Podcasts about Wide

On the eve of the NFL's legal tampering period, Monte and Sal break down what the New York Giants could do as free agency begins. Monte returns from Mexico sporting a visible injury (and plenty of cartel jokes), while the duo analyzes the team's key pending free agents—Jermaine Eluemunor, Cor'Dale Flott, and Wan'Dale Robinson—predicting which will return and which are likely gone. They game out cap space after restructures, debate top needs (cornerback, interior offensive line, linebacker, run-stuffing defensive tackle, weapons), evaluate realistic targets like Elijah Vera-Tucker, Jamal Dean, Kaden Elliss, Sebastian Joseph-Day, Rico Dowdle, Dallas Goedert, and Mike Evans, and discuss building a wide-receiver-by-committee approach around Malik Nabers versus chasing a splash veteran. Expect split predictions, scheme-fit arguments, and growing excitement for the new Harbaugh/Ponte/Shane era.Timestamps (Shortened with Corrected Names):00:00 – Intro & Monte's Mexico update01:03 – Free agency timeline & expectations01:57 – Team priorities & targets overview03:56 – Pending free agents breakdown19:15 – Cap space & restructuring plans26:30 – Cornerback targets & debate32:36 – Interior O-line targets & predictions38:44 – Linebacker targets & picks41:48 – Interior D-line targets46:58 – Weapons philosophy (run game focus)49:01 – Tight end targets & strategy53:48 – Running back targets & committee approach58:00 – Wide receiver committee & targets1:02:00+ – Final predictions & closing hypePlease Rate and Subscribe!Follow Us:@HesAGiantPod@montecri5to@queens_guy

Finally profitable again, the auto insurance industry has developed a renewed sense of competition for customers. Clark shares guidelines for finding companies big on customer service and value.  Also,  Americans are saving big bucks through “no spending” trends, and switching retailers. Thrift-centered businesses like Goodwill and Dollar Tree are thriving across all demographics. Clark admits he was wrong about Dollar Tree's decision to move past its signature $1 price point, explaining how the transition to a multi-price range has elevated the brand across the country. Best Auto Insurers: Segment 1 Ask Clark: Segment 2 Discounters Thriving: Segment 3 Ask Clark: Segment 4 Mentioned on the show: Best Auto Insurance Companies - Clark Howard Report: These 10 Vehicles Are the Best for the Money in 2026 New York Post: Dollar Tree is invading posh neighborhoods after years of catering to low-income customers— breaking ‘stigma of the dollar store' Best Term Life Insurance Companies, Plans & Coverage How To Buy Term Life Insurance in 7 Easy Steps - Clark Howard What Is a Credit Union? - Clark Howard 16 of the Best High-Yield Online Savings Accounts in March 2026 Clark.com resources: Episode transcripts Community.Clark.com  /  Ask Clark Clark.com daily money newsletter Consumer Action Center Free Helpline: 636-492-5275 Learn more about your ad choices. Visit megaphone.fm/adchoices

The Wide, Wide World (1850) by Susan Warner follows a young girl named Ellen who must leave her mother and travel through the countryside, learning patience, kindness, and resilience as she encounters new people and places.My name is Teddy and I aim to help people everywhere get a good night's rest. Sleep is so important and my mission is to help you get the rest you need. The podcast is designed to play in the background while you slowly fall asleep.For those new to the podcast, it started from my own struggles with sleep. I wanted to create a resource for others facing similar challenges, and I'm so grateful for the amazing community we've built together.

