Podcasts about European Commission

Plus: IPO documents show Softbank-backed data center venture issued perks to land OpenAI. And SLB acquires data-center cooling company Kelvion for $4.1 billion. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Plus: BYD's overseas push drives quarterly profit growth. And Google will change how it ranks certain websites in most of Europe to appease antitrust regulators. Julie Chang hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Why a job at the European Commission is a dream for many, but a disappointment for some. Plus, why fast fashion audit reports often miss the reality of working conditions in factories. And a migration special starting with the Pope's remarkable stance and why that matters at a time when Europe is implementing more restrictive rules. ++ https://shorturl.at/YmTsY https://shorturl.at/Lazzj ++ ?maca=en-podcast_inside-europe-949-xml-mrss

Cristina Gomez reviews the latest UFO / UAP news and covers a new Euronews investigation showing the European Commission has secretly monitored UFOs since 2023, a Malaysian astronomer case tied to nuclear and military sites, testimony from European airline pilots, and a new CBS News poll showing eighty four percent of Americans believe their government is withholding UFO information. To see the VIDEO of this episode, click or copy link - https://youtu.be/1PP9X93Vv4UVisit my website with International UFO News, Articles, Videos, and Podcast direct links -www.ufonews.co00:00 - EU's Hidden UFO Secret00:38 - UFO Documents Exposed01:09 - Malaysia's UFO Case02:27 - Pilots Confirm UFO Sightings03:34 - New UFO Poll Numbers05:06 - UFOs Near Nuclear Sites06:08 - Europe's UFO Response Become a supporter of this podcast: https://www.spreaker.com/podcast/strange-and-unexplained--5235662/support.

Your morning briefing. All the news you need to start your day.On today's podcast:(1) JPMorgan Chase's Jamie Dimon warned UK Chancellor of the Exchequer John Healey in a call last week against higher taxes on banks as Prime Minister Andy Burnham’s government prepares its budget for October, the Financial Times reported.(2) Europe's lenders are hopeful the European Commission will tackle some of their biggest complaints. The continent is weighing a deregulation push after President Donald Trump’s administration vowed to unshackle banks from what it sees as excessive curbs introduced after the 2008 financial crash.(3) President Donald Trump said he’s told the Pentagon to “substantially reduce” joint military exercises with South Korea, indicating his shift was driven by frustration the longtime US ally hadn’t provided more support for his war with Iran.(4) Middle Eastern oil producers are pressing ahead with shuttling large volumes of crude out of the Persian Gulf, helping keep a lid on prices and assuaging fears of an energy-driven inflation spike, even as the Iran war drags on.(5) French Prime Minister Sebastien Lecornu will hold a crisis meeting Monday to respond to the cyberattack disclosed last week targeting the country’s tax collection agency.(6) Emergency services were attempting to control a large wildfire in the east of Belgium on Sunday, after the blaze destroyed about 2,700 hectares (6,700 acres) of a nature reserve and forced about 600 residents to evacuate in an area near the German border.Podcast Conversation: For Chefs and CEOs Alike, Vision Is PricelessSee omnystudio.com/listener for privacy information.

Jack Horgan-Jones and Ellen Coyne join Hugh to look back on the week in politics:Simon Harris has lobbied the European Commission over the prospect of Ireland's Central Bank once again being responsible for approving Israeli state bonds. Opposition parties have said the bonds are used to raise money for Israel's military campaigns. Ultimately, aside from some political messaging, it's an issue the Government can do little about.Excise cuts implemented in response to last spring's fuel protests are due to start tapering next month, just as fuel prices are beginning to rise again. With the disruptive protests still a painful memory and the Budget coming into view, Jack Chambers and Simon Harris are in an unenviable position. How will they play it?News that the Department of Children and Equality will spend money on a campaign to warn about the misogyny of the “manosphere” and “tradwife” influencers who “promote restrictive, stereotypical roles for women and girls” has enraged culture warriors and prompted a debate on the socioeconomic pressures that make working and caring in the home an impossibility for many families. Should the Government stay out of such debates and focus instead on structural issues that hold people back from living their lifestyle of choice?The Government's recent lack of transparency around two reports, one on Aughinish Alumina and another on data centres, left a lot to be desired.Entertaining documents released to The Irish Times under the Freedom of Information Act have cast light how two prominent pols - Mayor of Limerick John Moran and Minister for Justice Jim O'Callaghan - go about their business.And finally the panel pick their favourite IT stories of the week.Would you like to receive daily insights into world events delivered to your inbox? Sign up for Denis Staunton's Global Briefing newsletter here: irishtimes.com/newsletters/global-briefing/ Hosted on Acast. See acast.com/privacy for more information.

In April 2026, the European Commission adopted interim guidance stipulating that solar and battery storage projects using inverters or power conversion systems sourced from high-risk countries would be ineligible for EU funding, citing concerns over cybersecurity and grid resilience. Among the affected countries is China, Europe's dominant supplier of clean energy technologies. In this episode of Energy Evolution, host Eklavya Gupte is joined by Lena Dias Martins, electricity pricing reporter at S&P Global Energy Platts, to explore the implications of this policy for Europe's rapidly expanding solar and battery storage sectors. They examine how markets have responded, which regions may be most affected, and whether viable alternatives to China-made inverters are available at scale. The episode features Cormac Gilligan, director of clean technologies and supply chains at S&P Global Energy Horizons, who explains how the restrictions could signal the start of a broader global shift toward greater diversification of clean energy supply chains. We also hear from Jan Krčmář, executive director of the Czech Solar Association, who shares the industry perspective on the practical challenges facing developers and installers, how the sector is responding to the new requirements, and what the changes could mean for solar deployment across Europe in the years ahead.

In April 2026, the European Commission adopted interim guidance stipulating that solar and battery storage projects using inverters or power conversion systems sourced from high-risk countries would be ineligible for EU funding, citing concerns over cybersecurity and grid resilience. Among the affected countries is China, Europe's dominant supplier of clean energy technologies. In this episode of Energy Evolution, host Eklavya Gupte is joined by Lena Dias Martins, electricity pricing reporter at S&P Global Energy Platts, to explore the implications of this policy for Europe's rapidly expanding solar and battery storage sectors. They examine how markets have responded, which regions may be most affected, and whether viable alternatives to China-made inverters are available at scale. The episode features Cormac Gilligan, director of clean technologies and supply chains at S&P Global Energy Horizons, who explains how the restrictions could signal the start of a broader global shift toward greater diversification of clean energy supply chains. We also hear from Jan Krčmář, executive director of the Czech Solar Association, who shares the industry perspective on the practical challenges facing developers and installers, how the sector is responding to the new requirements, and what the changes could mean for solar deployment across Europe in the years ahead.

‘The populists, nationalists, stupid nationalists, they are in love with their own countries', declared Jean-Claude Juncker, the former president of the European Commission, in May 2019. This familiar retort of a leading figure in the globalised elite exemplifies the recent fashion for regarding any manifestation of national pride with contempt. But what was intended as a snide insult about love of country then, now seems to have been embraced with pride by millions throughout the West. Whether it's the seeming unstoppable rise of national populist parties throughout Europe or the popular MAGA support for Donald Trump's pursuit of national interest, it seems that unapologetic nationalism is in the ascendant. In Britain, one very visual grassroots campaign, Operation Raise the Colours, illustrates this shift. Local people have been inspired to hang thousands of Saint George's Cross and Union flags on lampposts all over the country. And as quickly as local councils rip them down, flags are defiantly raised again, a symbolic gesture of an unashamed nationalist pride. This is a momentous shift in the West because, until recently, many felt inhibited about voicing their patriotic sentiments in the wake of an implicit but dogged, top-down cultural crusade against nationalism. Its negative associations with national rivalries, war and fascism continue to resonate.  Many commentators are perhaps understandably queasy. Is this an emboldened demonstration of xenophobia and bigotry? However, others point out that the growth of supranational institutions, as a counter to these alleged negatives, has undermined the legitimacy of the nation-state per se. This has led to official scepticism of borders, an embrace of mass migration and an associated disregard for the specific privileges of national citizenship. Meanwhile, the gradual detachment of the governing elites from the institutions of the nation has contributed to their alienation from their own nation's culture and popular sentiment. In many places, this has included increasing institutional hostility to the country's historic legacy, presented as a national story of shame, slavery, colonialism, oppression. But perhaps the governing classes' loss of ability to inspire loyalty and pride in the nation has fomented a backlash. Now a people's rebellion seems determined to take back control of the national narrative. Meanwhile, the ideology of globalisation is rapidly unravelling. Postwar international legal agreements and institutions, such as the European Convention on Human Rights, are now exposed as barriers to pursuing national interest in global affairs. Is the national sovereignty now emerging a key to the conduct of global affairs once more? At a time when many feel an increasing sense of isolation, of being disconnected from any larger shared project, is a return to national identity an inevitable, even welcome trend? Or does it reflect an absence of alternatives, a feeling that ordinary people have little else to hold on to? Does nationalism still retain its worrying, discredited associations with everything from racism to warmongering? Or is nationalism a return to our democratic roots, a force capable of forging national solidarity that can overcome the divisive fragmentation of demographic, cultural, ethnic, identitarian and political changes that have left citizens feeling like strangers in their own land? Can political elites learn to love their country again, and allow national interest to guide policies in the best interest of their nation state? SPEAKERS Ada Akpala writer and commentator Dr Rakib Ehsan author, Beyond Grievance: what the Left gets wrong about ethnic minorities Eric Kaufmann professor of politics, University of Buckingham; advisory council member, Free Speech Union; author, Taboo: How Making Race Sacred Led to a Cultural Revolution Professor Robert Tombs emeritus professor of French history, Cambridge University; co-editor, History Reclaimed Bruno Waterfield Brussels correspondent, The Times CHAIR Claire Fox director, Academy of Ideas; independent peer, House of Lords; author, I STILL Find That Offensive!

