Podcasts about SF

In our 36th episode of This F*cking Guy, Erin and Crooked Media's Kendra James dive deep into the past of supermodel villain, Naomi Campbell. From her “feud" with Tyra Banks, to her unsavory taste in men, to her laundry list of assault charges, to her murky friendship with Jeffrey Epstein, this may be one of our most hostile, prima donna guys yet.For a closed-captioned version of this episode, click here. For a transcript of this episode, please email transcripts@crooked.com and include the name of the podcast.Sources: Timeline https://nymag.com/news/intelligencer/topic/67521/ Daily Mail allegations about Epstein from 2019 https://www.dailymail.co.uk/lifestyle/article-7367825/As-model-unexpectedly-honoured-philanthropy-meet-Naomi-Campbells-rum-chums.html Now Campbell met Mike https://www.heristical.com/p/a-j-ayer-vs-mike-tyson Campbell response video https://www.youtube.com/watch?v=DwgJzb7fllICampbell responds https://www.usatoday.com/story/entertainment/celebrities/2019/08/21/naomi-campbell-addresses-her-ties-jeffrey-epstein/2077443001/ Another accounting of the denial https://www.the-independent.com/life-style/naomi-campbell-jeffrey-epstein-youtube-video-watch-sex-trafficking-a9074121.html Daily Mail write-up https://www.dailymail.co.uk/news/article-7382151/Naomi-Campbell-says-knew-Jeffrey-Epstein-denies-knowledge-sex-crimes.htmlVictoria's Secret Fashion Show https://en.wikipedia.org/wiki/Victoria%27s_Secret_Fashion_Show Epstein Victoria's Secret NYT https://archive.ph/DjoBM2026 Epstein fileshttps://www.dailymail.co.uk/news/article-15538709/Naomi-Campbells-role-helping-Jeffrey-Epstein-try-buy-luxury-flat-near-Kremlin.html https://www.youtube.com/watch?v=OPt-O_lkHZA Charity https://archive.ph/i7ZcV#selection-879.0-915.152 Hadn't read own book https://uk.style.yahoo.com/in-defence-of-zoella--why-it-doesn-t-matter-if-her-book-was-ghost-written-121449326.html?guccounter=1&guce_referrer=aHR0cHM6Ly9kdWNrZHVja2dvLmNvbS8&guce_referrer_sig=AQAAAJ_swY1rJjJwhfuoMGZr3Ob-QLYx6XjAryJz5oZVEllHQrRu1LBfyoLokbR1VzpxTNQtu2-XbPBZhFwpD-sc_w3GberIT-b6CjkKa5u3RlAruE2TVlIZbOqIeIv_XW8qax057MR3rYe21kzQaWRKnjYOH5LaTL8yeGazHSOXQnCVAir ragehttps://www.cnn.com/2008/SHOWBIZ/06/20/campbell.court/index.html Abuse accusationshttps://www.the-independent.com/news/uk/crime/naomi-campbell-is-accused-of-abuse-for-the-eighth-time-421832.htmlLong legs, short fuse https://archive.ph/sz3qICampbell correcting the record https://www.youtube.com/watch?v=ibBE1akKRucDiddy on Campbell https://www.vogue.com/slideshow/the-naomi-factor-the-supermodels-friends-and-collaborators-on-how-she-became-an-icon Fashion for relief https://archive.ph/i7ZcV#selection-879.0-915.152 Elite model management dumps Campbell at the height of her career https://web.archive.org/web/20160413082507/http://www.people.com/people/archive/article/0,,20106429,00.htmlMention of Troy Beher's fight https://www.upi.com/Archives/1992/12/15/People/4329724395600/ Another mention of the Beher fight https://archive.ph/QBL0c Campbell assault 1998https://www.tampabay.com/archive/1998/12/05/naomi-campbell-faces-assault-charge-in-toronto/ Ana assault https://archive.ph/sz3qISunshine Sachs editing wiki entries https://www.nytimes.com/2015/06/23/business/media/a-pr-firm-alters-the-wiki-reality-of-its-star-clients.html Her album https://web.archive.org/web/20080507045326/http://www.independent.co.uk/arts-entertainment/music/news/the-worst-album-in-the-world-ever-471490.html Epstein files presence https://www.nytimes.com/2026/02/15/style/epstein-files-naomi-campbell.htmlMore on Epstein  https://www.yahoo.com/entertainment/celebrity/articles/naomi-campbell-gave-jeffrey-epstein-013602188.html?guccounter=1 https://www.harpersbazaar.com/fashion/models/a1401/24-hours-with-naomi-campbell-0214/https://archive.nytimes.com/www.nytimes.com/specials/magazine4/articles/campbell.htmlhttps://www.interviewmagazine.com/fashion/naomi-campbell-1https://www.bbc.com/news/articles/c361k687115ohttps://www.theguardian.com/observer/focus/story/0,6903,651663,00.htmlhttps://www.today.com/popculture/naomi-campbell-discusses-her-drug-addiction-wbna5962519Campbell did the vagina monologues in SF https://www.sfgate.com/performance/article/A-model-actress-Naomi-Campbell-says-painful-2886133.php Campbell wearing a Nelson Eandela hathttps://archive.ph/ZyzFj#selection-1621.0-1687.1https://archive.ph/1Mnuk  W magazine https://www.wmagazine.com/culture/naomi-campbell-probationhttps://www.youtube.com/watch?v=ibBE1akKRuc Assault https://www.wthr.com/article/news/local/naomi-campbell-released-bail/531-e10146e8-769f-4975-99f9-9892a2bb9fc4 Phone at maid assault https://www.cleveland19.com/story/5944870/naomi-campbell-pleads-guilty-to-assault/Missing jeans assault https://www.today.com/popculture/naomi-campbell-sued-another-maid-1c9432812Campbell community service couture https://www.wmagazine.com/culture/naomi-campbell-probation Breach of contract lawsuit https://www.nbcmiami.com/news/local/sobe-perfume-maker-says-naomi-campbell-stinks/1847782/British Airways https://www.thetimes.com/uk/crime/article/naomi-campbell-escapes-jail-over-pc-assault-and-tirade-on-ba-jet-c2v09tlvr7rAmazed by Venezuela https://venezuelanalysis.com/news/2792/ Rumor of Chavez affair? https://observer.com/2008/01/naomi-campbell-model-interviewer-of-south-american-heads-of-state/ Animal rights group fires Campbell after appearing in fur https://www.upi.com/Archives/1997/03/11/Animal-rights-group-fires-Naomi-Campbell/2579858056400/ Kate Moss and Naomi Campbell https://www.papermag.com/hollyweird-naomi-kate-fidel Naomi gets in a slapfight at a Brazilian restaurant https://www.today.com/popculture/no-model-behavior-naomi-campbell-wbna8669444 Convicted of assault in Italy https://archive.ph/YEZp8 Badr Jafar dust up https://archive.ph/QBL0c#selection-1515.2-1515.137Tyra-Naomi confrontation https://www.youtube.com/watch?v=516JwxaFVy4&t=256s Naomi talking about Tyra fight https://www.youtube.com/watch?v=BMSWEdz5qo8Video: shady Naomi moments https://www.youtube.com/watch?v=Q8DI7dcJyIoDisavowing Epstein https://www.youtube.com/watch?v=DwgJzb7fllI The Mirror's worst books of all time https://www.mirror.co.uk/3am/celebrity-news/7-worst-celebrity-books-you-36813997VIDEO: Barbara interviews her https://www.youtube.com/watch?v=EdprTCElJsg VIDEO: Wendy Williams compilation https://www.youtube.com/watch?v=g3vnmnlf6N4VIDEO: Blood diamond walk out https://www.youtube.com/watch?v=FT-6jzaVwkI VIDEO: Naomi's song Love And Tears, Live https://www.youtube.com/watch?v=mtb3Vj28vKk&list=RDmtb3Vj28vKk&start_radio=1Music video for Campbelll's Love and Tears https://www.youtube.com/watch?v=WdzfTJIa8_A&list=RDWdzfTJIa8_A&start_radio=1 Blood diamonds, Campbell turned over to police https://www.youtube.com/watch?v=HWlBHzd_rNQ Community service runway https://www.youtube.com/watch?v=g5IH61o3HPE 

Willam and Alaska discuss the toilet bowl of podcast comments, Raja's upcoming drag sale, and softly lit and heavily mugged doctors and nurses on TV. Plus Alaska goes to SF and Willam flies to Alaska; face lifts in Hollywood, and the soundboard sounds go head to head in a March Madness bracket! Race Chaser LIVE in Boise on Thursday, March 26th at The Egyptian Theatre!Rainbow Spotlight - I Really Need To Know by Silver OttoListen to Race Chaser Ad-Free on MOM PlusFollow us on IG at @racechaserpod and click the link in bio for a list of organizations you can donate to in support of Black Lives MatterRainbow Spotlight - Empathy Gooner by Ricki Lantanahttps://music.apple.com/us/song/empathy-gooner/1877325902FOLLOW ALASKAhttps://twitter.com/Alaska5000https://www.instagram.com/theonlyalaska5000https://www.facebook.com/AlaskaThunderhttps://www.youtube.com/channel/UC9vnKqhNky1BcWqXbDs0NAQFOLLOW WILLAMhttps://twitter.com/willamhttps://www.instagram.com/willamhttps://www.facebook.com/willamhttps://www.youtube.com/channel/UCrO9hj5VqGJufBlVJy-8D1gRACE CHASER IS A FOREVER DOG PODCASTSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The RHOSLC girlies are in SF, we have to talk about Taylor Frankie Paul, and March MANness starts tomorrow! The Charmers really showed up for the reunion ready to fight. Are Craig and Austen scorned lovers? Back off our Salley! We break down Southern Hospitality: a lot of apologies, partying, and a car wash. Come judge with us! You can find us:Linktree: Two Judgey GirlsPodcast: ACast, iTunes, Spotify, wherever you listen!Instagram & Threads: @twojudgeygirlsTikTok: @twojudgeygirls // @marytwojudgeygirls // @courtneytjgYouTube: @twojudgeygirlsFacebook: www.facebook.com/twojudgeygirlsMerch: www.etsy.com/shop/twojudgeygirlsPatreon: www.patreon.com/twojudgeygirls LTK: @marytwojudgeygirls // @courtneytjg Hosted on Acast. See acast.com/privacy for more information.

Mason spotted the Real Housewives of Salt Lake City here in SF. Is Timothee Chalamet cursed? Zendaya addresses the AI wedding rumors. Did everyone eat their cabbage yesterday? What is chicken fried steak? Mason has the answer. Oakland's own Alysa Liu is an inspiration AND a lucky charm.

Hour 1: Mason spotted the Real Housewives of Salt Lake City here in SF. Is Timothee Chalamet cursed? Zendaya addresses the AI wedding rumors. Did everyone eat their cabbage yesterday? What is chicken fried steak? Mason has the answer. Oakland's own Alysa Liu is an inspiration AND a lucky charm. Hour 2: Mason's got an update on Taylor Frankie Paul's allegations. PSA: Bad Bunny is insanely famous. Pizza Hut is looking for free crust content. Meghan Markle and Prince Harry add another failure to their resume. A deaf woman was kicked off of a Frontier flight - Should we take sides? Is drinking coffee and doing nothing a hobby? A woman who wrote a children's book about grief was found guilty of murdering her husband. (56:51) Hour 3: Rumors are swirling that Leonardo DiCaprio might be more serious about this girlfriend than the last 50. Taylor Frankie Paul addresses the child abuse allegations ahead of her Bachelorette premier. There's an update on the shooting at Rihanna's house. Anne Hathaway looks amazing, but we don't think this “hack” is how. Bruno Mars has beef with Taylor Swift? Bad idea. What circumstances make a proposal at Chili's romantic? Vinnie is telling us! (1:35:46) Hour 4: Zac Brown is on Survivor this week! When the heck did Taylor Swift date an F1 driver? Paradise was renewed for Season 3. Vinyl record sales continue to rise. Should Matty get rid of his physical media collection? Kid Rock isn't happy about Conan's joke at the Oscars, and it sparks a conversation about separating the art from the artist. Florida fails to pass a bill banning first cousin marriages… lovely. Vinnie tells us the story of his proposal, and Matty tries out a brand new game! (1:51:10)

Big Dipper and Meatball are back with another chaotic catch-up as they ask the most important question facing America today: will Ben Affleck and JLo get back together? On a drive from LA to SF, Dipper encounters a disturbing amount of roadside cow activity and attends a wild muscle party. Meanwhile, Meatball claims she can literally smell steroids sweating out of gym boys and she narrates a porno live on air. They also debate the deeper cultural meaning of pup play and take listener voicemails about kink discoveries and Oprah leaves a voicemail! As always, it's messy, hilarious, and just a little bit unhinged.Call us with your sex stories at 213-536-9180!Or e-mail us at ⁠sloppysecondspod@gmail.com⁠⁠FOLLOW SLOPPY SECONDS⁠⁠FOLLOW BIG DIPPER⁠⁠FOLLOW MEATBALL⁠SLOPPY SECONDS IS A FOREVER DOG AND MOGULS OF MEDIA (M.O.M.) PODCASTSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Jimmy drove down to have dinner at Nan Ban Kan, and record a fresh episode of the podcast. Jannik Sinner wins his first Indian Wells crown, which was the only Masters 1000 hard court title missing from his resume. Having only played 2 tournaments so far this year it was nice to see the young Italian play some of the best tennis of the year. Aryna Sabalenka also broke through to win her first IW title after being runner up in 2025 to Andreeva. She played an instant classic vs AO champ Elena Rybakina in the final winning 7-6 in the third. Daniil Medvedev is back playing some of the best tennis of his career and is back in the top ten of the ATP tour. Med played a great match beating Carlos Alcaraz in the SF and almost pushing Sinner to 3 in the final. With 2 titles on the year already it seems like there is more positive things ahead for the Russian. Elena Rybakina has been one of the best players in the world the past 9 months. The AO champ played some amazing tennis to get to the final and was up a set and a break on Sabby before things turned around. In what has to be one of the best matches of the year the two biggest hitters on tour blasted away for 3 high powered sets. Sadly someone had to lose, but something tells us these two will play more important matches down the road. All that plus more on a new episode of the Advantage Connors podcast. Follow us on - Twitter - @AdvConnors @JimmyConnors @Brett_Connors Instagram - @AdvConnors @Bretterz @GolddoodIsabella Facebook - Jimmy Connors official Facebook page Leave your questions/topics/or links to stories you want us to talk about next week on Jimmy's official Facebook page. Learn more about your ad choices. Visit megaphone.fm/adchoices

