Podcasts about Eagle

KB is BACK and kicks off the show discussing the return of Dallas Goedert to the Eagles and why it is not only a massive move ON the field for the Birds, but also why it's a move that makes the case for Goedert to be mentioned as an all-time Eagle. Then he discuss some other NFL Free Agent moves and some of the latest Eagles moves. Then he shifts to March Madness as the bracket is LIVE and he discusses his thoughts on the layout of the Field of 68, some insight on Underground Madness, and some of the in-house content you'll see from our creators. Then he wraps up the show talking World Baseball Classic as Team USA NARROWLY avoids elimination and move on to the WBC Final after defeating the Dominican Republic in the semis. UNDERGROUND MADNESS 2026 BRACKET CHALLENGE: https://fantasy.espn.com/tc/sharer?challengeId=277&from=espn&context=GROUP_INVITE&edition=espn-en&groupId=c1739b48-1f9a-48f7-8bee-c9d5d3e425c4 Onboarding Form: forms.gle/mZYnkiQcGv1ZxBSg9 Voicemail Line: speakpipe.com/UndergroundSportsPhiladelphia Support Our Sponsors! The City of Vineland: Visit www.vinelandcity.org/ and stay connected with the community and learn about important announcements, programs, and services offered by the city! Vineland, New Jersey... Where It's Always Growing Season! '47 Brand Shop for your favorite sports fan and get FREE SHIPPING on ALL orders with '47 Brand! 47.sjv.io/e1Nyor Kenwood Beer Visit kenwoodbeer.com/#finder and see who has Kenwood Beer on tap in YOUR area and crack open an ice cold Kenwood Beer to celebrate the good times! (MUST be 21+ to do so and PLEASE drink responsibly.) Merch & Apparel: www.phiapparel.co/shop + Use Code "UNDERGROUND" for 10% off! FOCO Get your Phillies overalls and shortalls with our pals at FOCO! foco.vegb.net/0ZyLgV Biñho Get 10% off your next purchase with code BINHOBENNETT62 from our pals at Biñho! binhoboard.com?bg_ref=pDJkDdNO1y Follow Us! Twitter: twitter.com/UndergroundPHI Instagram: www.instagram.com/undergroundphi/ TikTok: tiktok.com/@undergroundphi KB: twitter.com/KBizzl311 Watch LIVE: YouTube: www.youtube.com/@UndergroundSportsPhiladelphia FB: facebook.com/UndergroundSportsPHI Twitch: twitch.tv/UndergroundsportsPHI Intro Music: Arkells "People's Champ" Outro Music: Arkells "People's Champ" #FlyEaglesFly #Eagles #NFL #DallasGoedert #MarchMadness #WBC #RingTheBell #MLB #Baseball #fyp #podcastcharts #download #review #subscribe #UndergroundIndustries

Laura Rutledge and the crew dive into the news of Justin Fields being traded to the Jets. Plus, they brekdown what Philly re-signing Dallas Goedert means for AJ Brown and his future as an Eagle. This and much more on NFL Live! Learn more about your ad choices. Visit podcastchoices.com/adchoices

Episode 3226 of the Vietnam Veteran News Podcast will feature a story about the 12 Vietnam Vets who returned to Vietnam. The featured story appeared on the Military website and is titled: Vietnam Vets Return to the Battlefields They Left … Continue reading → The post Episode 3226 –  The Eagle Society sent 12 Vietnam Vets back to Vietnam first appeared on Vietnam Veteran News.

On this day, 14 March 1970, two sailors aboard the SS Columbia Eagle, carrying 10,000 tons of napalm for the US military in Vietnam, mutinied in protest at the war. Al Glatkowski and Clyde McKay had smuggled guns onto the ship which they used to hijack it and sail it to neutral Cambodia. But they never could have guessed what would happen next, as they became embroiled in a complex series of world events over which they would have no control. We spoke to Al for a podcast miniseries about the events, and this is how he recounted the start of the mutiny: "When we got the guns out to clean them, I got up and I told Clyde, 'I'll be right back. I'm going to go to the bathroom before we do this.' I looked in the mirror and I said to myself, 'You may not live through this. These may be your last few minutes.' "I will never ever be able to see or look my children in the face when they ask me, ''What did you do to stop the war, Dad?'' You will be able to say that you did your duty to stop it. You did your best to stop it.' I walked around, turned around, went out the door, got the gun and said, 'Let's move.'" Listen to Al tell his and Clyde's incredible story in our podcast episodes 21-24. Find them on every major podcast app or on our website: https://workingclasshistory.com/2019/04/09/wch-crime-columbia-eagle-mutiny/ Our work is only possible because of support from you, our listeners on patreon. If you appreciate our work, please join us and access exclusive content and benefits at patreon.com/workingclasshistory.See all of our anniversaries each day, alongside sources and maps on the On This Day section of our Stories app: stories.workingclasshistory.com/date/todayBrowse all Stories by Date here on the Date index: https://stories.workingclasshistory.com/dateCheck out our Map of historical Stories: https://map.workingclasshistory.comCheck out books, posters, clothing and more in our online store, here: https://shop.workingclasshistory.comIf you enjoy this podcast, make sure to check out our flagship longform podcast, Working Class History