"If you go together and if you fight for it, then you are visible."Over the last four episodes of this series, we've heard about the daily struggles, exhaustion, the invisibility, and the structures that keep these burdens in place. In our final episode, we ask cleaners themselves what resistance looks like.From “Justice for Janitors” across the Atlantic, to the Cleaners Parliament in the Netherlands,this episode traces the rise of worker-led organising—and shows how cleaners are turning isolation into solidarity, and silence into a demand for justice that can no longer be ignored.In this episode, we hear from:

Wade Sutton, PwC's International Tax Leader for the Washington National Tax Services Office, fills in as host while Doug is away on assignment. Wade welcomes Will Morris, PwC's global tax policy lead and former chair of the AmCham EU Tax Committee. In this episode, Wade and Will discuss the EU Foreign Subsidies Regulation (FSR). They cover its state-aid origins, reach into M&A and public procurement, and early enforcement record. The episode examines the European Commission's recent assessment, possible reductions in reporting burdens, and the three-step analysis from foreign financial contribution (FFC) to subsidy to market distortion. The conversation also covers tax incentives and credits, Inflation Reduction Act and Pillar Two interactions, data-collection challenges, geopolitical considerations, standstill risks, and practical steps before an EU transaction or procurement bid.

Helene Banner shares her vision about feminine and authentic leadership, building a business that aligns with your personality and your energy, and the importance of recognizing that rhythm plays a significant role in women's lives.She is an international keynote speaker and leadership mentor. Since 2020, her initiative “Let's Just Be Imperfect, Ladies” has inspired women to embrace their authentic leadership style with confidence. In summer 2026, she will return to the European Commission in Brussels, where she previously served as an EU spokesperson and speechwriter for Commission President Jean-Claude Juncker.www.helenebanner.com

Can regulators promote growth and competitiveness while preserving financial stability? In this episode of Current Account, Clay is joined by IIF's Kyle Grieser, Director, Regulatory Affairs, and Miguel Lobo, Policy Advisor, to examine two major developments shaping the future of banking regulation: the ongoing implementation of Basel III and the European Commission's new banking competitiveness agenda. They discuss how post-crisis reforms have strengthened the banking sector, why policymakers are increasingly focused on regulatory simplification and modernization, and what the latest proposals could mean for banks in the United States, Europe, and the United Kingdom. The conversation also explores whether global regulators are finally approaching the end of the Basel III process and what comes next for cross-border regulatory alignment and growth. Programming note — Current Account will return in September after a summer break. This IIF Podcast was hosted by Clay Lowery, Executive Vice President, Research and Policy, with production and research contributions from Christian Klein, Digital Graphics and Production Associate and Miranda Silverman, Senior Program Assistant.

The EU just fined Google €890M for making it hard to steer users to cheaper web stores — another crack in the 30% wall, and genuinely good news for every developer. That's the lead of a quieter, summer-holiday news week, with Felix flying solo while Matej and Jakub are at ChinaJoy.Felix Braberg walks two stories and a charts tour. First, the European Commission fined Google €890M (split €460M + €430M) under the Digital Markets Act for antitrust practices — preventing developers from freely informing users about cheaper offers and steering them to web stores or third-party channels. Google has 60 days to comply or face periodic penalties of up to 5% of worldwide turnover (~$403B), and it's another blow in the slow unwinding of the 30% app-store tax that companies like FastSpring exist to route around. Second, a Seeking Alpha analysis argues the market keeps underestimating AppLovin: the stock came under pressure in 2026 (swept up in the "SaaS apocalypse" sell-off after the CloudX agentic-buying launch), but the fundamentals are strong, the gaming runway is bigger than assumed, and as the dominant mediation player (AppLovin Max), it holds a structural advantage. Then the US charts: Smash Fest (Flow Games, Turkey) is now #1 in free downloads — beating Roblox — followed by Meow Doku and Vita Mahjong (same studio), with the standout story being that a copycat of Smash Fest (Royal Smash by Cypher Games) has itself cracked the top six out of ~70 clones. Plus Level Devil sold and scaling under new ownership, EA Sports FC still strong post-World Cup, and Turkey vs China duking it out for chart dominance.The through-line of a quiet week: the 30% tax keeps cracking, AppLovin keeps winning, and the copycat economy is faster and more brutal than ever.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━⏱️ TIMESTAMPS00:00 Solo news week — Matej and Jakub at ChinaJoy00:40 Google fined €890M under the Digital Markets Act04:00 Why it's another crack in the 30% wall05:00 AppLovin: why the market keeps underestimating it07:30 US charts — Smash Fest beats Roblox08:30 The copycat that cracked the top six10:00 Level Devil sold, EA Sports FC, and Turkey vs China---------------------------------------This is no BS gaming podcast 2.5 gamers session. Sharing actionable insights, dropping knowledge from our day-to-day User Acquisition, Game Design, and Ad monetization jobs. We are definitely not discussing the latest industry news, but having so much fun! Let's not forget this is a 4 a.m. conference discussion vibe, so let's not take it too seriously.Panelists: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jakub Remia⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠r,⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Felix Braberg, Matej Lancaric⁠Join our slack channel here: https://join.slack.com/t/two-and-half-gamers/shared_invite/zt-3bckldvr8-8PXvzciMWdheOzED9hq0SA---------------------------------------Matej LancaricUser Acquisition & Creatives Consultant⁠https://lancaric.meFelix BrabergAd monetization consultant⁠https://www.felixbraberg.comJakub RemiarGame design consultant⁠https://www.linkedin.com/in/jakubremiar---------------------------------------Please share the podcast with your industry friends, dogs & cats. Especially cats! They love it!Hit the Subscribe button on YouTube, Spotify, and Apple!Please share feedback and comments - matej@lancaric.me---------------------------------------If you are interested in getting UA tips every week on Monday, visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠lancaric.substack.com⁠⁠⁠⁠⁠⁠ & sign up for the Brutally Honest newsletter by Matej LancaricDo you have UA questions nobody can answer? Ask ⁠⁠⁠⁠⁠⁠⁠⁠Matej AI⁠⁠⁠⁠⁠⁠ - the First UA AI in the gaming industry! https://lancaric.me/matej-ai

Our Summer Playlist rolls on this week with Mark Lewis, Partner and Managing Director at Climate Finance Partners LLC. David Greely sits down with Mark to discuss the recently released European Commission's EU ETS review proposals and what they'll mean for the outlook for the EU ETS and other carbon markets.

Microsoft surged 15% on its fastest cloud growth since 2022, while Meta slid 10% defending its AI spending. Aschenbrenner's hedge fund unwound positions after the AI rout, the EU targeted ChatGPT under the DSA, and airlines let AI set fares. Microsoft's Shares Surge on Fastest Cloud Growth Since 2022 (Bloomberg) Meta Falls After Defending AI Bets to Skeptical Investors (Bloomberg) AI investor Leopold Aschenbrenner forced to unwind all public stock positions after steep losses, sources say (CNBC) Source: the European Commission plans to designate OpenAI's ChatGPT and Roblox as "very large online platforms" under the DSA as soon as August (Bloomberg) Airlines are using AI to adjust seat prices more quickly, capturing more revenue while narrowing the pricing gaps that once let travelers find bargain fares (Bloomberg) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

"As a migrant working here… it's not easy, and it has never been easy."In many European countries, a staggering proportion of cleaners come from migrant backgrounds. This isn't a coincidence. It's a pattern shaped by discriminatory immigration policies, labour market barriers, and the systematic failure to recognise qualifications and skils gained elsewhere.In this episode, we explore the intersection of migration, gender, labour exploitation, and the fight for dignity. We hear how visa status compounds precarity, how unrecognised qualifications trap skilled professionals in low-paid work, and how migrant workers— women and men—are fighting back against a system designed to keep them invisible.In this episode, we hear from:

Rescue efforts are underway following an explosion at a shopping mall in southwest Japan, triggered by a powerful 7.1-magnitude earthquake (01:02). The European Commission says the fast-spreading fires in France and Spain have exceeded their capacity to respond, prompting calls for cross-border firefighting aid from member nations (23:52). Beijing has slammed the Democratic Progressive Party authorities in Taiwan for rejecting the entry applications of a Shanghai delegation to Taipei for a ceremony marking the public debut of two red pandas gifted by the mainland (32:21) .

