Podcasts about Neon

The digital comics market has evolved massively in the last few years. It's time we had a proper conversation about our relationship with it, and we're eager to have it with Comixology veterans and Neon Ichiban founders David Steinberger and Chip Mosher. With San Diego Comic-Con International in full swing, we brought them onto the show to discuss their evolution with digital comics and what they're delivering to readers AND collectors stumbling around the con floor. They recently launched Neon Ichiban 2.5. This next chapter in their development promises huge growth to their community. Steinberger and Mosher are bringing the convention environment to their platform. Meet your favorite creator. Get a signature. Walk artist alley and discover something new. Hang out with the like-minded and get nerdy together. Neon Ichiban 2.5 offers digital signatures, commissionable remarques, community profiles, reviews, reading lists, collections, and a whole lot more. We get into it all with David Steinberger and Chip Mosher. And we talk about why San Diego Comic-Con is still an essential place to present digital comics. Today's podcast is Part Two in our San Diego Comic-Con coverage. Make sure you listen to Part One with Christopher Cantwell, all about IDW Publishing's upcoming Star Trek relaunch (speaking of fandom and community). Visit Neon Ichiban, browse around, and follow them on their socials (Instagram and Bluesky). Other Relevant Links to This Week's Episode: Subscribe to the Comic Book Couples Counseling YouTube Channel Watch The Stacks, Comic Creators Name Their Favorite Comics Previously on CBCC: Christian Ward on The Forever Home Comic Book Club: Spider-Man: Brand New Day at Meanwhile...Coffee in Herndon, Virginia, on 8/2 at 3:30 PM Comic Book Film Club: Nausicaä of the Valley of the Wind at the Alamo Drafthouse in Winchester, Virginia on 8/9 at 5:00 PM Final Round of Plugs (PHEW): Support the Podcast by Joining OUR PATREON COMMUNITY. And, of course, follow Comic Book Couples Counseling on Facebook, on Instagram, and on Bluesky @CBCCPodcast, and you can follow hosts Brad Gullickson @MouthDork & Lisa Gullickson @sidewalksiren. Send us your Words of Affirmation by leaving us a 5-star Review on Apple Podcasts. Continue your conversation with CBCC by hopping over to our website, where we have reviews, essays, and numerous interviews with comic book creators. Podcast logo by Jesse Lonergan and Hassan Otsmane-Elhaou. This Week's Sponsors The Future is Calling! 2000 AD is the Galaxy's Greatest Comic, with new issues published every single week! Every 32-page issue of 2000 AD brings you the best in sci-fi and horror, featuring characters like Judge Dredd, Rogue Trooper, and more. Get a print subscription to 2000 AD and it'll arrive to your mailbox every week - and your first issue is free! Or subscribe digitally, and you can download DRM-free copies of each issue for only $9 a month. That's 128 pages of incredible comics every month for less than $10! Head to 2000AD.com and click on ‘subscribe' now – or download the 2000 AD app and start reading today! What happens when the love of your life is buried on the other side of the country, and you're a ghost who can't leave your grave? That's the beautifully haunting setup of Till Death, a new romantic horror-comedy from Michael Schwartz, Rachael Schaefer, and artist Gaia Cardinali now on Kickstarter from Clover Press! Vivian has waited decades for her husband to join her in the afterlife. But when she discovers he's been buried across the country, she makes a deal with Mack, a man whose near-death experience allows him to see ghosts. We've read Till Death, and we absolutely loved it. It's a bold, original four-color romance, fitting snugly inside comics' most unsung genre. Till Death is on Kickstarter now. Visit the campaign and make your pledge today! Third Eye Comics is opening its biggest store ever: Third Eye 97, a 10,000-square-foot comic, game, and collectibles mega-store inside a former Walmart in Glen Burnie, Maryland, with the doors opening July 25th. Grand opening month goes huge with a Rob Liefeld signing at the new flagship on July 31st, the legend behind Youngblood, Deadpool, and Cable, live and in person. Can't make it to Maryland? The entire Third Eye world ships to your door at thirdeyecomics.com: new releases, back issues, games, and exclusives, sent anywhere with Third Eye Ships. See Third Eye's massive inventory while watching THE STACKS and then order those same books your favorite creators talk about online! Use codeword: STACKSORDIE for 15% off your order! The Alamo Drafthouse in Winchester, Va is not only unlike any theater in America; it's unlike any Alamo Drafthouse. It's a franchise. In fact, it's the first Alamo Drafthouse location outside of Texas. On July 5th, their Film Club is celebrating America's 250th with the 85th Anniversary of the Greatest Movie Ever Made, Citizen Kane! They'll have an encore screening of Kane on Wednesday, July 8th, too. Film Club is great, but so is their Psycho Cinema series hosted by Faye. On July 14th, they're screening truly one of the best bad movies of all time, Samurai Cop. Golly, have you even lived until you've seen Samurai Cop on the big screen? I think not. Get your tickets today!

"Her Private Hell" is a 2026 science fiction horror thriller film produced and directed by Nicolas Winding Refn, from a story he wrote and a screenplay he co-wrote with Esti Giordani. It stars Sophie Thatcher as a troubled young woman who searches for her father as a mysterious mist engulfs a futuristic metropolis, unleashing a deadly and elusive entity. Her quest collides with an American G.I. (Charles Melton) who's on a harrowing odyssey to rescue his daughter from hell. The film also stars Havana Rose Liu, Kristine Froseth, Shioli Kutsuna, Aoi Yamada, Dougray Scott, Diego Calva, and Hidetoshi Nishijima. It had its world premiere out of competition at the 2026 Cannes Film Festival, where it received mixed reviews, but its visuals, performances, and the score by legendary Italian composer Pino Donaggio were praised. Thatcher, Melton and Winding Refn were all kind enough to spend some time talking with us about their work and experiences making the film, which you can listen to below. Please be sure to check out the film, which will be released in theaters by NEON on July 24th. Thank you, and enjoy! https://youtu.be/r4ENIJpyPLo https://youtu.be/-52ywXkEti0 Check out more on NextBestPicture.com Please subscribe on... Apple Podcasts - https://itunes.apple.com/us/podcast/negs-best-film-podcast/id1087678387?mt=2 Spotify - https://open.spotify.com/show/7IMIzpYehTqeUa1d9EC4jT YouTube - https://www.youtube.com/channel/UCWA7KiotcWmHiYYy6wJqwOw And be sure to help support us on Patreon for as little as $1 a month at https://www.patreon.com/NextBestPicture and listen to this podcast ad-free Learn more about your ad choices. Visit megaphone.fm/adchoices

The sequel to 2024's Most Excellent Whizzbang American Roller-Coaster Adventure! This time: the South. Charlie and Luther discuss their trip in a pickup truck from Richmond to New Orleans, via the Rappahannock Oyster Company, Busch Gardens Williamsburg, Monticello, the Michie Tavern, The Andy Griffith Show, The Tail of the Dragon, Knoxville, Nashville, Shiloh, the Jug's One Stop gas station, the Bass Pro Pyramid, Graceland, Johnny's Drive-in, and Vicksburg. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In episode 123 of The Neon Crew Podcast, Kyle and Mac discuss big disasters, the idea of American values through adversity, and the confusing existence of Randy Quaid.LISTEN TO PODCAST HERE:YouTube: https://www.youtube.com/@theneoncrewpodcast/featured Spotify: https://open.spotify.com/show/3AI17IdYnujCrtSc7M5EKG?si=58d599af20514ae8 Apple Podcasts: https://podcasts.apple.com/us/podcast/the-neon-crew-podcast/id1585795358SOCIAL MEDIA:Facebook: https://www.facebook.com/NeonCrewPodcastYouTube Community: https://www.youtube.com/@theneoncrewpodcast/community Instagram: https://www.instagram.com/neon_crew_podcast/ MERCH: https://www.etsy.com/shop/TheNeonCrewPodcast?ref=shop-header-name&listing_id=1374844203&from_page=listing Music by Gideon HunterGideon's Channel: https://www.youtube.com/@wakerisefall Logo design by Lauren HunterLauren's Instagram: https://www.instagram.com/pineandsun/?fbclid=IwAR1zgGnVTNcnK6lji2A5NhDj-NCmD3f1PLqj1ckjr220HiWvsFJisfy9n8g Films covered on the podcast:https://boxd.it/UKmGq Kyle's Letterboxd profile:https://letterboxd.com/NeonKyle/ Timestamps:00:00 | Intro13:01 | Independence Day1:33:13 | The Patriot2:44:29 | Kyle's recommendation for episode 124

