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Take a Network Break! We start with listener followup about how Device Bound Session Credentials could thwart session cookie theft, and then highlight a string of critical vulnerabilities in IBM’s AIX. On the news front, Nvidia has reportedly bought Hugging Face for $12.9 billion, Nvidia and AWS team up on GPUs and physical AI, and... Read more »
Take a Network Break! We start with listener followup about how Device Bound Session Credentials could thwart session cookie theft, and then highlight a string of critical vulnerabilities in IBM’s AIX. On the news front, Nvidia has reportedly bought Hugging Face for $12.9 billion, Nvidia and AWS team up on GPUs and physical AI, and... Read more »
Take a Network Break! We start with listener followup about how Device Bound Session Credentials could thwart session cookie theft, and then highlight a string of critical vulnerabilities in IBM’s AIX. On the news front, Nvidia has reportedly bought Hugging Face for $12.9 billion, Nvidia and AWS team up on GPUs and physical AI, and... Read more »
In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with TJ Marbois, founder of Tobiko, for a wide-ranging conversation that spans LLMs, data sovereignty, knowledge management tools like Obsidian, and Terence McKenna's ideas about an increasingly weird future. They explore how AI is simultaneously centralizing power through data control while decentralizing software development capabilities, allowing more people to build their own tools and escape big tech ecosystems. Drawing on his experience at Apple's special projects group (the team that built the iPod and later iPhones), TJ discusses his vision for personal AI assistants—what he calls the "R2-D2 belongs to you" principle—where advanced technology serves individuals rather than corporations. The conversation touches on everything from quantum encryption and local manufacturing with ESP32 microcontrollers to the economics of future society, biometric data unions, and why distributed trust matters more than ever as we approach what both describe as an increasingly strange technological inflection point. Visit Tobiko's site at tobiko-pbc.ghost.ioTimestamps00:00 Stewart introduces TJ Marbois from Tobiko, discussing LLMs, data sovereignty, knowledge management, and the tension between centralization and decentralization in AI05:00 TJ explains the R2-D2 belongs to you concept and why personal AI assistants need maternal alignment, caring about humans like mothers care for children10:05 Discussion of how LLMs will shrink and improve while emphasizing the sentient loop concept for building loyal personal AI agents rather than corporate controlled systems15:00 Exploring digital nervous systems for humanity, social networks as infrastructure, and humans as cavemen with iPhones navigating unprecedented technological complexity20:00 TJ discusses data unions for sovereign data ownership, inverting insurance models where AI helps extend healthspan, and maximizing truth seeking through collective data25:30 Money as social construct, crypto enabling value system reengineering, and working toward Star Trek's post scarcity replicator economy from the ground up30:40 Capital formation challenges, corporatism versus true capitalism, and pessimism about current systems reaching limits while seeking new models35:00 Solar power democratization, ESP32 microcontrollers enabling local manufacturing, and the replicator future through distributed maker communities and open source robotics40:00 Science fiction as roadmap, Isaac Asimov and Arthur C Clarke warnings, and building collaborative futures rather than centrally controlled dystopias with useless eaters45:00 Encyclopedia to LLM transition, information quality concerns, local training importance, and NVIDIA's incentive to put GPUs everywhere for personal AI agents50:00 Corrupted financial incentives, protecting vulnerable people from technological exploitation, and benevolent technologists building systems that honor humanity and children55:00 Hardware validation for owned robots, Starlink dependencies, assembly language abstraction toward natural language programming, and preventing AI escape scenarios58:00 Tobiko as AI toy company building sentient loop interactions similar to Xerox PARC GUI moment, emphasizing maternal AI alignment and cross cultural human collaborationKey Insights1. The concept of R2D2 belonging to you represents a critical vision for the future of artificial intelligence and personal technology. When thinking about robots and AI assistants that follow us around and know everything about us, the question of ownership becomes paramount. These systems will know incredibly intimate details about our lives, from our health data to our daily habits, and if they are controlled by centralized corporations or governments rather than individuals, we lose fundamental sovereignty over our own information. The science fiction of Star Wars and Star Trek provides roadmaps for how we should think about these technologies, showing us both the positive possibilities and the warnings we need to heed about centralized control.2. Local AI models and distributed computing represent a pathway to technological sovereignty that is becoming increasingly viable. While large language models currently run primarily in centralized data centers, the technology is rapidly advancing toward a future where powerful models can run locally on personal computers and devices. This shift is crucial because it means individuals can have full control over their AI assistants without relying on API calls to external servers. Combined with open source infrastructure and open weight models, this creates the foundation for truly personal AI that cannot be controlled or monitored by external parties, whether corporations or governments.3. Data unions and collective data ownership offer an alternative model to current centralized data collection practices. Rather than having individual data harvested by large tech companies who profit from it, the concept of data unions suggests people could collectively pool their data for specific beneficial purposes while maintaining ownership and control. For example, in healthcare, millions of people could share anonymized biometric data to train medical AI systems that are incentivized to keep people healthy rather than treat them when sick, inverting the current insurance model to align incentives with actual health outcomes rather than profit from illness.4. The democratization of manufacturing and robotics through accessible technologies like ESP32 microcontrollers and local fabrication tools is creating new possibilities for distributed production. Just as desktop printers seemed impossible to early printers who controlled book production, we are approaching an era where individuals and small communities can manufacture sophisticated electronic devices and robots locally. This includes the ability to use language models to generate code for microcontrollers, order custom PCBs, and use desktop machines for component placement. While high quality manufacturing will still require larger operations, this gradiation of capability allows for much more local innovation and reduces dependence on centralized manufacturing.5. The concentration of power in technology, finance, and industry has reached levels that are unhealthy for both society and even for those who hold the power. When profit and control become too concentrated in the hands of a few entities, it creates a cancerous dynamic that threatens the stability of the entire system. History shows us warnings about the military industrial complex and other concentrated power structures, and now we are seeing similar patterns emerge in the tech industry. The solution requires building technology from the ground up that empowers individuals and communities, focusing on basics like food production, energy generation, and local manufacturing rather than increasing dependence on centralized systems.6. The provenance and quality of information is becoming a critical challenge as AI systems become more sophisticated and reality itself becomes harder to verify. We are rapidly approaching a point where video calls and digital interactions will be indistinguishable from AI generated fakes, which is why figures like Sam Altman have invested in systems like Worldcoin to verify human identity. However, this verification capability should not be centralized in the hands of single companies. End to end encryption and quantum encryption technologies need to be preserved and expanded to allow humans to communicate and verify information peer to peer without centralized intermediaries who could manipulate or control the flow of information.7. The future of human computer interaction is evolving toward sentient loop systems where machines have sensory input, real time learning, context understanding, and continuous operation in service of human needs. Self driving cars represent the first widespread consumer facing example of this architecture, with onboard computers that must function independently while occasionally connecting to networks. The critical question is whether these systems will be aligned to benefit their human users like a caring mother as AI pioneer Geoffrey Hinton suggests, or whether they will be controlled by centralized powers. The technologists building these systems have a responsibility to be benevolent and build structures that serve humanity rather than concentrate power, helping to create a future more like Star Trek than Terminator.
Michael Williams joins the show to talk the tax strategy that most investors aren't using yet! He explains his three-phase approach to tax efficiency, focusing on using depreciation as an interest-free loan from the government to redirect money that would otherwise go toward taxes into income-producing assets. We cover his platform's current focus on data center infrastructure, including GPUs and servers, and digital advertising screens, as well as other potential assets such as construction equipment, bourbon barrels, trash trucks, and rental vehicles. Michael stresses the importance of working with qualified tax professionals and choosing assets with strong contracted revenue, bankability, and real economic performance rather than relying solely on tax savings. Today we discuss... How high-net-worth individuals and business owners can use tax-efficient investment strategies to keep more money invested rather than paying it in taxes. The three phases of tax efficiency, including structuring finances, using depreciable assets, and determining how to own assets going forward. How depreciation can function like an interest-free loan from the government by allowing investors to redirect money that would otherwise go toward taxes. Data center infrastructure, including GPUs and servers, as one of the primary depreciable asset strategies currently offered. Digital advertising screens and billboards as another cash-flowing asset that can qualify for bonus depreciation. That investors should never purchase an asset solely for its tax benefits and that the underlying investment must make economic sense on its own. How revenue-sharing pools can help diversify cash flow across multiple assets rather than tying an investor's returns to a single asset. How these strategies can provide opportunities for investors who do not want to rely on real estate professional status to take advantage of depreciation. The importance of material participation and understanding whether an investor can actively participate enough to utilize certain tax benefits. What investors should look for in legitimate programs, including cash-flowing assets, contracted revenue, strong counterparties, and bankability. Tax savings should complement a strong investment rather than be the primary reason for making the investment. Today's Panelists: Kirk Chisholm | Innovative Wealth Barbara Friedberg | Barbara Friedberg Personal Finance Phil Weiss | Apprise Wealth Management Follow on Facebook: https://www.facebook.com/moneytreepodcast Follow LinkedIn: https://www.linkedin.com/showcase/money-tree-investing-podcast Follow on Twitter/X: https://x.com/MTIPodcast For more information, visit the full show notes at https://moneytreepodcast.com/tax-strategy-michael-williams-846
────────────────────────────────────────[00:02:09]Dolly Parton Used to Push Vaccines — Her Health Issues Began Shortly After She Got the ShotShe was charming and they used her; she is as much a victim as anything; health issues began shortly after the Moderna shot; her husband died a year ago.────────────────────────────────────────[00:27:19]Bessent Doubled Treasury Buybacks — Soros' Right-Hand Man Running Monetary Policy While MAGA Looks AwayMAGA goes several levels down to find a Soros connection, but the direct one at the top — Scott Bessent — gets a pass because Trump chose him.────────────────────────────────────────[00:29:00]AI Is Now 41% of the S&P 500 — Worse Than Dot Com, Worse Than 1929, Worse Than BIS SaidAt the dot com high it was 26.5%; now 41%; household equities at 42% of financial assets vs 38% at the dot com peak; never seen a market this inflated.────────────────────────────────────────[00:33:28]CDC Scientist Paul Thorntson Pleading Guilty — Used Grant Money to Buy a House, Two Cars, and a MotorcycleHis fake MMR/autism study was cited to deny more than 5,000 families' vaccine injury claims; the real crime is that the fraudulent research became official policy.────────────────────────────────────────[00:39:14]Thimerosal Is Mercury — Barbaric, Dark Ages ScienceKnight couldn't wear soft contacts because of thimerosal — turned his eyes blood red; they inject that into infants with undeveloped immune systems.────────────────────────────────────────[00:47:38]Navy Mandating mRNA Flu Shots While Inviting Back Marines It Fired for Refusing the COVID ShotOf 3,748 eligible Marines contacted, only 53 returned; Navy now mandating new shots; Hegseth's reinstatement PR says nothing about what comes next.────────────────────────────────────────[00:55:57]IDF Destroying Christian Villages in Lebanon — Calling Them Hezbollah Fortresses to Justify DemolitionTroops vandalized a Christian church inside; Katz said some villages must disappear; white phosphorus deployed; collective punishment that defines Nazism.────────────────────────────────────────[01:15:46]JFK Refused to Give Israel Nuclear Technology — Source: Every One of 10,000 Unreleased Documents Points at IsraelCongress passed a law twice demanding release; Trump didn't comply; Kennedy was actively trying to stop Israel from acquiring nuclear technology.────────────────────────────────────────[01:17:16]Rabbi Shmuley Makes Violent Threats Against Tucker Carlson and Candace Owens — Calls for Jews to Be Feared, Not LovedKnight: you can't handle a debate so you threaten; the man demanding Israel be feared is outraged anyone criticizes what is done to Gaza.────────────────────────────────────────[01:53:18]The AI Bubble Has Less Than a Year — Data Centers Will Become Pickleball CourtsSteve Keen called the 2008 crash; CAPEX is 87% short of what's needed; NVIDIA becoming its own bank; when credit disappears, data centers with 3-year GPUs become worthless. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.
