Podcasts about gpus

Linktree: ⁠https://linktr.ee/Analytic⁠Join The Normandy For Additional Bonus Audio And Visual Content For All Things Nme+! Join Here: ⁠https://ow.ly/msoH50WCu0K⁠In the Notorious Mass Effect segment, Analytic Dreamz dives deep into the RAM Price Crisis (2025–2026), unpacking the key data, market drivers, and real consumer impact behind the dramatic surge in memory costs.RAM prices have skyrocketed into a sustained inflation cycle heading into 2026, fueled by explosive AI data center demand that prioritizes high-bandwidth memory (HBM) and diverts supply from consumer DRAM. Manufacturing bottlenecks, limited cleanroom capacity, and lithography constraints exacerbate the shortage, while major players like Micron exit consumer RAM sales (Crucial brand in December 2025) to focus on higher-margin AI segments. Samsung and SK hynix report massive profit surges amid the boom.DDR5 RAM has seen prices more than quadruple (+340–344%) since July 2025, with a +27% month-on-month jump from December to January 2026. DDR4 and older standards are rising even faster recently (+46% MoM in January), narrowing the gap with newer tech. ComputerBase's fixed-basket analysis confirms average prices have quadrupled versus September 2025, with Germany's retail tracking—Europe's largest PC hardware market—mirroring global trends, including growing secondary-market distortions.Secondary effects hit related components hard: SSDs up +79%, hard drives +53%, GPUs +14% (with street prices far exceeding MSRP on models like RTX 5070 Ti). Specific examples include 2TB NVMe drives jumping 60–159% and NAS HDDs doubling.Analyst forecasts from TrendForce and Omdia point to +50–60% DRAM contract price hikes in Q1 2026, following 40–70% YoY increases in 2025. PC shipments grew +9.2% in 2025 but face potential declines in 2026, while smartphone output forecasts drop ~20% for some brands, risking +30% price hikes or spec downgrades. Gaming consoles may see delays or higher launch prices.Apple's upgrade costs (e.g., $400 for 16GB→32GB) already outpace comparable DDR5 sticks, with M6 Macs potentially facing steeper hikes or supply delays if AI firms continue outbidding.The core takeaway: This AI-driven structural shift has quadrupled RAM prices in under six months, with volatility persisting through 2026. A plateau is the most optimistic scenario—no full reversal in sight. Analytic Dreamz breaks down the data, root causes, and widespread ripple effects across PCs, smartphones, and beyond.Support this podcast at — https://redcircle.com/analytic-dreamz-notorious-mass-effect/donationsPrivacy & Opt-Out: https://redcircle.com/privacy

Episode 95: The Ryzen 7 9850X3D has been released and at best all we can say about it is that it's inoffensive. Also, more reports have emerged that signal the end of GPUs at MSRP.CHAPTERS00:00 - Intro00:26 - So The 9850X3D Has Been Released16:04 - More GPU Supply Information29:40 - Zotac Might Be In Trouble43:11 - Intel Launching Big Battlemage for Pros?49:09 - Updates From Our Boring LivesSOURCESder8auer video: https://www.youtube.com/watch?v=0lS1S_VhUK4&pp=2AYBZotac Korea statement: https://videocardz.com/newz/zotac-korea-warns-of-steep-rtx-5090-and-rtx-5060-price-hikes-says-some-models-may-be-unavailable-for-a-whileArc Pro B70: https://x.com/SquashBionic/status/2015648577511629092SUBSCRIBE 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.

Main pointsOpenAI's Financial Instability: OpenAI is facing a catastrophic financial burn of approximately $15 million daily, with projected losses exceeding $14 billion in 2026. This is coupled with a mass exodus of key leadership (CTO, Chief Research Officer, and Chief Scientist) and a massive $134 billion lawsuit from Elon Musk.The Component Crisis & Market Saturation: OpenAI's hoarding of GPUs, RAM, and SSDs has caused consumer prices to skyrocket (e.g., DDR5 RAM jumping from $300 to over $1,000). Despite this, newer models like GPT-5 are reportedly disappointing users, while Google's Gemini has surged to 650 million monthly active users.The "Agent" Marketing Myth: An internal Google playbook reveals that 99% of "AI Agents" currently on the market are merely "marketing buzzword packaging" consisting of simple API calls. True autonomous agents require a rigorous "AgentOps" infrastructure—including four-layer evaluation frameworks and security protocols—that most startups currently lack.Unsustainable Infrastructure & Economics: Experts warn that the AI bubble mirrors the 2008 housing crash. The "fundamental math" is failing: energy and capital costs are quintupling while performance gains diminish, requiring OpenAI to generate $2 trillion in annual revenue (15x current growth) just to remain viable.The AI Layoff Wave: Significant job cuts are being attributed to AI restructuring and automation, with 245,000 tech jobs lost in 2025. Major 2026 layoffs include 48,000 at UPS due to automation and 30,000 corporate roles at Amazon, signaling a shift from human capital to AI integration.Referenced X Users @BoringBiz_@nitinthisside_ @anon_opin

In this conversation, Rick Bentley discusses the rising costs of compute in AI, the challenges faced by smaller companies in accessing necessary technology, and the implications of AI on the job market. He emphasizes the importance of building data centers and exploring cost-effective solutions for AI compute. The discussion also touches on the future of education, vocational skills, and the impact of AI on outsourcing and consulting.