Download MP3 | Watch Video Episode Full Timestamps: https://docs.google.com/document/u/1/d/e/2PACX-1vSKkGchDQV5RvTwa2uFyOu3z4YHl-n8vPz90khvgMEew2dZ7dzKuGJ8Sf2wZ1-qsPvt3gs5qQ7uYTMJ/pub Watch full episodes: https://www.youtube.com/@CastleSuperBeastArchive NEW CASTLE SUPER BEAST "LEGACY" SHIRT & DESKMAT AVAILABLE NOW: https://www.orchideight.com/collections/castle-super-beast Go to http://heroforge.com and use code CASTLE to get 5% off on all orders of physical miniatures. Docket: According to wowhead, reddit and others a game master intervened in a +23 NPX and ported himself into the dungeon to kill some trash for the group who finished the last boss under %. The group is friends with the GM and were in VC at the time and asked for him to do them a solid.  Blizzard fires World of Warcraft game master who insta-killed bosses for friends It will also be "taking action" against the players who were involved. The Fire's Edge, the first new DLC for Darkest Dungeon since 2020, is releasing on August 18th. The Duelist and Runaway, heroes who debuted in Darkest Dungeon II, bring their unique abilities to bear against horrors that lurk beneath the manor.  Disney's Former CEO Seems To Have No Memory Of Approving Kingdom Hearts The US $55 billion leveraged buyout of Electronic Arts (EA) has been approved by the European Commission's competition regulators. Adult Aang concept art quotes "According to ChatGPT" The crew is anti AI and respond UMvC3 Community Edition - Character Reveal Trailer 3

The revised European Sustainability Reporting Standards (ESRS (2026)) introduce significant revisions, simplifications, clarifications, and new reporting reliefs for companies reporting—or preparing to report—under the CSRD. This episode discusses the European Commission's July 2026 revisions, including changes to the materiality assessment, more flexibility to entities in relation to GHG emissions reporting, anticipated financial effects, and phase-in provisions. It also explains the reporting choices and reliefs available.For more on the revised ESRS, see our publication ESRS (2026)—a deep dive into the revised standards.Looking for the latest developments in sustainability reporting? Follow this podcast on your favorite podcast app and subscribe to our weekly newsletter to stay in the loop.About our guestsKatie Woods is a senior director in PwC's Global Corporate Reporting Services - Sustainability group advising on sustainability and international accounting standards. Katie specializes in the new and emerging ESG reporting frameworks working across the PwC network. She has over 30 years of experience working with a broad range of companies.Katie DeKeizer is a director in PwC's Corporate Reporting Services team. She works on sustainability reporting under multiple frameworks including ESRS, the IFRS Sustainability Disclosure Standards, and the GHG Protocol. She has experience developing technical guidance and delivering training on sustainability reporting.About our hostHeather Horn is the PwC National Office Sustainability and Thought Leader, responsible for developing our communications strategy and conveying firm positions on accounting, financial reporting, and sustainability matters. In addition, she is part of PwC's global sustainability leadership team, developing interpretive guidance and consulting with companies as they transition from voluntary to mandatory sustainability reporting. She is also the engaging host of PwC's accounting and reporting weekly podcast and quarterly webcast series. Transcripts available upon request for individuals who may need a disability-related accommodation. Please send requests to us_podcast@pwc.com.Did you enjoy this episode? Text us your thoughts and be sure to include the episode name.

IT'S been years of waiting and lobbying, but we finally have Europe's proposals for how the EU Emissions Trading System will look beyond 2030. The European Commission has released its long list of proposals for how to reform the cap-and-trade scheme, including how much shipping pays, and how much of the proceeds it gets back. Shipowners, like most European businesses, have to buy and surrender credits called allowances for each tonne of carbon they emit. The industry reckons it will pay about 90 billion euros into the scheme between 2030 and 2040, and it wants that money reinvested in decarbonisation. To remedy that, the European Commission wants to include earmarking 110 million allowances in a mechanism called Sustainable Maritime Alternative Propulsion, or SMAP, to subsidise low and zero-emission fuels. That's about ten billion euros, give or take. It will crack down on evasive port calls by including some 20 more neighbouring non-EU ports in the schem. And it will also cover smaller vessels, with the minimum gross tonnage limit lowered from 5000 to just 400. Are the revisions fair? Has shipping got what it's asked for? To find out, Lloyd's List senior editor Declan Bush is joined by: Sotiris Raptis, secretary general of European Shipowners Simon Bergulf, vice president for environment and climate, World Shipping Council Delphine Kaczorowski, EU advocacy manager, Opportunity Green

-The Open Source AI Alliance argues that to best defend against attacks in the age of AI models like Anthropic's Mythos 5, security researchers need access to both open and closed frontier models. -The European Commission has accused TikTok of failing to protect the privacy of accounts belonging to minors, since they're visible to the public by default. -As first reported by The Verge, Meta is pausing its rate limits for the accessibility feature that uses the glasses' speakers to amplify the voice of who you're talking to. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Plus: SAP shares rise after earnings beat. And CATL profit surges on booming battery demand. Imani Moise hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Recorded at the PSE-CEPR Policy Forum, Paris.In 2019 the IMF called the increasing adoption of industrial policy: "The return of the policy that shall not be named". No one is scared to name it in 2026. Governments in rich and poor economies alike are intervening to change what their countries produce, and the pace has picked up sharply.Zsóka Kóczán (EBRD) was one of the leads on the Transition Report 2024-25, which draws on a database of more than 31,000 industrial policies in 150 economies. She talks to Tim Phillips about who is using these policies, and the mistakes that happen when they aren't managed well. They multiply before elections, they discriminate against foreign interests, many are firm-specific - and until recently few had an end date, whether they worked or not. Picking winners is hard. Letting go of losers is even harder, she warns. The research behind this episode:EBRD. 2024. "Transition Report 2024-25: Navigating Industrial Policy." London: European Bank for Reconstruction and Development. The digital edition, with country assessments and interactive charts, is at 2024.tr-ebrd.com.To cite this episode:Phillips, Tim, and Zsoka Koczan. 2026. "Navigating industrial policy." VoxTalks Economics (podcast).About the guestZsoka Koczan is Associate Director and Lead Economist in the Office of the Chief Economist at the European Bank for Reconstruction and Development, where she works on the Transition Report, edits the Regional Economic Prospects and runs the Life in Transition Survey. Before joining the EBRD she was an economist at the International Monetary Fund. She holds a PhD in economics from the University of Cambridge, and her research spans income disparities within countries, migration and inequality.Research cited in this episodeMoving the goalposts. The analysis of industrial policy objectives in the report is developed in Koczan, Zsoka, Victoria Marino, and Alexander Plekhanov. 2025. "Moving the Goalposts: The Changing Objectives of Industrial Policy." EBRD Working Paper No. 311. It codifies the stated objectives of more than 31,000 industrial policies using large language model processing; in the EBRD regions and other emerging markets, around 75% of policies pursue multiple objectives, and more than 10% pursue three or more.The Juhász, Lane, Oehlsen and Pérez dataset. The report builds on the industrial policy dataset assembled by Réka Juhász, Nathan Lane, Emily Oehlsen, and Verónica C. Pérez in "The Who, What, When, and How of Industrial Policy: A Text-Based Approach" (STEG Working Paper No. WP050, 2023), which uses natural language processing to identify industrial policies in the Global Trade Alert repository; the EBRD team extended its coverage of emerging markets.The Global Trade Alert. An independent monitoring initiative that has documented policy interventions affecting international commerce since 2009; it is the underlying source for both datasets above.The policy that shall not be named. Cherif, Reda, and Fuad Hasanov. 2019. "The Return of the Policy That Shall Not Be Named: Principles of Industrial Policy." IMF Working Paper No. 19/74. The title captures how unfashionable the subject was among economists before its recent revival, which is Koczan's point in raising it; the interventions themselves never went away.Reagan's nine words. In 1986 President Ronald Reagan remarked that the nine most terrifying words in the English language were "I'm from the government and I'm here to help." Koczan cites the line as a marker of the era when industrial policy fell out of favour, and as a reminder that government failures can replace the market failures these policies are meant to correct.The Industrial Accelerator Act. The European Commission's proposal, presented in March 2026, would introduce "Made in EU" and low-carbon requirements for public procurement and support schemes in strategic sectors. Koczan cites it as evidence that the upward trend in industrial policy adoption is continuing.More VoxTalks Economics episodesEurope in the Middle, recorded at the same forum, in which Pol Antras and Beata Javorcik ask how Europe should make policy when it is caught between the US and China in a realigning world trade system.Addressing Global Imbalances, also from the forum, in which Gita Gopinath and Philip Lane discuss the third wave of global imbalances and what central banks can and cannot do about it.Related reading on VoxEUThe visible hand of the state: Industrial policies in emerging markets, a VoxEU column by the EBRD team presenting the Transition Report's findings on how emerging markets use industrial policy.The new economics of industrial policy, a VoxEU column by Réka Juhász, Nathan Lane and Dani Rodrik summarising the recent empirical literature on when these policies work.The return of industrial policy in data, a VoxEU column introducing the New Industrial Policy Observatory and documenting the recent wave of interventions.

