xe BYD hoạt động khắp châu Âu. Trái lại, phía Trung Quốc nhắm những Loockheed Martin, Raytheon …, những tên tuổi lớn trong các lĩnh vực công nghiệp quốc phòng và hàng không quân sự mà rất ít người Trung Quốc biết đến. Cũng vì tính chất nhạy cảm trong các hoạt động của hãng Mỹ liên quan, cho nên về thực chất, họ rất ít giao dịch với Trung Quốc. Nếu như Bắc Kinh thật sự muốn đáp trả Washington một cách tương xứng thì họ đã nhắm tới những tập Apple hay Microsoft : Đó là những nhãn hiệu đã bắt rễ sâu vào Trung Quốc và Trung Quốc là thị trường lớn của hai thương hiệu này ». RFI : Xin thành thật cảm ơn bà Isabelle Feng, phó chủ tịch trung tâm nghiên cứu về châu Á Asia Centre Paris.

George Black, guest author, introduces two central protagonists, Manus Campbell and Chuck Searcy, who arrived in Vietnam in June 1967. Campbell, a young Marine from New Jersey, was driven by a desire to prove himself to his demanding father and joined the elite Marines to become a hero. He was assigned to the first battalion of the fourth Marines and deployed to I Corps, the most dangerous combat zone in the country. Conversely, Searcy, a former Goldwater supporter from Georgia, enlisted in military intelligence to avoid the frontline combat he dreaded. While Campbell faced the brutal reality of the A Shau Valley—a strategic North Vietnamese stronghold that was never recovered by the US—Searcy was stationed in Saigon. In Saigon, Searcy began to see the war's disconnect from reality, observing that intelligence reporting was often manipulated to provide the "rosy face" demanded by politicians and generals. The A Shau Valley remained critical because its difficult, fog-shrouded terrain provided a bastion for the North to launch attacks on cities like Hue during the upcoming Tet Offensive. Both men arrived as the war reached a stalemate, forcing both sides to change their tactics. The Long Reckoning (3)

George Black, guest author, describes how Manus Campbell's experience in the mountains of I Corps was defined by the arbitrariness of death and survival. His unit frequently walked into triangular ambushes set by elite North Vietnameseregulars, resulting in horrific firefights where survival had little to do with skill. Campbell witnessed companions die in his place due to random movements, a primary root of his subsequent PTSD and survivor guilt. Meanwhile, Chuck Searcy experienced the Tet Offensive from Saigon, realizing that while the North suffered military losses, they won a strategic victory by turning the American public against the war. Searcy and his colleagues in intelligence were acutely aware that they had been asked to misrepresent the war's progress to the public. A pivotal moment for both men occurred in June 1968, when they heard about the death of Robert F. Kennedy on Armed Forces Radio. This event signaled a deep fracture in American society, leaving them to wonder what kind of country they would return to. After their tours, Campbell struggled with alcoholism and psychological torment in Europe, while Searcy eventually joined the anti-war movement after becoming convinced of its credibility during his time in Germany. The Long Reckoning (4)

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#高雄 正義站&黃線捷運計劃，平面車位3房全新完工 實品屋預約鑑賞中。正義站通勤南科，未來捷運串連衛武營、Lalaport。正義公園，風景入門廳 。陽明國中自由學區07-7801988 洽澄清路227號 https://sofm.pse.is/99uk7m -- #高雄 正義站&黃線捷運計劃，平面車位3房全新完工 實品屋預約鑑賞中。正義站通勤南科，未來捷運串連衛武營、Lalaport。正義公園，風景入門廳 。陽明國中自由學區07-7801988 洽澄清路227號 https://sofm.pse.is/99uk7m -- (裕富數位 | 吉速袋) 急用周轉 為你應援  線上申辦3步驟  資料齊全最快 5 分鐘  專人依序審核，最快當日撥款 前往了解更多: https://sofm.pse.is/9ct6wj (警語) 總費用年百分率約16.45%-23.97%。利率15.75%~15.99%，手續費1~2.5千元。詳參裕富官網。實際撥款時間與條件視審核而定。請謹慎理財。 －－－－以上為 SoundOn 動態廣告－－－－ AI熱潮持續席捲全球，科技巨頭市值屢創新高，不免讓人聯想到2000年的網路泡沫，究竟是歷史會重演，還是這次「真的不同」？當年不少dot-com企業純靠「本夢比」支撐，缺乏實質營收，而當前AI 巨頭已有強勁的獲利能力與現金流，是否代表目前的AI行情有更扎實的基本面支撐？還是市場仍存在估值過熱的風險？AI基礎建設規模迅速膨脹，企業競相擴建資料中心，會不會重演當年電信商大量鋪設光纖，導致頻寬嚴重過剩的慘劇？目前雲端算力需求強勁，但似乎尚未出現能引發大規模付費意願的殺手級應用，AI 產業變現效率跟上資本投資速度嗎？AI獨角獸企業的模型訓練成本與營運支出持續攀升，若提供資金的大型科技企業縮手，會不會對AI新創圈造成致命打擊？相較於2000年前後的低利率環境，此次AI 狂潮發生在相對高利率、資金成本升高的週期，將資金集中於少數 AI企業，是在追逐成長，還是尋求相對確定的投資標的？AI產業是否正形成更明顯的「大者恆大」格局？這會讓市場比過去更具穩定性，還是加劇未來市場修正時的風險？若AI產業未來一兩年內發生估值修正、甚至泡沫破裂，會是大崩盤，還是像網路泡沫後的「健康洗牌」？投資人現階段該如何看待AI概念資產配置？哪些市場訊號值得特別留意？精彩訪談內容，請鎖定@華視三國演議！ 本集來賓：#Miula #矢板明夫 主持人：#汪浩 以上言論不代表本台立場 #AI概念股 #泡沫化 #投資 #失業 電視播出時間

******Support the channel******Patreon: https://www.patreon.com/thedissenterPayPal: paypal.me/thedissenterPayPal Subscription 3 Dollars: https://tinyurl.com/ybn6bg9lPayPal Subscription 5 Dollars: https://tinyurl.com/ycmr9gpzPayPal Subscription 10 Dollars: https://tinyurl.com/y9r3fc9mPayPal Subscription 20 Dollars: https://tinyurl.com/y95uvkao ******Follow me on******Website: https://www.thedissenter.net/The Dissenter Goodreads list: https://shorturl.at/7BMoBFacebook: https://www.facebook.com/thedissenteryt/Twitter: https://x.com/TheDissenterYT This show is sponsored by Enlites, Learning & Development done differently. Check the website here: http://enlites.com/ Dr. Arvid Ågren is Assistant Professor at the Cleveland Clinic Lerner College of Medicine at Case Western Reserve University. At the Cleveland Clinic, he is affiliated with the Theory Division at the Lerner Research Institute. He is the author of The Gene's-Eye View of Evolution.Dr. Manus Patten is Teaching Professor in the Department of Biology at Georgetown University. His main interests are genetic conflicts, adaptation, and the levels of selection. He teaches courses in evolution, ecology, and genetics.They are editors of The Paradox of the Organism: Adaptation and Internal Conflict. In this episode, we focus on The Paradox of the Organism. We start by discussing what the paradox of the organism is. We explore the notions of organism, conflict in evolutionary biology, multilevel selection, individuality, internal conflicts, organisms as unified agents, and organisms as ecosystems. We talk about how internal conflicts might get expressed in different pathologies, with a focus on cancer. Finally, we discuss the body-as-machine approach in medicine and its limitations, and whether genetic conflicts can get expressed on a psychological level.--A HUGE THANK YOU TO MY PATRONS/SUPPORTERS: PER HELGE LARSEN, BERNARDO SEIXAS, ADAM KESSEL, MATTHEW WHITINGBIRD, ARNAUD WOLFF, TIM HOLLOSY, HENRIK AHLENIUS, ROBERT WINDHAGER, RUI INACIO, ZOOP, MARCO NEVES, COLIN HOLBROOK, PHIL KAVANAGH, SAMUEL ANDREEFF, FRANCIS FORDE, TIAGO NUNES, FERGAL CUSSEN, HAL HERZOG, NUNO MACHADO, JONATHAN LEIBRANT, JOÃO LINHARES, STANTON T, SAMUEL CORREA, ERIK HAINES, MARK SMITH, JOÃO EIRA, TOM HUMMEL, SARDUS FRANCE, DAVID SLOAN WILSON, YACILA DEZA-ARAUJO, ROMAIN ROCH, YANICK PUNTER, CHARLOTTE BLEASE, NICOLE BARBARO, PAWEL OSTASZEWSKI, NELLEKE BAK, GUY MADISON, GARY G HELLMANN, SAIMA AFZAL, ADRIAN JAEGGI, JOÃO BARBOSA, JULIAN PRICE, HEDIN BRØNNER, FRANCA BORTOLOTTI, GABRIEL PONS CORTÈS, URSULA LITZCKE, SCOTT, ZACHARY FISH, TIM DUFFY, SUNNY SMITH, JON WISMAN, WILLIAM BUCKNER, LUKE GLOWACKI, GEORGIOS THEOPHANOUS, CHRIS WILLIAMSON, PETER WOLOSZYN, DAVID WILLIAMS, DIOGO COSTA, ALEX CHAU, CORALIE CHEVALLIER, BANGALORE ATHEISTS, LARRY D. LEE JR., OLD HERRINGBONE, DAN SPERBER, ROBERT GRESSIS, JEFF MCMAHAN, JAKE ZUEHL, MARK CAMPBELL, TOMAS DAUBNER, LUKE NISSEN, KIMBERLY JOHNSON, JESSICA NOWICKI, LINDA BRANDIN, VALENTIN STEINMANN, ALEXANDER HUBBARD, BR, JONAS HERTNER, URSULA GOODENOUGH, DAVID PINSOF, SEAN NELSON, MIKE LAVIGNE, JOS KNECHT, LUCY, MANVIR SINGH, PETRA WEIMANN, CAROLA FEEST, MAURO JÚNIOR, TONY BARRETT, NIKOLAI VISHNEVSKY, STEVEN GANGESTAD, TED FARRIS, HUGO B., JORDAN MANSFIELD, CHARLOTTE ALLEN, PETER STOYKO, DAVID TONNER, LEE BECK, PATRICK DALTON-HOLMES, NICK KRASNEY, RACHEL ZAK, DENNIS XAVIER, CHINMAYA BHAT, RHYS, ALEX MACLEOD, HAIDAR, JULIEN PORCHER, ROBERT SUNDSTRÖM, JON STEWART, AND JENNY M!A SPECIAL THANKS TO MY PRODUCERS, YZAR WEHBE, JIM FRANK, ŁUKASZ STAFINIAK, TOM VANEGDOM, BERNARD HUGUENEY, CURTIS DIXON, THOMAS TRUMBLE, KATHRINE AND PATRICK TOBIN, JONCARLO MONTENEGRO, NICK GOLDEN, CHRISTINE GLASS, IGOR NIKIFOROVSKI, PER KRAULIS, ADAM HUNT, AND JOÃO BARBOSA!AND TO MY EXECUTIVE PRODUCERS, MATTHEW LAVENDER,SERGIU CODREANU, AND GREGORY HASTINGS!

In this episode of 3 Movies That Changed Your Life screenwriter Stuart Wright talks with script consultant Danny Manus about: A Few Good Men, My Cousin Vinny, and The Ice Storm. Discover how these films shaped his screenwriting journey, personal growth, and understanding of cinema's power. Plus, Danny Manus discusses what a script consultant does and how they can help you improve a script and become a better writer. Movies That Changed Your Life   Find out about what a script consultant does and how they can help you write a script and become a better writer and the lasting impact of cinema on Danny Manus's life with Stuart Wright on his movie podcast.   Three common aspects of script feedback Danny Manus gives to writer: [1:20] 1) Integrating the plot and character; [6:40] 2) Being able to identify your hook; and  [18:00] 3) The art of scene writing. [40:20] What makes a good writer for a script consultant? 3 Films That Have Impacted Everything In Your Adult Life A Few Good Men (1992): Noticing writing [15:40] Today, Danny Manus is a huge fan of both Aaron Sorkin and Rob Reiner, but watching A Few Good Men as a 12/13 year old, he saw for the first time, the power in the writing of a movie. It's a master class in the rhythm and build of a story through dialogue. My Cousin Vinny (1992): Unable to stop laughing [21:30] My Cousin Vinny is Danny Manus's favourite comedy of all time. He's seen it over and over 100 times, but when he saw it in theatres aged 12/13 it was the first time he couldn't catch his breath because he was laughing too hard. The Ice Storm (1997): Teen storylines   [27:40] Danny believes there is no American Beauty without The Ice Storm. He simply loves a family dysfunction movie. The teen storylines spoke to him and were echoed in his own early screenwriting efforts at college. Key Take Aways:   Discover how movies that changed your life shape personal and professional growth.  How to integrating plot and character; Can you identify your hook? Learn the art of scene writing. What makes a good writer for a script consultant? Learn what a script consultant does and how they can help you improve a script and become a better writer Understand cinema's transformative power through A Few Good Men (1992), My Cousin Vinny (1992), The Ice Storm (1997) Subscribe on Apple Podcasts, follow on Spotify or wherever you listen to your podcasts for more movies that impacted your life!  Share your favourite movies that impacted your life on X (@leytonrocks) and leave a 5-star review and tell us which 3 films impacted your adult life. Best ones get read out on the podcast About my Guest:   Danny Manus is a script consultant and founder of No BullScript Consulting, which has been helping writers since 2009.  For more about his script consultancy services see https://www.nobullscript.net/about-daniel/    Credits:   Written, produced, and hosted by Stuart Wright for [Britflicks.com](https://www.britflicks.com/britflicks-podcast/)   Learn more about your ad choices. Visit megaphone.fm/adchoices

Familjen har begått ett massmord på Sharon Tate, hennes ofödda barn och Sharons vänner. Har ni inte lyssnat på avsnitt 226-229 av Massmördarpodden om massmordet tipsar vi om att ni gör det innan ni lysnar på detta avsnitt. Men Charles är inte nöjd - nu ska han visa hur man egentligen ska mörda oskyldiga människor.Manus av Jennie Sterner. Klippning av Josefine Molén.Reklam. Om du gillar Mördarpodden kan du vara med och sponsra den på Patreon. https://www.patreon.com/user?u=10466265 Som tack får du tillgång till förhandlyssning och alla avsnitt från Richard Chase del 1 och framåt utan reklam. För dig som sponsrar Mördarpodden via Patreon finns samtliga 16 delar i vår serie om Charles Manson tillgängliga redan nu helt reklamfritt!Vill du som inte redan sponsrar oss via Patreon ta del av serien om Charles Manson helt reklamfritt så var med och sponsra podden på Patreon med ett valfritt belopp: https://www.patreon.com/user?u=10466265Vill du höra ett specifikt fall i podden? Önska dina fall i det här formuläret: https://docs.google.com/forms/d/e/1FAIpQLSfDlQxf9SgZyeGS-qFPaB4BP-L59lQhs7BbZACfwk7xSs-AFw/viewform?fbclid=IwAR0astYAY_SJLcst89FwKaPIeHHV9zlfAxEz6Cmrh37bbMwvMHGc8z5cwg4Det här är en podcast av Dan Hörning och Josefine Molén.Instagram: @mordarpoddenE-post: zimwaypodcast@gmail.comFölj Josefine Molén här:https://www.instagram.com/j.molenFölj Dan Hörning här:X: @danhorningInstagram: https://www.instagram.com/dan_horning/?hl=enYoutube: https://www.youtube.com/channel/UCV2Qb7SmL9mejE5RCv1chwgErik SegerstedtSpotify:https://open.spotify.com/artist/63q3l3pKBpvqEjUM5Vf1TG?si=fYtdOwIvTn6noQJW6ffPwwInstagram: https://instagram.com/e Hosted on Acast. See acast.com/privacy for more information.

