Podcasts about gpus

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop interviews Aurelio Gialluca, an economist and full stack data professional who works across finance, retail, and AI as both a data engineer and machine learning developer, while also exploring human consciousness and psychology. Their wide-ranging conversation covers the intersection of science and psychology, the unique cultural characteristics that make Argentina a haven for eccentrics (drawing parallels to the United States), and how Argentine culture has produced globally influential figures from Borges to Maradona to Che Guevara. They explore the current AI landscape as a "centralizing force" creating cultural homogenization (particularly evident in LinkedIn's cookie-cutter content), discuss the potential futures of AI development from dystopian surveillance states to anarchic chaos, and examine how Argentina's emotionally mature, non-linear communication style might offer insights for navigating technological change. The conversation concludes with Gialluca describing his ambitious project to build a custom water-cooled workstation with industrial-grade processors for his quantitative hedge fund, highlighting the practical challenges of heat management and the recent tripling of RAM prices due to market consolidation.Timestams00:00 Exploring the Intersection of Psychology and Science02:55 Cultural Eccentricity: Argentina vs. the United States05:36 The Influence of Religion on National Identity08:50 The Unique Argentine Cultural Landscape11:49 Soft Power and Cultural Influence14:48 Political Figures and Their Cultural Impact17:50 The Role of Sports in Shaping National Identity20:49 The Evolution of Argentine Music and Subcultures23:41 AI and the Future of Cultural Dynamics26:47 Navigating the Chaos of AI in Culture33:50 Equilibrating Society for a Sustainable Future35:10 The Patchwork Age: Decentralization and Society35:56 The Impact of AI on Human Connection38:06 Individualism vs. Collective Rules in Society39:26 The Future of AI and Global Regulations40:16 Biotechnology: The Next Frontier42:19 Building a Personal AI Lab45:51 Tiers of AI Labs: From Personal to Industrial48:35 Mathematics and AI: The Foundation of Innovation52:12 Stochastic Models and Predictive Analytics55:47 Building a Supercomputer: Hardware InsightsKey Insights1. Argentina's Cultural Exceptionalism and Emotional Maturity: Argentina stands out globally for allowing eccentrics to flourish and having a non-linear communication style that Gialluca describes as "non-monotonous systems." Argentines can joke profoundly and be eccentric while simultaneously being completely organized and straightforward, demonstrating high emotional intelligence and maturity that comes from their unique cultural blend of European romanticism and Latino lightheartedness.2. Argentina as an Underrecognized Cultural Superpower: Despite being introverted about their achievements, Argentina produces an enormous amount of global culture through music, literature, and iconic figures like Borges, Maradona, Messi, and Che Guevara. These cultural exports have shaped entire generations worldwide, with Argentina "stealing the thunder" from other nations and creating lasting soft power influence that people don't fully recognize as Argentine.3. AI's Cultural Impact Follows Oscillating Patterns: Culture operates as a dynamic system that oscillates between centralization and decentralization like a sine wave. AI currently represents a massive centralizing force, as seen in LinkedIn's homogenized content, but this will inevitably trigger a decentralization phase. The speed of this cultural transformation has accelerated dramatically, with changes that once took generations now happening in years.4. The Coming Bifurcation of AI Futures: Gialluca identifies two extreme possible endpoints for AI development: complete centralized control (the "Mordor" scenario with total surveillance) or complete chaos where everyone has access to dangerous capabilities like creating weapons or viruses. Finding a middle path between these extremes is essential for society's survival, requiring careful equilibrium between accessibility and safety.5. Individual AI Labs Are Becoming Democratically Accessible: Gialluca outlines a tier system for AI capabilities, where individuals can now build "tier one" labs capable of fine-tuning models and processing massive datasets for tens of thousands of dollars. This democratization means that capabilities once requiring teams of PhD scientists can now be achieved by dedicated individuals, fundamentally changing the landscape of AI development and access.6. Hardware Constraints Are the New Limiting Factor: While AI capabilities are rapidly advancing, practical implementation is increasingly constrained by hardware availability and cost. RAM prices have tripled in recent months, and the challenge of managing enormous heat output from powerful processors requires sophisticated cooling systems. These physical limitations are becoming the primary bottleneck for individual AI development.7. Data Quality Over Quantity Is the Critical Challenge: The main bottleneck for AI advancement is no longer energy or GPUs, but high-quality data for training. Early data labeling efforts produced poor results because labelers lacked domain expertise. The future lies in reinforcement learning (RL) environments where AI systems can generate their own high-quality training data, representing a fundamental shift in how AI systems learn and develop.

Timestamps: 0:00 shakin' it up 0:07 Dell un-re-brands, XPS is back 1:47 WiFi 8 devices at CES 2026 3:03 Weird Storage Tech! 5:42 QUICK BITS INTRO 5:51 Nvidia, AMD bringing back old GPUs, CPUs 6:44 First Light game requirements snafu 7:47 Govt probes into Grok 8:50 Texas accuses Samsung TVs of spying 9:32 Wacky keyboard tech at CES 2026 NEWS SOURCES: https://lmg.gg/tBcmY Learn more about your ad choices. Visit megaphone.fm/adchoices

a16z co-founder and General Partner Marc Andreessen joins an AMA-style conversation to explain why AI is the largest technology shift he has experienced, how the cost of intelligence is collapsing, and why the market still feels early despite rapid adoption. The discussion covers how falling model costs and fast capability gains are reshaping pricing, distribution, and competition across the AI stack, why usage-based and value-based pricing are becoming standard, and how startups and incumbents are navigating big versus small models and open versus closed systems. Marc also addresses China's progress, regulatory fragmentation, lessons from Europe, and why venture portfolios are designed to back multiple, conflicting outcomes at once. Resources:Follow Marc Andreessen on X: https://twitter.com/pmarcaFollow Jen Kha on X: https://twitter.com/jkhamehl Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X :https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://twitter.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.    Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Our 230th episode with a summary and discussion of last week's big AI news!Recorded on 01/02/2026Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:Nvidia's acquisition of AI chip startup Groq for $20 billion highlights a strategic move for enhanced inference technology in GPUs.New York's RAISE Act legislation aims to regulate AI safety, marking the second major AI safety bill in the US.The launch of GLM 4.7 by Zhipu AI marks a significant advancement in open-source AI models for coding.Evaluation of long-horizon AI agents raises concerns about the rising costs and efficiency of AI in performing extended tasks.Timestamps:(00:00:10) Intro / Banter(00:01:58) 2025 RetrospectiveTools & Apps(00:24:39) OpenAI bets big on audio as Silicon Valley declares war on screens | TechCrunchApplications & Business(00:26:39) Nvidia buying AI chip startup Groq for about $20 billion, biggest deal(00:34:28) Exclusive | Meta Buys AI Startup Manus, Adding Millions of Paying Users - WSJ(00:38:05) Cursor continues acquisition spree with Graphite deal | TechCrunch(00:39:15) Micron Hikes CapEx to $20B with 2026 HBM Supply Fully Booked; HBM4 Ramps 2Q26(00:42:06) Chinese fabs are reportedly upgrading older ASML DUV lithography chipmaking machines — secondary channels and independent engineers used to soup up Twinscan NXT seriesProjects & Open Source(00:47:52) Z.AI launches GLM-4.7, new SOTA open-source model for coding(00:50:11) Evaluating AI's ability to perform scientific research tasksResearch & Advancements(00:54:32) Large Causal Models from Large Language Models(00:57:33) Universally Converging Representations of Matter Across Scientific Foundation Models(01:02:11) META-RL INDUCES EXPLORATION IN LANGUAGE AGENTS(01:07:16) Are the Costs of AI Agents Also Rising Exponentially?(01:11:17) METR eval for Opus 4.5(01:16:19) How to game the METR plotPolicy & Safety(01:17:24) New York governor Kathy Hochul signs RAISE Act to regulate AI safety | TechCrunch(01:20:40) Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers(01:26:46) Monitoring Monitorability(01:32:07) Sam Altman is hiring someone to worry about the dangers of AI | The Verge(01:33:38) X users asking Grok to put this girl in bikini, Grok is happy obliging - India TodaySee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This Week In Startups is made possible by:Crusoe Cloud - https://crusoe.ai/buildUber - http://uber.com/twistEvery.io - http://every.io/Today's show: Jason and Alex are BACK on TWiST for 2026! This holiday season was anything but calm, with deca-corn acquisitions, massive Polymarket bets, and major new startups breaking from stealth!Jason talks the recent Nvidia-Groq $20B acquisition, a major exit for Chamath as the lead investor back in 2017! Jason delves into how the VC fund math shapes out for pre-seed VC funds vs. Series A VC funds.Jason and Alex delve into drama swirling META's AI team. Yann LeCun, META's former Chief AI Scientist, announced that he would be leaving META to become Executive Chairman at AMI Labs. LeCun left the META team in the new year, calling the new Chief AI Scientist, Alexandr Wang, inexperienced. LeCun now looks to move AI beyond the era of LLM at AMI Labs.PLUS Jason and Alex talk about the new social media app Tangle, from Biz Stone, co-founder of Twitter, and Evan Sharp, co-founder of Pinterest. Their Startup, West Co, launched tangle, which seeks to become an “intentional living” app. The two look to improve how humans interact with modern tech. Jason points out that very few news products have worked, but is eager to see how two industry veterans build in the space. Timestamps:(00:00) Why Restaurants are OVER — Peptides and other self medications(06:41) Nvidia Acqui-Hires Groq for $20 BILLION(9:48) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(11:00) The VC fund math between seed vs. Series A funds(15:00) META buys TWiST 500 Company, Manus! Why it matters.(20:20) Uber AI Solutions: Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/twist(21:24) Why Yann LeCun left META, and what could be behind it(25:27) Producer Claude on the Gondola Crash in Zurich(29:13) Jason's Request for Augmented human intelligence(30:11) Every.io - For all of your incorporation, banking, payroll, benefits, accounting, taxes or other back-office administration needs, visit http://every.io/(32:04) How one Trader made $436.8k on one bet on polymarket!(36:05) Jason's Predictions for 2026 IPOs(40:01) Is news broken? How Tangle is tackling it.(45:53) How much should startup incur in legal expenses? Should founders try to use AI to avoid costs?(50:59) Why Google should let NotebookLM cook, make it a standalone brand! *Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis/*Thank you to our partners:(9:48) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(20:20) Uber AI Solutions: Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/twist(30:11) Every.io - For all of your incorporation, banking, payroll, benefits, accounting, taxes or other back-office administration needs, visit http://every.io/

The future of AI training is shaped by one constraint: keeping GPUs fed.In this episode, Lukas Biewald talks with CoreWeave SVP Corey Sanders about why general-purpose clouds start to break down under large-scale AI workloads.According to Corey, the industry is shifting toward a "Neo Cloud" model to handle the unique demands of modern models.They dive into the hardware and software stack required to maximize GPU utilization and achieve high goodput.Corey's conclusion is clear: AI demands specialization.Connect with us here:Corey Sanders: https://www.linkedin.com/in/corey-sanders-842b72/ CoreWeave: https://www.linkedin.com/company/coreweave/ Lukas Biewald: https://www.linkedin.com/in/lbiewald/ Weights & Biases: https://www.linkedin.com/company/wandb/(00:00) Trailer(00:57) Introduction(02:51) The Evolution of AI Workloads(06:22) Core Weave's Technological Innovations(13:58) Customer Engagement and Future Prospects(28:49) Comparing Cloud Approaches(33:50) Balancing Executive Roles and Hands-On Projects(46:44) Product Development and Customer Feedback

This week, John, Niki, and Lotus stare down the barrel of a very slow gaming news week, so they tackle some additional stuff, too, including:Twitter's Gen AI CSAM and sexual violence catastropheMicrosoft's CEO begging us to stop calling Gen AI "slop"GOG cofounder buys GOG from CD PROJEKT (which he also cofounded)GPUs are going to get even more expensiveSplitgate sequel is not going very wellWe played:Formless Star, the follow-up to sublime FrankenFinal Fantasy IX, perhaps the best of the entire franchiseWe also answer your burning HIVE QUESTIONS straight from our lovely Discord.