Friends of the Rosary,Today, March 17, is the Memorial of St. Patrick, a bishop chosen by God 1.500 years ago to preach His glory by bringing Christianity to Ireland, a little country which would be converted from their pagan gods to the one true God.Today, Irishmen venerate him as their father in the Faith.Sf. Patrick was born about 385 in the British Isles. In Roman Britain, when he was 16, while he was tending his sheep, Irish raiders captured him and sold him into slavery. Six years later, he escaped to Europe, became a monk, and was ordained; he then returned to Ireland to preach the Gospel.During the thirty years of missionary work, he covered the Island with churches and monasteries and founded the metropolitan see of Armagh.Many legends are associated with St. Patrick: how he drove the snakes out of Ireland and how he used the shamrock to teach the mystery of the Trinity.Ireland, although a small country, played a large role in spreading the true faith to the world. During the early Dark Ages, and while Europe remained in darkness, the Irish monasteries preserved Western writingsIn his autobiography, Confessions, written in true humility, St. Patrick said,“I am greatly God's debtor, because he granted me so much grace, that through me many people would be reborn in God.”Ave Maria!Come, Holy Spirit, come!To Jesus through Mary!Here I am, Lord; I come to do your will.Please give us the grace to respond with joy!+ Mikel Amigot w/ María Blanca | RosaryNetwork.com, New YorkEnhance your faith with the new Holy Rosary University app:Apple iOS | New! Android Google Play• ⁠March 17, 2026, Today's Rosary on YouTube | Daily broadcast at 7:30 pm ET

Rae Alexandra has 35 stories to share with you, plus her own. In this Women's History Month episode, meet and get to know Rae. She recently published a book with City Lights Publishing called Unsung Heroines: 35 Women Who Changed the Bay Area. It's of course available at City Lights, but you can also find it at your local independent bookstore. I read the book and could not put it down. Only toward the end of the 35 essays did I start to recognize the women Rae features. I love history and I love learning and I have mixed feelings about the fact that there are so many rad women whose stories are untold. Thank you, Rae Alexandra, for shining on a light on these incredible women. These days, she's a staff writer at KQED. But Rae's story starts in Wales in the UK. She grew up in Cardiff, the capital of the country. (I learn in the conversation that Wales is a country. I also learn that "United Kingdom" and "Great Britain" are the same thing. Now, British vs. English we don't touch, for obvious reasons. But I digress …) Ed. note: I'll describe my conversation with Rae as two Gen Ex journalist types with ADHD (is that redundant?) doing their best to be linear. To me, the meanderings of our talk are totally normal. Rae says that Wales is delightful and has all the best castles, but that's because of the number times the country has been invaded and conquered. Close to where her mom lives today is a castle that boasts the world's largest crossbow. When I ask when Rae was born (1978), we discover that she's a horse as in Year of the Horse (aka 2026). Cool. Rae continued to call Cardiff home up through her college years. She didn't go to another school outside of Wales that had accepted her because she was attached to a group of skateboarders in her hometown. After she graduated, though, she moved to London. Music has been central for Rae as far back as she remembers (same). She shares stories of being maybe 5 and listening to the Top 40 with her cassette recorder ready to nab her favorite songs (same). According to Rae, the English look down on the Welsh, and have for some time, based on classist generalizations. Wales is where the UK mines most of its coal. London-types consider their neighbors to the southwest feral, and in some regards, the Welsh are, she says. In the Eighties, she remembers stories about IRA bombings appearing on the news nightly. Also, in Wales, miners went on strike and everyone knew about it. Rae says that Wales in the Eighties was essentially like listening to The Clash. We go on a sidebar about siblings, birth order, and what it means to be the youngest, which Rae and I both are. Growing up, she was close with both her older sisters. Today, one lives in Australia and the other lives in the London suburbs. Around age 10, Rae discovered metal. By 12, she decided that she would become a music journalist. In her teen years, she "snuck" her writing into local and college newspapers. The music journalism she consumed in those days included publications like Smash Hits, Kerrang!, NME, and Melody Maker. In fact, her first job out of college was at Kerrang! We go on a sidebar on the whole idea of living somewhere vs. visiting, and how they're so totally different on every level. I use Chicago, where I lived for a full six months in the Nineties, as my example. Rae offers up a stay in Brooklyn as hers. That job at Kerrang! is what brought Rae to London, another place she found impossible to live. I ask her to expound on what it was about the place, and she indulges me. She says that you have to be obscenely wealthy to live in Central London, so most folks are forced to the outskirts. But the jobs are in the middle of town, and so you end up spending around two or three hours a day commuting underground. It was/is also gray—the weather, the architecture—and the people in London were, as Rae describes it, hostile. When she goes into detail about the ways in which they were hostile, we agree that only you get to shit on your own hometown. People who aren't from there aren't allowed. It's a rule. Look it up. After a year working for the magazine in London, Rae met a guy from San Francisco. She'd been to The City and even spent significant time here working for Maximum Rock 'n' Roll. (At this point in the recording, I mistakenly call the BBQ place near Hayes and Divisadero until sometime in the early 2000s "Brothers." It was in fact called Brother in-law's. My apologies.) She moved in with that guy she met, lived with him for six months in London, and then it was time for him to come home to SF. He asked her if she wanted to join him and she accepted. She had already transitioned to freelance writing for the magazine, because office life didn't suit her, so work wasn't so much a problem. But upon arrival, she soon discovered how difficult it was to do anything without a Social Security number. That added an extra layer to moving here. But it wasn't the place itself or its people that made things hard. It was the system, so to speak. Also, while she was getting settled and learning how to survive in the US without an SSN, she started to see that the guy was, let's just say, not for her. She felt he'd been playing the long game when they lived together in London, but once back on his home turf, some of his sociopath tendencies emerged. It was 2002 and she lived in Bernal Heights on Cortland. She spent most of her time in the Mission, just down the hill. After a short time, the guy convinced her that they needed to get married, so they moved back to London. The marriage lasted three months, and Rae returned to her new home—San Francisco. When she came back, she experienced a stretch of housing instability. You could call it "couch surfing," but either way, it was dicey. Six months or so later, things settled. It was easier to live cheaply in the early 2000s, also. A $5 burrito could be a whole day's worth of food. And Rae had befriended enough bartenders that she rarely paid full-price for booze. She describes "The Blackout Triangle" of Killowatt, Delirium, and Dr. Bombay's. She also regularly visited Beauty Bar until that place went downhill. Check back this Thursday for Part 2 with Rae Alexandra. We recorded this episode at Vesuvio in North Beach in February 2026. Photography by Jeff Hunt

State of the Bay checks out the contest to find SF's dumbest law, sits down with State Senator Scott Wiener to discuss his Congressional bid and explores an art exhibit imagining the future looking back at us.

在忙碌中迷失了節奏？讓心靈深呼吸。《城市使命》每日 7–10 分鐘短篇靈修，為你的日常靈性充電！我們透過經文與生命見證，把你的通勤與休息時間，轉化為與神對話的神聖時刻。不長篇大論，只給你最純粹的屬靈養分。現在就收聽，在城市的喧囂中找回你的屬靈方向！Overwhelmed by the hustle? Take a deep breath. We offers 7–10 minute short devotionals to recharge your spirit on the go. Through quick biblical insights and powerful testimonies, we turn your commute or coffee break into a divine dialogue. Simple, deep, and exactly what your soul needs today. Tune in now, quiet the noise, and realign your spiritual compass!

Scott Connor (@CharlesChillFFB) goes through a 2-round, community 2026, superflex Rookie Mock Draft using a 12-team SF format with 1.75 TE Premium and .15 PPC. He discusses the trade value of pick slot and takes LIVE trade offers from the DD Fantasy Football community. If the deal is accepted, the community member makes the pick. This mock is POST-NFL Free Agency as we discuss the new pick tiers and some new names! Thank you for checking out the Podcast, be sure to follow and comment if you have any questions, we are always happy to answer any. For Access to our Premium Tools (Trinity, WAR & More) & Discord Community https://ddfantasyfootball.com/subscriptions/ Join the Discord for FREE: https://discord.gg/TAeWz3B5VW Subscribe to the Youtube Channel DDFFB https://www.youtube.com/@DDFFB Sub to the Wake up YT Channel: https://www.youtube.com/channel/UCaIJqSepjl-eZ2YEaaLciFA Subscribe to Ray's Channel: https://www.youtube.com/@RayGQue Check out All of Ray's Articles at Yahoo!: https://sports.yahoo.com/author/ray-garvin/ Follow Ray on Bleacher Report: https://br.app.link/7ExIDsWfHVb Follow us on Twitter: https://x.com/destinationdevy Become a Member on Youtube for access to the Dynasty Deal Show Live, Destination Chill and other member benefits, like priority reply to comments and unique badges and emojis: https://www.youtube.com/channel/UCV84gHvtBMXxzN9ZPI9XHfg/join Learn more about your ad choices. Visit megaphone.fm/adchoices

With all of the major players on hand, the Department of Transporation held a National AV Safety Forum in D.C.. And Princeton's Alain Kornhauser says the focus on empowering AV innovators is opening doors. Join Alain and co-host Fred Fishkin for that plus an AARP podcast on mobility featuring ITN America's Katherine Freund, reports on impact of AVs on vehicle miles traveled and the hidden costs of Waymo robotaxis on SF streets. And concerns about what the U.S.-Israeli reported disruptions of traffic signals and such in Iran may mean. Tune in and subscribe!

This Week on the Toy Power Podcast; we get the ball rolling with another Classic Round of The Team. This episode focusing on two unique 80's Toy Properties that are much larger than majority of your other Action-Figures in your ToyBox. Centurions & Bravestarr; join forces to build the Ultimate Good-Guys Crew! Consisting of the stand-out Characters that fit the criteria of: Leader, Muscle, Specialist & Wheelman. Plus an Iconic Vehicle they can get around in! (Spoiler alert, there aren't many characters to pull from this round, so be ready for some clear winners & some heated debate too! Then in our second segment for the episode; we lean on another staple classic topic: Show & Tell. With a VERY mixed bag of Toys to chat towards, its an overall fun round table discussion around what each of us have brought in; as well as why each item is special in it's own right. Enjoy! Support the show: http://patreon.com/toypowerpodcastSee omnystudio.com/listener for privacy information.

Comprehensive coverage of the day's news with a focus on war and peace; social, environmental and economic justice. Defense Secretary Pete Hegseth (Image: Gage Skidmore) Defense Secretary Hegseth touts military successes amid Iran war escalation; CAIR report finds patterns of increasing claims of discrimination against Islamic people and organizations including CAIR itself; Lawmakers, consumer advocates speak out on home insurance difficulties amid climate change; SF tenants on rent strike over damages from fire that happened a year ago; San Jose tightens controls over license plate cameras amid surveillance concerns; Workers picket all 10 UC campuses, claim unfair labor practices The post Defense Secretary Hegseth touts military success as Iran war escalates; New report finds increasing discrimination against Islamic people, organizations – March 13, 2026 appeared first on KPFA.