Escape rooms let your family cooperate in new and interesting ways. But do you prefer a physical, in-person escape room, a video game, or a board game experience? 0:00:00 Fact for 418 HTTP code 418: “I’m a teapot” Sponsor Message If you want help planning for your kid’s college education, set up a time for a free 15-minute call by going to firstmovefinancial.com/familygamers. 0:05:00 What We’ve Been Playing Embers (our review)Lands of AmazementAspensVerdant Arizona 0:12:50 The Family Gamers Community We’re so happy to welcome new members! You can join the community on Facebook too. 0:13:30 #Backtalk You shared your purging regrets on Facebook and the #backtalk channel of the Discord. 0:19:25 Escape Rooms Physical escape rooms – we’ve done a few. Very cool but can feel high pressure. They’re great to do in a group, letting everybody work on different things. Doing it as a family is expensive! Video games are a much cheaper way to capture this style really well: Portal, The Room, Escape Academy Board Game “Escape Rooms” These range in size and playtime. Some are more puzzley, some are more narrative-driven. But any of them can be a great family experience. And we have reviewed a bunch of them – we’ll talk about six series here: EXIT series – Fairly immersive, with a plot and setting that hangs together. Everything you need is in the box. Wide variety of puzzles to write on, manipulate, cut, etc. But comes with a downside – that wide variety means you almost always run into a puzzle in the game that is not figure-out-able (for us). They come in a huge range of difficulty, including several that are appropriate to do with younger kids who are just barely reading. Unlike the other games in this list, we think they’re best with more than 2 players. There are also EXIT Kids games now! (Check out the EXIT games we’ve reviewed.) Unlock series – These require an app. Other than the app, completely card-based and re-settable to pass on to a friend to try. These also have a juvenile line now – Unlock Kids. Our experience has been really uneven. Some really great (Wizard of Oz, Star Wars). Others are just really weird, with puzzles don’t make sense. We generally recommend these, but use caution. Holiday Hijinks – probably our favorite compact escape-room type game. Packs a ton of puzzles into 18 cards and a web app. Full of puns, trivia, and holiday cultural references. Still best for very small groups, since there’s such a small space to work in. Family friendly, although younger kids will probably be frustrated that they don’t have the trivia knowledge to contribute unless they’re very knowledgeable about the holiday. (Check out our reviews and interviews about Holiday Hijinks.) Deckscape – feels like a “choose your own adventure” narrative. Mostly a deck of cards, but with a few accessories that made it more immersive. Puzzles could not be attempted more than once, which made the choices feel high-stakes. Best with 2-3 players, because you’re only looking at a few cards at a time – unless you’re willing to take your time and pass them around the table. (We reviewed Deckscape: The Mystery of El Dorado.) Backstories – not really an escape room, more of a narrative adventure. Work through decisions one at a time as a group. But not only re-settable, it’s replayable, with branching paths and different endings depending on the decisions made! Not exactly family-friendly. Lots of violence and some death. (Check out our Backstories reviews.) Star Trek: Cryptic – as Trek fans we really loved this one. Work through three different “chapters” in a Starfleet officer’s life, with very thematic puzzles. Pretty much re-settable, but you’ll get great value out of this one even if you only play it once – it takes 3-4 hours to do the whole thing, split into several sessions. Coded Chronicles (we reviewed Scooby Doo & The Goonies games) – also very narrative driven. But spreads out the responsibility to progress the narrative to all the players! There are multiple books to read in different character “voices”, even though the team is making decisions together. Also re-settable. Very family-friendly, even for kids who are unfamiliar with Scooby Doo or The Goonies. 0:42:00 New Backtalk Question Have you ever done an in-person escape room? If so, what did you think of it? If not, why not – cost, family-friendliness, or something else? Tell us on the #backtalk channel on our Discord, or in our Facebook community. Find Us Online: Facebook: @familygamersaa and thefamilygamers.com/communityTwitter (X): @familygamersaaInstagram: @familygamersaaTikTok: @familygamersaaBluesky: @familygamersaaThreads: @familygamersaaYoutube: TheFamilyGamers or join the Family Tabletop Community on Discord! thefamilygamers.com/discord Or, for the most direct method, email us! andrew@thefamilygamers.com and anitra@thefamilygamers.com. PLEASE don’t forget to subscribe to the show, tell your friends about the show, and leave us a review at Apple Podcast or whatever your podcast subscription source is. We’re also on Amazon Music, TuneIn, and Spotify. You can also now find us on YouTube Music! So pull it up and give us a listen while you’re toiling away at work :) Music for The Family Gamers Podcast is provided with permission from You Bred Raptors? The Family Gamers is sponsored by First Move Financial. Go to FirstMoveFinancial.com/familygamers to learn how the team at First Move Financial can help you pile up the victory points. The post Episode 418 – Escape Rooms appeared first on The Family Gamers.

Marc Vandermeer and John Harris deliver a Texans offseason progress report and talk to MJ Stewart about his return to Houston. In this episode: * Offseason progress report — grading RB, TE, OL and WR moves so far * David Montgomery addition and remaining running back needs heading into the draft * Foster Moreau signing and the state of the tight end room * Offensive line retooling: Braden Smith, Ed Ingram, Trent Brown and draft targets * Wide receiver outlook: Jayden Higgins, Jaylin Noel, Tank Dell's return, Christian Kirk to San Francisco * MJ Stewart in-studio interview — culture, leadership, and the Baltimore game * NFL news: Justin Fields traded to Kansas City Chiefs, Darius Slay retiresSee omnystudio.com/listener for privacy information.

Today's episode of the Punk CX podcast features Raymond Gerber, the Co-Founder of the Institute for Journey Management (I4JM), Founder of JourneyCentric-CX and author of three new books. He joins me today to talk about the third book (Journey to Customer Obsession- A Leadership Blueprint for CX Maturity and Enterprise Transformation: How executives can turn fragmented CX efforts into enterprise-wide customer obsession), which is effectively the executive edition of the other two books. We talk about the 9-stage journey that organisations go through on the road to customer obsession, journey management and orchestration, why many organisations often stumble into the first stage, Awareness, by accident, the non-negotiable output of consideration, the second stage of the journey, a brief overview of the other stages, and how a leader and their team should get started with all of this. This interview follows on from my recent interview – More Than A Motto – Interview with Justin Robbins of Metric Sherpa – and is number 577 in the series of interviews with authors and business leaders who are doing great things, providing valuable insights, helping businesses innovate and delivering great service and experience to both their customers and their employees.

From a mile-wide UFO over Arizona to the little girl who secretly named a planet, March 13 has always had something to hide. | The Morning Weird Darkness*No AI Voices Are Used In The Narration Of This Podcast*WeirdDarkness® is a registered trademark. Copyright ©2026, Weird Darkness.EPISODE PAGE: https://WeirdDarkness.com/MWD20260313NOTE: Some of this content may have been created with assistance from AI tools, but it has been reviewed, edited, narrated, produced, and approved by Darren Marlar, creator and host of #WeirdDarkness — who, despite popular conspiracy theories, is NOT an AI voice.