Live Recorded Set from VirtualDJ Radio ClubZone

Live Recorded Set from VirtualDJ Radio Hypnotica

What does it take to write the very first check into a company that has almost nothing to show yet, sometimes not even a finished idea?Afore Capital helped invent the pre-seed category. When Gaurav Jain and Anamitra Banerji started the firm ten years ago, "pre-seed" was almost a slight, a label for founders who couldn't raise a proper seed round. They set out to build the world's largest pre-seed fund anyway, closing $47 million on a $40 million target, and every fund since has closed above plan. Afore now runs more than $500 million across four funds, with top-quartile DPI on the first three. The idea has become so mainstream that when Sequoia launched its latest fund, it said, "I guess we're pre-seed investors too."The real substance of the conversation is how Gaurav thinks. He is clear about what matters most in venture, and the order tends to surprise people. Being in the very best companies matters more than anything else, ownership comes after that, and the entry price that so many investors fixate on matters least, because fifty per cent of zero is still zero. He is also convinced that the genuine bottleneck is talent. There is a great deal of money in the world and very few people who can build something truly large, which is why at the earliest stage founders tend to choose their investors as much as investors choose them. You give a founder a million dollars with no collateral, and then you still have to convince them to take it. A pre-seed pitch, he says, is almost entirely storytelling with very little data behind it.If you want to understand how the earliest checks actually get written, and what it really costs to say no, this episode is worth your time.00:00 - Trailer01:00 - From Dehradun to Google to starting Afore02:08 - The Waterloo co-op that talked him out of every job03:18 - Back when "pre-seed" was an insult05:44 - When Sequoia said "I guess we're pre-seed investors too"07:26 - Afore's three products, and the experiments that failed09:01 - Hightouch was a travel company when they invested11:02 - Goldcast: no visa, no money, funded anyway12:07 - The through line is always the team14:44 - The Ramp miss17:24 - "Founders pick us more than we pick them"18:45 - The constraint isn't capital, it's talent22:24 - The Solana miss, when it was still Loom Protocol24:46 - Ramp's Super Bowl ad, the buses, his wife's business25:32 - What he looks for in founders28:50 - Coachability, happy ears, and the Mom Test31:28 - The biggest mistake: falling in love with the idea35:04 - The three things that matter, and "50% of zero is still zero"39:25 - "100% storytelling, 0% data"41:25 - Investing in India, and the fear of being dumb capital44:41 - "Sign the deal before Monday"47:26 - One engineer now does the job of 2051:43 - Raising from LPs, the undiscussed part of VC-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

Time marches on! You can almost hear the cadence! I DON'T KNOW, BUT I BEEN TOLD! THESE PODCAST HOSTS ARE MIGHTY OLD! This week, El'Ahrai and John bring reviews of "The Invite" and "Evil Dead Burn"! Plus a beloved trilogy looks to be expanding, video picks, questions, answers, and so much more! YOU DON'T KNOW WHAT YOU'LL BE MISSIN'! IF YOU DON'T DOWNLOAD AND LISTEN! Any man that'd leave you oughtta be monkey-stomped and have his brains mailed back to his mother.

What does it actually take to build a robot that cleans your home when everyone before has failed?Matic is a home robot that sweeps and mops your floors, navigating entirely with cameras, no LIDAR. It shipped its first unit in 2024 and has since sold 6,000 units at ~2,000 a month, almost entirely by word of mouth. And is now the largest consumer robotics company shipping in the United States.Navneet Dalal (a computer-vision pioneer who co-invented HOG) and Mehul Nariyawala met building Flutter, a gesture-recognition app that became #1 in 72 countries and was acquired by Google, where they then worked on Nest cameras and shipped one of the first deep learning algorithms in the wild. Matic is the company they decided would be their last: they wrote "Not For Sale" on the wall on day one and built it to last 20 to 30 years.Their bet was deliberately contrarian. They chose the "unsexy" floor-cleaning market, a category with a net promoter score of -1 that people keep buying anyway (21 million robot vacuums sold in 2024), because entering an existing market beats creating a new one and because it's the foundation for true indoor autonomy. Then they put roughly $35 million of their own money in, about 70% of their net worth, with no plan B.Along the way they lay out a full worldview: why robotics is 100x harder than software (the demo is only the first 20% of the work); why humanoids doing your chores are still 5 to 20 years away (the data problem), why no consumer hardware sells above $2,000; and the skin-in-the-game philosophy captured by his late father's advice: "Sell your home if you have to, but keep the company alive."If you're excited about how home robots actually get built and what it really takes to bet everything on hard tech, this episode is for you.00:00 - Trailer01:08 - When they quit Google to start Matic03:30 - Solving home cleaning with cameras only — no LIDAR04:46 - The $35M bet: funding Matic themselves07:36 - What a "level 5" robot in your home really means08:00 - Why they started with floor cleaning — on purpose09:45 - The rule: never create a new market with your first product10:02 - iPod, iPhone, Tesla — all entered existing markets11:38 - Why new hardware gives you only one shot13:02 - "Make something people NEED, not want"16:25 - Why the demo is only 20% of robotics18:50 - Teaching a robot like raising a child21:30 - How far are humanoids from real homes?22:22 - The data problem: "500 years of driving data a day"22:56 - 90% in the lab, 60% in the real world26:49 - Why no consumer device sells above $2,00027:38 - Would you buy a $10,000 humanoid — for what?28:47 - "History rhymes": General Magic to the iPhone29:38 - Earning trust after 20 years of broken robot promises30:31 - Shipping the first robot30:45 - 6,000 units, all word of mouth, zero marketing31:10 - Why they're US-only for now 31:50 - The investors: Sutter Hill to the Collison brothers33:20 - Two companies, both acquired by Google35:00 - The Flutter story: #1 app in 72 countries35:25 - Why nobody believed machine learning worked in 201138:40 - Microsoft Kinect: 8 million units in 60 days40:30 - The Google acquisition — and the $35M number44:40 - The near-death moment: switching to NVIDIA53:10 - iRobot's bankruptcy and what it means for Matic53:55 - The real scale of robotics: 21M robot vacuums a year57:45 - Putting 70% of their net worth on the line58:40 - His father's advice: "sell your home, keep the company"-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram:   / theneonshoww  LinkedIn:   / beneon  Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn:   / siddharthaahluwalia  Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

We are featuring the first episode of a new series from Rusty Quill: Rez HighIn the ruins of what was once a place called Yorkshire, sits the town of River Mill.Jo-C, Dogwood, and Reflex discover a relic of the past while on a scavenging mission.Content Notes:- mild innuendo- bullyingTranscripts: https://shorturl.at/pJQV7Neon Inkwell: https://shows.acast.com/neon-inkwell Next episode: https://shows.acast.com/neon-inkwell/episodes/neon-inkwell-rez-high-2-class-action Into and Outro by Shahan HamzaShowrunner Elizabeth MoffattDirected by Lucy WrayWritten by Brendon ConnellyProduced by April SumnerExecutive Producers Alexander J Newall & April SumnerFeaturingOlivia Hirst as Jo-CLozza Gilbert as ReflexGeorge Bunting as DogwoodChristine Walsh as Mrs. SevenKazeem Tosin Amore as HeadBeth Alsbury as LiviaRyan Hopevere-Anderson as GroanWilliam Kilgour as QuartzShahan Hamza as KametTyreke Leslie as Masc NPCsBeth Eyre as Fem NPCsDialogue Editor and Sound Designer – Katharine SeatonMastering Engineer – Catherine RinellaMusic by Katharine SeatonSFX from Katharine Seaton, Soundly, Soundsnap, 13FPanska_Marval_Lukas; Elenalostale; JotrainG; kyles and previously credited artists.Check out our merchandise available at https://www.redbubble.com/people/RustyQuill/shop and https://www.teepublic.com/stores/rusty-quillSupport Rusty Quill by purchasing from our Affiliates; DriveThruRPG – DriveThruRPG.comJoin our community:WEBSITE: rustyquill.comFACEBOOK: facebook.com/therustyquillX: @therustyquillEMAIL: mail@rustyquill.comNeon Inkwell is a podcast distributed by Rusty Quill Ltd. and licensed under a Creative Commons Attribution Non-Commercial Share alike 4.0 International Licence.For ad-free episodes, bonus content and more, join members.rustyquill.com or our Patreon.Pre-order FROM THE LIBRARY OF JURGEN LEITNER, a Magnus novel releasing October 27th: rustyquill.com/novel Hosted on Acast. See acast.com/privacy for more information.

How well do you REALLY know one of the most popular fish the USA? What's the science behind its neon blue stripe? Where does it come from? What conditions does it prefer? Katrina and Guy get curious about this freshwater aquarium fish that Americans love so much.

Bible or The Bottle is a country blues music podcast. This is an acoustic, atmospheric, melancholic, and deeply cinematic blues music. The Bottle and the Bible, Tire Iron & Tumbleweed, Blue Smoke Morning, She Left in a Chevy, Half a Candle, The Barber of Tucson, Dry County Heart, Sawdust on the Floor, Moon Over Amarillo, The Tinker's Wagon, Honest Work, The Long Bar at the Edge of Town, Borrowed Time Blues, River Bend Woman, One Good Truck, The Night Jasper Quit Drinking, Cold Coffee and Regret, The Cattle Drive Gospel, Whisky Color Eyes, Hard Soil, Neon and Stardust, The Road That Doesn't End, Blackbird Diner, Until the Last Star Goes. End. This is the perfect background for whiskey sippin', late-night drives, rainy evenings, or solitary daydreaming. Please check this out and enjoy. Thanks for listening to Ken Steele Music.