Kindred Ventures' Steve Jang talks with TITV Host Akash Pasricha about the massive 60-gigawatt AI infrastructure supply gap looming by 2030 and his firm's new $355 million fund. We also talk with OpenAI and Google reporter Erin Woo about star researcher Noam Shazeer leaving Google for OpenAI, Asia Bureau Chief Jing Yang about the Chinese government forcing Meta to unwind its $2 billion acquisition of AI agent startup Manus, AI reporter Stephanie Palazzolo about Hermes—a new open-source agent platform outperforming Open Claw on GitHub, and Amazon reporter Catherine Perloff about why enterprises are choosing Amazon's Trainium and Inferentia chips over Nvidia to slash costs by 80%.Articles discussed on this episode: https://www.theinformation.com/articles/manus-revenue-soars-original-investors-move-reverse-meta-dealhttps://www.theinformation.com/articles/star-google-ai-researcher-shazeer-joins-openaihttps://www.theinformation.com/newsletters/ai-agenda/competitor-openclaw-emergesSubscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/Chapters:00:00 - Introduction01:13 - Google AI Star Noam Shazeer Joins OpenAI05:59 - China Forces Meta to Reverse $2B Manus Acquisition10:00 - Hermes Emerges as Open Claw's New Open-Source Agent Rival17:13 - Amazon Chip Play Attacks Nvidia on Price23:33 - Kindred Ventures' Steve Jang on $355M Fund & 60GW Compute Shortage

In this episode, we share exciting personal news alongside discussions on Meta's unwinding of their $2 billion Manus acquisition and the repercussions stemming from that decision. We also cover recent developments involving Anthropic's AI models, Apple's Siri updates, and Jeff Bezos' Prometheus company raising $14 billion for physical AI innovation.Chapters00:00 Introduction00:59 Personal News02:01 Meta's Manus Acquisition Unwinding06:00 Anthropic's AI Model Controversy14:59 Siri's Future Changes16:50 Bezos' Prometheus Funding Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

If you're running a painting company and still handling your own scheduling, emails, social media, and back-office tasks — this episode is for you.In this episode of the Elite Business Advice Podcast, host Chris Moore, founder of Elite Business Advisors, tackles one of the most common and costly mistakes painting contractors and painting business owners make: waiting too long to hire administrative help.What You'll Learn:·      Why every painting contractor needs admin support — and why most wait far too long to get it·      Creative ways to hire admin help at every stage of your business — from virtual assistants and part-time help under $500K, to a network hire between $500K–$1M, to full-time staff at $1M+·      How to use AI tools (including tools like Manus) to handle graphic creation, redesigns, and repetitive tasks·      How to build your admin task list — the work they take off your plate and the growth work they can drive for you (social posting, Google My Business updates, email campaigns to past clients, marketing coordination, and more)·      The systems that make admin hires actually work — Trello, SOPs/Admin Playbooks, Loom videos, and building processes as you scale·      The ROI question every painting business owner needs to answer: What would 5 to 7 hours back per week do for your company?Interested to learn more about what we do to help Painting Contractors all over North America? Schedule a free business analysis meeting with us at www.elitebusinessadvisors.com!

If you are within three feet of Ed Mathews, you are probably talking about real estate. This week the conversation is with Tom Dunkel, managing principal at Eagle Capital Investments, and it is a clinic in how to vet a deal before a dollar leaves your account. Tom has been a full-time investor for two decades. Over that span he has raised more than $50 million in private capital from a network of investors who lean on his experience to place money into alternatives most people never see: multifamily, self-storage, mobile home parks, medical office, and private lending. His pitch is simple. Real diversification is not large cap versus small cap or value versus growth. It is owning assets that do not move when a headline does. As Tom puts it, a tsunami hitting Japan can knock the stock market down 15 percent overnight, but it does nothing to an apartment building in Phoenix or a storage facility in North Carolina. The backbone of the episode is Tom's SAFE Investing Method, the same screen he uses every day. S is for sponsor: who are you writing the check to, what is their track record, and have you earned the right to ask the hard questions. A is for asset: if you cannot explain the investment to your kid or your elderly parent, you do not understand it well enough to fund it. F is for financials: do the projections hold up, and has this sponsor actually hit numbers like these before. E is for exit: you cannot click your way out of a syndication on a Tuesday afternoon, so you need to know exactly what has to happen, and over what time horizon, before your money comes back. Then Tom goes off the mainstream script on taxes. The standard advice is to 1031 exchange again and again until you die and hand your heirs a stepped-up basis. Tom's question is blunt: do you really want to be managing properties at 90 the way his mother could be. He prefers the lazy man's 1031, taking the gain, then using fresh depreciation from the next deal to shelter income, all without the rigid timelines and same-title rules that make a true 1031 nearly impossible across a group of 20 or 30 investors. Pay the freedom tax, he argues, and buy yourself passive income and time. The buy box conversation is just as practical. Tom likes private lending for first-position security and monthly checks. He likes mobile home parks and co-living because they answer the housing affordability crisis with real, unsubsidized supply, and he breaks down how a Philadelphia operator turns a $1,000 row home into $3,000 a month by renting furnished rooms to tenants on fixed income. He covers where self-storage sits after its boom and consolidation, and why he treats it like multifamily underwriting now. On technology, Tom is candid that he is still early but already getting leverage from AI. His current workflow is to go back and forth with Claude to build a long, specific prompt, then hand it to Manus for deep research on a market like Phoenix multifamily. He even has an AI clone at tomdunkel.ai that will answer your investing questions, as long as you do not bring up the Eagles. The lightning round digs into purpose beyond family, the best advice he ever got from a nine-figure investor, a job he probably should have turned down, and how he defines success now as an empty nester: geographic and time freedom, plus the room to give back through Tunnel to Towers and a scholarship he started for a friend lost to ALS. Find Tom at investwitheagle.com, grab his book The Wealth Builder's Playbook, or talk to his clone at tomdunkel.ai. Chapters 00:00 Don't let the tax tail wag the freedom dog 01:00 Meet Tom Dunkel and Eagle Capital Investments 03:00 Why true diversification lives outside the stock market 04:00 The SAFE Investing Method: Sponsor, Asset, Financials, Exit 08:00 Taxes and the lazy man's 1031 exchange 13:00 The Wealth Builder's Playbook and being the "who" 17:00 The buy box: mobile home parks, co-living, multifamily 22:00 Where self-storage sits after the boom 24:00 Using Claude and Manus to move faster 27:00 Lightning round: purpose, significance, and legacy 30:00 The best advice he ever got 33:00 A decision he would take back 34:00 On the nightstand: Invest Like a Billionaire 36:00 Defining success as an empty nester 38:00 Golf, a rock and roll cover band, and where to find Tom This week's book: Invest Like a Billionaire: Unlocking the Wealth Secrets of the Ultra-Rich by Bob Fraser and Ben Fraser https://www.amazon.com/dp/B0F3W2SNDS?tag=clarkstholdin-20 More Real Estate Underground episodes: clarkst.com/podcast Elevista: elevista.com/podcast Elevista - Speed as a Service™Elevista Connect is the first AI-powered lead conversion system built for real estate investors.

Tuesday June 16, 2026 Meta Begins dismantling $2 billion Manus deal on China's orders

In this episode, we share exciting personal news alongside discussions on Meta's unwinding of their $2 billion Manus acquisition and the repercussions stemming from that decision. We also cover recent developments involving Anthropic's AI models, Apple's Siri updates, and Jeff Bezos' Prometheus company raising $14 billion for physical AI innovation.Chapters00:00 Introduction00:59 Personal News02:01 Meta's Manus Acquisition Unwinding06:00 Anthropic's AI Model Controversy14:59 Siri's Future Changes16:50 Bezos' Prometheus Funding Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we share exciting personal news alongside discussions on Meta's unwinding of their $2 billion Manus acquisition and the repercussions stemming from that decision. We also cover recent developments involving Anthropic's AI models, Apple's Siri updates, and Jeff Bezos' Prometheus company raising $14 billion for physical AI innovation.Chapters00:00 Introduction00:59 Personal News02:01 Meta's Manus Acquisition Unwinding06:00 Anthropic's AI Model Controversy14:59 Siri's Future Changes16:50 Bezos' Prometheus Funding Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we share exciting personal news alongside discussions on Meta's unwinding of their $2 billion Manus acquisition and the repercussions stemming from that decision. We also cover recent developments involving Anthropic's AI models, Apple's Siri updates, and Jeff Bezos' Prometheus company raising $14 billion for physical AI innovation.Chapters00:00 Introduction00:59 Personal News02:01 Meta's Manus Acquisition Unwinding06:00 Anthropic's AI Model Controversy14:59 Siri's Future Changes16:50 Bezos' Prometheus Funding Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

In this episode, we share exciting personal news alongside discussions on Meta's unwinding of their $2 billion Manus acquisition and the repercussions stemming from that decision. We also cover recent developments involving Anthropic's AI models, Apple's Siri updates, and Jeff Bezos' Prometheus company raising $14 billion for physical AI innovation.Chapters00:00 Introduction00:59 Personal News02:01 Meta's Manus Acquisition Unwinding06:00 Anthropic's AI Model Controversy14:59 Siri's Future Changes16:50 Bezos' Prometheus Funding Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we share exciting personal news alongside discussions on Meta's unwinding of their $2 billion Manus acquisition and the repercussions stemming from that decision. We also cover recent developments involving Anthropic's AI models, Apple's Siri updates, and Jeff Bezos' Prometheus company raising $14 billion for physical AI innovation.Chapters00:00 Introduction00:59 Personal News02:01 Meta's Manus Acquisition Unwinding06:00 Anthropic's AI Model Controversy14:59 Siri's Future Changes16:50 Bezos' Prometheus Funding Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we share exciting personal news alongside discussions on Meta's unwinding of their $2 billion Manus acquisition and the repercussions stemming from that decision. We also cover recent developments involving Anthropic's AI models, Apple's Siri updates, and Jeff Bezos' Prometheus company raising $14 billion for physical AI innovation.Chapters00:00 Introduction00:59 Personal News02:01 Meta's Manus Acquisition Unwinding06:00 Anthropic's AI Model Controversy14:59 Siri's Future Changes16:50 Bezos' Prometheus Funding Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter

In this episode, we share exciting personal news alongside discussions on Meta's unwinding of their $2 billion Manus acquisition and the repercussions stemming from that decision. We also cover recent developments involving Anthropic's AI models, Apple's Siri updates, and Jeff Bezos' Prometheus company raising $14 billion for physical AI innovation.Chapters00:00 Introduction00:59 Personal News02:01 Meta's Manus Acquisition Unwinding06:00 Anthropic's AI Model Controversy14:59 Siri's Future Changes16:50 Bezos' Prometheus Funding Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleGet the AI Chat Daily Newsletter: https://www.aichatdaily.com/newsletter See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

It's not clear which states are involved, but they're asking about everything from OpenAI's ad policies to its handling of health data. Also, Meta started dismantling its $2 billion Manus acquisition after Beijing ordered the deal reversed. And, Amazon CEO Andy Jassy may have been the source of security concerns that led Anthropic to cut off worldwide access to two models on Friday. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Flera personer visste att 21-årige James Stoneham ville mörda sin ex-flickvän, 20-åriga Adriana Donato. Ingen sa något till Adriana. Och därför gick hon med på att sätta sig i James bil den 23 augusti 2012. Kvällen som skulle bli hennes sista i livet.Manus av Sofie Karlsson. Klippning av Josefine Molén.Reklam. Om du gillar Mördarpodden kan du vara med och sponsra den på Patreon. https://www.patreon.com/user?u=10466265.Som tack får du tillgång till förhandlyssning och alla avsnitt från Richard Chase del 1 och framåt utan reklam. Vill du höra ett specifikt fall i podden? Önska dina fall i det här formuläret: https://docs.google.com/forms/d/e/1FAIpQLSfDlQxf9SgZyeGS-qFPaB4BP-L59lQhs7BbZACfwk7xSs-AFw/viewform?fbclid=IwAR0astYAY_SJLcst89FwKaPIeHHV9zlfAxEz6Cmrh37bbMwvMHGc8z5cwg4Det här är en podcast av Dan Hörning och Josefine Molén.Instagram: @mordarpoddenE-post: zimwaypodcast@gmail.comFölj Josefine Molén här:https://www.instagram.com/j.molenFölj Dan Hörning här:X: @danhorningInstagram: https://www.instagram.com/dan_horning/?hl=enYoutube: https://www.youtube.com/channel/UCV2Qb7SmL9mejE5RCv1chwgErik SegerstedtSpotify:https://open.spotify.com/artist/63q3l3pKBpvqEjUM5Vf1TG?si=fYtdOwIvTn6noQJW6ffPwwInstagram: https://instagram.com/e Hosted on Acast. See acast.com/privacy for more information.

