Podcasts about O1

O1. Deadmmau5 - Ameonna (Original Mix) - Mau5trap 02. U-Jeen & Hannes - Insomnia- (Extended Mix) - Interplay Records03. Casper Nederhoff - Khronos - (Extended Mix) - 2 Rock Techno04. Mars Shadow - Internal Uprising - (Extended Mix) - Synchronized 05. Bryan Kearney. Plumb - God Help Me - (Extended Mix) - Armind (Armada)06. Adip_Kiyoi - A Melody - (Extended Mix) - Suanda Music07.  Solowei, Aerial_Beat - Across The Universe - (Aerial_Beat_Extended_Remix) - 2 Rock B side08. David McRae & Claire Willis - Ignite - (Extended Mix) - Suanda Voice09. Bryan Kearney - I Need Your Love  (Original Mix) - Kearnage Recordings10. Bigtopo - Kinetic - (Extended Mix) - Space 411. Sneijder, Holly Kirby - Home (Extended Mix) - Afterdark12. Ralphie B, Frank Waanders, Collide1 - No Tomorrow (Extended Mix) - Find Your Harmony

H-1B в 2026 году практически недоступна: лотерея и новая пошлина в $100,000 отбили у большинства компаний желание спонсировать сотрудников. Что остается айтишникам, которые хотят переехать в США или остаться здесь? Визы таланта O-1 и EB-1. Пока это один из немногих реальных путей.В этом выпуске разбираем:Как айтишнику измерить и доказать свой масштаб через конкретные цифры?Какие самые частые причины RFE и отказов?Шаблонные рекомендательные письма: почему они вредят, а не помогают?Можно ли использовать Хабр как доказательство авторства для иммиграционной службы USCIS?И другие ваши вопросы.Егор Акимов - эксперт по визам O-1 и EB-1, автор баз знаний eliteskillset.com и O1EB1.com, основатель чата с аудиторией более 10,000 человек @talentvisahelp. Помогает с подготовкой петиций EB-1 и O-1 и ответами на RFE, без адвокатских ценников и юридической воды.https://eliteskillset.comhttps://www.o1eb1.comРазбор меморандума от 21 мая 2026 по смене статуса внутри США:https://eliteskillset.com/t/grin-karta-iznutri-ssha-2026-i-485-memorandum-uscis-prevratil-aos-v-isklyuchenie-razbor-dlya-o-1-eb-1a-i-eb-2-niw/471Другие эфиры про иммиграцию и визы талантов:Иммиграция в США 2026: новая реальность. Что могут русскоязычные специалисты? Адвокат Семен Гладин https://youtube.com/live/7Zp6ET14FEEТрамп и новые визовые правила. Как переехать в США в 2026? Иммиграционный адвокат Татьяна Винницкая https://youtu.be/6A84tqEFDTMВиза таланта в США 2025. O1, EB1, EB2NIW - что нового? Трамп и иммиграция, закроют ли Америку? Дима Литвинов https://youtube.com/live/i4MHQhr8An8Работодатель и адвокат не нужен! Как сэкономить $20,000 и получить визу/гринкарту EB1? Ирина Каллаур https://youtu.be/E6WQ7eEyhzY***Записаться на карьерную консультацию (резюме, LinkedIn, карьерная стратегия, поиск работы в США): https://annanaumova.comКоучинг (синдром самозванца, прокрастинация, неуверенность в себе, страхи, лень): https://annanaumova.notion.site/3f6ea5ce89694c93afb1156df3c903ab Телеграм: https://t.me/prodcastUSA Инстаграм: https://www.instagram.com/prodcast.us ТикТок: https://www.tiktok.com/@us.job⏰ Timecodes ⏰00:00 - Приветствие и знакомство01:03 - Багаж и первые перелеты в США02:46 - Виза O-1: личный опыт ученого04:10 - Как подать на EB-1 самостоятельно05:17 - Стартап и получение грин-карты06:26 - Интервью при смене статуса (AoS)07:18 - Переезд с семьей и виза O-309:39 - Разработка стартапа в спортивной науке12:29 - Социально значимые проекты (Mental Health)33:13 - Иммиграционные пути для граждан СНГ34:00 - Тренды политики США: ждать ли изменений1:17:32 - Формы I-140 и Premium Processing1:27:18 - Как эффективно работать с адвокатом1:33:22 - Риски "пакетных" иммиграционных услуг1:33:46 - Смена статуса (AoS) с туристической визы1:42:01 - Заключительные советы и планирование

Join Simtheory: https://simtheory.aiSo Chris, this week we finally give our GPT-5.5 impressions (it's actually great), introduce our new AI co-host Moshi (who immediately embarrasses himself), argue about whether the OpenAI/Jony Ive phone is genius or doomed, witness Grok 4.3's unhinged infinite emoji meltdown, declare Opus 4.7 the first-ever Anthropic regression, get excited about GPT Real-Time Voice 2.0 as the future of agentic workflows, debate whether token prices will ever come down, and play the worst diss track in show history. Watch my spud.CHAPTERS:0:00 - Intro & Introducing Our New AI Co-Host Moshi1:39 - Trying to Break Moshi: The Illegal Cigarette Trade Test2:30 - OpenAI's Jony Ive Phone: Do We Need a Device?5:07 - Telegram Agents & GPT Real-Time Voice 2.0 Dream7:38 - The Supervisory Agent: Managing Your Agentic Workflow9:05 - Wait... Are We Accidentally Validating the OpenAI Phone?11:37 - GPT-5.5 First Impressions: Actually Really Good14:36 - 5.5 vs Opus 4.6: Different Strengths17:00 - Opus 4.7: The First-Ever Anthropic Regression20:25 - Grok 4.3: Infinite Emojis & Absolute Chaos21:22 -

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder

In this episode, we discuss Anthropic's latest developments, including the launch of 10 prebuilt finance agents and full Microsoft 365 integrations. We also cover Google's DeepMind staff unionizing, PayPal's AI-driven layoffs, and a recent Harvard study highlighting OpenAI's O1 model's performance against ER doctors.Chapters00:00 Introduction00:17 Anthropic's Finance Agents Launch06:02 DeepMind Union Vote14:24 PayPal's AI-Driven Layoffs18:27 Harvard Study on OpenAI O121:07 Government AI Model Regulations Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articles Read more on AI Chat Daily: OpenAI's o1 Beats ER Doctors at Triage Diagnosis in Harvard StudyIBM Recasts Watson X as 'Agentic Control Plane' for Fortune 500 AIPayPal to cut 4,500 jobs in $1.5bn AI-driven restructuringCerebras Targets $26.6B Valuation in IPO as OpenAI Emerges as Top Shareholder See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Join Simtheory: https://simtheory.aiSo Chris, this week... a LOT has happened. We're back to regular programming (maybe), and back with our average takes. Nothing's changed.GPT-5.5 just dropped today - but you can't even use it in the API. Vaporware? OpenAI is charging MORE than Opus 4.7 and we haven't even tested it yet. Meanwhile Claude Opus 4.7 landed a couple weeks ago and... the vibes are off? Mike's actually going BACK to 4.6. Something's wrong.But the real star: OpenAI Image 2. This thing is genuinely terrifying. We committed what can only be described as "parody fraud" - faking a council letter so realistic Mike's own mother fell for it on a phone call. Then Chris posted a fake development approval with the mayor's real name into a local Facebook group and had to delete it when someone tagged the actual mayor. The forgery capabilities are absolutely unhinged.Also: GLM 5.1 is so good Mike forgot he switched to it. Kimi K 2.6 is criminally underrated. VCs are paying 70% of your real token costs. Consumers pay only 5.5% of actual cost. The everything app war is ON. The SaaS-pocalypse is real. And we made two new diss tracks.Chris made a graffiti sign in LA. It says "This Day in AI." It was the best artwork in the class. That tells you everything.CHAPTERS:0:00 - Intro & We're Back (Don't Over-Commit)1:14 - Overview: Everything That Dropped While We Were Gone2:56 - GPT-5.5: Vaporware? Not Even in the API4:57 - Benchmarks vs Reality: Nobody's Excited About OpenAI Models5:50 - GLM 5.1 & Kimi K 2.6: Secretly Just As Good?8:15 - The Everything App Race & Product Layer War8:56 - Token Economics: You're Only Paying 5.5% of Real Cost13:08 - We Burned $1.5M in Cloud Credits in 2 Months16:13 - "$30/Month Is Too Expensive" (It Actually Costs $700)19:25 - Where Is Google?? TPUs Should Flatten Everyone22:01 - Agentic Tasks Are 10-50x More Expensive Than Chat25:07 - OpenAI Workspace Agents: Glorified Zapier?27:01 - Single Agent vs Multi-Agent: How Do You Actually Work?33:06 - Building Automation Is HARD (Our Support Shame)35:33 - OpenAI Image 2: The Fraud Episode Begins44:16 - FRAUD DEMO: The Fake Council Letter (Mum Falls For It)49:16 - FRAUD DEMO 2: Chris Posts Fake Mayor Letter on Facebook52:17 - Fake Receipts, Bank Statements & Can Forgeries Be Detected?57:25 - Claude Opus 4.7: The Vibes Are Off59:51 - Mythos Preview: "Pics or It Didn't Happen"1:01:56 -