有道是，“每个音乐人的首张作品，都是 ta 前半生的精选辑。” ……我其实忘了这句话是谁说的了，但这些年里一直在不断地拿出来讲。对于卫柏Neon 来说这句话也完全适用，只不过，措辞可以再轻盈一点。 卫柏Neon 的首作 EP《MeMe Collection》说的不是 meme（梗图），而是 me 和 me，自己和自己。在她做客的这期节目里，我们刚好可以从每首歌里听到一片她的生活：朋友间的评头论足其实充满了爱意，小时候不爱笑的回忆多年后又浮起，与合租室友在疲惫的时刻突然走心……卫柏还贴心地为每首自己的歌搭配了一首喜欢的歌，一点呼应，一点学习和借鉴，还有很多的回忆，都放在了其中。 希望你也能在这期节目里，重拾起生活的一些有所触动的瞬间。 曲目单： (01:13) 卫柏Neon - Skip Dat Step Map (12:47) 宇多田ヒカル - タイム・リミット (Time Limit) (19:17) 卫柏Neon - 你是我的音乐 (31:44) Hi-Posi - You are my music (37:22) 卫柏Neon - 别把我绑架 (51:19) カヒミ・カリィ - Zoom Up! (53:51) 卫柏Neon - 她不说话 (01:00:01) Imogen Heap - Hide and Seek (01:04:34) 卫柏Neon - DooDoo Language (01:10:13) bice - How deep is your love 《周末变奏》开通豆瓣页面，欢迎标记、点评。 → 选曲/撰稿/配音/制作/包装：方舟 → 主题音乐：Yu Su → 题图版式：六花 → 私信/合作联络： 小红书/微博/网易云/小宇宙 @线性方舟 → 《周末变奏》WX听友群敲门群主：aharddaysnight

What's the real difference between dreaming and waking consciousness?  Neil deGrasse Tyson and co-hosts Chuck Nice and Gary O'Reilly sit down with sleep expert Matt Walker to answer fan questions about the most mysterious thing humans do every single night: sleeping & dreaming. What's the science behind your sleep paralysis demon?  NOTE: StarTalk+ Patrons can listen to this entire episode commercial-free here:  https://startalkmedia.com/show/the-dreaming-brain-with-matt-walker/ Thanks to our Patrons Rhagor, Beans, Eric Grant, DOCTOR FN ASTRONAUT, Richard Thompson, Niclas Larsson, Cathy Hayes, SunshineKat Snyder, Brandon, Matt Caldwell, Tim Davies, M.Victoria Delpiano, Heyo13579, Erin McCullough, Shalon Sorensen, Kaydence Johnson, RJ, Dave, Sindre Skybert, Mr. V, Neon lion Blacklight cozylazy, Mary Mitchell, Trip Ni Selo, S. H., Cloud3X, P.M., Dallas, Dan, Getyoducksinarow, David S, Michael Koenig, Jason A, Reg Anderson, Sean Marien, Adeel Rahman, joe hoffmann, Ronald Merrifield, Jesse Miner, David Pazer, Toshi Jordan, Pat Voss, Nicholas Wiseman, Antoine Portes, Colin, David Crouse, Sander van Liempd, Wendy R., J P, Kenneth Cook, Joey, Fixxxer331, Nathan Hinote, Hara Kannajosyula, Heath Horne, Pixtle, Brett M Garabedian, Ryan Alba, Paul Tindall, Tony Stewart, and Stephanie Moore for supporting us this week. Subscribe to SiriusXM Podcasts+ to listen to new episodes of StarTalk Radio ad-free and a whole week early.Start a free trial now on Apple Podcasts or by visiting siriusxm.com/podcastsplus. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The midyear is here! And to mark the occasion, John and El'Ahrai have invited in the effervescently entertaining Cati Glidewell--that's right, The Blonde in Front herself--for a discussion of the Best Movies of 2026 So Far! (The only title on all three lists? You guessed it: "K-Pops!".) Plus! Reviews of "Minions & Monsters" and "Iron Lung"! Plus the usual bits of idiosyncratic delight that make The Neon Movie Bunker the bulwark of popularity you've all come to know and love. You should listen! Turns out I don't need a medal to tell me I'm a good guy. Because if that little kid likes me...how bad can I be?

On this episode of THE HOT MIC, John Rocha and Jeff Sneider talk DC possibly finding its Gorilla Grodd for the Jimmy Olsen series, Dune Part 3 trailer teases an epic for the ages, live action Moana's terrible tracking and Dwayne Johnson's next movie, James Gunn and DC updates after Supergirl fallout, Emmys snubs and surprises, Neon's 'Artificial' deal, The Odyssey reactions, tracking and lies about influencer screenings, Inde Navarette meeting with Marvel and Heat 2 for possible roles, Heat 2 news, Armie Hammer turning on Citizen Vigilante, Denzel's Hannibal is dead, Free Willy remake is in motion and more. HOT MIC MERCH LINK: https://www.bestnametape.com/The-Hot-Mic-Shop-s/4592.htm________________________________________________________________________________________________________________________Chapters:0:00 Intro and Rundown2:02 Free Willy Gets a Reimagining at WB6:11 HBO Cancels V for Vendetta Remake with Pete Jackson, Seeks New Writer10:20 Sneider Confirms Poison Ivy Series Thru a New DC Source12:08 DC Finds Its Gorilla Grodd in Jimmy Tatro for Jimmy Olson Series14:46 James Gunn and Supergirl Fallout Affecting Gunn or Is He Fine at DC?28:35 Emmys Reactions, Surprises and Snubs33:43 Inde Navarette Meets With Marvel for X-Men Movie?, The Rock for Apocalypse42:45 MOANA Looks To Bomb, Is This on Dwayne Johnson?47:00 Heat 2 Casting News Includes DiCaprio, Bale and Stephen Graham50:54 Dune 3 Trailer Talk, Other Trailers From the Week1:01:34 The Odyssey Lies About Barring Influencers at Screenings1:03:45 Netflix Kills Denzel Washington's Hannibal Show1:05:14 Neon Buys 'Artificial' Movie, 1:06:46 Spider-Man Brand New Day Box Office Discussion1:10:00 Streamlabs and Superchat QuestionsFollow John Rocha: @therochasays Follow Jeff Sneider: @TheInSneider Become a supporter of this podcast: https://www.spreaker.com/podcast/the-hot-mic-with-jeff-sneider-and-john-rocha--5632767/support.

James May's Shed Load of Ideas James May takes on humanity's biggest bugbears one ingenious invention at a time. With his trusty engineer, Sim and carpenter, ‘Tony the Tool' in tow, there's no problem too big or small for this tenacious trio! (TVNZ+) Make That Movie Created by and starring stand-up comedian Sam Campbell. Hotshot director Sam scours the country looking for everyday people who have an idea for a feature film. Sam and his elite crew of filmmakers then race against the clock to transform these chaotic ideas into hit movies (Neon). LISTEN ABOVE See omnystudio.com/listener for privacy information.

How do you know whether an AI agent is doing its job or quietly failing in production?Galileo is building the trust layer for AI. Its evaluation and observability platform is how enterprises measure whether the output of an LLM or an agent is good or bad.Galileo started before "LLM" was even a word. When Atin showed his prototype to Stanford's Chris Ré, his own first question was "what is a language model?" Today its customers include Reddit, Airbnb, P&G, Comcast, and six of the Fortune 50. Atin spent a decade in big tech before co-founding Galileo with Vikram Chatterji in early 2021. He worked on the knowledge graphs behind Siri at Apple, then became one of the leads and architects of Michelangelo, Uber's AI platform, that hosts thousands of models across pricing, ETA, and demand.That Uber experience taught him the lesson the whole company is built on; that in AI, observability and evaluation are the real bottleneck, and bad data is catastrophic.As ChatGPT turned every AI output into something a user sees directly, the measurement problem went from academic to mission-critical. So Atin made a contrarian bet: instead of using giant LLMs to judge other LLMs, Galileo built Luna, small 1-3B parameter models that run evals at breakthrough latencies of 100 milliseconds and below.If you are excited about how AI actually gets shipped, trusted, and controlled inside real enterprises, this episode is for you.00:00 - Trailer01:14 - From India to Apple, Uber, and Galileo01:34 - Where the name "Galileo" came from02:38 - Building Siri's early knowledge graphs at Apple03:29 - Becoming an architect of Uber's Michelangelo05:15 - Why every AI output is now mission-critical06:45 - How Atin and Vikram zeroed in on Galileo07:42 - "What is a language model?"09:38 - Building the world's first feature store at Uber11:27 - Language models and tokens, explained simply14:19 - Where the observability insight came from15:53 - Quantifying uncertainty and hallucinations16:36 - The first customers and first use case19:15 - How the product evolved from a data scientist tool23:18 - Why ChatGPT changed everything for Galileo23:57 - The enterprise AI adoption curve, 2021 to 202626:35 - Why they built the Luna model28:32 - Turning LLM "writers" into "calculators"28:51 - Attacking the latency problem31:48 - Luna: the modeling and infrastructure innovation33:09 - What evals are, and why they blew up34:26 - The case for small language models36:58 - What "general reasoning" really means40:39 - AI usage is exploding — and why that matters43:08 - Online vs offline: the "it worked on my machine" problem44:33 - The evals flywheel and evals-driven development46:56 - Galileo in a nutshell47:39 - What real agents in production look like today49:30 - A sales intelligence platform, powered by Galileo50:47 - The agent control product52:12 - Building GTM as a hardcore engineer from India54:43 - Garbage in, garbage out: nailing the ICP55:42 - How the pitch changed from customer 1 to 2057:27 - Why Atin switched from CTO to CPO-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

