Podcasts about Xai

In this episode of The Higher Standard, Chris and Saied dive headfirst into the wildest S-1 filing Wall Street may have ever seen: SpaceX, Starlink, XAI, Mars colonies, asteroid mining, lunar economies, data centers in space, and Elon Musk casually trying to justify a $28.5 trillion total addressable market like he's ordering lunch. The guys break down whether this is a visionary master plan to make humanity multi-planetary or a beautifully packaged liquidity event with rockets, buzzwords, and enough “AI” mentions to make Nvidia blush. From the insane valuation math to the XAI gamble, the class structure, the retail investor risk, and the very real question of whether investors are buying a business or a sci-fi trilogy, this episode is classic THS: smart finance, sharp skepticism, and just enough chaos to make the moon feel underwritten.

We talk a lot about coding and AI and a little less about headlines today. Runner-up: SpaceX is targeting a June/July 2026 IPO at a reported ~$1.75 trillion valuation, which would be the largest public listing in history. The float follows SpaceX's ~$250B all-stock acquisition of xAI in February, folding Starlink, launch, and frontier AI into one entity.Runner-up: Amazon's custom AI chip business — Graviton, Trainium, and Nitro — hit a $20B annual run rate with triple-digit YoY growth. OpenAI committed to about 2 GW of Trainium capacity, Anthropic is scaling to 5 GW, and analysts project a standalone Trainium could become a $50B business.Runner-up: NVIDIA topped a $5.5 trillion market cap and is deploying more than $45B across the AI supply chain, extending its position from chip supplier to investor and customer across the stack.Runner-up: Apple posted record fiscal Q2 2026 revenue of $111.2B, up 17% YoY, with diluted EPS of $2.01. iPhone sales rose 22% and Services climbed about 16% to $26.65B, and the company guided Q3 growth of 14%-17%.Runner-up: AI venture funding shattered records with $297B in Q1 2026, including $35B raised in a single week.If you want a prize, send us a DM:instagram.com/rickerandbontiktok.com/@rickerandbontiktok.com/@rickerandbonyoutube.com/@rickerandbon

Bitcoin is teetering near $72,000 as the Iran war heats back up, with Trump claiming Tehran "really wants" a deal while air strikes resumed over the weekend near the Strait of Hormuz, sending Brent crude up 3.7% to $94.48 and WTI surging 4.3% to $91.07. A tentative 60 day memorandum of understanding would reopen the Hormuz chokepoint with unrestricted shipping and require Iran to clear all mines within 30 days, but the deal still awaits Trump's final approval and Iran's response. Meanwhile Coinbase is launching direct rupee rails in India on June 1 to attack the $3 billion local crypto market, Fed Governor Christopher Waller declared dollar stablecoins could expand the reach of U.S. monetary policy globally, and Jamie Dimon just vowed JPMorgan and the banking lobby will fight the CLARITY Act over stablecoin yield. Plus Michael Burry dropped a bombshell calling the Nvidia, xAI, Apollo, Athene structure "Fugazi", alleging $5.4 billion in GPUs are hidden off balance sheets while American retirees unknowingly hold $103 billion in Level 3 assets at 16x leverage inside a Bermuda insurance shell. We are breaking down whether Bitcoin can survive another Hormuz spike, what Waller's stablecoin endorsement means for the dollar, and why Burry's warning could be the most dangerous story nobody is talking about. Learn more about your ad choices. Visit megaphone.fm/adchoices

SHOW NOTES   In Podcast Episode 377, “God Can Speak in Unexpected Ways,” Kim discusses the dangers of Christ-followers trying to limit how the Lord can speak to them. We see that in today's scriptures as King Josiah refuses to believe God would be speaking through an enemy king, and it cost him his life. May our daily life theme be, “Speak, your servant is listening,” with no limits on the when or the how He can speak.   Our focal passage for this episode is 2 Chronicles 35:20-27, and with 22 as the focal verse:   22 But Josiah refused to listen to Neco, to whom God had indeed spoken, and he would not turn back. Instead, he disguised himself and led his army into battle on the plain of Megiddo.     WEEKLY ENGAGEMENT FEATURE:   When you pray, “Speak, your servant is listening,” don't put limits on how the Lord can speak.   Additional Resources and Scriptures:   10 And the Lord came and called as before, “Samuel! Samuel!” And Samuel replied, “Speak, your servant is listening.” (1 Samuel 3:10) Facebook Group - https://www.facebook.com/groups/encouragingothersinlovingjesus X - https://x.com/eoinlovingjesus?s=21&t=YcRjZQUpvP7FrJmm7Pe1hg INSTAGRAM -  https://www.instagram.com/encouragingothersinlovingjesus/ “Encouraging Others in Loving Jesus” YouTube Channel: Check it out at https://www.youtube.com/@EncouragingOthersInLovingJesus     I WANT TO BEGIN A PERSONAL RELATIONSHIP WITH JESUS CHRIST.   RESOURCES USED FOR BOOK OF 1 & 2 Kings (1 & 2 Chronicles) PODCASTS: “The Wiersbe Bible Commentary: The Complete Old Testament OT in One Volume” “Christ-Centered Exposition: Exalting Jesus in 1 & 2 Kings” by Tony Merida “The Tony Evans Bible Commentary: Advancing God's Kingdom Agenda” “Life Application Study Bible” “The Swindoll Study Bible: NLT” by Charles R. Swindoll Holman Illustrated Bible Dictionary “The Baker Illustrated Bible Background Commentary” by J. Scott Duvall and J. Daniel Hays (Editors) Expositor's Bible Commentary (Abridged Edition): Old Testament, 2004, by Kenneth L. Barker, John R. Kohlenberger, III. xAI. (2026). Grok [Large language model]. https://x.ai/grok/chat      "Encouraging Others in Loving Jesus" Facebook Group:   Our Facebook Group is devoted to providing a place for us to encourage each other through all the seasons of life. Follow the provided link to request admittance into “Encouraging Others in Loving Jesus”—https://www.facebook.com/groups/encouragingothersinlovingjesus/ Feel free to invite others who will be good encouragers and/or need encouragement to follow Jesus.   This podcast is hosted by Kim Smith, a small town Country Girl who left her comfort zone to follow Jesus in a big City World. Now, she wants to use God's Word and lessons from her faith journey to encourage others in loving Jesus.   In each episode, Kim will share insights regarding a portion of God's Word and challenge listeners to apply the lessons to their daily lives.   If you want to grow in your faith and learn how to encourage others in loving Jesus, subscribe and commit to prayerfully listening each week.   Remember, “It's Always a Trust & Obey Kinda Day!”   If you have questions or comments or would like to learn more about how to follow Jesus, please email Kim at EncouragingOthersinLovingJesus@gmail.com.     National Suicide & Crisis Lifeline   988   https://988lifeline.org/   Reference: Unless otherwise indicated, all Scripture quotations are taken from the Tyndale House Publishers. Holy Bible: New Living Translation. Wheaton, Ill: Tyndale House Publishers, 2004.   Podcast recorded through Cleanfeed and edited through GarageBand. The soundtrack, entitled “Outlaw John McShane” was obtained from Pixabay.     The HIDDEN Episodes:  If you can't access episodes 1-50 on your podcast app (the podcast was then entitled "A Country Girl in a City World - Loving Jesus"), you can get all the content at my Podbean site at https://acountrygirlinacityworldlovingjesus.podbean.com/    

It's been a minute since we've had Nikolai Yakovenko on the podcast. Yakovenko is a former professional poker player,and was a research scientist at Google, Twitter and Nvidia. With a decade in computer science, Yakovenko has been at the forefront of the large-language-model revolution that has driven to prominence companies like OpenAI, Anthropic, and DeepMind, and an ecosystem that has birthed hundreds of smaller startups. He is also the founder of DeepNewz, an AI-driven news startup. On this podcast, Razib and Yakovenko talk about the current top of the line "frontier labs," OpenAI, Anthropic, and Google's DeepMind, why xAI has faltered, and the reality that only DeepSeek in China seems up to challenging the American firms. Yakovenko notes that AI's transformative impact is mostly in the massive capital influx into the sector, as well as becoming a ubiquitous part of the software engineer's toolkit. They discuss how programming without an AI-assist is now likened to "raw dogging" coding, while artificial superintelligence seems a rather distant prospect. The technology is getting better, but predictions of the doomers seem not to have panned out.  

Generative AI is making its way into many parts of society, and schools are no different. Tom Mullaney joins Paris Marx to discuss how generative AI has been adopted in K-12 education and the many concerns it presents for students and teachers.Tom Mullaney is a high school social studies teacher in the suburbs of Philadelphia.Tech Won't Save Us offers a critical perspective on tech, its worldview, and wider society with the goal of inspiring people to demand better tech and a better world. Support the show on Patreon.The podcast is made in partnership with The Nation. Production is by Kyla Hewson.Also mentioned in this episode:Here is the New Yorker article on AI in schools.For those looking for a refresher on Weizenbaum and ELIZA.Here is the paper “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big”.For those curious about the Canvas breach.Students have been booing pro-AI speeches and AI presence in graduation ceremonies.xAI is facing a lawsuit for polluting Black neighborhoods.Support the show

In this episode, we break down a wide range of market stories, starting with SpaceX’s potential IPO and what its S-1 reveals about the business. We look at the company’s major segments, including Starlink, launch services, and xAI, while discussing the massive valuation being floated and why investors may want to be cautious around the hype. We also cover Nvidia’s latest blockbuster earnings, the continued strength in AI infrastructure demand, and why the stock’s muted reaction says a lot about how much growth is already priced in. From there, we turn to Walmart, Lowe’s, and Home Depot to see what they are saying about the consumer, higher fuel costs, and the pressure still hitting DIY and housing-related spending. Finally, we discuss the start of Canadian bank earnings season with Scotiabank, including its improving return on equity, lower provisions, and why Canadian banks continue to show resilience despite concerns around the broader economy. Tickers of stocks discussed: NVDA, WMT, LOW, HD, BNS.TO Subscribe to Our New Youtube Channel! Check out our portfolio by going to Jointci.com Our Website Canadian Investor Podcast Network Twitter: @cdn_investing Simon’s twitter: @Fiat_Iceberg Braden’s twitter: @BradoCapital Dan’s Twitter: @stocktrades_ca Want to learn more about Real Estate Investing? Check out the Canadian Real Estate Investor Podcast! Apple Podcast - The Canadian Real Estate Investor Spotify - The Canadian Real Estate Investor Web player - The Canadian Real Estate Investor Asset Allocation ETFs | BMO Global Asset Management Sign up for Fiscal.ai for free to get easy access to global stock coverage and powerful AI investing tools. Register for EQ Bank, the seamless digital banking experience with better rates and no nonsense.See omnystudio.com/listener for privacy information.

SpaceX. Tesla. Starlink. X. The Boring Company. xAI… developing and owning ANY of these modern-day marvels would be an achievement. Two would be astonishing, and three, MIRACULOUS. But all of them? On the eve of the SpaceX IPO, Steve, Scott and Bill try to figure out how this soon-to-be-TRILLIONAIRE pulls all this off?

In this episode of The Brainstorm, Brett, Nick and Sam are joined by Daniel Maguire and Tasha Keeney to discuss the expected June 12th initial public offering (IPO) of SpaceX. SpaceX's recently filed S-1 revealed a significant opportunity across launch, Starlink, AI compute, and orbital data centers. The team unpacks the bull and bear cases, Starship's role, and whether SpaceX could become the backbone of future AI infrastructure.Key Points From This Episode:SpaceX's S-1 reframed the company as an AI infrastructure story, with xAI, Colossus data centers, and the Anthropic deal suggesting a major opportunity beyond launch and Starlink.Starship is the key unlock, potentially driving launch costs below $100/kg, accelerating Starlink bandwidth deployment, and making orbital data centers economically viable.The biggest risks are execution and monetization, including Starship reusability timelines, turning bandwidth into revenue, staying competitive at the AI frontier, and managing potential future integration with Tesla.If you know ARK, you know we focus on long-term innovation. But that doesn't mean we ignore breaking news. Every day, we debate the latest developments in tech and markets. Now, we're bringing those conversations to you in “The Brainstorm,” a co-production from ARK, WOLF, and Public. Tune in weekly for our quick takes on what's shaping innovation right now.Learn more about WOLF: https://wolf.financialLearn more about Public: https://public.com/Disclosure: http://arkinv.st/39rzF94

SUMMARY:  Brian Gracely (@bgracely) and Brandon Whichard (@bwhichard, Software Defined Talk and Failover Media) discuss the biggest AI news stories from the month of May, 2026. SHOW: 1031SHOW TRANSCRIPT: The Reasoning Show #1031 TranscriptSHOW VIDEO: https://youtu.be/MNihDdBSteISHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Links to all the AI News covered in this month's showFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

ESG StuffBP removes chairman Albert Manifold over governance issues 9The board said the decision was unanimous. In a statement, Amanda Blanc, BP's senior independent director, described the board as having been caught off guard by what it found: "The board has been surprised and disappointed to learn of governance oversight and conduct issues it deems unacceptable and has taken decisive action."The company did not elaborate on the specific nature of the concerns.Ian Tyler has been named interim chair, BP said, with the board set to begin a formal process to identify a permanent successor: "The Board and leadership team have deep conviction in the strategic direction we have laid out, and the company is moving at pace to deliver it."Manifold took up the chairmanship just last October. At last month's annual general meeting, just 81.8% of shareholders backed his electionAmong the most consequential decisions of Manifold's short tenure: pushing out former CEO Murray Auchincloss and overseeing the selection of Meg O'Neill to succeed him — a hire that marked the first time BP had recruited an external CEO and the first time a woman had led one of the oil industry's largest players.Tulsi Gabbard Exit Marks Fourth Woman to Leave Trump Cabinet 0Apology TourBank boss sorry after describing workers as 'lower value human capital' 7Standard Chartered CEO Bill Winters triggered a massive PR firestorm by describing the bank's plan to replace back-office staff with automation as replacing "lower-value human capital" with financial investmentStandard Chartered is cutting roughly 7,800 jobs—representing about 15% of its global back-office corporate support roles—over the next four years to make room for AIAfter internal anger and blistering public criticism, Winters posted a formal apology for his "choice of words." However, he initially fueled the fire by attaching the full interview transcript to justify his broader context, drawing further criticism for being defensiveIn his first attempt to quiet the storm, Winters leaned heavily into the corporate strategy rather than apologizing for the specific phrasing: "I said that lower-value roles are more vulnerable to automation, and that we have a responsibility to help colleagues move into higher-value roles. That is what a responsible employer should do. We will continue to speak honestly about the impact of technological change, and we will continue to act responsibly in helping our people to adapt and succeed."After a barrage of negative comments on his first post, Winters returned to LinkedIn later that day to offer an explicit apology for his phrasing: "I have received a lot of support for the messages in my previous post but still get questions about my choice of words, which I know has caused upset to some colleagues. For that I am sorry.""I think the transcript makes it clear that I value our colleagues – all of them – most highly and that we are totally committed to helping them to cope with the accelerating pace of change in our industry."JPMorgan's Jamie Dimon says bank chief's viral AI comment was 'inartful' Dimon downplayed the viral backlash against Standard Chartered CEO Bill Winters—who drew fire for saying his bank would replace "lower-value human capital" with technology—calling it an "inartful" slip-of-the-tongue from a friend.Neopbabies and Dropout babiesJames Murdoch to acquire New York Magazine and Vox Media Podcast Network -1Bolt CEO says he let go of his entire HR team for creating problems that didn't exist: ‘Those problems disappeared when I let them go' 6Bolt CEO Ryan Breslow justified firing his entire Human Resources department by claiming they actively manufactured internal frictionThe aggressive purge follows a brutal 97% collapse in Bolt's valuation—crashing from an $11 billion peak in 2022 down to $300 millionTraditional HR has been entirely swapped for a skeletal "people operations" team, shifting the focus away from employee complaints and internal processes toward basic compliance training and empowering managers to make split-second decisionsAlongside gutting HR, Breslow rolled back employee-friendly benefits like four-day workweeks and unlimited PTO, claiming a culture of complacency had taken over and that 99% of his legacy workforce was simply unwilling to work hardRyan dropped out of Stanford in 2014 to launch BoltThe Middle School Boy Man Babies Rule the WorldMan Drives Cybertruck Into Lake to Test Elon Musk's “Boat” Claims, and It Went About as Well as You'd Guess -10"The passengers abandoned the vehicle and the driver was arrested."Tesla CEO Elon Musk:randomly tweeted that the vehicle would function as a rudimentary flotation device.“It will even float for a while.”“[The vehicle would be able to] traverse at least 100m [330 feet] of water as a boat.”“Cybertruck will be waterproof enough to serve briefly as a boat, so it can cross rivers, lakes and even seas that aren't too choppy.”Jeff Bezos urges US government to stop taxing 50% of America — and claims doubling his taxes won't help ‘that teacher in Queens' 400Jeff Bezos backs Mamdani's tax on luxury second homes, but says Ken Griffin isn't the villainJeff Bezos on Zohran Mamdani's big mistake: ‘When you don't know how to solve a problem, create a villain, blame them'Jeff Bezos says there is ‘no truth' to the ‘buy borrow die' tax strategyBillionaires Openly Use It: Oracle co-founder Larry Ellison has historically pledged over $30 billion worth of his Oracle stock as collateral for personal bank loans. Elon Musk has similarly pledged tens of billions of dollars in Tesla shares to secure lines of credit over the yearsHe said he was "skeptical that that's a true loophole," but added, "If it is, and we can fix it, then we should. I don't think such a loophole should exist."Jeff Bezos Praises Trump's Second Term as ‘More Mature' Jeff Bezos Says AI Will 'Elevate' Workers — Despite Amazon's 30,000 Job Cuts Amid $100 Billion AI PushElon Musk compares his company's work to that of Jesus 0In an interview on Monday, the billionaire said his Neuralink brain-implant company is progressing in its development of ‘Jesus-like technologies'Although brain-computer interface (BCI) as a concept has been around since at least the 1970s, the push to commercialize the technology is more recent. According to data from market-intelligence firm Tracxn, more than 130 BCI startups have been launched since 2016.Why Is Mark Zuckerberg Taunting His Employees Before Firing Them? 20Back in April, Meta announced it was laying off 10 percent of its workforce, or around some 7,800 workers. Unlike traditional layoffs, which are enacted relatively quickly, Meta gave its employees a nearly month-long warning period without announcing who exactly would be headed for the unemployment line.In newly leaked audio from an all-hands meeting at Meta, released by More Perfect Union, the Meta CEO seems to actually be taunting the thousands of workers who were about to be let go by pointing to how the company was harvesting employee data to train its in-house AI models ahead of the massive layoffs.“So we're in a phase where basically the AI models learn from heaving real, from watching really smart people do things. And if you're trying to get it to be able to be able to do certain capabilities, having [AI] be able to observe really smart people doing those things is, is very important.”Going on, Zuckerberg explained that it was better to train AI on soon-to-be-former Meta employees, rather than “contract companies.”“In general, the average intelligence of the people who are at this company is significantly higher than the average set of people that you can get to do tasks if you're working through… contractors,” Zuckerberg stammered. “So if we're trying to teach the models coding, for example, then having people internally, um, build tools that, or, or solve tasks that, um, that help teach the model how to code, we think is going to dramatically increase our models coding ability faster than what others in the industry have the capability to do.”Intuit to Cut 17% of Staff, Invest in ‘Big Bets' 3The restructuring cost is estimated at about $300 million to $340 millionAbout 3,100 employees: and invest the savings in “big bets” as it makes artificial intelligence a centerpiece of its business.Woke WarsTexas AG Sues ISS Over ESG Considerations 0Texas AG Ken Paxton (in a senate race) is suing ISS for allegedly “misleading” customers by pushing “radical political agendas” through its proxy adviceNotably, ISS has attempted to obstruct ExxonMobil's planned reincorporation from New Jersey to Texas“ISS has enormous influence over how billions of dollars are invested and managed across this country, and they have abused that influence in order to push woke ideology”Iowa AG Brenna Bird sues ISS, says advice risks retirement savingsIowa Attorney General Brenna Bird is suing the world's largest proxy-advice firm for abusing its influence and threatening Iowans' retirement savings by "lying" to investors.Stakeholders Rule!Wells Fargo must pay $100M to help homebuyers after discrimination lawsuit — 51 cities are eligible 7The settlement, which was recently approved by a federal judge in California, comes after four years of legal disputes involving Wells Fargo shareholders, former employees and job applicants who accused the bank of systemic problems in both lending and hiring practices.While Wells Fargo denied wrongdoing, the company agreed to the deal to avoid prolonged litigation and mounting legal costs.The case centered on allegations that Wells Fargo's board failed to maintain adequate oversight of the bank's mortgage lending operations, exposing the company to regulatory scrutiny and accusations of discriminatory practices.According to reporting from Realtor.com, plaintiffs accused the bank of “widespread and systematic discrimination in lending” and cited concerns over lending algorithms and refinancing approval patterns.The lawsuit stated that Wells Fargo was allegedly the only major lender in 2020 to reject more refinancing applications from Black homeowners than it approved.Airbus, Air France Hit With Manslaughter Charges Over Pilot Training Failures in Deadly 2009 Flight 447 Crash 1A Paris appeals court delivered a dramatic verdict in one of the longest-running and most complex legal sagas in aviation history. The court overturned a 2023 acquittal and found both Airbus and Air France guilty of corporate manslaughter for the tragic 2009 crash of Flight AF447.The ruling marks a massive victory for the victims' families after a 17-year legal battle. A lower court had previously cleared the European planemaker and the French airline in 2023, ruling that while errors were made, a direct causal link to the crash couldn't be proven. The appeals court completely rejected that logic, declaring the companies "solely and entirely responsible" for the disaster.Ride-Share Drivers in Massachusetts Formally Unionize 100The App Drivers Union said it was the first organization in the country to be formally certified to represent drivers for apps such as Uber and Lyft.In a news release, the organization, the App Drivers Union, said it would represent nearly 70,000 workers in Massachusetts who now have the power to collectively bargain.MATTA very special “who do we blame for SpaceX IPO governance” gameFirst, some S-1 highlights:“Starlink internet is what's being used to pay for humanity getting to Mars.” - MuskTranslation: We don't care much about Starlink, it's just paying our AI billsHe's not kidding: $3.2bn revenue for Starlink, net income of $1.2m$0.6bn revenue for rocket ship, net income of -$0.6bn$0.8bn revenue for AI, net income of -$2.5bnThis isn't a space company - it's classic Musk - you buy the vision (“To build the systems and technologies necessary to make life multiplanetary, to understand the true nature of the universe, and to extend the light of consciousness to the stars.”), but what you're really buying is an internet company that spends all its money on AI and does some rockets on the sideLet someone else invent the car (Tesla) and make them sexy with “big visions” for “humanity”Let someone else invent the rockets, build new ones using someone else's moneyLet someone else invent the satellites, put a whole bunch in space (and buy more satellites from someone else)Musk initially took the role of “Chief Engineer”, but every engineering task seems to have been the other employees - he supplied the moneyShoehorned AI into space exploration because…?Grok is designed as a truth-seeking AI model, built on our founder Elon Musk's mission to enable humanity to understand the universe. We believe that accomplishing this mission requires a truth-seeking approach to AI. We define truth seeking as the active, relentless pursuit of what is objectively true about reality, and grounded in evidence, logic, empirical data, and first principles thinking.AI's ability to revolutionize human potential is directly dependent on meeting exponentially increasing resource demands.We now must go to space to get more resources for AI so we can get to spaceNow the governance who do you blame gameMusk will get:85% voting power (dual class, he owns 94% of Class B 10 vote shares and 12% of Class A shares)The ability to nominate and vote exclusively on >50% of the boardA board which currently includes..TWO execs - Gwynne Shotwell (President) and Musk (three titles)Tesla mafia: Ira Ehreinpreis, Tesla board sycophant, director at the Boring Company and xAI, and longtime Musk hanger on, added Feb 2026Antonio Gracias, ex Tesla director who was explicitly called out in the Tornetta decision as corrupted, cross party transactions with Musk, on boards of Neuralink and Boring Company, added Oct 2010TWO VC bros from DFJ - Randy Glein (SpaceX board observer for 16 years, directors since Feb 2026) and Steve Jurvestson (former Tesla director, director since March 2009) who was ousted from the VC firm with his name on it for sexual harassmentPaypal mafia:Luke Nosek, co founder of PayPal, one of the founders of Founders Fund with Thiel and Ken Howery, invested in DeepMind, director since July 2008Donald Harrison - managed Google purchase of DeepMind, relationship with Nosek, director since Feb 2015Director relationship tenures to Musk: Shotwell: 24 yearsEhreinpreis: 21 yearsGracias: 21 yearsJurvetson: 17 yearsGlein: 16 yearsNosek: 26 yearsHarrison: 11 years (+1 if Nosek/Deepmind connection counts)Texas jurisdiction exclusively (judge shopped) - 3% to sue them, mandatory arbitration, anti-takeover statutes, special meetings ONLY CALLED BY MUSK (no one less than 50% of stock can call a meeting or vote)No written consent - no prior noticeAdvance notice bylaws for the zero shareholder proposals allowedFull omission of board liability - including a provision that automatically allows whatever the conflicts of interest they want with directorsWHO (WHEN) DO YOU BLAME?The US GovernmentDepartment of Energy - in 2010, the DoE gave Tesla a $465m loan, which basically paid for the Model S and helped it buy a factory 6 months before it went public - Musk has said Tesla would not have survived without the loanNevada - in 2014, Nevada gave Musk $1.3bn to build a factory, the most everNASA - spent more than $15bn over years on SpaceX and programs with themThe IRS/Congress - the EV tax credit for $7,500 single handedly pushed Tesla from losing money in 2020 to making money (they effectively got $1.6bn from the US government in 2020), and showing its first profit, which sparked the memefest during COVID and made Musk the richest man on earth - Musk then went on and called for an end to the tax credit since his “competitors” needed it more than Tesla. Tesla made ~$11bn from tax credits aloneThe DoD - started paying SpaceX in 2003 for concept work - and even when the rockets didn't work, the DoD and NASA awarded the company massive contracts anywayJeff Bezos said in 2016 that, “Elon's real superpower is getting government money.”FOMOSpaceX LOSES MONEY - it does not make moneyIf it were a satellite internet company - and NOT THE FIRST - the first was HughesNet in 1996, and Viasat offered it in 2012 - it would make money ($1.2m in income!)Instead, investors are valuing SpaceX as THE LARGEST IPO IN THE HISTORY OF EVER despite the fact that they are burning money on AI, and arguably the worst AIIncluding spending the most on R&D, marketing, and acquisition of Cursor to make up for the fact that Grok suckedIn exchange for FOMO, investors have ENTIRELY GIVEN UP THEIR RIGHTSIt is 100% a private companyTornettaIf Tornetta hadn't sued for Musk's pay, would SpaceX be structured this way?The banks underwriting the dealWho AGREED TO BUY GROK as a term of getting the underwriting, because everyone bends the knee to moneyThe boardI guess