FOUNDING OPENAI Colleague Keach Hagey, The Optimist. In 2016, Sam Altman, Greg Brockman, and Ilya Sutskever founded OpenAI as a nonprofit research lab to develop safe artificial general intelligence (AGI). Backed by investors like Elon Musk and Peter Thiel, the organization aimed to be a counterweight to Google's DeepMind, which was driven by profit. The team relied on massive computing power provided by GPUs—originally designed for video games—to train neural networks, recruiting top talent like Sutskever to lead their scientific efforts. NUMBER 13 1955

SHOW 12-2-2026 THE SHOW BEGIJS WITH DOUBTS ABOUT AI --  a useful invetion that can match the excitement of the first decades of Photography. November 1955 NADAR'S BALLOON AND THE BIRTH OF PHOTOGRAPHY Colleague Anika Burgess, Flashes of Brilliance. In 1863, the photographer Nadar undertook a perilous ascent in a giant balloon to fund experiments for heavier-than-air flight, illustrating the adventurous spirit required of early photographers. This era began with Daguerre's 1839 introduction of the daguerreotype, a process involving highly dangerous chemicals like mercury and iodine to create unique, mirror-like images on copper plates. Pioneers risked their lives using explosive materials to capture reality with unprecedented clarity and permanence. NUMBER 1 PHOTOGRAPHING THE MOON AND SEA Colleague Anika Burgess, Flashes of Brilliance. Early photography expanded scientific understanding, allowing humanity to visualize the inaccessible. James Nasmyth produced realistic images of the moon by photographing plaster models based on telescope observations, aiming to prove its volcanic nature. Simultaneously, Louis Boutan spent a decade perfecting underwater photography, capturing divers in hard-hat helmets. These efforts demonstrated that photography could be a tool for scientific analysis and discovery, revealing details of the natural world previously hidden from the human eye. NUMBER 2 SOCIAL JUSTICE AND NATURE CONSERVATION Colleague Anika Burgess, Flashes of Brilliance. Photography became a powerful agent for social and environmental change. Jacob Riis utilized dangerous flash powder to document the squalid conditions of Manhattan tenements, exposing poverty to the public in How the Other Half Lives. While his methods raised consent issues, they illuminated grim realities. Conversely, Carleton Watkins hauled massive equipment into the wilderness to photograph Yosemite; his majestic images influenced legislation signed by Lincoln to protect the land, proving photography's political impact. NUMBER 3 X-RAYS, SURVEILLANCE, AND MOTION Colleague Anika Burgess, Flashes of Brilliance. The discovery of X-rays in 1895 sparked a "new photography" craze, though the radiation caused severe injuries to early practitioners and subjects. Photography also entered the realm of surveillance; British authorities used hidden cameras to photograph suffragettes, while doctors documented asylum patients without consent. Finally, Eadweard Muybridge's experiments captured horses in motion, settling debates about locomotion and laying the technical groundwork for the future development of motion pictures. NUMBER 4 THE AWAKENING OF CHINA'S ECONOMY Colleague Anne Stevenson-Yang, Wild Ride. Returning to China in 1994, the author witnessed a transformation from the destitute, Maoist uniformity of 1985 to a budding export economy. In the earlier era, workers slept on desks and lacked basic goods, but Deng Xiaoping's realization that the state needed hard currency prompted reforms. Deng established Special Economic Zones like Shenzhen to generate foreign capital while attempting to isolate the population from foreign influence, marking the start of China's export boom. NUMBER 5 RED CAPITALISTS AND SMUGGLERS Colleague Anne Stevenson-Yang, Wild Ride. Following the 1989 Tiananmen crackdown, China reopened to investment in 1992, giving rise to "red capitalists"—often the children of party officials who traded political access for equity. As the central government lost control over local corruption and smuggling rings, it launched "Golden Projects" to digitize and centralize authority over customs and taxes. To avert a banking collapse in 1998, the state created asset management companies to absorb bad loans, effectively rolling over massive debt. NUMBER 6 GHOST CITIES AND THE STIMULUS TRAP Colleague Anne Stevenson-Yang, Wild Ride. China's growth model shifted toward massive infrastructure spending, resulting in "ghost cities" and replica Western towns built to inflate GDP rather than house people. This "Potemkin culture" peaked during the 2008 Olympics, where facades were painted to impress foreigners. To counter the global financial crisis, Beijing flooded the economy with loans, fueling a real estate bubble that consumed more cement in three years than the US did in a century, creating unsustainable debt. NUMBER 7 STAGNATION UNDER SURVEILLANCE Colleague Anne Stevenson-Yang, Wild Ride. The severe lockdowns of the COVID-19 pandemic shattered consumer confidence, leaving citizens insecure and unwilling to spend, which stalled economic recovery. Local governments, cut off from credit and burdened by debt, struggle to provide basic services. Faced with economic stagnation, Xi Jinping has rejected market liberalization in favor of increased surveillance and control, prioritizing regime security over resolving the structural debt crisis or restoring the dynamism of previous decades. NUMBER 8 FAMINE AND FLIGHT TO FREEDOM Colleague Mark Clifford, The Troublemaker. Jimmy Lai was born into a wealthy family that lost everything to the Communist revolution, forcing his father to flee to Hong Kong while his mother endured labor camps. Left behind, Lai survived as a child laborer during a devastating famine where he was perpetually hungry. A chance encounter with a traveler who gave him a chocolate bar inspired him to escape to Hong Kong, the "land of chocolate," stowing away on a boat at age twelve. NUMBER 9 THE FACTORY GUY Colleague Mark Clifford, The Troublemaker. By 1975, Jimmy Lai had risen from a child laborer to a factory owner, purchasing a bankrupt garment facility using stock market profits. Despite being a primary school dropout who learned English from a dictionary, Lai succeeded through relentless work and charm. He capitalized on the boom in American retail sourcing, winning orders from Kmart by producing samples overnight and eventually building Comitex into a leading sweater manufacturer, embodying the Hong Kong dream. NUMBER 10 CONSCIENCE AND CONVERSION Colleague Mark Clifford, The Troublemaker. The 1989 Tiananmen Squaremassacre radicalized Lai, who transitioned from textiles to media, founding Next magazine and Apple Daily to champion democracy. Realizing the brutality of the Chinese Communist Party, he used his wealth to support the student movement and expose regime corruption. As the 1997 handover approached, Lai converted to Catholicism, influenced by his wife and pro-democracy peers, seeking spiritual protection and a moral anchor against the coming political storm. NUMBER 11 PRISON AND LAWFARE Colleague Mark Clifford, The Troublemaker. Following the 2020 National Security Law, authorities raided Apple Daily, froze its assets, and arrested Lai, forcing the newspaper to close. Despite having the means to flee, Lai chose to stay and face imprisonment as a testament to his principles. Now held in solitary confinement, he is subjected to "lawfare"—sham legal proceedings designed to silence him—while he spends his time sketching religious images, remaining a symbol of resistance against Beijing's tyranny. NUMBER 12 FOUNDING OPENAI Colleague Keach Hagey, The Optimist. In 2016, Sam Altman, Greg Brockman, and Ilya Sutskever founded OpenAI as a nonprofit research lab to develop safe artificial general intelligence (AGI). Backed by investors like Elon Musk and Peter Thiel, the organization aimed to be a counterweight to Google's DeepMind, which was driven by profit. The team relied on massive computing power provided by GPUs—originally designed for video games—to train neural networks, recruiting top talent like Sutskever to lead their scientific efforts. NUMBER 13 THE ROOTS OF AMBITION Colleague Keach Hagey, The Optimist. Sam Altman grew up in St. Louis, the son of an idealistic developer and a driven dermatologist mother who instilled ambition and resilience in her children. Altmanattended the progressive John Burroughs School, where his intellect and charisma flourished, allowing him to connect with people on any topic. Though he was a tech enthusiast, his ability to charm others defined him early on, foreshadowing his future as a master persuader in Silicon Valley. NUMBER 14 SILICON VALLEY KINGMAKER Colleague Keach Hagey, The Optimist. At Stanford, Altman co-founded Loopt, a location-sharing app that won him a meeting with Steve Jobs and a spot in the App Store launch. While Loopt was not a commercial success, the experience taught Altman that his true talent lay in investing and spotting future trends rather than coding. He eventually succeeded Paul Graham as president of Y Combinator, becoming a powerful figure in Silicon Valley who could convince skeptics like Peter Thiel to back his visions. NUMBER 15 THE BLIP AND THE FUTURE Colleague Keach Hagey, The Optimist. The viral success of ChatGPT shifted OpenAI's focus from safety to commercialization, despite early internal warnings about the existential risks of AGI. Tensions over safety and Altman's management style led to a "blip" where the nonprofit board fired him, only for him to be quickly reinstated due to employee loyalty. Elon Musk, having lost a power struggle for control of the organization, severed ties, leaving Altman to lead the race toward AGI. NUMBER 16

Recorded January 1, 2026 - but only due to popular demand.  We cover the GOG purchase, the ever rising price of DDR and the fallout from all that, and talk about getting a Dumb TV again.Thanks to Copilot Money for the sponsorship again!  Get all your financials on a single piece of glass and bring order to your spending with smart analysis.  Support our show and check them out https://try.copilot.money/pcper0:00 Intro01:21 Patreon02:24 No food segment this week02:57 The rising cost of RTX 5090 and what this means for GPUs in 202604:50 SSD prices rising05:43 DDR5 continues to rise08:51 ASUS reportedly increasing DDR4 motherboard production in 202613:28 GOG acquired by co-founder18:37 Cinebench 2026 arrives22:47 Direct3D 6 support comes to D7VK as retro gaming on Linux evolves26:56 When you don't want a "smart" TV30:17 Podcast sponsor - Copilot Money31:47 (In)Security Corner37:16 Gaming Quick Hits42:39 Picks of the Week53:18 Outro ★ Support this podcast on Patreon ★

The lesson Austin Lyons says he will take away from 2025 is the deep ties AI has to the CapEx story. Companies like Nvidia (NVDA) and TSMC (TSM) are juggernauts he expects to benefit as AI spending accelerates in 2026. When it comes to growing TPU competition from Alphabet (GOOGL), he doesn't see it serving as a perfect substitute to Nvidia's GPUs. Austin later taps Apple's (AAPL) AI story, or lack thereof, and how it serves as a company bull case. ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