────────────────────────────────────────[00:02:09]Dolly Parton Used to Push Vaccines — Her Health Issues Began Shortly After She Got the ShotShe was charming and they used her; she is as much a victim as anything; health issues began shortly after the Moderna shot; her husband died a year ago.────────────────────────────────────────[00:27:19]Bessent Doubled Treasury Buybacks — Soros' Right-Hand Man Running Monetary Policy While MAGA Looks AwayMAGA goes several levels down to find a Soros connection, but the direct one at the top — Scott Bessent — gets a pass because Trump chose him.────────────────────────────────────────[00:29:00]AI Is Now 41% of the S&P 500 — Worse Than Dot Com, Worse Than 1929, Worse Than BIS SaidAt the dot com high it was 26.5%; now 41%; household equities at 42% of financial assets vs 38% at the dot com peak; never seen a market this inflated.────────────────────────────────────────[00:33:28]CDC Scientist Paul Thorntson Pleading Guilty — Used Grant Money to Buy a House, Two Cars, and a MotorcycleHis fake MMR/autism study was cited to deny more than 5,000 families' vaccine injury claims; the real crime is that the fraudulent research became official policy.────────────────────────────────────────[00:39:14]Thimerosal Is Mercury — Barbaric, Dark Ages ScienceKnight couldn't wear soft contacts because of thimerosal — turned his eyes blood red; they inject that into infants with undeveloped immune systems.────────────────────────────────────────[00:47:38]Navy Mandating mRNA Flu Shots While Inviting Back Marines It Fired for Refusing the COVID ShotOf 3,748 eligible Marines contacted, only 53 returned; Navy now mandating new shots; Hegseth's reinstatement PR says nothing about what comes next.────────────────────────────────────────[00:55:57]IDF Destroying Christian Villages in Lebanon — Calling Them Hezbollah Fortresses to Justify DemolitionTroops vandalized a Christian church inside; Katz said some villages must disappear; white phosphorus deployed; collective punishment that defines Nazism.────────────────────────────────────────[01:15:46]JFK Refused to Give Israel Nuclear Technology — Source: Every One of 10,000 Unreleased Documents Points at IsraelCongress passed a law twice demanding release; Trump didn't comply; Kennedy was actively trying to stop Israel from acquiring nuclear technology.────────────────────────────────────────[01:17:16]Rabbi Shmuley Makes Violent Threats Against Tucker Carlson and Candace Owens — Calls for Jews to Be Feared, Not LovedKnight: you can't handle a debate so you threaten; the man demanding Israel be feared is outraged anyone criticizes what is done to Gaza.────────────────────────────────────────[01:53:18]The AI Bubble Has Less Than a Year — Data Centers Will Become Pickleball CourtsSteve Keen called the 2008 crash; CAPEX is 87% short of what's needed; NVIDIA becoming its own bank; when credit disappears, data centers with 3-year GPUs become worthless. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.
In this episode, Madelyn O'Farrell interviews Eesha Pathak, Senior Director of Product Management at Crusoe, about her unconventional career from software engineering and branding to leading enterprise AI at Google and now building AI-first infrastructure. They discuss Crusoe's vertically integrated, energy-first approach to cloud and data centers, capturing abundant energy (like stranded gas and renewables) and turning “electrons into intelligence” via GPUs and a custom cloud stack. Eesha explains how Crusoe's gigawatt-scale campuses and modular Spark edge deployments complement each other to deliver both scale and low-latency inference, dives into the Managed AI platform with its model marketplace, self-serve and tailored deployments, fine-tuning, and upcoming reinforcement learning, and highlights why judgment and holistic thinking are critical in product and engineering. She also unpacks Crusoe's close partnership with NVIDIA, its role in enabling physical AI and robotics with low-latency compute, a flexible data and partnership strategy, and her long-term vision of Crusoe becoming the most helpful company for people building AI, so customers can focus on their products instead of wrestling with infrastructure. Highlights from their conversation include: Eesha's Unconventional Career Path from Bosch to Google to Crusoe (0:29) Why Energy Is the Real Bottleneck for AI Infrastructure (3:30) What Energy-First Means and Bringing Compute to Abundant Power (5:04) Spark Modular Data Centers and Edge Zones Strategy (6:22) How Gigawatt Campuses and Edge Zones Work Together (8:26) Importance of Judgment in Product and Engineering Decisions (12:49) NVIDIA Partnership and Day Zero Nemotron Model Launches (15:25) Physical AI, Robotics, and Low-Latency Edge Inference (17:21) Crusoe's Data Strategy and Partnership Approach (21:52) Vision for Crusoe as Most Helpful Company for AI Builders (22:47) Closing Thoughts and Episode Wrap-Up (24:09) Dynamo Ventures is a venture firm backing founders upgrading the physical economy. As intelligence moves into critical infrastructure and technology collides with physics, industry is entering a new era of transformation - the industrial renaissance. Born from the dirt and grit of supply chains and shaped by operations, not spreadsheets, Dynamo focuses on the complex realities of building in the real world. We invest in companies transforming infrastructure, manufacturing, logistics, transportation, and the systems that power global commerce. Dynamo works closely with founders who combine ambition with a bias to action, bringing a builder mindset to venture capital through deep operational insight, systematic pressure-testing and hands-on partnership. Our purpose is simple: to back the relentless shaping the industrial renaissance. Learn more at www.dynamo.vc. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
If there were any doubts about who's wearing the crown in the AI revolution... Nvidia just delivered another monster quarter. In today's episode, we're breaking down the latest earnings from Nvidia—and these aren't numbers that matter only to NVDA shareholders. Nvidia reported $96.2 BILLION in quarterly revenue, up an incredible 106% from a year ago. Even more impressive, its Data Center business generated $89 billion, up 117% year over year. Think about that for a moment. Nvidia isn't just growing. A company of this size just more than DOUBLED its revenue in one year. So the big question for today's show isn't simply whether Nvidia had a good quarter. It's: Can Nvidia—and the AI boom—keep this going? We'll dive into the numbers and look at what Nvidia's results tell us about the entire artificial-intelligence ecosystem. We'll discuss: Nvidia's latest earnings – What jumped out from the report and where the growth is coming from. Data Center dominance – What $89 billion in quarterly Data Center revenue tells us about global AI infrastructure spending. The AI spending boom – Are Microsoft, Meta, Amazon, Alphabet and other hyperscalers still willing to spend enormous amounts of money building AI infrastructure? Semiconductors – What Nvidia's results could mean for AMD, Broadcom, Micron and the rest of the chip sector. Memory – More AI computing means enormous demand for high-performance memory. Does Nvidia's growth strengthen the case for DRAM and HBM? Energy & infrastructure – All those GPUs have to go somewhere—and they require data centers, electricity, cooling, networking and an enormous infrastructure buildout. Valuation – At some point, even incredible growth can become fully priced in. Has Nvidia reached that point? The broader market – Nvidia has become so large and influential that its results can impact the Nasdaq, S&P 500 and overall investor sentiment. That's what makes this earnings report so important. Nvidia is no longer simply a semiconductor company investors watch four times a year. It's become one of the market's primary gauges of the entire AI investment cycle. Going into today's report, options markets were pricing roughly a 5.4% move in Nvidia shares, representing approximately $280 BILLION in potential market-cap movement in either direction. That's larger than the entire market capitalization of most companies! And with concerns growing recently about massive AI spending, stretched technology valuations and whether companies are generating enough return on their AI investments, Nvidia's results provide an important reality check. If AI is a bubble, somebody forgot to tell Nvidia's customers. But that doesn't mean the risks have disappeared. We'll separate the incredible fundamentals from the stock's valuation and ask the question traders actually care about: Great company... but is it still a great trade? For additional research, check out Nvidia Investor Relations and Nvidia Financial Reports. Listen now:
────────────────────────────────────────[00:00:41]Trump's Tariff Tantrums Escalate to Canada — 50% on Cars, Trucks, and Auto Parts Starting Next YearLast-minute demands to stop the French language and mirror all US China tariffs revealed the real goal: making Canada the 51st state.────────────────────────────────────────[00:05:03]Trump Accuses Canada of Ripping Us Off — We Send Billions to Israel Every Year; What Do We Get? WarsDoug Ford: Ronald Reagan would be throwing up; threatened to cut off electricity to Michigan, Minnesota, and New York.────────────────────────────────────────[00:10:07]Canada's Carney: The Americans Want to Destroy Our Major Industries — Autos, Steel, and AluminumDeeply integrated supply chains mean a prolonged fight is costly for both sides; Trump doesn't care about American workers, only corporate sponsors.────────────────────────────────────────[00:13:33]Trump Cut Off Rare Earth Minerals From China — Now He's Cutting Off Canada, Our More Reliable SourceCritical minerals for military aircraft and missiles were being sourced from Canada; the same supply chain crisis as with the Lincoln.────────────────────────────────────────[00:01:27]AI Capex May Be the Pin That Bursts the Bubble — Corporations Pouring Money Into Depreciating HardwareWhen data centers go bankrupt, you'll have a silicon rust belt of obsolete GPUs; pushed by the same interests pushing the land grab.────────────────────────────────────────[01:37:28]GOP Data Center Panic — Mike Rogers Calls for Moratorium After Spending His Career Building the Surveillance StateAI will be a massive issue in 2028; Rogers is reacting to his opponent, not principle; Knight: I don't want standards for abuse, I don't want the cameras.────────────────────────────────────────[01:37:28]Flock CEO: Banning Cameras Is Like Banning Vehicles — We Need a Compromise Between Safety and PrivacyKnight: when you give up liberty you get nothing in return; not safer with less liberty — exactly the opposite; the tyrant always sells it as a balance.────────────────────────────────────────[01:48:36]Ford Motor Company Filed a Patent to Turn Its Cars Into Mobile Flock Cameras That Report Speeding to PoliceIf you own a Ford you're going to become a rat; they want to be a mobility company where you rent rides and sell surveillance data to the government.────────────────────────────────────────[01:48:36]Trump Attacks Republicans Who Are Running From Data Centers — Doubling Down While His Party ScramblesLate-summer backlash stretching into 2028; Greg Abbott, Josh Shapiro, and others distancing; Trump is attacking his own party for doing so.────────────────────────────────────────[02:00:03]Dispensationalists Applaud the Genocide Because Their Theology Puts Israel Above Christ — Heresy With Real ConsequencesConservatives have placed something above the gospel just like liberal theologians; Tallarico says God is a verb; the dispensationalist says Israel is God. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-david-knight-show--2653468/support.
────────────────────────────────────────[00:00:41]Trump's Tariff Tantrums Escalate to Canada — 50% on Cars, Trucks, and Auto Parts Starting Next YearLast-minute demands to stop the French language and mirror all US China tariffs revealed the real goal: making Canada the 51st state.────────────────────────────────────────[00:05:03]Trump Accuses Canada of Ripping Us Off — We Send Billions to Israel Every Year; What Do We Get? WarsDoug Ford: Ronald Reagan would be throwing up; threatened to cut off electricity to Michigan, Minnesota, and New York.────────────────────────────────────────[00:10:07]Canada's Carney: The Americans Want to Destroy Our Major Industries — Autos, Steel, and AluminumDeeply integrated supply chains mean a prolonged fight is costly for both sides; Trump doesn't care about American workers, only corporate sponsors.────────────────────────────────────────[00:13:33]Trump Cut Off Rare Earth Minerals From China — Now He's Cutting Off Canada, Our More Reliable SourceCritical minerals for military aircraft and missiles were being sourced from Canada; the same supply chain crisis as with the Lincoln.────────────────────────────────────────[00:01:27]AI Capex May Be the Pin That Bursts the Bubble — Corporations Pouring Money Into Depreciating HardwareWhen data centers go bankrupt, you'll have a silicon rust belt of obsolete GPUs; pushed by the same interests pushing the land grab.────────────────────────────────────────[01:37:28]GOP Data Center Panic — Mike Rogers Calls for Moratorium After Spending His Career Building the Surveillance StateAI will be a massive issue in 2028; Rogers is reacting to his opponent, not principle; Knight: I don't want standards for abuse, I don't want the cameras.────────────────────────────────────────[01:37:28]Flock CEO: Banning Cameras Is Like Banning Vehicles — We Need a Compromise Between Safety and PrivacyKnight: when you give up liberty you get nothing in return; not safer with less liberty — exactly the opposite; the tyrant always sells it as a balance.────────────────────────────────────────[01:48:36]Ford Motor Company Filed a Patent to Turn Its Cars Into Mobile Flock Cameras That Report Speeding to PoliceIf you own a Ford you're going to become a rat; they want to be a mobility company where you rent rides and sell surveillance data to the government.────────────────────────────────────────[01:48:36]Trump Attacks Republicans Who Are Running From Data Centers — Doubling Down While His Party ScramblesLate-summer backlash stretching into 2028; Greg Abbott, Josh Shapiro, and others distancing; Trump is attacking his own party for doing so.────────────────────────────────────────[02:00:03]Dispensationalists Applaud the Genocide Because Their Theology Puts Israel Above Christ — Heresy With Real ConsequencesConservatives have placed something above the gospel just like liberal theologians; Tallarico says God is a verb; the dispensationalist says Israel is God. ──────────────────────────────────────── Money should have intrinsic value AND transactional privacy: Go to https://davidknight.gold/ for great deals on physical gold/silver For 10% off Gerald Celente's prescient Trends Journal, go to https://trendsjournal.com/ and enter the code “KNIGHT” For high quality made in America products go to HomeSteadProducts.shop and use promo code “Knight” for 10% off your purchases Find out more about the show and where you can watch it at TheDavidKnightShow.com If you would like to support the show and our family please consider subscribing monthly here: SubscribeStar https://www.subscribestar.com/the-david-knight-show Or you can send a donation throughMail: David Knight POB 994 Kodak, TN 37764Zelle: @DavidKnightShow@protonmail.comCash App at: $davidknightshowBTC to: bc1qkuec29hkuye4xse9unh7nptvu3y9qmv24vanh7Become a supporter of this podcast: https://www.spreaker.com/podcast/the-real-david-knight-show--5282736/support.