Send us Fan MailIn this third episode of our SIU Series, Astrid Cousin, Director for Horizontal Policies at the European Commission's DG FISMA in conversation with Yvonne Bendinger-Rothschild, Executive Director of the EACCNY, lays out the benefits of the SIU for private savers, companies and institutional investors, both in the EU and the U.S.Thank you for listening! Please be sure to check us out at www.eaccny.com or email membership@eaccny.com to learn more!

The European Commission announced yesterday, 23 July, that it is fining Google €890 million. The American tech giant has been found to be in breach of the EU's competition rules. A decision that is likely to irritate U.S. President Donald Trump.So, what should Europeans expect in return?Production: By Europod, in co-production with the Sphera network.Follow us on:LinkedIn •. Instagram Hosted on Acast. See acast.com/privacy for more information.

P.M. Edition for July 23. The U.S. plans to impose new tariffs on most trade partners, replacing President Trump's temporary global 10% tariff. Plus, the threat of escalating conflict in the Middle East drove oil prices over $100, and concerns around higher inflation made bond yields surge. WSJ markets reporter Sam Goldfarb discusses how that ripples through the economy. Meanwhile, heavy AI spending from Alphabet and Tesla spooked investors, and the Nasdaq dropped more than 2%. And after IBM issued a rare profit warning last week, the company's earnings shed more light on what went wrong. We hear from reporter Anissa Gardizy about where its business goes from here, while tech columnist Christopher Mims spoke with IBM CEO Arvind Krishna. Alex Ossola hosts. Correction: New U.S. tariffs target 60 economies, or more than 80 countries. An earlier version of this podcast incorrectly said the tariffs target 60 countries. (Corrected on July 24.) Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

"The biggest problem is that they choose the lowest bid. That ends up being paid by the worker."Our taxes might be used to exploit cleaners through public contracts. But how does it work, who is responsible for this, and what can we do about it?In this episode, we follow the money. We expose how "public procurement"—the system by which governments award cleaning contracts—has created a race to the bottom. When contracts go to the cheapest bidder, the savings come from one place only: workers' wages, hours, and dignity.In this episode, we hear from:

European regulators recently issued a historic $1 billion fine against Google for multiple violations of the Digital Markets Act. The investigation concluded that the tech giant engaged in self-preferencing by prioritizing its own shopping and travel services within search results over those of its competitors. Additionally, officials found that Google utilized anti-steering practices on its app store to prevent developers from directing users toward more affordable payment options. While the company intends to appeal the decision and warns of potential product degradation, the European Commission has mandated a 60-day deadline for Google to implement fair, non-discriminatory practices. This landmark ruling represents the largest penalty yet under new digital laws designed to ensure a level playing field for online innovation and consumer choice.

The European Commission has fined US tech giant Google 890 million euros, or about 1.02 billion US dollars, for violating the EU's Digital Markets Act by favoring its own services and restricting app developers.

China expressed grave concern on Wednesday over the European Commission's decision to fine Chinese company AliExpress under the European Union's Digital Services Act, with a spokesperson for the Ministry of Commerce urging the bloc to stop using platform regulation as a pretext to erect digital trade barriers.周三，中方对欧盟委员会依据欧盟《数字服务法》处罚中国企业速卖通的决定表示严重关切。商务部发言人敦促欧盟不要以平台监管为借口设置数字贸易壁垒。On Monday, the European Commission, the EU's executive arm, imposed a 550 million euro ($627.55 million) fine on AliExpress, an Alibaba-owned cross-border e-commerce platform, accusing the company of failing to address the sale of illegal, unsafe and counterfeit products.周一，欧盟执行机构欧盟委员会向阿里巴巴旗下跨境电商平台速卖通处以5.5亿欧元（合6.2755亿美元）罚款，指控该平台未能整治非法、不安全及假冒商品销售问题。Responding to the move, a ministry spokesperson said in a statement that China will firmly support its companies in safeguarding their legitimate rights and interests through legal means and will take resolute measures to protect the lawful interests of Chinese businesses.商务部发言人就此举措发表声明称，中方坚定支持本国企业通过法律途径维护自身合法权益，并将采取有力措施保护中国企业正当利益。China firmly opposes the EU's use of platform regulation to create digital barriers and adopt discriminatory measures that restrict the normal business operations of Chinese e-commerce companies in Europe, said the commerce official.这位商务部官员表示，中方坚决反对欧盟借平台监管制造数字壁垒，实施歧视性措施，限制中国电商企业在欧洲正常经营。The spokesperson urged the EU to stop abusing its discretionary powers by exploiting ambiguities in legal provisions and to treat Chinese companies in a fair and impartial manner.发言人敦促欧盟不要再利用法律条款模糊之处滥用自由裁量权，公平公正对待中国企业。counterfeit /ˈkaʊntəfɪt/ adj.假冒的；伪造的discriminatory /dɪˈskrɪmɪnətəri/ adj.歧视性的discretionary /dɪˈskreʃənəri/ adj.自由裁量的legitimate /lɪˈdʒɪtɪmət/ adj.合法的；正当的pretext /ˈpriːtekst/ n.借口，托词erect /ɪˈrekt/ v.设立，建立（壁垒）

Send us Fan Mail93.2%. That is the Google AI Overview citation rate for the builder Anewgo has been working with on its AEO initiative - meaning when buyers ask Google's AI real questions about communities, floor plans, features, and pricing in that builder's market, the AI cites that builder's website as a source 93% of the time. In this July State of AI episode, Anya Chrisanthon - CCO at Anewgo - walks through the newest data from Anewgo CTO Keng Lim's follow-up study and rounds out the month's biggest AI news for home builders.Finding one: the builder became part of more buyer conversations - on every platform ChatGPT surged early (16% to 72%), gave back some ground, and finished at 61%. Gemini climbed steadily to a new high of 75%. Google AI Overview climbed at every single measurement and finished at 93.2%. Three platforms, three different trajectories, all moving up. The lesson: buyers ask the same question in different AI tools and get different answers. If you're only measuring one platform - or not measuring at all - you have an incomplete picture.Finding two: being cited is not the same as being recommended Google cited the builder's website 93% of the time but ranked them number one only 43% of the time - a 50-point gap. Getting found and trusted by AI is step one. Step two is making the case: clear community details, plan options, included features, real points of difference. That's what converts a citation into a recommendation.Finding three: AEO creates value before the website visit While AI visibility went up, website sessions dropped about 47%. The study can't attribute the traffic change to AEO - but the opposing trends prove that sessions alone can no longer measure AEO progress. A buyer can have a meaningful brand encounter with your business inside an AI answer, and your analytics never see them. The new scorecard: are AI tools citing you, are they recommending you, and are the visits you do get more engaged and qualified?The rest of July in AI The model race kept sprinting - GPT-5.6 shipped as a full lineup and the industry theme shifted from "best model wins" to "best fit wins." The European Commission ordered Google to open Android to rival AI assistants - one more sign that the AI on your buyer's phone is becoming a choice, not a default, and your digital presence has to work for all of them. And agent frameworks went from theoretical to shipping - moving AI from answering questions to completing work.

Michel Barnier is best known in Ireland for his central role in the EU's negotiations with the UK over Brexit almost ten years ago. But Barnier has also played a central role in French politics for decades, including a brief stint as prime minister. Today he is a member of the French parliament. Last week he was in Dublin for a series of political meetings with Taoiseach Micheál Martin, Minister for Foreign Affairs Helen McEntee and other senior figures, and on Wednesday Hugh interviewed him at Europe House, the European Commission's Dublin base, in front of an audience. Their conversation ranged from Barnier's first political awakening as a teenager in the 1960s through to his verdict on Brexit 10 years after the referendum, figures like Nigel Farage who led the UK out of the EU, the rise of France's far right and the prospects for the French presidential election which takes place in April of next year. Would you like to receive daily insights into world events delivered to your inbox? Sign up for Denis Staunton's Global Briefing newsletter here: irishtimes.com/newsletters/global-briefing/ Hosted on Acast. See acast.com/privacy for more information.