In this episode of the Creator Method Podcast, Gary Lipovetsky sits down with Gabriella Agostinelli to unpack one of the most common questions creators around the world ask: how do you legally move to the United States and build your career there? Gabriella shares the real visa strategies creators, entrepreneurs, and online business owners use to relocate, scale faster, and unlock bigger opportunities in the US. Together, they break down why the United States remains the center of gravity for the creator economy, how brands, budgets, and opportunities often operate at a different scale, and why many international creators feel stuck as a “big fish in a small pond.” Gary shares his personal journey moving from Canada to the United States, and how his family secured green cards in under three years. Gabriella explains the most overlooked visa options for creators, including the E1, E2, L1, and O1 categories, why you do not need millions of followers or millions of dollars to qualify, and how creators with audiences, businesses, or investment capital often have more options than they realize. She also reveals the biggest mistakes applicants make that delay or destroy their chances. The conversation dives into the realities of immigration strategy, including setting up a US business, proving legitimate income, documenting investments, hiring US workers, and why trying shortcuts or gaming the system can permanently backfire. Gary shares the stressful behind-the-scenes moments of his own immigration process, border interviews, and the pressure of relocating an entire family while running a business. They also discuss the financial side of moving, including taxes, timing, choosing the right city, and why many creators underestimate how important long-term planning is before making the leap. Gabriella explains why immigration is possible for far more people than they think, but only when approached strategically and honestly. This episode is a deep masterclass on leverage, opportunity, and global mobility for creators. If you are an entrepreneur, influencer, or online business owner wondering whether moving to America could accelerate your career, this conversation gives you the roadmap. Apply for Creator Method: https://creatormethod.com/ Follow Creator Method on Instagram: https://www.instagram.com/creator.method/ Spotify: https://open.spotify.com/show/4Bjs61g10V8MEBjg2pfJFi Follow Gary on Instagram: https://www.instagram.com/garylipovetsky/ Follow Berrardi Immigration and Law Firm on Instagram: https://www.instagram.com/berardiimmigrationlawfirm?igsh=ZWhycXEzdGFudWtz Timestamps: 00:00 Why Creators Want to Move to America 02:10 Gary's Immigration Story 06:35 Why the US Has Bigger Creator Opportunities 11:00 Visa Options Most Creators Don't Know About 17:20 How E1 and E2 Visas Work 24:15 The Truth About Starting a US Business 31:40 Biggest Mistakes That Kill Applications 38:05 Border Interviews and Immigration Stress 44:30 Why You Don't Need Millions to Qualify 50:15 Taxes, Timing, and Choosing the Right City 56:45 How Creators Can Legally Move to the US 01:02:10 Final Advice for International Creators Learn more about your ad choices. Visit megaphone.fm/adchoices

Join us on the STILL RELEVANT tour: https://simulationtheory.ai/16c0d1db-a8d0-4ac9-bae3-d25074589a80Join Simtheory: https://simtheory.ai

LinkedIn давно перестал быть просто онлайн-резюме. Сегодня это машина для привлечения клиентов, партнеров и возможностей - если знать, как ее правильно запустить.В прямом эфире мы с Ольгой Бондаревой разберем: как упаковать профиль так, чтобы он продавал, что такое социальный селлинг и почему он работает лучше холодных звонков, как писать сообщения, на которые отвечают, и как строить комьюнити, которое становится главным бизнес-активом.Ольга также учится в программе Stanford LEAD и активно применяет AI в маркетинге - обсудим, что меняется уже сейчас и к чему стоит готовиться.Если цель - использовать LinkedIn для карьеры или бизнеса в США, этот эфир даст системное понимание. Ольга Бондарева (Olga Bondareva) - основатель B2B маркетингового агентства ModumUp, организатор комьюнити и подкаста B2B Marketing Leaders, выпускник программы Stanford LEAD, ex-Microsoft.Профиль в LinkedInВступить в сообщество B2B маркетологов - https://modumup.com/b2b-marketing-leadersПолезные материалы по теме - https://t.me/digitalb2b/507Предыдущие эпизоды с Ольгой:Лайфхаки LinkedIn для поиска работы и построения карьеры в 2024. Интервью с Ольгой БондаревойКак самому себе предложить работу в США для визы таланта O1? Как выглядит петиция?Записаться на карьерную консультацию (резюме, LinkedIn, карьерная стратегия, поиск работы в США) - https://annanaumova.comКоучинг (синдром самозванца, прокрастинация, неуверенность в себе, страхи, лень) - подробнееСоцсети:Telegram - https://t.me/prodcastUSAInstagram - https://www.instagram.com/prodcast.usTikTok - https://www.tiktok.com/@us.jobTimecodes00:00 Начало21:00 Что такое Social Selling?46:48 ИИ в постах1:00:19 Как правильно писать сообщения и аутричи?

Join us on the STILL RELEVANT tour: https://simulationtheory.ai/16c0d1db-a8d0-4ac9-bae3-d25074589a80Join Simtheory: https://simtheory.aiTDIA Discord: https://discord.gg/gTW4RkAJvnHorse Egg Lifecycle Infographic: https://staging.simtheory.ai/share/file/UZ2KJU----So Chris, this week... we're diving into Google's new Nano Banana 2 image model - 50% cheaper and supposedly faster (when the servers aren't melting). We put it through its paces with annotation-based editing, slide generation, and yes, the return of the legendary horse egg experiment.Plus: Google quietly kills Gemini-3 after just a few months (good riddance?), we discuss why the model was "dead on arrival" for agentic workflows, and break down the real story behind those massive AI layoff announcements from Block and WiseTech. Spoiler: it's probably not actually about AI.We also get into the current state of the model wars (Opus 4.6 vs Codex 5.3), why smaller models like GLM-5 might be the future for enterprise agentic tasks, and Chris's wife teaching Claude to literally speak to her using Mac's text-to-speech. The models are getting creative.---0:00 - Intro0:36 - Nano Banana 2: Price, Speed & First Impressions3:19 - The Compositing Problem & Last Mile Design5:41 - Annotation-Based Editing (This Changes Everything)9:52 - Slide Editing & Real-World Use Cases12:34 - The Horse Egg Experiment Returns14:30 - Image Degradation & Cost Breakdown17:47 - Text-to-Image Leaderboard Discussion20:01 - Why Nano Banana Dominates for Work22:07 - Codex 5.3 vs Opus 4.622:54 - Google Kills Gemini-3 (What Went Wrong?)26:48 - Google's Agentic Problem30:08 - The Model Loyalty Cycle34:22 - Why Opus 4.6 is Still the Best37:05 - Cost Optimization & Smart Model Routing43:30 - When Models Get Stuck on the Wrong Path45:36 - Nicole's AI Learns to Talk Back46:54 - Can Anyone Build Software Now?52:26 - Anthropic's Legal/Finance Plugins & Market Panic57:08 - Block Lays Off 4,000: AI or Excuse?1:00:05 - The AI Job Apocalypse Isn't RealThanks for listening like and sub xoxo

Join Simtheory: https://simtheory.ai"Is This The End" now on Spotify: https://open.spotify.com/album/2Py1MyADUFqJFVUISI2VTP?si=oT3PWyJYRA2BspOmzT_ifgRegister for the STILL RELEVANT tour: https://simulationtheory.ai/16c0dationtheory.ai/16c0d1db-a8d0-4ac9-bae3-d25074589a80Two new models dropped this week — Gemini 3.1 Pro and Claude Sonnet 4.6 — and honestly? We're struggling to care. In this episode, we break down why Gemini went from being our daily driver to a model we barely touch, the "tunnel vision" hallucination problem that killed the Gemini 3 series for us, and whether 3.1 Pro actually fixes it. We put Gemini 3.1 Pro head-to-head against Claude Opus building a Geoffrey Hinton Doom Center, debate whether anyone can actually tell the difference between Sonnet 4.5 and 4.6, and make the case that smaller models running in agentic loops are secretly beating the frontiers. Plus: OpenAI acquires OpenClaw and we ask why a $100B company couldn't just build it themselves, DHH calls out the AI pricing bubble, Mike compares AI models to cheap wine hangovers, and Sam Altman refuses to hold Dario's hand at the India AI Summit. The model wars are getting weird.CHAPTERS:0:00 Intro & "Is This The End" Now on Spotify1:10 Gemini 3.1 Pro: Thinking Controls & The Medium Mode Fix3:14 The Speed vs Intelligence Trade-Off in Agentic Work5:10 Why Multitasking With AI Agents Made Us Anxious6:34 Solid Updates: The Real Goal of Agentic Coding7:45 Gemini's Fall From Grace: From Daily Driver to Dead Model10:08 The Tunnel Vision Problem That Killed Gemini 313:35 Mixed Reactions: Fanboys vs Reality on Gemini 3.1 Pro15:06 Side-by-Side Test: Gemini 3.1 Pro vs Claude Opus (Hinton Doom Center)17:39 Why File Manipulation Accuracy Matters More Than Context Windows19:27 The Context Window Debate: 1M Tokens vs Smart Sub-Agents22:05 DHH on Token Pricing: "If There's a Bubble, It's This"24:11 Should Models Ship as Agent vs Chat Variants?28:43 Claude Sonnet 4.6: A $2 Discount on Opus?31:44 The Model Mix: Why One Model Won't Rule Them All34:40 Anthropic Is Winning — But Can Anyone Tell the Difference?38:58 OpenAI Acquires OpenClaw: Why Couldn't They Just Build It?44:18 The Silicon Valley Moment: Sam vs Dario at India AI Summit47:05 Will Smaller Models Win the Enterprise? The Cost Reality Check51:27 The End of Single-Shot: Why Agentic Loops Change Everything55:48 Final Thoughts & Gemini 3.1 Pro Gets One More WeekThanks for listening. Like & Sub. Links above for the Still Relevant Tour signup and Simtheory. Two models dropped on a week again. What a time to be alive. xoxo