Florida State wrapped up the first week of spring camp Friday with its first padded practice, with coach Mike Norvell pointing to several newcomers who have made early impressions on a roster still taking shape. “There were some good things that we did and there's some ugly moments, and some really good responses throughout the course of practice,” Norvell said. “Some big plays showed up both sides of the ball.” We were aggressive in our installations, just trying to force guys with their study, their process, and the application of the things we put in,” he said. “I felt the winter program prepared them.” The linebacker room drew particular praise. Freshman Noah LaVallee forced a fumble in the opening practice Monday and followed with open-field tackles on Friday. Norvell also mentioned freshmen Karon Maycock and Daylen Green as contributors in the early going. Linebacker Izayia Williams remains sidelined working back from a knee injury but has been present in meetings. Veteran linebacker Chris Jones said the first day in pads brought a different kind of energy to the group. “I love to hit, so it was just good to be back in pads for sure,” Jones said. He also credited the group's “gradership program” under position coach Coach Sims, where upperclassmen are tasked with pulling younger players aside and coaching them up throughout practice: “That one thing you tell him that one time, he can remember that and that'll make him better.” On the defensive line, Norvell said Franklin Whitley has shown natural strength despite limited football experience, while Earnest Rankins drew praise Friday after being challenged heading into the padded session. “We've got big expectations for him,” Norvell said of Rankins. Norvell also singled out edge rusher Deamontae Diggs, who missed most of last season with an injury, as a standout Friday. “He's not fully there, but if he keeps taking steps, he's going to provide a real presence on the edge.” First-year edge coach Nick Williams also drew praise. “I love his energy,” Norvell said. “He's going to push guys to an expectation of what it needs to be, and he does that for himself.” Legacy wide receiver Devin Carter has also caught Norvell's eye. “He's a good worker. He really loves the game. You could tell he's a technician of the game,” Norvell said. “Not everything has gone well for him this week, but even in the moments where it wasn't a great play, you can feel his urgency to go get better.” Wide receivers Darryon Williams and EJ White have also been seeing reps, with Norvell noting good moments alongside areas still to develop. In the backfield, Norvell called transfer Tre Wisner “about all the right things that you want,” pointing specifically to his leadership, football IQ and work in pass protection. “He's smart, he studies, he's got versatility — protections are something that's important to him,” Norvell said. Sophomore Ousmane Kromah was quick to echo the praise, saying that “he really does take care of everybody.” Participating in his first spring camp after arriving last summer as true freshmen, Kromah said Wisner has helped him process the game faster. “My game has grown in majority vision,” Kromah said. Kromah also praised four-star freshman Amari Thomas, saying the room has barely scratched the surface with him. “Just wait till we actually groom him and teach him how to do certain things,” Kromah said. “It's over.” At quarterback, Norvell said Auburn transfer Ashton Daniels has produced at least one explosive vertical play in each of the first three practices. “For a guy that has a lot of recognition for his movement skills, he's been able to locate the ball and put it in good places,” Norvell said. Freshman Jaden O'Neal, out for the season due to injury, has remained active in the meeting room, something Norvell said he's been pleased with. Learn more about your ad choices. Visit megaphone.fm/adchoices

Snow is forecast to develop across central and southern Minnesota through the day Saturday and intensify Saturday night. Winter storm warnings are in place for the weekend for most of the southern half of the state, including the Twin Cities. A Minnesota Senate Committee Friday approved a bill that bans assault weapons.Those stories and more in today's evening update. Hosted by Emily Reese. Music by Gary Meister.

In this episode, Jesus compares the Kingdom of God to a net that is cast wide to catch all kinds of fish!

A philosopher, a mage, and a swordsman are sent on an impossible quest from which they know they will not return alive. Genre: Mythology   Excerpt:The philosopher felt her heart go still. She felt the cold steel of the swordsman's sword quivering by her right side. She felt the warm spark of the mage's magic prickling by her left side.  In that moment, and none other since, she had wished her friends would unleash their might and fury…   The Wheel of Fiction Turns. What did it land on this time?Each Season 9 story follows a theme chosen by the Wheel of Fiction. Thirteen spokes. Eight are the themes from previous seasons. One is "Turn Again." One is a wild card. And three are covered in question marks and will be revealed when the wheel lands on them. See a story trailer and a (satisfying) video of the wheel turning here: The Last Night of Grief This episode landed on CREATURES. Find more stories and episodes about creatures here: Year of Creatures.   MERCH!Interested in merch, like mugs and notebooks, featuring my artwork?Please visit my Store page for info on where you can buy: STORYFEATHER STORE   The Store page also has sign-up forms for my two email newsletters: Storyfeather Gazette (if you'd like to keep up with the fiction I create)Fictioneer's Field Guide (if you'd like writing tips and guidance from me) Choose what you want. (Either way, you're choosing high jinks.)   MY FIRST BOOK (yay)Ever wonder how I've gotten all these hundreds of stories written? I have a method. You can learn it in my book called Fictioneer's Field Guide: A Game Plan for Writing Short Stories. It's now available from Amazon as an eBook, paperback, and hardcover. You can also get there from my Store page: STORYFEATHER STORE   CREDITS Story: "The Last Night of Grief" Copyright © 2022 by Nila L. PatelNarration, Episode Art, Editing, and Production: Nila L. Patel   Music:"Flames on ice" by NICHOLAS JEUDY (Intro)"Haven" by NICHOLAS JEUDY (Outro)"Abstract Vision #5" by ANDREW SITKOV (Outro)   Music by NICHOLAS JEUDY (Dark Fantasy Studio)"Whispers""Scroll of the wind walker""Wide place""Fallen leaves (seamless)""To Falgalown""Signs of desolation""The last stand""Adventure""Haven""Runes""Compass""In the shadows""Flames on ice"   Music by Nicholas Jeudy and Andrew Sitkov is licensed from GameDev MarketSound effects from AudioJungle, GameDevMarket, and Soundly (through Hindenburg)Vocal effects created with Audacity Changes made to the musical tracks? Just cropping of some to align with my narration.  Find more music by Nicholas Jeudy and Andrew Sitkov at gamedevmarket.net Find more stories by Nila at storyfeather.com   Episode Art Description:Digital drawing. Facing forward stands a creature with three dog-like heads with different fur colors. The heads emerge from serpent-like necks attached to a central body from which the top heads of three legs are visible. All eyes are glowing. All the snouts are contracted as if growling, mouths parted, revealing fangs. All ears are perked up. A forked tongue emerges from the head at right. Snake-like fangs drip a drop of venom from the head at left. Behind and above the heads, an armored segmented body is visible extending up out of frame. Extending down from top left of frame is a segmented spiked tail curling upward. Behind the creature is the opening of a cave. Rectangular image is made square with top and bottom borders that reflect blurred versions of the faces in the main image. Watermark of "Storyfeather" on cave wall, along right side of torso.