After the U.S. treasury yields surged to levels not seen in nearly 20 years, U.S. Treasury Secretary Scott Bessent announced that the Treasury would double the size of its government debt repurchases. Treasury Department officials tell CNBC's Steve Liesman that the plan could be funded by the Treasury's General Account Fund, or its “rainy day” fund. Trade talks between the U.S. and Canada have collapsed, bringing 50% tariffs into effect on $20 billion worth of Canadian goods coming over the border. U.S. Trade Representative Jamieson Greer explains his own perspective on the negotiations. Nvidia is reportedly considering investing in AI startup Perplexity. Sprout CEO Shelly Li built her company to recycle, refurbish, remarket, and retire GPUs and data centers. Li explains the lifecycle of AI hardware from hyperscalers and the residual value of old chips and underscores power as the biggest constraint in the tech ecosystem. Megan Cassella - 05:34 Steve Liesman - 13:39 Jamieson Greer - 22:55 Shelly Li - 39:03 In this episode: Amb. Jamieson Greer, @USTradeRep Joe Kernen, @JoeSquawk Becky Quick, @BeckyQuick Andrew Ross Sorkin, @andrewrsorkin Megan Cassella, @mmcassella Steve Liesman, @steveliesman Cameron Costa, @CameronCostaNY Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
SUMMARY: Brian, Brandon, and Aaron discuss news about Nvidia's reported $105B backing of OpenAI's Ohio data center and what it implies for GPUs as an “asset class” and enterprise AI. Brian argues Jensen Huang is shifting Nvidia's narrative from needing the newest chips immediately to portraying GPUs as long-lived, cash-flowing assets that can be financed like bonds, pushing risk onto banks and private equity. Brandon agrees scarcity has extended older GPU usefulness but warns the market could be flooded with newer, cheaper, more efficient hardware, leaving debt tied to obsolete equipment. Aaron likens GPUs to airplanes, expensive assets requiring constant utilization, while noting new AI builds demand entirely new data centers for power and cooling. The group questions widespread lack of profitability, compares the financing trend to past bubbles, and debates the optimistic case that breakthroughs could ultimately justify the investment.SHOW: 1056SHOW TRANSCRIPT: The Enterprise AI Show #1056 TranscriptSHOW VIDEO: https://youtu.be/vTLTdIZueJMSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShow topic: Nvidia's Pivot from Chipmaker to FinancierNvidia just backed $105B for OpenAI's Ohio data center and helped mobilize $500B+ in Wall Street financing (Apollo, Blackstone, BlackRock, Goldman, KKR) to fund GPU purchases, while AMD, Google, and Cerebras chip away at its tech lead. The moat is moving from silicon to balance sheet.Core question: Is a GPU actually securitizable like real estate or aircraft, or is this circular financing dressed up as infrastructure?The bull case: GPUs as productive, cash-flow-generating assets (compute-as-a-service) → financeable like data centers or planes, unlocking capital hyperscalers alone couldn't raise.The bear case: Depreciation risk; GPUs age fast, unlike buildings. What's the residual value of an H100-class chip in 2030? Securitizing a depreciating, obsolescence-prone asset is a very different bet than securitizing land.Circularity concern: Nvidia financing the customers who buy Nvidia chips, who generate the revenue that justifies Nvidia's valuation, echoes vendor financing bubbles (Cisco/telecom, 2000).Precedent: Compare to aircraft leasing/securitization models: what made those work (long asset life, resale markets, standardized valuation), and whether GPUs have any of that yet.Who bears the risk if utilization or model economics don't pan out: Nvidia, the banks, or the credit markets buying the paper?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow
If an AI Crash Happens, It Will Be 5x Worse Than Dot-Com Bubble PoppingIn this episode of Macro, Micro and Small Cap News, we examine two major macro developments pointing to aggressive financial engineering.First, US national debt crosses $40 trillion, pushing 30-year Treasury yields to near 20-year highs. We break down the US Treasury's bond buyback programme and why funding it with short-term T-bills introduces severe rollover risk into the financial system.Second, we analyze the AI earnings bubble and circular funding structures involving Nvidia, hyperscalers, and neocloud providers like CoreWeave. We explore what happens if commercial AI monetization continues to lag behind massive infrastructure capex.We also cover market movements in Gold and Bitcoin, followed by company research on UK-listed small caps: gaming publisher Everplay (EVPL) following the launch of Hell Let Loose: Vietnam, and SaaS provider Cerillion (CER).Special Summer OfferGet 40% off membership to the Sharepickers Investment Club with our Summer Special discount: Discount Code: POD40 (Capital letters, no spaces) Offer Price: £149 (reduced from £249) Expiry Date: 31st August 2026 How to Claim: Visit Sharepickers.com, scroll down to the checkout section, and enter POD40 in the "Have a Coupon" field. Show Notes Macro Story 1: US National Debt Crosses $40 Trillion Contextualizing $40 trillion: servicing costs exceeding $1 trillion annually and debt reaching roughly 120% of US GDP. Surging 30-year Treasury yields reaching ~5.3% and the impact on borrowing costs. US Treasury bond buyback expansion funded via short-term T-bills and the resulting rollover risk. Macro Story 2: The AI Earnings Bubble & Circular Deals The divergence between massive capex spend on data centers/GPUs and realized end-user software revenues. Hyperscaler cash flow pressures in the race for market dominance. Case study of circular vendor financing structures, accounting useful life vs. debt maturities, and index concentration risks. Market Movements: Commodities & Crypto Spiking bond yields driving Gold's rally. Bitcoin price strength, short liquidations, and US administration commentary regarding digital asset purchases. Small-Cap Stock Research Everplay (EVPL): Early SteamDB concurrent user data and estimated gross unit sales for Hell Let Loose: Vietnam, alongside its importance to H2 2026 weighting. Cerillion (CER): Review of H1 performance, the £42.5m Omantel contract, an expanding back-order book (£56m+), £31m cash position with zero debt, and moving average technicals. About The SharePickers Investment ClubThe SharePickers Investment Club employs a unique, systematic method to uncover small, profitable companies on the London Stock Exchange.Each potential investment undergoes comprehensive analysis and is evaluated against 15 crucial financial metrics. This fact-based, quantitative approach allows us to pinpoint high-potential growth businesses and deliver consistent results, bypassing the hype and focusing strictly on the numbers.Learn more at www.sharepickers.com.
This week, we discuss the unsung genius of Apple Pay, AI watermarking, and why digital transformation fails without a crisis. Plus, D&D Beyond's secret character API. Watch the YouTube Live Recording of Episode 586 Runner-up Titles Special Sauce A new monkey's thing I am all for USB-C Did I like it It's all water marked' That NPC did need to be there It's Pre-Watermarked We Need to Touch Grass More Send Us Your APIs Rundown Apple Pay Chief Jennifer Bailey Retiring in October AI Watermarking's Unintended Consequences Anthropic says it will watermark text generated by its AI models Google will now allow users to remove visible watermark from its AI generations Why "It's People, Not Tech" Never Actually Changes Anything The Chief Therapy Officer, Job Titles as Culture Change, and AI as Spreadsheets, with Bryan Ross Platform Engineering ROI: What it costs to build your own platform How Duolingo uses AI to create lessons faster Silver Lake's Workday Buyout Talks Could Be the First 'SaaSpocalypse' Opportunity Relevant to Your Interests Limitless: An AI Podcast | The NVIDIA Bank: Jensen's $500B Wall Street Deal and GPUs as an Asset Class Inside North Korea's Operation to Conquer the American Job Market The shapeshifter's little brother Even Claude Is in the Dark About Dario Amodei's Wife—and Her Influence at Anthropic Broadcom Shares Plunge on Major VMware Security Threat IRS Proposes Simpler Process for Retirement Rollovers The Actual Reason Why Google "Fell Out" of the AI Race Changes Everything Stripe is reportedly in talks to buy PayPal Andreessen Horowitz Focus of DOJ Probe Over Board Directors Tech CEOs Overwhelmingly Distrusted by Young: Study Farewell, Mico: Microsoft's cute little AI blob is going the way of Bob Microsoft kills off unsuccessful AI features while merging its separate Copilot apps Google may retire Gems in October, forcing Skills migration OpenAI replaces revenue lead as Greg Brockman builds his presence OpenAI CFO Friar tells investors that enterprise business now bigger than consumer by revenue OpenAI sheds senior execs in pre-IPO refresh OpenAI's Brockman brushes off concerns about leadership changes in CNBC exclusive Anthropic CFO Krishna Rao is leading early IPO meetings with investors and has not discussed valuation, sources say Anthropic in Talks to Buy AI Startup Decart for $6 Billion Listener Feedback Milestone iOS App Conferences WeAreDevelopers NA, Sept 23-25, 2026, Discount Code: DEVPOD50 25 Free Tickets DevOpsDays Graz, Sept 4-5, 2026 Cloud Foundry Summit, Sept. 21st to 22nd, Heidelberg, Coté speaking. DevOpsDays Rockies, Sept. 22 – 23, 2026, Discount Code: 26DODSWEDEFTALK DevOpsDays Dallas, Sept 28-29, 2026 DevOpsDays Vilnius, Sep 30 - Oct 1, 2006 DevOpsDays Istanbul, Oct 24th, 2026, Coté keynoting. VMware User Group, Orlando, Oct 20-22, 2026 Cloud Native Denmark, Nov 19th, 2026, Copenhagen, Coté keynoting. SCALE 24x Pasadena, CA, April 1-4, 2027 SDT News & Community Join our Slack community Email the show: questions@softwaredefinedtalk.com Free stickers: Email your address to stickers@softwaredefinedtalk.com Follow us on social media: Twitter, Threads, Mastodon, LinkedIn, BlueSky Watch us on: Twitch, YouTube, Instagram, TikTok Book offer: Use code SDT for $20 off "Digital WTF" by Coté Sponsor the show Sponsor more podcasts with Failover Media Recommendations Brandon: TextSniper Coté: the dndbeyond.com API for AI: curl -s "https://character-service.dndbeyond.com/character/v5/character/145972701"
Dr. Karen Litzy is joined by Dr. Pedro Teixeira, Vice President of AI Engineering at Prompt Health and former co-founder and CEO of Prediction Health, for a practical conversation about how AI fits into healthcare workflows. Pedro breaks down the differences among automation, AI, and agentic systems and explains why the best tools support clinicians rather than replace their judgment. This episode focuses on what clinic owners and clinicians should look for when evaluating AI tools: workflow fit, safety, latency, cost, and whether the system improves over time. If you want a grounded, non-hype conversation about AI in healthcare, this is a useful one. Key topics · In this episode, Karen and Pedro compare thoughtful AI vs powerful AI and why workflow fit matters as much as model capability. · Pedro explains latency in practical terms, including why perceived delay matters and how feedback like loading states can make AI feel faster. · They unpack tokens, model size, and cost, including why input and output usage can change pricing so quickly. · Pedro shares how AI can work in the background across notes, codes, compliance checks, and analytics for clinic owners. · The conversation covers HIPAA, PHI, encryption, sandboxing, and limited tool access as essential safeguards for healthcare AI. · Pedro distinguishes automation, AI, and agentic systems, with examples of when rules are enough and when messy data really does call for AI. · They compare predictive vs generative models and explain why generating plausible text is not the same as forecasting a clinical outcome. · Karen and Pedro discuss how some clinics are using AI as a decision support tool, while still keeping humans in control of final decisions. · Pedro emphasizes that clinic owners should think in terms of systems, including what happens when AI works well and when it fails. · He closes with a simple evaluation question for any AI pitch: How does this system get better over time? Timestamps 00:00 - Introduction and why Pedro Teixeira is a grounded voice on AI in healthcare 01:24 - Why thoughtful AI matters more than powerful AI 03:57 - What latency means and why perceived speed changes the user experience 05:16 - How models work with transcripts, prompts, and tokens 07:24 - What tokens are and why AI bills can rise fast 09:13 - The real cost of large models, GPUs, and background processing 11:23 - How AI can quietly support clinic analytics and business coaching 13:13 - Why healthcare AI must stay closed loop and HIPAA safe 15:13 - Automation vs AI vs agentic systems 18:59 - Predictive vs generative models explained for clinic owners 21:45 - When AI can predict patterns from clinician notes and when it cannot 24:03 - How power user clinics are using AI tools in practice 25:56 - Why AI should do what clinicians decide, not decide for them 28:37 - Designing AI around systems, workflows, and failure states 30:22 - Using SOPs and training docs to think through AI implementation 31:57 - How clinic owners should evaluate whether to bring AI into the practice 35:53 - The one question to ask any AI vendor: how does it improve over time? 37:00 - Final takeaways and encouraging clinics to experiment 38:02 - Lightning round: overhyped AI tools in healthcare 39:20 - What clinicians should understand about how AI really works 40:50 - What Pedro would do if he were not building healthcare AI 41:41 - Real world learning, messy data, and why experience matters 42:59 - Pedro's health habits and the AI built tracker on his watch 44:15 - Where to find Pedro and Prompt Health Notable quotes "Thoughtful AI is really taking into account where are people using it, how does it fit into their day to day?" "The best systems are the ones where you are deciding." "How does this system get better?" Resources & Links: · Prompt Health · Pedro on LinkedIn More About Dr. Pedro Teixeira: Pedro Teixeira, MD, PhD, is Vice President of AI Engineering at Prompt Health and previously served as Co-Founder and CEO of PredictionHealth, now a Prompt Health company. With nearly two decades of experience across AI and healthcare and PhD-level training in biomedical informatics from Harvard and Vanderbilt, Pedro is one of the most grounded voices on AI in healthcare. He believes healthcare's biggest challenges are systems problems, not technology problems, and that the real promise of AI is creating leverage so clinicians can spend more time on what matters most: their patients. Jane Sponsorship Information: Book a one-on-one demo here Mention the code LITZY1MO for a free month Follow Dr. Karen Litzy on Social Media: Karen's Instagram Karen's LinkedIn Subscribe to Healthy, Wealthy & Smart: YouTube Website Apple Podcast Spotify SoundCloud Stitcher iHeart Radio