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

Catch up on the latest headlines from Chemical Watch News & Insight  This week's Podcast Short reviews our top stories, plus other interesting developments from around the globe.  In New York, the state attorney general has sued six chemical manufacturers over their use of PFAS in consumer products, with the lawsuit going beyond allegations typically raised in state-led PFAS cases.  In the EU, committees in the European Parliament have given a green light to a provisional agreement among EU lawmakers on the Chemicals Omnibus, bringing the measure one step closer to adoption. Meanwhile, regulators in China have proposed a unified framework for managing national and industry standards for cosmetics and toothpaste. Other stories include: Illinois prohibiting two dozen cosmetic ingredients; the European Commission proposing to ban 16 cosmetic ingredients deemed to be carcinogenic, mutagenic or reproductive toxicants; Brazil finalising its RoHS resolution restricting substances in electrical and electronic equipment; and a feature story looking at how some investors view the long-term risks of PFAS. Tune in to hear more and then visit Chemical Watch News & Insight to catch all the latest news on global developments in chemicals management.Have a podcast idea or a comment to share? Let us know by emailing the editor at Terry.Hyland@Enhesa.com.

META's stock surged last week, but investors shouldn't ignore the risks. Meta shares climbed last week as Wall Street became increasingly optimistic about the company's AI strategy. The stock was up about15% for the week and erased the year-to-date losses. Investors are betting that Meta's enormous spending on AI infrastructure, custom chips, top engineering talent, and next-generation models will lead to faster revenue growth, stronger advertising tools, and new revenue streams over the next several years. The market clearly believes Meta has positioned itself as one of the leaders in the AI race. But while investors were celebrating, Europe reminded everyone that even great companies face meaningful risks. The European Commission announced preliminary findings that Facebook and Instagram may violate the Digital Services Act because of what regulators call "addictive design" features, including infinite scrolling, autoplay videos, and recommendation algorithms that encourage users to stay engaged for longer periods. If the findings become final and Meta does not make sufficient changes, the company could face fines of up to 6% of its global annual revenue, along with potential changes to how its platforms operate across Europe. Meta has disputed the findings and says it has already implemented significant protections for younger users. This could amount to a fine of around $12 B, but the bigger problem I see is a potential hit to ad revenue if they must change their business practices. Europe is an important part of their business considering it accounts for about 23% of overall company sales. We also can't forget the legal liability Meta is facing in the United States, which could ultimately total as much as $1.4 trillion. That number may sound shocking, but it stems from multiple lawsuits brought by numerous states and plaintiffs. The first major cases are scheduled to go to trial in August, with California, Colorado, New Jersey, and Kentucky leading the way. The lawsuits allege deceptive business practices, and potential penalties range from $2,000 to $20,000 per violation. Given Meta's massive user base, those fines could accumulate rapidly if the courts rule against the company. Beyond civil penalties, the states are also seeking disgorgement of profits, which would require Meta to surrender profits earned from the alleged misconduct during the relevant period. If Meta performs poorly in these initial cases, another 25 states have similar lawsuits waiting in the wings, significantly increasing the company's legal exposure. There are already signs that these legal challenges carry real financial risk. New Mexico recently won a $375 million judgment against Meta, and a separate federal trial is scheduled to begin early next year. The AI opportunity is also far from guaranteed. Today, investors are rewarding companies that appear to be winning the AI race, but the competitive landscape is becoming more crowded every quarter. OpenAI, Anthropic, Google, Microsoft, xAI, and others are investing billions of dollars to develop better models and attract developers. Meta has responded aggressively by spending heavily on infrastructure and recruiting top AI researchers, but there is no guarantee those investments will generate returns that justify the enormous capital being deployed. A big problem is today's leader in AI can quickly become tomorrow's follower if innovation slows. I also believe that all of these companies will not succeed in this space, which will mean enormous amounts of wasted capital for the losers. Wall Street seemed to be focused almost entirely on Meta's AI upside last week, and that optimism may continue to drive the stock higher. But investors should remember that valuation is increasingly dependent on AI execution while regulatory scrutiny remains elevated. If AI spending fails to produce the expected returns or regulators force changes that weaken engagement, today's bullish narrative could change quickly. Meta remains one of the strongest companies in technology, but even great businesses are not risk-free. As investors, it's important to weigh both the opportunities and the risks, not just the headlines driving the stock higher today.   The spring home sales season disappointed in June The spring home-selling season ended on a disappointing note. Through May, existing home sales had been showing signs of improvement, and many real estate professionals were becoming more optimistic about the housing market. However, June's data told a different story. The conflict involving Iran contributed to higher inflation expectations and pushed mortgage rates higher, weighing on buyer demand. Existing home sales fell 2.4% in June to a seasonally adjusted annual rate of 4.09 million homes, well below economists' expectations for a 0.7% increase. Despite the monthly decline, the longer-term trend remains somewhat more encouraging. Existing home sales were still up 2.8% compared with a year ago, suggesting that underlying demand has not disappeared. There continues to be pent-up demand from prospective buyers, but many seem unwilling to make such a large financial commitment while borrowing costs remain elevated, even as housing inventory continues to improve According to Freddie Mac, the average 30-year fixed mortgage rate was 6.43% last week. If mortgage rates remain near these levels, many prospective homebuyers may continue to delay their purchases, preventing a stronger recovery in the housing market.   Another Hidden Cost of AI: Steel Most people know that the AI buildout has driven up demand for advanced computer chips, contributing to higher prices for smartphones, laptops, and other electronics. They also know that AI data centers require enormous amounts of electricity, putting upward pressure on utility rates as more power is diverted to support AI infrastructure. But there's another cost that receives far less attention: steel. Steel is a critical component of every data center. Industry estimates suggest that new data centers will consume roughly 1 million tons of steel annually, representing approximately $1.4 billion in demand. Steel is used throughout these facilities from the structural columns, roof joists, and roof decking to the server racks that house thousands of AI processors. This growing demand has ripple effects throughout the economy. Higher steel demand can contribute to increased costs for automobiles, household appliances, commercial buildings, bridges, and countless other products that rely on steel. The impact doesn't stop there. Steel production is one of the most energy-intensive manufacturing processes. A single electric furnace steel mill can consume anywhere from around 50 to 200 megawatts of electricity per day, competing for the same power resources as AI data centers. As both industries demand more electricity, utilities face increasing pressure to expand generating capacity. Ultimately, who pays for that increased demand? The answer is often the consumer. Higher electricity demand can translate into higher utility bills for households and businesses as utilities invest in additional generation and transmission infrastructure. In regions where electricity supply is already tight, the competition for power is becoming even more apparent. For example, PJM Interconnection, the nation's largest regional transmission organization, plans to begin conducting supplemental power auctions with electricity generators in September to help secure additional supply. Auctions reward the highest bidders, meaning electricity increasingly flows to those willing to pay the most. As large industrial users and AI data centers bid aggressively for power, consumers could face higher electricity prices if supply fails to keep pace with demand. AI will likely bring enormous productivity gains and economic benefits over the long run. However, it is also creating secondary inflationary pressures that extend well beyond semiconductors. Steel, electricity, construction materials, and other critical inputs are all experiencing increased demand, and those costs eventually work their way through the economy. As the AI revolution accelerates, these indirect costs are likely to become an increasingly important part of the inflation story.   Inflation Is Cooling... But Don't Pop the Champagne Yet The latest CPI report was another encouraging sign that inflation is moving in the right direction. Headline CPI declined 0.4% in June, marking the largest monthly drop since 2020, while the annual inflation rate slowed to 3.5% from 4.2% in May. Core inflation, which excludes food and energy, was flat on the month and eased to 2.6% year over year. Much of the improvement was driven by a sharp decline in gasoline and broader energy prices. While this is welcome news, I'd caution against declaring victory over inflation. One of the biggest challenges with inflation is that it doesn't always show up in the headline numbers immediately. It often works its way through the economy in waves, especially when it comes to energy. A good example is my own pool service. My pool guy recently raised his prices, likely for two reasons: higher chemical costs and the increased cost of driving from house to house. Those are both directly tied to energy markets. Even if gasoline prices temporarily fall and help bring down CPI for a month, businesses often adjust prices more slowly because they have to account for prior cost increases and the uncertainty of where energy prices are headed next. That's why I think investors should remain cautious. The recent improvement in inflation was helped significantly by lower oil and gasoline prices following a temporary easing in geopolitical tensions. But with conflict in the Middle East once again threatening energy supplies and oil prices recently moving higher, that relief could prove short-lived. The trend is encouraging, and the Federal Reserve will certainly welcome softer inflation data. But as long as energy prices remain vulnerable to geopolitical events, inflation is likely to remain unpredictable. Businesses from manufacturers to small local service providers will likely continue to pass along higher input costs whenever they have to. One softer CPI report is good news. But sustained price stability will likely require a concrete outcome in the Middle East and more stability in the energy market. While again we welcome the positive news in this CPI report, the conversation around in inflation and what to do with interest rates will continue with the ongoing developments in Iran.   Higher Gas Prices Aren't Stopping the American Consumer If you were looking for evidence that higher gas prices are slowing down the American consumer, the latest retail sales report doesn't provide much support. The headline number was relatively modest, with retail and food services sales increasing 0.2% from May. But the year-over-year numbers tell a much stronger story. Total retail and food services sales were up 6.7% from June of last year. Even if you exclude gas stations, which saw an increase of 19.8%, retail sales still grew at an impressive rate of 5.7%. More importantly, when you look across the major spending categories, not a single major category declined year over year. Furniture and home furnishing stores was the only major category that was flat compared to last year, but again it wasn't negative! Some of the strongest performers included non-store retailers, which primarily includes online shopping, increased 14.2%. Electronics and appliance stores were up 8.6%, while clothing and clothing accessories increased by 4.8%. Building materials and garden equipment stores were up 3.5% One of the more interesting data points is that Americans are still spending money at restaurants and bars. Food services and drinking places were up 3.8% year over year, showing that consumers continue to spend on experiences and dining out despite higher costs and concerns about the economy. The big takeaway is that the consumer remains remarkably resilient. Yes, higher gas prices can eventually put pressure on household budgets. But so far, consumers have continued to spend across virtually every major category. The year-over-year numbers show broad-based growth, not just spending concentrated in one or two areas. The consumer may be under pressure, but they are clearly not out of the game yet.   Financial Planning: What's Next for Social Security The Social Security Trustees' most recent solvency report highlights the need for Congress to address the program's long-term funding shortfall. Under current projections, the retirement trust fund is expected to be depleted in 2032, at which point ongoing payroll tax revenue would be sufficient to pay only about 78% of scheduled benefits unless legislative changes are made. Importantly, this does not mean Social Security will become insolvent or stop paying benefits, it means benefits would be reduced if Congress takes no action. While no specific legislation has emerged, many policy experts expect Congress to adopt a combination of gradual reforms rather than a single sweeping change. Potential solutions include increasing the Social Security payroll tax rate from 6.2%, raising or eliminating the taxable wage cap from $184,500, increasing the full retirement age from 67 for younger workers, and slowing future benefit growth for higher-income retirees. Historically, when Congress has made changes to Social Security, it has phased them in over many years, and most proposals would leave current retirees and those approaching retirement largely unaffected. As a result, individuals already receiving benefits or those within roughly the next decade of retirement are generally expected to experience little or no change, with the majority of reforms likely to apply to younger generations who have more time to prepare.   Companies Discussed: Nike, Inc. (Ticker: NKE)  

