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Enjoy this interview from before our rebrand to The Brothaship!No funny business in today's Dragon Call – here we take this podcast very seriously and ask all audience members to refrain from laffing because nothing we say here should be viewed as a joke. It is important to laff when the going gets tough; it's also important to cry. And most importantly, when it's time to lock in, display respect, and have fun while doing it, our guests know whom to call. Ironically, all jokes aside, there will be plenty of laffter and whimsical fun in today's episode! Voice actor for characters such as King Gomah, Page One, Reiji Yamamoto, and many others, press play and learn more about Mr. Tom Laflin!Find Tom at:X (Twitter): @TomLaflinWebsite: tomlaflin.studioFollow our socials by clicking through the ALL POWERFUL LINKTREE OF MIGHT: https://linktr.ee/thebrothaship Listen to us on Apple Podcasts here:https://podcasts.apple.com/us/podcast/the-brothaship/id1645000686 Listen to us on Spotify Here: https://open.spotify.com/show/0WTmVFsC3z7sdl0UEZiP2X?si=PZJVuRa7QuasiAupkAo3hA&utm_medium=share&utm_source=linktree&nd=1&dlsi=0fb09c5746294757 Check out our Musical contributors AOX by following their linktree: https://linktr.ee/aoxmusic
Jason and Nick welcome in former Morning X producer Alex 'Son of a Preacher Man' Diamond for an all movies, Christmas episode. They start by running down their top 5 movies of 2025 before firing off a Nitpickers™️ breakdown of National Lampoon's Christmas Vacation.Bonus episodes available at patreon.com/jasondick or https://creators.spotify.com/pod/show/jason-dick/subscribe
This one is a two-fer. We skipped the news of the week because we recorded this episode so long ago BUT content is still fresh! Dandadan season two! YMF's favorite anime right now, maybe of the year! We debate it. AND if you haven't had a chance to listen to any of our filler episodes, the back half is STRAIGHT FILLER. Miscellaneous conversations about Main Character Energy, Respect, Karma, Dragons & Mermaids and Girl Math (yes).. check us out! 0:00 Intro 2:20 Dandadan Season Two 55:00 Whatcha Reading, Whatcha Watching, Whatcha Playing???
Episode 001 marks the launch of Melodic Electronic, a new monthly journey through progressive, melodic, and trance-tinged sounds curated by Hyperbolic Function. This opening mix leans into shimmering melodies, warm low-end movement and that late-night emotional pull, setting the tone for what this show is all about. ⚡️Like the Show? Click the [Repost] ↻ button so more people can hear it!
Matt Spiegel and Laurence Holmes reacted to Bears head coach Ben Johnson's recent comments about quarterback Caleb Williams' development.
Happy Thanksgiving to all! Another cooking anime and this time we mix in some isekai with our cooking anime and sprinkle it with some slice of life and a pinch or a dash of fantasy action! Actually a good anime! But you might already know that. Thankful to you all that continue to listen to the podcast and support us in our other ventures; movie reviews, video game streams and of course hyperbolic bevs coming to a convention near you!
Send us a textBuckle up, Ones Ready fam—Aaron and Trent dive headfirst into the clown show of Democratic lawmakers (all ex-military or intel vets) dropping a cringy, scripted video urging service members to ditch "illegal orders." Spoiler: They're gaslighting the ranks with zero specifics, just vibes. Trump fires back calling it sedition punishable by death (he got the penalty wrong, but the charge? Spot on). We break down the real deal—sedition's 20 years, treason's the death penalty stuff like Milley's China stunt. Hot takes fly on media narratives, the Tweedledee-Tweedledum incitement defense, and why defying orders could land you in Leavenworth if you're wrong. No sugarcoating: Politicians are trash, oaths matter, and this is how civil wars brew. If you're in uniform, listen up—we're calling out the hypocrisy from Jason Crow's Jan 6 cowardice to Biden's vaccine mandates. Truth bombs only, no BS.⏱️ Timestamps:00:00 - Sedition 101: Clearing Up the Death Penalty Mix-Up02:23 - Vet Hosts Spill: Leaving Politics at the Door (Kinda)03:59 - Dem Lawmakers' Cringy Video Breakdown: Scripted AF06:59 - Illegal Orders? Pin That Thought, Baby Bird09:04 - Trump's Maximalist Truth: Art of the Deal Style12:27 - Governor's Dumb Take: Trump's Always Talked Tough13:47 - Treason vs. Sedition: Milley's Pardon Says It All15:59 - Tweedledee Defense: Inciting Without Saying It18:39 - Media Gaslighting: Conditioning Troops for Chaos20:52 - Oaths Over Feelings: Defy at Your Own Risk22:49 - Historical Violence: Presidents Have Always Been Brutal24:07 - Crying Victim While Striking: Classic Dem Move26:40 - Sedition Act History: Used to Jail Opponents28:31 - Turning Down the Rhetoric? Yeah, Right30:01 - Political Violence Myth: Words Ain't Bullets32:37 - UCMJ Reality: Article 92 Saves (or Sinks) You33:56 - Vaccine Mandate Hypocrisy: Where Was the Outrage?37:34 - Spy Ops on Congress: Crossfire Hurricane Exposed39:37 - Rangers Shoutout: Love Y'all (Minus Crow)42:55 - Civil War Warning: Factions Shooting Each Other45:13 - Accountability Dream: Hold Everyone to the Oath48:45 - Buyer Beware: Defy Orders, Face the Music
Fillers are back in rotation and back OUTSIDE. This time after a day at the fair with our kids, we went to our local spacious hole in the wall pizza joint slash pinball arcade slash exotic drink spot, Nice Guys Pizza! Good conversations, great drinks, tatter tot pizza? There's a lot going on in this episode, just check us out!
If you feel stupid while learning something new, you're doing it right. But if you keep doing the same thing over and over hoping it'll suddenly make sense - that's on you. The trick isn't to push harder; it's to find a new teacher, a new explanation, a new way in.That's exactly how Matthew Broussard approaches comedy - and everything else. A stand-up comedian, math nerd, and former financial analyst, Matthew is obsessed with learning and cracking the formula behind how things work. He treats every joke like an equation, testing, refining, and solving for laughter.He's the creator of Monday Punday, a puzzle webcomic and app, and has been featured on The Tonight Show with Jimmy Fallon, Conan and Comedy Central's Roast Battle. He's also made appearances on The Marvelous Mrs. Maisel and The Mindy Project. His storytelling, including his viral tales about his mother-in-law, proves that logic and vulnerability can live in the same sentence.In this episode, we explore the overlap between comedy and leadership—the art of experimenting, iterating, and connecting through honesty. We talk about the hidden work beneath success, the difference between purpose and perfection, and why laughter might just be the purest form of optimism.This is A Bit of Optimism.---------------------------This episode is brought to you by the Porsche USA Macan---------------------------Check out Matthew's Youtube page for his full comedy special “Hyperbolic”: https://www.youtube.com/@mondaypunday---------------------------
Halloween is here and here we are again talking about horror anime. This time, what some say is the BEST horror anime of all time, we watched Parasyte! Both the anime and the Netflix Live-Action Spin-Off! Which is actually really good btw. Better than the anime? Listen and find out0:00 Intro 3:06 A.News - Crunchyroll Silently Drops Parasyte8:35 VG.News - Halo Comes to Playstation 16:38 M.News - ChainsawMan Reze Movie Numbers 19:49 Meat and Potatoes 1:05:00 Whatcha Reading, Whatcha Watching, Whatcha Playing? 1:21:12 Outro
https://thecommunists.org/2025/09/17/leaflets/no-deportations-defend-tfl-workers/ The ruling class is working overtime to pit worker against worker. We must not allow it to succeed in its aim of neutralising our resistance. Hyperbolic statements about the ‘threats' posed by migrants and asylum seekers, alongside blanket media coverage given to theatrical acts of deportation, are being used to stoke social tensions, distract workers from the real cause of their problems, justify militarisation of the police, and encourage scapegoating. All of which keeps migrant workers disciplined and fearful, while simultaneously fuelling the narrative amongst the rest of the working class that migration is responsible for all the social and economic problems they face. Download this leaflet as a pdf. Subscribe! Donate! Join us in building a bright future for humanity! www.thecommunists.org www.lalkar.org www.redyouth.org Telegram: t.me/thecommunists Twitter: twitter.com/cpgbml Soundcloud: @proletarianradio Rumble: rumble.com/c/theCommunists Odysee: odysee.com/@proletariantv:2 Facebook: www.facebook.com/cpgbml Online Shop: https://shop.thecommunists.org/ Education Program: Each one teach one! www.londonworker.org/education-programme/ Join the struggle www.thecommunists.org/join/ Donate: www.thecommunists.org/donate/
Time Codes BelowKid Luis shares a hidden gem anime that deserves to be on the Normn's Top 10 Anime List. Don't worry, we argue on what makes this anime GREAT and if it's underrated or Mid. If you haven't seen it before, we're gonna spoil the hell out of it. But we all 3 agree, it's worth a watch. Check it out, then check us out. Or just enjoy the anime through us. You know the deal. 0:00 Intro 04:24 A.News - Most Popular Anime on Crunchyroll09:13 VG.News - Call of Duty Movie14:30 M.News - Demon Slayer Infinity Castle Box Office18:45 Meat and Potatoes01:13:30 Whatcha Reading , Whatcha Watching , Whatcha Playing ???01:29:10 Outro
Matthew Broussard is a comedian (Hyperbolic) who shares his struggles with mental health and opens up, for the first time, about his experience with self-harm.For more about Matthew, including his most recent standup special. https://www.youtube.com/watch?v=5UECGG-CD88The New York Times called it a "pleasingly punchy debut hour" and said "His precisely timed and rarefied jokes are polished to a sheen. These are comedy-nerd bits about subjects you don't tend to hear comics at clubs ranting about."This episode is sponsored by NOCD. If you're struggling with OCD or unrelenting intrusive thoughts, NOCD can help. Book a free 15 minute call to get started: https://learn.nocd.com/mentalpodIf you're interested in seeing or buying the furniture that Paul designs and makes follow his IG @ShapedFurniture or visit the website www.shapedfurniture.comWAYS TO HELP THE MIHH PODCASTSubscribe via Apple Podcasts (or whatever player you use). It costs nothing. It's extremely helpful to have your subscription set to download all episodes automatically. https://itunes.apple.com/us/podcast/mental-illness-happy-hour/id427377900?mt=2Spread the word via social media. It costs nothing.Our website is www.mentalpod.com our FB is www.Facebook.com/mentalpod and our Twitter and Instagram are both @Mentalpod Become a much-needed Patreon monthly-donor (with occasional rewards) for as little as $1/month at www.Patreon.com/mentalpod Become a one-time or monthly donor via PayPal at https://mentalpod.com/donateYou can also donate via Zelle (make payment to mentalpod@gmail.com) To donate via Venmo make payment to @Mentalpod See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Another filler but this time we're out at the local bubble tea shop! We're also announcing that The Normn is getting into selling lemonade! We talk all about that, what we're willing to give for Fame, do we believe in spirits and ghosts, and many more topics!