Kyle Okamoto is the Chief Technology Officer at Aethir: the leading decentralized enterprise-grade cloud computing network. With over 20 years of experience in cloud and edge computing, digital media, IoT and AI, Kyle's leadership has been pivotal in scaling growth businesses and driving technological innovation at Aethir.Before joining Aethir, Kyle served as the General Manager of Aeris Communications and Ericsson's enterprise businesses, overseeing Internet of Things, Security, and Connected Vehicle portfolio companies. He was also the Chief Executive Officer of Edge Gravity, a global edge cloud platform facilitating cloud gaming, AI, and media and entertainment applications. Kyle's extensive experience also includes his tenure as Chief Network Officer of Verizon Media and his role as a founding member of Verizon Digital Media Services, which grew to a multi-billion dollar business before its acquisition by Private Equity.In addition to his work with Aethir, Kyle is an early investor and advisor to Theta Labs, holds board positions in various technology companies and non-profit organizations, and is an active angel investor and advisor in the venture capital and private equity spaces. Kyle holds a Master of Business Administration from New York University and a Bachelor of Engineering degree from Stevens Institute of Technology.In this conversation, we discuss:- AI's growth is now gated by access to compute rather than model quality - Compute is becoming a financial asset class - AI demand continues to outpace supply - GPUs - Investors are starting to treat compute like infrastructure, not software - Financial structures are becoming essential to scaling AI infrastructure - Decentralized compute offers an alternative path during the global GPU shortage- Enterprises are moving toward multi-source compute strategies - Financing compute - The financing of compute is as important as the tech side AethirX: @AethirCloudWebsite: www.aethir.comLinkedIn: AethirKyle OkamotoLinkedIn: Kyle Okamoto---------------------------------------------------------------------------------This episode is brought to you by PrimeXBT.PrimeXBT offers a robust trading system for both beginners and professional traders that demand highly reliable market data and performance. Traders of all experience levels can easily design and customize layouts and widgets to best fit their trading style. PrimeXBT is always offering innovative products and professional trading conditions to all customers.  PrimeXBT is running an exclusive promotion for listeners of the podcast. After making your first deposit, 50% of that first deposit will be credited to your account as a bonus that can be used as additional collateral to open positions. Code: CRYPTONEWS50 This promotion is available for a month after activation. Click the link below: PrimeXBT x CRYPTONEWS50FollowApple PodcastsSpotifyAmazon MusicRSS FeedSee All

Fal ignites 10X image fire with strategic $140 million injection. Hyper-optimized for GPUs enables massive parallel image tasks. Developers celebrate Fal's production-ready acceleration.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiAI Chat YouTube Channel: https://www.youtube.com/@JaedenSchaferJoin my AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

A year ago, AI was still moving faster than everyone else, outpacing companies, governments, and just about anyone trying to keep up. By the end of 2025, that finally started to change. In this episode, our host Leslie D'Monte and Shouvik Das recap 2025 - the year AI stopped being just a breakthrough story and became a governance story. As generative models gave way to agentic systems, and as frameworks like India's DPDP Act came into sharper focus, AI entered a new phase, one where rules, guardrails, and accountability mattered as much as capability. The conversation looks at how 2025 forced a reset. Enterprises rushed to deploy GenAI and agents, only to encounter hallucinations, broken integrations, and the limitations of legacy systems. At the same time, the question shifted from what AI can do to where it should actually be used. A big part of the episode zooms out to India's approach. Instead of heavy regulation, the focus has been on setting boundaries about content labeling, competition oversight, and applying existing laws while still pushing investments in GPUs, data centres, and Indic language models. The goal isn't dominance; it's relevance. And then there's the bigger test: can AI work outside the bubble? In a country where most people don't live in metros or use cutting-edge devices, success looks less like chatbots and more like IVRs, public services, healthcare tools, and systems that disappear into daily life. By the end, the takeaway is simple: 2025 wasn't about AI replacing humans or reaching artificial general intelligence. It was about learning where AI fits, where it fails, and how human judgment, guardrails, and local context still matter more than raw capability. Learn more about your ad choices. Visit megaphone.fm/adchoices

Big Tech spent $560B on AI and made $35B back—no profits, just GPUs and vibes.We break down why NVIDIA is propping up the market, why AI agents don't work, and why the AI boom looks increasingly brittle under the hood.In this episode, we dissect the AI trade using hard data:$560B in capex from the Magnificent 7$35B in AI revenueNo sustainable profits—except for NVIDIAWe cover:Why NVIDIA is the single point of failure for US equitiesHow OpenAI and Anthropic extract value from their own customersWhy “agents” are marketing fictionAnd why AI startups scale by burning cash, not building moatsThis isn't contrarianism.It's what the balance sheets are saying—quietly.

The AI supercycle is expanding beyond just GPUs. In our first episode of the 2026 series, we break down the critical infrastructure that acts as the "roads and freeways" for data: data center networking, optics, and silicon photonics.Logic chips (like CPUs and GPUs) are the "office" where work gets done, but the network is the "commute" that moves that data. Without advanced cabling, transceivers, and switches, AI clusters simply cannot function.Find out what companies are involved in this fast growing market and how to approach investing in them. Join us on Discord with Semiconductor Insider, sign up on our website: www.chipstockinvestor.com/membershipSupercharge your analysis with AI! Get 15% of your membership with our special link here: https://fiscal.ai/csi/Sign Up For Our Newsletter: https://mailchi.mp/b1228c12f284/sign-up-landing-page-short-formChapters:00:00 - Investing in Chip Stocks 2026 01:43 - The "Roads" of AI: What is Data Center Networking? 02:46 - Copper vs. Fiber Optics: The Differences 03:59 - Market Size: Logic vs. Optoelectronics Sales 05:32 - The Cable Kings: Amphenol, Corning & CommScope 08:12 - Light Sources: Coherent, Lumentum & Broadcom 11:15 - Signal Integrity: Re-timers (Astera Labs, Credo) & DSPs 15:16 - Transceivers: Nvidia, Jabil & Intel 17:18 - Switching, Routing & The Full Stack (Broadcom, Marvell) 18:48 - Investment Strategy: Niche Players vs. Supply Chain ControllersIf you found this video useful, please make sure to like and subscribe!*********************************************************Affiliate links that are sprinkled in throughout this video. If something catches your eye and you decide to buy it, we might earn a little coffee money. Thanks for helping us (Kasey) fuel our caffeine addiction!Content in this video is for general information or entertainment only and is not specific or individual investment advice. Forecasts and information presented may not develop as predicted and there is no guarantee any strategies presented will be successful. All investing involves risk, and you could lose some or all of your principal.#Semiconductors #ChipStocks #AIInvesting #DataCenter #SiliconPhotonics #Nvidia #Broadcom #OpticalNetworking #TechStocks #Investing2026Nick and Kasey own shares of a Nvidia, Broadcom, Credo, Amphenol and a number of others mentioned in the video.

Happy holidays from Sinica! This week, I speak with Paul Triolo, Senior Vice President for China and Technology Policy Lead at DGA Albright Stonebridge Group and nonresident honorary senior fellow on technology at the Asia Society Policy Institute's Center for China Analysis. On December 8th, Donald Trump announced via Truth Social that he would approve Nvidia H200 sales to vetted Chinese customers — a decision that immediately sparked fierce debate. Paul and I unpack why this decision was made, why it's provoked such strong reactions, and what it tells us about the future of technology export controls on China. We discuss the evolution of U.S. chip controls from the Entity List expansions under Trump's first term through the October 2022 rules and the Sullivan Doctrine, the role of David Sacks and Jensen Huang in advocating for this policy shift, whether Chinese firms will actually want to buy H200s given their heterogeneous hardware stacks and Beijing's autarky ambitions, what the Reuters report about China cracking ASML's EUV lithography code tells us about the choke point strategy, and whether selective engagement actually strengthens Taiwan's Silicon Shield or undermines it. This conversation is essential listening for understanding the strategic, technical, and political dimensions of the semiconductor competition.6:44 – What the H200 decision actually changes in the real world 9:23 – The evolution of U.S. chip controls: from Entity Lists to the Sullivan Doctrine 18:28 – How Jensen Huang and David Sacks convinced Trump 25:21 – The good-faith case for why export control advocates see H200 approval as a strategic mistake 32:12 – What H200s practically enable: training, inference, or stabilizing existing clusters 38:49 – Will Chinese companies actually buy H200s? The heterogeneous hardware reality 46:06 – The strategic contradiction: exporting 5nm GPUs while freezing tool controls at 16/14nm 51:01 – The Reuters EUV report and what it reveals about choke point technologies 58:43 – How Taiwan fits into this: does selective engagement strengthen the Silicon Shield? 1:07:26 – Looking ahead: broader rethinking of export controls or patchwork exceptions? 1:12:49 – What would have to be true in 2-3 years for critics to have been right about H200?Paying it forward: Poe Zhao and his Substack Hello China TechRecommendations: Paul: Zbig: The Life of Zbigniew Brzezinski, Amerca's Great Power Propheti by Ed Luce; Hyperdimensional Substack by Dean Ball Kaiser: Everything Is Tuberculosis by John Green; The Anthropocene Reviewed by John Green; So Very Small by Thomas LevensonSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Hoy hablamos de movimientos que no salen en una keynote, pero que dicen mucho más de lo que parece.Samsung toma una decisión clave para su futuro en chips móviles y pone al mando de Exynos a un perfil con pedigrí en GPUs. No es un simple fichaje: es una declaración de intenciones tras años de promesas incumplidas. ¿Cambio real… o último intento?Apple, por su parte, sigue recolocando piezas del iPhone lejos de China. Parte de la cámara del iPhone 18 se fabricará en Estados Unidos, en un movimiento que mezcla política, aranceles y control del silicio. No es un “Made in USA”, pero se le empieza a parecer.Y cerramos con un gesto silencioso pero muy ruidoso: Tim Cook compra acciones de Nike en pleno golpe bursátil. No da entrevistas, no tuitea… pero cuando el CEO de Apple abre la cartera, Wall Street escucha.Todo esto, explicado rápido, al grano y con el toque justo de mala uva.Dale al play.

This Week In Startups is made possible by:Caldera + Lab - http://calderalab.com/TWISTCrusoe Cloud - https://crusoe.ai/buildUber - http://uber.com/twistToday's show: Why did a power outage in the Bay Area cause Waymos to pile up on city streets?Jason was actually in San Francisco to take in the spectacle of Waymos blocking traffic. But why did this happen? And can we look forward to a day when automated cars are more graceful and coordinated than ballet dancers performing “Swan Lake”? We're asking the tough (and also culturally erudite) questions!PLUS self-driving cars are coming to London, Coinbase's buying spree continues, another entrant in our nearly-complete Gamma Pitch Deck Competition, AND why Jason predicts that Google is going to buy UBER!You won't want to miss this holiday TWiST!Timestamps:(00:00) It's a holiday TWiST! Jason's calling in from vacay in Lake Tahoe.(03:11) Jason was in SF for the great Waymo power outage!(06:06) Why Jason says one day Waymos will be better coordinated than dancers in “Swan Lake”(07:33) We predicted Starlink coming to every Tesla nearly 3 years ago!(09:05) Caldera + Lab: Whether you're starting fresh or upgrading your routine, Caldera Lab makes skincare simple and effective. Head to http://calderalab.com/TWIST and use TWIST at checkout for 20% off your first order.(11:29) Jason calls what Tesla's Optimus team is planning “otherworldly”(14:39) Why Jason thinks we're all going to live in an “Opt-In Truman Show” someday soon(18:52) Baidu, Lyft, and Uber bring self-driving cars to London… they don't have them already?!(20:49) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(24:02) When do we get to 50% of all rides being done by autonomous vehicles… and how many robotaxis will that take?(27:50) Why Jason thinks Google is going to buy… UBER?!(31:12) Uber AI Solutions: Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/twist(32:30) Will it eventually come down to which car can drive a mile for the cheapest?(35:08) Coinbase picks up The Clearing Company, which makes frameworks for prediction markets(39:50) How much did the biggest AI models improve this year?(44:09) Who's going to actually buy Warner Bros? We're checking the Polymarket.(47:06) GAMMA PITCH w/ Jonathan Sherman of Lumix Ads(51:00) Why Jason says Jonathan's pitch is a 9.5 out of 10(52:50) What Jason looks for in a founder: “a big audacious vision”(54:18) How Lumix (safely) collects users' “mobile ad ID” on the go to identify themSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis/*Thank you to our partners:(09:05) Caldera + Lab: Whether you're starting fresh or upgrading your routine, Caldera Lab makes skincare simple and effective. Head to http://calderalab.com/TWIST and use TWIST at checkout for 20% off your first order.(20:49) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(31:12) Uber AI Solutions: Your trusted partner to get AI to work in the real world. Book a demo with them TODAY at http://uber.com/twist