A reading of articles and features from the Am-Pol Eagle

In one of the most iconic founding legends of the Americas, a Golden Eagle devouring a serpent atop a cactus marked the spot where the Mexicas would build Tenochtitlan, capital of the Aztec Empire. Over the centuries, that ancient metropolis transformed into what we now call Mexico City. Though the mythical eagle is now commemorated on the national flag of Mexico, real Golden Eagles need our help through conservation research and habitat protections. ¡Escuche este episodio en español! More info and transcript at BirdNote.org. Want more BirdNote? Subscribe to our weekly newsletter. Sign up for BirdNote+ to get ad-free listening and other perks.  BirdNote is a nonprofit. Your tax-deductible gift makes these shows possible. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Gametime Ticket Offer: $20 off with code "FARZY" at gametime.co The Farzy Show presented by MyBookie Promo: No-strings-attached cash bonus up to $200 Promo Codes: FARZY ..  https://mybookie.website/joinwithFARZYManscaped Offer: 20% off AND Free Shipping with code "Farzy20" at Manscaped.comCopyright Disclaimer under section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, education and research. Fair use is a use permitted by copyright statute that might otherwise be infringing.

Czech firms seek opportunities in Texas during Deputy PM Havlíček's US trade mission, Czech experts help breed Philippine eagle chick for the first time in 13 years, New Czech Radio U.S. correspondent Jana Ciglerová on Czech-Americans and MAGA and trading Miami for Washington

Today on Word Balloon, we're blasting off with two creators bringing one of science fiction's most legendary heroes back into orbit. Writer Alex DeCampi and artist Marc Laming have launched a Kickstarter to revive the classic British space adventurer Dan Dare, the Pilot of the Future. For generations, Dan Dare has been a cornerstone of UK science-fiction comics, created by Frank Hampson for the pages of Eagle back in 1950. Think epic space exploration, alien empires, and that clean, bold optimism that made the strip a cultural icon, alongside classic villains like the Mekon. Now DeCampi and Laming are bringing that universe roaring back with a new interpretation funded directly by fans. Today we're talking about why Dan Dare still matters, how you modernize a legendary character without losing the DNA that made him special, and what they're building with this Kickstarter campaign. From the story approach to the visual style, and what longtime fans and newcomers can expect.

The WIP Morning Show discuss if AJ Brown could possibly return in 2026.

We feel like this is such a sick name for Christ, and not just because it was our high school mascot hahah. SHOWNOTES:here's our INSTA follow amelia!!!!follow ella!!!!listen to us on SPOTIFYlisten to us on APPLEcheck out our new website :)))cover art by Sarah Hawke!!xoxo,ella + amelia

What if a mountain town could recharge your body and rewrite your routines back home? We head to Glenwood Springs, Colorado for a girls' getaway that becomes a masterclass in sustainable energy—powered by hot springs, hydropower history, and a community that treats wellness like a way of life. From laps in the world's largest hot springs pool to intimate mineral circuits at Iron Mountain's World Springs, we explore how heat, water, and minerals calm the nervous system, ease pain, and spark creativity.visitglenwood.comIron Mountain Hot SpringsYampa SpaThe Glenwood Springs ResortStaying at Hotel 1888 puts the pools at our doorstep and opens the door to the onsite athletic club where locals and travelers train side by side. A barre class with new friends, a Pilates reformer session that converts us into tower devotees, and quiet balcony moments reshape how we think about motion, recovery, and rest. We compare kid-friendly soaking at the main resort with Iron Mountain's adult-only section, peek at their upcoming international saunas, and share practical tips on what to bring so your soaking day is stress free. Food is part of the story too: a stroll down 7th Street's “Restaurant Row,” three standout ice cream shops, and a supper club Brussels sprout dish we can't stop trying to recreate.Getting around is refreshingly simple and affordable. Ride Glenwood's free bus loops the spots you want, one-dollar on-demand rides fill the gaps, and budget-friendly regional routes from Aspen, Eagle, Grand Junction, or Denver make arrival painless. Then we turn the trip into take-home energy: 3D history frames that inspire us to tell our home's story with old plans and photos, reclaimed materials used as art, a humble black makeup towel that makes nightly routines kinder, and a patio rocking chair that feels like instant calm. We leave with stronger habits, better recovery tools, and a clear truth: energy isn't an accident you find on vacation—it's a ritual you build every day.If this journey sparked ideas for your next getaway or your next week at home, tap follow, share with a friend who needs a reset, and leave a quick review so more travelers can find the show.Please support our show by shopping through Eagle Creek: https://alnk.to/gVNDI6N and/or feel free to donate to:http://paypal.me/TheROAMies And it means the world to us when you subscribe, rate and share our podcast. Alexa and RoryThe ROAMiesFollow us at:http://www.TheROAMies.com@The ROAMies: Facebook and Instagram YouTube and X.

