Podcasts about ipo

Today, I'm talking with Hayden Field, The Verge's senior AI reporter, about the major trade secrets lawsuit between Apple and OpenAI, and what this tells us about OpenAI's future.  Hayden has been covering OpenAI for years now, and she also just talked to a bunch of lawyers who specialize in intellectual property and trade secret law to get a sense of how serious this case is. The answer is not entirely positive for OpenAI. This legal battle could also affect OpenAI's hardware plans, its forthcoming IPO, and its already-damaged reputation.  Links:  Sam Altman didn't need another lawsuit | The Verge OpenAI's first device will be moveable, screenless speaker | Bloomberg Apple sues OpenAI for allegedly stealing hardware secrets | The Verge The 6 wildest claims in Apple's lawsuit against OpenAI | The Verge OpenAI is buying Jony Ive's AI hardware company | The Verge Subscribe to The Verge to access the ad-free version of Decoder! Credits: Decoder is a production of The Verge and part of the Vox Media Podcast Network. Decoder is produced by Kate Cox and Nick Statt and edited by Ursa Wright. Our editorial director is Kevin McShane.  The Decoder music is by Breakmaster Cylinder. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Dan Nathan sits down with Rick Heitzmann, co-founder and partner at FirstMark Capital, to kick off a new Okay, Computer. series on AI investing. They dig into the circular financing behind the AI infrastructure boom — from Nvidia backstopping Apollo's private credit for xAI to Meta's off-balance-sheet data center deals with KKR and Blue Owl — plus the shift from "tokenmaxxing" to an efficiency era, the rise of Chinese open-source models, memory stock froth, and what's next for the IPO market after SpaceX. Show Notes Big Tech Is Hiding $1.65 Trillion in Debt. How Worried Should Investors Be? (Yahoo Finance) SpaceXAI Explores Major Data Center Expansion in Texas (The Information) —FOLLOW USYouTube: @RiskReversalMediaInstagram: @riskreversalmediaTwitter: @RiskReversalLinkedIn: RiskReversal Media The financial opinions expressed in Risk Reversal content are for information purposes only. The opinions expressed by the hosts and participants are not an attempt to influence specific trading behavior, investments, or strategies. Past performance does not necessarily predict future outcomes. No specific results or profits are assured when relying on Risk Reversal. Before making any investment or trade, evaluate its suitability for your circumstances and consider consulting your own financial or investment advisor. The financial products discussed in Risk Reversal carry a high level of risk and may not be appropriate for many investors. If you have uncertainties, it's advisable to seek professional advice. Remember that trading involves a risk to your capital, so only invest money that you can afford to lose. Derivatives are not suitable for all investors and involve the risk of losing more than the amount originally deposited and any profit you might have made. This communication is not a recommendation or offer to buy, sell or retain any specific investment or service.

Plus: OpenAI says two of its models hacked a company in a cybersecurity test gone wrong. And U.S. data-center operator TECfusions plans to go public. Danny Lewis hosts. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

How do we align the rapid, exponential rise of artificial intelligence with humanity's best interests before we reach a point of no return? In this classic throwback episode from our old Edge of AI Podcast, we sit down with tech visionary Eric Pulier, a prolific technologist who has founded over 15 companies, raised more than $1 billion, and led exits from IPOs to major mergers.In this deep dive, Eric explores his leadership roles as Co-Chair of the AI Coalition at the Future Investment Initiative (FII) Institute and CEO of Vatom. He outlines the global push for AI ethics, the looming existential threats of synthetic biology and mass deepfakes, and why preserving human culture in local AI models is crucial to preventing algorithmic erasure.Eric also reflects on inventing the "Vatom" (the virtual atom) in early 2015, the precursor to modern smart NFTs, and explains why self-sovereign identity, tokenized real-world assets, and human-first connection will dictate the next generation of the internet.Support us through our Sponsors! ☕ Want to make content like ours? Sign up with Castmagic to make your creative process easy: https://bit.ly/CastmagicReferral Work smarter, grow faster. Automate your SEO, get AI insights, and manage all your clients in one place with Helm. Start today 50% off your first month at helmseo.com

“I am not Nicholas Rossi!” gasps Arthur Knight through an oxygen mask in March 2022. Recently discharged from a Covid ward in Glasgow, he's in a wheelchair. The police say he's Nicholas Rossi, suspected of faking his death and wanted for rape in Utah. The story makes headlines globally.When journalist Jane MacSorley meets Arthur Knight and his wife Miranda, she thinks the police have made a mistake. She embarks on a yearlong investigation, making a unique discovery which changes everything. Listen to I Am Not Nicholas Season 1 on Audible or wherever you get your podcasts. You can binge all episodes early and ad-free by joining Audible on the Audible App or on Apple Podcasts.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Plus: Novo Nordisk files a deceptive advertising lawsuit against Eli Lilly. And the latest Chinese AI model launches rattle expectations for the biggest AI players in the US. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Live July 20, 2026 | Yaron Brook Show(Season 12, Episode 127)Iran - What Next?; AI - China Coming; ICE; DSA; Vance & GDP; Achievement | Yaron Brook ShowIran After the Strike? China's AI Race, Socialist Delusions & The Fatal Misunderstanding of ProsperityWhat happens after Iran? Is China catching America in AI? Why are politicians—from the Left to the Right—still getting economics fundamentally wrong?In this wide-ranging live episode, Yaron Brook tackles the biggest geopolitical and philosophical questions shaping the future. From America's strategy toward Iran and the growing AI race with China to government interference in technology, ICE controversies, Democratic Socialists of America, JD Vance's critique of GDP, and what real human achievement actually means, this episode connects today's headlines to the deeper ideas driving them.Yaron also answers an outstanding slate of audience questions covering SpaceX, Trump, Reagan, welfare, Silicon Valley, Alex Epstein, capitalism, sanctions, Ayn Rand, Catholicism, Objectivism, commodity trading, financial markets, and much more.If you want analysis that goes beyond the headlines and gets to first principles, this episode is for you. Watch now: https://youtube.com/live/J8_hKMVNOH8Timestamps00:00 Introduction00:32 World Cup highlights & opening thoughts06:36 Upcoming events and seminars07:48 Iran developments and America's strategy15:32 AI breakthroughs, China, and the global race29:16 Government intervention in AI companies38:00 ICE assault investigation45:35 Democratic Socialists of America platform54:07 JD Vance, GDP, opioids & economic misunderstanding1:07:52 Poverty, consumerism & what GDP really measures1:12:05 Shipping innovation, satellites & global energy access1:18:10 Closing thoughtsLive Audience Questions1:28:15 Why did SpaceX stock fall so quickly after its IPO?1:28:23 Is Trump's refusal to apologize the secret to his political success?1:30:07 Why does altruism appeal to people who think in binaries?1:32:29 Does the welfare state prevent—or create—socialism?1:40:09 Why do people make their beliefs part of their identity?1:42:57 Do corrupt politicians still need capitalism to survive?1:45:01 What's the hardest part of teaching Ayn Rand?1:47:09 Why isn't New Hampshire another Silicon Valley?1:52:55 Has Alex Epstein changed the energy debate?1:54:09 Why did Trump strike Iran?1:58:08 Why doesn't Trump pursue Reagan-style tax cuts?1:59:53 Does Objectivism protect against despair and nihilism?2:01:24 Tom Brady, Jake Paul & the "sanction of the victim"2:02:53 Scholarship eligibility question2:03:14 Why are intellectuals embracing Catholicism?2:07:19 Are Trump's investment accounts really pro-capitalist?2:13:27 What would make Gulf states confront Iran?2:19:02 Why do wealthy elites promote welfare policies?2:24:14 Is trading with sanctioned nations moral?2:25:10 What did Reagan actually deregulate?2:26:49 What would markets look like under genuine capitalism?Like this episode?Subscribe, share it with friends, and become a Patreon supporter to access monthly AMAs, exclusive content, and commercial-free audio.#Iran #ChinaAI #ArtificialIntelligence #Trump #JDVance #economics #China #Politics #AynRand #Objectivism #Capitalism The Yaron Brook Show is Sponsored by[The Ayn Rand Institute](https://www.aynrand.org/starthere)[Energy Talking Points, featuring AlexAI, by Alex Epstein](https://alexepstein.substack.com/)[Express VPN](https://www.expressvpn.com/yaron)[Hendershott Wealth Management](https://www.youtube.com/watch?v=X4lfC...) &(https://hendershottwealth.com/ybs/)[Michael Williams & The Defenders of Capitalism Project](https://www.DefendersOfCapitalism.com)[Support the Show]( / yaronbrookshow )[Sponsor the Show](askyaron@yaronbrookshow.com/)[One-time donation](https://bit.ly/2RZOyJJ)Join the [Yaron Brook Show YouTube channel]( / @yaronbrook )Like what you hear? Like, share, and subscribe to stay updated on new videos and help promote the [Yaron Brook Show](https://bit.ly/3ztPxTx)Continue the discussion by following Yaron on [Twitter](https://bit.ly/3iMGl6z) and [Facebook](https://bit.ly/3vvWDDC )Want to learn more about Ayn Rand and Objectivism? Visit the [Ayn Rand Institute](https://bit.ly/35qoEC3)Become a supporter of this podcast: https://www.spreaker.com/podcast/yaron-brook-show--3276901/support.Yaron is the executive chairman of the Ayn Rand Institute and a world class speaker. He is the coauthor of the national best-seller Free Market Revolution: How Ayn Rand's Ideas Can End Big Government, Equal is Unfair: America's Misguided Fight Against Income Inequality and In Pursuit of Wealth: The Moral Case for Finance. He speaks around the world on a variety of topics including the morality of capitalism, Ayn Rand and her philosophy, finance and economics, and the value of inequality.

Connect with Early Riders — https://www.earlyriders.com/contactConnect with Onramp — https://onrampbitcoin.com/contact-us/Presented collaboratively by Early Riders & Onramp Media…Final Settlement is a weekly podcast covering capital markets, dealmaking, early-stage venture, bitcoin applications and protocol development.This week Michael, Liam, and Brian break down Moonshot's Kimmy K3 release and what a more open, cheaper Chinese frontier model means for the race against Claude Fable 5 and GPT 5.6, from cyber guardrails and export controls to the Trump administration weighing a ban on Chinese models. They dig into the AI capital markets: Anthropic and DeepSeek's IPO plans, Nous Research's $75 million raise at a $1.5 billion valuation, Gavin Baker's intelligence-per-dollar thesis, Liquid AI, and OpenShip's self-hostable app platform. The guys run through the payments story: the $53 billion Stripe, Advent, and Block bid for PayPal, Visa's new OUSD stablecoin platform, and Amazon Japan's move into a yen-backed stablecoin. They cover a stack of digital asset headlines: IBIT options limits rising to 1 million contracts, Citadel's $400 million investment in Crypto.com at a $20 billion valuation, the ECB's digital euro pilot, Velocity's $38 million Series A, Tether's Genius Act countdown, and Lynn Alden's new Bitcoin-focused PE firm. They close on where the Clarity Act stands, Early Riders' mid-year letter, Onramp's back-to-basics promo, and AI's arrival in film and music.Chapters00:00 - Introduction and Weekly Recap01:26 - Kimmy K3 Release and Open Source AI Models05:43 - Meta-level Analysis of AI Race and AGI08:04 - AI Development: Capabilities and Guardrails09:44 - AI as a Commodity and Data Strategies11:08 - Global AI Race and Export Controls13:13 - US-China AI Power Dynamics16:46 - US Regulatory Posturing and Competition21:55 - US and Chinese AI Model Competition24:58 - AI Infrastructure and Market Share Shifts31:40 - AI and Financial Markets: IPOs and Capital Flows36:29 - Open Source AI Projects and Sovereignty37:16 - Fintech and Payments: Stripe, PayPal, and Crypto49:05 - Digital Asset Headlines: Tether, Stablecoins, and Regulation52:58 - Crypto Market Dynamics and Capital Flows55:25 - Bitcoin and Digital Asset Strategies01:00:16 - AI and Bitcoin: The Future of Capital and Innovation01:12:50 - Closing Remarks and Future OutlookIf you found this valuable, please subscribe to Early Riders Insights for access to the best content in the ecosystem weekly: https://www.earlyriders.com/researchKeep up with Michael:https://x.com/MTangumaKeep up with Liam:https://x.com/Lnelson_21Keep up with Brian:https://x.com/BackslashBTC

Big Tech once again ruled the options market as NVIDIA, Tesla, Apple, Microsoft, Amazon, Alphabet, Micron, and Intel accounted for the day's most active contracts despite a lighter overall trading session. On this episode of The Hot Options Report, Mark Longo breaks down the biggest options movers of Monday's session, including: NVIDIA once again claims the top spot on the options leaderboard Tesla extends its recent slide as traders swarm same-day expiration calls Apple's impressive rally finally cools off Microsoft, Amazon, Micron, Intel and Alphabet all see heavy 0DTE activity SpaceX continues trading below its IPO price while the mysterious 330 calls remain active IREN surges nearly 20% as options traders chase the move QuikOptions' latest Congressional and Senate trading scans Plus, we examine how many of today's hottest same-day expiration options briefly traded in the money before reversing by the closing bell. For institutional-quality options flow, unusual activity, dark pool analytics, Congressional trading data, and much more, visit TheHotOptionsReport.com, powered by QuikOptions.

Markets never stop moving, and neither do the conversations that matter most to investors and future retirees. Join Wes Moss and Connor Miller on this episode of the Money Matters Podcast as they break down the latest retirement planning, investing, financial planning, and personal finance headlines with historical perspective and practical context. • Find out how the latest inflation data may influence Federal Reserve policy and interest rate expectations. • See what early projections for the 2027 Social Security COLA—and rising Medicare Part B premiums—may mean for retirement income planning. • Compare wage growth and inflation to better understand what's happening with purchasing power. • Explore the buzz around IPOs while examining what history suggests about IPO investing versus long-term index investing. • Discover how stocks, bonds, and cash have historically performed after inflation across different investment time horizons. • Consider how oil prices, global events, and corporate earnings may influence market volatility and investor sentiment. • Follow the broadening earnings story across the S&P 500, including the growing impact of artificial intelligence spending and wider sector participation. • Learn about the retirement planning tools and bonus resources available with The Retire Sooner Method. Listen to the Money Matters Podcast for more conversations connecting today's headlines with retirement planning, investing, financial planning, and personal finance. Subscribe wherever you get your podcasts so you never miss a new episode.

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. Today, we're navigating through a myriad of transformative advancements reshaping the industry. From artificial intelligence-driven research breakthroughs to strategic acquisitions in emerging therapeutic areas, these developments are setting new benchmarks in drug discovery and patient care. **Strategic Acquisitions and Expansions:** Samsung Biologics' recent proposal to acquire Swiss CDMO Polypeptide for $1.8 billion marks a significant expansion into peptide production, underscoring the growing therapeutic importance of peptides. Their specificity and efficacy make them particularly appealing for metabolic disorders such as obesity. This acquisition reflects a strategic move to capture emerging market opportunities as demand for innovative metabolic treatments rises. Eli Lilly's bold $2.8 billion acquisition of Atai-Beckley highlights the pharmaceutical industry's shifting focus towards psychedelics. As mental health disorders like depression and PTSD become more prominent, psychedelics hold great promise for new therapeutic approaches. This acquisition may pave the way for further research and acceptance of psychedelics within mainstream medicine, offering new hope for patients. Another notable development is Tempus' acquisition of Personalisis for $1.5 billion. This move strengthens Tempus' cancer treatment portfolio by leveraging genomics-driven insights, emphasizing precision medicine's critical role in oncology. **AI Integration and Technological Innovation:** Bristol Myers Squibb is doubling down on AI integration by expanding its collaboration with Nvidia to build what promises to be the most powerful AI supercomputer dedicated to life sciences. This development is pivotal as it signifies a deeper commitment to harnessing computational power in R&D. By accelerating drug discovery and optimizing clinical trial processes, AI stands to revolutionize how treatments are developed and tailored to individual patients. Overall, these developments indicate a dynamic phase characterized by technological innovation and strategic collaborations. The integration of AI into drug development processes stands out as a transformative force, promising enhanced efficiency and efficacy in bringing new treatments to market. **Regulatory Milestones and Clinical Trials:** In regulatory news, Takeda's Qdenga has achieved a milestone by becoming India's first approved dengue vaccine. This approval is crucial in addressing neglected tropical diseases, with significant implications for public health in regions where dengue is prevalent. By reducing dengue fever incidence, this vaccine could play a vital role in improving health outcomes in many tropical countries. Promising results have emerged from clinical trials across various therapeutic areas. 4D Molecular Therapeutics reported an 87% reduction in treatment burden for wet AMD using their gene therapy candidate 4D-150 in Phase 2b trials—demonstrating potential as a transformative approach with reduced intervention frequency. Latigo Biotherapeutics' Nav1.8 inhibitor LTG-001 outperformed Vicodin in Phase 2 trials for acute pain, offering a non-opioid alternative amidst the opioid crisis. Meanwhile, Regenxbio's five-year data on surabgene lomparvovec shows sustained efficacy in wet AMD and diabetic retinopathy—underscoring its potential as a long-term treatment option. **Financial Performance and IPO Activity:** Financially, Abbott exceeded expectations with strong sales from their device and diagnostic divisions, prompting an upward revision of their full-year profit forecast. This reflects sustained demand for innovative diagnostic solutions and medical devices—highlighting Abbott's strategic market positioning. The IPO landscape remains active with companies like Nuvox Therapeutics seeking to raise funds for advancing oxygen therapeutics targeting hypoxia-related diseases—showcasing renewed investor interest and confidence within biotech innovation. Latigo Biotherapeutics is preparing for an IPO to advance its pipeline, demonstrating a strategic response to the opioid crisis. By developing alternatives that minimize addiction risks while providing effective relief, Latigo underscores the industry's commitment to safer pain management solutions. Turning to clinical trials, Scribe Therapeutics plans a $96 million IPO to advance its CRISPR-based lipid-lowering therapies, marking significant interest in genetic solutions for cardiovascular diseases like hyperlipidemia. The precision offered by CRISPR technology could revolutionize treatment options for conditions contributing significantly to cardiovascular health burdens. **Geopolitical Influences:** Geopolitical factors are also influencing market dynamics, particularly in the UK biotech sector where IPO plans are being shaped by global uncertainties despite robust venture capital backing. This situation underscores the complex interplay between regional economic conditions and global investment trends in biotech innovation. As these trends continue unfolding across the industry landscape—from AI-driven research advancements to strategic acquisitions—the potential impact on patient care paradigms remains profound. These developments not only promise new possibilities within drug development but also influence broader healthcare delivery models aimed at improving patient outcomes globally.Support the show

Moonshot AI plans for IPO. Moonshot AI's Kimi K3 model outscored every AI rival except Fable 5 and GPT-5.6, triggering a semiconductor selloff. Now the company is preparing for a Hong Kong IPO at a $30 billion-plus valuation. CoinDesk's Sam Ewen hosts "CoinDesk Daily." - This episode is brought to you by RealFi, a smarter stablecoin, backed by real-world assets. Find out more at⁠⁠⁠⁠⁠⁠⁠ realfi.co⁠⁠⁠⁠⁠⁠⁠. - Ledn provides a secure and transparent way to access liquidity while maintaining your bitcoin holdings. Perfect 8 year track record of keeping clients assets safe. Don't sell your bitcoin. Get a bitcoin-backed loan. Check out your rate by using their loan calculator at⁠⁠⁠⁠⁠⁠⁠ ledn.io⁠⁠⁠⁠⁠⁠⁠ JPEG Trading is a global proprietary trading firm specializing in cryptocurrency and decentralized finance markets. From market structure and liquidity provision to quantitative trading strategies, JPEG Trading operates across the full spectrum of blockchain-based assets. Follow @jpegtrading on X to stay ahead of the latest developments in digital asset markets:⁠⁠⁠⁠⁠⁠⁠ https://x.com/jpegtrading⁠⁠⁠⁠⁠⁠⁠ - This episode was hosted by Sam Ewen. “CoinDesk Daily” is produced by Jennifer Sanasie and edited by Victor Chen.