Turbopuffer came out of a reading app.In 2022, Simon was helping his friends at Readwise scale their infra for a highly requested feature: article recommendations and semantic search. Readwise was paying ~$5k/month for their relational database and vector search would cost ~$20k/month making the feature too expensive to ship. In 2023 after mulling over the problem from Readwise, Simon decided he wanted to “build a search engine” which became Turbopuffer.We discuss:• Simon's path: Denmark → Shopify infra for nearly a decade → “angel engineering” across startups like Readwise, Replicate, and Causal → turbopuffer almost accidentally becoming a company • The Readwise origin story: building an early recommendation engine right after the ChatGPT moment, seeing it work, then realizing it would cost ~$30k/month for a company spending ~$5k/month total on infra and getting obsessed with fixing that cost structure • Why turbopuffer is “a search engine for unstructured data”: Simon's belief that models can learn to reason, but can't compress the world's knowledge into a few terabytes of weights, so they need to connect to systems that hold truth in full fidelity • The three ingredients for building a great database company: a new workload, a new storage architecture, and the ability to eventually support every query plan customers will want on their data • The architecture bet behind turbopuffer: going all in on object storage and NVMe, avoiding a traditional consensus layer, and building around the cloud primitives that only became possible in the last few years • Why Simon hated operating Elasticsearch at Shopify: years of painful on-call experience shaped his obsession with simplicity, performance, and eliminating state spread across multiple systems • The Cursor story: launching turbopuffer as a scrappy side project, getting an email from Cursor the next day, flying out after a 4am call, and helping cut Cursor's costs by 95% while fixing their per-user economics • The Notion story: buying dark fiber, tuning TCP windows, and eating cross-cloud costs because Simon refused to compromise on architecture just to close a deal faster • Why AI changes the build-vs-buy equation: it's less about whether a company can build search infra internally, and more about whether they have time especially if an external team can feel like an extension of their own • Why RAG isn't dead: coding companies still rely heavily on search, and Simon sees hybrid retrieval semantic, text, regex, SQL-style patterns becoming more important, not less • How agentic workloads are changing search: the old pattern was one retrieval call up front; the new pattern is one agent firing many parallel queries at once, turning search into a highly concurrent tool call • Why turbopuffer is reducing query pricing: agentic systems are dramatically increasing query volume, and Simon expects retrieval infra to adapt to huge bursts of concurrent search rather than a small number of carefully chosen calls • The philosophy of “playing with open cards”: Simon's habit of being radically honest with investors, including telling Lachy Groom he'd return the money if turbopuffer didn't hit PMF by year-end • The “P99 engineer”: Simon's framework for building a talent-dense company, rejecting by default unless someone on the team feels strongly enough to fight for the candidate —Simon Hørup Eskildsen• LinkedIn: https://www.linkedin.com/in/sirupsen• X: https://x.com/Sirupsen• https://sirupsen.com/aboutturbopuffer• https://turbopuffer.com/Full Video PodTimestamps00:00:00 The PMF promise to Lachy Groom00:00:25 Intro and Simon's background00:02:19 What turbopuffer actually is00:06:26 Shopify, Elasticsearch, and the pain behind the company00:10:07 The Readwise experiment that sparked turbopuffer00:12:00 The insight Simon couldn't stop thinking about00:17:00 S3 consistency, NVMe, and the architecture bet00:20:12 The Notion story: latency, dark fiber, and conviction00:25:03 Build vs. buy in the age of AI00:26:00 The Cursor story: early launch to breakout customer00:29:00 Why code search still matters00:32:00 Search in the age of agents00:34:22 Pricing turbopuffer in the AI era00:38:17 Why Simon chose Lachy Groom00:41:28 Becoming a founder on purpose00:44:00 The “P99 engineer” philosophy00:49:30 Bending software to your will00:51:13 The future of turbopuffer00:57:05 Simon's tea obsession00:59:03 Tea kits, X Live, and P99 LiveTranscriptSimon Hørup Eskildsen: I don't think I've said this publicly before, but I just called Lockey and was like, local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you. But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working.So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people. We're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards. Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before.Alessio: Hey everyone, welcome to the Leading Space podcast. This is Celesio Pando, Colonel Laz, and I'm joined by Swix, editor of Leading Space.swyx: Hello. Hello, uh, we're still, uh, recording in the Ker studio for the first time. Very excited. And today we are joined by Simon Eski. Of Turbo Farer welcome.Simon Hørup Eskildsen: Thank you so much for having me.swyx: Turbo Farer has like really gone on a huge tear, and I, I do have to mention that like you're one of, you're not my newest member of the Danish AHU Mafia, where like there's a lot of legendary programmers that have come out of it, like, uh, beyond Trotro, Rasmus, lado Berg and the V eight team and, and Google Maps team.Uh, you're mostly a Canadian now, but isn't that interesting? There's so many, so much like strong Danish presence.Simon Hørup Eskildsen: Yeah, I was writing a post, um, not that long ago about sort of the influences. So I grew up in Denmark, right? I left, I left when, when I was 18 to go to Canada to, to work at Shopify. Um, and so I, like, I've, I would still say that I feel more Danish than, than Canadian.This is also the weird accent. I can't say th because it, this is like, I don't, you know, my wife is also Canadian, um, and I think. I think like one of the things in, in Denmark is just like, there's just such a ruthless pragmatism and there's also a big focus on just aesthetics. Like, they're like very, people really care about like where, what things look like.Um, and like Canada has a lot of attributes, US has, has a lot of attributes, but I think there's been lots of the great things to carry. I don't know what's in the water in Ahu though. Um, and I don't know that I could be considered part of the Mafi mafia quite yet, uh, compared to the phenomenal individuals we just mentioned.Barra OV is also, uh, Danish Canadian. Okay. Yeah. I don't know where he lives now, but, and he's the PHP.swyx: Yeah. And obviously Toby German, but moved to Canada as well. Yes. Like this is like import that, uh, that, that is an interesting, um, talent move.Alessio: I think. I would love to get from you. Definition of Turbo puffer, because I think you could be a Vector db, which is maybe a bad word now in some circles, you could be a search engine.It's like, let, let's just start there and then we'll maybe run through the history of how you got to this point.Simon Hørup Eskildsen: For sure. Yeah. So Turbo Puffer is at this point in time, a search engine, right? We do full text search and we do vector search, and that's really what we're specialized in. If you're trying to do much more than that, like then this might not be the right place yet, but Turbo Buffer is all about search.The other way that I think about it is that we can take all of the world's knowledge, all of the exabytes and exabytes of data that there is, and we can use those tokens to train a model, but we can't compress all of that into a few terabytes of weights, right? Compress into a few terabytes of weights, how to reason with the world, how to make sense of the knowledge.But we have to somehow connect it to something externally that actually holds that like in full fidelity and truth. Um, and that's the thing that we intend to become. Right? That's like a very holier than now kind of phrasing, right? But being the search engine for unstructured, unstructured data is the focus of turbo puffer at this point in time.Alessio: And let's break down. So people might say, well, didn't Elasticsearch already do this? And then some other people might say, is this search on my data, is this like closer to rag than to like a xr, like a public search thing? Like how, how do you segment like the different types of search?Simon Hørup Eskildsen: The way that I generally think about this is like, there's a lot of database companies and I think if you wanna build a really big database company, sort of, you need a couple of ingredients to be in the air.We don't, which only happens roughly every 15 years. You need a new workload. You basically need the ambition that every single company on earth is gonna have data in your database. Multiple times you look at a company like Oracle, right? You will, like, I don't think you can find a company on earth with a digital presence that it not, doesn't somehow have some data in an Oracle database.Right? And I think at this point, that's also true for Snowflake and Databricks, right? 15 years later it's, or even more than that, there's not a company on earth that doesn't, in. Or directly is consuming Snowflake or, or Databricks or any of the big analytics databases. Um, and I think we're in that kind of moment now, right?I don't think you're gonna find a company over the next few years that doesn't directly or indirectly, um, have all their data available for, for search and connect it to ai. So you need that new workload, like you need something to be happening where there's a new workload that causes that to happen, and that new workload is connecting very large amounts of data to ai.The second thing you need. The second condition to build a big database company is that you need some new underlying change in the storage architecture that is not possible from the databases that have come before you. If you look at Snowflake and Databricks, right, commoditized, like massive fleet of HDDs, like that was not possible in it.It just wasn't in the air in the nineties, right? So you just didn't, we just didn't build these systems. S3 and and and so on was not around. And I think the architecture that is now possible that wasn't possible 15 years ago is to go all in on NVME SSDs. It requires a particular type of architecture for the database that.It's difficult to retrofit onto the databases that are already there, including the ones you just mentioned. The second thing is to go all in on OIC storage, more so than we could have done 15 years ago. Like we don't have a consensus layer, we don't really have anything. In fact, you could turn off all the servers that Turbo Buffer has, and we would not lose any data because we have all completely all in on OIC storage.And this means that our architecture is just so simple. So that's the second condition, right? First being a new workload. That means that every company on earth, either indirectly or directly, is using your database. Second being, there's some new storage architecture. That means that the, the companies that have come before you can do what you're doing.I think the third thing you need to do to build a big database company is that over time you have to implement more or less every Cory plan on the data. What that means is that you. You can't just get stuck in, like, this is the one thing that a database does. It has to be ever evolving because when someone has data in the database, they over time expect to be able to ask it more or less every question.So you have to do that to get the storage architecture to the limit of what, what it's capable of. Those are the three conditions.swyx: I just wanted to get a little bit of like the motivation, right? Like, so you left Shopify, you're like principal, engineer, infra guy. Um, you also head of kernel labs, uh, inside of Shopify, right?And then you consulted for read wise and that it kind of gave you that, that idea. I just wanted you to tell that story. Um, maybe I, you've told it before, but, uh, just introduce the, the. People to like the, the new workload, the sort of aha moment for turbo PufferSimon Hørup Eskildsen: For sure. So yeah, I spent almost a decade at Shopify.I was on the infrastructure team, um, from the fairly, fairly early days around 2013. Um, at the time it felt like it was growing so quickly and everything, all the metrics were, you know, doubling year on year compared to the, what companies are contending with today. It's very cute in growth. I feel like lot some companies are seeing that month over month.Um, of course. Shopify compound has been compounding for a very long time now, but I spent a decade doing that and the majority of that was just make sure the site is up today and make sure it's up a year from now. And a lot of that was really just the, um, you know, uh, the Kardashians would drive very, very large amounts of, of data to, to uh, to Shopify as they were rotating through all the merch and building out their businesses.And we just needed to make sure we could handle that. Right. And sometimes these were events, a million requests per second. And so, you know, we, we had our own data centers back in the day and we were moving to the cloud and there was so much sharding work and all of that that we were doing. So I spent a decade just scaling databases ‘cause that's fundamentally what's the most difficult thing to scale about these sites.The database that was the most difficult for me to scale during that time, and that was the most aggravating to be on call for, was elastic search. It was very, very difficult to deal with. And I saw a lot of projects that were just being held back in their ambition by using it.swyx: And I mean, self-hosted.Self-hosted. ‘causeSimon Hørup Eskildsen: it's, yeah, and it commercial, this is like 2015, right? So it's like a very particular vintage. Right. It's probably better at a lot of these things now. Um, it was difficult to contend with and I'm just like, I just think about it. It's an inverted index. It should be good at these kinds of queries and do all of this.And it was, we, we often couldn't get it to do exactly what we needed to do or basically get lucine to do, like expose lucine raw to, to, to what we needed to do. Um, so that was like. Just something that we did on the side and just panic scaled when we needed to, but not a particular focus of mine. So I left, and when I left, I, um, wasn't sure exactly what I wanted to do.I mean, it spent like a decade inside of the same company. I'd like grown up there. I started working there when I was 18.swyx: You only do Rails?Simon Hørup Eskildsen: Yeah. I mean, yeah. Rails. And he's a Rails guy. Uh, love Rails. So good. Um,Alessio: we all wish we could still work in Rails.swyx: I know know. I know, but some, I tried learning Ruby.It's just too much, like too many options to do the same thing. It's, that's my, I I know there's a, there's a way to do it.Simon Hørup Eskildsen: I love it. I don't know that I would use it now, like given cloud code and, and, and cursor and everything, but, um, um, but still it, like if I'm just sitting down and writing a teal code, that's how I think.But anyway, I left and I wasn't, I talked to a couple companies and I was like, I don't. I need to see a little bit more of the world here to know what I'm gonna like focus on next. Um, and so what I decided is like I was gonna, I called it like angel engineering, where I just hopped around in my friend's companies in three months increments and just helped them out with something.Right. And, and just vested a bit of equity and solved some interesting infrastructure problem. So I worked with a bunch of companies at the time, um, read Wise was one of them. Replicate was one of them. Um, causal, I dunno if you've tried this, it's like a, it's a spreadsheet engine Yeah. Where you can do distribution.They sold recently. Yeah. Um, we've been, we used that in fp and a at, um, at Turbo Puffer. Um, so a bunch of companies like this and it was super fun. And so we're the Chachi bt moment happened, I was with. With read Wise for a stint, we were preparing for the reader launch, right? Which is where you, you cue articles and read them later.And I was just getting their Postgres up to snuff, like, which basically boils down to tuning, auto vacuum. So I was doing that and then this happened and we were like, oh, maybe we should build a little recommendation engine and some features to try to hook in the lms. They were not that good yet, but it was clear there was something there.And so I built a small recommendation engine just, okay, let's take the articles that you've recently read, right? Like embed all the articles and then do recommendations. It was good enough that when I ran it on one of the co-founders of Rey's, like I found out that I got articles about, about having a child.I'm like, oh my God, I didn't, I, I didn't know that, that they were having a child. I wasn't sure what to do with that information, but the recommendation engine was good enough that it was suggesting articles, um, about that. And so there was, there was recommendations and uh, it actually worked really well.But this was a company that was spending maybe five grand a month in total on all their infrastructure and. When I did the napkin math on running the embeddings of all the articles, putting them into a vector index, putting it in prod, it's gonna be like 30 grand a month. That just wasn't tenable. Right?Like Read Wise is a proudly bootstrapped company and it's paying 30 grand for infrastructure for one feature versus five. It just wasn't tenable. So sort of in the bucket of this is useful, it's pretty good, but let us, let's return to it when the costs come down.swyx: Did you say it grows by feature? So for five to 30 is by the number of, like, what's the, what's the Scaling factor scale?It scales by the number of articles that you embed.Simon Hørup Eskildsen: It does, but what I meant by that is like five grand for like all of the other, like the Heroku, dinos, Postgres, like all the other, and this then storage is 30. Yeah. And then like 30 grand for one feature. Right. Which is like, what other articles are related to this one.Um, so it was just too much right to, to power everything. Their budget would've been maybe a few thousand dollars, which still would've been a lot. And so we put it in a bucket of, okay, we're gonna do that later. We'll wait, we will wait for the cost to come down. And that haunted me. I couldn't stop thinking about it.I was like, okay, there's clearly some latent demand here. If the cost had been a 10th, we would've shipped it and. This was really the only data point that I had. Right. I didn't, I, I didn't, I didn't go out and talk to anyone else. It was just so I started reading Right. I couldn't, I couldn't help myself.Like I didn't know what like a vector index is. I, I generally barely do about how to generate the vectors. There was a lot of hype about, this is a early 2023. There was a lot of hype about vector databases. There were raising a lot of money and it's like, I really didn't know anything about it. It's like, you know, trying these little models, fine tuning them.Like I was just trying to get sort of a lay of the land. So I just sat down. I have this. A GitHub repository called Napkin Math. And on napkin math, there's just, um, rows of like, oh, this is how much bandwidth. Like this is how many, you know, you can do 25 gigabytes per second on average to dram. You can do, you know, five gigabytes per second of rights to an SSD, blah blah.All of these numbers, right? And S3, how many you could do per, how much bandwidth can you drive per connection? I was just sitting down, I was like, why hasn't anyone build a database where you just put everything on O storage and then you puff it into NVME when you use the data and you puff it into dram if you're, if you're querying it alive, it's just like, this seems fairly obvious and you, the only real downside to that is that if you go all in on o storage, every right will take a couple hundred milliseconds of latency, but from there it's really all upside, right?You do the first go, it takes half a second. And it sort of occurred to me as like, well. The architecture is really good for that. It's really good for AB storage, it's really good for nvm ESSD. It's, well, you just couldn't have done that 10 years ago. Back to what we were talking about before. You really have to build a database where you have as few round trips as possible, right?This is how CPUs work today. It's how NVM E SSDs work. It's how as, um, as three works that you want to have a very large amount of outstanding requests, right? Like basically go to S3, do like that thousand requests to ask for data in one round trip. Wait for that. Get that, like, make a new decision. Do it again, and try to do that maybe a maximum of three times.But no databases were designed that way within NVME as is ds. You can drive like within, you know, within a very low multiple of DRAM bandwidth if you use it that way. And same with S3, right? You can fully max out the network card, which generally is not maxed out. You get very, like, very, very good bandwidth.And, but no one had built a database like that. So I was like, okay, well can't you just, you know, take all the vectors right? And plot them in the proverbial coordinate system. Get the clusters, put a file on S3 called clusters, do json, and then put another file for every cluster, you know, cluster one, do js O cluster two, do js ON you know that like it's two round trips, right?So you get the clusters, you find the closest clusters, and then you download the cluster files like the, the closest end. And you could do this in two round trips.swyx: You were nearest neighbors locally.Simon Hørup Eskildsen: Yes. Yes. And then, and you would build this, this file, right? It's just like ultra simplistic, but it's not a far shot from what the first version of Turbo Buffer was.Why hasn't anyone done thatAlessio: in that moment? From a workload perspective, you're thinking this is gonna be like a read heavy thing because they're doing recommend. Like is the fact that like writes are so expensive now? Oh, with ai you're actually not writing that much.Simon Hørup Eskildsen: At that point I hadn't really thought too much about, well no actually it was always clear to me that there was gonna be a lot of rights because at Shopify, the search clusters were doing, you know, I don't know, tens or hundreds of crew QPS, right?