Podcasts about gpus

This Week In Startups is made possible by:Northwest Registered Agent - www.northwestregisteredagent.com/twistCrusoe Cloud - https://crusoe.ai/savingsLinkedIn Jobs - http://linkedIn.com/twistToday's show: On today's TWIST episode, Alex interviews two of the top startup co-founders: Keller Cliffton of Zipline and Anastasis Germanidis of Runway. Zipline announced its $600 million raise at a $7.6 BILLION valuation. Kellers breaks down the origins, economics, and future of Zipline's contrarian bet in drone delivery. What was science fiction a decade ago is now a regular part of life for many. In fact, Zipline operates more flights than United!Zipline is set to leapfrog the car delivery apps AND self driving cars with the superior economics of drone delivery. It is much cheaper to transport your burrito in a lightweight drone than a 6,000 pound self driving car!Then, Alex is joined by Anastasis Germanidis, the CTO and co-founder of Runway, to explain why the next frontier of generative AI is world models! Runway  is looking to build a universal simulation, which will unlock massive gains in robotics, autonomy, and simulations. The world model would be able to simulate rare edge cases that could take years to find naturally! Check out how this cutting edge AI startup's NYU Tisch School of Art's originsThen, See Jason's answer to the question: “When should founders pivot or give up?”Timestamps: (00:00) The Drone revolution is here!(02:46) Inside Zipline's factory to build 20K drones a year(04:40) American dynamism Vs. Chinese manufacturing dominance(09:00) How Zipline is growing 75% month on month(9:50) Northwest Registered Agent. Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity —  Learn more at www.northwestregisteredagent.com/twist(11:15) Zipline teleports food and goods to your house(21:54) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/savings to reserve your capacity for the latest GPUs today.(23:02) Is it affordable to use a drone to deliver a burrito?(29:18) Zipline DOUBLES United's flight numbers(31:11) LinkedIn Jobs - post your job for free at http://linkedIn.com/twist then promote it to get access to LinkedIn Jobs new AI assistant.(32:21) Anastasis break's down Runway's AI modeling(35:24) Runway's Gen 4.5 and the world model(40:57) Why do robotics companies need a world model?(43:04) Using AI to simulate robot laundry folding(52:37) Runway's origins at NYU's art school(55:46) Founder Q/A: When to pivot or give up on your startup*Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com/Check out the TWIST500: https://twist500.com)Subscribe 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:(9:50) Northwest Registered Agent. Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity —  Learn more at www.northwestregisteredagent.com/twist(21:54) Crusoe Cloud: Crusoe is the AI factory company. Reliable infrastructure and expert support. Visit https://crusoe.ai/savings to reserve your capacity for the latest GPUs today.(31:11) LinkedIn Jobs - post your job for free at http://linkedIn.com/twist then promote it to get access to LinkedIn Jobs new AI assistant.Check out all our partner offers: https://partners.launch.co/