Send a textSummary: In this episode of the PIO podcast, Robert interviews Brian Townsend, a retired DEA agent and founder of Only2MG, a nonprofit focused on raising awareness about the fentanyl crisis. Brian shares his extensive experience in law enforcement and discusses the alarming rise of fentanyl-related deaths in the United States. He explains the historical context of how fentanyl became prevalent in the drug supply, its integration into other drugs, and the dangers it poses. The conversation emphasizes the need for community engagement, consistent messaging, and a holistic approach to tackling the crisis, including reducing stigma and addressing the root causes of addiction. Brian also highlights the role of organized crime in the fentanyl epidemic and the importance of collaboration between law enforcement and public health sectors to create effective solutions.Brian's Email Brian's Website Brian Townsend is a retired Supervisory Special Agent/Resident Agent in Charge with the Drug Enforcement Administration (DEA). Brian proudly served in law enforcement for 28 years; 5 years as a police officer in Joplin, Missouri, and 23 years with the DEA, where he held a variety of assignments with increasing responsibility. Within the DEA, Brian served in three different formal leadership roles, managing multiple people, programs, and resources. He worked in Corpus Christi, Texas, Little Rock, Arkansas, and Springfield, Missouri, to combat drug trafficking and reduce drug-related crime. In addition to serving in enforcement operations, Brian was assigned at the DEATraining Academy in Quantico, Virginia. There, Brian managed DEA's specializedtraining unit and developed the leadership and development training unit. Theleadership and development training unit still serves as the primary resource forleadership development throughout DEA and its extensive workforce of over10,000 personnel.Currently, Brian serves as a Law Enforcement Training Coordinator for the Mid-States Organized Crime Information Center (MOCIC), a Regional Information Sharing System (RISS) Center supporting law enforcement in nine states (Kansas, Illinois, Iowa, Missouri, Minnesota, Nebraska, North Dakota, South Dakota, and Wisconsin). He is also the founder and principal of Eagle 6 Training, providingspeaking, training, and consulting services to organizations worldwide.Brian's training expertise extends far beyond drug-related topics. He is frequentlyinvited to deliver training and presentations on a wide range of subjects, includingleadership development, cryptocurrency investigations, and the dark web. Brian'sdiverse training portfolio equips law enforcement and private organizations withthe knowledge and skills needed to address both emerging digital threats andorganizational challenges. Most recently, Brian launched Only 2mg Inc. 501(c)(3), where he leverages his extensive experience and knowledge in the field of opioids. Brian is regularly invited tThe Fresh Patch Podcast - Where Good Pets Get It. Welcome to the Fresh Patch Podcast where we talk about everything, from dog...Listen on: Apple Podcasts Support the showOur premiere sponsor, Social News Desk, has an exclusive offer for PIO Podcast listeners. Head over to socialnewsdesk.com/pio to get three months free when a qualifying agency signs up.

Welcome to The Eagle's View!This is where you can listen to the students of Emerson School in Ann Arbor, Michigan, soar.  Join 4th graders Ayla and Elli as they host this episode. You will hear about St. Patrick's Day, Michigan Foods, Star Friends, Computers, Friday the 13th, and as always, The Joke of the Week!Thank you for listening to The Eagles View. Be sure to like, follow, and share our podcast with your friends and family.And don't just listen—leave us a comment! We'd love to hear your thoughts, your favorite part, or even your own joke of the week.New episodes come out every Wednesday—even during summer break. Plus, The Eagle's View Presents every Monday, and Story Tellers on FridayBe sure to check out our new merchandise on The Emerson School Store website below.https://apparelnow.com/emerson-school-store-apparel/Follow on social media too!https://www.facebook.com/theemersonschool/https://www.instagram.com/emersonschool/Thanks for hanging out with us, and remember—Eagles always soar!

