Podcast appearances and mentions of Michael Burry

In this episode, we speak with Brian Barlow, Co-Founder and CEO of Sidewalk Infrastructure Partners (SIP), a company focused on building and scaling businesses that support the next generation of critical energy and digital infrastructure. As demand for energy and computing power continues to grow, existing infrastructure systems are facing increasing strain. SIP develops businesses and projects designed to help modernize these systems and enable more intelligent, scalable infrastructure for the future. Brian has spent more than three decades as a private markets investor across technology and infrastructure. Prior to co-founding SIP, he served as Director of Infrastructure Investments for Alphabet's urban innovation platform.  Prior to that, he was a Managing director at American Infrastructure Funds.  Earlier, Brian was a senior member of Scion Capital, the investment firm founded by Dr. Michael Burry and featured in The Big Short. I am your host, RJ Lumba. We hope you enjoy the show. If you like the episode, click to follow.

In this episode of Tank Talks, Matt Cohen and John Ruffolo unpack the latest leaked details around Canada's national AI strategy, including a proposed Canadian Tech Growth Fund that would take direct equity stakes in AI startups and scale-ups. John pushes back on whether creating yet another government-backed fund solves the real problem or simply adds more confusion to an already crowded funding landscape.The conversation then moves into the AI capital arms race, where Anthropic, OpenAI, SpaceX, and Alphabet appear to be racing toward public markets and massive equity raises at the same time. Matt and John unpack Anthropic's reported path toward a late 2026 IPO, Alphabet's massive $80 billion equity raise to fund AI infrastructure, and why even companies with enormous free cash flow may be rushing to secure capital before debt markets tighten further.The episode closes with what Matt calls the “fugazi” layer of the AI boom: complex GPU financing structures, off-balance-sheet debt, SPVs, and Michael Burry's criticism of NVIDIA's xAI-related financing arrangement. From Canada's AI strategy to Alphabet's infrastructure spend to opaque AI financing models, the core question is clear: is this the beginning of a new AI-driven market cycle, or are the biggest players trying to raise capital before the music stops?Canada's New National AI Strategy & Tech Growth Fund (00:52)Matt introduces leaked details of Canada's expected national AI strategy, including a new Canadian Tech Growth Fund that would take direct equity stakes in AI startups and scale-ups, along with additional funding for the AI Compute Access Fund.Direct Investment vs. Backing Canadian VC Funds (05:02)John argues that government capital may be more effective when deployed through BDC, EDC, and Canadian venture funds, rather than direct government selection of startups. The concern is that direct investment could create political complications and distort private capital markets.Anthropic's $65B Raise and Potential 2026 IPO (09:02)The conversation shifts to Anthropic's massive fundraising round, reported $900 billion pre-money valuation, and potential late 2026 IPO path. Matt frames it as part of a broader wave of trillion-dollar AI and space-related public market activity.The IPO Race Between Anthropic, OpenAI, and SpaceX (10:04)Matt and John discuss whether the IPO window is reopening or whether the biggest private companies are rushing to get out before capital markets become less forgiving. John speculates that Anthropic may want to reach public markets before OpenAI captures investor attention.Alphabet's $80B AI Infrastructure Raise (12:18)Matt outlines Alphabet's reported $80 billion equity raise, including a private placement to Berkshire Hathaway, a public offering, and an at-the-market equity program. The raise is positioned as fuel for Alphabet's unprecedented AI infrastructure build-out.The AI Infrastructure Cold War (14:41)Matt argues that hyperscalers like Google are proving that frontier AI economics are fundamentally different from prior technology waves. John compares the AI arms race to baseball owners escalating salaries because no one can afford to fall behind.Michael Burry, NVIDIA, xAI, and “Fugazi” GPU Financing (16:01)Matt breaks down Michael Burry's critique of NVIDIA's GPU financing structure involving Valor, xAI, Apollo, Athene, and an SPV. The arrangement raises questions about revenue recognition, asset ownership, credit risk, and who ultimately carries the liability.The Real Question: What Happens When the Music Stops? (17:55)The episode ends with Matt and John questioning how these layered financing structures will play out as AI CapEx continues to explode. From public markets to SPVs to off-balance-sheet risk, the AI boom is starting to look less like a clean growth story and more like a capital market stress test.Connect with John Ruffolo on LinkedIn: https://ca.linkedin.com/in/joruffoloConnect with Matt Cohen on LinkedIn: https://ca.linkedin.com/in/matt-cohen1Visit the Ripple Ventures website: https://www.rippleventures.com/ This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit tanktalks.substack.com

Connect with Early Riders — https://www.earlyriders.com/contactConnect with Onramp — https://onrampbitcoin.com/contact-us/Presented collaboratively by Early Riders & Onramp Media…Final Settlement is a weekly podcast covering capital markets, dealmaking, early-stage venture, bitcoin applications and protocol development.This week Brian, Michael, and Liam cover MicroStrategy's first Bitcoin sale and the broader DAT unwind, Jamie Dimon's Clarity Act outburst against Coinbase, the AI IPO wave that Michael Burry compares to the 2000 dot-com peak, the CFTC approving Coinbase's first onshore BTC perpetuals, Falcon X's confidential IPO filing, Cash App and SoFi rolling out stablecoins to retail, MasterCard's NY BitLicense, and Binance launching tokenized shares.Chapters00:00 - Welcome Back and Market Overview00:46 - MicroStrategy's Bitcoin Sale and Market Sentiment08:06 - The State of Digital Asset Firms11:32 - Jamie Dimon's Stance on Stablecoins and Financial Rails22:53 - AI's Impact on Markets and Upcoming IPOs39:03 - CFTC Approval and Coinbase's Expansion40:41 - Falcon X IPO and Market Dynamics45:58 - Market Sentiment and Investment Strategies49:22 - Stablecoin Integration and Cash App's Innovations53:32 - SoFi's Stablecoin Launch and Regulatory Landscape56:01 - MasterCard's Bit License and Market Implications58:07 - Tokenized Stocks and the Future of Digital AssetsIf you found this valuable, please subscribe to Early Riders Insights for access to the best content in the ecosystem weekly: https://www.earlyriders.com/researchKeep up with Michael: https://x.com/MTangumahttps://www.linkedin.com/in/mtanguma/Keep up with Liam: https://x.com/Lnelson_21https://www.linkedin.com/in/liam-nelson1/Keep up with Brian: https://x.com/BackslashBTChttps://www.linkedin.com/in/brian-cubellis-00b1a660/

Donald Trump dijo en mayo "salid y comprad Dell". Quien le hizo caso lleva un +57% en 5 días. Esto es lo que ha pasado esta semana en los mercados, y por qué casi nadie lo está contando entero. Mercado en máximos, novena semana seguida subiendo (la racha más larga desde 2023) y la codicia mandando. Mientras tanto, Michael Burry avisa de que "huele a 1999". Repasamos el caso Dell de principio a fin, el acuerdo de 1.600M con IREN, el cohete de Micron, el nuevo club del billón de dólares, qué pasa con el value investing y la sangría del sector espacial tras la explosión de Blue Origin. Dos cosas que debes saber: 1 - Cada día mandamos un email con una idea, estrategia o reflexión privada para que avances más rápido en tu camino como inversor. El de hoy ya te lo has perdido, si quieres recibir el de mañana, te apuntas en: https://locosdewallstreet.com/7-errores/ 2 - Al apuntarte recibes un video titulado «7 errores fatales (muy habituales) en la selección de oportunidades en bolsa». Me da igual en lo que inviertas, tus años de experiencia o el tamaño de tu cartera. Si inviertes deberías verlo (antes de tomar una decisión de la que poder arrepentirte). Lo recibes al apuntarte en nuestra newsletter aquí: https://locosdewallstreet.com/7-errores/ ══════════════ DISCLAIMER El contenido de este canal de YouTube tiene exclusivamente fines educativos y no constituye asesoramiento financiero ni recomendaciones de inversión. Todos los temas tratados están diseñados para ayudar a los espectadores a entender mejor el mundo de las finanzas, pero las decisiones de inversión deben tomarse de forma personal y bajo la responsabilidad de cada individuo. Invertir en mercados financieros conlleva riesgos significativos debido a su complejidad y volatilidad. Es posible perder parte o la totalidad del capital invertido. Por ello, es fundamental que realices tu propio análisis antes de tomar cualquier decisión y, si lo consideras necesario, consultes con un profesional financiero acreditado. Recomendamos: - Contar con un fondo de emergencia equivalente a al menos tres meses de tus gastos básicos antes de invertir. - Analizar muy detenidamente y con precisión cualquier inversión. - En caso de duda consultes con un asesor financiero certificado por CNMV - Mantenerte alejado de promesas de rentabilidades astronómicas, dinero rápido u otros esquemas engañosos. En Locos de Wall Street, nuestra misión es fomentar una educación financiera sólida, ética y accesible para todos, ayudando a nuestros seguidores a tomar decisiones informadas y responsables. ══════════════ #Dell #Trump #ResumenDeMercado #Bolsa #LocoDeWallStreet

OpusClip: Start clipping at https://opus.pro/ich Airbnb: Find a co-host at https://airbnb.com/host Zapier: Get Started for FREE at https://Zapier.com/ICH FanDuel: Sign up now for your $25 bonus on FanDuel Predicts Subscribe To MeetKevin Here:  @MeetKevin  Timestamps: 00:00:00 - Intro 00:01:02 - Michael Burry & Biggest Stock Wins (Circle, Tesla, Nvidia) 00:03:08 - The $40M Tesla Portfolio & Lessons From Losses 00:05:52 - Happier With Less Stress / Should You Pay Off Debt? 00:08:11 - Iran War, Pickaxe Mountain & the Market Rally 00:11:17 - Forward Growth Valuations & the Circular AI Flow 00:13:35 - The Most Frustrating Rally Ever / Advice for $40-200K Earners 00:16:11 - OpusClip Sponsor / How the Average Person Should Invest in 2026 00:17:29 - QQQ vs TQQQ: Why Leveraged ETFs Will Go to Zero 00:21:04 - The #1 Risk Nobody's Talking About: Credit & Data Center Overbuild 00:24:58 - The Labor Market & The Wealth Effect 00:27:27 - Dry Powder & Why Cash Reduces Selling Pressure 00:29:06 - Kevin's Portfolio & Kevin O'Leary's $5M FU Money Take 00:31:02 - Are 5% Treasuries Actually a Good Buy? 00:34:54 - The Hantavirus & Real Estate Risk 00:37:31 - Airbnb & Zapier Sponsorships 00:40:04 - Is It Harder to Build Wealth in 2026? 00:42:00 - AI Implementation as the Path to Wealth (Cardone Comparison) 00:46:04 - The Best Decade Ever to Buy Real Estate (2022-2032) 00:48:34 - Graham Pushes Back: Why He's Selling His Real Estate 00:55:55 - Habitability Lawsuits & California Tenant Risk 00:57:42 - Mansion Tax & Anti-Investor Legislation 00:59:09 - Who Should Buy vs Rent / Kevin's Portfolio Allocation 01:00:55 - FanDuel Sponsor / Kevin's Top Stock Holdings 01:03:16 - Kevin's Fitness & Mediterranean Diet Transformation 01:06:38 - How Much Do You Need to Retire? ($8-10M for a Family) 01:09:19 - Spending More When You Have Free Time 01:11:43 - Buy Now Pay Later & Deferred Recession Risk 01:12:33 - Ideal Lifestyle: When Your Salary Covers Everything 01:14:57 - Best Money You'll Ever Spend & The $12.9M Jet Story 01:20:42 - SEC Investigations & The Large Options Trader Letter 01:23:48 - Zero-Day Options Trading Explained 01:27:07 - Jack's Weekly Covered Call Strategy 01:32:00 - Career Advice: Grinding on the Right Thing 01:34:08 - Podcasting & Corporate-Owned YouTube Channels 01:38:29 - The $2.2M Offer to Buy 10% of Graham's Channel 01:41:00 - Toddler Podcast Idea & Niching Down Your Audience 01:43:49 - Family Life: Kids, Personalities & a Dad Win 01:47:13 - Trump Accounts & Tax Strategies 01:48:18 - Final Advice & Wrap-Up *

In this episode, we unpack bitcoin's pullback toward $73K while AI-related capital formation and infrastructure investment continue to accelerate. The discussion covers Anthropic's latest raise, now at $965 billion post-money valuation, market commentary tied to Michael Burry's recent predictions, and the growing conversation around AGI versus the emergence of "RSI" (Recursive Self-Improvement), and what that could mean for markets, labor, and global competition. Finally, we explore the future of financial products tied to AI ecosystems, including the potential for AI token futures and new forms of market exposure as the sector matures. Chart of the week: Q1 M&A heats up as multiples rise Remember to Stay Current! To learn more, visit us on the web at https://www.morgancreekcap.com/morgan-creek-digital/. To speak to a team member or sign up for additional content, please email mcdigital@morgancreekcap.com Legal Disclaimer This podcast is for informational purposes only and should not be construed as investment advice or a solicitation for the sale of any security, advisory, or other service. Investments related to the themes and ideas discussed may be owned by funds managed by the host and podcast guests. Any conflicts mentioned by the host are subject to change. Listeners should consult their personal financial advisors before making any investment decisions.

Un documento ufficiale della SEC rivela una mossa che gela l'entusiasmo dei mercati: l'ex ricercatore di OpenAI Leopold Aschenbrenner ha puntato 8 miliardi di dollari contro i chip di Nvidia, AMD e ASML. In questo video analizziamo i dati contabili e geopolitici dietro questo short massiccio. Attraverso il suo saggio Situational Awareness, scopriremo perché il profeta della Silicon Valley non scommette sulla fine dell'IA, ma sul prossimo grande collo di bottiglia strutturale: l'energia e le infrastrutture. Vediamo cosa cambia per i tuoi investimenti e come gestire il tuo PAC con prudenza strategica. Cosa scoprirai in questo video:

Un documento ufficiale della SEC rivela una mossa che gela l'entusiasmo dei mercati: l'ex ricercatore di OpenAI Leopold Aschenbrenner ha puntato 8 miliardi di dollari contro i chip di Nvidia, AMD e ASML. In questo video analizziamo i dati contabili e geopolitici dietro questo short massiccio. Attraverso il suo saggio Situational Awareness, scopriremo perché il profeta della Silicon Valley non scommette sulla fine dell'IA, ma sul prossimo grande collo di bottiglia strutturale: l'energia e le infrastrutture. Vediamo cosa cambia per i tuoi investimenti e come gestire il tuo PAC con prudenza strategica. Cosa scoprirai in questo video:

HIMS: Get personalized and affordable care for Hair Loss, ED, Weight Loss, and more at https://Hims.com/ICEDAirbnb: Find a co-host at https://airbnb.com/hostGusto: Try Gusto for FREE for 3 months at https://gusto.com/ICEDShopify: Sign up for a $1 per month trial period at https://shopify.com/ichFollow Chris Camillo Here:  @DumbMoneyLive  Sign up for our new website to be an early user! http://www.extradollar.com/ Apply for The Index Membership: https://entertheindex.com/ Timestamps: 00:00:00 - Intro 00:01:01 - $8-Figure Trades & His $5.5M Single-Day Win 00:05:34 - The Three Waves of the AI Super Cycle 00:07:34 - Trimming Bloom, Loading Up on Amazon (4 Ways It Wins) 00:12:50 - HIMS Sponsor / Robinhood as the Other Conviction Pick 00:17:54 - Margin, Dry Powder & Pressing Into Drawdowns 00:20:44 - The Coconut Water Trade He Missed (Vita Coco) 00:22:46 - Sweet Green Wraps: The Next Social Arb Play 00:25:32 - Moving Markets with Tweets & His Ethics Rule 00:28:44 - SanDisk, Memory Chips & "Trade of a Lifetime" 00:31:02 - Airbnb Sponsor / How the Average Person Should Invest in 2026 00:34:42 - What Counts as a "Risk Asset" 00:37:02 - Gusto Sponsor / The Time His Portfolio Was Down 70% 00:41:05 - Michael Burry & the Bear Case Rebuttal 00:44:57 - Treasury Yields, Layoff Risk & Why AI Trumps the Fed 00:49:22 - Ken Griffin Just Realized What's Coming 00:52:25 - Anyone Can Now Operate Like a Hedge Fund 00:54:40 - Shopify Sponsor / The $500K-a-Year AI Implementer Path 01:00:20 - Bill Perkins Rebuilds a Website in 45 Minutes 01:03:40 - Why Podcasting Survives the AI Wave 01:08:00 - Spotting AI Content & The Rise of Live Events 01:10:53 - The Swatch x AP Frenzy (And Why He's Not Heavy in the Stock) 01:18:10 - Pokémon, Manga & The Collectibles Arbitrage 01:24:18 - Most Controversial Investing Philosophy & The SpaceX Mistake 01:28:35 - Why Anthropic Wins + His Bitcoin Take 01:30:57 - Best Founders: Andy Jassy & Amazon's AI Catch-Up 01:33:25 - Elon vs. OpenAI: Why He Saw the Loss Coming 01:35:36 - Advice to His Kids: Skip College, Travel, Build Relationships 01:40:54 - Why Chasing Bigger Numbers Doesn't Make You Happy 01:44:48 - When Does More Money Stop Mattering? Flying Private & Disconnecting 01:49:31 - Foundations Over Trust Funds & MrBeast in Ghana 01:55:34 - Portfolio Review: Jack's Account (8/10) 01:59:39 - Portfolio Review: Graham's Account (6.5/10) 02:04:44 - Tier List: Amazon, Apple, Bloom, GameStop & The Bitcoin Debate 02:08:38 - Tier List: Nvidia, Robinhood, Sweet Green, MicroStrategy 02:11:05 - Tier List: TQQQ, Tesla, Microsoft 02:13:52 - Tier List: Lululemon, Meta, Palantir, Swatch & Wrap-Up *