‘cause you just have to have a human sit and type in. But we did, you know, I don't know how many updates there were per second. I'm sure it was in the millions, right into the cluster. So I always knew there was like a 10 to 100 ratio on the read write. In the read wise use case. It's, um, even, even in the read wise use case, there'd probably be a lot fewer reads than writes, right?There's just a lot of churn on the amount of stuff that was going through versus the amount of queries. Um, I wasn't thinking too much about that. I was mostly just thinking about what's the fundamentally cheapest way to build a database in the cloud today using the primitives that you have available.And this is it, right? You just, now you have one machine and you know, let's say you have a terabyte of data in S3, you paid the $200 a month for that, and then maybe five to 10% of that data and needs to be an NV ME SSDs and less than that in dram. Well. You're paying very, very little to inflate the data.swyx: By the way, when you say no one else has done that, uh, would you consider Neon, uh, to be on a similar path in terms of being sort of S3 first and, uh, separating the compute and storage?Simon Hørup Eskildsen: Yeah, I think what I meant with that is, uh, just build a completely new database. I don't know if we were the first, like it was very much, it was, I mean, I, I hadn't, I just looked at the napkin math and was like, this seems really obvious.So I'm sure like a hundred people came up with it at the same time. Like the light bulb and every invention ever. Right. It was just in the air. I think Neon Neon was, was first to it. And they're trying, they're retrofitted onto Postgres, right? And then they built this whole architecture where you have, you have it in memory and then you sort of.You know, m map back to S3. And I think that was very novel at the time to do it for, for all LTP, but I hadn't seen a database that was truly all in, right. Not retrofitting it. The database felt built purely for this no consensus layer. Even using compare and swap on optic storage to do consensus. I hadn't seen anyone go that all in.And I, I mean, there, there, I'm sure there was someone that did that before us. I don't know. I was just looking at the napkin mathswyx: and, and when you say consensus layer, uh, are you strongly relying on S3 Strong consistency? You are. Okay.SoSimon Hørup Eskildsen: that is your consensus layer. It, it is the consistency layer. And I think also, like, this is something that most people don't realize, but S3 only became consistent in December of 2020.swyx: I remember this coming out during COVID and like people were like, oh, like, it was like, uh, it was just like a free upgrade.Simon Hørup Eskildsen: Yeah.swyx: They were just, they just announced it. We saw consistency guys and like, okay, cool.Simon Hørup Eskildsen: And I'm sure that they just, they probably had it in prod for a while and they're just like, it's done right.And people were like, okay, cool. But. That's a big moment, right? Like nv, ME SSDs, were also not in the cloud until around 2017, right? So you just sort of had like 2017 nv, ME SSDs, and people were like, okay, cool. There's like one skew that does this, whatever, right? Takes a few years. And then the second thing is like S3 becomes consistent in 2020.So now it means you don't have to have this like big foundation DB or like zookeeper or whatever sitting there contending with the keys, which is how. You know, that's what Snowflake and others have do so muchswyx: for goneSimon Hørup Eskildsen: Exactly. Just gone. Right? And so just push to the, you know, whatever, how many hundreds of people they have working on S3 solved and then compare and swap was not in S3 at this point in time,swyx: by the way.Uh, I don't know what that is, so maybe you wanna explain. Yes. Yeah.Simon Hørup Eskildsen: Yes. So, um, what Compare and swap is, is basically, you can imagine that if you have a database, it might be really nice to have a file called metadata json. And metadata JSON could say things like, Hey, these keys are here and this file means that, and there's lots of metadata that you have to operate in the database, right?But that's the simplest way to do it. So now you have might, you might have a lot of servers that wanna change the metadata. They might have written a file and want the metadata to contain that file. But you have a hundred nodes that are trying to contend with this metadata that JSON well, what compare and Swap allows you to do is basically just you download the file, you make the modifications, and then you write it only if it hasn't changed.While you did the modification and if not you retry. Right? Should just have this retry loops. Now you can imagine if you have a hundred nodes doing that, it's gonna be really slow, but it will converge over time. That primitive was not available in S3. It wasn't available in S3 until late 2024, but it was available in GCP.The real story of this is certainly not that I sat down and like bake brained it. I was like, okay, we're gonna start on GCS S3 is gonna get it later. Like it was really not that we started, we got really lucky, like we started on GCP and we started on GCP because tur um, Shopify ran on GCP. And so that was the platform I was most available with.Right. Um, and I knew the Canadian team there ‘cause I'd worked with them at Shopify and so it was natural for us to start there. And so when we started building the database, we're like, oh yeah, we have to build a, we really thought we had to build a consensus layer, like have a zookeeper or something to do this.But then we discovered the compare and swap. It's like, oh, we can kick the can. Like we'll just do metadata r json and just, it's fine. It's probably fine. Um, and we just kept kicking the can until we had very, very strong conviction in the idea. Um, and then we kind of just hinged the company on the fact that S3 probably was gonna get this, it started getting really painful in like mid 2024.‘cause we were closing deals with, um, um, notion actually that was running in AWS and we're like, trust us. You, you really want us to run this in GCP? And they're like, no, I don't know about that. Like, we're running everything in AWS and the latency across the cloud were so big and we had so much conviction that we bought like, you know, dark fiber between the AWS regions in, in Oregon, like in the InterExchange and GCP is like, we've never seen a startup like do like, what's going on here?And we're just like, no, we don't wanna do this. We were tuning like TCP windows, like everything to get the latency down ‘cause we had so high conviction in not doing like a, a metadata layer on S3. So those were the three conditions, right? Compare and swap. To do metadata, which wasn't in S3 until late 2024 S3 being consistent, which didn't happen until December, 2020.Uh, 2020. And then NVMe ssd, which didn't end in the cloud until 2017.swyx: I mean, in some ways, like a very big like cloud success story that like you were able to like, uh, put this all together, but also doing things like doing, uh, bind our favor. That that actually is something I've never heard.Simon Hørup Eskildsen: I mean, it's very common when you're a big company, right?You're like connecting your own like data center or whatever. But it's like, it was uniquely just a pain with notion because the, um, the org, like most of the, like if you're buying in Ashburn, Virginia, right? Like US East, the Google, like the GCP and, and AWS data centers are like within a millisecond on, on each other, on the public exchanges.But in Oregon uniquely, the GCP data center sits like a couple hundred kilometers, like east of Portland and the AWS region sits in Portland, but the network exchange they go through is through Seattle. So it's like a full, like 14 milliseconds or something like that. And so anyway, yeah. It's, it's, so we were like, okay, we can't, we have to go through an exchange in Portland.Yeah. Andswyx: you'd rather do this than like run your zookeeper and likeSimon Hørup Eskildsen: Yes. Way rather. It doesn't have state, I don't want state and two systems. Um, and I think all that is just informed by Justine, my co-founder and I had just been on call for so long. And the worst outages are the ones where you have state in multiple places that's not syncing up.So it really came from, from a a, like just a, a very pure source of pain, of just imagining what we would be Okay. Being woken up at 3:00 AM about and having something in zookeeper was not one of them.swyx: You, you're talking to like a notion or something. Do they care or do they just, theySimon Hørup Eskildsen: just, they care about latency.swyx: They latency cost. That's it.Simon Hørup Eskildsen: They just cared about latency. Right. And we just absorbed the cost. We're just like, we have high conviction in this. At some point we can move them to AWS. Right. And so we just, we, we'll buy the fiber, it doesn't matter. Right. Um, and it's like $5,000. Usually when you buy fiber, you buy like multiple lines.And we're like, we can only afford one, but we will just test it that when it goes over the public internet, it's like super smooth. And so we did a lot of, anyway, it's, yeah, it was, that's cool.Alessio: You can imagine talking to the GCP rep and it's like, no, we're gonna buy, because we know we're gonna turn, we're gonna turn from you guys and go to AWS in like six months.But in the meantime we'll do this. It'sSimon Hørup Eskildsen: a, I mean, like they, you know, this workload still runs on GCP for what it's worth. Right? ‘cause it's so, it was just, it was so reliable. So it was never about moving off GCP, it was just about honesty. It was just about giving notion the latency that they deserved.Right. Um, and we didn't want ‘em to have to care about any of this. We also, they were like, oh, egress is gonna be bad. It was like, okay, screw it. Like we're just gonna like vvc, VPC peer with you and AWS we'll eat the cost. Yeah. Whatever needs to be done.Alessio: And what were the actual workloads? Because I think when you think about ai, it's like 14 milliseconds.It's like really doesn't really matter in the scheme of like a model generation.Simon Hørup Eskildsen: Yeah. We were told the latency, right. That we had to beat. Oh, right. So, so we're just looking at the traces. Right. And then sort of like hand draw, like, you know, kind of like looking at the trace and then thinking what are the other extensions of the trace?Right. And there's a lot more to it because it's also when you have, if you have 14 versus seven milliseconds, right. You can fit in another round trip. So we had to tune TCP to try to send as much data in every round trip, prewarm all the connections. And there was, there's a lot of things that compound from having these kinds of round trips, but in the grand scheme it was just like, well, we have to beat the latency of whatever we're up against.swyx: Which is like they, I mean, notion is a database company. They could have done this themselves. They, they do lots of database engineering themselves. How do you even get in the door? Like Yeah, just like talk through that kind of.Simon Hørup Eskildsen: Last time I was in San Francisco, I was talking to one of the engineers actually, who, who was one of our champions, um, at, AT Notion.And they were, they were just trying to make sure that the, you know, per user cost matched the economics that they needed. You know, Uhhuh like, it's like the way I think about, it's like I have to earn a return on whatever the clouds charge me and then my customers have to earn a return on that. And it's like very simple, right?And so there has to be gross margin all the way up and that's how you build the product. And so then our customers have to make the right set of trade off the turbo Puffer makes, and if they're happy with that, that's great.swyx: Do you feel like you're competing with build internally versus buy or buy versus buy?Simon Hørup Eskildsen: Yeah, so, sorry, this was all to build up to your question. So one of the notion engineers told me that they'd sat and probably on a napkin, like drawn out like, why hasn't anyone built this? And then they saw terrible. It was like, well, it literally that. So, and I think AI has also changed the buy versus build equation in terms of, it's not really about can we build it, it's about do we have time to build it?I think they like, I think they felt like, okay, if this is a team that can do that and they, they feel enough like an extension of our team, well then we can go a lot faster, which would be very, very good for them. And I mean, they put us through the, through the test, right? Like we had some very, very long nights to to, to do that POC.And they were really our biggest, our second big customer off the cursor, which also was a lot of late nights. Right.swyx: Yeah. That, I mean, should we go into that story? The, the, the sort of Chris's story, like a lot, um, they credit you a lot for. Working very closely with them. So I just wanna hear, I've heard this, uh, story from Sole's point of view, but like, I'm curious what, what it looks like from your side.Simon Hørup Eskildsen: I actually haven't heard it from Sole's point of view, so maybe you can now cross reference it. The way that I remember it was that, um, the day after we launched, which was just, you know, I'd worked the whole summer on, on the first version. Justine wasn't part of it yet. ‘cause I just, I didn't tell anyone that summer that I was working on this.I was just locked in on building it because it's very easy otherwise to confuse talking about something to actually doing it. And so I was just like, I'm not gonna do that. I'm just gonna do the thing. I launched it and at this point turbo puffer is like a rust binary running on a single eight core machine in a T Marks instance.And me deploying it was like looking at the request log and then like command seeing it or like control seeing it to just like, okay, there's no request. Let's upgrade the binary. Like it was like literally the, the, the, the scrappiest thing. You could imagine it was on purpose because just like at Shopify, we did that all the time.Like, we like move, like we ran things in tux all the time to begin with. Before something had like, at least the inkling of PMF, it was like, okay, is anyone gonna hear about this? Um, and one of the cursor co-founders Arvid reached out and he just, you know, the, the cursor team are like all I-O-I-I-M-O like, um, contenders, right?So they just speak in bullet points and, and facts. It was like this amazing email exchange just of, this is how many QPS we have, this is what we're paying, this is where we're going, blah, blah, blah. And so we're just conversing in bullet points. And I tried to get a call with them a few times, but they were, so, they were like really writing the PMF bowl here, just like late 2023.And one time Swally emails me at like five. What was it like 4:00 AM Pacific time saying like, Hey, are you open for a call now? And I'm on the East coast and I, it was like 7:00 AM I was like, yeah, great, sure, whatever. Um, and we just started talking and something. Then I didn't know anything about sales.It was something that just comp compelled me. I have to go see this team. Like, there's something here. So I, I went to San Francisco and I went to their office and the way that I remember it is that Postgres was down when I showed up at the office. Did SW tell you this? No. Okay. So Postgres was down and so it's like they were distracting with that.And I was trying my best to see if I could, if I could help in any way. Like I knew a little bit about databases back to tuning, auto vacuum. It was like, I think you have to tune out a vacuum. Um, and so we, we talked about that and then, um, that evening just talked about like what would it look like, what would it look like to work with us?And I just said. Look like we're all in, like we will just do what we'll do whatever, whatever you tell us, right? They migrated everything over the next like week or two, and we reduced their cost by 95%, which I think like kind of fixed their per user economics. Um, and it solved a lot of other things. And we were just, Justine, this is also when I asked Justine to come on as my co-founder, she was the best engineer, um, that I ever worked with at Shopify.She lived two blocks away and we were just, okay, we're just gonna get this done. Um, and we did, and so we helped them migrate and we just worked like hell over the next like month or two to make sure that we were never an issue. And that was, that was the cursor story. Yeah.swyx: And, and is code a different workload than normal text?I, I don't know. Is is it just text? Is it the same thing?Simon Hørup Eskildsen: Yeah, so cursor's workload is basically, they, um, they will embed the entire code base, right? So they, they will like chunk it up in whatever they would, they do. They have their own embedding model, um, which they've been public about. Um, and they find that on, on, on their evals.It. There's one of their evals where it's like a 25% improvement on a very particular workload. They have a bunch of blog posts about it. Um, I think it works best on larger code basis, but they've trained their own embedding model to do this. Um, and so you'll see it if you use the cursor agent, it will do searches.And they've also been public around, um, how they've, I think they post trained their model to be very good at semantic search as well. Um, and that's, that's how they use it. And so it's very good at, like, can you find me on the code that's similar to this, or code that does this? And just in, in this queries, they also use GR to supplement it.swyx: Yeah.Simon Hørup Eskildsen: Um, of courseswyx: it's been a big topic of discussion like, is rag dead because gr you know,Simon Hørup Eskildsen: and I mean like, I just, we, we see lots of demand from the coding company to ethicsswyx: search in every part. Yes.Simon Hørup Eskildsen: Uh, we, we, we see demand. And so, I mean, I'm. I like case studies. I don't like, like just doing like thought pieces on this is where it's going.And like trying to be all macroeconomic about ai, that's has turned out to be a giant waste of time because no one can really predict any of this. So I just collect case studies and I mean, cursor has done a great job talking about what they're doing and I hope some of the other coding labs that use Turbo Puffer will do the same.Um, but it does seem to make a difference for particular queries. Um, I mean we can also do text, we can also do RegX, but I should also say that cursors like security posture into Tur Puffer is exceptional, right? They have their own embedding model, which makes it very difficult to reverse engineer. They obfuscate the file paths.They like you. It's very difficult to learn anything about a code base by looking at it. And the other thing they do too is that for their customers, they encrypt it with their encryption keys in turbo puffer's bucket. Um, so it's, it's, it's really, really well designed.swyx: And so this is like extra stuff they did to work with you because you are not part of Cursor.Exactly like, and this is just best practice when working in any database, not just you guys. Okay. Yeah, that makes sense. Yeah. I think for me, like the, the, the learning is kind of like you, like all workloads are hybrid. Like, you know, uh, like you, you want the semantic, you want the text, you want the RegX, you want sql.I dunno. Um, but like, it's silly to like be all in on like one particularly query pattern.Simon Hørup Eskildsen: I think, like I really like the way that, um, um, that swally at cursor talks about it, which is, um, I'm gonna butcher it here. Um, and you know, I'm a, I'm a database scalability person. I'm not a, I, I dunno anything about training models other than, um, what the internet tells me and what.The way he describes is that this is just like cash compute, right? It's like you have a point in time where you're looking at some particular context and focused on some chunk and you say, this is the layer of the neural net at this point in time. That seems fundamentally really useful to do cash compute like that.And, um, how the value of that will change over time. I'm, I'm not sure, but there seems to be a lot of value in that.Alessio: Maybe talk a bit about the evolution of the workload, because