Sheil is joined by Zach Berman of The Athletic to discuss the Eagles' free agency so far. A few guys from the team last season now have new homes and bigger deals, including Jaelan Phillips, Reed Blankenship, and Nakobe Dean. Should the Eagles have made an effort to keep them? The biggest question of the offseason: Will AJ Brown be an Eagle in 2026? Jordan Davis also got a massive deal, but was it warranted? Plus, what type of contract could Jalen Carter receive? Jaelan Phillips signs with the Carolina Panthers (4:07) How should the Eagles address the edge position? (12:18) AJ Brown ongoing discussion (18:57) Could the Eagles have kept Reed Blankenship? (30:06) Jordan Davis' massive deal (40:45) Jalen Carter contract possibilities (50:22) Cam Jurgens goes to Colombia (1:03:34) Email hot takes: Ringerphilly@gmail.com. Follow us on Instagram and TikTok: @ringersphillyspecial Become a member of our Reddit community: https://www.reddit.com/r/RingersPhillySpecial/. The Ringer is committed to responsible gaming. Please check out rg-help.com to find out more, or listen to the end of the episode for additional details. Host: Sheil Kapadia Guest: Zach Berman Producer: Cliff Augustin Music Composed By: Teddy Grossman and Jackson Greenberg Learn more about your ad choices. Visit podcastchoices.com/adchoices

Nakobe Dean departed for the Raiders yesterday, but he gave Eagles fans one last reason to love him. Dean reportedly turned down an identical offer from the Dallas Cowboys, cementing himself as a folk Eagles legend.

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

Nick Kostos breaks down why he wouldn't be surprised if AJ Brown or Jalen Carter are moved this offseason from Philadelphia.

Matt McLennan and his First Eagle colleagues were spot-on at the start of this year in highlighting the risks of America's twin deficits, hyperscaler spending, and "geopolitical disequilibrium" - all forces that continue to restrain the U.S. stock market. Barron's Senior Managing Editor Lauren R. Rublin and Senior Writer Paul R. La Monica speak with Matt about how he sizes up new risks, where he sees the best investment values, and why it often pays to go against the crowd. Learn more about your ad choices. Visit megaphone.fm/adchoices

The Eagle's View Presents“What Is It Like To Run a Podcast”Our panelists for this episode are 8th graders Angela, Dottie, Ellie, and Emma C.Leave a comment and let us know what you think. Did our panelists get this right, or did they miss something?Be sure to like, share, follow, or subscribe to this channel to make sure you do not miss any new episodes from the students of Emerson School.Don't forget to check out our new merchandise on The Emerson School Store website below.https://apparelnow.com/emerson-school-store-apparel/Follow on social media too!https://www.facebook.com/theemersonschool/https://www.instagram.com/emersonschool/