Today's Post - https://bahnsen.co/4yvcd4b David Bahnsen reviews a modest down day for markets as Iran tensions and reported American casualties push oil above $80 (ending above $83), with the Dow down ~300, S&P -19 bps, Nasdaq -5 bps, and the 10-year yield at 4.59%; communication services and energy led while healthcare lagged. He cites IPO froth cooling, noting SpaceX below $120 versus a $135 IPO and far off highs. In politics, he highlights Maine's Senate race likely featuring progressive Troy Jackson versus Susan Collins and notes Michigan Democrats consolidating behind Haley Stevens, outlining the difficult map for a Democratic Senate majority. Economically, he underscores the Supreme Court reversal of IEEPA tariffs lowering blended import tariffs from ~11% to ~6–6.5%, while flagging a record 105.8M outside the labor force, soft industrial production, rising import prices, and housing starts driven by multifamily. He previews next week's Fed meeting under Chair Kevin Warsh, balance-sheet maturity shortening, midstream earnings (Kinder Morgan), and answers why shorting stocks is inherently leveraged and generally unsuitable for most investors. 00:00 Welcome and Setup 00:17 Iran Tensions and Oil 01:24 Market Wrap and Sectors 02:17 IPO Froth Check 03:13 Senate Races Outlook 05:39 Economy Data and Tariffs 07:43 Housing and Fed Preview 09:08 Energy Earnings and Gas 10:01 Ask TBG Short Selling 12:00 Wrap Up and Links Links mentioned in this episode: DividendCafe.com TheBahnsenGroup.com

Is Cerebras Systems the next great AI chip stock or a red-hot IPO priced for perfection? In this episode of 7investing Live, Simon Erickson and executive producer Heather Horton welcome back Nick Rossolillo, co-founder of Chip Stock Investor, to break down three of the market's biggest stories.First up: Cerebras Systems (NASDAQ:CBRS), the wafer-scale chip maker that just IPO'd at a $40+ billion market cap. With 44GB of SRAM embedded directly on the chip, Cerebras was purpose-built to solve AI's "memory wall" problem for inference workloads. Now it's reportedly landed a ~$10 billion order from OpenAI and a deal with Amazon Web Services that could top $20 billion. Simon and Nick dig into whether these massive orders are real, how Cerebras stacks up against NVIDIA's GPUs and hyperscaler custom silicon, the TSMC capacity bottleneck that could throttle its growth, and how to value a company trading near 20x sales without profits.Then the conversation turns to Rocket Lab (NASDAQ:RKLB), which has pulled back from $150 to around $70 per share. Simon shares the latest iteration of his discounted cash flow valuation, and the duo debates the proposed Iridium acquisition — a deal that could pull Rocket Lab to EBITDA-positive on a pro forma basis — plus what the long-awaited Neutron rocket launch means for the company's future.Finally: Netflix (NASDAQ:NFLX). After another quarter of decelerating revenue guidance, is the streaming giant now a value stock rather than a growth stock? Nick explains why the advertising business hasn't reaccelerated growth the way he expected, and what he'd need to see before buying the dip.Plus: Nick's take on the recent chip stock sell-off across NVIDIA, AMD, Broadcom, SanDisk, and Kioxia and why "stocks go up, stocks go down" might be the healthiest way to think about it.Subscribe for more deep dives on AI infrastructure, semiconductors, and innovative growth stocks!Start your FREE 7-day trial of 7investing: https://www.7investing.com/subscribeFollow Nick and Casey Rossolillo at Chip Stock Investor: https://chipstockinvestor.comRocket Lab Deep Dive videos mentionedPart 1 https://youtu.be/AMDd0-JKUH0 (Deep Dive)Part 2: https://youtu.be/Z76xTGFNwBA (Valuation)Companies MentionedPublicly Traded:Cerebras Systems (NASDAQ:CBRS)Rocket Lab (NASDAQ:RKLB)Netflix (NASDAQ:NFLX)NVIDIA (NASDAQ:NVDA)Advanced Micro Devices (NASDAQ:AMD)Broadcom (NASDAQ:AVGO)Micron Technology (NASDAQ:MU)Taiwan Semiconductor Manufacturing (NYSE:TSM)Amazon (NASDAQ:AMZN)Alphabet (NASDAQ:GOOGL)Meta Platforms (NASDAQ:META)Iridium Communications (NASDAQ:IRDM)SanDisk (NASDAQ:SNDK)Kioxia Holdings (TSE:285A)Globalstar (NASDAQ:GSAT)SpaceX (NASDAQ: SPCX)Private / Pre-IPO:OpenAIAnthropicVideos Mentioned:https://www.youtube.com/watch?v=Z76xTGFNwBA&t=3shttps://www.youtube.com/watch?v=AMDd0-JKUH0&t=987sHere's the shifted chapter list, with all timestamps moved back 55 seconds:0:00 Welcome to 7investing Live0:54 Cerebras Systems: IPO recap & the Wafer-Scale Engine2:31 Is NVIDIA even the right comparison for Cerebras?5:38 The memory wall: why bigger AI models need new chips8:52 Latency vs. throughput — and the new AI alliances10:46 Are the $10B OpenAI & $20B Amazon orders real?14:02 Cerebras risks: how do you value a hot IPO?17:27 The TSMC capacity bottleneck20:01 Heather's take on Cerebras20:41 Rocket Lab: the sell-off & Iridium acquisition24:34 Simon's DCF valuation & price target for RKLB29:05 Why Neutron changes everything30:12 Q&A: Does Peter Beck carry an "Elon premium"?31:36 Netflix: buying opportunity or cheap for a reason?36:57 Q&A: Is Netflix a growth stock or a value stock?39:03 Chip stocks selling off: normal volatility or a warning?42:57 Wrap-up & final thoughts#7investing #Simonerickson #Cerebras #CBRS #NVIDIA #AIinvesting #semiconductors #chipstocks #RocketLab #RKLB #Netflix #NFLX #AIinference #stocks #investing #stockmarket #TSMC #AIdatacenters

Wall Street isn't the only place where billion-dollar deals are happening.This week, Anthony Cheung and Stephen Barnett break down ITV's agreement to sell its television and streaming business to Comcast, the owner of Sky, and explain why this is far more than just another media acquisition. They explore how investment banks advise on transformational M&A deals, why companies separate business divisions to unlock value, and what the transaction means for the future of UK broadcasting.They also analyse Reformation's upcoming IPO, using it as a case study to explain direct-to-consumer brands, private equity exits, consumer investing and why some retail companies become stock market winners while others collapse. Along the way, they compare brands including Nike, Lululemon, Abercrombie and Allbirds, discuss what makes an attractive IPO candidate, and explain how investment banks position companies before going public.Whether you're preparing for finance interviews, working in markets, or simply want to better understand the biggest business stories shaping the economy, this episode breaks down the commercial awareness behind the headlines.(00:00) England Exit(02:29) ITV Sold to Sky(06:37) The Deal Advisers(08:03) Comcast Explained(16:07) ITV Business Model(19:53) The Role of Banks(30:07) Reformation IPO(33:58) The Numbers(40:17) Nike vs Abercrombie(45:33) PE Exit Strategy(52:08) IPO Boom(53:54) Final Prediction

Mark Hamrick, chief economic analyst at The Hamrick Brief, says that the current affordability crisis has the potential to trigger a recession, if it gets to where there's a slowdown in spending that spills over to impact employment levels. That said, Hamrick says current conditions aren't yet deserving of the label of "economic crisis," even if it feels that way for some individuals and households, effectively the bottom portion of the k-shaped recovery. Still, Hamrick says the remarkable facet of the U.S. economy is that it has been able to avoid recession for this long. Vijay Marolia, chief investment officer at Regal Point Capital, says "Mr. Market is a manic depressive," and is showing those tendencies by getting so excited by positive guidance and potential that the reaction to strong earnings reports has been horrible stock action. He expects that to potentially continue this week, when the focus of earnings season shifts to A.I.-driven companies like Alphabet, Intel and Tesla. Marolia says the market's earnings swings have contributed to an ongoing downturn for tech stocks, though he believes it's more of a buying opportunity than the start of a correction. Plus, with June's inflation reading being partly positive (better than May) mixed with negative (worse than when conflict started with Iran), "Captain Inflation" gives his take on how to best read and cope with the numbers. David Trainer, founder and president at New Constructs, says that while fans may believe Jersey Mike's is "a sub above," the company's initial public offering is a deal from below. While the IPO's launch date hasn't been determined, Trainer says the expected $12 billion valuation is at least double what he thinks the numbers justify, and that the deal — particularly at that level — mostly benefits the private-equity firm that took control of Jersey Mike's in 2025.

Kevin Warsh is taking a different approach as Fed chair, and investors are trying to figure out whether his quieter style will bring more discipline to monetary policy or create a new layer of uncertainty.Chuck Zodda and Mike Armstrong break down Warsh's early approach to the Fed, why pulling back from forward guidance may not mean what markets think, and why his real test will come when inflation, employment, or stocks force him to make a difficult call. They also discuss rising single-stock volatility, how leverage and new trading products may be adding risk, what SpaceX's post-IPO drawdown says about newly public companies, why Americans are pulling back on retirement savings, and how housing affordability looks different once income growth and mortgage rates are included.

Derek Moore is joined by Mike Snyder and Shane Skinner to discuss SpaceX now being below its IPO price and whether it can grow into its current value. Plus, Apple sues OpenAI as the stock continues to run into earnings. Later, did anything fundamentally change with the memory stocks like Micron or people just don't want to be the last out. Finally, the Strait of Hormuz didn't matter to markets until the market decided it mattered again.   Apple sues OpenAI Micron and the memory stocks dip again Trading behavior psychology losing hurt more than winning feels good? Strait of Hormuz tanker tracker ticks lower More sellers than buyers in memory stocks SpaceX moves below its IPO price Looking at the Mag7 stocks and how they grew into their valuations over a decade    Were the Mag7 stocks expensive or undervalued in hindsight 10 years ago? SpaceX forward valuation Interest rates and oil prices Inflation surprises to the downside   Mentioned in this Episode     Derek Moore's book Broken Pie Chart https://amzn.to/3S8ADNT   Jay Pestrichelli's book Buy and Hedge https://amzn.to/3jQYgMt   Derek's book on public speaking Effortless Public Speaking https://amzn.to/3hL1Mag   Contact Derek derek.moore@zegainvestments.com  

Samuel Kerr helps investors navigate the AI landscape after bearish price action claws into many tech names. He says earnings "need to be better than great" for stocks to see significant rallies. Nvidia (NVDA) is the company Samuel continues to see acting as the main meter to gauge AI health. As for SpaceX (SPCX), Samuel considers it an AI-adjacent company and talks about expectations it set for OpenAI and Anthropic's upcoming IPOs. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

Want a quick estimate of how much your business is worth? With our free valuation calculator, answer a few questions about your business, and you'll get an immediate estimate of the value of your business. You might be surprised by how much you can get for it: https://flippa.com/exit What makes a business truly valuable to a buyer, and how do you know when it is actually time to sell? In this episode of The Exit, Steve McGarry sits down with Mike Krupit, founder and CEO of Trajectify, to unpack the leadership decisions that can make or break an exit. Drawing on a career that includes eight startups, three IPOs, an exit, and four failures, Mike explains why founders who remain at the center of everything can become a liability to their own business. He shares how putting the right people in the right seats, documenting critical processes, building strong systems, and delegating real authority can create a healthier and more valuable company.

 Mike also explores why the best time to sell is often when the business is performing well but approaching its next major plateau, and why founders need to prepare for what happens after the transaction before signing the deal. Steve and Mike discuss preserving company culture through an acquisition or IPO, communicating with employees when an exit process must remain confidential, evaluating leadership teams from the buy side, and avoiding the culture shock that can follow a major transaction. Whether you are actively preparing to sell or simply want to build a business that can thrive without you, this conversation offers a practical roadmap for creating a stronger, more transferable company.
 Mike Krupit is the founder and CEO of Trajectify, where he advises entrepreneurs, executives, and leadership teams on business growth, organizational development, and major transitions. A veteran of eight startups, Mike has held roles ranging from CTO to COO to CEO and has experienced three IPOs, mergers and acquisitions, and business failures throughout his career. Since founding Trajectify in 2013, he has focused on helping growth stage companies strengthen their leadership, align their people and processes, and successfully navigate the next stage of growth or an exit.


 LinkedIn - https://www.linkedin.com/in/mkrupit/ 


 Key Timestamps:

 [2:36] Introduction and Mike Krupit's Background 
 [2:56] Mike's Startup Journey and Leadership Lessons
 [4:24] Leadership and Business Valuation Factors
 [5:48] Preparing a Business for Exit: Documentation and Systems
 [7:12] Culture Preservation During Exit and IPO
 [10:03] Evaluating Leadership for Acquisition
 [11:35] Timing the Sale: When Is the Right Moment?
 [15:37] Mistakes in Exits and Post-Exit Planning
 [18:22] Driving Up Valuation: Processes and Leadership
 [19:30] Team Tactics for Confidentiality and Communication
 [22:27] IPO vs. Acquisition: Culture and Leadership Changes
 [26:35] Advice to Younger Self and Current Projects

 
 --
 The Exit—Presented By Flippa: A 30-minute podcast featuring expert entrepreneurs who have been there and done it. The Exit talks to operators who have bought and sold a business. You'll learn how they did it, why they did it, and get exposure to the world of exits, a world occupied by a small few, but accessible to many. To listen to the podcast or get daily listing updates, click on flippa.com/the-exit-podcast/

Apple's lawsuit accusing OpenAI of obtaining trade secrets through former employees raises questions about corporate ethics, recruitment practices, confidentiality agreements, and OpenAI's hardware ambitions. The panel considers the potential legal and financial consequences before examining Apple's plan to end support for encrypted HFS+ volumes and what users should do with older drives. Panel members include: Chuck Joiner, David Ginsburg, Marty Jencius, Eric Bolden, Brian Flanigan-Arthurs, Jim Rea, Web Bixby, Jeff Gamet, and Mark Fuccio. Today's MacVoices is supported by TV+ Talk, our MacVoices series with Charlotte Henry focused on Apple TV+. From shows and other content to the business side there's always something to learn about apple's streaming service. Find it at the Categories listings on the web site or go directly to macvoices.com/category/tvplustalk. Show Notes: Chapters:00:00 Apple challenges OpenAI over alleged trade secrets01:00 Former Apple employees and recruitment allegations02:00 OpenAI's finances, AI skepticism, and IPO risks04:03 Evidence, corporate devices, and Apple's legal strategy05:00 Recruitment culture and ethical concerns06:13 How the case could reveal Apple's hardware plans07:06 Possible legal exposure and the discovery process08:00 AI talent wars and multimillion-dollar compensation09:33 Confidentiality agreements after leaving Apple11:14 Apple's shifting relationships with OpenAI and Google12:06 John Ternus and speculation about Apple leadership13:00 Apple silicon, neural engines, and possible M7 plans14:36 Contractors, confidentiality, and additional legal risks15:16 Jony Ive and potential collateral damage17:01 macOS 28 and encrypted HFS+ support18:00 Apple's long-term transition away from HFS+19:00 Preparing and transferring data from legacy drives20:04 Microsoft support policies and software subscriptions21:05 Clarifying Windows access to HFS+ drives Links: Apple Sues OpenAI for Stealing Trade Secrets to Build AI Hardware https://www.macrumors.com/2026/07/10/apple-sues-openai/ Guests: Get detailed bios and contact information about for the panel on the MacVoices Live! Panel page on our web site:https://macvoices.com/macvoiceslive/macvoices-live-panel/ Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Welcome to Omni Talk's Retail Daily Minute, sponsored by R&S Logistics, Duvo and Mirakl.In today's Retail Daily Minute, Omni Talk's Chris Walton discusses:Wonder closes a $650 million Series D at a $9 billion valuation, with reports the food-platform company is gearing up for an IPO as early as next year.Instacart acquires Arpalus, an AI-powered shelf-scanning startup, to give its in-store shoppers real-time inventory data via smartphone and Caper Cart cameras.CVS Health opens its first pharmacy-focused store in Houston as it accelerates a scaled-down, pharmacist-centered format nationwide.The Retail Daily Minute has been rocketing up the Feedspot charts, so stay informed with Omni Talk's Retail Daily Minute, your source for the latest and most important retail insights.