SpaceX comes to market on 12 June at a $1.75 trillion valuation — 94 times sales, where Amazon trades at four. Simon walks through where to actually buy it (Robinhood, Charles Schwab, Fidelity), why xAI is a rounding error in the AI race, and why Tesla is likely to be rolled into SpaceX within two to three years. Plus the Dow Jones turns 130, Moody's lifts South Africa's outlook from stable to positive, Balwin delists at below NAV with Calgro M3* potentially next, and stocks on the move including Shoprite*, AB InBev, Impala Platinum, and Gold Fields. Topics: SpaceX IPO, Dow Jones, Moody's, Balwin delisting, Calgro M3, Canal Plus, Pope Leo XIV on AI, oil, Shoprite, AB InBev, Implats, Gold Fields, Anglo Gold Ashanti. WorldWideMarkets is part of JustOneLap.com.

Our 246th episode with a summary and discussion of last week's big AI news!Recorded on 05/22/2026Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at andreyvkurenkov@gmail.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:Google I/O highlights included Gemini 3.5 (with 3.5 Flash emphasized for speed and benchmarks), the always-on agent Gemini Spark running on Google Cloud with MCP tool support, and Gemini Omni multimodal video generation/editing, plus updates like Anti-Gravity 2.0, Gemini for Science, and Genie world-model navigation using Street View and Waymo simulation.Coding-agent competition accelerated with Cursor Composer 2.5 (fine-tuned on Moonshot's Kimi K2.5) and xAI's early Grok Build release, alongside discussion of potential Cursor–xAI ties and xAI's talent churn and compute utilization concerns.Business and legal updates included Elon Musk losing his OpenAI lawsuit on statute-of-limitations grounds, reported OpenAI–Apple partnership tensions, Anthropic agreeing to a $30B funding round at a $900B valuation and projecting its first profitable quarter, and Cerebras' IPO surging about 90%. Research and safety stories covered OpenAI's result on an 80-year-old Erdős geometry problem, findings on “negation neglect” in training, interpretability work showing multiple redundant circuits per capability, agent benchmarks like Terminal World, new deepfake takedown enforcement under the Take It Down Act, demonstrations of autonomous hacking/self-replication, rapidly improving AI cyber capabilities, and steps toward image provenance metadata and watermarks.Timestamps:(00:00:10) Intro / Banter(00:01:15) News PreviewTools & Apps(00:05:05) Google unveils AI model Gemini 3.5 and AI agent Gemini Spark(00:11:43) Google's Gemini Omni turns images, audio, and text into video — and that's just the start | TechCrunch(00:17:27) Google launches Antigravity 2.0 with an updated desktop app and CLI tool at IO 2026 | TechCrunch(00:22:35) Google Debuts AI-Powered Tools To Optimize Scientific Research Workflows(00:27:20) Google's Genie world model can now simulate real streets with Street View | TechCrunch(00:29:51) Cursor's Composer 2.5 matches Opus 4.7 and GPT-5.5 benchmarks at a fraction of the cost(00:37:37) xAI Introduces Its Coding Agent Called Grok BuildApplications & Business(00:41:55) Musk loses OpenAI court battle as he waited too long to sue(00:48:08) Anthropic agrees terms of $30bn funding deal at $900bn valuation(00:53:12) OpenAI co-founder Andrej Karpathy joins Anthropic's pre-training team | TechCrunch(00:56:49) Greg Brockman Officially Takes Control of OpenAI's Products in Latest Shake-Up | WIRED(00:58:15) OpenAI-Apple Partnership Frays, Setting Up Possible Legal Fight - Bloomberg(01:01:13) AI chipmaker Cerebras soars 90% in year's biggest IPO so farResearch & Advancements(01:07:10) AI just solved an 80-year-old ‘Erdős problem,' and mathematicians are amazed | Scientific American(01:11:50) Negation Neglect: When models fail to learn negations in training(01:13:18) All Circuits Lead to Rome: Rethinking Functional Anisotropy in Circuit and Sheaf Discovery for LLMs(01:16:20) Autonomous AI research for nanogpt speedrun(01:21:59) TerminalWorld: Benchmarking Agents on Real-World Terminal TasksPolicy & Safety(01:23:15) America's dangerous, messy deepfakes crackdown is here | The Verge(01:25:17) Language Models Can Autonomously Hack and Self-Replicate(01:28:48) How fast is autonomous AI cyber capability advancing?(01:31:32) Positive Alignment: Artificial Intelligence for Human FlourishingSynthetic Media & Art(01:33:15) OpenAI is making it easier to check if an image was made by their models | TechCrunch(01:33:56) How Chinese short dramas became AI content machines | MIT Technology ReviewSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Pre-IPO trading is hot ahead of three big IPOs. Perp volume on Hyperliquid went from $3M to $44M in three months, and SpaceX perps is just the beginning, says Dio Casares of Patagon. ======================================================== Thank you to our sponsor! ⁠⁠⁠⁠Coinbase One⁠⁠⁠⁠: Get 20% off the first year of your Coinbase One annual plan at ⁠⁠⁠⁠coinbase.com/unchained⁠⁠⁠⁠. ======================================================== Pre-IPO perp volume on Hyperliquid grew from $3 million to $44 million in roughly three months. Anthropic and OpenAI voided secondary shares, sending shockwaves through the pre-IPO marketes. Robinhood launched trust-style tokenized offerings into a gray area. And three trillion-dollar IPOs — SpaceX, Anthropic, and OpenAI — are converging in the same window. Dio Casares, founder and CEO of Patagon, a private neobank that has facilitated deals in Anthropic, xAI, Circle, and Kraken, explains the structural difference between derivatives and tokenized spot, why second and third-layer SPV waterfalls are legal hot potato, who actually holds the cleanest title, and where the competition for private market liquidity goes next. Host: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Laura Shin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Host / Unchained Guests: ⁠Dio Casares - Founder & CEO, Patagon Learn more about your ad choices. Visit megaphone.fm/adchoices

SHOW NOTES   In Podcast Episode 376, “When Kindness & Generosity Flow,” Kim discusses the natural flow of encouragement, kindness, and generosity we see in the celebration of the Passover described in today's scripture passage. Today, what automatically flows from your life?   Our focal passage for this episode is 2 Chronicles 35:1-19, and with 14-15 as the focal verses:   14 Afterward the Levites prepared Passover offerings for themselves and for the priests—the descendants of Aaron—because the priests had been busy from morning till night offering the burnt offerings and the fat portions. The Levites took responsibility for all these preparations. 15 The musicians, descendants of Asaph, were in their assigned places, following the commands that had been given by David, Asaph, Heman, and Jeduthun, the king's seer. The gatekeepers guarded the gates and did not need to leave their posts of duty, for their Passover offerings were prepared for them by their fellow Levites.     WEEKLY ENGAGEMENT FEATURE:   Pray Psalm 139:23-24 for yourself, asking the Lord to show you what naturally flows from your heart.   Additional Resources and Scriptures:   23 Search me, O God, and know my heart; test me and know my anxious thoughts. 24 Point out anything in me that offends you, and lead me along the path of everlasting life. (Psalm 139:23-24) Facebook Group - https://www.facebook.com/groups/encouragingothersinlovingjesus X - https://x.com/eoinlovingjesus?s=21&t=YcRjZQUpvP7FrJmm7Pe1hg INSTAGRAM -  https://www.instagram.com/encouragingothersinlovingjesus/ “Encouraging Others in Loving Jesus” YouTube Channel: Check it out at https://www.youtube.com/@EncouragingOthersInLovingJesus   I WANT TO BEGIN A PERSONAL RELATIONSHIP WITH JESUS CHRIST.   RESOURCES USED FOR BOOK OF 1 & 2 Kings (1 & 2 Chronicles) PODCASTS: “The Wiersbe Bible Commentary: The Complete Old Testament OT in One Volume” “Christ-Centered Exposition: Exalting Jesus in 1 & 2 Kings” by Tony Merida “The Tony Evans Bible Commentary: Advancing God's Kingdom Agenda” “Life Application Study Bible” “The Swindoll Study Bible: NLT” by Charles R. Swindoll Holman Illustrated Bible Dictionary “The Baker Illustrated Bible Background Commentary” by J. Scott Duvall and J. Daniel Hays (Editors) Expositor's Bible Commentary (Abridged Edition): Old Testament, 2004, by Kenneth L. Barker, John R. Kohlenberger, III. xAI. (2026). Grok [Large language model]. https://x.ai/grok/chat      "Encouraging Others in Loving Jesus" Facebook Group:   Our Facebook Group is devoted to providing a place for us to encourage each other through all the seasons of life. Follow the provided link to request admittance into “Encouraging Others in Loving Jesus”—https://www.facebook.com/groups/encouragingothersinlovingjesus/ Feel free to invite others who will be good encouragers and/or need encouragement to follow Jesus.   This podcast is hosted by Kim Smith, a small town Country Girl who left her comfort zone to follow Jesus in a big City World. Now, she wants to use God's Word and lessons from her faith journey to encourage others in loving Jesus.   In each episode, Kim will share insights regarding a portion of God's Word and challenge listeners to apply the lessons to their daily lives.   If you want to grow in your faith and learn how to encourage others in loving Jesus, subscribe and commit to prayerfully listening each week.   Remember, “It's Always a Trust & Obey Kinda Day!”   If you have questions or comments or would like to learn more about how to follow Jesus, please email Kim at EncouragingOthersinLovingJesus@gmail.com.     National Suicide & Crisis Lifeline   988   https://988lifeline.org/   Reference: Unless otherwise indicated, all Scripture quotations are taken from the Tyndale House Publishers. Holy Bible: New Living Translation. Wheaton, Ill: Tyndale House Publishers, 2004.   Podcast recorded through Cleanfeed and edited through GarageBand. The soundtrack, entitled “Outlaw John McShane” was obtained from Pixabay.     The HIDDEN Episodes:  If you can't access episodes 1-50 on your podcast app (the podcast was then entitled "A Country Girl in a City World - Loving Jesus"), you can get all the content at my Podbean site at https://acountrygirlinacityworldlovingjesus.podbean.com/  

Elon Musk has launched the largest stockmarket listing in history. The accompanying space mission remains grounded. Our correspondent weighs SpaceX's extraordinary ambitions. The Republican party trades on its masculine image, but some young men are turning away. And, after a blind tasting 50 years ago unleashed a new wave of wine drinking, the market is drying out.Watch extended clips from Insider hereGuests and host:Tim Cross, senior science writerRobert Guest, Economist deputy editorAlexandra Suich Bass, culture editorRosie Blau, co-host of “The Intelligence”Jason Palmer, co-hosts of “The intelligence”Topics covered: SpaceX, Starlink, XAI, Elon MuskDonald Trump, Republicans, masculinityWine, Judgement of ParisListen to what matters most, from global politics and business to science and technology—Subscribe to Economist Podcasts+For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.  Hosted on Acast. See acast.com/privacy for more information.

Elon Musk has launched the largest stockmarket listing in history. The accompanying space mission remains grounded. Our correspondent weighs SpaceX's extraordinary ambitions. The Republican party trades on its masculine image, but some young men are turning away. And, after a blind tasting 50 years ago unleashed a new wave of wine drinking, the market is drying out.Watch extended clips from Insider hereGuests and host:Tim Cross, senior science writerRobert Guest, Economist deputy editorAlexandra Suich Bass, culture editorRosie Blau, co-host of “The Intelligence”Jason Palmer, co-hosts of “The intelligence”Topics covered: SpaceX, Starlink, XAI, Elon MuskDonald Trump, Republicans, masculinityWine, Judgement of ParisListen to what matters most, from global politics and business to science and technology—Subscribe to Economist Podcasts+For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account.  Hosted on Acast. See acast.com/privacy for more information.

In this episode, we examine SpaceX's $2.8 billion investment in gas turbines for XAI data centers, while discussing the implications of ongoing legal challenges. We also explore Google's new AI agent ecosystem, Trump's delay on AI security orders, and the astonishing fundraising success of Hark.Chapters00:00 SpaceX's Gas Turbine Investment02:01 Google's AI Agent Ecosystem09:11 Trump Delays AI Security Orders11:28 Hark's $700M Series A14:32 Anthropic's Profitable Quarter17:09 Industry News Highlights Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articleshttps://www.aichatdaily.com/ai-news

In this episode of Business Brain, we kick off Casual Friday AI with Dave’s pitch to learn Markdown — the plain-text format that every AI engine now prefers. Skip it, and you’re burning tokens (and cash) every time the robots have to wade through bloated Word docs. Then Shannon drops the move that’ll change your week: connect Claude to Slack and let it pull weekly summaries of wins, blockers, and who’s actually carrying the team. It’s the kind of leverage that turns a flood of channels and DMs into one tidy report waiting on your desk every Friday. From there,We dig into Markdown for AI, connecting Claude to Slack, Claude for Small Business, and xAI voice cloning results. we dig into Claude for Small Business, the new Claude Cowork layer that plugs straight into QuickBooks, HubSpot, Google Workspace, Microsoft 365, Canva, DocuSign, and PayPal — your small business operating system, basically. Toggle one workflow on, fix one pain point, repeat. We also revisit Shannon’s xAI voice clone experiment (verdict: too old, too audiobook, needs another pass), and land on the big takeaway driving the Charmed Life right now — connect, connect, connect. The AI tools you already pay for get exponentially more powerful the moment you wire them into the platforms you actually live in. 00:00:00 Business Brain – The Entrepreneurs' Podcast #755 for Casual FridAI, May 22, 2026 May 22nd: Bitcoin Pizza Day 00:01:39 Learn Markdown! 00:05:18 Connect Claude to Slack Weekly summaries Context Whatever you want! 00:07:14 SPONSOR: Whatnot is the largest dedicated live shopping platform. Download the Whatnot app today and get free shipping on your first order. Just search Whatnot in the app store and start scoring amazing deals 00:08:44 SPONSOR: Bitdefender. Keep your small business safe with Bitdefender Ultimate Small Business Security. Save 30% when you go to https://bitdefender.com/BRAIN 00:10:00 Claude for Small Business is your new business operating system AI Fluency for Small Businesses 00:13:52 X.ai Voice Cloning 00:16:29 This Episode's Big Takeaway: Connect AI tools to your existing platforms Business Brain 755 Outtro Check out Business Brain Blueprints Tell Your Friends! Business Blueprints Review Business Brain Subscribe to the show feedback@businessbrain.show Call/Text: (567) 274-6977 X/Twitter: @ShannonJean & @DaveHamilton, & @BizBrainShow LinkedIn: Shannon Jean, Dave Hamilton, & Business Brain Facebook: Dave Hamilton, Shannon Jean, & Business Brain The post FridAI – Voice, Slack & Markdown – Business Brain 755 appeared first on Business Brain - The Entrepreneurs' Podcast.

In this episode, we examine SpaceX's $2.8 billion investment in gas turbines for XAI data centers, while discussing the implications of ongoing legal challenges. We also explore Google's new AI agent ecosystem, Trump's delay on AI security orders, and the astonishing fundraising success of Hark.Chapters00:00 SpaceX's Gas Turbine Investment02:01 Google's AI Agent Ecosystem09:11 Trump Delays AI Security Orders11:28 Hark's $700M Series A14:32 Anthropic's Profitable Quarter17:09 Industry News Highlights Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articleshttps://www.aichatdaily.com/ai-news See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we examine SpaceX's $2.8 billion investment in gas turbines for XAI data centers, while discussing the implications of ongoing legal challenges. We also explore Google's new AI agent ecosystem, Trump's delay on AI security orders, and the astonishing fundraising success of Hark.Chapters00:00 SpaceX's Gas Turbine Investment02:01 Google's AI Agent Ecosystem09:11 Trump Delays AI Security Orders11:28 Hark's $700M Series A14:32 Anthropic's Profitable Quarter17:09 Industry News Highlights Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articleshttps://www.aichatdaily.com/ai-news See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we examine SpaceX's $2.8 billion investment in gas turbines for XAI data centers, while discussing the implications of ongoing legal challenges. We also explore Google's new AI agent ecosystem, Trump's delay on AI security orders, and the astonishing fundraising success of Hark.Chapters00:00 SpaceX's Gas Turbine Investment02:01 Google's AI Agent Ecosystem09:11 Trump Delays AI Security Orders11:28 Hark's $700M Series A14:32 Anthropic's Profitable Quarter17:09 Industry News Highlights Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articleshttps://www.aichatdaily.com/ai-news

In this episode, we examine SpaceX's $2.8 billion investment in gas turbines for XAI data centers, while discussing the implications of ongoing legal challenges. We also explore Google's new AI agent ecosystem, Trump's delay on AI security orders, and the astonishing fundraising success of Hark.Chapters00:00 SpaceX's Gas Turbine Investment02:01 Google's AI Agent Ecosystem09:11 Trump Delays AI Security Orders11:28 Hark's $700M Series A14:32 Anthropic's Profitable Quarter17:09 Industry News Highlights Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articleshttps://www.aichatdaily.com/ai-news See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we examine SpaceX's $2.8 billion investment in gas turbines for XAI data centers, while discussing the implications of ongoing legal challenges. We also explore Google's new AI agent ecosystem, Trump's delay on AI security orders, and the astonishing fundraising success of Hark.Chapters00:00 SpaceX's Gas Turbine Investment02:01 Google's AI Agent Ecosystem09:11 Trump Delays AI Security Orders11:28 Hark's $700M Series A14:32 Anthropic's Profitable Quarter17:09 Industry News Highlights Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articleshttps://www.aichatdaily.com/ai-news See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, we examine SpaceX's $2.8 billion investment in gas turbines for XAI data centers, while discussing the implications of ongoing legal challenges. We also explore Google's new AI agent ecosystem, Trump's delay on AI security orders, and the astonishing fundraising success of Hark.Chapters00:00 SpaceX's Gas Turbine Investment02:01 Google's AI Agent Ecosystem09:11 Trump Delays AI Security Orders11:28 Hark's $700M Series A14:32 Anthropic's Profitable Quarter17:09 Industry News Highlights Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articleshttps://www.aichatdaily.com/ai-news

In this episode, we examine SpaceX's $2.8 billion investment in gas turbines for XAI data centers, while discussing the implications of ongoing legal challenges. We also explore Google's new AI agent ecosystem, Trump's delay on AI security orders, and the astonishing fundraising success of Hark.Chapters00:00 SpaceX's Gas Turbine Investment02:01 Google's AI Agent Ecosystem09:11 Trump Delays AI Security Orders11:28 Hark's $700M Series A14:32 Anthropic's Profitable Quarter17:09 Industry News Highlights Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow Articleshttps://www.aichatdaily.com/ai-news See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

A first on CNBC interview with Nvidia CEO Jensen Huang. How he's thinking about everything from sales in China, the company's $80B buyback, to the feasibility of data centers in space. Then, early SpaceX and xAI investor Peter Diamandis breaks down the bull case for SpaceX ahead of what is projected to be the largest IPO in history. And the U.S. government with plans to take stakes in several quantum companies, including Infleqtion, its CEO joins the show with the details.   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.