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. The industry continues to forge ahead, making significant strides in scientific advancements, regulatory approvals, and strategic business developments. These moves are reshaping the landscape of drug development and patient care. Starting with Merck & Co.'s recent FDA approval for Lipfendra, the world's first oral PCSK9 inhibitor, this marks a pivotal shift in managing hypercholesterolemia. Traditionally, PCSK9 inhibitors have been administered via injection, but Lipfendra offers a more convenient oral alternative. This could significantly improve patient adherence and outcomes by easing the administration process for those managing cholesterol levels. The drug's approval highlights a crucial advancement in cardiovascular treatment, with expectations of reaching peak annual sales of $5 billion, underscoring its market potential. In another significant development, Eli Lilly has entered the burgeoning field of psychedelic therapeutics with its acquisition of Ataibeckley for up to $3.8 billion. This move reflects a growing trend toward exploring novel therapeutic avenues for psychiatric disorders. Psychedelic compounds promise new hope for patients with depression and other mental health conditions where conventional therapies have shown limited efficacy. Eli Lilly's investment signals confidence in the transformative potential of psychedelics, which could revolutionize treatment paradigms for conditions like depression and PTSD. Turning to obesity treatment, Novo Nordisk's Wegovy pill has received European Commission approval for obesity and overweight adults. As a small molecule GLP-1 receptor agonist, semaglutide enhances satiety and reduces caloric intake. This development underscores the increasing focus on metabolic disorders and highlights the competitive landscape as companies race to dominate the weight management sector with innovative oral formulations. In oncology news, Merck & Co.'s Keytruda has achieved a milestone in becoming the first PD-1 inhibitor to demonstrate phase 3 benefits as a single agent in frontline mismatch repair-deficient endometrial cancer. This success not only reinforces Keytruda's role in oncology but also emphasizes the importance of precision medicine approaches targeting specific genetic mutations in cancer therapy. The industry is also seeing substantial financial maneuvers aimed at bolstering research capabilities and market reach. Johnson & Johnson has raised its 2026 financial guidance following Tremfya's impressive $2 billion revenue milestone with its IL-23 inhibitor for autoimmune diseases. Additionally, their strategic supply chain restructuring reflects efforts to enhance operational efficiency amid a broader U.S. manufacturing push. On the regulatory front, Johnson & Johnson received UK MHRA approval for Akeega in BRCA1/2-mutated metastatic prostate cancer, highlighting ongoing focus on precision medicine and targeted therapies in oncology. Meanwhile, Medtronic's recall of Harmony Catheter Delivery Systems due to safety concerns serves as a reminder of ongoing vigilance in medical device safety regulations. In clinical trial advancements, InnoCare Pharma's TYK2 inhibitor demonstrated efficacy in a Phase 2 trial for nonsegmental vitiligo, achieving its primary endpoint and paving the way for Phase 3 studies. This highlights TYK2 inhibition as a promising strategy for autoimmune diseases like vitiligo. Moreover, we witness movements towards public offerings with companies like Vogenx and Braveheart Bio aiming for IPOs to fund their respective drug development projects. These efforts underscore the continuous drive for capital to propel innovative therapies through clinical trials and towards commercialization. Finally, turning to regulatory updates, Sanofi has entered new chapters in mRNA patent litigation against Pfizer and Moderna, reflecting ongoing tensions over intellectual property rights within the high-stakes realm of COVID-19 vaccines and mRNA technology. The outcomes here could have far-reaching implications for mRNA-based therapeutics and vaccine development. As we look at these developments collectively, they illustrate a vibrant period for pharmaceutical and biotech companies innovating new treatments while navigating complex regulatory terrains. The implications for patient care are profound, with potential improvements in therapeutic options driven by new scientific breakthroughs and strategic industry shifts. These dynamics promise to reshape the future landscape of global healthcare delivery and pharmaceutical innovation as these trends continue to unfold.Support the show

"We are the invisibles. We clean when no one is around."Most people work during the day. But for nearly half of Europe's cleaners, the shift begins when everyone else goes home.In this episode, we examine the hidden toll of night work and split shifts—and why daytime cleaning is a proven, humane alternative. We hear from two cleaners living in two different realities: one trapped in the exhaustion of the night, and the other working under a better system but with its own challenges.In this episode, we hear from:

The Supreme Court just made it easier to fire SEC and CFTC commissioners. Katherine, Jessi, and Vy on why that could reset who controls crypto policy. Plus, the UK's new rulebook. ======================================================== Thank you to our sponsor! ⁠⁠Cape⁠⁠: Your biggest crypto vulnerability isn't your wallet, it's your phone number. Cape is America's privacy-first mobile carrier that rotates your SIM identity daily and blocks SIM swaps before they happen. Get 33% off your first six months at https://cape.co/unchained (use code: UNCHAINED). ======================================================== The Supreme Court just tore up a 90-year-old precedent that kept independent-agency commissioners safe from a president's whims, and almost no one in crypto is talking about what it means for the SEC and the CFTC. Katherine Kirkpatrick Bos, Jessi Brooks, and Vy Le trace how the ruling in Trump v. Slaughter changes who actually controls financial regulation. Then they cross the Atlantic to the UK's sweeping new crypto rulebook and the European Commission's move to expand MiCA just as its first version fully takes effect. They also dig into a Cambridge report showing fighters from one of the world's most brutal terror groups using chatbots to troubleshoot weapons and plan attacks, and ask why there's no Section 230 for crypto or AI, only a growing pile of civil lawsuits testing where liability lands. Jessi Brooks argues crypto's decade of learning to police neutral technology might be the only playbook AI has left to borrow. Host: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Katherine Kirkpatrick Bos⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, General Counsel. Previously held senior legal roles across DeFi and centralized exchanges. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jessi Brooks⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, General Counsel at Ribbit Capital⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Vy Le⁠⁠⁠⁠⁠⁠ - Co-host of DEX in the City and General Counsel of Veda Timestamps

For the first time, the European Commission is warning that demographic change is becoming one of the biggest challenges to the EU's competitiveness and welfare systems.Can Europe remain prosperous with a rapidly ageing population?Production: By Europod, in co-production with the Sphera network.Follow us on:LinkedInInstagram Hosted on Acast. See acast.com/privacy for more information.