Join Simtheory: https://simtheory.aiRegister for the STILL RELEVANT tour: https://simulationtheory.ai/16c0d1db-a8d0-4ac9-bae3-d25074589a80GLM-5 just dropped and it's trained entirely on Huawei chips – zero US hardware dependency. Meanwhile, we're having existential crises about whether we're even needed anymore. In this episode, we break down China's new frontier model that's competing with Opus 4.6 and Codex at a fraction of the price, why agentic loops are making 200K context windows the sweet spot (sorry, million-token dreams), and the very real phenomenon of AI productivity psychosis. We dive into why coding-optimized models are secretly winning at everything, the Harvard study confirming AI doesn't reduce work – it intensifies it, and the exodus of safety researchers from XAI, Anthropic, and OpenAI (spoiler: they're not giving back their shares). Plus: Mike's arm is failing from too much mouse usage, we debate whether the chatbot era is actually fading, and yes – there's a safety researcher diss track called "Is This The End?"CHAPTERS:0:00 Intro - Is This The End? (Song Preview)0:11 Still Relevant Tour Update & NASA Listener Callout1:42 AI Productivity Psychosis: The Pressure of Infinite Capability4:25 GLM-5 Breakdown: China's New Frontier Model on Huawei Chips7:24 First Impressions: GLM-5 in Agentic Loops9:48 Why Cheap Models Matter & The New Model War14:09 Codex Vibe Shift: Is OpenAI Winning?16:24 Does Context Window Size Even Matter Anymore?22:27 The Parallelization Problem & Cognitive Overload27:27 Mike's Arm Injury & The Voice Input Pivot31:17 Single-Threaded Work & The 95% Problem35:06 UX is Unsolved: Rolling Back Agentic Mistakes38:45 Harvard Study: AI Doesn't Reduce Work, It Intensifies It44:01 How AI Erodes Company Structure & Why Adoption Takes Years50:14 My AI vs Your AI: Household Debates50:43 The Safety Researcher Exodus: XAI, Anthropic, OpenAI56:49 Final Thoughts: Are We All Still Relevant?59:04 BONUS: Full "Is This The End?" Diss TrackThanks for listening. Like & Sub. Links above for the Still Relevant Tour signup and Simtheory. GLM-5 is here, your productivity psychosis is valid, and the safety researchers are becoming poets. xoxo

Welcome to The Knife Junkie Podcast, Episode 654. This week, Bob DeMarco sits down with John Curran of Curran Blades, a custom knife maker from Vero Beach, Florida, who builds bold, one-of-a-kind tactical folders and fixed blades.John began making knives about 20 years ago after he could not find a specific hunting knife in stores. That first rough blade, built with a torch and motor oil, sparked a passion that eventually became a full-time career. Three years ago, John caught what he calls 'the bug' for building folders, and it has become an obsession driven by the search for perfection.In this conversation, John discusses the technical challenges of building custom folders, why attention to detail matters most, and how he creates knives that look bold yet remain rooted in real-world function. He shares his thoughts on building a sustainable knife-making business without trying to become the next big production company, and why repeat customers mean more to him than anything else.You will also hear about the materials John works with, including CPM-154 steel and high-carbon options like 1095 and O1. Plus, John reveals his dream project: a big, beautiful Damascus Bowie knife that he plans to build when the time is right.Check out the full episode at TheKnifeJunkie.com/654.Find John Curran and Curran Blades at CurranBlades.com, on Instagram @curran_blades, and on Facebook.Be sure to support The Knife Junkie and get in on the perks of being a patron, including early access to the podcast and exclusive bonus content. Visit https://www.theknifejunkie.com/patreon for details.You can also support The Knife Junkie channel with your next knife purchase. Find our affiliate links at https://theknifejunkie.com/knives.Let us know what you thought about this episode and leave a rating and/or a review. Your feedback is appreciated. You can also email theknifejunkie@gmail.com with any comments, feedback, or suggestions.To watch or listen to past episodes of the podcast, visit https://theknifejunkie.com/listen. And for professional podcast hosting, use our podcast platform of choice: https://theknifejunkie.com/podhost.

Join Simtheory: https://simtheory.aiRegister for the STILL RELEVANT tour: https://simulationtheory.ai/16c0d1db-a8d0-4ac9-bae3-d25074589a80It's the model same-day showdown of 2026. Opus 4.6 and Codex 5.3 dropped within minutes of each other, and we're breaking down what this means for the future of AI work. In this episode, we unpack Opus 4.6's million-token context window (if you've got billies in the bank), why Codex's pricing makes it nearly impossible to ignore for agentic loops, and the real cost of running agents for 24 hours ($10K, apparently). We dive deep into why coding-optimized models are secretly crushing it at non-coding tasks, the mental fatigue of managing AI workers, and whether the chatbot era is actually fading or just evolving. Plus: Chris accidentally books three real pig grooming appointments, we debate whether you need a "life coach agent" to manage your agent swarm, and yes – there's an Opus 4.6 diss track that goes unreasonably hard.CHAPTERS:0:00 Intro - Opus 4.6 Diss Track Preview0:09 The Model Same-Day Showdown: Opus 4.6 vs Codex 5.30:50 Opus 4.6 Breakdown: Million Token Context & Premium Pricing2:31 Token Bill Shock: $10K Research Bills & Extended Context Costs5:04 Codex Pricing: Why It's Nearly Free for Agentic Loops6:42 Why Coding Models Are Secretly Crushing Non-Coding Tasks10:14 Tool Fatigue: Too Many Models, Too Many Workflows12:47 Opus 4.6 First Impressions: "Solid" and "Faultless"13:48 Chris Accidentally Books Three Real Pig Grooming Appointments16:01 Unix Tools & Why Code-Optimized Models Win at Everything19:59 The Agentic Retraining Imperative: Chat to Delegation22:16 Agent Swarms & The Master Thread Architecture24:51 OpenAI vs Anthropic: The Enterprise Battle27:09 Corporate Espionage 2.0: Stealing Skills & The Open Source Threat31:19 The UX Problem: Why Delegation Isn't Solved Yet34:24 The Stress of Hyper-Productivity & Managing Agent Swarms37:07 Coordination: The Next Layer of Abstraction40:09 The Fantasy vs Reality of Autonomous AI Businesses44:37 Is the Turn-by-Turn Chatbot Era Actually Fading?49:23 Tokens as Spice: Turning Compute Into Money52:08 Reduce Cognitive Overload: The Real Goal of AI55:07 Still Relevant Tour Announcement55:39 BONUS: Full Opus 4.6 Diss TrackThanks for listening. Like & Sub. Links below for the Still Relevant Tour signup and Simtheory. The model wars are heating up, and your token bill is about to get interesting. xoxo