The Dow closed at a record high today while the S&P 500 wrapped up its 8th straight week of gains, showing just how strong momentum has been despite constant concerns about inflation, interest rates, and global uncertainty. Nvidia once again crushed earnings, raised its dividend to $0.25 per share, and announced an $80 billion share buyback program. Even though the stock dipped after earnings, these moves are often viewed as bullish signs for long term investors and reinforce Nvidia's critical role in powering the AI buildout.At the same time, the 10 year U.S. Treasury yield nearly touched 4.7% earlier this week before falling back below 4.6% by Friday's close. For investors looking for stability or less market exposure, earning close to 4.7% backed by the U.S. government is becoming an increasingly attractive option. Gold futures also moved lower as investors continue weighing inflation expectations, interest rates, and broader market sentiment.We also discuss Michael Burry's latest warning that the stock market has “jumped the shark,” what that phrase actually means, and why some investors are questioning his repeated bearish calls over the years. Plus, we cover Kevin Warsh stepping in as the new Fed Chair, what history tells us about markets testing new leadership, and why AI may reshape jobs and productivity over the next decade rather than simply replace workers.As always, our goal is to help you cut through the headlines and focus on what actually matters for long term investing.Hosted by James Walters, CIMA®, CRPC®, and Brandon West, CPA, co-owners of West & Walters Tax and Wealth Management, a Registered Investment Advisor (RIA) and tax firm based in Carlsbad, California. Our goal is to share market insights, investing tips, tax strategies, and straightforward financial education to help viewers make smarter financial decisions. All Information is educational in its intent and distribution! Please do not consider this personal financial advice. We believe all clients have unique situations and thus require unique advice.

On episode 465 of Animal Spirits, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Michael Batnick⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ben Carlson⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ discuss: what can stop the stock market, Nvidia is too big, the boy who cried wolf predictions, market timing reminders, Michael Burry crash calls, AI portfolio strategies, AI is the new Netflix, the robots are coming, rich people who aren't happy, Harrison Ford, Martin Short and more. This episode is sponsored by Grayscale and ClearBridge. To learn more, visit https://www.grayscale.com/ Rising geopolitical tensions, continued market uncertainty, stocks backed by can offer more predictable cash flows as volatility increases. Visit https://www.clearbridge.com/ to learn more. Sign up for The Compound newsletter and never miss out: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠thecompoundnews.com/subscribe⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Find complete show notes on our blogs: Ben Carlson's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠A Wealth of Common Sense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Michael Batnick's ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Irrelevant Investor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Feel free to shoot us an email at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠animalspirits@thecompoundnews.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ with any feedback, questions, recommendations, or ideas for future topics of conversation.   Investing involves the risk of loss. This podcast is for informational purposes only and should not be or regarded as personalized investment advice or relied upon for investment decisions. Michael Batnick and Ben Carlson are employees of Ritholtz Wealth Management and may maintain positions in the securities discussed in this video. All opinions expressed by them are solely their own opinion and do not reflect the opinion of Ritholtz Wealth Management. The Compound Media, Incorporated, an affiliate of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ritholtz Wealth Management⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, receives payment from various entities for advertisements in affiliated podcasts, blogs and emails. Inclusion of such advertisements does not constitute or imply endorsement, sponsorship or recommendation thereof, or any affiliation therewith, by the Content Creator or by Ritholtz Wealth Management or any of its employees. For additional advertisement disclaimers see here ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://ritholtzwealth.com/advertising-disclaimers⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Investments in securities involve the risk of loss. Any mention of a particular security and related performance data is not a recommendation to buy or sell that security. The information provided on this website (including any information that may be accessed through this website) is not directed at any investor or category of investors and is provided solely as general information. Obviously nothing on this channel should be considered as personalized financial advice or a solicitation to buy or sell any securities. See our disclosures here: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://ritholtzwealth.com/podcast-youtube-disclosures/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Grayscale Disclosure: Grayscale is the world's largest crypto-focused asset manager based on AUM as of 12/31/2025. For other companies in this category, AUM is considered as of most recent public disclosure. AUM is subject to change. Investing involves risk, including loss of principal. For more information, visit grayscale.com  Learn more about your ad choices. Visit megaphone.fm/adchoices

O "Ulrich Responde" é uma série de vídeos onde respondo perguntas enviadas por membros do canal e seguidores, abordando temas de economia, finanças e investimentos. Oferecemos uma análise profunda, trazendo informações para quem quer entender melhor a economia e tomar decisões financeiras mais informadas.00:00 - Começando mais um Ulrich Responde00:13 – Game over para Flávio Bolsonaro?05:48 – O áudio do Flávio abre espaço para uma 3ª via?07:11 – Lula vai almoçar Zema e Michele nos debates?07:53 – Sábia a atitude de Zema?10:46 – Qual candidato você acha que conseguiria organizar a economia brasileira?11:21 – Com esse episódio do Flávio Bolsonaro, a esperança de derrotar o Lula acabou?12:03 – O mercado já está precificando uma possível derrota de Flávio Bolsonaro?13:07 – Dólar subindo é reação a possível vitória de Lula?13:34 – Por que não devemos gastar todo o nosso tempo acompanhando o noticiário político?17:01 – Visita da delegação americana à China: o que acontece se o "Air Force One" caísse?21:37 – Michael Burry e liquidez: em qual moeda ficar líquido para aproveitar oportunidades?22:33 – O modelo chinês de investimento público em infraestrutura pode ser replicado no Brasil?24:19 – Faz sentido usar a ação Stretch STRC como alocação de caixa para oportunidades?25:36 – Por que não falaram sobre metais do grupo da platina (PGM) com Marcelo Lopez?26:31 – Como o Bitcoin responderia a um eventual crash das ações de tecnologia?27:33 – Como libertário, você acredita que a democracia já falhou?28:04 – Estamos próximos de um novo "Cisne Negro"?28:26 – Visão sobre Inteligência Artificial: futuro caótico ou administrável?30:39 – O que acha de uma carteira composta por Strategy, Stretch e OranjeBTC OBTC3?30:50 – Por que o Euro não consegue se tornar a principal moeda global no lugar do dólar?31:37 – Por que Nasdaq subiu no meio da guerra?33:13 – Qual ativo você está mais exposto?33:15 – Não seria interessante para o Brasil um presidente que não se curva ao imperialismo americano?34:08 – Aeroporto, Bitcoin ou segundo passaporte: qual a melhor saída do Brasil?35:06 – Qual é a Stablecoin mais confiável e transparente atualmente?35:46 – Além de Richard Rytenband, quais mentores e autores impactaram sua trajetória?38:24 – Encerramento e considerações finais.

Today on Stinchfield, we expose one of the biggest financial frauds being pushed on the American people right now: the nonstop doom and gloom about the economy under President Trump. Michael Burry, the man made famous by The Big Short and portrayed as some kind of financial prophet, has spent years warning of collapse after collapse after collapse. The problem? He keeps getting it wrong. America didn’t implode. The markets didn’t permanently crash. And once again, the fear merchants are trying to convince you that disaster is around the corner. But according to Kip Herriage, this negativity campaign is no accident. Herriage says Burry and the financial elites pushing economic panic are part of a broader psyop designed to undermine confidence in President Trump, American capitalism, and the country’s economic resurgence. While the media screams recession, Kip Herriage and VRA Insider are predicting the exact opposite: a generational bull market fueled by Trump’s economic doctrine, exploding innovation, massive liquidity, and America First policies that are reigniting growth. The fear crowd wants Americans scared, cautious, and sitting on the sidelines. But what if this is actually the beginning of one of the greatest wealth creation periods in modern history? See omnystudio.com/listener for privacy information.

Greg and Doug Stokes analyze the recent market surge, IPO frenzy, and the implications of AI and tech stocks. They discuss upcoming IPOs like Cerebris and SpaceX, market bubble concerns, and insights from market experts like Michael Burry and Jeffrey Gunlock. Key Takeaways [00:17] - The AI IPO frenzy has begun [07:27] - Are bubble concerns unwarranted? [09:35] - The prediction charlatans are back View Transcript Links Matt Cerminaro: $100 Billion Companies Would We Be In A Recession Without AI Stocks? Connect with our hosts Doug Stokes Greg Stokes Stokes Family Office Subscribe and stay in touch Apple Podcasts Spotify lagniappe.stokesfamilyoffice.com Disclosure The information in this podcast is educational and general in nature and does not take into consideration the listener's personal circumstances. Therefore, it is not intended to be a substitute for specific, individualized financial, legal, or tax advice. To determine which strategies or investments may be suitable for you, consult the appropriate, qualified professional prior to making a final decision. Different types of investments involve varying degrees of risk. Therefore, it should not be assumed that future performance of any specific investment or investment strategy (including the investments and/or investment strategies referenced in our blogs/podcasts) or any other investment and/or non-investment-related content or services will be profitable, equal any historical performance level(s), be suitable or appropriate for a reader/listener's individual situation, or prove successful. Moreover, no portion of the blog/podcast content should be construed as a substitute for individual advice or services from the financial professional(s) of a reader/listener's choosing, including Stokes Family, LLC, a registered investment adviser with the SEC, with which the blogger/podcasters are affiliated.

On this episode of Simply Money presented by Allworth Financial, Bob and Brian break down why even famous market predictors like Michael Burry shouldn’t drive your investment decisions, how volatility and bad news can actually create opportunity in a diversified portfolio, whether a vacation home is worth it, and smart strategies for handling burnout, large RMDs, real estate complexity, and co-signing risks.See omnystudio.com/listener for privacy information.

En el capítulo 1.113 de este jueves, 14 de mayo, @franaldaya les comenta las operaciones del Banco Central para sostener al dólar en $1.400 y por qué lo hace, los resultados de Galicia con menor cargo por incobrabilidad, y los recortes de precio objetivo a MercadoLibre por parte de Citi, JPMorgan y Goldman Sachs mientras Michael Burry compra más acciones. Además, Mariano Espina con lo último de la política en #RecintosDelPoder.

Money Moves is back as Matty A. and Ryan Breedwell unpack a wild convergence of market signals. The S&P 500 has smashed through the 7,400 mark, locking in the best April in a decade, completely shrugging off geopolitical tensions and historically low consumer sentiment. But not everyone is buying the hype. "Big Short" legend Michael Burry has placed a massive $1 billion short against AI darlings like Palantir and Nvidia. Is a bubble about to burst, or is the AI revolution just getting started?The guys break down why institutional giants like Blackstone are doubling down on AI infrastructure, preview the incoming Fed Chair Kevin Warsh replacing Jerome Powell, and discuss whether a July rate cut is still in the cards. Plus, updates on the 10 million single-family home shortage, surging multifamily vacancies, and why Ryan believes Ethereum's volume will eventually flip Bitcoin.Episode HighlightsMichael Burry's Billion-Dollar Short: Analyzing Burry's massive bets against Nvidia and Palantir, and why Ryan argues the AI sector has real capital and utility backing it up, unlike the 2008 housing crisis.The S&P 500 Melt-Up: Unpacking the market's record-breaking run to 7,400, driven by broad participation beyond just the "Magnificent Seven."Fed Chair Shakeup: Jerome Powell is stepping down May 15th. What Kevin Warsh's Senate confirmation and hawkish history mean for the highly anticipated July rate cut.Geopolitical Chess: Trump is taking Elon Musk and Tim Cook to meet with China's Xi Jinping, while Russia signals a ceasefire in Ukraine.Real Estate Realities: Why the US is short 10 million single-family homes, the impact of 13-18% hard money rates, and Blackstone's $150 billion pivot into data center REITs.Crypto Watch: Bitcoin hovers near $81.7k, but Ethereum's trading volume is rapidly closing the gap.Episode Sponsored By:Discover Financial Millionaire Mindcast Shop: Buy the Rich Life Planner and Get the Wealth-Building Bundle for FREE! Visit: https://shop.millionairemindcast.com/CRE MASTERMIND: Visit myfirst50k.com and submit your application to join!FREE CRE Crash Course: Text “FREE” to 844-447-1555FREE Financial X-Ray: Text  "XRAY" to 844-447-1555IIMAGOS INCOME FUND: Full Investor Presentation: Text “INCOME” to 844-447-1555

Ropa znów podgrzewa rynkowe nastroje, inflacja w USA wraca na pierwszy plan, a obligacje – zwłaszcza brytyjskie – przypominają, że koszt pieniądza wciąż może być najważniejszym tematem dla inwestorów. Michael Burry (ten z „Big Short”) ostrzega przed giełdową euforią, a Wall Street próbuje godzić wysokie wyceny z bardzo mocnym sezonem wyników. W środowy poranek Rafał Bogusławski i Robert Stanilewicz porządkują ten rynkowy miks: bez sensacji, ale konkretnie – co naprawdę ma znaczenie dla inwestorów, funduszy, ETF-ów, obligacji i portfeli długoterminowych. Zapraszamy!!

Ohne Aktien-Zugang ist's schwer? Starte jetzt bei unserem Partner Scalable Capital. Mit eigenem KI-Chatbot, der dir alle Fragen rund ums Investieren beantwortet. Alle weiteren Infos gibt's hier: scalable.capital/oaws. Samsung droht Streik, Micron und SK Hynix profitieren. Monday.com kontert KI-Angst mit KI-Geschäftsmodell. Mosaic überrascht mit Verlust. Circle setzt auf KI-Agenten. Lumentum kommt in Nasdaq-100. Cerebras hebt IPO-Preis an. Delivery Hero: Aspex hält jetzt 15%. MercadoLibre (WKN: A0MYNP) wächst fast 50%, die Aktie fällt trotzdem 30%. Michael Burry sieht eine Riesenchance. Aber Shopee macht Druck in Brasilien und es gibt weitere Risiko-Faktoren. Buy the Dip? Grenke (WKN: A161N3) leidet unter Rekordinsolvenzen in Europa. Die Ausfallrate drückt aufs Ergebnis. Marc Niemann von 3D Invest hat für uns durchgerechnet, wie stark genau das die Zahlen von Grenke drückt. Diesen Podcast vom 12.05.2026, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung. Learn more about your ad choices. Visit megaphone.fm/adchoices

Michael Burry, o investidor da "Grande Aposta", alerta para um crash iminente no mercado em maio de 2026. Com paralelos à bolha de 2000, Burry aponta fragilidades no Nasdaq 100 e altas parabólicas em semicondutores como Intel e AMD. Nesse vídeo vamos exploras os argumentos sobre a euforia atual, a baixa amplitude do S&P 500 e por que apostar contra o mercado pode ser caro.