China's next AI shock isn't another DeepSeek-style model. It's hardware.After DeepSeek proved China could compete under constraints, that approach is moving from software to chips, power, and infrastructure. Instead of chasing the most advanced GPUs, China is scaling what it controls: domestic chips that are good enough, cheap power, and systems designed to work together. This is less about building a Chinese Nvidia and more about building an alternative AI stack and pushing it into markets that want AI now, not perfect performance. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

A CMO Confidential Interview with Rob Ward, co-founder and General Partner of Meritech Capital, a top Silicon Valley venture firm. Rob shares his take on what he calls a "super terrifying and exciting time" and provides perspective on AI receiving the most capital of any technology in history, the "durability of revenue" and how quickly start-ups are now reaching $100 million in revenue. Key topics include: why VC's focus on growth vs. profitability; the risks associated with massive long-term capital investment; why marketers should pick a "trusted advisor" as their AI partner; and why your data strategy needs "context. Tune in to hear how Astronomer handled the "Coldplay Concert Incident" which immediately became a PR classic and the "VC Foie Gras Effect."What happens when a top venture capitalist pulls back the curtain on AI, valuations, hype cycles, and what's actually working?In this episode of CMO Confidential, host Mike Linton sits down with Rob Ward, Co-Founder and General Partner at Metech Capital, to unpack the realities behind the AI boom. Rob has spent more than 26 years investing in category-defining companies like Facebook (Meta), Snowflake, NetSuite, Zipcar, and Cloudera — and he brings a rare, grounded perspective to today's AI frenzy.Together, they explore: • Why AI adoption is still early — despite explosive growth • The real risks behind inflated valuations and “AI-washing” • How VC decision-making changes during platform shifts • What marketers and executives should actually look for when choosing AI partners • Why data strategy, change management, and trust matter more than tools • What layoffs, productivity, and the future of work really look like beneath the headlines • A masterclass in crisis communications, featuring Ryan Reynolds, Gwyneth Paltrow, and ColdplayIf you're a CMO, CEO, board member, founder, or agency leader trying to make sense of AI without getting swept up in the hype — this is a must-listen conversation.New episodes of CMO Confidential drop every Tuesday.Subscribe for insider perspectives on the most misunderstood role in the C-suite.⸻Chapter Markers00:00 – Welcome to CMO Confidential00:19 – Introducing Rob Ward and today's AI conversation01:13 – Where we really are in AI adoption02:26 – Explosive AI growth: what's real vs hype03:35 – Why enterprise AI adoption is still a slog04:37 – Vendor spend, hyperscalers, and the trillion-dollar buildout06:12 – Is this an AI bubble? Public vs private market realities07:20 – Accelerating investment rounds and lack of diligence08:12 – AI-washing and durability of AI businesses09:46 – Proof-of-concepts, switching costs, and fragile loyalty10:55 – Big Tech vs startups: why this cycle is different11:40 – Why VCs chase platform shifts despite the risks13:05 – How AI is changing profitability and headcount math16:11 – “FOGRA” investing and capital distortion17:00 – Circular investing and data-center risk18:23 – Data centers, GPUs, and betting on the wrong future19:38 – Credit default swaps and financial warning signs21:45 – How executives should choose AI vendors22:58 – Change management and why culture matters most24:09 – Why data strategy is the real AI strategy26:36 – “Frequently wrong, never in doubt” and AI hallucinations27:01 – Practical AI use cases for marketers30:00 – Layoffs, productivity, and what's really happening to jobs33:05 – The best questions to spot real AI fluency35:00 – AI safety, geopolitics, and long-term risks36:38 – Crisis management masterclass: Astronomer, Coldplay & Ryan Reynolds39:58 – Final advice and closing thoughts⸻Comma-Separated TagsCMO Confidential, AI strategy, artificial intelligence, venture capital, Rob Ward, Metech Capital, AI adoption, AI hype, AI bubble, enterprise AI, generative AI, AI in marketing, CMO leadership, marketing leadership, venture investing, AI vendors, data strategy, change management, AI readiness, tech valuations, AI infrastructure, data centers, future of work, AI layoffs, crisis communications, brand crisis management, Ryan Reynolds marketing, Gwyneth Paltrow Astronomer, Coldplay controversy, Silicon Valley, marketing podcast, C-suite leadershipSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On this episode of That Tech Pod, we talk with Logan Lawler, Senior Director at Dell Technologies, about what it takes to make AI actually work in the real world. Logan shares his 16-year journey at Dell and why his focus today is less on hype and more on practical infrastructure choices that enable AI at scale.We break down Edge AI versus Cloud AI with clear, concrete examples, including how GPU-accelerated desktops, workstations, and hybrid cloud setups can turn “that's impossible” AI problems into manageable ones. Logan also highlights why storage, not compute, is often the biggest bottleneck, and the common mistakes organizations make when data can't keep up with GPUs. The conversation gets into energy and sustainability, from the environmental cost of massive data centers to what it means when nuclear power and AI collide. We also explore the human side of AI: whether instant answers are making us lazier, why struggle is still essential for learning, and how that idea shows up in parenting, education, and work. We close with real-world edge AI success stories, a few cautionary tales, and some lighter moments, making this a grounded discussion on AI, infrastructure, and the tradeoffs we rarely talk about.Logan Lawler works at Dell Technologies, where he leads strategy for Dell Pro Precision AI Solutions. Over his 16-year career at Dell, he's worked across sales, marketing, and e-commerce, and now helps enterprises and creative studios leverage high-performance AI workstations and hybrid cloud infrastructure. A frequent speaker and media guest, Logan explains how GPU-accelerated PCs and storage solutions are transforming industries from film and animation to healthcare research. Logan was raised in Missouri and is a graduate of the University of Missouri. He now lives in Texas with his family.

