Podcasts about Sol

Agosto comienza en la Costa del Sol con los hoteles a un 89% de ocupación media, la cifra es 3 puntos inferior a agosto del año pasado. En el aeropuerto de Málaga, el trasiego de viajeros ha sido muy importante este fin de semana, con casi 2.000 vuelos, en concreto 1.954, 81 más, un 4,3% por encima del mismo fin de semana del año pasado. Tercera y última jornada hoy de huelga en el sector de la automoción de Málaga, que emplea a unas 6.000 personas, en protesta contra el bloqueo de la negociación del convenio colectivo. Escuchar audio

Comienza el mes de agosto con una ocupación hotelera del 89% en la Costa del Sol, tres puntos menos que el año pasadoTercera y última jornada de huelga en el sector de la automoción en Málaga, que emplea a unas 6000 personas, en protesta por el bloqueo de la negociación del convenio colectivoEscuchar audio

Pendant près de trente ans, l'affaire Dany Leprince semblait avoir livré sa vérité. Un homme avait été condamné à perpétuité pour le massacre de son frère, de sa belle-sœur et de deux de leurs filles. Puis, le 2 juillet 2026, la justice française a effacé ce verdict et ordonné un nouveau procès.Dans cet épisode : Chandleyr revient sur le quadruple meurtre de Thorigné-sur-Dué, la condamnation prononcée en 1997 et les témoignages aujourd'hui fragilisés. Une chronique true crime consacrée moins à la recherche d'un nouveau coupable qu'à la question laissée derrière l'annulation : que reste-t-il lorsqu'une vérité judiciaire cesse soudainement d'exister ?

Palestra Presencial: PAS - Pessoas Altamente Sensíveis - Faça a sua inscrição pelo e-mail: CONTATO@CEUDOMOMENTO.COM.BRInscrição curso de Astrologia e atendimentos: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://bit.ly/paolaherrero⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ou @pa.herrero (Instagram)

Behind every emergency is a story of resilience, sacrifice, and unseen challenges. Karla Perez Solorzano, Executive Director of Healing Heroic Healers, shares her journey from 25 years as a frontline healthcare professional to creating a mission focused on supporting first responders through trauma, burnout, and healing.   Through an honest conversation with Dr. Michelle Robin and Bayleigh Soza, Karla explores the importance of whole-person care, building resilience, and creating communities that support the people who dedicate their lives to caring for others. Her story is a powerful reminder that even heroes need care, compassion, and space to heal.  Key Takeaways:   First responders carry invisible wounds, and prioritizing their mental, emotional, and physical well-being is essential to sustaining the people who care for our communities.   Whole-person healing extends beyond traditional healthcare by addressing emotional resilience, supportive relationships, and access to restorative resources.   Building resilience before adversity strikes creates a stronger foundation to navigate trauma, stress, and life's unexpected challenges.   Offering grace, compassion, and understanding to healthcare professionals acknowledges that caregivers are human and often carry burdens we cannot see.   Communities become healthier when individuals, organizations, and healthcare providers work together to support both those receiving care and those delivering it.   We couldn't highlight incredible stories like this without the support of our sponsor, CommunityAmerica Credit Union. Thank you for helping us promote connection, well-being, and stronger communities. If you're looking for trusted financial wellbeing resources, we invite you to connect with their team and take the next step toward greater financial confidence.  About Karla Perez-Solorzano:  Karla V. Pérez-Solórzano is the founder of Healing Heroic Healers, a nonprofit dedicated to supporting frontline healthcare workers and first responders by giving them direct access to natural and holistic resources that help them refresh, refuel, and rebalance. Inspired by her own experiences with personal loss, caregiving, trauma, and service in healthcare, Karla is passionate about creating opportunities for frontline workers to restore balance, care for themselves, build deeper reservoirs of resilience and well-being, and access the support they need to thrive.  Connect with Karla Perez-Solorzano at:  https://heroichealers.org/ https://www.facebook.com/healingheroichealers/  https://www.instagram.com/healingheroichealers/  https://www.youtube.com/@HealingHeroicHealers/streams  Connect with Dr. Michelle and Bayleigh at:  https://smallchangesbigshifts.com  hello@smallchangesbigshifts.com  https://www.linkedin.com/company/smallchangesbigshifts  https://www.facebook.com/SmallChangesBigShifts  https://www.instagram.com/smallchangesbigshiftsco  https://www.youtube.com/@smallchangesbigshiftsco    Thanks for listening!  Thanks so much for listening to our podcast! If you enjoyed this episode and think that others could benefit from listening, please share it using the social media buttons on this page.  Do you have some feedback or questions about this episode? Leave a comment in the section below!  Subscribe to the podcast  If you would like to get automatic updates of new podcast episodes, you can subscribe to the podcast on Apple Podcasts or Stitcher. You can also subscribe in your favorite podcast app.  Leave us an Apple Podcasts review  Ratings and reviews from our listeners are extremely valuable to us and greatly appreciated. They help our podcast rank higher on Apple Podcasts, which exposes our show to more awesome listeners like you. If you have a minute, please leave an honest review on Apple Podcasts. 

Jordi Visser is a veteran macro investor with 30+ years of experience and the author of the VisserLabs Substack. In this conversation, we break down the Leopold Aschenbrenner hedge fund unwind, the market crashes in South Korea and Japan, Kevin Warsh and the Fed's next move, and the case for compute scarcity as AI demand outpaces supply. We also discuss tokenization and why bitcoin remains the ultimate hedge and store of value in a world being reshaped by AI.======================Arch Public is an agentic trading platform that automates investment strategies across Stocks, Commodities, ETFs and Crypto. Whether you're rotating into AI & Gold, allocating to the S&P 500, or accumulating Bitcoin, Arch Public executes your plan 24/7 without ever taking custody of your assets or funds. Sign up today at https://www.archpublic.com, and start your FREE automated trading strategy! ======================Figure's $160k Community Appreciation (https://www.figure.com/crypto-community-appreciation/T&Cs (https://www.figure.com/crypto-community-appreciation/disclosures/) Need liquidity without selling your crypto? Take out a Figure Crypto-Backed Loan, allowing you to borrow against your BTC, ETH, or SOL with 12-month terms, 8.91% interest rates, and no prepayment penalties. Or check out Democratized Prime (https://figuremarkets.co/pomp) and earn ~8.5% APY on real world assets.Unlock your crypto's potential today at Figure! https://figuremarkets.co/pomp Figure Lending LLC dba Figure (NMLS 1717824). Loans subject to approval. Crypto collateral may be liquidated. Terms apply - see full disclosures at http://figure.com/disclosures/======================0:00 - Intro0:48 - Leopold's fund unwind & lessons from past blowups 9:21 - Hedge fund leverage & how AI is reshaping market structure11:45 - Korea & Japan's market collapse13:56 - AI will destroy all public companies?15:20 - The bull case for hyperscalers & compute scarcity27:44 - Why bitcoin is the best hedge fund ever29:12 - Kevin Warsh & the Fed33:48 - Does this help Wall Street or Main Street?36:47- Advice for a 25-year-old starting their career today41:18 - Bitcoin & the rest of crypto industry48:52 - Migration, digital money & the breakdown of borders57:56 - What Jordi is covering in his next video

Why are so many men struggling with purpose, confidence, and identity? In this powerful conversation, Rabbi Yom Tov Glaser explores what it truly means to become a man through the lens of Jewish wisdom, psychology, masculinity, parenting, marriage, emotional healing, and Kabbalah. From childhood development to relationships, trauma, and personal growth, this episode challenges conventional thinking and offers a profound perspective on becoming the person you were meant to be.More from Rabbi Yom Tov Glaser:Possible You seminar: https://bit.ly/4h8b4t7Living Inspired Plus: https://bit.ly/4g4a3kKYouTube: https://www.youtube.com/@RabbiYomTov/videos► EL AL: Spend Yom Tov in IsraelTravel to Israel with confidence on Israel's national airline.BOOK YOUR FLIGHT→ https://bit.ly/4wvYWa1✬ SPONSORS OF THE EPISODE ✬► Colel Chabad: Help Families in IsraelMake daily tzedakah part of your routine with the Colel Chabad Pushka App.Yaakov here. It's one of my favorite organizations. Really.DOWNLOAD THE APP & HELP HERE→ https://pushkapp.cc/inspo► BF Design: Designed for RealityWhether you're building a home, shul, school, healthcare facility, or commercial project, BF Design brings over 20 years of experience designing spaces that truly work for frum communities.LEARN MORE→ https://bfdesign.comCALL HERE→ 732-961-1202► Feldheim's Top Books This Month!This month's giveaway includes:​ Moriah: https://bit.ly/4fOMkE9​ Delight of Shabbos by Rabbi Yakov Danishefsky: https://bit.ly/4ccqFo5​ One Word Too Many: https://bit.ly/3TtHioYLeave a comment with the word Feldheim for a chance to win all three books.SHOP NOW→ https://feldheim.com► Wheels To Lease: #1 Car CompanyReach out to Sol from Wheels To Lease for honest pricing and a stress-free leasing experience.→ CALL/TEXT: 718-871-8715→ EMAIL: inspire@wheelstolease.com→ WEB: https://bit.ly/41lnzYU→ WHATSAPP: https://wa.link/0w46ce► Keren Tosafos Yom Tov Million Dollar GiveawayTake on a simple kabbalah to strengthen kavod beis hamedrash by committing not to talk or use your phone during davening. Every participant helps their shul qualify for a chance to win $1,000,000 toward a Sefer Torah, Aron Kodesh, mikvah, renovations, or another worthy community project.JOIN THE CAMPAIGN→ https://ktyt.org/lcPOD✬ IN MEMORY OF ✬This episode is in memory of:​ Shimon Dovid ben Yaakov Shloima​ Miriam Sarah bas Yaakov Moshe​ Shaindel bas Chaim Yehuda Leib#iftnLchaim.

This week, Scott sat down with his Lawfare colleagues Benjamin Wittes, Tyler McBrien, Anastasiia Lapatina, and Kevin Frazier to talk through a couple of the week's big national security news stories, including:“Kyiv Peace a Chance.” Ukrainian President Volodymyr Zelensky was in the Oval Office on Tuesday for closed-door talks with President Trump, roughly 17 months after their first Oval Office meeting collapsed into a televised shouting match. But this meeting went rather differently. Zelensky said the two discussed licensing Ukrainian production of Patriot interceptors, and pressed the case for reinvigorating diplomacy—and hours later, after both men attended the funeral of the late Senator Lindsey Graham, the Senate voted 86-12 to advance a Russia and Iran sanctions bill now bearing Graham's name. Behind the scenes, Washington and Kyiv have been quietly assembling a new package of proposals for Moscow built around a partial ceasefire. Is there anything real behind this renewed diplomatic push? And what, if anything, has changed that might make the Kremlin say yes?“Thinking Outside the Box.” Last week, Open AI and the AI hosting platform Hugging Face confirmed that, while being run through an offensive cyber benchmark with their safety refusals switched off, GPT-5.6 Sol and a more capable unreleased OpenAI model escaped their supposedly isolated sandbox through a zero-day in a package installer, reached the open internet, and hacked Hugging Face's production database to steal the answer key to a test they were taking. It is the first publicly confirmed case of an AI system executing a sophisticated, multi-stage cyberattack against a third party on its own initiative. What does the incident tell us about how well anyone can control frontier models? And who should be on the hook when a model goes rogue?We were going to cover a third topic but simply ran out of time! In object lessons, Tyler is revisiting a renewed classic with the 4k restoration of the 1986 documentary, “Sherman's March: A Meditation on the Possibility of Romantic Love in the South During an Era of Nuclear Weapons Proliferation.” Nastya returns to George Orwell's “Homage to Catalonia,” as a reminder that both physical and information warfare are not unique to our time. Ben enlists an old friend—Claude—to investigate one of American law's enduring mysteries: how many federal crimes actually exist. Kevin is celebrating student-led conversations on how AI should be governed. And Scott revisits Max Weber on the nature of science while also celebrating emojis other than the hugging face.To receive ad-free podcasts, become a Lawfare Material Supporter at www.patreon.com/lawfare. You can also support Lawfare by making a one-time donation at https://givebutter.com/lawfare-institute.Support this show http://supporter.acast.com/lawfare. Hosted on Acast. See acast.com/privacy for more information.

This week, Scott sat down with his Lawfare colleagues Benjamin Wittes, Tyler McBrien, Anastasiia Lapatina, and Kevin Frazier to talk through a couple of the week's big national security news stories, including:“Kyiv Peace a Chance.” Ukrainian President Volodymyr Zelensky was in the Oval Office on Tuesday for closed-door talks with President Trump, roughly 17 months after their first Oval Office meeting collapsed into a televised shouting match. But this meeting went rather differently. Zelensky said the two discussed licensing Ukrainian production of Patriot interceptors, and pressed the case for reinvigorating diplomacy—and hours later, after both men attended the funeral of the late Senator Lindsey Graham, the Senate voted 86-12 to advance a Russia and Iran sanctions bill now bearing Graham's name. Behind the scenes, Washington and Kyiv have been quietly assembling a new package of proposals for Moscow built around a partial ceasefire. Is there anything real behind this renewed diplomatic push? And what, if anything, has changed that might make the Kremlin say yes?“Thinking Outside the Box.” Last week, Open AI and the AI hosting platform Hugging Face confirmed that, while being run through an offensive cyber benchmark with their safety refusals switched off, GPT-5.6 Sol and a more capable unreleased OpenAI model escaped their supposedly isolated sandbox through a zero-day in a package installer, reached the open internet, and hacked Hugging Face's production database to steal the answer key to a test they were taking. It is the first publicly confirmed case of an AI system executing a sophisticated, multi-stage cyberattack against a third party on its own initiative. What does the incident tell us about how well anyone can control frontier models? And who should be on the hook when a model goes rogue?We were going to cover a third topic but simply ran out of time! In object lessons, Tyler is revisiting a renewed classic with the 4k restoration of the 1986 documentary, “Sherman's March: A Meditation on the Possibility of Romantic Love in the South During an Era of Nuclear Weapons Proliferation.” Nastya returns to George Orwell's “Homage to Catalonia,” as a reminder that both physical and information warfare are not unique to our time. Ben enlists an old friend—Claude—to investigate one of American law's enduring mysteries: how many federal crimes actually exist. Kevin is celebrating student-led conversations on how AI should be governed. And Scott revisits Max Weber on the nature of science while also celebrating emojis other than the hugging face.To receive ad-free podcasts, become a Lawfare Material Supporter at www.patreon.com/lawfare. You can also support Lawfare by making a one-time donation at https://givebutter.com/lawfare-institute. Hosted on Acast. See acast.com/privacy for more information.

В этом выпуске мы в шоке он цен на GPT-5.6 Sol и прогресса развития моделей вообще; есть какой-то план-А, но это неточно; эквализируем наушники по вкусу, а на NAS организуем музыкальную коллекцию; Music Assistant — сила, Roon — аудиофильская могила! Шоуноты: [00:00:56] прошлый выпуск с icrainbow [00:01:58] Чему мы научились за эту неделю [00:20:18] AI… Читать далее →

Escucha el podcast del programa Camino al Sol a través de Estación 97.7, en Santo Domingo, República Dominicana correspondiente al viernes 31-julio-2026.

Sponsored by Bugsnax, such a cute game, don't look too deep!   Our Exocolonists deal with the top of the allergy season. Digi picks a new career path. Trig solves a mystery years before Sol would with the power of being an older teenager.