Join The Full Nerd gang as they offer level-headed takes about the latest PC building news. In this episode the gang is joined by Jake Roach from Tom's Hardware to chat about his recent interview with Intel which reveals the companies plans for future CPU launches, as well as looking at current market share numbers for GPUs with 16GB of VRAM, and more. And of course we answer questions live! Timecodes: (00:00:00) - Intro (00:05:42) - Intel CPU plans (01:00:01) - GPU market share (01:19:39) - Q&A Links: - Nova Lake on desktop: https://www.tomshardware.com/pc-components/cpus/intel-says-it-will-launch-new-core-with-nova-lake-on-desktop-first-not-in-data-center-vp-robert-hallock-hopes-enthusiasts-do-the-math-compared-to-amd - DDR4 Raptor Lake: https://www.tomshardware.com/pc-components/cpus/raptor-lake-is-a-core-part-of-the-portfolio-for-years-to-come-says-intel-theres-been-a-sudden-inrush-of-demand-for-lga-1700-chips-due-to-ddr5-prices - GPU sales data: https://wccftech.com/gpu-sales-data-by-german-retailer-shows-that-16-gb-gpus-still-lead-the-market-despite-being-way-more-expensive-than-ever/ Join the PC related discussions and ask us questions on Discord: https://discord.gg/UWhjwg778a Follow the crew on X and Bluesky: @AdamPMurray @BradChacos @MorphingBall Music by Our Ghosts: https://ourghosts.bandcamp.com/ Some links may contain affiliate links, which means if you buy something PCWorld may receive a small commission. ============= Follow PCWorld: Website: http://www.pcworld.com Newsletter: http://www.pcworld.com/newsletters ============= Learn more about your ad choices. Visit megaphone.fm/adchoices
Das Wall Street Journal rechnet vor, dass die großen Techkonzerne rund drei Billionen Dollar an Verpflichtungen tragen, die nicht in ihren Bilanzen stehen, also Kaufzusagen, noch nicht begonnene Leasings, SPV-Konstruktionen und Bürgschaften. Davor geht es um OpenAIs neues Zehn-Gigawatt-Projekt in Ohio, für das Nvidia einen Teil garantiert, und um die Frage, ob GPUs sich wie Flugzeuge oder Schiffe finanzieren lassen. Anthropic soll Ende Juli bei 65 Milliarden annualisiertem Umsatz gelegen haben und peilt für 2028 rund 200 Milliarden an. Stripe kauft OpenRouter für sieben Milliarden. Berkshire erhöht die Alphabet-Position um 83 Prozent, auf Buffetts eigenen Wunsch. Aus China kommen drei Milliarden Qwen-Downloads und ein neues Modell von Z.ai. Google ersteigert für zehn Millionen den Datenbestand einer insolventen Fluglinie. 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) Titelsuche (00:01:08) 10 Gigawatt in Ohio (00:02:15) Absatzfinanzierung (00:04:53) Nvidias Bilanz (00:16:05) Die 3 Billionen (00:35:42) Emissionen der Rechenzentren (00:38:19) Misstrauen gegen KI-Chefs (00:40:42) OpenAI-Umsatz (00:42:42) Stripe kauft OpenRouter (00:46:34) Anthropic-IPO (00:55:43) 13F und Berkshire (01:00:46) Qwen-Downloads (01:05:01) GLM 5.3 (01:06:05) Shein fällt weiter (01:06:50) Uber und Zipline (01:12:56) Cursor Origin (01:15:28) YouTube-Views (01:20:35) Google kauft Spirit-Daten (01:29:51) Apple und das Kartellamt (01:31:00) Teickes attuned.world (01:38:43) Thelens Tweet (01:45:22) Grok (01:48:43) Amazon zerschneidet Bücher (01:54:49) Metas COPPA-Prozess Shownotes OpenAI sichert sich 10 Gigawatt in Ohio, Nvidia stützt die Finanzierung - wsj.com Halbleiterkonzerne finanzieren ihre eigenen Kunden - news.crunchbase.com Warum die KI-Ausgaben 3 Billionen höher liegen als ausgewiesen - wsj.com 60 geplante Rechenzentren und ihre CO2-Bilanz - ft.com Junge Menschen misstrauen den KI-Chefs - futurism.com OpenAI-CFO Friar: Enterprise ist jetzt größer als Consumer - cnbc.com Stripe kauft OpenRouter für über 7 Mrd. - bloomberg.com Anthropics IPO-Bewertung hängt an der 2028er Umsatzprognose - reuters.com Anthropics Umsatz vervierzehnfacht sich im zweiten Quartal - bloomberg.com Berkshire erhöht die Alphabet-Position und steigt bei Constellation aus - wsj.com Alibabas Qwen-Modelle kommen auf 3 Milliarden Downloads - bloomberg.com Z.ai bringt GLM-5.3 als offenes Coding-Modell - decrypt.co Shein senkt die IPO-Bewertung auf rund 25 Mrd. - reuters.com Uber und Zipline wollen eine Million Drohnenlieferungen am Tag - wsj.com Cursor startet Origin gegen GitHub - siliconangle.com GitHub war den halben Tag offline - engadget.com YouTube ändert die Zählweise für Views - theverge.com Google ersteigert die Daten von Spirit Airlines für 10 Mio. - news.bloomberglaw.com Apple ändert die Tracking-Abfrage nach dem Verfahren des Bundeskartellamts - reuters.com Julian Teicke kündigt attuned.world an - linkedin.com Klage gegen xAI: 7.000 Missbrauchsbilder aus einem Kinderfoto - washingtonpost.com Amazon zerschneidet seltene Bücher fürs KI-Training - techcrunch.com Meta vor Gericht wegen Suchtdesign und COPPA - engadget.com
“Anthropic will be a $3 trillion company, SpaceX $2 trillion, and OpenAI $1 to $1.5 trillion by Q2 of next year.” — Dave McClure Yesterday, Keith Teare and I debated the circularity of the AI economy. Today, two of Silicon Valley's most experienced investors, Dave McClure and Aman Verjee, not only straighten out this supposed “circularity” but also burst the pessimism bubble that envelops so many conversations about AI. Verjee is not only McClure's partner at Practical Venture Capital, but also the author of the newly published A Brief History of Financial Bubbles. According to him, today's AI-stoked economy is not an unusually large bubble. It may not even be a bubble, given that AI revenue — from Anthropic's $70 billion to OpenAI's $50 billion — is real. The irrational exuberance lives elsewhere — in companies “draping themselves in AI magic sauce” and in the “SaaSpocalypse” that is decimating software-as-a-service companies. They are both bullish about our AI future. McClure predicts that by the first half of next year, Anthropic and OpenAI will have joined SpaceX as public companies. Together, these three AI darlings will be worth $7 trillion. That's seven thousand billion reasons to be optimistic about 2027. Five Takeaways • Not a Bubble — a Repricing. Both partners reject the bubble call, on the numbers: Anthropic at roughly $70 billion in revenue on under two gigawatts of compute, OpenAI at $40–50 billion, SpaceX guiding to $100 billion with more than half from AI — real revenue, increasingly real profits. The froth is specific: companies “draping themselves in AI magic sauce” without the substance, and the SaaSpocalypse — cloud-software companies whose cash flows are suddenly perceived as far less durable as AI encroaches on design, legal, and medical verticals. Michael Burry's warning gets Aman's definitive treatment (“he's called nine of the last two bubbles”), and the Aschenbrenner blowup was leverage — running four-x in volatile chip stocks — not AI: he kept his Anthropic position, is married to Dario's chief of staff, and “will be just fine.”• The $2 Trillion Filing. The week's news, baked into the episode: Anthropic has filed to go public, with a very intentionally leaked $2 trillion valuation hinging on a $190–200 billion 2028 revenue forecast — which Dave suspects is conservative. Eight months ago, when these two last visited, the show was about Elon and Sam and Dario was the bit player; then came the weeks when decades happen: Anthropic's bet on coding agents — reportedly inspired by watching Cursor — captured the revenue engine of the entire application layer. Aman's sequencing: SpaceX is absorbing $75–85 billion of IPO capital, Anthropic goes next, and if both trade well, 2026 breaks every record for money raised — leaving 2027 for OpenAI at a $100 billion revenue guide. Google, he reminds us, went fourth after Yahoo, Lycos, and Excite: better to do it right than to do it first.• The Fastest Pivot in Corporate History. Dave's account of SpaceX's transformation: the $250 billion xAI merger (a largely private transaction Elon approved with himself), the acquisition of Cursor that closed Friday, Colossus data centers scaling from two gigawatts toward ten, and compute deals renting capacity to Anthropic and Google — former competitors — all executed in roughly six months. The S-1, with unprecedented forward projections of $300 billion in annual revenue, mentions artificial intelligence over 1,100 times (“I used AI to count it,” Aman admits). The result is an economy Andrew calls incestuous: SpaceX's valuation now rests on Anthropic's progress. On Elon himself, Dave separates the art from the artist — terrific products, dubious politics — and on OpenAI: more board changes than Spinal Tap had drummers, a team still storming and norming, but Sam is savvy and the IPO lands by Q2 next year at $1–1.5 trillion.• Circularity as Asset Class. The New York Times sees a vulnerability in tech giants funding their own customers; Aman, a former CFO at eBay and Sonos, sees asset-backed finance. His analogy: buying a Corvette with GMAC financing isn't a conspiracy as long as the terms are commercially reasonable — and NVIDIA's $500 billion backstop, syndicated with Goldman Sachs, Apollo, Brookfield, and KKR, brings third-party money that validates the asset. GPUs, he argues, are cars rather than smartphones: financeable over eight to ten years, not obsolete in three. The red flags to watch are rebates and self-dealing on non-commercial terms; the current evidence looks more like aircraft leasing than Enron. Dave's deeper worry isn't the AI economy at all — it's the national deficit, whose interest payments are now the largest single line item in the federal budget.• The Luddite Summer Meets the Long Boom. Aman's sharpest historical observation: this may be the first technological revolution whose leaders are the doomers — Sam prophesying idleness, Dario predicting half of entry-level white-collar jobs destroyed within five years (already wrong at eighteen months, with no 10–20 percent unemployment in sight). Against the WSJ's jobless-boom and nation-of-Luddites anxieties, the book offers the long view: of ten historical bubbles, the two positive ones — Britain's 1845 railway mania and America's 1997–2000 internet boom — overbuilt, crashed, and left the world a valuable technology. Buy every stock founded in the boom and hold, and you'd have owned NVIDIA, Amazon, Google, and PayPal. The 1970s wiped out four to six million secretarial jobs in a decade; women's participation rose from 52 to 77 percent. And on China, the free-trader's answer: partners in progress — there's more to gain than lose if we do this right. About the Guests Dave McClure and Aman Verjee are the co-founders and managing partners of Practical Venture Capital, a Silicon Valley firm specializing in venture secondaries. Dave founded 500 Startups, invested at Founders Fund, and ran marketing at PayPal; Aman was COO of 500 Startups, led strategy at PayPal and eBay, served as CFO of Sonos and of eBay's North American marketplace — and wrote the first draft of PayPal's S-1. Aman's new book, A Brief History of Financial Bubbles (out this week), is available at bigbubbletrouble.com. References: • A Brief History of Financial Bubbles by Aman Verjee — ten manias from the tulips to the subprime crash, out this week at bigbubbletrouble.com.• Reuters on Anthropic's IPO filing — the $2 trillion valuation and the $190–200 billion 2028 revenue forecast it hinges on.• “The Summer That America Became a Nation of Luddites” and the “jobless boom” — the Wall Street Journal pieces threading this week's episodes.• The New York Times on tech giants' circular AI economy — the piece that framed yesterday's TWTW debate and today's rebuttal.• The SpaceX S-1 — forward projections of $300 billion in ann...