On this episode the Cincinnati Pink Pony crew joins us at the After Party as they talk about working and partying at the Cincinnati party bar. Matt tells us about his staycations at El Paso County jail and Mad's catches us up from her last episode and her ex drama. Follow us on social media @AaronScenesAfterParty

JP Finlay and Mitch Tischler join you to discuss some of the moves Commanders in the 2nd wave of free agency including continue to address needs on the defense and what's next for Adam Peters and company moving forward. The guys also discuss the withdrawal of the Maxx Crosby deal and some other news and notes around the leagueSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The guys discuss every position group in the draft, talk about who could go in the first round, and chat about which players are rising up the board. :00 - Quarterbacks 10:35 - Running backs 16:35 - Tight ends 23:20 - Wide receivers 32:10 - Guards 36:00 - TacklesSee omnystudio.com/listener for privacy information.

TrulySignificant.com honors the extraordinary culture of the Texas Parks & Wildlife division led by Rodney Franklin.  Hear Rodney's backstory, starting with his upbringing in Paris, Texas and the positive influence of his Spanish teacher. And here is an excerpt from the upcoming book Big Hearted Texans that captures the spirit of this podcast:Every significant life has a moment—sometimes a single flash, sometimes a slow dawn—when a person realizes: This isn't just work. This is stewardship.For Rodney, it sharpened when his world expanded from a small historic site to the wide acreage of Lake Bob Sandlin State Park. Here was a state park as a backyard. Here was prescribed fire and wildlife biology and the living, breathing complexity of ecosystems. Here were school groups arriving wide-eyed—kids experiencing the outdoors for the first time.Rodney watched their faces change as they learned, as fear turned into curiosity, as wonder landed and stuck.And he realized something that sits at the center of this whole conversation: A Culture of Significance is built when you understand the impact of an ordinary day on someone else's forever.Seeing is believing. Check out www.tpwd.texas.gov and you will understand how this narrative unfoldsTexas parks have been called the “soul of the state.” If you're a native Texan—or even a long-term adopter—you understand why.Texas is rugged. Generous. Wide open. And proud. But Rodney makes the hard truth plain: in a state this big, less than five percent is public land. That fact changes the entire moral math. What you have is precious because there is so little of it.So the question becomes: how do you protect a place without turning it into a museum behind a fence? Rodney's answer is the balancing act at the heart of stewardship: protect the resource, and still invite the public in—because people won't fight to preserve what they've never been allowed to love. That means thoughtful trails. Responsible infrastructure. Planning systems that manage crowds. And experts—biologists, archaeologists, historians, interpreters—people who understand that parks are not “just” parks. They're habitat and heritage, science and story.Become a supporter of this podcast: https://www.spreaker.com/podcast/success-made-to-last-legends--4302039/support.

Today we are rehashing Younger Season 4, Episode 9: "The Incident at Pound Ridge." Join us as we discuss a jalapeño mishap, the annual Empirical picnic, the most competitive potato sack race (ever?), and so much more!

This week's Frankly is another edition of Nate's Wide Boundary News series, where he invites listeners to view the constant churn of headlines through a wider-boundary lens. In this installment, Nate addresses the U.S. and Israeli military offensive against Iran and traces the reverberating effects that extend far beyond the conflict itself, starting with what the closure of the Strait of Hormuz means for a civilization that routes a massive share of its physical economy through a single maritime corridor. Nate begins with the core misperception that oil registers as roughly 3% of GDP by cost, when in reality it underpins 100% of economic activity. Building off of that, he outlines a series of second- and third-order effects that rarely appear in headline coverage, including hidden dependencies on sulfur, liquefied natural gas, and nitrogen fertilizer that connect the Strait of Hormuz to mining operations, European energy security, and global food systems. He also explains the stock-and-flow imbalance between expensive missile interceptors and cheap drone warfare, and the difficult choices facing aging Middle Eastern oil fields if production is forced to shut in. Finally, Nate considers the religious narratives on all three sides of the conflict, where Christian, Jewish, and Shia Islamic end-times frameworks each cast the war as prophetic fulfillment, short-circuiting the feedback loops that normally slow escalation. What does the exposure of a single shipping corridor reveal about the deep energy dependencies of modern civilization? How might the second- and third-order effects of this conflict, from fertilizer to metals to food prices, reshape the global economy in ways that outlast the war itself? And when all parties in a conflict believe they are fulfilling divine prophecy, where do the off-ramps for de-escalation appear? (Recorded March 9th, 2026)   Show Notes and More   Watch this video episode on YouTube   Want to learn the broad overview of The Great Simplification in 30 minutes? Watch our Animated Movie.   ---   Support The Institute for the Study of Energy and Our Future   Join our Substack newsletter   Join our Hylo channel and connect with other listeners