This week we talk about energy consumption, pollution, and bipartisan issues.We also discuss local politics, data center costs, and the Magnificent 7 tech companies.Recommended Book: Against the Machine by Paul KingsnorthTranscriptIn 2024, the International Energy Agency estimated that data centers consumed about 1.5% of all electricity generated, globally, that year. It went on to project that energy consumption by data centers could double by 2030, though other estimates are higher, due to the ballooning of investment in AI-focused data centers by some of the world's largest tech companies.There are all sorts of data centers that serve all kinds of purposes, and they've been around since the mid-20th century, since the development of general purposes digital computers, like the 1945 Electronic Numerical Integrator and Computer, or ENIAC, which was programmable and reprogrammable, and used to study, among other things, the feasibility of thermonuclear weapons.ENIAC was built on the campus of the University of Pennsylvania and cost just shy of $500,000, which in today's money would be around $7 million. It was able to do calculators about a thousand times faster than other, electro-mechanical calculators that were available at the time, and was thus considered to be a pretty big deal, making some types of calculation that were previously not feasible, not only feasible, but casually accomplishable.This general model of building big-old computers at a center location was the way of things, on a practical level, until the dawn of personal computers in the 1980s. The mainframe-terminal setup that dominated until then necessitated that the huge, cumbersome computing hardware was all located in a big room somewhere, and then the terminal devices were points of access that allowed people to tap into those centralized resources.Microcomputers of the sort of a person might have in their home changed that dynamic, but the dawn of the internet reintroduced something similar, allowing folks to have a computer at home or at their desk, which has its own resources, but to then tap into other microcomputers, and to still other larger, more powerful computers across internet connections. Going on the web and visiting a website is basically just that: connecting to another computer somewhere, that distant device storing the website data on its hard drive and sending the results to your probably less-powerful device, at home or work.In the late-90s and early 2000s, this dynamic evolved still further, those far-off machines doing more and more heavy-lifting to create more and more sophisticated online experiences. This manifested as websites that were malleable and editable by the end-user—part of the so-called Web 2.0 experience, which allowed for comments and chat rooms and the uploading of images to those sites, based at those far off machines—and then as streaming video and music, and proto-versions of social networks became a thing, these channels connecting personal devices to more powerful, far-off devices needed more bandwidth, because more and more work was being done by those powerful, centrally located computers, so that the results could be distributed via the internet to all those personal computers and, increasingly, other devices like phones and tablets.Modern data centers do a lot of the same work as those earlier iterations, though increasingly they do a whole lot more heavy-lifting labor, as well. They've got hardware capable of, for instance, playing the most high-end video games at the highest settings, and then sending, frame by frame, the output of said video games to a weaker device, someone's phone or comparably low-end computer, at home, allowing the user of those weaker devices to play those games, their keyboard or controller inputs sent to the data center fast enough that they can control what's happening and see the result on their own screen in less than the blink of an eye.This is also what allows folks to store backups on cloud servers, big hard drives located in such facilities, and it's what allows the current AI boom to function—all the expensive computers and their high-end chips located at enormous data centers with sophisticated cooling systems and high-throughput cables that allow folks around the world to tap into their AI models, interact with them, have them do heavy-lifting for them, and then those computers at these data centers send all that information back out into the world, to their devices, even if those devices are underpowered and could never do that same kind of work on their own.What I'd like to talk about today are data centers, the enormous boom in their construction, and how these things are becoming a surprise hot button political issue pretty much everywhere.—As of early 2024, the US was host to nearly 5,400 data centers sprawled across the country. That's more than any other nation, and that number is growing quickly as those aforementioned enormous tech companies, including the Magnificent 7 tech companies, Nvidia, Apple, Alphabet, Microsoft, Amazon, Meta, and Tesla, which have a combined market cap of about $21.7 trillion as of mid-December 2025, which is about two-thirds of the US's total GDP for the year, and which is more than the European Union's total GDP, which weighs in at around $19.4 trillion, as of October 2025—as they splurge on more and more of them.These aren't the only companies building data centers at breakneck speed—there are quite a few competitors in China doing the same, for instance—but they're putting up the lion's share of resources for this sort of infrastructure right now, in part because they anticipate a whole lot of near-future demand for AI services, and those services require just a silly amount of processing power, which itself requires a silly amount of monetary investment and electricity, but also because, first, there aren't a lot of moats, meaning protective, defensive assets in this industry, as is evidenced by their continual leapfrogging of each other, and the notion that a lot of what they're doing, today, will probably become commodity services in not too long, rather than high-end services people and businesses will be inclined to pay big money for, and second, because there's a suspicion, held by many in this industry, that there's an AI shake-out coming, a bubble pop or bare-minimum a release of air from that bubble, which will probably kill off a huge chunk of the industry, leaving just the largest, too-big-to-fail players still intact, who can then gobble up the rest of the dying industry at a discount.Those who have the infrastructure, who have invested the huge sums of money to build these data centers, basically, will be in a prime position to survive that extinction-level event, in other words. So they're all scrambling to erect these things as quickly as possible, lest they be left behind.That construction, though, is easier said than done.The highest-end chips account for around 70-80% of a modern data center's cost, as these GPUs, graphical processing units that are optimized for AI purposes, like Nvidia's Blackwell chips, can cost tens of thousands of dollars apiece, and millions of dollars per rack. There are a lot of racks of such chips in these data centers, and the total cost of a large-scale AI-optimized data center is often somewhere between $35 and $60 billion.A recent estimate by McKinsey suggests that by 2030, data center investment will need to be around $6.7 trillion a year just to keep up the pace and meet demand for compute power. That's demand from these tech companies, I should say—there's a big debate about where there's sufficient demand from consumers of AI products, and whether these tech companies are trying to create such demand from whole cloth, to justify heightened valuations, and thus to continue goosing their market caps, which in turn enriches those at the top of these companies.That said, it's a fair bet that for at least a few more years this influx in investment will continue, and that means pumping out more of these data centers.But building these sorts of facilities isn't just expensive, it's also regulatorily complex. There are smaller facilities, akin to ENIAC's campus location, back in the day, but a lot of them—because of the economies of scale inherent in building a lot of this stuff all at once, all in the same place—are enormous, a single data center facility covering thousands of acres and consuming a whole lot of power to keep all of those computers with their high-end chips running 24/7.Previous data centers from the pre-AI era tended to consume in the neighborhood of 30MW of energy, but the baseline now is closer to 200MW. The largest contemporary data centers consume 1GW of electricity, which is about the size of a small city's power grid—that's a city of maybe 500,000-750,000 people, though of course climate, industry, and other variables determine the exact energy requirements of a city—and they're expected to just get larger and more resource-intensive from here.This has resulted in panic and pullbacks in some areas. In Dublin, for instance, the government has stopped issuing new grid connections for data centers until 2028, as it's estimated that data centers will account for 28% of Ireland's power use by 2031, already.Some of these big tech companies have read the writing on the wall, and are either making deals to reactivate aging power plants—nuclear, gas, coal, whatever they can get—or are saying they'll build new ones to offset the impact on the local power grid.And that impact can be significant. In addition to the health and pollution issues caused by some of the sites—in Memphis, for instance, where Elon Musk's company, xAI, built a huge data center to help power his AI chatbot, Grok, the company is operating 35 unpermitted gas turbines, which it says are temporary, but which have been exacerbating locals' health issues and particulate numbers—in addition to those issues, energy prices across the US are up 6.9% year over year as of December 2025, which is much higher than overall inflation. Those costs are expected to increase still further as data centers claim more of the finite energy available on these grids, which in turn means less available for everyone else, and that scarcity, because of supply and demand, increases the cost of that remaining energy.As a consequence of these issues, and what's broadly being seen as casual overstepping of laws and regulations by these companies, which often funnel a lot of money to local politicians to help smooth the path for their construction ambitions, there are bipartisan efforts around the world to halt construction on these things, locals saying the claimed benefits, like jobs, don't actually make sense—as construction jobs will be temporary, and the data centers themselves don't require many human maintainers or operators, and because they consume all that energy, in some cases might consume a bunch of water—possibly not as much as other grand-scale developments, like golf courses, but still—and they tend to generate a bunch of low-level, at times harmful background noise, can create a bunch of local pollution, and in general take up a bunch of space without giving any real benefit to the locals.Interestingly, this is one of the few truly bipartisan issues that seems to be persisting in the United States, at a moment in which it's often difficult to find things Republicans and Democrats can agree on, and that's seemingly because it's not just a ‘big companies led by untouchable rich people stomping around in often poorer communities and taking what they want' sort of issue, it's also an affordability issue, because the installation of these things seems to already be pushing prices higher—when the price of energy goes up, the price of just about everything goes up—and it seems likely to push prices even higher in the coming years.We'll see to what degree this influences politics and platforms moving forward, but some local politicians in particular are already making hay by using antagonism toward the construction of new data centers a part of their policy and campaign promises, and considering the speed at which these things are being constructed, and the slow build of resistance toward them, it's also an issue that could persist through the US congressional election in 2026, to the subsequent presidential election in 2028.Show Noteshttps://www.wired.com/story/opposed-to-data-centers-the-working-families-party-wants-you-to-run-for-office/https://finance.yahoo.com/news/without-data-centers-gdp-growth-171546326.htmlhttps://time.com/7308925/elon-musk-memphis-ai-data-center/https://wreg.com/news/new-details-on-152m-data-center-planned-in-memphis/https://www.politico.com/news/2025/05/06/elon-musk-xai-memphis-gas-turbines-air-pollution-permits-00317582https://www.datacenterwatch.org/reporthttps://www.govtech.com/products/kent-county-mich-cancels-data-center-meeting-due-to-crowdhttps://www.woodtv.com/news/kent-county/gaines-township-planning-commission-to-hold-hearing-on-data-center-rezoning/https://www.theverge.com/science/841169/ai-data-center-oppositionhttps://www.iea.org/reports/energy-and-ai/energy-demand-from-aihttps://www.cbre.com/insights/reports/global-data-center-trends-2025https://www.phoenixnewtimes.com/news/chandler-city-council-unanimously-kills-sinema-backed-data-center-40628102/https://www.mlive.com/news/ann-arbor/2025/11/rural-michigan-fights-back-how-riled-up-residents-are-challenging-big-tech-data-centers.html?outputType=amphttps://www.courthousenews.com/nonprofit-sues-to-block-165-billion-openai-data-center-in-rural-new-mexico/https://www.datacenterdynamics.com/en/news/microsoft-cancels-plans-for-data-center-caledonia-wisconsin/https://www.cnbc.com/2025/11/25/microsoft-ai-data-center-rejection-vs-support.htmlhttps://www.wpr.org/news/microsoft-caledonia-data-center-site-ozaukee-countyhttps://thehill.com/opinion/robbys-radar/5655111-bernie-sanders-data-center-moratorium/https://www.investopedia.com/magnificent-seven-stocks-8402262https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-cost-of-compute-a-7-trillion-dollar-race-to-scale-data-centershttps://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/ai-power-expanding-data-center-capacity-to-meet-growing-demandhttps://www.marketplace.org/story/2025/12/19/are-energyhungry-data-centers-causing-electric-bills-to-go-uphttps://en.wikipedia.org/wiki/Data_centerhttps://en.wikipedia.org/wiki/ENIAC This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit letsknowthings.substack.com/subscribe

Amolak Badesha has a habit of being ahead of the curve in GPUs and optics. So his outlandish and very futuristic claims in this podcast may seem crazy, but maybe the world will catch up with him. Orbital Composites is making large-scale composite structures, but its machines are also used for high-end bike shoes. The company wants to conquer space, and in this wide-ranging conversation we talk about all the implications and technologies that they’re working with. This episode of the 3DPOD is sponsored by EOS, a leading global partner for industrial 3D printing solutions in both metal and polymer. With decades of additive manufacturing expertise, technologies and partnerships, EOS empowers customers to innovate, differentiate and shape the future of manufacturing. 