Your morning briefing. All the news you need to start your day.On today's podcast:(1) Keir Starmer was facing growing pressure to step down as Britain’s prime minister after dozens of members of Parliament, including Cabinet allies, joined the calls for him to set out a timetable for his departure.(2) A Schroders bond-fund manager is steering clear of UK debt on concern that political upheaval will drag yields higher in the coming months.(3) The ceasefire between the US and Iran reached a particularly precarious moment Monday as President Donald Trump said the agreement was on “massive life support” after he rejected Tehran’s latest peace offer.(4) The US sanctioned a dozen entities and individuals over the sale of Iranian oil to China, stepping up economic pressure just days before President Donald Trump meets his counterpart Xi Jinping.(5) Michael Burry, the investor made famous in The Big Short, is warning that the Nasdaq 100 Index is headed toward a dramatic reversal after a “parabolic” surge that has driven technology valuations to unsustainable heights.(6) In the time it usually takes to watch one football match, the Kospi index shed more than $300 billion in value as the gauge slumped on Tuesday. That’s a bit more than $3 billion a minute in the benchmark index alone, and the scale of the slide helped sour sentiment across Asia.(7) On the 13th floor of the Berlaymont building in Brussels, Ursula von der Leyen has built a presidential operation that exerts control over every aspect of what goes on inside the European CommissionPodcast Conversation: What Teens Need From Parents in the Age of AISee omnystudio.com/listener for privacy information.

Heute ist Montag, der 11. Mai und Peter Bloed und Matthias Dworak sprechen über die Warnung vor dem „bloody Car Crash“ an den Märkten von Michael Burry, Chinas schwächelnden Automarkt und wir gehen der Frage nach, wer das erste Sechs-Billionen-Dollar-Unternehmen der Welt werden wird... ------ Ihr habt Fragen, schreibt uns an: missionmoney@focus-money.de Alle wichtigen Links: https://wonderl.ink/@mission_money

Die US-Börsen feiern neue Hochs, doch die Rallye wirkt zunehmend überhitzt. Während Nasdaq und S&P 500 außerhalb ihrer Bollinger-Bänder notieren, warnen Investoren wie Michael Burry vor Parallelen zur Dotcom-Blase. Im Fokus steht der „Trade der Woche“: ein spekulativer Short-Trade auf die stark gestiegene Intel-Aktie. Warum die implizite Volatilität auffällig hoch ist, welche Risiken drohen und weshalb der kleine Optionsverfall die Märkte zusätzlich antreiben könnte – alle Hintergründe jetzt im Podcast.

TEMPRANO: "El verdadero objetivo de Donald Trump no es Irán, es cortar el petróleo a China"Análisis profundo con Miguel Ángel Temprano sobre la escalada de tensión geopolítica y sus repercusiones económicas globales. Temprano explica por qué el conflicto con Irán responde a una estrategia de Estados Unidos para frenar el suministro energético a China y cómo el gigante asiático se ha blindado acaparando reservas comerciales. Analizamos el comportamiento del petróleo, el disparo en los costes del transporte marítimo a través del Baltic Dry Index y la comparativa con la crisis de las dotcom tras las advertencias de Michael Burry. Una visión imprescindible sobre el futuro de Trump ante las elecciones y la estabilidad de los mercados.#trump #iran #china #petroleo #geopolitica #inflacion #mercados #economia #crisis #michaelburry #negociostv #entrevista Si quieres entrar en la Academia de Negocios TV, este es el enlace:   https://www.youtube.com/channel/UCwd8Byi93KbnsYmCcKLExvQ/join Síguenos en directo ➡️ https://bit.ly/2Ts9V3pSuscríbete a nuestro canal: https://bit.ly/3jsMzp2Suscríbete a nuestro segundo canal, másnegocios: https://n9.cl/4dca4Visita Negocios TV https://bit.ly/2Ts9V3pMás vídeos de Negocios TV: https://youtube.com/@NegociosTVSíguenos en Telegram: https://t.me/negociostvSíguenos en Instagram: https://bit.ly/3oytWndTwitter: https://bit.ly/3jz6LptFacebook: https://bit.ly/3e3kIuy

11/5 Trump rifiuta la controproposta iraniana: “totalmente inaccettabile”. Nethanyau: la guerra non è finita, l'uranio va rimosso. Corre il Brent oltre 105$. Scorte petrolio: minimi dal 2018. Jet fuel europeo ai minimi da sei anni. Diesel Usa sui massimi, Wright pronti a sospendere imposte. Hormuz: passa una nave del Qatar che trasporta Gnl. Altri attacchi di droni alle navi. Futures misti: salgono dollaro e rendimento Treasury, Bitcoin sopra 80.000. Settimana nel segno di trimestrali e dati macro (inflazione, PPI, vendite detttafglio). Fed, venerdì ultimo giorno di Powell (che rimane nel board) per Pimco e Franklin Templeton dovrà alzare i tassi. Corsa inarrestabile dei chip: performance e analisi. L'Inizio di un nuovo super-ciclo? Michael Burry: bolla come durante le dot.com. Cerebras il competitor di Nvidia prepara Ipo: forchetta sale a 150-160$ vista domanda. Aspettando Trump e Xi: le quattro “T” sul tavolo: Trade, Teheran, Technolgy, Taiwan. Per l'Economist è il G2 del sospetto.  YouTube  *** Questo episodio è offerto da Scalable Capital   Investire comporta rischi  Interesse p.a. lordo variabile su liquidità illimitata. Condizioni e distribuzione della liquidità su scalable.capital/conto-deposito-non-vincolato*** Asia mista, Nikkei e Hang Seng in rosso. Kospi +4% di nuovo da record con nuovi massimi di SK Hynix e Samsung, In Cina sale l' Inflazione ad aprile +1,2% sopra attese; Prezzi produzione +2,8%. Import petrolio scende del 20% rispetto mese precedente. Oggi Bessent in Giappone: azione coordinata sullo Yen? PBOC fixing Yuan ai massimi da tre anni In Europa futures in verde. Focus su dati macro (inflazione), attesa per le parole di Lagarde. Bce, De Guindos: intervento Germania su Unicredit - Commerzbank contro spirito mercato unico. Armani verso vendita tripartita del 15% a L'Oreal, LVMH e EssilorLuxottica. Focus su: Delfin, Intesa SP, Diasorin, Tenaris, automotive.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Sponsored by Count — a tool we recommend for better financial tracking and clarity Learn more: https://www.getcount.com/us/partners/SoundFinancialGroup Why do financial influencers keep predicting the next big market crash—and why do people keep listening? In this episode of More Than Commas, we break down the real incentive behind repeated crash predictions, how attention drives extreme forecasts, and why being "right once" can be more profitable than being consistently accurate. Then, in a completely unexpected turn, we follow through on a wild real-life experiment involving a Cybertruck and a boat ramp—highlighting how reality doesn't always go as planned. -- Timestamps: 00:00 – Financial influencers + Cybertruck teaser 00:11 – Why influencers benefit from predicting crashes 00:30 – Example: Kiyosaki and Michael Burry notoriety 01:51 – Cybertruck story setup near boat ramp 03:06 – Self-driving mistake near the lake #Cybertruck #investing #stockmarket #financialeducation #wealthbuilding #longterminvesting  Next Episode: Robert Kiyosaki changed how millions think about money—but what happens when the message shifts? We take a closer look at his evolution, his repeated market crash predictions, and what investors can learn from separating valuable principles from fear-driven narratives. -- This Material is Intended for General Public Use. By providing this material, we are not undertaking to provide investment advice for any specific individual or situation, or to otherwise act in a fiduciary capacity. Please contact one of our financial professionals for guidance and information specific to your individual situation. Sound Financial Inc. dba Sound Financial Group is a registered investment adviser. Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. Investments involve risk and, unless otherwise stated, are not guaranteed. Be sure to first consult with a qualified financial adviser and/or tax professional before implementing any strategy discussed herein. Past performance is not indicative of future performance. Insurance products and services are offered and sold through Sound Financial Inc. dba Sound Financial Group and individually licensed and appointed agents in all appropriate jurisdictions. This podcast is meant for general informational purposes and is not to be construed as tax, legal, or investment advice. You should consult a financial professional regarding your individual situation. Guest speakers are not affiliated with Sound Financial Inc. dba Sound Financial Group unless otherwise stated, and their opinions are their own. Opinions, estimates, forecasts, and statements of financial market trends are based on current market conditions and are subject to change without notice. Past performance is not a guarantee of future results.

Michael Burry: Gã "Điên" Đặt Cược Chống Lại Phố Wall | SonyKieu | Thế GiớiVideo này được chuyển thể từ bài viết gốc trên nền tảng mạng xã hội chia sẻ tri thức Spiderum

Welcome to Omni Talk's Retail Daily Minute, sponsored by Duvo and Mirakl.In today's Retail Daily Minute, Omni Talk's Chris Walton discusses:Doris Fisher, co-founder of Gap Inc., passes away at 94, leaving behind a legacy that reshaped American retail from a single San Francisco storefront selling Levi's jeans into a multi-brand empire spanning Gap, Banana Republic, and Old Navy.Victoria's Secret faces a proxy battle from second-largest shareholder BBRC International's Brett Blundy, who is targeting two long-serving board members and demanding accountability for the struggling $591 million Adore Me acquisition.Michael Burry announces he has fully exited his GameStop position after the company made a $56 billion bid to acquire eBay, citing concerns about the debt load such a deal would require.The Retail Daily Minute has been rocketing up the Feedspot charts, so stay informed with Omni Talk's Retail Daily Minute, your source for the latest and most important retail insights.

Vous savez ce qui s'est passé le 10 mars 2000 ? Le Nasdaq touchait son sommet historique avant de PERDRE 80% en trois ans. Mais ne vous inquiétez pas : cette fois, c'est différent. (Si, si, on vous l'a dit.) Aujourd'hui dans le MorningBull, on fait le point sur le bull market le plus dingue de ces 1'000 dernières années — et on essaie de comprendre si Wall Street est devenu un casino, une religion ou juste une partie de Monopoly où la banque a pété un câble. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Topman Alex Karp van Palantir houdt met hart en ziel van de oorlog die Trump in het Midden-Oosten heeft ontketend. Zijn bedrijf is hofleverancier van software aan het Pentagon, en scoort dus enorme inkomsten ermee. In de Verenigde Staten verdubbelde de omzet zelfs. En volgens Karp zit er nog veel meer in het vat. Die defensie-industrie moet de kern van Palantir worden. En hij voorspelt dat die omzetgroei nog lang zal aanhouden. Maar toch geloven beleggers hem niet en vluchten ze, weg van het aandeel. Waarom? Dat zoeken we in deze aflevering voor je uit. Verder hebben we het ook over luchtigere zaken. We kijken naar de blijdschap onder beleggers van bierbrouwer AB InBev. Het merk achter Stella Artois (het lekkerste pils ter wereld), Corona en Budweiser ziet dat hun bier vooral aanslaat in landen als Brazilië en Zuid-Afrika. Maar, ironisch genoeg, zit de grootste groei juist in alles dat minder met bier te maken heeft. Moet de brouwer zich in de toekomst dan maar op Radler en cocktails in blik gaan focussen? Je hoort ook nog over alweer een rechtszaak met Elon Musk. Of ja, hij weet eronderuit te komen. Dan doelen we op de zaak rondom de overname van Twitter. Musk zou de prijs van het aandeel beïnvloed hebben voorafgaand aan die overname. Maar hij hoeft daar nu maar een fractie van de mogelijke boete voor te betalen. We vertellen je ook nog over Apple, dat ervoor zorgt dat de koers van chipmaker Intel alweer een enorme zet krijgt. En over PayPal, waar beleggers juist minder blij worden. En dat allemaal door één enkele misser bij de kwartaalcijfers. Te gast: Robbert Manders van het Antaurus Europe Fund BNR Beurs is een journalistiek onafhankelijke productie, mede mogelijk gemaakt door Saxo. Over de makers: Jelle Maasbach is presentator van BNR Beurs en freelance financieel journalist. Zijn favoriete aandeel om over te praten is Disney, maar daar lijkt hij de enige in te zijn. Sinds de eerste uitzending van BNR Beurs is 'ie er bij. Maxim van Mil is presentator van BNR Beurs en journalist bij BNR, waar hij zich focust op de financiële markten en ontwikkelingen in de tech-wereld. Je krijgt hem het meest enthousiast als hij kan praten over ASML, of oer-Hollandse bedrijven zoals Ahold of ABN Amro. Jorik Simonides is presentator van BNR Beurs, economieredacteur en verslaggever bij BNR. Hij wordt er vooral blij van als het een keer níet over AI gaat. Milou Brand is presentator van BNR Beurs, freelance podcastmaker en columnist bij het Financieele Dagblad. Jochem Visser is presentator van BNR Beurs, maakt Beursnerd XL en is redacteur bij de podcast Onder Curatoren. Vraag hem naar obscure zaken op financiële markten en hij vertelt je waarom het eigenlijk nóg leuker is dan je al dacht. Over de podcast: Met BNR Beurs ga je altijd voorbereid de nieuwe beursdag in. We praten je in een kleine 25 minuten bij over alle laatste ontwikkelingen op de handelsvloer. We blijven niet alleen bij de AEX of Wall Street, maar vertellen je ook waar nog meer kansen liggen. En we houden het niet bij de cijfers, maar zoeken ook iedere dag voor je naar duiding van scherpe gasten en experts. Of je nu een ervaren belegger bent of net begint met je eerste stappen op de beurs, de podcast biedt waardevolle inzichten voor je beleggingsstrategie. Door de focus op zowel de korte termijn als de lange termijn, helpt BNR Beurs luisteraars om de ruis van de markt te scheiden van de essentie. Van Musk tot Microsoft en van Ahold tot ASML. Wij vertellen je wat beleggers bezighoudt, wie de markten in beweging zet en wat dat betekent voor jouw beleggingsportefeuille.See omnystudio.com/listener for privacy information.

Today's top stories, with context, in just 15 minutes. On today's podcast: 1) President Trump said the US will help ships stranded in the Persian Gulf transit the Strait of Hormuz, describing it as a “humanitarian gesture” and testing his ability to restore traffic through the strategic waterway for the first time since the war with Iran began. The operation, dubbed Project Freedom, was set to begin on Monday with the US military pledging to provide support, including the use of guided-missile destroyers, aircraft and drones. “The Ship movement is merely meant to free up people, companies, and Countries that have done absolutely nothing wrong — They are victims of circumstance,” Trump wrote late Sunday in a social media post. “If, in any way, this Humanitarian process is interfered with, that interference will, unfortunately, have to be dealt with forcefully.” The plan has left shipping executives perplexed, with few details provided by the president. Iran’s military, after Trump’s announcement, said US forces would be attacked if they entered the Strait of Hormuz, according to a statement carried by Iranian broadcaster Press TV. 2) Transportation Secretary Sean Duffy said he doesn’t think the US government needs to provide financial lifelines for now to other low-cost carriers, following the collapse of Spirit Aviation Holdings Inc. “At this point, I don’t think it’s necessary,” he said during a press conference Saturday at Newark Liberty International Airport. “They do have access to cash.” Duffy spoke hours after Spirit ceased operations, leaving passengers and employees stranded across the US. Earlier in the day, he announced measures to support those passengers, saying several carriers including United Airlines Holdings Inc., Delta Air Lines Inc., Southwest Airlines Co., American Airlines Group Inc. and JetBlue Airways Corp. agreed to cap prices or reduce fares for customers impacted by the shutdown. 3) GameStop Corp. is proposing to buy eBay Inc. for about $56 billion in cash and stock, a bold attempt by Ryan Cohen to take over a storied e-commerce name several times larger. The gaming retail chain offered $125 per share in cash and stock for the online marketplace, or about a 20% premium to its Friday close. GameStop, which built a roughly 5% stake in eBay, said it’s secured an initial, non-binding “highly confident letter” from TD Bank to provide about $20 billion of debt financing. In a memo to investors Sunday, Cohen’s company pledged to find some $2 billion of annual savings within 12 months of closing. The takeover bid follows the surprising ascent of GameStop, a chain of video game outlets that shrank its brick-and-mortar footprint after gamers increasingly bought software in digital stores. In 2021, it became the center of a retail-investor frenzy. Michael Burry, the Scion Asset Management head who rose to prominence after a winning wager against mortgages ahead of the 2008 financial crisis, helped fuel GameStop’s rally by taking a bullish stance on the firm around 2019.See omnystudio.com/listener for privacy information.