Wyobraźcie sobie państwo, które w jednym pokoleniu każe swojej elitarnej kaście wojowników oddać miecze, zakłada urzędnikom zachodnie fraki i zaczyna masowo budować stocznie oraz huty. Robi to, bo wie, że w XIX-wiecznym, brutalnym świecie mocarstw można być tylko drapieżnikiem albo ofiarą. Japonia wyciągnęła trzeźwe wnioski z upokorzenia Chin przez Zachód i postanowiła, że nie da się skolonizować. Postanowiła, że sama stanie się imperium. **Wyjątkowa oferta NordVPN ➼ **https://nordvpn.com/HISTORYCZNY Wypróbuj bez ryzyka dzięki 30-dniowej gwarancji zwrotu pieniędzy! ✨

Who is funding the students that India's banks won't touch?Propelld is one of India's largest education-focused lenders, giving loans to roughly 1.5 lakh students every year — matching SBI — with a team a fraction of the size and no branch network. In a single financial year it now disburses more education loans than SBI did in six years of its history.Victor started Propelld in 2016 with a thesis born out of a Milton Friedman paper: a good student should never have to walk away from a good opportunity just because they don't have the money. Propelld hit its stride by going exactly where traditional lenders refuse to — 70% of its borrowers come from tier-3 cities, a segment banks treat as too risky.Instead of chasing the safe 1% of students at IITs and IIMs, Victor made a bet most lenders never make. He built the ability to underwrite the end-use itself — a "Crystal score" for institutes and courses that measures employability and real ROI. The result: NPAs held at ~1%, roughly one-tenth of what banks see the moment they step outside tier-1.Victor has a clear view of where lending goes next. In a post-LLM world, risk, distribution, and fulfillment get radically more efficient — one person already drives ₹50 crore of disbursal a year, and OPEX is projected to fall toward 2% at ₹6,000 crore AUM. His ranking never changes: NPAs first, unit economics second, growth third.If you are excited about how AI is rebuilding lending — and who gets to dream bigger because of it — this episode is for you.00:00 - Trailer00:50 - The two numbers that tell Propelld's story01:55 - Why 70% of borrowers come from tier-3 cities02:21 - How NPAs stay at 1%02:52 - Why education is a great asset class04:04 - Building a "Crystal score" for institutes and courses05:31 - End-use control: why an education loan isn't a personal loan06:27 - Why banks only lend to IITs and IIMs08:36 - Measuring employability to underwrite the end-use10:23 - 10 years at the intersection of fintech and edtech11:46 - Why education financing is only ~5% penetrated17:53 - Do India's graduate really not get a job?21:12 - The 8% data point, and quantifying ROI22:24 - The social mobility no one can price25:39 - From IIT Madras and a global bank to building Propelld27:41 - How the post-LLM world rewires lending30:26 - How fast an institute gets onboarded and a loan disbursed32:12 - Profitable at a ₹1 lakh ticket size34:13 - The financials: doubling revenue, holding costs flat to FY3037:19 - Lending as an ecosystem enabler, not just a loan39:33 - The most valuable courses in a post-LLM world41:40 - The bet on arts graduates as coding gets commoditized43:32 - The Milton Friedman paper that started it all46:53 - 100 investors, and the few who said yes48:33 - Co-founding with school friends since class 650:24 - Settling disagreements over food and Hampi trips51:31 - The most common mistake fintech founders make52:51 - The one metric that ranks above everything: NPAs-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

E draws a good circle, Brian writes backwards, and Ed knows all the birthdays.

The seventh and final director interview Wilson conducted at this year's Hong Kong International Film Festival is with the legendary Taiwanese filmmaker Tsai Ming-liang. Wilson asks one of his cinematic heroes about the state of filmmaking today, his methods for working with actors, and his decades-long collaboration with Lee Kang-sheng.Kiss a melon in our FREE patreon, discord server, and our socials @ www.deepcutpod.com Timestamps:00:00 intro03:42 What do you hope new audiences will take from your films?04:43 Rebels of the Neon god06:20 Tsai and realism07:35 The Hole09:30 Tsai's childhood11:13 Theaters, streamers, and art museums13:24 Video art versus narrative cinema16:15 Fruits and vegetables (props and crops)17:40 Abandoned buildings19:27 Pacing and directing actors21:22 Working with Lee Kang-sheng22:35 Tsai's Deep Cut picks

In episode 122 of The Neon Crew Podcast, Kyle and Mac discuss bananas, how quirky the French are, and the joys of recording in a heat wave.LISTEN TO PODCAST HERE:YouTube: https://www.youtube.com/@theneoncrewpodcast/featured Spotify: https://open.spotify.com/show/3AI17IdYnujCrtSc7M5EKG?si=58d599af20514ae8 Apple Podcasts: https://podcasts.apple.com/us/podcast/the-neon-crew-podcast/id1585795358SOCIAL MEDIA:Facebook: https://www.facebook.com/NeonCrewPodcastYouTube Community: https://www.youtube.com/@theneoncrewpodcast/community Instagram: https://www.instagram.com/neon_crew_podcast/ MERCH: https://www.etsy.com/shop/TheNeonCrewPodcast?ref=shop-header-name&listing_id=1374844203&from_page=listing Music by Gideon HunterGideon's Channel: https://www.youtube.com/@wakerisefall Logo design by Lauren HunterLauren's Instagram: https://www.instagram.com/pineandsun/?fbclid=IwAR1zgGnVTNcnK6lji2A5NhDj-NCmD3f1PLqj1ckjr220HiWvsFJisfy9n8g Films covered on the podcast:https://boxd.it/UKmGq Kyle's Letterboxd profile:https://letterboxd.com/NeonKyle/ Timestamps:00:00 | Intro4:48 | Minions & Monsters1:07:34 | PlayTime2:04:17 | Mac's recommendation for episode 123

Ya llegamos a la mitad de 2026 y había que hacer corte de caja.En este Cinemordida hablamos de las películas que más nos han gustado del año, las que más nos decepcionaron y las que más esperamos para lo que viene: La Odisea, Spider-Man: Brand New Day, Digger, Dune 3 y más.También de los movimientos rarísimos entre Warner, Paramount, Universal y Comcast que podrían cambiar Hollywood en los próximos años.Y sí, también actualizamos el chisme de Artificial: la película de Luca Guadagnino que ya encontró casa en Neon y ahora va directo a temporada de premios.¡Ahora sí! Esta vez toca hablar de lo mejor, lo peor y lo que todavía puede salvar el año.

This week, we're unpacking the major shakeups in Hollywood: why Supergirl flopped at the box office and what that means for the DC universe, plus the explosive rumor that DC Studios is already planning a Bane and Deathstroke film. We also follow the drama of Luca Guadagnino's Artificial, dropped by Amazon MGM but picked up by Neon. And for trailer lovers, we've got sneak peeks at Robert Eggers' Werwulf, Jesse Eisenberg's The Debut, and the magical return of the Owens sisters in Practical Magic 2. Don't miss it!

Most founders build one unicorn. Naveen Tewari built two.InMobi started with a simple bet: mobile would become the world's most important computing platform, and advertising could make it free for everyone. Every Indian VC said no. Naveen flew to San Francisco on a maxed-out credit card and returned with a $7 million round from Kleiner Perkins and Ram Shriram. Later came a $200 million investment from Masayoshi Son. Overnight, InMobi became India's first unicorn. Then he did it again.Glance, built quietly inside InMobi over three years, is now one of the fastest-growing consumer apps in the US, with more than 10 million monthly active users in the US.The thesis behind both companies is the same. The world's most powerful technologies, first mobile and now AI, only reach masses when someone figures out how to pay for them. Naveen believes advertising is that mechanism, and that InMobi is uniquely positioned to subsidise AI access at population scale, just as it helped subsidise mobile a decade ago.If you want to understand how one founder from India has quietly helped shape two technology eras, this episode is for you.00:00 - Trailer00:57 - Why Naveen became a founder03:26 - How co-founders met and came together11:33 - The pivot from mKhoj to InMobi15:02 - Can AI be subsidised for mass consumption?16:12 - Expanding globally before the US18:29 - Which industries can delay entry to US market?20:53 - What is Glance?23:55 - Incubated within InMobi for 2 years25:17 - What changes when you face failure in public?29:10 - How the SoftBank round changed InMobi32:53 - Maxing out credit cards to pay bills38:18 - $7Million Kleiner Perkins & Ram Shriram round43:07 - Hypergrowth journey: Series A to Series C45:41 - $200 million funding from Masa53:31 - Change of VC ecosystem in India54:34 - How building for B2B differs from B2C58:50 - How AI is changing InMobi and Glance-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

This is the 100th anniversary of Route 66 and that has many people traveling the old route and reliving its glory years.  In one town,...