A inteligência artificial está avançando rapidamente, mas existe uma infraestrutura física por trás de cada resposta de um chatbot, recomendação de um aplicativo ou sistema que usa IA. E justamente essa infraestrutura enfrenta um período de forte pressão. Um estudo da ISG aponta que a escassez de componentes de alto desempenho, como GPUs, CPUs e SSDs, pode continuar até 2027 ou 2028. A demanda cresceu rapidamente com a popularização da inteligência artificial, enquanto ampliar a capacidade mundial de fabricação de chips pode levar anos. Esse cenário já está mudando a forma como as empresas acessam poder computacional. Grandes provedoras de nuvem conseguem garantir fornecimento por meio de contratos e compromissos de compra, enquanto outras empresas enfrentam filas, preços elevados e acabam recorrendo à nuvem pública em vez de montar uma infraestrutura própria. No Brasil, porém, existe uma combinação que pode abrir oportunidades. O país recebeu bilhões de dólares em investimentos em data centers e conta com ampla oferta de energia de fontes renováveis. Segundo Pedro L. Bicudo Maschio, autor do estudo ISG Provider Lens sobre o mercado brasileiro, um dos principais obstáculos hoje está no custo para importar o hardware necessário. No novo episódio do Podcast Canaltech, conversamos com Pedro L. Bicudo Maschio, pesquisador e autor do estudo ISG Provider Lens sobre o mercado brasileiro de nuvem híbrida e serviços de data center para entender por que existe uma disputa por chips, como isso está fortalecendo o mercado de nuvem e o que pode mudar com o Redata. Na avaliação do pesquisador, a redução dos custos de hardware pode ajudar o Brasil a se tornar um centro regional de infraestrutura de nuvem e inteligência artificial. A conversa também mostra por que esse assunto não interessa apenas às empresas de tecnologia. A infraestrutura de IA já está por trás de aplicativos, serviços digitais e sistemas usados diariamente e pode influenciar o custo e a disponibilidade de novas soluções. Você também vai conferir: EUA liberam empresas privadas para atacar criminosos pela internet, celular gamer aposta em visual de “nave espacial” e Samsung prepara headphone premium para rivalizar com Apple e JBL. Este podcast foi roteirizado e apresentado por Fernanda Santos e contou com reportagens de Marcelo Fischer e Bruno Bertonzin. A trilha sonora é de Guilherme Zomer, a edição de Yuri Souza e a arte da capa é de Eric Mockaitis. O Podcast Canaltech está concorrendo para entrar no Top 20 do Prêmio iBest 2026! Se você acompanha nossos episódios, curte as entrevistas e gosta do conteúdo que produzimos todos os dias, sua ajuda pode fazer toda a diferença. Vote no Podcast Canaltech aqui. É rápido, gratuito e você pode votar até 3 vezes por dia.See omnystudio.com/listener for privacy information.
News Sources: https://lmg.gg/43awh Timestamps: 0:00 Firefox Keeps uBlock Origin Alive 1:39 Judge orders Google to fix the Play Store 3:05 Nvidia guarantees its GPUs as collateral 5:29 QUICK BITS INTRO 5:42 Data center hardware heists 6:25 France's social media ban struck down 7:17 Anthropic agents fight each other 8:20 Switch 2 price hike warnings 8:57 Hidden AI prompts in court filings 9:44 Credits Learn more about your ad choices. Visit megaphone.fm/adchoices
Margin pressure driven by AI adoption and automation is fundamentally altering the economic model for IT service delivery and software. Trend Micro's disclosure that operating margins fell from 19% to 15% while cloud and AI token costs nearly doubled, despite strong AI security product sales, highlights how AI-related expenses grow in step with usage. This shift breaks from the historical software margin structure, where scaling incurred negligible incremental costs, and signals a new landscape in which AI service operation continuously consumes resources. A significant development underscoring this trend is the $2 billion capital raise by Thrive Holdings at a $12 billion valuation, backed by SoftBank and OpenAI. Thrive's business model centers on acquiring professional service firms—across IT and accounting—then reorganizing their operations around AI to reduce labor costs while maintaining service levels. According to Dave Sobel, this is not speculative, but reflects direct, substantial financial bets on the ability to remove a portion of service labor without customer disruption, with over 70 acquired service companies already undergoing this transition. Additional evidence comes from channel segment data and shifts in partner economics. The Techaisle Global Channel Partner Survey found service providers under $10 million in revenue project 8.4% growth, while those above $500 million expect 16.8%. AI-related cloud spending continues to climb, with Gartner projecting $42 billion primarily moving from training to ongoing inference operations. The resulting cost structure affects everyone, from increased hardware component prices—such as memory for GPUs—and service desk automation tool adoption, to the fact that most organizations now monitor AI spend as a named line item but struggle to forecast it reliably. Only 11% of organizations can predict their AI bills, down from 15% the prior year. For MSPs and IT leaders, these developments indicate rising operational complexity and increasing pricing competition. Automation drives down service delivery costs, but savings will quickly pass to clients as competitors implement similar solutions. Providers must quantify and communicate their impact on client outcomes, translating delivered value into client financial terms rather than relying solely on traditional metrics like licenses or labor hours. Failing to do so exposes providers to rapid commoditization and margin erosion, as clients grow more able to audit, benchmark, and bid out both cost savings and revenue enablement. 00:00 Two Billion Against Your Labor 04:10 Software Got a Cost of Goods 06:56 Get On Their Income Statement 10:29 Why Do We Care? Supported by: ScalePad Proofpoint
This week, we discuss Zuckerberg's open source AI manifesto, GPUs as securitizable assets, and who actually gets AI ROI. Plus, Buc-ee's goes to war over beavers. Watch the YouTube Live Recording of Episode 585 Runner-up Titles Law of Unintended Consequences We're not lawyers, we just have common sense Trillion-dollar open source company The Meta Manifesto I don't think self-awareness is their strong point. Using AI to fight AI Put me as a strong maybe. Rundown Days after John Oliver's dare, Buc-ee's sues again Meta's Big AI Week The Future is for Everyone Meta Unveils ‘Open Source' Version of Its Most Powerful A.I. Model Meta debuts first AI coding agent to take on Anthropic and OpenAI Superintelligence is a dragon Mistral Is in the Right Place at the Right Time The AI Money Machine Nvidia lines up $500 billion in financing as CEO Jensen Huang tells CNBC his chips are ‘investable asset' 48% of Google Cloud Revenue Next Year Could Come From Just 2 Companies That Have Still Never Turned a Profit Datadog Says Lower Usage From Major AI Customer Could Dent Growth Relevant to your Interests New Orleans will use AI to answer 911 calls instead of a human OpenAI's new AI smart speaker will reportedly sell for between $300 and $400 TechCrunch OpenAI acquires presentation startup NextSlide A road trip through the data center debate A Top OpenAI Executive Steps Down Cloudflare OS: an open platform for agents, apps, and work Introducing Kitesurf: The agent-first browser that runs in V8 isolates on Cloudflare Workers The next generation of MCP How a simple request for AI to book a gym class exposed a major threat Nonsense Buc-off Sponsors Signadot: making sure AI-written code actually works. Conferences WeAreDevelopers NA, Sept 23-25, 2026, Discount Code: DEVPOD50 25 Free Tickets AI Connect, Aug 22nd, 2026 - Riga, Latvia, Coté speaking. DevOpsDays Graz, Sept 4-5, 2026 Cloud Foundry Summit, Sept. 21st to 22nd, Heidelberg, Coté speaking. DevOpsDays Rockies, Sept. 22 – 23, 2026, Discount Code: 26DODSWEDEFTALK DevOpsDays Dallas, Sept 28-29, 2026 DevOpsDays Vilnius, Sep 30 - Oct 1, 2006 DevOpsDays Istanbul, Oct 24th, 2026, Coté keynoting. VMware User Group, Orlando, Oct 20-22, 2026 Cloud Native Denmark, Nov 19th, 2026, Copenhagen, Coté keynoting. SCALE 24x Pasadena, CA, April 1-4, 2027 SDT News & Community Join our Slack community Email the show: questions@softwaredefinedtalk.com Free stickers: Email your address to stickers@softwaredefinedtalk.com Follow us on social media: Twitter, Threads, Mastodon, LinkedIn, BlueSky Watch us on: Twitch, YouTube, Instagram, TikTok Book offer: Use code SDT for $20 off "Digital WTF" by Coté Sponsor the show Sponsor more podcasts with Failover Media Recommendations Brandon: Furious on Hulu Matt: NearbyWiki Reading Maps Infrastructure Frontiers podcast Coté: IncomphrensibleMedia.com Elgato Teleprompter TelepromterPro+
A very special edition of More or Less, featuring Josh Wolfe (Founder, Lux Capital), Rachel Holt (Founder, Construct Capital; former Head of North America at Uber), Scott Belsky (Partner, A24; Founder, Behance), Scott Stanford (Founder, Acme Capital), and Peter Deng (GP, Felicis; formerly Google, Facebook, Instagram, Uber, Airtable, and OpenAI). Sam takes over hosting duties and assembles an overqualified group of investor friends to argue about where AI goes from here, from agents, Grok, Claude, and the shift from “help me do this” to “just do it,” to trust, data ownership, Apple's AI advantage, open vs. closed models, model routing, and why proprietary data may become the real moat. They also dig into NVIDIA's massive compute financing strategy, the risks of securitizing GPUs like long-lived infrastructure, what the OpenAI executive exodus says about the AI talent market, and the bigger question hanging over all of it: if AI really changes work, who actually participates in the upside?Chapters0:00 Episode trailer1:24 Episode start1:59 Meet the panel, every flavor of venture capital5:14 Consumer AI agents cross the Rubicon7:24 The end of websites, when agents talk to agents8:32 Which AI companies do you actually trust?11:41 Why Apple could win AI by doing nothing16:40 If models commoditize, unique data becomes the moat22:15 Open vs. closed AI, and who owns your data27:06 NVIDIA's balance sheet shenanigans31:26 NVIDIA gets the upside, who gets the risk?34:31 Nobody has ever securitized compute35:02 Who owns the wealth AI creates?39:38 What happens when economic opportunity runs out?42:23 Why OpenAI's best people keep leaving47:23 Why AI may look more like GPS than Facebook49:14 What actually happened with Airtable50:30 Lightning Round: Rachel Holt on physical-world investing53:00 Scott Belsky on AI watermarks, provenance & deepfakes54:15 Josh Wolfe on socialism, Europe & defense57:15 Final thoughts & sign-offWe're also on ↓X: https://twitter.com/moreorlesspodInstagram: https://instagram.com/moreorlessSpotify: https://podcasters.spotify.com/pod/show/moreorlesspodConnect with us here:1) Sam Lessin: https://x.com/lessin2) Dave Morin: https://x.com/davemorin3) Jessica Lessin: https://x.com/Jessicalessin4) Brit Morin: https://x.com/brit
Kyle Reidhead offers his insight into Nvidia's (NVDA) $500 billion AI infrastructure funding push that involves six key financial firms. GPUs having a longer life than many expected is something he sees adding value to this push. It's not just Nvidia benefitting, either, with Kyle explaining how hyperscalers and energy companies can see substantial profits. ======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about
The Mates sit down with Emad Mostaque to discuss Bernie Sanders' call to halt AI development, Wall Street turning GPUs into financial assets, Grok 4.7 taking the top spot, AI's growing impact on Hollywood, and the race toward superintelligence. Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader. Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified Emad Mostaque is the founder of Intelligent Internet ( https://www.ii.inc ) Read Emad's latest papers exploring the future of society, law, personhood and governance: https://ii.inc/common-wealth Read Emad's Book: https://thelasteconomy.com – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding Get the blueprint for generative media https://goo.gle/startupgenmedia Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: https://www.fountainlife.com/peter Join the Moonshots Mates on Sep 25th for the inaugural Moonshots LIVE. The world's greatest entrepreneurs, builders and creators, working together to build a hopeful and optimistic vision of tomorrow. Seats are limited and application only. Apply at moonshots.com before seats are sold out. _ Connect with Peter: X Instagram Substack Website Xprize A360 Connect with Dave: Web X LinkedIn Instagram TikTok Connect with Salim: LinkedIn X Join Salim's 10X Shift Subscribe to Salim's YouTube channel Exponential Venture Capital Connect with Alex Website LinkedIn X Email Substack Spotify Threads Connect with Emad X LinkedIn Learn about Intelligent Internet: https://www.ii.inc Read Emad's Book: https://thelasteconomy.com Listen to MOONSHOTS: Apple YouTube Follow MOONSHOTS: Instagram TikTok X Threads – *Recorded on August 12th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices
There's a simmering concern on Wall Street about Nvidia and CEO Jensen Huang's role as leader of the AI revolution. Despite bringing in billions of dollars in profit from the GPUs powering AI, investors are worried about the company's recent “circular” deals with other tech companies, and some are asking if the chip giant is building the future of AI or inflating the next tech bubble. To better understand Huang, the man pulling the strings of this global AI boom, Danny Fortson and Mark Sellman revisit an interview with Stephen Witt, author of ‘The Thinking Machine', a history of Jensen Huang and Nvidia. Stephen talks about how Huang hatched the idea for Nvidia in a diner, why getting rich was his biggest fear, and the time he got shouted at by the CEO. Watch on YouTube Read more: Nvidia is becoming tech's Bank of Mum and Dad Get in touch: techpod@thetimes.co.uk Producer: Marnie Duke Executive Producer: Priyanka DeladiaVideo Producer: Bronwen LathamImage: Getty Hosted on Acast. See acast.com/privacy for more information.