Building artificial intelligence tools requires a lot of graphic processing units, and those GPUs need huge amounts of ultra-fast memory to feed them data. Micron Technology is one of a handful of memory chip makers that has been selling a whole lot of memory, thanks to the AI boom.Plus, cloud company Oracle's data center debt is coming under scrutiny. And Merriam-Webster names the word of the year for 2025: slop.Marketplace's Meghan McCarty Carino spoke with Anita Ramaswamy, columnist at The Information, to learn more on this week's Marketplace Tech Bytes: Week in Review.

Building artificial intelligence tools requires a lot of graphic processing units, and those GPUs need huge amounts of ultra-fast memory to feed them data. Micron Technology is one of a handful of memory chip makers that has been selling a whole lot of memory, thanks to the AI boom.Plus, cloud company Oracle's data center debt is coming under scrutiny. And Merriam-Webster names the word of the year for 2025: slop.Marketplace's Meghan McCarty Carino spoke with Anita Ramaswamy, columnist at The Information, to learn more on this week's Marketplace Tech Bytes: Week in Review.

Jeetu Patel knows a few AI secrets. As the President of one of the largest companies in the world, he's helped pave the AI adoption roadmap. At Cisco, they provide full-stack, enterprise AI solutions spanning infrastructure, security, observability, and operations to the world's largest companies. So naturally, Jeetu could write a legit playbook on what's slowing enterprises down in the AI fast lane and how they can overcome those bottlenecks. And naturally, Jeetu is gonna share it all with us. The 3 Big Obstacles Holding AI Adoption Back -- An Everyday AI Chat with Cisco President Jeetu PatelNewsletter: Sign up for our free daily newsletterMore on this Episode:Episode PageJoin the discussion on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Enterprise AI Adoption Rates & ChallengesAI Workflow Automation Phase ExplainedThree Big Obstacles to AI AdoptionInfrastructure Constraints for Enterprise AITrust Deficit in AI SystemsData Gaps Impacting AI SuccessMeasuring ROI on Enterprise AI DeploymentFuture Trends: Agentic AI and Original InsightsTimestamps:00:00 AI Adoption Challenges in Enterprise05:18 AI Adaptation: The Key Strength08:56 AI Infrastructure and Trust Challenges10:23 Building Trust and Harnessing Data13:27 Unsatiated Demand Signals Growth19:12 Proactive AI Model Safeguards22:07 AI Strategy and Business Growth26:09 Key Metrics for AI Success28:10 Guardrails for AI Vulnerabilities31:34 AI Unlocking Revolutionary DiscoveriesKeywords:AI adoption, obstacles to AI adoption, enterprise AI, generative AI, AI strategies, chatbots, autonomous agents, workflow automation, business productivity automation, infrastructure for AI, AI power consumption, data center capacity, compute capacity, GPUs, Nvidia, AMD, network bandwidth, CapEx in AI, AI bubble, national security and AI, economic growth and AI, AI trust deficit, securing AI, AI safety, AI hallucinations, large language models, model unpredictability, AI guardrails, algorithmic jailbreak, AI security stack, AI defense, company data as moat, AI data pipeline, data gap in AI, machine data, human data, synthetic data, time series data, data correlation, AI model training, AI ROI, trust in AI systems, agentic workflows, future of AI, robotics, humanoid AI, physical AI, original insights with AI, economic prosperity with AI, AI-generated knowledge, workflow automation with AI agents, scaling AI in enterprisesSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

Episode 93: A rumor and news episode to round out 2025. We chat a bit more about 9850X3D expectations, the current and future state of Intel CPUs following some 225F testing, Nvidia cutting GPU supply, potential new GPUs and Steve kills some hardware.CHAPTERS00:00 - Intro02:33 - More Thoughts on the 9850X3D06:13 - Where is Intel at With Their CPUs?24:42 - Nvidia Cutting GPU Supply?37:38 - AMD Launches Radeon RX 9060 XT LP43:22 - More Intel Arc B770 Rumors49:12 - 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.

Comment on this episode by going to KDramaChat.comToday, we'll be discussing Episode 5 of Start-Up, the hit K Drama on Netflix starring Bae Suzy as Seo Dal-mi, Nam Joo Hyuk as Nam Do-san, Kim Seon Ho as Han Ji Pyeong, Kang Han Na as Won In Jae, and Kim Hae Sook as Choi Won Deok. We discuss:The songs featured during the recap: "Running" by Gaho and "Shake Shake."The intense and emotional hackathon that tests our characters' ambition, determination, and self-worth.Seo Dal-mi's rising ambition and her impressive performance as the new CEO of Samsan Tech.Nam Do-san's growing confidence, his romantic development, and his beautiful metaphor involving Tarzan.The theme of imposter syndrome and how both Dal-mi and Do-san feel they're not worthy — but believe in each other.The critical role APIs, GPUs, data sets, and artificial neural networks play in tech — and how they're introduced in the show.Han Ji Pyeong's internal turmoil, guilt, and shift from dismissive investor to personal mentor and backer of Samsan Tech.The heartbreaking reveal that Dal-mi didn't go to college because she wanted to buy a corn dog truck for her grandmother.Dal-mi's smart and humble recruitment of Jeong Sa Ha, a designer with top-tier credentials, by literally going down on her knees.The competitive and cold dynamic between the sisters, especially in the brutal bathroom scene.The sly arrival of stylish twins to In Jae Company and the challenge they pose to Samsan Tech.Alex Kwon's savvy evaluation of Samsan Tech's potential, not just performance — and his pivotal vote that secures their place in Sandbox.The ethics and motivations behind Han Ji Pyeong's involvement in the letters, and Seo Dal-mi's growing suspicions.Our reflections on the character of Han Ji Pyeong and whether redemption is possible.The amazing career of Kang Han Na, the actress who plays Won In Jae, including her roles in Moon Lovers, Bon Appetit, and her stint as a top DJ for KBS.ReferencesKang Han Na on WikipediaGUI Steakhouse in New York CityData.gov, the home of the US Government's Open DataRunning by Gaho

Try OCI for free at http://oracle.com/eyeonai  This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking.  Join Modal, Skydance Animation, and today's innovative AI tech companies who upgraded to OCI…and saved. Why is AI moving from the cloud to our devices, and what makes on device intelligence finally practical at scale? In this episode of Eye on AI, host Craig Smith speaks with Christopher Bergey, Executive Vice President of Arm's Edge AI Business Unit, about how edge AI is reshaping computing across smartphones, PCs, wearables, cars, and everyday devices. We explore how ARM v9 enables AI inference at the edge, why heterogeneous computing across CPUs, GPUs, and NPUs matters, and how developers can balance performance, power, memory, and latency. Learn why memory bandwidth has become the biggest bottleneck for AI, how ARM approaches scalable matrix extensions, and what trade offs exist between accelerators and traditional CPU based AI workloads. You will also hear real world examples of edge AI in action, from smart cameras and hearing aids to XR devices, robotics, and in car systems. The conversation looks ahead to a future where intelligence is embedded into everything you use, where AI becomes the default interface, and why reliable, low latency, on device AI is essential for creating experiences users actually trust. Stay Updated: Craig Smith on X: https://x.com/craigss     Eye on A.I. on X: https://x.com/EyeOn_AI 

En la última tertulia del año traemos Carles Reina (ElevenLabs) como responsable de go-to-market y, además, como inversor: comenta que ha hecho decenas de “tickets” y que acaba de levantar su propio fondo, Baobab Ventures.A partir de ahí, la conversación entra fuerte en el negocio de ElevenLabs: explican que construyen modelos de voz “naturales” y operan en ~70 idiomas, y que encima han montado productos de agentes, doblaje, transcripción, etc. Carles da cifras muy concretas de tracción (alrededor de 400 personas y más de 300M de facturación, alcanzados “hace unas semanas”) y describe un motor enterprise muy agresivo (hablan de 150–170 contratos al mes y de un día especialmente “loco” superando 14M en enterprise). También hablan de por qué siguen levantando rondas aun generando caja: señal al mercado, liquidez para empleados vía secundario, y capacidad de invertir/comprar (incluidas GPUs). En ese bloque bromean bastante con los múltiplos (el “33x” como estándar) y con la posible burbuja en el sector. Luego hablan del tema más “cultural” y polémico: el doblaje y los derechos de voz. Sale Masumi un actor de doblaje conocido en España (que es la voz de Harry Potter y Anakin, y su vínculo con el sindicato) y se discute la línea roja de “no entrenar modelos con nuestras voces” frente a usos consentidos. Carles cuenta casos prácticos en Hollywood donde actores ceden permiso para usar su propia voz en postproducción cuando no pueden grabar, y aparece la idea que vertebra todo el debate: poder ver una peli con “la misma voz del actor” en otro idioma (por ejemplo, el ideal de oír a la misma actriz hablando en catalán o castellano sin perder identidad), frente a la realidad del consumo en España (acostumbrados al doblaje) y la alternativa de VO con subtítulos. En “actualidad/noticias”, el bloque más largo gira alrededor de una supuesta ola de consolidación en streaming y medios: comentan una operación de Netflix con Warner (centrada en activos digitales tipo HBO/HBO Max) y, como contrapeso, una oferta de Paramount por “todo” (y el lío político/regulatorio alrededor del antitrust). Ahí meten nombres y contexto político: hablan de Donald Trump opinando públicamente, de la familia Ellison (Oracle) detrás de Paramount, de tensiones por contenidos/editoriales, y de cómo eso mueve preferencias y narrativas; incluso lo cruzan con TikTok como parte del “ruido” de esos días. A nivel de análisis, lo conectan con el choque entre “calidad premium” (HBO/Warner) y “volumen/variedad algorítmica” (Netflix/TikTok) y con el riesgo de que la consolidación reduzca competencia y, por tanto, incentive menos calidad. También mencionan otras “noticias” tech/IA del momento dentro de la tertulia: preguntan por un anuncio de OpenAI con Disney y si cambia algo en la relación (Carles dice que no), y en otro punto comentan como titular que Amazon “por fin” habría invertido fuerte en OpenAI y lo enlazan con la guerra de infraestructura (chips/TPUs vs Nvidia y el rol del cloud). Por último, se abre el foco a inversión y mercado: cuentan que ElevenLabs tiene un “venture” y que invierten desde balance, y aparecen conversaciones típicas de ciclo: comparan múltiplos (Databricks vs Snowflake), especulan con una posible “edad dorada” de salidas a bolsa y, ya en tono de anécdota, comentan que “hoy” alguien anunció una ronda de 200M a 6B (sin entrar demasiado en detalles, pero usándolo como termómetro del hype). Sigue a los "tertulianos" en Twitter:• Bernat Farrero: @bernatfarrero• Jordi Romero: @jordiromero• César Migueláñez: @heycesrSOBRE ITNIG

