Podcasts about South Korea

Henry Sokolski continues: the Saudi nuclear deal could trigger a proliferation race, with nations like Egypt, Turkey, and the UAE demanding similar enrichment rights. Furthermore, allies such as South Korea and Poland may reconsider their own nuclear ambitions if they view American security guarantees as insufficient. Proliferation is no longer "old news" but a growing threat as nations seek their own deterrents. The result is a destabilized global order where multiple states hover on the verge of nuclear weapon status. (8)1942 B-25 DOOLITTLE RAID ON TOKYO

SCHEDULE FOR THE JOHN BATCHELOR SHOW, 7-22-2026.1740 BATAVIA MASSACREGordon Chang and Rick Fisher examine Xi Jinping's introduction of the World Artificial Intelligence Cooperation Organization (WAICO), designed to establish Chinese dominance in setting global AI rules. Headquartered in Shanghai, the group aims to make international partners dependent on Chinese technology while promoting anti-democratic values. Meanwhile, China's economy is struggling, with real growth potentially near zero. Despite manufacturing strengths, China remains vulnerable due to a critical lack of high-end Nvidia chips required for advanced AI development. (1)Gordon Chang and Peter Huessy discuss the Democratic Socialists of America (DSA) bill to drastically reduce the U.S. nuclear triad, including cutting ICBMs from 400 to 150. Supported by Senators Bernie Sanders and Elizabeth Warren, the plan effectively promotes unilateral disarmament. Critics argue this trashes the concept of nuclear deterrence just as China and Russia expand their arsenals. Furthermore, there is a widespread "miseducation" of Americans regarding the necessity of a modernized nuclear deterrent. (2)Gordon Chang and Victoria Coates report that Iran has activated the Houthis to attack the Bab el-Mandeb strait, a critical choke point for Saudi Arabian oil exports. This escalation has pushed oil prices past $95 as the Houthis use Iranian-supplied missiles and drones to harass shipping. While the House of Saud is targeted, internal frictions between Saudi Arabia and the UAE complicate a unified regional response. The conflict represents a major humanitarian and economic disaster for global commerce. (3)Gordon Chang and Victoria Coates continue: China benefits from discounted Iranian oil but views the regime's economic instability as a "bad debt." Simultaneously, Saudi Arabia is deepening its partnership with the U.S. through a landmark nuclear cooperation deal. Iraq has also signaled a shift toward Washington, signing $60 billion in energy deals with American companies like Chevron. While Russia seeks to sell extra capacity to Asia, Ukrainian strikes on refineries may hinder Putin's ability to remain a reliable energy supplier. (4)Peter Earle traces how the word "trillion" entered the economic lexicon in 1981 when the U.S. passed $1 trillion in public debt. Today, the U.S. national debt approaches $40 trillion, with annual interest payments exceeding $1 trillion. Unlike 19th-century millionaires who faced high risks, modern trillion-dollar figures are often a product of government monetary expansion. We have entered "Trillionstan," where massive quantities of money are common, yet their long-term significance is often overlooked by the public. (5)Peter Earle argues that not all trillions are equal; some represent genuine wealth creation, such as SpaceX's $2 trillion valuation based on future technological potential. However, inflation and government borrowing have also inflated nominal values, potentially leading to a fiscal reckoning. If creditors lose faith in U.S. debt, the government may be forced to print more money, further devaluing the currency. Maintaining prosperity requires ensuring that economic forces focus on creating new wealth rather than merely redistributing it. (6)Henry Sokolski warns that the Trump administration's nuclear deal with Saudi Arabia allows the kingdom to enrich uranium, a process that can easily be diverted for bomb-making. Saudi Arabia has rejected the "additional protocol" for rigorous UN inspections, raising concerns about their true intentions. This "black box" arrangement lacks sufficient safeguards to prevent a rapid diversion of nuclear materials. Critics warn that providing enrichment technology to an ally involved in regional warfare is inherently delusional and dangerous. (7)Henry Sokolski continues: the Saudi nuclear deal could trigger a proliferation race, with nations like Egypt, Turkey, and the UAE demanding similar enrichment rights. Furthermore, allies such as South Korea and Poland may reconsider their own nuclear ambitions if they view American security guarantees as insufficient. Proliferation is no longer "old news" but a growing threat as nations seek their own deterrents. The result is a destabilized global order where multiple states hover on the verge of nuclear weapon status. (8)Michael Bernstam explains how Ukrainian drone strikes have destroyed 30% of Russia's refining capacity, causing the "crack spread"—the profit margin for refining oil—to triple worldwide. While Russia exports crude, it now suffers from severe domestic shortages of gasoline and jet fuel. Consequently, Russia is forced to buy back its own refined oil from India at premium prices. Putin has been "hoist on his own petard," creating a global energy weapon that has ultimately turned against the Russian economy. (9)Michael Bernstam reports that Ukrainian drones recently destroyed major distribution hubs for Wildberries, the Russian equivalent of Amazon, causing $2 billion in damage. These strikes have devastated small businesses and middle-class consumers, fueling internal resentment against the Kremlin. Simultaneously, 18 local Russian officials signed a petition calling for Putin's resignation as economic conditions worsen. The loss of consumer infrastructure and rising fuel costs are creating a constituency for ending the war to prevent a total economic collapse. (10)Bob Zimmerman reports that SpaceX is preparing for its 13th Starship flight, a prototype featuring major upgrades for future orbital missions and in-orbit refueling. In India, the startup Skyroot achieved a landmark success with the Vikram-1 rocket, signaling the rise of a private, capitalist space sector. However, the Indian government has counterproductively restricted ISRO employees from leaving for private firms. These contrasting approaches highlight the tension between state-run agencies and the efficiency of private enterprise in the global space race. (11)Bob Zimmerman surveys new discoveries: astronomers have detected a helium atmosphere on a terrestrial exoplanet located 48 light-years away in its star's habitable zone. Closer to home, archival data from Pluto reveals massive landslides, proving the dwarf planet is geologically active rather than dormant. Meanwhile, new images of Valles Marineris on Mars illustrate the canyon's staggering scale, with depths equivalent to the height of Mount McKinley. These discoveries emphasize that planetary bodies across our solar system are dynamic and evolving. (12)Simon Constable notes European energy prices are skyrocketing, with Brent crude hitting $95 and natural gas up 47% in a single month. In France, a heatwave and suspicious forest fires have added environmental stress to the economic crisis. A political movement in the U.S. is targeting data centers for their high energy consumption, which now exceeds 4% of usage. Surprisingly, the United Kingdom hosts the second-highest number of data centers globally, despite its historical association with "Luddite" skepticism. (13)Simon Constable observes that new British Prime Minister Andy Burnham faces immediate skepticism, with polls indicating nearly half of voters feel his government lacks direction. Burnham's focus on domestic issues like capping bus prices is criticized as a "tax and spend" policy that might alienate the wealthy. While he has emphasized national security, his early days have been defined by local populist initiatives. Critics worry his leadership style mimics a "Lord Mayor" rather than a strategic global prime minister. (14)Brandy Shufutinsky details how Qatar has provided extensive grants for Arabic language and culture programs in U.S.K-12 schools. These programs often utilize textbooks that omit Israel from maps and glorify extremist ideologies. Qatar Foundation International (QFI) even funds teacher salaries and work visas, raising concerns about who these educators truly report to. This funding creates a "pipeline" from elementary school to higher education, potentially instilling foreign-influenced perspectives in future generations of American citizens. (15)Conrad Black argues that Canada's economic growth has stalled due to high corporate taxes and "climate alarmist" policies under the Trudeau government. He suggests that new leadership under Mark Carney could revitalize the nation by making it more tax-competitive with the U.S. Canada's vast resources and skilled workforce provide the potential for a rapid rebound. For Canada to succeed, it must pivot back to pro-capitalist policies and attract foreign investment to drive future growth. (16)Two spelling corrections applied: Peter Earle (5, 6 — transcribed as "Pete Earl"; the AIER economist) and Brandy Shufutinsky (15 — transcribed as "Shubatinsky"). Both added to the log unless you'd prefer otherwise.