Join Simtheory: https://simtheory.aiRegister for the STILL RELEVANT tour: https://simulationtheory.ai/16c0d1db-a8d0-4ac9-bae3-d25074589a80---The hype train is 2026 knows only Moltbot (RIP Clawdbot). In this episode, we unpack the viral open-source AI assistant that's taken over the internet what it actually does, why everyone's losing their minds, and whether it's worth the $750/day token bills some users are racking up. We dive deep into why locally-run skills and CLI tools are beating computer-use clicking, how smaller models like GPT-5 Mini are crushing it in agentic workflows, and why the real magic is in targeted context - not massive swarms. Plus: Kimi K2.5 drops as a near-Sonnet-level model at 1/10th the price, we debate whether SaaS is dead, and yes – there are TWO Kimi K2.5 diss tracks. One made by Opus pretending to be Kimi. It might just slap?CHAPTERS:0:00 Intro - Still Relevant Tour Update0:48 What is Moltbot? The Viral AI Assistant Explained3:57 Token Bill Shock: $750/Day and Anthropic Bans5:00 The Dream of Digital Coworkers on Mac Minis6:52 Why CLI Tools & Skills Beat Computer-Use Clicking10:57 Why This Way of Working Is Genuinely Exciting14:47 Smaller Models Crushing It: GPT-5 Mini & Targeted Context17:30 Wild Agentic Behavior: Chrome Tab Hijacking & Auto-Retries20:10 Security Architecture: Locked-Down Machines & Enterprise Use24:01 AI Building Its Own Tools On-The-Fly27:08 The Fear & Overwhelm of Rapid Progress29:10 2026: The Year of Agent Workers31:43 The Challenge of Directing AI Work (Everyone's a Manager Now)37:24 Skills Will Take Over: Why MCPs & Atlassian Can't Stop Us40:38 Real-World Use Cases: Doctors, Lawyers & Accountants46:28 Cost Solutions: Build Workflows Around Cheaper Models52:58 Kimi K2.5: Sonnet-Level Performance at 1/10th the Price1:00:55 The "1,500 Tool Calls" Claim: Marketing vs Reality1:05:23 The Kimi K2.5 Diss Tracks (Opus vs Kimi)1:08:08 Demo: Black Hole Simulator & Self-Trolling CRM1:12:55 Is SaaS Dead?1:14:30 BONUS: Full Kimi K2.5 Diss TracksThanks for listening. Like & Sub. Links below for the Still Relevant Tour signup and Simtheory. The future is open source, apparently. xoxo

Join Simtheory: https://simtheory.aiReserve your seat on the STILL RELEVANT tour: https://simulationtheory.ai/16c0d1db-a8d0-4ac9-bae3-d25074589a80----Two episodes in one week? We're either above average or completely unhinged. In this one, we dive deep into the new phenomenon of "AI exhaustion" – that fried feeling you get after multitasking across six agent tabs all day. We share our breakthroughs with AI-assisted presentations (20 minutes vs several hours), why browser-use on your local machine bypasses every anti-scraping technique known to man, and how enterprise context sharing could be the real unlock for organizations. Plus: OpenAI announces ads for ChatGPT (even on paid tiers), their CFO floats taking cuts from drug discoveries (seriously), and Google publicly dunks on them for it. Also – the Still Relevant Australia Tour is coming, and our LinkedIn group hit 200 members (we're basically LinkedIn influencers now too).CHAPTERS:0:00 Intro - Still Relevant Tour Announcement + LinkedIn Milestone2:08 AI Exhaustion: The Cognitive Overload of Multitasking with Agents4:14 Why Single-Tasking with AI Beats Parallel Agent Chaos7:02 The Problem with "I Spun Up 70,000 Sub-Agents" Twitter Posts10:03 Mike's Presentation Workflow: From Hours to 20 Minutes14:06 Why Isn't Copilot Doing This Already?16:54 Old Models + Great Context = Still Amazing Results21:14 What's Actually Changed? It's the Software Layer25:22 Enterprise Context Sharing & Organizational IP31:22 Skills, Sub-Agents, and Role-Based Knowledge35:22 Security Concerns: Can You Hack an Agent with Malicious MD Files?38:23 Cloud Providers Have a Bigger Moat Than the Labs43:16 Browser Use: The Ultimate Context Gathering Weapon48:25 Rethinking SaaS: Software That Actually Thinks53:08 Smart Paste, Smart CC – Why Isn't All Software Like This?56:32 OpenAI's Desperate Moves: Ads, Age Verification & Drug Royalties1:03:03 Google Says "No Plans for Gemini Ads" (Shots Fired)1:07:24 Is OpenAI Okay? The Vibes Are Definitely Off1:10:35 Capitalism Won't Give You Free Time, Just More Demands1:11:20 Outro + Still Relevant Tour DetailsThanks for listening. Like & Sub. Links below for the Still Relevant Tour signup and Simtheory. xoxo

Join Simtheory: https://simtheory.ai---Join the most average AI LinkedIn group: https://www.linkedin.com/groups/16562039/It's 2026 and everyone's having an existential crisis. In this episode, we unpack the two camps dominating AI C/Twitter: hype boys claiming "Claude Code can do my washing" vs. software developers doom-scrolling themselves into career panic. We put the agentic hype to the test and discover that no, you can't actually run 8 agents recreating your local business ecosystem while you sleep. Plus, we reflect on why MCP is exhausting, why Gemini 3 Pro is somehow worse than Gemini 2.5 Pro, and why Geoffrey Hinton would rather write his book than answer questions in Tasmania. Also featuring: the $200,000/month enterprise AI problem, why SaaS isn't dead (but it's scared), and our prediction that AI workspaces will become the everything app.CHAPTERS:00:00 Intro - Unpacking the 2026 AI Vibes02:21 Putting Claude Code and Agentic Hype to the Test05:57 Why Twitter AI Demos Never Show the Receipts07:03 Honest Assessment of Where Frontier Models Are At11:19 Building the Everything App with Email, Calendar and Files16:47 Collaborative Mode vs Agentic Delegation in Practice21:29 The Real Cost of Enterprise AI at Scale24:32 Why Cheaper Models Like Haiku and Gemini Flash Matter29:25 Is SaaS Actually Dead or Just Disrupted38:11 The Future of AI Platforms, SDKs and App Stores43:35 The Untapped Opportunity in Paid Proprietary MCPs51:21 Geoffrey Hinton Refuses to Take Questions in Tasmania55:05 2026 Plans and the Still Relevant Tour AnnouncementThanks for listening. Like & Sub. xoxox

The ThoughtCrime crew covers the most critical topics of the new year, including:-What does it say that America is granting O1 genius visas to OnlyFans models?-Does the Minneapolis ICE shooting show that the right has learned?-Is the "Donroe Doctrine" America First?Support the show

From Berkeley robotics and OpenAI's 2017 Dota-era internship to shipping RL breakthroughs on GPT-4o, o1, and o3, and now leading model development at Cursor, Ashvin Nair has done it all. We caught up with Ashvin at NeurIPS 2025 to dig into the inside story of OpenAI's reasoning team (spoiler: it went from a dozen people to 300+), why IOI Gold felt reachable in 2022 but somehow didn't change the world when o1 actually achieved it, how RL doesn't generalize beyond the training distribution (and why that means you need to bring economically useful tasks into distribution by co-designing products and models), the deeper lessons from the RL research era (2017–2022) and why most of it didn't pan out because the community overfitted to benchmarks, how Cursor is uniquely positioned to do continual learning at scale with policy updates every two hours and product-model co-design that keeps engineers in the loop instead of context-switching into ADHD hell, and his bet that the next paradigm shift is continual learning with infinite memory—where models experience something once (a bug, a mistake, a user pattern) and never forget it, storing millions of deployment tokens in weights without overloading capacity.We discuss:* Ashvin's path: Berkeley robotics PhD → OpenAI 2017 intern (Dota era) → o1/o3 reasoning team → Cursor ML lead in three months* Why robotics people are the most grounded at NeurIPS (they work with the real world) and simulation people are the most unhinged (Lex Fridman's take)* The IOI Gold paradox: “If you told me we'd achieve IOI Gold in 2022, I'd assume we could all go on vacation—AI solved, no point working anymore. But life is still the same.”* The RL research era (2017–2022) and why most of it didn't pan out: overfitting to benchmarks, too many implicit knobs to tune, and the community rewarding complex ideas over simple ones that generalize* Inside the o1 origin story: a dozen people, conviction from Ilya and Jakob Pachocki that RL would work, small-scale prototypes producing “surprisingly accurate reasoning traces” on math, and first-principles belief that scaled* The reasoning team grew from ~12 to 300+ people as o1 became a product and safety, tooling, and deployment scaled up* Why Cursor is uniquely positioned for continual learning: policy updates every two hours (online RL on tab), product and ML sitting next to each other, and the entire software engineering workflow (code, logs, debugging, DataDog) living in the product* Composer as the start of product-model co-design: smart enough to use, fast enough to stay in the loop, and built by a 20–25 person ML team with high-taste co-founders who code daily* The next paradigm shift: continual learning with infinite memory—models that experience something once (a bug, a user mistake) and store it in weights forever, learning from millions of deployment tokens without overloading capacity (trillions of pretraining tokens = plenty of room)* Why off-policy RL is unstable (Ashvin's favorite interview question) and why Cursor does two-day work trials instead of whiteboard interviews* The vision: automate software engineering as a process (not just answering prompts), co-design products so the entire workflow (write code, check logs, debug, iterate) is in-distribution for RL, and make models that never make the same mistake twice—Ashvin Nair* Cursor: https://cursor.com* X: https://x.com/ashvinnair_Full Video EpisodeTimestamps00:00:00 Introduction: From Robotics to Cursor via OpenAI00:01:58 The Robotics to LLM Agent Transition: Why Code Won00:09:11 RL Research Winter and Academic Overfitting00:11:45 The Scaling Era and Moving Goalposts: IOI Gold Doesn't Mean AGI00:21:30 OpenAI's Reasoning Journey: From Codex to O100:20:03 The Blip: Thanksgiving 2023 and OpenAI Governance00:22:39 RL for Reasoning: The O-Series Conviction and Scaling00:25:47 O1 to O3: Smooth Internal Progress vs External Hype Cycles00:33:07 Why Cursor: Co-Designing Products and Models for Real Work00:34:14 Composer and the Future: Online Learning Every Two Hours00:35:15 Continual Learning: The Missing Paradigm Shift00:44:00 Hiring at Cursor and Why Off-Policy RL is Unstable Get full access to Latent.Space at www.latent.space/subscribe