GPUs dominate today's AI landscape, but Google argues they are not necessary for every workload. As AI adoption has grown, customers have increasingly demanded compute options that deliver high performance with lower cost and power consumption. Drawing on its long history of custom silicon, Google introduced Axion CPUs in 2024 to meet needs for massive scale, flexibility, and general-purpose computing alongside AI workloads. The Axion-based C4A instance is generally available, while the newer N4A virtual machines promise up to 2x price performance.In this episode, Andrei Gueletii, a technical solutions consultant for Google Cloud joined Gari Singh, a product manager for Google Kubernetes Engine (GKE), and Pranay Bakre, a principal solutions engineer at Arm for this episode, recorded at KubeCon + CloudNativeCon North America, in Atlanta. Built on Arm Neoverse V2 cores, Axion processors emphasize energy efficiency and customization, including flexible machine shapes that let users tailor memory and CPU resources. These features are particularly valuable for platform engineering teams, which must optimize centralized infrastructure for cost, FinOps goals, and price performance as they scale.Importantly, many AI tasks—such as inference for smaller models or batch-oriented jobs—do not require GPUs. CPUs can be more efficient when GPU memory is underutilized or latency demands are low. By decoupling workloads and choosing the right compute for each task, organizations can significantly reduce AI compute costs.Learn more from The New Stack about the Axion-based C4A: Beyond Speed: Why Your Next App Must Be Multi-ArchitectureArm: See a Demo About Migrating a x86-Based App to ARM64Join our community of newsletter subscribers to stay on top of the news and at the top of your game.  Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In our latest episode, our co-hosts Robby and Tim talk with Jon Morehouse, founder and CEO of infrastructure company Nuon which enables Bring Your Own Cloud (BYOC) for everyone. This is an exclusive podcast episode with Jon digging into their decision to open source Nuon! The episode discusses the industry's growing shift toward Bring Your Own Cloud (BYOC), where SaaS products run directly inside a customer's cloud account rather than the vendor's. This model is especially attractive to enterprises because it improves security, data sovereignty, and trust, while enabling earlier pilots and shorter sales cycles. Infrastructure products like Nuon focus on making this practical by packaging applications so they work in customer environments without requiring vendor access, positioning BYOC as an enterprise-first approach that is likely to become the default way software is delivered.A key theme is open source as a trust and distribution strategy. In the infrastructure space, open sourcing lowers perceived risk, deepens customer collaboration, and builds community, which in turn acts as sales enablement for large enterprise deals. The conversation also connects BYOC to AI, highlighting patterns like bring-your-own-model, keys, and GPUs, and frames BYOC as a spectrum rather than a binary choice. The broader vision is to define and lead a BYOC movement by uniting vendors around shared standards, trust, and community-driven adoption.

This episode is sponsored by AGNTCY. Unlock agents at scale with an open Internet of Agents.  Visit https://agntcy.org/ and add your support. Why is AI so powerful in the cloud but still so limited inside everyday devices, and what would it take to run intelligent systems locally without draining battery or sacrificing privacy? In this episode of Eye on AI, host Craig Smith speaks with Steve Brightfield, Chief Marketing Officer at BrainChip, about neuromorphic computing and why brain inspired architectures may be the key to the future of edge AI. We explore how neuromorphic systems differ from traditional GPU based AI, why event driven and spiking neural networks are dramatically more power efficient, and how on device inference enables faster response times, lower costs, and stronger data privacy. Steve explains why brute force computation works in data centers but breaks down at the edge, and how edge AI is reshaping wearables, sensors, robotics, hearing aids, and autonomous systems. You will also hear real world examples of neuromorphic AI in action, from smart glasses and medical monitoring to radar, defense, and space applications. The conversation covers how developers can transition from conventional models to neuromorphic architectures, what role heterogeneous computing plays alongside CPUs and GPUs, and why the next wave of AI adoption will happen quietly inside the devices we use every day. Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI  

In this episode of Hands-On IT, Landon Miles explores the history of servers and enterprise IT infrastructure, from early mainframe computers to cloud computing, Linux servers, virtualization, containers, and AI-driven data centers.This episode connects decades of server evolution into a clear, accessible story, focusing on the people, technologies, and ideas that shaped modern computing. From IBM's System/360 and minicomputers, to Unix and Linux, virtualization, cloud platforms like AWS and Azure, and container orchestration with Docker and Kubernetes, this episode explains how servers became the foundation of today's digital world.Topics covered include: • Server history and early computing systems • IBM mainframes and enterprise computing • Minicomputers and distributed computing • Unix, Linux, and open-source software • Virtualization and data center efficiency • Cloud computing and hyperscale infrastructure • Docker, Kubernetes, and cloud-native architecture • AI workloads, GPUs, and modern server hardwareLandon also highlights key figures in computing history, including Grace Hopper, Ken Olsen, Linus Torvalds, Dave Cutler, Diane Greene, and Jeff Bezos, and explains how their work still influences IT operations today.This episode is part of our December Best Of series, featuring some of our favorite moments and episodes from the past year.Originally aired March 20, 2025.

In this week's Stansberry Investor Hour, Dan and Corey welcome Luke Lango to the show. Luke is the senior investment analyst at our corporate affiliate InvestorPlace. He has built a reputation for spotting tech stocks on the verge of major market breakouts.   Luke kicks things off by sharing his thoughts on what many consider to be the current "AI bubble." He follows that up with how the jobs market is going to transition as AI continues to develop and how the economy will fare during that period. And he provides data for how the AI data-center epicenter has impacted the housing market. (0:00)   Next, Luke discusses the shift from companies using graphics processing units ("GPUs") to tensor processing units ("TPUs") for their data centers and why this is taking place. He then gives his thoughts on whether Intel can become a viable competitor again in this market. And he highlights the risks around the AI companies being interconnected and feeding into each other. (18:53)   Finally, Luke expresses why he's pleased that Alphabet has begun to act as a competitor to Nvidia with its own TPUs. He also covers AI being used in ads and how companies like Meta Platforms have seen success with utilizing it in that area. The three all share how they're all using AI in their personal use cases. And Luke gives his thoughts on what the big investment themes are going to be for 2026. (39:01)

- Nvidia H200 exports to China - H20, H200, Chinese chips: how do they stack up? - Few fast GPUs vs many slow GPUs - China's electricity production - Datacenter electricity use in the US - Cell-phone sized AI supercomputer - HPC at the edge - Regulating AI [audio mp3="https://orionx.net/wp-content/uploads/2025/12/HPCNB_20251215.mp3"][/audio] The post HPC News Bytes – 20251215 appeared first on OrionX.net.

This Week In Startups is made possible by:LinkedIn Ads - http://linkedin.com/thisweekinstartupsDevStats - https://www.devstats.com/twistCrusoe - https://crusoe.ai/buildToday's show: FINALLY, you can hang out with Kylo Ren and Olaf the Snowman… thanks to the magic of AI.On TWiST, we're digging into the mega OpenAI-Disney deal. Mickey is giving Sam Altman a $1 billion investment AND will allow is copyrighted characters to appear in Sora and ChatGPT images.Of course, Jason predicted this would happen WAY BACK during the summer months and even showed off his “Darth Calacanis” creation on the “All-In Podcast.”PLUS Amazon has been launching and pulling AI features from Prime Video… what gives? Jason's predictions on the coming AI blowback and who's on what side. Why he's so focused on Education, Health Care, and Housing as issues. AND why founders should always take calls from Big Companies, even if it might just be a fishing expedition.It's a new Friday TWiST! Check it out!Timestamps:(00:00) Lon joins Alex and Jason to talk about the big Disney-OpenAI deal bringing Disney characters to Sora(03:10) Jason totally called the Disney-OpenAI stuff on All-In(9:42) LinkedIn Ads: Start converting your B2B audience into high quality leads today. Launch your first campaign and get $250 FREE when you spend at least $250. Go to http://linkedin.com/thisweekinstartups to claim your credit.(18:59) DevStats - DevStats integrates your dev work and your business goals into a shared language that everyone can understand. Get 20% off, plus access to their dedicated Slack channel. Just go to https://www.devstats.com/twist.(20:15) Why Amazon Prime Video pulled its AI recaps and anime dubs(24:44) Who gets to set the rules around AI: The Debate Continues(26:13) Jason's predictions on the AI blowback coming in 2026… with clips!(30:11) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(31:21) Is AI here to help people or replace them?(35:55) It's all about EHH: Education, Health Care, Housing(40:47) How all of this and MORE will be impacted directly by AI automation(45:35) Why Alex wants to lower the temperature around AI Doomerism(51:19) JUST FOR FOUNDERS: When should you take a call from a BigCo?(53:45) Why Jason thinks just about everyone in media will lose to TikTok and YouTubeSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis/*Thank you to our partners:(9:42) LinkedIn Ads: Start converting your B2B audience into high quality leads today. Launch your first campaign and get $250 FREE when you spend at least $250. Go to http://linkedin.com/thisweekinstartups to claim your credit.(18:59) DevStats - DevStats integrates your dev work and your business goals into a shared language that everyone can understand. Get 20% off, plus access to their dedicated Slack channel. Just go to https://www.devstats.com/twist.(30:11) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.

This week in bitcoin mining news, ERCOT sees a 266 GW of interconnection requests in 2026, IREN closed a $2.3 billion convertible note offering, and GPUs are leaving ASICs in the dust. Subscribe to the Blockspace newsletter for market-making news as it hits the wire! Welcome back to The Mining Pod! Today, Ethan Vera, COO of Luxor, joins us as we dive into MicroBT's Whatsminer M70 launching into a challenging ASIC market, IREN's $2.3 billion convertible note offering, the precarious state of hashprice, Luxor's new GPU hardware sales business, the staggering 270% leap in ERCOT interconnection requests, and the controversial Cat bitcoin fork proposal aimed at filtering ordinals / inscriptions. Subscribe to the newsletter! https://newsletter.blockspacemedia.com **Notes:** - Hash price is below $40 per second - Three negative difficulty adjustments - Ercot requests leaped 270% in 2025 - 73% of requests from data centers - IREN raised $2.3B in convertible notes - M70 efficiency: 12.5 J/TH 00:00 Start 02:35 Difficulty Report by Luxor 07:26 IREN note 10:44 M70 launch 20:02 Luxor launches GPU trading 27:12 ERCOT LL requests up 270% in 2025 34:10 Cry Corner: another filter fork proposal

Episode 92: Edward Crisler from Radeon-exclusive AIB Sapphire joins the podcast to chat about the current GPU market. How will rising DRAM prices affect gaming GPUs? Can the GPU makers and AIBs absorb some of the increased cost? Also we talk about RDNA 4 and how successful it's been compared to previous generations, AMD's true market share, and of course, the Sapphire Puke box artCHAPTERS00:00 - Intro01:03 - RDNA 4 Launch at Sapphire05:11 - RDNA 4 vs Older Generations Success11:32 - The DRAM Crisis20:25 - AIBs Want More Control24:48 - Thoughts on 12VHPWR26:32 - How Are SKU Decisions Made?32:35 - Sapphire Puke35:27 - DRAM Pricing: What Can AMD and AIBs Do?44:50 - AI-Focused GPU Makers Owe Everything to Gamers50:56 - AMD's True Market Share59:05 - The Key to RDNA 4's Success1:03:13 - Outro with Ed's Favorite Sapphire GenerationSUBSCRIBE 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.