A viral Wall Street chart has kicked off a new round of AI bubble panic, but NLW argues the market is reading it wrong. The real story isn't collapsing demand — it's the shift from the token subsidy era to the token scarcity era, where companies are learning to route AI usage more efficiently. In the headlines: SpaceX's IPO, Bezos' Prometheus raise, Meta's Manus split, chip supply chain crunches, and Goldman's trillion-dollar AI infrastructure forecast.Check out the new ⁠https://aidailybrief.ai/⁠Brought to you by:KPMG – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠kpmg.com/us/Sophisticated⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Bolt - Claim a free month of Bolt Pro - ⁠⁠⁠⁠⁠⁠⁠https://bolt.new/partner/aidb/⁠⁠⁠⁠⁠⁠⁠Outsystems - Stop wondering how AI will change your business and start building the agents that will lead it - http://outsystems.com/Scrunch - The AI customer experience platform - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://scrunch.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Zenflow Work - Agents for knowledge work - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://zenflow.free/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai

Ce jeudi 11 juin, François Sorel a reçu Jérôme Marin, fondateur de cafetech.fr, Claudia Cohen, journaliste chez Bloomberg, et Frédéric Simottel, journaliste BFM Business. Ils sont revenus sur la possible baisse des prix d'OpenAI face à la concurrence, la finalisation de la séparation opérationnelle entre Meta et Manus, ainsi que la restructuration chez Ubisoft, dans l'émission Tech & Co, la quotidienne, sur BFM Business. Retrouvez l'émission du lundi au jeudi et réécoutez la en podcast.

Jocke krisar och tvingas flytta hem till sin mammas hyreshus. Som aldrig är tyst. En kväll har någon klottat i trapphuset och budskapet är riktat mot Jocke personligen. Vem? Varför? Fuck Jocke Fransson är en psykologisk thriller i fem delar, som blandar pulshöjande spänning med humor och lätthet. Manus av Paolo Iskra, i regi av Henrik Georgsson. Dramaturg: Magnus Lindman.Lyssna på Fuck Jocke Fransson, och följ P3 Serie i Sveriges Radios app.

In Pacific Waves today: Livestock deaths impact Sinlaku recovery on Saipan; Manus communities affected by pumice from Titan Ridge volcano; PNG Pumice rafts could linger for months - scientist. Go to this episode on rnz.co.nz for more details

Jocke krisar och tvingas flytta hem till sin mammas hyreshus. Som aldrig är tyst. En kväll har någon klottat i trapphuset och budskapet är riktat mot Jocke personligen. Vem? Varför? Fuck Jocke Fransson är en psykologisk thriller i fem delar, som blandar pulshöjande spänning med humor och lätthet. Manus av Paolo Iskra, i regi av Henrik Georgsson. Dramaturg: Magnus Lindman.Lyssna på Fuck Jocke Fransson, och följ P3 Serie i Sveriges Radios app.

Microsoft dominated Build with Scout, an always-on Teams agent, the Surface RTX Spark Dev Box, its first reasoning model MAI-Thinking-1 aimed squarely at Anthropic, and Project Solara for agent-first devices. Trump signed a scaled-back AI executive order on cybersecurity. Microsoft announces Scout, an always-on enterprise AI agent built on OpenClaw that appears as a Microsoft Teams contact to automate tasks such as scheduling (Wired) Microsoft unveils a Surface RTX Spark Dev Box, featuring Nvidia's Arm-based RTX Spark, 128GB of unified memory, and a 100W thermal envelope, for local AI tasks (The Verge) Microsoft debuts MAI-Thinking-1, its first advanced reasoning AI model, trained "from the ground up on clean data, without distillation from third-party models" (The Verge) Microsoft unveils Project Solara, an Android-based platform for agent-first devices, with concept hardware and pilots planned at Best Buy, Target, and others (GeekWire) Microsoft unveils Microsoft Execution Containers, a Windows-level sandbox for AI agents, and says partners OpenAI, Nvidia, Manus, and Nous Research are using it (VentureBeat) President Trump signs a scaled-back AI EO that seeks to address AI's cybersecurity threats; sources say it imposes less scrutiny on AI than the scrapped version (Politico) Learn more about your ad choices. Visit megaphone.fm/adchoices

China is running the EV playbook on humanoid robots — and it's working https://restofworld.org/2026/china-humanoid-robots-unitree-agibot-tesla-optimus/Flexion https://flexion .ai/ ETH robotics club https://www.ethrobotics.ch/ The co-founders of Manus are exploring options to fulfill Beijing's demand to unwind a controversial takeover by Meta, including raising about $1 billion from external investors to buy back the Chinese-founded AI operation https://www.bloomberg.com/news/articles/2026-05-21/manus-weighs-raising-1-billion-to-unwind-meta-takeover Agentic AI in Retail: How Autonomous Shopping Is Redefining the Customer Journeyhttps://www.bain.com/insights/agentic-ai-in-retail-how-autonomous-shopping-redefining-customer-journey/The fundamental issue with independent agentic commerce https://x.com/eric_seufert/status/2034727848498667642 Softbank announced a plan to spend ‘up to' €75bn ($87bn) to build 5GW of AI data centres in France, leveraging ‘data sovereignty' on one hand and France's nuclear-generated electricity on the other. https://group.softbank/en/news/press/20260531_0 IA jobpocalypse ou WFH ? https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6787638 Ferrari Luce https://www.ferrari.com/en-EN/auto/ferrari-luce Acquired podcast https://www.acquired.fm/episodes/ferrari INSPIRATION #EVENT :: Niptech Explore - Olivier Clerc 30.06 à Lausanne https://boutique.cah.ch/products/niptech-presente-au-dela-des-4-accords-tolteques-avec-olivier-clerc #LEARNING :: The "Gell-Mann amnesia effect" https://x.com/syde/status/2060680824324821445?s=20 #BOOK :: The Unheard Cry for Meaning: Psychotherapy and Humanism by Viktor Emil Frankl https://www.amazon.com/Unheard-Cry-Meaning-Psychotherapy-Humanism/dp/0671247360 #PODCAST :: Yuval Noah Harari https://www.nytimes.com/2026/05/26/opinion/ezra-klein-podcast-yuval-noah-harari.html #QUOTE ::“The truth is that as the struggle for survival has subsided, the question has emerged: survival for what? Ever more people today have the means to live but no meaning to live for.” Viktor Frankl, The Unheard Cry for Meaning Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

In this week's Behind The Scenes episode of The FasterFreedom Show, Sam breaks down how he's using AI across his educational business and social media content creation—and where he believes these tools are helping the most.He walks through the different platforms and programs he's experimented with, including tools like Claude, ChatGPT, Manus, and others, sharing which ones he uses the most today, which ones he's pulled back from, and why. You'll hear how AI has improved efficiency, brainstorming, content workflows, and idea generation, while also learning where overreliance on AI can start to hurt authenticity and creativity.From practical business applications to the evolving role of AI in content creation, this episode gives a real, behind-the-scenes look at how these tools can be leveraged effectively without losing the human side that actually builds trust and connection.Join my PREMIUM real estate community on Skool: ⁠⁠⁠https://www.skool.com/fasterfreedomrelaunchpro⁠⁠⁠FasterFreedom Capital Connection: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://fasterfreedomcapital.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Free Rental Investment Training: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://freerentalwebinar.com⁠⁠⁠⁠

In this episode, Dylan Silver and David Berneman discuss the intricacies of property management, the impact of AI tools like Claude and Manus on real estate operations, and strategies for maintaining control and quality in property management. They explore how technology is transforming the industry and share practical insights for investors and managers.   Professional Real Estate Investors - How we can help you: Investor Fuel Mastermind:  Learn more about the Investor Fuel Mastermind, including 100% deal financing, massive discounts from vendors and sponsors you're already using, our world class community of over 150 members, and SO much more here: http://www.investorfuel.com/apply   Investor Machine Marketing Partnership:  Are you looking for consistent, high quality lead generation? Investor Machine is America's #1 lead generation service professional investors. Investor Machine provides true 'white glove' support to help you build the perfect marketing plan, then we'll execute it for you…talking and working together on an ongoing basis to help you hit YOUR goals! Learn more here: http://www.investormachine.com   Coaching with Mike Hambright:  Interested in 1 on 1 coaching with Mike Hambright? Mike coaches entrepreneurs looking to level up, build coaching or service based businesses (Mike runs multiple 7 and 8 figure a year businesses), building a coaching program and more. Learn more here: https://investorfuel.com/coachingwithmike   Attend a Vacation/Mastermind Retreat with Mike Hambright: Interested in joining a "mini-mastermind" with Mike and his private clients on an upcoming "Retreat", either at locations like Cabo San Lucas, Napa, Park City ski trip, Yellowstone, or even at Mike's East Texas "Big H Ranch"? Learn more here: http://www.investorfuel.com/retreat   Property Insurance: Join the largest and most investor friendly property insurance provider in 2 minutes. Free to join, and insure all your flips and rentals within minutes! There is NO easier insurance provider on the planet (turn insurance on or off in 1 minute without talking to anyone!), and there's no 15-30% agent mark up through this platform!  Register here: https://myinvestorinsurance.com/   New Real Estate Investors - How we can work together: Investor Fuel Club (Coaching and Deal Partner Community): Looking to kickstart your real estate investing career? Join our one of a kind Coaching Community, Investor Fuel Club, where you'll get trained by some of the best real estate investors in America, and partner with them on deals! You don't need $ for deals…we'll partner with you and hold your hand along the way! Learn More here: http://www.investorfuel.com/club   —--------------------

No Braincast 634, Carlos Merigo, Cris Dias, Hiago Vinícius e Luiz Yassuda discutem o vibe coding, a nova febre da IA que promete permitir que qualquer pessoa crie aplicativos, dashboards, automações e protótipos apenas descrevendo o que quer. A conversa passa por Claude, Codex, Lovable, Replit, Bolt, Cursor, Manus, low-code, SaaSpocalipse, token maxing e a fantasia do “unicórnio de uma pessoa só”. Afinal, estamos diante de uma revolução criativa, em que mais gente pode transformar ideias em produtos, ou de uma fábrica de gambiarras em escala industrial? Também entram no papo os riscos de segurança, vazamento de dados, dependência das big techs, código ruim, Shadow IT, empresas tentando substituir times inteiros por IA e a importância de repertório, critério e bom gosto num mundo onde executar ficou mais fácil, mas saber o que pedir continua sendo o grande desafio. No Qual é a Boa, ainda tem Cinemático sobre Obsessão, jogos como Crimson Desert e The Last Caretaker, o Anti-Authoritarian Toolkit, IA em Curso, The Traitors e Momento Faustão. -- CONHEÇA OS CURSOS DA ESCOLA DE IA DA PUCPR https://posdigital.pucpr.br/areas/escola-de-ia?utm_source=podcast&utm_medium=braincast&utm_campaign=pucpr_externo_leads_ativacao-1_escola-ia&utm_content=audio_atributo_26-05-17 -- 04:17 PAUTA 05:37 O que é vibe coding 08:31 Origem e ferramentas 09:52 É programação mesmo 14:50 SaaSpocalipse e limites 19:59 Dilema do monstro 25:30 Token maxing e tralha 27:50 Low code e democratização 30:37 Agentes e checagem 34:10 Programadores e IA 34:52 Autocomplete e Vibe Code 38:52 Hype e corrida da IA 39:56 Segurança e dados 41:45 Automação pessoal útil 43:55 SaaS pequeno vs grande 46:07 Sites leves sem WordPress 49:57 Canva e custos ocultos 57:09 Dependência e mediação 59:45 Legado corporativo e suporte 01:02:57 Habilidades e formação 01:11:40 Bom gosto e repertório 01:12:46 Curiosidade como profissão 01:15:03 Educação e base teórica 01:18:00 A febre dos prompts 01:18:50 QUAL É A BOA 01:28:56 Toolkit anti autoritário 01:34:38 Cupom IA em Curso 01:35:24 Reality The Traitors 01:40:06 Momento Faustão -- ✳️ TORNE-SE MEMBRO DO B9 E GANHE BENEFÍCIOS: Braincast secreto; grupo de assinantes no Telegram; e episódios sem anúncios!