There are lofty shows, and there are other shows. This is certainly one of those two types. El'Ahrai and John review "Supergirl" and "Find Your Friends"! Plus! "Artificial" finds a home, videos are picked, questions are answered and so much more (well, OK, not a LOT more)! Download and listen! Or stream and listen! Or...don't. It's your time, and we're trying to respect that. Can I break through your complacency? Do you have compassion for the people suffering in this war? I'm telling you this war is a crime.

M

How do you get an inbound from OpenAI and Anthropic?Goldcast is the video content platform behind companies like OpenAI, Anthropic, GitHub, Uber and Airbnb, before it was acquired by Cvent in a nearly $300 million deal earlier this year.Palash Soni (Co-Founder and CEO, Goldcast) joins the Neon Show.Goldcast entered one of the most overfunded categories in SaaS. Hopin alone had raised more than $1 billion. This is the story of the decisions that helped Goldcast survive the category and ultimately become one of the biggest MarTech acquisition stories of the last few years.Enterprise customers are won long before they ever sign a contract. We trace that idea through Goldcast's journey, from landing Drift as its first marquee customer and reaching its first $1 million in ARR, to the relationships that quietly compounded over the years and eventually led to an inbound from the likes of OpenAI and Anthropic.We discuss how retention has always been MarTech's biggest challenge and why AI doesn't fundamentally change that. And why acquisition, not an IPO, is the most realistic outcome for most companies in the category.This episode is about winning in a market everyone had written off, and the decisions that turned Goldcast into one of the few companies left standing.00:00 - Trailer00:36 - How Palash caught the startup bug05:51 - Meeting the co-founders08:50 - Fundraising has never been easy for Goldcast10:36 - How we got a term sheet in 2 days12:43 - We quit HBS and they became our first customer18:47 - Customers told us our product looked ugly19:50 - How Drift founder changed the course of Goldcast21:44 - When competitors raised $250 million23:31 - How Goldcast got high-profile angel investors30:33 - The elevator pitch of Goldcast31:06 - When companies in your space are crashing32:36 - Was virtual events even a valid space after COVID?43:15 - How Goldcast won OpenAI44:38 - What led to the acquisition53:33 - One thing Palash would change about the last 5 years56:58 - Founders should define company values58:48 - Why we had an unusually large post-sales team01:01:09 - Retention in MarTech has always been subpar01:04:36 - Is acquisition the only path for a MarTech company?01:09:16 - How Goldcast got great logos01:11:01 - How the three co-founders split roles01:12:05 - If not acquisition, then what?01:14:20 - How founders move to higher ACVs01:16:21 - The ethos of the founding team01:17:25 - The book that changed me-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

Workplace Hazards, Neon Alley Thrills & Handyman Payments ConfessionsBecome a supporter of this podcast: https://www.spreaker.com/podcast/dear-nikky-hidden-desires--6316414/support.

Who powers the cloud infrastructure behind NBC, Warner Bros. Discovery, Olympics, and the Super Bowl?Amagi, built out of an office on Bannerghatta Road in Bengaluru. What started there grew into a company that went public at an $825 million valuation and today has a market cap of over $1.3 billion, earns 73% of its revenue from the US, and proved that world-class enterprise technology can be built in India and sold to the world.Co-founders Srividhya Srinivasan and Baskar Subramanian take us back to the days after selling their first startup to a NASDAQ-listed chipmaker, when they landed on an idea almost nobody in India's broadcast industry believed in: regionalizing satellite TV ads.That business grew to ₹180 crore in revenue. Then the founders made a bold call: "Enough of this hardware mess. We'll host only on the cloud." It meant shutting down an 8 year old profitable business to back a cloud platform that was barely making a few crores. That decision transformed Amagi into the company it is today.18 years later, Amagi went public, as a strong example of building a truly global enterprise software company from India. But the IPO itself was far from an obvious decision. The founders share why going public was the right choice despite not needing capital.This episode will tell you how category-defining companies are built.00:00 - Trailer01:00 - How three college kids became founders04:55 - The startup idea validated by a palmist07:10 - How founders split roles (w/o designations)11:04 - What Amagi 2.0 does14:29 - Bannerghatta Road runs Olympics for the US15:54 - Only 10% of TV networks are on the cloud16:50 - Why shut down a profitable business?21:25 - Why one co-founder moved to the US28:06 - Did Amagi really need the IPO?31:10 - What is Amagi 2.0?36:04 - Selling to the US: then vs. now40:44 - How NBC signed with Amagi43:56 - How intent is measured through contracts46:58 - 5 major decisions that changed Amagi52:08 - How AI is changing Amagi57:45 - Being the CTO of a public company1:02:57 - US vs India Market: US is fast to experiment1:04:48 - Enterprises Need Human Touch1:11:12 - Cloud and TV: No one Believed1:13:34 - What will Happen to Hollywood-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Nansi on:LinkedIn: https://in.linkedin.com/in/nansi-mishraX: https://x.com/nansi_mishra-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

Clarence, Monday and Doc Miller descend into the darkness of the Psy Wilds.The cavern is endless. The drop is impossible. And the deeper they go, the stranger things become.Pink shimmers ripple through the void, pulling the crew from one reality to the next. Sharks. Astronauts. Alien cats. Hotdog store owners. Old ladies. Pirates. Even clouds.And as the boundaries between dreams and reality begin to dissolve, one question becomes impossible to ignore:Whose mind are they trapped inside?PLAY THE DUST WORLD RPG NOW:We've released the epic RPG Dust world and we want your help. Dust World PBTA is RPG Empire's sci-fi western game that's simple, fast, and Powered By The Apocalypse. Are you ready? Enter The Gun-Filled Lands Of An Obliterated Civilization. Play as gunslinging anime-inspired heroes on their mission to discover the truth behind the lost civilization and its technology.GET THE GUIDE NOW:https://www.therpgempire.com/shop/p/b2ck9ai8u8d7i6j5xs48oojt742uq2Dust world RPG Podcast is an actual play Role-playing podcast like the Adventure Zone Podcast or Critical Role. The setting is a sci-fi western a few hundred years after a great war burned the earth and a virus called white horse dissolved most organic matter into dust creating the wastelands.Dust World RPG is a Powered By The Apocalypse game. Dust World is a Tabletop Role-Playing game created by Paul Parnell Copywrite 2020. The setting was created by Paul Parnell and Michael Yatskar. The game was written by Paul-Thomas Parnell and Dumaresq de Pencier.OTHER PROJECTS FROM THE RPG EMPIRE:Strangers in the Pines: A Monster Of The Week actually play roleplaying podcast inspired by things like Gravity Falls, Stranger Things, and Fringe. It takes place in a small strange town called Pine Forge nestled in the Blackwood national park in Northeast Oregon, USA, and follows, the exploits of 3 unusual high school students as they try to unravel the mysteries of the Strangers in the Pines.https://www.therpgempire.com/strangers-in-the-pinesCONNECT WITH US:Join our Discord Server to chat with us and talk all things RPGs: https://discord.gg/2jnyGv9Follow and send us DMs on Instagram: @theRPGempireJoin the Empire!