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

(0:00-21:21) The Eagles saw key defensive players leave in free agency, but it kind of went as it expected(21:21-33:01) Andrew and John react to Jesus Luzardo's contract extension (33:01-41:22) Wide receivers get paid on the open market & texters react to the Eagles seeing free agents walk Please note: Timecodes may shift by a few minutes due to inserted ads. Because of copyright restrictions, portions—or entire segments—may not be included in the podcast.For the latest updates, visit the show page Kincade & Salciunas on 975thefanatic.com. Follow 97.5 The Fanatic on Twitter, Facebook, and Instagram. Watch our shows on YouTube, and subscribe to stay up-to-date with all the best moments from Philly's home for sports!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Hour 3: Silver & JD continue reacting to Mike Evans agreeing to a three-year, $60 million deal to join the 49ers and weigh in on the implications of how it affects the team's wide receiver room. The guys also ask if the Evans signing should affect how they approach Trent Williams's situation if the team seems more committed to winning immediately. JD shares his thoughts on the 49ers' draft strategy and the importance of developing young players like Jordan Watkins and Ricky Pearsall.See omnystudio.com/listener for privacy information.

Hour 3: Silver & JD continue reacting to Mike Evans agreeing to a three-year, $60 million deal to join the 49ers and weigh in on the implications of how it affects the team's wide receiver room. The guys also ask if the Evans signing should affect how they approach Trent Williams's situation if the team seems more committed to winning immediately. JD shares his thoughts on the 49ers' draft strategy and the importance of developing young players like Jordan Watkins and Ricky Pearsall.See omnystudio.com/listener for privacy information.

Luke 4:5-8

Ask. It’s an open-ended word. Wide open. Ask who? Ask what? In this step, we humbly ask God to remove all our shortcomings. That’s a big Ask. Join us this Sunday, as we explore what this means for our salvation and spiritual growth.

America and Israel's attacks on Iran have dominated the news all week. The bombs are literally half a world away from regional Australia - but the flow on effects are widespread and do feel close to home, including for Iranians living in Australia, those caught up travelling in the regions and on every day activities from filling up to bowsers to regional Australians who expert lamb or yoghurt.

 ChatGPT has been in the news a lot lately and, as a result, quite a few STEM-Talk listeners have tossed us questions about the reliability and limitations of generative-artificial intelligence chatbots as well as large-language models more broadly.  Ken and Dawn tackle this question and a number of others in today's Ask Me Anything episode. We have listeners wondering why astronauts train in underwater conditions for spacewalks; icebreakers in antarctica; the value of supplementing with urolithin-A; and the effectiveness of L-citrulline in helping aging blood vessels. Ken also weights in on questions related to lithium deficiency and the onset of Alzheimer's disease; a study that found mTOR activation may not be necessary for ketamine's beneficial effects in the context of depression; and a paper that demonstrated short-term mTOR inhibition by rapamycin improved cardiac and endothelial function in older men. Show notes: [00:02:49] Ken opens our AMA with a listener question for Dawn, which asks why, despite the differences between diving and zero-gravity environments, why do astronauts train in underwater conditions for spacewalks. The listener goes on to mention an article they read about NASA's neutral buoyancy lab in Houston, which contains a partial replica of the International Space Station. [00:07:42] A listener asks Ken if he is still optimistic about the value of supplementing with urolithin-A, and if so, is there a brand he recommends. Ken mentions episodes 118, with Julie Anderson, and 173, with Anurag Singh. Ken also discusses a paper titled “Effect of the mitophagy inducer urolithin A on age related immune decline, a randomized placebo-controlled trial” co-authored by Anurag. Ken also mentions clinical research supporting the urolithin-A supplement Mitopure. [00:10:53] A listener asks Ken about a paper titled “Short-term mTOR inhibition by rapamycin improves cardiac and endothelial function in older men: a proof-of-concept pilot study.” [00:14:29] Ken discusses a 2020 paper from a research group at Yale, which suggested that mTOR activation may not be necessary for ketamine's beneficial effects in the context of depression. The paper also reported that m-TOR suppression via rapamycin might prolong ketamine's antidepressant effects. [00:18:47] A research scientist formerly working in Antarctica asks Ken about Russia's dominance in the realm of ice breakers. [00:23:55] A listener mentions that for some people, when they used ChatGPT to ask about the assassination of political commentator Charlie Kirk, ChatGPT sometimes responded by denying the assassination occurred. The listener asks Ken about the credibility and reliability of generative AI and large-language models. [00:28:49] Several listeners have submitted questions for Ken regarding a paper published in Nature in August of last year titled “Lithium deficiency in the onset of Alzheimer's disease.” Ken gives his thoughts on this paper. [00:31:56] For our final question this AMA, a listener asks Ken about the arginine paradox, which regards L-arginine, which is used by the body to make nitric oxide, which is necessary to relax and maintain flexibility of blood vessels. However, several papers have reported that supplementation of arginine does not reliably improve aging blood vessels. In contrast, recent research suggests that L-citrulline might be more effective. The listeners sent questions asking about the possible effects of citrulline in vascular health and aging. In his answer, Ken cites the following papers: — Administration of L-arginine plus L-citrulline or L-citrulline alone successfully retarded endothelial senescence. — Effects of L-Citrulline Supplementation on Endothelial Function, Arterial Stiffness, and Blood Glucose Level in the Fasted and Acute Hyperglycemic States in Middle-Aged and Older Adults with Type 2 Diabetes. — Citrulline Supplementation Improves Microvascular Function and Muscle Strength in Middle-Aged and Older Adults with Type 2 Diabetes. — Effects of L-citrulline supplementation and watermelon intake on arterial stiffness and endothelial function in middle-aged and older adults: a systematic review and meta-analysis of randomized controlled trials. — Citrulline regulates macrophage metabolism and inflammation to counter aging in mice. If you have questions for Ken and Dawn after listening to today's episode or any episode of STEM-Talk, please email our producer, Randy Hammer, at rhammer@ihmc.org.  Links: Learn more about IHMC STEM-Talk homepage Ken Ford bio Ken Ford Wikipedia page Dawn Kernagis bio    