Michelin star restaurant owner in South Korea faces jail for serving up ants on a dessert. US CD sales on the rise despite Gen-Z not owning CD players. Hitler's birthplace in Austria reopens as a police station. Weird AF News is the only daily weird news podcast in the world. Weird news 5 days/week and on Friday it's only Floridaman. SUPPORT by joining the Weird AF News Patreon http://patreon.com/weirdafnews - OR buy Jonesy a coffee at http://buymeacoffee.com/funnyjones Buy MERCH: https://weirdafnews.merchmake.com/ - Check out the official website https://WeirdAFnews.com and FOLLOW host Jonesy at http://instagram.com/funnyjones - wants Jonesy to come perform standup comedy in your city? Fill out the form: https://docs.google.com/forms/d/e/1FAIpQLSfvYbm8Wgz3Oc2KSDg0-C6EtSlx369bvi7xdUpx_7UNGA_fIw/viewform

On episode 474, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Michael Batnick⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ben Carlson⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ discuss: the bloodbath in certain tech stocks, investor behavior in South Korea, a normal market environment, the Mag 7 shine has worn off, Nike lost its moat, why we don't have recessions anymore, boomers aren't downsizing, stocks vs. housing as an investment, Netflix is crashing, movies are back, and more. This episode is sponsored by YCharts and Vanguard. To learn more and get 20% off your initial YCharts Professional subscription to take Y for a spin (new customers only), visit https://go.ycharts.com/animal-spirits To learn more about Vanguard bonds, visit https://vanguard.com/audio Sign up for The Compound newsletter and never miss out: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠thecompoundnews.com/subscribe⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Us On Social Media: Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠instagram.com/thecompoundnews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Twitter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠twitter.com/thecompoundnews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠linkedin.com/company/the-compound-media/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠tiktok.com/@thecompoundnews⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ 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/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about your ad choices. Visit megaphone.fm/adchoices

HEADLINES Nadia Comăneci says Ana Barbosu's legal fees in the fight to retain her Paris 2024 bronze medal will be covered. U.S. CLASSIC MORNING-AFTER COFFEE KLATSCH Reese Esponda Wins the U.S. Classic All-Around Esponda improved her top all-around score by nearly a full point, finished almost a point ahead of Jade Carey and entered the conversation for a World Championships team spot. Full U.S. Classic results and video of every routine Katelyn Ohashi Returns to Elite Gymnastics Ohashi made her triumphant return to elite gymnastics for the first time since 2013—and competed in her first senior U.S. Classic. Is Skye Blakely the All-Around Favorite for Nationals? MINI COMMISSION: EFFICIENT ROUTINE CONSTRUCTION: request for smart routine construction for Dulcy Caylor and Kaylia Nemour World Championships Qualifiers China, Japan, South Korea and North Korea qualified teams to Rotterdam. Amanda Yap of Singapore earned an individual Worlds spot. The Uzbekistani and Filipino men missed Worlds qualification despite outscoring the United States and Brazil, which did qualify. CHAPTERS 00:00 – Ana Barbosu's Legal Fees 06:51 – U.S. Classic Debrief 12:55 – Reese Esponda's Worlds Case 21:25 – Katelyn Ohashi's Next Move 27:07 – Skye Blakely and Jade Carey 36:39 – Who We're Worried About 43:36 – U.S. International Standing 48:20 – Gymternet News 54:00 – Efficient Routine Construction 1:13:03 – Commonwealth Games and Worlds Qualifiers RELATED EPISODES Behind the Scenes: U.S. Classic 2026 Meet Report  Behind the Scenes: Podium Training Report—U.S. Classic 2026 Behind the Scenes: Ohashi Is Back with Scott Bregman UP NEXT Behind the Scenes, our live Q&A podcast, Fridays at noon Pacific. SUPPORT OUR WORK Join Club Gym Nerd for weekly Behind the Scenes episodes, our complete members-only archive, games, the forum and live-show discounts. Shop GymCastic merchandise. Thanks to our sponsor Huel -our exclusive offer of 15% OFF with our code GYMCASTIC at huel.com/GYMCASTIC. New Customers Only. Thank you to Huel for partnering and supporting our show! GYMCASTIC TOOLS, GAMES AND RESOURCES LA 2028 Roster Lab Elite Score Explorer International Gymnastics Calendar GymCastic Games GymCastic Newsletters The Balance Beam Situation: Spencer's GIF Code of Points Gymnastics History: Uncle Tim's gymnastics history and Code of Points archive Resistance Resources Cover art photos of Skye Blakely, Jade Carey and Reese Esponda © GymCastic/Steve Cooper. All rights reserved. Katelyn Ohashi cover-art photo © Melissa J. Perenson/Cal Sport Media.

Michelin star restaurant owner in South Korea faces jail for serving dessert topped with ants. CD sales are on the rise despite Gen Z lacking CD players. Adolf Hitler's birthplace in Austria re-opens as a police station. Weird AF News is the only daily weird news podcast in the world. Weird news 5 days/week and on Friday it's only Floridaman. SUPPORT by joining the Weird AF News Patreon http://patreon.com/weirdafnews - OR buy Jonesy a coffee at http://buymeacoffee.com/funnyjones Buy MERCH: https://weirdafnews.merchmake.com/ - Check out the official website https://WeirdAFnews.com and FOLLOW host Jonesy at http://instagram.com/funnyjones - wants Jonesy to come perform standup comedy in your city? Fill out the form: https://docs.google.com/forms/d/e/1FAIpQLSfvYbm8Wgz3Oc2KSDg0-C6EtSlx369bvi7xdUpx_7UNGA_fIw/viewform Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jade Lee is an international real estate professional based in Seoul, South Korea, specializing in helping expatriates and overseas investors purchase, sell, and invest in Korean real estate. With a background as a New York attorney, she combines legal knowledge with local market expertise to guide international clients through cross-border real estate transactions.In this episode we discuss what it takes to specialize in serving international real estate clients. Jade shares how understanding different cultures, legal considerations, communication styles, and client expectations can help agents build trust and grow a successful niche serving buyers and investors from around the world.You Can Find Jade @:LinkedIn: https://www.linkedin.com/in/jade-lee-679474261/

What does it mean when the sons of empire become the heroes of the nation that once ruled them? Four years later, what happens when one of those same colonies turns round and beats France on the biggest stage there is? And could two World Cups, played four years and one continent apart, actually tell you where the world's centre of gravity was heading next?Peter and Afua trace France '98 and the first World Cup ever held in Asia, from Zidane's headed goals to Senegal's shock win over the champions, to ask what football reveals about migration, empire and a shifting world order.Join Legacy Plus for bonus episodes, early access, Q&A's, fewer adverts and more.legacy.supportingcast.fm[0:00] A million people on the Champs-Élysées, and a face that didn't fit the old postcard of France[2:56] The Republic's beautiful idea, and the empire it was built on[6:06] Zidane, Thuram, Vieira — the team Le Pen said wasn't really French[9:53] Ronaldo's mystery fit, hours before the final[15:05] Iran and the USA, white flowers, and a photograph that stopped the world[23:14] The World Cup leaves the Atlantic world for the first time in 72 years[27:26] South Korea's run to the semi-finals, and the making of a soft-power superpower[34:20] Senegal 1, France 0 — what it meant to beat the empireStay connected with Legacy:Instagram: @originallegacypodcastTikTok: @legacy_productionsExplore more from Peter and Afua — essays, sources, and ideas:Substack: peterfrankopan.substack.com | afuahirsch.substack.comJoin Legacy+ for bonus episodes, early access, Q&A's, fewer adverts and more.legacy.supportingcast.fmStay connected with Legacy:Instagram: @originallegacypodcastTikTok: @legacy_productionsExplore more from Peter and Afua — essays, sources, and ideas: Substack: peterfrankopan.substack.com | afuahirsch.substack.com Hosted on Acast. See acast.com/privacy for more information.