開盤前30分鐘，08:30 - 09:00 讓我們一起解讀財經時事 。 參加財經皓角總經訂閱： 新友會員 https://jackalopelin.com 老友會員 https://yutinghao.finance 我的粉絲專頁 https://reurl.cc/n563rd 網站參加會員手冊 https://reurl.cc/rvvqAr 如有疑問，歡迎來信 jackieyutw@gmail.com """"" ♥️ 打賞網址 ：https://p.ecpay.com.tw/B83478D """"" (不提供退款服務) 《早晨財經速解讀》是游庭皓的個人知識節目，針對財經時事做最新解讀，開播於2019年7月15日，每日開盤前半小時準時直播。議題從總體經濟、產業動態到投資哲學，信息量飽滿，為你顛覆直覺，清理投資誤區，用更寬廣的角度帶你一窺投資的奧秘。 免責聲明：《游庭皓的財經皓角》頻道為學習型頻道，僅用於教育與娛樂目的，無任何證券之買賣建議。任何形式的投資皆涉及風險，投資者需進行自己的研究，持盈保泰。

Dan Nathan and Guy Adami discuss major tech themes and trades, focusing on dispersion in mega-cap tech and the recent underperformance and rebounds of the “Mag 7.” They examine Microsoft's AI positioning and Azure deceleration amid ongoing capacity and power constraints, contrasted with rivals (AWS, Oracle, GCP) picking up demand tied to OpenAI. The conversation highlights Michael Burry's view that software-stock declines have been amplified by software credit stress and may be overextended, with Oracle as a key example given its steep drawdown and elevated CDS. They also cover Apple's AI strategy, reliance on Gemini, WWDC expectations to improve Siri, and key technical levels amid headline sensitivity. Finally, they assess Intel's sharp rally tied to a reworked CHIPS deal and Nvidia involvement, and preview Netflix earnings with a mixed technical setup and potential upside. Show Notes Trading Post Monday April 13th (Cassandra Unchained) Top of the Morning (Axios) —FOLLOW USYouTube: @RiskReversalMediaInstagram: @riskreversalmediaTwitter: @RiskReversalLinkedIn: RiskReversal Media

Friday roundup. Here's everything that mattered this week.NIO unveiled the ES9 — physically larger than a Rolls Royce Cullinan and projected to carry NIO's highest SUV gross margin. Pre-orders from outside NIO's existing community are already running 1.5x the ES8's pre-sale pace. We break down what it means for the business.ALSO THIS WEEK:— Inflation worst reading in 2 years — gas up $1+/gallon since US-Iran conflict began— 3,200 ships idle in the Strait of Hormuz— S&P 500 recovering war losses as ceasefire talks progress— Someone threw a Molotov cocktail at Sam Altman's house— Michael Burry posted and deleted — Palantir dropped anyway— Chinese NEV exports up 124% YoY in Q1 — Tesla China exports up 164%— Can NIO actually become the next BMW, Benz or Audi? The honest answer from the Chinese press— US crackdown on China academic collaboration — what it means for the tech warCourtside Financial. Hosted by Obi.Nord Security Products:NordVPN: ⁠https://go.nordvpn.net/aff_c?offer_id=15&aff_id=143053&url_id=902⁠NordPass: ⁠https://go.nordpass.io/aff_c?offer_id=488&aff_id=143053&url_id=9356⁠Discord: https://discord.gg/GSbp4wR

Este episodio recoge la charla del webinar emitido en directo el 25 de marzo con Fernan2 y Theveritas. Son dos inversores con enfoques muy distintos y me lo pasé muy bien en la charla, con muchos momentos divertidos. Nacho, desde su blog "Definitivamente quizá", disecciona los ciclos económicos, los excesos de los bancos centrales y sus inversiones personales. Fernando, desde su blog "Inversión, especulación y cosas mías", lleva más de 20 años educando y explicando sus inversiones con transparencia. Ambos han sido invitados míos del podcast en los episodio 4, 72, 81 y 87.La sesión cubre tres grandes bloques. En el primero, Nacho y Fernando repasan sus decisiones de inversión en el último año. Nacho explica su enfoque de ciclos y por qué mantiene un 90% en liquidez esperando el momento adecuado mientras Fernando defiende que estar fuera del mercado durante las subidas es el mayor riesgo para un inversor.En el segundo bloque entra la psicología inversora: el coste de oportunidad de la inversión activa frente a la gestión pasiva, la exuberancia irracional de los mercados, la importancia del pensamiento crítico y el peligro del FOMO. También debatimos sobre demografía, deuda, la tesis de abundancia sostenible de Elon Musk y los paralelismos con la burbuja puntocom. En el tercer bloque analizamos sus carteras en el Desafío Rankia 2026, la mecánica del primer rebalanceo mensual, la función de los equipos y feedback sobre la plataforma MyPortfolio.Este episodio está patrocinado por TaxDown. Si quieres hacer bien la declaración de la renta, te permiten hacerlo incluyendo deducciones autonómicas que ni sabías que existían. Si tienes inversiones se pueden conectar con tu bróker y calcular automáticamente tus plusvalías. Son Colaboradores Sociales de la Agencia Tributaria por lo que tu declaración se puede presentar directamente desde su plataforma con toda la seguridad.TEMAS0:00:00 – Introducción0:03:00 – Ciclos y gestión de la liquidez (Theveritas)0:05:40 – Arbitraje de OPAs y corto plazo (Grifols, Macro)0:11:23 – Renta fija: Oportunidades en bonos y subordinadas (Fernan2)0:16:10 – Tesis en Novo Nordisk, Semapa y Libertas 70:18:15 – Salida de BMW, Apple y Repsol0:20:10 – Psicología: Inversión activa como pasión vs. coste de oportunidad0:26:52 – Cartera actual de Theveritas0:28:12 – Exuberancia irracional y comprar a precios de derribo0:30:25 – Michael Burry, cortos y burbuja de IA0:36:30 – La importancia del pensamiento crítico para invertir0:41:00 – Cuándo usar la liquidez: El ruido mediático0:43:00 – Cartera actual de Fernan20:48:40 – El FOMO en las inversiones0:53:40 – Demografía, deuda y nuevos paradigmas0:55:05 – Abundancia sostenible, IA y burbuja puntocom1:03:20 – Sectores a evitar y gestión emocional1:13:30 – Desafío Rankia 2026: estrategia de carteras creadas1:27:53 – Reglas del Desafío: Rebalanceo mensual 1:31:07 – Equipos en el Desafío Más info con enlaces a contenidos comentados en mi blog en Rankia:www.rankia.com/blog/such/7276795-116-como-invierten-fernan2-theveritas-carteras-reales-apuestas-desafio-rankia