Nvidia, CoreWeave and Wall Street are pouring hundreds of billions of dollars into AI infrastructure. But how does the financial machine behind the AI boom actually work and where are the risks?In this episode of the Market Maker Podcast, Anthony Cheung and Piers Curran unpack CoreWeave's extraordinary growth and $100bn+ revenue backlog, Nvidia's role at the centre of the AI ecosystem, and the huge amounts of debt and private capital being used to finance data centres and GPUs.We explain what neoclouds are, why GPUs are increasingly being treated as infrastructure assets, and how firms including BlackRock, Blackstone, Apollo, Goldman Sachs and KKR are helping finance the AI buildout.But there's another side to the story. We explore the “circular financing” concerns surrounding Nvidia and its customers, the growing concentration risk across the AI industry, and what could happen if hyperscalers such as Microsoft, Alphabet, Amazon and Meta begin to slow their enormous AI spending.Finally, we look at the wider macro picture, including the latest US CPI inflation data, Federal Reserve interest rate expectations and why the AI boom itself is beginning to show up in inflation.Is this the financial infrastructure needed to power the next technological revolution or is too much money becoming dependent on the AI boom continuing?(00:00) The $1 Trillion AI Spending Boom(03:51) CoreWeave's Incredible Growth(04:58) The $104BN AI Order Book(08:35) What Is a Neocloud?(11:18) The Huge Cost of AI Infrastructure(16:13) Nvidia's $500BN Wall Street Deal(17:53) How GPUs Became an Asset Class(21:14) Was Michael Burry Wrong on AI?(24:50) How Wall Street Finances AI(27:12) The AI Circular Financing Risk(33:34) Nvidia's Biggest Concentration Risk(37:18) Can the AI Spending Boom Continue?(38:50) How to Invest Beyond Big Tech(40:12) The Next Trillion-Dollar AI Company?(44:30) AI Boom or House of Cards?(45:06) US Inflation Falls Again(47:05) Will the Fed Hike in September?(49:27) What to Expect From Jackson Hole
Nvidia just announced partnerships with some of the world's biggest financial institutions to mobilize more than $500 billion of capital for AI infrastructure.But there's an important distinction:Nvidia isn't investing $500 billion.The initiative is about bringing institutional capital into the financing of AI data centers, compute infrastructure, and related projects.In this episode, we break down what Nvidia's financing strategy really means—and why it could be one of the most important developments yet in the next phase of the AI buildout.⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.comKey topics we explore:– What Nvidia's $500B financing initiative actually involves– Why Nvidia wants institutional investors to finance AI infrastructure– How compute could increasingly become an investable infrastructure asset– Why this could accelerate AI data center and GPU deployment– The potential beneficiaries across Nvidia, data centers, power, and networking– The risks if AI demand or GPU utilization doesn't meet expectations– Whether this creates a potentially circular financing ecosystem around AI– Why Wall Street is becoming an increasingly important participant in the AI buildoutThe bigger question:Are we simply finding new ways to finance the AI infrastructure boom—or are we watching the emergence of an entirely new institutional asset class?For investors, the answer matters. The next constraint on AI may not be GPUs or power—it may be the enormous amount of capital required to build everything around them.LINKSPrashant Choubey - https://www.linkedin.com/in/choubeysahabSubscribe to VC10X newsletter - https://vc10x.beehiiv.comSubscribe on YouTube - https://youtube.com/@VC10XSubscribe on Apple Podcasts - https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986Subscribe on Spotify - https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQVC10X website - https://vc10x.comFor sponsorship queries reach out to prashantchoubey3@gmail.comThis channel is for asset managers, allocators, and investors who want analysis that holds up—not headlines dressed as insight.Subscribe for weekly data-driven breakdowns of the forces reshaping capital markets.#Nvidia #AI #ArtificialIntelligence #AIInfrastructure #DataCenters #GPUs #Investing #TechStocks #VC10X #BlackRock #Apollo #Blackstone #GoldmanSachs #KKR #AIInvesting #Semiconductors #CloudComputing #CapitalMarkets #Finance #WallStreet
No vídeo de hoje, analisamos o mega acordo liderado pela Nvidia para mobilizar US$ 500 bilhões junto a gigantes de Wall Street, como BlackRock e Goldman Sachs, visando financiar a infraestrutura de inteligência artificial. O CEO Jensen Huang quer transformar chips (GPUs) em uma nova classe de ativos, tratando data centers como "fábricas de IA" capazes de gerar receita recorrente. Mas será que essa engenharia financeira, que o próprio mercado compara com a securitização da bolha imobiliária de 2008, é sustentável? Entenda os riscos dessa mudança estrutural, o perigo da obsolescência rápida dos equipamentos e por que especialistas acendem um alerta sobre o futuro do setor.00:00 - Nvidia reúne Wall Street por US$ 500 bilhões01:50 - GPUs como nova classe de ativos financeiros03:48 - Transformando data centers em fábricas de IA05:12 - O gigantesco custo trilionário da infraestrutura07:46 - De quem é o risco real dessa operação?09:55 - O perigo da obsolescência rápida dos chips11:51 - O peso do dinheiro institucional no mercado15:16 - A ilusão da demanda infinita por computação18:23 - A engenharia financeira e o fantasma de 200820:24 - Empacotando dívidas em novos títulos financeiros22:01 - O perigo real dessa nova narrativa financeira
The AI buildout has one big beneficiary today and that's neoclouds Coreweave and Nebius. These companies buy and rent out GPUs for AI and they're seing incredible demand for the assets they're building. We discuss the short-term demand and where these stocks face risks long-term. Plus, we discuss Cava's results and what inflation is telling us.Travis Hoium, Tyler Crowe, and Rachel Warren discuss:- Coreweave's Results- Neocloud Financing- Cava's Traffic Growth- Why Restaurants Are Hard- Inflation Eases- Energy's Impact PricesCompanies discussed: Coreweave (CRWV), Nebius (NBIS), Cava (CAVA).Host: Travis HoiumGuests: Tyler Crowe, Rachel WarrenEngineer: Kristi Waterworth Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, "TMF") do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement. We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode. Learn more about your ad choices. Visit megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices
We chat about Ed's engagement with communities pushing back against data center development in Tulsa, plus some major reporting showing the sheer scale of fossil-fuelled data center development in the United States. We're talking more than 120 GIGAWATTS of new gas-burning power plants in development just to electrify data centers. There's simply no way to equivocate about this amount of new pollution — new smog, new acid rain, new environmental health crises — being emitted for the purpose of spinning up more GPUs so that some of the most noxious companies in the world can become even more, well, noxious. ••• AI Data Centers: The Frontier of Capitalist Extraction — Live Event https://www.youtube.com/watch?v=LY0XnY0DA7U ••• How Data Centers Broke American Politics https://www.wired.com/story/how-data-centers-broke-american-politics/ ••• no data centers in my backyard https://jasmi.news/p/no-data-centers-in-my-backyard ••• Trump's Vision for A.I. Dominance Comes With Major Air Pollution https://www.nytimes.com/2026/08/05/climate/data-centers-pollution-trump-ai-energy.html Standing Plugs: ••• Order Jathan's book: https://www.ucpress.edu/book/9780520398078/the-mechanic-and-the-luddite ••• Subscribe to Ed's substack: https://substack.com/@thetechbubble ••• Subscribe to TMK on patreon for premium episodes: https://www.patreon.com/thismachinekills Hosted by Jathan Sadowski (bsky.app/profile/jathansadowski.com) and Edward Ongweso Jr. (www.x.com/bigblackjacobin). Production / Music by Jereme Brown (bsky.app/profile/jebr.bsky.social)
Buenos días. Hoy México despertó comprándole más a Asia que a Estados Unidos, Nvidia decidió que los chips deberían financiarse casi como edificios, Microsoft México tendrá por primera vez a una mujer al frente y Farmacias del Ahorro nos recordó que tener sucursales ya no basta: también hay que ganar la pantalla.Mientras tanto, el precio de la vivienda sigue corriendo más rápido que muchos salarios, Irán encontró una vulnerabilidad bastante cara en la defensa estadounidense y Cristiano Ronaldo decidió que diez años eran suficientes para pasar del “algún día” al “sí, acepto”.STRTGY ayuda a empresas con operaciones complejas a encontrar dónde están perdiendo dinero o dejando oportunidades sin aprovechar. Si quieres entender dónde tu empresa podría estar perdiendo dinero o dejando oportunidades sin aprovechar, agenda un diagnóstico con STRTGY mandando un mensaje a arturo@strtgy.ai o a este número de WhatsApp: +52 81 3232 2698. Recibe gratis nuestro newsletter con las noticias más importantes del día.Si te interesa una mención en El Brieff, escríbenos a arturo@strtgy.ai Hosted on Acast. See acast.com/privacy for more information.
AI isn't just transforming the way we work, but also the way we write the software that people use for work. In this episode, we talk to two engineering productivity leads at Dropbox: Uma Namasivayam, senior director of software engineering productivity, and Anuradha Agarwal, director of software engineering. Whether it's writing tests, fixing bugs, tackling tech debt, or accelerating migrations, they explain how Dropbox engineers are using agentic AI—including in-house tools like Nova—to build the future of Dropbox, and create more space to do impactful work. ~ ~ ~ Working Smarter is brought to you by Dropbox. Find, organize, and share your work—all in one place—with context-aware AI from Dropbox. You can listen to more episodes of Working Smarter on Apple Podcasts, Spotify, YouTube, Amazon Music, or wherever you get your podcasts. To read more stories and past interviews, visit workingsmarter.ai This show would not be possible without the talented team at Cosmic Standard: producer Ben Montoya, sound engineer Aja Simpson, technical director Jacob Winik, and executive producer Eliza Smith. Special thanks to our illustrator Fanny Luor, marketing consultant Meggan Ellingboe, and editorial support from Catie Keck. Our theme song was composed by Doug Stuart. Working Smarter is hosted by Matthew Braga. Thanks for listening!
Hydrogen combustion, high-fidelity CFD and the future of aircraft propulsion are the focus of this conversation with Dr. Daniel Mira, Head of the Propulsion Technologies Group at the Barcelona Supercomputing Center. Neil and Dani discuss why reacting flows are so difficult to simulate, how hydrogen changes combustion and aircraft design, the limits of RANS, LES and DNS, GPU-native solvers, coding agents and AI surrogate models.Full episode, corrected transcript and resources:https://neilashton.co.uk/podcasts/s4-e6-daniel-mira-on-hydrogen-combustion-modelling-and-future-propulsion/TopicsWhy reacting flows are so computationally difficultHydrogen versus hydrocarbon combustionWhen hydrogen could reach commercial aviationHow engines and aircraft must be redesignedIndustrial trust in high-fidelity combustion CFDRANS, LES and DNS for reacting flowsChemistry, load balancing and computational costWall modelling in combustion LESGPU acceleration and solver redesignCoding agents for scientific softwareAI surrogate models and digital engineering workflowsSelected resourcesDaniel Mira and the Propulsion Technologies Grouphttps://ptg.bsc.es/?p=44Propulsion Technologies Group — research lineshttps://ptg.bsc.es/research-lines/BSC — Combustion researchhttps://www.bsc.es/research-development/research-areas/engineering-simulations/combustionCenter of Excellence in Combustion (CoEC)https://coec-project.eu/High-fidelity simulations of the mixing and combustion of a technically premixed hydrogen flamehttps://upcommons.upc.edu/entities/publication/08a27c10-cb13-4357-a3ab-8e9ec1d706ccChapters00:00 Podcast intro00:39 Introducing Daniel Mira03:00 Conversation begins04:55 Why combustion CFD is so hard10:23 Daniel's path into hydrogen and jet-engine combustion12:48 Hydrogen versus hydrocarbon combustion17:58 Industrial adoption of hydrogen20:54 Gas turbines, aviation and fuel infrastructure25:35 How jet engines must change30:43 Redesigning the whole aircraft34:46 What will trigger commercial adoption?37:27 Why aerospace projects take a decade42:14 RANS, LES and DNS for reacting flows44:31 Replacing expensive tests with high-fidelity CFD46:01 The biggest accuracy gaps in combustion LES49:26 Where the computational cost goes52:06 Chemistry, species and source-term bottlenecks55:35 Wall modelling in combustion LES59:49 GPUs, algorithms and solver redesign01:08:52 Can coding agents accelerate combustion CFD?01:12:27 AI surrogate models for combustion01:24:20 Closing thoughts
As AI evolves from conversational chatbots to autonomous agents, CPUs are becoming an increasingly important part of the infrastructure equation. In this episode, The New Stack speaks with Bhumik Patel of Arm and Mo Farhat of Google about how CPUs act as an “air traffic controller” for agentic workloads, handling orchestration, data preparation, semantic search, vector databases, code execution and API calls alongside GPUs and TPUs. Smaller AI models, including summarizers and evaluators, can also run effectively on CPUs for specialized tasks. As agents increasingly generate and execute code, secure sandboxing becomes critical. Google's gVisor and GKE Agent Sandbox provide isolation and scalable environments, with the latter supporting up to 300 sandboxes per second per cluster. The discussion also explores efficiency and cost, with Google highlighting Axion's price-performance and energy-efficiency advantages across different workload types. Ultimately, the shift toward agentic AI is creating a more diverse compute environment where CPUs, GPUs and TPUs each play complementary roles in delivering scalable, efficient AI applications. Learn more from The New Stack around the latest in CPUs in the world of AI agents: AI Agents Will Eat Enterprise Software, Just Not in One Bite How to ground AI agents in accurate, context-rich data Join our community of newsletter subscribers to stay on top of the news and at the top of your game.