Apple's lawsuit accusing OpenAI of obtaining trade secrets through former employees raises questions about corporate ethics, recruitment practices, confidentiality agreements, and OpenAI's hardware ambitions. The panel considers the potential legal and financial consequences before examining Apple's plan to end support for encrypted HFS+ volumes and what users should do with older drives. Panel members include: Chuck Joiner, David Ginsburg, Marty Jencius, Eric Bolden, Brian Flanigan-Arthurs, Jim Rea, Web Bixby, Jeff Gamet, and Mark Fuccio. Today's MacVoices is supported by TV+ Talk, our MacVoices series with Charlotte Henry focused on Apple TV+. From shows and other content to the business side there's always something to learn about apple's streaming service. Find it at the Categories listings on the web site or go directly to macvoices.com/category/tvplustalk. Show Notes: Chapters: 00:00 Apple challenges OpenAI over alleged trade secrets 01:00 Former Apple employees and recruitment allegations 02:00 OpenAI's finances, AI skepticism, and IPO risks 04:03 Evidence, corporate devices, and Apple's legal strategy 05:00 Recruitment culture and ethical concerns 06:13 How the case could reveal Apple's hardware plans 07:06 Possible legal exposure and the discovery process 08:00 AI talent wars and multimillion-dollar compensation 09:33 Confidentiality agreements after leaving Apple 11:14 Apple's shifting relationships with OpenAI and Google 12:06 John Ternus and speculation about Apple leadership 13:00 Apple silicon, neural engines, and possible M7 plans 14:36 Contractors, confidentiality, and additional legal risks 15:16 Jony Ive and potential collateral damage 17:01 macOS 28 and encrypted HFS+ support 18:00 Apple's long-term transition away from HFS+ 19:00 Preparing and transferring data from legacy drives 20:04 Microsoft support policies and software subscriptions 21:05 Clarifying Windows access to HFS+ drives Links: Apple Sues OpenAI for Stealing Trade Secrets to Build AI Hardware https://www.macrumors.com/2026/07/10/apple-sues-openai/ Guests: Get detailed bios and contact information about for the panel on the MacVoices Live! Panel page on our web site: https://macvoices.com/macvoiceslive/macvoices-live-panel/ Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Southeast Asia's venture market is not in a downturn. It is in a structural winter, and mid-2026 is when that distinction stopped being academic. Kristie Neo returns to break down what is actually happening across the region: Singapore's IPO revival is real but is being carried by data centres and REITs rather than homegrown tech; allocators now rank Southeast Asia at the bottom of Asia behind China, India, Japan, Korea and ANZ; and a generation of growth-stage companies is being kept alive past the point where a merger or a wind-down would have served everyone better. Jeremy Au and Kristie also work through what could actually restart the funding ladder, from encouraging tech M&A and fixing university IP commercialisation, to tax incentives for angels and support for syndicate leads who can assemble the $1 million to $5 million rounds that Singapore currently cannot fill. If you are a founder raising in Singapore, Indonesia, Vietnam, Philippines, Thailand or Malaysia, or an LP trying to work out where capital goes next in Asia, this is the honest state of the market. Watch, listen or read the full insight at https://www.bravesea.com/blog/kristie-neo-southeast-asia-zombie-unicorns  BRAVE is Southeast Asia's leading tech podcast, hosted by Jeremy Au. Honest conversations with the region's top founders, investors, and operators on building startups in Southeast Asia. New episodes every week. Subscribe so you never miss one. Listen & Subscribe YouTube (English), YouTube (Bahasa Indonesia), Spotify (English), Spotify (Bahasa Indonesia), Spotify (Chinese), Spotify (Vietnamese), Apple Podcasts Follow BRAVE LinkedIn, X (Twitter), Instagram, TikTok, WhatsApp Follow Jeremy Au LinkedIn, X / Twitter, Instagram, TikTok, Facebook, Threads, Twitch Resources Get transcripts, startup resources & community discussions at www.bravesea.com #SoutheastAsia #VentureCapital #SingaporeIPO 00:00 Intro 01:00 Singapore's IPO revival and what is really lifting SGX 06:30 Safe haven status and the Indonesia allocation problem 09:34 Why Southeast Asia sits at the bottom of the allocator stack 14:58 A generation of zombie companies 18:07 The case for mergers, folds and consolidation 21:50 Fixing the funding ladder: who writes the first check 23:55 The IP commercialisation gap and university tech licensing 35:15 Rethinking how governments seed VC funds 41:24 Where can an LP put money today 45:00 Incentivising angels, syndicates and family offices 52:43 The information gap and parting thoughts

Good morning from Pharma Daily: the podcast that brings you the most important developments in the pharmaceutical and biotech world. Today, we delve into a series of industry-shaping events, reflecting the ever-evolving landscape of drug development, regulatory challenges, and strategic maneuvers. In a significant move within the sector, Jasper Therapeutics has merged with Kira Pharmaceuticals, a strategic decision aimed at expanding its footprint in autoimmune therapeutics. This merger brings to Jasper a valuable asset in KP-104, a dual-inhibitor with the potential to address rare diseases—an area of considerable unmet need. Such consolidations highlight an industry trend where companies seek to bolster their portfolios with promising candidates that can tackle complex medical conditions. The merger exemplifies how strategic expansions are becoming increasingly integral to maintaining competitive edges in the biotech arena. Turning to clinical trials, Takeda's Zasocitinib has demonstrated promising results for patients suffering from moderate-to-severe plaque psoriasis. In Phase 3 trials, a significant 75% of patients achieved clearance of scalp psoriasis. Zasocitinib operates as a TYK2 inhibitor, targeting the IL-23 pathway—a crucial mechanism in autoimmune diseases like psoriasis. This breakthrough promises to enhance patient care by providing a more effective treatment option for those struggling with difficult-to-treat psoriasis. On the regulatory front, Novartis' Fabhalta (Iptacopan) has gained FDA approval for its role in slowing kidney function decline in patients with primary immunoglobulin A nephropathy. As a small molecule complement inhibitor, Iptacopan introduces a novel treatment class for this autoimmune kidney disorder. This approval underscores ongoing innovation within nephrology and offers renewed hope for improved patient outcomes. Recent regulatory updates also saw Novartis securing full FDA approval for Fabhalta—an affirmation of progress in addressing immunoglobulin A nephropathy through innovative therapeutic options. Business development remains a driving force in shaping industry landscapes. The acquisition of Mission Therapeutics' AKI candidate MTX652 by Dimerix is a prime example. This $5 million deal, with potential milestones up to $292 million, reflects high stakes and ambitions to advance treatments for acute kidney injuries—a field with significant unmet medical needs. The integration of artificial intelligence continues to revolutionize drug discovery processes. Aqemia's collaboration with Sanofi highlights this trend, showcasing AI's crucial role in expediting drug development and uncovering novel therapeutic targets. Their partnership potentially worth $140 million underscores AI's transformative potential within pharmaceutical research. Notably, Nobel laureate Jennifer Doudna's foray into AI-powered protein design signifies an exciting intersection between gene-editing technology and artificial intelligence. Her involvement signals potential revolutions in drug discovery through enhanced precision in protein engineering. However, regulatory challenges persistently loom over the industry. Novo Nordisk and Alvotech have faced FDA scrutiny concerning manufacturing deficiencies—an issue that accentuates the importance of stringent quality control and operational excellence in biologics manufacturing. The American Society of Health-System Pharmacists (ASHP) report on U.S. drug shortages during Q2 2026 reveals vulnerabilities within supply chains, notably impacting oncology drugs. These shortages emphasize the critical need for robust strategies to ensure consistent drug availability for essential therapies. Furthermore, geopolitical dynamics are influencing pharmaceutical supply chains. A U.S. Senate bill aimed at increasing transparency highlights concerns over China's dominance in drug ingredient supplies—an issue necessitating strategic adjustments by globally operating companies. Elsewhere within the sector, GSK made headlines by discontinuing the development of its chronic cough treatment camlipixant following mixed Phase 3 trial results—a setback illustrating the critical nature of trial outcomes in determining drug viability and market potential. In market trends, biotech IPOs have surged during the first half of 2026—a sign of robust investor interest fueled by innovations and favorable funding environments despite associated market volatility risks. Strategic adjustments continue across companies with mergers and acquisitions leading to workforce reductions—projected layoffs exceeding 14,000 within biopharma during H1 2026—as organizations streamline operations or pivot towards more promising research domains. Lastly, Merck's FDA approval for an oral PCSK9 inhibitor marks a significant achievement in cardiovascular care—representing another stride forward in therapeutic innovation. In summary, these developments encapsulate a landscape defined by scientific pursuits yielding mixed results amidst evolving regulatory interactions and strategic realignments—all contributing towards innovative healthcare solutions while navigating complex industry dynamics.Support the show

SpaceX's blockbuster IPO is losing altitude as shares fall below their listing price, short sellers pile in, and investors question whether its AI ambitions can justify the company's sky-high valuation. Plus, a potentially record-setting El Niño could disrupt global food supplies and drive up grocery prices for years, with exposed crops like rice, sugar, and coffee facing the biggest risks.And in The Big Picture: Wildfires continue to burn across Canada, the Crown narrows its case against Toronto police officers accused in Project South, and the U.S. and Iran trade strikes after a ceasefire falls apart.The Peak Daily is produced in partnership with reframevid.com

In this episode of BizNews Daybreak, political commentator Solly Moeng examines South Africa's deepening criminal justice crisis. On the global stage, President Trump demands harsher Iran sanctions as Middle Eastern oil routes shift. Meanwhile, Chinese tech startups Moonshot AI and DeepSeek prepare for massive IPOs, investors confront AI energy bottlenecks, Netflix pivots to live content to win screen time, and Andy Burnham prepares for Downing Street.

Warsh admitted monetary policy caused inflation. Bessent thinks silver certificates still redeem at Fort Knox. And import prices are up 7.1%.This is episode is sponsored by Function. Join at https://functionhealth.com/peter and use code PETER25 for a $25 credit.This episode is also sponsored by Pebl. Go to https://hipebl.ai to get a free estimate.Treasury Secretary Scott Bessent told Fox viewers that old silver and gold certificates can still be redeemed at Fort Knox. Gold certificates were repudiated in 1933 and silver certificates in 1968. Peter Schiff argues that if the man who signs the currency does not know basic monetary history, there is no reason to trust his assurance that the gold in Fort Knox is all there.Markets confirmed the AI bubble is deflating. SpaceX fell 13.25% on the week to close below $124, under its $135 IPO price, and anyone who bought the post-IPO high near $225 is down 45%. Only about 5% of the company trades today, but lockups expire through year end and take the float to roughly 40%, an eightfold increase in supply. Gold closed at $4,017 and silver at $55.83, which Schiff calls a head fake created by the false narrative that war is bad for gold.The honest inflation numbers tell a different story than the CPI: import prices are up 7.1% year over year and export prices are up 10.2%, against a reported 3.5%. Kevin Warsh admitted in Senate testimony that monetary policy caused the inflation, then offered a plan that amounts to talking about it while the Fed's balance sheet grew another $7.4 billion. Schiff also covers Trump selling paid early access to market-moving posts and explosive new FOIA emails showing Euro Pacific Bank was shut down for publicity, with the Australian Tax Office driving the operation to protect a journalist facing his defamation suit.Chapters:00:00 Trump Posts Paywall01:23 Market Week Wrap07:42 Gold Silver War09:52 Inflation Data Reality23:30 Warsh Hearing Grifts37:59 AI Jobs and Progress40:22 Trump Post and Fox Fallout44:05 FOIA Trail and Censorship Claims50:31 Nine Fraud Bank Shutdown Emails57:07 Operation Atlantis PR ExposedFollow @peterschiffX: https://twitter.com/peterschiffInstagram: https://instagram.com/peterschiffTikTok: https://tiktok.com/@peterschiffofficialFacebook: https://facebook.com/peterschiffFree Reports & Market Updates: https://www.europac.comBook Store: https://schiffradio.com/booksSign up for Peter's most valuable insights at https://schiffsovereign.comSchiff Gold News: https://www.schiffgold.com/news#PeterSchiffShow #FortKnox #InflationOur Sponsors:* Check out Chilipad and use my code GOLD for a great deal: https://sleep.me* Check out Fast Growing Trees and use my code GOLD for a great deal: https://www.fast-growing-trees.com* Check out Plaud AI and use my code GOLD for a great deal: https://plaud.ai* Check out Quince and use my code quince.com/gold for a great deal: https://www.quince.com* Check out TruDiagnostic and use my code GOLD20 for a great deal: https://www.trudiagnostic.comPrivacy & Opt-Out: https://redcircle.com/privacy

Episode Overview What if you could invest in some of the world's most valuable private technology companies—before they ever go public? In this episode of The Silicon Valley Podcast, host Shawn Flynn sits down with Mark Klein, CEO of Neostellar  Capital, one of the few publicly traded venture capital firms providing investors with exposure to late-stage private companies. Neostellar 's portfolio includes investments in some of the most influential technology companies of the AI era, including OpenAI, Canva, Whoop, Vast Data, and it was also an early investor in CoreWeave. Mark shares how Neostellar 's "Public VC" model opens the door for public market investors to participate in venture-backed innovation—an opportunity that has traditionally been reserved for institutional investors and elite venture capital firms. The discussion dives into one of Neostellar 's most notable investments: its $17.5 million investment in OpenAI during the company's September 2024 funding round. As OpenAI's valuation has risen dramatically, Mark explains what that means for Neostellar  shareholders and how the firm evaluates opportunities in today's rapidly evolving AI investment landscape.. Beyond AI, Mark provides a behind-the-scenes look at the venture capital ecosystem, discussing secondary markets, companies remaining private longer, valuation discipline, and the unique challenges of operating a publicly traded venture capital firm while investing in private businesses. Whether you're a founder, investor, venture capitalist, or simply fascinated by the intersection of AI and capital markets, this episode provides valuable insight into how some of today's most sought-after private companies become investment opportunities. In This Episode Mark Klein's path to leading Neostellar  Capital Understanding the Public Venture Capital model Why private companies are staying private longer Investing in OpenAI before its valuation surge Lessons from being an early CoreWeave investor The future of AI infrastructure investing The growing role of secondary markets in venture investing Balancing public company transparency with private company confidentiality Where Mark sees the next wave of technology investment opportunities About Mark Klein Mark Klein is the Chief Executive Officer of Neostellar  Capital Corp. (NASDAQ: SSSS), a publicly traded venture capital firm focused on investing in high-growth, venture-backed private technology companies. Since its inception, Neostellar  has provided public market investors with access to companies that traditionally remain unavailable until IPO, building a portfolio that includes OpenAI, Canva, Whoop, Vast Data, CoreWeave, and numerous other category-defining businesses. Key Takeaways Public markets can provide exposure to private innovation through specialized investment vehicles. Secondary markets have become an increasingly important source of liquidity and deal flow. Companies staying private longer have fundamentally changed venture investing. Successful venture investing requires balancing long-term conviction with disciplined valuation analysis. Connect with Mark Klein LinkedIn: https://www.linkedin.com/in/mark-klein-6a5b72198/   Disclaimer: The views expressed in this podcast are for informational purposes only. They do not constitute financial or legal, tax, or investment advice, nor do they necessarily reflect the views of Finalis Inc. or Finalis Securities LLC, Member FINRA/SIPC. Any discussion of investments, valuations, or portfolio companies is for educational purposes only and should not be considered a recommendation or solicitation to buy or sell any security. Investors should conduct their own due diligence and consult their professional advisors before making any investment decisions.   #SiliconValleySuccesses #VentureCapital #PrivateMarkets #OpenAI #ArtificialIntelligence #AIInfrastructure #CoreWeave #TensorWave #AMD #NVIDIA #PublicMarkets #NASDAQ #StartupInvesting #Innovation