Send us a textSteven & Derek review Thursday Night Football, get ready for week 3 in the NFL & discuss the crisis of freedom of speech currently. Stay tuned for a big announcement at the end...(00:34)-Clayton Kershaw's retirement (12:00)-Bills beat Dolphins 31-21, are they the best team in the AFC? Hyperbolic takes on Josh Allen (35:26)-More Tush Push Outrage (39:30)-Could Joe Burrow retire soon? (45:00)-Raiders taking on Marcus Mariota, Does Ashton Jeanty need "load management"? (1:00:52)-Mac Jones starting again for the 49ers (01:13:05)-Winz or Wangz: Week 3 Picks (01:28:02)-Jackass of the Week: Kuminga's agent & Brian Kelly (01:39:49)-Pop Culture Catchup: Jimmy Kimmel removed from TV Support the show
0:00 - It's essential that the Broncos beat the Chargers on Sunday. The stakes are incredibly high. Why? Is Brett being hyperbolic?16:40 - We're still navigating the new era of college football with NIL and the transfer portal. Does that change the standard we need to have for established college coaches? Or is the standard still the standard? Next, Moser is back with our new favorite segment: LAY IT DOWN! 33:14 - It's our favorite part of the week DRUNK TAKES! We take clips from thoughout the week, slow em down to half speed & it makes us sound like we're hammered.
Football Americans! We've so much to get to this episode: Lamar v Allen! The long kicks! Jalen Carter's spit! The sad, sad Dolphins. And we've got the right father and son duo to tell you all about it with Greg and Chris Cote from the Dan LeBatard show. Plus, we've bring in Geoff Schwartz to explain why he fell asleep and missed what could be the best game of the season. The Super Fuentes Brothers provide knee jerk reactions to Week One from Miami, and Newsman Bradley presents Aaron Rodgers unfiltered from New York. Hyperbolic, sure. Satisfying? Of course. Football is back, America, and here to cover it is Football America! **That said. Before you hit play we gotta protect our guy, Pittsburgh Hero Ryan Clark. A lot of people out there chose to get up on Mount Pious about Clark saying Tom Brady and Drew Brees weren't generational talents. They aren't. Neither guy was a measurable physical freak. Y'see the NFL's got two basic types of QBs. 1. Specimens like Josh Allen, Andrew Luck, Cam Newton, even Jeff George. These guys can evolve into gunslingers like John Elway, Brett Favre and Ben Roethlisberger and take you to the top of Mount Lombardi. 2. Assassins like Tom Brady, Peyton Manning, Drew Brees, and Joe Montana. They've been marginalized with the name ‘game manager' but they're calculated and lethally accurate. Big game trophy hunters. That's why I call 'em ASSASSINS. In superhero terms, it's like Superman v Batman. You'd of course like the measurables of the son of Jor-el over Bruce Wayne, but that doesn't mean Batman can't win thanks to being more clever. So, descend Mount Pious and just admit Brady and Brees are the Keaton and Bale Batmans (batmen?) of the NFL. And be good with it. As for serial killers, well... Mike Tomlin can go ahead explain that one. We're stumped. Now, start the show! Learn more about your ad choices. Visit podcastchoices.com/adchoices
OG Eng voice of Captain Ginyu and the "Next time, on Dragon Ball Z!" NARRATAOR from the OG anime sit with us as we talk about his new exciting IP Cycles of War! It spans Graphic Novels, Board Games, Card Games and many more things to come. Find out more about his universe and how you can even be featured in the next book at cyclesofwar.com !
*TIME CODES BELOW* Samurai Swords and Musical Records. We argue on if Samurai Champloo is THE BEST ANIME IN THE WORLD and if Kill Bill is Tarantino's BEST or WORST film. Jam out with us as we take this trip down memory lane to the early 2000s, PSP UMD era media. 0:00 Intro3:55 A.News - One Piece Indonesia Protest10:47 VG.News - Marvel Tokon: Fighting Souls PS5 Closed Beta18:21 M.New - Casting News Link and Zelda31:51 Meat and Potatoes - Samurai Champloo1:03:35 Kill Bill Vol. 1&21:45:10 Whatcha Reading, Playing and Watching???2:00:50 Outro
Knowledge is Eventually Consistent // MLOps Podcast #335 with Devin Stein, CEO of Dosu.Grateful to @Databricks and @hyperbolic-labs for supporting our podcast and helping us keep great conversations going.Join the Community: https://go.mlops.community/YTJoinInGet the newsletter: https://go.mlops.community/YTNewsletter// AbstractAI as a partner in building richer, more accessible written knowledge—so communities and teams can thrive, endure, and expand their reach.// BioDevin is the CEO and Founder of Dosu. Prior to Dosu, Devin was an early engineer and leader at various startups. Outside of work, he is an active open source contributor and maintainer.// Related LinksWebsite: https://github.com/devsteinhttps://www.youtube.com/watch?v=sC8aW47DqPghttps://www.youtube.com/watch?v=PuM0Gd3txfQhttps://www.youtube.com/watch?v=ah6diDQ9wywhttps://www.youtube.com/watch?v=x22FEQic8lg~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our Slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Devin on LinkedIn: /devstein/Timestamps:[00:00] Devin's preferred coffee[00:53] Facts agent overview[03:47] Decision state detection[07:55 - 8:41] Databricks ad[08:42] Context-dependent word meanings [15:25] Fact lifecycle management[24:40] Maintaining quality documentation[30:10 - 31:06] Hyperbolic ad[31:07] Agent collaboration scenarios [38:22] Knowledge maintenance[44:10] Deployment and integration strategies[48:13] Flywheel data approach[51:54] Horror story engineering function[54:32] Wrap up
We hosted the panel @ Charlie's Summerfest and it was GREAT! Super fun and engaging conversations with two local YouTube celebrities! Started on TikTok and blowing up everywhere online, you've most likely seen their shorts before, but sit down and chill out with the people behind those viral videos as we talk about how they started, where they get their ideas and cool behind the scenes info on what it's like having your video(s) go viral!!
19keys.com/tour to get your tickets today19keys.com/links or 19keystour@togmail.com to Support for the tour (venue partners, sponsors, team, etc) 19keys.com/links to sign of for Yah'ki Awakened x 19Keys Retreat Experience
WAGOP Chairman Jim Walsh says reforms to Medicaid are being distorted by political rhetoric and argues Washington's Apple Health program needs accountability. https://www.clarkcountytoday.com/opinion/opinion-wagop-chair-sets-the-record-straight-on-dems-hyperbolic-rhetoric-on-medicaid-program/ #Opinion #JimWalsh #MedicaidReform #AppleHealth #WAGOP #HealthcarePolicy #FederalFunding #WashingtonPolitics #UnderservedCommunities
TIME CODES BELOW Do y'all remember The Big O?? Neither do the citizens of Paradigm City. A whole town with amnesia and a Black Tuexedo'd Mech piloted by a Bruce Wayne Batman with a crappy job as a "negotiator". Is it worth your time to revisit this seldom mentioned but borderline iconic Black suited Mech that isn't a Gundam? 0:00 Intro 03:16 A.News - ChatGPT Subtitles Crunchyroll 11:20 VG.New - Switch 2 First Month Numbers20:24 M.News - Street Fighter Movie Cast 31:03 Meat and Potatoes 1:10:34 Whatcha Reading, Whatcha Watching, Whatcha Playing?1:33:36 Outro
SpaceTime with Stuart Gary | Astronomy, Space & Science News
In this episode of SpaceTime, we explore the latest cosmic revelations, including the astonishing discovery of an ancient interstellar comet, the intricate workings of a rare pulsar, and the safe return of the Axiom 4 crew from their mission.Ancient Interstellar Comet 3I/AtlasAstronomers have unveiled that the newly discovered interstellar object, 3I/Atlas, could be the oldest comet ever observed, potentially predating our solar system by over 3 billion years. This water-rich visitor, detected by NASA's ATLAS survey, is only the third known object from beyond our solar system to reach us. A study by Matthew Hopkins from Oxford University suggests that 3I/Atlas may be more than 7 billion years old, offering a glimpse into a part of the Milky Way previously unseen. As it approaches the sun, its activity is expected to increase, revealing more about its composition and the role ancient comets play in star and planetary formation.Unraveling the Mysteries of a Rare PulsarIn another exciting development, astronomers have made significant strides in understanding a unique pulsar system, PSRJ 1023 0038. This transitional millisecond pulsar, which interacts with a lower mass stellar companion, has been studied using data from NASA's Imaging X-Ray Polarimetry Explorer (IXPE). The findings suggest that the X-ray emissions originate from the pulsar wind rather than the accretion disk, challenging existing models and providing new insights into neutron star behavior and particle acceleration.Axiom Space AX4 Crew ReturnsThe Axiom Space AX4 crew has successfully splashed down in the North Pacific Ocean after nearly three weeks aboard the International Space Station. This mission, part of NASA's efforts to promote commercial activities in space, included a diverse crew and numerous scientific experiments. With the return of the AX4 crew, preparations are underway for NASA's upcoming Crew 11 mission, further expanding humanity's presence in low Earth orbit.www.spacetimewithstuartgary.com✍️ Episode ReferencesAstrophysical Journal Lettershttps://iopscience.iop.org/journal/1538-4357Journal of the American Medical Associationhttps://jamanetwork.com/journals/jamaBecome a supporter of this podcast: https://www.spreaker.com/podcast/spacetime-space-astronomy--2458531/support.00:00 New interstellar object 3I/Atlas may be older than our solar system06:44 Foreign astronomers have discovered new evidence Explaining how pulsing remnants interact in space14:09 Private company Axiom Space's AX4 crew return safely to Earth16:06 Having a higher body mass index from early childhood and adolescence is linked to aging17:32 New study looked at which over the counter medicines are good at treating depression18:43 Brazilian psychic issues chilling warning about dangers posed by artificial intelligence
On today's Top News in 10 we cover: The U.S. hits three nuclear sites in Iran, pulling off a massive deception & diversion campaign. The response from world leaders is muted and the response from media & officials is hyperbolic. Subscribe to The Tony Kinnett Cast: https://podcasts.apple.com/us/podcast/the-tony-kinnett-cast/id1714879044 Don't forget our other shows: Virginia Allen's Problematic Women: https://www.dailysignal.com/problematic-women Bradley Devlin's The Signal Sitdown: https://www.dailysignal.com/the-signal-sitdown Follow The Daily Signal: X: https://x.com/DailySignal Instagram: https://www.instagram.com/thedailysignal/ Facebook: https://www.facebook.com/TheDailySignalNews/ Truth Social: https://truthsocial.com/@DailySignal YouTube: https://www.youtube.com/user/DailySignal Rumble: https://rumble.com/c/TheDailySignal Thanks for making The Daily Signal Podcast your trusted source for the day's top news. Subscribe on your favorite podcast platform and never miss an episode. Learn more about your ad choices. Visit megaphone.fm/adchoices
On today's Top News in 10 we cover: The U.S. hits three nuclear sites in Iran, pulling off a massive deception & diversion campaign. The response from world leaders is muted and the response from media & officials is hyperbolic. Subscribe to The Tony Kinnett Cast: https://podcasts.apple.com/us/podcast/the-tony-kinnett-cast/id1714879044 Don't forget our other shows: Virginia Allen's […]
Stand-Up On The Spot! Featuring completely improvised sets from & Jeremiah Watkins. No material. Comedians create Stand-Up On The Spot off audience suggestions. Everything is covered from Pizza Hut Buffets, to Bill Belichick, Power Rangers, Telepathy, pig shotguns & more! Jeremiah Watkins you know from Trailer Tales, Dr. Phil Live, his special DADDY, and as the host and creator of Stand-Up On The Spot. Casey Rocket you know as a nationally touring headliner and as a regular of Kill Tony. Ian Bagg has multiple hilarious standup and crowd work specials you can watch on his YouTube page. Sklar Bros are the hosts of Dumb People Town and host of the Nosebleeds a show you can watch on UFC Fightpass. Matthew Broussard has a new special out called Hyperbolic. Laura Peek has appeared on late night and opens for Theo Von. Follow the Comedians! Jeremiah Watkins @jeremiahwatkins @TrailerTalesPod @standupots https://www.instagram.com/jeremiahstandup Casey Rocket @CaseyRocket https://www.instagram.com/caseyrocket Ian Bagg @IanBagg https://www.instagram.com/ianbagg Sklar Brothers https://www.instagram.com/sklarbros Matthew Broussard @mondaypunday https://www.instagram.com/mondaypunday Laura Peek @laurapeekcomedy https://www.instagram.com/laurapeek Stand-Up On The Spot https://www.instagram.com/standupots @standupots Sponsored by: Blue Chew Try your first month of BlueChew for free, just pay $5 for shipping. Use code SPOT at https://www.bluechew.com Sponsored by: Magic Spoon Support the show and get $5 off your Magic Spoon order at https://www.magicspoon.com/SPOT Interested in sponsoring the show? Email standupots@gmail.com for inquiries SOTS: #1HourSpecial #StandupComedy #CaseyRocket #KillTony #JeremiahWatkins SOTS Austin: Casey Rocket, Ian Bagg, Sklar Bros, Matthew Broussard, Laura Peek & J Watkins | Ep 75
BJ is tired of seeing all the hyperbolic videos all over social media.