We are back with a brand new episode featuring the return of Black Santa himself! He brings along his elf Mia, as she comes on answers our horny questions and tells us about her not so long relationship history. Plus Gee tells us about some Mia Mishaps at HQ The Lounge. Follow us on social media @AaronScenesAfterParty

Sermon from the pulpit of Falls Baptist Church

 takeaways   The NFL Combine generates excitement but can lead to overreactions. Not all athletic performances translate to on-field success. Draft capital is crucial for running backs in the NFL. Wide receiver speed was a highlight of this year's Combine. Players like Emmett Johnson and Kenyon Sadiq showed varying levels of performance. Combine results can influence rookie draft positions significantly. Quarterback performances were less impactful due to limited testing. It's important to maintain perspective on Combine results. Excitement for rookies can lead to more trades in fantasy leagues. Understanding player profiles is key to evaluating Combine performances. Chapters   00:00 NFL Combine Reactions and Overreactions 05:40 Evaluating Emmett Johnson's Performance 10:31 Kenyon Sadiq: A Rising Star? 18:39 Running Back Class Insights 25:28 Judarian Price and Jonah Coleman's Combine Impact 35:38 Eli Heidenreich's Combine Performance 37:39 Jeremiah Love: The Clear RB1 38:54 Seth McGowan's Surprising Athleticism 44:28 Wide Receiver Class: Speed and Talent 49:27 Bryce Lance: Rising Star from North Dakota State 55:37 Jeremy Bernard: The Unsexy Yet Reliable Pick     Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this second part of our series on engineering organizations, Jeff and Luca explore how companies that build products should focus their efforts differently depending on their stage and scope. We start with startups and early-stage companies desperately searching for product-market fit, where the brutal truth is: quality doesn't matter yet. Your MVP should embarrass you—if it doesn't, you waited too long. We discuss the critical mental shift from throwaway prototypes to proper engineering once validation arrives, and why technical founders often fail by solving the wrong problem brilliantly. Moving up the ladder, we examine narrow-focus companies that have found their niche—like the German firm that does nothing but maintain a 100-year-old anchor chain machine, or specialists in medium-power electrical switches. These companies win through efficiency and deep expertise, but face existential risk if the market shifts. Finally, we tackle wide-focus companies introducing multiple product lines, where the challenge becomes running internal startups while managing established products, each requiring radically different approaches. The key insight: your focus must match your product's lifecycle stage, whether that's ruthless speed, cost optimization, or high-level process learning. Key Topics [02:30] Startups and early-stage companies: the existential search for product-market fit [06:45] The MVP philosophy: if you're not embarrassed, you waited too long [11:20] Quality vs. speed vs. scope: why quality doesn't matter in early stages [15:40] The Potemkin village approach: building facades to validate demand [19:15] Embedded products and MVPs: when physical products need creative shortcuts [23:50] The critical switch: from prototypes to proper engineering after validation [28:30] Narrow-focus companies: German hidden champions and deep specialization [34:10] Wide-focus companies: running internal startups within established organizations [40:25] Product teams and parallel focuses: managing different lifecycle stages simultaneously [45:00] Large established companies: high-level process learning and avoiding organizational weight Notable Quotes "If you read the Lean Startup, they will explicitly say: if you weren't embarrassed by your MVP, you waited too long. It really has to be painfully flimsy because you cannot afford to do it well." — Luca "Quality doesn't even factor because you're very explicitly building mock-ups from chewing gum and paper mache. They are fully intended to be thrown away." — Luca "Getting that product-market fit is existential. You will die if you do not get it and get it relatively quickly." — Jeff Resources Mentioned The Lean Startup - Eric Ries' book discussing MVP philosophy and the importance of being embarrassed by your first product The Mom Test - Rob Fitzpatrick's book about getting real customer feedback and validation through financial commitment The Art of Innovation - Tom Kelley's book on IDEO's design process, including the clothespin switch story Luca's Website - Trainings on embedded agile, AI in embedded systems, and more Jeff's Website - Consulting services for medical device software development You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/

The guys review what they learned from the NFL Combine, talk about each position group, and discuss the biggest takeaways from the week. :00 - Quarterbacks 7:40 - Running backs 12:00 - Wide receivers 22:30 - Tight ends 25:55 - Offensive line 34:50 - Defensive line 36:20 - Edge rushers 44:10 - Linebackers 50:50 - Cornerbacks 54:05 - SafetiesSee omnystudio.com/listener for privacy information.