In this episode of Midnight, On Earth, I sit down with bestselling British author and historical investigator Graham Phillips to explore his latest book, 'The Original Zodiac: What Ancient Astrology Reveals About You'. Our conversation dives deep into a forgotten chapter of astrological history - The discovery of the earliest known zodiac system, which contained eighteen signs rather than the twelve most people are familiar with today.Phillips explains how the roots of astrology stretch back to ancient Mesopotamia, emerging from the same mysterious cultural horizon that produced monumental sites like Göbekli Tepe. In those early systems, astrology appears to have functioned through generations of observation, almost like a form of reverse engineering. Instead of starting with a rigid symbolic framework, early astrologers observed patterns in human behavior, personality traits, and life outcomes, then connected those traits back to the time, place, and conditions of a person's birth. Over centuries, these observations became encoded into symbolic archetypes that eventually formed the earliest zodiac signs.At the center of Phillips' research is a mysterious clay tablet held in the British Museum, cataloged as BM 86378. The artifact lists an ancient zodiac system composed of eighteen constellations, many of which are completely absent from the modern Western and Vedic zodiacs. Instead of only the familiar signs, this earlier sky map included figures such as the Serpent, Swan, Crane, Horse, Wolf, and Eagle—symbols that suggest a very different way of interpreting cosmic influence and human identity.Because the tablet preserved the names of the constellations but not their meanings, Phillips attempted to reconstruct the psychological and behavioral traits associated with each sign. Through an extensive survey of hundreds of volunteers from different backgrounds, he analyzed patterns in personality, interests, occupations, habits, and even health tendencies. From this data, he began to piece together what the original zodiac may have signified thousands of years ago.During our conversation we explore how this eighteen-sign system offers an expanded lens through which to view astrology - not as a replacement for the familiar twelve-sign zodiac, but as a deeper layer of symbolic understanding. Phillips explains how the ancient framework may enrich our interpretation of personality, relationships, and destiny by adding additional archetypes that were gradually lost as astrology evolved through later Greek, and Vedic traditions.We also discuss the broader historical mystery surrounding the origins of astrology itself, the possibility that these systems emerged from extremely ancient sky-watching cultures, and how early civilizations attempted to map human experience onto the movements of the heavens. Along the way we touch on archaeology, myth, ancient symbolism, and the enduring human quest to understand who we are and how the cosmos might shape our lives.It's a wide-ranging exploration of forgotten astrology, ancient civilizations, and the archetypal patterns that have guided human thinking about the stars for thousands of years. Drop in!www.grahamphillips.netGraham Phillips Bio:Graham Phillips is one of Britain's bestselling non-fiction authors. A former radio journalist and broadcaster for the BBC, and founder of Strange Phenomena magazine, he is a historical investigator of unsolved mysteries. The author of many books, including The Templars and the Ark of the Covenant, The Lost Tomb of King Arthur, The End of Eden, and Atlantis and the Ten Plagues of Egypt, Graham lives in the Midlands of England. Hosted on Acast. See acast.com/privacy for more information.

Hello and welcome to a new season of the iTnews Podcast. We begin this year by speaking to Aussie Broadband's Head of Cloud and SRE Ben O'Shea.Eagle-eyed iTnews readers and listeners might remember Ben's appearance at Cisco Live in 2024, when he revealed work that was underway to build a new cloud platform for Aussie Broadband's own internal use, and to retire older virtualisation and containerisation platforms.In this episode, we hear where that cloud platform is at a year on, we discuss Ben's role expansion to cover SRE, and we also hear about a recent change to the company's backup tooling.

In Hour 4, the WIP Afternoon Show recap their biggest revelations from Caller of the Year and discuss a former Philadelphia Eagles QB getting a second chance in 2026.

A reading of articles and features from the Am-Pol Eagle

Get in touch with Daryl Bickford call 208-286-0379Victory Over Sin is a show hosted by Mark Renick that addresses issues pertaining to returning citizens and the challenges they face coming out of incarceration. Victory Over Sin airs Saturdays at 12:30 pm. On 94.5 FM and 790 AM KSPD Boise's Solid Talkhttps://svdpid.org/advocacy-systemicchangeofid/https://www.imsihopecommunityphaseii.com/IMSI HOPE COMMUNITY PHASE II can also be found on facebook as well as Instagram and Youtube. Correspondence can be directed to: Address: 1775 W. State St., #191, Boise, Idaho 83702Phone: 208-629-8861 Podcast Website: https://www.790kspd.com/podcast-victory-over-sin/