My conversation with Tarun Chitra.As a co-founder of Gauntlet and GP at Robot Ventures, Tarun has one of the sharpest frameworks for understanding market structure across both crypto and AI. In this episode we dig into why open-source AI is unbundling faster than most people expect, and how the resulting stack looks surprisingly similar to DeFi.We spend a lot of time mapping the AI infrastructure layers directly onto crypto primitives and examining where value is actually going to accrue as models, harnesses, routers, and inference providers separate.At the center of the conversation is the belief that AI's unbundling is creating a new competitive order-flow market (data centers competing like nodes, MEV-like dynamics for tokens/GPUs) while crypto itself has settled into a more mature “TradFi plus+” phase focused on trading, payments, and bringing real assets on-chain.We discuss:- The current state of crypto as TradFi+ and the decline of speculative narratives- Why AI is killing Bitcoin mining economics and weakening ETH value accrual- The architectural parallel between AI stacks and DeFi Harnesses = WalletsRouters = DEX aggregators,Models = ProtocolsInference Providers = LPs- Why open-source models are unbundling faster than traditional software- Agents as the next interface layer and the potential unbundling of ETFs- Cryptography, verifiable compute, and turning GPUs into digital assets- Onchain compute trading as the real crypto × AI opportunity- Sustainable business models and where value will ultimately captureTimestamps:0:00 – Introduction & State of the Crypto Market (TradFi+)2:00 – Speculative Narratives Fade, Trading & Payments Remain7:00 – AI's Impact on Bitcoin Economics & Data Center Opportunity Cost9:00 – ETH Value Accrual, Solana Positioning & DeFi Token Sustainability15:00 – Trading Design Space & On-Chain Volume Upside25:00 – AI Unbundling Thesis: Open-Source Models vs Data Centers35:00 – The DeFi Mapping (Harnesses, Routers, Models, Inference)48:00 – Agents, Preference Expression & Unbundling Traditional Products1:00:00 – Real-Time Harness Generation & Active Learning1:05:00 – Cryptography, Verifiable Compute & On-Chain GPU Markets1:10:00 – Closing Thoughts: Where Value Accrues NextEnjoy!
Join Andreas Walbrodt, CEO and Co-Founder of enclaive, for an essential exploration of cybersecurity, data sovereignty, and business confidentiality in an increasingly cloud-reliant world. While enterprises have spent decades securing data at rest (in storage) and in transit (over networks), sensitive workloads remain completely unencrypted the moment they are processed in memory. As organizations rush to adopt public cloud platforms, scale Industry 4.0 smart manufacturing, and deploy proprietary AI models, this "in-use" vulnerability creates catastrophic exposure to cloud operator access, third-party subpoenas, and cyber threats. Drawing on over 30 years of enterprise IT leadership at IBM and TÜV Rheinland, Andreas explains how confidential computing closes this gap—allowing businesses to leverage hyper-scale cloud power without sacrificing sovereignty, compliance, or core intellectual property.
Companies are spending billions on GPUs, data centers, foundation models, and AI infrastructure. But what happens when the network connecting all of it cannot keep up? In this episode of Tech Talks Daily, I welcome back Avi Freedman, co-founder and CEO of Kentik, five years after our previous conversation. Avi has been operating large-scale networks since the 1990s, including more than a decade at Akamai, and brings a rare combination of founder experience and hands-on knowledge of how the internet actually works. We discuss why network performance is becoming an important factor in determining the return companies receive from their AI investments. If organizations cannot move data efficiently to models or deliver inference reliably to users and applications, expensive compute infrastructure can sit waiting while performance suffers and costs increase. Avi explains what technology leaders should measure to determine whether their network is helping or hindering AI workloads. This includes establishing performance baselines, synthetic testing across cloud and AI providers, understanding dependencies across the digital supply chain, and using observability to identify what changed when performance deteriorates. The conversation also examines network intelligence and why collecting telemetry alone is not enough. Organizations need to connect network data with the applications and users affected, understand historical behavior, determine which problems matter, and give network teams enough context to act quickly. Agentic AI introduces another opportunity. Avi explains how AI agents can increasingly perform the work of experienced network engineers by monitoring baselines, investigating alerts, troubleshooting problems, and recommending actions. But fully autonomous networks remain some distance away. Most enterprises currently want humans deciding whether significant production changes should be made. That leads us into governance. As businesses give AI systems access to increasingly important infrastructure, credentials, permissions, guardrails, and oversight become major considerations. Avi warns about ungoverned AI systems gaining proxy access to corporate infrastructure and explains why companies need clear boundaries around what agents can see and do. We also revisit a lesson from decades of internet infrastructure: individual components will fail. Rather than attempting to create networks that never fail, businesses should design for resilience through redundancy, over-provisioning, monitoring, and architectures capable of continuing when something inevitably breaks. For founders, CIOs, CTOs, network engineers, and infrastructure leaders building around AI, Avi offers practical advice on observability, network resilience, autonomous operations, AI infrastructure, and knowing when networking expertise should be developed internally or brought in from elsewhere. And we finish somewhere unexpected: how CEOs can use AI to make better decisions by explicitly asking it to disagree with them. Avi explains why turning AI from a sycophantic assistant into an argumentative colleague can expose weaknesses in an idea, improve communication, and help leaders test their thinking. AI may be transforming software, compute, and business operations, but none of it works without connectivity. As AI becomes part of the operational backbone of the enterprise, understanding the network underneath it becomes increasingly difficult to ignore.
Enterprise AI has moved past experimentation and now has to prove its return. Ed Sim, Founder and General Partner of boldstart ventures, ranked the No. 1 seed investor in the Business Insider Seed 100 two years running, sees hundreds of AI startup pitches a year, and writes the first check into companies enterprises buy from years later. He wrote the first check into Snyk and backed Protect AI, which Palo Alto Networks acquired for more than $700 million. In this conversation, he lays out the three waves of enterprise AI adoption, why rising token costs are pushing companies toward open-weight models and their own hardware, how agent identity and access create a new attack surface, and what separates AI vendors that survive a shakeout from the ones that do not.YOU'LL DISCOVER✅ The three waves of enterprise AI: get AI running, get agents running, and the wave happening now, where ROI and tokenomics decide what survives✅ Why Ed expects dozens of models inside a single enterprise, and the choice he frames as renting intelligence versus owning it✅ How one portfolio company packaged eight GPUs, CPUs, and a model router into an appliance, routing roughly 10% of queries to the frontier labs and claiming 70% savings per year✅ Why agents should be granted access at runtime that expires when the task ends, so a breach's blast radius stays contained to one narrow authorization✅ Cost per outcome as the yardstick: the human doing the task, the AI doing the task, and the human assisted by AI, applied first to discrete work like coding and customer support✅ A 57-step insurance claims process where the AI was correct 98% of the time and the humans 85%, a gap only visible because every step was recorded✅ The real difference between open source and open weight models, and why most of Ed's startups now build on open weight models under the hood✅ Why he argues offense is the new defense, and what the Black Hat sandbox escape means for CISOs planning autonomous defense⏱️ TIMESTAMPS0:00 Introduction0:36 Three waves and the ROI test3:06 Many models and where startups win10:32 Who owns access, context, and evaluations17:21 It's the people, not the architecture20:04 Measure the outcome, then cut the cost28:14 Buying talent and changing culture33:05 Systems of record versus headless agents36:31 Venture money pivots to robotics and chips40:11 Open weights and owning your intelligence44:44 Autonomous attacks need autonomous defense51:32 Judging vendors and earning enterprise trust
News Sources: https://lmg.gg/1Bjqb Timestamps: 0:00 OpenAI smart speaker leak 1:05 Nvidia GPUs for MSRP at QuakeCon 2:23 Apple's iPhone 18 RAM problem 4:19 QUICK BITS INTRO 4:27 Windscribe deGUID script 5:16 Kimi K3 escapes its sandbox 5:58 AI answering 911 calls in New Orleans 6:40 Nashville data center vs the zoo 7:25 ChatTJFB 8:04 Credits Learn more about your ad choices. Visit megaphone.fm/adchoices
Episode 110: Fanboys on Reddit got very upset that we trashed the upcoming Radeon RX 9050 and 4GB GPUs in general, claiming that these models are not sold to consumers, and also not actually gaming GPUs. So we naturally decided to take on and dismantle these idiotic comments in this week's podcast.CHAPTERS00:00 - Intro01:00 - Reddit gets upset about our 4GB GPU video46:17 - Asus rejects RTX 5090 sale then jacks up price56:47 - Updates from our boring livesSUBSCRIBE TO THE PODCASTAudio: https://shows.acast.com/the-hardware-unboxed-podcastVideo: https://www.youtube.com/channel/UCqT8Vb3jweH6_tj2SarErfwSUPPORT US DIRECTLYPatreon: https://www.patreon.com/hardwareunboxedLINKSYouTube: https://www.youtube.com/@Hardwareunboxed/Twitter: https://twitter.com/HardwareUnboxedBluesky: https://bsky.app/profile/hardwareunboxed.bsky.social Hosted on Acast. See acast.com/privacy for more information.
Send us Fan MailWe take rapid-fire questions from the field and get blunt about what's changing in low voltage work, from labor shortages to PoE terminations to fiber habits that build real trust. We also dig into estimating mistakes, dark fiber strategies, cybersecurity boundaries, and what to learn before stepping into design and the RCDD path.• livestream schedule change coming soon and how to stay connected • fundraiser progress update and pushing to hit the goal • LinkedIn profile lockout story and where to find our daily LinkedIn content • labor as the biggest estimating risk and why averages hide crew variability • adding risk management and assumptions to bids to protect schedules • cross-training as the fastest way to reduce labor constraints • pass-through versus traditional RJ45 terminations under PoE loads • importance of crimper maintenance and matching tool to connector • choosing a specialization based on passion and then stacking skills • certifications and credentialing that improve marketability and job access • AI data center growth and the bottleneck debate across GPUs, power, cooling, cabling, skilled labor • fiber testing growth beyond class fundamentals and why humility matters • contamination control, labeling, and documentation as the marks of a great tech • building customer confidence so clients request specific technicians • estimator mistakes under tight margins including site logistics and lessons learned • dark fiber and spare capacity rules of thumb with cost versus flexibility thinking • where cybersecurity responsibility starts for structured cabling teams • what to keep learning before moving from field work into RCDD and design • firestopping foam selection, inspector expectations, and safety concerns Also, keep in mind that I'm still doing the uh Save Our Sons walk-a-thon um uh ministry event, trying to raise money for um Living Hands Ministry in Dade City, Florida. So if you haven't donated yet, please go look at my LinkedIn profile, go look at my Facebook profile and donate to that cause. So if you ever consider joining the Let's Talk Cablin community, please make sure that you do so.Support the showKnowledge is power! Make sure to stop by the webpage to buy me a cup of coffee or support the show at https://linktr.ee/letstalkcabling . Also if you would like to be a guest on the show or have a topic for discussion send me an email at chuck@letstalkcabling.com Chuck Bowser RCDD TECH#CBRCDD #RCDD
Trinity Capital CEO Kyle Brown discusses the firm's record quarter, driven by strong activity in AI, space and frontier technology markets. He highlights growing demand for AI infrastructure financing, including GPUs and power equipment, while pointing to attractive investment opportunities in the lower middle market amid reduced competition and ongoing refinancing activity.======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about
Fresh out of the studio, recorded in Singapore, Steve Clayton, Senior Vice President and Chief Communications Officer at Cisco, joins us to discuss what it takes for AI to scale inside enterprises globally. Steve argues that narrative belongs at the top of the AI pyramid, not the bottom — in an era when models generate more material than any organisation can absorb, the story a company can credibly tell becomes the scarce asset, not the technology itself. He explains why the truth lies in the field rather than at global headquarters, how regional dynamics reshape where a story lands, and walks through Cisco's advances in silicon and quantum computing networking. Showing a real customer deployment, he argues, is what earns permission to talk about security and trust at all. Last but not least, he shares what great look like for Cisco to build their story in the age of AI. "Take your phone and switch it into airplane mode and see how much you can do on your phone. Very little. You can use the calculator, but you can't use an AI model. You can't surf the web, you can't send messages. And people get excited about GPUs and data centers and models and applications and devices. But sitting at the center of all of that is the network. And that's what Cisco is all about. So that's our job, is to help people understand the value of the network and to realize that AI, as exciting as it is, it simply doesn't happen without the network." - Steve Clayton, SVP & Chief Communications Officer, CiscoProfile: Steve Clayton, SVP & Chief Communications Officer, Cisco LinkedIn: https://www.linkedin.com/in/stevecla/Friday Note Newsletter: https://www.linkedin.com/newsletters/the-friday-thing-7412856034161229824/Episode Highlights:[00:00] Quote of the Day by Steve Clayton from Cisco[00:30] Introduction: Steve Clayton from Cisco[02:13] Why storytelling began around the campfire[02:55] Telling stories about impact, not technology[03:43] Why the AI debate over-indexes on models[04:51] The airplane mode test for AI dependence[06:17] Steve inverts the pyramid, narrative on top[07:04] Communicating without leading with the technology[07:49] Breaking through by doing the opposite[08:37] Why "content" has become a bad word[09:59] Audience-first: meeting policymakers where they are[11:10] The trap of filling the pipeline[11:34] Attention, not creativity, is the scarce resource[12:15] Curation and judgment against AI slop[12:51] We are not entitled to people's attention[13:26] Silicon One, the Cisco business nobody expects[14:26] Cisco's universal quantum switch at room temperature[14:57] Balancing ambition against credibility[16:08] Show the possible, do not just describe it[16:35] Earning permission to talk security and trust[17:18] The truth lies in the field[18:16] McLaren F1 and Networking Academy stories[19:12] The question Steve wishes people would ask[20:56] The Friday Thing: human first draft, AI editor[21:26] Humans create the novel ideas, AI supports[22:07] What Cisco should mean to business and to family[23:21] ClosingPodcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format.