HOUR 4 - Baseball reporter Alden Gonzalez joins the show to preview today’s Team USA vs. Giants exhibition matchup and what to watch for. In the final segment, we kick back for a lighthearted “Wide Shot Tuesday” and have some fun with the crew.See omnystudio.com/listener for privacy information.

HOUR 4 - Baseball reporter Alden Gonzalez joins the show to preview today’s Team USA vs. Giants exhibition matchup and what to watch for. In the final segment, we kick back for a lighthearted “Wide Shot Tuesday” and have some fun with the crew.See omnystudio.com/listener for privacy information.

This week Seth Paridon and Jon Parshall welcome author Justin LaBorde to the show to talk about his new book, Scattered Far and Wide: The Naval Academy Class of 38 at War. The guys dig into some of the incredible personalities that populated the Class of 38, some of the first Academy grads to see action during the war in the Pacific. With service at Pearl Harbor, Midway, Java Sea, and beyond, the stories are compelling and inspirational. Check out this week's episode for yet another book recommendation and discussion of some amazing young men. #wwiihistory #ww2 #usnavy #usa #usarmy #medalofhonor #enterprise #aircraft #aircraftcarrier #cv6 #midway #wwii #wwiihistory #ww2 #worldwar2 #usnavy #usnavyseals #usmc #usmarines #saipan #usa #usarmy #aircraft #aircraftcarrier #battleship #battleships #ussenterprise #aircraftcarriers #museum #essex #halsey #taskforce38 #wwii #wwiihistory #ww2 #usnavy #usa #usarmy #medalofhonor #enterprise #aircraft #aircraftcarrier #cv6 #midway #wwii #wwiihistory #ww2 #worldwar2 #usnavy #usnavyseals #usmc #usmarines #saipan #usa #usarmy #aircraft #aircraftcarrier #battleship #battleships #ussenterprise #aircraftcarriers #museum #hollywood #movie #movies #books #mastersoftheair #8thairforce #mightyeighth #100thbombgroup #bloodyhundredth #b17 #boeing #airforce wwii #wwiihistory #ww2 #usnavy #usa #usarmy #medalofhonor #enterprise #aircraft #aircraftcarrier #cv6 #midway #wwii #wwiihistory #ww2 #worldwar2 #usnavy #usnavyseals #usmc #usmarines #saipan #usa #usarmy #aircraft #aircraftcarrier #battleship #battleships #ussenterprise #aircraftcarriers #museum #hollywood #movie #movies #books #oldbreed #1stMarineDivision #thepacific #Peleliu #army #marines #marinecorps #worldwar2 #worldwar #worldwarii #leytegulf #battleofleytegulf #rodserling #twilightzone #liberation #blacksheep #power #prisoner #prisonerofwar #typhoon #hurricane #weather #iwojima#bullhalsey #ace #p47 #p38 #fighter #fighterpilot #b29 #strategicstudying #tokyo #boeing #incendiary #usa #franklin #okinawa #yamato #kamikaze #Q&A #questions #questionsandanswers #history #jaws #atomicbomb #nuclear #nationalarchives #nara #johnford #hollywood #fdr #president #roosevelt #doolittle #doolittleraid #pearlharborattack #salvaged #medalofhonor #tarawa #malayalam #singapore #guadalcanal #china #burma

Ashley Roberts, Content Director of Printing Impressions, joins Deborah Corn to discuss the role of journalism in the printing industry, AI's impact on trade media, how her team is focused on more original storytelling, and how thoughtful industry coverage supports smarter business decisions. Mentioned in This Episode: Ashley Roberts: https://www.linkedin.com/in/ashley-roberts-a9148465/ Printing Impressions: https://www.piworld.com/ PRINTING United Alliance: https://www.printing.org/ Subscribe to Printing Impressions Newsletter: https://www.piworld.com/newsletter-today-on-piworld-subscribe/ Packaging Impressions: https://www.packagingimpressions.com/ In-plant Impressions: https://www.inplantimpressions.com/ Wide-format Impressions: https://www.wideformatimpressions.com/ Apparelist: https://www.apparelist.com/ Storyworth: https://welcome.storyworth.com/ Deborah Corn: https://linkedin.com/in/deborahcorn/ Print Media Centr: https://printmediacentr.com Subscribe to News From The Printerverse: https://printmediacentr.com/subscribe-2 Girls Who Print: https://girlswhoprint.org PrintFM Radio: https://printfmradio.com Project Peacock: https://ProjectPeacock.TV

Join us Sundays at 11am and Wednesdays at 7pm. 13756 N. Lincoln Blvd. Edmond, OK 73013 Building #7 https://onelifeok.com Click here to partner with us: https://churchhalo.app/give/onelifeok

Introducing Deep and Wide — a brand new podcast hosted by Dean Still featuring conversations with influential Christian voices from around the world. Our first episode welcomes Rowan Williams, Archbishop of Canterbury from 2002 to 2012, for a thoughtful and timely conversation you won't want to miss.