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!On the product side, everyone is getting Computer - Perplexity, Manus, Cursor, and so on. Meanwhile on the research side, agentic evals like TerminalBench and GDPVal are also assuming computer (Harbor). On both ends, the consolidating LLM OS stack has become a standard toolkit, and Daytona is one of a small set of AI Infra companies that are booming because of it.“The end of localhost” has been Ivan Burazin's obsession for more than a decade.Something that is all too familiar…Long before agents became the default way people talked about software development, Ivan was already chasing the idea that development should not depend on a fragile local machine. CodeAnywhere, one of the first browser-based IDEs, was an early attempt at that future: move the development environment into the cloud, make setup reproducible, and free developers from the endless “works on my machine” tax.The thesis was directionally right, but the market wasn't ready yet.However, agents changed that. They do not care about a laptop, desk setup, or favorite editor. They need a computer they can access through an API: something stateful enough to keep working, fast enough to spin up instantly, flexible enough to resize, isolated enough to be safe, and composable enough to run the messy real-world workflows that real software engineering actually requires.Daytona isn't just selling “sandboxes” in the narrow code-execution sense. It is the latest version of Ivan's original localhost thesis.In this episode, Daytona's CEO joins swyx to explain why AI agents need more than code execution boxes: they need composable computers, stateful sandboxes, instant startup, dynamic resources, and infrastructure that can survive workloads going from zero to 100,000 CPUs.We go deep on the new agent compute market: Daytona's hard pivot from human dev environments to AI sandboxes, the New Year's Eve MVP that customers begged for, why Daytona runs on bare metal with its own scheduler, how one customer runs almost 850,000 sandboxes a day, and why RL/eval workloads went from 0% to roughly 50% of usage in just months. Ivan also explains why agents need Windows and macOS machines, why CLI may matter more than MCP, why Kubernetes is painful for this workload, and why the future AI cloud may look more like Stripe than AWS.We discuss:* How Daytona grew out of CodeAnywhere, Shift, and the “end of localhost” thesis* Why Daytona pivoted from human dev environments to AI sandboxes* Why agents need composable computers instead of disposable code execution boxes* The New Year's Eve MVP that customers chased API keys for* Why Daytona chose bare metal, stateful snapshots, and its own scheduler* How Daytona spins up one sandbox in ~60ms and 50,000 sandboxes in ~75 seconds* Why Daytona's biggest customer runs ~850,000 sandboxes a day* How RL/eval workloads create zero-to-100,000 CPU spikes* Why RL workloads went from 0% to roughly 50% of Daytona usage* Why customers compare Daytona against EKS/GKS and say they're “never going back”* Why every AI agent may need a computer, including Windows and macOS environments* The Apple licensing constraints that make macOS sandboxes hard* Why CLI gives agents more power than MCP* How open source helps agents integrate Daytona* Why agent-generated PRs may break today's CI/CD assumptions* Why AI SaaS companies reselling tokens may face a cold shower* Why the AI cloud may look more like Stripe than AWSIvan Burazin* LinkedIn: https://www.linkedin.com/in/ivanburazin* X: https://x.com/ivanburazinDaytona* Website: https://www.daytona.io* X: https://x.com/daytonaioTimestamps* 00:00:00 Hook* 00:01:12 Introduction* 00:03:15 CodeAnywhere, Shift, and the end of localhost* 00:05:58 What Daytona is: composable computers for AI agents* 00:08:07 The pivot from dev environments to AI sandboxes* 00:10:17 The New Year's Eve MVP and customers begging for API keys* 00:12:56 Bare metal, stateful sandboxes, and Daytona's scheduler* 00:17:28 60ms startup, 50,000 sandboxes, and 850K daily runs* 00:21:53 Spiky RL/eval workloads and the new agent infra problem* 00:28:12 RL workloads, Kubernetes pain, and dynamic resizing* 00:33:31 Why every AI agent needs a computer* 00:38:48 macOS sandboxes and Apple's licensing problem* 00:44:28 Why CLI may matter more than MCP* 00:48:11 Open source, GitHub stars, and agent integration* 00:53:11 Git, CI/CD, and agent collaboration bottlenecks* 00:58:15 Founder life and building a 25-person infra company* 01:02:44 AI SaaS, token resale, and API-first business models* 01:06:10 GPU sandboxes, data centers, and compute growth* 01:09:48 Why the AI cloud may look more like Stripe than AWS* 01:11:26 Closing thoughtsTranscriptIntroduction: Daytona, CodeAnywhere, and the End of LocalhostSwyx [00:00:02]: Okay, we're in the studio with Ivan Burazin, CEO of Daytona. Welcome.Ivan [00:00:07]: Thanks for having me, man.Swyx [00:00:08]: Ivan, you and I go back.Ivan [00:00:10]: Way back.Swyx [00:00:11]: How I don't even know how, you found, did you reach out or, for Shift.Ivan [00:00:17]: I reached out to you. The reason was you - we were just - we were thinking about I was one of the co-founders of CodeAnywhere, the first browser-based IDE, and so we were thinking a long time of, localhost should die. And you had this article.Swyx [00:00:29]: End of localhost.Ivan [00:00:30]: Then I reached out to you because of that, and then we talked, and I was actually at a different job and learning about I was the head of, developer experience, and you were quite well-versed in that, and I actually reached out to you, among other people, how do we go about that? What are the key things and whatnot at this point in time? And you were nice enough to take the call, and I remember I was late on your call with you.Swyx [00:00:51]: I don't remember.Ivan [00:00:52]: I remember because I was with my then I'm thinking of a girlfriend or wife at that point in time, I'm not sure. It's the same person, so that's great, and I was late ‘cause we were, in, Italy on, vacation, and then I was late for something. I felt so bad, and you were so nice to be, good about.Swyx [00:01:10]: The reason I'm nice is because I'm also late to other people, so it's like, who's, who's without sin here, yeah, so I have to, for those who don't know, InfoBip Shift, there's this whole thing that, you did in the past, and, and that was basically one of the inspirations for me starting AI Engineer, which is like, I have to thank you for giving me that push to be like, “Oh, you can, you can build and sell conferences?”Ivan [00:01:34]: I remember you asked you asked me at the beginning to give me advisory shares, and I was so focused on what we were doing, I said no, and I should've took the advisory shares. So I'm sorry, dude. But anyway.Swyx [00:01:43]: We're not, we're not venture backed.Ivan [00:01:44]: No, it doesn't matter.Swyx [00:01:45]: It's Yeah, anyway, so I think what's impressive about you is that CodeAnywhere is the thing that you've been trying to build, and, you kind of put it on hold and then came back after InfoBip. Just give us the story, do you - the story and the origin story, going into Daytona.From CodeAnywhere and Shift to DaytonaIvan [00:02:05]: Sure. Like, really way back, me and my co-founder have been together. I say this, I've said this multiple times, it's like we were married and divorced and married. Some people actually ask me is my co-founder my partner. they thought it literally. It's not literally, but we have done multiple companies together, and to your point, we had this shift where we went from the CodeAnywhere to the conference called Shift, and then back to, Daytona. We originally started stacking servers, doing like virtualization in the early 2000s and, routers and doing basically all these things, at a foundational level, and that was a services company which we sold to focus on what my co-founder actually invented, which was the very first browser-based IDE, right, I say the first. Before us was actually Heroku. They did it for a very short time until they became Heroku. But outside of them, we were the only one, and it was called.Swyx [00:02:55]: There was Cloud9.Ivan [00:02:57]: Cloud9 came out slightly after us. There was Replit, which came out when we stopped doing it, Replit came out, and they have been successful since then, which is great. There was Nitrous.io. There was quite a few that existed at the time, but it was like too early. But the interesting part is that we, at that point in time, because there was no VS Code, there was no Kubernetes, and Docker had just started when we Or I'm not sure if it was even public at that point in time. And so we had to build everything to the whole stack ourselves and that was the key learning that we brought into and that we've been using in Daytona today. So it was super early. There's about 3 million people used CodeAnywhere. It was slightly, it was angel-backed more than venture-backed. We ended up paying everyone back because it didn't have that sort of scale. But, three years ago, we started something similar with Daytona, which is not what we are today, but it was automating dev environments for human engineers, the basically the underlying stack of CodeAnywhere. And then we did a hard pivot last January to sandboxes. And so here we are.Swyx [00:04:01]: Historic pivot, yeah, and, it's one of those things where, I had independently invested in CodeAnywhere, but also in E2B, and then both of you pivoted into the same thing, and I'm like, “F**k.”Ivan [00:04:12]: You invested, you invested in Daytona. You invested in Daytona. But you were the first If we had not got your check, we wouldn't have done it.Swyx [00:04:18]: No way.Ivan [00:04:19]: No, it was like, “We have to get him on board first,” and you were that kicker that we, that got us off the ground.Swyx [00:04:23]: No, because you were putting me on your pitch deck, man. I was like, “Man, this is like a good trip if I don't invest.”Ivan [00:04:29]: That's because it was your quote. It's like we.Swyx [00:04:30]: Yeah. It's the end of localhost.Ivan [00:04:31]: Did a bunch of research about end of localhost and who was interested in that,.Swyx [00:04:34]: No, that's like, I put, I wrote that blog post, and every single company in that field reached out to me, and then every VC who was receiving those pitches then also had to call me and, talk it, talk through it with me.Ivan [00:04:47]: It's finally happening though.Swyx [00:04:48]: It was really super interesting.Ivan [00:04:48]: It's finally happening.Swyx [00:04:49]: It's finally happening.Ivan [00:04:49]: Yeah, it's finally.Swyx [00:04:49]: It's finally happening, with maybe sort of non-human users. Yeah, so what is Daytona today? Let's get like a quick description. I'm wearing the shirt.What Daytona Is Today: Composable Computers for AI AgentsIvan [00:04:58]: You're wearing the shirt. Yes,.Swyx [00:04:59]: It says, I think your branding is very good. Like, it's very consistent. It runs AI code. Like, it cannot be simpler.Ivan [00:05:05]: Exactly, but we're gonna probably have to change that.Swyx [00:05:07]: Oh, s**t.Ivan [00:05:07]: It's also a subset of what we do. Unfortunately, we really love this, Run AI Code is super simple. People interpret it different ways. I think we've given out 5,000, 6,000 of these shirts. People wear them with pride because it doesn't really market about us.Swyx [00:05:21]: Yeah, Daytona's on the back.Ivan [00:05:22]: It markets the back. It markets to the person itself, so I think we did a really good job on that one. But it is also a subset of what we do, because people, when they think about Run AI Code, they just think about these small, let's call it isolates, code execution boxes that, you send some code, you get an output. Whereas what Daytona is today is essentially composable computers for AI agents. It is, the market calls them sandboxes which can be misleading.Swyx [00:05:44]: All these things. All these things on.Ivan [00:05:45]: Yeah, exactly, ‘cause it can be misleading ‘cause people usually think about sandboxes as a demo or a test environment versus a production-grade environment. But what Daytona does, if you think of the laptop that you have in front of you or the computer that's over there, or, my wife is an architect, so she has like a Windows with a 3D graphics card inside to do 3D rendering. Like, as humans, we have different computers or different compositions of computers. And our belief is strongly that agents today and going forward will need all these different compositions of computers to do different types of tasks. And so we offer that basically through an API.Swyx [00:06:19]: Yeah, to give people - I'm trying to sort of front-load all the aha moments or the wow moments so that people can, stay engaged and click like and subscribe. the market is exploding, right? Like, you have been reporting 74% month-on-month growth, and it also, it's just been growing for a while. Like, it's been going like this. And every single - It's not just you guys. It's every single.Ivan [00:06:41]: Everyone, yeah.Swyx [00:06:42]: Sort of, compute provider. I don't know if you agree with me saying compute provider or not.Ivan [00:06:48]: It's fine.Swyx [00:06:48]: Yeah. So like organically PLG-driven growth, but also enterprise is doing super well, I think I wanna rewind to January of last year when you did the pivot. Like, so you obviously called this market early, and you were positioned for it, and you are now one of the market leaders. But what was the insight that made you do the pivot?The Pivot: From Human Dev Environments to Agent SandboxesIvan [00:07:06]: The insight that made us do this pivot is the quarter before that, so end of 2024, when we had - Basically, we did a demo with - I don't I think we discussed this as well, Devin was not public. You actually gave me access to Devin at that time. So Devin.Swyx [00:07:25]: I did?Ivan [00:07:26]: Yeah, you gave me access.Swyx [00:07:26]: I don't think I was supposed.Ivan [00:07:27]: Yeah, exactly.Swyx [00:07:28]: Yeah, I.Ivan [00:07:28]: So it doesn't matter. You.Swyx [00:07:29]: Yeah. I gave like three friends access.Ivan [00:07:31]: Yeah, or it was a call and you showed it to me. It doesn't matter. but OpenDevin was available, which is now called OpenHands. And so we're like, “Oh, this seems to be a thing. This is not public. Let's take our for human automation of dev environments and take, OpenDevin and launch that as a SaaS.” And we did that. Not very many people signed up and used it, but a lot of people reached out that were building agents, and they were like, “Hey, my agent needs a compute sandbox runtime,” whatever you wanna call it. I forgot what it was called at that point. And then we were like, “Oh, amazing. This is a new market. Here is our infrastructure. Here's our product, and go.” And what we found really fast, soon, was that people did not like what we had built. It didn't work. And I remember talking to people at the beginning when we're doing this, the sandbox we're building for agents. People were like, “Oh, why is it different? It's the same thing. We have like EC2, we have VMs, we have all these things.” But we saw that everyone we gave it to, it was like 20, 30 people, they all said, “No.” Like, “This is not what we need. This sort of breaks.” And basically, me and my co-founder not knowing a lot about - ‘cause we're infra people. We're not AI people. So I basically took it upon myself to like watch every single podcast that exists, including all of, all of these and all that, and sort of get up to date, read all the blogs, like get, understand what's going on.Swyx [00:08:45]: Do you wanna shout out who else was useful, just in case people are also looking.Ivan [00:08:49]: Generally we -, I looked at There's a few of podcast, different segments and different types. So there's you guys, No Priors, Bill Gurley's was great while.Swyx [00:09:04]: VG2, yeah.Ivan [00:09:05]: Yeah, while it was around. So there's a few. 20VC is interesting from a different dynamic, and some are different dynamic. But there was, also Red Points.Swyx [00:09:14]: We're not really about the compute market.Ivan [00:09:15]: It was also already - Sorry?Swyx [00:09:16]: You're, you want - You're looking at the agent infra market.Ivan [00:09:19]: I was looking at the agent market and the AI market in general and sort of understanding who are the players, what the perception, and how that goes. And like obviously you complement this with like going to conferences, going to events, going to meetups, reading white papers, like doing all the things that you have to do to understand what's happening. And so when we figured, when we sort of had an idea of what we had to build, literally over the New Year's Eve, literally on New Year's Eve, I half vibe coded the first MVP, first minimal viable product of what Daytona is today. And I went to sleep at like 3:00 AM or something like that. I was doing - I just put my like baby daughter and wife to sleep and, Happy New Year's, and go back to just, doing this. And I sent it to my co-founder, my CTO, and he saw it in the morning. He's like, “This is absolute garbage.” “Do not show this to anybody at all, but the idea is good.” And so he took two weeks, and he rebuilt it.Swyx [00:10:09]: Did it like look like that? Listen, I - It was rough idea.Ivan [00:10:12]: Oh, not even, not even close. Like it was it was way worse. But it was like a very - It was a simplistic view of what it should be. Like, it worked, but it was not ideal. And so he went, we went down the whole, which is his job as CTO, to go, and he came back with this version. We then called all the people that had said like, “This is garbage,” a quarter ago. And we set up these calls, and we gave it to - We just demoed it to everyone. And all the calls went long, every single one. They were 15-minute calls, and they all went to like 25, 30 minutes or whatnot. And everyone said, “We need, we want access.” There was no login, just an API key, ‘cause it was just a beta or an alpha. And they said, “Oh, we want access.” And we're like, “Sure, yeah. Okay, thank you very much.” But after like the next day, if we'd not send it, every single one, like every call that we did, everyone came back, “Where is my API key?” Like everyone wanted it. We're like, “S**t.” Like this is it. Like I've never felt So one, the understanding to your point was like most people thought it was the same infrastructure for humans and agents. We understood a quarter ago it's not. We just didn't know what was the right primitive. And then when we came, and we can talk about what that is, and we gave it to these people, I've never seen, I've never experienced - I've done multiple companies in my life. I've never experienced this, that people literally call you if you do not give them access. Like they want access right now. And so it's like, okay, they don't want this. the thing that they want doesn't seem to exist, or they have not found it, and they really want what we want. And then when we understood that we're onto something, and then when you think about the size of the market, like the market for human engineers and enterprise is a very large market, so think GitLab or whatnot. But the market for every single agent that will exist ever in the future is just like, what is that market? How big is that? And we're like, “We are all in on this.” And so that is where we made sort of the cut between the old product and the new one.Bare Metal, Stateful Sandboxes, and the Lambda + EC2 ModelSwyx [00:12:02]: Yeah. But it wasn't composable at the time?Ivan [00:12:05]: It was very - It was basically just a Linux box that you could change, that you could define number of CPUs, disk, and RAM. Like that is what you could do, but you couldn't have multiple operating systems, you couldn't resize it on the fly, you couldn't add a GPU, you couldn't do like all the things. It was just the, just the first sort of variation of that, yeah.Swyx [00:12:22]: Was it bare metal from the start?Ivan [00:12:24]: It was bare metal from the start. And so the interesting thing that we thought about right away, so our.Swyx [00:12:29]: Which, give people the background, what is the normal path?Ivan [00:12:32]: Yeah, so, basically most providers run this on top of VMs. And also.Swyx [00:12:37]: Firecracker.Ivan [00:12:38]: Yeah, they run on Firecracker and VM. And so we also fire - We can get - We have multiple isolation layers and we can do that. But the common way to do it is that they, one, that the state of the machine, or the hard disk is not part of the sandbox itself. And the other thing is they're not meant to last forever. So most of them are preemptible, like they can There's a time that they can live. And so our thought was when we were going into this is, agents will be like humans in the sense of you don't want your laptop to be shut down until you're done with work. Like, and you want to close the lid and open the lid, it's the same state. So you - Agents would want that, like the pause and come back. They want those two things. But also agents really want speed, right? Can they get it? So when we thought about it's like we need something insanely fast, how to make it fast, how to make it long-running, and stateful. And so those two things, it's like combining a Lambda and an EC2, right? Those two things together. And so we didn't have an idea how others did it, ‘cause we didn't know too that there was a market around this. It was more like, okay, this is what we need, what they need. And we looked at Kubernetes, it wasn't wasn't good enough for that. We looked at Nomad, it didn't enable that. And so our history in rewriting our own scheduler at CodeAnywhere is basically what my CTO came up with. Like, he's like, “Oh, the learnings from there,” and he brought it. And the funny thing is, our third co-founder, when he saw it, he's like, “Dude, what is this? This is like 2008.” Like, we went back in time, and he's like, “Exactly.” And so the reason why Daytona is like super fast, and you see this on benchmarks, is we essentially, we run on bare metal. We have our own scheduler, we use the underlying, disk, CPU, and RAM of the underlying machine, which means your IOPS are insanely fast because there's no, there's no network between an EBS or something like that. But also the snapshot, the point in time, the templates, are also preloaded on the bare metal machines. So when you fire off a sandbox from a template or a snapshot, you're essentially directed to the bare metal machine where that snapshot is based on that NVMe drive, and then it literally just turns on that machine, and it's local. There's no network latency, anything on there. And so that is sort of the specificities that we, when we're thinking from first principles, what a computer would look like for an agent, that is what we came up with, and that's what we created.Benchmarks, 60ms Startup, and 50,000 SandboxesSwyx [00:15:02]: Yeah. I should maybe, I don't know if you endorse this, but there's someone that does compute SDK, you guys do very well on there, with like the TTI, right? I. is this a, is this a is this a relevant benchmark for you guys? I don't know.Ivan [00:15:16]: I don't know, and it changes every day. So today RKL is.Swyx [00:15:18]: I don't know what RKL is. Never heard of it.Ivan [00:15:20]: Yeah. RK, yeah, so it is there.Swyx [00:15:22]: You are, at least a third of the next tier of performance, and then, there's a lot of other better-known names that are very slow to start.Ivan [00:15:31]: Yeah. We've been the number one by far for a long time, and now there's different, there's different definitions also of sandboxes, different isolation patterns, different other things. So RKL runs it literally on the S3, the data, so it's very different, and they spin up a sandbox, spin up a container for that, so it's a different type of thing. So the definition of a sandbox is something that we can all, we all need to get along with. But yeah, we're insanely fast on getting these things, up and running. And so you can see even there that it's a zero point 0.10 to 0.11, so.Swyx [00:16:03]: Close enough. Yeah. what else do you need, right?Ivan [00:16:05]: Yeah. So the benchmarks itself, so, in this, in I don't think the benchmarks equate to market ownership or revenue or anything like that. and I've seen this with multiple benchmarks, not just in sandboxes, but in general benchmarks around.Swyx [00:16:20]: It's table stakes. It's just like.Ivan [00:16:21]: Exactly. But it doesn't hurt.Swyx [00:16:22]: Just roughly check.Ivan [00:16:22]: Like you definitely have to be up there and you have to be competing so that people know that, oh, this is definitely one of the top. Because this is only one dimension of what customers look for. There's other things like how many can you spin up consecutively? There's a feature set, there's support, there's like all different things that people look at, but you definitely have to be there, on the benchmarks.Swyx [00:16:40]: How many people do people spin up consecutively?Ivan [00:16:43]: So we have.Swyx [00:16:43]: Or concurrently, is the Concurrency, right?Ivan [00:16:45]: There's three metrics that we look at. And so one is like time to spin up one, and so our time to spin up one is 60 milliseconds with network latency. So request, spin up, reply, 60, the whole thing, 60 milliseconds. That is one. But if you wanna spin up 50,000 at once, we are now at about 75 seconds. So it takes about 75 seconds to spin up concurrently 50,000. Some others, there's public data around this, like take 2,000 seconds, which is 30 minutes. Like there's different variations of that. And then there is the so it is speed of one, speed of like multiple, and then how many can you consistently have up and running. And so we basically have right now no limit to how much we can add because we basically own our own metal. But the biggest customer of ours does like about 850,000 every single day is sort of where they're, where they're just shy of a million every single day that they're running, we do have a request for half a million concurrent, which is literally half a million CPUs somewhere running. So that's an interesting.Swyx [00:17:44]: They pay by like vCPU seconds.Ivan [00:17:47]: By seconds, yeah.Swyx [00:17:47]: Or whatever. Yeah. Okay, and so and then, and the other thing is, the sleeping and the resuming, ‘cause it's all the stateful resumption of all these things, how, what kind of workload are people putting through this, right? Like how is it Do we measure by gigabytes in memory, gigabytes in storage? I don't In like network attached storage. I, what are the costly ones of, out of all these features?Workload Economics: CPU, RAM, Network, and StorageIvan [00:18:15]: The most expensive thing are CPU.Swyx [00:18:18]: Okay. Yeah, of course.Ivan [00:18:18]: The second one, yeah Then it's RAM, then it's disk. We actually don't charge.Swyx [00:18:22]: Which is snapshotting, right?Ivan [00:18:23]: No, it's actually the, snapshotting's part of it, but basically the size of your hard disk, of your machine. So do you have 10 gigabytes, do you have 20, do you have 50, do you have whatever? And then the transference of that. Right now, currently we don't charge for, network at all at Polychron.Swyx [00:18:37]: Oh, you gotta, yeah, you gotta fix.Ivan [00:18:38]: Yeah. It is very much a it's a larger and larger part of our bill, so we're working around, that part there. Obviously, that is the least, expensive, so the hard disk is the least expensive, so it's basically CPU, RAM, for us network, ‘cause we don't charge the customer, and then hard disk, is how it's split up. But there's also different types of workloads, so we basically split it up into two types of workloads in Daytona. One is what we call background agents or long-running agents. and the other is, basically RLs and evals, which I put sort of together. And so they have very different patterns of usage, and if you look at the usage of a background And I'll just name names of companies, not specifically.Background Agents vs. RL/Evals: Two Usage ShapesSwyx [00:19:21]: Yeah, open, all hands.Ivan [00:19:23]: Yeah. So like a background agent's a Cognition, a Lovable, a like all these things are Harvey. These are all long-running, background agents. And so if you look at their usage patterns, their usage patterns are similar to human, which is like follow the sun. Basically, the usage patterns of that is like noon is probably the highest, and the midnight is the lowest, and then weekends are lower. weekday is higher.Swyx [00:19:42]: Yeah, that's a fun question. How global is it? Is it very US-centric or?Ivan [00:19:46]: The US is a large part, but we have currently, we have Asia, Europe, and the US regions.Swyx [00:19:52]: So it's quite global.Ivan [00:19:53]: Yeah, it's quite global. We have it all over. It's interesting that our I talked to you a bit about this. Our number one city by user.Swyx [00:20:01]: Hmm.Ivan [00:20:02]: Is Singapore.Swyx [00:20:04]: Oh, wow. Amazing.Ivan [00:20:05]: Which is an interesting one, right? Not by revenue, just by just like by individual head count.Swyx [00:20:09]: Really?Ivan [00:20:09]: Just like an interesting thing.Swyx [00:20:10]: Singapore is, Singapore is weirdly high in the adoption charts of AI for the population. It's like an, seven, eight million population. And it's like keeps showing up.Ivan [00:20:20]: No, it's quite interesting. We were quite shocked, and I was like, “Oh, this is interesting.” And also one that's up there.Swyx [00:20:24]: There's a reason I'm doing AI using Singapore. it's because I'm from there.Ivan [00:20:27]: We're there. We're gonna, we're gonna be there as well. and it's interesting that Japan is in the top or like Tokyo's in the top, which is in all the tech cycles it has never been. It has never been, so it's quite interesting that they're.Swyx [00:20:39]: I think the Japanese just love AI. Yeah. It's that, and then it's Brazil. That's it.Ivan [00:20:44]: Brazil has always been in.Swyx [00:20:45]: I think.Ivan [00:20:46]: Even when I look, if you look at like GitHub's data and ask historically with CodeAnywhere, it was always like US, Western Europe, and then you'd have like India, Brazil, China, like that would be there. But like Singapore was not in, specifically Japan was never in sort of that top, that top.Swyx [00:21:01]: Yeah. Weird pockets.Ivan [00:21:01]: Weird. Yeah, so it's very global.Swyx [00:21:02]: Okay, so actually that, but that's helps you to distribute your load through, all time?Ivan [00:21:08]: The interesting thing is like we have those kind of loads, but if you look at the researcher loads, they're quite different. So what they are is like if you give them concurrency of 10,000 or 50,000 or 100,000 CPUs at ARMb, when they fire off a run, it's just 100%. And then it just runs, and then it stops. So it's very, the usage pattern is squares basically, right? And it's also not follow the sun, because people will fire it off at midnight before they go to sleep but then wake up and so it's very unpredictable, so you don't know where that is. So the shapes of the usage are quite different than we have had before. And also what's interesting is when it's sort of a follow the sun, even if you have a high growth company, you can sort of predict your usage patterns and have enough capacity for that, because it's sort of, it grows in a, in a way you can project. When you have companies doing sort of like evals and RL, they're super spiky. So they're gonna come in, it's like, “We're gonna use nothing, then can we have 100,000?” Right? And then go back down. And then 100,000, go back down. So it's very different, right? And.Swyx [00:22:09]: Do you want to lock them into commits so.Ivan [00:22:11]: Yeah, we do.Swyx [00:22:12]: Yeah, okay.Ivan [00:22:12]: We so we have to lock them into some sort of commits to have that capacity, because we have to have, basically we have to have the capacity for peak. Right? And so right now, Daytona's mean utilization is 15%, 1-5.Swyx [00:22:25]: Oh my God.Ivan [00:22:26]: So it's very low.Swyx [00:22:27]: Because it's very spiky.Ivan [00:22:27]: It's very spiky, but we get up to 90%. so we have these things. And so what we're, what we're looking at right now as a company is similar to Cloudflare where you can like geo move things around, but that works really well for basically the background agent where it's follow the sun. But this, it's not. Like it's a very different shape. Obviously with scale you figure these things out, but that's an interesting new problem that we have, as a compute provider in the agent space. And when we were doing the conference recently, and so we talked to like Nikita from Neon and.Swyx [00:22:57]: I should bring it up.Ivan [00:22:58]: Parag from Parallel and whatnot, everyone has the same problem. Whereas the usage is super spiky, and this is something that has not happened before, that you have these types of like it was always, it the amplitudes were not this high, right? So it's quite interesting use case and problem solve.Compute Conference and Spiky Agent InfrastructureSwyx [00:23:12]: Yeah, I don't know if we're gonna bring this up again, but let's just talk about the conference, you had like 1,000 something people at the Warriors game, at the Sorry, where is it? What's.Ivan [00:23:22]: Chase Center.Swyx [00:23:23]: Chase Center.Ivan [00:23:23]: Chase Center.Swyx [00:23:24]: I went. It was, it was very impressive. Obviously, you can, how to throw a conference, what did you learn? you put, you pulled together all these impressive names.Ivan [00:23:33]: What I.Swyx [00:23:34]: What were you looking for?Ivan [00:23:35]: My thesis behind the Compute Conference was let's bring together people that are building infrastructure for AI agents. Because when I think of what we're building, it is the agent is the primary user, what are the ergonomics and usage patterns of agents, and so we can do that. And what I found, this was a theory, it wasn't proven, is that we all have these problems, as I touched onto. And I was, as I was talking on stage, it was like we all have the same underlying infra problems, which is this spiky workloads, unpredictable workloads that we've never had before, in human, compute or human infrastructure. And it's, again, it's the same when I was talking to Parag or when I was talking.Swyx [00:24:20]: Lynn. Nikita.Ivan [00:24:21]: Lynn, Nikita. Lynn especially, I was talking to her the other day as well. Like the It is a very interesting type of problem to solve because I can touch on Cloudflare because there's a lot of like talk about that recently as to how they solve that, which is they have a bunch of geos, and basically, as users work in different places, and depending on your tier, they can move you around the geos. And so that how, that's how they get the higher utilization. But you can sort of predict these, and it's If it's something in You'll rarely get a spike that is 10 orders of magnitude. Like you'll get a like let's say one of your customers has some like an exponential curve. What is that to I'm using Cloudflare as an example. 10%, 20%, whatever it is. I don't, I don't have this data, I'm just assessing. It's surely not 10x, right? It's surely not something there. And so how do you go out and solve this problem? And we're all solving this in different ways. So we have.Swyx [00:25:11]: She also has the same thing.Ivan [00:25:12]: Yeah, I know specifically that like Neon had that issue as well. Like how are we solving these spiky loads and things like that ‘cause we talked about it. And so the interesting thing for me to actually internalize was, yes, everyone that's building for agents first is going through this, and we're all solving similar problems, which is quite.Swyx [00:25:28]: Let me let me double-click on this. Okay. So for example, Neon, I happen to know that they're very sort of S3 oriented, right? so they're just like fully bet on S3. And you get to benefit from S3's distribution and infrastructure. So I would imagine that Neon doesn't have to care, whereas Lynn maybe has to care a bit more because obviously she's doing GPU inference. And, for listeners, we did an episode with her, one and a half years ago. And you have to care. But like, right?Ivan [00:25:54]: Parag cares for sure, and Nikita.Swyx [00:25:58]: And Parag is C of, Parallel.Ivan [00:25:59]: Parallel, yeah.Swyx [00:26:00]: Former CTO of Twitter.Ivan [00:26:01]: Twitter, yeah.Swyx [00:26:02]: They are the search.Ivan [00:26:03]: Yeah, they're search, yeah.Swyx [00:26:03]: I You and I know but the listeners don't know.Ivan [00:26:08]: Yeah, we can put it down in the screen, and so ‘cause we, when we were talking.Swyx [00:26:11]: I'll put it up on the, on the screen.Ivan [00:26:12]: Yeah, right.Swyx [00:26:12]: People can look it up if they need.Ivan [00:26:14]: Look it up. And, yes, but they still have CPU and RAM, allocation that you have to have up and running. And so CPU and RAM, you have to allocate that and have that ready. And so there's basically two ways to do it. One is you either over-provision and you can handle the bursts, or two, you basically have, I don't know if this is a term, just-in-time compute, which is like as your load becomes, as your usage comes in, you can fire off requests for VMs or bare metals at other cloud providers and then get them up and running.Swyx [00:26:43]: This is if you go above 100%, right?Ivan [00:26:45]: Yeah, this is.Swyx [00:26:46]: Like your overflow.Ivan [00:26:46]: If your overflow, like spillage or whatever you do.Swyx [00:26:48]: You probably lose money on it, but it doesn't matter, right?Ivan [00:26:50]: It, not Well, you might, you might not That is a more cost-effective way to do it but it's a slower way to do it. Because basically what you have to do is you have to like queue your requests, spin up these just-in-time compute, get it all ready, provision it, and then get your workload there. And so if the time isn't important that much, that's fine, and you can do that. But if your customer, and especially for, let's say, the RL training runs, the reason why a lot of people come to us is because GPUs are more expensive than CPUs, right? So you want your GPU running at, what, 100% the entire time. And so when you're running runs on CPUs, when the when the CPU cycle is like down and spinning up the next one, you want that to be instantaneous so that your GPU doesn't go down, right? And if you then have to like go out and provision machines, you're essentially telling the GPU that it has to wait, and that's incurring our cost. So there's things that you have to try to solve for there.RL Workloads, Declarative Images, and Kubernetes ReplacementSwyx [00:27:43]: Yeah, let's talk about the different workload, right? You said that, what was it? A few months ago, you had zero RL workload and now it's 50%.Ivan [00:27:52]: It will be this one, 50%, yeah.Swyx [00:27:54]: Let's talk about how different it is, right? Like I imagine, for example, a lot less dynamic code generation of like arbitrary code. Like here, it's probably all the same code. You're just doing parallel runs or something, I don't know.Ivan [00:28:05]: Yeah. So you'll have multiple Depends on the like for each run, you'll have a snapshot. And they, for the most part, they actually do use our declarative image builder, which is like, “Oh, we, the agent wants these dependencies, these env vars.”Swyx [00:28:17]: These ones, yeah.Ivan [00:28:18]: Yeah, the declarative image builder, it.Swyx [00:28:20]: Which is a very modal like thing that they.Ivan [00:28:22]: Yeah. And so we build it on the fly and then we propagate that snapshot, and you can spin up as many sandboxes as you want against that snapshot. And then if you have to do changes, the model can, or like it could be also be automated. It's like, “Oh, now for the next run, we need to install these things or remove these things or whatever to get, a task done,” and then it goes off and runs that. So yes, that is something that it seems that they prefer. The number one reason I found, or should I say, let's take a step back. What we are competing against in that environment is essentially managed Kubernetes. So EKS, GKE, whatever. That is what the vast majority run on. And anyone that has tried Daytona versus GKE, EKS is like, “I'm never going back.” That has always been. There's a few reasons. One is the ergonomics. So if you have, if you're using Kubernetes to spin that up, you have to essentially manage the interface interactions with that. Daytona, although as a compute provider, it's more akin to a Twilio and Stripe from a consumption perspective than it is an AWS. Like you have an API, an SDK, it's quite like easy and seamless to get these things up and running, that's one. The other is the speed to which we spin up, which we mentioned earlier, which is much faster, and the scale to which we can go to. We haven't got into features, but an interesting feature is that it's very hard to OOM, or out of memory, our sandboxes, because we can dynamically on the fly.Swyx [00:29:48]: Resize.Ivan [00:29:49]: Resize, which is like impossible on almost any other thing. There are some technologies that enable you to do that, but it's like a very hard thing. And so we actually saw this when, the Terminal Revenge team is, brought us actually. So thank you, Alex and the team, that brought us into this whole space.Swyx [00:30:05]: It's just very rare that, a framework would just say, “Guys, just use Daytona.”Ivan [00:30:11]: Yeah, I think it says it somewhere. Yeah.Swyx [00:30:13]: Yeah. I was like, “What is this?”Ivan [00:30:15]: There's all, there's multiple there, but they also mention a few other places. and so Daytona specifically-We have, the, just jumping on themes here We, I don't know where it says Data Center.Swyx [00:30:27]: I, there.Ivan [00:30:27]: Doesn't matter.Swyx [00:30:28]: There's a very strong recommendation, which is, very unusual. Which is, it's.Ivan [00:30:33]: We do not pay them for this, just.Swyx [00:30:34]: I know, yeah. They just like you.Ivan [00:30:35]: Yeah, they like us. yeah, and also a thing, so, Data Center has multiple isolation sets underneath. The customer doesn't have to know what they are. But basically we have Docker, which is a container, that's hardened with Sysbox. So it's Docker's, isolation that is a security equivalent to a VM, but it's still a container. And that is the default, and they, especially in these training workloads, really like that as an interface to be able to use just a basic Docker container, and we enable Docker and Docker. Which for these RL runs, if you need to do a Docker compose or Kubernetes, you can spin up a K3S inside of these things, which unlocks a huge amount of workloads that you can do that you cannot do on other providers. So just on that part is much more interesting. And so we went that, through that. We showed them that we could do that, and they enjoyed that quite a bit. They being the general venture people.Swyx [00:31:28]: Those people, yeah.Ivan [00:31:29]: And Harbor people.Swyx [00:31:29]: Harbor people, do are they, are they a company yet?Ivan [00:31:33]: As far, I do not know.Customer Pull, Slack Connect, and the Computer Use BetSwyx [00:31:35]: Okay. All right. Yeah. It's like super obvious that like, there's a lot of excitement and success around these things, okay, so yeah, tell us more, right? Like, this is an exploding workload, Harbor adopted you, which helped speed things along. But what are you learning as this new workload comes online?Ivan [00:31:53]: There's a couple things that we learned, which we chat about in the beginning. We, and this has led our story, as we mentioned, we like talked to a lot of customers along the way, and we add more features and more tool sets as we talk to customers. And it's interesting that And I think it's that the ecosystem is so small and/or the models get smarter, where when we see one user come with a request, we know it goes on a roadmap if like three to five customers come with the same request in that week. It's like very bizarre. It happens so many times, which is.Swyx [00:32:27]: Because they're all friends.Ivan [00:32:28]: Sorry?Swyx [00:32:28]: They all, they're all friends. They're all in the same group chat.Ivan [00:32:30]: Yeah, probably, yeah. ‘Cause and they're like, “Oh, can you do this?” And I'm like, “Okay, this is interesting. We'll put it on a feature request.” And then the next one's like, “Oh, can you do this?” “Okay.” It's all the same, right? It's always the same. And so what we try to do, and I personally try to do, I try to be on as many call, quote-unquote “sales calls” I can. I'm in every Slack channel. We literally have about 1,000 Slack Connect channels, something like that. It's an interesting, there's so many interesting things you find out when you have all the Slack channels. You can also see where people, transfer between companies. You see leave Slack channel, enter Slack channel. It's an interesting thing. Also, just I digress, I feel that Slack Connect is literally LinkedIn what it should be. You have a list.Swyx [00:33:08]: LinkedIn charges you to, use your own connections, but Slack doesn't, right? Slack is like, do it for free. It's more lock-in. It's great.Ivan [00:33:15]: Yeah. It's amazing. Yeah. It's one of the reasons.Swyx [00:33:17]: You're gonna pay Slack for life.Ivan [00:33:18]: Exactly. You're there for life. So that's interesting. And so one of the things, the newer things we were talking about earlier is we made a big bet and put a lot of investment on computer use. that is not seen publicly the light of day. We haven't GA'd that yet, but we have.Swyx [00:33:32]: Is there a thing I can pull up?Ivan [00:33:33]: There is computer use there. It's right up a bit.Swyx [00:33:36]: Oh, yeah. Okay.Ivan [00:33:38]: What we have, what we talked about and what we've seen publicly is there's this theme now about, the human emulator where And Elon from XAI has talked about this publicly, and if you think about the models today, they're actually quite sophisticated and they can do a lot of work, but they still don't have access to all the tools. Like, I'm a strong believer that the most efficient way for an agent to work is essentially headless or through, terminal or whatnot. But if we, if we look at knowledge work in general, there's about 100 million knowledge workers in the US, about a billion in the world, and knowledge workers, and the salaries of them aggregate to 10 trillion in the US 50 trillion worldwide.Swyx [00:34:24]: Wow.Ivan [00:34:25]: Something like that. And if we look at, the five most important sectors of that, so like healthcare and government and financial services and whatnot, that's about 56% of that. So let's say it's about half of that. So in the US it's about 25 trillion, and most of them, most of that work is actually still locked into legacy apps inside of Windows, which is not going anywhere for a very long time. Like, people just won't invest in that. How much of it? our assumption is the following: if, in the RPA market, which is similar market, well, not the same 25% of, these white collar, workers', work is automated. If an agent is more sophisticated, can go through more runs, figure stuff out, let's say it's, 40%, right? And so if you take 40% of that, you get to essentially, $10 trillion a year.Swyx [00:35:17]: That's a TAM.Ivan [00:35:18]: That is a that is a TAM. So that's the TAM of the models, right? That's not our, essentially ours. But you get to that size, and to be able to do that, you essentially have to give agents these computers with the legacy. So computer use, either Mac or Windows or Linux. Linux we also obviously have and others have. But Windows specifically is something very new, and the only option right now is an EC2 with, Windows or on Azure. Both of them take anywhere from three to five minutes to spin up. We've created an actual sandbox, so it's a second instead of milliseconds, but you have, point in time snapshots, you have, forking, you have all the things that you have from a sandbox, but essentially enables you to hopefully unlock all this value. And so that's been our big push and bet, but we've sort of, kept our ear to the ground. What is sort of the next things in the market?RPA Returns: Why Agents Still Need ComputersSwyx [00:36:06]: Yeah, knowledge work, and building, and sort of RPA, the next wave of RPA. I got very excited about RPA kind of during COVID times. The UI path was IPO-ing. And it was, a very hot Isn't it, Eastern European?Ivan [00:36:20]: It is, Romanian.Swyx [00:36:21]: Romanian?Yeah, it might be the only Romanian, big unicorn okay, yeah. This I don't I don't, I don't have like a I think there's, I think there's a stage being set for the resurgence of RPA, ‘cause everyone understands that, yeah, no one wants to deal with these shitty apps and no one's gonna rewrite them. Like, you just have to do, a remote operation and programmatic operation of them.Ivan [00:36:45]: If you wanna unlock it, my own setup was basically the following. So I was doing a board deck recently, last month, whatever, and I'm like, “Okay, let's just, let's just do automated.” So, all our data's in, ClickHouse and PostHog and QuickBooks, where everyone else's is, and I'm basically, connected that all to, my Cloud code, like go off and go Cloud code whatever. Go off and, here's the integrations, go do that. It pulled out the first report, which was great. It connected to Brex and all these things, pulled it, which was great, and then I say, “Okay, now pull out this, and this,” and I kept getting, really well McKinsey-style design reports, but the data said partial data. all the missing data, partial data. Like, it can't access all the things, and I got so frustrated, and so I got, I got, my Mac Mini virtual sandbox with OpenClaw. I gave it its own account in our company, and then I went to all these services and created a read-only account, so literally like an intern in your company. And so I would say, “Now go and do this report,” and it would get the same, or like, “I can't via the MCP or the API or whatever. I can't get all the information.” I'm like, “Go log in.” And it will log into the website, then go in, export the data. It'll export the data and do the thing end to end. So even for things that have today APIs, not all of it is exposed, and I to get value, I get immense value right now, but it has to be a computer usage, unfortunately, and so I spend a bunch of tokens just on that, but I get the job done. And so if even a startup like ours, and using all the hottest tools, still needs a computer agent what hope does, Goldman have to have a headless, right?Swyx [00:38:22]: Yeah, what a - Why isn't Microsoft doing this?Ivan [00:38:27]: I'm pretty sure, Satya had a post yesterday.Swyx [00:38:29]: Oh, okay. I see.Ivan [00:38:29]: Which was like, “Every agent needs a computer.”Swyx [00:38:31]: I see, I see.Ivan [00:38:32]: So they have launched something recently.Swyx [00:38:34]: Yeah, they have Microsoft Power Automate, I'm sure, I'm sure, they're gonna have their version.macOS Sandboxes, Apple Constraints, and the Windows OpportunityIvan [00:38:39]: Version of that, yeah.Swyx [00:38:39]: You're gonna try to do yours, and it - I always know there's always demand for Mac, but I know it's, tricky to host, macOS sandboxes.Ivan [00:38:49]: We will have macOS sandboxes fairly soon. The problem with macOS, OS sandboxes is, I'm deep in this, I don't know how much interesting is.Swyx [00:38:55]: No, it's.Ivan [00:38:56]: MacOS has this problem.Swyx [00:38:57]: It's a licensing thing, right?Ivan [00:38:58]: Licensing thing. So one, you're allowed to run only two parallel VMs per machine, so that's one. Two, you can only license to a different user every 24 hours. So if you come in and theoretically, if I wanna charge you per second and I charge you one second, I have to have it idle for the rest of the day. I can't have anyone else doing that. So the pricing will be different in the sense that I will have to - we would have to charge for 24 hours, and that's not even, that's not even the most difficult thing. But the, thing above that is, from a security perspective, they enable you to do memory snapshot, pause, resume, but only on the same physical drive, physical machine. And so what you can do in, Windows world or Linux world is that I can move in the background, your snapshot from one to the other and manage load, right? Here, if you wanna do that, you essentially have to have your.Swyx [00:39:49]: Yeah, snapshots. Yeah.Ivan [00:39:50]: Your.Swyx [00:39:51]: It's like.Ivan [00:39:51]: Physical machine.Swyx [00:39:52]: You can't break it up.Ivan [00:39:53]: You can't, you can't move things around that, and all of that is, that part is, from a security standpoint, if it is written. Like, I understand the security aspect of that, but it disables you from doing these agentic, like really scalable agentic workloads.Swyx [00:40:08]: You need to do a vibe-coded, clean room implementation on macOS that you can then - That's like Clean OS or something. I don't know.Ivan [00:40:17]: So. We have.Swyx [00:40:18]: ‘cause like Linux was originally like a clean room rewrite of Unix.Ivan [00:40:21]: Okay. Yeah.Swyx [00:40:21]: Or something like that, right? Like same thing to macOS. Someone needs to do it.Ivan [00:40:25]: Someone will do that, and someone will have some long-running agents for a few days to figure this stuff out. But yeah. So definitely we - we're really close to offering something ‘cause people do want it, but the pricing will be different, and the feature set will be sort of stringent.Swyx [00:40:38]: Yeah, nobody's gonna use this. like, the labs, the labs will because they want to automate macOS.Ivan [00:40:42]: They have to do RL. They have to do RL again. But even if you The - So the point is with the RL part, if you, if you do RL on macOS, then the next iteration of the model comes out, it will be able to use these tools significantly. Then you actually need to run those, that somewhere. So you're gonna have to have that, later on. And from, if anyone at Apple is listening, I very much feel that they are shooting themselves in the foot of the scale of the revenue of compute or licensing they could get if they would just enable a concurrency model similar to what you can get on a Windows and a, and Linux.Swyx [00:41:17]: Yeah. Yeah. And I'm sure they've heard this before. They just don't care. Yeah, it's And maybe they will change their mind with the new CEO.Ivan [00:41:24]: Yeah. We'll see.Swyx [00:41:25]: We'll see.Ivan [00:41:25]: High hopes.Swyx [00:41:26]: High hopes.Ivan [00:41:26]: High hopes.Swyx [00:41:27]: Okay. But I, it's very clear the market opportunity is huge in Windows, and you can go for a long time on just Windows, but your customers are gonna want both. and I think, it is interesting to me that, this is the sort of God application of agents, right? Like, I don't It was - How big was OpenClaw for you guys? Like, was it, was there, a significant bump.OpenClaw, Agent Labs, and the B2B2C Sandbox MarketIvan [00:41:54]: Not for us because we.Swyx [00:41:54]: Because you already.Ivan [00:41:55]: We're kind of positioned differently. Whereas although it's completely PLG and we have individual developers that use it, most of the users that use Daytona are sort of a B2B2C. Sort of it's either B2B or B2B2C. So, in the researcher world, it's B2B, so you're selling to, labs and neo labs and things like that. But on the long-running agents, it's mostly, from a scale revenue perspective, it's mostly B2B2C, where you have a app layer agent that uses you at a big scale.Swyx [00:42:26]: Like a Manus. Yeah.Ivan [00:42:28]: Like a Manus Lovable type of thing.Swyx [00:42:31]: Yeah. I think that's the question of, well how, um-Uh, yeah, B2B to C is basically to me what I've been calling an agent lab, which is kind of like you're not in a model lab, but you're making a very good wrapper that is a platform that other people can sign up so they don't have to code those things. Yeah, it sound, it sounds like a much better market than the direct OpenClaw market.Ivan [00:42:56]: I've like - We I've done multiple things. So the CodeAnywhere's part of our career path R in the calendar, was very much an end user developer product. And so that is great. It You can get a lot of developer love, and I feel that we do as a company have a bunch of developer love. But it's a different type, where it's people building these things. Again, it's more akin to a Twilio because you don't really run - As a person, you wouldn't run Twilio. I don't know how many people remember. It was like ask your developer billboard and whatnot. And people really love Twilio, but they only used it inside of like, “Oh, I'm building this app or service for thing.” And so we're very much directly to that. And you also know that I used to work for a competitor for Twilio, so it's kind of ingrained, in my DNA.Swyx [00:43:35]: People don't know InfoBip is that big.Ivan [00:43:38]: Yeah, it's.Swyx [00:43:39]: Because.Ivan [00:43:40]: It's a billion euro.Swyx [00:43:40]: They're all American. They're like, “Whatever's in Europe doesn't matter to me.” But like it's the, it's the same size or bigger? Same size?Ivan [00:43:46]: It's about half the size.Swyx [00:43:47]: Half the size?Ivan [00:43:48]: Yeah, about half the size.Swyx [00:43:48]: It's like, yeah.Ivan [00:43:48]: Still huge. Multiple billions a year. Yes.Swyx [00:43:51]: That's crazy.Ivan [00:43:51]: Exactly, and so that - These are like really interesting and large revenue-generating, very sticky businesses. Whereas when you're selling to the - When your focus is the end developer, it is a very hard sell because they're very price sensitive, very price conscious, very around that. And there's very It's very hard to scale. Your cap is the number of people that are willing to spin up - First of all, wanna spin that up, and then spin up multiple of these. Whereas if you're in the enterprise one, like we know everyone's talking about like how many tokens they're spending, I'm spending. Like a lot of companies today are like, “If this is our company, spend as much as you can.” Like basically that is where we're going. And so if you think about that paradigm, where you're selling to companies that say, “Spend as much as you can to generate, productivity,” versus, “Oh, I'm a single person. I have this much budget, and I'm doing this thing because it's fun or it's helping me out or whatever.” Like it is a different, it's a different go-to-market, I think, strategy.MCP, CLIs, and Sandboxes as the Agent RuntimeSwyx [00:44:50]: Yeah, there's a lot of discussion. I'm just kind of going through like the mental list of things that are in your favor, which is, for example, MCP versus CLI. Like obviously you want CLI. It's been very good for you. I feel like it's maybe a drop in the bucket or maybe it's huge. I'm just checking whether it's like these are big trends.Ivan [00:45:10]: Those things you - work well in our favor, to your point just because every.Swyx [00:45:13]: They're kind of drop in the bucket, right?Ivan [00:45:15]: I think it's like sort of all the things come together. And so there's so many things that impact that. To your point, like OpenClaw wasn't huge for us, but like having the agent SDK, from Anthropic, so or Cloud Claude Code was very interesting. The reason why it was interesting is that a lot of, let's call them app I don't know what to call them, app layer agent companies, essentially they are like, “Oh, I can create this new app, this new agent. All I need, I just use Claude Code, and I throw it into a sandbox, and then I have my interface to the human to that.” And so that enabled so many more companies to actually offer this, and then they would pull on sandbox. So that was, that was interesting. And to your point, like MCP, versus the CLI, the MCP is an interface against an API, whereas the CLI is like you can actually go do things. Like this is it. The difference between integrations and actually running scripts or data or analysis against a thing. So being able to use a CLI very well enables the agent to do more things, and it's because that people will invoke a sandbox, they'll run it in the CLI, and but it'll do anal-analysis on that data and then give you an actual result versus just, pulling data from an API source.Swyx [00:46:29]: Yeah, it's a layer of indirection basically, it's the same thing as agentic search versus RAG, which where you're.Ivan [00:46:34]: Exactly, yeah.Swyx [00:46:34]: Just like you just win whenever people put more agents into their workflow. And so like it doesn't really matter, but I'm just kinda teasing out like what else have people heard about that like it's sort of, “Oh yeah, this is another sandbox use case. Oh yeah, that's another one.” Am I, am I missing any big ones?Ivan [00:46:51]: The thing, the thing that people, which is the computer use stuff, which I think is probably the most interesting one, is, and to your point, we've talked to so many people over the last year. It's like, “Oh, like why do you need a sandbox? Why do you need this? Why this?” And to your point, it's like, “Oh, I need sandbox for this. I need sandbox for that. I need sandbox-” It's like, “Oh, I need it for every single thing.” And so basically what I, what I - and it sounds like a broken record, it's like you use a laptop every single day, right? And you are n of one. It's just you. But now imagine how And by the way, the laptop, the computer PC market, the PC market is about equal to the cloud market in total. So it's about 150, 180 billion a year. Something like that. It's about roughly the three cloud hyperscalers is about equal to like Apple, HP, Lenovo, whatever, It's a little bit less, but it's sort of like that. And now imagine And that's just like, so how big is the addressable market? What, how many people are there in the world now? What's the last data?Swyx [00:47:45]: Let's call it eight billion.Ivan [00:47:46]: Eight billion. And so let's say you can have two computer, like you have one personal and one business, whatever. Like so it's double that, right? and so that's 16 billion, right? How many agents are gonna be running in two years, in 10 years, in 100 years? Like And for every single task, they will need one of these. And so how big is that? That market is essentially quote unquote “infinite”. You will get to the point, and Dylan Patel was at the conference talking about, from SemiAnalysis, that talks usually about GPUs, was also talking about how CPUs will now be a bottleneck because it will be the constraint. You won't be able to grow, or we won't be able to have enough of these because there won't be enough CPUs to basically do.Swyx [00:48:23]: Yeah. Well, I actually had a really good podcast with Doug Oliphant, who, which was his president at SemiAnalysis, where they've basically been like, yeah, it's been a GPU shortage first, but then it's cascaded down to memory and now to CPUs.Ivan [00:48:35]: CPU, yeah.Swyx [00:48:35]: It-What's next? So networking. So, networking actually has been in shortage for a while if you're looking at, just GPU networking. But, yeah, it's really crazy the amount of computer use that's going on, yeah, cool. I, other questions are, just the one very big part is the open sourceness which you didn't have to do, your competitors don't do, like it's not, a lot of people are worried about keeping their projects open source because some competitor can just slot fork it. I don't know if there's any reflections on just being an open source company.Open Source, Trust, and Enterprise ProcurementIvan [00:49:15]: Yeah. There's a bunch. So we the original product that we did was open source.Swyx [00:49:19]: Yeah. CodeAnywhere.Ivan [00:49:20]: So doing that was actually very good for us. There's basically a saying of, What's the saying? Like, companies that are, that are doing really well, measure themselves against, free cashflow, that are kinda okay, it's EBITDA, then, it's, it goes all the way down.Swyx [00:49:36]: The worst is like GitHub stars.Ivan [00:49:37]: GitHub stars. GitHub stars are the worst, yeah. So you go all the way down to GitHub stars. And so our original one was GitHub stars. That's what we talked about, we're at the point we're talking about revenue, so we're we've gone up the stack on that. And so we started.Swyx [00:49:47]: No, profit.Ivan [00:49:48]: Yeah. We haven't, we're, we'll get there. We'll get there. But basically at that point we did stars and GitHub and it was useful, and the original variation that we did, it we split the core into its own repo and it was Apache 2.0, so very, permissive. And then we basically would bundl