Market news for July 21, 2026: Asian shares climbed today, led by gains in Japan and South Korea. Oil prices edged lower on hopes of diplomatic progress in the Gulf. Iran-backed Houthis in Yemen have threatened a naval blockade on Saudi Arabia. Indonesia's parliament approved generous tax incentives under a new financial centre law. Synopsis: Market Focus Daily is a closing bell roundup by The Business Times that looks at the day’s market movements and news from Singapore and the region. Written by: Nicole Teo (nicolet@sph.com.sg) Produced and edited by: Chai Pei Chieh & Claressa Monteiro Produced by: BT Podcasts, The Business Times, SPH Media Produced with AI text-to-speech capabilities --- Follow Market Focus Daily and rate us on: Channel: bt.sg/btmktfocus Amazon: bt.sg/mfam Apple Podcasts: bt.sg/mfap Spotify: bt.sg/mfsp YouTube Music: bt.sg/mfyt Website: bt.sg/mktfocus Feedback to: btpodcasts@sph.com.sg Do note: This podcast is meant to provide general information only. SPH Media accepts no liability for loss arising from any reliance on the podcast or use of third party’s products and services. Please consult professional advisors for independent advice. Discover more BT podcast series: BT Money Hacks at: bt.sg/btmoneyhacks BT Correspondents at: bt.sg/btcobt BT Podcasts at: bt.sg/podcasts BT Lens On: bt.sg/btlensonSee omnystudio.com/listener for privacy information.

This week we're talking: USA Air Quality, Erie, PA True Crime, Sculptra in South Korea, Getting Better at accepting where we're at, hair transplants, Internet Spelling Bee Words, Jonathan Van News Desk, coming out in your 30s, and Madonna's new album.  Wanna see JVN on stage? Get tix to the Hot & Healed Comedy Tour here.  Catch Getting Better & The Monday Edit, now on YouTube!  Check out the JVN Patreon for exclusive content, bonus episodes, and more! www.patreon.com/jvn  Follow us on Instagram @gettingbetterwithjvn Jonathan on Instagram @jvn and senior producer Chris @amomentlikechris  Executive Producer, Chris McClure Producer, Editor & Engineer is Nathanael McClure Production support from Chad Hall Our theme music is also composed by Nathanael McClure. Curious about bringing your brand to life on the show? Email podcastadsales@sonymusic.com. Learn more about your ad choices. Visit podcastchoices.com/adchoices

How did a home-based reseller become a global e-commerce leader for a 9-figure K-beauty brand? Discover her Amazon strategy, future-customer targeting, TikTok tactics, and smart AI tools.   ► Watch The Podcasts On YouTube: https://www.youtube.com/@Helium10SeriousSellersPodcast?sub_confirmation=1 ► Instagram: instagram.com/serioussellerspodcast ► Free Amazon Seller Chrome Extension: https://h10.me/extension ► Sign Up For Helium 10: https://h10.me/signup  (Use SSP10 To Save 10% For Life) ► Learn How To Sell on Amazon: https://h10.me/ft   Bradley Sutton takes the Serious Sellers Podcast on the road, and onto a moving rail bike in South Korea, for a conversation with Jenna, Global E-commerce Team Manager at TONYMOLY. Jenna shares how she went from studying law and working as a programmer to spending ten years raising her daughter, discovering e-commerce from home, and eventually building a successful international selling career. She began by reselling Korean sporting goods to US customers through eBay before shifting her attention to Amazon, where one business reached as much as $10,000 in monthly profit. Her success during the pandemic earned her recognition from Amazon Korea and opened the door to managing accounts for other companies. Jenna has now used Helium 10 for approximately five years, and her favorite tool is the Xray Chrome Extension. She uses Xray while browsing Amazon to quickly review estimated sales, keywords, and Best Sellers Rank, helping her evaluate products and marketplace opportunities without leaving the search results. Today, she applies that experience at TONYMOLY, a 20-year-old K-beauty company generating approximately $163 million in annual sales. Jenna also reveals an unusual long-term marketing strategy: targeting customers before they become the brand's core buyers. If current anti-aging customers are between 40 and 50, her team may create content for women closer to 35, building awareness years before the need becomes urgent. TONYMOLY and its newer brand, BONCEPT, also use TikTok and Meta to drive product discovery, while positioning Amazon as the more attractive place to complete the purchase. The company supports these strategies through close collaboration between its e-commerce, sales, and R&D teams, allowing it to respond quickly to fast-moving beauty trends. From emerging ingredients such as PDRN, retinol, and retinal to the use of AI for copywriting, images, videos, and English-language content, this episode offers a fascinating look at how a global beauty company combines marketplace data, creative storytelling, and product innovation. Jenna's journey proves that starting small does not limit where e-commerce can take you. By continuing to learn, adapting when marketplaces change, and understanding customers before competitors do, sellers can turn an unexpected opportunity into a truly global career. In episode 757 of the Serious Sellers Podcast, Bradley and Jenna discuss: 00:00 - Introduction 01:28 - Meet Jenna From TONYMOLY 02:38 - From Law And Programming To E-Commerce 03:34 - Starting A Home-Based eBay Business 05:55 - Moving From eBay To Amazon 07:52 - Reaching $10,000 In Monthly Profit 09:59 - Winning An Amazon Korea Competition 10:38 - Five Years Using Helium 10 10:46 - Why Xray Is Her Favorite Tool 11:28 - Managing Global E-Commerce For TONYMOLY 14:17 - Launching The New BONCEPT Brand 16:11 - Expanding K-Beauty Across Amazon Europe 17:58 - Targeting Customers Five Years Early 20:17 - Using TikTok To Drive Amazon Sales 22:00 - How R&D And E-Commerce Work Together 23:52 - Retinol, Retinal, And PDRN Trends 27:27 - Using AI For Global Content Creation

Strategy's latest stock sale led today's discussion after the company raised another $163 million without purchasing additional Bitcoin, increasing its cash reserves while maintaining more than 843,000 BTC on its balance sheet. Matt questioned whether raising money to fund dividend obligations while continuing to hold Bitcoin is a sustainable long-term strategy. The episode also covered more companies adopting Bitcoin treasury strategies, Capital B's reverse stock split, and regulators missing the GENIUS Act deadline for finalizing stablecoin rules, leaving issuers waiting on key guidance before the law takes effect in early 2027. Matt also discussed France's decision to block Polymarket as unauthorized gambling, sharing his concerns about how prediction markets can be manipulated through coordinated betting activity in smaller political races. The episode wrapped up with South Korea's review of Upbit's 2025 hack, Zilliqa's investigation into a suspected cold wallet theft, and a look at the day's crypto markets, with Bitcoin trading around $64,600 and sentiment remaining in Fear territory. Happy Hodling, Everyone. Hosted on Acast. See acast.com/privacy for more information.

Korea 24 is a daily current affairs show that covers all the biggest stories coming out of South Korea. Every weekday, Korea 24 brings you the latest news updates, as well as in-depth analysis on the most important issues with experts and special guests, providing comprehensive insight into the events on the peninsula.

Business and finance news from the Asia-Pacific. Oil climbed to the highest level in more than a month and bonds fell as US and Iranian attacks escalated, renewing inflation concerns. Stocks stabilized after a technology-led selloff rattled markets last week. Treasury 10-year futures slipped 7/32, with trading in the cash market shut during Asian hours Monday because of a holiday in Japan. Government bonds in Australia and New Zealand also declined on concern that higher oil prices will stoke inflation. Equities were mixed. Nasdaq 100 futures rose 0.2% after Friday’s selloff, as Moonshot AI told investors it plans to go public within six months after its latest model challenged perceptions of US leadership in artificial intelligence. MSCI’s Asia Pacific equity index was little changed, while South Korea’s Kospi index fell 2.8% as traders returned following a holiday on Friday. For a look at the markets, Bloomberg TV Host Avril Hong spoke to Homin Lee, Senior Macro Strategist at Lombard Odier. Brent rose as much as 3.8% to $91.42 a barrel, the highest level since June, with back-and-forth strikes that have expanded beyond military targets. For an outlook of how the oil story is impacting the Asia-Pacific, Bloomberg TV Host Paul ALlen spoke to Illiana Jain, International Ecnomist at Westpac Banking Corporation.See omnystudio.com/listener for privacy information.