even like search, like maybe two years ago it was like one search at the start of like an LLM query to build the context. Now you have a gentech search, however you wanna call it, where like the model is both writing and changing the code and it's searching it again later.Yeah. What are maybe some of the new types of workloads or like changes you've had to make to your architecture for it?Simon Hørup Eskildsen: I think you're right. When I think of rag, I think of, Hey, there's an 8,000 token, uh, context window and you better make it count. Um, and search was a way to do that now. Everything is moving towards the, just let the agent do its thing.Right? And so back to the thing before, right? The LLM is very good at reasoning with the data, and so we're just the tool call, right? And that's increasingly what we see our customers doing. Um, what we're seeing more demand from, from our customers now is to do a lot of concurrency, right? Like Notion does a ridiculous amount of queries in every round trip just because they can't.And I'm also now, when I use the cursor agent, I also see them doing more concurrency than I've ever seen before. So a bit similar to how we designed a database to drive as much concurrency in every round trip as possible. That's also what the agents are doing. So that's new. It means just an enormous amount of queries all at once to the dataset while it's warm in as few turns as possible.swyx: Can I clarify one thing on that?Simon Hørup Eskildsen: Yes.swyx: Is it, are they batching multiple users or one user is driving multiple,Simon Hørup Eskildsen: one user driving multiple, one agent driving.swyx: It's parallel searching a bunch of things.Simon Hørup Eskildsen: Exactly.swyx: Yeah. Yeah, exactly. So yeah, the clinician also did, did this for the fast context thing, like eight parallel at once.Simon Hørup Eskildsen: Yes.swyx: And, and like an interesting problem is, well, how do you make sure you have enough diversity so you're not making the the same request eight times?Simon Hørup Eskildsen: And I think like that's probably also where the hybrid comes in, where. That's another way to diversify. It's a completely different way to, to do the search.That's a big change, right? So before it was really just like one call and then, you know, the LLM took however many seconds to return, but now we just see an enormous amount of queries. So the, um, we just see more queries. So we've like tried to reduce query, we've reduced query pricing. Um, this is probably the first time actually I'm saying that, but the query pricing is being reduced, like five x.Um, and we'll probably try to reduce it even more to accommodate some of these workloads of just doing very large amounts of queries. Um, that's one thing that's changed. I think the right, the right ratio is still very high, right? Like there's still a, an enormous amount of rights per read, but we're starting probably to see that change if people really lean into this pattern.Alessio: Can we talk a little bit about the pricing? I'm curious, uh, because traditionally a database would charge on storage, but now you have the token generation that is so expensive, where like the actual. Value of like a good search query is like much higher because they're like saving inference time down the line.How do you structure that as like, what are people receptive to on the other side too?Simon Hørup Eskildsen: Yeah. I, the, the turbo puffer pricing in the beginning was just very simple. The pricing on these on for search engines before Turbo Puffer was very server full, right? It was like, here's the vm, here's the per hour cost, right?Great. And I just sat down with like a piece of paper and said like, if Turbo Puffer was like really good, this is probably what it would cost with a little bit of margin. And that was the first pricing of Turbo Puffer. And I just like sat down and I was like, okay, like this is like probably the storage amp, but whenever on a piece of paper I, it was vibe pricing.It was very vibe price, and I got it wrong. Oh. Um, well I didn't get it wrong, but like Turbo Puffer wasn't at the first principle pricing, right? So when Cursor came on Turbo Puffer, it was like. Like, I didn't know any VCs. I didn't know, like I was just like, I don't know, I didn't know anything about raising money or anything like that.I just saw that my GCP bill was, was high, was a lot higher than the cursor bill. So Justine and I was just like, well, we have to optimize it. Um, and I mean, to the chagrin now of, of it, of, of the VCs, it now means that we're profitable because we've had so much pricing pressure in the beginning. Because it was running on my credit card and Justine and I had spent like, like tens of thousands of dollars on like compute bills and like spinning off the company and like very like, like bad Canadian lawyers and like things like to like get all of this done because we just like, we didn't know.Right. If you're like steeped in San Francisco, you're just like, you just know. Okay. Like you go out, raise a pre-seed round. I, I never heard a word pre-seed at this point in time.swyx: When you had Cursor, you had Notion you, you had no funding.Simon Hørup Eskildsen: Um, with Cursor we had no funding. Yeah. Um, by the time we had Notion Locke was, Locke was here.Yeah. So it was really just, we vibe priced it 100% from first Principles, but it wasn't, it, it was not performing at first principles, so we just did everything we could to optimize it in the beginning for that, so that at least we could have like a 5% margin or something. So I wasn't freaking out because Cursor's bill was also going like this as they were growing.And so my liability and my credit limit was like actively like calling my bank. It was like, I need a bigger credit. Like it was, yeah. Anyway, that was the beginning. Yeah. But the pricing was, yeah, like storage rights and query. Right. And the, the pricing we have today is basically just that pricing with duct tape and spit to try to approach like, you know, like a, as a margin on the physical underlying hardware.And we're doing this year, you're gonna see more and more pricing changes from us. Yeah.swyx: And like is how much does stuff like VVC peering matter because you're working in AWS land where egress is charged and all that, you know.Simon Hørup Eskildsen: We probably don't like, we have like an enterprise plan that just has like a base fee because we haven't had time to figure out SKU pricing for all of this.Um, but I mean, yeah, you can run turbo puffer either in SaaS, right? That's what Cursor does. You can run it in a single tenant cluster. So it's just you. That's what Notion does. And then you can run it in, in, in BYOC where everything is inside the customer's VPC, that's what an for example, philanthropic does.swyx: What I'm hearing is that this is probably the best CRO job for somebody who can come in and,Simon Hørup Eskildsen: I mean,swyx: help you with this.Simon Hørup Eskildsen: Um, like Turbo Puffer hired, like, I don't know what, what number this was, but we had a full-time CFO as like the 12th hire or something at Turbo Puffer, um, I think I hear are a lot of comp.I don't know how they do it. Like they have a hundred employees and not a CFO. It's like having a CFO is like a runningswyx: business man. Like, you know,Simon Hørup Eskildsen: it's so good. Yeah, like money Mike, like he just, you know, just handles the money and a lot of the business stuff and so he came in and just hopped with a lot of the operational side of the business.So like C-O-O-C-F-O, like somewhere in between.swyx: Just as quick mention of Lucky, just ‘cause I'm curious, I've met Lock and like, he's obviously a very good investor and now on physical intelligence, um, I call it generalist super angel, right? He invests in everything. Um, and I always wonder like, you know, is there something appealing about focusing on developer tooling, focusing on databases, going like, I've invested for 10 years in databases versus being like a lock where he can maybe like connect you to all the customers that you need.Simon Hørup Eskildsen: This is an excellent question. No, no one's asked me this. Um, why lockey? Because. There was a couple of people that we were talking to at the time and when we were raising, we were almost a little, we were like a bit distressed because one of our, one of our peers had just launched something that was very similar to Turbo Puffer.And someone just gave me the advice at the time of just choose the person where you just feel like you can just pick up the phone and not prepare anything. And just be completely honest, and I don't think I've said this publicly before, but I just called Lockey and was like local Lockie. Like if this doesn't have PMF by the end of the year, like we'll just like return all the money to you.But it's just like, I don't really, we, Justine and I don't wanna work on this unless it's really working. So we want to give it the best shot this year and like we're really gonna go for it. We're gonna hire a bunch of people and we're just gonna be honest with everyone. Like when I don't know how to play a game, I just play with open cards and.Lockey was the only person that didn't, that didn't freak out. He was like, I've never heard anyone say that before. As I said, I didn't even know what a seed or pre-seed round was like before, probably even at this time. So I was just like very honest with him. And I asked him like, Lockie, have you ever have, have you ever invested in database company?He was just like, no. And at the time I was like, am I dumb? Like, but I think there was something that just like really drew me to Lockie. He is so authentic, so honest, like, and there was something just like, I just felt like I could just play like, just say everything openly. And that was, that was, I think that that was like a perfect match at the time, and, and, and honestly still is.He was just like, okay, that's great. This is like the most honest, ridiculous thing I've ever heard anyone say to me. But like that, like that, whyswyx: is this ridiculous? Say competitor launch, this may not work out. It wasSimon Hørup Eskildsen: more just like. If this doesn't work out, I'm gonna close up shop by the end of the mo the year, right?Like it was, I don't know, maybe it's common. I, I don't know. He told me it was uncommon. I don't know. Um, that's why we chose him and he'd been phenomenal. The other people were talking at the, at the time were database experts. Like they, you know, knew a lot about databases and Locke didn't, this turned out to be a phenomenal asset.Right. I like Justine and I know a lot about databases. The people that we hire know a lot about databases. What we needed was just someone who didn't know a lot about databases, didn't pretend to know a lot about databases, and just wanted to help us with candidates and customers. And he did. Yeah. And I have a list, right, of the investors that I have a relationship with, and Lockey has just performed excellent in the number of sub bullets of what we can attribute back to him.Just absolutely incredible. And when people talk about like no ego and just the best thing for the founder, I like, I don't think that anyone, like even my lawyer is like, yeah, Lockey is like the most friendly person you will find.swyx: Okay. This is my most glow recommendation I've ever heard.Alessio: He deserves it.He's very special.swyx: Yeah. Yeah. Yeah. Okay. Amazing.Alessio: Since you mentioned candidates, maybe we can talk about team building, you know, like, especially in sf, it feels like it's just easier to start a company than to join a company. Uh, I'm curious your experience, especially not being n SF full-time and doing something that is maybe, you know, a very low level of detail and technical detail.Simon Hørup Eskildsen: Yeah. So joining versus starting, I never thought that I would be a founder. I would start with it, like Turbo Puffer started as a blog post, and then it became a project and then sort of almost accidentally became a company. And now it feels like it's, it's like becoming a bigger company. That was never the intention.The intentions were very pure. It's just like, why hasn't anyone done this? And it's like, I wanna be the, like, I wanna be the first person to do it. I think some founders have this, like, I could never work for anyone else. I, I really don't feel that way. Like, it's just like, I wanna see this happen. And I wanna see it happen with some people that I really enjoy working with and I wanna have fun doing it and this, this, this has all felt very natural on that, on that sense.So it was never a like join versus versus versus found. It was just dis found me at the right moment.Alessio: Well I think there's an argument for, you should have joined Cursor, right? So I'm curious like how you evaluate it. Okay, I should actually go raise money and make this a company versus like, this is like a company that is like growing like crazy.It's like an interesting technical problem. I should just build it within Cursor and then they don't have to encrypt all this stuff. They don't have to obfuscate things. Like was that on your mind at all orSimon Hørup Eskildsen: before taking the, the small check from Lockie, I did have like a hard like look at myself in the mirror of like, okay, do I really want to do this?And because if I take the money, I really have to do it right. And so the way I almost think about it's like you kind of need to ha like you kind of need to be like fucked up enough to want to go all the way. And that was the conversation where I was like, okay, this is gonna be part of my life's journey to build this company and do it in the best way that I possibly can't.Because if I ask people to join me, ask people to get on the cap table, then I have an ultimate responsibility to give it everything. And I don't, I think some people, it doesn't occur to me that everyone takes it that seriously. And maybe I take it too seriously, I don't know. But that was like a very intentional moment.And so then it was very clear like, okay, I'm gonna do this and I'm gonna give it everything.Alessio: A lot of people don't take it this seriously. But,swyx: uh, let's talk about, you have this concept of the P 99 engineer. Uh, people are 10 x saying, everyone's saying, you know, uh, maybe engineers are out of a job. I don't know.But you definitely see a P 99 engineer, and I just want you to talk about it.Simon Hørup Eskildsen: Yeah, so the P 99 engineer was just a term that we started using internally to talk about candidates and talk about how we wanted to build the company. And you know, like everyone else is, like we want a talent dense company.And I think that's almost become trite at this point. What I credit the cursor founders a lot with is that they just arrived there from first principles of like, we just need a talent dense, um, talent dense team. And I think I've seen some teams that weren't talent dense and like seemed a counterfactual run, which if you've run in been in a large company, you will just see that like it's just logically will happen at a large company.Um, and so that was super important to me and Justine and it's very difficult to maintain. And so we just needed, we needed wording for it. And so I have a document called Traits of the P 99 Engineer, and it's a bullet point list. And I look at that list after every single interview that I do, and in every single recap that we do and every recap we end with.End with, um, some version of I'm gonna reject this candidate completely regardless of what the discourse was, because I wanna see people fight for this person because the default should not be, we're gonna hire this person. The default should be, we're definitely not hiring this person. And you know, if everyone was like, ah, maybe throw a punch, then this is not the right.swyx: Do, do you operate, like if there's one cha there must have at least one champion who's like, yes, I will put my career on, on, on the line for this. You know,Simon Hørup Eskildsen: I think career on the line,swyx: maybe a chair, butSimon Hørup Eskildsen: yeah. You know, like, um, I would say so someone needs to like, have both fists up and be like, I'd fight.Right? Yeah. Yeah. And if one person said, then, okay, let's do it. Right?swyx: Yeah.Simon Hørup Eskildsen: Um. It doesn't have to be absolutely everyone. Right? And like the interviews are always the sign that you're checking for different attributes. And if someone is like knocking it outta the park in every single attribute, that's, that's fairly rare.Um, but that's really important. And so the traits of the P 99 engineer, there's lots of them. There's also the traits of the p like triple nine engineer and the quadruple nine engineer. This is like, it's a long list.swyx: Okay.Simon Hørup Eskildsen: Um, I'll give you some samples, right. Of what we, what we look for. I think that the P 99 engineer has some history of having bent, like their trajectory or something to their will.Right? Some moment where it was just, they just, you know, made the computer do what it needed to do. There's something like that, and it will, it will occur to have them at some point in their career. And, uh. Hopefully multiple times. Right.swyx: Gimme an example of one of your engineers that like,Simon Hørup Eskildsen: I'll give an eng.Uh, so we, we, we launched this thing called A and NV three. Um, we could, we're also, we're working on V four and V five right now, but a and NV three can search a hundred billion vectors with a P 50 of around 40 milliseconds and a p 99 of 200 milliseconds. Um, maybe other people have done this, I'm sure Google and others have done this, but, uh, we haven't seen anyone, um, at least not in like a public consumable SaaS that can do this.And that was an engineer, the chief architect of Turbo Puffer, Nathan, um, who more or less just bent this, the software was not capable of this and he just made it capable for a very particular workload in like a, you know, six to eight week period with the help of a lot of the team. Right. It's been, been, there's numerous of examples of that, like at, at turbo puff, but that's like really bending the software and X 86 to your will.It was incredible to watch. Um. You wanna see some moments like that?swyx: Isn't that triple nine?Simon Hørup Eskildsen: Um, I think Nathan, what's calledAlessio: group nine, that was only nine. I feel like this is too high forSimon Hørup Eskildsen: Nathan. Nathan is, uh, Nathan is like, yeah, there's a lot of nines. Okay. After that p So I think that's one trait. I think another trait is that, uh, the P 99 spends a lot of time looking at maps.Generally it's their preferred ux. They just love looking at maps. You ever seen someone who just like, sits on their phone and just like, scrolls around on a map? Or did you not look at maps A lot? You guys don't look atswyx: maps? I guess I'm not feeling there. I don't know, butSimon Hørup Eskildsen: you just dis What about trains?Do you like trains?swyx: Uh, I mean they, not enough. Okay. This is just like weapon nice. Autism is what I call it. Like, like,Simon Hørup Eskildsen: um, I love looking at maps, like, it's like my preferred UX and just like I, you know, I likeswyx: lotsAlessio: of, of like random places, soswyx: like,youswyx: know.Alessio: Yes. Okay. There you go. So instead of like random places, like how do you explore the maps?Simon Hørup Eskildsen: No, it's, it's just a joke.swyx: It's autism laugh. It's like you are just obsessed by something and you like studying a thing.Simon Hørup Eskildsen: The origin of this was that at some point I read an interview with some IOI gold medalistswyx: Uhhuh,Simon Hørup Eskildsen: and it's like, what do you do in your spare time? I was just like, I like looking at maps.I was like, I feel so seen. Like, I just like love, like swirling out. I was like, oh, Canada is so big. Where's Baffin Island? I don't know. I love it. Yeah. Um, anyway, so the traits of P 99, P 99 is obsessive, right? Like, there's just like, you'll, you'll find traits of that we do an interview at, at, at, at turbo puffer or like multiple interviews that just try to screen for some of these things.Um, so. There's lots of others, but these are the kinds of traits that we look for.swyx: I'll tell you, uh, some people listen for like some of my dere stuff. Uh, I do think about derel as maps. Um, you draw a map for people, uh, maps show you the, uh, what is commonly agreed to be the geographical features of what a boundary is.And it shows also shows you what is not doing. And I, I think a lot of like developer tools, companies try to tell you they can do everything, but like, let's, let's be real. Like you, your, your three landmarks are here, everyone comes here, then here, then here, and you draw a map and, and then you draw a journey through the map.And like that. To me, that's what developer relations looks like. So I do think about things that way.Simon Hørup Eskildsen: I think the P 99 thinks in offs, right? The P 99 is very clear about, you know, hey, turbo puffer, you can't run a high transaction workload on turbo puffer, right? It's like the right latency is a hundred milliseconds.That's a clear trade off. I think the P 99 is very good at articulating the trade offs in every decision. Um. Which is exactly what the map is in your case, right?swyx: Uh, yeah, yeah. My, my, my world. My world.Alessio: How, how do you reconcile some of these things when you're saying you bend the will the computer versus like the trade