Fresh off raising a monster $15B, Marc Andreessen has lived through multiple computing platform shifts firsthand, from Mosaic and Netscape to cofounding A16z. In this episode, Marc joins swyx and Alessio in a16z's legendary Sand Hill Road office to argue that AI is not just another hype cycle, but the payoff of an “80-year overnight success”: from neural nets and expert systems to transformers, reasoning models, coding, agents, and recursive self-improvement. He lays out why he thinks this moment is different, why AI is finally escaping the old boom-bust pattern, and why the real bottleneck may be less about models than about the messy institutions, incentives, and social systems that struggle to absorb technological change.This episode was a dream come true for us, and many thanks to Erik Torenberg for the assist in setting this up. Full episode on YouTube!We discuss:* Marc's long view on AI: from the 1980s AI boom and expert systems to AlexNet, transformers, and why he sees today's moment as the culmination of decades of compounding technical progress* Why “this time is different”: the jump from LLMs to reasoning, coding, agents, and recursive self-improvement, and why Marc thinks these breakthroughs make AI real in a way prior cycles were not* AI winters vs. “80-year overnight success”: why the field repeatedly swings between utopianism and doom, and why Marc thinks the underlying researchers were mostly right even when the timelines were wrong* Scaling laws, Moore's Law, and what to build: why he believes AI scaling laws will continue, why the outside world is messier than lab purists assume, and how startups can still create durable value on top of rapidly improving models* The dot-com crash and AI infrastructure risk: Marc's comparison between today's AI capex boom and the fiber/data-center overbuild of 2000, plus why he thinks this cycle is different because the buyers are huge cash-rich incumbents and demand is already here* Why old NVIDIA chips may be getting more valuable: the pace of software progress, chronic capacity shortages, and the idea that even current models are “sandbagged” by supply constraints* Open source, edge inference, and the chip bottleneck: why Marc thinks local models, Apple Silicon, privacy, trust, and economics all point toward a major role for edge AI* American vs. Chinese open source AI: DeepSeek as a “gift to the world,” why open models matter not just because they're free but because they teach the world how things work, and how open source strategies may shift as the market consolidates* Why Pi and OpenClaw matter so much: Marc's claim that the combination of LLM + shell + filesystem + markdown + cron loop is one of the biggest software architecture breakthroughs in decades* Agents as the new “Unix”: how agent state living in files allows portability across models and runtimes, and why self-modifying agents that can extend themselves may redefine what software even is* The future of coding and programming languages: why Marc thinks software becomes abundant, why bots may translate freely across languages, and why “programming language” itself may stop being a salient concept* Browsers, protocols, and human readability: lessons from Mosaic and the web, why text protocols and “view source” mattered, and how similar principles may shape AI-native systems* Real-world OpenClaw use: health dashboards, sleep monitoring, smart homes, rewriting firmware on robot dogs, and why the most aggressive users are discovering both the power and danger of agents first* Proof of human vs. proof of bot: why Marc thinks the internet's bot problem is now unsolvable via detection alone, and why biometric + cryptographic proof of human becomes necessaryTimestamps* 00:00 Marc on AI's “80-Year Overnight Success”* 00:01 A Quick Message From swyx* 01:44 Inside a16z With Marc Andreessen* 02:13 The Truth About a16z's AI Pivot* 03:29 Why This AI Boom Is Not Like 2016* 06:33 Marc on AI Winters, Hype Cycles, and What's Different Now* 10:09 Reasoning, Coding, Agents, and the New AI Breakthroughs* 12:13 What Founders Should Build as Models Keep Improving* 16:33 AI Capex, GPU Shortages, and the Dot-Com Crash Analogy* 24:54 Open Source AI, Edge Inference, and Why It Matters* 33:03 Why OpenClaw and PI Could Change Software Forever* 41:37 Agents, the End of Interfaces, and Software for Bots* 46:47 Do Programming Languages Even Have a Future?* 54:19 AI Agents Need Money: Payments, Crypto, and Stablecoins* 56:59 Proof of Human, Internet Bots, and the Drone Problem* 01:06:12 AI, Management, and the Return of Founder-Led Companies* 01:12:23 Why the Real Economy May Resist AI Longer Than Expected* 01:15:53 Closing ThoughtsTranscriptMarc: Something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic. Having said that, I think what's actually happened is an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years where that was controversial. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right?Which is like, it's an overnight success ‘cause it's like bam, you know, chat GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.If I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough.swyx: Before we get into today's episode, I just have a small message for listeners. Thank you. We will not be able to bring you the ai, engineering, science, and entertainment contents that you so clearly want if you didn't choose to also click in and tune into our content.We've been approached by sponsors on an almost daily basis, but fortunately enough of you actually subscribed to us to keep all this sustainable without ads, and we wanna keep it that way. But I just have one favor to ask all of you. The single, most powerful, completely free thing you can do is to click that subscribe button.It's the only thing I'll ever ask of you, and it means absolutely everything to me and my team that works so hard to bring the in space to you each and every week. If you do it, I promise you will never stop working to make the show even better. Now, let's get into it.Alessio: Hey everyone, welcome to the Lidian Space Pockets. This is CIO, founder Kernel Labs, and I'm joined by s Swix, editor of Lidian Space.swyx: Hello. And we're in a 16 Z with a, uh, mark G and welcome.Marc: Yes, yes. A and what, half of 16? Something like that. A one. Exactly,swyx: exactly. Uh, apparently this is the, the final few days in your, your current office.You're moving across the road.Marc: Uh, we're, yeah. We have a, we have some, we have some projects underway, but yeah, this is actually, oh, this is the original. We're in actually the original office. We're in the, we're in the, we're, we're in the whole thing.swyx: It's beautiful. Yeah. Great.Marc: Thank you.swyx: So I have to come out, uh, this is a, you know, I wanted to pick a spicy start in October, 2022.I just made friends with Roone and, uh, I wanted to give him something to sort of be spicy about. And I said, uh. Uh, it'll never not be funny. The A 16 Z was constantly going. The future is where the smart people choose to spend their time and then going deep into crypto and not in ai. And that was in October 22nd, 2022.And Ruen says there was an internal meeting in a 16 Z to reorient around Gen ai. Obviously you have, but was there a meeting? What, what was that?Marc: I mean, I don't, look, I've been doing AI since the late eighties.swyx: Yeah.Marc: So I, I don't know, like all that, as far as I'm concerned, this stuff is all Johnny cum lately.Yeah. You, I mean, look, we've been doing ar entire existence. I mean, we've been doing AI machine learning deep, you know, deeply. We've been doing this stuff way from the beginning. Obviously a AI is just core to computer science. I, I, I actually view them as like quite, uh, quite continuous. Um, you know, Ben and I both have computer science degrees.Um, you know, we, we both, Ben, Ben and I actually both are world enough to remember the actual AI boom in the 1980s. Yeah. There was like a, there was a big AI boom at the time. Um, and there was a, was names like expert systems. Um, and they of like lisp and lisp machines. Uh, I, I coded in lisp. I was coding a lisp in 1989.When that was the, the language of the AI future. Um, yeah. So this is something that we're like completely, you completely comfortable with. I've been doing the whole time and are very enthusiastic aboutswyx: is there a strong, like this time is different because, uh, my closest analog was 20 16 17. It was an AI boom.Mm-hmm. And it petered out very, very quickly. Um, we, it just, it just in terms of investingMarc: sort of, sort of,swyx: yeah. Investment, investment excitement.Marc: Although that's really when the, the, the Nvidia phenomenon really, it was, I would say it was in that period when it was very clear that at, at the time it, the vocabulary was more machine learning, but it, it was very clear at that time that machine learning was hitting some sort of takeoff point.Alessio: Yeah.Marc: Well, and as you guys, you guys have talked about this at length on, on your thing, but, you know, if you really track what happened, I think the real story is, it was, it was the Alex net, uh, basically breakthrough in like 2013. That was the, that was the real knee in the curve. Um, and then it was obviously the transformer breakthrough in 17.Alessio: Yeah.Marc: Um, and then everything that followed. But, but, you know, look, machine learning, you know, there were, you know, look, uh, I mean look, I've been working, you know, I've been working with, uh, one of my, you know, kind of projects working with Facebook since 2004. Um, and on the board since 2007, and of course, you know, they, they started using machine learning very early, um, and, you know, have used it basically, you know, for like 20 years for, you know, content, you know, feed optimization and advertising optimization.And obviously many, you know, financial services. You know, many, many, many companies, many different sectors have been doing this. And so it's like one of these things, it's like, it's not a, it's not a single thing. Like it's, it's like, it's like layers, right? Yeah. Um, and, and the layers arrive at different paces and, but they kind of build up.swyx: Yeah.Marc: Uh, they kind of build up over time and then, and then, yeah. And then look, in retrospect, it was 2017 was kind of the, you know, the key, the key point with the trans transformer and then. And then as you guys know, there was this really weird like four year period where it's like the, the transformer existed and then it was just like,swyx: let's go.Yeah.Marc: Well, but, but it was just, but, but between 2020, but between 2017 and 2021, I mean, that was the era of which like companies like Google had internal chat Botts, but they weren't letting anybody use them.swyx: Yeah.Marc: Right. And then, you know, and then OpenAI developed Chat GT or GPT two, and then they told everybody, this is way too dangerous to deploy.Right. Yeah. You know, we can't possibly let normal people, normal people use this thing. And then you, you guys, I'm sure remember AI Dungeon, um mm-hmm. So the o for, there was like a year where like the only way for a normal person to use GP T three was in, in AI dungeon.Alessio: Yeah.Marc: And so you, you, we would do this, you'd go in there and you'd pretend to play Dungeons and Dragons.In reality, you're just trying to talk to talk to GPT. And so there was this, you know, there was this long, you know, and I, you know, the big, big companies, you know, big companies are cautious and, you know, the big companies were cautious. It, it, by the way, it took open ai. You know, they, they, they talk about this, it took open AI time to actually adjust, you know, kind of re redirect their researchswyx: path.I, I think, uh, let say Rosewood, right? Uh, the, the dinner that founded OpenAI was right there.Marc: Right, right. But that, that dinner would've taken place in 20swyx: 18Marc: 19. The formation of OpenAI Uhhuh as late as 2018.swyx: Uh, uh, sorry. Uh, no, I'm, I'm, I'm, I'm wrong. Probably It should be 20. Yeah. They just celebrated a 10 year anniversary, so it it is 2025.Yeah, so, so 2015?Marc: Yeah. 2015. Yeah. 2015. But then, uh, um, Alec Radford did G PT one in what, probablyswyx: mm-hmm. 17, 18,Marc: yeah. 17, 18. So it, yeah. For, and then, and then they didn't really, and then GPT three was what? 2020? 2020.swyx: 2020.Marc: Because that became copilot immediately. Even open ai, which has been, you know, the leader of, of this thing in the last decade, you know, e even they had to adapt and, and, and lean into the new thing.And so. Um, yeah, I, I think it's just this process of basically sort of wave after wave layer after layer, you know, building on itself. And then you kind of get these catalytic moments where, where the whole thing pops and, and obviously that's what's happening now.swyx: Is it useful to think about will there be any ai, winter?‘cause there's always these patterns. Like, is this, in the summer is something I constantly think about because do I get, do I just like. Just get endlessly hyped and just trust that I will only be early and never wrong or right. Well, are we, will there be a winter?Marc: So there's something about, say the following.There's something about AI that has led to this repeated pattern. Um, and, and, and you guys know this,swyx: it's summer, winter, summer,Marc: winter, summer, winter, summer, winter. And it goes back 80 years. Yeah. 80 years. Uh, so the original neural network paper was 1943. Right. Which is, which is amazing. Uh, that it was, it was far back that long.And then there was you, if you guys have ever talked about this on your show, but there was this, uh, there was a big, uh, there was an a GI conference at Dartmouth University in 1950. 55. 55, yeah. And they got a NSF grant to, uh, for the, all the AI experts at the time to spend the summer together. And they figured if they had 10 weeks together, they could get a GI, uh, at the other end.And they got their, by the way, they got the grant, they got the 10 weeks and then, you know, 1955, you know. No, no. A GI. And like I said, I, I lived through the eighties version of this where there was a big, a big boom and a crash. And so, so there is this thing, and there, there is something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic.Um, and, and it's probably on both sides of like the, the, the boom bus cycle. You, you kind of see that play out. Having said that, I think what's actually happened is like just, and you know, and we now know in retrospect like an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years or that was controversial. And, and we now know that that's the case. And so we, we now, you know, everything we're building on today just sort of derives from the original idea in 1943. And so, so in retrospect, we, we now know that like, these, these guys are right.They, they, you know, they would get the timing wrong and they thought, you know, capabilities would arrive faster, or they were, it could be turned into businesses sooner or whatever, but like, they were fundamentally, the, the scientists who worked on this over the course of decades were fundamentally correct about what they were doing.And, and the, and the payoff from, from, from all their work is happening now. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right? Which is like, it's an overnight success.‘cause it's like bam, you know, chat, GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.Um, and thinking, and look, there were AI researchers who spent their entire lives. They got their PhD. They, they worked for, they've researched for 40 years. They retired in a lot of cases, they passed away and they never actually saw it work.swyx: Yeah. It's all sad.Marc: It is. It is sad. It's sad. Knewswyx: Jeff Hinton was like the last guy.Marc: Yeah. Yeah. Well, there were the guys, uh, was a guy, Alan Newell. I mean, there's tons of John McCarthy. You know, John McCarthy was like one of the inventors in the field. He's one of the guys who organized the Dartmouth Conference and you know, he taught at Stanford for 40 years. Wow. And passed, you know, passed away, I don't know, whatever, 10, 10 years ago or something.Never, never actually go. Got to see it happen. But like, it is amazing in retrospect, like, these guys were incredibly smart and they worked really hard and they were correct. So anyway, so then it's like, okay, you know, say history doesn't repeat, but it rhymes. It's like, okay, does that mean that there's gonna be another, like, you know, basically boom buzz cycle.And I, I will tell you, like, let, like in a sense, like yes, everything goes through cycles and, you know, people get overly enthusiastic and overly depressed and there's, there's a time, there's a timelessness to that. Having said that, there's just no question. Um, so the form, the foremost dangerous words in investing this time are, this time is different.Do you know the 12 most dangerous words investing? No. The four most d foremost dangerous words in investing are this time is different. Yeah. Um, the 12 most dangerous words. And so like, I'll tell you what's different. Like now it's working like, like there's just no, I mean, look, there's just no question.And by the way, I, I'll just give you guys my take. Like L LLMs, like from, from basically the Chad G PT moment through to spring of 25. I think you could still, I think well intention, well, and of. Form skeptics could still say, oh, this is just pattern completion. And oh, these things don't really understand what they're doing.And you know, the hall hallucination rates are way too high. And, you know, this is gonna be great for creative writing and creating, you know, Shakespeare and so sonnets and, you know, as, as rap lyrics or whatever, like, it's gonna be great and all that stuff, but we're not gonna be able to harness this to make this relevant in, you know, coding or in medicine or in law or in, you know, you know, kind of feels that, you know, kind of really, really matter.And I think basically it was the reasoning breakthrough. It, it was oh one and then R one that basically answered that question basically said, oh no, we're gonna be able to actually turn this into something that's gonna work in the real world. And, and then obviously the coding breakthrough over the, over basically the coding breakthrough that kind of catalyzed over the holiday break was kind of the third step in that.Mm-hmm. Where you're just like, alright, if, if, you know, if Linus Tova is saying that the AI coding is no better than he is like. Like, that's, that's never happened before. That's theswyx: benchmark.Marc: Yeah. That's never happened before. And so now we know that it's, it's gonna sweep through coding and, and then, and then we, we know, you know, we know that if it's gonna work in coding, it's gonna work in everything else.Right. It's just then, because that's, that's like, that's like, that's like the hardest in many ways. That's the hardest example. And how everything else is gonna be a, a derivative of that. And then on top of that, we just got the agent breakthrough, you know, with Open Claw, which is fantastic. Which is amazing and incredibly powerful.And then we just got the, the, um, the auto research, uh, you know, the, the self-improvement. You know, we're now into the self-improvement breakthrough. And so the, so the way I think about it is we've had four fundamental breakthroughs in functionality, l OMS reasoning, uh, agents, um, and then, uh, and, and then now RSI, um, and, and they're all actually working.Um, and so I'm, I'm just, as you like, you can tell I'm jumping outta my shoes. Like, like this is, like this is it like this, this is the culmination of 80 years worth of worth of work, and this is the time it's becoming real.Alessio: Yeah.Marc: I, I'm completely convinced.Alessio: I think the anxiety that people feel is like during the transistor era, yet Mors law, and it's like, all right, we understand why these things are getting better.We understand the physics of it. Yeah. With ai, it's. It's so jagged in like the jumps where like, like you said, it's like in three months you have like this huge jump like, and people are like, well this can keep happening. Right? But then it keeps happening,Marc: it'll keep happening.Alessio: And so like how do you think about also timelines of like what's we're building?I think we always have this question with guests, which is like, you know, should you spend time building harness for a model versus like the next model just gonna do it one shot in the lead space. Right. And how does that inform, like how you think about the shape of the technology? You know, you talk about how it's a new computing platform.If you have a computing platform, then like every six months it like drastically changes in what it looks like. It's hard to build companies on top of it.Marc: Yeah. So, so a couple things. So one is like, look, the, the Moore's law was what we now call a scaling law. Like Moore's Law was a scaling law and for your younger viewers, more Moore's Law was every chip chip chips either get twice as powerful or twice as cheap every, every 18 months.And that, and that and that, you know, that it's gotten more complicated in the last few years. But like that, that was like the 50 year trajectory of, of, of the computer industry. And then, and then by the way, and that's what took the mainframe computer from a $25 million current dollar thing into, you know, the phone in your pocket being, you know, a million times more powerful than that.Like that, you know, for, for 500 bucks. And so that, that was a scaling law. And then, and then, and then key to any scaling law, including Moore's Law and the AI scaling laws is, you know, they're not really laws, right? They're, they're, they're, they're predictions, but when they work, they become self-fulfilling predictions because they, they, they, they, they set a benchmark and, and then the entire industry, right?All the smart people in the industry kind of work to make sure that, that, that actually happens. And so they, they kind of motivate the breakthroughs that are required to, to keep that going. And, and in and in chips, that was a 50 year, that was a 50 year run. Right. And it, it was amazing. And it's still happening in, in some areas of, of chips.I think the same thing is happening with the, the core scaling laws. The core scaling laws. In, in, in ai, you know, they're, they're not really laws, but like they, they are basically. There are predictions and then they're motivating catalysts for the research work that is required to be. And, and, and, and by the way, also the investment, uh, dollars, um, uh, you know, required to basically keep, you know, keep the curves going and, and look, it, it is, it's gonna be complicated and it's gonna be variable and they're, you know, there're gonna be walls that are gonna look like they're fast approaching, and then they're gonna be, you know, engineers are gonna get to work and they're gonna figure out a way to punch through the walls.And obviously that's, you know, that's been happening a lot, you know, and then look, there's gonna be times when it looks like the walls have, you know, the, the, the laws have petered out and then they're gonna, they're gonna pick up again and surge and then, and then, and then it, it appears what's happening to the eyes is there's not multiple, you know, multiple scaling laws.Um, there's multiple areas of improvement. And, and I think, you know, I don't know how many more there are already yet to be discovered, but there are probably some more that we don't know about yet. You know, they, like, for example, there's probably some scaling law around, um, world models and robotics that we don't fully understand, you know, kind of acquisition of data at scale in the real world that we don't fully understand yet.So that, that, that one will probably kick in at some point here. There's a bunch of really smart people working on that. Um, and so, yeah, I, I think the expectation is that, that, you know, the, the scaling laws generally are gonna continue. Yeah. The, the pace of improvement will continue to move really fast.Um. To your question on like what to build. So, uh, I'm a complete believer the scaling laws are gonna continue. I'm a complete believer the capabilities are gonna keep getting amazing, um, you know, leaps and bounds. Uh, the part where I kind of part ways a little bit with how, what I would describe as the AI purists, um, you know, which is, which I would characterize as like the people who are.In many ways, the smartest people in the field, but also the people who spend their entire life, like at a lab, um, and have, have, I would say, have very little experience in the outside world. Um, the, the, the nuance I would offer is the outside world of 8 billion people and institutions and governments and companies and economic systems and social systems is really complicated.Um, and, um, and doesn't, you know, it it 8 billion people making collective decisions on planet Earth is not a simple process of like, just like you see this happening now. It's like a bunch of AI CEOs have this thing, which is just like, well, there's just this, they just all have this kind of thing when they talk in public where they're just like, well, there's these, these obvious set of things that so society to do.Alessio: Mm-hmm.Marc: And then they're like, society's not doing any of those things. Right. And it's like, how can society not, you know, what, whatever their theory is, how can society not see x, y, Z? Mm-hmm. And the answer is, well, society is number one. There's no single society, it's like 8 billion people. And they like all have a voice, and they all have a vote, like at the end of the day of how they, they react to change.And then, you know, it just like, it's just human reality is just really complicated and messy. Um, and, and, and so the specific answer to your question is like, as usual, it depends. Um, you know, it, it depends. Look, pe there's no question people are gonna, like, there's no question they're gonna be companies.It's already happening. There are companies that think that they're building value on top of the models and then they're just gonna get blissed by the, by the next model. There's no question that's happening. But I think there's no question also that just the process of adaptation of any technology into the real and into the real messy world of humanity is, is just going to be messy and complicated.It's, it's not going to be simple and straightforward. It's gonna be messy and complicated. And there are gonna be a lot of companies and a lot of products, um, uh, and in, in fact entire industries that are gonna get built to, to, to basically actually help all of this technology actually reach real people.Alessio: The amount of capital going into these companies, I mean, Dario talked about it on the Door Cash podcast and Door Cash was like, why don't you just buy 10 x more GPUs? And he is like, because I'm gonna go bankrupt if the model doesn't exactly hit the, the performance level. How do you think about that?Also as a risk on, you know, you guys are investors, open AI and thinking machines and world apps. It seems like we're leveraging the scaling loss at a pretty high rate, right? Like how comfortable, I guess, do you feel with the downside scenario, like, and say like things Peter out, you think you can kind of like restructure uh, these build outs and uh, you know, capital investments.Marc: Yeah. So should start by saying, so I live through the.com crash, um, and I can tell you stories for hours about the.com crash and it was horrible. No, it was awful. It was, it was, it was apocalyptic by the way. The, a lot of the.com crash was actually at the time, it was actually a telecom crash. It was a bandwidth crash.Like the, the thing that actually crashed, that wiped out all the money with the tele, the telecom companies.swyx: GlobalMarc: crossing. Global, global, yeah.swyx: I'm from Singapore and they, they laid so much cable o over over our oceans.Marc: Actually there was a scaling law in the.com. Era. And it was literally the, the US Commerce Department put out a report in 1996 and they said internet traffic was doubling every quarter.Um, and, and actually in 1995 and 1996, internet traffic actually did double every quarter. And so that became the scaling law. And so what all these telecom entrepreneurs did was they went out and they raised money to build fiber, anticipating that the demand for bandwidth is gonna keep doubling every quarter.Doubling every quarter though is like, you know, grains of chess and the chessboard, like at some point the numbers become extremely large. Right. And, and, and it really, and really what happened was the internet. The internet by the way, continuously kept growing basically since inception. And it's, you know, it's, it's continuously grown.It's never shrunk. And it's grown really fast compared to anything else. Mm-hmm. You know, in, in, in human history. But it wasn't doubling every quarter as of 19 98, 19 99. And so there was this gap in the expectation of what they thought was a scaling law versus reality. And that's actually what caused the.com crash, which was the, it they, they way over companies like global crossing way overbuilt fiber, which is sort of the, and by the way, fiber, telecom equipment, you know, so all the, all the networking gear, you know, and then, and then by the way, the actual physical data centers, like that was the beginning of the, of the, of the data center build and then, and the data center overbuild.And so you had that, but it was, it was literally, I think it was like $2 trillion got wiped out, right? It was like Jesus, it was like a big, it was. And by the way, the other, the other subtlety in it was the internet companies themselves never really had any debt. ‘cause tech, tech companies generally don't run on debt, but the telecom companies run on debt.Physical infrastructure companies run on debt. And so the companies like Global Crossing not just raise a lot of equity, they also raise a lot of debt. So they're highly levered. And so then you just do the thing. It's just like, okay, you have a highly levered thing where you're, you're just over, you're overbuilding capacity.Demand is growing, but not as fast as you hoped. And then boom, bankrupt. Right. And, and then it, and then it's like they say about the hotel industry, which is, it's always the third owner of a hotel that makes money. It has to go bankrupt twice, right? You have to wash out all of the over optimistic exuberance before it gets to actually a stable state.And then it makes money. So by the way, all of those data centers and all of those, all the fiber that they're in use, it's all in use today. Yeah. But 25 years later. But it, it, it took, and actually the elapsed time was, it took 15 years. It took 15 years from 2000 to 2015 to actually fill, fill up all that capacity.The cautionary warning is the, the overbuild can happen. Um, and, and, and, and, you know, you, you get into this thing where basically everybody, everybody who basically has any sort of institutional capital, it's like, wow. It's just, I, I don't know how to invest in these crazy software things. For sure I can put build data centers and for sure I can buy GPUs that I can deploy, you know, compute grids and, and all these things.Um, and so, you know, if you're a pessimist, you could look at this and you could say, wow, this is like really set up to be able to basically replicate, you know, what we went through, what we went through in 2000. Obviously that would be bad. The counter argument, which is the one I I agree with, which is the counter on, on the other side is a couple things.One is the companies that are investing all the, the companies that are investing the money are like the bluest chip of companies. And so back, back, back in the, in the do, like Global Crossing was like a, it was like an entrepreneur. It was like a, a new venture, but like the money that's being deployed now at scale is Microsoft, and, you know, and Amazon and Google, Facebook and Facebook and Nvidia and, you know, these, these, these, and, and now you know, by the way, open ai philanthropic, which are now at like, you know, really serious size, um, you know, as companies with, you know, very serious revenue.These are very large scale companies with like, lots, lots of cash, lots of debt capacity that they've, they've never used. And so th this is institutional in a way that, that really wasn't at the time. And then the other is, at least for now, every dollar that's being put into anything that results in a running GPU is being turned into revenue right away.Like so, and you guys know this, like everybody's starved for capacity, everybody's starved for compute capacity and then, you know, all the associated things, memory and, and, and interconnected and everything else. Um, data center space. And so e every dollar right now that's being put into the ground is turning into revenue.And, and it, and in fact, I actually think there's an interesting thing happening, which is because everybody starve for capacity, the models that we actually have that we can use today are inferior versions of what we would have if not for the supply constraints. That's true. Um, if Right pose a hypothetical universe in which GPUs were 10 times cheaper and 10 times more plentiful mm-hmm.The models would be much better. ‘cause you would just allocate a lot more money to training and you'd just build better models and they would be better. Um, and so we're, we're actually getting the sandbag version of the technology.swyx: Yeah. No. Everything we use is quantized because the, the labs have to keep the, the full versions,Marc: right?swyx: LikeMarc: we're not even getting the good stuff.swyx: Yeah.Marc: But, but getting the good stuff, it's, it's just, even if technical progress stops. Once there's like a much bigger build of like GPU manufacturing capacity and memory, you know, all, all the things that have to happen in the course of the next five or 10 years.Once it happens, even the current technology is gonna get, gonna get much better. And then as you know, like there's just like a million ways to use this stuff. Like there's just like a million use cases for this. Mm-hmm. Like, it, it, you know, this isn't just sending packets across a, a thing, whatever, and hoping that people find something to do with it.This is just like, oh, we apply intelligence into every domain of human activity. And then it works like incredibly well. Yeah. Um. Here's what I know, here's what I know. Um, in the next three or four year, it's like somewhere between three or four years out, basically everything is selling out. So like the, the entire supply chain is, is, is, is sold out or, or, or selling out.And so there, there's no, like, we're just gonna have like chronic supply shortage for, you know, for years to come. Um, there's going to be a response from the market that's gonna result in an enormous, you know, it's happening now. An enormous flood of investment in a new fab capacity and ev you know, every, everything else to be able to do that, at some point the supply chain constraints will unlock, you know, at least to some degree that will be another accelerant to industry growth when that happens.