Marco Rosso, global head of sustainability and corporate affairs at Syngenta Biologicals and Seed Care, talks with Ian Welsh about the shifting economics of farming. They discuss the psychology putting young people off agricultural careers and why sustainability has to deliver a real return on investment for farmers to adopt it. Plus: lab-grown cocoa as a hedge against cocoa price volatility; US coffee prices double on tariffs and Red Sea disruption; China's largest US soybean purchase since 2025; and, European Commission cuts sustainability reporting requirements by 60%, in the news digest. Host: Ian Welsh

Meta discontinues AI tool able to pull from any public Instagram account, the European Commission will propose a three tier system for minors on social media , and Waze announces new features including a ‘Less Chatty Mode’. MP3 Please SUBSCRIBE HERE for free or get DTNS shows ad-free. A special thanks to all our supporters–withoutContinue reading "Meta Ends New Instagram AI Image Generator After Backlash – DTH"

AP correspondent Karen Chammas reports the head of the European Commission at the EU weighs age restrictions for children using social media.

Story of the Week (DR):Social Media's 'Big Tobacco Moment': Meta Faces $1.4 Trillion Fine for Allegedly Fueling Teen Suicide and AddictionMeta is being sued by 33 US states, led by California, Colorado, Kentucky, and New Jersey.12 blue/12 red/9 purpleThe states allege that Meta deliberately designed Facebook and Instagram to be addictive to children and teens, fueling a youth mental health crisis (including anxiety, depression, self-harm, and suicide).They also accuse Meta of violating child privacy laws by collecting data from children under 13 without parental consent.Meta warned a federal court that it could face up to $1.4T in penalties if the states prevail at the upcoming trial (set for August 18, 2026). Meta extrapolated this massive figure—which is roughly equivalent to the company's entire stock market value—based on the methodology proposed by the lead states for calculating damages.Meta calls the penalty "outlandish" and "unsubstantiated," arguing it has no precedent in consumer protection history: 'A sanction of that size has no analog in the history of consumer protection enforcement.' The company accuses the states of improperly multiplying penalties (e.g., stacking fines based on daily usage time). Meta denies the allegations, asserting its platforms have extensive safety tools and that the claims are unmoored from actual unfair practices.‘I Don't Think I'm Ever Going to Stop,' Says Mark Zuckerberg. Even With 'Infinite Money,' He Has No Plans to Retreat to His Massive Hawaii EstateMeta found to breach EU laws with 'addictive' Instagram, Facebook designsInstagram and Facebook's “addictive” designs have put Meta in breach of the European Union's digital laws, the EU concluded Friday in a preliminary report.The tech giant violated the EU's Digital Services Act by failing to adequately consider the risks associated with design features that affected the physical well-being of its users, including minors and vulnerable adults, the European Commission said.These features include infinite scroll, which constantly shows fresh content, autoplay, push notifications and highly personalized recommendation systems — feeding users' compulsion to continue using platforms and putting them into “autopilot mode.”The EU Commission also accused Meta of ignoring available information about how much time young people are spending on Instagram or Facebook at night, and how different types of content formats, from reels to stories, could lead to excessive use of its services.Meta said, “We disagree with these preliminary findings.”New Zealand Moves To Ban Climate Change Litigation. Will The U.S. Follow?New Zealand has proposed a bill to limit the ability of individuals to sue high greenhouse gas emitters over the impacts of climate change, relying instead on the enforcement measures taken by the government. The bill appears poised to pass.The women who wouldn't let climate data disappear MMAfter losing their jobs at National Oceanic and Atmospheric Administration (NOAA), Rebecca Lindsey, her sister Mary and colleague Anna Eshelman teamed up to rebuild a pivotal resource the Trump administration took offlineRebecca Lindsey, a technical writer for NASA–one of 280,000 federal workers fired by Musk/Trump, joined forces with former NOAA employees Anna Eshelman, and Mary Lindsey, her older sister, to become the core team behind the deactivated site's successor, Climate.us, preserving over 15 years of key climate data and resources.Elon Musk says he always wanted his SpaceX employees to get rich — and now thousands of them are millionairesElon Musk's 'Chainsaw for Bureaucracy' Just Left an $11 Billion Budget Hole as Trump Rehires StaffThe trove features key maps, educational materials and climate indicator reports, including the now-deleted Fifth National Climate Assessment, the government's most comprehensive analysis of climate change that was at risk of being lost to the publicJersey Mike's $12 billion IPO filing reveals a $50 million payday for the founder's stepson and a $41 million jetFamily members of founder Peter Cancro were employed Jersey Mike's in various roles and received compensation in excess of $120,000 from the Company as follows for the years ended December 28, 2025 and December 31, 2024 and 2023:John Cancro, Mr. Cancro's brother, received total compensation of approximately $20,019,231, $519,231 and $500,000, respectively;Paul J. Cancro, Mr. Cancro's son, received total compensation of approximately $8,001, $216,022 and $208,023, respectively;Robert Cancro, Mr. Cancro's son, received total compensation of approximately $38,462, $1,038,462 and $1,000,000, respectively;Tatiana Cancro, Mr. Cancro's wife, received total compensation of approximately $11,538, $311,539 and $300,000, respectively;Caroline Jones, Mr. Cancro's daughter, received total compensation of approximately $38,462, $1,038,462 and $1,000,000, respectively;Alexandra Powers, Mr. Cancro's sister-in-law, received total compensation of approximately $0, $1,165,437 and $0;Daniel Powers, Mr. Cancro's brother-in-law, received total compensation of approximately $30,213,462, $1,793,952 and $0;John Tesauro Jr., Mr. Cancro's brother-in-law, received total compensation of approximately $0, $0 and $2,429,628, respectively;Phillip Sivolobov, Mr. Cancro's stepson, received total compensation of approximately $50,011,538, $311,539 and $276,923, respectively.GRAND TOTAL: $112MStepson Phillip got $51M, brother John got $21MOther Peter Cancro schwag in 2025:Got a $41 million jet and an additional fixed amount of $166,666.66 per month in light of the business expenses incurred by Mr. Cancro related to air transportation to travel from time to time for business purposes.Lease agreements valued at $1M in rent (leases go to 2030) Controlled company: Blackstone (will control more than 50% of voting power)Board: 8 directorsBlackstone:Chair Nigel Travis (also chair of Abercrombie & Fitch)David N. KestnbaumDevon L. RinkerMichael J. StaubFounder/former CEO/chair: Peter CancroCEO Charles R. MorrisonCheryl S. Miller, director on two controlled companies:Tyson FoodsOld Dominion Freight Line (Congdon brothers)Fran Horowitz, CEO of Abercrombie & Fitch (where chair serves as chair)Goodliest of the Week (MM/DR):DR: Amazon, Walmart and Other Large Employers Could Face New Costs As New Jersey Targets Companies With Medicaid Workers— Will Other States Follow?DR: UBS says rich people will be younger, female and openly queer thanks to the Great Wealth TransferMM: Meta Buried Research Linking Instagram To Teen Harm While Facing $1.4 Trillion Penalty That Could Erase Its Entire WorthMM: ESG!Madison Square Garden Kept a List of Gay CelebritiesAn internal Madison Square Garden database of VIPs labels Joe a “medium risk,” one of roughly 400 celebrities given a risk score.If you're a celebrity and you're marked with a risk score—even as a low risk—it means “you've done something in the publicity world, the social media world, that has caught the attention of the wrong people,” the source continues.The talent database also tracks some celebrities' race, gender identity, and sexual orientation; 93 entries are marked as “LGBTQIA.”MM: California vs. Elon Musk: Tesla Snubbed as New EV Incentives Boost Rivian, Lucid MM DRAssholiest of the Week (MM):Billionaire amplificationKen Griffin says everyone is misinterpreting the AI revolution — and wishes Zohran and Bernie would ‘read a damn history book for once'“[Capitalism is] the greatest success story in the history of humanity,” Griffin said, urging the self-identified socialist politicians, “whether it's Bernie Sanders, whether it's Mamdani,” to “read a damn history book for once and then tell us how to run our country.”Jeff Bezos 'Made All of Our Lives So Much Better,' Says Billionaire Investor Tim Draper"Amazon has made all of our lives so much better," Draper said.Draper said he has benefited from what Bezos has done, and that's a part of the world economy that isn't spoken about enough."Those geniuses who create this incredible world for us are benefiting all of us."40 Epstein-Tied Billionaires Have Injected $1.6B Into US Elections, Report FindsThese are the millionaires and billionaires pledging to fund Trump accountsZuckMeta AI Data Centre Contractor Triggers Biohazard Scare After Flushing Rare Bacterium Into Public SewersMeta Platforms To Build $9 Billion A.I. Data Centre In CanadaThe $145 Billion Lie? Zuckerberg's Leaked Town Hall Audio Exposes Massive AI Failures After Mass LayoffsMeta jumps into AI coding market in effort to chase Anthropic and OpenAIWhat person in their right mind would trust Zuckerberg with their coding?Hollywood Vs Zuckerberg: CAA Warns Meta's AI Image Tool Needs A Major Privacy Overhaul‘I Don't Think I'm Ever Going to Stop,' Says Mark Zuckerberg. Even With 'Infinite Money,' He Has No Plans to Retreat to His Massive Hawaii EstateJeff Sonnenfeld - DRIn defense of Musk, SpaceX, and dual class shares“the rigid formulas of proxy advisors create a perverse, socially destructive incentive: hoard your wealth like an oligarch to maintain your good governance rating, or give it away and risk losing your company”“The proxy advisors want a world governed by rigid mathematical formulas because auditing a checklist is easy. Evaluating human character, industry dynamics, track records of success and failure, and the capacity for visionary leadership is hard. But it is exactly that hard work of judgment which is vital. When it comes to dual-class shares, it is time for the critics to step out of the theoretical vacuum and look at the real-world scoreboards”Headliniest of the WeekDR: OpenAI Wants a $1 Trillion Valuation. But College Students Are Testing At The Level Of 10-Year-Olds AND Suspecting AI cheating, Ivy League prof ordered an in-person final; scores fell 50%MM: ‘Waymo Takes Revenge, Dropping Drunk Teens Directly Into Squad of CopsMM: West Virginia spent $3M to create university program to fight ‘woke ideology.' One student is enrolledWho Won the Week?DR: Free Float's new platformAnd blowhard Jeffrey Sonnenfeld for arguing that dualclass owners are necessary because the dualclass mechanism allows them to sell shares and maintain voting power so they can “cure diseases, endow universities, and combat poverty” MM: Free Float data: Elon Musk and the age of the corporate leviathanAbove a certain size the ordinary rules of governance apparently cease to apply.Of the 16 listed firms worth more than $1trn, seven are shareholder fundamentalists.None has an elaborate statement of corporate purpose, since they are mostly content making heaps of moneyFree Float says Nvidia, Amazon, Broadcom, Micron are all TOTALITARIANNext are the corporate paternalists, who believe that the problem with shareholder democracy is that its voters do not know what is best for them.Free Float says Berkshire, Google, Meta are all TOTALITARIANThe final clan presents the strongest argument against the end of corporate history: individual shareholders consent to hand over all of their rights to the world's richest man, who then governs as he sees fit.Free Float says SpaceX, Tesla are TOTALITARIANBasically, it's nice of the economist to recognize everything Free Float says every weekPredictionsDR: Jeff Sonnenfeld writes something on Fortune that triggers meMM: Jeff Sonnenfeld writes something on Fortune that triggers Damion