O Império da IA, com Karen HaoEm 2019 — tempos mais simples! — a jornalista Karen Hao foi fazer o primeiro “perfil” jornalístico da sua carreira, aquelas reportagens em que um jornalista passa dias acompanhando uma pessoa ou empresa, uma coisa meio biografia, meio retrato congelado no tempo.A tal empresa era uma startup do Vale do Silício, ainda pequena e desconhecida dos meros mortais como eu e você, mas que hoje é a mais valiosa da história: a OpenAI, também conhecida como “a criadora do ChatGPT”.A Karen Hao vendeu o projeto do perfil para o MIT Technology Review porque a OpenAI parecia, naquela época, uma startup diferente. O “open” no nome nasceu da visão de que inteligência artificial é um assunto tão importante para o futuro da humanidade que precisava ser explorado de um jeito aberto, compartilhando conhecimento com todo mundo, e mais preocupado em proteger esse tal futuro do que em só gerar lucro.Hoje, aqui direto de 2026, a gente já sabe que não foi exatamente isso que aconteceu. Com o tempo, a OpenAI se transformou numa empresa oficialmente voltada para o lucro como qualquer outra e chegou a ser processada por Elon Musk — um dos apoiadores iniciais do projeto — por quebrar essa promessa de ser ‘open'. Em maio, o Elno perdeu a causa, e a OpenAI agora se prepara para lançar as ações na bolsa e, pelos números atuais, já largar valendo mais de 1 trilhão de dólares.Mesmo em 2019, a Karen Hao sentiu que todo esse papo de “open” não era bem assim: segredos e competitividade em todas as conversas que ela ouvia na empresa. Publicou o tal perfil contando isso e o pessoal da OpenAI… não gostou muito. Achou que ela ia só falar bem deles, e a empresa cortou contato com ela por três anos.O Boa Noite Internet é uma publicação apoiada por pessoas como você, nosso público. Para receber novos posts e apoiar meu trabalho, considere tornar-se um assinante gratuito ou pago.Até que, em maio do ano passado, ela lançou nos EUA o livro O império da IA: Por dentro da corrida irresponsável pela dominação total, que segue contando a história da OpenAI — e abre com a bizarra saída do Sam Altman, demitido do cargo de CEO por “nem sempre falar a verdade” ao conselho da empresa, para voltar quatro dias depois nos braços dos funcionários.Mas esse livro não é exatamente uma biografia da OpenAI. Para mim, é mais um retrato de todo o sistema empresarial em que vivemos hoje — inteligência artificial ou não. O importante é que ele acabou de sair no Brasil pela Editora Rocco, que me procurou para saber se eu queria entrevistá-la aqui no programa, aproveitando que ela veio participar do Esquenta do Congresso Internacional de Jornalismo Investigativo da Associação Brasileira de Jornalismo Investigativo. O congresso, aliás, acontece dia 30 de julho — vai lá no site da Abraji saber mais, quem sabe comprar seu ingresso.Mas enfim, claro que eu queria conversar com ela. Obrigado, Abraji, obrigado, pessoal da Rocco, pelo presente. Quem me conhece sabe que IA agora é um assunto muuuito importante no meu trabalho. Eu fico aqui tentando navegar o meio do caminho entre o fim do mundo exterminador do futuro e a utopia vendida por muita gente. Não acredito em nenhum dos dois cenários, falei disso com a Karen antes e durante a conversa. Mas no final da entrevista a gente volta para falar não só disso, como também de como o IA em Curso, minha comunidade de letramento contínuo em IA, se conecta com tudo. Com promoção? Pode ser. Quem ficar até o fim, verá.A entrevista foi gravada em inglês — a Karen também fala mandarim, mas não fala brazilian —, então vai funcionar assim. Se ouvir no áudio, vai ser a versão original, do mesmo jeito que foi com o Ted Chiang ano passado, para você botar o seu cursinho para trabalhar. Aqui no site boanoiteinternet.com.br você está acompanhando a transcrição completa traduzida, se quiser ler enquanto ouve. E no YouTube tem uma versão legendada. Assim, você entra na conversa do jeito que preferir.Combinado? Então, bora lá entender O Império da IA com Karen Hao, no Boa Noite Internet.Cris: Karen Hao, bem-vinda ao Boa Noite Internet.Karen Hao: Obrigada pelo convite.Cris: Que bom ter você aqui. Espero que o Brasil esteja te tratando bem durante a Copa do Mundo — a gente veio falar sobre isso. Hoje é dia de falar de futebol, de Copa do Mundo, quais são as chances de cada país. Mas a primeira coisa que você precisa saber sobre essa conversa é que eu não sou jornalista. Não sei fazer isso. Peço desculpas antecipadas à sua profissão e ao seu ofício.Além disso, você foi enganada. Eu não estou aqui pra te entrevistar. Isso aqui é uma sessão de terapia. Você vai me ajudar a superar meus traumas.Porque eu sou da… do que eu chamo de “geração esquecida” — sou geração X, nasci nos anos 70. Esquecida porque, nessa guerra de gerações, as pessoas esquecem que a gente existe, e isso é incrível, porque a gente causou muito estrago no planeta. O Elon Musk é geração X, então é só isso que você precisa saber sobre a minha turma. Gente como ele, ou como Marc Andreessen… eu cresci lendo e assistindo à ficção científica que dizia que tecnologia é a melhor coisa do mundo, que ciência e engenheiros são incríveis e vão nos levar pra um lugar incrível.Sou uma daquelas pessoas que, quando a internet surgiu, falou: a paz mundial está logo ali. O conhecimento a um clique de distância, o futuro vai ser incrível. E aqui estamos nós. Então, quando usei o GPT pela primeira vez, e depois o ChatGPT, fiquei super empolgado. Foi a primeira vez, desde a internet, que eu fiquei realmente empolgado.Tenho até uma certa fama de ser mal-humorado com tecnologia: Bitcoin é lavagem de dinheiro, Clubhouse não presta — e as pessoas, ah, Clubhouse é a próxima grande coisa. Mas quando a IA chegou, eu falei: isso é importante. Só que eu já não era mais aquela criança dos anos 70. Tinha crescido, tinha visto o que aconteceu com a internet, tinha trabalhado numa big tech. E estava em desespero com o sistema em que a IA estava sendo construída.Dito tudo isso, o seu livro, aqui, já nas livrarias, recebe provavelmente o melhor elogio que eu posso dar: é otimista. Não é uma lista de reclamações e gente má fazendo coisas más. Claro, você fala muito sobre a OpenAI — ela é o fio condutor da história, especialmente aqueles quatro dias em que o Sam Altman saiu e voltou. E é muito divertido de ler. Mas você toma o cuidado de ser otimista.E uma das coisas que você menciona é como as pessoas na OpenAI, e em todas essas empresas, dizem: “isso é inevitável, a gente tem que fazer”. Quero falar sobre isso. Mas a gente tem que começar pela pergunta que você provavelmente ouve em todo podcast, a do título — Império da IA. Por que império?E acho que essa pergunta é ainda mais relevante no Brasil, país do sul global, colonizado. Por que império da IA?Karen Hao: Antes de mais nada, obrigada por dizer que o livro é otimista. Muita gente não reconhece isso, mas é verdade. Eu escrevo com um profundo otimismo de que os danos que a gente vê podem mudar. Não faria o trabalho que faço se não achasse que as coisas vão mudar.Sobre por que eu uso a expressão império, ou império da IA: a forma como empresas como a OpenAI operam é impressionantemente parecida com a dos impérios antigos. Eu traço quatro paralelos no livro. O primeiro é que elas reivindicam recursos que não são delas — os dados das pessoas, a propriedade intelectual de artistas, criadores como você, jornalistas.Segundo, elas exploram uma quantidade extraordinária de mão de obra. Isso vale tanto para os trabalhadores da cadeia de produção de IA, mal pagos e maltratados, que ainda assim geram uma riqueza extraordinária para essas empresas, quanto para os trabalhadores cujos empregos são automatizados e cujos direitos são corroídos pela implantação dessas tecnologias em diferentes setores.A terceira característica é que impérios controlam os fluxos de informação na sociedade. Essas empresas censuram a pesquisa fundamental sobre essas tecnologias, o que limita nossa capacidade de entender as verdadeiras limitações e capacidades dos modelos que desenvolvem. E estão criando uma tecnologia de informação que tentam transformar no portal único pelo qual qualquer pessoa se relaciona com o mundo.Esse portal impregna as ideologias do Vale do Silício, seus sistemas de valores, sua língua, e projeta a hegemonia do inglês. Isso influencia boa parte do conhecimento que a gente vai produzir daqui pra frente, porque cientistas e educadores usam essas plataformas e acabam perpetuando essas mesmas ideologias e valores.E o quarto e último paralelo é que impérios sempre se agarram a uma narrativa existencial ou moral sobre por que precisam existir. Essas empresas fazem a mesma coisa. Dizem que são o “império do bem”, numa missão civilizatória de trazer progresso e modernidade pra toda a humanidade, competindo contra um “império do mal” que ameaça mandar a humanidade pro inferno.Quando você conversa com algumas pessoas dentro dessas empresas, ou que as lideram, elas dizem: se você nos deixar construir uma inteligência artificial geral, que elas de alguma forma moldam como um deus, a gente vai acabar numa espécie de utopia, um paraíso onde a mudança climática é resolvida, o câncer é curado, a pobreza é aliviada.Mas, se os caras maus conseguirem isso antes, a gente pode acabar com todos os humanos mortos — um risco de extinção pra todos nós.Cris: E eles vêm dizendo isso há quase dez anos, e ainda usam como ferramenta. A gente está num país que foi influenciado por três impérios ao longo da história: Portugal, Inglaterra e agora os Estados Unidos. Então a gente olha pra essas empresas de um jeito meio cínico: sim, sim, já conhecemos essa história.Mas, ao mesmo tempo, ano passado, o Pew Research Center fez uma pesquisa sobre como o mundo enxerga a IA, e o sul global é bem mais otimista do que o norte. Uma das razões é a ideia de democratizar — não só informação, mas: ah, finalmente eu posso montar uma startup, sair desse lugar de exploração e criar o unicórnio de um bilhão de dólares. Os números são grandes na China. Países em desenvolvimento veem muito mais benefício do que risco na IA.China, 83%. Tailândia, 77%. Holanda, 36%. Canadá, 40%. Será que a gente está deixando passar alguma coisa? A gente está certo? Isso está democratizando mesmo? Até que ponto?Karen Hao: Provavelmente tem duas razões. Uma é que muitos dos danos que a indústria de IA causa à maioria global são bem escondidos. Ela se esforça muito pra esconder como polui o ambiente dessas comunidades, como explora e devasta a mão de obra, deixando traumas psicológicos — como documento no livro.E, recentemente, li um artigo de opinião no New York Times que trazia um bom ponto: muitas economias desenvolvidas estão especialmente atentas ao potencial da IA de desmontar oportunidades de emprego de tempo integral. A gente começa a ver isso cada vez mais. Já na maioria global, muito mais gente vive em economias informais, e aí a ideia de que a IA vai tomar um emprego de tempo integral não pesa tanto.Então os danos mais visíveis — a erosão do emprego formal de tempo integral — pesam mais no norte global, ou pelo menos é lá que as pessoas se sentem mais ansiosas. E os danos invisíveis, que atingem o sul global, ninguém percebe tanto, justamente porque são invisíveis. É meio por isso que tanta gente sente essa divisão que aparece na pesquisa do Pew.Cris: Eu tenho acompanhado as notícias sobre IA no Brasil, e toda semana tem um novo data center sendo construído em alguma cidade. Isso é vendido como uma coisa boa: que ótimo investimento, gera emprego. E me fez pensar de novo — a gente passou por três impérios, mas algumas famílias no Brasil, e aposto que em outros lugares também, estão no poder há 500 anos ao longo da história do país.Então, ao mesmo tempo, a gente pensa: é, estamos sendo explorados, é a mesma coisa. Eu já não tenho emprego, então deixa eu usar essa tecnologia pra melhorar minha vida. Mas as pessoas que realmente tomam as decisões, de novo, nos últimos 500 anos, se perguntaram: como a gente ajuda esse pessoal a explorar nosso país de um jeito que nos mantenha no poder e nos dê muito dinheiro?Mas também foi verdade que, sei lá, a Volkswagen abre uma fábrica no Brasil e aquilo gera emprego, contrata gente pro chão de fábrica e pros escritórios. Como é que isso é diferente com a IA?Karen Hao: De certa forma, não é diferente. Existe um fenômeno parecido: a indústria de IA terceiriza muitos dos trabalhos que ela não quer dentro dos centros de poder, e joga isso pra comunidades empobrecidas, do mesmo jeito que outras multinacionais fizeram por décadas.Mas também é diferente, porque a escala dos impactos trabalhistas e ambientais da IA é completamente outra, muito maior que a da indústria automobilística ou da moda. E a velocidade é outra, porque são tecnologias digitais que atravessam fronteiras muito rápido.E é diferente porque a maioria das pessoas não percebe que a IA, mesmo sendo tecnologia digital, tem uma cadeia de suprimentos muito física e intensiva em mão de obra manual.Quando você compra roupa, café, um carro, é mais óbvio que existem materiais que precisam ser extraídos e depois manuseados por pessoas pra criar aquele produto. Já com a IA, a maioria aceita a narrativa que o Vale do Silício projeta: a de que isso vem da “nuvem”, desses espaços etéreos que parecem nem existir no planeta. E a verdade é exatamente o oposto.Ela depende de uma quantidade extraordinária de extração mineral. Depende da construção de infraestruturas enormes — data centers, instalações de supercomputação espalhadas pelo mundo. E depende de muita, muita mão de obra manual: trabalhadores de dados que limpam, preparam e moderam o conteúdo dos sistemas de IA que chegam até você quando usa o ChatGPT.É isso que a torna tão diferente. E há também uma ideologia completamente diferente sustentando a expansão da IA. Quando você conversa com executivos da moda, eles não vão dizer: se você não comprar nossa roupa, vai pro inferno.Já a indústria de IA diz: se você não nos deixar capturar cada vez mais terra, mais recursos e mais mão de obra pra produzir essas tecnologias, vamos ter uma destruição civilizacional. Isso é, ao mesmo tempo, retórica política usada como arma pra moldar o debate público e a cabeça de quem formula políticas, e também está enraizado num sistema de crenças — algumas pessoas dentro dessas empresas realmente acreditam que, se uma AGI fosse construída, e construída nas mãos erradas, isso levaria mesmo a esse tipo de destruição.E é isso que move a sede cada vez maior da indústria por mais capital, mais recursos e mais terra.Cris: Eu quero falar sobre AGI, mas antes: ano passado, a OpenAI estava sendo processada no Reino Unido por violação de direitos autorais, basicamente todos os livros do mundo digitalizados e usados pra treinar modelos. E um dos executivos disse ao júri: bem, se a gente não puder fazer isso, fecha as portas. Me chocou que muita gente reagiu com um “ah, tá, o que a gente pode fazer? Eles vão fechar as portas”.Em parte porque a gente já está acostumado com essa narrativa. Outro dia, numa conferência, um ex-CEO dizia: a gente teve que usar embalagem de plástico porque é mais barata que papel, senão prejudicaria nosso resultado. E a plateia reagia: ah, então é só fechar as portas — a sociedade não pode arcar com isso.Mas isso também, como você disse, se conecta à ideia de uma grande missão, uma missão de salvar o mundo, que a gente precisa cumprir antes que seja tarde, senão estamos condenados. OpenAI está literalmente no nome — só que em português não é tão direto: é “inteligência artificial aberta”.Foi criada a partir de um sonho, um projeto que era pra ser uma coisa pro bem comum. Em 2019, num tempo bem distante, antes da pandemia, você cobriu a OpenAI, foi até o escritório deles, ficou lá dentro. O que você viu? E, mais importante, como essa missão mudou? O Elon Musk os processou outro dia justamente por mudarem a missão. Isso alguma vez foi verdade? Em algum momento eles pensaram mesmo “ah, a gente vai salvar o mundo”?Como essa narrativa de ser aberta funciona com a OpenAI?Karen Hao: Quando comecei a cobrir a OpenAI, levei a sério o que eles diziam — que tinham sido recrutados com a missão de beneficiar toda a humanidade. E aí, quando me infiltrei na empresa, fui ficando bem mais cética, porque via como eles operavam de um jeito completamente diferente, portas adentro, do que diziam em público.Diziam que iam publicar todas as pesquisas e abrir o código de tudo, e na prática eram uma das organizações mais secretas que já cobri. Eram muitas discrepâncias, e, na época, presumi que tinha havido algum tipo de corrupção que os levou a abandonar a missão original. Depois de cobrir a empresa por mais alguns anos e de trabalhar neste livro, mudei de ideia até sobre a missão original.Não acho mais que ela era um esforço sincero e generoso de beneficiar a humanidade. A missão foi criada pra dar à empresa — na época, uma organização sem fins lucrativos — uma margem de manobra extraordinária pra depois levantar muito capital, acumular muito talento e perseguir a força motriz de verdade por trás de tudo aquilo: se tornar a força dominante no desenvolvimento de IA.E penso assim agora porque, quando você olha pras narrativas de cada nova empresa de IA no começo — a Anthropic, a xAI, a Safe Superintelligence do Ilya Sutskever, a Thinking Machines Lab da Mira Murati —, todas usam a mesma narrativa da OpenAI: nós somos os mocinhos, eles são os bandidos.É por isso que precisamos criar uma nova empresa que avance a IA do nosso jeito, não do deles. E você começa a perceber, por esse padrão, que eles repetem a mesma coisa em parte porque acreditam nela até certo ponto, mas também porque ela funciona muito bem com a imprensa, com o público, com quem formula políticas.No livro, eu reproduzo os e-mails internos que Elon Musk, Sam Altman e Greg Brockman trocavam nos primeiros dias da OpenAI. Eles tinham plena consciência de que estavam criando uma missão que soasse bem para o público. E o propósito de verdade, que também deixaram registrado nesses e-mails, era vencer o Google. Viam o Google como a força dominante em IA e queriam ser eles essa força.Não gostavam de ver o Google na frente, então inventaram justificativas: o Google é uma empresa com fins lucrativos, então nós vamos ser sem fins lucrativos. Mas, no fundo, acho que era puro ego: tem que ser a gente, não eles, a gente quer ser quem lidera isso.E aí passaram um tempão moldando essa missão pública, que acabou sendo super útil pra recrutar o primeiro grupo de pesquisadores e turbinar o avanço deles.Cris: Então agora é um bom momento pra falar de AGI, a inteligência artificial geral. Muita gente pergunta: o que é AGI? O que “geral” quer dizer? E a impressão que peguei lendo seu livro é que, por design, isso nunca fica claro de verdade, porque é um alvo móvel. Essas empresas um dia vão dizer “chegamos, alcançamos a AGI”? Ou o plano é sempre “não, não, ainda não chegamos, me dá mais dinheiro, me dá mais poder”?Qual é o papel da AGI na narrativa dessas empresas?Karen Hao: Já que a gente está falando de ficção científica, eu costumo usar a analogia de que o mundo da IA é meio como Duna. Em Duna, o personagem principal, Paul Atreides, entende, ao chegar no planeta Arrakis, que o povo de lá foi semeado com um mito: o de que um dia viria um Messias pra libertá-los. Ele sabe que é um mito, mas decide entrar nele e agir como se fosse o Messias pra controlar melhor aquele povo.E, vivendo, respirando e encarnando esse mito dia após dia, ele começa a perder a noção de que é um mito. Passa a se perguntar se o mito era mesmo verdadeiro ou se foi ele quem o tornou verdadeiro. É essa confusão entre mito e realidade — ele vive num espaço intermediário, sem ter mais certeza do que é verdade e do que é ficção.E trago isso pra responder sobre a AGI porque a AGI é, ao mesmo tempo, um mito e algo que os líderes e os trabalhadores dessas empresas vivem, respiram e encarnam dia após dia, a ponto de perderem a noção do que é mito e do que é realidade. É a ideia de um sistema de IA teórico que um dia igualaria as capacidades humanas. Só que a gente nem tem consenso científico sobre o que é inteligência humana.Por isso, de certa forma, por design, é um termo bem maleável, que deixa essas empresas fazerem o que quiserem. Elas definem e redefinem a AGI conforme a necessidade, movem a trave pra onde quiserem. E, ao mesmo tempo, isso é sustentado por uma crença genuína de certas pessoas lá dentro, por causa dessa confusão entre mito e realidade. Pelas minhas contas, a OpenAI já usou pelo menos quatro definições diferentes de AGI.A primeira está no site deles: “sistemas altamente autônomos que superam humanos na maioria dos trabalhos economicamente valiosos”. É uma definição de automação do trabalho — eles dizem, de forma explícita, que estão atrás dos empregos mais bem pagos. A segunda apareceu no contrato com a Microsoft, por um tempo a maior investidora deles: ali, a AGI virou um sistema que geraria 100 bilhões de dólares em receita.Ou seja, uma definição feita pra incentivar a Microsoft a investir. Já o Sam Altman disse ao Congresso que AGI é um sistema que cura o câncer e resolve a mudança climática — uma definição de benefício social, muito útil quando você quer que os reguladores não te regulem.E, por fim, quando falam com o consumidor, dizem que vai ser o melhor assistente digital que você já teve — porque, claro, estão tentando vender o produto.E aí você percebe duas coisas. Primeiro, que é um conjunto de definições completamente incoerente. Segundo, que eles trocam de definição conforme o público que querem convencer. Mas também tem gente nessas empresas que acredita de verdade que está construindo uma tecnologia capaz de dar conta das quatro coisas.Então é uma realidade bem confusa e complicada: o que a AGI de fato é, e pra que ela serve, para essas empresas, para a agenda delas e também para as crenças delas.Cris: Como ex-funcionário da Meta — entrei em 2013 —, a missão era unir o mundo e torná-lo mais aberto e conectado. É uma missão incrível. E tem uma coisa que eu sempre digo, porque muito amigo meu vem falar comigo, “ah, esse cara da OpenAI, ou a própria Meta, são maus”. Eu conheci muita gente na empresa. Nunca conheci uma pessoa mal-intencionada.Todo mundo, independente da missão, era gente boa tentando entregar o melhor produto possível, pra dar poder a quem tem um pequeno negócio, por exemplo. Tenho amigos pessoais que construíram a empresa deles em cima da publicidade do Facebook e do Instagram. E esse é justamente o problema, porque ainda assim é uma corporação muito má, pelo que ela causa ao mundo pra bater as metas de negócio.Ou seja, você não precisa de um vilão tipo Lex Luthor pra causar um estrago desse tamanho no mundo. E adorei a referência a Duna. Duna é engraçado: é o livro que eu mais reli na vida que não foi escrito pelo Tolkien. Li o primeiro Duna umas três vezes, e toda vez é como se fosse um livro diferente. Na primeira, eu era adolescente, e era só o Paul Atreides, o cara durão.Na segunda, eu morava no Canadá e li com olhos de estrangeiro, pensando em colonização. E na terceira vez foi quando os filmes do Denis Villeneuve saíram, e aí era: ah, o Bene Gesserit criou esse mito, isso é meio pós-moderno. Narrativamente, fico me perguntando o que vai significar pra mim se eu ler uma quarta vez.Karen Hao: Eu ia te perguntar isso. Quando você disse que cresceu numa época cheia de ficção científica falando das maravilhas da tecnologia, fiquei curiosa: que histórias você estava lendo? Porque muita coisa que saiu nos anos 70 e 80 dizia exatamente o oposto. E muita gente já apontou que os executivos de tecnologia de hoje, que vivem citando essas histórias, interpretam elas justamente ao contrário da intenção original.Cris: Concordo plenamente. Mas, respondendo: foi basicamente Isaac Asimov e Arthur C. Clarke. E é por isso mesmo — os executivos de tecnologia, e o Elon Musk mais que todos, leem esses livros como receita, não como aviso. O livro de que eu mais me lembro, nem lembro o título, era um do Asimov em que ele descreve o elevador espacial que aparece na série da Apple TV, Fundação.E o enredo é: eu sou esse engenheiro brilhante, quero construir essa coisa no Sri Lanka, mas o governo trava tudo com regulação — eu sou um gênio e a regulação é a vilã. Hoje eu leio e penso: ah, sei. Mas, quando garoto, era só “olha, um elevador espacial, que genial, a gente nem precisa de foguete”. E aí você começa a entender. E aí eu parei de ler esses caras.E passei a ler gente com uma visão completamente diferente: o Ted Chiang, que entrevistei ano passado, a N.K. Jemisin, o Cory Doctorow, de quem sou muito fã. E talvez eles sejam mais explícitos, pra gente burra como eu entender: “não, bobo, a analogia é essa”. Mas Duna era incrível — vermes gigantes de areia, o tal garoto durão, e aquela coisa do “eu não aceito o meu destino”.Tenho esse grande destino, mas não quero ele. Do resto da série eu já não gosto tanto. Mas o mais importante de tudo: Duna gerou o melhor GIF de filme de todos os tempos, o “Lisan al Gaib” do Javier Bardem — que eu devia ter colocado durante a sua explicação, aquele “uau, ele está cumprindo a profecia, agindo como o profeta”.Mas, de novo, falando de vilões: você mencionou que essas empresas se colocam como o bem contra o mal, feito impérios antigos. Só que elas também jogam a carta da China, né? “Se a gente não fizer, a Rússia faz primeiro.” Só que a Rússia começou uma guerra e está ocupada demais. “Mas a China chega lá, e é por isso que a gente tem que ser fechado.” É por isso que Mythos e Fable e agora o GPT-5.6 foram proibidos pelo governo. Isso tem fundamento?Quero saber se é possível a China competir — quero mesmo essa resposta — mas também porque, desde toda essa conversa do Fable-Mythos, países como Índia e Brasil vêm dizendo que precisam de um modelo soberano. Dá pra fazer, ou a OpenAI, a Anthropic e o Google estão tão à frente que já não dá?Karen Hao: Sobre a China: você está certíssimo, o Vale do Silício usou por anos a carta do “e a China?” pra escapar de qualquer responsabilização de verdade. Fizeram muito isso na era das redes sociais.A Meta fez muito isso, com o Mark Zuckerberg dizendo ao governo dos EUA: vocês não podem nos regular, senão a gente perde. Mas, se a gente ganhar, vai ter um efeito liberalizante no mundo e nas democracias em todo lugar. E, infelizmente, o que a gente viu foi que jogar