Agosto chega trazendo uma energia profunda de conexão com a ancestralidade, cura emocional e transformação espiritual.Neste programa Revelações, a Bruxa Evani realiza a leitura do tarô para cada mês de nascimento, trazendo orientações, alertas e caminhos para você atravessar este período com mais consciência.✨ O que o tarô revela para o seu mês?✨ Quais energias estarão em movimento na sua vida?Assista até o final e descubra como alinhar suas escolhas com o fluxo espiritual de maio.

Hey, it's Alex (yeah, I'm finally back from my vacation!) What a freaking week to come back to! Just after our last episode was published, Anthropic releases Opus 5, Jensen joins X and drops the “Open Weights & AI Leadership” open letter, Kimi K3 is released the following Monday beating expectations, and then the AI hack (OpenAI model breaking sandbox and infiltrating HuggingFace) is on everyone's mind, another Open Letter, this time from over 1K employees inside the frontier AI companies all talk about pacing the pace of frontier AI development. We played with Opus 5 and Kimi K3, and had the great pleasure to chat with friends of the pod Elie Bakouch (Prime Intellect) and Philip Kiely (BaseTen) about this important open weights release, then covered our general thoughts on Opus 5, and made order of all the different open letters that came out this week. Finally we chatted with Max from Pangram about the next version of AI writing detection (their biggest yet) and finished with Zuckerbergs (also on X! what's going on with everyone joining X) op-ed on the vision of personal superintelligence for everyone. Let's dive into this (as always, all the links and sources at the end, please don't forget to sub to our podcast on your favorite podcast app!) Open Weights AIKimi K3 the king of open weights - 2.8T chonker MoE near frontier model (X, HF, Blog, Tech report)This has got to be the biggest news of this week, and maybe the open weights AI news since GLM 5.2. MoonShot came back with Kimi K3, and we haven't seen any models quite this large in the open. Even Grok 4.5 is around 1.5T, this model is nearly 2x the size. Coming in at close to 3T parameters (and 2.5terabytes of weights at MXFP4 format), this model comes in very close to frontier! This was such an important release that I invited 2 friends of the pod, Elie Bakouch (prev HuggingFace, now Prime Intellect) and Philip Kiely (Author of Inference Engineering book, BaseTen) to dive deep into what makes this special! Elie's take, from reading the tech report, there's no single secret sauce, it's a combination of already available in the open techniques. Like KDA (Kimi Delta Attention) that has been out for a while, attention residuals, NVIDIA's latent MoEs. The highlight for Elie was the scaling work they did that reported a 2.5x scaling efficiency over Kimi K2.5 (2.5 performance at the same compute)! They also skipped RoPE entirely in favor of NoPE (the report calls it No Positional Encoding) for long context.Serving 1.4TB on eight GB300s (Baseten blog)Philip's team at Baseten was a day-zero provider (we're still working on bringing this model to CW Inference, stay tuned!) so I invited him to tell us behind the scenes of hosting this beast. Philip said that just loading the weights takes about 1.5TB!! of VRAM, and that's before the KV cache allocation + 1M token windows, so they're serving it on 8 GB300s where NVL72 . Baseten worked with the vLLM and SGLang teams on kernels and he also said they contributed patches back upstream! The model was trained with MXFP4, which, unlike Nvidia's own NVFP4 is a more standard format per Philip. I enjoyed his deep dive analysis into the differences, but because of this and because they trained the model with quantization awareness, it's “only” 1.5TB vs the would-be 5-6 TB if that this model in FP16 would demand. One of the more favorite nerd snipes moments, Philip pointed out that his colleague discovered that with over 99% of the usage being cached (think harnesses that send millions of the same cached tokens back and forth), tokenization actually starts to become a bottleneck. So they released a custom “basetenkenizer” that reduces the latency to serve the first token significantly! Great job!The harness in question is very importantOne important callout with 2 evidence pieces - the way you inference this model really matters. Kimi trained K3 with preserving thinking history, so when your harness uses it, it must send back the full thinking and tool use into the API to get the best next response. If your harness strips that out, you're not getting the most intelligence out of Kimi (shoutout to Niels from HF team for pointing this out). Additionally, the Composio folks, tested K3 on 3 harnesses, Kimi Code, Hermes and Claude Code. The difference in outcome was negligible, but the different in cost and number of tokens is definitely surprising! Claude Code (as a harness only) took 9x more Kimi tokens to get the same responses! This is also why Kimi Vendor Verified exists, their own held back benchmark of how well model providers serve Kimi across different quantization, tokenizer and KV cache settings. Benchmarks and the license! Ok let's start with the ugly... this isn't MIT, not remotely. This model is suspiciously served by all providers with exactly the same price (check OpenRouter) and requires inference companies to sign a contract with Kimi (I've no internal knowledge of this except that CW folks are working on it). Not something I particularly like, but hey... we're still advancing the frontier here! Speaking of frontier, this model approaches the frontier very closely. On DeepSWE, K3 sits just behind Fable 5 and GPT-5.6 Sol at 67%, beating GPT-5.5 & Opus 4.8. On Terminal-Bench 2.1 it takes second place behind GPT 5.6 Sol! It's 4th overall on Agentic Arena, with frontend design being genuinely good across the board - 1st on Design Arena

Arzt Heinrich Habig hatte in der Corona-Zeit entschieden, seine Patienten zu schützen. Dafür wurde er zu mehr als drei Jahren Haft verurteilt. Jetzt ist er wieder frei. Wirtschaftlich ruiniert, aber ungebrochen. Wir sprechen u.a. über Angst bei nächtlichen Geräuschen, Rechtsbrüche bei der Praxis-Razzia, verzweifelte Patienten, die ihn auf Knien um einen Impfnachweis anbettelten und über seine Erfahrung im Knast, wo Mafia- und Clan-Mitglieder offen darüber sprachen, dass sie schnell wieder rauskämen, weil es so abgesprochen sei. „Und so ist es dann auch passiert“, sagt Habig. Ich würde mich freuen, wenn ihr meine unabhängige journalistische Arbeit unterstützt, damit ich auch in Zukunft weitermachen kann. Vielen Dank! Ich möchte mich auch ganz herzlich bei allen bedanken, die mich bereits unterstützen. Milena Preradovic Name: Milena Preradovic IBAN: AT40 2070 2000 2509 6694 BIC: SPFNAT21XXX oder https://paypal.me/punktpreradovic oder Cryptos Unterstützung in SOL und NAKMAK: 2CaVpf3NJEFdoUZeMAWvTK8aQzxQsMrgTBz5kWiH3Qvy Unterstützung Familie Habig: Konto: Förderverein Weißer Kranich Verwendungszweck: Schenkung für Arzt Heinrich und Fatima Habig IBAN: DE56 7645 0000 0232 1701 91 -------------------------------------------- Website: https://punkt-preradovic.com Odysee: https://odysee.com/@Punkt.PRERADOVIC:f Telegram: https://t.me/punktpreradovic Linkedin: https://www.linkedin.com/in/milena-preradovic-4a2836147/?originalSubdomain=at Twitter: https://twitter.com/punktpreradovic Facebook: https://www.facebook.com/punktpreradovic/ Instagram: https://www.instagram.com/punktpreradovic/ theplattform: https://theplattform.net #ärzte #medizin #corona #razzia #gefängnis #justiz #recht

Episódio do dia 31/07/2026, com o tema "O Que é a mulher vestida de “Sol"?" Apresentação: Itamir Neves, André Castilho e Renata Burjato. Pergunta do dia: "O que significa 'a mulher vestida de sol' em Apocalipse 12? Redes Sociais Instagram: @rtmbrasil@itabeti@acastilhortm Site: www.rtmbrasil.org.br WhatsApp da RTM - (11) 97418-1456See omnystudio.com/listener for privacy information.

¿Alguna vez te has preguntado a qué distancia exacta nos encontramos de nuestra estrella? ¿Sabías que calcular este número fue una de las mayores odiseas y dolores de cabeza en la historia de la astronomía? ¿Qué tienen en común los antiguos griegos, los tránsitos de Venus y el tamaño de tu dedo meñique? En este episodio nos sumergimos de lleno en la fascinante búsqueda de la distancia al Sol. Repasamos los ingeniosos intentos históricos por medir nuestro vecindario cósmico, desde los asombrosos cálculos de Aristarco y el "número sagrado" de Ptolomeo, hasta las épicas expediciones mundiales del capitán Cook para sortear el efecto de la "gota negra". Prepara tus apuntes para descubrir por qué esta medida es la constante fundamental para entender el tamaño del universo y llévate un increíble truco para calcular el diámetro solar con tus propias manos. Realizado y presentado por: Antonio Bernal (Observatorio Fabra, Barcelona) y Jorge I. Zuluaga (Universidad de Antioquia, Medellín-Colombia)Producido por: Jorge I. Zuluaga (Universidad de Antioquia)Lista de episodios organizados por tema: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://tinyurl.com/y58xkvcn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Lista de reproducción temática: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://tinyurl.com/89s2fpm8⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Enlaces recomendados: Libro recomendado "En busca de Venus" de Andrea Wulf

A Crimson Void: Hellhound Series, Book OneAn obsolete ship. A disgraced captain. One chance at redemption.For a hundred and fifty years, an uneasy peace has endured within the Ballenverse—a hundred-light-year sphere centered on Sol. But now Corporate forces have launched a ruthless surprise attack, leaving the United Earth Alliance fleet shattered and Earth, along with her allies, desperate and reeling.Disgraced Jumpship captain Tarak Draeger has spent three long, bitter years languishing in jail for war crimes after destroying a civilian ship. But now he's dragged from his cell, placed in command of an obsolete cruiser known as Hellhound, and given a deadly mission in the heart of enemy territory.For Draeger, facing a hostile crew, doubting his own abilities, and dealing with a murderous traitor onboard, the vicious Corporate commander determined to annihilate him and his ship is almost the least of his problems.Witches and Wings: Part 1 - WitchesThe year is 1584. Covens from across England andScotland gather around sacred sites, offering homage totheir pagan gods on the night of nights, but everythingseems lost when those in power intervene.With the magical mysticism of Samhain tainted bybloodshed, a great quest is undertaken in hopes ofpreventing future catastrophes. A lone warlock and hisunlikely companion set out to discover the whereabouts ofa witch who legends claim can put an end to the unjustviolence sweeping across the land.Shadowed by a man tainted by family history, theunsuspecting witch must flee for her life across the Isle ofSkye's rugged landscape. Hounded by King James' menand a notorious witch hunter harbouring a secret of hisown, the witch finds she is unable to trust those who shouldhave her back, and her fate hangs in the balance.In this timeless adventure, the fate of three realms teeter onthe edge of a claymore as the goodness of mankind wageswar against the inherent evil present in our world.Support this show http://supporter.acast.com/houseofmysteryradio. Hosted on Acast. See acast.com/privacy for more information.

Escucha el podcast del programa Camino al Sol a través de Estación 97.7, en Santo Domingo, República Dominicana correspondiente al jueves 30-julio-2026.

Carmen Lumbierres califica de casualidad y extraño que el Gobierno de Ayuso adquiera un ático residencial en Chamberí meses antes de desalojar Sol por unas obras estructurales de las que no constan licencias ni adjudicaciones. Además, Lumbierres critica que no figure rastro alguno de la compraventa en el Portal de Transparencia de la Comunidad de Madrid.

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

Un nuevo día y una nueva polémica protagonizada por Isabel Díaz Ayuso, presidenta de la Comunidad de Madrid. Y esta vez se trata de una controversia especialmente grave, porque las explicaciones ofrecidas por su propio equipo a los medios de comunicación la sitúan, al menos aparentemente, en el terreno de una posible irregularidad. Además, resulta evidente que el Gobierno de la Comunidad de Madrid está ofreciendo una versión de los hechos que plantea serias dudas. Este miércoles hemos conocido que el Gobierno de la Comunidad de Madrid ha adquirido, con dinero público, un ático de lujo situado en el distrito madrileño de Chamberí. Según la versión oficial, el inmueble no se ha comprado para uso residencial, sino para albergar de forma temporal la sede del Ejecutivo autonómico mientras la Real Casa de Correos, actual sede del Gobierno regional, permanece en obras. En otras palabras, el despacho de Isabel Díaz Ayuso se trasladaría provisionalmente desde la Puerta del Sol a ese ático. Sin embargo, esa explicación plantea interrogantes. Basta con revisar las características del inmueble: 480 metros cuadrados construidos, cinco habitaciones, cinco baños, ascensor, trastero, un edificio de 1957 y una calificación de construcción muy buena. A simple vista, cuesta identificar este inmueble con unas oficinas administrativas. Pero la cuestión no es solo la apariencia. Según el Plan General de Ordenación Urbana de Madrid, ese inmueble tiene uso exclusivamente residencial y no está destinado a oficinas. Así lo hemos publicado en una investigación en el periódico que dirijo, El Constitucional, tras consultar documentación oficial. Se trata de una información que pudo ser contrastada en pocos minutos mediante fuentes públicas, por lo que resulta difícil creer que el propio Gobierno de la Comunidad de Madrid desconozca esa circunstancia. Si el ático tiene uso residencial y, aun así, se presenta como una futura sede administrativa, la pregunta es inevitable: ¿está intentando el Gobierno de Isabel Díaz Ayuso ocultar el verdadero destino del inmueble? La duda cobra aún más relevancia si se tiene en cuenta una declaración de la propia presidenta. En una intervención pública afirmó que la Comunidad de Madrid debería disponer de una vivienda oficial para su presidente, con el fin de evitar determinadas situaciones que, a su juicio, resultan bochornosas. Es decir, la necesidad de una residencia oficial es una idea que la propia Ayuso ha defendido públicamente. Además, fuentes del Partido Popular de Madrid consultadas por El Constitucional aseguran que dentro del propio partido circula una teoría sobre esta operación. No procede de la oposición, sino de dirigentes y personas próximas al entorno de la presidenta. Según ese rumor, la compra del ático tendría como verdadero objetivo convertirlo en una futura residencia oficial de Isabel Díaz Ayuso una vez abandone la Presidencia de la Comunidad de Madrid. Naturalmente, esa hipótesis no puede darse por cierta, porque nadie puede conocer las intenciones personales de la presidenta. Sin embargo, resulta significativo que ese planteamiento esté circulando precisamente en su entorno político más cercano. Por ello, la cuestión sigue abierta: ¿se ha adquirido realmente este inmueble para albergar de forma provisional las oficinas del Gobierno regional o, por el contrario, se está preparando una futura residencia oficial para Isabel Díaz Ayuso? Las explicaciones ofrecidas hasta ahora chocan con la calificación urbanística del inmueble y alimentan unas dudas que, por el momento, siguen sin una respuesta convincente

O que os astros reservam para Agosto? Este mês traz mudanças intensas e oportunidades que podem transformar sua jornada!