Join Anthony Sardain, CEO and Founder of Cavela, for a conversation on the next revolution in global trade: the automation of physical product sourcing. Born into a family of trade in Southeast Asia, Anthony has spent nearly a decade at the intersection of AI and logistics. In this episode, we explore how Cavela is using AI to handle the heavy lifting of finding, vetting, and managing global suppliers—leveling the playing field for startups and scaling businesses that need to move as fast as the digital economy.

Alex and Kevin are together again on opposite sides of the Country. Kevin, live from SF, gives an honest review of his first Waymo ride, shares about his recent travels, and his surprising adoption of the Oakley Meta Glasses gifted to him by Alex. The two go on to discuss Zuck's Miami mansion, looksmaxxing, burger mogging, the new Snapple Rebrand, The Update Update, David's new protein ice cream, World's First Music-Streaming Urn, and more!

在忙碌的城市生活中，心靈常渴望一處安歇。我們以7–10分鐘的短篇靈修，帶領聽眾在日常節奏裡遇見神。內容涵蓋聖經經文反思、生命見證與屬靈啟示，幫助人在繁忙中停下腳步，重新對齊屬靈方向。每一集都是與神對話的邀請，讓聽眾透過簡單卻深刻的分享，經歷聖靈更新與心靈滋潤。無論在通勤、休息或安靜時刻，都能透過這平台得到信仰餵養。《城市使命》 願成為城市中的一盞柔光，照亮屬靈之路，引領你在日常中活出信仰，經歷神的真實同在。In the hustle and bustle of city life, the soul often longs for a place of rest. We offer 7–10 minute short devotionals to help listeners encounter God amidst their daily rhythm. Featuring biblical reflections, life testimonies, and spiritual insights, we help you pause and realign your spiritual compass.Each episode is an invitation to dialogue with God—a space to experience the Holy Spirit's renewal and soul-deep nourishment through simple yet profound sharing. Whether you are commuting, taking a break, or in a quiet moment, this platform provides the spiritual feeding you need."CityMission" aspires to be a gentle light in the city, illuminating your spiritual path and guiding you to live out your faith while experiencing God's real presence in the everyday.

Miercuri, Martie 11 - Sf. Sofronie, Patriarhul Ierusalimului; Sf. Mc. Lalu si Trofim

Join Trent and Jordan LIVE for instant, unfiltered NFL Free Agency Reactions!We're yelling at the screen, grading deals on the fly, roasting bad moves, hyping the winners, and reading your hottest (and wildest) takes straight from chat. This isn't analysis hour—it's pure reaction energy as the league flips upside down. Today's madness so far (and it's only getting crazier): Mike Evans to the 49ers: 3 years, $60.4M—does this finally give SF that alpha WR2? Or overpay for an aging stud?Malik Willis to the Dolphins: 3 years, $67.5M ($45M guaranteed) right after dumping Tua Tagovailoa—what a plot twist! Mobile QB era in Miami incoming?Maxx Crosby blockbuster trade: Ravens snag the perennial Pro Bowler from Raiders for TWO first-round picks (2026 & 2027)—Baltimore going all-in!Cowboys grab Rashan Gary from Packers for a 2027 4th-rounder after whiffing on Crosby—solid get or settling?Kenneth Walker III to the Chiefs—pairing with Mahomes & Kelce (who's back!) after his Super Bowl MVP run?Expect non-stop reactions: instant grades, "what were they thinking?!" rants, fan arguments in chat, overreactions, celebrations, and everything in between. If a deal drops mid-stream, we're breaking it live—no spoilers, just vibes.Drop your wildest takes, questions, or team panic in chat RIGHT NOW. LIKE if you're glued for the drama, SUBSCRIBE + hit notifications so you catch every live meltdown/reaction!Connect with the Showhttps://x.com/TFFDudes https://www.instagram.com/tffdudes/Watch the Dudes on Youtube athttps://www.youtube.com/channel/UC2JAx3YD3P-OJRiaqA7wSQwQuestions for the showtffdudes@gmail.com Watch the Dudes on Youtube athttps://www.youtube.com/channel/UC2JAx3YD3P-OJRiaqA7wSQw Sponsors Trophy Smackwww.trophysmack.com/dudes Sleeper www.sleeper.comDudes100 and they will match you $100

The SF mayor got attacked in broad daylight, and the mayor walked away.Democrats wanted more Epstein files so they are getting them.Did you see the video of the B2 buzzing one of our ships? That was something to see. The flying wing.A real game-changer in military warfare…[X] SB – Gay mapsGood maps. Gay maps. Czechia. Slovakia.Embarrassing.Non-binary and transfrancophoneInclusive French.DEI flashmob in “stan”Space Force is in the news…Space Force, mocked by Democrats, is unleashing the fury of Allah on the IraniansWhat if this war was not about what people think. Sure, Iran needs its butt kicked. That is 47 years overdue.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of Talking Smack 415, Jamie the Great and I dive into one of the biggest health conversations happening right now: GLP-1 weight-loss drugs.From celebrities like Oprah and Sharon Osbourne to friends, family members, and coworkers, medications like Ozempic and other GLP-1 drugs seem to be everywhere. Nearly 10% of U.S. adults are now taking GLP-1 medications, and the cultural conversation around them is growing fast.Are they a breakthrough for obesity and metabolic health — or the beginning of a new wave of diet culture?To help us unpack the science and the societal impact, we invited Dr. Erika Siegel, a naturopathic physician, acupuncturist, and author of The Nourish Me Kitchen. With more than two decades of experience in integrative medicine, Dr. Siegel blends functional medicine with nutrition and whole-food healing.In this episode we ask the questions everyone seems to be wondering: Are GLP-1 medications like Ozempic truly a miracle drug for weight loss and type 2 diabetes?  What exactly is “food noise,” and how do GLP-1 drugs reduce cravings? Why do many people regain weight after stopping GLP-1 medications?  What are the most common GLP-1 side effects, including hair loss, muscle loss, and digestive issues?  Is micro-dosing GLP-1 drugs becoming a new trend?  Can GLP-1 medications actually help reduce cravings for alcohol and other addictions?Dr. Siegel also explains why nutrition, strength training, and fiber intake (25–30 grams per day) are critical when using these medications — and why protein, sleep, and hormone balance still matter.We also explore the bigger cultural questions:• Are GLP-1 drugs fueling a new era of SkinnyTok and diet culture? • What are the long-term effects of GLP-1 medications, especially for younger people? • How might these drugs affect fertility, metabolism, and overall health? • And who were GLP-1 medications actually designed for — versus who is using them now?Whether you're curious about Ozempic, GLP-1 weight-loss drugs, food noise, addiction, or long-term safety, this conversation takes a deeper look at the science, the culture, and the future of one of the most talked-about medical trends today.You can follow along with all things Erika : Instagram @dr.erikasiegelInfo on her book on nourishme.comBuy her bookset on Amazon the Nourish Me KitchenShare this episode with your friends and family who love to laugh. Subscribe to Talking Smack 415 and leave us a rating and review so more peeps can find us for laughter and friendship to feed your soul!

In Hour 1, Bonta Hill joins Spadoni and Shasky to discuss his reaction to the Mike Evans to SF deal.

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

We discuss pedestrian safety in SF, sit down with Supervisor Connie Chan to discuss her bid for Congress and learn about Pescadero's Pie Ranch farm

From unsupported EV software to AI‑driven changes in office use and logistics, tech is reshaping collateral performance. Justin Patrie, Head of Fitch Ratings Credit Commentary and Research, and Suzanne Albers, Senior Director in Structured Finance, look at pressure points such as outdated EV systems, shifts in office demand linked to AI adoption, and the widening gap between legacy and modern logistics sites. Taken together, these trends are influencing risk across auto ABS, CMBS, and RMBS and accelerating how these sectors respond to the faster pace of technological change.Related Resources:Accelerating Technology May Increase Obsolescence Risk Within ABS, MBSStable Arrears Protect European Auto ABS Against Near-Term RiskU.S. CLO Note Ratings Resilient to Severe Software Sector Stress

在忙碌的城市生活中，心靈常渴望一處安歇。我們以7–10分鐘的短篇靈修，帶領聽眾在日常節奏裡遇見神。內容涵蓋聖經經文反思、生命見證與屬靈啟示，幫助人在繁忙中停下腳步，重新對齊屬靈方向。每一集都是與神對話的邀請，讓聽眾透過簡單卻深刻的分享，經歷聖靈更新與心靈滋潤。無論在通勤、休息或安靜時刻，都能透過這平台得到信仰餵養。《城市使命》 願成為城市中的一盞柔光，照亮屬靈之路，引領你在日常中活出信仰，經歷神的真實同在。In the hustle and bustle of city life, the soul often longs for a place of rest. We offer 7–10 minute short devotionals to help listeners encounter God amidst their daily rhythm. Featuring biblical reflections, life testimonies, and spiritual insights, we help you pause and realign your spiritual compass.Each episode is an invitation to dialogue with God—a space to experience the Holy Spirit's renewal and soul-deep nourishment through simple yet profound sharing. Whether you are commuting, taking a break, or in a quiet moment, this platform provides the spiritual feeding you need."CityMission" aspires to be a gentle light in the city, illuminating your spiritual path and guiding you to live out your faith while experiencing God's real presence in the everyday.

Marti, Martie 10 - Sf. Mc. Codrat, Ciprian, Dionisie si cei impreuna cu dansii

Episode 81: Slopeside with the Summit Syndicate Different episode today, featuring slopeside interviews from our second Summit Syndicate trip of 2026. The Summit Syndicate is a Lake Tahoe day trip event co-hosted by Cole-Frieman & Mallon, Eisner Amper, V17 Advisors and Juniper Square. We chartered a bus from SF, drove to Northstar, skid a full day and drove back to the city.    We had excellent turnout from industry friends old and new, and even if you didn't make the trip you can re-live it right here, on Tokens of Wisdom. If you have crazy fomo right now, reach out to your favorite podcast host and join us for the next trip! Key Points From This Episode: What's one thing you've learned on the mountain that you can apply to your work life? Disclaimer: This show is for informational purposes only. Nothing presented here constitutes legal, investment or tax advice. The guests that join us share their considerable fund-related wisdom, but everything they share here is their personal opinion and for educational purposes only. On this show, they are speaking for themselves, and not for their employer or any affiliated entity. Tokens of Wisdom is produced by Dave Rothschild, partner at Cole-Frieman & Mallon LLP headquartered in San Francisco, California. For more information, visit https://colefrieman.com/ Links Mentioned in Today's Episode: Dave Rothschild - https://www.linkedin.com/in/davidcrothschild/Cole-Frieman & Mallon LLP - https://colefrieman.com/Music by Joe Ginsberg - https://www.instagram.com/thejoeginsbergFor any questions or comments, email: tow@colefrieman.com

Iowa's 2026 governor's race is already drawing national attention — and this week it got expensive. Randy Feenstra launched a seven-figure statewide TV ad tying Rob Sand to the open borders left and positioning himself as the candidate who will "stand tall" on immigration. Chris Hagenow and ITR Foundation Policy Director John Hendrickson break down what the ad signals about the Republican primary, why immigration has become a centerpiece issue, and what it means for Sand as he tries to stake out a centrist lane in a state that keeps moving right.Rob Sand made waves this week with a social media reel blasting Iowa's budget continuation bill (SF 2461) — accusing Republicans of lacking accountability, calling out Education Savings Account vendor Odyssey, and strongly implying that if elected governor he should have the authority to force a government shutdown over budget disputes. Chris and John unpack the reel line by line: is Sand calling for shutdown power, or is this just a fundraising play? And what does his continued focus on ESA "accountability" tell us about his general election strategy — and its risks?Iowa just became the first state in the nation to receive a federal education waiver under the Trump administration's "Returning Education to the States" initiative — unlocking a $9.5 million block grant that gives Iowa parents and local schools dramatically more flexibility over how federal education dollars are spent. ITR Foundation's John Hendrickson, who wrote the definitive piece on this development, explains what the waiver actually does, why education belongs at the state level under the 10th Amendment, and why Iowa's track record on school choice — from ESAs to open enrollment to charter schools — makes it the ideal proving ground for this new model.ITR Tax Day Luncheon — April 1, 2026 at the Hilton Des Moines Downtown. Governor Kim Reynolds will be the featured speaker. Tickets and details at ITRFoundation.org. If you enjoy ITR Live, please subscribe, leave a review, and share the show — it helps us get the message out on the issues that matter most to Iowa taxpayers.0:00 - Welcome & Intro0:56 - Tax Day Luncheon Announcement (April 1 | Gov. Reynolds)1:41 - Trivia: The Only Man to Be Both Chief Justice and President5:27 - Feenstra Launches 7-Figure Ad in Iowa Governor's Race7:08 - Immigration as a Campaign Issue: Where Does Rob Sand Stand?12:12 - Rob Sand's Budget Reel: Shutdown Threat or Political Theater?15:11 - ESA Accountability Debate: Public Schools vs. Private Choice21:39 - Iowa Becomes First State to Win Federal Education Waiver28:26 - Why Education Belongs at the State Level (10th Amendment)31:38 - Outro & Where to Find ITR

We talk about interview prolific author of Third Horizon adventures Kevin Hassall00.00.40: Introductions00.02.22: Welcome to our new patron: Peter Taylor00.03.53: World of Gaming:   Temeraire RPG from Magpie Games currently Kickstarting; last ten days days of Dragonbane: Trudvang kickstarter; Pirate Borg starter set available and its great plus Down Among the Dead; The Serpent a very Coriolis flavoured Traveller campaign is being kickstarted .... 00.30.31: Old West News: beware AI misrepresentation00.46.26: Interview: Kevin Hassall on his extensive Coriolis and other RPG output.01.22.53: Next time and Goodbye Effekt is brought to you by Effekt Publishing. Music is by Stars in a Black Sea, used with kind permission of Free League Publishing.Like what we do?Sign up for updates on Tales of the Old West via our website and download Tales of the Old West QuickDraw available for free on DriveThru. The core rules are now available on DriveThru too.Put our brand on your face! (and elsewhere)Buy pdfs via our DriveThru Affiliate linkLeave a review on iTunes or PodchaserFind our Actual Play recordings on effektap ★ Support this podcast on Patreon ★

Well it has been a minute since I interviewed an author, but in this episode, I talk with Justin C. Key, the author of the fantastic debut novel the SF medical thriller Hospital at the End of the World. We talk about Justin's path as a doctor and writer, and talk about the process and themes of this excellent new novel.