Applied Digital CEO Wes Cummins joins Data Center Frontier Editor-in-Chief Matt Vincent to break down what it takes to build AI data centers that can keep pace with Nvidia-era infrastructure demands and actually deliver on schedule. Cummins explains Applied Digital's “maximum flexibility” design philosophy, including higher-voltage delivery, mixed density options, and even more floor space to future-proof facilities as power and cooling requirements evolve. The conversation digs into the execution reality behind the AI boom: long-lead power gear, utility timelines, and the tight MEP supply chain that will cause many projects to slip in 2026–2027. Cummins outlines how Applied Digital locked in key components 18–24 months ago and scaled from a single 100 MW “field of dreams” building to roughly 700 MW under construction, using fourth-generation designs and extensive off-site MEP assembly—“LEGO brick” skids—to boost speed and reduce on-site labor risk. On cooling, Cummins pulls back the curtain on operating direct-to-chip liquid cooling at scale in Ellendale, North Dakota, including the extra redundancy layers—pumps, chillers, dual loops, and thermal storage—required to protect GPUs and hit five-nines reliability. He also discusses aligning infrastructure with Nvidia's roadmap (from 415V toward 800V and eventually DC), the customer demand surge pushing capacity planning into 2028, and partnerships with ABB and Corintis aimed at next-gen power distribution and liquid cooling performance.

Your host, Sebastian Hassinger, talks with Alumni Ventures managing partner Chris Sklarin about how one of the most active US venture firms is building a quantum portfolio while “democratizing” access to VC as an asset class for individual investors. They dig into Alumni Ventures' co‑investor model, how the firm thinks about quantum hardware, software, and sensing, and why quantum should be viewed as a long‑term platform with near‑term pockets of commercial value. Chris also explains how accredited investors can start seeing quantum deal flow through Alumni Ventures' syndicate.Chris' background and Alumni Ventures in a nutshellChris is an MIT‑trained engineer who spent years in software startups before moving into venture more than 20 years ago.Alumni Ventures is a roughly decade‑old firm focused on “democratizing venture capital” for individual investors, with over 11,000 LPs, more than 1.5 billion dollars raised, and about 1,300 active portfolio companies.The firm has been repeatedly recognized as a highly active VC by CB Insights, PitchBook, Stanford GSB, and Time magazine.How Alumni Ventures structures access for individualsMost investors come in as individuals into LLC‑structured funds rather than traditional GP/LP funds.Alumni Ventures always co‑invests alongside a lead VC, using the lead's conviction, sector expertise, and diligence as a key signal.The platform also offers a syndicate where accredited investors can opt in to see and back individual deals, including those tagged for quantum.Quantum in the Alumni Ventures portfolioAlumni Ventures has 5–6 quantum‑related investments spanning hardware, software, and applications, including Rigetti, Atom Computing, Q‑CTRL, Classiq, and quantum‑error‑mitigation startup Qedma/Cadmus.Rigetti was one of the firm's earliest quantum investments; the team followed on across multiple rounds and was able to return capital to investors after Rigetti's SPAC and a strong period in the public markets.Chris also highlights interest in Cycle Dre (a new company from Rigetti's former CTO) and application‑layer companies like InQ and quantum sensing players.Barbell funding and the “3–5 year” viewChris responds to the now‑familiar “barbell” funding picture in quantum— a few heavily funded players and a long tail of small companies—by emphasizing near‑term revenue over pure science experiments.He sees quantum entering an era where companies must show real products, customers, and revenue, not just qubit counts.Over the next 3–5 years, he expects meaningful commercial traction first in areas like quantum sensing, navigation, and point solutions in chemistry and materials, with full‑blown fault‑tolerant systems further out.Hybrid compute and NVIDIA's signal to the marketChris points to Jensen Huang's GTC 2025 keynote slide on NVIDIA's hybrid quantum–GPU ecosystem, where Alumni Ventures portfolio companies such as Atom Computing, Classiq, and Rigetti appeared.He notes that NVIDIA will not put “science projects” on that slide—those partnerships reflect a view that quantum processors will sit tightly coupled next to GPUs to handle specific workloads.He also mentions a large commercial deal between NVIDIA and Groq (a classical AI chip company in his portfolio) as another sign of a more heterogeneous compute future that quantum will plug into.Where near‑term quantum revenue shows upChris expects early commercial wins in sensing, GPS‑denied navigation, and other narrow but valuable applications before broad “quantum advantage” in general‑purpose computing.Software and middleware players can generate revenue sooner by making today's hardware more stable, more efficient, or easier to program, and by integrating into classical and AI workflows.He stresses that investors love clear revenue paths that fit into the 10‑year life of a typical venture fund.University spin‑outs, clustering, and deal flowAlumni Ventures certainly sees clustering around strong quantum schools like MIT, Harvard, and Yale, but Chris emphasizes that the “alumni angle” is secondary to the quality of the venture deal.Mature tech‑transfer offices and standard Delaware C‑corps mean spinning out quantum IP from universities is now a well‑trodden path.Chris leans heavily on network effects—Alumni Ventures' 800,000‑person network and 1,300‑company CEO base—as a key channel for discovering the most interesting quantum startups.Managing risk in a 100‑hardware‑company worldWith dozens of hardware approaches now in play, Chris uses Alumni Ventures' co‑investor model and lead‑investor diligence as a filter rather than picking purely on physics bets.He looks for teams with credible near‑term commercial pathways and for mechanisms like sensing or middleware that can create value even if fault‑tolerant systems arrive later than hoped.He compares quantum to past enabling waves like nanotech, where the biggest impact often shows up as incremental improvements rather than a single “big bang” moment.Democratizing access to quantum ventureAlumni Ventures allows accredited investors to join its free syndicate, self‑attest accreditation, and then see deal materials—watermarked and under NDA—for individual investments, including quantum.Chris encourages people to think in terms of diversified funds (20–30 deals per fund year) rather than only picking single names in what is a power‑law asset class.He frames quantum as a long‑duration infrastructure play with near‑term pockets of usefulness, where venture can help investors participate in the upside without getting ahead of reality.