‘cause the products will get better and everything will get cheaper. Um, and so, so I know that's gonna happen. I know that, you know, the deployments, you know, the, the actual use cases are like really compelling. And then, like I said, you know, with reasoning and agents and so forth, like, I know they're just gonna get like much, much better from here.And so I, I, I know the capabilities are like really real and serious. I also know that the technical progress is not going to stop. It. It, it is excel. It is, is accelerating. Like the, the breakthroughs are are tremendous. I mean, even just month over month, the breakthroughs are really dramatic. And so, you know, I think if you were a cynic and there, there are cynics, you can look at 2000, you can find echoes.But I can't even imagine betting it that this is gonna like somehow disappoint and, you know, at least for years to come, I think it would be essentially suicidal to make that bet. Yeah. Um, it was that Michael Burry, uh, uh, that'sswyx: anMarc: interesting guy, huh? We'll pick on a guy. We'll pick, let's pick on one guy.We'll pick. Well ‘cause he did, he he came out with, it was, it was the, heswyx: doesn't mind.Marc: It was the Nvidia short. Right. He came with the Nvidia short. And then if you guys probably talked about this, which is the, the analysis now that like the current models are getting better faster at such a rate that if you are running an Nvidia, if you're running an Nvidia inference chip today, that's three years old, you're making more money on it today than you did three years ago because the pace of improvement of the software is, is faster than the, the, the depreciation cycle, the chip.And then my understanding is Google is running. I don't if they've, I don't know exactly what, uh, these are rumors that I've heard or maybe it's public, but, um, I think Google's running very old TPUs, very profitably. Ference. Yeah. And very profit and very profitably. Yeah. Um, and so, so it actually turns out, as far as I can tell, it's actually the opposite of the Beery thesis is actually.He was actually 180 degrees wrong. It's actually the, the, the, the old Nvidia chips are getting more valuable, which is something that's like literally never happened before. Like it's never been the case that you have an older model chip that becomes more valuable, not less valuable. And that, and again, that's an expression of the just ferocious pace of software progress.Ferocious pace of capability payoff. Yeah. Uh, that you're getting on the other side of this. And so I just, the idea of betting against that, like.swyx: Yeah. Yeah. Well, one ofMarc: my, it seems like an invitation to get your face ripped up.swyx: One of my early hits was like modeling the lifespan of the H 100 and h two hundreds and, and going like, you know, usually they advise like four to seven years and it was, you know, maybe you sort of realistically haircut cut it down to two to three.Yeah. But actually it's going up and not down. Yeah. And, and uh, that's, I mean that's, I think that's the dream. Uh, we are finding utilization and I think utilization solves all problems. Like, you can, you can find use, use cases for even like the poor, like even memory, we're having a shortage. Right. And, and even like the, the shittier versions of, of memory that we do have, we are finding use cases for it.So like That's great.Marc: Yeah.Alessio: How, how important is open source AI and kinda like edge inference in a world in which you have three years of supply crunch. Like, do you think in the, like, you know, if you fast forward like five years, like how do you think about inference, uh, in the data center versus at the edge?Marc: Well, so just to start, yeah. So I think, I think open source is very important for a bunch of reasons. I think edge, edge inference is very important for a bunch of reasons. I, I think just practically speaking, if we're just gonna have fundamental construc, supply crunches for the next, I mean, you, you guys know if you just project forward demand over the next three years, right?Yeah. Relative to supply, one of the, its main predictions you can do is what's gonna, what, what's gonna happen to the cost of, of inference in the core, uh, over the next three years? And like, it may rise dramatically, right? Like, so, so what is, and then is, is, you know, like the, the, the big model competition are subsidizing heavily right now.Right? Right. And so, so what's the, what will be the average person's, you know, per day, per month token cost, you know, three years from now to do all the things that they want to do. And I, I don't know, it's gonna. I mean, I have, you guys probably have friends, I have friends today who are paying a thousand dollars a day for open claw, for claw tokens to run open claw.Right? And so, okay. $30,000 a month. Right? And, and by the way, those, those friends have like a thousand more ideas of the things that they want their claw to do, right? Yeah. And so you, you could imagine there, there's like latent demand of up to, I don't know, five or $10,000 a day of, of, of tokens for a fully deployed, you know, per personal agent.Uh, and obviously consumers can't pay that, right? And so, so, but it gives you a sense of the fu of the fu of the future scope of demand, right? And so, so even, even if there's a 10 x improvement in price performance, that still, you know, goes to a hundred dollars a day, which is still way beyond what people can pay.Mm-hmm. So there's just gonna be like. Ferocious to me, by the way. The agent thing, the other interesting thing is I think the agent thing, so up until now, a lot of the constraints of GGPU constraints, I think the agent thing now also translates into CPU constraints. Mm-hmm. Right?swyx: CPU memory.Marc: Yes. CPU memory, right?And so, like the entire chip ecosystem is just gonna get wait,swyx: wait for network constraints, that that will be the killer.Marc: It's all bottleneck potentially for years. And so, so I, I think that Brad, and, and I think it's actually possible, I mean, generally inference costs are gonna keep coming down, but I think the, let's put it this way, the rate of decline, I think may level out here for a bit because of these supply constraints.And then at some point, maybe the lab stops subsidizing so much and that, that, that again, will be, be an issue. And so there's just gonna be so much more demand for inference than, than can be satisfied. Um, you know, kind of with the centralized model. And then, and then, you know, you guys know this, but like all the, just the dramatic, I mean just the dramatic innovations that have happened in the Apple silicon to be able to do, uh, inferences, it's quite amazing the level of effort being put.Like the open source guys are putting incredible effort into getting, you know, this recurring pattern where the big model will never run on a pc, and then six months later mm-hmm. Oh, it runs in a pc, right? It's like amazing. And there's very smart people working on that. So there's all that. And then look, there's also, you know.There's also like other, there's other motivators. There's other motivators which is just like, okay, how much trust are the big centralized model providers? You know, how much trust are they building in the market versus, you know, how much are, you know, at least for, in certain cases with some people, for certain use cases, people being like, well, I'm not willing to just like, turn everything over.So there, there, there's all the trust issues. Um, by the way, there's also just like straight up price optimization. There's many uses of AI where you don't need Einstein in the cloud. You just need like a, a a, a smart local model. There's also performance issues where you want, you know, you want, you know, you're gonna want your doorknob to have an AI model in it.Right. You know, to be able to, you know, do, um, you know, to be able to do access control. Um, obviously like everything with a chip is gonna have an AI model in it. Mm-hmm. And it, a lot of those are gonna be local. Um, and so, yeah. No, like I think, I think you're gonna have ti and then you're gonna, by the way, also wearable devices, you know, you don't wanna do a complete round trip.You want, you know, you, whatever your smart devices are, you want it to be like super low latency. Yeah.swyx: The question, do we care who makes it? Yeah. One of the biggest news this week was the collapse of AI two, the Allen Institute. Mm-hmm. One of the actual American open source model labs. Yeah. Um, and, uh, I'm not that optimistic on, on American open source.Yeah. Like you, you guys invested in MIS trial and MIS trial's doing extremely well outside of China. That's about it.Marc: Yeah. We'll see. We'll see. I look, I, number one, I do think we care. Uh, I do think we, I do think we care who makes it. Um, I would say this, the, the, the, the previous presidential administration wanted to kill it in the us Oh yeah.They wanted to drown in the bathtub. Um, and so they wanted to kill it. So at least we have a government now that actually like, actually wants it wants it to happen. And youswyx: earned to councilMarc: and Yeah. And the new and the P pcast. Yeah. So the, the, you know, this admin for whatever other political issues people have, which are many, you know, this administration has, I think a very enlightened view and in particular an enlightened view on AI and in particular on open source ai.Uh, and so they're very supportive. Um, my read is the Chi. The Chinese have a very, the various Chinese companies have a very specific reason to do open source, which is, they, they, they don't fundamentally, they don't think they can sell commercial, uh, AI outside of China right now. And or at least specifically not, not in the US for a combination of reasons.And so they, they kind of view, I think, open source AI as a bit of a loss leader against basically domestic, uh, you know, paid, paid services. And then kind of an, you know, kind of an ancillary products. You know, they're, they're very excited about it, by the way. I think it's great. I think it's great that they're doing it.Um, you know, I think Deeps seek was like a gift to the world. Um, I think. The great thing about open source, open source, the, the, the impact of open source is felt two ways. One is you, you get the software for free, but the other is you get to learn how it works, right? And so like the paper, the paper, the paper and, and the code, right?And the code. And so, like, for example, I thought this was amazing. So open comes out with L one and it's an amazing technical breakthrough, and it's just like, absolutely fantastic. But of course they don't explain how it works in detail. And then of course they hide the, they hide the reasoning traces, right?And, and then, and then, and then everybody's like, okay, this is great, but like, who's gonna be able to replicate this? Are other people gonna be able to do this? You know, is their secret sauce in there? And then our one comes out and it's just like, there's the code and there's the paper, and now the whole world knows how to do it.And then, you know, three months later, every other AI model is, is adding reasoning. And so, so you get this kind of double, like even if the Chinese models themselves are not the models that get used, the education that's taken place to the rest of the world, the information diffusion, you know, is incredibly powerful.So that happens and then, I don't know. We'll, we'll see. You know, there are a bunch of American, you know, open source, you know, ai, uh, model companies. I mean, look, there's gonna be tremendous, you know, there already is. There's, you know, there's gonna be tre there's tremendous competition, uh, among the primary model companies.You know, there's, depending on how you count, there's like four or five, you know, big co model companies now that are, you know, kind of neck and neck, uh, in different ways. Um, uh, you know, and, and, and, um, you know, and then obviously Bo Bo both X and then MetAware involved are, you know, both have huge, you know, huge attempts to, you know, kind of, to kind of leapfrog underway.And then you've got, you know, a whole fleet of startups, new companies, including a whole bunch that we're backing, that are, you know, trying to come out with different approaches. And then you've got whatever it is. I don't know how, how many, how many, like main line foundation model companies are there in China at this point?It's probably six. It'sswyx: five Tigers is what they call it. Yeah. Uh, Quinn is in questionable because there's change in leadership,Marc: right?swyx: Yeah.Marc: But that, does that include, that includes like Moonshot,swyx: yes. Can deep seek, uh, uh, ZI, um, Quinn oh one is in there.Marc: Right. And then, um, and by dance and, and then you see,swyx: ance would be like the next tier ance.They weren't as prominent. They weren't, didn't haveMarc: a leading. Yeah. But they, you at least, you know, ance is very inspiring and presumably they have more stuff coming and Tencent probably has more stuff coming and, and so forth. And so, so, so like, look, here, here would be a thing you can anticipate, which is there are not these markets, there are not going to be between the US and China right now, there's like a dozen primary foundation model companies that are like at scale, at, at some level of a critical mass.It's not gonna be a dozen in three years, right? Like, it just because these industries don't bear a dozen, it's, it's gonna be three or you know, there's gonna be three or four big winners or maybe one or two big winners. And so there's gonna be like a whole bunch of those guys that are gonna have to figure out alternate strategies.Um, and I think like open source is one of those strategies. And so I, I think you could see like a whole, i, I, I think the questions like, who's gonna do open source? I think that could change really fast. I, I think that, that, that's a very dynamic thing. I think it's very hard to predict what happens. And, and I think it's very important.swyx: NVIDIA's doing a lot.Marc: Well, I was gonna say. Well, exactly. And then you're got Nvidia and then, and then, you know, just to, again, indu, there's an old thing in business strategy, which is called, uh, commoditize Compliments. Commoditize the compliment. That's right. And so if your Jensen is just kind of obvious, of course, you wanna commoditize the software.Yeah. And he's, and to his enormous credit, he's putting enormous resources behind that. And so maybe it, maybe it's literally Nvidia and I think that would be great.Alessio: Yeah. Uh, narrative violation to European projects, uh, in the, uh, damn.swyx: I'm hosting my, uh, Europe, uh, conference soon. And I got both of them.Alessio: They got us.They got us. MarkMarc: finished. They got us, us. Well, wait a minute. Where was Peter? So where was Steinberger when he did? In AustriaAlessio: was, yeah, yeah, yeah.Marc: He was in what? He was in Vienna. Oh, he was in Vienna. And then where is he now?swyx: Uh, he's moving to sf.Marc: Okay. Okay. Alright. Okay, there we go. And then, yeah, the PI guy, right?The PI guys are European.swyx: Yeah, they're also, they're buddies inAlessio: Australia. Mario's also there. Yeah.Marc: Right. And are they, yeah, they haven't announced yet. Any sort of change changed or have theyAlessio: No, they're, they have a company there.Marc: Okay. Got, okay. Good.Alessio: Good, good,good.Alessio: Um,Marc: yeah, good.swyx: Anyways, I think pie and open cloud very important software things and, and I just wanted you to just go off on what you think.Marc: Yeah. So I think in co the, the combination of the two of them I think is one of the 10 most important softwares. Openswyx: Claw got all the attention, but Right. Talk about pie,Marc: pi pie's, kind of the Yeah. PI's, PI's kind of the architectural breakthrough for those of us who are older. There was this whole thing that was very important in the world of software basically from like 1970 to, I don't know, it still is very important, but like 19, from 1973 to like basically the creation of Linux, which is basically this, this thing used to call like the Unix mindset.Like so, so, ‘cause there were all these different, you know, theories. There are all these different operating systems and mainframes and, and then you know, all these windows and Mac and all these things. And then there was this, but kind of behind it all was this idea of kind of the Unix mindset. And the Unix mindset was this thing where basically you don't have these, like, like in the old days, like, like the operating system that like made the computer industry really work, like in the 1960s mm-hmm.Was this thing called o os 360, which was this big operating system that IBM developed that was supposed to basically run everything. And it was this like giant monolithic architecture in the sky. It was like a, you know, it was like a giant castle. Um, of software. And, and by the way, it worked really well and they were very successful with it.But like, it was this huge castle in the sky, but it was this thing, it was almost unapproachable, which is like, you had to be kind of inside IBM or very close to IBM. And you had to really understand every aspect, how the system worked. And then the, the Unix sky is originally out of at and t and then out out of Berkeley, um, you know, came out and they said, no, let's have a completely different architecture.And the way architecture's gonna work is we're gonna have, we're gonna have a, a prompt and, and a, and a shell. And then, and then we're gonna, all, all the functionality is gonna be in the form of these discreet modules, and then you're gonna be able to chain the modules together. Mm-hmm. Yeah. And so like the, the, the op, it's almost like the operating, operating system itself is gonna be a programming language.Um, and then that led led to the, the, the sort of centrality of the shell. Um, and then that led to sort of, uh, you know, basically chaining together Unix tools. And then that led to the emergence of these, these scripting languages like Pearl, where you, you could basically kind of very easily do this, and then the shells got more sophisticated and then, and then, and then look like, you know, that, that, that number one, that worked and that, that was the world I grew up in.Like I was, I was a Unix guy. You know, sort of from, call it 1988 to, you know, kind of all, all the way through my work and it worked really well. It, it's in the background, um, you know, nor normal people don't need to, didn't need to necessarily know about it, but like, if you were doing like system architecture, application development, you, you, you knew all about it.Um, and then, you know, it's been in the background ever since. And, you know, look, your Mac still has a Unix shell, you know, kind of in there, and your iPhone still has a Unix shell kind of buried in there somewhere. So they're kind of in there. And then, you know, the Windows shell is kind of a, you know, sort of a weird derivative of that.But, um, you know, but look, the inter, the internet runs on Unix, um, and that smartphones, actually, both iOS and Android are Unix derivatives. And so, you know, kind of Unix did end up winning. But, but anyway, and then we just started taking that for granted. And then, and then so, so basically the, the way I think about what happened with Pie and then with Open Claw is basically what those guys figured out is, I always say the, the great breakthroughs are obvious in retrospect, right?Which is the best kind, the best kind. They weren't obvious at the time or somebody else would've done them already. Um, and so there is a, like a real conceptual leap, but then you look at it sort of the backwards looking and you're just like, oh, of course. Mm-hmm. Like the, the, to me those are always the best breakthroughs.Well, actually language models themselves are like that. It's just like, oh, next token completion. Oh, of course.swyx: Yeah. What other objective mattered?Marc: Yeah, exactly. But, but like it, right. But she's even saying it wasn't obvious until somebody actually did it. Right. And so the conceptual breakthrough is real and deep and powerful and, and very important.And so the way I think about pie and olaw is it's basically marrying the, the language model mindset to the un to the Unix, basically shell prompt mindset. And so it's, it's basically this idea that what, what, so what is an agent, right? And as, as, and as you know, like many smart people who have been trying to figure out what an agent is for, for, for decades, and they've had many architectures to build agents and the whole thing.And it turns out what is an agent. So it turns out what we now know is an agent is the following. It's, so it's a language model. And then above that, it's a ba, it's a bash shell. Um, so it's a, it's a Unix shell, and then it's, and then the agent has access, uh, has access to, to the shell. And, you know, hopeful, hopefully in a sandbox, maybe in, maybe in a sandbox.So it's, it's the model. Um, it's the shell. Um, and then it's a fi, it's a file system. Um, and then the state is stored in files. And then, you know, there's the markdown format for the, you know, for, for the files themselves. And then, and then there's basically what in Unix is called Aron job. There's a loop and then there's a heartbeat for the, there's heartbeat and, and the thing basically Wake Wakes up.Wakes up. So it's basically LLM plus shell, plus file system, plus markdown, plus kron. And it turns out that's an agent. And, and, and every part of that, other than the model is something that we already completely know and understand. And in fact, it turns out that like the latent power of the Unix shell is like extraordinary because basically like all, like, there's just like an, there's just enormous latent power in the shell.There's enormous numbers of Unix commands, there's enormous number of command line interfaces into all kinds of things already in the, you know, your entire, I mean your entire, just to start with, your computer runs on a shell. If you're running a Mac or a, or, or a phone, your computer, your computer's running on a shell, uh, already.And so like the full power of your computer is available at the command line level. Um, and then it turns out it's really easy to expose other functions as a command line interface. And so like this whole idea where we need like MCP and these like product mm-hmm. Fancy protocols, whatever, it's like, no, we don't, we just need like a command, command line thing.So that's the architecture. And then it turns out what is your agent? Your agent has a bunch of files starting a file system. And then there's the thing that just like completely blew my mind when I write my head around it as a result of this, which is like, okay. This means your agent is now actually independent of the model that it's running on.Because you can actually swap out a different LLM underneath your agent and your, your agent will change personality somewhat. ‘cause the model is different, but all of the state stored in the files will be retained.swyx: Yeah. Different instruction set, but you just compiledit.Marc: Right, exactly. And it's all right.It's like right. Swapping out a ship and recompiling, but it's, it's still, it's still your agent with all of its memories. Um, and with all of its capabilities. And then by the way, you can also swap out the shell, uh, so you can move it to a different execution environment that is also, is also a b shell, by the way, you can also switch out the file system, right.Uh, and you can, and you can, and you can swap out the, the, the heartbeat for the, the crown framework, the, the loop that the agent framework itself. And so your agent basically is ba basically at the end of the day, it's just. It's just, its files. Um, and then, and then there's of course it a openswyx: call.Marc: Yeah, it's, it's basically, it's, it's just the files.Um, and then by the way, as a consequence of that, the agent and then the agent itself, it turns out a couple important things. So one is it, it's, it, it can migrate itself, right? And so you're, you can instruct your agent, migrate yourself to a different, uh, runtime environment, migrate yourself to a different file system, migrate yourself to a different, you know, swap out the language model.Your agent will do all that stuff for you. And then there's the final thing, which is just amazing, which is the agent is the agent actually has full introspection. It actually, it actually knows about its own files and it could rewrite its own files. Right. Which by the way, is basically no widely deployed software system in history where the, the, the thing that you're using actually has full introspective knowledge of how it itself works and is able to modify itself.Like that, that, I mean, there have been toy systems that have had that, but there, there's never been a widely deployed system that has that capability and then that leads you to the capability. That just like completely blew my mind when I wrap my head around it, which is you can tell the agent to add new functions and features to itself and it can do that.Extend yourself. Yeah. Right? Extend, extend yourself. Like extend yourself. Give yourself a new capability. Right? And so, and so literally it's just like you run into somebody at a party and they're like, oh, I have my open claw, do whatever, connect to my eat, sleep bed, and it gives me better advice and sleep.And you go home at night and you tell your claw, or if they're at the party, by the way, you tell your claw, oh, add this capability to yourself. And your claw will say, oh, okay, no problem. And it'll go out on the internet and it'll figure out whatever it needs and then it'll go out to claw code or whatever.It'll write whatever it needs. And then the next thing you know, it has this new capability. And so you don't even have to, like, you can have it upgrade itself without even having to, without having to do anything other than tell it that you want it to do that. And so anyway, so the, the combination of all this is just, I mean, this is just like a massive, incredible, I mean, it's just incredible.Like if I, if I were, if I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough. Yeah. And again, pe people are gonna look at it and they already get this response. People are gonna look at it and they're gonna say, oh, well, where's the breakthrough?‘cause these, the, all of these components were already known before. Mm-hmm. But, but this is the key, the key to the breakthrough was by using all these components that were known before, you get all of the underlying capability of that's buried in there. And so all, and so for example, computer use all of a sudden just kind of falls, trivi, trivial.Of course it's gonna be able to use your computer. It has full access to the shell. Right. And then, and then you just, you, you give it access to a browser, and then you've got the computer and the browser and, and often away it goes. And, and then you've got all the abilities of the browser also. Um, yeah.And so, and so the capability unlock here is profound. My friends who are, you know, deepest into this, are having their claw do like a, like, literally like a thousand things in their lives. They have new ideas every day. They're just like constantly throwing new challenges at the thing. And by the way, it's early and, you know, these are, you know, these are prototypes and there are, you know, as you guys know, there's security issues.Yeah. And, and so, you know, there's a bunch of stuff to be ironed out, but the, the unlock of capability is just incredible.swyx: Yeah.Marc: And I, I have absolutely no doubt that everybody in the world is gonna, is gonna have at least, you know, an agent like this, if not an entire family of agents. And w