The NFL Combine has wrapped up — now what does it all mean for the Tennessee Titans? In this special Combine wrap-up episode of OTP, the crew breaks down everything we learned in Indianapolis — from draft trends and defensive depth to wide receiver options and how medicals and measurables reshape draft boards. Featuring insight from Daniel Jeremiah, Bucky Brooks, and Trevor Sikkema, this episode dives into: • Titans options at Pick No. 4 • Defensive-heavy draft class trends • Wide receiver fits for Cam Ward • Blue-chip prospects vs. depth players • What really changes at the Combine As the Titans turn the page toward the NFL Draft, here's everything you need to know coming out of Combine week.See omnystudio.com/listener for privacy information.

John Schmeelk is joined by Ryan Fowler, Host of the Commanding the Huddle Podcast, and Jeff Risdon, Real GM’s NFL Draft Analyst, to review the player workouts and pressers at the NFL Combine. :00 - Combine testing 6:00 - Offensive linemen 13:20 - Quarterbacks 18:35 - Running backs 23:10 - Tight ends 27:15 - Wide receivers 34:00 - Defensive tackles 38:00 - Edge rushers 45:30 - Linebackers 50:15 - Cornerbacks 53:55 - SafetiesSee omnystudio.com/listener for privacy information.

Today on the Daily Nugget, Mike reflects on Matthew 7:13, where Jesus warns that the gate is narrow and the road is hard that leads to life—and few find it. This sobering teaching reminds us that following Christ isn't about drifting with the crowd but intentionally choosing the way of obedience and trust. Yet the narrow road is not meant to discourage us; it's an invitation to wholehearted discipleship and the abundant life Jesus promises to those who walk with Him.

This week's Patreon-only Thumb War is very a late February check-in — no formal review, just conversation. We talk about: Trivia and random pop-culture facts Splitsville mini-review Travel stories and side quests Media overload and burnout BAFTA Awards conversation and online reactions Letting conversations breathe instead of spiraling Loose and thoughtful— a classic Patreon hang. Full Patreon chaos on Thumb War. Like, subscribe, and let us know what you think. Ad-free episodes + bonus content on Patreon: http://bit.ly/44Mo8xU Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Hour 2: D-Pop and J.D. dive into the San Francisco 49ers' offseason moves. They discuss the recent trade of Jermaine Johnson to the Tennessee Titans and whether the 49ers missed out on a potential opportunity to acquire him. The guys also weigh in on the team's wide receiver needs, including the possibility of signing Jauan Jennings or Deebo Samuel. See omnystudio.com/listener for privacy information.

Get into the details of ebikes! Why ride one? Or not? Why did we make the product and design choices we've made in our ebike line? In this episode we sit down with Product Manager Mark Matson and Rider Support's own E-bike specialist, Chris Freeny (maybe he's helped you out!). Between these two experts, we deep dive into the world of E. The fastest growing category in MTB, whether you like it or not. Note: Recorded BEFORE the recent storms... it has since rained. Questions or comments? Email podcast@santacruzbicycles.com Thanks for listening!      

If you head for orbit around Jupiter, you might want to take along your dust mop. Wide but thin rings encircle the planet. And they’re made of tiny particles of dust. Jupiter’s rings are nothing like the magnificent set that encircles Saturn. The rings are so faint, in fact, that they weren’t discovered until 1979, when the Voyager 1 spacecraft flew close to Jupiter. The system consists of four main rings. The inner ring, known as the halo, contains especially tiny particles, like a thin haze. The particles in the main ring are a little larger, but still quite small. And the two outer rings – known as gossamer rings – are wide and thick, but still don’t add up to much. The particles that make up the rings probably were chipped off of some the small moons that orbit close to Jupiter. Chunks of ice and rock slam into the moons, blasting out clouds of debris. The particles in the rings spiral into Jupiter quickly – within hundreds or thousands of years. So the rings are being constantly replenished by more impacts – adding to the dusty environment around the solar system’s largest planet. Jupiter teams up with the Moon and the twins of Gemini tonight. The planet looks like a brilliant star below the Moon at nightfall. It’s far brighter than any of the true stars. Gemini’s twins – the stars Castor and Pollux – line up to the lower left of the Moon. More about this beautiful grouping tomorrow. Script by Damond Benningfield

Matt Spiegel and Laurence Holmes discussed how MLB teams league-wide are cutting their broadcasts of spring training games.

Ian Rapoport, Insider for NFL Network, talks about the NFL offseason, including the free agency landscape and the NFL Draft. :00 - NFL offseason chat 2:25 - Wide receivers in free agency 4:03 - John Harbaugh’s impact 5:50 - Giants in free agency 8:10 - Possible extensionsSee omnystudio.com/listener for privacy information.

Daniel Jeremiah, writer and analyst for NFL Network, talks about what the Giants could do at the fifth pick, what traits differentiate the top prospects are in the draft, and where the Giants could go in the second round. :00 - Top of the draft 3:45 - Caleb Downs 7:10 - Sonny Styles 9:30 - Arvell Reese 11:00 - Wide receivers 13:55 - Offensive linemen 15:20 - Mansoor Delane 16:30 - Giants second round pickSee omnystudio.com/listener for privacy information.

The crew debate what is the biggest need this offseason, Wide receiver or an edge rusher. T

The guys preview the NFL Combine, talk about each position group, and discuss how player results at the Combine can impact draft position. :00 - Quarterbacks 6:25 - Running backs 9:05 - Wide receivers 14:00 - Tight ends 17:15 - Offensive line 22:05 - Defensive line 25:55 - Edge rushers 29:00 - Linebackers 32:00 - Cornerbacks 35:05 - SafetiesSee omnystudio.com/listener for privacy information.