WANTED: Developers and STEM experts! Get paid to create benchmarks and improve AI models. Sign up for Alignerr using our link: https://alignerr.com/?referral-source=briankeating One of the most powerful AI systems we've ever built is succeeding for reasons we still don't understand. And worse, they may succeed for reasons that might lock us into the wrong future for humanity. Today's guest is Anil Ananthaswamy, an award-winning science writer and one of the clearest thinkers on the mathematical foundations of machine learning. In this conversation, we're not just talking about new demos, incremental improvements, or updates on new models being released. We're asking even harder questions: Why does the mathematics of machine learning work at all? How do these models succeed when they suffer from problems like overparameterization and lack of training data? And are large language models revealing deep structure, or are they just producing very convincing illusions and causing us to face an increasingly AI-slop-driven future? KEY TAKEAWAYS 00:00 — Book explores why ML works through math 02:47 — Perceptron proof shows simple math guarantees learning 05:11 — Early AI failed due to single-layer limits 07:12 — Nonlinear limits caused the first AI winter 09:04 — Backpropagation revived neural networks 10:59 — GPUs + big data enabled deep learning 15:25 — AI success risks technological lock-in 17:30 — LLMs lack human-like learning and embodiment 22:57 — High-dimensional spaces power ML behavior 27:36 — Data saturation may slow future gains 31:11 — Continual learning is still missing in AI 33:46 — Neuromorphic chips promise energy efficiency 41:49 — Overparameterized models still generalize well 45:05 — SGD succeeds via randomness in complex landscapes 48:27 — Perceptrons remain the core of modern neural net - Additional resources: Anil's NEW Book "Why Machines Learn: The Elegant Math Behind Modern AI": https://www.amazon.com/Why-Machines-Learn-Elegant-Behind/dp/0593185749 Get My NEW Book: Focus Like a Nobel Prize Winner: https://www.amazon.com/dp/B0FN8DH6SX?ref_=pe_93986420_775043100 Please join my mailing list here

Recorded at CES 2026, this special episode of the Washington AI Network Podcast examines how quantum computing and AI tools are moving from theory into real-world use.Host Tammy Haddad interviews Pouya Dianat, chief revenue officer of Quantum Computing Inc., about what quantum computing is—and is not—and its implications for encryption, national security, finance, and data centers. Dianat explains why quantum systems are designed to complement classical computing and how quantum processing units will operate alongside CPUs and GPUs.The episode also features a conversation with the Las Vegas stars of YouTube's Iced Coffee Hour, Graham Stephan and Jack Selby.

The MacVoices Live! panel discusses how artificial intelligence has shifted from a destination into an invisible layer within everyday software. Rather than visiting separate tools, AI is now embedded in operating systems and apps, increasingly becoming a natural part of workflows. Chuck Joiner, David Ginsburg, Marty Jencius, Brian Flanigan-Arthurs, Web Bixby, Jeff Gamet, Mark Fuccio and Jim Rea explore how this mirrors earlier machine-learning adoption and raises questions about awareness, dependence, and long-term impact.  The Antigravity A1 is the world's first 8K 360 drone, it's genuinely a game-changer. You get full immersive flight with the goggles, insanely intuitive controls, and endless creative freedom in editing.If you're thinking about buying a drone, make it this one. Check out the link in our show notes and get a free landing pad with your order!https://www.antigravity.tech/drone/antigravity-a1/buy?utm_term=macvoices Take your personal data back with Incogni! Get 60% off an annual plan at https://incogni.com/chuck and use code chuck at checkout. Show Notes: Chapters: 00:00 – AI moving from destination to built-in feature01:30 – Everyday workflows and slicker AI interfaces03:22 – Machine learning parallels and invisible automation04:12 – Ubiquitous AI and “fructose in everything” analogy06:05 – “AI slop” and low-value content inflation07:47 – Tech learning phases: fonts, flash, social media10:00 – AI investment, GPUs, and Apple's compute angle14:35 – Ongoing tech lawsuit discussion17:41 – Social media fragmentation and finding businesses20:21 – Aggregation tools to manage splintered platforms Guests: Web Bixby has been in the insurance business for 40 years and has been an Apple user for longer than that.You can catch up with him on Facebook, Twitter, and LinkedIn, but prefers Bluesky. Brian Flanigan-Arthurs is an educator with a passion for providing results-driven, innovative learning strategies for all students, but particularly those who are at-risk. He is also a tech enthusiast who has a particular affinity for Apple since he first used the Apple IIGS as a student. You can contact Brian on twitter as @brian8944. He also recently opened a Mastodon account at @brian8944@mastodon.cloud. Mark Fuccio is actively involved in high tech startup companies, both as a principle at piqsure.com, or as a marketing advisor through his consulting practice Tactics Sells High Tech, Inc. Mark was a proud investor in Microsoft from the mid-1990's selling in mid 2000, and hopes one day that MSFT will be again an attractive investment. You can contact Mark through Twitter, LinkedIn, or on Mastodon. Jeff Gamet is a technology blogger, podcaster, author, and public speaker. Previously, he was The Mac Observer's Managing Editor, and the TextExpander Evangelist for Smile. He has presented at Macworld Expo, RSA Conference, several WordCamp events, along with many other conferences. You can find him on several podcasts such as The Mac Show, The Big Show, MacVoices, Mac OS Ken, This Week in iOS, and more. Jeff is easy to find on social media as @jgamet on Twitter and Instagram, jeffgamet on LinkedIn., @jgamet@mastodon.social on Mastodon, and on his YouTube Channel at YouTube.com/jgamet. David Ginsburg is the host of the weekly podcast In Touch With iOS where he discusses all things iOS, iPhone, iPad, Apple TV, Apple Watch, and related technologies. He is an IT professional supporting Mac, iOS and Windows users. Visit his YouTube channel at https://youtube.com/daveg65 and find and follow him on Twitter @daveg65 and on Mastodon at @daveg65@mastodon.cloud. Dr. Marty Jencius has been an Associate Professor of Counseling at Kent State University since 2000. He has over 120 publications in books, chapters, journal articles, and others, along with 200 podcasts related to counseling, counselor education, and faculty life. His technology interest led him to develop the counseling profession ‘firsts,' including listservs, a web-based peer-reviewed journal, The Journal of Technology in Counseling, teaching and conferencing in virtual worlds as the founder of Counselor Education in Second Life, and podcast founder/producer of CounselorAudioSource.net and ThePodTalk.net. Currently, he produces a podcast about counseling and life questions, the Circular Firing Squad, and digital video interviews with legacies capturing the history of the counseling field. This is also co-host of The Vision ProFiles podcast. Generally, Marty is chasing the newest tech trends, which explains his interest in A.I. for teaching, research, and productivity. Marty is an active presenter and past president of the NorthEast Ohio Apple Corp (NEOAC). Jim Rea built his own computer from scratch in 1975, started programming in 1977, and has been an independent Mac developer continuously since 1984. He is the founder of ProVUE Development, and the author of Panorama X, ProVUE's ultra fast RAM based database software for the macOS platform. He's been a speaker at MacTech, MacWorld Expo and other industry conferences. Follow Jim at provue.com and via @provuejim@techhub.social on Mastodon. Support:      Become a MacVoices Patron on Patreon     http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:     http://macvoices.com      Twitter:     http://www.twitter.com/chuckjoiner     http://www.twitter.com/macvoices      Mastodon:     https://mastodon.cloud/@chuckjoiner      Facebook:     http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:     http://www.facebook.com/macvoices/      MacVoices Group on Facebook:     http://www.facebook.com/groups/macvoice      LinkedIn:     https://www.linkedin.com/in/chuckjoiner/      Instagram:     https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes     Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

The MacVoices Live! panel discusses how artificial intelligence has shifted from a destination into an invisible layer within everyday software. Rather than visiting separate tools, AI is now embedded in operating systems and apps, increasingly becoming a natural part of workflows. Chuck Joiner, David Ginsburg, Marty Jencius, Brian Flanigan-Arthurs, Web Bixby, Jeff Gamet, Mark Fuccio and Jim Rea explore how this mirrors earlier machine-learning adoption and raises questions about awareness, dependence, and long-term impact.  The Antigravity A1 is the world's first 8K 360 drone, it's genuinely a game-changer. You get full immersive flight with the goggles, insanely intuitive controls, and endless creative freedom in editing.If you're thinking about buying a drone, make it this one. Check out the link in our show notes and get a free landing pad with your order! https://www.antigravity.tech/drone/antigravity-a1/buy?utm_term=macvoices Take your personal data back with Incogni! Get 60% off an annual plan at https://incogni.com/chuck and use code chuck at checkout. Show Notes: Chapters: 00:00 – AI moving from destination to built-in feature 01:30 – Everyday workflows and slicker AI interfaces 03:22 – Machine learning parallels and invisible automation 04:12 – Ubiquitous AI and "fructose in everything" analogy 06:05 – "AI slop" and low-value content inflation 07:47 – Tech learning phases: fonts, flash, social media 10:00 – AI investment, GPUs, and Apple's compute angle 14:35 – Ongoing tech lawsuit discussion 17:41 – Social media fragmentation and finding businesses 20:21 – Aggregation tools to manage splintered platforms Guests: Web Bixby has been in the insurance business for 40 years and has been an Apple user for longer than that.You can catch up with him on Facebook, Twitter, and LinkedIn, but prefers Bluesky. Brian Flanigan-Arthurs is an educator with a passion for providing results-driven, innovative learning strategies for all students, but particularly those who are at-risk. He is also a tech enthusiast who has a particular affinity for Apple since he first used the Apple IIGS as a student. You can contact Brian on twitter as @brian8944. He also recently opened a Mastodon account at @brian8944@mastodon.cloud. Mark Fuccio is actively involved in high tech startup companies, both as a principle at piqsure.com, or as a marketing advisor through his consulting practice Tactics Sells High Tech, Inc. Mark was a proud investor in Microsoft from the mid-1990's selling in mid 2000, and hopes one day that MSFT will be again an attractive investment. You can contact Mark through Twitter, LinkedIn, or on Mastodon. Jeff Gamet is a technology blogger, podcaster, author, and public speaker. Previously, he was The Mac Observer's Managing Editor, and the TextExpander Evangelist for Smile. He has presented at Macworld Expo, RSA Conference, several WordCamp events, along with many other conferences. You can find him on several podcasts such as The Mac Show, The Big Show, MacVoices, Mac OS Ken, This Week in iOS, and more. Jeff is easy to find on social media as @jgamet on Twitter and Instagram, jeffgamet on LinkedIn., @jgamet@mastodon.social on Mastodon, and on his YouTube Channel at YouTube.com/jgamet. David Ginsburg is the host of the weekly podcast In Touch With iOS where he discusses all things iOS, iPhone, iPad, Apple TV, Apple Watch, and related technologies. He is an IT professional supporting Mac, iOS and Windows users. Visit his YouTube channel at https://youtube.com/daveg65 and find and follow him on Twitter @daveg65 and on Mastodon at @daveg65@mastodon.cloud. Dr. Marty Jencius has been an Associate Professor of Counseling at Kent State University since 2000. He has over 120 publications in books, chapters, journal articles, and others, along with 200 podcasts related to counseling, counselor education, and faculty life. His technology interest led him to develop the counseling profession 'firsts,' including listservs, a web-based peer-reviewed journal, The Journal of Technology in Counseling, teaching and conferencing in virtual worlds as the founder of Counselor Education in Second Life, and podcast founder/producer of CounselorAudioSource.net and ThePodTalk.net. Currently, he produces a podcast about counseling and life questions, the Circular Firing Squad, and digital video interviews with legacies capturing the history of the counseling field. This is also co-host of The Vision ProFiles podcast. Generally, Marty is chasing the newest tech trends, which explains his interest in A.I. for teaching, research, and productivity. Marty is an active presenter and past president of the NorthEast Ohio Apple Corp (NEOAC). Jim Rea built his own computer from scratch in 1975, started programming in 1977, and has been an independent Mac developer continuously since 1984. He is the founder of ProVUE Development, and the author of Panorama X, ProVUE's ultra fast RAM based database software for the macOS platform. He's been a speaker at MacTech, MacWorld Expo and other industry conferences. Follow Jim at provue.com and via @provuejim@techhub.social on Mastodon. Support:      Become a MacVoices Patron on Patreon      http://patreon.com/macvoices      Enjoy this episode? Make a one-time donation with PayPal Connect:      Web:      http://macvoices.com      Twitter:      http://www.twitter.com/chuckjoiner      http://www.twitter.com/macvoices      Mastodon:      https://mastodon.cloud/@chuckjoiner      Facebook:      http://www.facebook.com/chuck.joiner      MacVoices Page on Facebook:      http://www.facebook.com/macvoices/      MacVoices Group on Facebook:      http://www.facebook.com/groups/macvoice      LinkedIn:      https://www.linkedin.com/in/chuckjoiner/      Instagram:      https://www.instagram.com/chuckjoiner/ Subscribe:      Audio in iTunes      Video in iTunes      Subscribe manually via iTunes or any podcatcher:      Audio: http://www.macvoices.com/rss/macvoicesrss      Video: http://www.macvoices.com/rss/macvoicesvideorss

Will AGI happen soon - or are we running into a wall?In this episode, I'm joined by Tim Dettmers (Assistant Professor at CMU; Research Scientist at the Allen Institute for AI) and Dan Fu (Assistant Professor at UC San Diego; VP of Kernels at Together AI) to unpack two opposing frameworks from their essays: “Why AGI Will Not Happen” versus “Yes, AGI Will Happen.” Tim argues progress is constrained by physical realities like memory movement and the von Neumann bottleneck; Dan argues we're still leaving massive performance on the table through utilization, kernels, and systems—and that today's models are lagging indicators of the newest hardware and clusters.Then we get practical: agents and the “software singularity.” Dan says agents have already crossed a threshold even for “final boss” work like writing GPU kernels. Tim's message is blunt: use agents or be left behind. Both emphasize that the leverage comes from how you use them—Dan compares it to managing interns: clear context, task decomposition, and domain judgment, not blind trust.We close with what to watch in 2026: hardware diversification, the shift toward efficient, specialized small models, and architecture evolution beyond classic Transformers—including state-space approaches already showing up in real systems.Sources:Why AGI Will Not Happen - https://timdettmers.com/2025/12/10/why-agi-will-not-happen/Use Agents or Be Left Behind? A Personal Guide to Automating Your Own Work - https://timdettmers.com/2026/01/13/use-agents-or-be-left-behind/Yes, AGI Can Happen – A Computational Perspective - https://danfu.org/notes/agi/The Allen Institute for Artificial IntelligenceWebsite - https://allenai.orgX/Twitter - https://x.com/allen_aiTogether AIWebsite - https://www.together.aiX/Twitter - https://x.com/togethercomputeTim DettmersBlog - https://timdettmers.comLinkedIn - https://www.linkedin.com/in/timdettmers/X/Twitter - https://x.com/Tim_DettmersDan FuBlog - https://danfu.orgLinkedIn - https://www.linkedin.com/in/danfu09/X/Twitter - https://x.com/realDanFuFIRSTMARKWebsite - https://firstmark.comX/Twitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)Blog - https://mattturck.comLinkedIn - https://www.linkedin.com/in/turck/X/Twitter - https://twitter.com/mattturck(00:00) - Intro(01:06) – Two essays, two frameworks on AGI(01:34) – Tim's background: quantization, QLoRA, efficient deep learning(02:25) – Dan's background: FlashAttention, kernels, alternative architectures(03:38) – Defining AGI: what does it mean in practice?(08:20) – Tim's case: computation is physical, diminishing returns, memory movement(11:29) – “GPUs won't improve meaningfully”: the core claim and why(16:16) – Dan's response: utilization headroom (MFU) + “models are lagging indicators”(22:50) – Pre-training vs post-training (and why product feedback matters)(25:30) – Convergence: usefulness + diffusion (where impact actually comes from)(29:50) – Multi-hardware future: NVIDIA, AMD, TPUs, Cerebras, inference chips(32:16) – Agents: did the “switch flip” yet?(33:19) – Dan: agents crossed the threshold (kernels as the “final boss”)(34:51) – Tim: “use agents or be left behind” + beyond coding(36:58) – “90% of code and text should be written by agents” (how to do it responsibly)(39:11) – Practical automation for non-coders: what to build and how to start(43:52) – Dan: managing agents like junior teammates (tools, guardrails, leverage)(48:14) – Education and training: learning in an agent world(52:44) – What Tim is building next (open-source coding agent; private repo specialization)(54:44) – What Dan is building next (inference efficiency, cost, performance)(55:58) – Mega-kernels + Together Atlas (speculative decoding + adaptive speedups)(58:19) – Predictions for 2026: small models, open-source, hardware, modalities(1:02:02) – Beyond transformers: state-space and architecture diversity(1:03:34) – Wrap

Episode 144Happy New Year! This is one of my favorite episodes of the year — for the fourth time, Nathan Benaich and I did our yearly roundup of AI news and advancements, including selections from this year's State of AI Report.If you've stuck around and continue to listen, I'm really thankful you're here. I love hearing from you.You can find Nathan and Air Street Press here on Substack and on Twitter, LinkedIn, and his personal site. Check out his writing at press.airstreet.com.Find me on Twitter (or LinkedIn if you want…) for updates on new episodes, and reach me at editor@thegradient.pub for feedback, ideas, guest suggestions.Outline* (00:00) Intro* (00:44) Air Street Capital and Nathan world* Nathan's path from cancer research and bioinformatics to AI investing* The “evergreen thesis” of AI from niche to ubiquitous* Portfolio highlights: Eleven Labs, Synthesia, Crusoe* (03:44) Geographic flexibility: Europe vs. the US* Why SF isn't always the best place for original decisions* Industry diversity in New York vs. San Francisco* The Munich Security Conference and Europe's defense pivot* Playing macro games from a European vantage point* (07:55) VC investment styles and the “solo GP” approach* Taste as the determinant of investments* SF as a momentum game with small information asymmetry* Portfolio diversity: defense (Delian), embodied AI (Syriact), protein engineering* Finding entrepreneurs who “can't do anything else”* (10:44) State of AI progress in 2025* Momentous progress in writing, research, computer use, image, and video* We're in the “instruction manual” phase* The scale of investment: private markets, public markets, and nation states* (13:21) Range of outcomes and what “going bad” looks like* Today's systems are genuinely useful—worst case is a valuation problem* Financialization of AI buildouts and GPUs* (14:55) DeepSeek and China closing the capability gap* Seven-month lag analysis (Epoch AI)* Benchmark skepticism and consumer preferences (”Coca-Cola vs. Pepsi”)* Hedonic adaptation: humans reset expectations extremely quickly* Bifurcation of model companies toward specific product bets* (18:29) Export controls and the “evolutionary pressure” argument* Selective pressure breeds innovation* Chinese companies rushing to public markets (Minimax, ZAI)* (21:30) Reasoning models and test-time compute* Chain of thought faithfulness questions* Monitorability tax: does observability reduce quality?* User confusion about when models should “think”* AI for science: literature agents, hypothesis generation* (23:53) Chain of thought interpretability and safety* Anthropomorphization concerns* Alignment faking and self-preservation behaviors* Cybersecurity as a bigger risk than existential risk* Models as payloads injected into critical systems* (27:26) Commercial traction and AI adoption data* Ramp data: 44% of US businesses paying for AI (up from 5% in early 2023)* Average contract values up to $530K from $39K* State of AI survey: 92% report productivity gains* The “slow takeoff” consensus and human inertia* Use cases: meeting notes, content generation, brainstorming, coding, financial analysis* (32:53) The industrial era of AI* Stargate and XAI data centers* Energy infrastructure: gas turbines and grid investment* Labs need to own models, data, compute, and power* Poolside's approach to owning infrastructure* (35:40) Venture capital in the age of massive GPU capex* The GP lives in the present, the entrepreneur in the future, the LP in the past* Generality vs. specialism narratives* “Two or 20”: management fees vs. carried interest* Scaling funds to match entrepreneur ambitions* (40:10) NVIDIA challengers and returns analysis* Chinese challengers: 6x return vs. 26x on NVIDIA* US challengers: 2x return vs. 12x on NVIDIA* Grok acquired for $20B; Samba Nova markdown to $1.6B* “The tide is lifting all boats”—demand exceeds supply* (44:06) The hardware lottery and architecture convergence* Transformer dominance and custom ASICs making a comeback* NVIDIA still 90–95% of published AI research* (45:49) AI regulation: Trump agenda and the EU AI Act* Domain-specific regulators vs. blanket AI policy* State-level experimentation creates stochasticity* EU AI Act: “born before GPT-4, takes effect in a world shaped by GPT-7”* Only three EU member states compliant by late 2025* (50:14) Sovereign AI: what it really means* True sovereignty requires energy, compute, data, talent, chip design, and manufacturing* The US is sovereign; the UK by itself is not* Form alliances or become world-class at one level of the stack* ASML and the Netherlands as an example* (52:33) Open weight safety and containment* Three paths: model-based safeguards, scaffolding/ecosystem, procedural/governance* “Pandora's box is open”—containment on distribution, not weights* Leak risk: the most vulnerable link is often human* Developer–policymaker communication and regulator upskilling* (55:43) China's AI safety approach* Matt Sheehan's work on Chinese AI regulation* Safety summits and China's participation* New Chinese policies: minor modes, mental health intervention, data governance* UK's rebrand from “safety” to “security” institutes* (58:34) Prior predictions and patterns* Hits on regulatory/political areas; misses on semiconductor consolidation, AI video games* (59:43) 2026 Predictions* A Chinese lab overtaking US on frontier (likely ZAI or DeepSeek, on scientific reasoning)* Data center NIMBYism influencing midterm politics* (01:01:01) ClosingLinks and ResourcesNathan / Air Street Capital* Air Street Capital* State of AI Report 2025* Air Street Press — essays, analysis, and the Guide to AI newsletter* Nathan on Substack* Nathan on Twitter/X* Nathan on LinkedInFrom Air Street Press (mentioned in episode)* Is the EU AI Act Actually Useful? — by Max Cutler and Nathan Benaich* China Has No Place at the UK AI Safety Summit (2023) — by Alex Chalmers and Nathan BenaichResearch & Analysis* Epoch AI: Chinese AI Models Lag US by 7 Months — the analysis referenced on the US-China capability gap* Sara Hooker: The Hardware Lottery — the essay on how hardware determines which research ideas succeed* Matt Sheehan: China's AI Regulations and How They Get Made — Carnegie EndowmentCompanies Mentioned* Eleven Labs — AI voice synthesis (Air Street portfolio)* Synthesia — AI video generation (Air Street portfolio)* Crusoe — clean compute infrastructure (Air Street portfolio)* Poolside — AI for code (Air Street portfolio)* DeepSeek — Chinese AI lab* Minimax — Chinese AI company* ASML — semiconductor equipmentOther Resources* Search Engine Podcast: Data Centers (Part 1 & 2) — PJ Vogt's two-part series on XAI data centers and the AI financing boom* RAAIS Foundation — Nathan's AI research and education charity Get full access to The Gradient at thegradientpub.substack.com/subscribe