As usual, Jonathan and Gary raise a number of thorny questions about reading SF and fantasy, and resolve none of them. Beginning with Jonathan's account of his recent reading of Kazuo Ishiguro's Never Let Me Go, we speculate on what sort of expectations we bring as readers to novels in which the interiority of the characters is privileged over the SF elements, whether a novel can do both, and whether the reading protocols are different for different genres. This leads toward a customarily rambling discussion that touches upon everything from Jo Walton and Ada Palmer's new nonfiction book Trace Elements to novels by Le Guin, Wolfe, Bujold and others, and eventually leads us to a consideration of Matt Dinniman's Dungeon Crawler Carl novels, along with books we're either reading right now or looking forward to in the next few weeks.

 Rish presents M.R. James's 1904 spooky story, "The Number Thirteen." A historian in Denmark stays in Room 12 of the local inn . . . but who is in Room 13? And is there even a Room 13?Rish then talks and talks about the ending of the story (and so should you).If you wish to download the episode, Right-Click HERE.If you wish to support me on Patreon, click HERE.Logo by Gino "Thirteen Ain't Nothin But A Number" Moretto.

Scott (@CharlesChillFFB) and producer Brandon (@BGDashC) run through a 4-round, community 2026, superflex Rookie Mock Draft using a 12-team SF format with 1.75 TE Premium. This mock is POST-NFL Combine as we discuss the new pick tiers and some new names! This is the last mock before NFL free agency. Player values, tiers, and draft capital will continue to change. In this mock, Scott uses the new Mock Draft Simulator at [www.ddfantasyfootball.com](http://www.ddfantasyfootball.com) (free to sign up and mock) to talk through early rookie tiers, positional value, macro-strategy and how to get ahead of the picks you may be forced to make. More players to be added to the pool as well. Topics covered in this video: * The UPDATED VALUE of picks at 1.06 and beyond * Impact of 1.75 TE Premium on rookie drafts - every NFL Draft TE will be picked * How #AnyQBOnA2Deep is only viable with certain criteria * Drafting wide receivers in certain ranges can be a poison pill * How viable is this class for #AnyRBOnA53 Learn more about your ad choices. Visit megaphone.fm/adchoices

Indimellem kan man få en fornemmelse af, at forskellene i dansk politik er meget små: LA synes grundlæggende godt tilfredse med, at Danmark er en velfærdsstat, og SF er vist også godt tilfredse med, at vi har en stram udlændingepolitik. Men er det så en enighed, der er kommet med den "mærkelige" midterregering, eller er samarbejdet mellem de traditionelt ideologiske centrer i hver sin blok et produkt af netop en sådan enighed? Eller måske er fornemmelsen slet ikke rigtig? Måske er der lige så meget uenighed i dansk politik, som der altid har været. Udsyn spørger lektor ved Institut for Statskundskab på Københavns Universitet Karina Kosiara-Pedersen, hvordan det danske politiske landskab egentlig ser ud i dag - findes de grundlæggende ideologiske forskelle stadig, og orienterer vi os stadig efter de røde og blå blokke? Vært: Kaspar Colling Nielsen.

This Week on the Toy Power Podcast; we kick off with some rather sad News, that's hits very close to the Aussie Community, as we morn the loss of Jamie Dunn; the Voice & puppeteer of Agro. A staple of Australian programs & so many laughs! Then we bounce around with other News & Announcements, with everything from Thunder Cats, as well as a few Masters Of The Universe Reveals too. Mondo have another pair of Squads, this time from DC Comics & Lego create a damn near perfect Racecar. Plus Splinter from Mezco, is phenomenal - made more special with the amount of things he comes with. Then we check our Mail-Boxes & celebrate some of our Latest Scores! Samurai Pizza Cats, Mythic Legions Snakes & a slew of SilverHawks are among the praises! Then a round table chat towards 'State Of The Nation.' Our honest insights towards how we are tracking with our collections, plus what we might have planned for the future! All this & more! Enjoy!!! Support the show: http://patreon.com/toypowerpodcastSee omnystudio.com/listener for privacy information.

The week started great — Silicon Forest Tech Summit lineup, Agility's rebrand, SBIR grants returning, Portland Dining Month — and then Oregon's QSBS legislation landed on the governor's desk. Let's break down what qualified small business stock exclusion meant for Oregon founders and investors, why removing it hurts the people who can least afford it, and what (if anything) you can do about it. Plus: the annual Black History Month / Pitch Black recap tradition with Stephen Green.TIMECODES00:00 Oregon startup news intro04:27 Silicon Forest Tech Summit 202609:10 Oregon QSBS drama24:45 Black History Month 2026 recap28:35 SecretsLINKS Silicon Forest Tech Summit 2026 - Tickets / info: https://www.steamcircuit.com/events/61b8c1ba-e9bf-4dfc-b86e-17c125cd685b - SF post: https://siliconflorist.com/2026/03/06/why-is-no-one-talking-about-oregon-eliminating-qsbs-tax-breaks/ Black History Month / Pitch Black recap - SF post: https://siliconflorist.com/2026/03/02/black-history-month-2026-a-recap-of-pitch-black-participants/ - Pitch Black: https://pitchblack.org - Stephen Green's Instagram: https://instagram.com/pdxstepheng Mary Williams / Sasquatch Media Grounds - SF post: https://siliconflorist.com/2026/03/05/chatting-with-mary-williams-of-sasquatch-media-grounds/FIND RICK TUROCZY ON THE INTERNET AT…- https://patreon.com/turoczy- https://linkedin.com/in/turoczy- Portland Oregon startup news on Apple Podcasts https://podcasts.apple.com/us/podcast/portland-oregon-startup-news-silicon-florist/id1711294699- Portland Oregon startup news Spotify https://open.spotify.com/show/2cmLDH8wrPdNMS2qtTnhcy?si=H627wrGOTvStxxKWRlRGLQ- Startup Stories on Spotify https://open.spotify.com/show/1Tk7bbzaNYowGouI9ucKC3- Startup Stories on Apple Podcasts https://podcasts.apple.com/us/podcast/startup-stories-with-silicon-florist/id1849468494- The Long Con on Apple Podcasts https://podcasts.apple.com/us/podcast/the-long-con/id1810923457- The Long Con on Spotify https://open.spotify.com/show/48oglyT5JNKxVH5lnWTYKA- https://bsky.app/profile/turoczy.bsky.social- https://siliconflorist.substack.com/- https://pdxslack.comABOUT SILICON FLORIST ----------For nearly two decades, Rick Turoczy has published Silicon Florist, a blog, newsletter, and podcast that covers entrepreneurs, founders, startups, entrepreneurship, tech, news, and events in the Portland, Oregon, startup community. Whether you're an aspiring entrepreneur, a startup or tech enthusiast, or simply intrigued by Portland's startup culture, Silicon Florist is your go-to source for the latest news, events, jobs, and opportunities in Portland Oregon's flourishing tech and startup scene. Join us in exploring the innovative world of startups in Portland, where creativity and collaboration meet.ABOUT RICK TUROCZY ----------Rick Turoczy has been working in, on, and around the Portland, Oregon, startup community for nearly 30 years. He has been recognized as one of the “OG”s of startup ecosystem building by the Kauffman Foundation. And he has been humbled by any number of opportunities to speak on stages from SXSW to INBOUND and from Kobe, Japan, to Muscat, Oman, including an opportunity to share his views on community building on the TEDxPortland stage (https://www.youtube.com/watch?v=Cj98mr_wUA0). All because of a blog. Weird.https://siliconflorist.com#pdx #portland #oregon #startup #entrepreneur

Friday, March 6, 2026 - Week 10   WHAT DO WE NEED $ FOR? I talked in Episode 197 #S10e197 about scientific priorities, and in Episode 200 #S10e200 about areas of activity beyond science grants.  All of this is what we need to fund.   SPRINT FOR SYNGAP1 Sprint for SYNGAP is coming fast– 49 DAYS. Make a difference. Raise some money. Get on the map!  Text sprint26 to 71777 https://curesyngap1.org/calendar/sprint4syngap-2026/   INAUGURAL SF NIGHT OF IMPACT Also to raise funds, please join us in SF on May 28th. 83 DAYS. Thanks to the organizational team Justin, Zoe, Ed, Jessica, etc. cureSYNGAP1.org/SF26    NHS Matter I talked in episode 198 #S10e198 about the importance of natural history studies. Check out this paper on Zuvenersen from Dravet to understand the long-term impact these studies could have. https://www.nejm.org/doi/full/10.1056/NEJMoa2506295 Join ProMMiS and Citizen Health.   SHOUTOUTS Rosie Davilla on Univision  curesyngap1.org/rosie2026 - https://www.univision.com/local/dallas-kuvn/syngap1-el-diagnostico-que-cambio-la-vida-de-rosie-en-texas-video   #RareDiseaseDay Talks Emily Barnes @ Quiver; Paulina and Brian Sheehan @ Third Rock; Mike @ SparkNS; John Hill & Allison CNBC Cures.   Beata's double header SYNGAP1 Stories. Part 1. https://curesyngap1.org/podcasts/syngap1-stories/beata-tarasiuk/   DSCIII In addition to Colorado Children's & Stanford we are now in a study at Boston Children's, Rush and U Alabama aka UAB.  Attending kick off for this at the end of the month.   DATES TO TRACK Scramble for Syngap - 5th annual on October 3 in S. Carolina in 211 DAYS cureSYNGAP1.org/Scramble26    Conference in Denver CO!  271 DAYS.  Sponsorship options in our #Prospectus for industry are available here https://curesyngap1.org/prospectus  Science Day - cureSYNGAP1.org/SD2025Videos Family Day - cureSYNGAP1.org/FD2025Videos See our entire library of webinars & videos on YouTube youtube.com/cureSYNGAP1    BIOSAMPLES & EEGs! Biorepository needs more samples.  Check out the list and map here https://combinedbrain.org/roadshow/ and contribute both blood & EEGs.  The data and research we do with these samples is invaluable.  Let us know if you are going, email our CSO@curesyngap1.org PUBMED Pubmed 2026 is at 12, just like last week but am I seeing some amazing manuscripts! https://pubmed.ncbi.nlm.nih.gov/?term=syngap1&filter=years.2026-2026&sort=date    Two particularly cool papers: HDAC Inhibitors https://pubmed.ncbi.nlm.nih.gov/41777621/  A positive missense causing cognitive resiliencehttps://pubmed.ncbi.nlm.nih.gov/41777621/   SOCIAL MATTERS 4,732 LinkedIn.  https://www.linkedin.com/company/curesyngap1 1,535 YouTube.  https://www.youtube.com/@CureSYNGAP1 11.2k Twitter https://twitter.com/cureSYNGAP1 45k Insta https://www.instagram.com/curesyngap1   $CAMP stock is at $4.59 on 5 Mar. ‘26 https://www.google.com/finance/beta/quote/CAMP:NASDAQ   Like and subscribe to this podcast wherever you listen.  https://curesyngap1.org/podcasts/syngap10/ Episode 201 of #Syngap10 #CureSYNGAP1 #Podcast

The Gary & Shannon Show Hour 3 (03/06) - #WhatsHappening, #SwampWatch, and the Nine News Nuggets you definitely missed this week. #WhatsHappening: Oil surges to $91/barrel (up 13% today), DOW down 500+, Savannah Guthrie returns to Today but staffers were hoping she wouldn't so her job would open up, SF mayor's security team gets into a scuffle with a homeless man #SwampWatch: 92K jobs lost in February, FBI security system hacked, Trump attending ceremony for fallen soldiers, Rep. Tony Gonzales affair with staffer who later committed suicide, Noem's affair with Lewandowski the final straw, new Epstein files from DOJ Gary wants a nickname but won't admit it — Shannon sees right through him News Nuggets: robber uses Google Translate to announce a holdup, influencer "Non-Stop Dan" is "stuck" in Bali because there's no first class, ranch milkshake topped with nuggets, guy trapped in a UK phone booth ordering a kebab, DARE cop caught selling drugs, Polymarket draws the line at nuclear war betting, Girl Scouts partner with a cannabis dispensary See omnystudio.com/listener for privacy information.

Size matters… but not that much. Need Friday plans? Brandy Carlisle is playing the Chase Center tomorrow night! Nashville is getting a Sphere! What's going on with SF's mini spheres? Lil Uzi Vert is having issues with their insurance due to the diamond in their forehead. Check Sarah and Vinnie out on YouTube! Vinnie's telling us what's going on in the Bay Area, including Hype Con and Granny Con this weekend. 3D printed homes are here. Well, they're in Yuba County. Plus, When Did That Happen?