From airports to cricket broadcasts, India's family conglomerates keep turning up everywhere. According to the 2024 Barclays-Hurun report, one family's wealth alone equals nearly one-tenth of everything India produces in a year. India is running a version of the economic playbook that South Korea and Indonesia once ran — protect your conglomerates and let them do the building.South Korea came through it, at enormous political and economic cost. Indonesia's economy contracted by 13% in a single year.India is somewhere earlier in that story. In this episode of Daybreak, host Snigdha Sharma asks which ending we are heading toward.**This episode was first published on 26 May, 2026Daybreak is produced from the newsroom of The Ken, India's first subscriber-only business news platform. Subscribe for more exclusive, deeply-reported, and analytical business stories.

European champions Spain won their second World Cup on Sunday, defeating Argentina 1-0 in extra time at MetLife Stadium in East Rutherford, New Jersey.当地时间 7 月 19 日，在东卢瑟福大都会人寿体育场进行的世界杯决赛战至加时赛，西班牙凭借加时进球击败阿根廷夺冠。赢得了他们的第二座世界杯冠军。Ferran Torres scored the only goal of the game in extra time — his first of the tournament — kicking in a cross by Nico Williams, who had a goal 10 minutes early disallowed for a foul.费兰·托雷斯在加时赛中攻入全场唯一进球，也是他在本届赛事上的首粒进球——他接尼科·威廉姆斯的传中破门。威廉姆斯在10分钟前曾有一粒进球因犯规被判无效。A second goal by Torres in extra time was deemed offside and disallowed.托雷斯在加时赛中的第二粒进球被判越位无效。Argentina played extra time down one man, after Enzo Fernandez received a second yellow card and was sent off near the end of regulation.阿根廷在加时赛中少一人作战，恩佐·费尔南德斯在常规时间临近结束时吃到第二张黄牌被罚下场。Spain's only other World Cup championship was a 1-0 victory over the Netherlands in the 2010 tournament hosted by South Africa.西班牙此前唯一一次世界杯夺冠是在2010年南非世界杯上，当时他们以1比0战胜荷兰队。On their way to the championship, Spain knocked out other tournament favorites Portugal and France.在夺冠之路上，西班牙先后淘汰了另外两支夺冠热门球队葡萄牙和法国。Following a surprising 0-0 draw against Cape Verde in its first game, Spain went on to win its next seven games, allowing only one goal while scoring 14.在首场令人意外的0比0战平佛得角之后，西班牙在接下来的七场比赛中取得全胜，攻入14球仅失1球。Spain's defense did not even allow Argentina a shot on goal in the entire 120 minutes of the final, while Argentina's goalkeeper Emiliano Martinez set a World Cup final record with 10 saves.西班牙的防线在决赛120分钟内甚至没有让阿根廷队完成一次射正，阿根廷门将埃米利亚诺·马丁内斯则贡献了10次扑救，创下了世界杯决赛纪录。The loss ended a drive by Argentina, led by Lionel Messi, to win back-to-back World Cups, a feat only accomplished by Italy in 1934-38, and Brazil in 1958-62.这场失利终结了梅西率领的阿根廷队实现世界杯卫冕的征程——这一壮举此前仅有意大利（1934-1938年）和巴西（1958-1962年）完成过。A fourth Argentine victory would have put them in a tie with Germany and Italy for second place with four titles. Brazil, the only nation to appear in every World Cup, has five championships.如果阿根廷第四次夺冠，他们本将以4座冠军与德国和意大利并列历史第二位。巴西队则以5座冠军领跑——巴西也是唯一一支参加了每一届世界杯的国家。This year's World Cup was the first time three countries — the United States, Canada and Mexico — have co-hosted the tournament, with games in 16 cities. It was also the first time the field had been expanded to 48 teams.本届世界杯是首次由三个国家——美国、加拿大和墨西哥——联合主办，比赛在16座城市举行。这也是世界杯首次扩军至48支球队。Japan and South Korea co-hosted in 2002.此前2002年世界杯由日本和韩国联合主办。The next World Cup in 2030 will again see three host countries — Spain, Portugal and Morocco.2030年世界杯将由西班牙、葡萄牙和摩洛哥三个国家联合主办。knocked out /nɒkt aʊt/淘汰favorites /ˈfeɪvərɪts/夺冠热门draw /drɔː/平局shot on goal /ʃɒt ɒn ɡəʊl/射正saves /seɪvz/扑救back-to-back /bæk tə bæk/卫冕，连续夺冠

South Korea has the best performing stock market in the world for the second year running — and it's also in the middle of one of the worst bear markets on earth. The KOSPI is down around 27% from its June peak, more than 1.2 million retail accounts have been hit with margin calls, and hundreds of thousands of Korean investors have been wiped out entirely. But this isn't a story about meme stocks or worthless companies. Samsung Electronics and SK Hynix are enormously profitable businesses at the center of the global AI boom, and the traders buying them were right about the trend. In this video I look at how a national stock index became a two-stock bet on artificial intelligence, how single-stock leveraged ETFs turned ordinary volatility into a mechanical feedback loop, why Korea's retail "ants" took on so much leverage in the first place, and what Victor Haghani's famous biased-coin experiment tells us about how you can be completely right about a market and still lose everything.Patrick's Books:Statistics For The Trading Floor: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://amzn.to/3eerLA0⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Derivatives For The Trading Floor: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ https://amzn.to/3cjsyPF⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Corporate Finance: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://amzn.to/3fn3rvC ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ways To Support The Channel:Patreon: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.patreon.com/PatrickBoyleOnFinance⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Buy Me a Coffee: https://www.buymeacoffee.com/patrickboyle