Die Inflation in der Euro-Zone ist im März weniger stark gestiegen als befürchtet. Verbraucher und Notenbanker müssen sich aber auf weiter steigende Preise einstellen. Außerdem: Wetten auf fallende Kurse sind gerade beliebt – aber nicht ungefährlich.

With everything going on these days it seems like we should be seeing headlines about the market crashing and yet...here we are, just a few points off the all time highs. What gives? This week we're breaking down the reasons why we aren't tanking just yet, including an in-depth look at Michael Burry's latest blog post outlining what he believes will be the catalysts for a major market crash. NEW MERCH OUT! Get 10% off when you sign up and also get bonus content, ad-free versions and more plus your first 7 days free at https://benandemilshow.com ***THE SOUTHWEST COMPANION PASS IS BACK GET IT HERE: https://www.cardratings.com/bestcards/featured-credit-cards?src=691608&shnq=520080,4028088,4048122,4028085,3006151,4048149,4028089,4048084&var2= The newest acid video is out now so check it out! https://youtu.be/7vkFY3f5kkw WATCH THE LATEST EPISODE OF EMIL'S NEW SHOW! https://www.youtube.com/watch?v=PHG9iIjhXvI Give this video a thumbs up if you enjoyed it! And please leave us a comment! It helps us! ***Ben's new movies and tv podcast with Dillon is OUT NOW! GO WATCH the latest episode on our TOP MOVIES OF 2025: https://youtu.be/tbC-cMqcby8?si=tO0NK0PmpN2187ir **CHECK OUT EMIL'S LIVESTREAMS HERE: https://www.youtube.com/emilderosa __ SOME OTHER VIDEOS YOU MAY ENJOY: That's Cringe of Cody Ko: https://youtu.be/dTbEk0pVh2w Our AUSTIN VIDEO: https://youtu.be/yGSs56bFzRU Our episode with Kyla Scanlon: https://youtu.be/cIHWkY35cuc Big Tech is out of ideas (ft. ED ZITRON): https://youtu.be/zBvVGHZBpMw Arguing with a millionaire (ft. Chris Camillo): https://youtu.be/1ZUWTkWV_MM We bought suits HERE: https://youtu.be/_cM1XqA9n2U ***LINK TO OUR DISCORD: https://discord.gg/CjujBt8g ***Subscribe to Emil's Substack: https://substack.com/@emilderosa ***Trade with Ben at https://tradertreehouse.com __ GLD: New customers get 50% off with code BAES at https://gld.com. #ad FABRIC: Join the thousands of parents who trust Fabric to help protect their family—apply today in just minutes at https://meetfabric.com/BAES FACTOR: Head to https://factormeals.com/baes50off and use code baes50off to get 50% off and free breakfast for a year—offer valid for new customers with qualifying subscription purchase. __ Follow us on instagram! @ benandemilshow @ bencahn @ emilderosa Learn more about your ad choices. Visit podcastchoices.com/adchoices

The Investing Power Hour is live-streamed every Thursday on the Chit Chat Stocks Podcast YouTube channel at 5:00 PM EST. This week we discussed:(00:00) Introduction(01:17) Anthropic's Revenue Surge(07:13) Insider Buying(13:18) Berkshire Hathaway's Stock(23:05) Real Brokerage Earnings Review(30:15) Small Cap of the Week(39:58) Wix's Financial Engineering and Growth(44:57) The Future of E-commerce Stocks(51:52) Michael Burry and Adobe(57:00) Appreciating Capital Losses*****************************************************Subscribe to Emerging Moats Research: emergingmoats.com *********************************************************************Chit Chat Stocks is presented by Interactive Brokers. Get professional pricing, global access, and premier technology with the best brokerage for investors today: https://www.interactivebrokers.com/ Interactive Brokers is a member of SIPC. *********************************************************************Fiscal.ai is building the future of financial data.With custom charts, AI-generated research reports, and endless analytical tools, you can get up to speed on any stock around the globe. All for a reasonable price. Use our LINK and get 15% off any premium plan: ⁠https://fiscal.ai/chitchat *********************************************************************Disclosure: Chit Chat Stocks hosts and guests are not financial advisors, and nothing they say on this show is formal advice or a recommendation.