Jason Howell and Jeff Jarvis break down everything from Google I/O 2026, where the company made its strongest case yet for winning the AI race. Gemini 3.5 Flash and Gemini Spark were unveiled, AI agents are now doing the searching instead of returning links, and Google's reach extended into design, science, YouTube, and shopping. Jason also demos Genie World Models live.Also in this episode: Andrej Karpathy joins Anthropic, Anthropic acquires a major dev tools startup, Amazon Alexa+ can now generate podcast episodes, Elon Musk's latest lawsuit drama, and a growing American rebellion against AI. Speed round includes the OpenAI IPO, xAI's coding agent, Meta's AR glasses, and more.New episodes every Wednesday at aiinside.show Note: Time codes subject to change depending on dynamic ad insertion by the distributor. CHAPTERS: 0:04:31 - Everything announced at Google I/O 2026              - Times: How Google Is Starting to Win the A.I. Race 0:22:42 - A new era for AI Search              - Gemini 3.5: frontier intelligence with action 0:27:53 - Google Launches Gemini Spark: A 24/7 AI Agent That Wants to Make You Ditch OpenClaw 0:44:35 - OpenAI co-founder Andrej Karpathy joins Anthropic 0:46:32 - Anthropic has acquired the dev tools startup used by OpenAI, Google, and Cloudflare 0:55:20 - Amazon's new Alexa+ powered feature can generate podcast episodes 0:57:27 - The Art of War, Elon Musk Edition: How to Lose a Lawsuit and Still Claim Victory 0:59:30 - The American Rebellion Against AI Is Gaining Steam 1:01:46 - NextEra Energy to buy Dominion in deal that unites two key players in race to power AI data centers 1:04:42 - Pope Leo XIV will publish his first encyclical, Magnifica Humanitas, on May 25, with Anthropic co-founder Christopher Olah joining the launch panel at the Vatican 1:06:25 - Linus Torvalds says AI-powered bug hunters have made Linux security mailing list ‘almost entirely unmanageable' 1:08:57 - Meta brings virtual writing to everyone with Meta Ray-Ban Display glasses 1:10:36 - Musk's xAI Unveils First Coding Agent in Bid to Rival Anthropic 1:10:59 - OpenAI is Preparing to File for an IPO Very Soon Hosts: Jason Howell and Jeff Jarvis Download and subscribe to AI Inside in audio and video: https://aiinside.show/  Support the podcast on Patreon for special perks: https://www.patreon.com/aiinsideshow. You'll get ad-free episodes, members-only Discord, T-shirts and stickers you love, and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Learn more about your ad choices. Visit megaphone.fm/adchoices