Alex talks through the science of procrastination, his own journey with it, and tools he uses to take charge of it. — Show Notes: (0:00) A note from our sponsor (2:28) Welcome back to Founder's Journal (3:33) Why we procrastinate (5:23) Cognitive biases (6:28) Hyperbolic discounting (7:21) Temptation bundling (8:40) Social commitments (10:00) Conclusion — Thanks to our presenting sponsor, Gusto. Head to www.gusto.com/alex — Episode Links: • Cognitive Biases: https://foundersjournalpod.morningbrew.com/13-dangerous-psychological-biases/ • Pomodoro Method: https://foundersjournalpod.morningbrew.com/my-favorite-productivity-method/ Check Out Alex's Stuff: • storyarb - https://www.storyarb.com/ • growthpair - https://www.growthpair.com/ • CTA - https://www.creatortalentagency.co/ • X - https://x.com/businessbarista • Linkedin - https://www.linkedin.com/in/alex-lieberman/ Learn more about your ad choices. Visit megaphone.fm/adchoices
December 9-16, 2000 This week Ken welcomes pun loving comedian behind the comedy special "Hyperbolic", Matthew Broussard. Ken and Matthew discuss Pokemon, the repressed feelings from the turn of the century, giving up video games, enjoying arts and crafts, not being into sports, swimming, genius ads, homoerotic break in fantasies used to sell breath mints, Madden, sculpting, the genius of gang signs, economy of words, living in a sponsored society, SNL, the one t-shirt that offended Ken, being polite, miss opportunities with Tony Hawk, having your own rope, naked babies on Al Roker, Braveheart, the Discover E-Book, Cartoon Cartoon, Cow and Chicken, I am Weasel, how Adventure Time might just be the greatest show of the 21st Century, Emergency Vets handle vomiting monkeys, South Park, financial struggles, Sopranos, Malcolm in the Middle, Kirk Cameron hosting Santa's Funniest Moments, Brad Pitt's early days on Growing Pains, over the top acting, the heavy drama of Hey! Arnold!, Becker, Becker's 9/11 episode, silly accents, Uma Thurman for president, The Riddler, how Tom Waits influenced the Joker, the moneyball-ificiation of America, the mixed world of childhood play, limitless imagination, Looney Tunes, being shot in front of a live audience, puns, Tom Kenny, the Ice King, old school voice over talent, Sex and the City, Will and Grave, Tom and Jerry, writing for Sean Hayes, The Real World, how Puck is an a-hole, how Carrie is the Villain, how Ferris Buheler is the villain, and the man who is married to Claire Danes.
TIME CODES BELOWNETFLIX! Now that I have your attention, come see us passionately debate and dissect this latest entry in the bootleg multiverse that is video game netflix originals. We go in. Opinions are high and low. What did yall think about it?0:00 Intro 2:40 Anime News - New Ghost in the Shell Anime Series 6:46 Video Game News - Death Stranding Movie Updates10:46 Movie News - Toei Company Coproducing Live Action Yasuke Movie with South African Company Pambili Media15:49 Switch 2 Reaction 31:00 Meat and Potatoes - Devil May Cry1:20:33 Whatcha Reading, Watching and Playing???1:38:06 Outro
We are calling for the world's best AI Engineer talks for AI Architects, /r/localLlama, Model Context Protocol (MCP), GraphRAG, AI in Action, Evals, Agent Reliability, Reasoning and RL, Retrieval/Search/RecSys , Security, Infrastructure, Generative Media, AI Design & Novel AI UX, AI Product Management, Autonomy, Robotics, and Embodied Agents, Computer-Using Agents (CUA), SWE Agents, Vibe Coding, Voice, Sales/Support Agents at AIEWF 2025! Fill out the 2025 State of AI Eng survey for $250 in Amazon cards and see you from Jun 3-5 in SF!Coreweave's now-successful IPO has led to a lot of questions about the GPU Neocloud market, which Dylan Patel has written extensively about on SemiAnalysis. Understanding markets requires an interesting mix of technical and financial expertise, so this will be a different kind of episode than our usual LS domain.When we first published $2 H100s: How the GPU Rental Bubble Burst, we got 2 kinds of reactions on Hacker News:* “Ah, now the AI bubble is imploding!”* “Duh, this is how it works in every GPU cycle, are you new here?”We don't think either reaction is quite right. Specifically, it is not normal for the prices of one of the world's most important resources right now to swing from $1 to $8 per hour based on drastically inelastic demand AND supply curves - from 3 year lock-in contracts to stupendously competitive over-ordering dynamics for NVIDIA allocations — especially with increasing baseline compute needed for even the simplest academic ML research and for new AI startups getting off the ground.We're fortunate today to have Evan Conrad, CEO of SFCompute, one of the most exciting GPU marketplace startups, talk us through his theory of the economics of GPU markets, and why he thinks CoreWeave and Modal are well positioned, but Digital Ocean and Together are not.However, more broadly, the entire point of SFC is creating liquidity between GPU owners and consumers and making it broadly tradable, even programmable:As we explore, these are the primitives that you can then use to create your own, high quality, custom GPU availability for your time and money budget, similar to how Amazon Spot Instances automated the selective buying of unused compute.The ultimate end state of where all this is going is GPU that trade like other perishable, staple commodities of the world - oil, soybeans, milk. Because the contracts and markets are so well established, the price swings also are not nearly as drastic, and people can also start hedging and managing the risk of one of the biggest costs of their business, just like we have risk-managed commodities risks of all other sorts for centuries. As a former derivatives trader, you can bet that swyx doubleclicked on that…Show Notes* SF Compute* Evan Conrad* Ethan Anderson* John Phamous* The Curve talk* CoreWeave* Andromeda ClusterFull Video PodLike and subscribe!Timestamps* [00:00:05] Introductions* [00:00:12] Introduction of guest Evan Conrad from SF Compute* [00:00:12] CoreWeave Business Model Discussion* [00:05:37] CoreWeave as a Real Estate Business* [00:08:59] Interest Rate Risk and GPU Market Strategy Framework* [00:16:33] Why Together and DigitalOcean will lose money on their clusters* [00:20:37] SF Compute's AI Lab Origins* [00:25:49] Utilization Rates and Benefits of SF Compute Market Model* [00:30:00] H100 GPU Glut, Supply Chain Issues, and Future Demand Forecast* [00:34:00] P2P GPU networks* [00:36:50] Customer stories* [00:38:23] VC-Provided GPU Clusters and Credit Risk Arbitrage* [00:41:58] Market Pricing Dynamics and Preemptible GPU Pricing Model* [00:48:00] Future Plans for Financialization?* [00:52:59] Cluster auditing and quality control* [00:58:00] Futures Contracts for GPUs* [01:01:20] Branding and Aesthetic Choices Behind SF Compute* [01:06:30] Lessons from Previous Startups* [01:09:07] Hiring at SF ComputeTranscriptAlessio [00:00:05]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel, and I'm joined by my co-host Swyx, founder of Smol AI.Swyx [00:00:12]: Hey, and today we're so excited to be finally in the studio with Evan Conrad from SF Compute. Welcome. I've been fortunate enough to be your friend before you were famous, and also we've hung out at various social things. So it's really cool to see that SF Compute is coming into its own thing, and it's a significant presence, at least in the San Francisco community, which of course, it's in the name, so you couldn't help but be. Evan: Indeed, indeed. I think we have a long way to go, but yeah, thanks. Swyx: Of course, yeah. One way I was thinking about kicking on this conversation is we will likely release this right after CoreWeave IPO. And I was watching, I was looking, doing some research on you. You did a talk at The Curve. I think I may have been viewer number 70. It was a great talk. More people should go see it, Evan Conrad at The Curve. But we have like three orders of magnitude more people. And I just wanted to, to highlight, like, what is your analysis of what CoreWeave did that went so right for them? Evan: Sell locked-in long-term contracts and don't really do much short-term at all. I think like a lot of people had this assumption that GPUs would work a lot like CPUs and the like standard business model of any sort of CPU cloud is you buy commodity hardware, then you lay on services that are mostly software, and that gives you high margins and pretty much all your value comes from those services. Not really the underlying. Compute in any capacity and because it's commodity hardware and it's not actually that expensive, most of that can be sort of on-demand compute. And while you do want locked-in contracts for folks, it's mostly just a sort of de-risk situation. It helps you plan revenue because you don't know if people are going to scale up or down. But fundamentally, people are like buying hourly and that's how your business is structured and you make 50 percent margins or higher. This like doesn't really work in GPUs. And the reason why it doesn't work is because you end up with like super price sensitive customers. And that isn't because necessarily it's just way more expensive, though that's totally the case. So in a CPU cloud, you might have like, you know, let's say if you had a million dollars of hardware in GPUs, you have a billion dollars of hardware. And so your customers are buying at much higher volumes than you otherwise expect. And it's also smaller customers who are buying at higher amounts of volume. So relative to what they're spending in general. But in GPUs in particular, your customer cares about the scaling law. So if you take like Gusto, for example, or Rippling or an HR service like this, when they're buying from an AWS or a GCP, they're buying CPUs and they're running web servers, those web servers, they kind of buy up to the capacity that they need, they buy enough, like CPUs, and then they don't buy any more, like, they don't buy any more at all. Yeah, you have a chart that goes like this and then flat. Correct. And it's like a complete flat. It's not even like an incremental tiny amount. It's not like you could just like turn on some more nodes. Yeah. And then suddenly, you know, they would make an incremental amount of money more, like Gusto isn't going to make like, you know, 5% more money, they're gonna make zero, like literally zero money from every incremental GPU or CPU after a certain point. This is not the case for anyone who is training models. And it's not the case for anyone who's doing test time inference or like inference that has scales at test time. Because like you, your scaling laws mean that you may have some diminishing returns, but there's always returns. Adding GPUs always means your model does actually get. And that actually does translate into revenue for you. And then for test time inference, you actually can just like run the inference longer and get a better performance. Or maybe you can run more customers faster and then charge for that. It actually does translate into revenue. Every incremental GPU translates to revenue. And what that means from the customer's perspective is you've got like a flat budget and you're trying to max the amount of GPUs you have for that budget. And it's very distinctly different than like where Augusto or Rippling might think, where they think, oh, we need this amount of CPUs. How do we, you know, reduce that? How do we reduce our amount of money that we're spending on this to get the same amount of CPUs? What that translates to is customers who are spending in really high volume, but also customers who are super price sensitive, who don't give a s**t. Can I swear on this? Can I swear? Yeah. Who don't give a s**t at all about your software. Because a 10% difference in a billion dollars of hardware is like $100 million of value for you. So if you have a 10% margin increase because you have great software, on your billion, the customers are that price sensitive. They will immediately switch off if they can. Because why wouldn't you? You would just take that $100 million. You'd spend $50 million on hiring a software engineering team to replicate anything that you possibly did. So that means that the best way to make money in GPUs was to do basically exactly what CoreWeave did, which is go out and sign only long-term contracts, pretty much ignore the bottom end of the market completely, and then maximize your long-term contracts. With customers who don't have credit risk, who won't sue you, or are unlikely to sue you for frivolous reasons. And then because they don't have credit risk and they won't sue you for frivolous reasons, you can go back to your lender and you can say, look, this is a really low risk situation for us to do. You should give me prime, prime interest rate. You should give me the lowest cost of capital you possibly can. And when you do that, you just make tons of money. The problem that I think lots of people are going to talk about with CoreWeave is it doesn't really look like a cloud platform. It doesn't really look like a cloud provider financially. It also doesn't really look like a software company financially.Swyx [00:05:37]: It's a bank.Evan [00:05:38]: It's a bank. It's a real estate company. And it's very hard to not be that. The problem of that that people have tricked themselves into is thinking that CoreWeave is a bad business. I don't think CoreWeave is explicitly a bad business. There's a bunch of people, there's kind of like two versions of the CoreWeave take at the moment. There's, oh my God, CoreWeave, amazing. CoreWeave is this great new cloud provider competitive with the hyperscalers. And to some extent, this is true from a structural perspective. Like, they are indeed a real sort of thing against the cloud providers in this particular category. And the other take is, oh my gosh, CoreWeave is this horrible business and so on and blah, blah, blah. And I think it's just like a set of perception or perspective. If you think CoreWeave's business is supposed to look like the traditional cloud providers, you're going to be really upset to learn that GPUs don't look like that at all. And in fact, for the hyperscalers, it doesn't look like this either. My intuition is that the hyperscalers are probably going to lose a lot of money, and they know they're going to lose a lot of money on reselling NVIDIA GPUs, at least. Hyperscalers, but I want to, Microsoft, AWS, Google. Correct, yeah. The Microsoft, AWS, and Google. Does Google resell? I mean, Google has TPUs. Google has TPUs, but I think you can also get H100s and so on. But