essa carta repetidamente produziu exatamente o efeito contrário do que o Vale do Silício prometeu.Uma das empresas de rede social dominantes dessa era é a ByteDance. Ou seja, mesmo sem regulação das redes sociais nos EUA, existe uma empresa chinesa de rede social bem dominante. E as redes sociais estadunidenses acabaram tendo um efeito antiliberal no mundo — é bastante consensual que enfraqueceram democracias em todo lugar. E aí, na era da IA, elas seguiram jogando a mesma carta.Mas o que eu sempre aponto é que a gente definitivamente não devia acreditar nelas. Já existe evidência significativa de que tudo o que elas dizem está, de novo, se provando o oposto. Elas disseram: não regulem a gente como empresas de IA, regulem a China, via controles de exportação — um mecanismo do governo dos EUA com alcance extraterritorial.Só que as empresas chinesas agora estão produzindo modelos de IA de código aberto extremamente eficientes, que viraram super populares no próprio Vale do Silício. Existe um monte de startup de lá que prefere usar modelo chinês a OpenAI, Anthropic ou Google.Então, nesse sentido, é um conjunto de evidências bem decisivo, acho, pra mostrar que a gente devia simplesmente responsabilizar essas empresas, não importa o que digam sobre “ah, vamos perder pra China”. No fim das contas, é só retórica política. Não é um argumento real que elas consigam sustentar pra escapar da responsabilização.Responsabilizá-las vai fortalecer a democracia pelo mundo, vai trazer mais direitos humanos, trabalhistas e de privacidade de dados pras pessoas — é sempre o contrário do que elas dizem que aconteceria. E, sobre a sua pergunta em torno da IA soberana: acho a ideia realmente importante, mas acho também que muitos países estão meio confusos sobre o que querem dizer com isso.Muitos governos, hoje, pensam a IA soberana pela pergunta: a gente consegue construir o nosso próprio ChatGPT? O nosso próprio grande modelo de linguagem, o nosso sistema de IA generativa? Estão olhando só pro modelo que o Vale do Silício já definiu e tentando descobrir como recriar aquilo.E o que eu digo pra quem formula políticas é: defina pra que a IA serve no seu país, no seu contexto. Quais são, no fim das contas, os objetivos do seu país? Os objetivos do seu povo? E também os nossos objetivos coletivos, entre países?Porque a gente tem, por exemplo, os Objetivos de Desenvolvimento Sustentável da ONU. Já definimos coletivamente que há coisas que precisamos resolver juntos: superar a crise climática, reduzir a pobreza, melhorar a educação.E, enquanto o Vale do Silício adora dizer que está fazendo tudo isso, na prática não está. Mas a gente poderia — poderia desenvolver, de forma colaborativa, sistemas de IA que realmente avançassem em cada um desses objetivos coletivos que já acordamos.E cada país também devia fazer o exercício: quais objetivos você quer alcançar, e que tipos de sistema de IA você poderia desenhar pra chegar lá — sistemas que talvez não se pareçam em nada com um grande modelo de linguagem. Se os países fizessem isso, acho que descobririam que a maioria dos sistemas de que precisam exigiria muito menos recursos.Ou seja, contextos como o Brasil, a Índia e outros, quando não precisam competir construindo essas infraestruturas de computação gigantescas e gastando centenas de bilhões de dólares, na verdade já têm, localmente, todos os recursos necessários pra desenvolver um sistema de IA soberano.Cris: Quando ouvi falar do seu livro pela primeira vez, uma amiga me disse que você não poupa ninguém — fala mal do Sam Altman, mas também do Dario Amodei. E as pessoas costumam escolher um lado. Eu sou time Claude, odeio o ChatGPT, essas coisas. Então cheguei no livro pensando: ah, é mais um livro dizendo que a IA é terrível, que a gente não devia usar IA.Mas, conforme fui lendo, e ouvindo outras entrevistas suas, me pareceu que o seu problema é justamente o que você acabou de descrever: a forma como essa tecnologia é feita. E, em especial, a palavra escala — a ideia de que a solução é a escala. O que você quer dizer com isso?Karen Hao: Eu costumo usar a analogia de que “IA” é como a palavra “transporte”: na verdade se refere a uma coleção de tecnologias que vão da bicicleta ao foguete. São tipos bem, bem diferentes de tecnologia, que exigem insumos diferentes pra se desenvolver e depois têm impactos diferentes na sociedade.E você está certo: sou especificamente crítica ao que chamo de “foguetes da IA”, os sistemas que os impérios da IA estão desenvolvendo, aqueles que exigem uma quantidade enorme de exploração de mão de obra e extração ambiental.E sou bem otimista com o que chamo de “bicicletas da IA”: sistemas especializados, eficientes, com bom custo-benefício, governáveis pelas pessoas, cujo desenvolvimento pode ser participativo. Países como o Brasil, o Chile, a Índia, qualquer contexto, têm recursos pra desenvolver e se autodefinir, em vez de simplesmente herdar um sistema criado pelos dois únicos centros do mundo capazes de gastar uma quantidade extraordinária de capital: o Vale do Silício e o ecossistema tecnológico chinês.E o motivo pelo qual eu acho tão corrosivo o que os impérios da IA estão desenvolvendo é exatamente o que você disse: a forma como eles fazem isso, por um mecanismo de força bruta pra avançar as capacidades da IA em escala. Eles vão simplesmente empurrando cada vez mais dados de treinamento nesses modelos, e isso exige corroer a privacidade das pessoas, tomar a propriedade intelectual delas e, ainda por cima, baixa a qualidade dos dados que entram nos modelos — o que leva aos danos de exploração de mão de obra, porque aí você tem que dar conta da moderação de conteúdo.E aí você tem pessoas psicologicamente traumatizadas por serem expostas a todo aquele conteúdo horrível que se tenta “lavar” através desses modelos.E aí vem o problema dessas infraestruturas de computação enormes, com impactos ambientais que aumentam a conta de luz das comunidades que as hospedam e agravam a crise de custo de vida. Elas precisam ser alimentadas por fontes fósseis, que jogam mais carbono na atmosfera e mais poluição no ar dessas comunidades.Então todos os problemas que eu identifico, no que têm de corrosivo, derivam inteiramente da abordagem deles pro desenvolvimento de IA. Por que não descartar a abordagem, em vez de descartar a tecnologia? Redefinir e redesenhar de que tipos de sistema de IA a gente precisa de verdade, com uma cadeia de suprimentos fundamentalmente diferente. E isso não é exclusivo da IA.A gente já viu muitas outras indústrias que começaram com uma cadeia de suprimentos bem ruim. A moda, por exemplo: muita degradação ambiental, muita exploração de mão de obra.Com muita organização, protesto, ação de consumidores, regulação governamental e cooperação entre governos, a gente conseguiu criar mercados novos pra moda sustentável e ética, cadeias de suprimentos novas e inovações pra fazer roupa mais saudável pras pessoas e pro planeta.E é basicamente isso que eu defendo: transformar a indústria de IA do mesmo jeito que transformamos a moda, e as cadeias de suprimento de alimentos. Assim a gente fica com os benefícios da tecnologia, ajuda ela a avançar os objetivos que importam pra gente, sem jogar uma fração enorme da população mundial numa condição atrasada e numa qualidade de vida pior.Cris: O Brasil está agora, no Congresso, discutindo a escala de seis dias por semana. A regra atual é: você trabalha seis dias e descansa um. E muitas empresas, o comércio principalmente, dizem “vamos fechar as portas”, e os trabalhadores respondem “isso é problema seu, não meu”. É mais ou menos a mesma narrativa dessas empresas de IA: se eu não usar a sua água, a Idade das Trevas está chegando.Falando em Idade das Trevas, e falando em bicicleta: a sua analogia me lembrou uma coisa. Eu gosto de jogo de zumbi, de mundo aberto, e em nenhum deles tem bicicleta. Num desses jogos, instalei um plugin que deixava andar de bicicleta — você acha uma e sai pedalando. E aí entendi por que não tem bicicleta: desbalanceia tudo. Parte da graça do jogo é você precisar achar um carro, e daí pneu, gasolina, comida pra carregar. De bicicleta, você vai a qualquer lugar.E eu pensei: ah, é. Meio que estraguei o jogo pra mim, porque agora tenho uma bicicleta, é incrível. Enfim, em termos práticos: no fim do ano passado, uns meses atrás, a revista Wired publicou um artigo pedindo pra jornalistas de tecnologia contarem como usam IA no trabalho. E cada um usava de um jeito. Você usa IA no seu trabalho? Como?Karen Hao: Eu não uso nenhum sistema de IA generativa no trabalho — nem ChatGPT, nem Gemini, nem Claude. Por três motivos. O primeiro é uma postura ética, depois de tanto investigar essas empresas. O segundo é privacidade de dados: eu investigo essas empresas.Não quero que elas conheçam todo o meu raciocínio enquanto eu apuro o livro, literalmente investigando elas. E o terceiro é que, no meu caso específico, a força do meu trabalho está na capacidade de construir relações fortes com as fontes, pela empatia, e de contar histórias envolventes, pela narrativa. E os grandes modelos de linguagem simplesmente não são a ferramenta certa pra nenhuma das duas coisas.Não vão melhorar a minha empatia nem a minha escrita. Então eu não perco nada com essa postura ética: simplesmente corto essas ferramentas e sigo fazendo o meu trabalho muito bem. Pra outros jornalistas pode ser diferente, e pra quem está em outras áreas o cálculo pode ser outro.Mas eu incentivo as pessoas a pensarem primeiro: quais são as suas forças no trabalho? Quais são os seus objetivos? E aí ir de trás pra frente pra descobrir se a IA é a ferramenta certa, qual tipo de IA é a ferramenta certa, e qual fornecedor você quer de fato usar, apoiar, votar com os pés. Agora, eu uso, sim, IA preditiva.Aquelas ferramentas de IA especializadas, as “bicicletas da IA”, digamos. No livro, tinha um detalhe que eu queria muito ilustrar: como a OpenAI deu um salto quando passou de organização sem fins lucrativos a um empreendimento bancado pela Microsoft. Percebi que as cadeiras do escritório ficaram bem mais caras. Então fotografei as cadeiras de um escritório e as do outro.E joguei tudo na busca reversa de imagens do Google, que é um sistema de IA especializado — não é baseado em grandes modelos de linguagem, não é IA generativa. Assim descobri quanto essas cadeiras costumam custar. No primeiro escritório, cerca de 2 mil dólares por cadeira. No segundo, eram cadeiras de um designer brasileiro famoso, uns 10 mil dólares cada.Coloquei esse detalhe no livro pra ilustrar o tipo de riqueza e de concentração de recursos de que a gente está falando. Esses são alguns dos jeitos como eu uso IA, ainda que de forma bem limitada, sempre pontual, quando acho que vai ajudar. E, claro, uso ferramentas de transcrição por IA — outra IA especializada — em todas as minhas entrevistas.Cris: Essa foi uma das partes em que a minha cabeça explodiu, eu nunca tinha percebido: a OpenAI criou o Whisper. Deixa eu dizer de outro jeito, do meu ponto de vista. A OpenAI liberou abertamente essa ferramenta incrível de transcrição, o Whisper, em que eu jogo o áudio e ela me devolve as palavras que as pessoas disseram. E eu pensei: ah, que generoso da parte deles.Mas o motivo real de terem criado a ferramenta foi pegar todos os vídeos do YouTube, transcrever e alimentar a máquina. E aí é: ah, claro. Enfim, falando de ferramentas e de otimismo — a gente está chegando ao fim da conversa. Eu tenho uma regra desde o episódio dois deste programa, há oito anos: de novo, como eu disse do seu livro, não pode ser só uma lista de reclamações e coisa ruim. E a gente tem se saído bem até aqui.Você falou de caminhos e de bicicletas, mas eu quero ser mais específico. Se isso aqui fosse uma reunião de negócios: qual é o plano de ação, quais são os próximos passos? Só que uma das coisas que eu repito bastante, na vida e neste programa, é que problema sistêmico não se resolve com ação individual. Se eu tomar banhos mais curtos, isso nunca vai salvar o planeta do aquecimento global.E muitos amigos meus simplesmente: não quero falar de IA, não quero usar IA. Voltando aos videogames: leram que tal jogo usa IA e pronto, não vão jogar. E a minha primeira pergunta pra você é: como a gente ocupa esses espaços da IA generativa — ChatGPT, Gemini e por aí vai? Porque o que a gente viu com as redes sociais foi: ah, o Facebook é do mal, vou sair do Facebook. Ah, vou sair do Twitter.E, na esperança de quê, sei lá, talvez alguém diga: ah, sinto falta do Cris, cadê ele? Ah, está no Bluesky. Mas isso deixa o espaço aberto pra os radicais entrarem e postarem o que quiserem, sem ninguém contrapor ou tornar aquilo um lugar melhor. Então como a gente ocupa o espaço da IA — seja qual for a definição de “espaço da IA” que você preferir — com todos esses problemas que a gente vem discutindo?Karen Hao: Acho que tem duas categorias de ação pra gente pensar. Uma é desmantelar o império. A outra é investir e construir novos tipos de sistema de IA, que se tornem alternativas às tecnologias do império. Quando eu digo desmantelar o império, não estou dizendo que quero que a OpenAI, o Google, a Anthropic, seja quem for, simplesmente deixem de existir.É que eu não quero que elas sejam imperiais. Não quero que fiquem extraindo uma quantidade extraordinária de valor sem redistribuir nada em troca. Se elas voltassem a ser negócios que praticam uma troca justa de valor com o mundo, eu ficaria perfeitamente feliz com qualquer tecnologia que estivessem desenvolvendo.E a forma de desmantelar o império, acho, se resume a muita organização de base, que vai pressionar os governos a regular e responsabilizar essa indústria. No último ano, a gente viu uma quantidade incrível dessa organização de base florescendo pelo mundo.Recentemente, lancei com um grupo de jornalistas, pesquisadores de IA e acadêmicos críticos um projeto chamado AI Resist List, que busca documentar parte dessa organização de base pelo mundo. A gente encontrou cerca de 30 exemplos, de todas as regiões, de ações individuais, institucionais e movidas pela comunidade.Tinha ação artística, ação política. E isso mostra bem o seu ponto: não dá pra contar só com a ação individual, mas o indivíduo pode, sim, ter impacto. Até uma ação pequena pode gerar um grande efeito cascata. Claro que se juntar com os vizinhos pra protestar contra o data center é ainda mais eficaz. Se juntar dentro da sua escola ou universidade pra protestar contra a parceria dela com uma empresa de IA também é mais eficaz.Se juntar com os colegas de trabalho de um setor pra barrar a adoção de uma IA que corrói os direitos trabalhistas é mais um jeito eficaz. A gente tem um monte desses exemplos. Um dos meus favoritos é o de uma comunidade sobre a qual escrevi no livro, Quilicura, no Chile, na periferia de Santiago. É uma comunidade da classe trabalhadora, bem pobre, que vem sendo alvo incessante da expansão de data centers.E por isso protestaram de forma bem aguerrida contra essa expansão, porque não acharam bom negócio hospedar essas instalações sem tirar nenhum benefício, enquanto elas consomem uma parte significativa dos recursos naturais da região.E, logo depois que escrevi sobre eles, foram além na resistência e criaram uma plataforma chamada Quili.ai. É um site em que você entra e que parece um chatbot, parece o ChatGPT: tem uma interface de chat pra você digitar. Só que, quando você faz uma pergunta, em vez de um modelo de IA responder, a mensagem é encaminhada pra alguém que mora em Quilicura, no Chile. Aí, se você pede “quero a imagem de um cachorro”, aquilo vai pro artista local deles, o Benji. Ele pega um pedaço de papel, desenha um cachorro, tira uma foto e te manda de volta.Eles fizeram isso essencialmente como um projeto de arte performática, pra fazer as pessoas pensarem duas vezes antes de usar IA generativa pra bobagem. A mensagem era: ei, quando você fica brincando com essas ferramentas em pedido besta, isso afeta comunidades como a nossa, drena os recursos de que a gente precisa pra viver bem.E também queriam levar as pessoas a pensar: por que não perguntar pra alguém da sua própria comunidade aquela receita que você procurava, ou pedir aquela imagem? Porque aí você reconstrói as conexões que estão tão em falta na sociedade — a falta delas é o que nos deixa mais vulneráveis a esse tipo de colonização do império.Eles deixaram o projeto aberto por 24 horas, e qualquer pessoa no mundo podia mandar um pedido. Receberam uma quantidade extraordinária deles. Viralizou de vez. E essa cidadezinha conseguiu uma virada enorme de narrativa sobre a suposta inevitabilidade e necessidade dessa tecnologia, sobre tudo o que o Vale do Silício diz — que, se você não usar, vai ficar pra trás de quem usa.E esse é só um exemplo, entre muitos, de como pessoas comuns, não importa a sua posição na sociedade, podem ter impacto real no debate, na consciência pública e até na regulação. A gente está vendo isso agora com os protestos contra data centers. Nos EUA, em 2025, cerca de 150 bilhões de dólares em projetos de data center foram travados.Isso virou uma das questões políticas mais quentes nos EUA para as próximas eleições de meio de mandato. Tem gente eleita sendo literalmente tirada do cargo por ter aprovado data centers, contrariando a vontade do povo. E isso já está tendo efeito real sobre as empresas e sobre a trajetória do desenvolvimento de IA.A OpenAI teve que encerrar recentemente a sua ferramenta de geração de vídeo, o Sora. Quando lançaram, apresentaram como o segundo produto mais importante desde o ChatGPT. O que aconteceu entre o lançamento e o fim? Uma reportagem do Wall Street Journal apontou três motivos, todos moldados por ação de base. Um: um gargalo enorme de capacidade de computação.Muitos dos data centers travados ou parados eram da OpenAI. Dois: um cenário financeiro bem mais incerto. A OpenAI está se preparando pro IPO, o que significa ficar mais exposta a Wall Street — e Wall Street está cada vez mais nervoso com a capacidade dessas empresas de cumprir o que prometem.E aí a OpenAI teve que reforçar alguns projetos paralelos pra fazer o balanço parecer um pouco melhor aos olhos de Wall Street. E, terceiro: os consumidores simplesmente não estavam usando o produto — o que também é ação coletiva de consumidores. Então, por todo esse tipo de resistência, de várias formas, de baixo pra cima, as pessoas estão de fato tendo impacto real na indústria e responsabilizando ela.Essa é a primeira categoria de ação. A segunda é: ok, que tecnologias de IA a gente usaria como alternativa? E aí a gente precisa investir mais nelas. Muitas vezes, quando converso sobre o livro, a pessoa diz: ok, me convenci de que não quero usar ChatGPT, não quero usar Claude — mas então uso o quê no lugar?E o problema é que eu não tenho muitas respostas pra essa lista de alternativas. Tem umas poucas aqui e ali, uma plataforma, uma empresa.Cris: Dá pra rodar o modelo no seu próprio computador, como o Cory Doctorow faz, mas aí é limitado e…Karen Hao: Exatamente, exige mais habilidade técnica. Mas, pra quem consegue instalar modelos de código aberto no próprio computador, eu incentivo 100%. Só que a gente também precisa de mais gente desenvolvendo interfaces bem fáceis pra esses modelos de código aberto, pra que qualquer pessoa consiga usar.A gente também precisa de mais gente desenvolvendo “bicicletas da IA”, de investidores e governos investindo mais nesse tipo de solução, e de talento — pesquisadores de IA, desenvolvedores e outras pessoas dispostas a sacrificar um pouco e abrir mão dos pacotes de remuneração enormes.Cris: Eu estava começando a achar que agora as empresas precisam ter menos lucro — e isso nunca vai acontecer.Karen Hao: Não, não é a empresa ter menos lucro. É o trabalhador topar abrir mão do pacote de milhões de dólares pra levar o talento dele pra outro lugar. Mais fácil, bem mais fácil. Eu converso com muito pesquisador de IA cansado da abordagem da indústria, porque ela é completamente sem criatividade intelectual.Eu conversei com pesquisadores que não passaram seis anos num doutorado em IA só pra ficar empurrando mais dados na máquina — pra eles, é o trabalho mais chato do mundo. E depois automatizar a programação, que era justamente o que eles gostavam de fazer. Converso com tanta gente que já não acha graça nenhuma nisso. Estão meio presos por “algemas de ouro”.E estão tentando descobrir, dentro de si, que carreira alternativa poderiam ter. Eu costumo incentivar esses pesquisadores a gastar o talento deles construindo um tipo diferente de empresa, que trabalhe com “bicicletas da IA”. E a gente já começa a ver cada vez mais desse talento indo por aí.E a gente precisa que todas as facetas da sociedade invistam num ecossistema muito mais robusto e rico de tecnologias de IA, capaz de substituir as que hoje dominam. Eu ainda tenho as cicatrizes das minhas próprias “algemas de ouro”, mas concordo plenamente.Cris: E as redes sociais são o exemplo — veja o que aconteceu com elas. Tem aquela frase famosa: as mentes mais brilhantes da minha geração passam o tempo fazendo as pessoas clicarem em anúncios. E ainda dizem: ah, isso pode ser o futuro. Pois é.Você contou a história do Quili.ai e isso me lembrou um dos primeiros criadores de conteúdo do Brasil, o Cid Não Salvo. Uns 10, 15 anos atrás, ele tuitou o seguinte: “Gente, eu disse pro meu pai que, sempre que ele precisar pesquisar alguma coisa na internet, é pra ir no Twitter.com e digitar a pergunta na caixa”. E olha que ele tinha milhões de seguidores.E, por uns bons dias, quase um mês, você entrava no Twitter do pai dele e via perguntas tipo “onde eu compro pizza?”. Era engraçadíssimo. No fim, ele contou pro pai — ou talvez não. Mas eu adoro essa ideia. Antes de a gente terminar: você já deve ter respondido isso mil vezes, mas vai continuar cobrindo IA? O que está na sua cabeça, o que vem por aí? Turnê mundial? O que vem pela frente?Karen Hao: Com certeza estou pensando em como continuar responsabilizando essas empresas. Estou envolvida em várias colaborações, com gente incrível, em diferentes projetos ligados a isso. O AI Resist List foi um deles. Também co-criei um programa chamado AI Spotlight Series, com o Pulitzer Center, uma organização jornalística sem fins lucrativos que financia jornalismo investigativo pelo mundo.É um programa que treina jornalistas do mundo inteiro a cobrir IA por uma lente de responsabilização. Até agora, já treinamos mais de 3 mil. E eu sigo pensando em como construir mais capacidade dentro do jornalismo, da sociedade civil, de outros contextos, pra mobilizar ainda mais essa organização de base — pra conter de verdade os impérios da IA e ajudar a desmantelá-los.Cris: Adorei o seu exemplo da moda. É possível, já foi feito. Ou até a indústria automotiva. Ou o grande exemplo que a gente não mencionou, e que o pessoal da OpenAI vive citando: o Projeto Manhattan, a energia nuclear.O mundo não acabou. Quando eu era criança lendo Asimov, achava que ia tudo acabar num fogo nuclear. Enfim — alguma última palavra, alguma mensagem, algum palpite pros jogos do Brasil na Copa, alguma coisa que você queira dizer antes da gente encerrar?Karen Hao: No fim das contas, o que eu espero que fique desta conversa e do livro é o seguinte: neste momento, o Vale do Silício está concebendo a IA como um projeto político. E a característica central desse projeto é tirar a autonomia de todo mundo — a autonomia de moldar de verdade o próprio futuro e o nosso futuro coletivo. Mas, no instante em que você reconhece que já tem uma autonomia significativa pra resistir, o império começa a desmoronar.Então espero que as pessoas encontrem a própria voz, a afirmem, conquistem o seu lugar à mesa e se conectem com os vizinhos, com a comunidade, com os colegas de trabalho, pra criar mais movimentos juntos.Cris: Que ótimo. Karen Hao, o seu livro é O Império da IA: Por dentro da corrida irresponsável pela dominação total. Obrigado por vir ao Brasil conversar com a gente. Foi um prazer.Karen Hao: Muito obrigada.Uma das primeiras perguntas que anotei quando comecei a pensar nessa conversa foi justamente a do final, a da ocupação de espaços. Porque, como eu disse, quando as redes sociais chegaram para ficar, muita gente falou “ah, não vou usar, é do mal” — e aí as pessoas ruins, vamos chamar assim, acabam ocupando esse espaço e falando o que bem entendem. A gente precisa aprender essa lição agora, no mundo da IA.Fora que vejo muita gente falando de IA sem nunca ter usado — ou que usou, sei lá, dois anos atrás, acha que continua tudo igual e já diz que não quer chegar perto.E por quê? Porque essa abordagem de ocupar espaços é o que eu e a Ana Freitas buscamos fazer no IA em Curso, nossa comunidade de letramento contínuo em IA. Foi, aliás, uma conversa que tive com a Karen antes da entrevista: ao mesmo tempo que a gente fala do impacto da IA no mundo, também precisa focar no que é prático, no que dá para fazer hoje com IA, sem vender sonho nem desastre. A analogia que usei foi a de que é que nem quando a gente fazia curso de Word e Excel — é o que eu faço agora que vai facilitar minha vida, me fazer ganhar tempo, botar a IA para me ajudar. Quem viu minha conversa com a Ana aqui no Boa Noite Internet, no fim de 2025, sabe do que estou falando. Se não viu, volta lá e confere.Desde que a gente lançou este episódio, o IA em Curso já passou de 400 pessoas. Tem muita gente colocando projetos pessoais incríveis na rua, tirando do papel aquela ideia que rondava a cabeça há um tempão. E a comunidade tem mentoria ao vivo, aula gravada, newsletter, banco de agentes, grupo de Telegram… que mais? O que não falta é jeito de passar para você o conhecimento sobre IA de que você precisa hoje, agora. Quero te dar a bússola para navegar nesse universo.Se esse é o tipo de abordagem que você quer ter com a IA, passa lá no iaemcurso.com.br e usa o cupom BNI2026 para ganhar 20% de desconto no plano anual. Mas corre, porque daqui a duas semanas vou apagar esse cupom — não é todo dia que a gente dá um desconto desses.É isso. Boa Noite Internet, temporada 2026 começando — como todo ano, com mudança, ideia, projeto. Ou, como diz minha citação preferida de todos os tempos: “vivemos uma fase de transição, como sempre”. Espero ver você por aqui e lá no IA em Curso.Obrigado pelo seu tempo e pela sua atenção. Até o próximo episódio. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit boanoiteinternet.com.br/subscribe