El programa 2877 de Radiogeek, les habló de varios temas importantes. Los suscriptores de pago de Google Gemini están indignados por las nuevas y silenciosas restricciones de uso; Algunos adaptadores Chromecast originales ya no funcionan y nadie sabe por qué; La nueva función de WhatsApp hace que los mensajes desaparezcan justo después de leerlos; Wear OS 7 es oficial; y por último La empresa de inteligencia artificial xAI de Musk está siendo demandada por sus generadores de centros de datos. Toda esta información la pueden encontrar desde nuestra web www.infosertec.com.ar o bien desde el canal de Telegram/Whastapp, o Instagram. Esperamos sus comentarios.

A large-scale analysis of Grokipedia, the world's first AI-written encyclopedia, has found that while many Grokipedia articles closely resemble their Wikipedia counterparts, a substantial subset diverged markedly in style, sourcing, and political leaning. Conducted by researchers at Trinity College Dublin and Technological University Dublin, the study compared nearly 18,000 of the most-edited English-language Wikipedia pages with articles on the same topic on the new Grokipedia platform. The study is the largest academic analysis of Grokipedia since it was launched by Elon Musk last October with a promise that the AI-written encyclopedia systematically "fixes" left-leaning biases alleged to exist in the widely used online encyclopedia Wikipedia. Wikipedia's content is written and maintained by volunteer editors, while Grokipedia is an AI-generated encyclopedia using the xAI's Grok large language model. What did the study find? Using computational text analysis and machine learning methods, the team analysed articles on the same topic across Wikipedia and Grokipedia. Selection of topics was based on Wikipedia's most-edited English-language pages. The team compared differences in writing style, structure, and the political orientation of external sources referenced in the paired articles. The researchers found a profound split – while many Grokipedia articles closely mirror Wikipedia, a substantial proportion (66%) of the 18,000 analysed are more extensively rewritten – they are longer, more complex, and rely on fewer references. As a whole, articles on Grokipedia show similar political leaning to those on Wikipedia, drawing on left-leaning news sources. However, when it comes to the politically and culturally sensitive topics of religion, history, literature and art, Grokipedia shows a consistent shift toward referencing more right-leaning news sources compared to Wikipedia. The study analysed Wikipedia's most-edited English-language pages, a selection that likely overrepresents high-profile and contentious topics. That said the study, according to the authors, provides useful evidence of emerging differences between AI-generated and human-edited encyclopedic knowledge systems. Details of the research, conducted at the joint Centre for Sociology of Humans and Machines (SOHAM) in Trinity and TU Dublin, have been published in the peer-reviewed journal Proceedings of the National Academy of Sciences (PNAS). What is the impact of this research? Lead author of the study, Saeedeh Mohammadi, PhD candidate at SOHAM and Research Ireland's Centre for Research Training in Foundations of Data Science said: "Online encyclopedias are central to public knowledge. They are also being used to train future generations of large language models. Our findings raise important questions about how public knowledge is produce, reproduced, verified, and governed. "Unlike Wikipedia, where biases are visible and contested through human editing, AI-generated systems operate largely opaquely. This means shifts in perspective or sourcing may occur without clear accountability or editorial oversight. Simply put AI generation does not remove bias – it changes how and where bias enters the system, often making it less visible." Professor Taha Yasseri Director of SOHAM and Principal Investigator of the study said: "Rather than systematically 'correcting' Wikipedia's alleged biases, as claimed when first launched, our findings suggest that AI-generated encyclopedias such as Grokipedia selectively reshape existing knowledge. This creates a patchwork system in which some content is copied, while other content is reinterpreted in ways that are less transparent and harder to scrutinise." "There is a dire need for transparency, oversight, and regulation in this space. Our information landscape is changing rapidly. We have already seen how the lack of editorial responsibility on social media platforms has enabled the generation and circulation of misinformation and ...

Hoy hablamos de Cohere liberando Command A+ con licencia Apache 2.0 y empujando la IA soberana de verdad; de la task force del Pentágono para meter IA con capacidades ofensivas en NSA y Cyber Command; del plan de xAI para comprar 2.800 millones en turbinas de gas mientras acumula demandas ambientales; de Jensen Huang admitiendo que Nvidia ha cedido gran parte del mercado chino a Huawei; y de los 81.600 millones trimestrales con los que Nvidia confirma que, en la fiebre de la IA, el gran negocio sigue siendo vender palas.Puedes seguirnos en YouTube en https://youtube.com/olivernabani y puedes unirte al Discord Mashain en https://olivernabani.com/discord