In this episode of the Crazy Wisdom podcast, host Stewart Alsop sits down with Kelvin Lwin for their second conversation exploring the fascinating intersection of AI and Buddhist cosmology. Lwin brings his unique perspective as both a technologist with deep Silicon Valley experience and a serious meditation practitioner who's spent decades studying Buddhist philosophy. Together, they examine how AI development fits into ancient spiritual prophecies, discuss the dangerous allure of LLMs as potentially "asura weapons" that can mislead users, and explore verification methods for enlightenment claims in our modern digital age. The conversation ranges from technical discussions about the need for better AI compilers and world models to profound questions about humanity's role in what Lwin sees as an inevitable technological crucible that will determine our collective spiritual evolution. For more information about Kelvin's work on attention training and AI, visit his website at alin.ai. You can also join Kelvin for live meditation sessions twice daily on Clubhouse at clubhouse.com/house/neowise.Timestamps00:00 Exploring AI and Spirituality05:56 The Quest for Enlightenment Verification11:58 AI's Impact on Spirituality and Reality17:51 The 500-Year Prophecy of Buddhism23:36 The Future of AI and Business Innovation32:15 Exploring Language and Communication34:54 Programming Languages and Human Interaction36:23 AI and the Crucible of Change39:20 World Models and Physical AI41:27 The Role of Ontologies in AI44:25 The Asura and Deva: A Battle for Supremacy48:15 The Future of Humanity and AI51:08 Persuasion and the Power of LLMs55:29 Navigating the New Age of TechnologyKey Insights1. The Rarity of Polymath AI-Spirituality Perspectives: Kelvin argues that very few people are approaching AI through spiritual frameworks because it requires being a polymath with deep knowledge across multiple domains. Most people specialize in one field, and combining AI expertise with Buddhist cosmology requires significant time, resources, and academic background that few possess.2. Traditional Enlightenment Verification vs. Modern Claims: There are established methods for verifying enlightenment claims in Buddhist traditions, including adherence to the five precepts and overcoming hell rebirth through karmic resolution. Many modern Western practitioners claiming enlightenment fail these traditional tests, often changing the criteria when they can't meet the original requirements.3. The 500-Year Buddhist Prophecy and Current Timing: We are approximately 60 years into a prophesied 500-year period where enlightenment becomes possible again. This "startup phase of Buddhism revival" coincides with technological developments like the internet and AI, which are seen as integral to this spiritual renaissance rather than obstacles to it.4. LLMs as UI Solution, Not Reasoning Engine: While LLMs have solved the user interface problem of capturing human intent, they fundamentally cannot reason or make decisions due to their token-based architecture. The technology works well enough to create illusion of capability, leading people down an asymptotic path away from true solutions.5. The Need for New Programming Paradigms: Current AI development caters too much to human cognitive limitations through familiar programming structures. True advancement requires moving beyond human-readable code toward agent-generated languages that prioritize efficiency over human comprehension, similar to how compilers already translate high-level code.6. AI as Asura Weapon in Spiritual Warfare: From Buddhist cosmological perspective, AI represents an asura (demon-realm) tool that appears helpful but is fundamentally wasteful and disruptive to human consciousness. Humanity exists as the battleground between divine and demonic forces, with AI serving as a weapon that both sides employ in this cosmic conflict.7. 2029 as Critical Convergence Point: Multiple technological and spiritual trends point toward 2029 as when various systems will reach breaking points, forcing humanity to either transcend current limitations or be consumed by them. This timing aligns with both technological development curves and spiritual prophecies about transformation periods.

What happens when the AI race stops being about size and starts being about sense? In this episode of Tech Talks Daily, I sit down with Wade Myers from MythWorx, a company operating quietly while questioning some of the loudest assumptions in artificial intelligence right now. We recorded this conversation during the noise of CES week, when headlines were full of bigger models, more parameters, and ever-growing GPU demand. But instead of chasing scale, this discussion goes in the opposite direction and asks whether brute force intelligence is already running out of road. Wade brings a perspective shaped by years as both a founder and investor, and he explains why today's large language models are starting to collide with real-world limits around power, cost, latency, and sustainability. We talk openly about the hidden tax of GPUs, how adding more compute often feels like piling complexity onto already fragile systems, and why that approach looks increasingly shaky for enterprises dealing with technical debt, energy constraints, and long deployment cycles. What makes this conversation especially interesting is MythWorx's belief that the next phase of AI will look less like prediction engines and more like reasoning systems. Wade walks through how their architecture is modeled closer to human learning, where intelligence is learned once and applied many times, rather than dragging around the full weight of the internet to answer every question. We explore why deterministic answers, audit trails, and explainability matter far more in areas like finance, law, medicine, and defense than clever-sounding responses. There is also a grounded enterprise angle here. We talk about why so many organizations feel uneasy about sending proprietary data into public AI clouds, how private AI deployments are becoming a board-level concern, and why most companies cannot justify building GPU-heavy data centers just to experiment. Wade draws parallels to the early internet and smartphone app eras, reminding us that the playful phase often comes before the practical one, and that disappointment is often a signal of maturation, not failure. We finish by looking ahead. Edge AI, small-footprint models, and architectures that reward efficiency over excess are all on the horizon, and Wade shares what MythWorx is building next, from faster model training to offline AI that can run on devices without constant connectivity. It is a conversation about restraint, reasoning, and realism at a time when hype often crowds out reflection. So if bigger models are no longer the finish line, what should business and technology leaders actually be paying attention to next, and are we ready to rethink what intelligence really means? Useful Links Connect with Wade Myers Learn More About MythWorx Thanks to our sponsors, Alcor, for supporting the show.

Every episode this year just keeps getting better, try it, you'll see.  This food podcast brought to by the tech news!  Also, 9850X3D this month, welcome back 8GB GPUs, and 2026 will be tough for PC hardware enthusiats. Oh, that Micron shut down is really a good thing, trust them.  Enjoy Linux malware, CoPilot exploits, and even a StarCraft based shooter on the way plus so much more!  Seriously, look at the timestamps below.We thank our two sponsors this week:Notion Agent - Bringing all your notes, docs, and projects into one connected space that just works!Zapier - Where tech innovators break the hype cycle and put AI into their workflows - orchestrate it with Zapier!Timestamps0:00 Intro01:54 Patreon03:20 Food with Josh05:17 AMD reportedly launching the 9850X3D this month06:07 NVIDIA to increase 8GB GPU production?08:05 NVIDIA SUPER refresh delay09:32 Micron defends shutting down Crucial12:51 Zoicware is the one true way16:32 SK hynix to build new memory plant17:50 2026 is not going to be a great year for PC builders20:29 Podcast sponsor - Notion21:54 PSUs and CPU coolers are the next to go up in price28:29 Apple's Google Gemini deal31:02 Intel Nova Lake graphics33:06 (In)Security Corner38:37 Podcast sponsor - Zapier40:06 (In)Security Corner, continued46:46 We are not normal57:33 Gaming Quick Hits1:07:38 Picks of the Week1:17:52 Outro ★ Support this podcast on Patreon ★

Timestamps: 0:00 it's a SETUP! 0:12 Nvidia H200 sales approved; China says no 1:45 Microsoft makes datacenters less-bad 3:17 Nvidia possibly making more 8GB GPUs 5:21 QUICK BITS INTRO 5:31 Meta metaverse layoffs 6:08 Bandcamp bans AI 6:51 GOG on taking on Steam 7:39 Flock data breach 8:25 Moon hotel reservations NEWS SOURCES: https://lmg.gg/LAH0B Learn more about your ad choices. Visit megaphone.fm/adchoices

Nintendo stock dropped 33% as investors are nervous about Nintendo's lack of new games in the pipeline, tariffs, and the cost of RAM and GPUs. Could a massive price hike be coming soon? And why did sales of Switch 2 cool off so quickly after an impressive launch? Is this one of Nintendo's few misfires, or will the console rebound once there are games that take full advantage of its hardware specs?Watch the podcast episodes on YouTube and all major podcast hosts including Spotify.CLOWNFISH TV is an independent, opinionated news and commentary podcast that covers Entertainment and Tech from a consumer's point of view. We talk about Gaming, Comics, Anime, TV, Movies, Animation and more. Hosted by Kneon and Geeky Sparkles.Get more news, views and reviews on Clownfish TV News - https://more.clownfishtv.com/On YouTube - https://www.youtube.com/c/ClownfishTVOn Spotify - https://open.spotify.com/show/4Tu83D1NcCmh7K1zHIedvgOn Apple Podcasts - https://podcasts.apple.com/us/podcast/clownfish-tv-audio-edition/id1726838629

In episode 555 of 'Coffee with Butterscotch,' the brothers unpack what the How Many Dudes demo is teaching them about speed, feedback, and player expectations. They talk about influencer momentum, the challenges of balancing once players latch onto specific builds, and why moving fast matters more than ever. The episode closes with 2026 predictions, touching on AI, platform shifts, and why focused indie teams may thrive in the noise.Support How Many Dudes!Official Website: https://www.bscotch.net/games/how-many-dudesTrailer Teaser: https://www.youtube.com/watch?v=IgQM1SceEpISteam Wishlist: https://store.steampowered.com/app/3934270/How_Many_Dudes00:00 Cold Open00:35 Introduction and Welcome10:49 The Success of How Many Dudes Demo24:45 Marketing Strategies and Community Engagement25:42 Demo Development and Market Positioning29:00 Localization and International Reach31:52 Balancing Game Mechanics and Player Expectations40:19 Feedback and Iteration in Game Development45:15 Predictions for the Future of Gaming50:46 The Hardware Crisis: RAM and GPUs in the AI Era53:35 AI's Limitations: The Reality of Digital Assistants56:21 The Rise of Indie Games Amidst AI Slop01:00:29 The Search for Authenticity in Gaming Experiences01:07:51 The Future of Game Distribution: Predictions for Major PlatformsTo stay up to date with all of our buttery goodness subscribe to the podcast on Apple podcasts (apple.co/1LxNEnk) or wherever you get your audio goodness. If you want to get more involved in the Butterscotch community, hop into our DISCORD server at discord.gg/bscotch and say hello! Submit questions at https://www.bscotch.net/podcast, disclose all of your secrets to podcast@bscotch.net, and send letters, gifts, and tasty treats to https://bit.ly/bscotchmailbox. Finally, if you'd like to support the show and buy some coffee FOR Butterscotch, head over to https://moneygrab.bscotch.net. ★ Support this podcast ★

GPUs and TPUs will be the semiconductor story moving forward, says Investopedia's Caleb Silver, pointing to Mag 7 giants Nvidia (NVDA) and Alphabet (GOOGL) being at the center of it. He expects Google's TPUs stay largely centralized for Gemini but sees potential for expansion, especially for Big Tech peers like Apple (AAPL). ======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

One PC store in Japan is literally begging for users to sell them their old gaming PCs because RAM and GPUs are so hard to come by and expensive. Is old tech the new normal going forward?Watch the podcast episodes on YouTube and all major podcast hosts including Spotify.CLOWNFISH TV is an independent, opinionated news and commentary podcast that covers Entertainment and Tech from a consumer's point of view. We talk about Gaming, Comics, Anime, TV, Movies, Animation and more. Hosted by Kneon and Geeky Sparkles.Get more news, views and reviews on Clownfish TV News - https://more.clownfishtv.com/On YouTube - https://www.youtube.com/c/ClownfishTVOn Spotify - https://open.spotify.com/show/4Tu83D1NcCmh7K1zHIedvgOn Apple Podcasts - https://podcasts.apple.com/us/podcast/clownfish-tv-audio-edition/id1726838629

Send us a textWe're back! After taking a month-long break to recharge and deal with the holidays, the crew returns to break down a few topics that matter in the gaming world.In Episode 207, we recap 2025, talk about what we're looking forward to in 2026, discuss the rising prices of PC RAM and GPUs and how it impacts PC gaming, and cover GameStop closing even more stores. Plus, we hit a few other topics too… because of course we still manage to go off the rails.But hey, that's why you love us.So yeah… welcome back!Episode 207 Timestamps00:00 – Intro 10:37 – What We Have Been Playing 17:47 – 2025 Recap 52:58 – Wishes and Plans for 2026 1:09:22 – PC Gaming just got even more expensive1:28:29 – GameStop Closing More Stores 1:37:00 – Outro#GamingPodcast #VideoGames #GamingNews #gameindustry Make sure to listen, drop a comment, and share the episode if you enjoyed it. And we want to hear from you: what topics do you want us to cover in the next episode?Support the showYou can find the Spectator Mode podcast on the following podcast platforms. Please consider leaving a review on Apple Podcast, as it will go a long watch in more people discovering us. Thank you! Apple Podcasts YouTube Spotify Amazon Music

In this episode of the Crazy Wisdom podcast, host Stewart Alsop sits down with Peter Schmidt Nielsen, who is building FPGA-accelerated servers at Saturn Data. The conversation explores why servers need FPGAs, how these field-programmable gate arrays work as "IO expanders" for massive memory bandwidth, and why they're particularly well-suited for vector database and search applications. Peter breaks down the technical realities of FPGAs - including why they "really suck" in many ways compared to GPUs and CPUs - while explaining how his company is leveraging them to provide terabyte-per-second bandwidth to 1.3 petabytes of flash storage. The discussion ranges from distributed systems challenges and the CAP theorem to the hardware-software relationship in modern computing, offering insights into both the philosophical aspects of search technology and the nuts-and-bolts engineering of memory controllers and routing fabrics.For more information about Peter's work, you can reach him on Twitter at @PTRSCHMDTNLSN or find his website at saturndata.com.Timestamps00:00 Introduction to FPGAs and Their Role in Servers02:47 Understanding FPGA Limitations and Use Cases05:55 Exploring Different Types of Servers08:47 The Importance of Memory and Bandwidth11:52 Philosophical Insights on Search and Access Patterns14:50 The Relationship Between Hardware and Search Queries17:45 Challenges of Distributed Systems20:47 The CAP Theorem and Its Implications23:52 The Evolution of Technology and Knowledge Management26:59 FPGAs as IO Expanders29:35 The Trade-offs of FPGAs vs. ASICs and GPUs32:55 The Future of AI Applications with FPGAs35:51 Exciting Developments in Hardware and BusinessKey Insights1. FPGAs are fundamentally "crappy ASICs" with serious limitations - Despite being programmable hardware, FPGAs perform far worse than general-purpose alternatives in most cases. A $100,000 high-end FPGA might only match the memory bandwidth of a $600 gaming GPU. They're only valuable for specific niches like ultra-low latency applications or scenarios requiring massive parallel I/O operations, making them unsuitable for most computational workloads where CPUs and GPUs excel.2. The real value of FPGAs lies in I/O expansion, not computation - Rather than using FPGAs for their processing power, Saturn Data leverages them primarily as cost-effective ways to access massive amounts of DRAM controllers and NVMe interfaces. Their server design puts 200 FPGAs in a 2U enclosure with 1.3 petabytes of flash storage and terabyte-per-second read bandwidth, essentially using FPGAs as sophisticated I/O expanders.3. Access patterns determine hardware performance more than raw specs - The way applications access data fundamentally determines whether specialized hardware will provide benefits. Applications that do sparse reads across massive datasets (like vector databases) benefit from Saturn Data's architecture, while those requiring dense computation or frequent inter-node communication are better served by traditional hardware. Understanding these patterns is crucial for matching workloads to appropriate hardware.4. Distributed systems complexity stems from failure tolerance requirements - The difficulty of distributed systems isn't inherent but depends on what failures you need to tolerate. Simple approaches that restart on any failure are easy but unreliable, while Byzantine fault tolerance (like Bitcoin) is extremely complex. Most practical systems, including banks, find middle ground by accepting occasional unavailability rather than trying to achieve perfect consistency, availability, and partition tolerance simultaneously.5. Hardware specialization follows predictable cycles of generalization and re-specialization - Computing hardware consistently follows "Makimoto's Wave" - specialized hardware becomes more general over time, then gets leapfrogged by new specialized solutions. CPUs became general-purpose, GPUs evolved from fixed graphics pipelines to programmable compute, and now companies like Etched are creating transformer-specific ASICs. This cycle repeats as each generation adds programmability until someone strips it away for performance gains.6. Memory bottlenecks are reshaping the hardware landscape - The AI boom has created severe memory shortages, doubling costs for DRAM components overnight. This affects not just GPU availability but creates opportunities for alternative architectures. When everyone faces higher memory costs, the relative premium for specialized solutions like FPGA-based systems becomes more attractive, potentially shifting the competitive landscape for memory-intensive applications.7. Search applications represent ideal FPGA use cases due to their sparse access patterns - Vector databases and search workloads are particularly well-suited to FPGA acceleration because they involve searching through massive datasets with sparse access patterns rather than dense computation. These applications can effectively utilize the high bandwidth to flash storage and parallel I/O capabilities that FPGAs provide, making them natural early adopters for this type of specialized hardware architecture.

Moiz Kohari, VP of Enterprise AI and Data Intelligence at DDN, breaks down what it actually takes to get AI into production and keep it there. If your org is stuck in pilot mode, this conversation will help you spot the real blockers, from trust and hallucinations to data architecture and GPU bottlenecks.Key takeaways• GenAI success in the enterprise is less about the demo and more about trust, accuracy, and knowing when the system should say “I don't know.”• “Operationalizing” usually fails at the handoff, when humans stay permanently in the loop and the business never captures the full benefit.• Data architecture is the multiplier. If your data is siloed, slow, or hard to access safely, your AI roadmap stalls, no matter how good your models are.• GPU spend is only worth it if your pipelines can feed the GPUs fast enough. A lot of teams are IO bound, so utilization stays low and budgets get burned.• The real win is better decisions, faster. Moving from end of day batch thinking to intraday intelligence can change risk, margin, and response time in major ways.Timestamped highlights00:35 What DDN does, and why data velocity matters when GPUs are the pricey line item02:12 AI vs GenAI in the enterprise, and why “taking the human out” is where value shows up08:43 Hallucinations, trust, and why “always answering” creates real production risk12:00 What teams do with the speed gains, and why faster delivery shifts you toward harder problems12:58 From hours to minutes, how GPU acceleration changes intraday risk and decision making in finance20:16 Data architecture choices, POSIX vs object storage, and why your IO layer can make or break AI readinessA line worth stealing“Speed is great, but trust is the frontier. If your system can't admit what it doesn't know, production is where the project stops.”Pro tips you can apply this week• Pick one workflow where the output can be checked quickly, then design the path from pilot to production up front, including who approves what and how exceptions get handled.• Audit your bottleneck before you buy more compute. If your GPUs are waiting on data, fix storage, networking, and pipeline throughput first.• Build “confidence behavior” into the system. Decide when it should answer, when it should cite, and when it should escalate to a human.Call to actionIf you got value from this one, follow the show and turn on notifications so you do not miss the next episode.

This week on Autonomy Markets, Grayson Brulte and Walter Piecyk discuss CES 2026, Zoox's performance on the Las Vegas Strip and Uber's potential long-term autonomy plans. Zoox's performance was one of those hopefully “only in Las Vegas” moments, as the vehicle was seen stopping in the middle of traffic and blocking entrances on a regular basis. Which raises the question; what is Amazon going to do with Zoox? Do they overhaul management, make an acquisition, or simply shut it down and move on? While Zoox struggled, NVIDIA introduced their open-source Alpamayo AI models under an Apache 2.0 license to accelerate the development of autonomous vehicles and sell more GPUs. Closing out the show, the discussion shifts to hardware and global expansion, contrasting Waymo's bulky new Ojai vehicle with the well-designed Lucid-Nuro robotaxi.Episode Chapters0:00 CES 20262:13 Zoox CES Experience 8:41 NVIDIA's CES Announcements 12:45 SAE Level 216:59 Waymo Ojai19:31 Lucid / Nuro Robotaxi21:29 Does Uber Need to Vertically Integrate Autonomy in the Future?25:05 Waymo / Uber Relationship27:37 Tensor Auto 32:49 Foreign Autonomy Desk34:35 Disgrace of The Week38:24 Next WeekRecorded on Friday, January 9, 2026--------About The Road to AutonomyThe Road to Autonomy provides market intelligence and strategic advisory services to institutional investors and companies, delivering insights needed to stay ahead of emerging trends in the autonomy economy™. To learn more, say hello (at) roadtoautonomy.com.Sign up for This Week in The Autonomy Economy newsletter: https://www.roadtoautonomy.com/ae/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Cloud RTX on Tux | Linux Out Loud 119 digs into NVIDIA's new native GeForce NOW client for Linux and Fire TV, and what cloud gaming means for folks with aging GPUs, handhelds, and serious subscription fatigue. ​ Bill and Wendy also chat staycation gaming, NAS and home-lab cleanup, Ubiquiti and travel routers, the DaVinci Speed Editor, and the tragic tale of tea spilled directly onto a Steam Deck. Show Links: Main topic – GeForce NOW on Linux and Fire TV: * NVIDIA GeForce NOW CES 2026 announcement (Linux + Fire TV): https://blogs.nvidia.com/blog/geforce-now-ces-2026/ Gaming & distros mentioned: * Bazzite (Fedora-based gaming OS): https://bazzite.gg Home lab / networking / travel: * Synology DiskStation DS1825+ (Bill's NAS): https://nascompares.com/2025/05/07/synology-ds1825-nas-released-in-the-east/ * UniFi Travel Router (UTR): https://store.ui.com/us/en/category/wifi-special-devices/products/utr Special Guest: Bill.

What if we told you that CES did not feature any new GPUs?  But it did feature more frames!  MSI with LIGHTNING and GPU safeguard, Phison's new controller, and that wily AMD with new Ryzen 7 9850X3D (and confirmed Ryzen 9 9950X3D2) - whee!  Remember the Reboot computer generated cartoon?  Remember D-Link Routers and Zero Days?  Remember Intel?  It's all here! That and everything old is new again with Old GPUs and CPUs coming back .. because RAM.Thanks again to our sponsor with CopilotMoney!  Get on your single pane of financial glass and bring order to your money and spending - it's even actually fun to save again.  Get the web version and use our code for 26% off at http://try.copilot.money/pcperTimestamps:0:00 Intro00:56 Patreon01:37 Food with Josh04:10 AMD announces Ryzen 7 9850X3D05:41 AMD sort of confirmed the 9950X3D207:00 NVIDIA DLSS 4.509:34 Intel was at CES12:50 MSI LIGHTNING returns14:54 MSI also launching GPU Safeguard Plus PSUs19:44 WD_Black is now Sandisk Optimus GX Pro21:54 Phison has the most efficient SSD controller26:11 ASUS ROG RGB Stripe OLED28:44 First computer-animated TV show restored33:29 Podcast sponsor - Copilot Money34:57 (In)Security Corner44:32 Gaming Quick Hits1:06:31 Picks of the Week1:24:08 Outro ★ Support this podcast on Patreon ★

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.

In this episode, we discuss recent developments at Groq, including Nvidia's acquisition of certain Groq assets, and consider what this transaction may indicate about evolving priorities in AI infrastructure and compute markets. The conversation also examines how geopolitical dynamics could influence crypto markets, including regulation, capital allocation, and cross-border technology policy. Finally, we explore whether recent market behavior suggests crypto may be moving away from its historical four-year cycle. Remember to Stay Current! To learn more, visit us on the web at https://www.morgancreekcap.com/morgan-creekdigital/. To speak to a team member or sign up for additional content, please email mcdigital@morgancreekcap.com Legal Disclaimer This podcast is for informational purposes only and should not be construed as investment advice or a solicitation for the sale of any security, advisory, or other service. Investments related to the themes and ideas discussed may be owned by funds managed by the host and podcast guests. Any conflicts mentioned by the host are subject to change. Listeners should consult their personal financial advisors before making any investment decisions.

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

Welcome to episode 335 of The Cloud Pod, where the forecast is always cloudy! Welcome to the first show of 2026, and it's a full house, too! Justin, Jonathan, Ryan,  and Matt are all here to reflect on 2025, plus bring you their predictions for 2026. Let's get started!  Titles we almost went with this week SQL Me Maybe: AlloyDB Gets Chatty With Your Database **OpenAI SELECT * FROM natural_language WHERE accuracy LIKE ‘100%’ **Anthropic etcd You Were Worried About Database Limits: CloudWatch Has Your Back CSV You Later: Looker Adds Drag-and-Drop Data Uploads AWS Spots an Opportunity to Manage Your Container Costs EKS Network Policies: No More IP Address Whack-a-Mole AWS Security Hub Splits: It’s Not You, It’s CSPM Spot On: ECS Finally Manages Your Cheapest Compute TOON Squad: DigitalOcean’s New Format Makes JSON Look Bloated The Price is Wrong: AWS Breaks Two Decades of Downward Pricing Tradition Show Your Work: Why AI-Generated Code Without Tests is Just Expensive Spam No More Agent Orange: Google Simplifies VM Extension Deployment AWS Discovers Prices Can Go Both Ways, Raises GPU Costs 15 Percent Sovereignty Washing: When Your European Cloud Still Answers to Uncle Sam Agent Builder Gets a Memory Upgrade: Google’s AI Finally Remembers Where It Put Its Keys Ctrl+F for the Future: A year-end Scorecard & Next-Gen Bets AI Agents, GPU Prices, and The best of the Cloud Pod 2025 Beyond the Hype: The Cloud Pods Definitive 2025 Year in Review Apocalypse Now… What? Our 2026 Forecast Follow Up  01:27 RYAN’S PREDICTIONS Prediction Status Notes Quick LLM models for individuals ACCURATE Meta-Llama-3.1-8B-Instruct, GLM-4-9B-0414, and Qwen2.5-VL-7B-Instruct—each chosen for an outstanding balance of performance and computational efficiency, making them ideal for edge AI deployment. A new AI inference application called Inferencer allows even modest Apple Mac computers to run the largest open-source LLMs. AI at the edge natively (Lambda-esque) ACCURATE Akamai launched a new Inference Cloud product for edge AI using Nvidia’s Blackwell 6000 GPUs in 17 cities. AWS IoT Greengrass with Lambda functions for edge logic. “Edge AI allows for instant decision-making where it matters most—close to the data source.” Cloud native security mesh multi-cloud UNCLEAR Service mesh technologies continue to evolve (Istio, Linkerd), but I didn’t find a breakthrough “app-to-app at the edge” security mesh product announcement in 2025. This one needs more specific evidence. Ryan Score: 2/3 02:25 MATTHEW’S PREDICTIONS Prediction Status Notes FOCUS adopted by Snowflake or Databricks ACCURATE FOCUS version 1.2 was ratified on May 29, 2025. Three new providers announced support: Alibaba Cloud, Databricks, and Grafana. Databricks officially adopted FOCUS! AI security/ethical standard (SOC or ISO) ACCURATE ISO 42001 is the first international standard outlining requirements for AI governance. Major companies achieving certification in 2025: Automation Anywhere is among the first 100 companies worldwide to earn ISO/IEC 42001:2023 certification. Anthropic also achieved ISO 42001 certification. Amazon deprecates 5+ services (WorkMail bonus) ACCURATE (no bonus) 19 services are mothballed, four are being sunset, and one is end of its supported life. Deprecated services include CodeCommit, Cloud9, S3 Select, CloudSearch, SimpleDB, Forecast, Data Pipeline, QLDB, Snowball Edge, and more. WorkMail NOT deprecated – WorkDocs was (April 2025), but WorkMail remains active. Matthew Score: 3/3 03:22 JONATHAN’S PREDICTIONS Prediction Status Notes Company claims AGI achieved ACC