there are like two ways they can make money. One is by selling to small customers who aren't actually buying in any serious volume. They're testing around, they're playing around. And if they get big, they're immediately going to do one of two things. They're going to ask you for a discount. Because they're not going to pay your crazy sort of margin that you have locked into your business. Because for CPUs, you need that. They're going to pay your massive per hour price. And so they want you to sign a long-term contract. And so that's your other way that you can make money, is you can basically do exactly what CoreWeave does, which is have them pay as much as possible upfront and lock in the contract for a long time. Or you can have small customers. But the problem is that for a hyperscaler, the GPUs to... To sell on the low margins relative to what your other business, your CPUs are, is a worse business than what you are currently doing. Because you could have spent the same money on those GPUs. And you could have trained model and you could have made a model on top of it and then turn that into a product and had high margins from your product. Or you could have taken that same money and you could have competed with NVIDIA. And you could have cut into their margin instead. But just simply reselling NVIDIA GPUs doesn't work like your CPU business. Where you're able to capture high margins from big customers and so on. And then they never leave you because your customers aren't actually price sensitive. And so they won't switch off if your prices are a little higher. You actually had a really nice chart, again, on that talk of this two by two. Sure. Of like where you want to be. And you also had some hot takes on who's making money and who isn't. Swyx: So CoreUv locked up long-term contracts. Get that. Yes. Maybe share your mental framework. Just verbally describe it because we're trying to help the audio listeners as well. Sure. People can look up the chart if they want to. Evan: Sure. Okay. So this is a graph of interest rates. And on the y-axis, it's a probability you're able to sell your GPUs from zero to one. And on the x-axis, it's how much they'll depreciate in cost from zero to one. And then you had ISO cost curves or ISO interest rate curves. Yeah. So they kind of shape in a sort of concave fashion. Yeah. The lowest interest rates enable the most aggressive. form of this cost curve. And the higher interest rates go, the more you have to push out to the top right. Yeah. And then you had some analysis of where every player sits in this, including CoreUv, but also Together and Modal and all these other guys. I thought that was super insightful. So I just wanted to elaborate. Basically, it's like a graph of risk and the genres of places where you can be and what the risk is associated with that. The optimal thing for you to do, if you can, is to lock in long-term contracts that are paid all up front or in with a situation in which you trust the other party to pay you over time. So if you're, you know, selling to Microsoft or something or OpenAI. Which are together 77% of the revenue of CoreUv. Yeah. So if you're doing that, that's a great business to be in because your interest rate that you can pitch for is really low because no one thinks Microsoft is going to default. And like maybe OpenAI will default, but the backing by Microsoft kind of doesn't. And I think there's enough, like, generally, it looks like OpenAI is winning that you can make it's just a much better case than if you're selling to the pre-seed startup that just raised $30 million or something pre-revenue. It's like way easier to make the case that the OpenAI is not going to default than the pre-seed startup. And so the optimal place to be is selling to the maximally low risk customer for as long as possible. And then you never have to worry about depreciation and you make lots of money. The less. Good. Good place to be is you could sell long-term contracts to people who might default on you. And then if you're not bringing it to the present, so you're not like saying, hey, you have to pay us all up front, then you're in this like more risky territory. So is it top left of the chart? If I have the chart right, maybe. Large contracts paid over time. Yeah. Large contracts paid over time is like top left. So it's more risky, but you could still probably get away with it. And then the other opportunity is that you could sell short-term contracts for really high prices. And so lots of people tried that too, because this is actually closer to the original business model that people thought would work in cloud providers for CPUs. It works for CPUs, but it doesn't really work for GPUs. And I don't think people were trying this because they were thinking about the risk associated with it. I think a lot of people are just come from a software background, have not really thought about like cogs or margins or inventory risk or things that you have to worry about in the physical world. And I think they were just like copy pasting the same business model onto CPUs. And also, I remember fundraising like a few years ago. And I know based on. Like what we knew other people were saying who were in a very similar business to us versus what we were saying. And we know that our pitch was way worse at the time, because in the beginning of SF Compute, we looked very similar to pretty much every other GPU cloud, not on purpose, but sort of accidentally. And I know that the correct pitch to give to an investor was we will look like a traditional CPU cloud with high margins and we'll sell to everyone. And that is a bad business model because your customers are price sensitive. And so what happens is if you. Sell at high prices, which is the price that you would need to sell it in order to de-risk your loss on the depreciation curve, and specifically what I mean by that is like, let's say you're selling it like $5 an hour and you're paying $1.50 an hour for the GPU under the hood. It's a little bit different than that, but you know, nice numbers, $5 an hour, $1.50 an hour. Great. Excellent. Well, you're charging a really high price per GPU hour because over time the price will go down and you'll get competed out. And what you need is to make sure that you never go under, or if you do go under your underlying cost. You've made so much money in the first part of it that the later end of it, like doesn't matter because from the whole structure of the deal, you've made money. The problem is that just, you think that you're going to be able to retain your customers with software. And actually what happens is your customers are super price sensitive and push you down and push you down and push you down and push you down, um, that they don't care about your software at all. And then the other problem that you have is you have, um, really big players like the hyperscalers who are looking to win the market and they have way more money than you, and they can push down on margin. Much better than you can. And so if they have to, and they don't, they don't necessarily all the time, um, I think they actually keep pride of higher margin, but if they needed to, they could totally just like wreck your margin at any point, um, and push you down, which meant that that quadrant over there where you're charging a high price, um, and just to make up for the risk completely got destroyed, like did not work at all for many places because of the price sensitivity, because people could just shove you down instead that pushed everybody up to the top right-hand corner of that, which is selling short-term. Contracts for low prices paid over time, which is the worst place to be in, um, the worst financial place to be in because it has the highest interest rate, um, which means that your, um, your costs go up at the same time, your, uh, your incoming cash goes down and squeezes your margins and squeezes your margins. The nice thing for like a core weave is that most of their business is over on the, on the other sides of those quadrants that the ones that survive. The only remaining question I have with core weave, and I promise I get to ask if I can compute, and I promise this is relevant to SOF Compute in general, because the framework is important, right? Sure. To understand the company. So why didn't NVIDIA or Microsoft, both of which have more money than core weave, do core weave, right? Why didn't they do core weave? Why have this middleman when either NVIDIA or Microsoft have more money than God, and they could have done an internal core weave, which is effectively like a self-funding vehicle, like a financial instrument. Why does there have to be a third party? Your question is like... Why didn't Microsoft, or why didn't NVIDIA just do core weave? Why didn't they just set up their own cloud provider? I think, and I don't know, and so correct me if I'm wrong, and lots of people will have different opinions here, or I mean, not opinions, they'll have actual facts that differ from my facts. Those aren't opinions. Those are actually indeed differences of reality, is that NVIDIA doesn't want to compete with their customers. They make a large amount of money by selling to existing clouds. If they launched their own core weave, then it would be a lot more money. It'd make it much harder for them to sell to the hyperscalers, and so they have a complex relationship with there. So not great for them. Second is that, at least for a while, I think they were dealing with antitrust concerns or fears that if they're going through, if they own too much layers of the stack, I could imagine that could be a problem for them. I don't know if that's actually true, but that's where my mind would go, I guess. Mostly, I think it's the first one. It's that they would be competing directly with their primary customers. Then Microsoft could have done it, right? That's the other question. Yeah, so Microsoft didn't do it. And my guess is that... NVIDIA doesn't want Microsoft to do it, and so they would limit the capacity because from NVIDIA's perspective, both they don't want to necessarily launch their own cloud provider because it's competing with their customers, but also they don't want only one customer or only a few customers. It's really bad for NVIDIA if you have customer concentration, and Microsoft and Google and Amazon, like Oracle, to buy up your entire supply, and then you have four or five customers or so who pretty much get to set prices. Monopsony. Yeah, monopsony. And so the optimal thing for you is a diverse set of customers who all are willing to pay at whatever price, because if you don't, somebody else will. And so it's really optimal for NVIDIA to have lots of other customers who are all competing against each other. Great. Just wanted to establish that. It's unintuitive for people who have never thought about it, and you think about it all day long. Yeah. Swyx: The last thing I'll call out from the talk, which is kind of cool, and then I promise we'll get to SF Compute, is why will DigitalOcean and Together lose money on their clusters? Why will DigitalOcean and Together lose money on their clusters?Evan [00:16:33]: I'm going to start by clarifying that all of these businesses are excellent and fantastic. That Together and DigitalOcean and Lambda, I think, are wonderful businesses who build excellent products. But my general intuition is that if you try to couple the software and the hardware together, you're going to lose money. That if you go out and you buy a long-term contract from someone and then you layer on services, or you buy the hardware yourself and you spin it up and you get a bunch of debt, you're going to run into the same problem that everybody else did, the same problem we did, same problem the hyperscalers did. And that's exactly what the hyperscalers are doing, which is you cannot add software and make high margins like a cloud provider can. You can pitch that into investors and it will totally make sense, and it's like the correct play in CPUs, but there isn't software you could make to make this occur. If you're spending a billion dollars on hardware, you need to make a billion dollars of software. There isn't a billion dollars of software that you can realistically make, and if you do, you're going to look like SAP. And that's not a knock on SAP. SAP makes a f**k ton of money, right? Right. Right. Right. Right. There aren't that many pieces of software that you could make, that you can realistically sell, like a billion dollars of software, and you're probably not going to do it to price-sensitive customers who are spending their entire budget already on compute. They don't have any more money to give you. It's a very hard proposition to do. And so many parties have been trying to do this, like, buy their own compute, because that's what a traditional cloud does. It doesn't really work for them. You know that meme where there's, like, the Grim Reaper? And he's, like, knocking on the door, and then he keeps knocking on the next door? We have just seen door after door after door of the Grim Reeker comes by, and the economic realities of the compute market come knocking. And so the thing we encourage folks to do is if you are thinking about buying a big GPU cluster and you are going to layer on software on top, don't. There are so many dead bodies in the wake there. We would recommend not doing that. And we, as SF Compute, our entire business is structured to help you not do that. It's helped disintegrate these. The GPU clouds are fantastic real estate businesses. If you treat them like real estate businesses, you will make a lot of money. The cloud services you can make on that, all the software you want to make on that, you can do that fantastically. If you don't own the underlying hardware, if you mix these businesses together, you get shot in the head. But if you combine, if you split them, and that's what the market does, it helps you split them, it allows you to buy, like, layer on services, but just buy from the market, you can make lots of money. So companies like Modal, who don't own the underlying compute, like they don't own it, lots of money, fantastic product. And then companies like Corbeave, who are functionally like really, really good real estate businesses, lots of money, fantastic product. But if you combine them, you die. That's the economic reality of compute. I think it also splits into trading versus inference, which are different kinds of workloads. Yeah. And then, yeah, one comment about the price sensitivity thing before we leave this. This