  What Does This Week’s Market Volatility Mean for Your Retirement Portfolio? By Tom Dupree, Founder, Dupree Financial Group Inflation cooled. The big banks beat expectations. And somehow, it was still a wild week in the market. If you’ve been watching your account balance bounce around and wondering whether any of it has anything to do with the actual value of what you own, here’s the short answer: usually not. Most of what moved the market this week wasn’t new information about businesses — it was leverage, technical trading, and forced selling. That distinction matters more for your retirement than almost anything else you’ll read this month, because it tells you when to act and when to simply hold on. This week’s episode of The Tom Dupree Show walked through four separate stories — cooling inflation, strong bank earnings, a leveraged-ETF blowup on the other side of the world, and a regulatory fight over how often companies should report earnings — that all point to the same lesson: know what you own, know why the price is moving, and don’t confuse someone else’s forced selling with your own emergency. Key Takeaways Inflation cooled to 3.5% year-over-year in June, but the Fed’s new chair has questioned whether the 2% target is even the right one — the ground rules for bonds and rate-sensitive investments could shift. Bank profits this quarter came mostly from paying less on deposits, not from a borrowing boom — a reminder that cash flow, not headlines, tells the real story. A leveraged single-stock ETF collapse in South Korea forced hundreds of thousands of retail accounts into liquidation — a case study in what daily-compounding leverage does to a portfolio. Semiconductor stocks have swung hard on technical signals, not fundamentals — which can create real opportunity for patient, long-term owners. A federal proposal to let companies report earnings twice a year instead of four times has reignited a real debate about transparency versus short-termism. Why Does the Market Feel So Unpredictable Right Now? If you’re 55, 65, or 75 and watching a retirement account that’s supposed to fund the next 30 or 40 years of your life, a week like this one is unsettling. The headlines contradict each other: inflation is cooling, but chip stocks are getting hammered one day and ripping higher the next. Banks are thriving, but somewhere on the other side of the world, hundreds of thousands of retail investors just lost their entire trading accounts overnight. It’s a lot to hold at once, and it’s reasonable to wonder whether any of it should change what you do with your own money. Here’s the honest answer: for most retirees holding a diversified, income-producing portfolio, almost none of it should. But understanding why requires pulling apart what actually happened this week — and separating the noise from the signal. What Actually Happened This Week — The Data Start with the good news. The Bureau of Labor Statistics reported that headline inflation cooled to 3.5% year-over-year in June, with core inflation (which strips out food and energy) coming in at 2.6% — both below what economists expected, and producer prices actually declined for the month. That’s a meaningfully better inflation picture than markets were braced for. But the Fed’s target isn’t necessarily fixed anymore. Kevin Warsh, who was sworn in as Federal Reserve chairman this spring, has openly questioned the assumptions behind the central bank’s longstanding 2% inflation goal and launched a broader review of how the Fed operates. For retirees who own bonds or rate-sensitive income investments, that’s not a footnote — it’s a reason to pay attention to what “the target” even means over the next few years, rather than assuming the old rules still apply. Meanwhile, bank earnings came in strong — but not for the reason most people assume. The lift came primarily from banks paying less to fund themselves (short-term deposit rates have fallen faster than the loans on their books have repriced), not from a fresh wave of borrowing. It’s a good environment for financial stocks, but it’s a funding-cost story more than a booming-economy story, and that distinction matters if you’re trying to judge whether the rally has legs. Then there’s the semiconductor sector, which has been the market’s most volatile corner. Taiwan Semiconductor, the company that manufactures the vast majority of the world’s advanced AI chips, reported June revenue up nearly 68% year-over-year, a genuinely extraordinary number driven by AI infrastructure demand. And yet chip stocks broadly have been whipping up and down for reasons that have very little to do with numbers like that one. A lot of that action is technical: when a stock breaks below a widely watched moving average, institutional trading algorithms are programmed to sell, regardless of what the underlying business is doing. That selling then triggers more selling. It looks like panic. It’s often just mechanics. The starkest illustration of what leverage does in a downturn came out of South Korea this month, where a wave of new single-stock leveraged ETFs tied to semiconductor giants Samsung and SK Hynix triggered margin calls on more than 1.2 million retail trading accounts, with roughly 320,000 to 360,000 of those accounts fully liquidated in a matter of days. These products were designed to move twice the daily price swing of a single stock — which sounds appealing on the way up and is devastating on the way down, because the losses compound daily rather than tracking the stock’s actual return over time. It’s an ocean away from Lexington, Kentucky, but the lesson travels: leverage doesn’t just add risk, it changes the math entirely. Finally, there’s a quieter but genuinely important story developing in Washington. The SEC has proposed letting public companies choose to report earnings twice a year instead of four times, a change championed by President Trump and SEC Chairman Paul Atkins as a way to reduce short-term pressure on management teams. The idea splits reasonable people: less frequent reporting could free executives to run their businesses for the next several years instead of the next ninety days, but it could also mean investors — including retirees who depend on knowing exactly what they own — get less information, less often. This week’s news cycle also included a primetime presidential address in which Trump alleged that newly declassified intelligence showed foreign interference — including from China — in the 2020 election, along with claims of voter registration fraud in Michigan. Election security officials, including the Cybersecurity and Infrastructure Security Agency, have said they’ve found no evidence that any votes were altered in past elections. Whatever your read on the speech, it fed into a broader theme running through the whole hour: how much can you trust the numbers an institution hands you, whether that’s a vote count or a government inflation report? It’s why we do our own research instead of relying solely on government statistics or Wall Street’s sell-side analysts, and it’s the same instinct that should guide how you evaluate any claim, official or otherwise. The Reframe: Manufactured Volatility vs. Real Risk Here’s the framework we come back to on nearly every episode of the show, and it’s the one thing we want you to take from this week’s news: there is a real difference between manufactured volatility and real risk, and confusing the two is one of the most expensive mistakes a retiree can make. Manufactured volatility is what happens when a stock’s price swings because of leverage unwinding, algorithmic trading around technical levels, or funds racing to exit ahead of a quarterly number — not because the underlying business got worse. The Korean ETF collapse is manufactured volatility in its purest form: a Samsung or SK Hynix shareholder holding actual shares, with no leverage, watched the same news and the same earnings power, just without the forced-selling spiral. Real risk is different. Real risk is a company losing its competitive position, cutting its dividend, or piling on debt it can’t service. Real risk should change what you own. Manufactured volatility, more often than not, should not. The trouble is that from the outside, both look identical on a stock chart. A share price falling 10% doesn’t come labeled “manufactured” or “real.” Telling the difference requires actually knowing the business you own — its cash flow, its dividend history, its balance sheet — well enough to judge whether this week’s headline changed anything about that story. That’s the diligence part of the job, and there’s no shortcut around it. How Should Retirement Investors Respond to This Kind of Volatility? At Dupree Financial Group, this is exactly why our approach centers on dividend-paying stocks and bonds rather than chasing whatever sector is moving fastest. When you own a company for the income it generates — not for a price target — a week of manufactured volatility becomes far less threatening, and sometimes it becomes an opportunity. When institutions are forced to sell a good company for reasons that have nothing to do with its fundamentals, the price drop that scares one investor is simply a better entry point for another. That’s not a guarantee of a favorable outcome — all investing involves risk, including the possible loss of principal — but it’s a fundamentally different posture than reacting to every headline. Seven Steps to Retirement-Proof Your Portfolio Against Manufactured Volatility Know what you own, line by line. Pull up your statement and be able to explain, in one sentence each, why you own every major holding. If you can’t, that’s the first thing to fix — not the market. Separate the headline from the business. Before reacting to a price move, ask whether anything actually changed about the company’s earnings, dividend, or balance sheet — or whether it’s a technical or leverage-driven move like the ones described above. Keep leveraged and single-stock ETFs out of retirement money entirely. These products are built for daily traders, not long-term holders. The Korean ETF collapse is a real-world example of what daily compounding leverage can do to an account in a matter of days. Read past the quarterly headline number. Whether or not the reporting-frequency rules change, judge a company on multi-year cash flow and dividend trends, not a single quarter’s beat or miss. Keep a watchlist of quality companies for when panic creates a discount. When forced selling knocks a good business down for reasons unrelated to its fundamentals, that’s the moment long-term investors get paid for their patience. Revisit your income plan, not just your account balance. A retirement portfolio’s job is to produce cash flow you can live on for 30 to 40 years. Judge a volatile week by whether your income stream held up — not by the number on the login screen. Get a second set of eyes on your portfolio. If you’re not sure whether what you own is built to withstand this kind of volatility, or whether you’re carrying more leverage or concentration risk than you realize, that’s exactly what a portfolio review is for. Frequently Asked Questions Is a leveraged ETF a good way to boost my retirement returns? No. Leveraged ETFs reset and compound daily, so their long-term return can diverge sharply from the underlying stock’s actual performance — including large losses even when the stock has technically risen over time. They’re built for short-term traders, not retirement accounts. Does cooling inflation mean the Fed will cut interest rates soon? Not necessarily. While June’s cooler CPI reading supports the case for rate cuts, the Fed’s new chairman has signaled openness to rethinking the central bank’s approach to its inflation target, adding real uncertainty to the timeline for any rate decisions. Why do stock prices swing so much when a company’s earnings didn’t change? Much of the day-to-day movement in popular stocks comes from technical trading, algorithmic strategies tied to chart levels, and leveraged funds being forced to buy or sell — not from new information about the business itself. That’s manufactured volatility, not real risk. What does the debate over quarterly earnings reports mean for individual investors? If the SEC’s proposal is adopted, some companies may report financial results only twice a year instead of four times. That could reduce short-term pressure on management, but it may also mean investors get less frequent, less detailed information about what they actually own. How do I know if my retirement portfolio is built to handle volatility? Start by confirming you can explain why you own every major holding and that none of your retirement money sits in leveraged or single-stock products. A complimentary portfolio review with a fee-only fiduciary advisor is the fastest way to get an honest, unbiased answer. The Bottom Line Weeks like this one will keep happening. Leverage will keep building up somewhere and unwinding somewhere else. Traders will keep reacting to chart levels instead of cash flow. What won’t change is the difference between a business that’s actually worth less than it was last week and a stock price that simply got caught in someone else’s forced selling. Learn to tell those two things apart, build your income around companies you understand, and a volatile week stops being a threat to your retirement — it starts being background noise, or even opportunity. Schedule a Complimentary Portfolio Review If you’re not sure whether your portfolio is built to take advantage of volatility like we saw this week — instead of getting knocked around by it — we’ll take a look. No charge. No pressure. Just an honest conversation about what you own and whether it’s working for you. Call: 859-233-0400  |  Visit: dupreefinancial.com You Might Also Like Catch up on past episodes of The Tom Dupree Show — our full podcast archive, updated every week. Meet the team at Dupree Financial Group — learn about our fee-only, fiduciary approach and the people behind it. [PLACEHOLDER — link to a prior show notes/blog post on dividend investing fundamentals once a confirmed URL is available] About the Author: Tom Dupree is the founder of Dupree Financial Group and host of The Tom Dupree Show, heard weekly across Central Kentucky radio and podcast. With 47 years in the investment business, starting in municipal bonds in 1978, Tom built DFG’s investment philosophy around one idea: retirement money should generate income you can see, not just a balance you hope holds up. Dupree Financial Group is an independent, fee-only fiduciary Registered Investment Advisor based in Lexington, Kentucky. REGULATORY DISCLAIMER: This material is for informational and educational purposes only and does not constitute investment, legal, or tax advice, nor is it a solicitation to buy or sell any security. All investing involves risk, including the possible loss of principal. Past performance of any market index or security is not indicative of future results. Dupree Financial Group is a fee-only fiduciary and does not receive commissions on any products or securities discussed. 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This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