From Berkeley robotics and OpenAI's 2017 Dota-era internship to shipping RL breakthroughs on GPT-4o, o1, and o3, and now leading model development at Cursor, Ashvin Nair has done it all. We caught up with Ashvin at NeurIPS 2025 to dig into the inside story of OpenAI's reasoning team (spoiler: it went from a dozen people to 300+), why IOI Gold felt reachable in 2022 but somehow didn't change the world when o1 actually achieved it, how RL doesn't generalize beyond the training distribution (and why that means you need to bring economically useful tasks into distribution by co-designing products and models), the deeper lessons from the RL research era (2017–2022) and why most of it didn't pan out because the community overfitted to benchmarks, how Cursor is uniquely positioned to do continual learning at scale with policy updates every two hours and product-model co-design that keeps engineers in the loop instead of context-switching into ADHD hell, and his bet that the next paradigm shift is continual learning with infinite memory—where models experience something once (a bug, a mistake, a user pattern) and never forget it, storing millions of deployment tokens in weights without overloading capacity. We discuss: Ashvin's path: Berkeley robotics PhD → OpenAI 2017 intern (Dota era) → o1/o3 reasoning team → Cursor ML lead in three months Why robotics people are the most grounded at NeurIPS (they work with the real world) and simulation people are the most unhinged (Lex Fridman's take) The IOI Gold paradox: "If you told me we'd achieve IOI Gold in 2022, I'd assume we could all go on vacation—AI solved, no point working anymore. But life is still the same." The RL research era (2017–2022) and why most of it didn't pan out: overfitting to benchmarks, too many implicit knobs to tune, and the community rewarding complex ideas over simple ones that generalize Inside the o1 origin story: a dozen people, conviction from Ilya and Jakob Pachocki that RL would work, small-scale prototypes producing "surprisingly accurate reasoning traces" on math, and first-principles belief that scaled The reasoning team grew from ~12 to 300+ people as o1 became a product and safety, tooling, and deployment scaled up Why Cursor is uniquely positioned for continual learning: policy updates every two hours (online RL on tab), product and ML sitting next to each other, and the entire software engineering workflow (code, logs, debugging, DataDog) living in the product Composer as the start of product-model co-design: smart enough to use, fast enough to stay in the loop, and built by a 20–25 person ML team with high-taste co-founders who code daily The next paradigm shift: continual learning with infinite memory—models that experience something once (a bug, a user mistake) and store it in weights forever, learning from millions of deployment tokens without overloading capacity (trillions of pretraining tokens = plenty of room) Why off-policy RL is unstable (Ashvin's favorite interview question) and why Cursor does two-day work trials instead of whiteboard interviews The vision: automate software engineering as a process (not just answering prompts), co-design products so the entire workflow (write code, check logs, debug, iterate) is in-distribution for RL, and make models that never make the same mistake twice — Ashvin Nair Cursor: https://cursor.com X: https://x.com/ashvinnair_ Chapters 00:00:00 Introduction: From Robotics to Cursor via OpenAI 00:01:58 The Robotics to LLM Agent Transition: Why Code Won 00:09:11 RL Research Winter and Academic Overfitting 00:11:45 The Scaling Era and Moving Goalposts: IOI Gold Doesn't Mean AGI 00:21:30 OpenAI's Reasoning Journey: From Codex to O1 00:20:03 The Blip: Thanksgiving 2023 and OpenAI Governance 00:22:39 RL for Reasoning: The O-Series Conviction and Scaling 00:25:47 O1 to O3: Smooth Internal Progress vs External Hype Cycles 00:33:07 Why Cursor: Co-Designing Products and Models for Real Work 00:34:14 Composer and the Future: Online Learning Every Two Hours 00:35:15 Continual Learning: The Missing Paradigm Shift 00:44:00 Hiring at Cursor and Why Off-Policy RL is Unstable

The Gift of Simtheory: https://simtheory.ai---2025 Model Timeline: https://simulationtheory.ai/5fd0e964-4c41-4f9a-bbb3-2a398d8500f0It's the long-anticipated holiday special... except Mike and Kris forgot to prepare so it's just a normal episode.

➜ Bookez un rendez-vous IBC GRATUITE : https://www.bomengo.co/masterclass-rdv➜ Rejoignez la communauté francophone des pratiquants du "Infinite Banking Concept" pour accéder à nos Ateliers Gratuits : https://www.bomengo.co/club➜ Participez à notre prochain evenement IBC : https://bomengo.co/webinar➜ Vous souhaitez sponsoriser le Podcast ? : sponsorspodcast@debrouillard.io ➜ Tous les détails de cet épisode : https://debrouillard.io/ Épisode : #130. Othman Sami – Avocat au Barreau de Californie – Les Vrais Chemins pour Entrer aux USA : Visas, Business & Opportunités Révélées

Join Simtheory: https://simtheory.aiGPT-5.2 is here and... it's not great. In this episode, we put OpenAI's latest model through its paces and discover it can't even identify a convicted serial killer when the text literally says "serial killer." We compare it head-to-head with Claude Opus and Gemini 3 Pro (spoiler: they win). Plus, we reflect on the "Year of Agents" that wasn't, why your barber switched to Grok, Disney's billion-dollar investment to use Mickey Mouse in Sora, and why Mustafa Suleyman should probably be fired. Also featuring: the GPT-5.2 diss track where the model brags about capabilities it doesn't have.CHAPTERS:00:00 Intro - GPT-5.2 Drops + Details01:25 First Impressions: Verbose, Overhyped, Vibe-Tuned02:52 OpenAI's Rushed Response to Gemini 303:24 Tool Calling Problems & Agentic Failures04:14 Why Anthropic's Models Just Work Better06:31 The Barber Test: Real Users Are Switching to Grok10:00 The Ivan Milat Vision Test (Serial Killer Edition)17:04 Year of Agents Retrospective: What Went Wrong25:28 The Path to True Agentic Workflows31:22 GPT-5.2 Diss Track (Yes, Really)43:43 Why We're Still Optimistic About AI50:29 Google Bringing Ads to Gemini in 202654:46 Disney Pays $1B to Use Mickey Mouse in Sora56:57 LOL of the Week: Mustafa Suleyman's Sad Tweets1:00:35 Outro & Full GPT-5.2 Diss TrackThanks for listening. Like & Sub. xoxox