topic, I want to credit Martin Casado for coining or naming this thing, which is like, you know, you said, you said this thing about like, you don't have room for a 10% margin on GPUs for software. Yep. And Martin actually played it out further. It's his first one I ever saw doing this at large enough runs. So let's say GPT-4 and O1 both had a total trading cost of like a $500 billion is the rough estimate. When you get the $5 billion runs, when you get the $50 billion runs, it is actually makes sense to build your own. You're going to have to get into chips, like for OpenEI to get into chip design, which is so funny. I would make an ASIC for this run. Yeah, maybe. I think a caveat of that that is not super well thought about is that only works if you're really confident. It only works if you really know which chip you're going to do. If you don't, then it's a little harder. So it makes in my head, it makes more sense for inference where you've already established it. But for training there's so much like experimentation. Any generality, yeah. Yeah. The generality is much more useful. Yeah. In some sense, you know, Google's like six generations into the CPUs. Yeah. Yeah. Okay, cool. Maybe we should go into SF Compute now. Sure. Yeah.Alessio [00:20:37]: Yeah. So you kind of talked about the different providers. Why did you decide to go with this approach and maybe talk a bit about how the market dynamics have evolved since you started a company?Evan [00:20:47]: So originally we were not doing this at all. We were definitely like forced into this to some extent. And SF Compute started because we wanted to go train models for music and audio in general. We were going to do a sort of generic audio model at some points, and then we were going to do a music model at some points. It was an early company. We didn't really spec down on a particular thing. But yeah, we were going to do a music model and audio model. First thing that you do when you start any AI lab is you go out and you buy a big cluster. The thing we had seen everybody else do was they went out and they raised a really big round and then they would get stuck. Because if you raise the amount of money that you need to train a model initially, like, you know, the $50 million pre-seed, pre-revenue, your valuation is so high or you get diluted so much that you can't raise the next round. And that's a very big ask to make. And also, I don't know, I felt like we just felt like we couldn't do it. We probably could have in retrospect, but I think one, we didn't really feel like we could do it. Two, it felt like if we did, we would have been stuck later on. We didn't want to raise the big round. And so instead, we thought, surely by now, we would be able to just go out. To any provider and buy like a traditional CPU cloud would sell offer you and just buy like on demand or buy like a month or so on. And this worked for like small incremental things. And I think this is where we were basing it off. We just like assumed we could go to like Lambda or something and like buy thousands of at the time A100s. And this just like was not at all the case. So we started doing all the sales calls with people and we said, OK, well, can we just get like month to month? Can we get like one month of compute or so on? Everyone told us at the time, no. You need to have a year long contract or longer or you're out of luck. Sorry. And at the time, we were just like pissed off. Like, why won't nobody sell us a month at a time? Nowadays, we totally understand why, because it's the same economic reason. Because if you if they had sold us the month to month or so on and we canceled or so on, they would have massive risk on that. And so the optimal thing to do was to only to just completely abandon the section of the market. We didn't like that. So our plan was we were going to buy a year long contract anyway. We would use a month. And then we would. At least the other 11 months. And we were locked in for a year, but we only had to pay on every individual month. And so we did this. But then immediately we said, oh, s**t, now we have a cloud provider, not a like training models company, not an AI lab, because every 30 days we owed about five hundred thousand dollars or so and we had about five hundred thousand dollars in the bank. So that meant that every single month, if we did not sell out our cluster, we would just go bankrupt. So that's what we did for the first year of the company. And when you're in that position. You try to think how in the world you get out of that position, what that transition to is, OK, well, we tend to be pretty good at like selling this cluster every month because we haven't died yet. And so what we should do is we should go basically be like this broker for other people and we will be more like a GPU real estate or like a GPU realtor. And so we started doing that for a while where we would go to other people who had who was trying to sell like a year long contract with somebody and we'd go to another person who like maybe this person wanted six months and somebody else on six months or something and we'd like combine all these people. Together to make the deal happen and we'd organize these like one off bespoke deals that looked like basically it ended up with us taking a bunch of customers, us signing with a vendor, taking some cut and then us operating the cluster for people typically with bare metal. And so we were doing this, but this was definitely like a oh, s**t, oh, s**t, oh, s**t. How do we get out of our current situation and less of a like a strategic plan of any sort? But while we were doing this, since like the beginning of the company, we had been thinking about how to buy GPU clusters, how to sell them effectively, because we'd seen every part of it. And what we ended up with was like a book of everybody who's trying to buy and everyone is trying to sell because we were these like GPU brokers. And so that turned into what is today SF Compute, which is a compute market, which we think we are the functionally the most liquid GPU market of any capacity. Honestly, I think we're the only thing that actually is like a real market that there's like bids and asks and there's like a like a trading engine that combines everything. And so. I think we're the only place where you can do things that a market should be able to do. Like you can go on SF Compute today and you get thousands of H100s for an hour if you want. And that's because there is a price for thousands of GPUs for an hour. That is like not a thing you can reasonably do on kind of any other cloud provider because nobody should realistically sell you thousands of GPUs for an hour. They should sell it to you for a year or so on. But one of the nice things about a market is that you can buy the year on SF Compute. But then if you need to sell. Back, you can sell back as well. And that opens up all these little pockets of liquidity where somebody who's just trying to buy for a little bit of time, some burst capacity. So people don't normally buy for an hour. That's not like actually a realistic thing, but it's like the range somebody who wants, who is like us, who needed to buy for a month can actually buy for a month. They can like place the order and there is actually a price for that. And it typically comes from somebody else who's selling back. Somebody who bought a longer term contract and is like they bought for some period of time, their code doesn't work, and now they need to like sell off a little bit.Alessio [00:25:49]: What are the utilization rates at which a market? What are the utilization rates at which a market? Like this works, what do you see the usual GPU utilization rate and like at what point does the market get saturated?Evan [00:26:00]: Assuming there are not like hardware problems or software problems, the utilization rate is like near 100 percent because the price dips until the utilization is 100 percent. So the price actually has to dip quite a lot in order for the utilization not to be. That's not always the case because you just have logistical problems like you get a cluster and parts of the InfiniBand fabric are broken. And there's like some issue with some switch somewhere and so you have to take some portion of the cluster offline or, you know, stuff like this, like there's just underlying physical realities of the clusters, but nominally we have better utilization than basically anybody because, but that's on utilization of the cluster, like that doesn't necessarily translate into, I mean, I actually do think we have much better overall money made for our underlying vendors than kind of anybody else. We work with the other GPU clouds and the basic pitch to the other GPU clouds is one. So we can sell your broker so we can we can find you the long term contracts that are at the prices that you want, but meanwhile, your cluster is idle and for that we can increase your utilization and get you more money because we can sell that idle cluster for you and then the moment we find the longer, the bigger customer and they come on, you can kick off those people and then go to the other ones. You get kind of the mix of like sell your cluster at whatever price you can get on the market and then sell your cluster at the big price that you want to do for long term contract, which is your ideal business model. And then the benefit of the whole thing being on the market. Is you can pitch your customer that they can cancel their long term contract, which is not a thing that you can reasonably do if you are just the GPU cloud, if you're just the GPU cloud, you can never cancel your contract, because that introduces so much risk that you would otherwise, like not get your cheap cost of capital or whatever. But if you're selling it through the market, or you're selling it with us, then you can say, hey, look, you can cancel for a fee. And that fee is the difference between the price of the market and then the price that they paid at, which means that they canceled and you have the ability to offer that flexibility. But you don't. You don't have to take the risk of it. The money's already there and like you got paid, but it's just being sold to somebody else. One of our top pieces from last year was talking about the H100 glut from all the long term contracts that were not being fully utilized and being put under the market. You have on here dollar a dollar per hour contracts as well as it goes up to two. Actually, I think you were involved. You were obliquely quoted in that article. I think you remember. I remember because this was hidden. Well, we hid your name, but then you were like, yeah, it's us. Yeah. Could you talk about the supply and demand of H100s? Was that just a normal cycle? Was that like a super cycle because of all the VC funding that went in in 2003? What was that like? GPU prices have come down. Yeah, GPU prices have come down. And there's some part that has normal depreciation cycle. Some part of that is just there were a lot of startups that bought GPUs and never used them. And now they're lending it out and therefore you exist. There's a lot of like various theories as to why. This happened. I dislike all of them because they're all kind of like they're often said with really high confidence. And I think just the market's much more complicated than that. Of course. And so everything I'm going to say is like very hedged. But there was a series of like places where a bunch of the orders were placed and people were pitching to their customers and their investors and just the broader market that they would arrive on time. And that is not how the world works. And because there was such a really quick build out of things, you would end up with bottlenecks in the supply chain somewhere that has nothing to do with necessarily the chip. It's like the InfiniBand cables or the NICs or like whatever. Or you need a bunch of like generators or you don't have data center space or like there's always some bottleneck somewhere else. And so a lot of the clusters didn't come online within the period of time. But then all the bottlenecks got sorted out and then they all came online all at the same time. So I think you saw a short. There was a shortage because supply chain hard. And then you saw a increase or like a glut because supply chain eventually figure itself out. And specifically people overordered in order to get the allocation that they wanted. Then they got the allocations and then they went under. Yeah, whatever. Right. There was just a lot of shenanigans. A caveat of this is every time you see somebody like overordered, there is this assumption that the problem was like the demand went down. I don't think that's the case at all. And so I want to clarify that. It definitely seems like a shortage. Like there's more demand for GPUs than there ever was. It's just that there was also more supply. So at the moment, I think there is still functionally a glut. But the difference that I think is happening is mostly the test time inference stuff that you just need way more chips for that than you did before. And so whenever you make a statement about the current market, people sort of take your words and then they assume that you're making a statement about the future market. And so if you say there's a glut now, people will continue to think there's a glut. But I think what is happening at the moment. My general prediction is that like by the winter, we will be back towards shortage. But then also, this very much depends on the rollout of future chips. And that comes with its own. I think I'm trying to give you like a good here's Evan's forecast. Okay. But I don't know if my forecast is right. You don't have to. Nobody is going to hold you to it. But like I think people want to know what's true and what's not. And there's a lot of vague speculations from people who are not that close to the market actually. And you are. I think I'm a closer. Close to the market, but also a vague speculator. Like I think there are a lot of really highly confident speculators and I am indeed a vague speculator. I think I have more information than a lot of other people. And this makes me more vague of a spectator because I feel less certain or less confident than I think a lot of other people do. The thing I do feel reasonably confident about saying is that the test time inference is probably going to quite significantly expand the amount of compute that was used for inference. So a caveat. This is like pretty much all the inference demand is in a few companies. A good example is like