Recorded at the Paris School of Economics-CEPR Policy Forum 2026. Europe is under attack from the US, and under a different kind of attack from China.That is Olivier Blanchard's diagnosis. Blanchard (MIT, Paris School of Economics, Peterson Institute) is one of four economists leading Europe 2050, a new CEPR initiative asking where Europe wants to be in 25 years, and how it gets there. Blanchard's overriding principle: a vision without plumbing goes nowhere, and plumbing without vision is just reacting to the next tweet.Who can combine the vision and the plumbing, and produce ideas that we haven't seen before? Europe might be short of solutions to its current malaise, but it is not short of people with ideas: the project sent out 50 invitations for policy papers. Blanchard expected 30 replies. He got 48.The research behind this episode:Blanchard, Olivier, Pascal Lamy, Enrico Letta, and Beatrice Weder di Mauro. 2026. "Europe 2050: Geometries of Peace, Power, and Prosperity." VoxEU column, CEPR, 16 March 2026.The CEPR Europe 2050 initiative launched by Blanchard, Lamy, Letta and Weder di Mauro is generating a rolling series of commissioned policy papers and shorter open call submissions. The full set of contributions can be found at cepr.org/europe-2050-geometries-peace-power-and-prosperity.To cite this episode:Phillips, Tim, and Olivier Blanchard. 2026. "Europe in 2050." VoxTalks Economics (podcast). About the guestOlivier Blanchard is the Robert M. Solow Professor of Economics emeritus at MIT, Professor of Economics at the Paris School of Economics, and Senior Fellow at the Peterson Institute for International Economics. He is a CEPR Distinguished Fellow. Blanchard's research spans macroeconomics, monetary and fiscal policy, and the economics of European integration; he was chief economist and director of research at the IMF from 2008 to 2015. Research cited in this episodeEurope 2050: Geometries of Peace, Power, and Prosperity is the CEPR initiative behind this episode, launched by Blanchard, Lamy, Letta and Weder di Mauro. It commissions longer policy papers and runs an open call for shorter pieces, five to fifteen pages, on what Europe should aspire to become by 2050. Blanchard describes it as a box of tools rather than a single blueprint, deliberately open to contributors who disagree on fundamentals, including whether Europe should become a federation.The Draghi report refers to Mario Draghi's 2024 report for the European Commission, The Future of European Competitiveness. It diagnosed Europe's weak productivity growth, fragmented capital markets and insufficient scale financing for innovative firms. Blanchard contrasts it with Europe 2050, which he says is not trying to produce a similarly prescriptive plan.The Letta report refers to Enrico Letta's 2024 report Much More Than a Market, commissioned by the European Council, which set out proposals for deepening the EU single market. Letta is one of the four leaders of Europe 2050."Getting to Denmark" is a concept popularised by the political scientist Francis Fukuyama in his 2011 book The Origins of Political Order, describing the temptation to picture a distant, well governed destination without a plan for the institutional steps needed to reach it. Is this a risk for Europe 2050?Schengen is raised by Blanchard as a working example of a "coalition of the willing": a group of countries, not all of them EU members, that agreed to abolish border controls between themselves without waiting for unanimous agreement across the whole Union. He points to it as a template for how Europe might make progress on other issues where full consensus is unlikely.More VoxTalks Economics episodesThis episode was recorded at the Paris School of Economics-CEPR Policy Forum 2026, alongside a series of conversations with forum speakers.Europe in the Middle, the previous episode, features Pol Antràs and Beata Javorcik on how the US-China trade war is reshaping trade flows into Europe, and who wins and loses from it.Related reading on VoxEUEurope's challenge and opportunity: Building coalitions of the willing, a VoxEU column by Blanchard and Jean Pisani-Ferry, sets out the coalition of the willing idea in more detail, working through how it might apply to climate, trade and tax policy.Capitalising on Europe's strengths, a VoxEU column by Debora Revoltella and colleagues at the European Investment Bank, looks at what Europe already does well and how policy can build on it rather than only cataloguing weaknesses.Addressing European competitiveness: Investment, integration, and simplification, another VoxEU column from the European Investment Bank, sets out the scale of Europe's investment gap and where past bursts of EU investment have come from.EU capital markets reform should focus on innovation investment, a VoxEU column, argues that capital markets union, a project Blanchard mentions in the episode, should be judged by whether it gets money to innovative firms, not just by market integration for its own sake.

Volkswagen, whose 10 brands range from Seat to Porsche, is making sweeping production cuts in Germany. We take a look at the impact this is having on the automotive industry in the country.A row over Peking duck is adding to already tense relations between Brussels and Beijing. The European Commission has opened an investigation into whether Chinese duck meat is being sold in Europe at unfairly low prices. We take a look at the wider dispute.And since the United States imposed a near total fuel blockage on Cuba six months ago, the island's food crisis is deepening.Presenter: Leanna Byrne Producers: Rob Cave, Parisa Qurban, Aleeza Siddiq.

"The only time people notice what a cleaner does is when she doesn't do it."They disinfect hospital wards, scrub office floors, and sanitise the spaces we all rely on. Yet cleaners are among the most invisible workers in Europe.In this first episode, we pull back the curtain on a typical day in the life of a cleaner. From the marble corridors of the European Parliament to a high-dependency hospital unit in Ireland, we hear what it really means to do essential work that almost no one sees.In this episode, we hear from: