Podcasts about models

As artificial intelligence becomes a strategic capability for nations as well as companies, questions of governance, safety, and geopolitical competition are moving to the forefront. In this episode of TechSurge, host Sriram Viswanathan speaks with Helen Toner, Interim Executive Director of the Center for Security and Emerging Technology (CSET) at Georgetown and a former OpenAI board member, about the rise of sovereign AI stacks and the global implications of increasingly powerful AI systems.Helen brings a rare vantage point from both inside the frontier AI ecosystem and the policy world. She reflects on lessons from her time on the OpenAI board, including the governance challenges that arise when nonprofit missions intersect with enormous commercial incentives and rapid technological progress. As AI capabilities accelerate, she argues that the industry is still grappling with deep uncertainty about how these systems work, how they will evolve, and what responsibilities companies and governments should carry.The conversation explores the idea of sovereign AI; the growing push by countries to control key layers of the AI stack, including compute infrastructure, models, and data. Helen explains why governments increasingly view AI as a strategic national resource, comparable to past transformative technologies like electricity or the internet. At the same time, she cautions that full technological independence may be unrealistic for most nations, given the complexity and global interdependence of the AI supply chain.Sriram and Helen also examine the evolving US–China AI competition, the role of export controls and semiconductor supply chains, and how different countries, from China to emerging AI hubs in the Middle East, are positioning themselves in the race to build advanced AI capabilities. Along the way, they discuss whether the industry should slow down development, how companies are experimenting with “safety frameworks” for frontier models, and why installing guardrails may be more realistic than attempting to halt progress altogether.Ultimately, Helen argues that society is entering a period of profound uncertainty. AI is transitioning from a research discipline into a foundational system that will shape economies, security, and daily life. Navigating that transition will require not just technical breakthroughs, but new approaches to governance, transparency, and global cooperation.If you enjoy this episode, please subscribe and leave us a review on your favorite podcast platform.Sign up for our newsletter at techsurgepodcast.com for updates on upcoming TechSurge Live Summits and future Season 2 episodes.--Episode LinksConnect with Helen: linkedin.com/in/helen-toner-4162439aLearn more about CSET: https://cset.georgetown.edu/--Timestamps03:00 Lessons from the OpenAI Board: Governance in the Age of Frontier AI05:00 The Big Unknowns in AI Development: Why Experts Still Disagree12:05 Public Trust and the Risk of an AI Backlash14:20 When AI Became Infrastructure: From Research Field to Societal System16:00 Is AGI a Meaningless Term Now? Rethinking the Goalposts19:05 AI's True Scale: Internet-Level Impact or Something Bigger?23:15 Why Frontier AI Labs Struggle to Slow Down24:40 What “Sovereign AI” Actually Means for Nations28:10 Mapping the AI Stack: Chips, Cloud, Models, and Applications33:38 The US–China AI Competition: Who's Ahead and Why39:44 China's Progress in AI: Compute Constraints and Fast Followers44:03 US AI Policy: Export Controls, Regulation, and Federal Preemption48:40 Frontier AI Safety Frameworks: How Labs Define Dangerous Capabilities51:36 The Future of AI: Utopia, Industrialization, or Something Worse?56:04 Rapid Fire: AI Misconceptions, Governance Reforms, and Regions to Watch

What do particle physicists and Wall Street traders have in common? How did finance become more like physics, and how is physics now becoming more like finance? Emanuel Derman is an emeritus professor at Columbia in financial engineering and the author of several books, including My Life as a Quant: Reflections on Physics and Finance and Models. Behaving. Badly.: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life. His work examines the entanglement of physics and finance, using memoir to reveal hidden truths about the theories and models practitioners rely on.  Greg and Emanuel discuss his transition from physics to Wall Street, revealing that he found finance to be more social and creative. They also explore how early quant work required both theory and hands-on programming, what distinguishes models from theories, and why, despite some superficial similarities, the fields of finance and physics couldn't be more different. *unSILOed Podcast is produced by University FM.* Episode Quotes: Financial models require confidence without hubris 29:29: In my life as a quant, I think I said you had to be cocky when you were using models and push them as far as you possibly could, but stop short of hubris, and I think that's important. You ought to understand that your model isn't going to be correct. In the end, the world is going to violate it. When physics meets social sciences 09:35: I think to some extent they [psychists] confuse accuracy with point of view. Even progressive theories get more and more accurate. Newton's laws aren't as accurate as relativity, but they still, both theories, the one just does better than the other, but they still have this nature of saying, let me describe the way the world works rather than, let me make an analogy. Why model builders must explain where models fail 30:46: There's a clear distinction between concentrators to tell the people that use it that this is where it's going to fail, as best I can see. And they'll use it in this regime. And these are the assumptions I'm making. Don't just let them run wild with the formula. I think traders are smarter now and more numerate and maybe understand this better, but I think that's important. Why financial engineers need perspective beyond mathematics  28:13: I don't think one should be teaching philosophy necessarily, but I think one should learn enough to know about the history of finance and to be able to back off a little and look at what you're doing. Not just, I don't know. I have a feeling more and more of the programs focus on mathematics and behavioral psychology. Show Links: Recommended Resources: Dictionary of Financial Risk Management Salomon Brothers James Clerk Maxwell Baruch Spinoza Johann Wolfgang von Goethe Fischer Black Black Scholes Black Derman Toy model Put call parity Paul Wilmott Binomial options pricing model Mark Rubinstein Freeman Dyson Guest Profile: Faculty Profile at Columbia University Professional Website Professional Profile on X Guest Work: Brief Hours and Weeks: My Life as a Capetonian My Life as a Quant: Reflections on Physics and Finance The Volatility Smile: An Introduction for Students and Practitioners Models. Behaving. Badly.: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The coaching industry is a $30 billion machine built on "proven frameworks," but for experienced professionals, these models often lead to a bank account running on empty. Real transformation doesn't scale in a group of 300, and a weekend certification can't replace 35 years of clinical expertise. Lori pulls back the curtain on why "trusting the process" is often a deflection of coach responsibility and how to spot a coaching mismatch before you sign your next five-figure contract. Highlights: The Scale Myth: Why real identity work and transformation cannot be mass-produced. Certification vs. Expertise: The truth about why results are the only credentials that actually matter. The Cost of Mismatch: A cautionary tale of how the wrong program can erode professional confidence. AI and the Thinking Gap: How to ensure your coach is actually doing the thinking, not just generating "influencer bro" lingo. Schedule a call to discuss personalized coaching at TalkWithLori.com Schedule your Profitable Path Blueprint call.  If you're considering working together and want to see if it's a fit, book a Profitable Path Blueprint Call. It's a simple, no-pressure conversation to decide whether working together makes sense.  Resources: Click HERE to receive your free gift - Get Clients to Say "YES!" The Ultimate Social Proof Checklist Every Business Needs to Build Trust and Boost Sales Join Lori's private Facebook group - The Midlife Business Academy. A Facebook group for The Typewriter Generation!  A community to share business growth strategies that work for us! Join now!   Connect with Lori Follow me on social media - grab other free resources of book a call - it's all right here! Apply for a "Hot Seat" coaching session to work through your business challenges live: MyCoachLori.com

What if pediatric care were designed around families first — not systems, incentives, or billing complexity?   In this episode, Chris Johnson, Founder & CEO of Bluebird Kids Health, joins Mavericks in Healthcare to unpack how value‑based care can transform pediatric outcomes while making care more affordable, accessible, and sustainable — even for the most complex populations.   Chris shares why pediatrics has historically lagged behind adult care in value‑based models, what it truly takes to serve Medicaid populations at scale, and how Bluebird is rethinking everything from clinic design to care teams to better support children, families, and clinicians alike. Drawing on lessons from scaling prior value‑based care organizations, he breaks down what healthcare leaders often underestimate when building for equity, trust, and long‑term impact.   The conversation also explores the role of technology and AI in simplifying care delivery — not adding burden — and how thoughtful, human‑centered design can improve experience while driving measurable outcomes and cost savings.   This episode offers a practical, real‑world blueprint for health system leaders, payers, and innovators focused on improving pediatric care delivery without compromising quality, access, or clinician well‑being. If you're interested in the future of value‑based care, pediatric innovation, or building healthcare models that truly work for families, this is a must‑listen.

Stryker hospital tools safe, digital ordering services down Models apply to be the face of AI scams Cybercrime up 245% since Iran conflict Get links to all our stories in the show notes: https://cisoseries.com/cybersecurity-news-stryker-hospital-tools-safe-models-apply-to-power-ai-scams-cybercrime-up-245/ Huge thanks to our episode sponsor, Adaptive Security This episode is brought to you by Adaptive Security, the first security awareness platform built to stop AI-powered social engineering. Today's phishing doesn't just hit inboxes — it can sound like your CFO or look like your CEO on Zoom. AI voices, video, and deepfakes are turning trust into the attack surface. Adaptive fights back with AI-driven risk scoring, deepfake simulations featuring your own executives, and interactive training your team will actually remember. Take a three-minute tour or request a CEO deepfake demo at adaptivesecurity.com.

7. Cline addresses the vulnerability of the Minoan and Mycenaean civilizations, which served as models for "what not to do" during a crisis. Despite their outward appearance of strength, these societies were fragile systems that collapsed completely after the 12th century BC. Their writing system, Linear B, was limited to accounting, leaving no literary records of their downfall. The transition to the Iron Age saw the disappearance of their specific social structures, though names of gods like Zeus and Poseidon endured. This period illustrates how societies can appear vibrant while being internally decayed, leading to a total replacement of their political identities. (7)

Discover all of the podcasts in our network, search for specific episodes, get the Optimal Living Daily workbook, and learn more at: OLDPodcast.com. Episode 2937: Mark Manson cuts through the noise of modern dating advice by arguing that attraction starts with emotional health, self-respect, and authenticity, not clever lines or perfectly timed texts. He explores how neediness sabotages connection, why compatibility matters as much as chemistry, and how strong boundaries protect your wellbeing. This guide challenges you to become the kind of person who naturally attracts healthy, fulfilling relationships. Read along with the original article(s) here: https://markmanson.net/guide-to-modern-dating Quotes to ponder: "Neglecting to establish clear boundaries can lead to all sorts of problems, including resentment, anxiety, and even abuse." "Your emotional wellbeing is your top priority, and it's not worth sacrificing for the sake of someone who doesn't respect you." "By being clear and assertive about your boundaries, you'll attract partners who share your values and priorities, and build a relationship that's both fulfilling and sustainable." Episode references: Models: https://www.amazon.com/Models-Attract-Women-Through-Honesty/dp/1463750358

Welcome to Episode 119 of The Modelgeeks Podcast!  We have a special guest tonight!Jeremy Moore is joining us as a guest host and to help us with our model photography.After a bit of banter, we share what is on our bench and what we have picked up lately.  After we mention our March Madness projects we cover Mail Call (keep the cards & letters coming folks!).  Don't forget Listener Spotlight.  We then do a recap of the Old Dominion Open (Richmond IPMS) and then roll into a recap of future shows.  Our Patreon Giveaway has expanded!  We have added a second giveaway for our non-Pro Geek patrons.  Our main topic is “Photographing Scale Models” with Jeremy Moore.  Jeremy takes magazine quality photos of his models as can be seen on his web page and in the various modeling magazines his work where his work is published.  Even on the front cover!We would like to thank all our listeners out there for the continued support you have given the show. We hope to see you out and about as we hit show circuit. If you happen to see us at a show come on over and say hello, we may even put you in front of the mic!If you can't make it to the shows then you can still interact with us through social media, Facebook, Instagram, and of course email at:contact@modelgeekspodcast.com Also remember to surf over to the Geeks homepage at https://modelgeekspodcast.com.  Take a look at the Listener Gallery, and if you'd like your work there, send us your photos to contact@modelgeekspodcast.com.  File size and quantity is not an issue for us, but may be an issue for your email provider.  Feel free to send us a link to a sharing service if you use one, but please ensure the link expires at least 7 days after you send it.  We need a few days to get them published.  Make sure you check out our group / community on Facebook:The ModelGeeks Model ShackGet on there and feel free to share your work! We want to see what's on your bench.We also want to thank each of our sponsors for their support. We are very lucky to have them. When you have the time, pay a visit to their web sites, and have a look at their fine products.Please visit our Sponsors and see what new items they have:Furball Aero-DesignDetail & ScaleTamiya USABases By BillHypersonic ModelsLionHeart HobbyMatters of ScaleKotare ModelsWe are very fortunate to be able to join the scale modeling podcast community and are in the company of several other really GREAT podcasts. Hopefully, someday we'll earn our wings and be able to keep up with those guys!  Please check them all out at https://modelpodcasts.com.  It's a consortium website created by Stuart Clark of the Scale Model Podcast.Blogs:The Kit Box Sprue Pie with Frets Matters of ScaleSupport the showModel Geeks Podcast

Can the Democrats finally seize on President Trump's increasing unpopularity and end their slump? It seems to me as though 2026 is providing them ample opportunity. But I wanted to know what they actually stand for. Have they learned anything about immigration? Are they ready for the new politics of artificial intelligence? To find out, I asked someone I consider a true man of the left, Chris Hayes, the host of “All In With Chris Hayes” on MS NOW. 00:00 Intro 02:09 - Democrats: The state of play in 2026 06:46 - How Israel fractures the Democrats 09:19 - Immigration reform beyond the “old consensus” 19:46 - Models for Democratic leadership: Mark Kelly, Ruben Gallego, Rafael Warnock, and Jon Ossoff 27:22 - 2028: Kamala Harris, Gavin Newsom and “the Hillary Clinton problem”  30:41 - The politics of attention 36:19 - The challenges of achieving a Leftist society 45:37 - A Leftist case against A.I. 1:04:23 - Will A.I. define the 2028 election? (A full transcript of this episode is available on the Times website.) Thoughts? Email us at interestingtimes@nytimes.com. Please subscribe to our YouTube Channel, Interesting Times With Ross Douthat. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Jeffrey discusses the possibility of rethinking our current support model that was developed decades ago.Email Jeffrey with any questions or feedback (jtefertiller@servicemanagement.us)Each week, Jeffrey will be sharing his knowledge on Service Delivery (Mondays) and Service Management (Thursdays). Jeffrey is the founder of Service Management Leadership, an IT consulting firm specializing in Service Management, Asset Management, CIO Advisory, and Business Continuity services.  The firm's website is www.servicemanagement.us.  Jeffrey has been in the industry for 30 years and brings a practical perspective to the discussions. He is an accomplished author with seven acclaimed books in the subject area and a popular YouTube channel with approximately 1,600 videos on various topics.  Also, please follow the Service Management Leadership LinkedIn page.

Doomscrollin hosted by Sam Tripoli and Midnight Mike Sam Tripoli's new comic book "Chaos Twins!" 2nd issue is about to drop! Visit www.chaostwins.com to support Sam's family-friendly project! Check out Sam Tripoli's 3rd Crowd Work Special "Barbecued: Live From Kansas City" Sept 20th on Youtube.com/SamTripoliComedy Grab Tickets To Sam Tripoli's Live Shows At SamTripoli.com: Hollywood, CA: 3/10 Batavia, IL: 3/26-3/28 Dallas, TX: 4/24 Fort Worth, TX: 4/25 Austin, TX: 5/22 (Live Filming Of Sam Tripoli's New Comedy Taping) Albuquerque, NM: 6/12-6/13 Austin, TX: 6/18 Lawerence, KS: 9/17-9/19 Tulsa, OK: 10/9-10/10 Austin, TX: Dec 11th-13th Watch Sam's comedy special here: www.youtube.com/samtripoli  Please check out Sam Tripoli's Linktree: https://linktr.ee/samtripoli  Please check out Midnight Mike's Internet: The OBDM Podcast Website: https://ourbigdumbmouth.com/  Twitter: https://x.com/obdmpod  Check out the Naked Gardener's Band: The 3rd Pyramid Band - Topic https://bit.ly/4fpNMMr1. 1. small towns turn to nestle for salvation -@zephzoid2. the art of deception in cupcake recipe -@lavizrap133. the hidden science behind humor -@humangarage4. secrets in Argentinas nazi past -@ninjaarebutterflies5. shadows in utah valley -@realmoonhenry6. secrets buried in the swiss mountains -@itsmattw_017. strangers tardmaxxing - @imjakeh8. whispers of a nations discontent -@chaoticthoughtz_9. new york post published a story on ancient giants -@shanevibes_truth10. if USA sends ground forces into Iran -@brandonlkroll_krollology_10111. whale sperm death -@crittercommander30 raw eggs a month -@theshotclock12. train station surveillance scandal unfolds -@its_The_Dr13. japans unsettling animatronic kissing toilet -@whyjordie14. the enigmatic stranger left a note behind -@marshallsstrangeworld15. what the teachers need to be teaching -@trevormoore16. revolutionizing beauty in every frame -@mindofjulia_17. the art of working on water -@learnwithsherlock18. drone pilots experiments at MIT uncovered -@catherinelovesastrology19. photographer seeks truth behind mysterious signals -@whatthetvcanttelevise20. the golden video -@te_erika21. the algorithm that controls everything -@eddieyoon22. the ghostly footprint of unseen forces -@theemakethatmagic23. prime numbers of theoretical power -@gravityassistus24. corny street jokes -@josh_uglyasfkey bumps on national television  @swearingsport25. a woman's math -@alphafoxstretcher chair rolling vertical -@thefeelingscenter26. wartime breakdown -@magic_shaun.son27. snapped out of hip hop hypnosis to ascend to unc status -@alfonsofrfr28. $2.00 English lesson from India -@ClownWorld29. i was never gay -@epicclipvault30. mr beast escape dubai w netanyahu -@myhilism31. pov your teammates in a spelling bee -@DudespostingWs Learn more about your ad choices. Visit podcastchoices.com/adchoices

Send a textSend a textJB leads all 5 of us as we talk about the upcoming 2026 Edition of the 48 in 48 Global Group Build and fundraiser to benefit Models for Heroes the weekend of March 20, 2026. We also do a Modelfiesta Wrap Up, talk about our visits to The Model Box in Boerne, Texas and Lionheart Hobby in Kyle, Texas, and finally a summary of a GREAT model show - Winterblitz - located at the Museum of the American GI in College Station. JB also leads us in two discussion points - lessons learned when moving across different genres, and also why are Vintage kits so popular? All of the hosts have strong opinions on this one, and that end of things, one side prevails - either the practicality or new, better kits, or the nostalgia and romance of vintage kits. Tune in to see which side came out on top! Remember to check out our YouTube page and our new regular video content at the Plastic Posse Podcast YouTube Page: https://www.youtube.com/channel/UCP7O9C8b-rQx8JvxFKfG-Kw If you would like to become a Posse Outrider, and make a recurring monthly donation of $ 1 and up, visit us at www.patreon.com/plasticpossepodcast .Plastic Posse Podcast on Facebook: https://www.facebook.com/PlasticPossePlastic Posse Group on Facebook: https://www.facebook.com/groups/302255047706269Plastic Posse Podcast MERCH! : https://plastic-posse-podcast.creator-spring.com/Plastic Posse Podcast on YouTube:https://www.youtube.com/channel/UCP7O9C8b-rQx8JvxFKfG-KwOrion Paintworks (TJ): https://www.facebook.com/orionpaintworksJB-Closet Modeler (JB): https://www.facebook.com/closetmodelerThree Tens' Modelworks (Jensen): https://www.facebook.com/ThreeTensModelWorksRocky Mountain Expo: https://rockymtnhobbyexpo.com/SPONSORS:Tankraft: https://tankraft.com/AK Interactive: https://ak-interactive.com/Tamiya USA: https://www.tamiyausa.com/Micro World Games: https://mwg-hobbies.com/Bases By Bill: https://basesbybill.com/?srsltid=AfmBOoojwgAlnXwsJcB_SlYzeclVt9ZuIX3Fd18Ig9k5f4vyIYmihobbSupport the showSupport the show

I think the future is cheaper and Open Source SOTA models combined with context, not custom, narrow models.Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

Send a textAYOOO welcome back to Luck Management. The bros, aside from eckhaus are getting absolutely demolished by AI. What a freaking world we live in where AI is now just destroying everything. Brother, Lucky has to figure his shit out. Never bet unders and fade me if you want to make so much money. Its an oxy moron- but aye here we are and here we go into March. Big moves coming- be on the lookout for the bros on Twitter. Keep living the Luck Management LifestyleSupport the showInstagram: @luck_managementApple Podcasts: https://podcasts.apple.com/podcast/id1637190216Spotify: https://open.spotify.com/show/4JsxM55BY6tRlGzJCiUnvzBrought to you by CharmND. Check us out on Instagram @charm_ND & @CharmNDShop on EtsyKeep living The Luck Management Lifestyle!

- Porsche Cuts Costs and Plans New Luxury Models - U.S. New Vehicle Inventory Hits 3 Million Units - BYD Explores Entering Formula 1 - Zoox And Uber Partner for Robotaxi Launch - Wayve And Qualcomm Partner on AI Driving System - Ram ProMaster City Van Returns to U.S. Market - Mercedes Reveals Luxurious VLE Electric Van - Toyota bZ3X Sales Top 80,000 Units in China

- Porsche Cuts Costs and Plans New Luxury Models - U.S. New Vehicle Inventory Hits 3 Million Units - BYD Explores Entering Formula 1 - Zoox And Uber Partner for Robotaxi Launch - Wayve And Qualcomm Partner on AI Driving System - Ram ProMaster City Van Returns to U.S. Market - Mercedes Reveals Luxurious VLE Electric Van - Toyota bZ3X Sales Top 80,000 Units in China

Meeting Jesus: Wednesdays Evenings In Luke With Dr. Clint Archer. Tonight's Sermon Is "Three Models Of Unbelief: Pilate, Herod, Israel" From Luke 23:1-25. Sermon Outline - 3 Types Of unbelief So That We Avoid Rejecting The Savior: 1. Indifference - Pilate 2. Curiosity - Herod 3. Hostility - Israel

In this episode we are rebroadcasting an episode from 2024 and reflect on the how a flexible approach to service delivery can improve the accessibility, adaptability, and efficacy of our supports There are many unknowns in the lead up to changes such as the introduction of Thriving Kids, and flexibility may help us weather these changes. We speak with Tania Kelly, Yadanar Tut, and Gaenor Dixon from the Department of Education in Queensland. Gaenor, Tania and Yadanar have been working with schools to establish flexible ways of delivering their services without compromising on quality. We discuss some of the enablers, barriers, and outcomes of these flexible models and the equitable service this promotes. SPA resources: Telepractice toolkit: https://learninghub.speechpathologyaustralia.org.au/topclass/topclass.do?expand-OfferingDetails-Offeringid=3279 Telepractice in speech pathology position statement: https://www.speechpathologyaustralia.org.au/Common/Uploaded%20files/Smart%20Suite/Smart%20Library/1ebffbac-b78f-4956-963d-f12b00542dc5/FINAL_Telepractice-Position-Statement.pdf Speech Pathology in Education Position Statement: https://www.speechpathologyaustralia.org.au/Members/libraryviewer?ResourceID=101 Speech pathology in Education Practice Guideline: https://www.speechpathologyaustralia.org.au/Members/libraryviewer?ResourceID=130 Speech Pathology Australia acknowledges the Traditional Custodians of lands, seas and waters throughout Australia, and offers our respect to Elders, across all times and places. The Speak Up podcast recognises the central role of yarning and oral storytelling in Aboriginal and Torres Strait Islander culture, how this translates to knowledge translation, and that colonisation has interrupted these practices of Language and knowledge sharing. The Speak Up podcast acknowledges the need for truth-telling and deep listening, the central role that Language plays in connecting Aboriginal and Torres Strait Islander People with Culture, Country, and Community, and the interwoven nature of health, and social and emotional wellbeing. We recognise that the Traditional Owners of the Lands across Australia have been here since time immemorial, and that their sovereignty over this land, was never ceded. Free access to transcripts for podcast episodes are available via the SPA Learning Hub (https://learninghub.speechpathologyaustralia.org.au/), you will need to sign in or create an account. For more information, please see our Bio or for further enquiries, email speakuppodcast@speechpathologyaustralia.org.au Disclaimer: © (2026) The Speech Pathology Association of Australia Limited. All rights reserved. Important Notice, Please read: The views expressed in this presentation and reproduced in these materials are not necessarily the views of, or endorsed by, The Speech Pathology Association of Australia Limited (“the Association”). The Association makes no warranty or representation in relation to the content, currency or accuracy of any of the materials comprised in this recording. The Association expressly disclaims any and all liability (including liability for negligence) in respect of use of these materials and the information contained within them. The Association recommends you seek independent professional advice prior to making any decision involving matters outlined in this recording including in any of the materials referred to or otherwise incorporated into this recording. Except as otherwise stated, copyright and all other intellectual property rights comprised in the presentation and these materials, remain the exclusive property of the Association. Except with the Association's prior written approval you must not, in whole or part, reproduce, modify, adapt, distribute, publish or electronically communicate (including by online means) this recording or any of these materials.

Amazon is implementing new safeguards to protect against outages related to generated code, and Google is unifying its suite of Gemini integrations inside Google Drive.Starring Tom Merritt and Jason Howell.Links to stories found in this episode can be found here. Hosted on Acast. See acast.com/privacy for more information.

What does the day-to-day of a math is figureoutable classroom look like? In this episode, Pam and Kim discuss the new book for teachers of Grades 3-5 to transform their teaching. Talking Points:New book release for Grades 3-5!Development of Mathematical ReasoningAdditive ReasoningMultiplicative ReasoningProblem String walkthroughs and videosRich tasks, routines, models and modelingNext steps for teachers, specific to their needs and experienceShark Metaphor Podcast episode: Ep 245: Three Distortions that Ruin Math TeachingCheck out our social mediaTwitter: @PWHarrisInstagram: Pam Harris_mathFacebook: Pam Harris, author, mathematics educationLinkedin: Pam Harris Consulting LLC 

  What separates scalable real estate platforms from everyone else? In this episode of The Capital Raiser Show, Richard Wilson sits down with Joe Williams, Co-Founder of Keller Williams, to unpack the principles that helped build one of the largest real estate platforms in the world — now operating in dozens of countries with hundreds of thousands of agents. Joe shares: The coaching moment that transformed Keller Williams from 60 offices to global scale The "Stable Table Theory" — the four foundational pillars every serious enterprise must build Why hiring talent is the most expensive lesson entrepreneurs learn How culture becomes a competitive moat Why real estate remains one of the most learnable and predictable asset classes The power of structure in scaling partnerships and investment platforms How relationships — not pitch decks — drive real opportunity Joe also discusses land investing, the importance of systems in volatile markets, and why today's interest rates are simply a reset — not a crisis. If you're building a family office, scaling a real estate portfolio, or raising capital in 2026's environment, this conversation will sharpen your framework for long-term growth.

Join Kyle, Nader, Vibhu, and swyx live at NVIDIA GTC next week!Now that AIE Europe tix are ~sold out, our attention turns to Miami and World's Fair!The definitive AI Accelerator chip company has more than 10xed this AI Summer:And is now a $4.4 trillion megacorp… that is somehow still moving like a startup. We are blessed to have a unique relationship with our first ever NVIDIA guests: Kyle Kranen who gave a great inference keynote at the first World's Fair and is one of the leading architects of NVIDIA Dynamo (a Datacenter scale inference framework supporting SGLang, TRT-LLM, vLLM), and Nader Khalil, a friend of swyx from our days in Celo in The Arena, who has been drawing developers at GTC since before they were even a glimmer in the eye of NVIDIA:Nader discusses how NVIDIA Brev has drastically reduced the barriers to entry for developers to get a top of the line GPU up and running, and Kyle explains NVIDIA Dynamo as a data center scale inference engine that optimizes serving by scaling out, leveraging techniques like prefill/decode disaggregation, scheduling, and Kubernetes-based orchestration, framed around cost, latency, and quality tradeoffs. We also dive into Jensen's “SOL” (Speed of Light) first-principles urgency concept, long-context limits and model/hardware co-design, internal model APIs (https://build.nvidia.com), and upcoming Dynamo and agent sessions at GTC.Full Video pod on YouTubeTimestamps00:00 Agent Security Basics00:39 Podcast Welcome and Guests07:19 Acquisition and DevEx Shift13:48 SOL Culture and Dynamo Setup27:38 Why Scale Out Wins29:02 Scale Up Limits Explained30:24 From Laptop to Multi Node33:07 Cost Quality Latency Tradeoffs38:42 Disaggregation Prefill vs Decode41:05 Kubernetes Scaling with Grove43:20 Context Length and Co Design57:34 Security Meets Agents58:01 Agent Permissions Model59:10 Build Nvidia Inference Gateway01:01:52 Hackathons And Autonomy Dreams01:10:26 Local GPUs And Scaling Inference01:15:31 Long Running Agents And SF ReflectionsTranscriptAgent Security BasicsNader: Agents can do three things. They can access your files, they can access the internet, and then now they can write custom code and execute it. You literally only let an agent do two of those three things. If you can access your files and you can write custom code, you don't want internet access because that's one to see full vulnerability, right?If you have access to internet and your file system, you should know the full scope of what that agent's capable of doing. Otherwise, now we can get injected or something that can happen. And so that's a lot of what we've been thinking about is like, you know, how do we both enable this because it's clearly the future.But then also, you know, what, what are these enforcement points that we can start to like protect?swyx: All right.Podcast Welcome and Guestsswyx: Welcome to the Lean Space podcast in the Chromo studio. Welcome to all the guests here. Uh, we are back with our guest host Viu. Welcome. Good to have you back. And our friends, uh, Netter and Kyle from Nvidia. Welcome.Kyle: Yeah, thanks for having us.swyx: Yeah, thank you. Actually, I don't even know your titles.Uh, I know you're like architect something of Dynamo.Kyle: Yeah. I, I'm one of the engineering leaders [00:01:00] and a architects of Dynamo.swyx: And you're director of something and developers, developer tech.Nader: Yeah.swyx: You're the developers, developers, developers guy at nvidia,Nader: open source agent marketing, brev,swyx: and likeNader: Devrel tools and stuff.swyx: Yeah. BeenNader: the focus.swyx: And we're, we're kind of recording this ahead of Nvidia, GTC, which is coming to town, uh, again, uh, or taking over town, uh, which, uh, which we'll all be at. Um, and we'll talk a little bit about your sessions and stuff. Yeah.Nader: We're super excited for it.GTC Booth Stunt Storiesswyx: One of my favorite memories for Nader, like you always do like marketing stunts and like while you were at Rev, you like had this surfboard that you like, went down to GTC with and like, NA Nvidia apparently, like did so much that they bought you.Like what, what was that like? What was that?Nader: Yeah. Yeah, we, we, um. Our logo was a chaka. We, we, uh, we were always just kind of like trying to keep true to who we were. I think, you know, some stuff, startups, you're like trying to pretend that you're a bigger, more mature company than you are. And it was actually Evan Conrad from SF Compute who was just like, you guys are like previousswyx: guest.Yeah.Nader: Amazing. Oh, really? Amazing. Yeah. He was just like, guys, you're two dudes in the room. Why are you [00:02:00] pretending that you're not? Uh, and so then we were like, okay, let's make the logo a shaka. We brought surfboards to our booth to GTC and the energy was great. Yeah. Some palm trees too. They,Kyle: they actually poked out over like the, the walls so you could, you could see the bread booth.Oh, that's so funny. AndNader: no one else,Kyle: just from very far away.Nader: Oh, so you remember it backKyle: then? Yeah I remember it pre-acquisition. I was like, oh, those guys look cool,Nader: dude. That makes sense. ‘cause uh, we, so we signed up really last minute, and so we had the last booth. It was all the way in the corner. And so I was, I was worried that no one was gonna come.So that's why we had like the palm trees. We really came in with the surfboards. We even had one of our investors bring her dog and then she was just like walking the dog around to try to like, bring energy towards our booth. Yeah.swyx: Steph.Kyle: Yeah. Yeah, she's the best,swyx: you know, as a conference organizer, I love that.Right? Like, it's like everyone who sponsors a conference comes, does their booth. They're like, we are changing the future of ai or something, some generic b******t and like, no, like actually try to stand out, make it fun, right? And people still remember it after three years.Nader: Yeah. Yeah. You know what's so funny?I'll, I'll send, I'll give you this clip if you wanna, if you wanna add it [00:03:00] in, but, uh, my wife was at the time fiance, she was in medical school and she came to help us. ‘cause it was like a big moment for us. And so we, we bought this cricket, it's like a vinyl, like a vinyl, uh, printer. ‘cause like, how else are we gonna label the surfboard?So, we got a surfboard, luckily was able to purchase that on the company card. We got a cricket and it was just like fine tuning for enterprises or something like that, that we put on the. On the surfboard and it's 1:00 AM the day before we go to GTC. She's helping me put these like vinyl stickers on.And she goes, you son of, she's like, if you pull this off, you son of a b***h. And so, uh, right. Pretty much after the acquisition, I stitched that with the mag music acquisition. I sent it to our family group chat. Ohswyx: Yeah. No, well, she, she made a good choice there. Was that like basically the origin story for Launchable is that we, it was, and maybe we should explain what Brev is andNader: Yeah.Yeah. Uh, I mean, brev is just, it's a developer tool that makes it really easy to get a GPU. So we connect a bunch of different GPU sources. So the basics of it is like, how quickly can we SSH you into a G, into a GPU and whenever we would talk to users, they wanted A GPU. They wanted an A 100. And if you go to like any cloud [00:04:00] provisioning page, usually it's like three pages of forms or in the forms somewhere there's a dropdown.And in the dropdown there's some weird code that you know to translate to an A 100. And I remember just thinking like. Every time someone says they want an A 100, like the piece of text that they're telling me that they want is like, stuffed away in the corner. Yeah. And so we were like, what if the biggest piece of text was what the user's asking for?And so when you go to Brev, it's just big GPU chips with the type that you want withswyx: beautiful animations that you worked on pre, like pre you can, like, now you can just prompt it. But back in the day. Yeah. Yeah. Those were handcraft, handcrafted artisanal code.Nader: Yeah. I was actually really proud of that because, uh, it was an, i I made it in Figma.Yeah. And then I found, I was like really struggling to figure out how to turn it from like Figma to react. So what it actually is, is just an SVG and I, I have all the styles and so when you change the chip, whether it's like active or not it changes the SVG code and that somehow like renders like, looks like it's animating, but it, we just had the transition slow, but it's just like the, a JavaScript function to change the like underlying SVG.Yeah. And that was how I ended up like figuring out how to move it from from Figma. But yeah, that's Art Artisan. [00:05:00]Kyle: Speaking of marketing stunts though, he actually used those SVGs. Or kind of use those SVGs to make these cards.Nader: Oh yeah. LikeKyle: a GPU gift card Yes. That he handed out everywhere. That was actually my first impression of thatNader: one.Yeah,swyx: yeah, yeah.Nader: Yeah.swyx: I think I still have one of them.Nader: They look great.Kyle: Yeah.Nader: I have a ton of them still actually in our garage, which just, they don't have labels. We should honestly like bring, bring them back. But, um, I found this old printing press here, actually just around the corner on Ven ness. And it's a third generation San Francisco shop.And so I come in an excited startup founder trying to like, and they just have this crazy old machinery and I'm in awe. ‘cause the the whole building is so physical. Like you're seeing these machines, they have like pedals to like move these saws and whatever. I don't know what this machinery is, but I saw all three generations.Like there's like the grandpa, the father and the son, and the son was like, around my age. Well,swyx: it's like a holy, holy trinity.Nader: It's funny because we, so I just took the same SVG and we just like printed it and it's foil printing, so they make a a, a mold. That's like an inverse of like the A 100 and then they put the foil on it [00:06:00] and then they press it into the paper.And I remember once we got them, he was like, Hey, don't forget about us. You know, I guess like early Apple and Cisco's first business cards were all made there. And so he was like, yeah, we, we get like the startup businesses but then as they mature, they kind of go somewhere else. And so I actually, I think we were talking with marketing about like using them for some, we should go back and make some cards.swyx: Yeah, yeah, yeah. You know, I remember, you know, as a very, very small breadth investor, I was like, why are we spending time like, doing these like stunts for GPUs? Like, you know, I think like as a, you know, typical like cloud hard hardware person, you go into an AWS you pick like T five X xl, whatever, and it's just like from a list and you look at the specs like, why animate this GP?And, and I, I do think like it just shows the level of care that goes throughout birth and Yeah. And now, and also the, and,Nader: and Nvidia. I think that's what the, the thing that struck me most when we first came in was like the amount of passion that everyone has. Like, I think, um, you know, you talk to, you talk to Kyle, you talk to, like, every VP that I've met at Nvidia goes so close to the metal.Like, I remember it was almost a year ago, and like my VP asked me, he's like, Hey, [00:07:00] what's cursor? And like, are you using it? And if so, why? Surprised at this, and he downloaded Cursor and he was asking me to help him like, use it. And I thought that was, uh, or like, just show him what he, you know, why we were using it.And so, the amount of care that I think everyone has and the passion, appreciate, passion and appreciation for the moment. Right. This is a very unique time. So it's really cool to see everyone really like, uh, appreciate that.swyx: Yeah.Acquisition and DevEx Shiftswyx: One thing I wanted to do before we move over to sort of like research topics and, uh, the, the stuff that Kyle's working on is just tell the story of the acquisition, right?Like, not many people have been, been through an acquisition with Nvidia. What's it like? Uh, what, yeah, just anything you'd like to say.Nader: It's a crazy experience. I think, uh, you know, we were the thing that was the most exciting for us was. Our goal was just to make it easier for developers.We wanted to find access to GPUs, make it easier to do that. And then all, oh, actually your question about launchable. So launchable was just make one click exper, like one click deploys for any software on top of the GPU. Mm-hmm. And so what we really liked about Nvidia was that it felt like we just got a lot more resources to do all of that.I think, uh, you [00:08:00] know, NVIDIA's goal is to make things as easy for developers as possible. So there was a really nice like synergy there. I think that, you know, when it comes to like an acquisition, I think the amount that the soul of the products align, I think is gonna be. Is going speak to the success of the acquisition.Yeah. And so it in many ways feels like we're home. This is a really great outcome for us. Like we you know, I love brev.nvidia.com. Like you should, you should use it's, it's theKyle: front page for GPUs.Nader: Yeah. Yeah. If you want GP views,Kyle: you go there, getswyx: it there, and it's like internally is growing very quickly.I, I don't remember You said some stats there.Nader: Yeah, yeah, yeah. It's, uh, I, I wish I had the exact numbers, but like internally, externally, it's been growing really quickly. We've been working with a bunch of partners with a bunch of different customers and ISVs, if you have a solution that you want someone that runs on the GPU and you want people to use it quickly, we can bundle it up, uh, in a launchable and make it a one click run.If you're doing things and you want just like a sandbox or something to run on, right. Like open claw. Huge moment. Super exciting. Our, uh, and we'll talk into it more, but. You know, internally, people wanna run this, and you, we know we have to be really careful from the security implications. Do we let this run on the corporate network?Security's guidance was, Hey, [00:09:00] run this on breath, it's in, you know, it's, it's, it's a vm, it's sitting in the cloud, it's off the corporate network. It's isolated. And so that's been our stance internally and externally about how to even run something like open call while we figure out how to run these things securely.But yeah,swyx: I think there's also like, you almost like we're the right team at the right time when Nvidia is starting to invest a lot more in developer experience or whatever you call it. Yeah. Uh, UX or I don't know what you call it, like software. Like obviously NVIDIA is always invested in software, but like, there's like, this is like a different audience.Yeah. It's aNader: widerKyle: developer base.swyx: Yeah. Right.Nader: Yeah. Yeah. You know, it's funny, it's like, it's not, uh,swyx: so like, what, what is it called internally? What, what is this that people should be aware that is going on there?Nader: Uh, what, like developer experienceswyx: or, yeah, yeah. Is it's called just developer experience or is there like a broader strategy hereNader: in Nvidia?Um, Nvidia always wants to make a good developer experience. The thing is and a lot of the technology is just really complicated. Like, it's not, it's uh, you know, I think, um. The thing that's been really growing or the AI's growing is having a huge moment, not [00:10:00] because like, let's say data scientists in 2018, were quiet then and are much louder now.The pie is com, right? There's a whole bunch of new audiences. My mom's wondering what she's doing. My sister's learned, like taught herself how to code. Like the, um, you know, I, I actually think just generally AI's a big equalizer and you're seeing a more like technologically literate society, I guess.Like everyone's, everyone's learning how to code. Uh, there isn't really an excuse for that. And so building a good UX means that you really understand who your end user is. And when your end user becomes such a wide, uh, variety of people, then you have to almost like reinvent the practice, right? Yeah. You haveKyle: to, and actually build more developer ux, right?Because the, there are tiers of developer base that were added. You know, the, the hackers that are building on top of open claw, right? For example, have never used gpu. They don't know what kuda is. They, they, they just want to run something.Nader: Yeah.Kyle: You need new UX that is not just. Hey, you know, how do you program something in Cuda and run it?And then, and then we built, you know, like when Deep Learning was getting big, we built, we built Torch and, and, but so recently the amount of like [00:11:00] layers that are added to that developer stack has just exploded because AI has become ubiquitous. Everyone's using it in different ways. Yeah. It'sNader: moving fast in every direction.Vertical, horizontal.Vibhu: Yeah. You guys, you even take it down to hardware, like the DGX Spark, you know, it's, it's basically the same system as just throwing it up on big GPU cluster.Nader: Yeah, yeah, yeah. It's amazing. Blackwell.swyx: Yeah. Uh, we saw the preview at the last year's GTC and that was one of the better performing, uh, videos so far, and video coverage so far.Awesome. This will beat it. Um,Nader: that wasswyx: actually, we have fingersNader: crossed. Yeah.DGX Spark and Remote AccessNader: Even when Grace Blackwell or when, um, uh, DGX Spark was first coming out getting to be involved in that from the beginning of the developer experience. And it just comes back to what youswyx: were involved.Nader: Yeah. St. St.swyx: Mars.Nader: Yeah. Yeah. I mean from, it was just like, I, I got an email, we just got thrown into the loop and suddenly yeah, I, it was actually really funny ‘cause I'm still pretty fresh from the acquisition and I'm, I'm getting an email from a bunch of the engineering VPs about like, the new hardware, GPU chip, like we're, or not chip, but just GPU system that we're putting out.And I'm like, okay, cool. Matters. Now involved with this for the ux, I'm like. What am I gonna do [00:12:00] here? So, I remember the first meeting, I was just like kind of quiet as I was hearing engineering VPs talk about what this box could be, what it could do, how we should use it. And I remember, uh, one of the first ideas that people were idea was like, oh, the first thing that it was like, I think a quote was like, the first thing someone's gonna wanna do with this is get two of them and run a Kubernetes cluster on top of them.And I was like, oh, I think I know why I'm here. I was like, the first thing we're doing is easy. SSH into the machine. And then, and you know, just kind of like scoping it down of like, once you can do that every, you, like the person who wants to run a Kubernetes cluster onto Sparks has a higher propensity for pain, then, then you know someone who buys it and wants to run open Claw right now, right?If you can make sure that that's as effortless as possible, then the rest becomes easy. So there's a tool called Nvidia Sync. It just makes the SSH connection really simple. So, you know, if you think about it like. If you have a Mac, uh, or a PC or whatever, if you have a laptop and you buy this GPU and you want to use it, you should be able to use it like it's A-A-G-P-U in the cloud, right?Um, but there's all this friction of like, how do you actually get into that? That's part of [00:13:00] Revs value proposition is just, you know, there's a CLI that wraps SSH and makes it simple. And so our goal is just get you into that machine really easily. And one thing we just launched at CES, it's in, it's still in like early access.We're ironing out some kinks, but it should be ready by GTC. You can register your spark on Brev. And so now if youswyx: like remote managed yeah, local hardware. Single pane of glass. Yeah. Yeah. Because Brev can already manage other clouds anyway, right?Vibhu: Yeah, yeah. And you use the spark on Brev as well, right?Nader: Yeah. But yeah, exactly. So, so you, you, so you, you set it up at home you can run the command on it, and then it gets it's essentially it'll appear in your Brev account, and then you can take your laptop to a Starbucks or to a cafe, and you'll continue to use your, you can continue use your spark just like any other cloud node on Brev.Yeah. Yeah. And it's just like a pre-provisioned centerswyx: in yourNader: home. Yeah, exactly.swyx: Yeah. Yeah.Vibhu: Tiny little data center.Nader: Tiny little, the size ofVibhu: your phone.SOL Culture and Dynamo Setupswyx: One more thing before we move on to Kyle. Just have so many Jensen stories and I just love, love mining Jensen stories. Uh, my favorite so far is SOL. Uh, what is, yeah, what is S-O-L-S-O-LNader: is actually, i, I think [00:14:00] of all the lessons I've learned, that one's definitely my favorite.Kyle: It'll always stick with you.Nader: Yeah. Yeah. I, you know, in your startup, everything's existential, right? Like we've, we've run out of money. We were like, on the risk of, of losing payroll, we've had to contract our team because we l ran outta money. And so like, um, because of that you're really always forcing yourself to I to like understand the root cause of everything.If you get a date, if you get a timeline, you know exactly why that date or timeline is there. You're, you're pushing every boundary and like, you're not just say, you're not just accepting like a, a no. Just because. And so as you start to introduce more layers, as you start to become a much larger organization, SOL is is essentially like what is the physics, right?The speed of light moves at a certain speed. So if flight's moving some slower, then you know something's in the way. So before trying to like layer reality back in of like, why can't this be delivered at some date? Let's just understand the physics. What is the theoretical limit to like, uh, how fast this can go?And then start to tell me why. ‘cause otherwise people will start telling you why something can't be done. But actually I think any great leader's goal is just to create urgency. Yeah. [00:15:00] There's an infiniteKyle: create compelling events, right?Nader: Yeah.Kyle: Yeah. So l is a term video is used to instigate a compelling event.You say this is done. How do we get there? What is the minimum? As much as necessary, as little as possible thing that it takes for us to get exactly here and. It helps you just break through a bunch of noise.swyx: Yeah.Kyle: Instantly.swyx: One thing I'm unclear about is, can only Jensen use the SOL card? Like, oh, no, no, no.Not everyone get the b******t out because obviously it's Jensen, but like, can someone else be like, no, likeKyle: frontline engineers use it.Nader: Yeah. Every, I think it's not so much about like, get the b******t out. It's like, it's like, give me the root understanding, right? Like, if you tell me something takes three weeks, it like, well, what's the first principles?Yeah, the first principles. It's like, what's the, what? Like why is it three weeks? What is the actual yeah. What's the actual limit of why this is gonna take three weeks? If you're gonna, if you, if let's say you wanted to buy a new computer and someone told you it's gonna be here in five days, what's the SOL?Well, like the SOL is like, I could walk into a Best Buy and pick it up for you. Right? So then anything that's like beyond that is, and is that practical? Is that how we're gonna, you know, let's say give everyone in the [00:16:00] company a laptop, like obviously not. So then like that's the SOL and then it's like, okay, well if we have to get more than 10, suddenly there might be some, right?And so now we can kind of piece the reality back.swyx: So, so this is the. Paul Graham do things that don't scale. Yeah. And this is also the, what people would now call behi agency. Yeah.Kyle: It's actually really interesting because there's a, there's a second hardware angle to SOL that like doesn't come up for all the org sol is used like culturally at aswyx: media for everything.I'm also mining for like, I think that can be annoying sometimes. And like someone keeps going IOO you and you're like, guys, like we have to be stable. We have to, we to f*****g plan. Yeah.Kyle: It's an interesting balance.Nader: Yeah. I encounter that with like, actually just with, with Alec, right? ‘cause we, we have a new conference so we need to launch, we have, we have goals of what we wanna launch by, uh, by the conference and like, yeah.At the end of the day, where isswyx: this GTC?Nader: Um, well this is like, so we, I mean we did it for CES, we did for GT CDC before that we're doing it for GTC San Jose. So I mean, like every, you know, we have a new moment. Um, and we want to launch something. Yeah. And we want to do so at SOL and that does mean that some, there's some level of prioritization that needs [00:17:00] to happen.And so it, it is difficult, right? I think, um, you have to be careful with what you're pushing. You know, stability is important and that should be factored into S-O-L-S-O-L isn't just like, build everything and let it break, you know, that, that's part of the conversation. So as you're laying, layering in all the details, one of them might be, Hey, we could build this, but then it's not gonna be stable for X, y, z reasons.And so that was like, one of our conversations for CES was, you know, hey, like we, we can get this into early access registering your spark with brev. But there are a lot of things that we need to do in order to feel really comfortable from a security perspective, right? There's a lot of networking involved before we deliver that to users.So it's like, okay. Let's get this to a point where we can at least let people experiment with it. We had it in a booth, we had it in Jensen's keynote, and then let's go iron out all the networking kinks. And that's not easy. And so, uh, that can come later. And so that was the way that we layered that back in.Yeah. ButKyle: It's not really about saying like, you don't have to do the, the maintenance or operational work. It's more about saying, you know, it's kind of like [00:18:00] highlights how progress is incremental, right? Like, what is the minimum thing that we can get to. And then there's SOL for like every component after that.But there's the SOL to get you, get you to the, the starting line. And that, that's usually how it's asked. Yeah. On the other side, you know, like SOL came out of like hardware at Nvidia. Right. So SOL is like literally if we ran the accelerator or the GPU with like at basically full speed with like no other constraints, like how FAST would be able to make a program go.swyx: Yeah. Yeah. Right.Kyle: Soswyx: in, in training that like, you know, then you work back to like some percentage of like MFU for example.Kyle: Yeah, that's a, that's a great example. So like, there's an, there's an S-O-L-M-F-U, and then there's like, you know, what's practically achievable.swyx: Cool. Should we move on to sort of, uh, Kyle's side?Uh, Kyle, you're coming more from the data science world. And, uh, I, I mean I always, whenever, whenever I meet someone who's done working in tabular stuff, graph neural networks, time series, these are basically when I go to new reps, I go to ICML, I walk the back halls. There's always like a small group of graph people.Yes. Absolute small group of tabular people. [00:19:00] And like, there's no one there. And like, it's very like, you know what I mean? Like, yeah, no, like it's, it's important interesting work if you care about solving the problems that they solve.Kyle: Yeah.swyx: But everyone else is just LMS all the time.Kyle: Yeah. I mean it's like, it's like the black hole, right?Has the event horizon reached this yet in nerves? Um,swyx: but like, you know, those are, those are transformers too. Yeah. And, and those are also like interesting things. Anyway, uh, I just wanted to spend a little bit of time on, on those, that background before we go into Dynamo, uh, proper.Kyle: Yeah, sure. I took a different path to Nvidia than that, or I joined six years ago, seven, if you count, when I was an intern.So I joined Nvidia, like right outta college. And the first thing I jumped into was not what I'd done in, during internship, which was like, you know, like some stuff for autonomous vehicles, like heavyweight object detection. I jumped into like, you know, something, I'm like, recommenders, this is popular. Andswyx: yeah, he did RexiKyle: as well.Yeah, Rexi. Yeah. I mean that, that was the taboo data at the time, right? You have tables of like, audience qualities and item qualities, and you're trying to figure out like which member of [00:20:00] the audience matches which item or, or more practically which item matches which member of the audience. And at the time, really it was like we were trying to enable.Uh, recommender, which had historically been like a little bit of a CP based workflow into something that like, ran really well in GPUs. And it's since been done. Like there are a bunch of libraries for Axis that run on GPUs. Uh, the common models like Deeplearning recommendation model, which came outta meta and the wide and deep model, which was used or was released by Google were very accelerated by GPUs using, you know, the fast HBM on the chips, especially to do, you know, vector lookups.But it was very interesting at the time and super, super relevant because like we were starting to get like. This explosion of feeds and things that required rec recommenders to just actively be on all the time. And sort of transitioned that a little bit towards graph neural networks when I discovered them because I was like, okay, you can actually use graphical neural networks to represent like, relationships between people, items, concepts, and that, that interested me.So I jumped into that at [00:21:00] Nvidia and, and got really involved for like two-ish years.swyx: Yeah. Uh, and something I learned from Brian Zaro Yeah. Is that you can just kind of choose your own path in Nvidia.Kyle: Oh my God. Yeah.swyx: Which is not a normal big Corp thing. Yeah. Like you, you have a lane, you stay in your lane.Nader: I think probably the reason why I enjoy being in a, a big company, the mission is the boss probably from a startup guy. Yeah. The missionswyx: is the boss.Nader: Yeah. Uh, it feels like a big game of pickup basketball. Like, you know, if you play one, if you wanna play basketball, you just go up to the court and you're like, Hey look, we're gonna play this game and we need three.Yeah. And you just like find your three. That's honestly for every new initiative that's what it feels like. Yeah.Vibhu: It also like shows, right? Like Nvidia. Just releasing state-of-the-art stuff in every domain. Yeah. Like, okay, you expect foundation models with Nemo tron voice just randomly parakeet.Call parakeet just comes out another one, uh, voice. TheKyle: video voice team has always been producing.Vibhu: Yeah. There's always just every other domain of paper that comes out, dataset that comes out. It's like, I mean, it also stems back to what Nvidia has to do, right? You have to make chips years before they're actually produced.Right? So you need to know, you need to really [00:22:00] focus. TheKyle: design process starts likeVibhu: exactlyKyle: three to five years before the chip gets to the market.Vibhu: Yeah. I, I'm curious more about what that's like, right? So like, you have specialist teams. Is it just like, you know, people find an interest, you go in, you go deep on whatever, and that kind of feeds back into, you know, okay, we, we expect predictions.Like the internals at Nvidia must be crazy. Right? You know? Yeah. Yeah. You know, you, you must. Not even without selling to people, you have your own predictions of where things are going. Yeah. And they're very based, very grounded. Right?Kyle: Yeah. It, it, it's really interesting. So there's like two things that I think that Amed does, which are quite interesting.Uh, one is like, we really index into passion. There's a big. Sort of organizational top sound push to like ensure that people are working on the things that they're passionate about. So if someone proposes something that's interesting, many times they can just email someone like way up the chain that they would find this relevant and say like, Hey, can I go work on this?Nader: It's actually like I worked at a, a big company for a couple years before, uh, starting on my startup journey and like, it felt very weird if you were to like email out of chain, if that makes [00:23:00] sense. Yeah. The emails at Nvidia are like mosh pitsswyx: shoot,Nader: and it's just like 60 people, just whatever. And like they're, there's this,swyx: they got messy like, reply all you,Nader: oh, it's in, it's insane.It's insane. They justKyle: help. You know, Maxim,Nader: the context. But, but that's actually like, I've actually, so this is a weird thing where I used to be like, why would we send emails? We have Slack. I am the entire, I'm the exact opposite. I feel so bad for anyone who's like messaging me on Slack ‘cause I'm so unresponsive.swyx: Your emailNader: Maxi, email Maxim. I'm email maxing Now email is a different, email is perfect because man, we can't work together. I'm email is great, right? Because important threads get bumped back up, right? Yeah, yeah. Um, and so Slack doesn't do that. So I just have like this casino going off on the right or on the left and like, I don't know which thread was from where or what, but like the threads get And then also just like the subject, so you can have like working threads.I think what's difficult is like when you're small, if you're just not 40,000 people I think Slack will work fine, but there's, I don't know what the inflection point is. There is gonna be a point where that becomes really messy and you'll actually prefer having email. ‘cause you can have working threads.You can cc more than nine people in a thread.Kyle: You can fork stuff.Nader: You can [00:24:00] fork stuff, which is super nice and just like y Yeah. And so, but that is part of where you can propose a plan. You can also just. Start, honestly, momentum's the only authority, right? So like, if you can just start, start to make a little bit of progress and show someone something, and then they can try it.That's, I think what's been, you know, I think the most effective way to push anything for forward. And that's both at Nvidia and I think just generally.Kyle: Yeah, there's, there's the other concept that like is explored a lot at Nvidia, which is this idea of a zero billion dollar business. Like market creation is a big thing at Nvidia.Like,swyx: oh, you want to go and start a zero billion dollar business?Kyle: Jensen says, we are completely happy investing in zero billion dollar markets. We don't care if this creates revenue. It's important for us to know about this market. We think it will be important in the future. It can be zero billion dollars for a while.I'm probably minging as words here for, but like, you know, like, I'll give an example. NVIDIA's been working on autonomous driving for a a long time,swyx: like an Nvidia car.Kyle: No, they, they'veVibhu: used the Mercedes, right? They're around the HQ and I think it finally just got licensed out. Now they're starting to be used quite a [00:25:00] bit.For 10 years you've been seeing Mercedes with Nvidia logos driving.Kyle: If you're in like the South San Santa Clara, it's, it's actually from South. Yeah. So, um. Zero billion dollar markets are, are a thing like, you know, Jensen,swyx: I mean, okay, look, cars are not a zero billion dollar market. But yeah, that's a bad example.Nader: I think, I think he's, he's messaging, uh, zero today, but, or even like internally, right? Like, like it's like, uh, an org doesn't have to ruthlessly find revenue very quickly to justify their existence. Right. Like a lot of the important research, a lot of the important technology being developed that, that's kind ofKyle: where research, research is very ide ideologically free at Nvidia.Yeah. Like they can pursue things that they wereswyx: Were you research officially?Kyle: I was never in research. Officially. I was always in engineering. Yeah. We in, I'm in an org called Deep Warning Algorithms, which is basically just how do we make things that are relevant to deep warning go fast.swyx: That sounds freaking cool.Vibhu: And I think a lot of that is underappreciated, right? Like time series. This week Google put out time. FF paper. Yeah. A new time series, paper res. Uh, Symantec, ID [00:26:00] started applying Transformers LMS to Yes. Rec system. Yes. And when you think the scale of companies deploying these right. Amazon recommendations, Google web search, it's like, it's huge scale andKyle: Yeah.Vibhu: You want fast?Kyle: Yeah. Yeah. Yeah. Actually it's, it, I, there's a fun moment that brought me like full circle. Like, uh, Amazon Ads recently gave a talk where they talked about using Dynamo for generative recommendation, which was like super, like weirdly cathartic for me. I'm like, oh my God. I've, I've supplanted what I was working on.Like, I, you're using LMS now to do what I was doing five years ago.swyx: Yeah. Amazing. And let's go right into Dynamo. Uh, maybe introduce Yeah, sure. To the top down and Yeah.Kyle: I think at this point a lot of people are familiar with the term of inference. Like funnily enough, like I went from, you know, inference being like a really niche topic to being something that's like discussed on like normal people's Twitter feeds.It's,Nader: it's on billboardsKyle: here now. Yeah. Very, very strange. Driving, driving, seeing just an inference ad on 1 0 1 inference at scale is becoming a lot more important. Uh, we have these moments like, you know, open claw where you have these [00:27:00] agents that take lots and lots of tokens, but produce, incredible results.There are many different aspects of test time scaling so that, you know, you can use more inference to generate a better result than if you were to use like a short amount of inference. There's reasoning, there's quiring, there's, adding agency to the model, allowing it to call tools and use skills.Dyno sort came about at Nvidia. Because myself and a couple others were, were sort of talking about the, these concepts that like, you know, you have inference engines like VLMS, shelan, tenor, TLM and they have like one single copy. They, they, they sort of think about like things as like one single copy, like one replica, right?Why Scale Out WinsKyle: Like one version of the model. But when you're actually serving things at scale, you can't just scale up that replica because you end up with like performance problems. There's a scaling limit to scaling up replicas. So you actually have to scale out to use a, maybe some Kubernetes type terminology.We kind of realized that there was like. A lot of potential optimization that we could do in scaling out and building systems for data [00:28:00] center scale inference. So Dynamo is this data center scale inference engine that sits on top of the frameworks like VLM Shilling and 10 T lm and just makes things go faster because you can leverage the economy of scale.The fact that you have KV cash, which we can define a little bit later, uh, in all these machines that is like unique and you wanna figure out like the ways to maximize your cash hits or you want to employ new techniques in inference like disaggregation, which Dynamo had introduced to the world in, in, in March, not introduced, it was a academic talk, but beforehand.But we are, you know, one of the first frameworks to start, supporting it. And we wanna like, sort of combine all these techniques into sort of a modular framework that allows you to. Accelerate your inference at scale.Nader: By the way, Kyle and I became friends on my first date, Nvidia, and I always loved, ‘cause like he always teaches meswyx: new things.Yeah. By the way, this is why I wanted to put two of you together. I was like, yeah, this is, this is gonna beKyle: good. It's very, it's very different, you know, like we've, we, we've, we've talked to each other a bunch [00:29:00] actually, you asked like, why, why can't we scale up?Nader: Yeah.Scale Up Limits ExplainedNader: model, you said model replicas.Kyle: Yeah. So you, so scale up means assigning moreswyx: heavier?Kyle: Yeah, heavier. Like making things heavier. Yeah, adding more GPUs. Adding more CPUs. Scale out is just like having a barrier saying, I'm gonna duplicate my representation of the model or a representation of this microservice or something, and I'm gonna like, replicate it Many times.Handle, load. And the reason that you can't scale, scale up, uh, past some points is like, you know, there, there, there are sort of hardware bounds and algorithmic bounds on, on that type of scaling. So I'll give you a good example that's like very trivial. Let's say you're on an H 100. The Maxim ENV link domain for H 100, for most Ds H one hundreds is heus, right?So if you scaled up past that, you're gonna have to figure out ways to handle the fact that now for the GPUs to communicate, you have to do it over Infin band, which is still very fast, but is not as fast as ENV link.swyx: Is it like one order of magnitude, like hundreds or,Kyle: it's about an order of magnitude?Yeah. Okay. Um, soswyx: not terrible.Kyle: [00:30:00] Yeah. I, I need to, I need to remember the, the data sheet here, like, I think it's like about 500 gigabytes. Uh, a second unidirectional for ENV link, and about 50 gigabytes a second unidirectional for Infin Band. I, it, it depends on the, the generation.swyx: I just wanna set this up for people who are not familiar with these kinds of like layers and the trash speedVibhu: and all that.Of course.From Laptop to Multi NodeVibhu: Also, maybe even just going like a few steps back before that, like most people are very familiar with. You see a, you know, you can use on your laptop, whatever these steel viol, lm you can just run inference there. All, there's all, you can, youcan run it on thatVibhu: laptop. You can run on laptop.Then you get to, okay, uh, models got pretty big, right? JLM five, they doubled the size, so mm-hmm. Uh, what do you do when you have to go from, okay, I can get 128 gigs of memory. I can run it on a spark. Then you have to go multi GPU. Yeah. Okay. Multi GPU, there's some support there. Now, if I'm a company and I don't have like.I'm not hiring the best researchers for this. Right. But I need to go [00:31:00] multi-node, right? I have a lot of servers. Okay, now there's efficiency problems, right? You can have multiple eight H 100 nodes, but, you know, is that as a, like, how do you do that efficiently?Kyle: Yeah. How do you like represent them? How do you choose how to represent the model?Yeah, exactly right. That's a, that's like a hard question. Everyone asks, how do you size oh, I wanna run GLM five, which just came out new model. There have been like four of them in the past week, by the way, like a bunch of new models.swyx: You know why? Right? Deep seek.Kyle: No comment. Oh. Yeah, but Ggl, LM five, right?We, we have this, new model. It's, it's like a large size, and you have to figure out how to both scale up and scale out, right? Because you have to find the right representation that you care about. Everyone does this differently. Let's be very clear. Everyone figures this out in their own path.Nader: I feel like a lot of AI or ML even is like, is like this. I think people think, you know, I, I was, there was some tweet a few months ago that was like, why hasn't fine tuning as a service taken off? You know, that might be me. It might have been you. Yeah. But people want it to be such an easy recipe to follow.But even like if you look at an ML model and specificKyle: to you Yeah,Nader: yeah.Kyle: And the [00:32:00] model,Nader: the situation, and there's just so much tinkering, right? Like when you see a model that has however many experts in the ME model, it's like, why that many experts? I don't, they, you know, they tried a bunch of things and that one seemed to do better.I think when it comes to how you're serving inference, you know, you have a bunch of decisions to make and there you can always argue that you can take something and make it more optimal. But I think it's this internal calibration and appetite for continued calibration.Vibhu: Yeah. And that doesn't mean like, you know, people aren't taking a shot at this, like tinker from thinking machines, you know?Yeah. RL as a service. Yeah, totally. It's, it also gets even harder when you try to do big model training, right? We're not the best at training Moes, uh, when they're pre-trained. Like we saw this with LAMA three, right? They're trained in such a sparse way that meta knows there's gonna be a bunch of inference done on these, right?They'll open source it, but it's very trained for what meta infrastructure wants, right? They wanna, they wanna inference it a lot. Now the question to basically think about is, okay, say you wanna serve a chat application, a coding copilot, right? You're doing a layer of rl, you're serving a model for X amount of people.Is it a chat model, a coding model? Dynamo, you know, back to that,Kyle: it's [00:33:00] like, yeah, sorry. So you we, we sort of like jumped off of, you know, jumped, uh, on that topic. Everyone has like, their own, own journey.Cost Quality Latency TradeoffsKyle: And I, I like to think of it as defined by like, what is the model you need? What is the accuracy you need?Actually I talked to NA about this earlier. There's three axes you care about. What is the quality that you're able to produce? So like, are you accurate enough or can you complete the task with enough, performance, high enough performance. Yeah, yeah. Uh, there's cost. Can you serve the model or serve your workflow?Because it's not just the model anymore, it's the workflow. It's the multi turn with an agent cheaply enough. And then can you serve it fast enough? And we're seeing all three of these, like, play out, like we saw, we saw new models from OpenAI that you know, are faster. You have like these new fast versions of models.You can change the amount of thinking to change the amount of quality, right? Produce more tokens, but at a higher cost in a, in a higher latency. And really like when you start this journey of like trying to figure out how you wanna host a model, you, you, you think about three things. What is the model I need to serve?How many times do I need to call it? What is the input sequence link was [00:34:00] the, what does the workflow look like on top of it? What is the SLA, what is the latency SLA that I need to achieve? Because there's usually some, this is usually like a constant, you, you know, the SLA that you need to hit and then like you try and find the lowest cost version that hits all of these constraints.Usually, you know, you, you start with those things and you say you, you kind of do like a bit of experimentation across some common configurations. You change the tensor parallel size, which is a form of parallelismVibhu: I take, it goes even deeper first. Gotta think what model.Kyle: Yes, course,ofKyle: course. It's like, it's like a multi-step design process because as you said, you can, you can choose a smaller model and then do more test time scaling and it'll equate the quality of a larger model because you're doing the test time scaling or you're adding a harness or something.So yes, it, it goes way deeper than that. But from the performance perspective, like once you get to the model you need, you need to host, you look at that and you say, Hey. I have this model, I need to serve it at the speed. What is the right configuration for that?Nader: You guys see the recent, uh, there was a paper I just saw like a few days ago that, uh, if you run [00:35:00] the same prompt twice, you're getting like double Just try itagain.Nader: Yeah, exactly.Vibhu: And you get a lot. Yeah. But the, the key thing there is you give the context of the failed try, right? Yeah. So it takes a shot. And this has been like, you know, basic guidance for quite a while. Just try again. ‘cause you know, trying, just try again. Did you try again? All adviceNader: in life.Vibhu: Just, it's a paper from Google, if I'm not mistaken, right?Yeah,Vibhu: yeah. I think it, it's like a seven bas little short paper. Yeah. Yeah. The title's very cute. And it's just like, yeah, just try again. Give it ask context,Kyle: multi-shot. You just like, say like, hey, like, you know, like take, take a little bit more, take a little bit more information, try and fail. Fail.Vibhu: And that basic concept has gone pretty deep.There's like, um, self distillation, rl where you, you do self distillation, you do rl and you have past failure and you know, that gives some signal so people take, try it again. Not strong enough.swyx: Uh, for, for listeners, uh, who listen to here, uh, vivo actually, and I, and we run a second YouTube channel for our paper club where, oh, that's awesome.Vivo just covered this. Yeah. Awesome. Self desolation and all that's, that's why he, to speed [00:36:00] on it.Nader: I'll to check it out.swyx: Yeah. It, it's just a good practice, like everyone needs, like a paper club where like you just read papers together and the social pressure just kind of forces you to just,Nader: we, we,there'sNader: like a big inference.Kyle: ReadingNader: group at a video. I feel so bad every time. I I, he put it on like, on our, he shared it.swyx: One, one ofNader: your guys,swyx: uh, is, is big in that, I forget es han Yeah, yeah,Kyle: es Han's on my team. Actually. Funny. There's a, there's a, there's a employee transfer between us. Han worked for Nater at Brev, and now he, he's on my team.He wasNader: our head of ai. And then, yeah, once we got in, andswyx: because I'm always looking for like, okay, can, can I start at another podcast that only does that thing? Yeah. And, uh, Esan was like, I was trying to like nudge Esan into like, is there something here? I mean, I don't think there's, there's new infant techniques every day.So it's like, it's likeKyle: you would, you would actually be surprised, um, the amount of blog posts you see. And ifswyx: there's a period where it was like, Medusa hydra, what Eagle, like, youKyle: know, now we have new forms of decode, uh, we have new forms of specula, of decoding or new,swyx: what,Kyle: what are youVibhu: excited? And it's exciting when you guys put out something like Tron.‘cause I remember the paper on this Tron three, [00:37:00] uh, the amount of like post train, the on tokens that the GPU rich can just train on. And it, it was a hybrid state space model, right? Yeah.Kyle: It's co-designed for the hardware.Vibhu: Yeah, go design for the hardware. And one of the things was always, you know, the state space models don't scale as well when you do a conversion or whatever the performance.And you guys are like, no, just keep draining. And Nitron shows a lot of that. Yeah.Nader: Also, something cool about Nitron it was released in layers, if you will, very similar to Dynamo. It's, it's, it's essentially it was released as you can, the pre-training, post-training data sets are released. Yeah. The recipes on how to do it are released.The model itself is released. It's full model. You just benefit from us turning on the GPUs. But there are companies like, uh, ServiceNow took the dataset and they trained their own model and we were super excited and like, you know, celebrated that work.ZoomVibhu: different. Zoom is, zoom is CGI, I think, uh, you know, also just to add like a lot of models don't put out based models and if there's that, why is fine tuning not taken off?You know, you can do your own training. Yeah,Kyle: sure.Vibhu: You guys put out based model, I think you put out everything.Nader: I believe I know [00:38:00]swyx: about base. BasicallyVibhu: without baseswyx: basic can be cancelable.Vibhu: Yeah. Base can be cancelable.swyx: Yeah.Vibhu: Safety training.swyx: Did we get a full picture of dymo? I, I don't know if we, what,Nader: what I'd love is you, you mentioned the three axes like break it down of like, you know, what's prefilled decode and like what are the optimizations that we can get with Dynamo?Kyle: Yeah. That, that's, that's, that's a great point. So to summarize on that three axis problem, right, there are three things that determine whether or not something can be done with inference, cost, quality, latency, right? Dynamo is supposed to be there to provide you like the runtime that allows you to pull levers to, you know, mix it up and move around the parade of frontier or the preto surface that determines is this actually possible with inference And AI todayNader: gives you the knobs.Kyle: Yeah, exactly. It gives you the knobs.Disaggregation Prefill vs DecodeKyle: Uh, and one thing that like we, we use a lot in contemporary inference and is, you know, starting to like pick up from, you know, in, in general knowledge is this co concept of disaggregation. So historically. Models would be hosted with a single inference engine. And that inference engine [00:39:00] would ping pong between two phases.There's prefill where you're reading the sequence generating KV cache, which is basically just a set of vectors that represent the sequence. And then using that KV cache to generate new tokens, which is called Decode. And some brilliant researchers across multiple different papers essentially made the realization that if you separate these two phases, you actually gain some benefits.Those benefits are basically a you don't have to worry about step synchronous scheduling. So the way that an inference engine works is you do one step and then you finish it, and then you schedule, you start scheduling the next step there. It's not like fully asynchronous. And the problem with that is you would have, uh, essentially pre-fill and decode are, are actually very different in terms of both their resource requirements and their sometimes their runtime.So you would have like prefill that would like block decode steps because you, you'd still be pre-filing and you couldn't schedule because you know the step has to end. So you remove that scheduling issue and then you also allow you, or you yourself, to like [00:40:00] split the work into two different ki types of pools.So pre-fill typically, and, and this changes as, as model architecture changes. Pre-fill is, right now, compute bound most of the time with the sequence is sufficiently long. It's compute bound. On the decode side because you're doing a full Passover, all the weights and the entire sequence, every time you do a decode step and you're, you don't have the quadratic computation of KV cache, it's usually memory bound because you're retrieving a linear amount of memory and you're doing a linear amount of compute as opposed to prefill where you retrieve a linear amount of memory and then use a quadratic.You know,Nader: it's funny, someone exo Labs did a really cool demo where for the DGX Spark, which has a lot more compute, you can do the pre the compute hungry prefill on a DG X spark and then do the decode on a, on a Mac. Yeah. And soVibhu: that's faster.Nader: Yeah. Yeah.Kyle: So you could, you can do that. You can do machine strat stratification.Nader: Yeah.Kyle: And like with our future generation generations of hardware, we actually announced, like with Reuben, this [00:41:00] new accelerator that is prefilled specific. It's called Reuben, CPX. SoKubernetes Scaling with GroveNader: I have a question when you do the scale out. Yeah. Is scaling out easier with Dynamo? Because when you need a new node, you can dedicate it to either the Prefill or, uh, decode.Kyle: Yeah. So Dynamo actually has like a, a Kubernetes component in it called Grove that allows you to, to do this like crazy scaling specialization. It has like this hot, it's a representation that, I don't wanna go too deep into Kubernetes here, but there was a previous way that you would like launch multi-node work.Uh, it's called Leader Worker Set. It's in the Kubernetes standard, and Leader worker set is great. It served a lot of people super well for a long period of time. But one of the things that it's struggles with is representing a set of cases where you have a multi-node replica that has a pair, right?You know, prefill and decode, or it's not paired, but it has like a second stage that has a ratio that changes over time. And prefill and decode are like two different things as your workload changes, right? The amount of prefill you'll need to do may change. [00:42:00] The amount of decode that you, you'll need to do might change, right?Like, let's say you start getting like insanely long queries, right? That probably means that your prefill scales like harder because you're hitting these, this quadratic scaling growth.swyx: Yeah.And then for listeners, like prefill will be long input. Decode would be long output, for example, right?Kyle: Yeah. So like decode, decode scale. I mean, decode is funny because the amount of tokens that you produce scales with the output length, but the amount of work that you do per step scales with the amount of tokens in the context.swyx: Yes.Kyle: So both scales with the input and the output.swyx: That's true.Kyle: But on the pre-fold view code side, like if.Suddenly, like the amount of work you're doing on the decode side stays about the same or like scales a little bit, and then the prefilled side like jumps up a lot. You actually don't want that ratio to be the same. You want it to change over time. So Dynamo has a set of components that A, tell you how to scale.It tells you how many prefilled workers and decoded workers you, it thinks you should have, and also provides a scheduling API for Kubernetes that allows you to actually represent and affect this scheduling on, on, on your actual [00:43:00] hardware, on your compute infrastructure.Nader: Not gonna lie. I feel a little embarrassed for being proud of my SVG function earlier.swyx: No, itNader: wasreallyKyle: cute. I, Iswyx: likeNader: it's all,swyx: it's all engineering. It's all engineering. Um, that's where I'mKyle: technical.swyx: One thing I'm, I'm kind of just curious about with all with you see at a systems level, everything going on here. Mm-hmm. And we, you know, we're scaling it up in, in multi, in distributed systems.Context Length and Co Designswyx: Um, I think one thing that's like kind of, of the moment right now is people are asking, is there any SOL sort of upper bounds. In terms of like, let's call, just call it context length for one for of a better word, but you can break it down however you like.Nader: Yeah.swyx: I just think like, well, yeah, I mean, like clearly you can engage in hybrid architectures and throw in some state space models in there.All, all you want, but it looks, still looks very attention heavy.Kyle: Yes. Uh, yeah. Long context is attention heavy. I mean, we have these hybrid models, um,swyx: to take and most, most models like cap out at a million contexts and that's it. Yeah. Like for the last two years has been it.Kyle: Yeah. The model hardware context co-design thing that we're seeing these days is actually super [00:44:00] interesting.It's like my, my passion, like my secret side passion. We see models like Kimmy or G-P-T-O-S-S. I'm use these because I, I know specific things about these models. So Kimmy two comes out, right? And it's an interesting model. It's like, like a deep seek style architecture is MLA. It's basically deep seek, scaled like a little bit differently, um, and obviously trained differently as well.But they, they talked about, why they made the design choices for context. Kimmy has more experts, but fewer attention heads, and I believe a slightly smaller attention, uh, like dimension. But I need to remember, I need to check that. Uh, it doesn't matter. But they discussed this actually at length in a blog post on ji, which is like our pu which is like credit puswyx: Yeah.Kyle: Um, in, in China. Chinese red.swyx: Yeah.Kyle: It's, yeah. So it, it's, it's actually an incredible blog post. Uh, like all the mls people in, in, in that, I've seen that on GPU are like very brilliant, but they, they talk about like the creators of Kimi K two [00:45:00] actually like, talked about it on, on, on there in the blog post.And they say, we, we actually did an experiment, right? Attention scales with the number of heads, obviously. Like if you have 64 heads versus 32 heads, you do half the work of attention. You still scale quadratic, but you do half the work. And they made a, a very specific like. Sort of barter in their system, in their architecture, they basically said, Hey, what if we gave it more experts, so we're gonna use more memory capacity.But we keep the amount of activated experts the same. We increase the expert sparsity, so we have fewer experts act. The ratio to of experts activated to number of experts is smaller, and we decrease the number of attention heads.Vibhu: And kind of for context, what the, what we had been seeing was you make models sparser instead.So no one was really touching heads. You're just having, uh,Kyle: well, they, they did, they implicitly made it sparser.Vibhu: Yeah, yeah. For, for Kimmy. They did,Kyle: yes.Vibhu: They also made it sparser. But basically what we were seeing was people were at the level of, okay, there's a sparsity ratio. You want more total parameters, less active, and that's sparsity.[00:46:00]But what you see from papers, like, the labs like moonshot deep seek, they go to the level of, okay, outside of just number of experts, you can also change how many attention heads and less attention layers. More attention. Layers. Layers, yeah. Yes, yes. So, and that's all basically coming back to, just tied together is like hardware model, co-design, which isKyle: hardware model, co model, context, co-design.Vibhu: Yeah.Kyle: Right. Like if you were training a, a model that was like. Really, really short context, uh, or like really is good at super short context tasks. You may like design it in a way such that like you don't care about attention scaling because it hasn't hit that, like the turning point where like the quadratic curve takes over.Nader: How do you consider attention or context as a separate part of the co-design? Like I would imagine hardware or just how I would've thought of it is like hardware model. Co-design would be hardware model context co-designKyle: because the harness and the context that is produced by the harness is a part of the model.Once it's trained in,Vibhu: like even though towards the end you'll do long context, you're not changing architecture through I see. Training. Yeah.Kyle: I mean you can try.swyx: You're saying [00:47:00] everyone's training the harness into the model.Kyle: I would say to some degree, orswyx: there's co-design for harness. I know there's a small amount, but I feel like not everyone has like gone full send on this.Kyle: I think, I think I think it's important to internalize the harness that you think the model will be running. Running into the model.swyx: Yeah. Interesting. Okay. Bash is like the universal harness,Kyle: right? Like I'll, I'll give. An example here, right? I mean, or just like a, like a, it's easy proof, right? If you can train against a harness and you're using that harness for everything, wouldn't you just train with the harness to ensure that you get the best possible quality out of,swyx: Well, the, uh, I, I can provide a counter argument.Yeah, sure. Which is what you wanna provide a generally useful model for other people to plug into their harnesses, right? So if youKyle: Yeah. Harnesses can be open, open source, right?swyx: Yeah. So I mean, that's, that's effectively what's happening with Codex.Kyle: Yeah.swyx: And, but like you may want like a different search tool and then you may have to name it differently or,Nader: I don't know how much people have pushed on this, but can you.Train a model, would it be, have you have people compared training a model for the for the harness versus [00:48:00] like post training forswyx: I think it's the same thing. It's the same thing. It's okay. Just extra post training. INader: see.swyx: And so, I mean, cognition does this course, it does this where you, you just have to like, if your tool is slightly different, um, either force your tool to be like the tool that they train for.Hmm. Or undo their training for their tool and then Oh, that's re retrain. Yeah. It's, it's really annoying and like,Kyle: I would hope that eventually we hit like a certain level of generality with respect to training newswyx: tools. This is not a GI like, it's, this is a really stupid like. Learn my tool b***h.Like, I don't know if, I don't know if I can say that, but like, you know, um, I think what my point kind of is, is that there's, like, I look at slopes of the scaling laws and like, this slope is not working, man. We, we are at a million token con

Behind some OnlyFans models making money from chatting to paying subscribers is the unseen human labour people who pretend to be the models and chat on their behalf. We speak to a woman in the Philippines about her jobs as a “chatter'. Also on the programme, scientists using AI to help advance their research. And the White House has been cutting real footage from the war with Iran with clips from video games. We analyse their strategy.Presenter: Shiona McCallum Producer: Imran Rahman-Jones

Tesla recently announced its intention to sunset manufacturing of its Model S and Model X cars, in favor of... robots? On this episode Lisa, Chris, and Derek break down the "why's" behind this decision, and the effects it could have on Tesla's legacy. In our Condensed Soup segment, the team discusses what we're naming our first humanoid robot, and where we're storing them in our homes.

Jill and Tom open the show discussing the sudden resignation of Chrysler CEO Chris Feuell. Tom thinks Feuell's departure prefaces the end of the Chrysler brand. Jill is not so sure. Listen in for details. The hosts go on to share news of two car models that will disappear after the 2026 model year. One is no surprise, the other a little bit sad. Still in the first segment, Jill and Tom review the 2026 Mazda CX-70 midsize crossover. The hosts have driven a lot of similar-size crossovers recently, listen in to hear how this big Mazda compares. In the second segment, Jill and Tom welcome veteran auto writer Gary Witzenburg to the the podcast. Garry's new book Legends in Motion is a collection of the author's favorite reviews and stories written over the past four decades of his career. From the book, Gary shares details of the Cadillac Allanté Air Bridge, and the legendary Cannonball Rally. In the last segment, Jill is subjected to Tom's "Just a Gosh Darn Minute" quiz. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this powerful, high-frequency conversation, Dr. Anna Marie welcomes back Anthony, a transformational coach who has spent nearly three decades helping people optimize their physical, emotional, mental, and spiritual well-being. Building on their earlier episode together ("Unlocking the Code of Human Potential" – Episode 229), they explore new paradigms of personal development that help leaders and individuals step into who they were truly designed to be.   In this Episode, You'll Learn: How your words, thoughts, and beliefs shape your health, finances, and relationships Why inner work (healing, self-responsibility, self-love) must come before outer success Simple daily practices: meditation, grounding, and movement to raise your energy How to work with healing and abundance frequencies (528 Hz, 777 Hz, 963 Hz) What it means to live as a soul-led leader instead of an ego-driven one   About Anthony Cudio: Anthony Cudjo, known as "Coach Cudjo," is the Founder and Head Coach of Human Optimization 3.0 (H3O) and a leading expert in human performance and life optimization. With over 35 years of experience as a business consultant, executive coach, and performance specialist, he helps individuals elevate their health, mindset, and success. A former professional athlete and certified life coach, advanced NLP practitioner, nutritionist, and metabolic specialist, Anthony integrates mind, body, and spirit to unlock peak potential. Through his Human Optimization 3.0 method, he empowers individuals and leaders to achieve high performance and purposeful living. Connect with Anthony: Website: https://urh3o.com/ Facebook: https://www.facebook.com/humanoptimization3.0/ Instagram: https://www.instagram.com/Humanoptimization3.0 Youtube: https://www.youtube.com/@Humanoptimization3.0 LinkedIn: https://www.linkedin.com/in/urh3oanthonycudjo/ Tiktok: https://www.tiktok.com/@humanoptimization3.0 Connect with Anna: Email: annamarie@happywholeyou.com / info@HappyWholeYou.com Website: www.happywholeyou.com / https://linktr.ee/happywholeyou Personal Website: www.DrAnnaMarie.com Instagram: @happywholeyou Personal Instagram: @Dr.Anna.Marie Facebook: Happy Whole You LinkedIn: Anna Marie Frank Venmo: @happywholeyou

Send a textPart two of my interview with Barbara Adler is as juicy if not juicier than part one and I did not expect that. I start by laying out every single one of Epstein's 46 shell companies — the real estate holdings, the aviation companies, the offshore financing vehicles, the pass-through shells, and the master trust with 40 secret beneficiaries named for his birth year. I name the three people who ran his in-house accounting and compliance — Richard Kahn, Bella Klein, and Harry Beller — and ask why none of them have been brought in front of Congress when Bella literally pleaded the Fifth. I break down Liquid Funding Limited out of Bermuda that was loaded with the exact mortgage-backed securities that caused the 2008 financial crash — and then play you the clip of Epstein bragging about being on the phone with Bear Stearns and JP Morgan simultaneously during the crash FROM PRISON. Then Barbara and I go deeper than part one. She tells me about Naomi Campbell trafficking her best friend Sky to Russell Simmons — LSD, Bahamas weekends, threesomes, and how Russell would pay for their apartments and then replace them when they got boring. She brings up Vladislav Doronin and the mystery island he supposedly built for Naomi in the shape of a horus eye — there are architectural drawings in magazines BUT... I found out who Barbara's modeling agent was — Faith Cates who founded Next Model Management — and when I dug into the Epstein files what I found made my jaw drop. Faith had social emails with Epstein, invited models to his dinner parties, and he's telling her he's spending Thanksgiving with Trump and others in 2017 — years after his conviction. Epstein donated to her cancer charity and a tennis center where her son worked. And Faith is the agent who introduced Stacey Williams to Epstein — and Stacey is the woman who alleges Trump groped her at Trump Tower with Epstein watching and smiling. Jean-Luc Brunel owned 25% of Faith's company. I tell Barbara about Ruslana Korshunova — the Russian model who jumped from a ninth floor balcony in 2008 after visiting Epstein Island two years before. No drugs or alcohol in her system. Her mother believes she was murdered. I tell her about Karen Mulder — one of the biggest supermodels  I connect Paul Marciano from Guess to Mohamed Hadid and explain how the shadow mansion network worked with girls. Barbara tells me about Epstein speaking to her directly — how he was non-emotional with a creepy smile and asked very specific questions about her upbringing and background.  And what about the second Island...Full episode only available at Dishing Drama Dana Patreon, it's only $6.00 a month, join the fun! https://www.patreon.com/cw/DishingDramaWithDanaWilkeySupport the showDana is on Cameo!Follow Dana: @Wilkey_Dana$25,000 Song - Apple Music$25,000 Song - SpotifyTo support the show and listen to full episodes, become a member on PatreonTo send Dana information, show requests and sponsorships reach out to our new email: dishingdramadana@gmail.comDana's YouTube Channel

Brian Kippen is back after nearly four years to talk about an incredible period of growth and change at KAD Models. From teaching machining to acquiring a wire forming business, adding a MAM with automation, and managing three facilities across two coasts—all while raising a toddler. We dive into the cultural challenges of bringing precision work to a fast-paced prototype shop, the reality of machine automation ROI, and why delegation is harder than it sounds.Check out Brian's IG @kadmodels-----------------------------------------Help support the podcast www.patreon.com/withintolerancepodcast

In this episode, part 2 of our latest chat with @Formscapes , we map the emerging landscape of modern aether theory, tracing the structural ideas proposed by researchers who've appeared on DemystifySci. What begins as a survey becomes a deeper look at why so many independent models are quietly aligning around similar mechanical principles. As the conversation unfolds, the old boundaries between fields dissolve, revealing a shared intuition about the medium beneath observable phenomena. Ultimately, the shadows feel less like obscurity and more like the place where a new framework is taking shape.Part 1: https://youtu.be/R8MbZ8DI1ZAPATREON https://www.patreon.com/c/demystifysciPARADOX LOST PRE-SALE: https://buy.stripe.com/7sY7sKdoN5d29eUdYddEs0bHOMEBREW MUSIC - Check out our new album!Hard Copies (Vinyl): FREE SHIPPING https://demystifysci-shop.fourthwall.com/products/vinyl-lp-secretary-of-nature-everything-is-so-good-hereStreaming:https://secretaryofnature.bandcamp.com/album/everything-is-so-good-herePARADIGM DRIFThttps://demystifysci.com/paradigm-drift-show00:00 Go! Requirements for an Aether Theory04:11 Aether as Foundational Medium08:12 Structural Ether and Material Complexity13:16 Limits of Mathematical Modeling20:07 Material Principles and Subunit Configuration23:13 Elasticity, Shear, and the Mechanics of Light26:42 Subunit Connectivity and Solid Ether Models32:12 Mass as a Foundational Concept36:00 Relational Physics and Michelson–Morley Reconsidered41:16 Observational vs Controlled Science47:44 Questioning Particle Physics Paradigms50:58 Structural Failures in Stellar Models57:37 Abstraction, Mystery, and Scientific Authority01:11:22 Cosmological Patchwork and Theoretical Contradictions01:19:09 Reclaiming Comprehensibility Through Structural Thinking01:25:07 A Renaissance of Shared Understanding #Aether, #quantumphysics, #Physics, #FoundationalPhysics, #Reality #MechanicalModels #fields , #physicspodcast, #philosophypodcast MERCH: Rock some DemystifySci gear : https://demystifysci-shop.fourthwall.com/AMAZON: Do your shopping through this link: https://amzn.to/3YyoT98DONATE: https://bit.ly/3wkPqaDSUBSTACK: https://substack.com/@UCqV4_7i9h1_V7hY48eZZSLw@demystifysci RSS: https://anchor.fm/s/2be66934/podcast/rssMAILING LIST: https://bit.ly/3v3kz2S SOCIAL: - Discord: https://discord.gg/MJzKT8CQub- Facebook: https://www.facebook.com/groups/DemystifySci- Instagram: https://www.instagram.com/DemystifySci/- Twitter: https://twitter.com/DemystifySciMUSIC: -Shilo Delay: https://g.co/kgs/oty671

In this powerful episode of The Mike Litton Experience, Mike sits down with entrepreneur and model manager Tina Rattigan, founder of Propel Models, to explore her incredible journey from Jamaica to building a purpose-driven modeling agency in the United States. Tina shares her inspiring story of resilience—growing up in Jamaica, moving to the U.S. at 21, navigating cultural shifts, overcoming personal challenges, and ultimately launching Propel Models with a mission to protect, mentor, and elevate talent in the modeling industry. After witnessing firsthand the gaps in model representation—especially through her daughter's international modeling experience—Tina redefined what leadership in fashion should look like. Today, she leads with integrity, strong boundaries, and a deep commitment to guiding models mentally, emotionally, and professionally. In this episode, viewers will discover: • The power of resilience and reinvention• Why boundaries are essential in leadership and business• Behind-the-scenes truths about the modeling industry• How to build a purpose-driven company from experience• What it takes to protect and propel young talent globally• Lessons in entrepreneurship, motherhood, and vision Tina Rattigan is not just building a modeling agency—she's building confidence, strength, and sustainable careers. If you're an aspiring entrepreneur, creative professional, model, parent, or leader, this conversation will challenge and inspire you. Don't forget to LIKE, COMMENT, and SUBSCRIBE to The Mike Litton Experience for more powerful conversations with leaders, innovators, and difference-makers from around the world. Turn on notifications so you never miss an episode! Welcome to The Mike Litton Experience Podcast! Mike is passionate about being a father, a teacher, a Realtor, an investor and a leader! Everyone has a story and our passion is to help them tell it! We never want you to miss an episode, so please be sure to subscribe. Could we ask you for two quick favors? If you like our program, please tell a friend. Wherever you get your podcasts please leave us a rating. It helps us to connect with quality people just like you! Reach out to Mike on Instagram @themikelittonexperience. Thank you for joining us for The Mike Litton Experience! Who you work with matters and we would be honored to interview with you or anyone you know to sell your home! If you have questions, please reach out text or call 760-522-1227. Thank you! #livinginsandiego, #movingtosandiego, #themikelittonexperience, #homesforsaleinsandiego, #mikelitton, #sellahomeinsandiego, #buyahomeinsandiego, #toptipstogetthebestoffer #themikelittonexperience

In this episode, we discuss… What science really is, both as body of knowledge and a constantly evolving process  Why one study is never enough and the importance of multiple methods, reproducibility, and scientific consensus over time When "gold standard" research falls short and why fields like nutrition require more flexible, creative approaches Science's built-in caution and how new ideas face a high bar of proof, slowing acceptance but strengthening reliability How doubt is manufactured, from the tobacco era to climate science, using fringe voices to challenge strong consensus The role of ideology, and how "freedom" narratives can shape public resistance to scientific evidence Acting without certainty and why we must make public health decisions even when data isn't 100% complete AI and misinformation and the promise and risk of tools like OpenAI in shaping how we consume science Naomi Oreskes Henry Charles Lea Professor of the History of Science Affiliated Professor of Earth and Planetary Sciences ON LEAVE SPRING 2026 emailoreskes@fas.harvard.edu Faculty Assistant: Yaz Alfata Primary Areas of Research: Agnotology; the Political Economy of Scientific Knowledge; History and Philosophy of Earth and Environmental Sciences, Science and Technology Studies (STS); the History of Climate Change Disinformation Secondary Areas of Interest: Science Policy, Science and Religion, Women and Gender Studies   Naomi Oreskes is Henry Charles Lea Professor of the History of Science and Affiliated Professor of Earth and Planetary Sciences at Harvard University. A world-renowned earth scientist, historian and public speaker, she is the author of the best-selling book, Merchants of Doubt (2010) and a leading voice on the role of science in society, the reality of anthropogenic climate change, and the role of disinformation in blocking climate action. Oreskes is author or co-author of 9 books, and over 150 articles, essays and opinion pieces, including Merchants of Doubt (Bloomsbury, 2010), The Collapse of Western Civilization (Columbia University Press, 2014), Discerning Experts (University Chicago Press, 2019), Why Trust Science? (Princeton University Press, 2019), and Science on a Mission: American Oceanography from the Cold War to Climate Change, (University of Chicago Press, 2021). Merchants of Doubt, co-authored with Erik Conway, was the subject of a documentary film of the same name produced by participant Media and distributed by SONY Pictures Classics, and has been translated into nine languages. A new edition of Merchants of Doubt, with an introduction by Al Gore, was published in 2020. Her latest book, with Erik Conway, is The Big Myth: How American Business Taught Us to Loath Government and Love the Free Market, which has been translated to French and Italian. Oreskes wrote the Introduction to the Melville House edition of the Papal Encyclical on Climate Change and Inequality, Laudato Si, and her essays and opinion pieces on climate change have appeared in leading newspapers around the globe, including The New York Times, The Washington Post, The Los Angeles Times, the Times (London), and Frankfurter Allegemeine. Her numerous awards and prizes include the 2019 Geological Society of American Mary C. Rabbitt Award, the 2016 Stephen Schneider Award for outstanding Climate Science Communication, the 2015 Public Service Award of the Geological Society of America, the 2015 Herbert Feis Prize of the American Historical Association for her contributions to public history, and the 2014 American Geophysical Union Presidential Citation for Science and Society. She is a fellow of the American Geophysical Union, the Geological Society of America, the American Association for the Advancement of Science, the American Academy of Arts and Sciences, and the American Philosophical Society. In 2018, she was named a Guggenheim Fellow, and in 2019 she was awarded the British Academy Medal. In 2024, she was awarded the Nonino Foundation "Maestro del Nostro Tempo" award. And in 2025, she was awarded the Volvo Environment Prize for her contributions in "shaping our understanding of how scientific knowledge is collectively constructed and addressing the challenges of misinformation in public discourse."  Curriculum Vitae   Select Publications The Big Myth: How American Business Taught Us to Loath Government and Love the Free Market, 2023 (Bloomsbury Press) Science on a Mission, 2021 (University of Chicago Press) Why Trust Science?, 2019 (Princeton University Press) Science and Technology in the Global Cold War, 2014 (MIT Press) The Collapse of Western Civilization: A View from the Future, 2014 (Columbia University Press)   Collapse of Western Civilization Home Page Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming, 2010. (New York: Bloomsbury Press.) Merchants of Doubt Home Page Merchants of Doubt at the 52nd New York Film Festival, October 8, 2014 Models in Environmental Regulatory Decision Making, Whipple, Chris et al. (fourteen additional authors), 2007. (Washington DC: National Academy of Sciences National Research Council, Board on Environmental Studies and Toxicology), 287 pp. The Rejection of Continental Drift: Theory and Method in American Earth Science, 1999. (New York: Oxford University Press) In the Media Testimony Before the US Senate Budget Committee, Twitter, June 22, 2023 Science Isn't Always Perfect - But We Should Still Trust It, TIME, October 2019 Climate Change Will Cost Us Even More Than We Think, New York Times, October 2019 Escaping Extinction, World Economic Forum, January 2019 Yes, ExxonMobil Misled the Public, LA Times, September 2017 What Exxon Mobil Didn't Say About Climate Change, The New York Times, August 2017 Assessing ExxonMobil's Climate Change Communications (177-2014), Environment Research Letters, August 2017 Scientists Dive Into the Political Fray, PBS Newshour, April 2017 How to Break the Climate Deadlock, Scientific American, November 2015 What Did Exxon Know?, On The Media, November 2015 The Pope and the Planet, The Open Mind, November 2015 Exxon's Climate Concealment, New York Times, October 2015 Naomi Oreskes, a Lightning Rod in a Changing Climate, New York Times, June 2015 A Chronicler of Warnings Denied, New York Times, October 2014 Merchants of Doubt, Documentary from Sony Pictures Classics, 2014 "Why We Should Trust Scientists," TED Talk, June 2014 The 2014 Vatican Environmental Summit: Can a Pope Help Sustain Humanity and Ecology?, New York Times Interview for Cosmologics Magazine Prof. Oreskes discusses her book, "The Collapse of Western Civilization..."  Naomi Oreskes - The Collapse of Western Civilization, Inquiring Minds Podcast "A View From the Climate Change Future," National Public Radio via Boston's WBUR Edited Volumes Oreskes, Naomi, ed., with Homer E. Le Grand, 2001.  Plate Tectonics: An Insider's History of the Modern Theory of the Earth (Boulder: Westview Press), paperback edition February 2003. Edited Journal Volumes Oreskes, Naomi and James R. Fleming, eds. 2000.  "Perspectives on Geophysics," Special Issue of   Studies in the History and Philosophy of Modern Physics, 31B, September 2000.

Outsourcing podcast Learn more about this outsourcing podcast and Inside Outsourcing here: https://www.outsourceaccelerator.com/podcast/inside-outsourcing-podcast-series/   We're publishing the entire book, Inside Outsourcing, written by Derek Gallimore, on this podcast feed over the coming weeks. This episode: Episode 578 - Chapter 4.2.2 Outsourcing Service Models If you're tuning in for the first time, go back to Episode 563 to catch the book from the beginning. — — — About the book: Inside Outsourcing: How Remote Work, Offshoring & Global Employment is Changing the World Outsourcing has long been criticized for low wages and poor conditions, yet nearly every major company—from Apple to JP Morgan—depends on it. Once a $200 billion industry limited to multinationals, outsourcing is now accessible to small and mid-sized firms, offering up to 70% savings and access to a global talent pool of 2 billion professionals. Inside Outsourcing unpacks the industry's evolution, misconceptions, and future—offering clear insights and practical guidance for businesses ready to harness outsourcing as a driver of innovation and growth.   NOTES on listening: We will be publishing full chapters of the book over the coming weeks. Start with Ep 563 first, and tune in next week for the following chapter(s). Please share with your friends.   Get a copy of the book: You can buy a full version of Inside Outsourcing for yourself from Amazon - with audio, Kindle, and hardcopy available. https://www.amazon.com/Inside-Outsourcing-Offshoring-Employment-Changing/dp/1739623002   Please leave a review: If you've listened to the book and enjoyed it, please support us by leaving a review on Amazon or Goodreads. https://www.amazon.com/Inside-Outsourcing-Offshoring-Employment-Changing/dp/1739623002 or https://www.goodreads.com/book/show/61210866-inside-outsourcing Enjoy.   Start Outsourcing Outsource Accelerator can help you transform your business with outsourcing. Get in touch now, or use one of the resources below.   Business Process Outsourcing Get a Free Quote - Connect with 3 verified outsourcing experts & see how outsourcing can transform your business Book a Discovery Call - See how Outsource Accelerator can help you enhance your company's innovation and growth with outsourcing The Top 40 BPOs - We have compiled this review of the most notable 40 Business Process Outsourcing companies in the Philippines Outsourcing Calculator - This tool provides you with invaluable insight into the potential savings outsourcing can do for your business Outsourcing Salary Guide - Access the comprehensive guide to payroll salary compensation, benefits, and allowances in the Philippines Outsourcing Accelerator Podcast - Subscribe and listen to the world's leading outsourcing podcast, hosted by Derek Gallimore Payoneer - The leading global B2B payment solution for the outsourcing industry   About Outsource Accelerator Outsource Accelerator is the world's leading outsourcing marketplace and advisory. We offer the full spectrum of services, from light advisory and vendor brokerage, though to full implementation and fully-managed solutions. We service companies of all sectors, and all sizes, spanning all departmental verticals. Outsource Accelerator's unique approach to outsourcing enables our clients to build the best teams, access the most flexible solutions, and generate the best results possible. Our unrivaled sector knowledge and market reach mean that you get the best terms and results possible, at the best ALL-IN market-leading price - guaranteed.

Luma introduced Luma Agents, powered by its new “Unified Intelligence” models, designed to coordinate multiple AI systems and generate end-to-end creative work across text, images, video and audio. Learn more about your ad choices. Visit podcastchoices.com/adchoices

In this episode of Mark & Pete, we explore a fascinating development in modern science: how mathematical models are helping scientists identify genetic material that could dramatically improve the resilience of global food crops.Researchers are increasingly using advanced mathematics, computational biology, and genetic analysis to pinpoint the specific genes responsible for drought tolerance, disease resistance, and environmental adaptability in crops such as wheat, rice, and maize. The goal is simple but crucial: strengthen the world's food supply in the face of climate change, population growth, and unpredictable agricultural conditions.But this technological breakthrough raises bigger questions. When mathematics begins guiding genetic discovery, are we witnessing the next great leap in agricultural science—or are we stepping into a new era where humanity attempts to redesign the natural world?In this episode we unpack how mathematical modelling, genetics, and agricultural science intersect, and why this approach is rapidly becoming one of the most powerful tools in modern crop research. From predictive algorithms that identify useful genetic traits to data-driven plant breeding, the science behind food security is becoming increasingly mathematical.At the same time, we ask an important cultural and philosophical question: what does stewardship of creation look like in an age of genetic precision? The Bible speaks of humanity being placed in the garden “to work it and keep it.” Does modern genetic science fulfil that mandate—or challenge it?This conversation brings together science, ethics, agriculture, and faith, offering a thoughtful look at how technological innovation intersects with biblical ideas about stewardship, responsibility, and wisdom.If you are interested in food security, agricultural science, genetics, biotechnology, climate resilience, and the Christian perspective on science, this episode provides a clear and engaging discussion of one of the most important developments shaping the future of global food production.Keywords:crop resilience genetics, mathematical models genetics, food crop resilience science, agricultural genetics research, genetic material crops, drought resistant crops research, crop breeding algorithms, biotechnology agriculture, global food security science, mathematics in biology, computational genetics agriculture, Christian perspective on science, stewardship of creation agriculture

Welcome back to the NASM Peak Physique Podcast! In this inspiring episode, IFBB Olympian & Master Trainer Andre Adams sits down with featured guest, 8-time Figure Olympian and renowned fitness coach, Wendy Fortino. Get ready to dive deep into longevity, building an athletic foundation, and how to evolve your physique without sacrificing your edge.

Episode 109 - All Models Are Wrong But Some Are Random by Dan Vacanti & Prateek Singh

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Guest: Drs. Shuibing Chen and Hans Clevers, members of the Steering Committee for the ISSCR Consortium on Advanced Stem Cell-Based Models in Drug Discovery and Development, discuss the need to accelerate the responsible integration of stem cell–derived models into preclinical drug development. Their conversation reflects growing regulatory and policy momentum around new approach methodologies (NAMs) and underscores the importance of rigorous standards, regulatory alignment, and cross-sector collaboration to improve reproducibility and advance more predictive, human-relevant therapies. Building on its long-standing leadership in global standards, ethics, and policy, the ISSCR is uniquely positioned to convene industry, academia, and regulators around this effort. The initiative also reflects the Society's expanding industry engagement, with industry membership increasing nearly 180% over the past five years – creating new opportunities for strategic partnerships to address shared scientific and translational challenges. Featured Products and Resources: Learn how organoids can be used to expand clinical applications of diseases and disorders.   Get a free wallchart showing how organoids are used as model systems to study infectious diseases, cancer, congenital disorders, and tissue regeneration. The Stem Cell Science Round Up Treating Frailty with Stem Cells – In a clinical trial, mesenchymal stem cell therapy improved walking distance and physical function in older adults with frailty. Combined Bone & Bone Marrow Organoids – Researchers developed a scalable iPSC-derived bone marrow organoid that models human lympho-myeloid hematopoiesis and disease. CAR-NK Progenitors Prevent Relapse – Engineered pluripotent stem cell–derived CAR-expressing NK progenitor cells reduced minimal residual disease and prevented relapse in leukemia models following chemotherapy. Whole-Body Single-Cell Mapping – Scientists have developed a 3D single-cell-resolution map of mouse organs and the whole neonatal body. Photo Reference: Courtesy of Drs. Shuibing Chen and Hans Clevers Subscribe to our newsletter! Never miss updates about new episodes. Subscribe

In this episode of the Innovations and Clinical Implementation podcast recorded at LongevityFest, host Tom Blue interviews Harry Bane, CEO of Lifespan.MD, about a novel investment model for concierge medicine dubbed "Entrepreneurial Equity". Unlike traditional private equity that often focuses on cost-cutting, Bane explains that Lifespan.MD builds long-term partnerships with established physician-entrepreneurs, allowing them to retain clinical autonomy while leveraging shared infrastructure, AI technology, and a collaborative "brain trust" to drive organic growth rates of 30–40%. The conversation highlights the Company's origin story—born from a patient-doctor relationship—and its five core values, emphasizing how the model reinvigorates practitioners by turning their practices into tangible wealth assets through equity while solving critical succession planning and supply-demand challenges in the longevity sector.   For access to episode resources, click HERE.

One of the most common dilemmas facing entrepreneurs today is what comes first: making the money or mastering the mindset to keep it? Much like the age-old "chicken or the egg" riddle, these two pillars of business are deeply interconnected, feeding into one another to create a thriving ecosystem, and Jenni and I are breaking it all down for you in this one. Today we look at where you should start in terms of a self-audit, how the three essential skills of money help you identify exactly where you should be pouring your energy based on the current stage of your business, and so much more. Whether you are a brand-new creator building from scratch, a seasoned pro looking to scale without burnout, or a leader trying to determine why your high revenue isn't translating into profit, this episode will light the way for what to do next! Want my Business Profitability Playbook? Come follow me on IG and DM me PROFIT and I'll send it over! And don't forget, if you want to be the first to know when Jenni reopens the doors to her monthly meditation membership, The InnerStellar Collective? If you're craving more intuition, mindfulness, and intentional space in your life, join the waitlist here. You'll be the first to hear what's coming next - go to www.bbdcoaching.com/innerstellarcollective. ✨ If you haven't yet signed up for my free weekly newsletter for online experts, The Digital CEO Weekly, you can sign up now and get it delivered straight to your inbox every Monday morning at www.jameswedmore.com/newsletter.  Hey there, Digital CEO! If you're loving this episode and you know this is your year to finally build, launch, or scale your digital business the right way — then I've got something for you. Business By Design, my signature program that gives you everything you need to design a leveraged, profitable digital product business, only opens once a year… If you want to be the FIRST notified when doors are open, you can get on the waitlist for BBD 2026 right now. That way, you'll be the first to know when we open enrollment again (and trust me, you do not want to miss it!). Head to www.businessbydesign.net/ and join the waitlist today! Snap a screenshot of the episode playing on your device, post it to your Instagram Stories and tag us, @jameswedmore and @jenniwedmore. We'd love to hear what resonated with you the most from this episode and especially what you want covered in future ones!  In this episode you'll hear:  Jenni's inspiring story of launching her dream membership that was 15 years in the making Why I have zero interest in hearing you're "bad at sales" if you aren't willing to put in the 15-minute daily reps The profit margin to aim for early on in business, and the specific reason I tell people to avoid in-person hires until they hit $500k Why your business will never actually give you financial freedom, and the one thing you must do with your cashflow to actually get it My personal philosophy on why money left sitting in a business account is a liability that will always find a way to get spent A scary realization that if you have to talk to every lead for an hour to sell a digital course, your business isn't actually scalable How to use recurring and renewable revenue models to stop feeling like you're only one bad launch away from your business going under Why "getting rich fast" is the literal death of financial freedom, and how to master the  habits that actually build a portfolio What can help stop you from freaking out over every algorithm change that comes at us  For full show notes and links, visit: www.mindyourbusinesspodcast.com/blog/803 

Enterprise IT spending is projected to reach $4.5 trillion by 2026, but this growth is concentrated in software, cloud services, and AI infrastructure for large organizations, according to HG Insights and Omdia research cited by Dave Sobel. The system integration market is positioned to approach $950 billion in 2025, with enterprises working with an average of 6.3 technology partners. A substantial surge in AI-optimized server sales, as reflected in Dell Technologies' reported 342% year-over-year increase in revenue for those systems, is reshaping supply chains and vendor dynamics, leading to shortages of DRAM, SSDs, and hard drives. Underlying this development are volatile component costs. DRAM prices have doubled quarter over quarter, and both Micron Technologies and Western Digital have indicated they are sold out for 2026. HP reports that RAM now constitutes 35% of new PC materials costs, up dramatically from 18% the previous quarter. Such cost shifts are creating downstream risks for managed service providers (MSPs) with fixed-price agreements, as the economic assumptions underpinning many contracts—stable hardware prices and predictable cloud costs—no longer hold. The episode also highlights an increase in application sprawl and a widening gap between IT budgets and other operational costs. A Torii report shows large enterprises use over 2,191 applications on average, with more than 61% bypassing formal IT approvals, resulting in unmanaged security and compliance exposure. Additionally, 80% of small businesses report rising energy costs that directly compete with IT budget allocations. Industry analysis from Jefferies and Boston Consulting Group signals that AI and automation are not viewed uniformly as productivity boosters and may compress revenue models in both Indian and domestic IT services sectors. The practical implication for MSPs is the urgent need to audit and reprice contracts related to hardware procurement and refresh cycles, clearly documenting and communicating current cost realities with clients. Dave Sobel stresses reframing device lifecycle extensions as a security risk rather than a cost-saving measure and warns against selling clients on speculative AI market projections. The advice is to focus on specific, scoped use cases and to structure agreements that accurately reflect volatility in component costs and the operational burden of application sprawl, ensuring financial and legal accountability as the IT services landscape evolves. 00:00 $4.96T IT Spend Surge Bypasses SMBs as AI Infrastructure Captures Enterprise Budgets 03:58 Dell's $43B AI Server Backlog Triggers DRAM Shortage, Repricing Downstream Hardware 05:52 AI Shrinks IT Services Revenue Model; MSPs Face Contested Implementation Role   This is the Business of Tech.    Supported by:

Rob and Vinnie welcome Danny Hall begin a multi-episode discussion looking at toxic church environments. How has the “church growth” and “mega church” model (since the 1970s) impacted the modern church? What should a healthy church leader look like? How important is self-awareness for the church leader?   This is part 1 of a conversation that will talk about cultivating a healthy church environment and how to understand church hurt and church abuse.    Check us out: https://www.determinetruth.com/ Danny Hall: danny@dhallconsult.com Great Resources on the topic of Creating Healthy Churches   A Church Called Tov (Scot McKnight) https://www.amazon.com/Church-Called-Tov-Goodness-Promotes/dp/1496446003/ref=tmm_hrd_swatch_0?_encoding=UTF8&dib_tag=se&dib=eyJ2IjoiMSJ9.4lBAQzf3oJglpTj_7R8NbAeOg0H2oH4CTgx81Cm9okZZVtD9VFcS1uSUfVV2EQm5KZL1himBpHsyFB4D_Gifo4cf1QusTB-POg2TVGG7LdGmQvQa0IB928VE-Lzebn0QaYbWTVGVFLpXeUIBI_xAwisMWdvmpzjWJxaEPeX_KDzkLcEidFqxV9x2KN137nu9_VqW_lpT5_tSt6oq8-Jdy9yqaU0SHRxzumNuhx47RWQ.FqeuaDuA2RxUSi8NLD1Eu9aVNCvxijZDHQxchJMDJm0&qid=1772398542&sr=8-1 Something's Not Right: Decoding the Hidden Tactics of Abuse--and Freeing Yourself from Its Power (Wade Mullens) https://www.amazon.com/dp/1496444701/ref=mes-dp?_encoding=UTF8&pd_rd_w=DfllH&content-id=amzn1.sym.476b1b7d-c787-4147-8a3c-fdef209103a1&pf_rd_p=476b1b7d-c787-4147-8a3c-fdef209103a1&pf_rd_r=0KK0SC6CEWNJ2Q64975X&pd_rd_wg=GCNhP&pd_rd_r=79c691b9-0dac-456b-bda2-afdb8d5268e5 When Narcissism Comes to Church (Chuck DeGroat) https://www.amazon.com/dp/1514005093/ref=mes-dp?_encoding=UTF8&pd_rd_w=zdSwU&content-id=amzn1.sym.476b1b7d-c787-4147-8a3c-fdef209103a1&pf_rd_p=476b1b7d-c787-4147-8a3c-fdef209103a1&pf_rd_r=WKKWWGSF6Y2GYRHQ8926&pd_rd_wg=mFZQA&pd_rd_r=a6182de3-e16f-4416-9ef7-e30aa5043369 When the Church Harms God's People (Diane Langberg) https://www.amazon.com/dp/1587436450/ref=mes-dp?_encoding=UTF8&pd_rd_w=uVPPK&content-id=amzn1.sym.476b1b7d-c787-4147-8a3c-fdef209103a1&pf_rd_p=476b1b7d-c787-4147-8a3c-fdef209103a1&pf_rd_r=CAM1FBFN0J7Y0RS0HF0V&pd_rd_wg=KaJ0d&pd_rd_r=a0246e35-7d3f-4feb-89db-facae6fa4a8a FOLLOW THE PODCAST Subscribe to be notified of our new episodes (each Monday).  Want to help us expand the Gospel of the Kingdom? Leave a review, “like” the podcast, or share it with others.   CONNECT WITH DETERMINETRUTH MINISTRIES The Determinetruth Podcast is a ministry of Determinetruth Ministries. We offer free resources to equip pastors, leaders, and the body of Christ in the US and worldwide for service in the kingdom of God. You can visit us online at https://www.determinetruth.com   SUPPORT DETERMINETRUTH MINISTRIES Determinetruth is a non-profit 501(c)(3), and relies completely on the financial support of our partners around the world.  Please consider partnering with us and making a tax-deductible donation https://tithe.ly/give_new/www/#/tithely/give-one-time/3648601   Want a FREE CHAPTER from Rob's latest book? Sign up for email updates from Determinetruth.   https://mailchi.mp/5672d33f2b95/dt-podcast Music: “Love is Against the Grain” (Dime Store Prophets) #megachuch #churchgrowth #churchhurt #abuse #trauma #deconstruction #exvangelical #thechurch #ecclesiology #Fellowship #Mutual encouragement #Service #Corporateworship #pastors #authority #housechurch   

The episode centers on the evolving responsibility and risk allocation within cybersecurity distribution, with particular focus on Exclusive Networks' approach. Jason Beal, as president of Exclusive Networks North America, outlines their emphasis on a technical workforce, maintaining a 1:3 ratio of engineers to sales representatives. This structure is positioned to address the increasing complexity of cybersecurity and the demands faced by service provider partners, aiming to support solution integration and customer needs while clarifying each party's liability. Supporting this structure, Jason Beal identifies the role of the distributor as both an extension and enabler for MSPs and IT services companies. Distributors are expected to supplement partners' capabilities—whether technical, financial, or operational—without assuming technology failure risk, which remains with the original technology vendors. Discussion of shared responsibility models also distinguishes between sales success (customer adoption, retention) and risk management. Recent developments in cyber insurance are cited as having reduced the direct risk burden on MSPs, shifting much of the liability away from service providers toward technology creators, albeit within contractually defined limits. Adjacent to cybersecurity, the conversation addresses skill and adoption gaps prompted by rapid technical innovation, specifically referencing artificial intelligence (AI). Jason Beal quantifies educational efforts by highlighting a collaboration with Cal Poly San Luis Obispo, which has seen 100 students engaged to help address workforce shortfalls in cybersecurity and AI. Additionally, academic experience informs the importance of modernizing IT operations curricula to better reflect current business challenges, such as cloud, AI, and global supply chain impacts. For MSPs and IT service providers, implications include the growing necessity to audit core competencies and allocate resources strategically, leveraging distributors not just for sourcing products but for specialized expertise, integration, and operational support. Risk mitigation remains tied to understanding contract language, vendor accountability, and developments in cyber insurance. The pace of AI and other technology adoption requires continuous education and careful evaluation of both operational risk and the practical limitations of solutions promoted by the channel and distribution partners.

Dr. Ryan Mullins joins the podcast to discuss the problems of Creation and how models of God impact this question. Dr. Mullins' Website: https://www.rtmullins.com/ ----------------------------- SOCIAL MEDIA --------------------------- Twitter: https://twitter.com/AApologetics Facebook: https://www.facebook.com/adherentapol... Instagram: https://www.instagram.com/adherentapo... TikTok: https://www.tiktok.com/@adherentapologetics

BrainChip CEO Sean Hehir joins me to unpack where artificial intelligence is actually headed—and why the dominant “everything in the data center” narrative is incomplete.Most AI conversations fixate on massive models, GPU farms, and trillion-dollar infrastructure bets. This episode shifts the frame. Sean and I explore the structural reality that power consumption, latency, and grid constraints are forcing AI to decentralize—and what that means for founders, engineers, and the broader economy.Sean explains how neuromorphic computing and ultra-low-power silicon enable AI inference outside the data center—inside wearables, medical devices, drones, manufacturing systems, and even space applications. We examine why CPUs and GPUs aren't optimized for edge workloads, how custom silicon changes the economics, and why power efficiency isn't a side issue—it's the bottleneck that determines what scales.The conversation expands into workforce displacement, labor fluidity, productivity cycles, and whether technological acceleration inevitably creates unemployment crises—or simply reshuffles value creation again, as history repeatedly shows.This isn't a speculative futurism episode. It's a grounded look at model trends, infrastructure limits, and how companies survive inside a market moving at month-scale rather than decade-scale.The lesson isn't that AI replaces everything.It's that architecture determines outcomes.TL;DR* AI is centralizing in data centers—but it's also rapidly decentralizing to the edge* Power constraints will shape the next phase of AI more than hype cycles* Neuromorphic and event-driven silicon drastically reduce energy per compute* Edge AI enables medical wearables, safety detection, space systems, and industrial automation* Models are getting larger—but optimization techniques will shrink them into smaller form factors* Productivity gains historically displace tasks—not human adaptability* The future isn't about bigger servers—it's about smarter distribution* Lowest power per compute is a strategic advantage, not a marketing lineMemorable Lines* “Don't bet against humanity. We're very creative.”* “The future of AI isn't just in data centers.”* “Power isn't a feature—it's the constraint.”* “If you're the lowest power solution, you will always have customers.”* “Architecture decides what becomes possible.”GuestSean Hehir — CEO of BrainChipTechnology executive leading the commercialization of neuromorphic AI processors focused on ultra-low-power edge inference. Oversees BrainChip's evolution from early engineering innovation to market-driven, customer-focused deployment.

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Send a textJoin all 5 of us plus very special guest Scott Samo AKA Nemo from the Modelgeeks joins in the fun. We talk about the upcoming 2026 Edition of the 48 in 48 Global Group Build and fundraiser to benefit Models for Heroes the weekend of March 20, 2026. We also get serious and do a deep dive into each of the hosts "why" - why this hobby? What keeps each of us coming back to it over other pursuits.JB and Scott have a terrific interview with Boyd Brown, AKA the Quiet Corner Modeler, and we cover a wide range of topics and just generally have a great time! If you would like to become a Posse Outrider, and make a recurring monthly donation of $ 1 and up, visit us at www.patreon.com/plasticpossepodcast .Plastic Posse Podcast on Facebook: https://www.facebook.com/PlasticPossePlastic Posse Group on Facebook: https://www.facebook.com/groups/302255047706269Plastic Posse Podcast MERCH! : https://plastic-posse-podcast.creator-spring.com/Plastic Posse Podcast on YouTube:https://www.youtube.com/channel/UCP7O9C8b-rQx8JvxFKfG-KwOrion Paintworks (TJ): https://www.facebook.com/orionpaintworksJB-Closet Modeler (JB): https://www.facebook.com/closetmodelerThree Tens' Modelworks (Jensen): https://www.facebook.com/ThreeTensModelWorksRocky Mountain Expo: https://rockymtnhobbyexpo.com/SPONSORS:Tankraft: https://tankraft.com/AK Interactive: https://ak-interactive.com/Tamiya USA: https://www.tamiyausa.com/Micro World Games: https://mwg-hobbies.com/Bases By Bill: https://basesbybill.com/?srsltid=AfmBOoojwgAlnXwsJcB_SlYzeclVt9ZuIX3Fd18Ig9k5f4vyIYmihobbSupport the showSupport the show

‘I was there to party myself. It was guys with younger girls, sex, a lot of sex, a lot of cocaine, top-shelf liquor' but no smoking. Trump didn't approve of cigarettes.Become a supporter of this podcast: https://www.spreaker.com/podcast/the-opperman-report--1198501/support.

Tesla unveils a new $60,000 trim of the Cybertruck, and while it does make some sacrifices, it's pretty darn appealing. I'll tell you all about it on this episode. Plus: one option on the outgoing Model S and X has already been retired, Ford talks up their Tesla-like next-gen EV platform, and more! If you enjoy the podcast and would like to support my efforts, please check out my Patreon at https://www.patreon.com/teslapodcast and consider a monthly or (10% discounted!) annual pledge. Every little bit helps, and you can support for just $5 per month. And there are stacking bonuses in it for you at each pledge level, like early access to each episode at the $5 tier and the weekly Lightning Round bonus mini-episode (AND the early access!) at the $10 tier! And NO ADS at every Patreon tier! Also, don't forget to leave a message on the Ride the Lightning hotline anytime with a question, comment, or discussion topic for next week's show! The toll-free number to call is 1-888-989-8752. INTERESTED IN A FLEXIBLE EXTENDED WARRANTY FOR YOUR TESLA? Be a part of the future of transportation with XCare, the first extended warranty designed & built exclusively for EV owners, by EV owners. Use the code Lightning to get $100 off their "One-time Payment" option! Go to www.xcelerateauto.com/xcare to find the extended warranty policy that's right for you and your Tesla. P.S. Get 15% off your first order of awesome aftermarket Tesla accessories at AbstractOcean.com by using the code RTLpodcast at checkout. Grab the SnapPlate front license plate bracket for any Tesla at https://everyamp.com/RTL/ (don't forget the coupon code RTL too!). Enhance your car with cool carbon-fiber upgrades from RPMTesla.com and use the promo code RTLPOD+ for 10% off your next purchase. And make your garage door foolproof with the Infinity Shield – get yours at infinity-shield.com and use the promo code RTL at checkout for a $35 discount.