 In this week's episode, David and Ian discuss the S&P 500 continuing to be rangebound, some of the potential concerns with price action of the Nasdaq, margin calls in South Korea, areas of the market holding up well and trying to go out to all time highs. They also discuss which commodities are doing well, especially with the strong U.S. Dollar, international leaders year-to-date, long-term treasuries and interest rates.  

Korea 24 is a daily current affairs show that covers all the biggest stories coming out of South Korea. Every weekday, Korea 24 brings you the latest news updates, as well as in-depth analysis on the most important issues with experts and special guests, providing comprehensive insight into the events on the peninsula.

Comment on this episode by going to KDramaChat.com Today, we're discussing Parasite, the Oscar-winning Korean film directed by Bong Joon Ho and starring Song Kang Ho, Choi Woo Sik, Park So Dam, Jang Hye Jin, Lee Sun Kyun, Cho Yeo Jeong, Lee Jung Eun, and Park Myung Hoon. Joining us for this special episode is our friend Ellen Sullivan, screenwriter and movie critic extraordinaire. We discuss: Why Parasite became the first non-English language film to win the Academy Award for Best Picture, in addition to Best Director, Best Original Screenplay, and Best International Feature Film. The Kim family's elaborate social engineering scheme to infiltrate the wealthy Park household and why trust and referrals make the con possible. The symbolism of the semi-basement apartment, the Park family's hilltop home, and the hidden bunker beneath the house as visual representations of class and social hierarchy. How the film dramatically shifts in tone at its midpoint, transforming from a dark comedy into a suspenseful psychological thriller. Why the Park family's comments about the Kim family's "smell" become one of the film's most powerful metaphors for poverty, class, and social exclusion. The Scholar's Rock (Suseok), its cultural significance, and how it evolves from a symbol of hope and prosperity into an instrument of tragedy. Whether hard work, education, and determination are still enough to achieve upward mobility in modern South Korea—or anywhere else. The themes of plans versus fate, social mobility, inequality, and the myth that anyone can escape the circumstances of their birth. Which characters, if any, are the true "parasites," and whether the relationships in the film are parasitic, commensal, or mutually beneficial. Whether the tragic ending was inevitable and if any of the families truly deserved the fate that awaited them. Ellen's screenwriting analysis of Bong Joon Ho's remarkable construction of the story, including why the house itself functions as the film's McGuffin. The outstanding performances from the all-star cast, including Song Kang Ho, Choi Woo Sik, Cho Yeo Jeong, Lee Jung Eun, and the surprise appearance of Park Seo Jun. The history of Seoul's semi-basement apartments (banjiha), their origins, and why they have become such a powerful symbol in Korean society. The conclusion of Season 14, our announcement that Hospital Playlist will be the show we discuss in Season 15 of K Drama Chat, and a preview of our upcoming special episode talking about Joanna's trip to the Philippines before we begin our next K Drama.

Semiconductor stocks are sliding again as investors question whether the AI trade has moved too far, too fast.Chuck Zodda and Mike Armstrong break down why chip stocks are seeing another sharp pullback, how margin calls in South Korea show the risks of leveraged bets on semiconductors, and why a new Chinese AI model is raising fresh questions about pricing pressure across the AI industry. They also discuss corporate insiders selling stock at a near-record pace, Google's delayed Gemini rollout, Netflix's slowing growth and weaker content outlook, rising oil and gas prices, and why the World Cup is giving Boston bars a major sales boost.

WWJ auto analyst John McElroy reports some workers in South Korea want to work until they are 65 so they don't have to wait for their pension.

On 29th October 2022, 20,000 people were celebrating Halloween in the Itaewon neighbourhood of Seoul in South Korea. One particularly narrow street became very overcrowded, and a huge crush ensued, leading to the deaths of 153 people, with many more injured. A month later, we still don't know exactly what caused the crush.  One of the theories out there is that a rumour spread in the crowd, leading them to believe that a celebrity was in a nearby bar. But a lot of blame has been apportioned to the authorities for poor planning and a slow response to events. A lot of people think that crowd crushes are down to a stampede of people running in panic and crushing others on the floor. Why do things get dangerous in such situations? Are crowd crushes rare or do they happen often? How can I protect myself and others if I end up in an overcrowded area?  In under 3 minutes, we answer your questions! To listen to the latest episodes, click here: ⁠⁠Is Britain the new place to get your wine?⁠⁠ ⁠⁠Why is there such a taboo over the prostate?⁠⁠ ⁠⁠How can I take part in Giving Tuesday?⁠⁠ A Bababam Originals podcast, written and produced by Joseph Chance. First Broadcast: 30/11/2022 Learn more about your ad choices. Visit megaphone.fm/adchoices

00:00 KFC scammed me 06:14 I Celebrated Our Anniversary Way Too Hard 07:13 I'm Very Irresponsible When Alone 08:16 South Korea Is Obsessed with Beauty 10:43 Traveling in Africa Worries Me 13:17 This Guy Hates My Blue Ball 14:04 I'm Trying to Get Fit. It's Hard... 15:19 Which Is Better, iPhone or Samsung? 18:26 the Channel's Biggest Worldwide Audiences 19:16 There Are a Lot of Unknown Hangout Lines in Gta

On this week's episode of the Korea Pro Podcast, John and Joon Ha discuss President Lee Jae Myung's new economic growth strategy for the second half of 2026, including his push for the state to play a much more active role as an investor in South Korea's future industries. They also break down the Bank of Korea's decision to raise the base rate to 2.75%, as inflation, rising energy prices, household debt and a weak won continue to create financial stability concerns. The episode then turns to the Lee administration's proposal to merge South Korea's three main military academies into a single institution, a plan the government says would improve jointness and modernize officer education.  John and Joon Ha also revisit South Korea's defense export ambitions after Hanwha Ocean's loss in Canada's submarine procurement competition, looking at how Seoul is shifting attention to Southeast Asian markets such as Thailand and the Philippines as it seeks to become one of the world's top arms exporters. About the podcast: The Korea Pro Podcast is a weekly conversation hosted by Korea Risk Group Executive Director Jeongmin Kim, Managing Editor John Lee and correspondent Joon Ha Park, delivering deep, clear analysis of South Korean politics, diplomacy, security, society and technology for professionals who need more than headlines. Uploaded every Friday. This episode was recorded on Thursday, July 16, 2026. Audio edited by Alannah Hill

The South Koreans are going all in on drone warfare, announcing that every soldier will be trained to operate drones. This is a relatively inexpensive way to offset the challenges facing South Korea.Join the Patreon here: https://www.patreon.com/PeterZeihan Full Newsletter: https://bit.ly/4eSAVnt

Nvidia is finally derisked enough to buy, according to GMO's Tom Hancock. New York becomes the first state to pass anti-data center development legislation. Plus, the steps South Korea plans to take to calm the Kospi's wild swings.    Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ben and Tom discuss the sharp value-over-momentum rotation with high-flying names getting smashed while broader market breadth improves, SpaceX Starship's critical launch attempt tonight at 5:45 PM local time in South Texas after May's booster spin-out — a launch essential to defending SPCX's $4 billion NASA moon-landing contracts and the broader SpaceX investment thesis — and the levered ETF blowups with South Korea halting new single-stock leveraged ETFs and the Lucid 2x levered ETF liquidating after its NAV went negative.Join our live YouTube stream Monday through Friday at 8:30 AM EST:http://www.youtube.com/@TheMorningMarketBriefingPlease see disclosures:https://www.narwhal.com/disclosure

Investors weigh results from Netflix, Alcoa and Intuitive Surgical. Andrew Goldberg, Chief Global Strategist at Nomura Asset Management, explains how investors should position as earnings season gathers momentum. Evercore's Mark Mahaney analyzes Netflix's results and what they signal for growth, advertising and the broader media landscape. Our Annika Kim Constantino reports on Eli Lilly's move into psychedelics while Michael Yee of UBS discusses the latest wave of biotech M&A and where deal activity could accelerate next. Plus, a look at South Korea's move to ban new single-stock leveraged ETFs and growing short interest in SpaceX as investors debate whether early holders are hedging ahead of future share sales. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Korea 24 is a daily current affairs show that covers all the biggest stories coming out of South Korea. Every weekday, Korea 24 brings you the latest news updates, as well as in-depth analysis on the most important issues with experts and special guests, providing comprehensive insight into the events on the peninsula.