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!On the product side, everyone is getting Computer - Perplexity, Manus, Cursor, and so on. Meanwhile on the research side, agentic evals like TerminalBench and GDPVal are also assuming computer (Harbor). On both ends, the consolidating LLM OS stack has become a standard toolkit, and Daytona is one of a small set of AI Infra companies that are booming because of it.“The end of localhost” has been Ivan Burazin's obsession for more than a decade.Something that is all too familiar…Long before agents became the default way people talked about software development, Ivan was already chasing the idea that development should not depend on a fragile local machine. CodeAnywhere, one of the first browser-based IDEs, was an early attempt at that future: move the development environment into the cloud, make setup reproducible, and free developers from the endless “works on my machine” tax.The thesis was directionally right, but the market wasn't ready yet.However, agents changed that. They do not care about a laptop, desk setup, or favorite editor. They need a computer they can access through an API: something stateful enough to keep working, fast enough to spin up instantly, flexible enough to resize, isolated enough to be safe, and composable enough to run the messy real-world workflows that real software engineering actually requires.Daytona isn't just selling “sandboxes” in the narrow code-execution sense. It is the latest version of Ivan's original localhost thesis.In this episode, Daytona's CEO joins swyx to explain why AI agents need more than code execution boxes: they need composable computers, stateful sandboxes, instant startup, dynamic resources, and infrastructure that can survive workloads going from zero to 100,000 CPUs.We go deep on the new agent compute market: Daytona's hard pivot from human dev environments to AI sandboxes, the New Year's Eve MVP that customers begged for, why Daytona runs on bare metal with its own scheduler, how one customer runs almost 850,000 sandboxes a day, and why RL/eval workloads went from 0% to roughly 50% of usage in just months. Ivan also explains why agents need Windows and macOS machines, why CLI may matter more than MCP, why Kubernetes is painful for this workload, and why the future AI cloud may look more like Stripe than AWS.We discuss:* How Daytona grew out of CodeAnywhere, Shift, and the “end of localhost” thesis* Why Daytona pivoted from human dev environments to AI sandboxes* Why agents need composable computers instead of disposable code execution boxes* The New Year's Eve MVP that customers chased API keys for* Why Daytona chose bare metal, stateful snapshots, and its own scheduler* How Daytona spins up one sandbox in ~60ms and 50,000 sandboxes in ~75 seconds* Why Daytona's biggest customer runs ~850,000 sandboxes a day* How RL/eval workloads create zero-to-100,000 CPU spikes* Why RL workloads went from 0% to roughly 50% of Daytona usage* Why customers compare Daytona against EKS/GKS and say they're “never going back”* Why every AI agent may need a computer, including Windows and macOS environments* The Apple licensing constraints that make macOS sandboxes hard* Why CLI gives agents more power than MCP* How open source helps agents integrate Daytona* Why agent-generated PRs may break today's CI/CD assumptions* Why AI SaaS companies reselling tokens may face a cold shower* Why the AI cloud may look more like Stripe than AWSIvan Burazin* LinkedIn: https://www.linkedin.com/in/ivanburazin* X: https://x.com/ivanburazinDaytona* Website: https://www.daytona.io* X: https://x.com/daytonaioTimestamps* 00:00:00 Hook* 00:01:12 Introduction* 00:03:15 CodeAnywhere, Shift, and the end of localhost* 00:05:58 What Daytona is: composable computers for AI agents* 00:08:07 The pivot from dev environments to AI sandboxes* 00:10:17 The New Year's Eve MVP and customers begging for API keys* 00:12:56 Bare metal, stateful sandboxes, and Daytona's scheduler* 00:17:28 60ms startup, 50,000 sandboxes, and 850K daily runs* 00:21:53 Spiky RL/eval workloads and the new agent infra problem* 00:28:12 RL workloads, Kubernetes pain, and dynamic resizing* 00:33:31 Why every AI agent needs a computer* 00:38:48 macOS sandboxes and Apple's licensing problem* 00:44:28 Why CLI may matter more than MCP* 00:48:11 Open source, GitHub stars, and agent integration* 00:53:11 Git, CI/CD, and agent collaboration bottlenecks* 00:58:15 Founder life and building a 25-person infra company* 01:02:44 AI SaaS, token resale, and API-first business models* 01:06:10 GPU sandboxes, data centers, and compute growth* 01:09:48 Why the AI cloud may look more like Stripe than AWS* 01:11:26 Closing thoughtsTranscriptIntroduction: Daytona, CodeAnywhere, and the End of LocalhostSwyx [00:00:02]: Okay, we're in the studio with Ivan Burazin, CEO of Daytona. Welcome.Ivan [00:00:07]: Thanks for having me, man.Swyx [00:00:08]: Ivan, you and I go back.Ivan [00:00:10]: Way back.Swyx [00:00:11]: How I don't even know how, you found, did you reach out or, for Shift.Ivan [00:00:17]: I reached out to you. The reason was you - we were just - we were thinking about I was one of the co-founders of CodeAnywhere, the first browser-based IDE, and so we were thinking a long time of, localhost should die. And you had this article.Swyx [00:00:29]: End of localhost.Ivan [00:00:30]: Then I reached out to you because of that, and then we talked, and I was actually at a different job and learning about I was the head of, developer experience, and you were quite well-versed in that, and I actually reached out to you, among other people, how do we go about that? What are the key things and whatnot at this point in time? And you were nice enough to take the call, and I remember I was late on your call with you.Swyx [00:00:51]: I don't remember.Ivan [00:00:52]: I remember because I was with my then I'm thinking of a girlfriend or wife at that point in time, I'm not sure. It's the same person, so that's great, and I was late ‘cause we were, in, Italy on, vacation, and then I was late for something. I felt so bad, and you were so nice to be, good about.Swyx [00:01:10]: The reason I'm nice is because I'm also late to other people, so it's like, who's, who's without sin here, yeah, so I have to, for those who don't know, InfoBip Shift, there's this whole thing that, you did in the past, and, and that was basically one of the inspirations for me starting AI Engineer, which is like, I have to thank you for giving me that push to be like, “Oh, you can, you can build and sell conferences?”Ivan [00:01:34]: I remember you asked you asked me at the beginning to give me advisory shares, and I was so focused on what we were doing, I said no, and I should've took the advisory shares. So I'm sorry, dude. But anyway.Swyx [00:01:43]: We're not, we're not venture backed.Ivan [00:01:44]: No, it doesn't matter.Swyx [00:01:45]: It's Yeah, anyway, so I think what's impressive about you is that CodeAnywhere is the thing that you've been trying to build, and, you kind of put it on hold and then came back after InfoBip. Just give us the story, do you - the story and the origin story, going into Daytona.From CodeAnywhere and Shift to DaytonaIvan [00:02:05]: Sure. Like, really way back, me and my co-founder have been together. I say this, I've said this multiple times, it's like we were married and divorced and married. Some people actually ask me is my co-founder my partner. they thought it literally. It's not literally, but we have done multiple companies together, and to your point, we had this shift where we went from the CodeAnywhere to the conference called Shift, and then back to, Daytona. We originally started stacking servers, doing like virtualization in the early 2000s and, routers and doing basically all these things, at a foundational level, and that was a services company which we sold to focus on what my co-founder actually invented, which was the very first browser-based IDE, right, I say the first. Before us was actually Heroku. They did it for a very short time until they became Heroku. But outside of them, we were the only one, and it was called.Swyx [00:02:55]: There was Cloud9.Ivan [00:02:57]: Cloud9 came out slightly after us. There was Replit, which came out when we stopped doing it, Replit came out, and they have been successful since then, which is great. There was Nitrous.io. There was quite a few that existed at the time, but it was like too early. But the interesting part is that we, at that point in time, because there was no VS Code, there was no Kubernetes, and Docker had just started when we Or I'm not sure if it was even public at that point in time. And so we had to build everything to the whole stack ourselves and that was the key learning that we brought into and that we've been using in Daytona today. So it was super early. There's about 3 million people used CodeAnywhere. It was slightly, it was angel-backed more than venture-backed. We ended up paying everyone back because it didn't have that sort of scale. But, three years ago, we started something similar with Daytona, which is not what we are today, but it was automating dev environments for human engineers, the basically the underlying stack of CodeAnywhere. And then we did a hard pivot last January to sandboxes. And so here we are.Swyx [00:04:01]: Historic pivot, yeah, and, it's one of those things where, I had independently invested in CodeAnywhere, but also in E2B, and then both of you pivoted into the same thing, and I'm like, “F**k.”Ivan [00:04:12]: You invested, you invested in Daytona. You invested in Daytona. But you were the first If we had not got your check, we wouldn't have done it.Swyx [00:04:18]: No way.Ivan [00:04:19]: No, it was like, “We have to get him on board first,” and you were that kicker that we, that got us off the ground.Swyx [00:04:23]: No, because you were putting me on your pitch deck, man. I was like, “Man, this is like a good trip if I don't invest.”Ivan [00:04:29]: That's because it was your quote. It's like we.Swyx [00:04:30]: Yeah. It's the end of localhost.Ivan [00:04:31]: Did a bunch of research about end of localhost and who was interested in that,.Swyx [00:04:34]: No, that's like, I put, I wrote that blog post, and every single company in that field reached out to me, and then every VC who was receiving those pitches then also had to call me and, talk it, talk through it with me.Ivan [00:04:47]: It's finally happening though.Swyx [00:04:48]: It was really super interesting.Ivan [00:04:48]: It's finally happening.Swyx [00:04:49]: It's finally happening.Ivan [00:04:49]: Yeah, it's finally.Swyx [00:04:49]: It's finally happening, with maybe sort of non-human users. Yeah, so what is Daytona today? Let's get like a quick description. I'm wearing the shirt.What Daytona Is Today: Composable Computers for AI AgentsIvan [00:04:58]: You're wearing the shirt. Yes,.Swyx [00:04:59]: It says, I think your branding is very good. Like, it's very consistent. It runs AI code. Like, it cannot be simpler.Ivan [00:05:05]: Exactly, but we're gonna probably have to change that.Swyx [00:05:07]: Oh, s**t.Ivan [00:05:07]: It's also a subset of what we do. Unfortunately, we really love this, Run AI Code is super simple. People interpret it different ways. I think we've given out 5,000, 6,000 of these shirts. People wear them with pride because it doesn't really market about us.Swyx [00:05:21]: Yeah, Daytona's on the back.Ivan [00:05:22]: It markets the back. It markets to the person itself, so I think we did a really good job on that one. But it is also a subset of what we do, because people, when they think about Run AI Code, they just think about these small, let's call it isolates, code execution boxes that, you send some code, you get an output. Whereas what Daytona is today is essentially composable computers for AI agents. It is, the market calls them sandboxes which can be misleading.Swyx [00:05:44]: All these things. All these things on.Ivan [00:05:45]: Yeah, exactly, ‘cause it can be misleading ‘cause people usually think about sandboxes as a demo or a test environment versus a production-grade environment. But what Daytona does, if you think of the laptop that you have in front of you or the computer that's over there, or, my wife is an architect, so she has like a Windows with a 3D graphics card inside to do 3D rendering. Like, as humans, we have different computers or different compositions of computers. And our belief is strongly that agents today and going forward will need all these different compositions of computers to do different types of tasks. And so we offer that basically through an API.Swyx [00:06:19]: Yeah, to give people - I'm trying to sort of front-load all the aha moments or the wow moments so that people can, stay engaged and click like and subscribe. the market is exploding, right? Like, you have been reporting 74% month-on-month growth, and it also, it's just been growing for a while. Like, it's been going like this. And every single - It's not just you guys. It's every single.Ivan [00:06:41]: Everyone, yeah.Swyx [00:06:42]: Sort of, compute provider. I don't know if you agree with me saying compute provider or not.Ivan [00:06:48]: It's fine.Swyx [00:06:48]: Yeah. So like organically PLG-driven growth, but also enterprise is doing super well, I think I wanna rewind to January of last year when you did the pivot. Like, so you obviously called this market early, and you were positioned for it, and you are now one of the market leaders. But what was the insight that made you do the pivot?The Pivot: From Human Dev Environments to Agent SandboxesIvan [00:07:06]: The insight that made us do this pivot is the quarter before that, so end of 2024, when we had - Basically, we did a demo with - I don't I think we discussed this as well, Devin was not public. You actually gave me access to Devin at that time. So Devin.Swyx [00:07:25]: I did?Ivan [00:07:26]: Yeah, you gave me access.Swyx [00:07:26]: I don't think I was supposed.Ivan [00:07:27]: Yeah, exactly.Swyx [00:07:28]: Yeah, I.Ivan [00:07:28]: So it doesn't matter. You.Swyx [00:07:29]: Yeah. I gave like three friends access.Ivan [00:07:31]: Yeah, or it was a call and you showed it to me. It doesn't matter. but OpenDevin was available, which is now called OpenHands. And so we're like, “Oh, this seems to be a thing. This is not public. Let's take our for human automation of dev environments and take, OpenDevin and launch that as a SaaS.” And we did that. Not very many people signed up and used it, but a lot of people reached out that were building agents, and they were like, “Hey, my agent needs a compute sandbox runtime,” whatever you wanna call it. I forgot what it was called at that point. And then we were like, “Oh, amazing. This is a new market. Here is our infrastructure. Here's our product, and go.” And what we found really fast, soon, was that people did not like what we had built. It didn't work. And I remember talking to people at the beginning when we're doing this, the sandbox we're building for agents. People were like, “Oh, why is it different? It's the same thing. We have like EC2, we have VMs, we have all these things.” But we saw that everyone we gave it to, it was like 20, 30 people, they all said, “No.” Like, “This is not what we need. This sort of breaks.” And basically, me and my co-founder not knowing a lot about - ‘cause we're infra people. We're not AI people. So I basically took it upon myself to like watch every single podcast that exists, including all of, all of these and all that, and sort of get up to date, read all the blogs, like get, understand what's going on.Swyx [00:08:45]: Do you wanna shout out who else was useful, just in case people are also looking.Ivan [00:08:49]: Generally we -, I looked at There's a few of podcast, different segments and different types. So there's you guys, No Priors, Bill Gurley's was great while.Swyx [00:09:04]: VG2, yeah.Ivan [00:09:05]: Yeah, while it was around. So there's a few. 20VC is interesting from a different dynamic, and some are different dynamic. But there was, also Red Points.Swyx [00:09:14]: We're not really about the compute market.Ivan [00:09:15]: It was also already - Sorry?Swyx [00:09:16]: You're, you want - You're looking at the agent infra market.Ivan [00:09:19]: I was looking at the agent market and the AI market in general and sort of understanding who are the players, what the perception, and how that goes. And like obviously you complement this with like going to conferences, going to events, going to meetups, reading white papers, like doing all the things that you have to do to understand what's happening. And so when we figured, when we sort of had an idea of what we had to build, literally over the New Year's Eve, literally on New Year's Eve, I half vibe coded the first MVP, first minimal viable product of what Daytona is today. And I went to sleep at like 3:00 AM or something like that. I was doing - I just put my like baby daughter and wife to sleep and, Happy New Year's, and go back to just, doing this. And I sent it to my co-founder, my CTO, and he saw it in the morning. He's like, “This is absolute garbage.” “Do not show this to anybody at all, but the idea is good.” And so he took two weeks, and he rebuilt it.Swyx [00:10:09]: Did it like look like that? Listen, I - It was rough idea.Ivan [00:10:12]: Oh, not even, not even close. Like it was it was way worse. But it was like a very - It was a simplistic view of what it should be. Like, it worked, but it was not ideal. And so he went, we went down the whole, which is his job as CTO, to go, and he came back with this version. We then called all the people that had said like, “This is garbage,” a quarter ago. And we set up these calls, and we gave it to - We just demoed it to everyone. And all the calls went long, every single one. They were 15-minute calls, and they all went to like 25, 30 minutes or whatnot. And everyone said, “We need, we want access.” There was no login, just an API key, ‘cause it was just a beta or an alpha. And they said, “Oh, we want access.” And we're like, “Sure, yeah. Okay, thank you very much.” But after like the next day, if we'd not send it, every single one, like every call that we did, everyone came back, “Where is my API key?” Like everyone wanted it. We're like, “S**t.” Like this is it. Like I've never felt So one, the understanding to your point was like most people thought it was the same infrastructure for humans and agents. We understood a quarter ago it's not. We just didn't know what was the right primitive. And then when we came, and we can talk about what that is, and we gave it to these people, I've never seen, I've never experienced - I've done multiple companies in my life. I've never experienced this, that people literally call you if you do not give them access. Like they want access right now. And so it's like, okay, they don't want this. the thing that they want doesn't seem to exist, or they have not found it, and they really want what we want. And then when we understood that we're onto something, and then when you think about the size of the market, like the market for human engineers and enterprise is a very large market, so think GitLab or whatnot. But the market for every single agent that will exist ever in the future is just like, what is that market? How big is that? And we're like, “We are all in on this.” And so that is where we made sort of the cut between the old product and the new one.Bare Metal, Stateful Sandboxes, and the Lambda + EC2 ModelSwyx [00:12:02]: Yeah. But it wasn't composable at the time?Ivan [00:12:05]: It was very - It was basically just a Linux box that you could change, that you could define number of CPUs, disk, and RAM. Like that is what you could do, but you couldn't have multiple operating systems, you couldn't resize it on the fly, you couldn't add a GPU, you couldn't do like all the things. It was just the, just the first sort of variation of that, yeah.Swyx [00:12:22]: Was it bare metal from the start?Ivan [00:12:24]: It was bare metal from the start. And so the interesting thing that we thought about right away, so our.Swyx [00:12:29]: Which, give people the background, what is the normal path?Ivan [00:12:32]: Yeah, so, basically most providers run this on top of VMs. And also.Swyx [00:12:37]: Firecracker.Ivan [00:12:38]: Yeah, they run on Firecracker and VM. And so we also fire - We can get - We have multiple isolation layers and we can do that. But the common way to do it is that they, one, that the state of the machine, or the hard disk is not part of the sandbox itself. And the other thing is they're not meant to last forever. So most of them are preemptible, like they can There's a time that they can live. And so our thought was when we were going into this is, agents will be like humans in the sense of you don't want your laptop to be shut down until you're done with work. Like, and you want to close the lid and open the lid, it's the same state. So you - Agents would want that, like the pause and come back. They want those two things. But also agents really want speed, right? Can they get it? So when we thought about it's like we need something insanely fast, how to make it fast, how to make it long-running, and stateful. And so those two things, it's like combining a Lambda and an EC2, right? Those two things together. And so we didn't have an idea how others did it, ‘cause we didn't know too that there was a market around this. It was more like, okay, this is what we need, what they need. And we looked at Kubernetes, it wasn't wasn't good enough for that. We looked at Nomad, it didn't enable that. And so our history in rewriting our own scheduler at CodeAnywhere is basically what my CTO came up with. Like, he's like, “Oh, the learnings from there,” and he brought it. And the funny thing is, our third co-founder, when he saw it, he's like, “Dude, what is this? This is like 2008.” Like, we went back in time, and he's like, “Exactly.” And so the reason why Daytona is like super fast, and you see this on benchmarks, is we essentially, we run on bare metal. We have our own scheduler, we use the underlying, disk, CPU, and RAM of the underlying machine, which means your IOPS are insanely fast because there's no, there's no network between an EBS or something like that. But also the snapshot, the point in time, the templates, are also preloaded on the bare metal machines. So when you fire off a sandbox from a template or a snapshot, you're essentially directed to the bare metal machine where that snapshot is based on that NVMe drive, and then it literally just turns on that machine, and it's local. There's no network latency, anything on there. And so that is sort of the specificities that we, when we're thinking from first principles, what a computer would look like for an agent, that is what we came up with, and that's what we created.Benchmarks, 60ms Startup, and 50,000 SandboxesSwyx [00:15:02]: Yeah. I should maybe, I don't know if you endorse this, but there's someone that does compute SDK, you guys do very well on there, with like the TTI, right? I. is this a, is this a is this a relevant benchmark for you guys? I don't know.Ivan [00:15:16]: I don't know, and it changes every day. So today RKL is.Swyx [00:15:18]: I don't know what RKL is. Never heard of it.Ivan [00:15:20]: Yeah. RK, yeah, so it is there.Swyx [00:15:22]: You are, at least a third of the next tier of performance, and then, there's a lot of other better-known names that are very slow to start.Ivan [00:15:31]: Yeah. We've been the number one by far for a long time, and now there's different, there's different definitions also of sandboxes, different isolation patterns, different other things. So RKL runs it literally on the S3, the data, so it's very different, and they spin up a sandbox, spin up a container for that, so it's a different type of thing. So the definition of a sandbox is something that we can all, we all need to get along with. But yeah, we're insanely fast on getting these things, up and running. And so you can see even there that it's a zero point 0.10 to 0.11, so.Swyx [00:16:03]: Close enough. Yeah. what else do you need, right?Ivan [00:16:05]: Yeah. So the benchmarks itself, so, in this, in I don't think the benchmarks equate to market ownership or revenue or anything like that. and I've seen this with multiple benchmarks, not just in sandboxes, but in general benchmarks around.Swyx [00:16:20]: It's table stakes. It's just like.Ivan [00:16:21]: Exactly. But it doesn't hurt.Swyx [00:16:22]: Just roughly check.Ivan [00:16:22]: Like you definitely have to be up there and you have to be competing so that people know that, oh, this is definitely one of the top. Because this is only one dimension of what customers look for. There's other things like how many can you spin up consecutively? There's a feature set, there's support, there's like all different things that people look at, but you definitely have to be there, on the benchmarks.Swyx [00:16:40]: How many people do people spin up consecutively?Ivan [00:16:43]: So we have.Swyx [00:16:43]: Or concurrently, is the Concurrency, right?Ivan [00:16:45]: There's three metrics that we look at. And so one is like time to spin up one, and so our time to spin up one is 60 milliseconds with network latency. So request, spin up, reply, 60, the whole thing, 60 milliseconds. That is one. But if you wanna spin up 50,000 at once, we are now at about 75 seconds. So it takes about 75 seconds to spin up concurrently 50,000. Some others, there's public data around this, like take 2,000 seconds, which is 30 minutes. Like there's different variations of that. And then there is the so it is speed of one, speed of like multiple, and then how many can you consistently have up and running. And so we basically have right now no limit to how much we can add because we basically own our own metal. But the biggest customer of ours does like about 850,000 every single day is sort of where they're, where they're just shy of a million every single day that they're running, we do have a request for half a million concurrent, which is literally half a million CPUs somewhere running. So that's an interesting.Swyx [00:17:44]: They pay by like vCPU seconds.Ivan [00:17:47]: By seconds, yeah.Swyx [00:17:47]: Or whatever. Yeah. Okay, and so and then, and the other thing is, the sleeping and the resuming, ‘cause it's all the stateful resumption of all these things, how, what kind of workload are people putting through this, right? Like how is it Do we measure by gigabytes in memory, gigabytes in storage? I don't In like network attached storage. I, what are the costly ones of, out of all these features?Workload Economics: CPU, RAM, Network, and StorageIvan [00:18:15]: The most expensive thing are CPU.Swyx [00:18:18]: Okay. Yeah, of course.Ivan [00:18:18]: The second one, yeah Then it's RAM, then it's disk. We actually don't charge.Swyx [00:18:22]: Which is snapshotting, right?Ivan [00:18:23]: No, it's actually the, snapshotting's part of it, but basically the size of your hard disk, of your machine. So do you have 10 gigabytes, do you have 20, do you have 50, do you have whatever? And then the transference of that. Right now, currently we don't charge for, network at all at Polychron.Swyx [00:18:37]: Oh, you gotta, yeah, you gotta fix.Ivan [00:18:38]: Yeah. It is very much a it's a larger and larger part of our bill, so we're working around, that part there. Obviously, that is the least, expensive, so the hard disk is the least expensive, so it's basically CPU, RAM, for us network, ‘cause we don't charge the customer, and then hard disk, is how it's split up. But there's also different types of workloads, so we basically split it up into two types of workloads in Daytona. One is what we call background agents or long-running agents. and the other is, basically RLs and evals, which I put sort of together. And so they have very different patterns of usage, and if you look at the usage of a background And I'll just name names of companies, not specifically.Background Agents vs. RL/Evals: Two Usage ShapesSwyx [00:19:21]: Yeah, open, all hands.Ivan [00:19:23]: Yeah. So like a background agent's a Cognition, a Lovable, a like all these things are Harvey. These are all long-running, background agents. And so if you look at their usage patterns, their usage patterns are similar to human, which is like follow the sun. Basically, the usage patterns of that is like noon is probably the highest, and the midnight is the lowest, and then weekends are lower. weekday is higher.Swyx [00:19:42]: Yeah, that's a fun question. How global is it? Is it very US-centric or?Ivan [00:19:46]: The US is a large part, but we have currently, we have Asia, Europe, and the US regions.Swyx [00:19:52]: So it's quite global.Ivan [00:19:53]: Yeah, it's quite global. We have it all over. It's interesting that our I talked to you a bit about this. Our number one city by user.Swyx [00:20:01]: Hmm.Ivan [00:20:02]: Is Singapore.Swyx [00:20:04]: Oh, wow. Amazing.Ivan [00:20:05]: Which is an interesting one, right? Not by revenue, just by just like by individual head count.Swyx [00:20:09]: Really?Ivan [00:20:09]: Just like an interesting thing.Swyx [00:20:10]: Singapore is, Singapore is weirdly high in the adoption charts of AI for the population. It's like an, seven, eight million population. And it's like keeps showing up.Ivan [00:20:20]: No, it's quite interesting. We were quite shocked, and I was like, “Oh, this is interesting.” And also one that's up there.Swyx [00:20:24]: There's a reason I'm doing AI using Singapore. it's because I'm from there.Ivan [00:20:27]: We're there. We're gonna, we're gonna be there as well. and it's interesting that Japan is in the top or like Tokyo's in the top, which is in all the tech cycles it has never been. It has never been, so it's quite interesting that they're.Swyx [00:20:39]: I think the Japanese just love AI. Yeah. It's that, and then it's Brazil. That's it.Ivan [00:20:44]: Brazil has always been in.Swyx [00:20:45]: I think.Ivan [00:20:46]: Even when I look, if you look at like GitHub's data and ask historically with CodeAnywhere, it was always like US, Western Europe, and then you'd have like India, Brazil, China, like that would be there. But like Singapore was not in, specifically Japan was never in sort of that top, that top.Swyx [00:21:01]: Yeah. Weird pockets.Ivan [00:21:01]: Weird. Yeah, so it's very global.Swyx [00:21:02]: Okay, so actually that, but that's helps you to distribute your load through, all time?Ivan [00:21:08]: The interesting thing is like we have those kind of loads, but if you look at the researcher loads, they're quite different. So what they are is like if you give them concurrency of 10,000 or 50,000 or 100,000 CPUs at ARMb, when they fire off a run, it's just 100%. And then it just runs, and then it stops. So it's very, the usage pattern is squares basically, right? And it's also not follow the sun, because people will fire it off at midnight before they go to sleep but then wake up and so it's very unpredictable, so you don't know where that is. So the shapes of the usage are quite different than we have had before. And also what's interesting is when it's sort of a follow the sun, even if you have a high growth company, you can sort of predict your usage patterns and have enough capacity for that, because it's sort of, it grows in a, in a way you can project. When you have companies doing sort of like evals and RL, they're super spiky. So they're gonna come in, it's like, “We're gonna use nothing, then can we have 100,000?” Right? And then go back down. And then 100,000, go back down. So it's very different, right? And.Swyx [00:22:09]: Do you want to lock them into commits so.Ivan [00:22:11]: Yeah, we do.Swyx [00:22:12]: Yeah, okay.Ivan [00:22:12]: We so we have to lock them into some sort of commits to have that capacity, because we have to have, basically we have to have the capacity for peak. Right? And so right now, Daytona's mean utilization is 15%, 1-5.Swyx [00:22:25]: Oh my God.Ivan [00:22:26]: So it's very low.Swyx [00:22:27]: Because it's very spiky.Ivan [00:22:27]: It's very spiky, but we get up to 90%. so we have these things. And so what we're, what we're looking at right now as a company is similar to Cloudflare where you can like geo move things around, but that works really well for basically the background agent where it's follow the sun. But this, it's not. Like it's a very different shape. Obviously with scale you figure these things out, but that's an interesting new problem that we have, as a compute provider in the agent space. And when we were doing the conference recently, and so we talked to like Nikita from Neon and.Swyx [00:22:57]: I should bring it up.Ivan [00:22:58]: Parag from Parallel and whatnot, everyone has the same problem. Whereas the usage is super spiky, and this is something that has not happened before, that you have these types of like it was always, it the amplitudes were not this high, right? So it's quite interesting use case and problem solve.Compute Conference and Spiky Agent InfrastructureSwyx [00:23:12]: Yeah, I don't know if we're gonna bring this up again, but let's just talk about the conference, you had like 1,000 something people at the Warriors game, at the Sorry, where is it? What's.Ivan [00:23:22]: Chase Center.Swyx [00:23:23]: Chase Center.Ivan [00:23:23]: Chase Center.Swyx [00:23:24]: I went. It was, it was very impressive. Obviously, you can, how to throw a conference, what did you learn? you put, you pulled together all these impressive names.Ivan [00:23:33]: What I.Swyx [00:23:34]: What were you looking for?Ivan [00:23:35]: My thesis behind the Compute Conference was let's bring together people that are building infrastructure for AI agents. Because when I think of what we're building, it is the agent is the primary user, what are the ergonomics and usage patterns of agents, and so we can do that. And what I found, this was a theory, it wasn't proven, is that we all have these problems, as I touched onto. And I was, as I was talking on stage, it was like we all have the same underlying infra problems, which is this spiky workloads, unpredictable workloads that we've never had before, in human, compute or human infrastructure. And it's, again, it's the same when I was talking to Parag or when I was talking.Swyx [00:24:20]: Lynn. Nikita.Ivan [00:24:21]: Lynn, Nikita. Lynn especially, I was talking to her the other day as well. Like the It is a very interesting type of problem to solve because I can touch on Cloudflare because there's a lot of like talk about that recently as to how they solve that, which is they have a bunch of geos, and basically, as users work in different places, and depending on your tier, they can move you around the geos. And so that how, that's how they get the higher utilization. But you can sort of predict these, and it's If it's something in You'll rarely get a spike that is 10 orders of magnitude. Like you'll get a like let's say one of your customers has some like an exponential curve. What is that to I'm using Cloudflare as an example. 10%, 20%, whatever it is. I don't, I don't have this data, I'm just assessing. It's surely not 10x, right? It's surely not something there. And so how do you go out and solve this problem? And we're all solving this in different ways. So we have.Swyx [00:25:11]: She also has the same thing.Ivan [00:25:12]: Yeah, I know specifically that like Neon had that issue as well. Like how are we solving these spiky loads and things like that ‘cause we talked about it. And so the interesting thing for me to actually internalize was, yes, everyone that's building for agents first is going through this, and we're all solving similar problems, which is quite.Swyx [00:25:28]: Let me let me double-click on this. Okay. So for example, Neon, I happen to know that they're very sort of S3 oriented, right? so they're just like fully bet on S3. And you get to benefit from S3's distribution and infrastructure. So I would imagine that Neon doesn't have to care, whereas Lynn maybe has to care a bit more because obviously she's doing GPU inference. And, for listeners, we did an episode with her, one and a half years ago. And you have to care. But like, right?Ivan [00:25:54]: Parag cares for sure, and Nikita.Swyx [00:25:58]: And Parag is C of, Parallel.Ivan [00:25:59]: Parallel, yeah.Swyx [00:26:00]: Former CTO of Twitter.Ivan [00:26:01]: Twitter, yeah.Swyx [00:26:02]: They are the search.Ivan [00:26:03]: Yeah, they're search, yeah.Swyx [00:26:03]: I You and I know but the listeners don't know.Ivan [00:26:08]: Yeah, we can put it down in the screen, and so ‘cause we, when we were talking.Swyx [00:26:11]: I'll put it up on the, on the screen.Ivan [00:26:12]: Yeah, right.Swyx [00:26:12]: People can look it up if they need.Ivan [00:26:14]: Look it up. And, yes, but they still have CPU and RAM, allocation that you have to have up and running. And so CPU and RAM, you have to allocate that and have that ready. And so there's basically two ways to do it. One is you either over-provision and you can handle the bursts, or two, you basically have, I don't know if this is a term, just-in-time compute, which is like as your load becomes, as your usage comes in, you can fire off requests for VMs or bare metals at other cloud providers and then get them up and running.Swyx [00:26:43]: This is if you go above 100%, right?Ivan [00:26:45]: Yeah, this is.Swyx [00:26:46]: Like your overflow.Ivan [00:26:46]: If your overflow, like spillage or whatever you do.Swyx [00:26:48]: You probably lose money on it, but it doesn't matter, right?Ivan [00:26:50]: It, not Well, you might, you might not That is a more cost-effective way to do it but it's a slower way to do it. Because basically what you have to do is you have to like queue your requests, spin up these just-in-time compute, get it all ready, provision it, and then get your workload there. And so if the time isn't important that much, that's fine, and you can do that. But if your customer, and especially for, let's say, the RL training runs, the reason why a lot of people come to us is because GPUs are more expensive than CPUs, right? So you want your GPU running at, what, 100% the entire time. And so when you're running runs on CPUs, when the when the CPU cycle is like down and spinning up the next one, you want that to be instantaneous so that your GPU doesn't go down, right? And if you then have to like go out and provision machines, you're essentially telling the GPU that it has to wait, and that's incurring our cost. So there's things that you have to try to solve for there.RL Workloads, Declarative Images, and Kubernetes ReplacementSwyx [00:27:43]: Yeah, let's talk about the different workload, right? You said that, what was it? A few months ago, you had zero RL workload and now it's 50%.Ivan [00:27:52]: It will be this one, 50%, yeah.Swyx [00:27:54]: Let's talk about how different it is, right? Like I imagine, for example, a lot less dynamic code generation of like arbitrary code. Like here, it's probably all the same code. You're just doing parallel runs or something, I don't know.Ivan [00:28:05]: Yeah. So you'll have multiple Depends on the like for each run, you'll have a snapshot. And they, for the most part, they actually do use our declarative image builder, which is like, “Oh, we, the agent wants these dependencies, these env vars.”Swyx [00:28:17]: These ones, yeah.Ivan [00:28:18]: Yeah, the declarative image builder, it.Swyx [00:28:20]: Which is a very modal like thing that they.Ivan [00:28:22]: Yeah. And so we build it on the fly and then we propagate that snapshot, and you can spin up as many sandboxes as you want against that snapshot. And then if you have to do changes, the model can, or like it could be also be automated. It's like, “Oh, now for the next run, we need to install these things or remove these things or whatever to get, a task done,” and then it goes off and runs that. So yes, that is something that it seems that they prefer. The number one reason I found, or should I say, let's take a step back. What we are competing against in that environment is essentially managed Kubernetes. So EKS, GKE, whatever. That is what the vast majority run on. And anyone that has tried Daytona versus GKE, EKS is like, “I'm never going back.” That has always been. There's a few reasons. One is the ergonomics. So if you have, if you're using Kubernetes to spin that up, you have to essentially manage the interface interactions with that. Daytona, although as a compute provider, it's more akin to a Twilio and Stripe from a consumption perspective than it is an AWS. Like you have an API, an SDK, it's quite like easy and seamless to get these things up and running, that's one. The other is the speed to which we spin up, which we mentioned earlier, which is much faster, and the scale to which we can go to. We haven't got into features, but an interesting feature is that it's very hard to OOM, or out of memory, our sandboxes, because we can dynamically on the fly.Swyx [00:29:48]: Resize.Ivan [00:29:49]: Resize, which is like impossible on almost any other thing. There are some technologies that enable you to do that, but it's like a very hard thing. And so we actually saw this when, the Terminal Revenge team is, brought us actually. So thank you, Alex and the team, that brought us into this whole space.Swyx [00:30:05]: It's just very rare that, a framework would just say, “Guys, just use Daytona.”Ivan [00:30:11]: Yeah, I think it says it somewhere. Yeah.Swyx [00:30:13]: Yeah. I was like, “What is this?”Ivan [00:30:15]: There's all, there's multiple there, but they also mention a few other places. and so Daytona specifically-We have, the, just jumping on themes here We, I don't know where it says Data Center.Swyx [00:30:27]: I, there.Ivan [00:30:27]: Doesn't matter.Swyx [00:30:28]: There's a very strong recommendation, which is, very unusual. Which is, it's.Ivan [00:30:33]: We do not pay them for this, just.Swyx [00:30:34]: I know, yeah. They just like you.Ivan [00:30:35]: Yeah, they like us. yeah, and also a thing, so, Data Center has multiple isolation sets underneath. The customer doesn't have to know what they are. But basically we have Docker, which is a container, that's hardened with Sysbox. So it's Docker's, isolation that is a security equivalent to a VM, but it's still a container. And that is the default, and they, especially in these training workloads, really like that as an interface to be able to use just a basic Docker container, and we enable Docker and Docker. Which for these RL runs, if you need to do a Docker compose or Kubernetes, you can spin up a K3S inside of these things, which unlocks a huge amount of workloads that you can do that you cannot do on other providers. So just on that part is much more interesting. And so we went that, through that. We showed them that we could do that, and they enjoyed that quite a bit. They being the general venture people.Swyx [00:31:28]: Those people, yeah.Ivan [00:31:29]: And Harbor people.Swyx [00:31:29]: Harbor people, do are they, are they a company yet?Ivan [00:31:33]: As far, I do not know.Customer Pull, Slack Connect, and the Computer Use BetSwyx [00:31:35]: Okay. All right. Yeah. It's like super obvious that like, there's a lot of excitement and success around these things, okay, so yeah, tell us more, right? Like, this is an exploding workload, Harbor adopted you, which helped speed things along. But what are you learning as this new workload comes online?Ivan [00:31:53]: There's a couple things that we learned, which we chat about in the beginning. We, and this has led our story, as we mentioned, we like talked to a lot of customers along the way, and we add more features and more tool sets as we talk to customers. And it's interesting that And I think it's that the ecosystem is so small and/or the models get smarter, where when we see one user come with a request, we know it goes on a roadmap if like three to five customers come with the same request in that week. It's like very bizarre. It happens so many times, which is.Swyx [00:32:27]: Because they're all friends.Ivan [00:32:28]: Sorry?Swyx [00:32:28]: They all, they're all friends. They're all in the same group chat.Ivan [00:32:30]: Yeah, probably, yeah. ‘Cause and they're like, “Oh, can you do this?” And I'm like, “Okay, this is interesting. We'll put it on a feature request.” And then the next one's like, “Oh, can you do this?” “Okay.” It's all the same, right? It's always the same. And so what we try to do, and I personally try to do, I try to be on as many call, quote-unquote “sales calls” I can. I'm in every Slack channel. We literally have about 1,000 Slack Connect channels, something like that. It's an interesting, there's so many interesting things you find out when you have all the Slack channels. You can also see where people, transfer between companies. You see leave Slack channel, enter Slack channel. It's an interesting thing. Also, just I digress, I feel that Slack Connect is literally LinkedIn what it should be. You have a list.Swyx [00:33:08]: LinkedIn charges you to, use your own connections, but Slack doesn't, right? Slack is like, do it for free. It's more lock-in. It's great.Ivan [00:33:15]: Yeah. It's amazing. Yeah. It's one of the reasons.Swyx [00:33:17]: You're gonna pay Slack for life.Ivan [00:33:18]: Exactly. You're there for life. So that's interesting. And so one of the things, the newer things we were talking about earlier is we made a big bet and put a lot of investment on computer use. that is not seen publicly the light of day. We haven't GA'd that yet, but we have.Swyx [00:33:32]: Is there a thing I can pull up?Ivan [00:33:33]: There is computer use there. It's right up a bit.Swyx [00:33:36]: Oh, yeah. Okay.Ivan [00:33:38]: What we have, what we talked about and what we've seen publicly is there's this theme now about, the human emulator where And Elon from XAI has talked about this publicly, and if you think about the models today, they're actually quite sophisticated and they can do a lot of work, but they still don't have access to all the tools. Like, I'm a strong believer that the most efficient way for an agent to work is essentially headless or through, terminal or whatnot. But if we, if we look at knowledge work in general, there's about 100 million knowledge workers in the US, about a billion in the world, and knowledge workers, and the salaries of them aggregate to 10 trillion in the US 50 trillion worldwide.Swyx [00:34:24]: Wow.Ivan [00:34:25]: Something like that. And if we look at, the five most important sectors of that, so like healthcare and government and financial services and whatnot, that's about 56% of that. So let's say it's about half of that. So in the US it's about 25 trillion, and most of them, most of that work is actually still locked into legacy apps inside of Windows, which is not going anywhere for a very long time. Like, people just won't invest in that. How much of it? our assumption is the following: if, in the RPA market, which is similar market, well, not the same 25% of, these white collar, workers', work is automated. If an agent is more sophisticated, can go through more runs, figure stuff out, let's say it's, 40%, right? And so if you take 40% of that, you get to essentially, $10 trillion a year.Swyx [00:35:17]: That's a TAM.Ivan [00:35:18]: That is a that is a TAM. So that's the TAM of the models, right? That's not our, essentially ours. But you get to that size, and to be able to do that, you essentially have to give agents these computers with the legacy. So computer use, either Mac or Windows or Linux. Linux we also obviously have and others have. But Windows specifically is something very new, and the only option right now is an EC2 with, Windows or on Azure. Both of them take anywhere from three to five minutes to spin up. We've created an actual sandbox, so it's a second instead of milliseconds, but you have, point in time snapshots, you have, forking, you have all the things that you have from a sandbox, but essentially enables you to hopefully unlock all this value. And so that's been our big push and bet, but we've sort of, kept our ear to the ground. What is sort of the next things in the market?RPA Returns: Why Agents Still Need ComputersSwyx [00:36:06]: Yeah, knowledge work, and building, and sort of RPA, the next wave of RPA. I got very excited about RPA kind of during COVID times. The UI path was IPO-ing. And it was, a very hot Isn't it, Eastern European?Ivan [00:36:20]: It is, Romanian.Swyx [00:36:21]: Romanian?Yeah, it might be the only Romanian, big unicorn okay, yeah. This I don't I don't, I don't have like a I think there's, I think there's a stage being set for the resurgence of RPA, ‘cause everyone understands that, yeah, no one wants to deal with these shitty apps and no one's gonna rewrite them. Like, you just have to do, a remote operation and programmatic operation of them.Ivan [00:36:45]: If you wanna unlock it, my own setup was basically the following. So I was doing a board deck recently, last month, whatever, and I'm like, “Okay, let's just, let's just do automated.” So, all our data's in, ClickHouse and PostHog and QuickBooks, where everyone else's is, and I'm basically, connected that all to, my Cloud code, like go off and go Cloud code whatever. Go off and, here's the integrations, go do that. It pulled out the first report, which was great. It connected to Brex and all these things, pulled it, which was great, and then I say, “Okay, now pull out this, and this,” and I kept getting, really well McKinsey-style design reports, but the data said partial data. all the missing data, partial data. Like, it can't access all the things, and I got so frustrated, and so I got, I got, my Mac Mini virtual sandbox with OpenClaw. I gave it its own account in our company, and then I went to all these services and created a read-only account, so literally like an intern in your company. And so I would say, “Now go and do this report,” and it would get the same, or like, “I can't via the MCP or the API or whatever. I can't get all the information.” I'm like, “Go log in.” And it will log into the website, then go in, export the data. It'll export the data and do the thing end to end. So even for things that have today APIs, not all of it is exposed, and I to get value, I get immense value right now, but it has to be a computer usage, unfortunately, and so I spend a bunch of tokens just on that, but I get the job done. And so if even a startup like ours, and using all the hottest tools, still needs a computer agent what hope does, Goldman have to have a headless, right?Swyx [00:38:22]: Yeah, what a - Why isn't Microsoft doing this?Ivan [00:38:27]: I'm pretty sure, Satya had a post yesterday.Swyx [00:38:29]: Oh, okay. I see.Ivan [00:38:29]: Which was like, “Every agent needs a computer.”Swyx [00:38:31]: I see, I see.Ivan [00:38:32]: So they have launched something recently.Swyx [00:38:34]: Yeah, they have Microsoft Power Automate, I'm sure, I'm sure, they're gonna have their version.macOS Sandboxes, Apple Constraints, and the Windows OpportunityIvan [00:38:39]: Version of that, yeah.Swyx [00:38:39]: You're gonna try to do yours, and it - I always know there's always demand for Mac, but I know it's, tricky to host, macOS sandboxes.Ivan [00:38:49]: We will have macOS sandboxes fairly soon. The problem with macOS, OS sandboxes is, I'm deep in this, I don't know how much interesting is.Swyx [00:38:55]: No, it's.Ivan [00:38:56]: MacOS has this problem.Swyx [00:38:57]: It's a licensing thing, right?Ivan [00:38:58]: Licensing thing. So one, you're allowed to run only two parallel VMs per machine, so that's one. Two, you can only license to a different user every 24 hours. So if you come in and theoretically, if I wanna charge you per second and I charge you one second, I have to have it idle for the rest of the day. I can't have anyone else doing that. So the pricing will be different in the sense that I will have to - we would have to charge for 24 hours, and that's not even, that's not even the most difficult thing. But the, thing above that is, from a security perspective, they enable you to do memory snapshot, pause, resume, but only on the same physical drive, physical machine. And so what you can do in, Windows world or Linux world is that I can move in the background, your snapshot from one to the other and manage load, right? Here, if you wanna do that, you essentially have to have your.Swyx [00:39:49]: Yeah, snapshots. Yeah.Ivan [00:39:50]: Your.Swyx [00:39:51]: It's like.Ivan [00:39:51]: Physical machine.Swyx [00:39:52]: You can't break it up.Ivan [00:39:53]: You can't, you can't move things around that, and all of that is, that part is, from a security standpoint, if it is written. Like, I understand the security aspect of that, but it disables you from doing these agentic, like really scalable agentic workloads.Swyx [00:40:08]: You need to do a vibe-coded, clean room implementation on macOS that you can then - That's like Clean OS or something. I don't know.Ivan [00:40:17]: So. We have.Swyx [00:40:18]: ‘cause like Linux was originally like a clean room rewrite of Unix.Ivan [00:40:21]: Okay. Yeah.Swyx [00:40:21]: Or something like that, right? Like same thing to macOS. Someone needs to do it.Ivan [00:40:25]: Someone will do that, and someone will have some long-running agents for a few days to figure this stuff out. But yeah. So definitely we - we're really close to offering something ‘cause people do want it, but the pricing will be different, and the feature set will be sort of stringent.Swyx [00:40:38]: Yeah, nobody's gonna use this. like, the labs, the labs will because they want to automate macOS.Ivan [00:40:42]: They have to do RL. They have to do RL again. But even if you The - So the point is with the RL part, if you, if you do RL on macOS, then the next iteration of the model comes out, it will be able to use these tools significantly. Then you actually need to run those, that somewhere. So you're gonna have to have that, later on. And from, if anyone at Apple is listening, I very much feel that they are shooting themselves in the foot of the scale of the revenue of compute or licensing they could get if they would just enable a concurrency model similar to what you can get on a Windows and a, and Linux.Swyx [00:41:17]: Yeah. Yeah. And I'm sure they've heard this before. They just don't care. Yeah, it's And maybe they will change their mind with the new CEO.Ivan [00:41:24]: Yeah. We'll see.Swyx [00:41:25]: We'll see.Ivan [00:41:25]: High hopes.Swyx [00:41:26]: High hopes.Ivan [00:41:26]: High hopes.Swyx [00:41:27]: Okay. But I, it's very clear the market opportunity is huge in Windows, and you can go for a long time on just Windows, but your customers are gonna want both. and I think, it is interesting to me that, this is the sort of God application of agents, right? Like, I don't It was - How big was OpenClaw for you guys? Like, was it, was there, a significant bump.OpenClaw, Agent Labs, and the B2B2C Sandbox MarketIvan [00:41:54]: Not for us because we.Swyx [00:41:54]: Because you already.Ivan [00:41:55]: We're kind of positioned differently. Whereas although it's completely PLG and we have individual developers that use it, most of the users that use Daytona are sort of a B2B2C. Sort of it's either B2B or B2B2C. So, in the researcher world, it's B2B, so you're selling to, labs and neo labs and things like that. But on the long-running agents, it's mostly, from a scale revenue perspective, it's mostly B2B2C, where you have a app layer agent that uses you at a big scale.Swyx [00:42:26]: Like a Manus. Yeah.Ivan [00:42:28]: Like a Manus Lovable type of thing.Swyx [00:42:31]: Yeah. I think that's the question of, well how, um-Uh, yeah, B2B to C is basically to me what I've been calling an agent lab, which is kind of like you're not in a model lab, but you're making a very good wrapper that is a platform that other people can sign up so they don't have to code those things. Yeah, it sound, it sounds like a much better market than the direct OpenClaw market.Ivan [00:42:56]: I've like - We I've done multiple things. So the CodeAnywhere's part of our career path R in the calendar, was very much an end user developer product. And so that is great. It You can get a lot of developer love, and I feel that we do as a company have a bunch of developer love. But it's a different type, where it's people building these things. Again, it's more akin to a Twilio because you don't really run - As a person, you wouldn't run Twilio. I don't know how many people remember. It was like ask your developer billboard and whatnot. And people really love Twilio, but they only used it inside of like, “Oh, I'm building this app or service for thing.” And so we're very much directly to that. And you also know that I used to work for a competitor for Twilio, so it's kind of ingrained, in my DNA.Swyx [00:43:35]: People don't know InfoBip is that big.Ivan [00:43:38]: Yeah, it's.Swyx [00:43:39]: Because.Ivan [00:43:40]: It's a billion euro.Swyx [00:43:40]: They're all American. They're like, “Whatever's in Europe doesn't matter to me.” But like it's the, it's the same size or bigger? Same size?Ivan [00:43:46]: It's about half the size.Swyx [00:43:47]: Half the size?Ivan [00:43:48]: Yeah, about half the size.Swyx [00:43:48]: It's like, yeah.Ivan [00:43:48]: Still huge. Multiple billions a year. Yes.Swyx [00:43:51]: That's crazy.Ivan [00:43:51]: Exactly, and so that - These are like really interesting and large revenue-generating, very sticky businesses. Whereas when you're selling to the - When your focus is the end developer, it is a very hard sell because they're very price sensitive, very price conscious, very around that. And there's very It's very hard to scale. Your cap is the number of people that are willing to spin up - First of all, wanna spin that up, and then spin up multiple of these. Whereas if you're in the enterprise one, like we know everyone's talking about like how many tokens they're spending, I'm spending. Like a lot of companies today are like, “If this is our company, spend as much as you can.” Like basically that is where we're going. And so if you think about that paradigm, where you're selling to companies that say, “Spend as much as you can to generate, productivity,” versus, “Oh, I'm a single person. I have this much budget, and I'm doing this thing because it's fun or it's helping me out or whatever.” Like it is a different, it's a different go-to-market, I think, strategy.MCP, CLIs, and Sandboxes as the Agent RuntimeSwyx [00:44:50]: Yeah, there's a lot of discussion. I'm just kind of going through like the mental list of things that are in your favor, which is, for example, MCP versus CLI. Like obviously you want CLI. It's been very good for you. I feel like it's maybe a drop in the bucket or maybe it's huge. I'm just checking whether it's like these are big trends.Ivan [00:45:10]: Those things you - work well in our favor, to your point just because every.Swyx [00:45:13]: They're kind of drop in the bucket, right?Ivan [00:45:15]: I think it's like sort of all the things come together. And so there's so many things that impact that. To your point, like OpenClaw wasn't huge for us, but like having the agent SDK, from Anthropic, so or Cloud Claude Code was very interesting. The reason why it was interesting is that a lot of, let's call them app I don't know what to call them, app layer agent companies, essentially they are like, “Oh, I can create this new app, this new agent. All I need, I just use Claude Code, and I throw it into a sandbox, and then I have my interface to the human to that.” And so that enabled so many more companies to actually offer this, and then they would pull on sandbox. So that was, that was interesting. And to your point, like MCP, versus the CLI, the MCP is an interface against an API, whereas the CLI is like you can actually go do things. Like this is it. The difference between integrations and actually running scripts or data or analysis against a thing. So being able to use a CLI very well enables the agent to do more things, and it's because that people will invoke a sandbox, they'll run it in the CLI, and but it'll do anal-analysis on that data and then give you an actual result versus just, pulling data from an API source.Swyx [00:46:29]: Yeah, it's a layer of indirection basically, it's the same thing as agentic search versus RAG, which where you're.Ivan [00:46:34]: Exactly, yeah.Swyx [00:46:34]: Just like you just win whenever people put more agents into their workflow. And so like it doesn't really matter, but I'm just kinda teasing out like what else have people heard about that like it's sort of, “Oh yeah, this is another sandbox use case. Oh yeah, that's another one.” Am I, am I missing any big ones?Ivan [00:46:51]: The thing, the thing that people, which is the computer use stuff, which I think is probably the most interesting one, is, and to your point, we've talked to so many people over the last year. It's like, “Oh, like why do you need a sandbox? Why do you need this? Why this?” And to your point, it's like, “Oh, I need sandbox for this. I need sandbox for that. I need sandbox-” It's like, “Oh, I need it for every single thing.” And so basically what I, what I - and it sounds like a broken record, it's like you use a laptop every single day, right? And you are n of one. It's just you. But now imagine how And by the way, the laptop, the computer PC market, the PC market is about equal to the cloud market in total. So it's about 150, 180 billion a year. Something like that. It's about roughly the three cloud hyperscalers is about equal to like Apple, HP, Lenovo, whatever, It's a little bit less, but it's sort of like that. And now imagine And that's just like, so how big is the addressable market? What, how many people are there in the world now? What's the last data?Swyx [00:47:45]: Let's call it eight billion.Ivan [00:47:46]: Eight billion. And so let's say you can have two computer, like you have one personal and one business, whatever. Like so it's double that, right? and so that's 16 billion, right? How many agents are gonna be running in two years, in 10 years, in 100 years? Like And for every single task, they will need one of these. And so how big is that? That market is essentially quote unquote “infinite”. You will get to the point, and Dylan Patel was at the conference talking about, from SemiAnalysis, that talks usually about GPUs, was also talking about how CPUs will now be a bottleneck because it will be the constraint. You won't be able to grow, or we won't be able to have enough of these because there won't be enough CPUs to basically do.Swyx [00:48:23]: Yeah. Well, I actually had a really good podcast with Doug Oliphant, who, which was his president at SemiAnalysis, where they've basically been like, yeah, it's been a GPU shortage first, but then it's cascaded down to memory and now to CPUs.Ivan [00:48:35]: CPU, yeah.Swyx [00:48:35]: It-What's next? So networking. So, networking actually has been in shortage for a while if you're looking at, just GPU networking. But, yeah, it's really crazy the amount of computer use that's going on, yeah, cool. I, other questions are, just the one very big part is the open sourceness which you didn't have to do, your competitors don't do, like it's not, a lot of people are worried about keeping their projects open source because some competitor can just slot fork it. I don't know if there's any reflections on just being an open source company.Open Source, Trust, and Enterprise ProcurementIvan [00:49:15]: Yeah. There's a bunch. So we the original product that we did was open source.Swyx [00:49:19]: Yeah. CodeAnywhere.Ivan [00:49:20]: So doing that was actually very good for us. There's basically a saying of, What's the saying? Like, companies that are, that are doing really well, measure themselves against, free cashflow, that are kinda okay, it's EBITDA, then, it's, it goes all the way down.Swyx [00:49:36]: The worst is like GitHub stars.Ivan [00:49:37]: GitHub stars. GitHub stars are the worst, yeah. So you go all the way down to GitHub stars. And so our original one was GitHub stars. That's what we talked about, we're at the point we're talking about revenue, so we're we've gone up the stack on that. And so we started.Swyx [00:49:47]: No, profit.Ivan [00:49:48]: Yeah. We haven't, we're, we'll get there. We'll get there. But basically at that point we did stars and GitHub and it was useful, and the original variation that we did, it we split the core into its own repo and it was Apache 2.0, so very, permissive. And then we basically would bundl