lots of bio and pharma was using H100s training sort of the bio models of sorts. And they would come along and they would buy, you know, thousands of H100s for training and then just like not a lot of stuff for inference. Not in any, not relative to like an opening iron anthropic or something because they like don't have a consumer product. Their inference event, if they can do it right. There's really like only one inference event that matters. And obviously I think they're going to run into it. And Batch and they're not going to literally just run one inference event. But like the one that produces the drug is the important one. Right. And I'm dumb and I don't know anything about biology, so I could be completely wrong here. But my understanding is that's kind of the gist. I can check that for you. You can check that for me. Check that for me. But my understanding is like the one that produces the sequence that is the drug that, you know, cures cancer or whatever. That's the important deal. But like a lot of models look like this where they're sort of more enterprising use cases or they're so prior to something that looks like test time inference. You got lots and lots of demand for training and then pretty much entirely fell off for inference. And I think like we looked at like Open Router, for example, the entirety of Open Router that was not anthropic or like Gemini or OpenAI or something. It was like 10 H100 nodes or something like that. It's just like not that much. It's like not that many GPUs actually to service that entire demand. But that's like a really sizable portion of the sort of open source market. But the actual amount of compute needed for it was not that much. But if you imagine like what an OpenAI needs for like GPT-4, it's like tremendously big. But that's because it's a consumer product that has almost all the inference demand. Yeah, that's a message we've had. Roughly open source AI compared to closed AI is like 5%. Yeah, it's like super small. Super small. It's super small. Super small. But test time inference changes that quite significantly. So I will... I will expect that to increase our overall demand. But my question on whether or not that actually affects your compute price is entirely based on how quickly do we roll out the next chips. The way that you burst is different for test time.Alessio [00:34:01]: Any thoughts on the third part of the market, which is the more peer-to-peer distributed, some are like crypto-enabled, like Hyperbolic, Prime Intellect, and all of that. Where do those fit? Like, do you see a lot of people will want to participate in a peer-to-peer market? Or just because of the capital requirements at the end of the day, it doesn't really matter?Evan [00:34:20]: I'm like wildly skeptical of these, to be frankly. The dream is like steady at home, right? I got this $15.90. Nobody has $15.90. $14.90 sitting at home. I can rent it out. Yeah. Like, I just don't really think this is going to ever be more efficient than a fully interconnected cluster with InfiniBand or, you know, whatever the sort of next spec might be. Like, I could be completely wrong. But speaking of... I mean, like, SpeedoLite is really hard to beat. And regardless of whatever you're using, you just like can't get around that physical limitation. And so you could like imagine a decentralized market that still has a lot of places where there's like co-location. But then you would get something that looks like SF Compute. And so that's what we do. That's why we take our general take is like on SF Compute, you're not buying from like random people. You're buying from the other GPU clouds, functionally. You're buying from data centers that are the same genre of people that you would work with already. And you can specify, oh, I want all these nodes to be co-located. And I don't think you're really going to get around that. And I think I buy crypto for the purposes of like transferring money. Like the financial system is like quite painful and so on. I can understand the uses of it to sort of incentivize an initial market or try to get around the cold start problem. We've been able to get around the cold start problem just fine. So it didn't actually need that at all. What I do think is totally possible is you could launch a token and then you could like subsidize the crypto. You could compute prices for a bit, but like maybe that will help you. I think that's what Nuus is doing. Yeah, I think there's lots of people who are trying to do things like this, but at some point that runs out. So I would, I think generally agree. I think the only thread in that model is very fine grained mixture of experts that can be like algorithms can shift to adapt to hardware realities. And the hardware reality is like, okay, it's annoying to do large co-located clusters. Then we'll just redesign attention or whatever in our architecture to distribute it more. There was a little bit buzz of block attention last year that Strong Compute made a big push on. But I think like, you know, in a world where we have 200 experts in MOE model, it starts to be a little bit better. Like, I don't disagree with this. I can imagine the world in which you have like, in which you've redesigned it to be more parallelizable, like across space.Evan [00:36:43]: But assuming without that, your hardware limitation is your speed of light limitation. And that's a very hard one to get around.Alessio [00:36:50]: Any customers or like stories that you want to shout out of like maybe things that wouldn't have been economically viable like others? I know there's some sensitivity on that.Evan [00:37:00]: My favorites are grad students, are folks who are trying to do things that would normally otherwise require the scale of a big lab. And the grad students are like the worst pilots. They're like the worst possible customer for the traditional GPU clouds because they will immediately turn if you sell them a thing because they're going to graduate and they're not going to go anywhere. They're not going to like, that project isn't continuing to spend lots of money. Like sometimes it does, but not if you're like working with the university or you're working with the lab of some sort. But a lot of times it's just like the ability for us to offer like big burst capacity, I think is lovely and wonderful. And it's like one of my favorite things to do because all those folks look like we did. And I have a special place in my heart for that. I have a special place in my heart for young hackers and young grad students and researchers who are trying to do the same genre of thing that we are doing. For the same reason, I have a special place in my heart for like the startups, the people who are just actively trying to compete on the same scale, but can't afford it time-wise, but can afford it spike-wise. Yeah, I liked your example of like, I have a grant of 100K and it's expiring. I got to spend it on that. That's really beautiful. Yeah. Interesting. Has there been interesting work coming out of that? Anything you want to mention? Yeah. So from like a startup perspective, like Standard Intelligence and Find, P-H-I-N-D. We've had them on the pod.Swyx [00:38:23]: Yeah. Yeah.Evan [00:38:23]: That was great. And then from grad students' perspective, we worked a lot with like the Schmidt Futures grantees of various sorts. My fear is if I talk about their research, I will be completely wrong to a sort of almost insulting degree because I am very dumb. But yeah. I think one thing that's maybe also relevant startups and GPUs-wise. Yeah. Is there was a brief moment where it kind of made sense that VCs provided GPU clusters. And obviously you worked at AI Grants, which set up Andromeda, which is supposedly a $100 million cluster. Yeah. I can explain why that's the case or why anybody would think that would be smart. Because I remember before any of that happened, we were asking for it to happen. Yeah. And the general reason is credit risk. Again, it's a bank. Yeah. I have lower risk than you due to credit transformation. I take your risk onto my balance sheet. Correct. Exactly. If you wanted to go for a while, if you wanted to go set up a GPU cluster, you had to be the one that actually bought the hardware and racked it and stacked it, like co-located it somewhere with someone. Functionally, it was like on your balance sheet, which means you had to get a loan. And you cannot get a loan for like $50 million as a startup. Like not really. You can get like venture debt and stuff, but like it's like very, very difficult to get a loan of any serious price for that. But it's like not that difficult to get a loan for $50 million. If you already have a fund or you already have like a million dollars under your assets somewhere or like you personally can like do a personal guarantee for it or something like this. If you have a lot of money, it is way easier for you to get a loan than if you don't have a lot of money. And so the hack of a VC or some capital partner offering equity for compute is always some arbitrage on the credit risk. That's amazing. Yeah. That's a hack. You should do that. I don't think people should do it right now. I think the market has like, I think it made sense at the time and it was helpful and useful for the people who did it at the time. But I think it was a one-time arbitrage because now there are lots of other sources that can do it. And also I think like it made sense when no one else was doing it and you were the only person who was doing it. But now it's like it's an arbitrage that gets competed down. Sure. So it's like super effective. I wouldn't totally recommend it. Like it's great that Andromeda did it. But the marginal increase of somebody else doing it is like not super helpful. I don't think that many people have followed in their footsteps. I think maybe Andreessen did it. Yeah. That's it. I think just because pretty much all the value like flows through Andromeda. What? That cannot be true. How many companies are in the air, Grant? Like 50? My understanding of Andromeda is it works with all the NFTG companies or like several of the NFTG companies. But I might be wrong about that. Again, you know, something something. Nat, don't kill me. I could be completely wrong. But the but you know, I think Andromeda was like an excellent idea to do at the right time in which it occurred. Perfect. His timing is impeccable. Timing. Yeah. Nat and Daniel are like, I mean, there's lots of people who are like... Sears? Yeah. Sears. Like S-E-E-R. Oh, Sears. Like Sears of the Valley. Yeah. They for years and years before any of the like ChatGPT moment or anything, they had fully understood what was going to happen. Like way, way before. Like. AI Grant is like, like five years old, six years old or something like that. Seven years old. When I, when it like first launched or something. Depends where you start. The nonprofit version. Yeah. The nonprofit version was like, like happening for a while, I think. It's going on for quite a bit of time. And then like Nat and Daniel are like the early investors in a lot of the sort of early AI labs of various sorts. They've been doing this for a bit.Alessio [00:41:58]: I was looking at your pricing yesterday. We're kind of talking about it before. And there's this weird thing where one week is more expensive of both one day and one month. Yeah. What are like some of the market pricing dynamics? What are things that like this to somebody that is not in the business? This looks really weird. But I'm curious, like if you have an explanation for it, if that looks normal to you. Yeah.Evan [00:42:18]: So the simple answer is preemptible pricing is cheaper than non-preemptible pricing. And the same economic principle is the reason why that's the case right now. That's not entirely true on SF Compute. SF Compute doesn't really have the concept of preemptible. Instead, what it has is very short reservations. So, you know, you go to a traditional cloud provider and you can say, hey, I want to reserve contract for a year. We will let you do a reserve contract for one hour, which is the part of SFC. But what you can do is you can just buy every single hour continuously. And you're reserving just for that hour. And then the next hour you reserve just for that next hour. And this is obviously like a built in. This is like an automation that you can do. But what you're seeing when you see the cheap price is you're seeing somebody who's buying the next hour, but maybe not necessarily buying an hour after that. So if the price goes up. Up too much. They might not get that next hour. And the underlying part of this of where that's coming from the market is you can imagine like day old milk or like milk that's about to be old. It might drop its price until it's expired because nobody wants to buy the milk that's in the past. Or maybe you can't legally sell it. Compute is the same way. No, you can't sell a block of compute that is not that is in the past. And so what you should do in the market and what people do do is they take. They take a block. A block of compute. And then they drop it and drop it and drop it and drop into a floor price right before it's about to expire. And they keep dropping it until it clears. And so anything that is idle drops until some point. So if you go and use on the website and you set that that chart to like a week from now, what you'll see is much more normal looking sort of curves. But if you say, oh, I want to start right now, that immediate instant, here's the compute that I want right now is the is functionally the preemptible price. It's where most people are getting the best compute or like the best compute prices from. The caveat of that is you can do really fun stuff on SFC if you want. So because it's not actually preemptible, it's it's reserved, but only reserved for an hour, which means that the optimal way to use as of compute is to just buy on the market price, but set a limit price that is much higher. So you can set a limit price for like four dollars and say, oh, if the market ever happens to spike up to four dollars, then don't buy. I don't want to buy that at that price for that price. I don't want to buy that at that price for that price for an hour. But otherwise, just buy at the cheapest price. And if you're comfortable with that of the volatility of it, you're actually going to get like really good prices, like close to a dollar an hour or so on, sometimes down to like 80 cents or whatever. You said four, though. Yeah. So that's the thing. You want to lower the limit. So four is your max price. Four is like where you basically want to like pull the plug and say don't do it because the actual average price is not or like the, you know, the preemptible price doesn't actually look like that. So what you're doing when you're saying four is always, always, always give me this compute. Like continue to buy every hour. Don't preempt me. Don't kick me off. And I want this compute and just buy at the preemptible price, but never kick me off. The only times in which you get kicked off is if there is a big price spike. And, you know, let's say one day out of the year, there's like a four dollar an hour price because of some weird fluke or something. If there are other periods of time, you're actually getting a much lower price than you. It makes sense. Your your average cost that you're actually paying is way better. And your trade off here is you don't literally know what price you're going to get. So it's volatile. But your actual average historically has been like everyone who's done this has gotten wildly better prices. And this is like one of the clever things you can do with the market. If you're willing to make those trade offs, you can get a lot of really good prices. You can also do other things like you can only buy at night, for example. So the price goes down at night. And so you can say, oh, I want to only buy, you know, if the price is lower than 90 cents. And so if you have some long running job, you can make it only run on 90 cents and then you recover back and so on. Yeah. So what you can kind of create as like a spot inst is what other the CPU world has. Yes. But you've created a system where you can kind of manufacture the exact profile that you want. Exactly. That is not just whatever the hyperscalers offer you, which is usually just one thing. Correct. SF Compute is like the power tool. The underlying primitives of like hourly compute is there. Correct. Yeah, it's pretty interesting. I've often asked OpenAI. So like, you know, all these guys. Cloud as well. They do batch APIs. So it's half off of whatever your thing is. Yeah. And the only contract is we'll return in 24 hours. Sure. Right. And I was like, 24 hours is good. But sometimes I want one hour. I want four hours. I want something. And so based off of SF Compute's system, you can actually kind of create that kind of guarantee. Totally. That would be like, you know, not 24, but within eight hours, within four hours, like the work half of a workday. Yes. I can return your results to you. And then I can return it to you. And if your latency requirements are like that low, actually it's fine. Yes. Correct. Yeah. You can carve out that. You can financially engineer that on SFC. Yeah. Yeah. I mean, I think to me that unlocks a lot of agent use cases that I want, which is like, yeah, I worked in a background, but I don't want you to take a day. Yeah. Correct. Take a couple hours or something. Yeah. This touches a lot of my like background because I used to be a derivatives trader. Yeah. And this is a forward market. Yeah. A futures forward market, whatever you call it. Not a future. Very explicitly not a future. Not yet a futures. Yes. But I don't know if you have any other points to talk about. So you recognize that you are a, you know, a marketplace and you've hired, I met Alex Epstein at your launch event and you're like, you're, you're building out the financialization of GPUs. Yeah. So part of that's legal. Mm-hmm. Totally. Part of that is like listing on an exchange. Yep. Maybe you're the exchange. I don't know how that works, but just like, talk to me about that. Like from the legal, the standardization, the like, where is this all headed? You know, is this like a full listed on the Chicago Mercantile Exchange or whatever? What we're trying to do is create an underlying spot market that gives you an index price that you can use. And then with that index price, you can create a cash settled future. And with a cash settled future, you can go back to the data centers and you can say, lock in your price now and de-risk your entire position, which lets you get cheaper cost of capital and so on. And that we think will improve the entire industry because the marginal cost of compute is the risk. It's risk as shown by that graph and basically every part of this conversation. It's risk that causes the price to be all sorts of funky. And we think a future is the correct solution to this. So that's the eventual goal. Right now you have to make the underlying spot market in order to make this occur. And then to make the spot market work, you actually have to solve a lot of technology problems. You really cannot make a spot market work if you don't run the clusters, if you don't have control over them, if you don't know how to audit them, because these are super computers, not soybeans. They have to work. In a way that like, it's just a lot simpler to deliver a soybean than it is to deliver it. I don't know. Talk to the soybean guys. Sure. You know? Yeah. But you have to have a delivery mechanism. Your delivery mechanism, like somebody somewhere has to actually get the compute at some point and it actually has to work. And it is really complicated. And so that is the other part of our business that we go and we build a bare metal infrastructure stack that goes. And then also we do auditing of all the clusters. You sort of de-risk the technical perspective and that allows you to eventually de-risk the financial perspective. And that is kind of the pitch of SF Compute. Yeah. I'll double click on the auditing on the clusters. This is something I've had conversations with Vitae on. He started Rika and I think he had a blog post which kind of shone the light a little bit on how unreliable some clusters are versus others. Correct. Yeah. And sometimes you kind of have to season them and age them a little bit to find the bad cards. You have to burn them in. Yeah. So what do you do to audit them? There's like a burn-in process, a suite of tests, and then active checking and passive checking. Burn-in process is where you typically run LINPACK. LINPACK is this thing that like a bunch of linear algebra equations that you're stress testing the GPUs. This is a proprietary thing that you wrote? No, no, no. LINPACK is like the most common form of burn-in. If you just type in burn-in, typically when people say burn-in, they literally just mean LINPACK. It's like an NVIDIA reference version of this. Again, NVIDIA could run this before they ship, but now the customers have to do it. It's annoying. You're not just checking for the GPU itself. You're checking like the whole component, all the hardware. And it's a lot of work. It's an integration test. It's an integration test. Yeah. So what you're doing when you're running LINPACK or burn-in in general is you're stress testing the GPUs for some period of time, 48 hours, for example, maybe seven days or so on. And you're just trying to kill all the dead GPUs or any components in the system that are broken. And we've had experiences where we ran LINPACK on a cluster and it rounds out, sort of comes offline when you run LINPACK. This is a pretty good sign that maybe there is a problem with this cluster. Yeah. So LINPACK is like the most common sort of standard test. But then beyond that, what you do is we have like a series of performance tests that replicate a much more realistic environment as well that we run just assuming if LINPACK works at all, then you run the next set of tests. And then while the GPUs are in operation, you're also going through and you're doing active tests and passive tests. Passive tests are things that are running in the background while somebody else is running, while like some other workload is running. And active tests are during like idle periods. You're running some sort of check that would otherwise sort of interrupt something. And then the active tests will take something offline, basically. Or a passive check might mark it to get taken offline later and so on. And then the thing that we are working on that we have working partially but not entirely is automated refunds, which is basically like, is the case that the hardware breaks so much. And there's only so much that we can do and it is the effect of pretty much the entire industry. So a pretty common thing that I think happens to kind of everybody in the space is a customer comes online, they experience your cluster, and your cluster has the same problem that like any cluster has, or it's I mean, a different problem every time, but they experience one of the problems of HPC. And then their experience is bad. And you have to like negotiate a refund or some other thing like this. It's always case by case. And like, yeah, a lot of people just eat the cost. Correct. So one of the nice things about a market that we can do as we get bigger and have been doing as we can bigger is we can immediately give you something else. And then also we can automatically refund you. And you're still gonna experience it like the hardware problems aren't going away until the underlying vendors fix things. But honestly, I don't think that's likely because you're always pushing the limits of HPC. This is the case of trying to build a supercomputer. that's one of the nice things that we can do is we can switch you out for somebody else somewhere, and then automatically refund you or prorate or whatever the correct move is. One of the things that you say in this conversation with me was like, you know, you know, a provider is good when they guarantee automatic refunds. Which doesn't happen. But yeah, that's, that's in our contact with all the underlying cloud providers. You built it in already. Yeah. So we have a quite strict SLA that we pass on to you. The reason why
It should have been so simple. In fact, the hook is just two words: space vampires. That's it! And yet what resulted is a roiling boil of Dracula tropes, sweaty performances, extended nudity, and some of the best shriveled puppets you'll ever see! That's right, we're zapping the energy out of 1985's LIFEFORCE with the help of actor and stand-up, Matthew Broussard (watch his new comedy special, Hyperbolic here!!). Along the way, we learn all Tobe Hooper's magic touch, how the producers of Cannon Films nearly tore the film apart, why Steve Railsback is playing so many different Bram Stoker roles in one movie, and Matthew schools us on physics!! All this, plus fallopian flashbacks, biscuit bribes, physician prescribed swords, helicopter blood conferences, male ass technology, Patrick Stewart bald pate worship, and a cosmically insane edition of Choose Your Own Deathventure!! Blast off with a very new episode of Kill By Kill with us today, won't you? Control Body Odor ANYWHERE with @shop.mando and get $5 off your Starter Pack (that's over 40% off) with promo code KILLPOD. Go to shopmando.com and use KILLPOD when you check out! #mandopod Part of the BLEAV Network.Get even more episodes exclusively on Patreon! Artwork by Josh Hollis: joshhollis.com Kill By Kill theme by Revenge Body. For the full-length version and more great music, head to revengebodymemphis.bandcamp.com today! Our linker.ee Click here to visit our TeePublic shop for killer merch! Join the conversation about any episode on the Facebook Group! Follow us on IG @killbykillpodcast!! Join us on Threads or even Bluesky Check out Gena's Substack called Gena Watches Things!! Check out the films we've covered & what might come soon on Letterboxd!
Dave and Buster Filler! Not much Dave and Buster talk, some, but we get into a bunch of topics. Unscripted and unfiltered in these fillers like always. Exciting News! We'll be at Charlie's Epic Con @ Fort Myers! Come by and see us April 6th at Booth 36! We'll be doing a Giveaway, selling dope new shirts, doing a mini episode (maybe a filler) and gonna be on video asking questions and taking pictures! Play and Beat CaptnKillamanjaro at Sparking Zero or Tekken and get an additional entry into the raffle! I bet you can't. We're on our way to be the best podcast for Anime, Video Games and Movies!!!
The very funny Matthew Broussard swings by the Mad House this week to talk about his new hour-long stand up special 'Hyperbolic', and we're NOT exaggerating when we tell you it's a hoot and a half!! He and Maddy also discuss math (Matthew's a biggg numbers guy), standing up for ourselves, current events, and more! Plus, stay tuned for our hotline, featuring a vengeful carpet store employee!!Call the FUPA Hotline: (347) 480-9006Check out Matthew's stand up special, 'Hyperbolic':https://www.youtube.com/watch?v=5UECGG-CD88&t=41sFollow Matthew:https://www.instagram.com/mondaypunday/?hl=enFollow Maddy:https://www.instagram.com/somaddysmith/?hl=enhttps://www.tiktok.com/@somaddysmith?lang=enAll tour dates: https://maddysmithcomedy.com/Want more Mad House?!Go to https://gasdigitalnetwork.com/ to subscribe!Use promo code MAD to save big on your membership :)Get early access to our weekly episodes on Tuesdays, along with EXCLUSIVE episodes every Thursday.UPCOMING STAND UP DATES:3/20-3/23 DENVER, CO3/27 BROOKFIELD, WI3/28 CHICAGO, IL3/30 HOBOKEN, NJ4/4-4/5 AUSTIN, TX4/11-4/12 CARY, NC5/1-5/3 TULSA, OKProducer: Caroline MazzeiSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
We loved chatting and laughing with comedian Matthew Broussard about proposals, orgasms, fights in a relationship, and more. He shares his unconventional engagement story and lets us into his relationship with his fiancé, including why vibrators are a must in the bedroom. We also talk about masturbating stigma, the complexity of the female orgasm, and whether guys fake orgasms. And we answer the question “Who starts more fights in the relationship – men or women?” and analyze some listener emails about blowjobs to completion, and why one woman's boyfriend won't let her post him on social media. Before Matthew joins us, we catch up on our trip to Austin, Ashley being deep in wedding planning, and Rayna going hard in her dating era. Enjoy! Follow Matthew on Instagram @mondaypunday and watch his special Hyperbolic. Follow us on Instagram @girlsgottaeatpodcast, Ashley @ashhess, and Rayna @rayna.greenberg. Visit girlsgottaeat.com for more. Thank you to our partners this week: Addyi: Learn more at https://addyi.com Skims: Shop Skims best intimates collection at https://skims.com and in stores. Nutrafol: Get $10 off your first month's subscription and free shipping at https://nutrafol.com with code GGE10. Rocket Money: Cancel your unwanted subscriptions at https://rocketmoney.com/gge. Helix: Get 20% off at https://helixsleep.com/gge.
I sit down with comedians, Matthew Broussard & Ari Shaffir. We talk about Matthews brain, his new special, confrontations, judaism, and much more! Check out Matthew's new special “HYPERBOLIC” on YouTube here: https://www.youtube.com/watch?v=5UECGG-CD88&t=226s Check out Ari's special “America's Sweetheart” on Netflix Follow Matthew YT: https://www.youtube.com/@mondaypunday IG: https://www.instagram.com/mondaypunday Follow Ari YT: https://www.youtube.com/@arishaffir IG: https://www.instagram.com/arishaffir --------------------------------------------------- Sponsors: Helix Sleep - Go to https://helixsleep.com/bert for 20% Off Sitewide Robinhood - To receive your 3% boost on annual IRA contributions, sign up at https://robinhood.com/gold Magic Spoon - Get 5 dollars off your next order at https://MagicSpoon.com/BERT. Liquid I.V. - Get 20% off your first order of Liquid I.V. when you go to https://www.LIQUIDIV.COM and use code BERT at checkout. BetterHelp - Get 10% off your first month at https://www.betterhelp.com/bert Manscaped - Get The Beard & Balls Bundle for 20% OFF + Free International Shipping with code “BERT” at https://Manscaped.com! #ManscapedPartner Cigars International - Visit www.cigarsinternational.com/BERT or use code BERT at checkout for 20% off PLUS free shipping on your entire order. --------------------------------------------------- SUBSCRIBE so you never miss a video https://bit.ly/3DC1ICg For all TOUR DATES: http://www.bertbertbert.com For Fully Loaded: https://fullyloadedfestival.com For Merch: https://store.bertbertbert.com YouTube▶ http://www.YouTube.com/user/Akreischer X▶ http://www.Twitter.com/bertkreischer Facebook▶ http://www.Facebook.com/BertKreischer Instagram▶ http://www.Instagram.com/bertkreischer TikTok▶ http://www.TikTok.com/@bertkreischer Text Me▶ https://my.community.com/bertkreischer Learn more about your ad choices. Visit megaphone.fm/adchoices
TIME CODES BELOW!Quote from Toriyama, "Due to a conspiracy, Goku and his friends are turned small. In order to fix things, they'll head off to a new world! It's a grand adventure with intense action in an unknown and mysterious world. Things will unfold that close in on the mysteries of the Dragon Ball world. Hope you all enjoy these different-from-usual battles that are cute and powerful!"Did Daima deliver? Find out in this exciting episode of THE HYPERBOLIC PODCAST! 0:00 Intro 01:58 Oda's Favorite Devil Fruit07: 18 Yu-Gi-Oh! GX Remaster Video Game News10:23 Live Action Street Fighter Release Date and Director 13: 05 Meat and Potatoes 58:11 Whatcha Reading Whatcha Playing Whatcha Watching01:21:51 Outro
As the Florida Gators gear up for the 2025 season, spring practice is officially underway, bringing renewed energy and anticipation to Gainesville. This pivotal period allows the team to assess talent, integrate new coaching staff, and refine strategies for the upcoming challenges. We also welcome Chuck Jeroloman, Associate Head Coach, of the Florida Gators baseball program to the show. Key Storylines: Coaching Updates: Head Coach Billy Napier has promoted Russ Callaway to Offensive Coordinator, aiming to inject fresh perspectives into the Gators' offensive schemes. Position Battles: Intense competition is expected, particularly at wide receiver and right tackle positions, as players vie to secure starting roles. Returning Talent: The Gators are bolstered by a strong contingent of returning players, enhancing both experience and depth across the roster. gatorsbreakdown.com Join us as we delve into these developments, providing in-depth analysis and interviews with players and coaches. Stay tuned for insights into how the Gators are preparing to make a significant impact in the upcoming season. Stadium and Gale is your number-one source for all things Florida Gators!
Time Codes BelowAFRO! Samurai. You gotta be the number one samurai. 0:00 Intro 02:34 Dragonball Super Manga Comeback 05:57 Onimusha Way of Sword Casting 09:56 Dungeons & Dragons Series on Netflix 15:30 Meat and Potatoes - Afro Samurai 57:45 Yasuke 1:03:45 Anime Superlative: Best Hair (where it concerns an afro)1:11:22 Watcha Reading, Watcha Watching, Watcha Playing ???
TIME CODES BELOW! From Tamagotchis to a massive media franchise, come take a trip down the digital memory lane (RAM) and explore current news on the beloved anime some say is as good as if not better than Pokémon, Digimon! Return guest AlexisTheSnail chill with the Hyperbolic Boys in the new studio setup which maybe should be the start to a new season of The Normn Hyperbolic Podcast! 0:00 Intro 2:35 Anime News - Spider-Man Manga: Shadow Warrior 6:54 Video Game News - Switch 2 Rumor Launch Titles 20:01 Movie News - Harry Potter x Detective Conan and New Harry Potter HBO Max 31:08 Meat and Potatoes- DIGIMON! 52:10 Digi Destined DRIP 56:11 Digimon Movie 01:02:41 Digimon Video Games 01:12:57 Digimon TCG 01:22:53 Digimon Beyond and Future of Digimon 01:30:30 Whatcha Reading, Whatcha Watching, Whatcha Playing? 01:51:26 Outro
Hello Seekers! Ben here, Hesse and Jacques join me today to talk about the Inauguration, the various facelifts it featured, and of course what we expect from a 2nd Trump turn. Then we turn to two of the most annoying people we frequently cover on this show–Bill Maher and Bryan Johnson and watch the Club Random episode wherein Bryan literally talks about dating his own son. Get Tickets to Jacques LA show here: https://www.lodgeroomhlp.com/shows/game-show-pig/
Welcome back to the JTrain Podcast, hosted by Jared Freid! It's Chit Chat Wednesday, and we're kicking off the new year with the incredibly sharp and hilarious Matthew Broussard. Matthew joins Jared to talk about his brand-new stand-up special, Hyperbolic, now streaming on YouTube (link in the episode description). Already racking up over 125,000 views, Hyperbolic showcases Matthew's brilliantly crafted jokes and relatable yet unexpected humor.This week, Jared and Matthew dive deep into the art of comedy—sharing battle stories from tough New Year's Eve gigs, the intricacies of joke-writing, and the unique stress (and humor) that comes from having family in the audience. They unpack Matthew's standout joke about a heartfelt letter from his mom, Jared's reflections on his mom seeing his set on The Tonight Show, and how vulnerability adds depth to stand-up.The conversation also explores the emotional highs and brutal lows of comedy life, debating what “making it” really means in the world of stand-up. With hilarious anecdotes about performing at hotels and the pressure of NYE countdown duties, this episode is a celebration of comedy, connection, and the joy of storytelling.So, grab your headphones and tune in for a fun, insightful, and laugh-out-loud episode that's sure to brighten your week. And don't forget to check out Matthew's special Hyperbolic for even more laughs!Check out Matthew Broussard's YouTube special, Hyperbolic Also listen to the comedy war stories from New Year's Eve gigs!
Comedian Matthew Broussard stops by to talk about his new special, “Hyperbolic”. They also discuss New Jersey lawyer billboards, flying private, Adam trying to smuggle leftovers into Madison Square Garden, and the one part of his new special that Matthew's mom doesn't like. Next, Jason “Mayhem” Miller reads the news including stories about Senator Josh Hawley introducing legislation intended to ban airlines from making passengers pay fees as a condition of boarding a flight, ABC settling with Donald Trump for $16 million after George Stephanopoulos repeatedly insisted Trump had been found liable for rape, and the mysterious drone sightings around the country. Then, they wrap the show with Adam talking about his lifelong battle with stucco. For more with Matthew Broussard: ● NEW SPECIAL: Hyperbolic - Available on YouTube. ● INSTAGRAM & X: @mondaypunday ● WEBSITE: broussard.live ● LIVE SHOWS: ○ Rooster's Comedy Club - Sunnyvale, CA: December 19th - 22nd For more with Sam Tripoli: ● NEW SPECIAL: Quiet - Available on his website samtripoli.com ● INSTAGRAM & X: @samtripoli ● WEBSITE: samtripoli.com ● LIVE DATES: ○ The Comedy Vault - Batavia, IL: January 23-25 Thank you for supporting our sponsors: ● http://SimpliSafe.com/Adam ● http://Hydrow.com, use code ADAM to save up to $800 ● RosettaStone.com/Adam ● http://TommyJohn.com/Adam ● http://OReillyAuto.com/Adam
It's a comedy round table in the midst of this comedy boom! @MichaelYoComedy and @RudyPavich are joined by Matthew Broussard @mondaypunday to chat about his new special HYPERBOLIC out now on Youtube! Plus, Michael gives some details about his upcoming special SNACK DADDY, dropping January 28th, also on Youtube! 꼭 봐야 할 코미디 스페셜 | Matthew Broussard의 쌍곡선 | 마이클 요의 SNACK DADDY Watch Matthew's HYPERBOLIC: https://www.youtube.com/watch?v=5UECGG-CD88 Follow Matthew: Insta: https://www.instagram.com/mondaypunday/?hl=en X: https://x.com/mondaypunday Facebook: https://www.facebook.com/matthewbroussardlive/ More from Michael Yo Support Michael Yo
Comedian Matthew Broussard (@mondaypunday) returns to the show to chat with Jesse, Andy and Matt about Matthew's new special Hyperbolic, exaggerated accents, the CEO shooter, cyborg beetles, a quantum computing milestone, gray goo, online security in a post-quantum world, elliptic curves, conic sections, Fermat's Enigma and a super old bird mother.
This week, our friends Matthew Broussard and Gregory Lay join Dave for some word cloud singing, Zucc puns, and Tickle Me Elmo trivia. Matthew Broussard would like to plug his special Hyperbolic and recommends 3Blue1BrownGregory Lay would like to plug Greg in LA and recommends Tom Sibley's SubstackDave is on Bluesky! Find us on Instagram! We are @TroubledPodWritten by Riley Silverman and John-Luke Roberts, recorded remotely over Zoom and produced by Christian Dueñas and Laura Swisher.Join the MaxFun fam:maximumfun.org/join
Matthew Broussard (@MondayPunday) is a comic (he has a new special/album out Dec 13 Hyperbolic) loves sci fi but likes it when the science seems plausible. So fun. It's November and that means I ask you NOT to donate to The Dork Forest, but to donate to your local food bank instead. FeedingAmerica.org will have you put your zip code in OR... if you have the google skills... or you live outside the US... GOOGLE "food bank" and the name of your Town/City. January I'll ask you for money for the show again. Nov and Dec ... donate to a local food bank!! Yay dorks. THERE IS NEW MERCH: BEES TSHIRT and BEANIES. I'm Made of BEES. Are you? www.JackieKashianStore.com is the direct. www.jackiekashian.com and www.dorkforest.com have so many other things. Extra TDF / standup and a storytelling album are available here: https://thedorkforest.bandcamp.com/ Lots of stuff here: https://www.youtube.com/@JackieKashianInc And it's @jackiekashian on all the social mediaz. Audio and Video by Patrick Brady Music is by Mike Ruekberg Learn more about your ad choices. Visit megaphone.fm/adchoices