AI isn't running out of GPUs… it's running out of power. Today on Dumb Money, the overlooked AI energy supplier that could be one of the most misunderstood stocks in the market.

Subscribe to the Blockspace newsletter for market-making news as it hits the wire! Welcome back to The Mining Pod! Today, Ethan Vera, COO of Luxor, joins us as we dive into MicroBT's Whatsminer M70 launching into a challenging ASIC market, IREN's $2.3 billion convertible note offering, the precarious state of hashprice, Luxor's new GPU hardware sales business, the staggering 270% leap in ERCOT interconnection requests, and the controversial Cat bitcoin fork proposal aimed at filtering ordinals / inscriptions. Subscribe to the newsletter! https://newsletter.blockspacemedia.com **Notes:** - Hash price is below $40 per second - Three negative difficulty adjustments - Ercot requests leaped 270% in 2025 - 73% of requests from data centers - IREN raised $2.3B in convertible notes - M70 efficiency: 12.5 J/TH 00:00 Start 02:35 Difficulty Report by Luxor 07:26 IREN note 10:44 M70 launch 20:02 Luxor launches GPU trading 27:12 ERCOT LL requests up 270% in 2025 34:10 Cry Corner: another filter fork proposal

AI demand for GPUs is exploding – and most of that capacity is locked inside underused data centers.In this episode, I talk with Mark from Aethir, a decentralized GPU cloud that aggregates idle, enterprise-grade GPUs into a global network. We discuss how Aethir feels like AWS on the front end but works like “Airbnb for data centers” behind the scenes, why compute demand outpaces supply, and how they keep latency low across 90+ countries.Mark also explains Aethir's token and revenue model, their work with EigenLayer, and why he believes solo founders now have superpowers in an AI-native world.Nothing in this episode is financial or investment advice.Key timestamps[00:00:00] Intro: Sam introduces Mark and Aethir's decentralized GPU cloud.[00:01:00] Mark's journey: From oil and gas infra and biotech to building GPU infrastructure for AI.[00:04:00] What Aethir is: AWS-style GPU cloud on the front end, “Airbnb for data centers” on the back end.[00:06:00] Enterprise-only GPUs: Why they only use data-center-grade hardware and no consumer devices.[00:07:00] Exploding demand: GPU demand 6–8x supply, with inference-heavy apps driving the next wave.[00:14:00] Global coverage: 90+ countries and routing users to nearby nodes for low latency.[00:31:00] Business model: 20% protocol fee, 80% to GPU hosts, plus token rewards and staking for large clusters.[00:39:00] Solo founder era: Why one-person AI-native companies will be extremely powerful.[00:41:00] Mark's message: Focus on projects with strong fundamentals and keep building through cycles.Connecthttp://aethir.com/https://www.linkedin.com/company/aethir-limited/https://x.com/AethirCloudhttps://www.linkedin.com/in/markrydon/https://x.com/MRRydonDisclaimerNothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Get featuredBe a guest on the podcast or contact us – https://www.web3pod.xyz/

In this panel session from the 2025 Data Center Frontier Trends Summit (Aug. 26-28) in Reston, Va., JLL's Sean Farney moderates a high-energy panel on how the industry is fast-tracking AI capacity in a world of power constraints, grid delays, and record-low vacancy. Under the banner “Scaling AI: The Role of Adaptive Reuse and Power-Rich Sites in GPU Deployment,” the discussion dives into why U.S. colocation vacancy is hovering near 2%, how power has become the ultimate limiter on AI revenue, and what it really takes to stand up GPU-heavy infrastructure at speed. Schneider Electric's Lovisa Tedestedt, Aligned Data Centers' Phill Lawson-Shanks, and Sapphire Gas Solutions' Scott Johns unpack the real-world strategies they're deploying today—from adaptive reuse of industrial sites and factory-built modular systems, to behind-the-fence natural gas, microgrids, and emerging hydrogen and RNG pathways. Along the way, they explore the coming “AI inference edge,” the rebirth of the enterprise data center, and how AI is already being used to optimize data center design and operations. During this talk, you'll learn: * Why record-low vacancy and long interconnection queues are reshaping AI deployment strategy. * How adaptive reuse of legacy industrial and commercial real estate can unlock gigawatt-scale capacity and community benefits. * The growing role of liquid cooling, modular skids, and grid-to-chip efficiency in getting more power to GPUs. * How behind-the-meter gas, virtual pipelines, and microgrids are bridging multi-year grid delays. * Why many experts expect a renaissance of enterprise data centers for AI inference at the edge. Moderator: Sean Farney, VP, Data Centers, Jones Lang LaSalle (JLL) Panelists: Tony Grayson, General Manager, Northstar Lovisa Tedestedt, Strategic Account Executive – Cloud & Service Providers, Schneider Electric Phill Lawson-Shanks, Chief Innovation Officer, Aligned Data Centers Scott Johns, Chief Commercial Officer, Sapphire Gas Solutions

My guest this week is Gavin Baker. Gavin is the managing partner and CIO of Atreides Management, and he has been on the show many times before.  I will never forget when I first met Gavin in 2017. I find his interest in markets, his curiosity about the world to be as infectious as any investor that I've ever come across. He's encyclopedic on what is going on in the world of technology today, and I've had the good fortune to host him every year or two on this podcast. Gavin began covering Nvidia as an investor more than two decades ago, giving him a rare perspective on how the company – and the entire semiconductor ecosystem – has evolved. A lot has changed since our last conversation a year ago, making this the perfect time to revisit the topic. In this conversation, we talk about everything that interests Gavin – Nvidia's GPUs, Google's TPUs, the changing AI landscape, the math and business models around AI companies and everything in between. We also discussed the idea of data centers in space, which he communicates with his usual passion and logic. In closing, at the end of this conversation, because I've asked him my traditional closing question before, I asked him a different question, which led to a discussion of his entire investing origin story that I had never heard before. Because Gavin is one of the most passionate thinkers and investors that I know, these conversations are always amongst my most favorite. I hope you enjoy this latest in the series of discussions with Gavin Baker. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠.⁠⁠⁠⁠⁠⁠⁠⁠ ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ramp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ramp's mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ramp.com/invest to sign up for free and get a $250 welcome bonus. ----- This episode is brought to you by⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Ridgeline⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Head to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgelineapps.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to learn more about the platform. ----- This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AlphaSense⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. AlphaSense has completely transformed the research process with cutting-edge AI technology and a vast collection of top-tier, reliable business content. Invest Like the Best listeners can get a free trial now at⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Alpha-Sense.com/Invest⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and experience firsthand how AlphaSense and Tegus help you make smarter decisions faster. ----- Editing and post-production work for this episode was provided by The Podcast Consultant (⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thepodcastconsultant.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠). Show Notes: (00:00:00) Welcome to Invest Like The Best (00:04:00) Meet Gavin Baker (00:06:00) Understanding Gemini 3  (00:09:05) Scaling Laws for Pre-Training (00:12:12) Google v. Nvidia (00:16:52) Google as  Lowest Cost Producer of Tokens (00:28:05)  AI Can Automate Anything that can be Verified (00:34:30) The AI Bear Case: Edge AI (00:37:18) Going from Intelligence to Usefulness (00:43:44) AI Adoption in Fortune 500 Companies (00:48:58) Frontier Models and Industry Dynamics (00:56:40) China's Mistake and Blackwell's Geopolitical Leverage (00:57:50) OpenAI's Code Red (01:00:46) Data Centers in Space (01:07:13) Cycles in AI (01:11:10) Power as a Bottleneck (01:14:17) AI Native Entrepreneurs (01:16:21) Semiconductor VC (01:20:41) The Mistake the SaaS Industry is Making (01:26:50) Series of Bubbles (01:28:56) Whatever AI Needs, It Gets (01:29:57) Investing is the Search for Truth (01:31:24) Gavin's Investing Origin Story

In this conversation, Rob Jones, Area Vice President of Sales at Chatsworth Products (CPI), discusses the critical need for advanced cooling solutions in data centers driven by the convergence of AI and high-performance computing (HPC). He highlights CPI's innovative liquid cooling technologies, which are essential for managing the increasing heat output from modern GPUs. The discussion also covers the types of organizations adopting CPI's solutions and how CPI is future-proofing infrastructure to accommodate evolving technology demands.Thank you to Chatsworth Products/CPI for their sponsorship of the podcast. Their expertise and support helps us to the keep the lights on here at the podcast. Please check out their selection of products on Graybar's website or reach out to your local Graybar representative to learn how CPI can help keep your data center efficient and cool.https://www.graybar.com/manufacturers/chatsworth/c/sup-chatsworth-group?utm_source=podcast&utm_medium=show-notes&utm_campaign=Sponsor-Highlight-2025-ChatsworthYouTube link: https://youtu.be/GDTl_Mux9SQ 

How can you scale AI at the enterprise, yet still hit your climate goals? And can heavy AI usage and an enterprise's ESG mission co-exist? Ashutosh Ahuja lays it out for us. Aligning AI With Climate And Business Goals -- An Everyday AI Chat with Jordan Wilson and Ashutosh AhujaNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion:Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:AI's Environmental Impact and Climate ConcernsCompanies Aligning AI with ESG GoalsAI Adoption Versus Carbon Footprint TradeoffsMetrics for Measuring AI's Environmental ImpactBusiness Efficiency Gains from AI AdoptionReal-World Examples: AI Offsetting Carbon FootprintIndustry Opportunities for Sustainable AI IntegrationFuture Trends: Efficient AI Models and Edge ComputingTimestamps:00:00 Everyday AI Podcast & Newsletter05:52 Balancing Progress and Legacy07:03 "Should Companies Limit AI Usage?"12:02 "Sentiment Analysis for Business Growth"17:07 "Energy Efficiency Impacts ESG Metrics"19:40 Robots, Energy, and AI Opportunity21:41 AI Efficiency and Climate Balance25:04 "Trust Instincts in Investments"Keywords:AI and climate, climate goals, aligning AI with ESG, environmental impact of AI, carbon footprint, energy use in AI data centers, water cooling for GPUs, sustainable business practices, enterprise AI strategy, ESG compliance, climate pledges, AI adoption in business, carbon footprint metrics, machine learning for sustainability, predictive analytics, ethical AI, green AI solutions, renewable energy sector, AI in waste management, camera vision for waste sorting, delivery robots, edge AI, small business AI implementation, AI efficiency, sentiment analysis, customer patterns, predictive maintenance, IoT data, auto scaling, cloud computing, resource optimization, SEC filings, brand sentiment tracking, LLM energy consumption, environmental considerations for AI, future of AI in climate action, business efficiency, human in the loop, philanthropic business practices, sustainable architecture, large language models and climate, tech industry climate initiatives, AI-powered resource savings, operational sustainability.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Ready for ROI on GenAI? Go to youreverydayai.com/partner 