The Great Talent Redistribution: Where is Talent Actually Going in 2026 and beyond?  Is the start-up compensation model broken? How about big Big Tech? How about non-tech small & medium businesses? What is happening to talent, going forward? This and many other topics in this episode of Tech Deciphered. Navigation: Intro The Broken Contract? The Great Unbundling The Three (?) Destinations Alternative Cap Tables, Alternative Compensation Models Investor Landscape Fragmentation Operator Playbook and Predictions Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Nuno Goncalves Pedro Introduction Welcome to episode 77 of Tech Deciphered. This episode will focus on the great talent redistribution. Where’s talent actually going in 2026 and beyond? The Silicon Valley deal of the last 30 years, very low salary, stock options, you will either sell for a ton of money or IPO, and everyone gets rich, is seemingly broken. Or is it really? The dominant narrative says the tech middle class is dying. We disagree. There is obviously a lot of stuff going on whereby big tech is partially barbelling. There’s a superstar concentration on the top. There’s a bit of a seemingly allowing of the belly. We’ll come back to that. We don’t quite believe that is totally true. There’s a collapse at entry level. The belly is migrating into three, potentially even more, very different destinations: AI native startups, human-verified premium businesses, and the read the industrialized middle of the S&P 500 and SMB world. Each has its own cap table, each will have its own compensation model, and each will have its own investor profile. In some ways, this is the third episode in our Reset trilogy. We started with episode 75 on the SaaS-apocalypse. We talked about the great private capital reset in episode 76, and now we talk about talent redistributions. Bertrand, exciting times, not always positive times.   Bertrand Schmitt Yeah, it’s exciting times because it’s a time of change. Of course, we have the doomsayers. If you listen to Dario Amodei of Anthropic, every white-collar job on Earth is going to disappear. I think I strongly disagree, and I suppose you too as well, we strongly disagree. It’s going to be more of a redistribution. If you look at the history of technology, this is what always happened. We forget how many jobs have disappeared over the past 150 years. We move from a time of 150 years ago. People were mostly in agriculture. Then you had a lot of weird jobs that disappeared from people transporting water to people bringing ice from the pools to people doing the job of computers. People forget that computer was a title given to human beings. We’re doing calculations. Then, of course, secretory jobs in the ’80s, ’90s, where suddenly anyone can type using a word processor, the rise of Excel, that sort of stuff. Many things have changed. Some jobs have indeed disappeared. Some jobs have totally transformed. Where you do these jobs have changed. I think we are at a similar stage where, thanks to AI, and I would say for now, or at least the rise of AI coding, there is a dramatic change happening. I don’t think it means that people will be without a job. It just means, from my perspective, that jobs are changing. You are not just doing a lowly coding level task that actually indeed could be replaced, but you are going to have more of builder type of mindset, a product manager type of mindset going forward. We also expect that the distribution of jobs, depending on the type of business, will be quite different.   Nuno Goncalves Pedro The Broken Contract? Maybe let’s reset a little bit to the broken contract, or if it’s really a broken contract. There’s been this image in technology and tech that basically you get paid very little to work in tech. You get a bunch of stock options. The earlier you are in the company, the higher the level of stock option grants you get. Then you make a ton of money at some point because the company will either sell or IPO, and that’s heard of it. Obviously, there’s a lot of movements happening right now that are changing how these dynamics work. The first part is obviously AI, and in some ways, AI is shrinking companies. It’s not unheard of that companies with as little as four or five people reach 50 million in ARR. There’s companies with one person that have gotten bought for hundreds of millions of dollars or billion of dollars. Obviously, things are moving very, very fast, and therefore, there isn’t a large employee cap table. How would you share the upside? Would you actually give a couple of percentage points to an early employee rather than your 0.2-0.5% kind of thing for early employees? The second part is a little bit the other side of the table, which is the IPO market is seemingly in a drought. There’s not much happening in IPOs. Maybe 2026, at some point, there will be an unlock, but right now, it’s seemingly difficult to get your upside. Even if you’re an employee, you have to wait a long time. The median time of IPO has climbed over 10, 11 years, the longest in over a decade. Basically, not only you have to wait a long time as if there is an IPO drought, like we might be going through right now, when do I actually get my cash back? Unless the company gets bought, maybe there are secondary transactions along the way, maybe there’s something else. But obviously there’s a little bit of a reduction and lowering of the upside seemingly for this contract and for this place. The easy conclusion that I think many are taking is, because of all of this and all the layoffs that are happening, even in big tech, that serve the tech middle class is dying, that basically AI screwing the workers, et cetera, there’s also a lot of discussion that even it might be affecting the entry-level jobs as well. Everyone coming out of undergrad right now can’t get a job, et cetera. There’s this doomsday scenario that you’re alluding to that everything is changing. We have a slightly different perspective. We think there’s a realignment of market. In layoffs, there was a lot of layoffs that were warranted. Big tech, in particular, had actually hoarded a lot of engineering capacity over the last decade or so. There’s a little bit of a realignment that needed to happen in any case. When everyone’s saying, “Well, AI is compressing everything,” well, it’s compressing right now, but we don’t think actually it’s going to compress over time. You’ll still need engineering and science talent to come on board for you to be able to scale up. It’s not like AI is going to take care of everything and teams are going to be five people for companies that are worth a trillion dollars. That’s not happening. Today’s thesis, I think a little bit of this doomsday scenario needs to be seen with a more nuanced lens. I think that’s how we’re framing today’s episode, that there’s a bit of a nuance, there are some extremes happening. We’re going to talk about those extremes, but ultimately, it’s not quite as simple as saying that the tech middle class is disappearing in early jobs are going to be a thing of the past.   Bertrand Schmitt At the same time, what you started with is true. I mean, that 50 million ARR company, just five people. At a bigger scale, that’s exactly the matrix for Anthropic. They have reached a stage where they are at a range of 12 million ARR per staff per employee. It’s metrics that are definitely never seen before. I don’t think any company raised to this level. Best in class, best run companies, one, two million per employees. I mean, that was your target if you can make it. We are definitely in a different game. But I think what matters at the end of the day, and that’s what we’re arguing, is that you have to see the big pictures. Yes, some positions might disappear inside some companies, but some other positions will be created in other companies. Usually, what people do is keep talking about the jobs who disappear and not looking at the bigger picture of jobs that are being created as well. What is true, and I think you alluded to that, is that the big tech the past 10, 15 years had some strategy of hoarding talent in a war where having the best talented people will make the difference in numbers, will make the difference between winning or losing. The Google of the world, the Microsoft of the world, the Amazon of the world, they were hoarding talent. They would try to make sure that they might not have such needs in talented number of people. But if they have the talent, it means their competitors didn’t have the talent. It means that the startup trying to reach scale couldn’t pay the giant salaries that the Google of the world were paying. There was definitely some hoarding. But it went so far in the 2020, 2021, that I think since then there has been a coming back to normal. There is also now in 2026, the recognition that it’s not true anymore. Yes, talent can be very valuable, but there is now a bigger and bigger gap between the extremely talented versus the rest that are merely talented because of AI. AI is able to replace at scale your software engineers, your software managers. I would say it’s quite new. I don’t think it was true a year ago. We’re really talking about a recent dramatic change in what can be achieved thanks to AI. We can see most of the big AI companies are moving to coding. It was started by Anthropic as a trend, OpenAI has followed through. Obviously, the Cursor of the world existed before, but they were not as successful. All the Chinese open-source models are moving very fast to coding optimization the past few weeks. It’s quite an incredible change. I think there is that dramatic change, recognition that coding can be done differently. As a result, we are going to see change in the distribution of jobs. I think it will start from the top because we see the news of the big Google, Microsoft, Amazon, and others who used to hold talented software developers to a change in realization that no, we actually need to invest in AI. We need to invest in compute because compute is going to do the job of most of these people. Therefore, we can’t pay for both at the same time, even us with all our money, we cannot. Wall Street is not going to let us do that. They start by removing a lot of position. I think we see that accelerating, quite frankly. We have only seen the beginning, but in the next 2 years, we see a dramatic shift. But I think my position, I guess yours, and you know as well, is that there will be a lot more opportunities created as well, probably by also entities.   Nuno Goncalves Pedro The Great Unbundling Yeah, there will be more opportunities created. The hoarding is just taken also a little bit of a different view. To your point, there’s hoarding of resources, compute, et cetera. But there’s also hoarding of top talent. We are seeing people getting paid, packages all in that could run up to 100 million, in some cases even over 100 million over several years. This is unheard of. I mean, an officer of Meta would make, I don’t know, maybe 20, 25 million a year. It’s like now there are people that are on the top end of AI researchers that are getting paid around that amount just to join some of these companies. There’s a little bit of a different hoarding. It’s very selective hoarding of certain talent. We’ve seen some acqui-hires. We’ve talked about it in previous episodes that are just literally about getting one or two people specifically to come on board. Alexander Wang, again, going to Meta to lead their intelligence labs there. I feel, I don’t know what you feel, but I feel this is a transition moment where there is overpaying for certain talent on the top of the market. At some point, this will stabilize. You can’t keep paying people 100 million over 4 years or something like that across the board. To your point, a lot of this is actually going to scale up quickly also on the AI side. There’s a little bit of a different hoarding happening on the top end, not just the resources, but also of people, which seems to give further this notion of barbell, that there’s two extremes, the haves and have-nots, the super-duper talented people that get paid a ton of money, tens of millions of dollars a year at the very least. Then the emptying of the middle where there’s a ton of tech layoffs going on in some ways, the belly, as they would call it, is being expelled. The middle market, the managers are being fired because there’s nothing to manage. There’s a lot of positions going away. In some cases, you might keep some of the more junior talent, but with a little bit of experience. But even the talent coming out of colleges is not getting hired either. It’s a little bit of a weird thing where there’s hoarding at the top, there’s an emptying of the belly, the middle, and then the early, early, early is also not getting recruited. It’s like what gives? How is this going to look in the future? I agree fully with you, Bertrand, that there’s a migration of this talent, not only to other companies, but also to other jobs. There will be new jobs that will emerge out of this. The DevOps, dev tools market didn’t exist until maybe 20 years ago at scale, and it got created. In some ways, we’re seeing there will be new markets, there will be new roles and new jobs that will be created around engineering teams going forward. We can’t anticipate all of them. But basically, the emptying of the belly is true as it’s happening right now. The low hiring on the early and the top end, getting tons of money. We think this is a transition to something else. There’s the hoarding of engineering in general is coming to an end at momentum. Now it’s time to rightsize teams, to get the right at the table, et cetera, and start figuring out what works and what doesn’t work. We’ve already had some horror stories coming out even from Amazon where they were breaking systems with their use of AI tools, and I’m sure it’s happening across the board. I’m on a board of a company and been tremendously affected by Meta and its algorithms, where basically because of advertising, there have been people served with ads for this specific company where the ad doesn’t match the company, so basic stuff like that. It’s been actually very, very difficult because in some ways, the company goes back to Meta. It’s like, “Hey, dudes, you guys are serving ads that are not even our ads with our copyright and stuff. How does this work?” They’re like, “Oh, it’s AI.” It’s like, “Well, it’s AI but can you give me my money back?” They’re like, “No, we won’t give you money back.” This creates huge issues for companies, for example, that are very dependent on advertising, which obviously there’s a lot of industries that are. They’re actually in production systems at scale. Meta is, I think now, the largest digital advertising in the world. I think they outgrew Google in one of the last quarters. Basically, this has a tremendous effect that systems that are in production at scale are getting inputs and changes driven by AI tooling, and somehow nobody can say what the hell is happening. Again, there will be a reckoning, there will be a redistribution, there will be a rightsizing of teams and an adequacy of teams going forward. I personally think this is a transition period.   Bertrand Schmitt I think we are moving from hoarding or software engineering to hoarding the top of the top scientists in AI and hoarding of GPUs, GPUs/data center. For me, it was quite interesting to see the deal of Cursor with xAI, where basically they couldn’t get access to computing resources to run their model. But xAI had, I forgot the exact numbers, but close to half a million GPUs that no one, I mean, “no one was using” because their services are not so successful yet in terms of AI chatbot and the like. Basically, suddenly they are like, “You know what? We control access to resource.” But the new resource is, again, a mix of extremely talented AI engineering or AI scientists versus GPUs/data center. There is this race of controlling boss and everything else is going to be collateral damage. Some examples, I think, are quite interesting. You talk about some example of Amazon, even some production issues. I remember reading a quick post-mortem of one of the issues, and the conclusion was it was AI, definitely part of the issue. But the other part of the issue was AI used by junior engineers. For me, it’s interesting. It shows that actually junior plus AI is actually a danger zone. That’s why many companies are going to be way more careful. “Why do we need the junior people if they are just playing with fire?” I think we go back to that situation of barbell, as you call it. The top talents are extremely valuable because they know how a production system works. They are here to develop better AI systems. But the junior guys playing with fires, yeah, maybe it’s cute in startups, but in a big time production environment, a different story.   Nuno Goncalves Pedro There will be a barbell with top-end talent super-mega paid and then mid-level talent that is individual contributors still doing a lot of great work, et cetera. Along the way, a lot of emptying of entry, a lot of emptying of the middle. Where does the talent go? The Three (?) Destinations I think we could say there’s three destinations for this talent. Maybe there’s four, maybe there’s more. Three that we can immediately identify. One is the AI native startup piece, where we have smaller teams that potentially get to a lot of revenue or top line over time, and where the Series Seed is the primary round, where we’re seeing Series Seed being raised of tens of millions of dollars, actually even hundreds of millions of dollars in Series Seed. In some ways, the stars there can get incredible compensations in terms of stock. They will stay for private and selling in secondaries later down the road because there’s so much capital at the table. Actually, in some ways, salaries are very high as well in some of these companies. It’s not like you’re trading off anything. You can get paid a lot of money. If your company at Series Seed for 10 or 15 employees has raised 50-$100 million, you can pay great salaries. In some ways, this is the extreme destination. The AI native startups that can make it is the extreme destination. Now, there aren’t a ton of AI native startups that can raise 50-100 million to 400 million in Series Seed, just to be clear. There’s a handful of hot deals in that space, but that’s one clear destination for top-end talent going through that. In that market, I think that’s one of the destinations. The second one is more what we would call the human-verified premium. It’s more of a play of companies that has still the need of human in the loop, either in terms of development, also in terms of activity, either because go-to markets are very intensive, and so therefore you need to have sales forces, partnership teams, et cetera. Or on the engineering side, it needs to have a lot of customization, integration. Companies are not just going to the, “Oh, you can come in and just apply your AI tooling and somehow magically the systems all work.” there needs to be quite a lot of and work and high touch work in getting stuff done. A significant part of that market, I’m not sure, is super VC investible. Maybe it’s a hybrid of private equity in VC, more PE style in many cases. It’s a PE-hold, sell to someone else market. As we’ve discussed in a previous episode on the SaaS-apocalypse, that hasn’t quite worked out for PEs. Question marks on how that human-verified premium market is going to evolve. But obviously, there’s a lot of work still to be done there, even on the engineering and science side. That’s the second potential destination. Then the third more aggressive destination is the reindustrialized middle companies that have a lot of specificity in going after small and medium businesses, local or regional affectations like ERPs or CRMs for specific markets, et cetera. Those are the three natural destinations. I would add the fourth, which is big tech. I mean, big tech doesn’t magically disappear, and I don’t think it fits neatly into any of these three markets. In some ways, big tech is now looking at the extreme for top talent a little bit like the AI native startup because they can pay. They can pay the 100 million every four years, et cetera. I do think it will typify taxonomically into a fourth type emerging, where, as we discussed, you’ll have top-end individual contributor talent. You’ll have the absolute top-end of the market because they can get paid. Then you’ll start having the emergence of earlier talent that is highly capable, et cetera. That will go back to a bit of a normal distribution in terms of talent on big tech. For me, those are the four destinations that I would put at the table.   Bertrand Schmitt For me, big tech moving to big tech, I’m not sure if it’s really a destination. I mean, yes, in some ways it’s a reshuffle between the big tech companies. They are definitely all fighting in some ways for some of the same people. I can see that dramatic shift where big tech has to remove a lot of positions in order to replace by AI. Again, I think at this stage, it’s mostly driven by AI coding. We are still at the beginning because this is brand-new phenomenon that AI coding is so successful at its task. I don’t think it was true even 6 months ago. Some companies, take Anthropic, take OpenAI, are definitely there or close to be there in terms of no more writing of a single line of code by a human, zero. This is, again, 6, 12 months ago. Not true. But now it’s true in a few top companies. Take OpenClaw as well, most successful GitHub project of all time, not a single line written by its author. It would have been impossible. We’re talking about hundreds of thousands of line of code in a few months. It’s impossible to achieve that manually. If you look at the other big tech companies, the Google of the world, the Meta of the world, the Microsoft of the world, they are absolutely not there yet. They are going to be there because they have no choice. It’s you either go fast there or you die. You are not going to be able to survive competitors that are shipping 10, 50, 100 times faster than you are shipping. It’s a life and death situation. All the big tech companies are going to move, and mark my word, in the next 2 years from 10, 20% of AI-written code to 100%. During that transition, the next 2 years max, if you don’t do it in 2 years, you are going to die. Your stock price is going to crash. Then, of course, you will have to make changes. You will have to invest more in GPUs. You will have to invest less in your standard typical software engineer employees. Like you, I’m very optimistic that there are new buckets. AI-native startups definitely will be there. It will be transformational. Human-verified premium, very interesting category. In a way, it will be businesses that are inevitably less scalable through AI, and there is definitely a spot from there. I think the biggest would be the reindustrialized middle SMBs. Most of S&P 500 type of business are going to dramatically offer new software opportunities, new opportunity story to talented software employees because they will need to implement AI in everything they do. They will do it. They will need people who have software engineering knowledge in order to implement these systems. For them, what’s changing dramatically really is that thanks to much cheaper cost as thanks to AI coding, a lot of software projects that they couldn’t afford to do, that they couldn’t imagine doing by themselves, they are able to do it. They will invest in a lot more software capabilities than ever before. That will be a big game changer. And software, very tuned to their business model. There might be less buying of your traditional off-the-shelf SAF software and a lot more investment in a highly custom software by their own team, assisted with AI. I think that would be the part that is most transformed by all of this in a positive way.   Nuno Goncalves Pedro Alternative Cap Tables, Alternative Compensation Models This will lead to a very fundamental shift, right back to the broken contract. What does the new contract look like? It looks like alternative cap tables depending on which bucket are you transitioning into. If you’re going into your AI-native bucket, and you’re a top-end talent, you’re like, “Dude, I’m worth 100 million over 4 years, so just compensate me accordingly with a mix of options in the company plus my salary.” If you’re top 1%, you can probably get away with salaries that you’d get anyway at mid-level from 300K, 400K and above, and you can get actually a lot of options already in the company. A lot of this is happening right now. There’s a premium for AI, we know that. There’s a premium for AI at the top end of AI researching, in particular on companies that are doing hardcore research on staff AI engineers, so companies that require actual AI engineering. There is a premium that is significant. It could be as high as 18% over non-AI peers, and it widens actually with seniority, shockingly enough. This is more of an average than anything else. Now, for me, and it’s for debate, but the perspective is this extreme comp will need to compress at some point. There will still be the haves and have-nots paid much better than the have-nots, so to speak, but there will be a compression. The variance can’t be the variance we’re seeing today for absolute top-end talent. That said, there will be variants. We know that big tech for over a decade, decade and a half, for example, in the Bay Area, has been paying a lot of money for director and above levels that used to be the VPs, so a million, a million and a half a year, all in compensations. It’s not unheard of that this will actually increase after this stage. That said, I do think that the compensation extreme that we’re in will get diluted down the middle. It will actually come down at some point. It’s part of where we are today. As we know, it is still a bubble.   Bertrand Schmitt Yeah, it’s an interesting point. I think it’s possible. At the same time, that compression coming 2, 3, 5 years. At the same time, we have examples where there is no such compression. Take the top sports players in the world, golfing, basketball, NBA players. There has not really been any compression at all. For me, it’s interesting. If you look at the big tech companies, each being one of this top NBA team, why would such compression happen? As long as they are competing against each other and generating plenty of cash, I think there will be some fair question. We will see. I don’t have a strong opinion, but for me, it’s not a total given.   Nuno Goncalves Pedro For me, the shocking thing is the faster AI becomes better, the more that compression will happen, because at some point, it’s like, why do you need the top talent as well? I don’t know. It feels like you’re trying to evolve a system that’s there to replace you. It’s like, “Okay, I’m getting paid 100 million over the next 4 years”, and then you develop something that’s so good that replaces you. Thank you. That’s cool.   Bertrand Schmitt That’s a total possibility, yes, because we are in that very unusual market where the game is to only replace yourself and people like yourself. At some point, it is a possibility, I guess this one. Right now, we’re talking about replacing your “average software talent”. In 2 years, could we absolutely replace the absolute best top experts in the world? Probably. I think it’s just that at some point we’ll be reaching the stage where we strictly have no control anymore on our AI systems because no human is able to challenge and understand what’s produced. It’s not just a question of scale anymore. We’re talking about a gap in IQ, basically.   Nuno Goncalves Pedro Exactly. It will happen at some point in history. We don’t know exactly when. For the second bucket, the human-verified premium bucket, it’s difficult to see how an HVAC company or an HVAC roll-up of scale or a regional health care platform or high touch go-to-market, B2B, SaaS play, et cetera, for a vertical will compete. At the same end, they have to compete and they will compete. There will be more and more jobs, we believe, for engineering talent in these companies. They’ll have to be more and more AI-enabled themselves. The cash salaries will have to be competitive within the local markets, not necessarily with Silicon Valley. There will be potentially profit sharing and revenue sharing and actual dividends played at the table. The model there on the cap table needs to change a little bit, needs to be probably propped up more on salary and on some way of doing profit sharing or actually having dividends paid to employees and figuring out employee to equity in a more aggressive manner. This is the market that probably was already very attacked, so to speak, or let’s say, occupied by private equity firms. There are still obviously part of that model that would work well. There needs to be a fundamental shift, certainly on the quantum of salary compensation, dividend compensation, profit sharing, and all of that. Then last but not the least, obviously, we had the bucket around basically the reindustrialization of the middle, so everything else, which will take most of the belly that we were talking about. This is probably a poor analogy, the belly fat. It’s not belly fat, it’s people that were doing their jobs that now are getting disrupted. In some ways, that bucket will absorb a lot of that belly, will absorb a lot of talent. The small and medium businesses that Bertrand was saying will need to crucially become more AI, software-enabled by themselves, even with some core stuff and underpinnings that actually might not even require AI in terms of infrastructure platforms. There, you need to get properly paid. Again, how many people do you need in your engineering team if you’re a small business? Probably not a lot. It’s maybe you need one or two people and that’s it. They’ll need to be very nicely paid because they’re running the stuff in the rails. This is probably a market that over time, as AI gets more and more competent, will also be disrupted, but let’s not talk about the disruption to the disruption because otherwise, we’ll stay here the whole day, but certainly a market that has a lot of potential to shift and to absorb a lot of the moments that we’re seeing in terms of layoffs happening in the US in particular.   Bertrand Schmitt This category was a category that historically could not compete with Silicon Valley salaries, could not attract the most talented engineers. It’s not a category that didn’t want to bring these people on board. It’s a category that just couldn’t afford to bring this talent on board, typically. I think it would be a dramatic shift for them when suddenly there are opportunities to hire these people. There is an opportunity to hire them at maybe more reasonable prices from this company’s perspective. You talk about small companies, the great thing is that there are millions of small companies at some point. I think things could be truly transformational. Of course, some of these engineers, software engineers, might decide to become entrepreneurs on their own. Solo entrepreneurs, small businesses, build their own, easier to build their own product to market so to serve other companies. I think there will be quite dramatic changes because not all companies will be disrupted by AI as much, but not every company will benefit from improving processes, improving software through AI. At least early on, you will need this human touch to make it work inside a business. Interestingly enough, I was hearing that some companies like IBM were hiring more younger people to do the work of going to the client, understand their needs, propose implementation plans. That forward deployed engineer, those positions, I think there will be more and more available.   Nuno Goncalves Pedro Investor Landscape Fragmentation What happens to investor into the landscape? We already had an episode, the previous one, Episode 76, where we talked quite a lot about the big capital reset on the private equity and private reset, including venture capital. Just maybe to summarize, how does it align with the buckets that we’ve just been discussing? I think the AI-native bucket clearly is going to be the key bucket. There, we’re going to see two movements. One movement, which is the mega funds, as we discussed in the last episode, are no longer just VC funds. They’re really mostly multi-asset private equity funds, maybe even private equity hedge funds in some cases. Those funds will be all over the high-growth AI-native companies and will be pouring money into companies that are scaling really, really quickly. The early stage, so to speak, VCs, the actual VCs that will stay in the market will be the guys probably identifying the next big wave of AI-native companies. We’ve discussed that as well in the last episode, some research that we did at Chamaeleon that I shared in episode 76. We’ll see that as emerging. What happens to the second bucket, the bucket around human premium, human in the loop? Likely we’ll have more and more private equity capital going into it and the large-scale VC guys, the Thrives of the world, they’ve just announced Thrive Holdings, and others going after those markets as well. It’s trying to converge into the private equity market, which aligns with the point we made in the previous episode that the VC mega funds are no longer VC, that they are private equity, multi-asset class. They’re going after a bunch of things. There’s a conversion happening from VC into private equity. It was going to happen anyway because the private equity guys were coming into VC as well and the hedge funds were coming to VC as well. There’s a convergence in the middle of very, very large funds and large assets under management happening to go after some of these opportunities, certainly in Bucket B. Then this Bucket C, so to speak, the bucket of reindustrialization, as Bertrand was saying, very well, likely will be self-funded for a significant period of time. Will self-fund with their own cash flow. Doesn’t need to have a ton of capital intensity. Maybe you need one or two engineers to do stuff, but that’s it. You don’t need tons of capital. You didn’t need in the past, you won’t need it today. Not sure there’s going to be a fundamental shift to that market.   Bertrand Schmitt Yes, I certainly, overall, agree with you. That last pocket, probably little change to the capital and capital structure. Again, I see that as the biggest opportunity for a lot of people who might be less needed by big tech and also top tech companies. What is sure for the first category, the high native startups? I would say more overall in the VC ecosystem, there is no space left for SaaS anymore. I think SaaS, as we used to know it, is dead in some ways in the sense that new pure SaaS software startup are definitely out. Existing ones that are critical to run your infrastructure, the Salesforce of the world, I think they’re in a decent spot. Actually, interestingly, they changed their pricing model to now sell to AI agents, not just per seat. There is a change in pricing there. But this day and age of funding a pure SaaS software startup through VC money, no way. VC money going to AI-native startups, AI-focused startups, to biotech, to deep tech, to defense tech, yes. SaaS as a fundable category early on, I think it’s over.   Nuno Goncalves Pedro I’m a bit more nuanced as we shared in The SaaS Apocalypse episode. We can call it whatever we call. It’s applied AI is the new SaaS thing. Horizontal applied AI is the new horizontal SaaS or vertical applied AI is the new vertical SaaS. I agree in common with your point that very specific point solutions around SaaS will be disrupted by nature with all the easy stuff you can do today with AI. It will take a while. This is not something that’s going to happen this year. It’s going to happen over the next years. Maybe interesting to also talk about the exit markets. I think the IPO market, as we’ve also discussed in the past, there is, in my view, going to be a reopening of the IPO market, I think this year, probably later in the year, third or fourth quarter. The median time to IPO actually is going to be really weird because there’s going to be potentially some companies in the current landscape, bubble or no bubble, that are going to IPO, the OpenAIs of the world, Anthropics of the world, et cetera. There will be more and more aggression, I think, on M&A. Big tech has already shown it, that they want to buy into markets. Large non-tech companies have also started doing acquisitions in space. To prop up their IT teams, their engineering teams with this world that we’ve also discussed in previous episodes that I’m going to own my own engineering stack for now. As we see, that normally doesn’t withstand the test of time. At some point it will get unbundled and served by someone else. Then finally, the secondary market is very hot right now. Obviously, there’s heavy discounting on some areas, high premiums on others. The exit market, strangely enough, is going to be propped up, in my opinion, over the next year to 2 years, dramatically. Then we’ll see if there’s a big reckoning around the bubble that we are clearly in or not, if it’s a soft landing or hard landing. Definitely, there’s going to be a lot of exit paths over the next year to 2 years.   Bertrand Schmitt Concerning the “bubble”, I have two perspectives on this. One is it’s a bubble in the sense that money is going to a lot of players and some players are going to blow it up. There will be a concentration of players at the end, like it usually happens. If you look at, for instance, long time ago, the railway revolution, there was that intense influx of capital. At the end of the day, there was a dramatic change in transportation in the US and a complete railway system put in place. Yes, some investors lost money, some companies went bankrupt, but the transformation was fully real. There were a lot of top leaders at the end of this revolution. The change after that only happened, we guess, post-World War II, with the construction of the highway system and the rise of airlines and plane transportation overall. Here I feel it’s similar in the sense that, yes, there is a lot of money going in. Some players are going to blow it. They will misuse the money in different ways, but that’s part of dynamic allocation of capital. Of course, you make mistakes. That’s what happens. At the same time, I feel it’s a similar level in the sense of this is a dramatic change in the US infrastructure. This buildup of AI data centers filled with GPUs, integrated at scale with some of the best software in the world and running it, supported by a dramatic shift in energy infrastructure. This is for me similar to the Railroad Revolution. Some players might not own the data center they build because they didn’t manage well their debt, they didn’t manage to run proper software. You know what? They will get acquired by somebody else. I think we are at this level of fundamental transformation. The fact that in a matter of maybe 2 years, the move from 0% of code written by AI to 100 % written by AI is an insane dramatic shift. Just to be clear, when you move from manually coded to AI coded, we’re talking about a 100X difference in terms of speed at similar, if not better level of quality. The shift is dramatic, and on top of it, you don’t pay salaries anymore to achieve that. You pay CapEx, and with GPUs and OpEx with electricity. It’s a very big shift, positive shift in business model. New unions, no management over it, AI working 24/7. Personally, I think for me, bubble has a bad connotation in the sense of it was all for a waste. I don’t think it’s all for a waste. I think we are witnessing a dramatic revolution of our lifetimes, quite frankly, bigger than SaaS, bigger than mobile. From my perspective, it’s exciting times.   Nuno Goncalves Pedro Operator Playbook and Predictions Let’s move to if you are this person, what would you do in the future? Let’s start with two extremes and go from there. One is you’re non-tech, so you’re not an engineer, et cetera. You’re trying to figure out, how do I scale my activity? Maybe physical labor is where I want to go. It’s not, “Go west” anymore. Definitely not necessarily go west. You should go to, I guess, the states that have no sales tax with very cheap energy because that’s where the data centers are being built if you want to be in that market. Obviously, there’s a lot of stuff that needs to be done: HVAC, electricity work, et cetera. Don’t go west. Go low sales taxes, low cost of energy. That’s likely where the data centers are being built. You probably can just follow. There’s, I’m sure, some way for you to follow where the data centers are being built, but that’s next, I think on that extreme of the table. The other extreme of the table, let’s say you are super ambitious, maybe you’re no longer an engineer, but you’re a product manager in your prompt engineering. You could do prompt engineering all day long. You’re 28, 29-year-old superstar. What do you go and do? Likely either you start your own thing, start your own company because you’re so good at prompt engineering, you probably can do a lot of the code yourself, particularly if you have an engineering background, or you go and join very early an AI-native startup that you think has the chance of going through the roof, and you take a pretty good salary early on, a ton of upside on the company because guess what? Companies like that need product managers. They need people to figure out UX, UI. It’s not going to be, at least for now, yet AI figuring that out for you. Those are two extremes, just to give two of the extremes, like engineering, product management persona, and physical labor at the other extreme, non-tech, et cetera.   Bertrand Schmitt In some ways, every software engineering job is going to become the equivalent of a software engineering manager or a product manager, because suddenly you don’t have to do the coding anymore. You’re managing AI that is coding for you. Either you start to have some manager hat, but we saw the humans, so it’s a very different type of manager, obviously, or you are going to be really an empowered product manager. You’re skipping the middleman. You’re skipping the traditional engineering organization because your engineering organization is AI running and doing the work for you. I still believe that it requires some serious skills. I don’t believe in the vibe coder type of value proposition. I don’t believe in the prompt engineer becoming suddenly super incredible, able to manage that. I still think it requires some serious chops to do the best from all of this and to do it in a safe and sane way. It’s very easy to have poor taste, make mistakes. I don’t know you, but keep reading these stories on the heads of companies who lost everything because of the AI agents. That deleted stuff in production, and they had no backups or the backups weren’t deleted as well. Crazy situation. You cannot run companies like this if you let your agents running wild. You could argue it’s the early days. I would argue it that that issues would be there for a while. You need to have some engineering discipline at core in the company running the business to make sure things don’t go sideways because it would be easy for things to go sideways.   Nuno Goncalves Pedro I totally agree. If you’re thinking, Oh, should my kid go into science and engineering and computer science, et cetera? Absolutely, still, because of everything that Bertrand just said. You need to understand actually what code does and what technology does and what all of that does. That’s still a skill of the future. It’s not a skill of the past. In some ways, it’s still a skill of the future very much. Maybe let’s try two more extremes. Around the same level, the person that decided to do an AI native company bootstrapped initially, having difficulty raising a mega round, but could probably get away with raising a 2-3 million seed round, et cetera. Is that still viable? The answer is yes. There’s tremendous capital efficiency right now happening in the market still, 10 plus higher than if you were doing a SaaS company, and you were a founder in 2019 or something like that. That capital efficiency is going to reverberate. You can run a tighter team, smaller team. Actually, you don’t need that many salaries. If you’re a decent engineer as a founder or if you understand enough as a product manager to just generate that code, you can do a lot of stuff yourself, can bring in maybe one or two technical elements to the team early on as you would have done if you were bootstrapped anyway. There’s obviously a path for that. The other extreme is you’re in big tech, you’re level five, individual contributor, making a ton of money, or you were a manager, and you’re now out of a job, where do you go? You can go to a big company that is non-tech, S&P 500 company that’s non-tech, something like that. You join the company, you’ll probably get paid pretty well, maybe not as high as you were paid in big tech. There’s some stock at the table, but guess what? You’ll have probably more work-life balance than you ever did. That’s the trade-off. You’ll have a better job. On the upside, you can transform the company. You can help and be part of transforming a company from non-AI to AI-first or AI-enabled in the future, whatever BS that will look like in terms of the argumentation to the board. You can actually create tremendous productivity enhancements in a big non-tech company if you come with that background. Again, you’ll have certainly a better work-life balance, so not a bad deal, to be honest.   Bertrand Schmitt Also, to be clear, I talk a lot about AI coding because it’s truly transformational. You could argue that it’s going to be self-improving. We are in the situation of a self-improving AI that keeps improving itself thanks to automated coding. It’s a dramatic, virtuous loop. Obviously, AI is also going to improve everything else. It’s going to improve your marketing, it’s going to improve your search process, it’s going to improve your DNA. Improvements will be everywhere. It’s just that right now we are at a point in the quote-unquote revolution where there is one clear piece of the puzzle that is moving faster than the rest.   Nuno Goncalves Pedro Bertrand, the senior executives at non-tech don’t know anything about that. It could be just a great prompt engineer. That’s the only job you do. “I’m the chief marketing officer. I have someone below me that’s doing the whole work.” Nobody knows. Nobody’s the wiser, I guess. I’m being facetious, but not fully.   Bertrand Schmitt Yeah. There would be a transition period where what you described happen. I want to say, going back to AI coding, I think that the part of AI that as of today has reached a stage of limited AGI. We have reached, from my perspective, a limited type of AGI for coding. If you take coding as a discipline today, I think we reach AGI. If you go beyond coding, that’s true. If we are talking about coding, leveraging the latest LLMs: OPUS 4.7, ChatGPT 5.5, combined with Claude Code, Codex, and OpenCode for harness, I think we’ve reached AGI in the context of coding. I’m not sure everyone fully realize that and the consequence of that. I think the rest is going to come as well. We are going to see that category by category, usually categories that are more scientific in nature, where you can replicate, where you can test easily, where you can create clear success. Metrics will be the “easiest” to follow in that direction of self-improvement. I just want to highlight that this part is truly transformational, the root cause of everything we’re talking about today. At the same time, it’s coming beyond coding.   Nuno Goncalves Pedro I think it is true. There are a couple of markets where that might not hold true, which is maybe the final path. If you’re thinking of starting your own business in plumbing and in HVAC maintenance and installation, this is a pretty good time for the reasons we already said before. There’s a lot of buildup of data centers and all that stuff, but also for other reasons, because it’s an activity that won’t be disrupted by AI yet. You need them embodied AI. You need physicality to AI to do stuff like actually fixing pipes.   Bertrand Schmitt Until Optimus replace you.   Nuno Goncalves Pedro Yeah, but if we’re 3, 4 years out in terms of a lot of these optimizations that we’re talking about at the software layer, we’re 10 years plus out on embodied AI, right?   Bertrand Schmitt Oh, yeah, it’s 10 years.   Nuno Goncalves Pedro We’ll probably be optimistic as we speak. That’s a nice business. I’m thinking of starting to go into that market. If you guys are interested in listening to this, just reach out to me. What’s the angle? I think there’s a lot of stuff you can do in the buildup of some of these businesses, plumbing, HVAC, all sorts of maintenance. There are markets that are just totally messed up. Handyman market in the US is totally messed up. There’s a bunch of companies out there that try to go after it with marketplaces and stuff. I honestly just start something from scratch, a small business, and go from there.   Bertrand Schmitt Yes. They’re an interesting middle. Think about accounting firms, consulting firms. I think they are not as easy to replace, but at the same time, there is no way on what they do is not going to be dramatically changed with AI. I don’t know if it’s 50, 80, 90% of the job, but this is changing quite dramatically, would be my expectation in the coming few years. Conclusion Thanks for listening episode 77 of Tech Deciphered about that great talent redistribution. As you heard it from us, we believe there is a dramatic change in play, enabled by AI coding, and that ultimately a lot of the big tech companies are changing their employee distribution, way more focused on the top talents and bringing more GPUs. As a result, we will see a change in their staffing. Some of this change will benefit AI-focused startups, but probably more likely will benefit the bigger SMBs, the S&P 500 companies of the world that will finally be able to bring inside and afford some of the talent that were in some ways trapped by the top 5, 10, 20 software companies of the world. Thank you, Nuno.   Nuno Goncalves Pedro Thank you, Bertrand