"I think what I know now is to be a little more slow." "My style was to steal the best from Japan and the U.S." "What I would do is pick your fights." "Someone who can make a decision without all the information." "A leader can function gracefully with an abundance of ambiguity." Robert Roche is the President and CEO of Oak Lawn Marketing, the company behind the Shop Japan brand. His career in Japan began as an exchange student at Nanzan University in Nagoya, followed by law school in Denver and further study in Nanzan's law department. He returned to Japan without a conventional corporate career path and built his business through persistence, experimentation and a willingness to learn from failure. Early ventures in importing were unsuccessful, but they led to the creation of H&R Consultants and eventually Oak Lawn Marketing. Roche helped pioneer the infomercial and direct-response television shopping model in Japan, building a major business from Nagoya before it became widely known in Tokyo's foreign business community. He later established Acorn International in China, adapting a related television-shopping model to a very different market. His career reflects deep adaptability across Japan, China, media, retail, entrepreneurship and large-company partnerships, including working with NTT Docomo as a major shareholder in the business. Robert Roche's business story is a powerful lesson in entrepreneurial leadership, cultural adaptability and decision-making under uncertainty. His path did not begin with a polished strategy, venture capital or a prestigious corporate appointment. It began with an exchange programme at Nanzan University in Nagoya, an interest in Japan, a willingness to learn Japanese and an instinct that he could build something of value despite having no obvious roadmap. His first ventures were failures. Imported clamshells for cultured pearls did not work. Neon clocks did not work. The experience gave Roche an early and memorable lesson: buying products is easy; selling them is difficult. Rather than treating these setbacks as reasons to retreat, he used them as practical education. That resilience later became central to the development of Oak Lawn Marketing and Shop Japan. The company's breakthrough came through television shopping. Roche initially sold parallel-imported products such as Tiffany goods and Lands' End bags, before being introduced to Japanese television retailing. He had to learn every part of the operation: presenting products on television, answering calls, packing goods, applying shipping labels and even cleaning the office. The experience gave him an unusually grounded understanding of direct-response retail. It also demonstrated that leadership credibility is built when leaders understand the real work of the organisation. As the business grew, Roche and his colleagues recognised an opportunity in imported infomercials. They secured products that were already successful overseas, localised them for Japan and bought television time to reach Japanese consumers directly. Oak Lawn Marketing became a Japan market-entry specialist, acquiring exclusive rights to successful products and adapting media, language, labels, customer service and fulfilment for the Japanese market. Growth created new leadership challenges. Roche describes a company that scaled quickly, often without elegant systems or conventional management infrastructure. Recruiting was difficult in Nagoya, and hires from elite corporations often struggled with the radically different pace, ambiguity and hands-on demands of an entrepreneurial company. He learned that individuals needed the right cultural bridge before moving from highly structured institutions into a fast-moving, experimental business. Roche's leadership evolved over time. Earlier in his career, speed, impatience and relentless momentum helped propel the company forward. Later, he realised that patience, long-term planning, automation and more thoughtful communication were equally important. His experience in China reinforced this lesson. Japan required encouragement for people to take initiative; China often required leaders to channel intense entrepreneurial energy. He came to see the two markets as yin and yang: both dynamic, but requiring very different leadership responses. His ultimate leadership definition is especially relevant for executives in Japan: leadership is the ability to make decisions without complete information and to function gracefully amid ambiguity. It is a lesson that combines entrepreneurship, cultural intelligence, decision intelligence and the humility to understand that there are multiple valid paths to the same goal. Q&A Summary What makes leadership in Japan unique? Leadership in Japan requires an appreciation of process, relationships and organisational harmony. Formal authority alone is rarely enough. Effective leaders need to understand how nemawashi, informal consensus-building, supports later decisions; how ringi-sho processes formalise approval; and how trust is often built through consistent behaviour rather than forceful declarations. Roche's experience shows that Japanese workplaces can contain deeply valuable traditions of respect, service and collective responsibility. The aim is not to discard these practices as outdated, but to distinguish useful traditions from unproductive ones. Why do global executives struggle? Global executives often struggle because they mistake unfamiliarity for inefficiency. A leader arriving from headquarters may see different communication patterns, slower consensus-building or less visible individual initiative and conclude that the organisation lacks capability. Roche argues that this reaction misses the point. Japan has a high-quality workforce, strong attitudes towards responsibility and significant organisational knowledge. The challenge is to separate material differences from immaterial differences and to avoid imposing headquarters habits where they do not improve results. Is Japan truly risk-averse? Japan is often described as risk-averse, but Roche's experience suggests a more nuanced view. The issue is not necessarily fear of risk; it is uncertainty avoidance and the preference to reduce exposure before acting. In a direct-response television business, decisions had to be made rapidly, media had to be purchased and products had to be tested before perfect information was available. This required a more entrepreneurial rhythm. Japanese organisations can act decisively when leaders provide enough context, credibility and confidence that the downside is understood and managed. What leadership style actually works? Roche's preferred style blends the best aspects of Japan and the United States. It values work ethic, respect, disciplined execution and attentiveness to detail, while also encouraging speed, experimentation and direct accountability. It avoids a simplistic choice between command-and-control leadership and consensus-only leadership. The most effective approach is situational: clear about outcomes, flexible about pathways and patient enough to allow people to contribute. It also requires the discipline not to react emotionally when employees lack historical knowledge or make uninformed comments. How can technology help? Technology can help organisations become more deliberate rather than merely faster. Roche sees a need for greater understanding of data science, sales technology, algorithms, automation and decision intelligence. Digital twins, predictive modelling and customer data can help organisations test offers, improve fulfilment, forecast demand and reduce wasted effort. However, technology is not a replacement for judgement. It should support better decisions, not create false certainty. Leaders still need to assess ambiguity, understand customers and make choices before all information is available. Does language proficiency matter? Language proficiency matters because it signals effort, respect and a willingness to understand the local environment. Roche's Japanese enabled him to build relationships, negotiate with regional media figures and understand the realities of Japanese business beyond the expatriate bubble. Full fluency is not the only requirement, but even a practical level of Japanese can deepen trust and reduce distance. It also helps global executives recognise the important difference between what is said formally and what is communicated through context, timing and relationships. What's the ultimate leadership lesson? Roche's core lesson is to pick the right fights. Leaders should identify non-negotiable business outcomes while remaining open about how those outcomes are achieved. They should avoid dismissing local practices simply because they differ from headquarters norms. Strong leadership combines clarity, patience, humility, cultural intelligence and the courage to act amid incomplete information. The best leaders understand that several paths may lead to the same mountaintop. Author Credentials Dr. Greg Story, Ph.D. in Japanese Decision-Making, is President of Dale Carnegie Tokyo Training and Adjunct Professor at Griffith University. He is a two-time winner of the Dale Carnegie "One Carnegie Award" (2018, 2021) and recipient of the Griffith University Business School Outstanding Alumnus Award (2012). As a Dale Carnegie Master Trainer, Greg is certified to deliver globally across all leadership, communication, sales, and presentation programs, including Leadership Training for Results. He has written several books, including three best-sellers — Japan Business Mastery, Japan Sales Mastery, and Japan Presentations Mastery — along with Japan Leadership Mastery and How to Stop Wasting Money on Training. His works have also been translated into Japanese, including Za Eigyō (ザ営業), Purezen no Tatsujin (プレゼンの達人), Torēningu de Okane o Muda ni Suru no wa Yamemashō (トレーニングでお金を無駄にするのはやめましょう), and Gendaiban "Hito o Ugokasu" Rīdā (現代版「人を動かす」リーダー). In addition to his books, Greg publishes daily blogs on LinkedIn, Facebook, and Twitter, offering practical insights on leadership, communication, and Japanese business culture. He is also the host of six weekly podcasts, including The Leadership Japan Series, The Sales Japan Series, The Presentations Japan Series, Japan Business Mastery, and Japan's Top Business Interviews. On YouTube, he produces three weekly shows — The Cutting Edge Japan Business Show, Japan Business Mastery, and Japan's Top Business Interviews — which have become leading resources for executives seeking strategies for success in Japan.

Gather 'round the electronic fireside, children, it's time for another film-based chinwag. John and El'Ahrai are back for another seamless, uninterrupted, problem-free episode. Reviews of "Toy Story 5" and "The Terror: Devil in Silver" are on offer this week. Plus! News, video picks, questions, answers, and...more! Please listen! Oh my God, for a minute there I thought that man didn't have an arm.

On this edition of FLZ presents: DAVID STEINBERGER & CHIP MOSHER come through to talk about the revolutionary digital Marketplace you need as a comic and Manga fan: NEON ICHIBAN & the latest with the fearless line of stories coming from DSTLRY!   Sign up now at: https://neonichiban.com/   Follow DSTLRY at: https://dstlry.co/   For your must stop destination for New Comic Book Day reviews: https://www.fanlightzone.com/comics   Find A Comic Shop at: https://leagueofcomicgeeks.com/stores...   Find out more about COMICS! The Magazine: https://comicsthemagazine.com/   FOR ALL THINGS FLZ: https://linktr.ee/fanlightzone   #comics #comicbooktalk #comicbook #neonichiban #dstlry #davidsteinberger #chipmosher #digital #digitalcomics #comicbookdiscussion #business #community #storytelling #fanlightzone

This week's Dollar Bin Discovery is Neon! Everything is louder, brighter, and just a little more extreme. Mike got into some vibrant sci-fi with Radical Dreamer #1. Jessika, meanwhile, checked out Deadpool: Back in Black #1, proving that black costumes can still deliver colorful action. Grab your sunglasses! 