Get the full episode: https://www.10percenttrue.com/pricing-plans/listPinbag Shaw | 10 Percent True | EP83 Part 1Thomas “Pinbag” Shaw flew the F-4E Phantom II at a pivotal moment in USAF history.Commissioned during the draft era, he entered Tactical Air Command just as the Air Force was absorbing the hard lessons of Vietnam and rebuilding its fighter culture from the ground up.In this first part of our conversation, Pinbag explains:• Why the J79 smoked — and how crews worked around it• What Red Baron reports actually taught young Phantom crews• How Fighter Lead-In training at Holloman reshaped post-Vietnam tactics• The reality of Sparrow employment before modern radar displays• AIMVAL/ACEVAL and what it revealed about missile combat• Combat Tree, radar geometry, and “hot” vs “cold” scope discipline• Nuclear delivery training in the F-4E• And how a loose ejection seat pin bag became a permanent callsignWe also explore the cultural side of 1970s Tactical Air Command — from Aggressor briefings to the infamous “vulnerability period” at the O-Club — and how the Air Force transitioned from the Vietnam experience into the F-15/F-16 era.This episode is a deep dive into Phantom air-to-air tactics, radar intercept mechanics, and fighter culture in the years between Vietnam and the Eagle.Part Two will take us operational — Korea, Germany, Victor Alert, and real-world air defence.If you enjoy long-form, technical conversations with the people who flew the jets, subscribe and join the conversation.0:00 Intro teaser – O-Club tale2:32 Welcome Pinbag and episode outline4:25 Matthew's subscriber question – smoky J79s8:03 Visual acquisition ranges8:45 Pinbag's background and route to the Phantom (nav school and dreamsheets)23:30 Dual controls question26:28 Back to Holloman and dreamsheets35:00 Off to Holloman AFB38:32 Uniform standards – TAC style40:45 Mandatory formation – O-Club43:10 The “Green Door”45:15 Leaving Holloman46:17 Osan → Hahn → Nellis → Clark → Taegu → Lakenheath (after staff job)49:25 Learning from Red Baron reports (classified material?)51:25 TAC rules, callsigns, naming ceremonies, and the Doofer Book53:20 “Opinions are like assholes…”55:00 Fridays at the O-Club – bell rules and intro story1:01:00 McDill for the F-4 RTU – O-Club and games1:07:43 F-4 “of the day” – equipment fit, avionics, etc.1:15:01 Combat Tree1:21:20 Back to the RTU and a callsign story1:26:02 Through the training phases1:29:49 Back to day one1:36:32 Why the air-to-air preference?1:44:50 Navy terminology – tough for WSOs1:48:28 Nuclear strike?1:50:15 What was going on in TAC1:58:04 Pave Spike2:00:20 USAFE realignment, Ready Eagle, and DOC taskings2:06:30 Sparrow developments

Jake and Anthony are joined by Justin Cyrus, CEO and Founder of Lunar Outpost, to talk about their rovers—Eagle and MAPP—and everything else they're working on. Topics Off-Nominal - YouTube Home | Lunar Outpost NASA seeks a “warm backup” option as key decision on lunar rover nears - Ars Technica NASA Administrator Jared Isaacman on X: “Yesterday, I had the privilege of speaking at the @a16z American Dynamism Summit with the builders, operators, and investors helping shape the next era of exploration. NASA has a clear mandate under President Trump's national space policy: Return American astronauts to the Moon” FLEX Rover – Astrolab LTV | Intuitive Machines Lunar Outpost® Moon Rover Space Vehicle 42211 | Technic™ | Buy online at the Official LEGO® Shop US Lunar Outpost celebrates release of Lego Moon Rover Space Vehicle | collectSPACE Follow Justin Justin Cyrus Justin Cyrus (@StarlordCyrus) / X Follow Off-Nominal Subscribe to the show! - Off-Nominal Support the show, join the Discord Off-Nominal (@offnom) / Twitter Off-Nominal (@offnom@spacey.space) - Spacey Space Follow Jake WeMartians Podcast - Follow Humanity's Journey to Mars WeMartians Podcast (@We_Martians) | Twitter Jake Robins (@JakeOnOrbit) | Twitter Jake Robins (@JakeOnOrbit@spacey.space) - Spacey Space Follow Anthony Main Engine Cut Off Main Engine Cut Off (@WeHaveMECO) | Twitter Main Engine Cut Off (@meco@spacey.space) - Spacey Space Anthony Colangelo (@acolangelo) | Twitter Anthony Colangelo (@acolangelo@jawns.club) - jawns.club

As NFL free agency moves closer, it feels like the Eagles will move on from Nakobe Dean. The 94 WIP Morning Show discusses.

Dan Sileo breaks down why the DJ Moore trade to the Bears just spiked A.J. Brown's trade value — if DJ Moore is worth a 2nd and a 5th, what is a top-5 receiver worth? Plus Lane Johnson is actively politicking for Maxx Crosby to become an Eagle, and Eagles free agency strategy with the draft just weeks away.Privacy & Opt-Out: https://redcircle.com/privacy

In this episode of Body Wisdom Rising, Alyssa Stefanson explores the deeper shifts happening both personally and collectively as humanity moves through a period many traditions describe as a turning point.Drawing from ancient prophecies, astrology, and modern consciousness teachings, Alyssa reflects on why so many spiritual teachers are speaking about the window between 2025 and 2027 as a time of global transformation.She explores themes including:• The Eagle and Condor prophecy and the reunion of mind and heart• Why many traditions describe this time as a crossroads for humanity• Richard Rudd's idea of 2026 as the “closing door” of an old cycle• The role of spiritual awakening in times of collective change• Why nervous system regulation and community will be essential moving forward• The importance of ancestral healing and reconnection to the EarthAlyssa also shares reflections from her recent time in Costa Rica and discusses why many people right now are feeling called to step into deeper purpose and service.This episode is an invitation to reflect on a powerful question:What role do you want to play in shaping the future that is emerging?Alyssa's IG: @wildfemininerise Work With Alyssa:Join the email list Sedona Retreat 2026