In 1776 — that same year America declared its independence — Adam Smith published the equally revolutionary The Wealth of Nations, his founding explanation of national economic value. Two hundred and fifty years later, Tim O'Reilly argues in the free-market Economist that Elon Musk and his fellow tech barons are building a monarchical form of capitalism that the proto-democratic Smith would have hated. Musk, O'Reilly reports, believes that SpaceX will become “worth more than the rest of Earth”. The merchants are becoming princes, O'Reilly warns. And the rest of us are becoming peasants. Such is the road to serfdom in our AI age. So who should own the AI in our bewildering age of multi-trillion dollar start-ups like SpaceX, Anthropic and OpenAI? Or as That Was The Week publisher Keith Teare asks in his latest editorial, who should own the “intelligence” of our AI age? Keith uses a bottling plant as a metaphor to describe our dilemma. Since no single entity can own this intelligence — the sum total of our common experience — charging us for it would be like seizing the Earth's water supply and selling it back to us, Coca-Cola style, in plastic bottles. Except that the Hayekian Keith approves of the bottling process. Private companies, rather than governments, he argues, are most suited to doing this. For Keith, this dilemma is also an opportunity to redistribute the ownership of intelligence. He argues for a “Human Wealth Fund” into which every consequential AI company should put a slice of its equity. In the manner of Norway's sovereign wealth fund, this fund would be distributed to all citizens. Rather than Denmark, now we should become like Norway, a tiny homogenous nation with a cultural distaste for Muskian individual wealth. Not very realistic, I fear. On top of that, it's hard to imagine our tech princes collaborating on anything. Musk and Altman aren't on speaking terms while Altman and Amodei, who also loathe each other, are focused on their IPOs. Meanwhile, the Trump administration, which presumably would coordinate this fund, is pitching a $100,000-a-month fast feed of the president's posts. Keith's question, “who owns the intelligence”, is the right one. But the answer won't come from trickle-down funds set-up by our tech princes. Such supposed munificence is about as likely as America becoming Norway. Read the fine print of any “Human Wealth Fund” set up by Sam Altman and Elon Musk. As we should know all too well by now, when a “revolutionary” Silicon Valley gives stuff away, it turns out to be exorbitantly expensive. Free plastic bottles of intelligence, anyone? Five Takeaways •       Intelligence, Not AI. The week's framing shift: the word AI is too small, because AI is merely the tool for harvesting and delivering the thing itself — intelligence, the sum total of our common human experience. Keith argues the renaming is not semantic but political: the moment intelligence sits at the center of the discussion, everyone's opinion has to be shaped by what it actually is, and the idea that any single entity could own it starts to look as bizarre as owning the world's water supply. Andrew's rejoinder: they're still just words — though he concedes intelligence is the better one. •       Bottled Intelligence Is Good — The Question Is Who Benefits. Keith refuses the critic's role: bottling intelligence, like Google's bottling of the world's words into search, is a good thing, because only massively capitalized private companies can innovate at that scale — and between private entities and governments as owners of intelligence, he'll take the companies every time. What's wrong is the distribution of the benefits. Even insiders are complaining: Alex Karp is publicly angry at OpenAI and Anthropic's pricing, while China's Kimi K3 — released the day of recording and, Keith claims, better than Claude Fable — signals that very good models are about to get very cheap. •       Capitalism Adam Smith Would Hate. Tim O'Reilly argues in The Economist that Musk and his type are building a capitalism Smith would despise — founders as monarchs, a point Henry Farrell reinforces with a slide from Peter Thiel's startup class placing the king of a monarchy and the founder of a startup side by side. Keith's response is characteristically unsentimental: Smith would have hated everything since the Federal Reserve, and the founder-king structure — Larry and Sergey's voting shares, Zuckerberg's special rights, corporations bigger than countries with user bases bigger than China — is simply the stage of capitalism we're at. The question is whether there's a path from here to somewhere better. •       The Human Wealth Fund. Keith's path comes in two versions: government-down, a sovereign wealth fund holding AI equity for every citizen; or company-up, the AI companies voluntarily endowing a global fund — and it only takes one to move first, because everyone else would have to react. His proxy is Norway, where every citizen benefits from ownership — not payouts, ownership — in the oil fund; AI revenues, unlike Norwegian oil, could eventually drive most of a doubled global GDP. His critique of the Brynjolfsson economists' much-signed statement is that “must act now” is vacuous: he'd have added a point four naming the actual mechanism. •       The Bet. Andrew's counter-case: Musk and Altman loathe each other, the mob hates AI so thoroughly that no pro-AI politician can survive, the states from Newsom's California to Florida are embracing nothing, New York just enacted the first data center moratorium, and the founders — eyes on their IPOs — are in the pockets of the banks. Hence the wager: 5% of the Teare Wealth Fund says no Human Wealth Fund this year, and none in the twenties. Keith declined the bet, on principle: he's an advocate, and only through advocacy does public opinion change. As Andrew put it: keep fighting the good fight — maybe one of the crazy ideas will stick. About the Guest Keith Teare is the founder and editor of the That Was The Week tech newsletter, and Andrew's weekly co-host. A British-born Silicon Valley entrepreneur and investor, he was a co-founder of TechCrunch and runs the Palo Alto–based venture firm SignalRank. He and Andrew have been arguing about technology — productively — every week for years. References: •       That Was The Week — Keith's newsletter; this week's editorial argues that the word AI is too small, and that the central question of the age is who owns intelligence. •       Tim O'Reilly in The Economist — on Elon Musk building a form of capitalism that Adam Smith would hate, quoting Musk's claim that SpaceX will become worth more than the rest of the Earth. •       Henry Farrell — the big tech critic's companion piece, featuring the slide from Peter Thiel's startup class that plac...