What do you do when a new data point drops—and all eyes turn to you? In this episode, John Dues and Andrew Stotz explore the leadership discipline required when performance data changes. Instead of reacting to a single data point, they unpack how Deming thinking (understanding variation, avoiding tampering, and pausing to interpret patterns) can protect trust, stability, and improvement. A practical conversation for leaders who want wisdom—not speed—to guide their decisions. TRANSCRIPT 0:00:02.3 Andrew Stotz: My name is Andrew Stotz, and I'll be your host as we dive deeper into the teachings of Dr. W. Edwards Deming. Today, I'm continuing my discussion with John Dues, who is part of the new generation of educators striving to apply Dr. Deming's principles to unleash student joy in learning. The topic for today is when the numbers change and everyone looks at you. John, take it away.   0:00:28.4 John Dues: Yeah, it's good to be back, Andrew. I think this is sort of an interesting topic. Many of us that have been in leadership roles have been in this position where the numbers change, whatever they may be. For me, they're dips in attendance, they're assessment results changing, something like that, a subgroup's results changes from the previous year. Sometimes the changes are small, sometimes they're big. But I'm thinking about times when they're just large enough to draw attention in a meeting. And it's not even really so much the size of the change that's important, it's what happens next.   0:01:12.9 John Dues: So you can kind of put yourself in one of these meetings where you're looking at data and maybe you didn't even expect it, but people kind of notice. Then someone asks what went wrong? And then the next thing that comes is someone suggests some type of fix or solution, and then this pressure starts to build. Especially if they're all sort of looking at you, the silence can feel irresponsible. And so what do we do? We react in some way. We call another... For explanations, maybe from others. We adjust a plan that's already in place. We launch a new initiative or tighten expectations on people, whatever it may be. None of it's out of malice. It's done out of care, most typically, or at least in the settings I've observed this sort of phenomenon.   0:02:13.1 Andrew Stotz: Don't just stand there, do something.   0:02:15.2 John Dues: Don't just stand there, do something. But the thing is, very often it just makes things worse. Right?   0:02:21.0 Andrew Stotz: Don't just do something. Stand there.   0:02:23.8 John Dues: Right, right. The opposite. But even if you know that, it's very, very difficult in the moment to...   0:02:32.5 Andrew Stotz: The pressures.   0:02:33.6 John Dues: Yeah.   0:02:34.9 Andrew Stotz: Well, I have a little... Little thing happened last night when a friend of mine came to see my mom and me, and we went out for there's a restaurant nearby, so we got the walker and got mom going. And her natural inclination was to help mom in getting up and that type of thing. And I was explaining to her the difference between what I call a caregiver and a caretaker. And I was saying that most people are caretakers where they're just taking care and they want to just help. And she's like, "It's irresistible. I mean, in my bones, I want to help." And I said, "It's very hard to see that sometimes the best help is to let her struggle and use her legs to get up, not to help her on that." And that was like a revelation for her last night, it just made me think about that.   0:03:33.8 John Dues: No, that's actually a perfect analogy because her health is sort of a high stakes environment. Just like schools are high stakes environments or many of the businesses that people run that listen to this podcast have high stakes. In our cases, it's students and families matter, outcomes matter. There's a lot of different stakeholders that are interested in what's going on in schools. And when those numbers do change, it can feel like neglect if you don't do anything. We're expected to notice. We're expected to... Good leaders are supposed to respond. They're supposed to act decisively, right?   0:04:12.0 Andrew Stotz: Yeah, because there's another aspect to it too. Let's just say that you have a boss that understands it and you're like, "Yeah, it's just noise. It's not signal." But how many times can you say that? Right?   0:04:27.8 John Dues: Yeah, that's right.   0:04:28.5 Andrew Stotz: That's another kind of pressure in that situation.   0:04:31.6 John Dues: Yeah, that's like the second-in-command type person, right? So they have their own pressure. And what you can see happening, this like visible action is sort of like evidence of competence because you can see it. And so the reaction becomes the default. So just like in this example you're giving with your mom, that action to help is very hard to resist. Even though by doing so, like you were saying, she doesn't get the physical exercise and actually makes things worse in the long term for your mom's health.   0:05:10.4 Andrew Stotz: "Boss, why did Kevin get a promotion and not me?" "Well, Kevin's a man of action."   0:05:14.8 John Dues: Man of action, right. Exactly. Exactly. And there's all these risks for a leader that doesn't react right away. Are they disengaged? If they're asking questions instead of acting right away, are they just uncertain? They lack certainty? Are you ignoring the data if you are pausing or waiting? Again, under these conditions, which I think are prevalent just about everywhere that I've been, at least, reacting quickly feels like the safest move. But I think the conflation is speed and wisdom. But speed is not, definitely not the same thing as wisdom, right?   0:06:02.1 John Dues: In all of our organizations, the data fluctuates naturally over time. No different in schools, like we've talked about. Attendance rises and falls, assessment results bounce up and down, behavior incidents they spike and they dip. And it's not necessarily a sign that something's broken. It's often just how systems typically behave, the systems that we're paying attention to. I think the main mistake leaders typically make in that moment when they see that movement is that they think that automatically means something changed. And so you get these concerns if it's a bad move in the data. If it's a short-term increase, maybe we trigger some type of celebration. So this works both ways, actually. But the main point is that one data point becomes a story. It becomes the story of what's... We try to attach an explanation to this dip or this increase that's actually not grounded in any kind of reality. We would say they're just reacting to noise, kind of like what you just said. And the problem, though, is that there's a number of then very predictable things that happen. First, educators, and I felt this as a teacher. I taught in Atlanta Public Schools, a big district that was trying lots of new things in the early 2000s. You feel this whiplash. So priority shifts, guidance changes. Yesterday's focus is replaced by today's concern.   0:07:44.5 John Dues: And what happens in a setting like that, that I found, is that people start explaining instead of learning. Especially when there's a strong accountability system like there is in education systems, results are questioned immediately, often. And so the safest response at almost all levels of the organization is just to justify what's already happened, not to explore what might be improved. Very, very, very difficult. And that then leads to trust eroding. And over time, what I've seen is that educators learn that any fluctuation brings scrutiny. They become cautious, defensive, quiet. And obviously none of that improves outcomes. And again, just like in the example with your mom, it actually makes things harder to improve in the long term. So this overreacting to this routine variation then often increases variation, and so the system actually becomes noisier and not more capable. You get this vicious cycle. What's that?   0:09:00.5 Andrew Stotz: Tampering.   0:09:01.8 John Dues: Yeah, tampering. Exactly. That's what Deming would call it, tampering. When you intervene in a stable system.   0:09:07.3 Andrew Stotz: It's interesting. The one data point becomes a story is a great, great line. In the world of finance, everybody's trying to get the next wave. As a financial analyst, you're trying to think, okay. And all we do constantly is look at the next data point and say, "Does this confirm or not my view that gold's going to crash now, or gold's going to rise, or US stocks are going to X, or the dollar is going to... " And most of the time, we're just making one data point become a story, and then the next data point comes out and it's like, "Okay, so there's a different story here." And then...   0:09:51.3 John Dues: Yeah. That explanation there it's sort of... The key idea is reaction. It's literally seductive. It is seductive because it feels productive.   0:10:04.3 Andrew Stotz: In my finance work, when I help people with their money, what I do introduce what I've learned from Dr. Deming to say it really helps me separate the signal from the noise in the stock market, and therefore, I will never react. And I even set parameters where I rebalance my portfolio every three months. So when they go, "What are you going to do about such and such?" it's like, "Everything's set. I'm going to wait until the results are in, and I'm going to reevaluate on a framework, on a systematic way," which just helps me from getting whipsawed this way or whiplash this way or that way. And it's proven to be not only great for helping people feel like I have a deeper understanding and follow what I'm doing, but it also improves performance.   0:11:07.7 John Dues: Yeah. And you know, I'm definitely no financial expert by any means, but it makes me think of The Big Short, the movie, when I don't know how true to reality it is, but when the character played by Christian Bale, Michael Burry, is sticking to his guns with his shorting of the housing market and people are coming into his office and screaming at him. He's getting emails that are coming in one after another calling him an idiot, threatening him with lawsuits, and he holds. So that's like an extreme example of not reacting to noise. And you can see what it does to him in the movie, the intestinal fortitude, before sort of it comes to the conclusion. He got less and less certain even though he stuck to his guns, that he was doing the right thing. Right.   0:12:00.3 Andrew Stotz: I got to get that clip because I want to combine that with Mel Gibson in that movie, I can't remember, the Celtic battles in England where he's saying, "Hold the line! Hold the line!" What is it?   0:12:13.6 John Dues: Braveheart, probably.   0:12:16.3 Andrew Stotz: Braveheart. Yeah.   0:12:17.9 John Dues: Braveheart. Yeah. That's because when you're having a conversation like this and you talk about this leadership concept, just about everybody's going to nod along with you. But when you are actually in the moment, very few people hold the line, very few people hold the line. But at least if you have this grounding, at least you'll be more likely to hold the line because you have some techniques and some ways to sort of paint this picture that there's a firm logic. There's never certainty, but at least there's a firm logic for why you're holding the line in a particular situation. But it's very, very hard. Very hard.   0:12:58.2 Andrew Stotz: One question is, could there be such a thing like a mantra that the management team could have? Something like, "One point is not the full story," or something that they talk about in non-emotional times so that they've got it set. So when all of these numbers change and everyone looks at you, it's like, "Guys, remember, one point is not the story."   0:13:28.1 John Dues: Yeah, no, that's a really good idea. That would be a good sort of internal value or something marketing-wise that you could sort of, something sticky that would remind people of this, especially in those moments of anxiety or even panic, depending on the particular situation and the type of data that you're talking about. That's a good idea. I think the key thing is that activity is not the same as improvement. It feels good. It feels good to change something, introduce something new, new rules, new expectations, even though the system itself hasn't changed. And like you said, that's tampering. You make adjustments to a stable system based on something that's just routine ups and downs and it degrades performance. I think a lot of people are familiar with Deming's Red Bead Experiment. Less of them are familiar with the Funnel Experiment. He basically talks about when you are trying to hit a target through a funnel and you move it each time to sort of adjust for the variation from the mark. You actually, he called it going off into the Milky Way in terms of where you end up when you make these adjustments every single time.   0:14:46.1 Andrew Stotz: I thought that demonstration was so... I don't remember that he did it in the seminars that I attended. I remember the Red Bead Experiment. But that tampering is so powerful to understand the mess you can end up in.   0:15:05.7 John Dues: Yeah. And that was in The New Economics. I don't think he ever did it in a four-day seminar that I remember. But the interesting thing is generally the best choice is just to keep the funnel in the same place and keep going. But again, that's very hard. Especially let's say you're doing this as a group activity and group two, three, four, and five, you're looking over and they're making these adjustments every time, and you're just sitting there. And you're like, "Maybe they're onto something," or "Maybe I do need to move." But at the end of it, they're much farther away than you are.   0:15:43.4 Andrew Stotz: And I feel like the title you talked about, "When the Numbers Change and Everyone Looks at You," is evoking that emotion of, "Am I doing something wrong? Other people would do it a different way. Oh, they're making progress. I'm just sitting here." Those kind of emotions are the types of things that cause that tampering.   0:16:02.7 John Dues: Yeah. And then that shows up as initiative overload. You get these contradictory messages, constant course correction like in the Funnel Experiment. And the irony is you typically have a leader who cares deeply and they don't realize they're creating the very instability that makes improvement impossible. It's a tough realization. So what I would say is that when the data does change, the most important leadership move is not action, but it's interpretation. So instead of asking, "What should we do?" maybe a good first question is, "Is this shift within the range of what we should expect?" So just that question kind of slows the moment down. It shifts attention from reaction to understanding and it invites the group to look at data over time rather than point to point. It opens up this possibility that nothing is wrong even if the results aren't yet acceptable.   0:17:15.4 Andrew Stotz: Love that. Love that.   0:17:16.8 John Dues: Yeah, I think it's a really important...   0:17:17.5 Andrew Stotz: Is this shift within the range of what we would expect?   0:17:20.6 John Dues: Yeah.   0:17:21.1 Andrew Stotz: Answer's going to be "Yes, this is in the range." So next topic in a meeting.   0:17:28.5 John Dues: Right. And we've talked about this before. And it's possible when you've asked that question that the system itself looks stable, but it also may be producing outcomes we don't like. And so the key is even in those cases, reacting to an individual data point is not going to help. In that case, if you have stability but outcomes you don't like, you need thoughtful system redesign. But these sort of urgency-driven immediate fixes, overreaction, that's not going to help. That's not going to help.   0:18:06.9 John Dues: So the big thing is pausing before reacting. But that's often misunderstood. We talked about is he or she ignoring the data? Are they lowering expectations? Is that leader just indecisive? I don't think so. I think that's really what discipline is. And pausing, being that person that says, "Let's take a breath and pause here," it creates the space to study patterns rather than focusing on those individual data points. It allows leaders to separate stability from acceptability. It prevents unnecessary pressure then cascading through the system, which is what often happens. And so what I think is when you actually pause, what you're doing is protecting the people in your organization. When you do that, I think in an education system it protects teachers from being judged on noise they can't control. I think it protects leaders from... They are often then turning around and making promises that the system can't actually keep. It's sort of like a short-term thing, but you're hurting the long term. And then it protects students because they don't then undergo all these constant changes that disrupt their learning.   0:19:43.1 John Dues: So I think what a leader, a strong leader does that's different is they ask questions. What does this look like over time? Is this a meaningful signal from what we've seen before? What should we expect if nothing changes? Just some basic questions. I think resisting the urge to explain every up and down movement. And it's really at the end of the day what it comes down to is you're not trying to assign meaning to every data point, but what you're trying to do is understand the underlying system behavior. Now sometimes action is warranted, and in those cases, you're going to act in a deliberate way. When it's not, they're going to communicate that and communicate why we're going to wait in this particular scenario and why that's the responsible choice. So there's got to be this underlying logic whichever direction you're going to go. And I think if you've ever been around a leader like this, it feels calm. It just feels calm. It feels steady. And over time, the key thing is it creates this system that's trusting and then as a result, it's far more capable of improvement. It's far more likely that improvement's going to happen.   0:21:13.4 Andrew Stotz: That's amazing. And I was just taking lots of notes, but I wrote down pause, have discipline, protect employees, protect students. But I wrote down protect the aim.   0:21:27.0 John Dues: Yeah, protect the aim. That's good.   0:21:28.7 Andrew Stotz: Protect the aim of the system. Why are we here? And if we can't do that pause and look at it carefully, there's just no way we're going to achieve that.   0:21:43.3 John Dues: Yeah, no, I agree. And I think the thing is with these situations is that the most damaging decisions in schools are often made after the numbers change, but not because of the numbers themselves. Like even if they've declined, typically it's not to the point that it's catastrophic, but what's catastrophic is the series of decisions that are made as a result of the decline. And so in those situations again, this reaction feels responsible. But really what happens when you react without understanding is it creates more noise, more stress, more instability, and you still don't have the improvement at the end of all that consternation.   0:22:30.1 Andrew Stotz: Yeah, I would sum up my sum of this is the bad manager says, "That's a terrible result. Let's make it worse."   0:22:42.0 John Dues: And that's really what's happening. They're obviously not saying it, but that's exactly what's happening. Exactly. That's a really good summary. And I would kind of sum it up with three big ideas that would be helpful for listeners. I think the first one is that not all variation is meaningful. Most fluctuations actually are just routine, should not trigger action. The second one we've talked about, that overreaction creates instability. Acting on noise makes systems worse, not better. And then the third thing I would say is that pausing is a leadership skill and understanding must come before action.   0:23:30.2 John Dues: And I say it's a skill 'cause you actually have to practice it. I think you have to prepare yourself for what you're going to do when you get in front of a group and you're going to talk about results and those results maybe aren't exactly where you want them to be. You have to practice that, rehearse it. What are you going to say? How are you going to back that up? What's the logic? But I think when leaders learn to have that pause before reacting, they actually protect learning, they protect trust, and then they actually create the conditions for improvement. And I think that's the work that matters most when everyone's looking at you to make a key decision. Not easy, but certainly important work.   0:24:08.6 Andrew Stotz: That's a great wrap. I'm not going to add anything to it. John, on behalf of everyone at the Deming Institute, I want to thank you again for this discussion. And for listeners, remember to go to deming.org to continue your journey. You can find John's book, Win-Win: W. Edwards Deming, the System of Profound Knowledge, and the Science of Improving Schools on amazon.com. This is your host, Andrew Stotz, and I'll leave you with one of my favorite quotes from Dr. Deming, "People are entitled to joy in work."      

Nvidia just posted another monster quarter, so why did the stock drop nearly 10% after earnings?In this deep dive, Zaid breaks down Nvidia's blowout results, the growing fears of an AI bubble, Michael Burry's warning about massive purchase commitments, and the real risk that hyperscalers could slow their spending. Then we flip to the bull case: agentic AI, a potential China comeback, new inference chips, and why Nvidia might actually be cheap at 22x forward earnings.Check out the Public app for incredible investing tools and to support the show (LINK)Follow us on Instagram (@TheRundownDaily) for bonus content and instant reactions.

Absolutely the BEST podcast I have done if you're looking for a pre earnings analysis of $NVDA or a post earnings analysis of $MSFT or $AMZN. Absolute buy zones identified through Sidekick and spot on stock analysis of the memory names and Cybersecurity names. The longer live Youtube version has my entire process of getting ready for the podcast too. Click Here for the longer LIVE YouTube versionGet my FREE newsletter or sign up for the paid version with benefits like the Office Hours and tracking the portfolios in Savvy Trader ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://dailystockpick.substack.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠THESE SALES END SOON: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TRENDSPIDER $9 2 week trial WEEKEND SALE - get any annual plan and I'll send you my 4 hour algorithm. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Seeking Alpha's Tool kit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠*BEST DEAL - SEEKING ALPHA BUNDLE - Save over $150 and get Premium and Alpha Picks together ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ALPHA PICKS - Want to Beat the S&P? Save $75 ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Seeking Alpha Premium - FREE 7 DAY TRIAL and 15% OFF⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠SEEKING ALPHA PRO - TRY IT FOR A MONTH FOR ONLY $89 ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠EPISODE SUMMARY

Nick Valdez looks at the CRASH of Bitcoin. Where are we heading? Is this the bottom? How long will this downtrend last? Michael Burry of "The Big Short" fame has a VERY dire warning. Make sure to watch the levels I think we hit next at the end!

In this episode, we dig into the big question likely on everyone's mind: has Bitcoin found its bottom? We kick things off with a recap of BTC's recent drops and the mounting woes facing Strategy, then take a closer look at Michael Burry's latest Bitcoin prediction and what it could mean for the market. From there, we shift to industry moves, including Ledger's potential IPO, Elon Musk's xAI ambitions, and TI's acquisition of Silicon Labs.   For the chart of the week, we examine the 50-week exponential moving average and discuss whether long-term Bitcoin holders may be starting to accumulate again.  Remember to Stay Current! To learn more, visit us on the web at https://www.morgancreekcap.com/morgan-creek-digital/. To speak to a team member or sign up for additional content, please email mcdigital@morgancreekcap.com  Legal Disclaimer  This podcast is for informational purposes only and should not be construed as investment advice or a solicitation for the sale of any security, advisory, or other service. Investments related to the themes and ideas discussed may be owned by funds managed by the host and podcast guests. Any conflicts mentioned by the host are subject to change. Listeners should consult their personal financial advisors before making any investment decisions. 

Rebel Capitalist Live VII: Protect & Grow Your Wealth Before the Next Crisis https://rcl.georgegammon.com/live Want the cheat code to protect and grow your wealth? Check out Rebel Capitalist Pro https://rcp.georgegammon.com/pro

Crypto News: Democrats meet to discuss passing Clarity Act. Wall Street giant CME Group is eyeing its own 'CME Coin,' CEO says. Michael Burry shares bearish post on Bitcoin.Brought to you by ✅ VeChain is a versatile enterprise-grade L1 smart contract platform https://www.vechain.org/

"Big Short" Michael Burry bashes bitcoin. Michael Burry, the investor who famously predicted the 2008 crash, says bitcoin's drop is triggering a "collateral death spiral" in precious metals. He warns that liquidations in tokenized gold and silver are dragging crypto down, and if BTC slips to $50,000, the market for tokenized metals could collapse into a "black hole." CoinDesk's Jennifer Sanasie hosts "CoinDesk Daily." - This episode was hosted by Jennifer Sanasie. “CoinDesk Daily” is produced by Jennifer Sanasie and edited by Victor Chen.

Patrick Bet-David reacts to Michael Burry warning that markets are missing a major shift. From Venezuela to China, oil collateral, and Taiwan, Pat explains why this is not about one raid, but a Cold War level move that Wall Street is badly underpricing.

The stock market is where the real gangsters operate — not the streets, not the movies. Wall Street will break you mentally, financially, and emotionally if you don't understand the game. In this video, Wallstreet Trapper breaks down the truth behind Nvidia, Michael Burry's warnings, AI stocks, market manipulation, and what's really happening behind the scenes.We talk about:

Group Chat News is back with the hottest news of the week including Space X plans to go public in 2026,  the one line Americans like to wait in, Disney signs deal with Open A I, Michael Burry now has over 156K subscribers on Substack, rent prices are starting to drop, and Netflix is working on buying Warner Bothers