This Week In Startups is made possible by:Northwest Registered Agent - https://www.northwestregisteredagent.com/twistCrusoe - http://crusoe.ai/buildGusto - https://www.gusto.com/twistToday's show: Delegating is its own unique skill, requiring training and a real investment of time and attention.On TWiST, Jason chats for a full hour with the founder of one of his favorite startups, Athena, which trains online assistants and pairs them with busy founders and executives. (Jason has 2!) But getting the MOST out of your executive assistants is less obvious than it looks. Jonathan unpacks some of the secrets to “Black Diamond Delegating,” and how he manages to keep 6 different high-level helpers operating at once.Plus, Jason and Jonathan look back at the Open Angel Forum days, where Jason invested in Jonathan's previous company, Thumbtack, praise the “Checklist Manifesto,” discuss the telltale signs you've achieved market pull, and lots more insights.Timestamps:(01:53) We're joined by Jonathan Swanson from one of JCal's fav startups, Athena!(02:02) Jason and Jonathan first met during the Open Angel Forum, when Jonathan was working on Thumbtack(06:44) Finding the “little touches” that can help make an app more delightful(9:47) Northwest Registered Agent - Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit https://www.northwestregisteredagent.com/twist today!(12:05) The shift from Thumbtack to Athena was all about time(12:52) How Jonathan delegates to 6 exec assistants at once(14:22) Pricing Athena's EAs: Jason runs the numbers(15:09) Why Athena made Jason believe in hiring assistants again(18:15) Getting past the “Cardinal Sins of Delegation”(19:38) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(20:48) Will AI ever be able to replace Athena assistants?(23:41) Inside how Athena finds and trains assistants from around the world(27:01) How JCal became an Athena Ambassador… and almost crashed the system!(30:55) Gusto - Check out the online payroll and benefits experts with software built specifically for small business and startups. Try Gusto today and get three months FREE at https://www.gusto.com/twist(32:11) The magic of having assistants work on “backstop projects” and creative tasks(37:14) How to know when you have achieved market pull(40:05) Why getting the most out of delegating takes real investment and training(44:36) More praise for the Checklist Manifesto(46:26) Jonathan gives us a peek at what “Black Diamond Delegation” looks like(52:14) Jason's early experiences hiring overseas assistants, from the Mahalo days*Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcp*Follow Lon:X: https://x.com/lons*Follow Alex:X: https://x.com/alexLinkedIn: https://www.linkedin.com/in/alexwilhelm/*Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanis/*Thank you to our partners:(9:47) Northwest Registered Agent - Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit https://www.northwestregisteredagent.com/twist today!(19:38) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(30:55) Gusto - Check out the online payroll and benefits experts with software built specifically for small business and startups. Try Gusto today and get three months FREE at https://www.gusto.com/twist

CoreWeave CFO Nitin Agrawal joins Run the Numbers to unpack the finance engine behind one of the fastest-growing AI infrastructure companies on the planet. CJ and Nitin dive into what it takes to build financial discipline in an environment where business models are being invented in real time, discussing the company's 700% growth last year and massive first-quarter performance as a newly public company. They cover capex strategy, securitizing GPUs, managing billion-dollar revenue backlogs, and structuring incentives for hyperscale deals, all while keeping investors grounded and servers running at full tilt. If you want a front-row seat to finance in the AI arms race, this episode delivers.—SPONSORS:Tipalti automates the entire payables process—from onboarding suppliers to executing global payouts—helping finance teams save time, eliminate costly errors, and scale confidently across 200+ countries and 120 currencies. More than 5,000 businesses already trust Tipalti to manage payments with built-in security and tax compliance. Visit https://www.tipalti.com/runthenumbers to learn more.Aleph automates 90% of manual, error-prone busywork, so you can focus on the strategic work you were hired to do. Minimize busywork and maximize impact with the power of a web app, the flexibility of spreadsheets, and the magic of AI. Get a personalised demo at https://www.getaleph.com/runFidelity Private Shares is the all-in-one equity management platform that keeps your cap table clean, your data room organized, and your equity story clear—so you never risk losing a fundraising round over messy records. Schedule a demo at https://www.fidelityprivateshares.com and mention Mostly Metrics to get 20% off.Sage Intacct is the cloud financial management platform that replaces spreadsheets, eliminates manual work, and keeps your books audit-ready—so you can scale without slowing down. It combines accounting, ERP, and real-time reporting for retail, financial services, logistics, tech, professional services, and more. Sage Intacct delivers fast ROI, with payback in under six months and up to 250% return. Rated #1 in customer satisfaction for eight straight years. Visit Sage Intacct and take control of your growth: https://bit.ly/3Kn4YHtMercury is business banking built for builders, giving founders and finance pros a financial stack that actually works together. From sending wires to tracking balances and approving payments, Mercury makes it simple to scale without friction. Join the 200,000+ entrepreneurs who trust Mercury and apply online in minutes at https://www.mercury.comRightRev automates the revenue recognition process from end to end, gives you real-time insights, and ensures ASC 606 / IFRS 15 compliance—all while closing books faster. For RevRec that auditors actually trust, visit https://www.rightrev.com and schedule a demo.—LINKS:Nitin on LinkedIn: https://www.linkedin.com/in/nitin-agrawal-cloudcfo/Company: https://www.coreweave.com/CJ on LinkedIn: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:The Art and Science of a Day-One IPO Pop with OneStream Software CFO Bill Koefoedhttps://youtu.be/kYCn7XNkCBcFrom Facebook's Hypergrowth to Daffy's Disruption: A CFO's Playbook for Saying Yeshttps://youtu.be/bRIZ6oNPGD0—TIMESTAMPS:00:00:00 Preview and Intro00:02:54 Sponsors – Tipalti | Aleph | Fidelity Private Shares00:06:12 Interview Begins: Scaling CoreWeave00:06:52 CoreWeave's Pivot From Crypto to AI00:11:41 Why CoreWeave Is Uniquely Positioned to Lead AI Infrastructure00:13:32 Hiring for Both Scrappiness and Scale00:16:01 Post-IPO Whirlwind: Acquisitions, Debt Raises, and 10-Year Deals00:16:43 Sponsors – Sage Intacct | Mercury | RightRev00:20:13 Managing Investor Expectations With Radical Transparency00:22:39 Doubling Active Power in Six Months00:25:19 Risk-Balanced Capital Deployment: Power First, GPUs Second00:27:12 Financing GPUs With Delayed-Draw Facilities00:29:38 CoreWeave Rated Platinum for GPU Cluster Performance00:32:25 Compute as the Bottleneck for AI Growth00:33:47 Explaining Revenue Backlog Shape & Timing00:35:06 The Strength of Reserved Instance Contracts00:36:07 Giving Tight but Honest Guidance00:40:26 How Mega-Deals Require C-Suite Participation00:42:19 Tackling Revenue Concentration Through Diversification00:44:05 Building an AI-Only Cloud, Not a General-Purpose Cloud00:46:27 Capital Markets Muscle: Raising Billions at Speed00:47:47 Accounting Complexity in a Business With No Precedent00:49:33 Even the CFO Must Unlearn Old Cloud Assumptions00:51:29 Scaling Public-Company Processes in 90-Day Cycles00:54:42 The Couch Fire vs. House Fire Framework00:57:17 Balancing Risk Mitigation With Opportunity Seeking01:00:30 No Downtime for ERP Changes During Hypergrowth01:02:33 Why the Team Stays Energized Despite the Chaos#RunTheNumbersPodcast #CFOInsights #Hypergrowth #AIInfrastructure #FinanceStrategy This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cjgustafson.substack.com

In this episode, Zain Asgar, co-founder and CEO of Gimlet Labs, joins us to discuss the heterogeneous AI inference across diverse hardware. Zain argues that the current industry standard of running all AI workloads on high-end GPUs is unsustainable for agents, which consume significantly more tokens than traditional LLM applications. We explore Gimlet's approach to heterogeneous inference, which involves disaggregating workloads across a mix of hardware—from H100s to older GPUs and CPUs—to optimize unit economics without sacrificing performance. We dive into their "three-layer cake" architecture: workload disaggregation, a compilation layer that maps models to specific hardware targets, and a novel system that uses LLMs to autonomously rewrite and optimize compute kernels. Finally, we discuss the complexities of networking in heterogeneous environments, the trade-offs between numerical precision and application accuracy, and the future of hardware-aware scheduling. The complete show notes for this episode can be found at https://twimlai.com/go/757.

Ranjan Roy from Margins is back for our weekly discussion of the latest tech news. We cover: 1) Black Friday secrets 2) Google may sell its TPUs to Meta and financial institutions 3) Nvidia sends an antsy tweet 4) How does Google's TPU stack up next to NVIDIA's GPUs 5) Could Google package the TPU with cloud services? 6) NVIDIA responds to the criticism 7) HSBC on how much OpenAI needs to earn to cover its investments 8) Thinking about OpenAI's advertising business 9) ChatGPT users lose touch with reality 10) Ilya Sustkever's mysterious product and revenue plans 11) X reveals our locations --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Questions? Feedback? Write to: bigtechnologypodcast@gmail.com Learn more about your ad choices. Visit megaphone.fm/adchoices

Register here to join Founder University Japan's kickoff: https://luma.com/cm0x90mkToday's show:Google and Meta had their cases dismissed (or received a slap on the wrist)… Despite all the backlash and cynicism, AI companies continue making bank and releasing hot new products… What does it all mean?For Jason Calacanis, the signs are pointing to a “major M&A moment,” with huge opportunities for increased efficiency and consolidation among America's favorite brands and largest companies?Who will it be? Join Jason and Alex for a round of hot speculation.PLUS why Jason thinks Michael Burry is both right and wrong about GPU depreciation, why NOTHING is certain about these OpenAI mega-deals, Google's Nano Banana Pro can make infographics and they're VERY impressive… and much more.Timestamps:(1:54) Jason's calling in from Vegas… He's doing a hot lap at F1!(3:18) How restaurants are becoming the new Hot IP(6:50) Founder University is heading to TOKYO!(9:27) Why Jason thinks the future of startups is truly global(10:06) Pipedrive - Bring your entire sales process into one elegant space. Get started with a 30 day free trial at pipedrive.com/twist(11:39) Nvidia killed it on the numbers… but what are the vibes around AI? Jason sounds off.(13:05) Why nothing is certain when it comes to the Nvidia/OpenAI deal(19:40) Is Google now WINNING consumer adoption of AI? How did it get this close?(19:57) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(26:07) Meanwhile, AI apps are still dominating the iOS Store(27:09) Why Jason and Alex think Michael Burry's both right and wrong about GPU depreciation(30:13) Northwest Registered Agent - Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit https://www.northwestregisteredagent.com/twist today!(37:46) We're testing out Nano Banana Pro on a BBQ infographic challenge(43:42) What a week for AI models! It doesn't seem like things are slowing down…(46:12) Kalshi is growing fast, but can it catch Polymarket?(47:50) Is a rate cut coming? Jason and Alex read the tea leaves.(50:13) Why Jason predicts a “major M&A moment” in the next six months(52:09) VIEWER QUESTION: What should a software engineer be working on RIGHT NOW.(54:02) Founder Friday is now… STARTUP SUPPER CLUBSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(10:06) Pipedrive - Bring your entire sales process into one elegant space. Get started with a 30 day free trial at pipedrive.com/twist(19:57) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/build to reserve your capacity for the latest GPUs today.(30:13) Northwest Registered Agent - Form your entire business identity in just 10 clicks and 10 minutes. Get more privacy, more options, and more done—visit https://www.northwestregisteredagent.com/twist today!Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.com