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

Apex Fintech Solutions provides the tools and services that enable hundreds of clients to launch, scale, and support digital investing for tens of millions of end investors. The company provides essential infrastructure and a comprehensive ecosystem of cloud-based products to enable and streamline trading, wealth management, cost basis, tax reporting, and, through its subsidiary Apex Clearing™, custody and clearing. LEARN MORE: https://apexfintechsolutions.com/?utm_source=Risk+Reversal&utm_medium=Podcast&utm_campaign=701PJ00000fnXhaYAE Dan and Guy speak with legendary short seller Jim Chanos about extreme market dispersion beneath an S&P near all-time highs, rising retail speculation, and a new wave of IPOs, secondaries, and insider selling. Chanos explains his hedged 40-stock model portfolio and argues the AI build-out is driving a torrent of equity and debt financing, often off balance sheet, into long-lived assets with uncertain economics. He warns that long-term projects are being justified by spot pricing, while “construction in progress” accounting and depreciation timing defer costs, inflating earnings and masking obsolescence. He compares today to—and “worse” than—the late-1990s infrastructure boom, highlights falling incremental returns on hyperscaler invested capital, notes shifting neo-cloud business models toward “asset light,” and says bull markets price promises while ignoring financial reality. —FOLLOW USYouTube: @RiskReversalMediaInstagram: @riskreversalmediaTwitter: @RiskReversalLinkedIn: RiskReversal Media The financial opinions expressed in Risk Reversal content are for information purposes only. The opinions expressed by the hosts and participants are not an attempt to influence specific trading behavior, investments, or strategies. Past performance does not necessarily predict future outcomes. No specific results or profits are assured when relying on Risk Reversal. Before making any investment or trade, evaluate its suitability for your circumstances and consider consulting your own financial or investment advisor. The financial products discussed in Risk Reversal carry a high level of risk and may not be appropriate for many investors. If you have uncertainties, it's advisable to seek professional advice. Remember that trading involves a risk to your capital, so only invest money that you can afford to lose. Derivatives are not suitable for all investors and involve the risk of losing more than the amount originally deposited and any profit you might have made. This communication is not a recommendation or offer to buy, sell or retain any specific investment or service.

Big tech selling off to wrap up the week as names like Microsoft, Google and Meta aggressively ramp up AI spending. The traders break down how to trade these tech giants, and if massive AI buildouts will eventually lead to growth. Then, will market volatility persist? Citi Wealth's head of portfolio strategy J.P. Coviello lays out where he sees opportunity in a time of high volatility and geopolitical uncertainty. Plus, why selling Tesla could be the move, Netflix crumbling after a disappointing second quarter, and why the biggest IPO in history is on a six day losing streak. Fast Money Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Tech stocks come under renewed pressure as the Nasdaq heads for its first weekly loss in three weeks. On today's Squawk on the Street, Apollo Chief Economist Torsten Slok explains how much of the economy's outlook now depends on the AI trade. Plus, Netflix tumbles after disappointing guidance, but one Wall Street analyst says the selloff is a buying opportunity. And with SpaceX trading below its $135 IPO price, we examine what the options market is signaling about where the stock could go next.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Wrapping up a volatile week for stocks, Carl Quintanilla, Sara Eisen and Michael Santoli delved into the chip sector extending its global sell-off on AI jitters. The anchors reacted to Netflix shares tumbling on current quarter guidance that indicated slower growth. TD Cowen analyst John Rutledge joined the Netflix conversation. Apple gets an analyst upgrade and surpasses Nvidia to reclaim the title of the world's most valuable company. Also in focus: Shares of SpaceX slide further below their $135 IPO price after an aborted Starship launch, Micron falls out of the trillion-dollar market cap club, PayPal M&A watch, LeBron James speaks about Nike's challenges, oil rallies on U.S.-Iran tensions, President Xi's AI game plan for China.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Story of the Week (DR):‘We faltered': IBM stock collapses after a grave warning about AI Customers are Prioritizing AI Hardware: While IBM mostly sells software nowadays, businesses are currently cutting back on their software budgets. Instead, they are rushing to spend their money on physical computer parts (like chips and servers) needed to build new Artificial Intelligence systems.Board skills/tenureFormer Intel CEO says the chipmaker went off the rails ‘when it started to be run by business people'The inside story of IBM's shocking profit warningXbox CEO Joins Fed AI Jobs Task Force Days After Announcing 3,200 LayoffsXbox CEO Asha Sharma, who previously worked in Microsoft's Core AI group before taking over Xbox, joins Marc Andreessen, co-founder and general partner at Andreessen Horowitz, and Charles I. Jones, a Stanford University economics professor currently on leave at Anthropic.Productivity and Jobs task force, which will study the economic impact of new general-purpose technologies, including AI, as part of the central bank's approach to monetary policy.Marc Andreessen Says AI Is 'Already a Better Doctor Than 99.99% of Human Doctors'Jamie Dimon says he understands why people have grown 'anti-rich'Gallup CEO says colonizing Mars may be closer than fixing today's ‘broken' workplace—where disengagement levels are as high as 2020Elon Musk Says His Goal Is for SpaceX to Be Worth More than the Entire EarthThe U.S. Added 441,000 Millionaires Last Year, While the Typical American Got 20% PoorerJames Murdoch may have reaped as much as $7.5 billion from his pre-IPO investment in Elon Musk's SpaceXPalantir CEO Alex Karp Warns AI Could Become America's Biggest Driver of Wealth Inequality"You now have a revolution where, you know, I could become 20 times wealthier than I am now," he added. Karp said AI is creating a "complete decoupling" between ordinary economic gains and a small group of people accumulating "unimaginable wealth."The AI Backlash Has Tech Executives Fearing for Their Lives MMPeter Thiel and other tech billionaires are publicly shielding their children from the products that made them richAnthropic's New AI Ad Is So Disturbing, OpenAI CEO Sam Altman Thought It Was SatireMeta Oversight Board study: AI chatbots may be the most perfect propaganda machine ever inventedA Majority of Americans Now Support Seizing Wealth From AI IndustryGoodliest of the Week (MM/DR):DR: New York bans data center construction for a year, rattling AI industry AND New York becomes first U.S. state to impose AI data center banMM: FREE FLOAT! MMMicrosoft's emissions rose 25% last year. Experts say they'll surge even more dramatically in the years aheadWe said FIVE YEARS AGO that MSFT board was one of the worst at managing carbon despite setting a net negative target at the timeWe were correctAssholiest of the Week (MM):It's not us, it's youxAI sued a Grok user for allegedly generating deepfakes of child sexual abuseIn the ultimate in tech bro manbaby id, Musk is blaming the USERS for his failure to stop child sex abuseLike a gun company suing a gun owner for using the gun used in murder - gun terms of service!Dimon urges calm over fear about AI's impact on jobs: 'Stop being breathless over it'AI isn't the problem, your breathless fear isRobotaxis Are Turning Passengers Into Horrible and Entitled Menaces to SocietyIt's not the service, it's the user… Meta CTO Says He'd Like to Sue Leakers, Then Audio From That Same Meeting LeaksIt's not what I said that's the problem, it's that you told someonePeter Thiel and other tech billionaires are publicly shielding their children from the products that made them richBut YOUR children should use them, obviouslyIt's the USER's fault now… unless, of course, it's a school - in which case the SCHOOL is to blame:84% of students use AI for homework. Only 3 in 10 schools have rules for itAccessWhite House teleprompter operator investigated over alleged trades on Trump speechesTrump Media to Sell Faster Access to President's Social PostsOpenAI Strikes Bold Deal With Kalshi to Mix Together the Most Hated Technologies in Existence: AI and Prediction MarketsDOJ Defends Musk's Unpermitted Gas Turbines, Saying Shutting Down Grok Threatens National SecurityElon Musk's $1 million offers to voters in Wisconsin election were probably illegal bribes, bipartisan panel rulesParamount Shareholder Sues Ellisons, Board For Alleged Side Deal, Promises To Donald TrumpMichael Dell has nailed his relationship with Donald Trump, and it's paying offMeritocracyPete Hegseth Announces Military Will Test Service Members' Testosterone Levels and Offer Hormone TherapyEveryone is a trans man!Is AI Rejecting Your CV Because of Your Age or Race? Landmark Lawsuit Could Reshape RecruitmentFor Black women hit by anti-DEI backlash, this election is personalAustralia's highest paid CEO makes 500 times the average salaryThe American E.V. Has Been Crushed. Will It Take the U.S. Auto Industry With It?WE WANT THE CARS. Just give us the Chinese ones nowJim Cramer on Meta: “Zuckerberg's Not a Bozo, You Can Quote Me on That”Paul Fucking Atkins and The War on John Cheveddan DR“Regardless of the fate of Rule 14a-8 next season and beyond, I implore all who have a role in the shareholder proposal process to not let it be weaponized by those who represent fringe interests. Annual meetings are not vehicles for political or social debates that have little or no bearing on investors' financial returns.”“This past season, one—yes, one—individual was the sole or lead proponent for approximately 41 percent of the shareholder proposals that were voted upon.[20] Of this individual's proposals, only eight percent received majority support.[21] Simply put, when a single shareholder can seize annual meetings to present scores of proposals on issues that are not generally supported by other shareholders, the system is woefully ineffective and in desperate need of reformation.”That individual is John CheveddanAtkins neglected to mention the rise of anti-ESG filers as a group, and their average of

This week, the squad breaks down Norwegian Air's World Cup Instagram stunt that cost next to nothing and generated more brand equity than campaigns with budgets a hundred times the size. Eivind Hammer Myhre, who leads comms and marketing at Norwegian, joins us live to walk through exactly how it happened — the 25-minute brainstorm, the one phone call to get sign-off, and what came after when the whole thing blew up overnight. Then we get into the Ennismore story. Skift's Rafat Ali floated a thought experiment this week that reads less like an op-ed and more like a deal memo left on the wrong desk — a potential distribution and loyalty partnership between Airbnb and Accor's lifestyle hotel subsidiary ahead of a $3.7 billion IPO. Ben, Edwin, and Scott dig into whether the math actually works for owners, who benefits more, and why Wall Street keeps struggling to put a number on cool. And finally — Vrbo is launching sponsored listings. The beta is live. The full rollout is coming. And if you've been around long enough to remember what happened when organic reach died on Meta, you already know where this is going. Scott's spice of the week ties it all together: four stories that seem unrelated until you realize they're all asking the same question. How do you earn trust at scale? And what happens to the brands — and the platforms — that can't figure that out? — This Week in Hospitality is presented to you by Journey. Journey is a loyalty platform built specifically for independent boutique hotels and high-touch hospitality brands. Our mission is to give operators the same powerful rewards engine, data intelligence, and guest insights that major chains rely on — without asking them to give up the individuality, soul, or story that makes their property extraordinary. If you're an owner or operator of an extraordinary, independently owned and operated hotel or residence — and you want to see whether your property is a fit for the Journey Alliance — you can learn more and apply at https://www.journey.com/alliance — Key Topics & Timestamps 00:00 — Intro 03:18 — Interview: Norwegian Air's Viral Women's Euro Campaign 26:53 — Story #1: Airbnb and Ennismore Hook Up 33:47 — Story #2: The Slow Death of Organic Discovery on Vrbo 39:52 — Story #3: South Korea Could Strip Hotels of Stars for Price Gouging 1:04:47 — Spice of the Week — Your Hosts: Zach Busekrus — Journey LinkedIn: https://www.linkedin.com/in/zachbusekrus/ Instagram: https://www.instagram.com/behindthestays/   Scott Eddy — Global Travel & Hospitality Expert @MrScottEddy LinkedIn: https://www.linkedin.com/in/mrscotteddy/ Instagram: https://www.instagram.com/mrscotteddy/   Ben Wolff — Founder of Onera & Oasi LinkedIn: https://www.linkedin.com/in/ben-wolff/ Instagram: https://www.instagram.com/iambenwolff/   Edwin Kramer — Luxury Hotelier Consultant & Former GM LinkedIn: https://www.linkedin.com/in/edwinckramer/ Instagram: https://www.instagram.com/edwinkramer/

Brandon interviews Arjun Iyer, CEO & Co-founder of Signadot. They discuss how Ephemeral Environments eliminate developer toil by shifting validation earlier in the dev cycle, how Signadot's MCP server lets AI coding agents run end-to-end tests autonomously, and real-world results including Brex saving $2M in cloud spend. Plus, how Cisco bought AppDynamics for ~$4 billion the day before their IPO. Watch the YouTube Live Recording of Episode 581 Show Links Signadot Free Trial Brex Case Study Signadot Documentation Overview Contact Arjun Iyer LinkedIn: Arjun Iyer Twitter: @arjuniyer_ SDT News & Hype Join us in Slack. Get a SDT Sticker! Send your postal address to stickers@softwaredefinedtalk.com and we will send you free laptop stickers! Follow us: Twitch, Twitter, Instagram, Mastodon, BlueSky, LinkedIn, TikTok, Threads and YouTube. Use the code SDT to get $20 off Coté's book, Digital WTF, so $5 total. Become a sponsor of Software Defined Talk! Special Guest: Arjun Iyer.