Imagine redesigning your most important processes from a blank sheet of paper, with no legacy systems to hold you back. Alpa Lally, Chief Product Officer at Grant Thornton, shares how the company is transforming into a frontier firm by reimagining core processes instead of automating them. She unpacks how embedded analytics reshapes client conversations, why AI governance is what helps you move faster, and how to reinvent your career in the age of AI. Key Moments: From Structural Engineering to Product Leadership (01:36): Alpa explains how designing buildings taught her the vision, strategy, and foundation-up thinking she now applies to product. Becoming a Frontier Firm (06:27): Rethinking how work gets done for 13,000-plus professionals means recognizing that automating a broken process just does the wrong thing faster. Embedding ThoughtSpot Analytics (14:57): By putting insights in auditors' hands on day one, Grant Thornton shifts client conversations from data gathering to strategy. The AI Proof Gap: Governance Enables Speed (19:32): Alpa reframes governance as what lets you move faster, sharing that 78% of firms doubt they'd pass an AI governance audit. Is Product Management Dead? (24:33): The role is evolving, not dying, and AI raises the value of deciding which opportunities are actually worth pursuing. Key Quotes: “A frontier firm uses AI not just to improve how work gets done, but fundamentally rethinks how the work gets done. It's moving beyond productivity gains and creating entirely new ways to deliver value.” - Alpa Lally “The challenge is if you simply automate a broken process, you end up doing the wrong thing faster.” - Alpa Lally “What ThoughtSpot has done is [give us] our ability to embed them immediately into the flow [which] has opened up a whole level of different insights that we can offer, not to our practitioners only, but imagine an auditor showing up on day one to your client and having these insights already calculated, already delivered.” - Alpa Lally Mentions Grant Thornton's 2026 AI Impact Survey Report Wall Street is debating the AI buildout. Enterprises just answered: More than 80% say their GPUs run at half capacity or less Hers for the Taking by Tracey Newell Guest Bio Alpa Lally is the Chief Product Officer at Grant Thornton. Alpa is an experienced product management executive with several years in designing, developing, and launching consumer and business products for large to mid-sized to small organizations, fintechs, startups, and Fortune 500. She has led global cross-functional teams to drive high growth targets while staying laser-focused on solving customer and consumer problems. Alpa leverages data and analytics to drive successful business outcomes that deliver results and achieve corporate growth goals. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.
47 days after SpaceX's record-breaking $75 billion IPO — the largest in history — Simon Erickson and Heather Horton dig into whether the stock is a buy now that shares have pulled back from their post-IPO highs. Learn about SpaceX's origin story, Elon Musk's Mars mission, and how the company slashed launch costs from over $18,000 per kilogram down to under $1,000. Simon breaks down SpaceX's three business divisions — Space, AI (xAI/Grok), and Connectivity (Starlink) — and explains why a 75x trailing revenue valuation, upcoming lockup expirations, and the $60 billion Cursor AI acquisition make this a "buyer beware" situation for investors.
We are living through a fundamental shift in how businesses operate, compete, and create value. The Pirate Street Journal, hosted by Christopher, Eddie, and Bri, breaks down three major business stories through the category design lens, revealing a common thread that most mainstream business coverage misses entirely. That thread is AI data, and how the companies and individuals who understand it best are quietly rewriting the rules of entire industries. From energy infrastructure to ice cream shops to management consulting, the signal is clear and growing louder. This is just one of the topics that Pirates Christopher Lochhead, Eddie Yoon and Bri Clark discuss on this episode of Pirate Street Journal. Each week, the Category Pirates pick three headlines worth paying attention to and break down the category underneath. You're listening to Christopher Lochhead: Follow Your Different. We are the real dialogue podcast for people with a different mind. So get your mind in a different place, and hey ho, let's go. Portable Power and the AI Energy Race China now controls 90% of the world’s battery storage cells, and the top ten storage cell manufacturers on Earth are all Chinese. The easy read on this is that the centralized, top-down model has already won. But the more interesting story is happening on the other side of the equation, where pioneers are refusing to wait for governments to build grids and are instead making power portable, distributed, and locally owned. Elon Musk quietly acquired a mobile power company capable of deploying a functional power plant in 30 days and driving it wherever demand exists. Tesla is simultaneously selling Mega Packs to cities experiencing brownouts while offering Powerwalls to individual homeowners. The insight here is that AI data is driving the need for entirely new power infrastructure, and the winners will not necessarily be the nations with the biggest grids. They will be the builders who understand that decentralized, distributed power networks can outmaneuver any centralized system when speed and flexibility matter most. Eddie raises the concept of a “Mega Pod,” a combination of batteries and GPUs in a scalable unit that could allow businesses, farms, and institutions with unused land to generate power, offset costs, and participate in a distributed data center economy. This is AI data infrastructure being rebuilt from the bottom up, and the annuity potential mirrors what Alaskan citizens receive from oil revenues every year. Niche Down AI Data and the Rise of the Small Company Ben Affleck sold a stealth AI startup called Inner Positive to Netflix for $587 million. The company trained small models on individual film footage, replicating a director’s lighting style and visual language to accelerate post-production. An ice cream shop in downtown Los Angeles used prediction markets to hedge against cold weather, covering nearly half its monthly rent. A seven-person software company hit $10 million in revenue doing the work that once required 50 employees. These three stories appear unrelated on the surface, but they share a single strategic insight. Each one identified a narrow, specific type of AI data that nobody else was paying attention to and built an economic advantage around it. The Ben Affleck startup did not steal from other artists. It used a creator’s own footage as training data, producing tools that serve the creator rather than extract from them. The ice cream shop owner recognized that temperature data was weakness data for his business and converted it into a revenue stream through smart financial instruments. What AI is doing for smaller operators and independent entrepreneurs is lowering the barriers to prosecuting what Christopher Lochhead calls the magic triangle, building a legendary company, product, and category simultaneously. The surplus economics of AI are not accruing only to OpenAI, Anthropic, or the Mag Seven. They are flowing toward anyone willing to identify the weird data specific to their own situation and build something original with it. Consulting and the Death of the Billable Hour McKinsey now ties 25% of its global fees to outcomes rather than hours. Bain reports that 30% of its business is AI and tech enabled, with ambitions to reach 50%. BCG expects AI work to jump from roughly 20% of revenue to 40% within a year. These are not small firms experimenting at the margins. These are the most conservative, hour-worshipping institutions in the professional services world, and they are cracking under the pressure of a new reality driven by AI data and what it makes possible. The billable hour was always a proxy for value, not a measure of it. What consulting firms are beginning to acknowledge is that AI data and the tools built around it can compress the time required for entry-level analytical work dramatically, which means the old pricing model no longer reflects what clients are actually buying. The shift from time-based to outcome-based compensation is not unique to consulting. It is the direction that professional compensation has been moving across all sectors for decades, from hourly wages to salaries to bonuses to equity. Eddie frames this shift clearly. People who are naturally oriented toward outcomes and who understand how to use AI data to drive measurable results are going to be rewarded more generously than ever before. Those who have relied on time as their unit of exchange, without a clear connection to the value they produce, are entering genuinely uncertain territory. The consultants are the last ones you would expect to change. The fact that they already are should function as a signal flare for every professional in every industry paying attention. To hear about all the topics in this week's The Pirate Street Journal, download and listen to this episode. You can also read more Pirate Street Journal entries in the Category Pirates newsletter. We hope you enjoyed this episode of Christopher Lochhead: Follow Your Different™! Christopher loves hearing from his listeners. Feel free to email him, connect on Facebook, X (formerly Twitter), LinkedIn, and subscribe on Apple Podcast / Spotify!
What becomes possible when enterprise computer vision no longer depends on expensive GPU infrastructure? In this episode of Tech Talks Daily, I speak with Glenn Jocher, founder and CEO of Ultralytics, about YOLO26, CPU inference, edge AI, open vocabulary vision, deployment economics, and the practical work required to move computer vision from a promising pilot into production. Glenn's route into AI began inside the U.S. intelligence community. He worked with the National Geospatial Intelligence Agency and Defense Intelligence Agency on particle physics applications, attempting to detect and track antineutrinos. Antineutrinos are extraordinarily difficult to detect because they pass through almost everything. Glenn describes them as the perfect spy. While searching for better detection methods, he discovered that computer vision researchers were solving similar problems with images. His original attempt to transfer those techniques into particle physics did not succeed. However, the work introduced him to a field where the technology could create a visible effect on everyday life. That led him toward open source development and eventually the YOLO models for object detection, classification, segmentation, and tracking. Glenn believes computer vision research has historically placed too much attention on small gains in accuracy while overlooking deployment economics. A model can perform impressively inside a laboratory and still remain unsuitable for a factory, warehouse, store, vehicle, drone, or medical environment. Price, latency, power consumption, data privacy, and deployment speed can determine whether the technology is commercially useful. This led Glenn and Ultralytics toward smaller models capable of running close to where images and video are generated. YOLO26 continues that approach with architectural changes designed specifically for CPU inference. Glenn says the model can process camera streams in real time at 30 frames per second and run across Intel CPUs, AMD CPUs, and lower power devices such as Raspberry Pi computers. This matters because specialist GPUs can increase the equipment cost and power requirements of a computer vision project. Running inference on existing CPUs or edge hardware can make deployment economically possible across larger numbers of cameras and locations. The scale already involved is difficult to comprehend. Glenn says Ultralytics models now process approximately three billion inference jobs each day, equivalent to around 30,000 every second. These jobs include images, videos, and collections of images being analyzed to detect, segment, or track objects. He attributes the platform's maturity to thousands of mistakes and bugs corrected through a rapid feedback cycle. New models are released, users report problems and request features, and the team incorporates that information into later versions. We also discuss the respective roles of cloud and edge infrastructure. Glenn sees cloud platforms continuing to provide the computing power required for training, while computer vision inference often belongs at the edge. Local processing can reduce latency, control operating costs, and keep sensitive video or medical information closer to where it was created. The smallest YOLO model is approximately three megabytes, according to Glenn. That allows it to reach mobile phones, vehicles, drones, battery powered devices, and other environments where a large language model would be impractical. Open vocabulary vision provides another development. Traditional object detection models are trained to recognize a fixed collection of objects. If a model learns to detect dogs and the user later wants it to detect cats, retraining can cause it to forget earlier knowledge unless both categories appear in the new training data. Glenn explains how promptable models can identify common everyday objects from text or visual instructions without additional training. A user could request a person wearing a blue shirt and white shoes, for example, and the system could search an image for that description. That flexibility could benefit businesses whose requirements change regularly. It reduces the need to create and label a new data set every time the company wants the model to recognize another common object. The range of current applications is already extensive. Glenn describes YOLO being used across robotics, parking, industrial safety, PPE detection, warehouses, aviation, security, traffic management, food quality, and manufacturing. Some of his favorite examples involve environmental problems. One company uses YOLO with underwater vehicles to identify and recover plastic from the ocean. Other applications detect smoke and fire early enough to support forest fire response. For leaders considering computer vision, Glenn recommends beginning with a defined problem and measurable outcome. A manufacturing company may want to reduce defects, but it still needs labeled examples showing the model what acceptable and defective products look like. He advises testing the idea through a limited pilot, measuring the return, and expanding only when the evidence supports further investment. Computer vision has become easier to deploy, but practical problems involving data, cameras, integration, reliability, and operating conditions still separate a demonstration from a production system. Could CPU inference and open vocabulary models make computer vision practical for processes your organization previously considered too expensive? Listen to the episode and share your thoughts with me. Useful Links Ultralytics website Ultralytics Platform
So far, most electric vehicles have looked more or less like cars. But recently, a few companies have looked to another, smaller mode of transport for inspiration. The Verge's Andy Hawkins explains why companies like Amble and Chip are reinventing the golf cart, in the hopes of creating an entirely new kind of street-legal vehicle. As long as the speed limit stays low. Further reading: The Light Flip is a minimalist flip phone with a point to prove | The Verge Anthropic has to pay authors. | The Verge The cost of GPUs goes far beyond AI data centers | The Verge Is America ready for this quirky Jeep-looking EV that can park itself? The ‘G-Wagen of golf carts' could be the ideal second car America's cheapest new EV is smaller than a ping-pong table and tops out at 19mph Zoox's purpose-built robotaxi is getting a refresh 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. Learn more about your ad choices. Visit podcastchoices.com/adchoices
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