Hour 1: Bob's Movie Club presents: Frankenstein (2025). Who is the real monster in this story? Because it certainly isn't Jacob Elordi in his bandage booty shorts. Sarah, Vinnie, and Bob discuss the movie and share listener thoughts. Does it count as a sandcastle if it has scaffolding? Is Vinnie harboring a childhood crush in his dreams? Hour 2: Britney Spears has been arrested for a DUI. A disgusting Survivor first happened on last night's episode. Rob bought Maura a Birkin bag! An update on the bay area woman who was throwing parties for underaged kids. Sitting next to your partner on a flight means someone needs to be in the middle seat. Is this necessary, or should we be getting a seat divorce? (52:09) Hour 3: Let us solve your problems! Email us at badadvice973@gmail.com You can expect a Rob Reiner tribute at the Oscars. Will Barbra Streisand be included?? The Beckhams wished Brooklyn a happy birthday. The inspiration for Jurassic Park is in the Epstein files, but he says it's all about his dino chicken project! A Game of Thrones movie is in the works! Prince Andrew is being evicted. Should Meghan Markle move in? Bridgerton Part 2 is here. Vinnie is remembering his futon days. Here are things that make millennials feel like they've made it. Vinnie gives us a lesson on Irish good byes. (1:31:56) Hour 4: Size matters… but not that much. Need Friday plans? Brandy Carlisle is playing the Chase Center tomorrow night! Nashville is getting a Sphere! What's going on with SF's mini spheres? Lil Uzi Vert is having issues with their insurance due to the diamond in their forehead. Check Sarah and Vinnie out on YouTube! Vinnie's telling us what's going on in the Bay Area, including Hype Con and Granny Con this weekend. 3D printed homes are here. Well, they're in Yuba County. Plus, When Did That Happen? (2:17:55)

What would happen if you could step into the past? Would you fix a mistake? Change the course of history? Save someone? Or would one small action send shockwaves into the present? This week on Ron's Amazing Stories, we explore two unforgettable science fiction tales that tackle one of the genre's most fascinating questions: Can the past truly be changed? First, we journey back to the age of dinosaurs in "A Sound of Thunder," based on the classic story by Ray Bradburyand originally broadcast on SF '68. A wealthy hunter travels millions of years into the past for the ultimate trophy — but one misstep may alter the future in ways no one expects. Then, from the legendary radio series X Minus One, we present "Time and Time Again." A soldier on the brink of death finds himself thrown backward in time — and attempts to change history. But is the past something we can rewrite… or is it already written? In This Episode: The science (and speculation) behind time travel The danger of paradoxes and the famous "butterfly effect" "A Sound of Thunder" – time tourism with catastrophic consequences "Time and Time Again" – can one man alter history? The idea that the past may be fixed — and why that might be comforting Thank you for listening to Ron's Amazing Stories. If you enjoyed this episode, be sure to subscribe, leave a review, and share it with a fellow sci-fi fan. Until next time… stay amazing. Ron's Amazing Stories Is Sponsored by: Audible - You can get a free audiobook and a 30 day free trial at audibletrial.com/ronsamazingstories. Your Stories: Do you have a story that you would like to share on the podcast or the blog? Head to the main website, click on Story Submission, leave your story, give it a title, and please tell me where you're from. I will read it if I can. Links are below. Music Used In This Podcast: Most of the music you hear on Ron's Amazing Stories has been composed by Kevin MacLeod (incompetech.com) and is Licensed under Creative Commons: By Attribution 3.0. Other pieces are in the public domain. You can find great free music at FreePd.com which is a site owned by Kevin. Program Info: Ron's Amazing Stories is published each Thursday. You can download it from Apple Podcasts, stream it on Stitcher Radio or on the mobile version of Spotify. Do you prefer the radio? We are heard every Thursday at 10:00 pm and Sunday Night at 11:00 PM (EST) on AMFM247.COM. Check your local listing or find the station closest to you at this link. Social Links: Main Podcast Site by LibSynThe Blog Site by WordPressFacebook LinkTwitter Link Contact Links: EmailStory Submissions Contact Ron

Part 3 picks up right where we left off in Part 2. While she was still working that real estate job, Sonia was treating dating like a part-time job. She signed up on several dating sites (this was before swipe apps like Bumble). She went on many awkward coffee dates. Then a friend introduced her to a guy, and the two hit it off right away. They were inseparable from the moment they met, in 2008. They moved in a couple months later. In 2010, they got married, and had a kid shortly after that. But in the middle of all this amazing life shit, Sonia was smacked with a breast cancer diagnosis. She was 38. Sonia had never necessarily wanted to be a mom. She was always happy for friends when they started having kids, but figured it just wasn't in her stars because she wanted a different kind of life. But her new partner and eventual husband told her it was a deal-breaker, and she figured, Why not? They moved from Dogpatch to Glen Park around this time, because they wanted to raise their kid in The City but needed more space to do that, and the options weren't great. Their son was born and they began raising him, eventually getting him into SF public schools. When the kid was about two-and-a-half, Sonia and her husband started to wonder whether he was on the autism spectrum. A positive diagnosis was made eventually. Sonia praises The City and its programs for kids with special needs. And, like some kids on the spectrum, he's obsessed with public transportation, so he's in the right place. (If you listen all the way through to the end of this episode, you'll hear his recording of a BART announcement.) Like most of us, the pandemic did a number on Sonia's little family. Their version went like this: The marriage did not survive. Ed note: We had Sonia and her then-husband on for our Valentine's 2019 episode. After the break-up, at Sonia's request, we took that episode down. She says that before the pandemic, she imagined that the relationship was as good as it gets. In hindsight, she thinks maybe her second breast cancer diagnosis, after her son was born, broke her husband. Up to that point, he'd been a great partner and excellent dad and solid caretaker for his wife through her first bout. The second diagnosis, coupled with a worldwide pandemic, inspired him to do not great things. Sonia tried to save the marriage, but some of her girlfriends took her down to the Madonna Inn and, as she puts it, "shook the shit out of" her. Her new reality meant figuring out what to do every other weekend when she didn't have her son. It was a lot of going to movies solo and doing 1,000-piece jigsaw puzzles while listening to podcasts. The road to healing involved early stints on dating apps, but usually only to wake up the next morning and immediately pull back. She's really learned to love her alone time. We rewind back to 2015 to talk about the origins of a big part of Sonia's life today—podcasting. She and her now-ex-husband launched Old Movies, New Beer, a show where they'd drink a beer that was new to them while chatting about some film from the past. She enjoyed it, but he fell off quickly. A friend from her movie theater days hit her up to do a show about movies, and so Dorking Out was born. It also didn't last long, but in that time, Sonia started discovering podcasts she liked. There was F This Movie and Book vs. Movie. One of the Book vs. Movie hosts was Margo Donahue, and Sonia was a fan. She reached out and the two started following each other. The love was mutual. Dorking Out had Margo on as a guest and she and Sonia gelled so well, her co-host essentially became a third wheel. When he left for unrelated reasons, she kept having Margo come back on the show. Margo slid in to become the show's new co-host. The two became as close as you can living across the continent from each other. One day, Margo shared an idea she had for a new show. She wanted to call it Seriously, Fuck That Guy. It was amid the Me Too Movement, and they'd talk about whatever piece of shit man they wanted (think: Kevin Spacey or Harvey Weinstein). But every episode would end with someone who's not an asshole. Sonia was in, no question, but she thought maybe they needed a different name. It was early 2017, and What a Creep was born. Early episode creeps included Lance Armstrong and Newt Gingrich, someone Sonia considers an OG creep. When Sonia and her ex split up, Margo was her main support. They continued doing What a Creep until 2025, when Margo suddenly passed away. They were supposed to record one day last year and Margo didn't show up. Sonia called and texted mutual friends and eventually called NYC police. Sonia had to decide whether to keep What a Creep going. She settled on having rotating guest hosts on (Erin of Bitch Talk Podcast was on recently to talk about Dick Cheney; we're in talks to have me on soon as well, which I'd be stoked to do). She appreciates the community that has developed over the years around the show. She loves it so much that it's what keeps up her presence on Facebook. I ask Sonia whether there are any San Francisco creeps we might hear more about in the future. She mentions our mayor and our governor while saying that the show leaves space for so-called roads to redemption. I like that. But I also suggest doing episodes on AI or the stupid-ass billboards all over The City. In contrast to that, we end the episode with Sonia talking about the kind of tech we do want. We recorded this episode at Rosamunde in The Mission in January 2026. Photography by Jeff Hunt

Trump's Iran War Is Rapidly Escalating Into Full World War! US SF Soldiers Are Already On-The-Ground In Northwest Iran As Washington/Israel Prepare To Break The Country Up

History of the Bay Podcast Ep. 142: Shortkut is a legendary DJ from Daly City. He's a member of Invisibl Skratch Piklz with Qbert, Mix Master Mike, Apollo and more; and also part of Beat Junkies along with J Rocc, Babu, and Rhettmatic. Shortkut got his start doing mobile DJing at garage parties and eventually ended up rocking venues at the height of San Francisco's club scene. Not only does he blend and rock parties, but he's a certified scratch DJ and turntablist. In 2024 he suffered a life-threatening stroke that left him partially paralyzed, but he bounced back through physical therapy and continues to DJ around the world.--Join the Patreon: https://www.patreon.com/dregsoneSubscribe to our clips channel: https://youtube.com/@UCYR1ormrdd-9gFSUoZgv3wA --For promo opportunities on the podcast, e-mail: info@historyofthebay.com--History of the Bay Spotify Playlist: https://open.spotify.com/playlist/3ZUM4rCv6xfNbvB4r8TVWU?si=9218659b5f4b43aaOnline Store: https://dregsone.myshopify.com Follow Dregs One:Spotify: https://open.spotify.com/artist/1UNuCcJlRb8ImMc5haZHXF?si=poJT0BYUS-qCfpEzAX7mlAInstagram: https://instagram.com/dregs_oneTikTok: https://tiktok.com/@dregs_oneTwitter: https://twitter.com/dregs_oneFacebook: https://facebook.com/dregsone41500:00 Recent party with Qbert02:32 Growing up in Daly City 06:04 Early hip-hop DJs15:52 Filipinos & DJing20:52 Learning how to DJ23:44 Mobile DJing & garage parties28:03 Invisibl Skratch Piklz34:21 SF clubs in the ‘90s38:56 Differences in today's club scene45:23 ISP vs X-Ecutioners47:48 Beat Junkies55:38 DJing for rappers?57:58 New generation of DJs 1:04:01 Touring with LL Cool J1:07:14 Recovering from a stroke1:17:30 New ISP album

Most Colorado investors have never seriously considered industrial real estate. At first, it feels like a different world — big buildings, commercial tenants, unfamiliar terminology. But once you understand how the asset class actually works, it starts to look a lot like the multifamily investing you already know, just with fewer headaches. To start, industrial real estate covers a wide range. On one end you have a 2,000 square foot bay rented to an HVAC company. On the other end, million square foot distribution centers broken into 20,000-50,000 square foot bays. For individual investors, though, the sweet spot is the middle — small-bay multi-tenant buildings in the $1-4 million range where spaces run 1,500 to 5,000 square feet. These attract the same kinds of small businesses that keep renewing: trade contractors, lumber companies, light manufacturers. Tenants that need space and don’t want to move. And in a triple net lease, those tenants pay your taxes, your insurance, and your maintenance costs. You collect the check. That’s where Drew Williams comes in. Drew is an industrial and retail broker at North Peak Commercial Brokers in Denver. Over the last four years he’s focused on exactly this segment of the market — multi-tenant industrial along the Front Range — and in this episode he walks through the asset class from the ground up. Deal types, tenant profiles, how to read a cap rate, what flex industrial actually means, and how to think about risk when you’re underwriting a business instead of a household. From there, the conversation turns to where the 2026 Denver industrial real estate market stands right now. Prices have pulled back. The ask-to-close gap has averaged 15% over the last 12 months. Meanwhile, rents have held flat at $12-13 per square foot triple net while expenses have climbed. On top of that, lenders now want 35-40% down and a 1.3 DSCR. It sounds like a tough market — and in some ways it is. Still, Drew explains why these conditions are also creating real opportunities for buyers who know how to find them. In This Episode We Cover: What industrial real estate actually is — deal types, tenant profiles, and the difference between small bay, flex, and single tenant The three buyer profiles — passive investor, owner-user, and syndication group — with real Denver deal examples How triple net leases work and why tenants pay taxes, insurance, and maintenance Where the 2026 Denver industrial real estate market stands — cap rates, rents, price per square foot, and the 15% ask-to-close gap The value-add playbook — converting gross leases to triple net and recovering expenses landlords have been absorbing for years The three physical features that make a Denver industrial building significantly easier to lease and sell The zoning trap that turns a promising purchase into an expensive mistake If industrial real estate has ever been on your radar but felt too unfamiliar to pursue, this episode is the place to start — and if you’re already looking at the 2026 Denver industrial real estate market, Drew gives you the ground-level data to move with confidence. Watch the YouTube Video https://youtu.be/YNNetKjReDg Timestamps 00:00 – Welcome & Introductions  01:30 – Drew’s Background – Tech consulting to leading North Peak’s industrial team  02:44– What Is Industrial Real Estate? – 2,000 sq ft to million sq ft complexes  03:50 – 3 Buyer Profiles – Passive investors, owner-users, and syndications 05:44 – Stabilized vs. Value-Add – Two main investment strategies  06:58 – What Is Flex Industrial? – Office-to-warehouse ratios explained ' 08:50– Underwriting a Stabilized Deal – 7% cap, 35-40% down, 1.3 DSCR 15:06– How Long Should You Hold? – 5-7 year holds and lease value decay 22:52 – What’s Driving the Price Pullback? – 15% ask-to-close gap, flat rents at $12-13/sq ft  24:22– Value-Add Playbook – Gross to triple net conversions and deferred maintenance  26:56– Lease-Up Timelines – Why deals now take 4-8 months to fill  29:35– Where the Opportunities Are – Yard space, clear heights, and access 35:55 Policy & Market Uncertainty – Why most investors are still holding  40:38– Energize Denver – 30,000 sq ft threshold and compliance fines  41:58– Multifamily Investors Moving to Industrial – Why triple net is winning 43:06 – Advice for Transitioning Investors – Start small-bay multi-tenant, know your zoning  48:15 Risk Tolerance – Matching your investment profile to the right deal 52:20 Zoning Pitfalls – How a change of use can kill a deal  55:42 – How to Reach Drew – 303-917-5232 | drew@northpeakcre.com Connect with our Guests Drew Williams: drew@northpeakcre.com 303-917-5232 Links in Podcast NorthPeakCRE Drew referenced two active North Peak listings during the conversation — both available now in the Denver metro: 3600 S Huron St, Englewood CO 80110 — $1,750,000 8,000 SF brick flex building near the Santa Fe and 285/Hampden junction. Includes a 4,500 SF fenced yard, two drive-in doors, and a new 5-year NNN lease in place. Strong 1031 exchange candidate with long-term redevelopment upside. 2610 S Raritan Circle, Englewood CO 80110 — $9.90/SF 10,200 SF industrial available for lease. 18-foot clears, two drive-in doors, two dock doors, I-2 zoning. Works for an owner-user or investor with a tenant ready to move in. Energize Denver — Check If Your Building Is Covered

Matt and John react to NFL Draft Combine winners and losers in a four round SF, TEP, PPR mock draft patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Adrian has a bunch of UFO experiences and cat pics to share with us. Jen is astral projecting in her dreams and helping lives pass over. Heidi had some spooky stuff happening in her SF apartment. Sam scared her dorm mates while playing with ouija board. Ashley went on a ghost tour/bar crawl in Nashville. Andrea remembers the first dream she ever had. Please send us your own true paranormal experiences in either a voice memo or e-mail to funnyfeelingpod@gmail.com.
 SpectreVision Radio is a bespoke podcast network at the intersection between the arts and the uncanny, featuring a tapestry of shows exploring creativity, the esoteric, and the unknown. We're a community for creators and fans vibrating around common curiosities, shared interests and persistent passions.
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