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/

Join The Full Nerd gang as they talk about the latest PC building news. In this episode the gang talks about the RTX 5070 Ti and 5060 Ti messaging and potificates on whether those GPUs are truly end of life, and the reports of dead X3D CPUs. And of course we answer questions live. Asus denial: https://www.pcworld.com/article/3035212/asus-denies-that-its-canceling-the-rtx-5070-or-rtx-5060-ti.html Check out the audio version of the podcast on iTunes, Spotify, Pocket Casts and more so you can listen on the go, and be sure to subscribe so you don't miss the latest live episode here on YouTube! Join the PC related discussions and ask us questions on Discord: https://discord.gg/UWhjwg778a Follow the crew on X and Bluesky: @AdamPMurray @BradChacos @MorphingBall @WillSmith

Wilder Lopes is the CEO and Founder of Ogre.run, working on AI-driven dependency resolution and reproducible code execution across environments.How Universal Resource Management Transforms AI Infrastructure Economics // MLOps Podcast #357 with Wilder Lopes, CEO / Founder of Ogre.runJoin the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractEnterprise organizations face a critical paradox in AI deployment: while 52% struggle to access needed GPU resources with 6-12 month waitlists, 83% of existing CPU capacity sits idle. This talk introduces an approach to AI infrastructure optimization through universal resource management that reshapes applications to run efficiently on any available hardware—CPUs, GPUs, or accelerators.We explore how code reshaping technology can unlock the untapped potential of enterprise computing infrastructure, enabling organizations to serve 2-3x more workloads while dramatically reducing dependency on scarce GPU resources. The presentation demonstrates why CPUs often outperform GPUs for memory-intensive AI workloads, offering superior cost-effectiveness and immediate availability without architectural complexity.// BioWilder Lopes is a second-time founder, developer, and research engineer focused on building practical infrastructure for developers. He is currently building Ogre.run, an AI agent designed to solve code reproducibility.Ogre enables developers to package source code into fully reproducible environments in seconds. Unlike traditional tools that require extensive manual setup, Ogre uses AI to analyze codebases and automatically generate the artifacts needed to make code run reliably on any machine. The result is faster development workflows and applications that work out of the box, anywhere.// Related LinksWebsite: https://ogre.runhttps://lopes.aihttps://substack.com/@wilderlopes https://youtu.be/YCWkUub5x8c?si=7RPKqRhu0Uf9LTql~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Wilder on LinkedIn: /wilderlopes/Timestamps:[00:00] Secondhand Data Centers Challenges[00:27] AI Hardware Optimization Debate[03:40] LLMs on Older Hardware[07:15] CXL Tradeoffs[12:04] LLM on CPU Constraints[17:07] Leveraging Existing Hardware[22:31] Inference Chips Overview[27:57] Fundamental Innovation in AI[30:22] GPU CPU Combinations[40:19] AI Hardware Challenges[43:21] AI Perception Divide[47:25] Wrap up

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.

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

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

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

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

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