What actually keeps customers coming back? In this episode of Limited Supply, Nik sits down with retention expert Joseph Siegel to break down the systems behind high-retention ecommerce brands. From his time leading growth and retention at Feastables to building retention programs for some of the fastest-growing supplement brands in the world, Joseph shares how modern retention goes far beyond email marketing. They dive into onboarding flows, product inserts, gifting strategies, subscriber psychology, and why the best brands obsess over customer experience at every touchpoint. They also explore how AI is changing ecommerce operations from CRO systems and generative email workflows to building smarter customer insights with tools like Claude, Manus, Fireflies, and OpenAI voice models. If you run a subscription brand, consumable product, or ecommerce company focused on long-term growth, this episode is packed with actionable retention strategies. --- What's Instant? It's the secret weapon to triple your email revenue with AI-powered flows and campaigns. Instead of sending the same cart reminders to everyone, Instant gives every shopper a personalized email experience: Copy, products, and offers that adapt to your shopper's behavior and purchase history in real time. Emails sent at the exact moment each shopper is most likely to buy. 11+ abandonment flows and smart multi-step campaigns live in minutes. Built for DTC marketers. Made for revenue growth. See why brands are replacing their ESP with Instant: ⁠⁠⁠instant.one/sharma⁠⁠⁠. --- Want more DTC advice? Check out the⁠⁠⁠ Limited Supply YouTube page⁠⁠⁠ for more insider tips. And if you're looking for an instant stream of on-demand DTC gold, check out the⁠⁠⁠⁠ Limited Supply Slack Channel⁠⁠⁠⁠ for Nik's most unfiltered, uncensored thoughts. Check out the Nik's ⁠⁠⁠⁠DTC newsletter⁠⁠⁠⁠ Follow Nik on Twitter:⁠⁠⁠⁠ https://www.twitter.com/mrsharma⁠⁠