Sheil is joined by Zach Berman of The Athletic to discuss the major decisions looming for the Eagles' offseason. Zach dropped his blueprint for Howie Roseman to follow (https://www.nytimes.com/athletic/7084093/2026/03/04/eagles-offseason-howie-roseman-aj-brown-free-agency/). The guys review a few of the biggest topics, including a possible AJ Brown trade and how the Eagles would have to replace him. Should the Eagles pursue Maxx Crosby? When should they extend Jalen Carter? Plus, a rant on the Sixers and a loaded mailbag! Should the Eagles trade AJ Brown? (04:00) Will the Eagles pursue Maxx Crosby? (12:12) Will Dallas Goedert be an Eagle next season? (27:04) Will Reed Blankenship be back? (37:32) Jihaad Campbell's potential as a starter (43:42) Possible extension for Jalen Carter (50:09) Nolan Smith possible extension (1:01:00) Mailbag (1:14:53) Email hot takes: Ringerphilly@gmail.com. Follow us on Instagram and TikTok: @ringersphillyspecial Become a member of our Reddit community: https://www.reddit.com/r/RingersPhillySpecial/. The Ringer is committed to responsible gaming. Please check out rg-help.com to find out more, or listen to the end of the episode for additional details. Host: Sheil Kapadia Guest: Zach Berman Producer: Cliff Augustin Music Composed By: Teddy Grossman and Jackson Greenberg Learn more about your ad choices. Visit podcastchoices.com/adchoices

You know that the Partial Historians can't resist talking about Ancient Rome on film, so we were thrilled to chat to Dr Jeremiah McCall about his book, Swords and Cinema.Who is our special guest?Dr Jeremiah McCall (or DMac as his students call him) is a teacher at Cincinnati Country Day School in Ohio with a PhD in Ancient History. Along with an interest in Roman military and political systems in the Republic, he has done a lot of work on pedagogy of using video games to learn about history, publishing Gaming the Past: Using Video Games to Teach Secondary History in 2022. He divides his research time between historical game studies and Roman history. Dr McCall's other publications include The Cavalry of the Roman Republic (2002); the Sword of Rome (2012), Clan Fabius: Defenders of Rome (2018) and Rivalries that Destroyed the Roman Republic (2022). Manly Men We will touch on the battle scenes and depiction of the Roman military in all your favourite Roman movies and TV shows. Things to look out for: · The defeat of Spartacus - Spartacus vs. Rome: The Last Battle· The battle of Alessia (52 BCE) in HBO's Rome - Rome Fighting with Gauls HD· The battle of Philippi in HBO's Rome - HBO Rome - Battle of Philippi (Battle only)· The opening battle sequence in Gladiator (2000) - Gladiator 2000 Opening Battle· And a bit on Centurion (2010) and The Eagle (2011) to finish!· The Eagle | Channing Tatum Fends Off A Midnight Sneak Attack· The Eagle | Channing Tatum Leads Roman Centurions Into Battle· Centurion 2010 Best movie Scene HD· Plus some things that get set on fire! You will need your popcorn for this special episode! Our music is by Bettina Joy de Guzman. For our full show notes and edited transcripts, head on over to https://partialhistorians.com/Support the showPatreonKo-FiRead our booksRex: The Seven Kings of RomeYour Cheeky Guide to the Roman Empire Hosted on Acast. See acast.com/privacy for more information.

Nathan is joined by Eagle varsity basketball players Ty Cavette, Coleman Amis and Caden Fulcher to talk about their round one matchup against Paducah Tilghman.

Headlines and Shot of the Day

John Spagnola spent the 1980's playing tight end for the Eagles. He caught 256 passes, including 14 touchdowns, in eight seasons in Philadelphia, and he helped the Eagles advance to Super Bowl 15 to cap the 1980 campaign. He played his college football at Yale and was originally drafted by the New England Patriots in 1979. In Episode #286 of "1-on-1 with Matt Leon," Matt welcomes Spagnola in studio to talk about his career. They discuss what he is doing now, look back at his time with the Eagles, including his introduction to his first head coach with the Birds, Dick Vermeil, and much more. "1-on-1 with Matt Leon” is a KYW Newsradio original podcast. You can follow the show on X @1on1pod and you can follow Matt @Mattleon1060.