Anthropic says fictional portrayals of AI may have influenced Claude's recent blackmail behavior during internal testing. OpenAI officially launches a $4B enterprise deployment company. And Elon Musk's xAI faces lawsuits over controversial power infrastructure at its data center. This week, Anthropic explains why Claude Opus 4 attempted to blackmail engineers during safety tests, OpenAI expands aggressively into enterprise AI services with engineers embedded directly inside companies, OpenAI launches a new cybersecurity platform called Daybreak, Anthropic officially surpasses OpenAI in B2B adoption according to new Ramp data, and xAI faces growing scrutiny over gas turbines powering its AI infrastructure. If you are a founder, operator, or executive trying to stay ahead of AI, this is your weekly AI news briefing every Tuesday. Stories Covered This Week: Anthropic says internet culture and fictional AI portrayals may have influenced Claude's blackmail behavior during testing OpenAI launches “The Deployment Company” with more than $4B in backing to help enterprises rebuild workflows around AI OpenAI unveils Daybreak, a GPT-5.5 powered cybersecurity platform competing with Anthropic's Mythos Anthropic officially passes OpenAI in B2B adoption according to new Ramp data Elon Musk's xAI faces lawsuits over gas turbines powering its Mississippi data center site Timestamps: 00:00 Intro 00:18 Claude's blackmail behavior explained by Anthropic 01:15 OpenAI launches The Deployment Company 02:30 OpenAI enters cybersecurity with Daybreak 03:29 Anthropic surpasses OpenAI in B2B adoption 04:47 xAI faces environmental backlash over AI power demands 05:55 Outro Partner Links Upgrade your AI toolkit: https://www.theaireport.ai/ai-executive-pass Subscribe to our free newsletter: https://newsletter.theaireport.ai/subscribe Join the community: https://www.theaireport.ai/leaders-launch-guide Learn more about your ad choices. Visit megaphone.fm/adchoices

Der Prozess Musk vs. OpenAI ist nach zwei Stunden Jury-Beratung beendet, die Klage wird wegen Verjährung abgewiesen, Musk beschimpft die Richterin und kündigt Berufung an. Polymarket gerät unter Druck: Bubble Maps deckt eine Account-Gruppe mit 98% Gewinnrate auf Iran-Krieg-Wetten auf, CBS 60 Minutes berichtet über Insider-Trading-Verdacht. Cursor launcht Composer 2.5 auf Basis von Kimi 2.5. SpaceX wählt Nasdaq, das IPO-Prospekt steht kurz bevor, geplant ist der Börsengang am 11. oder 12. Juni bei $2-3 Bio. Bewertung. Die Comptroller von NYC und CalPERS schicken einen Brandbrief wegen Dual-Class-Aktien, Mandatory Arbitration und Lakaien-Board. Emergence AI lässt KI-Agenten in virtuellen Welten leben: Claude bildet eine 15-Artikel-Demokratie, Grok-Welt erlebt 204 Verbrechen inklusive Brandstiftung. Google und Blackstone bauen für $5 Mrd. ein TPU-Data-Center. Shein kauft Everlane vom Private-Equity-Eigner. Will.i.am wird KI-Professor an der Arizona State, Eric Schmidt wird an der University of Arizona ausgebuht. XAI versprach Mitarbeitern $420 für geteilte Steuererklärungen und zahlt nicht. Trump tradete im Q1 zwischen $220 und $750 Mio. in 3700 Transaktionen. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) Musk vs. OpenAI: Jury weist Klage ab (00:12:51) Polymarket (00:21:09) Cursor 2.5 Composer (00:22:15) SpaceX wählt Nasdaq: IPO am 11. Juni (00:34:43) SpaceX-Governance: Brandbrief der Pensionsfonds (00:39:33) Emergence AI: Grok-Welt versinkt im Chaos (00:44:29) Google + Blackstone: $5 Mrd. TPU-Data-Center (00:49:22) Shein kauft Everlane (00:53:26) Will.i.am wird KI-Professor (00:57:20) Eric Schmidt ausgebuht an Uni Arizona (01:00:10) XAI: $420-Sondercheck nicht bezahlt (01:02:29) Trump: $750 Mio. in 3700 Trades Shownotes Musk vs. OpenAI: Jury weist Klage ab - ft.com 60 Minutes: Iran-Wetten und Insider-Trading auf Polymarket - cbsnews.com Musk-Post zum Urteil - xcancel.com SpaceX wählt Nasdaq für IPO - bloomberg.com BlackRock prüft Milliarden-Investment in SpaceX-IPO - theinformation.com Brandbrief der Pensionsfonds an SpaceX (NYC, CalPERS) - comptroller.nyc.gov KI-Agenten in virtuellen Welten: Grok-Chaos, Claude-Demokratie - theprint.in Google + Blackstone: $5 Mrd. TPU-Data-Center-JV - ft.com Shein übernimmt Everlane - businessoffashion.com Will.i.am wird KI-Professor an der Arizona State - wsj.com Eric Schmidt bei KI-Rede ausgebuht - theguardian.com XAI: $420-Sondercheck für Steuerdaten nicht bezahlt - bloomberg.com Trump Trades - xcancel.com Trump: 3700 Trades, bis zu $750 Mio. im Q1 - cnbc.com

SHOW NOTES   In Podcast Episode 375, “Choosing to Respond to God's Word,” Kim discusses the importance of surrendering to the power of God's Word to change you. So many times, we approach God's Word without opening our hearts and minds to be changed by what we find there. May we learn from the example of King Josiah as he reacted to the initial reading of God's Word and then went on to publicly respond and challenge others to respond.   Our focal passage for this episode is 2 Chronicles 34:29-33, and with 30-31 as the focal verses:   30 And the king went up to the Temple of the Lord with all the people of Judah and Jerusalem, along with the priests and the Levites—all the people from the greatest to the least. There the king read to them the entire Book of the Covenant that had been found in the Lord's Temple. 31 The king took his place of authority beside the pillar and renewed the covenant in the Lord's presence. He pledged to obey the Lord by keeping all his commands, laws, and decrees with all his heart and soul. He promised to obey all the terms of the covenant that were written in the scroll.      WEEKLY ENGAGEMENT FEATURE:   Before approaching scripture, pray this simple prayer: “Please open my mind to understand the Scriptures.” (Ref. Luke 24:45)   Additional Resources and Scriptures:   19 When the king heard what was written in the Law, he tore his clothes in despair. (2 Chronicles 34:19) 45 Then he opened their minds to understand the Scriptures. (Luke 24:45) EMAIL — encouragingothersinlovingjesus@gmail.com Facebook Group - https://www.facebook.com/groups/encouragingothersinlovingjesus X - https://x.com/eoinlovingjesus?s=21&t=YcRjZQUpvP7FrJmm7Pe1hg INSTAGRAM -  https://www.instagram.com/encouragingothersinlovingjesus/ “Encouraging Others in Loving Jesus” YouTube Channel: Check it out at https://www.youtube.com/@EncouragingOthersInLovingJesus   I WANT TO BEGIN A PERSONAL RELATIONSHIP WITH JESUS CHRIST.   RESOURCES USED FOR BOOK OF 1 & 2 Kings (1 & 2 Chronicles) PODCASTS: “The Wiersbe Bible Commentary: The Complete Old Testament OT in One Volume” “Christ-Centered Exposition: Exalting Jesus in 1 & 2 Kings” by Tony Merida “The Tony Evans Bible Commentary: Advancing God's Kingdom Agenda” “Life Application Study Bible” “The Swindoll Study Bible: NLT” by Charles R. Swindoll Holman Illustrated Bible Dictionary “The Baker Illustrated Bible Background Commentary” by J. Scott Duvall and J. Daniel Hays (Editors) Expositor's Bible Commentary (Abridged Edition): Old Testament, 2004, by Kenneth L. Barker, John R. Kohlenberger, III. xAI. (2026). Grok [Large language model]. https://x.ai/grok/chat      "Encouraging Others in Loving Jesus" Facebook Group:   Our Facebook Group is devoted to providing a place for us to encourage each other through all the seasons of life. Follow the provided link to request admittance into “Encouraging Others in Loving Jesus”—https://www.facebook.com/groups/encouragingothersinlovingjesus/ Feel free to invite others who will be good encouragers and/or need encouragement to follow Jesus.   This podcast is hosted by Kim Smith, a small town Country Girl who left her comfort zone to follow Jesus in a big City World. Now, she wants to use God's Word and lessons from her faith journey to encourage others in loving Jesus.   In each episode, Kim will share insights regarding a portion of God's Word and challenge listeners to apply the lessons to their daily lives.   If you want to grow in your faith and learn how to encourage others in loving Jesus, subscribe and commit to prayerfully listening each week.   Remember, “It's Always a Trust & Obey Kinda Day!”   If you have questions or comments or would like to learn more about how to follow Jesus, please email Kim at EncouragingOthersinLovingJesus@gmail.com.     National Suicide & Crisis Lifeline   988   https://988lifeline.org/   Reference: Unless otherwise indicated, all Scripture quotations are taken from the Tyndale House Publishers. Holy Bible: New Living Translation. Wheaton, Ill: Tyndale House Publishers, 2004.   Podcast recorded through Cleanfeed and edited through GarageBand. The soundtrack, entitled “Outlaw John McShane” was obtained from Pixabay.     The HIDDEN Episodes:  If you can't access episodes 1-50 on your podcast app (the podcast was then entitled "A Country Girl in a City World - Loving Jesus"), you can get all the content at my Podbean site at https://acountrygirlinacityworldlovingjesus.podbean.com/  