Use code TURFNERDS for 5% off orders $600 and up at Magna-Matic! Use discount code for TURFNERDS10 for 10% off at Strauss, valid starting April 29 through May 31 Use code NERDS to save 10% on Spencer Products! Chad Manus works full-time in transportation and logistics, has six kids, and still manages to service 40 lawn care clients out of Headland, Alabama on afternoons and Saturday mornings only. In this Turf Nerds on Turf's Up Radio episode, Chad breaks down how he grew from 10 clients in year one to 40 in year three, why his second season nearly broke him, and the Facebook ad strategy he used to build killer route density without wasting a dollar. If you've ever wondered whether you can build a real lawn care business without quitting your day job, this one's for you. Use code TURFNERDS for 5% off orders $600 and up at Magna-Matic! Use discount code for TURFNERDS10 for 10% off at Strauss, valid starting April 29 through May 31 Use code NERDS to save 10% on Spencer Products! Tap Here for Turf Nerds Merch!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Look! We Have A Website!⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Don't forget to check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Green Frog Web Design⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and tell them the Turf Nerds sent you. Or Greg will scalp your lawn! Use promo code TURFNERDS for 50% off Equip Expo 2026 registration! Shoot us an email! Evan@TurfNerdsPod.com ⁠⁠Instagram⁠⁠ ⁠⁠Facebook⁠⁠ ⁠⁠TikTok⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Subscribe on YouTube: ⁠⁠⁠https://www.youtube.com/@TurfNerdsPodcast?sub_confirmation=1⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠#LawnCare #LawnMaintenance #Mowing #MowingGrass #LawnCareBusiness #Toro #ToroMultiforce #CubCadet #BibleStudy #Bible #Christian #Business #Entrepreneurship #Comedy #2024 #Marketing #Advertising #TipsAndTricks #Tips #Success #Yakta #YaktaMowers #YaktaOutdoor #Spring #SpringRush #FYP #Mower #NewMower #UsedMower #RouteDensity #EquipExpo #EquipExpo2024 #Echo #Stihl #RedMax #Shindaiwa #StringTrimmer #WeedWhip #GreenFrogWebDesign #WebDesign #EzraMcCarthy #Aerator #Aeration #ZAerate #Bobcat #BobcatMowers #Husqvarna #HusqvarnaGroup #HYGREENTOOL #GOMOW #ThunderLightingSupply #ChristmasLights #Christmas #Trump #DonaldTrump #PresidentTrump #ElectionDay #EZDumper #DumpInsert #StempkyNursery #Mulch #MulchInstallation #TurfNerds #Newsmax #NewsmaxTV #CarlHigbie #CharlieKirk

Join use at the STR AI Summit — June 23-24 at the Freedom Factory in Beverly, MA. 100 seats only strsecrets.com/aisummitMike Sjogren spent over $5,000 in API credits in two months learning AI the hard way. And he wants to make sure you don't have to.In this Portfolio Clinic training, Mike breaks down the top 10 AI mistakes that cost him real money — from not understanding context windows to memory file bloat to giving an agent 15 tasks at once and wondering why nothing got done. He then walks through exactly how STR operators should be using AI right now across three buckets: getting more properties, getting more bookings, and getting more time back.He also shows how he rebuilt his Florida direct booking website in under a day for under $200 using Manus, how his AI agent scrapes top boutique hotel social media content overnight and delivers a morning brief, and why the goal is never to build your own software — it's to use AI as a bolt-on to everything you already have.DM Mike on Instagram @mike.sjogren and comment PROMPT to get the free PDF of all the prompts he used to build his direct booking website.STR AI Summit — June 23-24 at the Freedom Factory in Beverly, MA. 100 seats only.strsecrets.com/aisummitFree 6-step course for scaling STR operators: https://level.strsecrets.com/pc-bookSTR Secrets FB group: https://www.facebook.com/groups/STRentalsecretsTimestamps:0:00 - Why Mike Is Doing This Training (And How Much It Cost Him)2:15 - Mistake #1: Not Understanding Context Windows ($6 Per Message)5:30 - Mistake #2: Memory File Bloat — Why AI Gets Dumber Over Time7:45 - Mistake #3: Using Your Most Expensive Model for Everything10:00 - Mistake #4: Broken Cron Jobs — How to Schedule Tasks That Actually Run13:00 - Mistake #5: Treating AI Like an Employee Who Can Handle 15 Things at Once16:30 - Mistake #6: Not QC-ing the Output18:00 - Mistake #7: Trying to Build Your Own PMS or Pricing Tool20:30 - The 3 STR Buckets: More Properties, More Bookings, More Time23:00 - How to Use AI to Automate Your Entire Prospecting Pipeline27:00 - How to Use AI to Get More Bookings Right Now30:00 - How to Rebuild Your Direct Booking Website With AI for Under $20036:00 - How Mike's Overnight Agent Scrapes Top Hotel Content Every Night39:00 - The 10 Rules for Using AI Without Burning Your Budget42:00 - How to Motivate Your Team to Use AI Without Fear46:00 - Where to Start If You're Brand New to AI48:00 - STR AI Summit: June 23-24 at the Freedom Factory

十年前的三月，那是人类最后一次战胜AI。如今，AI领域发生着剧烈变化，从 GPT最新图像模型展现出惊人的真实理解能力，到AI公司Manus收购案引发的监管风波，再到AI短剧、AI游戏对传统行业的碾压式替代，AI革命已进入不可逆阶段。AI不仅在内容生产上全面取代人力，甚至企业开始用AI“蒸馏员工”，科技巨头批量裁员。与此同时，中美在AI领域形成两极博弈，算力、算法、监管规则重新划分边界。在AI这场海啸下的我们，应该何去何从？您请听庄明浩和划水怪一一道来。更多精彩内容，欢迎收听本期节目~主播 / 相征嘉宾 / 庄明浩音频后期 / 陆凯BBBBUDDHA音频上传 / 恬恬-本节目由深夜谈谈 Midnight Network出品 -Timeline:00:02:45 Image 2断档式领先00:11:10 年化收入1亿美金的公司之一00:23:00 人家商业公司就是为了挣钱00:36:10 滴滴非要去上市00:49:19 一次扔爆炸瓶，一次枪击01:18:46 处处受限制01:22:58 中美科技博弈01:33:51 AI音乐的发展01:37:57 阿尔法狗战胜李世石已经十年了01:46:03 AI能操控游戏么？01:47:35 Fun. - Carry On藏式金刚断烦恼，紫檀咒珠守心安。二十八宿催红鸾，甲子莲蓬伴流年。大内上新四款手串，愿你遇事不慌，少些内耗，遇见真心，白首不离。微信搜索小程序“大内夜市”，把祝福戴在腕间，日子自有光亮。每年夏天，我们都相约在一个森林山谷共同接受阳光、音乐、快乐的洗礼，今年也不例外！7月23日-7月27日，五天四晚，“大内海贼团”正式起航！由船长·相征、航海士·Miya、狂厨·王涛、大剑士·杨凯、疗愈士·郭小寒、观测士·米地、回声·宋晓辉这七位主播领衔带队，快快加入七武海的伟大队伍吧！微信搜索小程序“大内夜市”，即可报名～（报名咨询请微信搜索：DNYS-midnightalks）-你还可以在这里找到我们：小红书：@深夜谈谈、@相征terry、 @miyaB站：@大内密谈midnightalks视频号&抖音：@深夜谈谈微博：@大内密谈微信公众号：大内密谈商务合作邮箱：biz@midnightalks.com加听众群：加深夜谈谈子微信（微信号:SYTT-midnightalks2）并回复【听众群】即可进群。

"Not a creative"?

Subscribe now to skip the ads and get all of our episodes.  King Charles paid his respects at AP HQ, but was put off by Danny's pet ferrets. In this week's news: Iran talks collapse as Trump weighs a blockade and strikes (1:56); the UAE leaves OPEC (7:45); Mali rebels and jihadists seize Kidal (16:49); Derek interviews Alex Thurston about Mali's escalating rebel offensive and the implications for the junta government (18:08); Israel kills civilians and expands evacuation zones in Lebanon (33:43) as the U.S. and Israel demand a Hezbollah disarmament plan from Lebanon (35:25); Israel adds an orange line to its Gaza map (37:08); Afghanistan and Pakistan exchange border fire (38:59); China blocks the sale of AI startup Manus to Meta (40:46); Sudan's Blue Nile faces a humanitarian crisis (44:23); King Charles visits the United States and addresses Congress (46:27); Trump and Putin discuss a Ukraine ceasefire (48:53), plus Ukraine accuses Israel of procuring stolen grain (48:53); and the United States charges Sinaloa Governor Ruben Rocha (52:18). Don't forget to download our latest miniseries Marx Prestige. All episodes out now! And paid subscribers will get access to the full interview with Alex Thurston. Learn more about your ad choices. Visit megaphone.fm/adchoices

Episode 833: Neal and Toby dive into China's block of Meta's acquisition of AI startup Manus, citing national security concerns. Then, the Supreme Court hears arguments on whether ‘geofence' warrants violate the US Constitution's right to privacy, even when committing criminal acts. Next, the MAHA Moms march to the Supreme Court to protest the use of a pesticide used on oat and corn as they claim it causes cancer. Meanwhile, Toby looks into the trend of brides buying wedding dresses much closer to their wedding day because they're quickly losing weight thanks to GLP-1 drugs.  Learn more at https://www.windmillair.com/MBD Get tix for Morning Brew's live show! https://www.caveat.nyc/events/morning-brew-presents-business-island-4-30-2026  Subscribe to Morning Brew Daily for more of the news you need to start your day. Share the show with a friend, and leave us a review on your favorite podcast app. Listen to Morning Brew Daily Here:⁠ ⁠⁠https://www.swap.fm/l/mbd-note⁠⁠⁠  Watch Morning Brew Daily Here:⁠ ⁠⁠https://www.youtube.com/@MorningBrewDailyShow⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

This Week In Startups is made possible by:IM8 Health - IM8health.com/twistSentry - Sentry.io/twistDeel - Deel.com/twistPlaud - https://Plaud.ai/twistWhat's the technology story of the year? No, it's not Anthropic's Mythos model, nor any other AI model. Upcoming IPOs? Wrong again. Jason thinks it's China's government's decision to block Meta's acquisition of Manus. The multi-billion-dollar deal was heralded as evidence that AI companies founded in China could sidestep onerous government meddling by moving their operations to Singapore. That loophole now appears closed.Jason and Lon then dug into the newly-reforged OpenAI-Microsoft partnership. The two companies have had a mutually beneficial, if fractious, operating relationship to date; that they had to rework their agreement is not a shock.Then, your hosts watched and digested a video from China purportedly showing a self-driving car hitting a child at speed. What would happen in the United States if such a tragedy struck? And is that fait accompli?Closing the show, Jason and Lon reacted to the latest Russell Brand implosion, discussed Lon's new favorite show ‘Criminal Record,' and shared recommended foot pedals (for AI dictation) and headphones for the road warriors tuning in.Key Links: OpenAI and MicrosoftOpenAI's announcement of its new Microsoft dealMicrosoft's announcement of its new OpenAI dealOpenAI announces its deal with AWSNews that Microsoft was considering legal action against OpenAIMicrosoft-OpenAI negotiations late 2025 edition, and terms announced in early 2026Amazon announces that OpenAI models are coming to AWSTimestamps:0:00 Show starts1:24 OpenAI and Microsoft have a new deal3:22 Why would Microsoft cede exclusive access to OpenAI models?5:36 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off!8:09 Why Jason thinks Microsoft and Apple should work together on AI9:45 China will block the Meta-Manus deal12:12 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit https://deel.com/twist to learn more.12:23 Golden Shares and what they provide14:57 How do you unravel a multi-billion-dollar deal?22:08 Sentry - New users can get $240 in free credits when they go to https://sentry.io/twist and use the code TWIST24:42 The Huawei ADC crash29:49 What happens when something similar happens in the United States?31:55 IM8 Health: Start feeling like your best self every day. Go to https://IM8health.com/twist and use the code TWiST to get a free welcome kit, five free travel sachets, and 10% off your order.36:15 Russell Brand's public humiliation41:22 Don't trust palm reading!43:59 Lon's Off Duty streaming pick: Criminal Record46:25 Jason's Pick: Which foot pedal for AI dictation is right for you?48:43 Jason's Pick: In the market for new headphones?Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisCheck out all our partner offers: https://partners.launch.co/Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.com

Plus: China bans Meta's acquisition of AI startup Manus. And a court in Taiwan hands down prison sentences for stealing TSMC trade secrets. Danny Lewis hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

China blocked Meta's $2B Manus acquisition and ordered both sides to unwind the deal, closing the "Singapore washing" loophole for Chinese AI startups. OpenAI is developing smartphone chips with Qualcomm and MediaTek, Google controls ~25% of global AI compute, and SaaS pricing shifts to usage-based. China blocks Meta's $2B Manus acquisition, after reviewing whether it violated investment rules, and tells both to cancel it; Manus moved to Singapore in 2025 (FT) Kuo: OpenAI is working with MediaTek and Qualcomm to develop smartphone chips, with Luxshare handling the system co-design; mass production is expected in 2028 (Ming-Chi Kuo) Epoch AI: Google controls ~25% of global AI compute, with ~3.8M TPUs and 1.3M GPUs; Google Cloud CEO Thomas Kurian says demand and revenue justify the spend (FT) Analysis: as of late 2025, 79 of 500 tracked software companies including HubSpot, Adobe, and Salesforce adopted usage-based AI fees, more than doubling on 2024 (The Information) Anthropic details Project Deal, a marketplace experiment where Claude models bought, sold, and negotiated personal belongings on behalf of Anthropic employees (Anthropic) Learn more about your ad choices. Visit megaphone.fm/adchoices