Fernando Augusto Pacheco is here with the final instalment of our World Cup of music. But between South Korea, Turkey, Côte d’Ivoire, Cape Verde, Argentina and Colombia, which nation will strike the right chord? See omnystudio.com/listener for privacy information.

The ceasefire crumbles as the US tries to loosen Iran's grip on the Strait of Hormuz with bombing. Ukraine and its European allies join forces to protect the continent from ballistic missiles. Plus, how will the death of US Senator Lindsey Graham impact US foreign policy? And would you let South Korea's Buddhist monks lead you to love?

Hyperliquid is back in the spotlight after listing China's biggest AI chip IPO ahead of its public debut, showcasing how crypto markets are increasingly driving price discovery before Wall Street. We also cover the launch of EthSystems, a new institutional privacy initiative from Ethereum Foundation researchers, and why Japan, South Korea, and the UK are accelerating crypto-friendly regulation to attract digital asset innovation. Plus, we break down why soft inflation data and strong bank earnings pushed the odds of the Fed holding rates steady above 90%, the regulatory risks facing AI infrastructure after New York paused new data center permits Learn more about your ad choices. Visit megaphone.fm/adchoices

S&P futures are indicating a higher open following a strong Asia session. Semiconductor names rebounded with strong gains seen in South Korea, Japan, Hong Kong, and Taiwan. Mainland China benchmarks were rather flat. European markets are edging lower in early trading. Companies Mentioned: PayPal, CoreWeave, Lionsgate Studios

Korea 24 is a daily current affairs show that covers all the biggest stories coming out of South Korea. Every weekday, Korea 24 brings you the latest news updates, as well as in-depth analysis on the most important issues with experts and special guests, providing comprehensive insight into the events on the peninsula.

Morse Tan is a freedom-fighter who served as ambassador-at-large for Global Criminal Justice during the first Trump administration. Today, he is effectively a political prisoner in South Korea.  Amb. Tan has long spoken truth to power. In particular, he has warned about the lengths to which the Republic of Korea's radical leftists have subverted freedom and elections. He's even courageously done so in South Korea.  Now that the hard Left is fully in power in Seoul under a Communist named Lee Jae-myung, the Ambassador has been prevented from leaving South Korea for over five weeks. That is outrageous. When Lee visited Washington last year, President Trump declined to criticize him over myriad, serious concerns about his guest's decades of anti-American activism. It's high time Mr. Trump let Lee know his present mistreatment of Amb. Tan is utterly unacceptable. This is Frank Gaffney.

Episode 1997 - brought to you by our incredible sponsors: Lucy - Level up your nicotine, get a discount on your first order by using promo code HARDFACTOR at lucy.co/hardfactor 00:00:00 Timestamps 00:02:20 Korea fun facts and culture  00:05:15 South Korea launches app which allows stalking victims to track their stalkers in real time 00:18:50 A new space flashlight that can illuminate 3 square miles is coming to a sky near you 00:28:05 Homeless man finally gets his day in court for shitting on business and wiping with sandwich 00:37:20 Japanese woman charged with sewing her roommate's mouth shut with string For more head over to patreon.com/hardfactor for weekly bonus episodes and most importantly HAGFD! Learn more about your ad choices. Visit megaphone.fm/adchoices

We're taking you on a fast-paced, culture-packed journey through Seoul, South Korea. From digging into crispy Korean fried chicken and sizzling BBQ, to exploring ancient palaces and tea houses, to stepping foot near the tension-filled border of the DMZ, we made the most of every moment. Jamal shares the wild adventure of navigating Seoul's public transit, Brittanie gets cozy with traditional teas and sweets, and we offer travel tips to help you explore Seoul like a pro. Don't miss this episode filled with history, K-culture, epic eats, and real talk about what it's like to squeeze Seoul into just two days!Stay at the ⁠Moxy Hotel⁠, a trendy, metro-accessible hotel with a rooftop barGet an eSim from ⁠Airalo ⁠before you goEat Korean Fried Chicken at KyoChon and Korean BBQ at MyeongdongTake a ⁠DMZ Tour⁠ and explore this forbidden land (you can book with ⁠Julie, our amazing tour guide on Instagram⁠)Wander through the traditional Bukchon Hanok VillageRelax at Chatteul Tea HouseTour the iconic Gyeongbokgung PalaceRide the Namsan Cable Car to the ⁠Observation Deck Seoul Tower⁠ for panoramic nighttime views.Find a great flight deal to Seoul, or anywhere else, by signing up for ⁠⁠⁠⁠Thrifty Traveler Premium⁠⁠⁠⁠ and get flight deals sent straight to your inbox. Use our promo code TSP to get $20 off your first year subscription.—---------------------------------------Shop:⁠⁠⁠⁠ Trip Itineraries ⁠⁠⁠⁠⁠&⁠⁠⁠⁠ ⁠Amazon Storefront ⁠⁠⁠⁠⁠Connect:⁠⁠⁠⁠ ⁠YouTube⁠⁠⁠⁠⁠,⁠⁠⁠⁠ ⁠TikTok⁠⁠⁠⁠⁠, and⁠⁠⁠⁠ ⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠and contact us at travelsquadpodcast@gmail.com to submit a question of the week or inquire about guest interviews and advertising. Submit a question of the week or inquire about guest interviews and advertising.Contains affiliate links, thanks for supporting Travel Squad Podcast!

S&P futures are slightly lower following a volatile Asia session. Japan saw steady gains, Hong Kong tech names were sharply higher in the morning but flattened out near close, South Korea experienced a V-shape rebound, and Mainland China saw modest increase. European benchmarks are all edging lower in early trading.Companies Mentioned: NVIDIA

Korea 24 is a daily current affairs show that covers all the biggest stories coming out of South Korea. Every weekday, Korea 24 brings you the latest news updates, as well as in-depth analysis on the most important issues with experts and special guests, providing comprehensive insight into the events on the peninsula.

Plus: Meta nearly doubles its planned investment in Louisiana data center project. And Intel will ramp up spending on expanded manufacturing in Ireland. Imani Moise hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

Bitcoin remains stuck in its multi-month range as investors wait for this week's key U.S. inflation data and Fed Chair Kevin Warsh's testimony, which could determine the next move for both crypto and traditional markets. We also cover South Korea's sharp market selloff and why its housing market could become a bigger macro risk, rising oil prices as tensions in the Strait of Hormuz disrupt shipping, and why record-low cash on the sidelines may leave markets more vulnerable if selling accelerates. Finally, we discuss the recent pullback in stablecoin supply and why analysts believe it reflects slowing trading activity rather than the end of the crypto bull market. Learn more about your ad choices. Visit megaphone.fm/adchoices

Stalin's Strategic Shift and the Path to the Korean War GUEST: Nick Bunker Throughout 1949, Stalin was skeptical of Kim Il-sung's plan to invade South Korea, doubting North Korea's capability and the strategic rationale. However, in January 1950, Stalin abruptly authorized the planning of the attack. This shift was fueled by several factors: his newfound confidence in Mao as an ally and the perception that the United States would not intervene. Stalin interpreted Dean Acheson's "defensive perimeter" speech and the congressional defeat of the Korean aid bill as signals of American withdrawal from the peninsula. Furthermore, Stalin saw Korea as strategically vital for securing the Soviet Far East and strengthening communist states in Asia. While Washington remained largely oblivious to these plans, Stalin benefited from an abundance of intelligence gathered simply by reading American newspapers, which were filled with leaks about the "confusion" and "dissension" within the Truman administration. (6)

The US demands a public guarantee from Iran that the Strait of Hormuz is open and that ships will not be targeted as they pass through, to ensure that talks can move forward. President Trump says both sides have agreed to continue talks, despite the escalation in hostilities. Mediators from Qatar are travelling to Iran to try to salvage the fragile peace deal. Also: there's relief in Nigeria after all the children and teachers who were kidnapped from a school in Oyo State in May are rescued. We have a special report about the increasing number of Russian drones and bombs that are killing civilians and causing severe damage in the Ukrainian city of Zaporizhzhia. Apple files a lawsuit against OpenAI, accusing the artificial intelligence company of stealing trade secrets. Deforestation is slowing down in the Brazilian Amazon, but the presidential election in October could be crucial in determining its future. Spain beat France to reach the semi-final of the men's football World Cup. Palaeontologists in Thailand discover a new species of dinosaur, and we visit a Buddhist temple in South Korea that's hosting dating retreats to help boost population growth.The Global News Podcast brings you the breaking news you need to hear, as it happens. Listen for the latest headlines and current affairs from around the world. Politics, economics, climate, business, technology, health – we cover it all with expert analysis and insight. Get the news that matters, delivered twice a day on weekdays and daily at weekends, plus special bonus episodes reacting to urgent breaking stories. Follow or subscribe now and never miss a moment. Get in touch: globalpodcast@bbc.co.uk Photo: Map of the Strait of Hormuz and Iran taken June 22, 2025. Credit: REUTERS/Dado Ruvic

Headline: Pacific Watch: High Swells and Beach Controversies in San Diego Guest: Jeff Bliss Jeff Bliss reports from Sail Bay, San Diego, discussing the arrival of massive 30-foot El Niño swells. The conversation covers local beach controversies regarding yoga permits, the upscale enclave of Laguna Beach, and an unusual early-season arson fire in the nearby hills. (1)Headline: Las Vegas Sports Expansion and the "Secret Menu" at In-N-Out Guest: Jeff Bliss Bliss discusses the potential for an NBA team in Las Vegas, possibly named the "Las Vegas Jacks." He also highlights the famous In-N-Out "secret menu," explaining "animal style" burgers and fries. Seattle remains a top contender for a returning NBAfranchise alongside Las Vegas. (2)Headline: The Myth of Birthright Citizenship and the 14th Amendment Guest: Richard Epstein Professor Richard Epstein analyzes birthright citizenship, arguing the 14th Amendment's original intent excluded foreigners. He critiques the concept of "tourist babies" and suggests the president's plenary naturalization powers could be used to restrict entry for pregnant mothers seeking citizenship for their children. (3)Headline: Presidential Immunity and the Legal Challenges Facing Donald Trump Guest: Richard Epstein Epsteindiscusses the Supreme Court's 2024 immunity ruling, distinguishing between official and unofficial acts. He critiques President Trump's private business ventures, like cryptocoin deals, as non-official acts subject to litigation. Epstein also argues that Todd Blanche is disqualified from being Attorney General. (4)Headline: Lancaster County's Economy: Weather Disruptions and Inflationary Pressures Guest: Jim McTagueJim McTague reports on violent thunderstorms in Lancaster County that caused widespread blackouts. Despite the weather, the economy remains resilient, with full hotels and strong retail demand. However, rising gasoline prices and wage-driven inflation are impacting the local community's purchasing power. (5)Headline: Italian Summer: Over-Tourism, Extreme Heat, and the Charm of Bassano del Grappa Guest: Lorenzo Fiori Lorenzo Fiori describes record-breaking heat and humidity in Italy, suggesting tourists visit Bassano del Grappato avoid crowds. He discusses the historic Palio horse race in Siena and recommends enjoying grappa with chocolate and ciabatta bread while overlooking the beautiful Dolomite mountains. (6)Headline: Strategic Stability and the Erosion of the Nuclear Taboo Guest: Peter Huessy Peter Huessy explores the weakening nuclear taboo, noting Putin's near-use of tactical nukes in Ukraine. He contrasts this with historic deterrence during the Cuban Missile Crisis, where Kennedy provided Khrushchev a "way out." Huessy emphasizes that hybrid warfare now complicates traditional deterrence strategies. (7)Headline: The Value of Deterrence in a Proliferating World Guest: Peter Huessy Huessy argues that the U.S. nuclear umbrella remains vital for protecting allies like South Korea from North Korean aggression. He asserts that nuclear weapons are cost-effective compared to massive conventional forces. Without a credible deterrent, reckless actors are more likely to trigger catastrophic global conflicts. (8)Headline: The New Space Race: Chinese Advances and Orbital Threats Guest: Henry Sokolski Henry Sokolskidiscusses China's Long March 10B booster, which successfully demonstrated first-stage recovery. He warns about potential nuclear mines in orbit and the challenge of verifying them. Additionally, Russia and China are reportedly collaborating to disable the Starlink satellite network in Ukraine. (9)Headline: Nuclear Safety and the Fog of War in Iran Guest: Henry Sokolski Sokolski examines reports of strikes near Iran's Bushehr nuclear power plant, noting that targeting reactors is legal if they serve military purposes. He expresses concern over the lack of a baseline inventory for Iran's centrifuges and enriched uranium, which complicates future nuclear negotiations. (10)Headline: Main Street Resilience: Small Business Success in 2026 Guest: Gene Marks Gene Marks reports that American small businesses are thriving, with strong consumer spending and rising revenues. He notes that wages are outpacing inflation, contributing to historical levels of personal wealth. While some use AI for content, most businesses still avoid AI for core transactions. (11)Headline: AI Productivity vs. Headcount in the Small Business Sector Guest: Gene Marks Marks argues that AI is not replacing workers but rather increasing productivity for existing staff. He highlights innovative applications like the "AI Shop Advisor" at The Vitamin Shoppe and automated inventory management tools like Zenput. Small businesses continue to face a shortage of labor. (12)Headline: The Secretive Construction of Iran's Pickaxe Mountain Guest: Andrea Stricker Andrea Stricker warns of a deeply buried nuclear site at Pickaxe Mountain, which may house advanced centrifuges. The facility is located two-thirds of a mile underground, making it extremely difficult to disable via airstrikes. Stricker recommends the U.S.demand IAEA inspections to verify compliance. (13)Headline: Latin America's Shift Toward Democratic Capitalism Guest: Conrad Black Conrad Black observes a "tidal wave" of reform across South America as nations reject left-wing "gangster" governments in favor of market economies. He highlights the success of Colombia's President Abelardo De La Espriella, a Trump ally. This regional shift is significantly influenced by Trump's economic model. (14)Headline: SETI Protocols and the Scientific Search for Extraterrestrial Life Guest: Michael Garrett Michael Garrett introduces updated SETI protocols for handling potential contact with extraterrestrial intelligence. The guidelines emphasize the scientific method and verification to avoid false alarms. Garrett suggests searching for machine technology or waste heat from advanced civilizations across the electromagnetic spectrum. (15)Headline: SETI vs. UAPs: Distinguishing Science from Folklore Guest: Michael Garrett Garrett clarifies that SETIfocuses on astronomy, not atmospheric phenomena like UFOs or UAPs. While supportive of UAP research to understand drones or rockets, he remains skeptical of extraterrestrial visits. These updated guidelines aim to assist astronomers who might stumble upon technological signatures. (16)Each segment now runs as a single paragraph, headline through tail.

Headline: The Value of Deterrence in a Proliferating World Guest: Peter Huessy Huessy argues that the U.S. nuclear umbrella remains vital for protecting allies like South Korea from North Korean aggression. He asserts that nuclear weapons are cost-effective compared to massive conventional forces. Without a credible deterrent, reckless actors are more likely to trigger catastrophic global conflicts. (8)