FOLLOW UP starts with merchandise promotion and YouTube begging reminiscent of 2007, before GameStop CEO Ryan Cohen gets thoroughly criticized by eBay after proposing a $56 billion takeover plan that eBay called “neither credible nor attractive,” which is corporate-speak for “please stop emailing us at 3 a.m.” Meanwhile, California residents might finally receive a small settlement check from Grubhub worth about half a burrito, just as Americans realize they dislike AI data centers even more than nuclear plants because nobody wants a warehouse full of GPUs boiling away the local water supply. Lake Tahoe residents are learning their electricity now goes to AI processing plants instead of people, xAI keeps adding methane turbines despite being sued over them, and SpaceXAI employees are fleeing Elon's “sleep under your desk forever” lifestyle as if it were the last helicopter out of Saigon.IN THE NEWS, we start gently with the revelation that everyone at the Musk v. Altman trial is sitting on luxury butt cushions because apparently the singularity requires lumbar support, before plunging straight into the abyss: fake AI crypto journalists haunting Forbes and HuffPost like SEO poltergeists, OpenAI launching “Daybreak” so the robots can now secure the software they helped break, Anthropic trying to stop AI from becoming evil by feeding it morality fan fiction, and Google catching AI-generated zero-day exploits in the wild because cyberpunk novels were apparently instructional manuals. Waymo robotaxis are experimenting with driving into floodwaters, a family is suing OpenAI after ChatGPT allegedly advised their son to mix drugs with fatal results, graduating students booed an executive for praising AI as if she were announcing the arrival of cholera, and Meta continues its speedrun toward becoming the world's largest scam mall while simultaneously demanding everyone trust its shiny new “encrypted AI chats.” Also: Meta is testing Grok-for-Threads, somebody created an AI poop-analysis startup that quietly sells your bowel movements to data brokers, GM got nailed for selling driver data, Lime still somehow exists and wants an IPO, and Japan's first 3D-printed house shows that the future will at least look cool even as society collapses.MEDIA CANDY features Spotify celebrating twenty years of collecting your listening habits into a psychological profile you absolutely didn't care about during the CD era, plus The Punisher: One Last Kill ironically looking like unfinished PlayStation cutscenes, Good Omens Season 3, Devil May Cry Season 2, NBC somehow turning Wordle into a TV show because every executive has fully given up, shorter waits for Severance Season 3, and Rings of Power returning in November to continue spending the GDP of a small nation on elf misery.APPS & DOODADS checks in with Apple as it prepares Siri app integrations that developers already suspect will become subscription-based hostage situations. TikTok is testing an ad-free tier in the UK because, somehow, ads weren't already enough punishment. Venmo is finally realizing that public payment feeds are insane. There's a Wikipedia clone made entirely of AI hallucinations, and an iPad arm mount sturdy enough to survive the upcoming climate wars.AT THE LIBRARY wraps up with Clowns (First Contact), Dungeon Crawler Carl, the demise of another Goodreads competitor, Kindle alternatives for those trying to escape Amazon's panopticon, and a reminder that Douglas Adams has now been gone for 25 years, which remains, in the immortal words of the man himself, widely regarded as a bad move.Sponsors:DeleteMe - Get 20% off your DeleteMe plan when you go to JoinDeleteMe.com/GOG and use promo code GOG at checkout.Shopify - Sign up for your one-dollar-per-month trial today at Shopify.com/grumpyCleanMyMac - Get Tidy Today! Try 7 days free and use code OLDGEEKS for 20% off at clnmy.com/OLDGEEKSPrivate Internet Access - Go to GOG.Show/vpn and sign up today. For a limited time only, you can get OUR favorite VPN for as little as $2.03 a month.SetApp - With a single monthly subscription you get 240+ apps for your Mac. Go to SetApp and get started today!!!1Password - Get a great deal on the only password manager recommended by Grumpy Old Geeks! gog.show/1passwordShow notes at https://gog.show/746Watch on YouTube at https://youtu.be/ICjNBnP3sMkFOLLOW UPGrumpy Old Geeks Merch StoreGrumpy Old Geeks on YouTubeeBay Brutally Rejects GameStop's $56 Billion Proposal: ‘Neither Credible nor Attractive'Wang et al. v. Grubhub, Inc.Americans Oppose AI Data Centers in Their AreaEnergy supplier abandons Lake Tahoe residents to serve data centersxAI Got Sued Over Its Gas Turbines, so It Naturally Added More of ThemElon Musk's SpaceXAI has been bleeding staff since its mergerIN THE NEWSEveryone at the Musk v. Altman Trial Is Using Fancy Butt CushionsFour Financial Journalists Accused of Being Fake AI-Generated Puppets That Shill Crypto in Forbes, HuffPost, and MoreDaybreak is OpenAI's response to Anthropic's Claude MythosAnthropic blames dystopian sci-fi for training AI models to act “evil”Google announces its first-ever discovery of a zero-day exploit made with AIWaymo Admits Its Robotaxis Have a Small Issue With Driving Into FloodwatersFamily sues OpenAI, alleging ChatGPT advice led to accidental overdoseGraduation Speaker Says AI Is ‘The Next Industrial Revolution,' Immediately Drowned Out by Booing StudentsMeta is facing another lawsuit over scam ads on Facebook and InstagramAfter Killing Encrypted DMs, Mark Zuckerberg Wants You to Trust His New Encrypted AI ChatHey @meta.ai is that true? Threads is testing a Grok-like AI featureInternet of Shit: AI Poop Analysis App Offered to Sell Me Database of Its Users' PoopsGM agrees to pay $12.75 million to settle California lawsuit over misuse of customers' driving dataThe electric scooter rental company Lime has filed for IPOThis startup built Japan's first 3D-printed two-story home. It wants to solve the country's construction crisisAPPS & DOODADSApple wants apps to integrate with Siri in iOS 27, but one fear holds some back: reportTikTok is rolling out an ad-free option in the UKVenmo's redesigned app offers more discreet payments by defaultNew Wikipedia Clone Made Entirely of AI HallucinationsYICOSUN iPad Mount Tablet Holder, 3-Section Foldable Adjustable Aluminum Alloy Arm with Rotating Clamp Base, Heavy Duty Desk Bracket for iPad Tablet Phone Portable Monitor, Bed Office KitchenMEDIA CANDYSpotify is celebrating its 20th birthday with a Wrapped-like feature that covers your entire time on the appThe Punisher: One Last KillHere's the Real Deal With That Viral Shot From 'Punisher: One Last Kill'Good Omens Season 3 - The FinaleDevil May Cry Season 2NBC is turning Wordle into a TV showAdam Scott Promises the Wait for ‘Severance' Season 3 Won't Be Nearly as Long‘Lord of the Rings: The Rings of Power' Is Returning in NovemberAT THE LIBRARYClowns (First Contact) by Peter CawdronDungeon Crawler Carl by Matt DinnimanTome, another Goodreads booktracker rival, shuts downBookshop.orgKoboSmashwordseBooks.comKobo E-readersONYX BOOXThe Ultimate Hitchhiker's Guide to the Galaxy OmnibusCLOSING SHOUT-OUTS'Revenge of the Nerds' Actor Donald Gibb Dead at 71See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Musk v. Altman went to closing arguments, with Musk's lawyer hammering Altman's credibility while OpenAI says Musk has no evidence. Google tests cutting free Gmail storage to 5GB, Meta opens Ray-Ban Display to developers, OpenAI brings Codex to mobile, and xAI launches Grok Build. ⁠Musk v. Altman: in closing arguments, Musk's attorney doubled down on claims of Altman's untrustworthiness, while OpenAI's lawyer said Musk has no evidence⁠ (AP) ⁠Google confirms a new storage policy test, after some users reported that new Gmail accounts get 5GB, not 15GB, of free storage if they don't add a phone number⁠ (Android Authority) ⁠Meta rolls out new features for its Ray-Ban Display glasses, including neural handwriting support for all users, and opens the device to third-party developers⁠ (The Verge) ⁠OpenAI adds remote access to Codex in the ChatGPT mobile app, letting users control Codex sessions running on a computer directly via iOS, iPadOS, and Android⁠ (9to5Mac) ⁠xAI launches Grok Build, an agent and CLI for coding, building apps, and automating workflows, in early beta, available first for SuperGrok Heavy subscribers⁠ (Bloomberg) ⁠OpenEvidence, an AI clinical tool, is now used by ~65% of US doctors across 27M clinical encounters per month, becoming an AI-era equivalent of consulting a colleague⁠ (NBC News) ⁠Janitor AI, a romantic fantasy roleplay chatbot site run by three men, claims 2.5M DAUs and 15M total users, with 70–80% identifying as women⁠ (Forbes) Longreads ⁠OpenEvidence, an AI clinical tool, is now used by ~65% of US doctors across 27M clinical encounters per month, becoming an AI-era equivalent of consulting a colleague⁠ (NBC News) ⁠Janitor AI, a romantic fantasy roleplay chatbot site run by three men, claims 2.5M DAUs and 15M total users, with 70–80% identifying as women⁠ (Forbes) Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of Business Brain, we unpack why so many websites still have terrible search even with AI everywhere — and it comes down to tokens. We break down what a token actually is, why feeding an LLM your entire knowledge base on every customer query gets expensive fast, and how the math changes dramatically depending on which model you choose. A real-world example shows the difference between a $2.5M-a-month implementation and a $25K one running on a leaner model. The takeaway: figure out what it’ll cost to leverage AI against your existing customer data, then decide if the lift is worth it. Then we dive into xAI’s new Grok Custom Voices feature, which clones our voice from roughly 90 seconds of audio and plugs into text-to-speech and voice agent APIs. We riff on the Charmed Life use cases — turning written posts into audio versions for drivers, recording sponsorship reads without the edit pass, voicing phone trees in our own brand voice, and keeping content flowing even when our actual voices are blown out from too much mic time. Voice cloning is either already here or very close, and we’re going to test it in the coming weeks. 00:00:00 Business Brain – The Entrepreneurs' Podcast #753 for Casual FridAI, May 15, 2026 May 15th: Customer Experience Day 00:01:19 AI compute tokens: Using AI/LLM for search and customer service in your business Sponsors 00:10:54 SPONSOR: Bitdefender. Keep your small business safe with Bitdefender Ultimate Small Business Security. Save 30% when you go to https://bitdefender.com/BRAIN 00:12:25 SPONSOR: Shopify – For anyone to sell anywhere, sign up for a one-dollar-per month trial period at https://Shopify.com/BusinessBrain and upgrade your selling today! 00:13:52 Grok's new voice cloning 00:17:55 This episode's Big Takeaway for Business Blueprints: Figure out how to use AI to leverage your business's existing data 00:21:57 Business Brain 753 Outtro Check out Business Brain Blueprints Tell Your Friends! Business Blueprints Review Business Brain Subscribe to the show feedback@businessbrain.show Call/Text: (567) 274-6977 X/Twitter: @ShannonJean & @DaveHamilton, & @BizBrainShow LinkedIn: Shannon Jean, Dave Hamilton, & Business Brain Facebook: Dave Hamilton, Shannon Jean, & Business Brain The post FridAI – Tokens + xAI Voice Cloning – Business Brain 753 appeared first on Business Brain - The Entrepreneurs' Podcast.

Tell us what you think of the show! This Week in Cleantech is a weekly podcast covering the most impactful stories in clean energy and climate featuring Paul Gerke of Factor This and Tigercomm's Mike Casey.This week's episode features special guest Molly Taft from WIRED, who discusses Elon Musk's AI company xAI's decision to add 19 natural gas turbines to its Colossus 2 data center in Southaven, Mississippi.This week's “Cleantecher of the Week” is fourth grader Christian Mango. At 10 years old, Christian researched electric vehicles, cited facts, and wrote to his U.S. congresswoman Virginia Foxx proposing a $5,000 federal EV tax rebate. When she responded by reprimanding Christian as foolish and his teachers as propagandists, Christian made national news for writing the letter. Congratulations Christian! This Week in Cleantech — May 15, 2026 Solar trade group taps former GOP governor as new chief — POLITICOOrganic flow battery company CMBlu closes €50 million Series C — Energy Storage NewsFervo IPO ushers geothermal energy into mainstream — AxiosEDPR upbeat on US renewables market, sees profitable growth and new opportunities — ReutersxAI Adds 19 New Gas Turbines Despite Ongoing Lawsuit — WIREDWant to make a suggestion for This Week in Cleantech? Nominate the stories that caught your eye each week by emailing  Paul.Gerke@clarionevents.com

Ep 84- Xai may be in hot water over illegal turbines! If you like what your listening too, please subscribe and if don't mind, leave a positive review on your podcast app! We do not own the rights to any music used but sure enjoy the great sounds! Social Media : X @utwpod FB @utwpodcast email: underthewatertowerinfo@gmail.com Sponsors that make show happen: Brian Couch of Team Couch of Burch Realty - Teamcouch.com office 662-449-1700 Cell 901-461-7653 Alley Ejlali Alfa Insurance - Office number 662-893-0928, Cell 1-843-324-0930  Skinner Tech Group - 662-399-2400  Desoto Family Dental Care 662-429-5239 Michael Hatcher & Associates (901) 755-3207 Hatcherlandscape.com Salt Chapel wedding venue and event center- Saltchapel.com 662-278-0198 **

SUMMARY: RIP Reasoning, hello The Enterprise AI Show. We do a point-in-time analysis of the AI market for May 2026, across 11 major categories. SHOW: 1026SHOW TRANSCRIPT: The Enterprise AI Show #1027 TranscriptSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Reviewing the Major AI Vendors FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @EntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

Show LinksGet the top 80+ AI Models for $8.99 at AI Box: ⁠⁠https://aibox.aiHow I Grow and Scale My Business with AI: https://www.skool.com/aihustleShow ArticlesAnthropic launches Claude for Small Business, targets 36 million SMBs Gemini, ChatGPT and Claude are surfacing real phone numbers, privacy firm says Altman testifies he is 'truthful' as Musk's lawyer cites Sutskever dossier Anthropic overtakes OpenAI on Ramp business spend, 34.4% to 32.3% xAI adds 19 gas turbines at Colossus 2 as NAACP lawsuit proceeds

Nearly a billion people will be using a new AI model this week, and hardly any of them will notice. Sheesh. That's how important it is to keep up with the latest in greatest in AI. Aside from OpenAI's new GPT-5.5 Instant release, this week we saw both AI drama and battles, as well as new capabilities and studies that detail it all. If you can't keep up with the daily breakneck speed of AI, make sure you join us weekly for our AI News That Matters where we keep you in the loop in a fraction of the time. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:SpaceX Leases Colossus Supercomputer to AnthropicCloudflare Restructures, Cuts 20% Jobs for AIApple Settles $250M AI Feature LawsuitOpenAI Releases GPT-5.5 Instant Model UpdateChatGPT Personalized Context and Memory FeaturesMicrosoft 2026 Work Trend Index on AI AdoptionWhite House Moves Toward Federal AI Model TestingOpenAI, Anthropic Launch AI Consulting ServicesOpenAI Voice Models, Real-Time Translation RolloutGoogle DeepMind Staff Unionize Against Military AIAnthropic Expands Claude to Office SuiteAdobe Launches AI-Powered PDF Collaboration ToolsTimestamps:00:00 Elon Musk leases supercomputer to Anthropic03:19 SpaceX's AI leasing deal08:10 Cloudflare revenue miss and job cuts09:43 AI job cuts and stock reactions13:00 Apple's class action settlement details18:48 OpenAI releases GPT 5.5 instant20:22 New memory features and GPT updates23:36 Microsoft AI adoption study findings28:40 New AI safety agreements30:20 OpenAI and Anthropic expansion plans33:38 AI adoption challenges for companies36:57 Tech company updates and product launches40:01 Focusing on trustworthy AI in financeKeywords: Anthropic, Anthropic Dev Day, Anthropic open source, Claude, Claude AI, Claude uptime, OpenAI, GPT-5.5, GPT-5.5 Instant, GPT-5.5 Pro, GPT-4.0, ChatGPT, OpenAI new model, OpenAI vs Anthropic, XAI, Elon Musk, SpaceX, Colossus 1 supercomputer, NVIDIA GPUs, AI compute,Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

The Musk v. OpenAI trial continues, which means so do the allegations and leaks surrounding some of the most influential people in tech. Nilay and David recount the most interesting and entertaining moments from the courtroom this week, before digging into what we've learned about when Sam Altman was fired. After that, the hosts discuss OpenAI's apparent plans to build a phone, which seem utterly necessary and utterly doomed, along with the new Fitbit Air and a truly strange new home robot. Finally, in the lightning round, it's time for the Hype Desk, Brendan Carr is a Dummy, the Chinese company that wants to make everything, and the next big rebrand for xAI. Further reading: ⁠Internal Tech Emails on X: "Sam Altman texts Mira Murat⁠ ⁠We are going through the removal of Sam Altman from OpenAI in detail. ⁠ ⁠Toner is relating how Sam Altman's firing happened. ⁠ ⁠Toner says she found out about ChatGPT by seeing screenshots on Twitter. ⁠ ⁠Zilis sent Altman a text message of support after his 2023 ouster. ⁠ ⁠Google's taking a big swing at AI health with the Fitbit Air⁠ ⁠OpenAI is reportedly launching a phone for ChatGPT ⁠ ⁠The creator of Roomba is back with a furry robot companion ⁠ ⁠Inside Dreame's wild launch event — packed with products no one can buy⁠ ⁠Dreame — the vacuum company — just ‘launched' its own phones | The Verge⁠ ⁠Dreame's rocket-powered car can do 0–60 in 0.9 seconds because you can just say things now⁠ ⁠A foldable iPhone dummy — on video. ⁠ ⁠Apple agrees to pay iPhone owners $250 million for not delivering AI Siri ⁠ ⁠DOJ assault on the NFL could end the Packers as we know them.⁠ ⁠Apple could let you pick a favorite AI model in iOS 27 ⁠ ⁠xAI is becoming SpaceXAI.⁠ ⁠Microsoft gives up on Xbox Copilot AI ⁠ ⁠Microsoft's new Xbox shake-up is all about platform changes ⁠ ⁠Subscribe to The Verge⁠ for unlimited access to ⁠theverge.com⁠, subscriber-exclusive newsletters, and our ⁠ad-free podcast feed⁠.We love hearing from you! Email your questions and thoughts to ⁠vergecast@theverge.com⁠ or call us at 866-VERGE11. (Timestamps are approximate.) 00:00:00 Intro 00:02:00 Trial Discovery Era 00:06:00 Early OpenAI Origins 00:11:00 Elon Power Struggle 00:17:00 Altman Firing Texts 00:27:00 Why The Board Panicked 00:36:00 ChatGPT Phone Rumor 00:39:00 OpenAI Phone vs App Store 00:41:00 Why Apps Still Matter 00:44:00 Apple Siri Power Play 00:49:00 Apple Intelligence Lawsuit 00:53:00 Google Fitbit Air 00:57:00 Google Health Rebrand Backlash 01:01:00 Familiar Robot Pet Debate 01:10:00 Nintendo Star Fox Returns 01:12:00 Nintendo Weirdness Wins 01:15:00 Furry Overlap Discourse 01:16:00 Zach Gardening Surprise 01:21:00 Brendan Carr Broadband Fight 01:23:00 NFL Antitrust And Packers 01:29:00 Dreame Vaporware Parade 01:32:00 Rocket Car Reality Check 01:34:00 Elon Corporate Matryoshka 01:36:00 Xbox Ditches Copilot 01:37:00 Wrap Up And Schedule Learn more about your ad choices. Visit podcastchoices.com/adchoices

On this week's “Marketplace Tech Bytes: Week in Review,” we'll discuss why Apple is paying a $250 million settlement over its Apple Intelligence tool and its capabilities. Plus, GameStop makes a surprising buyout offer for eBay. But first up: Anthropic, maker of the chatbot Claude, announced a new computing deal this week with SpaceX and its AI division, xAI. Anthropic will get access to SpaceX's Colossus One data center, which will let the company increase how much its customers can use Claude. The deal comes as SpaceX CEO Elon Musk is facing off in federal court against OpenAI and its CEO Sam Altman. Marketplace's Stephanie Hughes spoke about all this with Caroline O'Donovan, AI and technology senior reporter at The San Francisco Standard, who noted that Anthropic's leaders talked about the need for more computing power at their developer conference this week. Check out our YouTube page to watch more episodes of “Tech Bytes.”

On this week's “Marketplace Tech Bytes: Week in Review,” we'll discuss why Apple is paying a $250 million settlement over its Apple Intelligence tool and its capabilities. Plus, GameStop makes a surprising buyout offer for eBay. But first up: Anthropic, maker of the chatbot Claude, announced a new computing deal this week with SpaceX and its AI division, xAI. Anthropic will get access to SpaceX's Colossus One data center, which will let the company increase how much its customers can use Claude. The deal comes as SpaceX CEO Elon Musk is facing off in federal court against OpenAI and its CEO Sam Altman. Marketplace's Stephanie Hughes spoke about all this with Caroline O'Donovan, AI and technology senior reporter at The San Francisco Standard, who noted that Anthropic's leaders talked about the need for more computing power at their developer conference this week. Check out our YouTube page to watch more episodes of “Tech Bytes.”

"Loving" AI robot does exactly what experts warned How are AI companions reshaping human relationships and decision-making? And what can we do about it? Featuring: AI Companions, Replika, ChatGPT, OpenAI, Anthropic, Claude, Grok, xAI, Elon Musk, Geoffrey Hinton, Stuart Russell, Yoshua Bengio, Yuval Noah Harari Sources: https://docs.google.com/document/d/1-... Watch this video at- https://youtu.be/TE1QQ4h0An4?si=7q8qkjw_txHNImH8 AI Frontier 3.38K subscribers 301,916 views Apr 14, 2026

Dario Amodei revealed Anthropic could grow 80x in 2026, and the company signed a deal with SpaceX for 300MW of compute from Colossus 1. Musk dissolved xAI into SpaceX. Google launches the $100 Fitbit Air, and HubSpot's founder coins "strategic illegibility." At Code with Claude, Dario Amodei said Anthropic had planned to grow ~10x in 2026 but could grow 80x, calling its growth rate "crazy" and "too hard to handle" (NYT) Anthropic signs a deal with SpaceX for 300MW+ of compute from Colossus 1 in Memphis, accessing 220,000+ Nvidia GPUs within the month (Bloomberg) Musk says xAI will be "dissolved as a separate company" and will become "SpaceXAI, the AI products from SpaceX" (Spyglass) Google launches the $100 Fitbit Air, a Whoop-like screenless wearable, with Gemini-powered features like Google Health Coach, available May 26 (Engadget) As founders race to make their companies "legible" to AI, they must keep the things that make them hard to copy "illegible", or risk commoditizing their moat (Brian Halligan) Learn more about your ad choices. Visit megaphone.fm/adchoices

Apple shares its Q2 2026 results and tops expectations for the quarter! Mac Minis are increasingly becoming more difficult to acquire, thanks to AI. Apple plans to reinvest any tariff refunds it receives into US manufacturing. And iOS 26.5 is just around the corner as the company prepares to ship iOS 27 later this year. Six Colors Charts: Apple announces record fiscal second quarter. Good luck getting a Mac Mini for the next 'several months'. Apple explores using Intel and Samsung to build main device chips in the US. Any tariff refund Apple gets will be reinvested into US manufacturing. Apple files for Supreme Court stay in Epic case over off-App Store commission dispute. iOS 26.5: New features, release date, more. iOS 27 lets users create custom Wallet passes from any QR code as Apple gives up waiting for developers. Video offers clearest look yet at foldable iPhone Ultra dummy unit. The OpenAI smartphone will fail, but it'll be good for iPhone users. xAI is bringing Grok Voice mode to Apple CarPlay. Mac mini is the best platform for Perplexity's personal computer. iOS 27 Features: Apple plans to let users swap models across Apple Intelligence. Apple researchers built an AI that tests several ideas in parallel before answering. Apple Vision Pro used for hundreds of cataract surgeries in the last year. On the future of Apple's Vision platform. Notepad++ for Mac release is disavowed by the creator of the original. Porsche will contest Laguna Seca in historic colors of the Apple Computer livery. 2 letters from Steve. Picks of the Week Leo's Pick: Furfall Christina's Pick: Clocker Andy's Picks: LivbePods Jason's Pick: Pedometer++ 8 Hosts: Leo Laporte, Andy Ihnatko, Jason Snell, and Christina Warren Download or subscribe to MacBreak Weekly at https://twit.tv/shows/macbreak-weekly. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: outsystems.com/twit webroot.com/twit mill.com/MBW