Irena Cronin has been studying XR since 2016 — first as Robert Scoble's co-author, now as CEO of Infinite Retina, consulting for clients from IKEA's labs division to a major law firm tracking the industry. She joins Charlie, Ted, and Rony for a blunt assessment of how the biggest companies in tech actually operate.The centerpiece is Rony's question: Meta has spent roughly $120 billion on Reality Labs since acquiring Oculus. Where did it all go? Irena's answer is unsparing — complete mismanagement, no follow-up, and a lack of imagination that money can't fix. Apple gets a different diagnosis. Irena tracked the Vision Pro through hundreds of iterations since 2019 and predicted exactly how it would land. Her real news: it isn't dead. People inside Apple are still working on it intensely while the glasses project ramps up. The news segment covers OpenAI's Apple IP scandal and whether the Valley now operates in a post-IP world.Key Moments:[00:01:30] OpenAI caught in Apple's cookie jar — IP theft accusations on the eve of the IPO[00:05:00] Sherlocking and the post-IP world — how big companies strip-mine startups through fake M&A talks[00:12:00] AI regulation — Hassabis, Altman, and Amodei; Rony's case for why the public gets Cessnas, not F-47s[00:18:45] Irena joins — Infinite Retina, IKEA, and why physical AI is just spatial computing renamed[00:24:30] Why isn't anyone afraid of Google? — fifteen years of planetary data and no strategy to use it[00:33:30] Where did Meta's $120 billion go? — "complete mismanagement" and a failure of imagination[00:38:00] The Vision Pro isn't dead — Apple is still working on it intensely as the glasses ramp up[00:41:45] Why is XR so obscenely hard? — the industry chased consumers before enterprise[00:44:30] The display is everything — why smart glasses "go bonkers" the moment AR hits the lensBrought to you by Zappar and Mattercraft, the leading visual development environment for immersive 3D web experiences. Start building at mattercraft.io. Hosted on Acast. See acast.com/privacy for more information.

In this episode, we break down how crypto markets are showing renewed strength as Bitcoin and Ethereum erase most of June's losses, and crypto ETFs snap their longest losing streak on record. Around the globe, momentum continues to build as Japan, the UK, and Bolivia advance initiatives that could further accelerate digital asset adoption.  We also explore how Cantor Fitzgerald and Securitize are bringing IPOs onchain, highlighting the growing convergence of traditional finance and blockchain technology. Finally, we dive into Nous Research's reported $75 million fundraising round at a $1.5 billion valuation and what its expanding Hermes AI agent platform could mean for the next wave of artificial intelligence innovation.  Chart of the week: The IMF's July 2026 World Economic Outlook  Remember to Stay Current!  To learn more, visit us on the web at https://www.morgancreekcap.com/morgan-creek-digital/. To speak to a team member or sign up for additional content, please email mcdigital@morgancreekcap.com  Legal Disclaimer  This podcast is for informational purposes only and should not be construed as investment advice or a solicitation for the sale of any security, advisory, or other service. Investments related to the themes and ideas discussed may be owned by funds managed by the host and podcast guests. Any conflicts mentioned by the host are subject to change. Listeners should consult their personal financial advisors before making any investment decisions. 

In this episode, I sat down with Bryan Hasling who works exclusively with tech employees navigating 7-8 figures of startup equity. We broke down how the current IPO landscape is completely different from what it used to be, why the lockup period is more stressful than the IPO itself, and the one question every employee needs to answer before the stock starts moving.---------✅ Financial planning for 30-50 year old entrepreneurs: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.allstreetwealth.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠✅ My personal blog & newsletter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.thomaskopelman.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Disclaimer: None of this should be seen as financial advice. It is just for informational purposes.

The landmark Clarity Act is stuck in the Senate over a provision seeking to address Trump's business ties to the the industry. The CLARITY Act is back in focus after a House panel moved the crypto regulation debate to New York, giving the industry another look at whether Washington can still push digital-asset legislation through a crowded political calendar. ~This episode is sponsored by Tangem~ Tangem ➜ https://bit.ly/TangemPBN Use Code: "PBN" for Additional Discounts! 00:10 Sponsor: Tangem 00:45 One Year Later 01:10 Still waiting on last minute 01:20 CLARITY 01:50 Hearing for two bullshit bills 02:15 3-pages 02:40 Bitcoin strategic Reserve 03:00 Hearing room? 03:30 Chuck-E-Cheese? 03:40 CLARITY Hearing was a waste of time 04:20 ZERO showed up 04:50 Hard at work 05:20 He still hopeful? 05:30 Gallego says nope 06:00 Deputy Director Harry Jung 06:40 Wishing it would not go away doesn't make it go away 08:00 Elizabeth Warren is always ready with a FUD drop 09:00 Robinhood & Solana don't give a shit about CLARITY 09:45 IPO season will be constant reminder that markets are broken 10:40 Ripple is screwed though #Crypto #XRP #Ethereum ~CLARITY Act Finally Drops Today?

StubHub faces class action Ghost Ticket lawsuits… as the CEO was outed as a ticket scalper.Béis sells $250M in luggage every year… its newest viral Weekender bag was designed by haters.China's DeepSeek reportedly plans to IPO this year… because most American businesses don't need Ferrari AI.Plus, Chipotle's opening its 1st restaurant in Mexico… $STUB $RACE $CMGGrab your Tickets to the IPO Tour: Our In-Person OfferingSan Francisco 9/23: https://www.ticketmaster.com/event/1C0064AFB5F688BDBoston 10/14: https://tickets.citywinery.com/event/tboy-the-ipo-tour-in-person-offering-8cdhupSeattle 11/4 (21+): https://www.axs.com/events/1446394/the-best-one-yet-ticketsNEWSLETTER:https://tboypod.com/newsletter OUR 2ND SHOW:Want more business storytelling from us? Check our weekly deepdive show, The Best Idea Yet: The untold origin story of the products you're obsessed with. Listen for free to The Best Idea Yet: https://wondery.com/links/the-best-idea-yet/NEW LISTENERSFill out our 2 minute survey: https://qualtricsxm88y5r986q.qualtrics.com/jfe/form/SV_dp1FDYiJgt6lHy6GET ON THE POD: Submit a shoutout or fact: https://tboypod.com/shoutouts SOCIALS:Instagram: https://www.instagram.com/tboypod TikTok: https://www.tiktok.com/@tboypodYouTube: https://www.youtube.com/@tboypod Linkedin (Nick): https://www.linkedin.com/in/nicolas-martell/Linkedin (Jack): https://www.linkedin.com/in/jack-crivici-kramer/Anything else: https://tboypod.com/ About Us: The daily pop-biz news show making today's top stories your business. Formerly known as Robinhood Snacks, The Best One Yet is hosted by Jack Crivici-Kramer & Nick Martell. Hosted on Acast. See acast.com/privacy for more information.

A.M. Edition for July 16. President Trump mulls a further escalation of the war in Iran. That could include more airstrikes, targeting the fortified tunnel complex at nuclear site Pickaxe Mountain or sending in ground troops near the Strait of Hormuz. Plus, the U.S. slaps 25% tariffs on certain Brazilian goods, citing unfair trade practices, but excludes beef and coffee. And WSJ special writer Gregory Zuckerman debates whether the recent surge in IPOs and share listings is a sign of a market downturn. Daniel Bach hosts. Sign up for the WSJ's free What's News newsletter. Learn more about your ad choices. Visit megaphone.fm/adchoices

On this episode of Christopher Lochhead: Follow Your Different, Bruce Cleveland, legendary entrepreneur and venture capitalist, joins us to discuss his powerful new book, “Market Engineering: Because Markets Don’t Build Themselves.” The conversation brought together two former competitors who have since become allies in a shared mission: helping founders and executives understand that markets, like products, can be deliberately designed and engineered. Cleveland’s insights are drawn from decades of operating experience at companies like Siebel and Apple, as well as his work as a venture capitalist guiding early-stage startups. The core argument is simple but often ignored. Over 90% of startups fail not because their products are bad, but because they never take responsibility for shaping the market around those products. Cleveland and Lochhead agree that the companies who teach the market how to think about a problem, and then how to solve it, are the ones who become category kings and queens. You're listening to Christopher Lochhead: Follow Your Different. We are the real dialogue podcast for people with a different mind. So get your mind in a different place, and hey ho, let's go.   Bruce Cleveland on What Market Engineering Actually Means Bruce Cleveland defines market engineering as a five-part discipline that includes category design, positioning, messaging, storytelling, and thought leadership. When these elements are combined intentionally and consistently, they create gravitational pull. Customers seek you out, attend your events, and associate your brand with the future they want to be part of. Cleveland draws a sharp distinction between marketing and market engineering. He uses the analogy of a short-order cook at Denny’s versus a chef at a Michelin-star restaurant. Both have the same basic ingredients, but the outcomes are vastly different. The difference is knowing how to combine those ingredients with precision, purpose, and craft.   The Book as an Instruction Manual, Not Just Inspiration One of the most refreshing aspects of Bruce Cleveland’s approach is his insistence on practicality. He openly criticizes business books that fire readers up but leave them with no clear path forward. “Market Engineering” was written as a prescriptive guide, walking readers through specific frameworks like the Market Blueprint, Messaging Matrix, and Market Charter. To take this even further, Cleveland built an AI-powered platform called the Market Engineering Virtual Studio, trained on his own methodology using a neural symbolic recursion model named Finn. The platform allows users to actually build the documents and artifacts described in the book, turning static ideas into dynamic action. Cleveland and Lochhead both agree this model, combining a book, an AI companion, and a community, represents the future of business education.   Why Former Competitors Are Now Building the Same Category Together Perhaps the most telling moment in the conversation is when Lochhead reflects on the fact that he and Bruce Cleveland spent years as direct competitors, yet now champion nearly identical ideas. Rather than seeing this as a conflict, both men view it as validation. A category only exists when multiple credible voices contribute to defining it. Their combined efforts have helped make category design and market engineering part of the mainstream business conversation. Cleveland also speaks candidly about why he works primarily with pre-seed and early-stage companies that have limited capital. He prices his tools and services accessibly on purpose, takes small equity positions, and focuses on creating real economic impact. His philosophy is that helping startups succeed contributes more to society than any check he could write to a traditional charitable cause. For Bruce Cleveland, market engineering is not just a framework. It is a form of giving back. To hear more from Bruce Cleveland on the benefits of Market Engineering, download and listen to this episode.   Bio Bruce Cleveland's career in Tech spans more than 40 years as a venture investor and operating executive. He was a first investor and a board member of Marketo, which held an IPO in 2013 and was acquired in 2018 by Adobe for $4.75B. He was an early-stage investor in other notable companies such as C3.ai, Doximity, Vlocity, and Workday. Bruce also held senior executive roles in engineering, product management and product marketing at Apple, AT&T, C3.ai, Oracle and Siebel Systems. His book, Traversing the Traction Gap, is a prescriptive guide for startups and new product initiatives within larger companies helping teams to use ‘market engineering' techniques to successfully transition from Ideation to Scale. He attended the US Military Academy, West Point, New York, and received a BS in business administration from CSU, Sacramento. He lives in the San Francisco Bay Area.   Connect with Bruce Cleveland! LinkedIn | X (Formerly Twitter) | Website Check out his book here: Market Engineering: Because Markets Don’t Build Themselves   We hope you enjoyed this episode of Christopher Lochhead: Follow Your Different™! Christopher loves hearing from his listeners. Feel free to email him, connect on Facebook, X (formerly Twitter), Instagram, and subscribe on Apple Podcast / Spotify!

Carl Quintanilla and Jim Cramer explored what to make of the pullback in the AI trade: Taiwan Semiconductor shares dragged the chip sector lower despite the company's record quarterly results. A different story for UnitedHealth Group, up sharply on its blowout earnings and raised guidance. The anchors discussed the SpaceX stock slump one day after shares fell below their $135 IPO price for the first time ever. Also in focus: Earnings movers from GE Aerospace to United Airlines; June retail sales reaction; Uber to buy Germany's Delivery Hero in a $14.8 billion deal; Eli Lilly's psychedelic M&A takeover; FDA approves Merck's new cholesterol pill; Trump Media's new move; Cramer previews the CNBC Investing Club Monthly Meeting.     Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Electricity demand in the U.S. is climbing faster than the grid can comfortably absorb, driven largely by AI data centers that need power 24 hours a day, seven days a week. The U.S. power system needs all the reliable clean energy it can get, and once-forgotten geothermal energy is one such resource. In the 1960s, the United States was a world leader in building large-scale geothermal power plants, but during the fracking boom of the mid-2000s, drillers turned their attention to oil and gas. As wind, solar and batteries got cheaper, bankers and developers put their money into those resources. Geothermal development around the world had flatlined, until a new generation of geothermal developers and entrepreneurs borrowed the horizontal drilling techniques that powered the fracking boom and used them to make geothermal viable in far more geographies One of those entrepreneurs is Tim Latimer, Co-Founder and CEO of Fervo Energy. Fervo Energy is a geothermal developer using advanced drilling techniques from fracking in the oil and gas industry to make it easier to find and harness heat underground. In our conversation, recorded in December 2021, Tim told me about how he combined his expertise in oil and gas drilling with a dedication to solving the climate crisis, and used his experience to break open an overlooked renewable resource. Tim predicted the 2020s would be "the geothermal decade," noting that we can't transition to a zero-carbon grid without round-the-clock clean energy resources to supplement intermittent renewables. Geothermal offers that always-on feature needed now more than ever. We're revisiting this conversation now in celebration of what Fervo has accomplished: signing hundreds of megawatts of power purchase agreements with hyperscalers and utilities alike, and recently completing the largest IPO of any clean energy company. About Powerhouse Innovation and Powerhouse Ventures Powerhouse Ventures backs seed stage founders building the future power system across energy, infrastructure, and AI. If you are thinking about building something in this space, get in touch with our team. Powerhouse Innovation is a best in class consulting firm, powered by the strongest energy innovation network, data and team in our industry. We partner with world's leading corporations, investors, and utilities to source and evaluate disruptive startups shaping the future of energy and industry. To hear more stories of founders building our energy abundant future, hit the “subscribe” button and leave us a review.

On today's MJ Morning Show:Natural Light's 'Cool Shed'Morons in the news"Nation's Dumbest"Rachael RayMJ can't read his own writing, or doesn't remember what it meant"Bailey the Intern's" car scrape sagaMJ's U-Haul sagaPole dancer hits sprinklerListener Colleen lost her Crotchety CD'sGoing to see 'Odyssey'Caller with a West Point dorm sprinkler storySenator Schumer's fartLicense plate "SQZ A55"Woman get addicted to cosmetic procedures more than gambling2 DUI principalsSpaceX dropped below IPO price (briefly??)No-proof class-action lawsuitsReporter's live shot with a roach crawling on herLights went out at MJ's house twiceMJ's dog Gatsby 'glitched'Complaint about FesterInfluencer didn't want to pay price of lobsterFirefighters rescued man from a porta-potty/Classic CrotchetySee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Stephanie Roth is the Chief Economist at Wolfe Research. In this conversation, we break down whether inflation has peaked, why tariffs, AI chip shortages, and the Iran war are driving short-term prices, and why consumers feel poor despite a resilient economy. We also cover trust in government data, incoming Fed chair Kevin Warsh, the 2026 IPO wave, and the bitcoin and gold debasement trade.==================Award-winning Fountain Life - Energy supercharged. Memory sharper. Life extended. Ready for the best investment you'll ever make? Schedule a life-changing call at http://fountainlife.com/pomp Get $1,000 off the cost of a life-changing membership with Fountain Life when you schedule a call at https:www.http://fountainlife.com/pomp==================Arch Public is an agentic trading platform that automates investment strategies across Stocks, Commodities, ETFs and Crypto. Whether you're rotating into AI & Gold, allocating to the S&P 500, or accumulating Bitcoin, Arch Public executes your plan 24/7 without ever taking custody of your assets or funds. Sign up today at https://www.archpublic.com, and start your FREE automated trading strategy!==================Simple Mining makes Bitcoin mining simple and accessible for everyone. We offer a premium white glove hosting service, helping you maximize the profitability of Bitcoin mining. For more information on Simple Mining or to get started mining Bitcoin, visit https://www.simplemining.io/pomp==================0:00 - Intro1:03 - Has inflation peaked? Tariffs, AI & energy price drivers5:14 - Why consumers feel poor despite a strong economy7:43 - Can you trust government economic data?13:54 - Housing affordability & why NYC rent hit an all-time high17:43 - Return to office, commutes & worker productivity21:37 - Kevin Warsh takes over the Fed — what's changed?30:57 - Could the Fed cut rates to influence the 2026 election?35:42 - The mega IPO wave & the AI bubble question41:32 - What happened to the bitcoin & gold debasement trade?43:00 - What keeps a chief economist up at night?