We're excited to have Databricks join us at AIEWF, among hundreds of the top companies in the AI Engineer ecosystem. LS subscribers can use their discount to get past the late bird pricing and access over $50k in sponsor offers! Everyone is still talking about Satya's Frontier Ecosystems post, but few have actually built a (now $175 billion) frontier ecosystem and cloud like our guests today.From open-sourcing the layer above coding agents to rethinking databases for the agent era, Databricks cofounders Matei Zaharia and Reynold Xin are pushing the company beyond the lakehouse into a full data-and-AI operating system. In this episode, Matei and Reynold join swyx at the 2026 Data + AI Summit to unpack Omnigent, LTAP, Lakebase, agent security, open formats, Mosaic, and why databases may matter more than ever once AI agents start doing real work.We go deep on Omnigent: Databricks' open-source meta-harness for combining, controlling, and sharing agents across Claude Code, Codex, Cursor, Pi, custom agents, and internal tools. Matei explains why coding agents and enterprise agents run into the same problems: portability, collaboration, session history, security, spend controls, and the need for a common API above every harness.Then Reynold walks through Databricks' database dream: why CDC is brittle enough to joke that it means “continuous data corruption,” why HTAP has been the holy grail of database engineering, and why Databricks thinks LTAP gets most of the benefits by unifying the storage layer instead of collapsing every query engine. We also cover Databricks' infrastructure scale, the culture behind rapid prototyping, the difference between tech and enterprise customers, Databricks vs Snowflake, whether vector databases should have ever existed, the Mosaic model strategy, Genie, AI Runtime, RL fine-tuning, and the thesis that traditional software gets rewritten once the data is in the right place and agents sit on top.Databricks began as a company for the big data era. The origination of Spark from the Berkeley AMPLab which eventually turned into the product Lakehouse convinced enterprises that they didn't need a separate data lake, warehouse, ML platform, and governance layer. They just needed one open foundation where all of their data could live and be reasoned over.Since then a lot has changed, but data has only become more important. Data is no longer something you keep track of and analyze ad hoc, it's the necessary context agents need in order to act. So the framing has shifted from “where do we put all of our data?” to “how do we expose the right slice of state, history, permissions, and business logic to an AI system at the exact moment it's doing work?”If frontier model performance becomes commoditized, the durable advantage then becomes the company-specific context around them: proprietary data, governed access, operational state, transaction logs, workflows, and feedback loops. Which makes Databricks positioned perfectly.Now coming fresh off the Data + AI Summit 2026, the company is moving just as fast to keep up, announcing Genie One, Omnigent, LTAP, and many more, indicating a central mission in its newer work: Databricks is trying to become the operating system for enterprise agents.Models are getting good enough, but agents are only useful if they have the right context, permissions, memory, state, cost controls, and access to live business data. Fundamentally it appears that significantly better model performance in production is a systems problem, one that data guys like us are remarkably well prepared to solve!We discuss:* Why Databricks built Omnigent as a meta-harness above existing AI agents* Why coding agents and custom enterprise agents need the same infrastructure* The common API for agent sessions, files, streams, tool calls, and cancellation* Why persistent sessions, cloud sandboxes, sharing, search, and collaboration matter* Why Databricks open-sourced Omnigent instead of keeping it proprietary* Databricks' internal agent usage, cloud sandboxes, and coding workflows* The scale of Databricks: 50–60 million virtual machines a day and exabytes before breakfast* Why agent security needs contextual and stateful policies* How an agent could read confidential docs, install a compromised npm package, and leak data* Why spend control matters when an agent can burn $500 reading logs* Startup opportunities around coding-agent analytics, quality, skills, and spend* LTAP, Lakebase, and why Databricks wants to rethink the database stack* OLTP vs OLAP, CDC, and why data pipelines break at 3 a.m.* Why HTAP has historically been the holy grail of database engineering* Why Databricks thinks LTAP is “HTAP done right”* How writing transactional data into column-oriented formats changes analytics* Why agents need live operational context from databases, not just telemetry* How Databricks prototypes strategic systems without endless process* Enterprise vs tech customers, governance, procurement, and DIY culture* The “second system syndrome” risk of rewriting a database engine* Building a database engine from a decade of traces and quadrillions of data points* Why vector databases should never have been a separate category* Why open formats and AI changed the race with Snowflake* The Mosaic story, DBRX, Genie, document parsing models, and specialized model training* Why model customization and RL fine-tuning may become mainstream* Why “get the data there, slap some agent on top” may rewrite traditional softwareMatei Zaharia* LinkedIn: https://www.linkedin.com/in/mateizaharia* X: https://x.com/matei_zahariaReynold Xin* LinkedIn: https://www.linkedin.com/in/rxin* X: https://x.com/rxinDatabricks* Website: https://www.databricks.com* X: https://x.com/databricksTimestamps00:00:00 Introduction00:02:22 Omnigent and the Agent Infrastructure Layer00:08:39 Agent Clouds, Common APIs, and Open Source00:16:52 Databricks Scale and Internal AI Workflows00:18:03 Agent Security, Governance, and Spend Controls00:27:34 LTAP and the Database Dream00:30:30 CDC, HTAP, and Why Data Pipelines Break00:34:05 Lakebase, Parquet, and Live Data for Agents00:36:47 Databricks' Culture of Fast Prototyping00:43:40 The Dream Engine and Rewriting the Database Stack00:51:02 Vector Databases, Query Engines, and LTAP00:52:36 Databricks vs Snowflake00:57:48 Mosaic, DBRX, Genie, and Specialized Models01:03:11 Context, AI Runtime, and RL Fine-Tuning01:06:15 Why Data + Agents May Rewrite Software01:07:09 Closing ThoughtsTranscriptIntroduction: Databricks, Data + AI Summit, and Founder DynamicsSwyx [00:00:00]: Matei and Reynold from Databricks, welcome to Latent Space.Reynold Xin [00:00:06]: Hey, thanks for having us.Swyx [00:00:07]: Yeah.Matei Zaharia [00:00:08]: Yeah, thanks so much.Swyx [00:00:09]: thanks for taking time out. You have your Databricks, Data AI Summit going on. You were just telling me how the first summit that you guys ran was just 50 peopleReynold Xin [00:00:17]: Yeah, it wasSwyx [00:00:17]: in BerkeleyReynold Xin [00:00:18]: little meetup at Berkeley, I thinkMatei Zaharia [00:00:19]: YeahReynold Xin [00:00:19]: put togetherMatei Zaharia [00:00:20]: We were doing these tutorials and, yeah, just teach people Spark.Swyx [00:00:23]: Yeah. obviously now it's like, I think like the headline number's like 100,000 people around the world, 30,000 in person.Swyx [00:00:30]: it's a crazyMatei Zaharia [00:00:31]: AmazingSwyx [00:00:31]: community. Well, I just saw the keynote.Swyx [00:00:35]: Ali's just. Did was it obvious or that back when that Ali would be, like, such a great, like, CEO? LikeReynold Xin [00:00:42]: OhSwyx [00:00:42]: such a great presenter?Reynold Xin [00:00:43]: What do you think?Matei Zaharia [00:00:44]: I think among our group of founders it was clear that, I think he'd be the best at this.Swyx [00:00:50]: Yeah.Matei Zaharia [00:00:50]: And yeah, it turned out great. And he's, he's ramped up on so many topics growing a company. He would just go in and, like, study it and, be talk to all the experts. Like, even if he can't hire the person, learn enough about, like, finance and sales and whatever it was, and, and go from there. Yeah.Swyx [00:01:09]: Yeah.Reynold Xin [00:01:10]: he's obviously very high IQ and a very high EQ, but it wasn't. Like, Ali today is quite different from Ali from, like 10 years ago. I think there's a lot of work that he put in to, get to this point.Swyx [00:01:20]: Yeah. no, to me the most appealing thing about him is that he's funny. And like, it, it's, it'Matei Zaharia [00:01:26]: It's true, yeahSwyx [00:01:26]: it's hard to make jokes about, data warehousesReynold Xin [00:01:30]: About serious topicsSwyx [00:01:31]: securityMatei Zaharia [00:01:32]: YeahSwyx [00:01:32]: what have you.Matei Zaharia [00:01:33]: Oh, yeah. That's for sure.Swyx [00:01:34]: Yeah. So you guys launched a whole bunch of things. I'll, I'll just name check briefly, the stuff because we're not gonna cover everything. Omnigentt, your baby. LTAP, your baby, your dream engine.Swyx [00:01:47]: we're also gonna cover Genie, cover CustomerLake, you acquired PantherMatei Zaharia [00:01:52]: YeahSwyx [00:01:52]: Open Sharing, and there's Unity AI Gateway. A lot of these, I think, like, are things that you would expect a Databricks to do. It's, it's like part of the roadmap. Everyone in your category has similar things. But I think, probably the two of you are leading the two most unique and differentiated initiativesOmnigent and the Agent Infrastructure LayerSwyx [00:02:09]: on, in the landscape. Maybe we'll start with, Omnigentt we'll, we'll, we'll, we'll go into it. I do think that a lot of people are exploring this meta harness concept.Matei Zaharia [00:02:21]: Yeah, totally.Swyx [00:02:21]: What led you to it?Matei Zaharia [00:02:22]: Yeah. There were a couple of, like, converging lines, which I think is a good sign that you need something new. So on the one hand, there's all the coding agent info internally. We have really great, dev infra team. they built something called Isaac, that's like a wrapper on Claude Code and Codex, and, lets you use them either on the web in, like, sandboxes or, just on your dev machine or on your laptop or whatever. And then, they were adding all kinds of stuff there. And we saw all the more advanced engineers like, were building their own workflows with tons of agents, and they were building their own UIs and stuff on top or even on top of that. And then the other one was, like, us building agents. We ship this, like, data science agent called Genie on the research team, which I lead. We also build a lot of internal ones for various things, and then we have all the customer ones. And all of them running into this thing of like, “Oh, I need to switch model and harness and so on,” every few months. Plus the agent is, like, completely useless if you can't share sessions with someone and have history and have search and all this, like, layer on top of it