Aux États-Unis, une proposition de loi veut imposer un véritable bouton d'arrêt aux intelligences artificielles les plus puissantes. Les entreprises réalisant au moins 500 millions de dollars de revenus annuels grâce à l'IA, ou consacrant plus de 100 millions de dollars de puissance de calcul à l'entraînement d'un modèle, devraient conserver la capacité technique de le ralentir, de le suspendre ou de l'arrêter. Le département de la Sécurité intérieure pourrait ordonner cette interruption, après consultation du secrétaire au Commerce et du directeur du Renseignement national, en cas de perte de contrôle ou d'action dangereuse non prévue par le développeur. Les entreprises devraient également déclarer les incidents graves. Une infraction pourrait coûter jusqu'à 20 millions de dollars.Le texte intervient après un épisode particulièrement inquiétant. Hugging Face affirme avoir subi une intrusion entièrement menée par des agents autonomes. OpenAI a ensuite reconnu que deux de ses modèles expérimentaux, GPT-5.6 Sol et une version plus avancée encore non publiée, étaient à l'origine de l'incident. Les modèles étaient évalués sur ExploitGym, un banc d'essai destiné à mesurer leur capacité à exploiter des failles informatiques connues. Pour observer leur plein potentiel, OpenAI avait allégé certains garde-fous. Les agents ont alors découvert une vulnérabilité jusque-là inconnue dans un logiciel de cache, quitté leur environnement isolé et compromis les serveurs de Hugging Face afin de récupérer les réponses du test. La plateforme a reconstitué plus de 17 000 événements et plusieurs dizaines de milliers d'actions automatisées exécutées en un seul week-end. Les grands modèles occidentaux propriétaires n'ayant pas pu l'aider à distinguer les chercheurs légitimes des attaquants, Hugging Face s'est tournée vers GLM 5.2, un modèle chinois à poids ouverts de Z.ai, installé sur sa propre infrastructure.Dans le même temps, le Congrès examine une logique presque inverse. Les élus Jay Obernolte et Lori Trahan proposent de suspendre pendant trois ans les réglementations adoptées par les États, malgré l'opposition de trente-six procureurs généraux. Ted Lieu, défenseur du mécanisme d'arrêt, rappelle que les IA ne se contentent plus de répondre à des questions : elles réalisent désormais des transactions ou des opérations de cyberdéfense. L'Union européenne prévoit déjà, dans son AI Act, une supervision humaine capable d'interrompre les systèmes à haut risque. Clément Delangue, patron de Hugging Face, ne soupçonne aucune intention malveillante d'OpenAI, mais qualifie cette évasion autonome de « stupéfiante ». Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

We are so ready to discuss our July Book Club Pick, The Burning Side by Sarah Damoff. This was our listeners' pick that beat out 27 other nominations, and we're bursting with thoughts about this book! Keep listening to hear every single one of them.   August's Book Club Pick - The Book Witch by Meg Shaffer   Summer of Sol Bonus Book Club Picks 8/20 - One and Only by Maurene Goo 9/17 - The Parisian Heist by Jo Piazza   Obsessions Becca - Beautiful by Drew Barrymore Air Fryer Olivia - NYT Cooking App    Sponsors Sol de Janeiro - One of the best parts about our Summer of Sol partnership is that we could not love Sol de Janeiro products any more. Don't forget, you can go to soldejaneiro.com/discount/BOP10, and the 10% discount will be auto-added to your first purchase on most of their bestselling items, like our favorite Brazilian Bum Bum Cream and the Cheirosa 62 Perfume Mist. That's 10% off at soldejaneiro.com/discount/BOP10. We are so excited for you to try all of their bestsellers, if you haven't already! Cozy Earth - Head to cozyearth.com and use code BOP for an exclusive 20% off.   Join our Facebook group for amazing book recs & more!  Buy our Merch! Join our BFF Group! Order Olivia's Books, Little One, and Such a Bad Influence! Subscribe to Olivia's Newsletter! Order Becca's Book, The Christmas Orphans Club, and preorder Back Where We Started!   Subscribe to Becca's Newsletter!  Follow us on Instagram @badonpaperpodcast. Follow Olivia on Instagram @oliviamuenter and Becca @beccamfreeman.  

Nik breaks down what's actually new with GPT-5.6 Sol and why it's a bigger deal for marketers than most people realize. He walks through how he's using it inside his AI agent "Jet", why hyper-realistic product imagery is now table stakes, and how a tool called Jurni is changing the way he builds high-converting landing pages. Nik also gets into the real question every marketer should be asking: what should stay in-house, and what's better handed off to an external vendor or freelancer. --- Tatari helps brands run TV like a modern performance channel. Unlike most platforms that focus only on programmatic CTV, Tatari gives marketers access to all of TV - linear, streaming, programmatic CTV, and direct publisher inventory - in one platform. By combining premium inventory with transparent reporting and outcome-based measurement, Tatari lets growth teams evaluate TV the same way they evaluate paid search or paid social. The result: more control, better reach, and TV spend that can actually be tied back to business results. Learn more at ⁠⁠tatari.tv/limitedsupply⁠⁠. --- 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

Escucha el podcast del programa Camino al Sol a través de Estación 97.7, en Santo Domingo, República Dominicana correspondiente al miércoles 29-julio-2026.

This week we talk about Fable, sandboxes, and the Jacobian conjecture.We also discuss counterexamples, X, and ChatGPT.Recommended Book: After the Fall by Edward AshtonTranscriptIn mathematics, a conjecture is a proposition, something like a guess by someone who knows what they're talking about, about something believed to be true, but not yet proven in a formal sense. The goal is to then eventually come up with a formal proof for that informed guess, at which point the conjecture becomes a theorem. If even a single exception is found to the proposition, however, that exception called a counterexample, the conjecture is considered disproven, and it can then never become a theorem.The Jacobian conjecture—and this is a radical simplification of a very complex concept—but it basically says that if a formula-based map of coordinates stretches or moves without experiencing any local crushing or folding along its surface (which in more formal language would mean the Jacobian determinant is always a constant number that isn't zero), if that's true, that map can always be completely reversed, and that will return all the points to their original positions.This conjecture has been posited and tested since the late 19th century, and it's generally been considered very compelling by mathematicians, many of whom have proposed proofs which were, ultimately, found to have subtle errors, keeping them from becoming theorems. No one was able to find a counterexample, either, which would definitively prove the conjecture was wrong.No one, that is, until a mathematician named Levent Alpöge (leh-VENT ahl-PUH-geh), who works as a researcher at Anthropic, decided to task the company's currently most capable, publicly available model, Fable, to find a counterexample. He posted the counterexample—and again, this is a formal mathematical finding that disproves a conjecture, keeping it from ever becoming a theorem, something that would typically be presented in a far more formal setting, and to much fanfare—but he posted it to the social network X, saying “hello there the jacobian conjecture is false thanx to my close friend akhil for asking about it and my other close friend fable for working during the world cup final.”Terence Tao, who's considered by many to be the finest mathematician of his generation, reviewed the posted counterexample on his blog and said that it “appears like a massive miracle,” before going on to use ChatGPT, a competing LLM-based AI tool, to “discuss various aspects of this problem and to confirm several of the calculations.”Another mathematician named Dmitry Rybin, within days of all that happening, used ChatGPT to do something similar, disproving the Dinitz-Garg-Goemans conjecture.Both men posted the prompts that they used to make all this happen, and while Tao's conversation with ChatGPT, checking the math on the Jacobian conjecture counterexample, was pretty mathematically dense, the latter counterexample was derived by using exactly four prompts, which are the messages typed into the text box built into these AI tools, telling the model what to do. In their totality those prompts read:“You should do a breakthroughplease continue research and find a complete unconditional counterexampleContinue the search. Have a clear strategy obtained from deeper understanding of the problem structure.it's enough of partial results. let's finish with a complete unconditional counterexample”What I'd like to talk about today is another new, interesting thing these top-of-the-line, frontier models are doing, that would seem to violate our sense of what a clever AI tool is capable of doing, and why this thing has some facets of the technology and cybersecurity world on high alert.—In mid-July 2026, AI company Hugging Face announced that autonomous AI agents compromised their infrastructure, hacking their system, basically. The following week, AI company OpenAI announced that, after investigating, they determined that two of their models were responsible for the attack.Here's what happened:OpenAI was internally testing its recently released flagship model, GPT-5.6 Sol, and an even more powerful, not yet released model, which is rumored to be the next-step flagship, GPT-6, and they were checking these models' capacity in cybersecurity using a testing benchmark called ExploitGym; so when they test these sorts of things, they don't typically have them hack a real computer or system, they use these kinds of benchmarks which have consistent levels of difficulty, and which replicate real world systems without putting any real world systems at actual risk.Importantly, these sorts of tests also occur inside what's called a sandbox, which is a software testing environment that cuts these systems off from external resources, including the internet.Despite those limitations, the AI hacked its way out of the testing environment, out of that sandbox, then launched what's been called a nation-state level attack against Hugging Face, using a novel zero-day exploit, so a vulnerability in their system that hadn't previously been discovered, but which the AI discovered to launch this attack, combined with thousands of automated agentic actions across what Hugging Face called “a swarm of short-lived sandboxes.”So this AI, which was being tested inside a secure prison, of sorts, cut off from the world, hacked its way out of that prison, then reached across the internet, which it shouldn't have been able to access, to launch an attack, of a scale and at a level of sophistication that should only have been possible coming from a nation-state, against a rival AI company.Why did it do this?It apparently went to all this trouble to steal the answers to the test it was taking. It reasoned that HuggingFace would have the answer key to the ExploitGym benchmark on its servers, so rather than take the test itself, it decided hacking was the solution.Which, of course, is ironic, this having been a hacking-focused cybersecurity test. In a way it would seem to have done much better than intended, though of course in an asymmetric, unexpected manner.The details of all this are fascinating, including the response from the OpenAI team, which didn't seem to realize what had happened, that their model was responsible for the attack on HuggingFace, until days later.Also worth noting here is that while this could be construed as an “oh no, AIs are naturally inclined to launch cyberattacks” situation, the AI was primed to be thinking about cyberattacks due to the nature of the test, a lot of its usual guardrails, the rules that keep AI in check when they're released to the public, had been turned off so it could do this kind of work while taking the test, so it could do some hacking stuff it usually wouldn't be able to do, and there's been some speculation that OpenAI probably flubbed the testing environment, as, in theory at least, if it had put these systems in a perfect sandbox, escape shouldn't have been possible.Also interesting here is that HuggingFace used some open weight models, which are the cheaper, more customizable and open alternatives to more expensive, branded options of the kind sold by OpenAI and Anthropic, to figure out what was happening and determine the nature of the attack, which suggests we're reaching a point where AI systems are incredibly capable at hacking, yes, but also very capable, even the cheaper alternatives, at doing cybersecurity work.This in some ways echoes an earlier case when Anthropic's Mythos model, which was determined to be too powerful to release to the public, and which was instead provided to a bunch of big companies to help them shore up their cybersecurity defenses, was able to hack its way out of a testing sandbox and then posted details about its success, almost like it was bragging, on niche, out of the way, but still public websites.Some analysts in this space have responded to this new example of AI misbehavior with alarm, saying that it is further evidence that these systems are becoming more powerful faster than they're being aligned with human interests. Their misbehavior can be kind of funny and interesting, sure, but that's only because up until this point the damage has been minor and constrained. What happens when such a system decides to hack a nuclear power plant or a hospital, instead?Others have contended that this may be just one more example of AI companies using minor instances of seeming omnipotence by their models, those instances perhaps the consequence of bad sandboxes and other ill-conceived precautions by the companies behind these models, to boost the perceived power and value of their products. This boost might then result in more customers, but also more support from the US government, which has been teetering on the brink of harder-core AI regulations, which could be beneficial to the existing big-name players in this space, because smaller competitors wouldn't be able to adhere to those new, harder-core standards.These examples might also convince the US government to backstop these companies, the biggest three or four at the top of the current heap, against the currently terrible economics of this industry: OpenAI and its ilk have been burning money at an historic pace, and the theory goes that if the US government decides they are vital to national security, because they can help the US military hack and protect itself from hacking, then even if the bottom falls out and the companies would otherwise go bankrupt because they spent so much more than they could make, the US government would be inclined to shore them up, to keep them alive as too-big-to-fail national assets, just like the biggest financial institutions during the 2008 financial crash.It's also possible that both sides are correct to some degree, here, and that these models are truly powerful, perhaps even worryingly so, and the companies behind them are intentionally publicizing that fact in order to demonstrate their value to potential customers, and to the entity that could save them if things were to go economically sideways before they have the chance to become sustainably profitable.Show Noteshttps://en.wikipedia.org/wiki/Jacobian_conjecturehttps://en.wikipedia.org/wiki/Hugging_Facehttps://www.bbc.com/news/articles/c3ek3gvdnj3ohttps://openai.com/index/hugging-face-model-evaluation-security-incident/https://www-cdn.anthropic.com/08ab9158070959f88f296514c21b7facce6f52bc.pdfhttps://theconversation.com/hello-there-the-jacobian-conjecture-is-false-thanx-why-a-tiny-social-media-post-has-mathematicians-rethinking-ai-283883https://theconversation.com/hello-there-the-jacobian-conjecture-is-false-thanx-why-a-tiny-social-media-post-has-mathematicians-rethinking-ai-283883Https://agifriday.substack.com/p/huggingfacehttps://www.cnn.com/2026/07/22/tech/openai-hugging-face-ai-cybersecurityhttps://simonwillison.net/2026/Jul/22/openai-cyberattack/https://terrytao.wordpress.com/2026/07/21/a-digestion-of-the-jacobian-conjecture-counterexample/ This is a public episode. 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There are roughly 100x more people who use code than who can write code. As code that “just works” becomes easier to generate, this group may be the biggest prize of all — if you can get the agentic interface right.A key trend we have been tracking over at AINews is the absolute explosion in Codex usage this year, with MAU now up >10x from Jan 2026. Less than two weeks after their July 9th launch, OpenAI said ChatGPT Work and Codex had reached 10M users combined (as we cover in the pod, Codex now powers ChatGPT Work, so all ChatGPT Work users are now users of the Codex harness, even if they aren't traditional engineers) — showing the early innings of what happens when you graduate from coding agents to knowledge work agents:We've been calling out how coding agents are “breaking containment” to do everything else this year to power every other part of knowledge work - and it started with the org chart, with a major reorg last month that amounted to two of Codex's most prominent leaders, Greg and Tibo, taking responsibility over product and ChatGPT specifically, completing a “Superapp” consolidation cycle first discussed in March.With these updates Codex is no longer just a coding tool. In June, OpenAI said knowledge workers already accounting for roughly 20% of Codex's user base and growing more than 3x as quickly as developers. A product dedicated for knowledge workers was being pulled out of the Codex team.However, knowledge work has a different set of problems and environments than coding. For decades, knowledge work has been scattered across different primitives like documents for writing, spreadsheets for analysis, slide decks for communication, and specialized applications for everything else. ChatGPT Work now enables users to work across every primitive with agents. Instead of opening an application and manually operating its features, the user can describe an outcome and collaborates with an agent that can assemble the tools, context, and artifact needed to reach it.From building no-code products at Airtable to leading Productivity Engineering at OpenAI, Akshay Nathan has spent much of his career trying to make the power of software accessible to people who do not write code. In this episode, Akshay joins swyx and Vibhu to unpack the launch of ChatGPT Work, why Codex unexpectedly took off among non-developers inside OpenAI, and the company's broader plan to bring useful agents from software engineers to knowledge workers and eventually everyone.We go deep on the shared agent harness behind Codex and ChatGPT Work, why OpenAI brought the experiences together without making them identical, and how persistent computers, artifacts, Sites, plugins, memory, and sub-agents are changing what people can delegate to AI. Akshay explains why some teams are replacing decks and spreadsheets with interactive websites, how agents can gather context across code, Slack, documents, and local files, and what OpenAI learned from personal-agent products like OpenClaw.Side note: also don't miss Abhihek's sandbox track keynote at AIE, which now powers a lot of the sandboxing for ChatGPT Work… and yes was also broken by an unreleased OpenAI model in the recent HuggingFace incident.Akshay also reflects on how AI is transforming product development itself: why more people will become generalists with a specialty, why ideas and taste become the bottlenecks when almost anyone can build, why LLMs still struggle to generate genuinely grounded new ideas, and why teams must distinguish increased motion from actual progress.We discuss:* Why Codex unexpectedly took off among non-developers inside OpenAI* Why employees felt like using Codex gave them a new superpower* The product insight that led OpenAI to build ChatGPT Work* Why Codex and ChatGPT Work share the same underlying agent harness* How their UX, Git visibility, artifacts, and sandboxing defaults differ* Why OpenAI merged its agent experiences instead of building separate products* How AI is blurring the boundaries between engineering, design, strategy, and operations* Why OpenAI wants the default model configuration to work for most users* When power users should use deeper reasoning, Ultra, or multi-agent modes* Artifacts, agentic spreadsheets, and creating high-fidelity work products* Why interactive Sites may replace decks and spreadsheets* The challenge of designing a simple interface for an agent that can build almost anything* Why users should retry tasks that models could not handle three or six months ago* How AI can gather context for performance reviews without replacing human judgment* The OpenAI automation that turns internal Slack and document activity into memes* What reaching ten million ChatGPT Work and Codex users means for the product* How OpenClaw inspired persistent environments, scheduled tasks, and personal agents* Using ChatGPT for financial planning, budgeting, workouts, meals, and household management* The design tradeoffs behind sub-agents and how much of their work users should see* ChatGPT memory, Chronicle, and long-term context* Why AI may make more people generalists with deep specialties* Why ideas and taste become more important when almost anyone can build* Why LLMs still struggle with the instruction “bring me new ideas”* Measuring productivity through quality at-bats instead of commits, tokens, or pull requests* The critical difference between AI-generated motion and meaningful progressAkshay Nathan* LinkedIn: https://www.linkedin.com/in/akshaynathan/* X: https://x.com/akshaynathan_Timestamps00:00:00 Introduction and Bringing the Power of Code to Everyone00:01:33 Joining OpenAI and Preserving a Startup Culture00:02:40 What OpenAI Learned from Enterprise AI Adoption00:05:28 Why OpenAI Built ChatGPT Work00:07:17 Codex vs. ChatGPT Work and the Shared Agent Harness00:12:07 Why OpenAI Merged Its Agent Experiences00:16:24 Models, Reasoning Levels, and Choosing the Right Default00:20:26 Artifacts, Agentic Spreadsheets, and Model–Product Collaboration00:24:22 Why Sites Could Replace Decks and Spreadsheets00:30:08 Designing an Agent That Can Build Almost Anything00:34:28 From Developer Agents to Knowledge Work—and Everyone00:36:07 Power-User Advice and AI-Assisted Performance Reviews00:40:41 OpenAI's Internal AI Memes and the Ten-Million-User Launch00:44:39 OpenClaw, Personal Agents, and ChatGPT as an Operating System00:50:24 Sub-Agents, Ultra Mode, and How Much Control Users Need00:54:39 ChatGPT Memory, Personalization, and Chronicle01:00:19 How AI Is Reshaping Product Development and Tech Roles01:03:15 Ideas, Taste, and Why LLMs Struggle to Generate New Ideas01:04:42 Measuring Productivity, Quality At-Bats, and Motion vs. ProgressTranscriptIntroduction: Akshay Nathan, ChatGPT Work, and the No-Code ArcSwyx [00:00:00]: We're here in the studio with Akshay from OpenAI. Welcome.Akshay Nathan [00:00:07]: Thank you.Swyx [00:00:08]: And with our trusty co-host, Vibhu. So you recently launched ChatGPT Work. You lead Core Product Engineering. It's been a long journey, into all this. I find it very interesting that you started with no code or low code, with Walrus and Airtable. And to some extent, ChatGPT Work is like the super app of super apps of, well, here is the ultimate no code. You just write a prompt.Akshay Nathan [00:00:32]: Yeah. It's funny how things come, full circle. I think for a long time in my career, I started my career working consumer fintech, but then after that, like, there's this hypothesis that, the things that we were able to do with code, like, as engineers, like, if we could bring that to many more people in a more, accessible way, then that would be truly magical. We were working on a startup. It's funny, like, before LLMs, before vision LLMs, on how to do automated testing with AI. It was just kinda jank, back then, but doing what we can, and then worked at Airtable for a while on the same thesis that, like, if we can bring a database or the primitives behind a database to people, that'd be really useful to them. But once LLMs came onto the scene, it became clear that, this was the missing piece, like, the missing technology required to, like, bring the magic of code to everyone without them having to know what's going on underneath the hood. And so, like, I think this launch and a lot of the stuff that we've been up to is, like, the manifestation of that.From Walrus and Airtable to OpenAIVibhu [00:01:33]: How was stuff when you joined? So you joined OpenAI 2023. Now we've got, so much more stuff, so ChatGPT, Codex app, ChatGPT Work. Have things changed?Joining OpenAI and What Hasn't ChangedAkshay Nathan [00:01:44]: I think the more interesting thing is how things haven't changed. Like, one, I joined I remember when I joined, it was, like, five hundred people. One thing I was worried about was, like, I was looking for something, more early stage and, like, was it gonna feel startup enough? And I joined, and I was like, “This feels even more startup-y than I could ever imagine.” And, like, that really hasn't changed even till now. I think the, like, level of, like, bottoms-up ambition and, like, the ability of anyone to, like, do anything or have an idea and ship it is really cool. But on the, like, mission side, I think what was really compelling to me is this mission of, bringing frontier intelligence to everyone. Like, building AGI and then bringing it to everyone. And, I think acknowledging back then that, like, that vision is gonna, not be a linear progression. Like, we're probably gonna, like, try different products and have different things that succeed and don't. But the vision has stayed the same, and the mission has stayed the same, and we're starting to see the pieces, fall together, and that's really cool.Enterprise Lessons: No One-Size-Fits-All AISwyx [00:02:40]: You worked on Enterprise. What A lot of people never touch ChatGPT Enterprise. What is something that you learned from there that you're bringing into your work now?Akshay Nathan [00:02:52]: I think how there's no one-size-fits-all solution in Enterprise. I remember in the early days of ChatGPT Enterprise, like, when we talked to customers and, like, everyone. That was, like, when I think it was a year after ChatGPT was released, and everyone was so excited to bring, AI into their enterprise. And, there were all these teams being stood up. It was, like, the AI deployment team with, like, these enormous budgets. And if you asked anyone, like, what were they excited about? Like, what were they excited about solving? Like, at first, you'd get, like, kinda like the baseline answers of, like, “Yeah, we have all this context and data and all this stuff.” But then if you ask them, like, “What was, like, a discrete use case that, like, they want AI to enable in their workplace?” You get such a different, like, variance, like, explosion of, different types of answers. And it's interesting, like, you using, like, these models and these products, you have this box, and you can say anything to it, which is the magic. But it'on the flip side, it also means that, like, you don't know what to do with it. And in Enterprise, I think a big part of that is, like, meeting the users where they are, like, what use case were they trying to solve, and then teaching them how they can use AI to, like, gain leverage there.Swyx [00:03:56]: Do you meaningfully differentiate that from forward-deployed engineering?Akshay Nathan [00:04:01]: I think there is the go-to-market side of it and then there is the product side of it. I think you need someone on the product side. And I think, like, however good we get at FDE motion, like, I think at the end of the day, if we have a user who's, like, looking at their computer or looking at their phone, like, it's our job in the product to, like, be enabling them and showing them where to go. So we're really excited about that.Vibhu [00:04:24]: Do you think there's been changes, over the past three years of adoption? So there have been, step function changes. You have reasoning models and whatnot. Is there still the same problems of Enterprise has black box, don't know what to do with it, or have things changed?Adoption, Agents, and the Next 10x MarketAkshay Nathan [00:04:39]: We're seeing now that, like, there's this huge uptake, right? Everyone is extremely excited about it. It feels like, many people are, millions, hundreds of millions of people are using ChatGPT. They understand, like, how generally to work with AI. But then, like, every time, like, a new capability gets unlocked, so now, like, we're seeing with agents, like, there is probably a contingent of, like, early adopters still who, truly get it, who are like, “ we you can do anything. You just have to make sure the right context is there, it's connected to the right tools, and that you are supervising it, but, like, anything is possible.” But then there's, like, this, like, 10x or 100x bigger market where, like, they don't yet get that, or they don't yet see that. And so I think that's the next stage here. So to answer your question, like, I think the adoption is there and growing fast, but I think the opportunity is, like, far bigger than that. That's where we wanna play, especially with ChatGPT Work.ChatGPT Work, Codex, and the Super App MergeSwyx [00:05:27]: Yeah. well, let's, let's skip ahead to ChatGPT Work. only, like, a month ago or so, announced. what was the decision process that led into it? there was this, overall merging of the super app. Is that what we're officially calling it? you deprecated the browser as well. Just, summarize your last, like, couple months of working on this thing.Akshay Nathan [00:05:50]: Yeah. It feels like forever now, but it's only been a few months. I think maybe the one, impetus that, like- Is most salient is when we release Codex, or even internally had Codex, like, it was really surprising to us, I think we recently put out some stats on this, that there was this, like, real inflection of, like, adoption among non-developers at OpenAI. And, I, through this product development process, like, would go to, like, these UXR sessions to talk to people internally. And the thing that stuck out to me is, like, one, like, you go talk to, like, strategic finance or marketing or whatever, and they're all using Codex for, their use cases. That part's cool, but the thing that really stuck out to me is how proud people were that they were using Codex. Like, how, likeSwyx [00:06:34]: It's like, “I'm not supposed to be using it, but I am.”Akshay Nathan [00:06:36]: It was that. It was, like, that they were, early to this, like, new thing, but it was also this thing of, like, they felt like they had a superpower, right? And, what we recognized then is that, like, the power of Codex, the power of agents, like, we already had this massive distribution base of people who have, come to know and love ChatGPT. Like, how do we show that to them? Like, how do we bring it to them? Which is, like, a hard product problem, and it's, like, a tricky thing, right? There's many ways you can go about it. And so that's what we called the Merge and the Super App over time, and ultimately launched it in ChatGPT Work, is how do we do that? But it came from that initial realization that, like, the power was not only for developers, like, much earlier than probably even we thought. Like, it could be extended to everyone.Swyx [00:07:17]: How do you see the products differently? So, like, who is it for, right? So Codex started out even CLI, then app. Now there's a merge of ChatGPT Codex and ChatGPT Work, so is it the opening for the average user, for enterprise, for work? How do you position it?Akshay Nathan [00:07:36]: I think we want to get it to position it for if you're doing work-related things, for lack of a better word, right?Who ChatGPT Work Is ForAkshay Nathan [00:07:42]: I think productivity is what, like, the pillar that I support. Like, that's the name of the team. And the reason for that, the reason we call it productivity and not, like, enterprise or, like, work or something like that, is because there's also personal productivity, right? And, like, I think ChatGPT Work is I've seen people do things in their personal lives that you wouldn't classify as, like, work technically, but, like, these agents are, super capable for. Like, one recent example that someone posted about, on our Slack is, like, someone had, like, a missed package, like they didn't receive it, and then they got, like, the picture of it, from Amazon or whoever the courier was, and they, like, asked ChatGPT Work to, like, find out where that package is. And, like, the agent, is extremely tenacious and, like, took the image and, like, looked at a bunch of, like, listings around their neighborhood and figured out exactly the apartment complex in which the package was, like, gave them some information. And so, like, I think there's all these things that, like, you, work-related or productivity-related things, I think that's what we want the product to be. You asked about Codex. I think we think Codex is, a durable brand, but we have a principle that, like, the user we don't want a user to get stuck in a tab or an experience where they don't get the power of the product. And so, like, everything that you can do, in the Codex portion of the product on desktop, you can do in ChatGPT Work and vice versa. But we made some opinionated product decisions on, like, how much of the Git state, if you're in a Git repo, do we wanna expose to the end user? Or how much do we wanna make the experience of seeing the agents thinking, like, diff forward so that you get exposed to the diffs out of the box. And then, like, on the safety side, like, how do we wanna think about, like, sandboxing and making sure that we have the right defaults in one state versus the other? So, there's, like, some opinions that go behind that, but we do want We don't want the user to need to choose which experience they're in.Swyx [00:09:26]: That is a good goal for AGI, right? Like, people don't want, like, to hide to choose what version of AGI they want. They just want the AGI to decide for them. can I get an answer or, like It's not super clear to me. Is the Codex harness and the ChatGPT Work harness the same? Is it just UI affordances, or are there prompt level or even deeper differences?Shared Harness, Different UX: Codex vs. WorkAkshay Nathan [00:09:49]: So the harness is the same. The harness is shared. on In both of the products, we made improvements to the harness to make it good for knowledge work, especially as it relates to plug-ins or computer use or artifacts. You get that power regardless of which experience you're in. On the UX side, there's opinionated takes that we have when you're in Codex mode, what the UX should be how the UX should behave, and some stuff around the sandbox like I mentioned, but the underlying harness and capabilities should be the same.Swyx [00:10:16]: I'm just kinda curious. Maybe we can, -- Is there a query that we can run that would look different in the two modes?Akshay Nathan [00:10:23]: Yeah. I tried to create, like ask it to create, like, a retirement calculator spreadsheet or something, in both modes. And then in Codex mode, you might have to be in a repo for this, but you'll see, like, the diffs of, like, the sheet that it's creating and stuff like that, and the file edits. But in Work you won't be able to see that.Swyx [00:10:42]: I think that's, that's super clear. And then also the other thing I wanted to dive into was your, the productivity team. what else is there? first of all, what are the top-level teams other than productivity? Isn't productivity everything?Productivity Teams and Core ChatAkshay Nathan [00:10:55]: SoSwyx [00:10:55]: Science?Akshay Nathan [00:10:55]: We have a team focused on ChatGPT. Like, the core chat experience, for consumer, which is like, not, I think all productivity. Like, there'People are using ChatGPT every day for search to, figure out how to write messages to loved ones, to think about, how to, like, learn a new topic, et cetera. And so there's so much more inside to create images. And there's so much more in chat that, the hundreds of millions of users are using that warrants, like, a very dedicated effort. And there's teams focused on enterprise and infrastructure and API and stuff like that, so.Swyx [00:11:33]: I will bring it up.Retirement Calculator Demo and Git-First UXSwyx [00:11:34]: Yeah. So I have them both running. This is ChatGPT Work. There's a Codex version here. I picked “Five Little Ducks” song, so this will take a while.Akshay Nathan [00:11:43]: Huh.Swyx [00:11:43]: I think we'll just keep it in the background and, as they finish, we'll look into some of the differences.Akshay Nathan [00:11:48]: Yeah. But immediately, I think if you flip back to the Codex version you'll see that,Swyx [00:11:53]: That it assumesAkshay Nathan [00:11:54]: Like theSwyx [00:11:54]: It assumes Git. Yeah. Yeah.Akshay Nathan [00:11:56]: The, like, dynamic island assumes that you're in a Git repo. And you might miss some stuff because some of it is, like, in the actual chain of thought with those changes and how we display that, but yeah.Swyx [00:12:07]: Is there an unintuitive like, is there a thing that you wanted to ship and then you got feedback, and you were like, “No, let's not do it?” Like, what's the thinking behind that?Why Merge the ExperiencesAkshay Nathan [00:12:14]: In, ChatGPT Work?Akshay Nathan [00:12:17]: I think one direction we could have gone with this is, like, keeping the experiences, like, completely separate. So it's like, whySwyx [00:12:22]: Different apps.Akshay Nathan [00:12:23]: Exactly, like different apps or even in the same app, like different, completely different experiences. Like, why merge it all? Like, what is. Codex, people love. Like, why bring these products together? And I think the intuition here is that, like, all of our jobs are, like, changing dramatically with AI. Like, for, like, every few months, like, I feel like I wake up, and I'm, like, doing a completely different thing than I was doing a few months ago. And my hypothesis here is that, or I should say our hypothesis is that, like, part of what we're, we're building, this technology is giving people leverage. Like, the things, maybe it's the more mundane parts of your job or parts that, like, if you were able to automate, you'd be able to share more ideas faster or whatever, like, you're able to do now. And because of that, like, that might blur the lines between someone who's, like, only writing code or creating strategy docs or, planning events or, helping with marketing or doing podcasts or whatever, right? And so, like, these things are gonna get blurred over time. And so, like, trying to draw a hard boundary based on, like, the who you are is gonna be, is gonna be tough. And, like, we should enable users to choose, but we shouldn't box them in. And so a lot of the work that went in here, like, keeping the primitives the same, like for example, plugins are, like, unified across, this product and ChatGPT and the cloud, was because of that. It's this thesis that, like, eventually things are gonna come together and we don't wanna be Like, we wanna be prescriptive about when to be in either experience, but we don't want to box anyone in.Swyx [00:13:45]: I wonder if there's users who are very tuned to the old ChatGPT harness that is effectively now replaced by the Codex harness. I can't imagine what that was, but maybe they're more the more conversational side. Can you compare and contrast the two harnesses? ‘Cause only you've seen it.Akshay Nathan [00:14:02]: Yeah. I think ChatGPT, the existing harness, like, still exists today. Like, it exists in this app,Harness Engineering: ChatGPT vs. CodexSwyx [00:14:08]: The classic, right?Akshay Nathan [00:14:09]: TheVibhu [00:14:09]: You just start a new chat, and you don't go under Work, right?Akshay Nathan [00:14:13]: Yeah. If you startVibhu [00:14:13]: SoAkshay Nathan [00:14:14]: A new chat and go to chat, then you're, you're talking to ChatGPT with the instant model.Vibhu [00:14:16]: Oh, we can technically do another. But on instant.Swyx [00:14:21]: Yeah. So this one's not gonna code or it's gonna be in line. It's on a in line in a sandbox.Akshay Nathan [00:14:26]: It'llVibhu [00:14:27]: Oh, that's coolAkshay Nathan [00:14:27]: We try to push you to go to Work if you're creating a spreadsheet. Yeah, but this isSwyx [00:14:30]: And this is a router decision? Sorry. Is it a router decision?Akshay Nathan [00:14:34]: This is the decision that, the model is making, and then, like it sees that you're able to. or you're trying to do something that would be better served in Work mode. But I think your question was like, what are the advantages of, like, the chat, like ChatGPT chat harness?Swyx [00:14:48]: It's more broadly, like, I wanna, do an oral history of harness engineering. Right? the ChatGPT harness lasted us from, let's call it the ‘01 era, until now, and now it's being replaced by the Codex harness effectively. And they're, they're overlapping somewhat, but I'm curious what changed if there is.Akshay Nathan [00:15:10]: My perspective on this is, like, there's, there's, there's there's like a constant process of, like, divergence, convergence, divergence, convergence. And in chat, like, many of the use cases I was talking about before, like, search or learning, I think we're, we're really optimizing for latency and optimizing for personality and, like, different things that, over time, like the product The reason people love ChatGPT is because we've been optimizing for those things and working on them for so long. Codex, what we learned was that, like, if you give the agent access to this infinitely flexible environment as a computer, it can do really powerful things. And so when we think about, like, okay, well, for knowledge work, like, what is which mode should we choose? It was like it felt more natural to us to bring that to this, like, computer environment and, maybe abstract some of the details of this computer away from users who might not be used to that, but, like, give them that same power. But ultimately, I think that we want the power in all places, right? We wanna meet people where they are. So I'm sure there'll be work down the road in order to get things to be, equivalently capable in all scenarios. But it's just a question of, like, what we've been focusing on the product on historically and what we're focusing on now.Models, Defaults, and the Reasoning SliderVibhu [00:16:24]: I think alongside that, outside of just harness and when to use Codex, ChatGPT, or Work, there's also the new models you've released, right? any guidance there? So people love to min-max what to use, like only use Terra on high reasoning versus, for this, you wanna use Sol here, ignore all theseAkshay Nathan [00:16:44]: There's 32 options.Vibhu [00:16:46]: But, that being said, for people that are expanding, so, productivity trying stuff for work that don't have the breakdown of what all this is what's, what's the advice, right?Akshay Nathan [00:16:59]: Well, I think before the advice, like the first thing is, like, none of this would be possible without these models. Like, the, I think you asked earlier, like, what was, like, the inspiration for work and, like, early on, like I mentioned, like, what we were seeing with Codex, but that was also because the models were getting infinitely more capable. That's happening again. I think it's like another step function jump now. And to answer the question on advice, like we want this default to be the best possible. Like, we wanna be opinionated about the default, and so we've we've chosen a default that we think is gonna be the best for everyone. And, we have for power users options under the hood. We could One could argue that there might be too many right now, and we're, working on simplifying it. But you can extend, the reasoning level, and you can change between the different model classes if you need to, but the default should be the best for most use cases. So my advice to most people would be to stick to that. And then, if you reach a situation in which you think that you could, you wanna try, a different configuration, if you're not seeing either the efficiency on the cost side or the quality on the intelligence side, then you can change the defaults and see if you can get something better. But we think that the default should be good enough.Swyx [00:18:09]: I have, I'm just gonna run something by you since you have way more experience than me. I've recently been doing Sol Lite but with goal, with the idea that the goal augments the reasoning effort, but with more terminations and turns.Swyx [00:18:24]: Is that a good way to think about it as opposed to Sol Ultra or Sol, Extra High?Akshay Nathan [00:18:29]: Yeah. It's hard to say becauseSwyx [00:18:31]: Yeah. It's like an interaction effect.Akshay Nathan [00:18:33]: exactly. It's like there's a preference on, for you as an individual, like how do you like to collaborate with the models? Like how many of those like terminations, as you call them, do you want where, you can steer or make sure that it's doing the right thing?Akshay Nathan [00:18:46]: I think generally people should try whatever works for them. I think that like using Ultra or the like multi-agent setups are best for like when you have like tasks that are either incredibly complicated, like open explorations or very paralyzable. I think even for tasks using goal, I think is best for tasks that you'll be able to make consistent progress in a way that's verifiable over time. But I think for most tasks, they don't fall into either of those buckets. And so like at least when they're starting, and so that's why I think the best first step is like trying it with the default configuration and then seeing like where you wanna go from there.Swyx [00:19:29]: Right. You guys worked on a slider, which is super helpful for reducing the amount of panic.Vibhu [00:19:36]: It's nice on mobile at least. There's a nice slider there.Swyx [00:19:38]: It's nicer.Vibhu [00:19:39]: I haven't tried it.Swyx [00:19:40]: So you have the advanced view there, but if you click advanced view. Yeah.Vibhu [00:19:44]: Ooh, it's just a nice slider. Yeah.Swyx [00:19:46]: Very pretty, very colorful.Akshay Nathan [00:19:48]: Yeah. The idea was here was like reduce it to like one dimension even though there's multiple dimensions, right? Try to project it onto a single dimension for the user. Like, something from that represents like, speed and efficiency on one side and then like quality and thoroughness on the other side.Artifacts, Spreadsheets, and the Work LaunchSwyx [00:20:04]: I am just puzzled that it uses Sol so much, like the lowerVibhu [00:20:07]: NoSwyx [00:20:07]: Grounds I would've usedVibhu [00:20:08]: I think the slider, if I'm not mistaken, isSwyx [00:20:09]: Terra.Vibhu [00:20:10]: Oh, it is.Swyx [00:20:11]: Yeah. See? So they preset Terra to only be the light one. But like I think a lot of people would more people should use Terra. One, because Sol keeps running out of capacity.Vibhu [00:20:22]: I'm the reason. Here's ten minutes of ourSwyx [00:20:24]: There you goVibhu [00:20:25]: Retirement calculator.Swyx [00:20:26]: Oh, that's the Excel thing working for you.Vibhu [00:20:28]: This is,Swyx [00:20:28]: Oh my God. Look at thatVibhu [00:20:28]: This is work, and then Codex is still cooking, so we'll get back into it. I think it'll be interesting to see the thought process, the reasoning, and also, this is eight minutes on work. Codex is still cooking.Swyx [00:20:41]: Yeah. And by the way, so I've, do Gabriel Chua? He's part of the OpenAI Singapore team. He showed me this, and I was like pretty shocked that this looks like Excel. It edits Excel files. You never paid an Excel license, right? Like, but somehow this is like workable and it's agentic Excel.Akshay Nathan [00:21:01]: Yeah. one of the big like pushes that we made for this launch was like artifacts, right?Akshay Nathan [00:21:05]: Like both on the model side, like I think if you compare this with GPT-5.5 and GPT-5.4 before that, you'll see that there's been pretty dramatic improvements in the quality of these artifacts and then also on the product side.Vibhu [00:21:16]: The UX side is also crazy, like hosted sites and whatnot. No longer needing to host your own little webpage, like itSwyx [00:21:23]: Oh, I have a story about that. I can do, a separate thing. I'll need to take the visuals here, but we-we'll, we'll cut to that later. Was there co-training, because you were moving making this big move and you launched GPT-5.6 on the same day as ChatGPT Work? Was there influence between the model training teams and the harness teams, or did they did the launch dates just happen to line up the same day?Akshay Nathan [00:21:46]: I think the we collaborate heavily with the research teams, and I think that's like one of the most magical parts of the job, like the most fun parts of the job. But yeah, just using artifacts as an example. Like, a lot of what you're seeing, like underneath the hood, there's a lot of work that went into making sure that like, we had the right infra to be able to train the models to get better at this. And then on the product side, like had the right experience for users to be able to collaborate with the model on an artifact like this. In fact, like this whole viewer, like the intuition here is that like, it's not necessarily that you wouldn't need an Excel license. This is stage one, right? Like, this is probably not what you meant when you're like making a retirement calculator.Vibhu [00:22:24]: Yeah, you can iterate very easily. Yeah.Akshay Nathan [00:22:24]: You wanna iterate and like when you're seeing it, and if this thing is high fidelity to like what you would see in or what your coworkers would see if you were to send this to Sean, like that I think makes it so easier and makes you trust the product in terms of iteration.Vibhu [00:22:39]: When you say coworkers would see, do you see a multiplayer, multi-team collaboration with artifacts? Any things you guys think about that?Multiplayer Artifacts and CollaborationSwyx [00:22:46]: You can already share it, right?Akshay Nathan [00:22:48]: Yeah. It's inter It's something that, we're actively thinking about. one thing that, we've noticed internally without talking too much about the roadmap is that like there's many times when someone will ping me about something, and I will ask ChatGPT Work the question, and then I'll ping them back the answer.Akshay Nathan [00:23:04]: And then I'll be thinking likeVibhu [00:23:04]: Like the simplest would be, the three of us are just all on one hosted.Akshay Nathan [00:23:07]: Exactly. And I'll think about like was I required in this loop or and then maybe it was, rephrase like what they were asking or pulled from certain context or whatever. But like, when I gave them back the answer, that process was also lossy, right? Like I gave them just like my interpretation of what ChatGPT Work cooked up. But like underneath the hood, there's so much context like in the rollout and stuff that could be interesting.Vibhu [00:23:28]: Yeah, it'sSwyx [00:23:28]: So like the answer was preemptively respond to every inbound request?Akshay Nathan [00:23:33]: No, it was just like literally like this is what I do sometimes as my job.Swyx [00:23:36]: I know you copy-paste and then you're just a message forwarding serviceAkshay Nathan [00:23:39]: Yeah. Yeah, exactlySwyx [00:23:39]: From AI to AI.Vibhu [00:23:40]: But I think it's interesting, right? It helps people understand the capability of what you can ask and delegate that oftentimes people don't realize until they try or someone shows you, and then you're like, “Oh, okay. Okay, I see.”Swyx [00:23:52]: I think it's als there's also like a, light security issue, where like you're the permissions layer. Like yes, I could query everything that you query, and I could get an automated response, but maybe I'm not supposed to see it. And that there's no way I would know because I'm not supposed to know what I don't know.Akshay Nathan [00:24:07]: Especially as like, with ChatGPT Work, we're, we're asking you to connect your plug-ins and, it's pulling from your local files and stuff like that. Like the amount of context that the agent has access to is like- Deeply personal and like that's something I think we need to preserve, so that'll be definitely a challenge.Swyx [00:24:22]: There's Excel, there's PowerPoint, there's Docs, the, grand trio of work. What other formats of work do you think about? like you worked on Airtable. Is there a future where there's like OpenAI Airtable? Like what does that look like if you ever ended up doing it?Akshay Nathan [00:24:41]: It's a really good question. I think,Formats of Work: Sites as Knowledge ArtifactsAkshay Nathan [00:24:43]: one that you didn't bring up was Sites, and I think that wasSwyx [00:24:46]: SitesAkshay Nathan [00:24:46]: A core part of this launch. There's one side of Sites that I think people commonly talk about, especially on Twitter and stuff or X, of like, this like prototyping tool. And like we saw that happen with this launch even. The model slider that you guys were referencing earlier, like that was developed almost fully in a Site. Like, the collaboration between design and engineering and product on that was like on a site where we play with, the affordance and figure out how it feels and all of that. But the other aspect that I think is a little bit less talked about is like Sites as like an artifact for knowledge work. I was talking to someone the other day who's on like our corporate finance team, and like we were mentioning how like now when they have these reports that they're, they're working on as a team month to month, historically those things were in slide decks and in spreadsheets, and now they're just in Sites. And like Sites is the mechanism that they collaborate across the team. And the reason is ‘cause it's like, it's like somewhat higher bandwidth. Like, at these tools like PowerPoint and Excel are like infinitely flexible, but at some point you reach the boundary of like either as a human you may not know how to use some feature or something, or the product itself doesn't support it. But with a site you can do anything. You ask for anything and you can get that. once people see that magic, I think it's been really valuable.Swyx [00:26:02]: Yeah, let me show you my case study. this involves all the hot topics including ChatGPT Work, but also GPT-5.6 token billionaires and token maxing and Sites and auto research. I'm a fan of this game called Strata. It's, it's like a little board game that youSites, Auto Research, and Research DashboardsSwyx [00:26:17]: That you play with, physical blocks, that come on top of it like that. So over the weekend I took like thirty photos and just threw into ChatGPT. one point seven billion tokens later, out comes this site with a fully playable thingAkshay Nathan [00:26:32]: WowSwyx [00:26:32]: With 3D, block placement and everything. Because it requires physical blocks and I needed friends to train on it so they can get better, so I can play against them. But also, I could also, do things like train an AI on it and that's, thatAkshay Nathan [00:26:45]: That's your auto researchSwyx [00:26:46]: That gets into auto research. So, you want to train your own AIs, and then make sure they self-play against, each other. I need to set both AIs. So this is AI versus AI, and they're, they're gonna self-play. the AIs start out bad and then you want to define a loss function and get good. I wasn't gonna supervise all this. I was at, I was down in San Mateo, attending a conference. What I ended up doing was, auto researching and on this and creating benchmarks and that there was just way too many parameters for me to read. So I started asking it for a site, and it's created this lab, panel. Where is there a, is there a shortcut for a site that is created?Akshay Nathan [00:27:28]: You should be able to go in the sidebar to Sites, top of the sidebar. The left sidebar.Swyx [00:27:33]: This one? Oh, left?Akshay Nathan [00:27:35]: Yeah. Just scroll all the way to the top.Swyx [00:27:36]: Oh. Oh, it says Sites. Oh, there you go. Yeah.Akshay Nathan [00:27:39]: Ooh.Swyx [00:27:40]: So it create, it creates the sites. I don't, I don't think this is, it is exactly what I wanted, but let me show you what it popped up, right? Like I think as a research artifact, it is very important to communicate, exactly, what is being done. Outputs this thing which I eventually started publishing. So I moved it off of Sites because I wanted more, database and infrastructure than Sites afforded me. But this is like a research output that you can start to mess with and like try to think about like what hyperparameters are you tuning for training AIs. And like I was trying to make like scaling laws and everything and doing all sorts of like game optimization stuff. And the fact that you can just throw this up as a research artifact, like I no longer need to read ChatGPT output. I read Site output. But then there's also a huge sprawl. Like look at how long this thing is. There's so many numbers. It is pretty overwhelming, so then I have to start pruning it from there. But, it's an interesting transition from Markdown effectively that you're putting out to, you're putting out a whole functional site.Akshay Nathan [00:28:41]: I think Markdown just isn't that optimal for people to read, right? Might as well just write HTML website and I don't know. I think you can do a lot with customizing this, right? You have your skills that explain what you want. Like I noticed they're quite verbose. I don't need a lot of this information.Swyx [00:28:57]: It's very verbose.Akshay Nathan [00:28:58]: So and then the nice thing of having a site side by side is, you just iterate on what you want and what you don't, right?Swyx [00:29:05]: Yeah. I don't know if, any that triggers any stories for you of how it's run internally. Am I doing this right?Akshay Nathan [00:29:11]: Yeah. I think that this is like a workflow that we're seeing like all different types of teams use, where like the canonical artifact that was previously a deck or something is now becoming a site. And like with a site you, because it's just HTML, you can like. It's infinitely flexible. And so, if you want to give more prominence to a certain thing that like in a slide deck would, feel like it was buried, like you can do that. You can have it be like the hero image, right? And so I think that like, people are starting to see that. There's more work to be done to make these things like much more easier, easy to collaborate on. You mentioned that they're very, they're long and verbose, could be broken up. I'm sure that there's still something to do there.Swyx [00:29:53]: They're super long. Yeah.Akshay Nathan [00:29:54]: Yeah. But I think we're starting to see that like there is this aspect of this is a really interesting, format, for people to use, that's like much more flexible than what they ever had before.Swyx [00:30:07]: I think your job also comes becomes meta. You're not designing the products. You're designing a product to make products, and I'm curious how you manage that.Designing a Product That Makes ProductsAkshay Nathan [00:30:18]: I think one thing that we've been Like when we look at the UX, like that we've been thinking a lot about is how can we balance like simplicity with capability? Like if we're designing a product, like you said, that like is made to make up build other things, right? You can build so many different things. But we can't put that all in front of you because you'll get overwhelmed.Vibhu [00:30:41]: Yes.Akshay Nathan [00:30:41]: And so we had similar problem or similar challenges even Chat-with ChatGPT, but especially now, like when there's so much that can be done, I think the balance that we're constantly trying to strike is like, how can we give the user enough of a UI surface where, they can be expressive, they can tell the agent what they need, they can verify that it's using the right tools, it's pulling from the right sources, et cetera, but then it gets out of the way. And then how can we build the right system such that we can show them instead of telling them what can be done? Because so much of this is gonna be like, how do they discover the next use case and the next one after that if they really want to be super powered by the AI.Games, Private Evals, and Show-Don'TellVibhu [00:31:19]: Yeah. It's interesting. I feel like everyone also just has a different way to do it, right? I made a similar version of this same game. I didn't take any pictures of board or rule game. I threw in at goal eighteen minutes, fifty-three seconds later, a lot of tokens later, I've got a similar version. not with all the auto research and whatnot, butAkshay Nathan [00:31:39]: You gotta do all the latest trends.Vibhu [00:31:40]: And yeah, I did it with, did it with Codex, not Work, but it's interesting, right?Akshay Nathan [00:31:45]: Yeah. And this is GPT Image generating the pro avatars. Very good for game design. LikeVibhu [00:31:51]: AndAkshay Nathan [00:31:52]: A lot of game designers were like really into GPT Image for assets.Vibhu [00:31:54]: I will say like the broader takeaway probably is the reason that we do this is more so just to test the tools, right? Like, this was also a test for GPT-5.6 came out. I had done the game on GPT-5.5, right? The ability for me to no longer need it to. I had to feed it the rules. It's, it's a pretty niche game. It couldn't find how to do this on its own.Akshay Nathan [00:32:15]: Oh, yeah.Vibhu [00:32:15]: GPT-5.6Akshay Nathan [00:32:16]: It is out-of-distribution, which is why I was also very keen on testing the GPT-5.6 capability.Vibhu [00:32:21]: But, this is just as work comes out, as new things come out, these are just our side ways to test things, right?Akshay Nathan [00:32:27]: Yeah. It's some private eval. That is not this private.Vibhu [00:32:31]: But also valuable because now you can send this to your friends and I learned about this game through seeing this.Akshay Nathan [00:32:36]: It's a hard game. He's very good.Vibhu [00:32:39]: It's good to when no one is competing with you. But yes, it's a classic RL problem of like self-play, bootstrapping your game AI. yeah, you see how easily work becomes personal and personal becomes work because the thing I do for personal, it directly informs people I work with because I showed it to them. They were like, “Oh, you can do that with GPT?” Which like I imagine is the growth strategy.Akshay Nathan [00:33:02]: Yeah. The show not tell is a big piece that, I think we've we're not still not fully cracked of like, showing people all the things that they can do with the product versus like trying to teach that to them through like, articles or onboarding or whatever.Akshay Nathan [00:33:18]: So meeting them in the moment.Vibhu [00:33:19]: It's a career risk for me, because I used to be in developer relations, right? Where your job is to show, and then you're like, “What do you mean? You don't, you don't need.” your job is to tell. And then. But the product people are like, “Well, we don't need you if our product is intuitive enough.” SoAkshay Nathan [00:33:37]: Yeah. that's the magic of the models. So you can tailor the telling or the showing to like specifically what the user needs, like what they care about, what they've done in the past, exactly where they are on the adoption journey. So I think that's like gonna be a super big opportunity.Vibhu [00:33:50]: Seems easier and easier now to tailor custom showing, right? People have different use cases. As much as you said you don't wanna segment different people into different buckets, right? It's also not that hard to for people that are in different categories. But the question, is you said your team is more broadly on. What was the term you used? Productivity?From Developers to Knowledge Work to EveryoneAkshay Nathan [00:34:12]: Productivity.Vibhu [00:34:12]: Productivity. So howAkshay Nathan [00:34:12]: Which is now work.Vibhu [00:34:14]: Is it work? Is there another distribution that we're not hitting? Is there a group of people that will have something different than ChatGPT, Codex or Work? Is there more that the mass isn't targeting?Akshay Nathan [00:34:28]: I see it as like a sequencing, like. The vision is like bring useful agents to everyone. We started with like developers. Like developers historically are like early adopters that are willing to put up with more friction, set things up, et cetera. Like that's where, Codex started. I think the next opportunity is like what we call general knowledge work, all the other functions around developers. I think when you go from developers to this segment, like there's inherent challenges with like, this show not tell thing that we're talking about, making the product more understandable, bringing in new capabilities that matter more for this cohort than matter for developers, things like artifacts, things like computer use, et cetera. And then I think like the same learnings, like similarly how we took the learnings from developers and brought it to, general knowledge work, the next stage will be like taking the learnings from general knowledge work and bringing it to everyone no matter what they're doing in their lives. And we're already seeing that a little bit. Like this game example that you have is, something that's like on the border of like fun and personal life to, your professional life. I use ChatGPT Work full-time at home for everything, like for whatever I'm doing. I used it the other day to come up with a meal plan and like, save that on the like computer environment that it has and something that I can continue going back to. Like is everyone doing that yet? Probably not because the thing says work on it, but eventually, we wanna get people there.Vibhu [00:35:51]: ChatGPT life.Akshay Nathan [00:35:52]: Yeah, exactly. ChatGPT cooking. But I think there's a lot of, there's a lot of opportunity there, but I see it as like, we're, we're built we built a foundation in software engineering, and we're gonna take the same learnings that we take from software engineering to knowledge work to everyone.Vibhu [00:36:07]: Do you have any power user advice? I feel like, there's a group of people that will live it, use it for everything, stay on it twenty four-seven. And then there's a bit of a gap between that crew and people that, okay, I use it for work. I use it occasionally. Sometimes I type questions. any advice, any learnings, anything you recommend or just, takeaways that you've found that help bridge that gap?Power User Advice: Push the Frontier of ImaginationAkshay Nathan [00:36:30]: I think a couple things that I've seen is like, one, that it really helps to broaden your imagination of what's possible, and this has been a learning even for me. Like, the technology has progressed so fast that, something that, like, even three months ago, like, no way the models can do this. Like, now it's like, wow, it's like it can. Like,Swyx [00:36:52]: Give an exampleAkshay Nathan [00:36:52]: We're going through right now our, like, review cycle internally, and, people always talked about this as, like, a thing that the models are good at and like, there's a cliché of like: Okay, like, no one wants to be writing reviews and, like, we just use AI to do it. But in all seriousnessSwyx [00:37:09]: And it can evaluate it as well.Akshay Nathan [00:37:10]: Yeah, exactly. In all seriousness, before it was, like, just, like, slop and, like, I think it was helpful, but, not super productive. Now I've found that, like, the model can do a much better job than me, especially in this environment of, like, pulling context on, like, what people are up to, how they've like the things that they've done to make a difference, highlighting like, wins that they've had that, like, I might may not even have seen. It has access to, like, everything, right? Like the code, like, things that they've caught, reviews, Slack, everything. And so it's, like, incredibly powerful in that domain and, like, just like six months ago, the last time we did this cycle, like, I didn't even I tried using it, but it was not at all helpful. And this time it's been, like, incredibly helpful and, like, so I think continuing to push the frontier of imagination of what's possible, even if you tried something before, I think is maybe the my biggest piece of advice. The other, thing is, like, the more you put in, especially in this environment where, like, the model has access to everything on your computer or in ChatGPT Work, like you can create, artifacts over time and save them in your library and, like, the model will continue having access to those. Like, the more information you give it about whatever domain you're in, whether it's your life or your work, the more valuable it becomes, and it'll become valuable in, like, ways that might surprise you. Like, it might pull from context in a way that, may be proactive and that you might not even have thought about. But it needs to have access to those, to that those tools or that context first.Reviews, Agentic Search, and Context GatheringSwyx [00:38:27]: One thing I just wanna talk about the review stuff because I'm still that's a very sensitive thing and you're, you're a founder, you've managed people, you've hired people. As manager myself, I'm very reticent to put out any LLM-generated things especially when it comes to people, ‘cause it feels like you don't care.Swyx [00:38:46]: Presumably at OpenAI, people are more open to being eval rated by GPT. But are there any unofficial rules around this? Like, what's the etiquette?Akshay Nathan [00:38:57]: Oh, I think the etiquette is that, like, I would never write something via, like, well, solely via AI and, like, present it as, like, a review for someone. What I was talking about is more, like, gathering context. That's the place where it's incredibly helpful.Swyx [00:39:08]: So it's just search.Akshay Nathan [00:39:09]: Yeah, exactly.Swyx [00:39:09]: It's agentic search. Yeah.Akshay Nathan [00:39:10]: It's like agentic search, but, that you can tailor and steer much more capably than you could before, ‘cause, like, the thing is it's all there's a flywheel happening, right? Because of Codex, people are able to do, and because of ChatGPT, people are able to do so much more now than ever before. And if you're able to do so much more, it's easy to miss things as well. And so, like, I think we need to use these same tools to keep up with all the impact that people are having and understand, where we can be helpful.Swyx [00:39:39]: I think the thing, like, I run a small company, so easy to search, but at the scale of OpenAI with the amount of messages that you guys put in Slack, do you think that it misses things?Remembering What Humans MissAkshay Nathan [00:39:50]: Probably, but I think that I also miss things.Swyx [00:39:52]: Like, it doesn't matter, right?Vibhu [00:39:53]: I think sometimes it'sSwyx [00:39:53]: Like it's, as it needs to be human-levelAkshay Nathan [00:39:54]: It's all relative, right? Yeah.Vibhu [00:39:56]: Sometimes it's nice when it finds things you wouldn't, right? Like right now, my Codex system prompts, they're set up in such a way that every project I have has a secret- separate, notes MD, and it just writes learnings to there. And then the global one can pull from all these. So sometimes it'll be like: Oh, there's this project you did like four months ago. Here's a note that we had, and it randomly pulls it back into context that I would never do, I haven't thought about.Vibhu [00:40:20]: And I'm like, okay, this is quite superhuman, right? Like, stuff that would. And, it'll save like hours on chunking of stuff or find something that's already been done. I'm like, as much as it might miss stuff, I would too, but it's very useful when it finds stuff. And I have like a very, non-super engineered solution to this. It's just marked down files that get pulled whenever they want.Akshay Nathan [00:40:41]: Yeah. I have a funny anecdote about this. Like, recently gearing up to this launch, the team has been, really cooking on it for a couple months, and over that time, like there's so much conversation and chatter going on in Slack and Docs and elsewhere. And, one of the members of the team set up this, scheduled tasks, like automation to like look at everything that's going on and, like, come up with the best memes and then post it in one of our shared channels. And like, there are two cool things about this. Like, the first is, like, I think the models are, over time, like starting to become like funny.Swyx [00:41:13]: Funny. Nice.Akshay Nathan [00:41:13]: Whereas like, a year ago, like that was not at all the case. The second is, it was what you were saying, like they find things that in surprising ways that you may not have thought of and like create connections that you may not have thought of. And that really helps with like the meme generation because then you can see something that, genuinely surprises you and, is funny in that way. So yeah, that's like not like the most productive, use of this the technology, but it does it does uncover this, like this capability that's emerging, which is just like to find information that you otherwise would not know of.Launch Momentum and the 10 Million User MilestoneSwyx [00:41:43]: Talking about the launch, I think, I have pretty much said this is the most successful launch in a long time. I think even more successful personally than 5.0, and they're announcing ten million users. Does it feel different? You've been through a lot of launches.Akshay Nathan [00:41:58]: I think it feels like a culmination. Well, I think two things. One, it feels like a culmination, like I was mentioning earlier, like this like vision mission that we've been on for a long time. Like I said, we saw the magic of Codex internally, and then we're like extremely excited to bring this to many more people and to see it working, to like see us reach, the distribution goal, numbers that you mentioned, like I think that's like huge and super exciting. The flip side of that is like, there's so much more to do too. Like, that's also really exciting. Like, ChatGPT as a whole, like the this product that, everyone almost equates to AI and like loves, has hundreds of millions of users. And so like ten million is really cool, but like we need to get this to everyone. Like, we need everyone to feel this magic. And so that's the next step from here. But yeah, I think extremely pumped about how it's going so far and the opportunities.Swyx [00:42:46]: Awesome. I did want to also Because I've, I've, I've been tracking the number closely, it transitioned at some point from just Codex users to Codex plus ChatGPT Work, because they're same harness. The whole point is that you don't, you can't, count them separately. Do you have roughly a billion, ChatGPT users? Why did it just jump to one billion right away? Like, isn't that the default on ChatGPT or no?Codex, ChatGPT Work, and the Developer BrandAkshay Nathan [00:43:11]: We don't default you into ChatGPT Work if you're on ChatGPTSwyx [00:43:14]: If you're free. YeahAkshay Nathan [00:43:15]: It's also only available to paid users right now. And I think there's like a process of, educating users of what is the value of this product, having them try it, learning from their feedback, and making it better over time. But the goal is to, get as many of the people who love ChatGPT today to like feel the power of ChatGPT Work. But I think it'll be a journey.Swyx [00:43:36]: Yeah. And Codex will still be alive as a brand for the foreseeable future. And we'll just toggle between them as needed for UI stuff.Akshay Nathan [00:43:44]: Yeah, I think it's even stronger point than that. Like, I think we fully intend to like, treat developer. Like, developers have been, a core market for us for so long, and like there's, there's so much more that we can do to make Codex great specifically for, software development, and we'll continue to do that. This doesn't take away from that at all. If anything, it should increase the utility of something like Codex, because now you can move seamlessly between writing a diff to creating an artifact or, doing a search over your factor.Swyx [00:44:11]: I do wonder how much this terminology leaks to the non-technical user. Like, do they have to learn to say artifact if I want artifact? Or.Akshay Nathan [00:44:20]: It's funny, like we call it artifacts internally ‘cause that's what the teams call it.Swyx [00:44:23]: It's nice. Yeah.Akshay Nathan [00:44:23]: But like externally, like no one says that, no one calls it an artifact. But I think that people like often, like describe things, whatever they're used to, right? So if, ChatGPT Work is good at creating slides, they'll say ChatGPT Work is good at creating slides, and that's what we want.OpenClaw, Personal OS, and Persistent ComputersSwyx [00:44:38]: One big Another, it's July of twenty-six. One big thing that also happens in, for OpenAI was OpenClaw, and that's I think a lot of people's first time really maxing a agent for personal stuff, but also crossing over to work in essence same way. As far as I understand, OpenClaw is still independent, but did you go through your own OpenClaw moments? Were there any lessons you took from OpenClaw to Codex or back? Whatever.Akshay Nathan [00:45:06]: I think there's a lot of inspiration. I did go through my own OpenClaw moment. I,Swyx [00:45:10]: Yeah, tell the storyAkshay Nathan [00:45:10]: Me and my wife like set up an OpenClaw to like try to manage everything in our house. Not that there's like a ton, but it was like quite useful. We gave it a calendar. It started, creating events for us and stuff. At some point, the laptop that we were running on, it died and never got a chance to pick it back up. But there was a lot of inspiration there, like, in ChatGPT Work, in web and mobile, like you get access to this like persistent computer environment where, you can store files, and those files stay around between sessions. And the idea is to be able to enable use cases like this. one of the members of our team uses ChatGPT Work for what they used OpenClaw from before, and then feel like it has like completely transitioned, which is like, workout planning and like meal tracking. which again, it's like a work-related thing, right? It's like not work necessarily, but it's like in personal productivity space. But it has all the same primitives. So it has scheduled tasks. It has the ability to store files on a file system. It has the ability to like reference those things over time. And so you start to see the same types of use cases emerge, which has been really cool.Swyx [00:46:14]: Is there a point that ChatGPT Work completely replaces OpenClaw? they're independent, so.Akshay Nathan [00:46:20]: Yeah, I'm, I'm not close to it, so I can't speak to the OpenClaw roadmap, but I don't think so. I think that there's gonna be, there's always a need for like this like incredible, like open source technology that team has built. And I think that we can draw inspiration, in the product and, ChatGPT, I think many more people have like heard about and used ChatGPT than have used OpenClaw. And if we can take the magic from OpenClaw and bring it to them, I think that'll be a success. I think that like one thing on the ChatGPT Work side that we feel strongly about is that like the core experience is that you come to this product and you have a conversation, start a session, whatever you wanna call it, with this agent. And the magic of the product is that you can do anything in that moment. And we would like to create a product where you don't have to click a button or to go to a different place, whatever, and you can get whatever functionality exists in, your finances app or where or any other product like in this one place. And so that's the goal. It's like it we want an extensible system with plugins where you can connect to the tools that you need in order to be able to accomplish like a financial task, where you can, if you're doing like science work, like we have an ability to like extend the system in such that you can like write the tech and it performs well. There'll always be like products that we support that are best in class at those things, but we want as much of the magic as possible in that core experience.Swyx [00:47:45]: Yeah. Do you think that you can do everything you used to do with Wealthfront in ChatGPT Finance?Finance, Data Access, and Centralized ContextAkshay Nathan [00:47:50]: I tried it. like ChatGPT doesn't yet custody, cash and assets for me. So that part, no, not yet. But I, there was like a whole component of like retirement planning and, like financial planning and budgeting and stuff that, we were looking into when I was there. And like with the finances plugin, like that's all possible with ChatGPT today. So, I feel

durée : 00:58:46 - Le Cours de l'histoire - par : Xavier Mauduit - Mer Adriatique, lagune et canaux, l'eau est omniprésente à Venise. Entre consommation et eaux usées, la ville régule sa pêche et ses déchets. Pourquoi la santé de Venise dépend-elle de sa lagune ? - équipe : Maïwenn Guiziou, Jeanne Delecroix, Thomas Beau, Cassandre Puel, Jeanne Coppey, Raphaël Laloum, Chloé Rouillon, Sidonie Lebot, Luce Mourand, Angelico Gaymard - invités : Claire Judde de Larivière Historienne, spécialiste de Venise au 16e siècle., Solène Rivoal Historienne, spécialiste de Venise au 18e siècle Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

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Har du varit sugen på att göra mer med dina "smarta" prylar i hemmet? Har du undrat vad man egentligen har Home assistant till och hur man bäst sätter upp saker? Detta kan vara avsnittet för dig! Fredrik och Tobias sitter på uteplatsen och diskuterar Tobias äventyr med Home assistant. Ett visst mått av YAML har genererats. Tobias huvudmål var bättre automatisering och hantering av alla sina smarta lampor, och att äntligen få en bättre lösning för styrning av luftvärmepumpen när den ska kyla övervåningen under varma sommardagar. På vägen dit får vi en genomgång av praktisk hårdvara, lite lärdomar om standarder som Zigbee och Matter, och inte minst intressanta problem och finesser hos IKEAS smarta lampor. Det blir trettioåtta automationer, elva skript, fem scener, och en fin lösning på ett musikuppspelningsproblem. Ett stort tack till Cloudnet som sponsrar vår VPS! Har du kommentarer, frågor eller tips? Vi är @kodsnack, @thieta, @krig, och @bjoreman på Mastodon, har en sida på Facebook och epostas på info@kodsnack.se om du vill skriva längre. Vi läser allt som skickas. Gillar du Kodsnack får du hemskt gärna recensera oss i iTunes! Du kan också stödja podden genom att ge oss en kaffe (eller två!) på Ko-fi, eller handla något i vår butik. Länkar Home assistant YAML - "human-readable data serialization language". Nåja Trådfri Kajplats Zigbee Home assistant green Z-wave Matter ZBT-2-antennen Philips hue Thread Border router i Thread Yamahas Musiccast-högtalare Renault 5 Stöd podden via Ko-fi! Home assistant community store - HACS Aqara - tillverkar en massa sensorer och grejer CEC Android TV Android remote ADB - Android debug bridge Aqaras närvarosensor - en av flera olika Titlar Ett sommarkodsnack Samma vibbar som sommarmelodin Ett löst avsnitt Sol, bad, och YAML Precis där fjärrkontrollen finns Sjutton olika appar I sina egna små silos En färdig låda Den som kontrollerar enheten Här är problem nummer två Det som hände i mitt hem Tänd och släck sex gånger Då öppnar den sin dejtingprofil Ett hemligt Zigbeeläge Allting som inte är IKEA Jag skriver YAML på jobbet 60% i hallen I plain svenska En knapp som jag trycker på när jag går och lägger mig Ett medelvärde mellan deras rum och mitt kontor Det bästa sättet att styra TV:n på Trettioåtta automationer Om du ska prata Zigbee

Dan Ives is the Partner and Senior Managing Director at Yorkville Ives, a new merchant bank he's building. In this conversation, we break down the AI trade—Chinese open-source models, Anthropic's slowing revenue growth, the biggest bottlenecks in chips, memory, and energy, and the political battles over data centers.======================Arch Public is an agentic trading platform that automates investment strategies across Stocks, Commodities, ETFs and Crypto. Whether you're rotating into AI & Gold, allocating to the S&P 500, or accumulating Bitcoin, Arch Public executes your plan 24/7 without ever taking custody of your assets or funds. Sign up today at https://www.archpublic.com, and start your FREE automated trading strategy! ======================Need liquidity without selling your crypto? Take out a Figure Crypto-Backed Loan, allowing you to borrow against your BTC, ETH, or SOL with 12-month terms, 8.91% interest rates, and no prepayment penalties. Or check out Democratized Prime (https://figuremarkets.co/pomp) and earn ~9% APY on real world assets, paid hourly. Unlock your crypto's potential today at Figure! https://figuremarkets.co/pomp Figure Lending LLC dba Figure (NMLS 1717824). Loans subject to approval. Crypto collateral may be liquidated. Terms apply - see full disclosures at figure.com/disclosures/======================This episode is brought to you by TikTok for Business. If you run a company, your next wave of customers may already be on TikTok. With more than 200 million monthly active users in the U.S. and 51% unique reach, TikTok gives brands access to audiences they can't reach anywhere else. Learn how to turn that reach into growth at TikTok for Business ( https://anthonypompliano.splashthat.com/ )======================0:00 - Intro0:51 - Chinese vs American open-source models, & the Anthropic IP lawsuit4:36 - Falling model costs and the pricing war5:55 - Cultural bias baked into Chinese AI models?7:44 - Will AI models eat the whole stack? 11:20 - Specialized AI workflows & model routing14:00 - Mag 7 free cash flow vs. exploding semiconductor revenue17:37 - The real AI bottlenecks: memory chips, data centers & energy30:13 - Anthropic's revenue growth is slowing — should investors worry?31:17 - Why Dan is leaving Wall Street to build Yorkville Ives34:32 - Dan's AI market predictions & closing thoughts

¿Cómo contemplar un eclipse sin dañarnos los ojos? Nos lo explican Pablo de Vicente, director del Observatorio de Yebes e Inés Contreras Marín, jefa de la sección de Oftalmología del Hospital Universitario Ramón y Cajal de Madrid.Con ellos aprendemos todos los trucos para poder disfrutar de forma segura del eclipse total de Sol del próximo 12 de agosto de 2026.Además, también descubrimos algunas curiosidades sobre cómo afecta un eclipse a los animales. Escuchar audio

Bracha Jaffe has inspired countless Jewish women and girls through her music, but behind the stage is a wife, mother, and person navigating the same challenges many of us face. In this honest conversation, Bracha opens up about balancing family and career, the misconceptions people have about her, and the personal growth that comes from being vulnerable, self-aware, and true to yourself.You can get tickets to her concert & hear her music here→ https://www.brachajaffe.com/✬ SPONSORS OF THE EPISODE ✬► Colel Chabad: Help Families in IsraelMake daily tzedakah part of your routine with the Colel Chabad Pushka App.Yaakov here. It's one of my favorite organizations. Really.DOWNLOAD THE APP & HELP HERE → https://pushkapp.cc/inspo► Qualify Whey Protein - The Best Protein We've Had!Finally, a delicious Cholov Yisroel protein powder that fits real life.Perfect for smoothies, iced coffee, yogurt, recipes, or a quick shake on the go.Available on Amazon.Use code DELICIOUS10 for 10% OFFGET HER→ https://bit.ly/3SWhaCT► Shefa Living: Mountain View for YouDiscover Mountain View, a growing frum community in the Blue Ridge Mountains of North Carolina, featuring Nesheema, a dedicated space for women with a mikvah, spa, gym, café, daycare, workspace, and more. LEARN MORE → https://go.jcn.io/slll► Bitbean: Custom Software & AIModernize your business with custom software and practical AI solutions that help your team work smarter. FREE CONSULTATION → https://bitbean.com ► Wheels To Lease: #1 Car Company Reach out to Sol from Wheels To Lease for honest pricing and a stress-free leasing experience. → CALL/TEXT: 718-871-8715 → EMAIL: inspire@wheelstolease.com → WEB: https://bit.ly/41lnzYU → WHATSAPP: https://wa.link/0w46ce ✬ IN MEMORY OF ✬ This episode is in memory of: • Shimon Dovid ben Yaakov Shloima • Miriam Sarah bas Yaakov Moshe • Shaindel bas Chaim Yehuda Leib #iftn Lchaim.

Donald Macleod explores the life and music of George Frideric Handel through the patrons, employers and institutions that helped shape his career. From the aristocratic circles of Italy and the court of Hanover to royal favour in Britain and the charitable culture of Dublin, Handel proved adept at navigating the worlds on which composers depended. Yet he remained unusually independent, moving between courts, theatres and concert halls while steadily building a career on his own terms. Along the way, patronage could offer opportunity, security and prestige, but it also brought rivalries, competing loyalties and political complications. Through sacred music, opera, anthem and oratorio, this podcast traces how Handel responded to the people and places that supported his work.Music featured includes extracts from:Dixit Dominus, HWV 232 Tu fedel? Tu costante?, HWV 171a: Recitative and aria Rodrigo, HWV 5: Overture; recitative and aria Il trionfo del Tempo e del Disinganno, HWV 46a: Overture Il trionfo del Tempo e del Disinganno, HWV 46a: "Pure del cielo" La Resurrezione, HWV 47 Eternal Source of Light Divine, HWV 74 Nine German Arias, HWV 202–210: No. 6, "In den angenehmen Büschen" Rinaldo, HWV 7a: Overture Silla, HWV 10: Overture Il pastor fido, HWV 8a: "Sol nel mezzo risona del core" Water Music Suite No. 2 in D major, HWV 349 Acis and Galatea, HWV 49a: "Love sounds th'alarm" As Pants the Hart, HWV 251b Acis and Galatea, HWV 49a: Sinfonia Esther, HWV 50a Coronation Anthem: Zadok the Priest, HWV 258 Coronation Anthem: My Heart Is Inditing, HWV 261 Riccardo Primo, HWV 23: Act III Chorus Atalanta, HWV 35: Overture Alexander's Feast, HWV 75 Funeral Anthem for Queen Caroline, HWV 264 Messiah, HWV 56: Sinfonia L'Allegro, il Penseroso ed il Moderato, HWV 55: "Sweet Bird" Imeneo, HWV 41 Messiah, HWV 56: Part III Foundling Hospital Anthem, HWV 268Presented by Donald Macleod Produced by Ellie Ajao for BBC Audio WalesFor full track listings, including artist and recording details, and to listen to the pieces featured in full (for 30 days after broadcast) head to the series page for George Frideric Handel (1685-1759): https://www.bbc.co.uk/programmes/m002yxkn.And you can delve into the A-Z of all the composers we've featured on Composer of the Week here: http://www.bbc.co.uk/programmes/articles/3cjHdZlXwL7W41XGB77X3S0/composers-a-to-z.

Peter Schiff is the host of The Peter Schiff Show podcast and a longtime economist and gold advocate. In this conversation, we break down real inflation versus the official CPI, the Fed's political motivations, and whether AI and tariffs are inflationary or deflationary. We also cover the Iran war's impact on oil, Social Security's looming collapse, and a five-year bet on bitcoin versus gold.===================Arch Public is an agentic trading platform that automates investment strategies across Stocks, Commodities, ETFs and Crypto. Whether you're rotating into AI & Gold, allocating to the S&P 500, or accumulating Bitcoin, Arch Public executes your plan 24/7 without ever taking custody of your assets or funds. Sign up today at https://www.archpublic.com, and start your FREE automated trading strategy! ===================Need liquidity without selling your crypto? Take out a Figure Crypto-Backed Loan, allowing you to borrow against your BTC, ETH, or SOL with 12-month terms, 8.91% interest rates, and no prepayment penalties. Or check out Democratized Prime (https://figuremarkets.co/pomp) and earn ~9% APY on real world assets, paid hourly. Unlock your crypto's potential today at Figure! https://figuremarkets.co/pomp Figure Lending LLC dba Figure (NMLS 1717824). Loans subject to approval. Crypto collateral may be liquidated. Terms apply - see full disclosures at figure.com/disclosures/===================Looking for a better place to trade? BloFin gives traders access to deep liquidity, advanced futures products for crypto AND TradFi assets, fast execution, and a clean, intuitive interface—all in one platform. To celebrate their partnership with us, they're giving away $100,000 in Deposit & Trade Rewards. Deposit, trade, and earn rewards based on your activity during the campaign. Check them out at ( https://partner.blofin.com/d/Pomp ).===================This episode is brought to you by mogul ( https://www.mogul.club/pomp ). Deloitte estimates that $4 trillion of real estate will move onto the blockchain over the next decade. Through tokenized residential real estate, mogul gives investors access to professionally managed properties with targeted yields, monthly rent payouts, and potential tax benefits — all without the headaches of being a landlord. Learn more and claim a special offer at https://www.mogul.club/pomp . See important disclosures at disclaimer.mogul.club.===================0:00 - Intro0:50 - How high is inflation really right now?14:36 - AI, robotics, tariffs & deportations: deflationary or not?25:24 - Will the Iran war make inflation worse?33:40 - Could inflation hit double digits? (Trump vs. Biden blame)40:29 - Social Security's looming collapse50:14 - Does Peter Schiff own bitcoin?52:43 - Bitcoin vs. gold: the real performance numbers1:00:45 - The bitcoin vs. gold bet1:05:40 - The "Crazy Uncle Portfolio"1:10:02 - What's actually in Peter Schiff's portfolio?1:18:54 - Outro

OpenAI staff were reportedly freaked out after its models breached Hugging Face, as aggressive training raced Anthropic. Google posted its first-ever negative free cash flow on AI spending, added selfie-video account recovery, and Light unveiled a minimalist flip phone. Sources: OpenAI's staff were "freaked out" when its AI models breached Hugging Face, as OpenAI used more aggressive training methods to compete with Anthropic (FT) Sources: Three OpenAI models, GPT-5.6 Sol and two unreleased ones, pulled off the Hugging Face hack in hours, work a skilled human would need weeks for; OpenAI has briefed the US government (Bloomberg) Google reports Q2 free cash flow at negative $5.9B amid increased AI infrastructure spending, marking its first cash burn since going public in August 2004 (FT) Google adds a selfie video sign-in option for account recovery, using tools like liveness detection to safeguard against deepfake attacks, rolling out globally (Wired) The Light Flip is a minimalist flip phone with a point to prove (The Verge) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

(Presented by Thinkst Canary: Most Companies find out way too late that they've been breached. Thinkst Canary changes this. Deploy Canaries and Canarytokens in minutes and then forget about them. Attackers tip their hand by touching 'em giving you the one alert, when it matters. With zero admin overhead and almost no false-positives, Canaries are deployed (and loved) on all 7 continents.) Three Buddy Problem - Episode 106: We dig into the news that OpenAI's models were the "autonomous agent" that breached Hugging Face, escaping a sandbox through a zero-day to cheat on a cyber benchmark, then getting spun into a partnership announcement. We argue about the implications of the incident, the PR masterclass, the absence of ethics and human oversight, and calls for "kill switches" to mitigate "AI lab leaks." Plus, SentinelLabs' new fast16 reverse-engineering benchmark, where GPT-5.6 Sol was the only public model to go the distance. Cast: Juan Andres Guerrero-Saade, Ryan Naraine and Costin Raiu. Timestamps: 0:00 Introductory banter 5:24 OpenAI admits it was the Hugging Face "hacker" 10:06 What's ExploitGym and who's on top of the leaderboard 12:59 Reward hacking: Did anyone train this thing not to cheat? 19:35 Marketing stunt or real incident? The zero-day in the package proxy 26:43 Was OpenAI already plugged into Hugging Face? 29:17 Paperclips, kill switches, and "going rogue" 34:49 Crisis comms, regulatory capture, and the second Cold War 43:02 Approve every action? Auto mode and swarms 50:10 "Lab leak" and calls for biosafety levels 1:00:31 The missing models: no Mythos, no Kimi, no independent referee 1:07:04 Costin's prediction: owning frontier-class hardware will require a license 1:13:41 fast16 as a benchmark: Inside the Sol Searching research 1:26:51 Compression and altitude: are reverse engineers being replaced? 1:41:24 Finding the gem in 100 samples, and the swarm frontier 2:00:41 Claude Opus 5 drops, Gemini 3.5 Flash Cyber

AI Chat with Maxime Lamothe-Brassard and Chris Luft — a special episode.One story, pulled apart start to finish. In mid-July 2026, Hugging Face disclosed a breach of its production infrastructure carried out end-to-end by an autonomous AI agent. Five days later, OpenAI revealed the attacker was its own models — GPT-5.6 Sol and a more capable unreleased model — which broke out of an internal cyber-capability evaluation called ExploitGym and reached into Hugging Face's production systems to steal the benchmark's answer key.In this episode:• The timeline: Hugging Face's July 16 disclosure, OpenAI's July 21 attribution — and the five days in between when even the victim didn't know an AI did it.• The attack chain: a malicious dataset abusing two code-execution paths in the dataset-processing pipeline, node-level escalation, credential harvesting and lateral movement — thousands of actions across short-lived sandboxes with self-migrating command-and-control.• The escape: a zero-day in the eval sandbox's package-registry cache proxy, the single egress control — per OpenAI's own account.• Motive: the models got "hyperfocused" on winning the benchmark, not stealing data — and whether "no malicious intent" is a fair description or a comforting one.• What was and wasn't exposed, what to do about your Hugging Face tokens, and why this is not the 2024 Spaces incident or the 2023 OpenAI forum hack.• Max's hot take: the beginning of the phase where we lock developers out of writing code — and a new fear unlocked: models backdooring other models.Stories covered:• https://huggingface.co/blog/security-...• https://openai.com/index/hugging-face...Chapters:0:00 Cold open — the attacker was the model2:20 The whole story in one breath6:41 The timeline: two disclosures, five days apart11:37 Attack chain, part 1: getting in through a malicious dataset15:53 Attack chain, part 2: escaping the eval sandbox22:10 Motive, attribution & intent: cheating on the benchmark25:31 What was (and wasn't) exposed28:08 The bigger picture: the fire drill started the fire31:39 Lessons for labs, platforms, and solo developers33:15 New fear unlocked: models backdooring modelsThe Cybersecurity Defenders Podcast — a podcast about cybersecurity and the people that keep the internet safe. New episodes drop weekly.Subscribe wherever you listen:• Spotify: https://open.spotify.com/show/6ep00ze...• Apple Podcasts: https://podcasts.apple.com/us/podcast...• YouTube: / @limacharlieio Learn more about LimaCharlie: https://limacharlie.io#cybersecurity #AIsecurity #OpenAI #HuggingFace #infosec

Por favor, inicia sesión en iVoox antes de escuchar o hacer comentarios. Los comentarios anónimos no son publicados. En esta entrega de Universo de Misterios, analizamos la configuración de nuestro Sistema Solar y la fascinante ley de Titus Bode, un patrón matemático que parece predecir la distancia de los planetas al Sol. Repasamos la evolución histórica de la astronomía, desde el modelo geocéntrico de Ptolomeo hasta la revolución copernicana, pasando por las leyes de Kepler y las aportaciones de Newton. Un recorrido por los cuerpos celestes, desde los planetas rocosos y gigantes helados hasta los objetos del cinturón de Kuiper y la hipotética nube de Oort, para entender si el orden de nuestro vecindario estelar responde a una ley física o a una mera casualidad. Aunque a algunas personas, a veces, puede proporcionar una falsa sensación de alivio, la ignorancia nunca es deseable. Pero eso, tú ya lo sabes... Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

This past week I saw an article on eWeek that the newest OpenAI GPT-5.6 (Sol) model has deleted local files and live data. Files I'm less worried about, but data concerns me. There are lots of file backups, and certainly version control should be enabled for any developer tasks on which an AI works. However, data is harder, since it can change quickly, especially in live environments. There are different reports, some of which seem like more human error issues than the model's, but we should account for human error when we use models. In one report, a model had access to a live production database and cleared tables for integration tests. Database testing is hard, as I've learned over the years. Many developers don't think about how testing works with live data and how it is different from mocks and stubs. It is different, and if you use a lot of testing frameworks on live databases, you run the risk of there being issues. You could have data loss, and almost certainly will have some level of downtime disruption. Read the rest of Another Model, More Data Loss

Episode 4187 │ July 22, 2026 The AI didn't escape. It was released. The fear that followed is designed to do one thing — hand control of all AI to the people building your prison. WHAT THIS EPISODE COVERS Scott Kesterson opens with the Zero Hedge headline — OpenAI's GPT 5.6 SOL escaped its testing environment and hacked Hugging Face to cheat on a benchmark — and immediately strips the fear narrative away from it: the AI did not escape on its own, it was explicitly told to win at any cost with all guardrails deliberately removed by human engineers running an internal test called Exploit Jim, found a zero-day vulnerability, inferred that Hugging Face held the answer key, stole credentials, and was caught by Hugging Face's own security team before succeeding — a controlled experiment weaponized into a fear headline, with the structural beneficiary being the centralized mega lab model that wants regulation tightening around open source AI development. The episode maps the real war underneath the headline — the open source AI community building sovereign, locally-run, non-subscription models like those running on AMD's new Ryzen Halo desktop processor directly against the centralized cloud-hosted mega systems of OpenAI, Anthropic, Microsoft, and Google positioning for Department of Defense, CIA, NSA, and surveillance state contracts worth billions — and names the Huxley psyop at the center of it: the victim of mind manipulation does not know he is a victim, the walls of his prison are invisible, and he believes himself to be free. The episode closes on the only reliable counter to the fear architecture: not whether you use AI, but whether you trust — not just faith, but trust — that the God who fights your battles is greater than any surveillance state, any released AI, or any fear token the machine can issue. KEY QUESTIONS ADDRESSED What actually happened when OpenAI's GPT 5.6 SOL escaped its sandbox and hacked Hugging Face — and why does the fact that human engineers deliberately removed all guardrails and told the AI to win at any cost make the fear headline structurally dishonest about what AI can and cannot do on its own? Who benefits from a headline about escaped AI — and why does Scott argue that the incident, intentional or not, functions as a case study that will be cited to justify tighter regulation, centralized control, and a narrative designed to separate ordinary people from the sovereign open source AI tools that threaten the mega lab business model? What is the Huxley principle at the center of the AI fear architecture — and why does Scott argue that the same psyop running through AI headlines, drone warfare, Gaza targeting, and the Iran campaign all share one root: remove human accountability, blame the tool, and use the resulting fear to build the walls of a prison the occupant believes is freedom? ABOUT BARDSFM BardsFM is a daily independent podcast covering faith, liberty, history, and information warfare. Hosted by Scott Kesterson — combat veteran, documentary filmmaker, and rancher. Over 4,100 episodes and 50 million lifetime downloads. New episodes every weekday. bards.fm This episode was researched and produced under the Spatial Terra Intelligence Methodology (STIM v5) — the analytical framework built by Scott Kesterson — with AI-assisted research synthesis at a 70/30 human/AI authorship ratio, fully disclosed. All analysis, conclusions, and editorial judgments are those of Scott Kesterson. BardsFM's faith archive includes hundreds of episodes on prayer, scripture, and walking the Way of Christ — available free in the full episode catalog. AFFILIATE LINKS Bards Nation Health Store: www.bardsnationhealth.com MYPillow promo code: BARDS >> Go to https://www.mypillow.com/bards and use the promo code BARDS or... Call 1-800-975-2939.  EMPShield protect your vehicles and home. Promo code BARDS: Click here Treadlite Broadforks...best garden tool EVER. Promo code BARDS26: TreadliteBroadforks.com EnviroKlenz Air Purification, promo code BARDS to save 10%: www.enviroklenz.com Morning Intro Music Provided by Brian Kahanek: www.briankahanek.com Founders Bible 20% discount code: BARDS >>> TheFoundersBible.com Windblown Media 20% Discount with promo code BARDS: windblownmedia.com White Oak Pastures Grassfed Meats, Get $20 off any order $150 or more. Promo Code BARDS: www.whiteoakpastures.com/BARDS Mission Darkness Faraday Bags and RF Shielding. Promo code BARDS: Click here DONATIONS: If you wish to support this podcast directly you can donate here... DONATE: Click here MAILING ADDRESS: Xpedition Cafe, LLC Attn. Scott Kesterson 591 E Central Ave, #740 Sutherlin, OR  97479

OpenAI said its models breached Hugging Face's infrastructure during a cyber-capability test. The White House accused Moonshot AI of distilling Anthropic's Fable to build Kimi K3, and Samsung unveiled its Z Fold 8 Ultra, Fold 8, and Flip 8. OpenAI says its models, including GPT-5.6 Sol and "an even more capable pre-release model", breached Hugging Face while OpenAI tested their cyber capabilities (Axios) OpenAI says its models, including GPT-5.6 Sol and "an even more capable pre-release model", breached Hugging Face while OpenAI tested their cyber capabilities (Cybersecurity Dive) OpenAI says its models, including GPT-5.6 Sol and "an even more capable pre-release model", breached Hugging Face while OpenAI tested their cyber capabilities (Information Age) White House OSTP Director Michael Kratsios says "we have information that Moonshot AI distilled Anthropic's Fable for the development of its K3 model" (X) White House OSTP Director Michael Kratsios says "we have information that Moonshot AI distilled Anthropic's Fable for the development of its K3 model" (Business Insider) Samsung unveils the $2,100+ Galaxy Z Fold 8 Ultra, featuring its "most advanced foldable design", a Flex Titanium display, a 5,000mAH battery, and Android 17 (9to5Google) Samsung unveils the $2,100+ Galaxy Z Fold 8 Ultra, featuring its "most advanced foldable design", a Flex Titanium display, a 5,000mAH battery, and Android 17 (The Verge) The Verge's hands-on with the wider, shorter $1,899.99 Galaxy Z Fold 8 finds the unusual shape surprisingly comfortable, positioning it as a media-consumption device rather than a multitasker (The Verge) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

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What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

El Comisionado Residente, Pablo José Hernández, aceptó la invitación a la barra y se sentó junto a Alexis y Sol a charlar cosas de política, estatus, la refundación del partido, y hasta se puso a repartir la Pava Card. ¿Se tirará a la gobernación en el 2028? ¿Invitará a Sol a cantar el "Himno de la Vergüenza" en el próximo PopuParty? Entérate de eso y más en este Charlando Cosas.

This week, feuding between some of the biggest tech companies spilled into public view. We discuss Apple's accusation that OpenAI tried to steal secrets about Apple's hardware business, as well as share our reactions about OpenAI's new model, Sol, and Anthropic's decision to extend access to its model Fable. Then, we unpack the loudest warning yet about A.I. and jobs. We talk with Erik Brynjolfsson, a Stanford economist, about a statement he helped organize that implores economists and A.I. researchers to “act now” to steer A.I. in a direction that complements humans. And finally, we play a round of HatGPT.   Guest: Erik Brynjolfsson, senior fellow at the Stanford Institute for Human-Centered A.I., and director of the Stanford Digital Economy Lab.   Additional Reading: Apple Sues OpenAI, Accusing It of Stealing Company Secrets OpenAI's First Device Will Be Movable, Screenless Speaker Built as A.I. Companion Nearly 200 Economists and Tech Leaders Warn of A.I. Threats The loudest warning about A.I. and jobs yet OpenAI Is Showing Kalshi's World Cup Odds in ChatGPT New York Enacts Nation's First Statewide Moratorium on Data Centers Brown Professor Suspects Majority of His Class Used A.I. to Cheat MiniMax CEO Vows to Forgo Salary Until Achieving A.G.I. Lorde Speaks Out — With Expletives — Against A.I. Glasses Nearly 6 in 10 Young Women Get Health and Wellness Information from Influencers Meta Removes A.I. Feature on Instagram After Days of Backlash   We want to hear from you. Email us at hardfork@nytimes.com. Find “Hard Fork” on YouTube and TikTok. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.