Canty's stroller costs more than Pat makes in a week. Which of his trades is most likely to happen? People are actually buying into the Cowboys! We debate if Kevin Durant's career has been a disappointment and which team he's most closely identified with. Canty's Best Bet & UnSportsmanLike Moments of the Day: Maxx Crosby tweeted an Eagle emoji! Learn more about your ad choices. Visit podcastchoices.com/adchoices

Canty's stroller costs more than Pat makes in a week. Which of his trades is most likely to happen? People are actually buying into the Cowboys! We debate if Kevin Durant's career has been a disappointment and which team he's most closely identified with. Canty's Best Bet & UnSportsmanLike Moments of the Day: Maxx Crosby tweeted an Eagle emoji! Learn more about your ad choices. Visit podcastchoices.com/adchoices

Time to Get Up with franchise tag day! We're looking at ALL of the biggest tag targets! Kenneth Walker! Daniel Jones! (0:00) Meanwhile - a rusty return for Giannis as Boston's B team beats up the Bucks - is Milwaukee running out of time to keep their star from freaking out? (13:30) Plus - bye bye Birdie - why this Eagle absolutely should fly out of the nest and we've got the exact spot he needs to land! (23:00) Learn more about your ad choices. Visit podcastchoices.com/adchoices

Canty's stroller costs more than Pat makes in a week. Which of his trades is most likely to happen? People are actually buying into the Cowboys! We debate if Kevin Durant's career has been a disappointment and which team he's most closely identified with. Canty's Best Bet & UnSportsmanLike Moments of the Day: Maxx Crosby tweeted an Eagle emoji! Learn more about your ad choices. Visit podcastchoices.com/adchoices

Canty's stroller costs more than Pat makes in a week. Which of his trades is most likely to happen? People are actually buying into the Cowboys! We debate if Kevin Durant's career has been a disappointment and which team he's most closely identified with. Canty's Best Bet & UnSportsmanLike Moments of the Day: Maxx Crosby tweeted an Eagle emoji! Learn more about your ad choices. Visit podcastchoices.com/adchoices

Canty's stroller costs more than Pat makes in a week. Which of his trades is most likely to happen? People are actually buying into the Cowboys! We debate if Kevin Durant's career has been a disappointment and which team he's most closely identified with. Canty's Best Bet & UnSportsmanLike Moments of the Day: Maxx Crosby tweeted an Eagle emoji! Learn more about your ad choices. Visit podcastchoices.com/adchoices

The Gary & Shannon Show Hour 3 (03/03) - #WhatsHappening, #SwampWatch, Gary's poolside heroics, and #TrueCrimeTuesday. #WhatsHappening: Market drop and rebound, oil at $75/barrel, 4th person dies in Austin terror-suspected shooting, Georgia father found liable in son's school shooting, Jackie the Eagle lays a rare second egg #SwampWatch: Iran strikes lingering, market impact on stocks and oil, Kristi Noem grilled on Capitol Hill, primaries in North Carolina and Texas Gary rescued a hummingbird from the pool — but hasn't checked back since, so hero or prolonged suffering? #TrueCrimeTuesday: Nancy Guthrie still missing at Day 31, family left a heartbreaking handwritten card, Pima County "reallocating" resources Content creators and conspiracy theorists descending on Guthrie's home — is the online sleuth community helping or hurting? See omnystudio.com/listener for privacy information.

Nick Kostos is joined by Noah Eagle of NBC to talk the NBA and Noah's broadcasting career

Nick Kostos is joined by Noah Eagle, the best sound from the weekend in sports and best bets for Monday Night!

Hour 2: Silver & Carlos Ramirez recap their conversation with Jennifer Lee Chan and carry it into the 11:00 hour, where they rank the 49ers' most pressing areas of need. While offensive line is the number one most talked about deficiency among listeners, does it rank above other needs such as D-line or wide receiver? NBC play-by-play voice Noah Eagle also stops by ahead of calling Warriors vs Clippers tonight at Chase Center.See omnystudio.com/listener for privacy information.

NBC play-by-play announcer Noah Eagle joins Greg Silver & Carlos Ramirez ahead of tonight's Warriors vs Clippers matchup at Chase Center. They dive into Darius Garland's anticipated Clippers debut and the Warriors' struggles without Steph Curry. Noah shares his insights on how the absence of top players affects the team's style and the importance of developing young players like the Warriors' newly paid Gui Santos. They also discuss the issue of tanking in the NBA and potential solutions, including reversing the lottery odds to incentivize teams to compete.See omnystudio.com/listener for privacy information.