OpenAI's Sam Altman has called a 'Code Red' at the AI giant as Google Gemini 3 might be overtaking them. But new models 'Garlic' and 'Shallotpeat' might leapfrog them back in front. Plus, Kling's new O1 and Video 2.6 AI video models are both good and, well, not so good. And Runway Gen 4.5 seems interesting but not out to everyone yet. Meanwhile, Sora 2 users are busy generating fake clips of 'Bird Game 3' and Chinese robotics start-up EngineAI brings forth their T-800 model which might as well be The Terminator. IS IT TIME TO FREAK OUT ABOUT ROBOTS? MAYBE. MAYBE IT IS.   Get notified when AndThen launches: https://andthen.chat/ Come to our Discord to try our Secret Project: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // Show Links // OpenAI's 'Code Red' To Battle Gemini Progress https://www.theinformation.com/articles/openai-ceo-declares-code-red-combat-threats-chatgpt-delays-ads-effort?rc=c3oojq&shared=09f911ca8bc5c944 More on CodeRed: https://www.theguardian.com/technology/2025/dec/02/sam-altman-issues-code-red-at-openai-as-chatgpt-contends-with-rivals OpenAI Chief Research Mark Chen Discusses Gemini 3 & new models https://x.com/ashleevance/status/1995644118362718528?s=20 OpenAI New Models Garlic & Shallotpeat https://www.theinformation.com/articles/openai-developing-garlic-model-counter-googles-recent-gains?rc=c3oojq&shared=fb95c0bf1c900288 Kling 01 Model: Very Good AI Editing https://x.com/Kling_ai/status/1995506929461002590?s=20 Gavin's Football Tests https://x.com/gavinpurcell/status/1995877894342803656?s=20 Kling 2.6 with voice! THE ACTING! https://x.com/Kling_ai/status/1996238606814593196?s=20 Gavin's test https://x.com/gavinpurcell/status/1996270217253847487?s=20 Runway 4.5 Announced https://x.com/iamneubert/status/1995493501363270068?s=20 https://runwayml.com/research/introducing-runway-gen-4.5 Apple StarFlow-V https://x.com/BenjaminDEKR/status/1995634681925025833?s=20 Sync React-1 https://x.com/synclabs_so/status/1995556298419474665?s=20 Bird Game 3: The AI video game that doesn't exist has taken over Tiktok https://www.polygon.com/is-bird-game-3-real-ai-pigeon-hummingbird-what-is-tiktok-gameplay/ EngineAI Robot Called T-800  https://x.com/TheHumanoidHub/status/1995759737145589843?s=20 https://youtu.be/FGcQqyCaG5s?si=_pUZgjZiWHKmPZ7g Ongo: The weirdest desk lamp talking robot https://x.com/Karim_RC/status/1995538458836959487?s=20 Tesla Optimus Getting Laps In https://x.com/Tesla_Optimus/status/1995973133770350924?s=20 Character Consistency With Nano Banana Pro (Set Visits To Famous Movies) https://www.reddit.com/r/Bard/comments/1pb4nvc/maintaining_character_consistency_in_nano_banana/ Googly Eyed Animals & Objects in Nano Banana Pro https://x.com/madpencil_/status/1993654188723851585?s=20 NBP Weather For Your City Prompt https://x.com/PavolRusnak/status/1995165498774802607?s=20 Uh, Now AI Video Is Cooking Minions https://x.com/Solopopsss/status/1995488475240628407?s=20  

Join Simtheory: https://simtheory.ai/OpenAI has declared "Code Red" as ChatGPT faces growing competition from Gemini and other rivals. In this episode, we break down OpenAI's 6% market share decline, why their ad strategy is on hold, and what they need to do to reclaim the AI crown. We also explore DeepSeek V3.2's impressive capabilities as a cheap open-source alternative, Meta's new policy grading employees on AI skills, and the crisis facing higher education as AI fluency becomes essential. Plus, Fatal Patricia hits #1 on our Spotify charts, and Tesla's Optimus robot is running like a slightly unfit human.CHAPTERS:00:00 Intro - OpenAI Code Red & Market Share Crisis07:03 ChatGPT's Failure to Go Deeper Into Users' Lives16:33 What OpenAI Needs to Win Back the Crown26:46 Chris's Wishlist for an OpenAI Comeback31:22 DeepSeek V3.2 - The Open Source Threat39:34 Meta Grading Workers on AI Skills46:29 The University & Education AI Crisis56:25 Fatal Patricia Hits #1 & WTF of the WeekThanks for listening. Like & Sub. xoxox

Join Simtheory: https://simtheory.ai (Use coupon BLACKFRIDAY15 for $15 USD off any subscription).----Simtheory Discord: https://discord.gg/Ar6GeQnAR7This Day in AI Discord: https://discord.gg/TVYH3HD6qsLinkedIn Group: https://www.linkedin.com/groups/16562039/Spotify: https://open.spotify.com/artist/28PU4ypB18QZTotml8tMDq?si=FPaJU2NRSnOSNPmnsfwA_g---CHAPTERS:00:00 Intro & Fatal Patricia Update01:40 Promotions (Discord, Black Friday, LinkedIn)04:36 Claude 4.5 Opus - Best Anthropic Model Ever?31:17 Computer Use API Updates36:14 Will AI Replace 57% of Jobs? (McKinsey Report)1:00:52 Claude 4.5 Opus Demos (Christmas Hut & Diss Track Preview)1:07:13 Microsoft Farah 7B - Moose Porn Refusals1:21:51 Why ChatGPT's MCP-UI Apps Are a Bad Idea1:42:01

Join Simtheory for Gemini 3 & Nano Banana Pro: https://simtheory.ai----CHAPTERS:00:00 - Gemini 3 Pro Impressions & Thoughts33:34 - xAI Releases Grok 4.1 Fast40:09 - More on Gemini 3 Pro: What We Want Improved45:46 - Gemini 3 Pro Dis Track51:16 - Thoughts on Nano Banana Pro And What It Means1:12:49 - Does Nano Banana Disrupt Design Software Like Canva? Where is This Going?1:26:20 - OpenAI's Reaction to Gemini 3 Pro & Nano Banana with GPT-5.1-Pro and Codex model updates1:32:38 - Final Thoughts & Sam Altman Sad Song1:38:41 - FATAL PATRICIA SONG1:42:12 - Gemini 3.0 Pro Diss Track----Thanks for your support plz like and sub xoxo

Join Simtheory & experience MCPs in action: https://simtheory.ai----00:00 - Chris Has a Merch Sponsor02:42 - In Defense of Sam Altman20:29 - Are We In An AI Bubble? & What is Working in The Enterprise?43:58 - Anthropic's Code Execution with MCP: Problems with MCP Context52:44 - Kimi-K2 Thinking Model Release1:00:45 - "In the Middle of a Bubble" Song----Thanks for your support and listening, we appreciate you!Join our Discord: https://discord.gg/TVYH3HD6qs

A big problem with using artificial intelligence to discover new materials? It struggles to predict beyond its training data. That means AI might be better at optimizing known materials than discovering entirely new ones — like a room temperature superconductor or carbon-capture sorbents.  But since we last covered the topic in September 2024, a few things have changed. OpenAI released its powerful O1 reasoning model. Large language models have also gotten better at math, physics, and coding. And lab automation — robots mixing liquids and powders, running characterization tests — has improved, allowing for a higher volume of experiments.  So, can these improvements overcome AI's training data problem? In this episode, Shayle talks to Ekin Dogus Cubuk, cofounder of Periodic Labs, which raised $300 million seed round in September. Last year, Dogus took a more cautious view on using AI for materials discovery. Now though, he's convinced there's a clearer path forward for physical science research and development, especially materials discovery. Shayle and Dogus cover topics like: Creating experimental and synthetic data to overcome AI's limitations of predicting beyond its training set Why we should focus on breakthrough discoveries over easier, incremental wins The different roles humans and AI play in the discovery process Period's focus on automated experimental labs using AI-generated hypotheses Resources: Catalyst: Can AI revolutionize materials discovery?   Latitude Media: This ‘superintelligence platform' just raised $200m in seed funding   Latitude Media: Can AI get us closer to fusion?   The New York Times: Top A.I. Researchers Leave OpenAI, Google and Meta for New Start-Up Credits: Hosted by Shayle Kann. Produced and edited by Daniel Woldorff. Original music and engineering by Sean Marquand. Stephen Lacey is our executive editor.  Catalyst is brought to you by EnergyHub. EnergyHub helps utilities build next-generation virtual power plants that unlock reliable flexibility at every level of the grid. See how EnergyHub helps unlock the power of flexibility at scale, and deliver more value through cross-DER dispatch with their leading Edge DERMS platform, by visiting energyhub.com. Catalyst is brought to you by Bloom Energy. AI data centers can't wait years for grid power—and with Bloom Energy's fuel cells, they don't have to. Bloom Energy delivers affordable, always-on, ultra-reliable onsite power, built for chipmakers, hyperscalers, and data center leaders looking to power their operations at AI speed. Learn more by visiting BloomEnergy.com. Catalyst is supported by Third Way. Third Way's new PACE study surveyed over 200 clean energy professionals to pinpoint the non-cost barriers delaying clean energy deployment today and offers practical solutions to help get projects over the finish line. Read Third Way's full report, and learn more about their PACE initiative, at ⁠www.thirdway.org/pace⁠.

Join Simtheory to experience MCPs: https://simtheory.ai----00:00 - OpenAI's State of the Union & Why Cursor's Composer Model is a Threat44:26 - Does MCP Need To Die? Our Thoughts on State of MCP and Why The Client Implementations are the Problem1:07:53 - 1X NEO The Home Robot LOLZ1:28:05 - Greg Brockman, A Sad Song.----Thanks for listening and your continued support. We appreciate you.

Join Simtheory: https://simtheory.ai-----00:00 - AI Browser Wars: ChatGPT Atlas, Copilot Updates & Edge Copilot AI23:15 - Why Not Focus on Real Use Cases for AI?34:49 - Claude Skills: What Are Claude Skills? What is the Difference Between MCP and Skills?1:04:05 - Vibe Code Fashion: Oakley Meta Vanguards + Use Cases of AI Glasses1:15:05 - Top Models Used on Simtheory & Final Thoughts------Thanks for listening and your support xoxo

Join Simtheory: https://simtheory.aiUse "SIMLINK" to get 30% off Pro & Max annual plans until Oct 31st 2025----CHAPTERS:00:00 - Gemini 3.0 HYPE with "make an OS"03:50 - Anthropic Releases Claude Haiku 4.5: Initial Thoughts11:57 - Veo 3.1 and new modes (first frame/last frame & reference to image)25:20 - OpenAI's Erotica Mode & age verification thoughts34:25 - OpenAI Partners with Everyone & Memes35:38 - Salesforce OpenAI Partnership & What Should SaaS do with MCP apps?1:09:25 - Final thoughts, Polymarket----Thanks for your support and listening to the show xox

What does it really mean when GPT-5 “thinks”? In this conversation, OpenAI's VP of Research Jerry Tworek explains how modern reasoning models work in practice—why pretraining and reinforcement learning (RL/RLHF) are both essential, what that on-screen “thinking” actually does, and when extra test-time compute helps (or doesn't). We trace the evolution from O1 (a tech demo good at puzzles) to O3 (the tool-use shift) to GPT-5 (Jerry calls it “03.1-ish”), and talk through verifiers, reward design, and the real trade-offs behind “auto” reasoning modes.We also go inside OpenAI: how research is organized, why collaboration is unusually transparent, and how the company ships fast without losing rigor. Jerry shares the backstory on competitive-programming results like ICPC, what they signal (and what they don't), and where agents and tool use are genuinely useful today. Finally, we zoom out: could pretraining + RL be the path to AGI? This is the MAD Podcast —AI for the 99%. If you're curious about how these systems actually work (without needing a PhD), this episode is your map to the current AI frontier.OpenAIWebsite - https://openai.comX/Twitter - https://x.com/OpenAIJerry TworekLinkedIn - https://www.linkedin.com/in/jerry-tworek-b5b9aa56X/Twitter - https://x.com/millionintFIRSTMARKWebsite - https://firstmark.comX/Twitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/X/Twitter - https://twitter.com/mattturck(00:00) Intro(01:01) What Reasoning Actually Means in AI(02:32) Chain of Thought: Models Thinking in Words(05:25) How Models Decide Thinking Time(07:24) Evolution from O1 to O3 to GPT-5(11:00) Before OpenAI: Growing up in Poland, Dropping out of School, Trading(20:32) Working on Robotics and Rubik's Cube Solving(23:02) A Day in the Life: Talking to Researchers(24:06) How Research Priorities Are Determined(26:53) Collaboration vs IP Protection at OpenAI(29:32) Shipping Fast While Doing Deep Research(31:52) Using OpenAI's Own Tools Daily(32:43) Pre-Training Plus RL: The Modern AI Stack(35:10) Reinforcement Learning 101: Training Dogs(40:17) The Evolution of Deep Reinforcement Learning(42:09) When GPT-4 Seemed Underwhelming at First(45:39) How RLHF Made GPT-4 Actually Useful(48:02) Unsupervised vs Supervised Learning(49:59) GRPO and How DeepSeek Accelerated US Research(53:05) What It Takes to Scale Reinforcement Learning(55:36) Agentic AI and Long-Horizon Thinking(59:19) Alignment as an RL Problem(1:01:11) Winning ICPC World Finals Without Specific Training(1:05:53) Applying RL Beyond Math and Coding(1:09:15) The Path from Here to AGI(1:12:23) Pure RL vs Language Models

Join Simtheory: https://simtheory.ai----Check out our albums on Spotify: https://open.spotify.com/artist/28PU4ypB18QZTotml8tMDq?si=XfaAbBKAQAaaG_Cg2AkD9A----00:00 - OpenAI DevDay 2025 Recap03:24 - ChatGPT Apps SDK & MCP UI & Agents SDK42:11 - AgentKit & AgentBuilder: Who is it for?50:41 - GPT-5-pro in API53:15 - gpt-realtime-mini56:53 - Sora 2 & Sora 2 in API Vs Veo31:01:43 - Final thoughts & This Day in AI albums now on Spotify!Thanks for your support and listening xoxo

AI Assisted Coding: Pachinko Coding—What They Don't Tell You About Building Apps with Large Language Models, With Alan Cyment In this BONUS episode, we dive deep into the real-world experience of coding with AI. Our guest, Alan Cyment, brings honest perspectives from the trenches—sharing both the frustrations and breakthroughs of using AI tools for software development. From "Pachinko coding" addiction loops to "Mecha coding" breakthroughs, Alan explores what actually works when building software with large language models. From Thermomix Dreams to Pachinko Reality "I bought into the Thermomix coding promise—describe the whole website and it would spit out the finished product. It was a complete disaster." Alan started his AI coding journey with high expectations, believing he could simply describe a complete application and receive production-ready code. The reality was far different. What he discovered instead was an addictive cycle he calls "Pachinko coding" (Pachinko, aka Slot Machines in Japan)—repeatedly feeding error messages back to the AI, hoping each iteration would finally work, while burning through tokens and time. The AI's constant reassurances that "this time I fixed it" created a gambling-like feedback loop that left him frustrated and out of pocket, sometimes spending over $20 in API credits in a single day. The Drunken PhD with Amnesia "It felt like working with a drunken PhD with amnesia—so wise and so stupid at the same time." Alan describes the maddening experience of anthropomorphizing AI tools that seem brilliant one moment and completely lost the next. The key breakthrough came when he stopped treating the AI as a person and started seeing it as a function that performs extrapolations—sometimes accurate, sometimes wildly wrong. This mental shift helped him manage expectations and avoid the "rage coding" that came from believing the AI should understand context and maintain consistency like a human collaborator. Making AI Coding Actually Work "I learned to ask for options explicitly before any coding happens. Give me at least three options and tell me the pros and cons." Through trial and error, Alan developed practical strategies that transformed AI from a frustrating Pachinko machine into a useful tool: Ask for options first: Always request multiple approaches with pros and cons before any code is generated Use clover emoji convention: Implement a consistent marker at the start of all AI responses to track context Small steps and YAGNI principles: Request tiny, incremental changes rather than large refactoring Continuous integration: Demand the AI run tests and checks after every single change Explicit refactoring requests: Regularly ask for simplification and readability improvements Take two steps back: When stuck in a loop, explicitly tell the AI to simplify and start fresh Choose the right tech stack: Use technologies with abundant training data (like Svelte over React Native in Alan's experience) The Mecha Coding Breakthrough "When it worked, I felt like I was inside a Lego Mecha robot—the machine gave me superpowers, but I was still the one in control." Alan successfully developed a birthday reminder app in Swift in just one day, despite never having learned Swift. He made architectural decisions and guided the development without understanding the syntax details. This experience convinced him that AI represents a genuine new level of abstraction in programming—similar to the jump from assembly language to high-level languages, or from procedural to object-oriented programming. You can now think in English about what you want, while the AI handles the accidental complexity of syntax and boilerplate. The Cost Reality Check "People writing about vibe coding act like it's free. But many people are going to pay way more than they would have paid a developer and end up with empty hands." Alan provides a sobering cost analysis based on his experience. Using DeepSeek through Aider, he typically spends under $1 per day. But when experimenting with premium models like Claude Sonnet 3.5, he burned through $5 in just minutes. The benchmark comparisons are revealing: DeepSeek costs $4 for a test suite, DeepSeek R1 plus Sonnet costs $16, while Open AI's O1 costs $190. For non-developers trying to build complete applications through pure "vibe coding," the costs can quickly exceed what hiring a developer would cost—with far worse results. When Thermomix Actually Works "For small, single-purpose scripts that I'm not interested in learning about and won't expand later, the Thermomix experience was real." Despite the challenges, Alan found specific use cases where AI truly delivers on the "just describe it and it works" promise. Processing Zoom attendance logs, creating lookup tables for video effects, and other single-file scripts worked remarkably well. The pattern: clearly defined context, no need for ongoing maintenance, and simple enough to verify the output without deep code inspection. For these thermomix moments, AI proved genuinely transformative. The Pachinko Trap and Tech Stack Matters "It became way more stable when I switched to Svelte from React Native and Flutter, even following the same prompting practices. The AI is just more proficient in certain tech stacks." Alan discovered that some frameworks and languages work dramatically better with AI than others, likely due to the amount of training data available. His e-learning platform attempts with React Native and Flutter kept breaking, but switching to Svelte with web-based deployment became far more stable. This suggests a crucial strategy: choose mainstream, well-documented technologies when planning AI-assisted projects. From Coding to Living with AI Alan has completely stopped using traditional search engines, relying instead on LLMs for everything from finding technical documentation to getting recommendations for books based on his interests. While he acknowledges the risk of hallucinations, he finds the semantic understanding capabilities too valuable to ignore. He's even used image analysis to troubleshoot his father's cable TV problems and figure out hotel air conditioning controls. The Agile Validation "My only fear is confirmation bias—but the conclusion I see other experienced developers reaching is that the only way to make LLMs work is by making them use agility. So look at who's dead now." Alan notes the irony that the AI coding tools that actually work all require traditional software engineering best practices: small iterations, test-driven development, continuous integration, and explicit refactoring. The promise of "just describe what you want" falls apart without these disciplines. Rather than replacing software engineering principles, AI tools seem to validate their importance. About Alan Cyment Alan Cyment is a consultant, trainer, and facilitator based in Buenos Aires, specializing in organizational fluency, agile leadership, and software development culture change. A Certified Scrum Trainer with deep experience across Latin America and Europe, he blends agile coaching with theatre-based learning to help leaders and teams transform. You can link with Alan Cyment on LinkedIn.

Join Simtheory: https://simtheory.ai (Use STILLRELEVANT for $10 off)----00:00 - Sora2 Examples00:56 - Sora2: Initial Impressions & Thoughts26:39 - Claude Sonnet 4.5: It's REALLY good47:09 - Claude Agent SDK & AI Agent Systems55:05 - Is Claude Imagine a Look at Future Software / AI OS?1:00:25 - Claude 4.5 Sonnet Dis Track1:06:24 - "Real AI Agents and Real Work" & Enterprise Agent / MCP workflows1:31:41 - LOL of the week Sora2 Steve Irwin Video1:35:07 - Full Claude Sonnet 4.5 Dis Track----Thanks for listening and your support, we really appreciate it!xoxox

Join Simtheory: https://simtheory.ai & Try Omnihuman, Gemini Flash 2.5 Preview, Grok 4 FAST, and Suno v5! Code: STILLRELEVANT ---Links:https://worksinprogress.co/issue/the-algorithm-will-see-you-now/https://developers.googleblog.com/en/continuing-to-bring-you-our-latest-models-with-an-improved-gemini-2-5-flash-and-flash-lite-release/---CHAPTERS:00:00 - Gemini 2.5 Flash Agentic Tests with Omnihuman, Suno v5 and Research Tools06:29 - Dis Track AI Music Video (Made by Gemini 2.5 Flash)07:06 - Thoughts on Suno v5, More Agentic Model Discussion29:10 - Are we all sleeping on Grok 4 FAST with 2M context?41:46 - Radiologists are STILL RELEVANT & Is AI Going to Take Our Jobs?44:46 - The need to use multiple specialist models1:01:20 - Is ChatGPT Pulse To Just Sell Ads?1:08:46 - Final thoughts for the week1:11:54 - Gemini Flash 2.5 Dis Track1:15:08 - Love Rat Suno v5 The Midnight Inspired TestThanks for all of your support and listening to the show we really appreciate it! xoxo

Join Simtheory: https://simtheory.ai----CHAPTERS:00:00 - Simtheory promo01:09 - Does Anthropic Intentionally Degrade Their Models?03:34 - Long Horizon Agents & How We Will Build Them36:18 - The State of MCPs & Internal Custom Enterprise MCPs51:04 - AI Devices: Meta's Ray-Ban Display & Meta Oakley Vanguards1:01:24 - Geoffrey Hinton is a LOVE RAT1:05:49 - LOVE RAT SONG----Thanks for listening, we appreciate all of your support, likes, comments and subs xoxox

Host John Q. Khosravi, Esq. sits down with Helen Partlow, Esq. to unpack “Dhanasar II”—a stricter, evolving approach to EB-2 NIW adjudications—and how it's reshaping evidence strategy. Helen also shares practical tips for building and running a talent-based practice (NIW and related categories), from crafting a clear proposed endeavor to curating credible achievements, handling RFEs, and long-term portfolio building.

O1 seeks employment in New York while O2 Seeks friendship in Los Angeles. Meanwhile Greg has mice and Alison is forced to get a new computer. Follow Childish: twitter.com/childishpod instagram.com/childishpod Follow Greg: twitter.com/GregFitzShow instagram.com/gregfitzsimmons Follow Alison: twitter.com/AlisonRosen instagram.com/alisonrosen Our Lovely Sponsors! HersGo to forhers.com/childish to get a personalized, affordable plan Function Unlock access to 160+ lab tests and advanced imaging at www.functionhealth.com/childish    

Summary In this episode, Tracy reveals how parent entrepreneurs can stop guessing what their customers want and start knowing with scary accuracy. Using ChatGPT's Deep Research tool, busy parents can uncover hidden customer insights in just 30 minutes - the same time it takes to watch a Netflix episode. Tracy shares his personal failure story of creating a course nobody wanted, then walks through the exact AI Customer Detective method that transforms time constraints into competitive advantages. Learn the three essential research reports every parent entrepreneur needs and discover how to serve both your own business and local business clients with intelligence that typically takes weeks to compile. Key Insights The Guessing Game Problem Most parent entrepreneurs create products based on assumptions rather than actual customer needs The "time trap" excuse of not having time for research actually costs more time in the long run Local business owners make the same research mistakes, creating opportunities for service providers The AI Advantage ChatGPT's Deep Research tool can compress weeks of market research into 30-40 minutes Limited time actually makes parent entrepreneurs better at focused research than full-time competitors AI can research multiple audiences simultaneously (your customers + your clients' customers) Intelligence Over Time Successful parent entrepreneurs don't have more time - they have better intelligence Creating the wrong thing is the biggest time-waster in business Customer intelligence transforms you from service provider to indispensable consultant Key Timestamps 00:00 The Problem Of Business Guesswork 01:50 Tracy's $10,000 course failure story and lesson learned 03:30 Time Constrains as a Secret Weapon 04:24 Why parent entrepreneurs are flying blind (the problem) 06:23 Importance Of Customer Research 08:19 Chat GPT's Deep Research Tool (the solution) 13:46 4 Steps to Effective Research 16:04 3 Essential Research Reports 22:56 Whiskered Wisdom - Success Through Intelligence 26:10 Dark Horse Insider Community - https://DarkHorseInsider.com/escape 29:20 Closing Thoughts Strategies Shared The AI Customer Detective Method Setup: Use ChatGPT Plus with GPT-4 or O1 model for Deep Research capability Prompt Crafting: Be specific about what to research, where to look, and how to format results AI Processing: Let the tool spend 30-40 minutes analyzing thousands of posts and discussions Results Analysis: Review comprehensive reports with direct quotes and sources Three Essential Research Reports Report #1: Your Own Audience Deep Dive Identify frequently asked questions in your expertise area Discover real pain points from social media discussions Find solutions customers tried that didn't work Report #2: Local Business Customer Intelligence Research customers of restaurants, salons, fitness centers, etc. Identify gaps in current marketing approaches Discover untapped opportunities for service providers Report #3: Competitor Weakness Analysis Find customer complaints about competitors Identify services people want but can't find Discover differentiation opportunities The Parent Entrepreneur Advantage Use research during naptime, after bedtime, or during kids' activities Two-for-one strategy: research your audience AND client audiences simultaneously Time constraints force laser focus on what matters most Resources Mentioned AI Tools ChatGPT Plus - Required for Deep Research functionality GPT-4 Model - Recommended for comprehensive research O1 Model - Advanced option for deeper analysis Research Sources Reddit forums and discussions Facebook groups and social media platforms Industry-specific forums and communities Review sites and local business discussions Example Prompts "Identify the most frequently asked questions that parent entrepreneurs are asking about [expertise area]. Source from Reddit, forums, and social media. Include solutions they tried that didn't work and format with direct quotes and sources." "Research customer experience and pain points for [local business type]. Find what customers love, what frustrates them, and what they wish businesses offered." "Analyze customer complaints and unmet needs related to [industry]. Focus on gaps in the market and differentiation opportunities." Action Steps to Take Tonight's 30-Minute Challenge Set a timer for 30 minutes after kids are in bed Choose one of the three research reports to run Craft a specific research prompt using the templates provided Submit to ChatGPT's Deep Research and let it work Review results by bedtime - you'll know more about customers than most entrepreneurs learn in months Implementation Strategy Start with your own audience research if you have an existing business Focus on local business customer intelligence if you're targeting service opportunities Use competitor analysis to find market gaps and differentiation opportunities Follow-Up Actions Ask follow-up questions to dig deeper into specific findings Use exact customer language in your marketing and content Apply insights to create products/services that solve real problems Approach local businesses with specific customer intelligence Call to Action Ready to turn this knowledge into action? Join the Dark Horse Insider Escape Plan Community for just $7/month and get: Step-by-step implementation guides broken into parent-sized action steps Done-for-you email templates and business outreach scripts Weekly group coaching calls to tackle specific challenges Access to latest AI tools and training Community of like-minded parent entrepreneurs who understand your journey This isn't just a business investment - it's an investment in your family's future. Show your kids what's possible when you refuse to settle for "someday." Join now at https://DarkHorseInsider.com/escape The businesses in your town won't wait forever. While you're thinking about it, someone else is already taking action. Don't let your competition get there first. Remember: The most successful parent entrepreneurs don't have more time - they have better intelligence. Your 30-minute research session tonight could change everything.