In this episode of The Data Center Frontier Show, DCF Editor in Chief Matt Vincent speaks with Kevin Ooley, CFO of DataBank, about how the operator is structuring capital to support disciplined growth amid accelerating AI and enterprise demand. Ooley explains the rationale behind DataBank's expansion of its development credit facility from $725 million to $1.6 billion, describing it as a strong signal of lender confidence in data centers as long-duration, mission-critical real estate assets. Central to that strategy is DataBank's “Devco facility,” a pooled, revolving financing vehicle designed to support multiple projects at different stages of development; from land and site work through construction, leasing, and commissioning. The conversation explores how DataBank translates capital into concrete expansion across priority U.S. markets, including Northern Virginia, Dallas, and Atlanta, with nearly 20 projects underway through 2025 and 2026. Ooley details how recent deployments, including fully pre-leased capacity, feed a development pipeline supported by both debt and roughly $2 billion in equity raised in late 2024. Vincent and Ooley also dig into how DataBank balances rapid growth with prudent leverage, managing interest-rate volatility through hedging and refinancing stabilized assets into fixed-rate securitizations. In the AI era, Ooley emphasizes DataBank's focus on “NFL cities,” serving enterprise and hyperscale customers that need proximity, reliability, and scale while Databank delivers power, buildings, and uptime, and customers source their own GPUs. The episode closes with a look at Databank's long-term sponsorship by DigitalBridge, its deep banking relationships, and the market signals—pricing, absorption, and customer demand—that will ultimately dictate the pace of growth.

NVIDIA is rumored to be bringing back the GeForce RTX 3060 again due to skyrocketing RAM and GPU prices, with AI being blamed. Man, you really don't want to build a gaming PC in 2026...Watch this podcast episode on YouTube and all major podcast hosts including Spotify.CLOWNFISH TV is an independent, opinionated news and commentary podcast that covers Entertainment and Tech from a consumer's point of view. We talk about Gaming, Comics, Anime, TV, Movies, Animation and more. Hosted by Kneon and Geeky Sparkles.D/REZZED News covers Pixels, Pop Culture, and the Paranormal! We're an independent, opinionated entertainment news blog covering Video Games, Tech, Comics, Movies, Anime, High Strangeness, and more. As part of Clownfish TV, we strive to be balanced, based, and apolitical. Get more news, views and reviews on Clownfish TV News - https://more.clownfishtv.com/On YouTube - https://www.youtube.com/c/ClownfishTVOn Spotify - https://open.spotify.com/show/4Tu83D1NcCmh7K1zHIedvgOn Apple Podcasts - https://podcasts.apple.com/us/podcast/clownfish-tv-audio-edition/id1726838629

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.

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

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

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.

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.

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 

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)

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

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

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