for collaboration. I thought a bit about it from both contexts and, at first people thought it was weird. They're like, “Why are you doing coding agents and custom agents in the same thing?” But I said it's, it's the same problems and, you just wanna build the stuff that lets you deliver the agent, maybe control it if you care about security, and, make it portable across things. And then we prototyped some things as experiments. We saw, yeah, we can make it work, and then we built that for real.Swyx [00:04:06]: I'm wondering if this let's call it architectureMatei Zaharia [00:04:11]: YeahSwyx [00:04:11]: maps to anything in your careers in the past. like I always think about how a lot of things just tie back to operating systems.Swyx [00:04:18]: A lot of operatingMatei Zaharia [00:04:19]: YeahSwyx [00:04:20]: systems tie back to databases,Matei Zaharia [00:04:21]: SoSwyx [00:04:21]: or the other way aroundMatei Zaharia [00:04:22]: so the thing, I do think it ties a lot to, like, network protocols, internet protocol. we alsoSwyx [00:04:29]: Communication between entities.Matei Zaharia [00:04:30]: Yeah. We did stuff with, like, data sharing also, which is probably, most viewers probably won't know unless they'Swyx [00:04:36]: Yeah, open protocol is the term.Matei Zaharia [00:04:37]: Yeah.Swyx [00:04:38]: Open sharing. Open sharing.Matei Zaharia [00:04:38]: Open sharing.Swyx [00:04:39]: Yes.Matei Zaharia [00:04:39]: Yeah. So it's like you have a company, you maintain some table, like let's say like a Walmart or something. They have like the, inventory and what's been sold in each store. And then you also have suppliers, and they would love to produce more things and ship them, like, exactly the moment you need them. So they would love, like, real-time access to your table. So instead of like sending emails around or Excel sheets or phone calls, why can't you share like a view of that table in real time with them? Then they query, they, join it with their data, and they decide what to send. So it's one of these things where you, like you might ask like today since we can vibe code anything so fast, why do we even need to design like protocols or APIs or software? Why can't you just vibe code things on demand? But for this type of interoperability where multiple parties that are moving at different speeds are building stuff and you still want some layer on top to coordinate, you do wanna design it and build it. So it reminds me of that, like agents talking to each other and, users talking to agents and tools.Agent Clouds, Cloud Sandboxes, and Keeping Sessions AliveSwyx [00:05:42]: Reynold, any other comments alternative viewpoints?Reynold Xin [00:05:46]: I think, by the way, we had a debate on exactly which set of benefits would, matter a lot, and I think around the time we decided to do this thing I was telling Matei, “Hey,” it just happened to be there's a particular week that I was coding nonstopSwyx [00:06:00]: from the moment I woke up to, like, the moment I went to bed, I was, like, looking at my Claude sessions, my Codex sessions. And one of the things that was particularly annoying was having to keep my laptop open.Swyx [00:06:12]: I was driving to a doctor's appointment, and I remember because I wanted to make sure the whole thing continues working.Matei Zaharia [00:06:18]: But by the way, it's so comforting to hear you say that because I'm like, “I don't know if I'm a clown and I'm doing this or like.”Swyx [00:06:25]: Yeah. Like honestly, I was driving and I was tethering my laptop to my phone.Matei Zaharia [00:06:29]: huh.Swyx [00:06:29]: Keeping it on the side. Whenever I hit a red light, I started looking at what's going on my laptop.Matei Zaharia [00:06:35]: Yeah.Swyx [00:06:35]: And I just felt that was ridiculous.Matei Zaharia [00:06:37]: Yeah.Swyx [00:06:37]: It felt like we went back to the dark agesMatei Zaharia [00:06:39]: YeahSwyx [00:06:40]: programming. the productivity you gain from all this coding age is amazing, but, yeah.Matei Zaharia [00:06:45]: Have you heard of cloud?Swyx [00:06:47]: Yeah.Swyx [00:06:48]: It was crazy to me.Matei Zaharia [00:06:49]: Oh, the thing you were working on was the sandboxes or was this before that?Swyx [00:06:52]: It was a sandbox.Matei Zaharia [00:06:53]: Okay.Swyx [00:06:54]: I was workMatei Zaharia [00:06:54]: So you were inSwyx [00:06:55]: So I was approaching from a very different angle. I wanted to, “Hey, we're gonna have cloud sandboxes that doesn't shut down. You can get one very quickly,” but not just for running agentic sessions.Matei Zaharia [00:07:06]: Yeah.Swyx [00:07:06]: It's also for running development. So I was personally building that week, and through building that, I ran into all these issues, and then I wroteMatei Zaharia [00:07:15]: YeahSwyx [00:07:15]: a document for Matei, it's like, “Here's my wish list of what the actual environment should do.” And I think he ended up almost implementingMatei Zaharia [00:07:22]: YeahSwyx [00:07:22]: every single one of them.Matei Zaharia [00:07:23]: Yeah, I remember Reynolds saying, ‘cause my first prototype of this had just chats with your agent and he said, “I have to be able to open a shell, like my own shell and like list files and like tail them and stuff.” SoSwyx [00:07:36]: So SSH into a mainframe.Matei Zaharia [00:07:37]: Yeah. it has that now.Swyx [00:07:39]: Tailing my log.Matei Zaharia [00:07:40]: Yeah.Matei Zaharia [00:07:41]: Yeah.Swyx [00:07:41]: And also another thing I think I asked was, I had. I still use cursor for the sole purpose of rendering markdown files.Matei Zaharia [00:07:48]: huh. Yes.Swyx [00:07:49]: So I said, “If you just give me a way to see my markdown files and renderMatei Zaharia [00:07:53]: YeahSwyx [00:07:53]: them properly, I don't need a separate tool anymore.”Matei Zaharia [00:07:55]: Yeah.Swyx [00:07:56]: And I think you also built that in.Matei Zaharia [00:07:57]: Yeah, we, yeah, we did that, yeah. Yeah, we had a lot of engineers building, their own vibe coding setup. But then the other thing they all said is like, “Hey, I built something that's amazing for me, but, like, no one else on the team can use it ‘cause I don't have a server to collaborate.” And this is why we tried to set up, Omnigent, so you can have a server and have the security, set up in there. So, like log in with Google or whatever and, like securely share stuff. which. And that's where we've seen a lot of other agents like hit things. Like people think they prototyped an awesome agent, but it's not allowed to connect to like some really important data or whatever because of the security team.Omnigent Architecture, Open Source, and Common APIsSwyx [00:08:38]: Yeah.Matei Zaharia [00:08:38]: So yeah.Swyx [00:08:39]: Yeah. At this point, so for those watching along on YouTube, we're gonna putting up a image of the structure here, and we can talk a little bit of the architecture. I think I just want to have people understand, ‘cause like when we're talking about software, it can be very abstract and like here is what we're talking about. You've worked out in open source this entire platform and there's a runner component and server component with a uniform API that you've, you've figured out. any other element and obviously you can plug in all this, persistence layers and compute layers. This is a whole cloud. It's an agent cloud.Matei Zaharia [00:09:12]: Yeah. It's, it's got these components to work with it. The, a lot of the action happens like on the machine where you deploy your agent too. So whatever you've got on there, you can run. But yeah, it's, I think it's the minimal thing you want to have hosted, like collaborative agents and to have that server. And one of the reasons we open sourced it is, anyone building agents, this gives them an app they can start with and customize, which we were seeing in Databricks too. Like someone would make a nice, agent app and then other teams would ask, “Oh, can I just use yours for my agent?”Swyx [00:09:45]: Yeah, I think we had like five or six different agentic frameworksMatei Zaharia [00:09:48]: YeahSwyx [00:09:48]: built by every different team. They do all do more or less the same thing. Yeah, you need to. people wanna take something that works in Forkit, and you might as well have something open source. Yeah, which also was another question, which is interesting for Databricks. Like what do you choose to open source? What do you choose to make it proprietary? It's in. this goes back to Spark, right?Matei Zaharia [00:10:05]: Yeah.Matei Zaharia [00:10:06]: One, so one of the reasons to open source something is if you think it's a layer that will there'll be some network effect, it'll benefit from many, people collaborating, on it. So, for example, with Spark, I don't know if when Spark came out, we also focused a lot on letting you have libraries on top. So like there used to be differentSwyx [00:10:28]: EcosystemMatei Zaharia [00:10:28]: distributed computing engines for like machine learning and graph computation. We said they should all be libraries that you can compose. And we made it super easy to add connectors to data sources too. And then we benefit because, we don't have the time to write like connectors to like, 1,000 like different databases and file formats, but we can just use the ones people make, and of course they benefit from joining, this thing. So that's like one of these as it. Another way to think about it is like imagine, we our thing wasn't open. We had some agent hosting thing, but it's not open and then there is an open one. if you're. Which one's gonna win in the long run? So like here, because there is this benefit from like people writing integrations, it'll be, it'll be that. And then there are other things that like you just can't, even deliver as open source that are things the company does. Like for example, how do you make sure you're like streaming, jobs or your Lakebase database doesn't like, lose all your data at night? Well, that requires an operational team that's gonna sit there. There's no way it has to be a service. So like we wanna make sure as a company we're really good at those infra services and then we're as open as we can in terms of like what you build on top.Swyx [00:11:42]: speaking from a benefits, I think we are already seeing pull requestsMatei Zaharia [00:11:45]: YeahSwyx [00:11:45]: of all kinds of ecosystem integration, even though it was only released on Saturday.Matei Zaharia [00:11:50]: Yeah, Saturday. Yeah. So someoneSwyx [00:11:51]: Let's see, let's see what's going on. Yeah, you can look at the merge ones. I asked Sam Nigon this morning aboutMatei Zaharia [00:11:59]: 400 merge already?Matei Zaharia [00:12:00]: Yeah. I think Recent quite, I would guess around half are not from our team. but for example, someone added support for running it on Kubernetesrnetes. people added, many cloud sandboxes, so this can launch a cloud sandbox and run your agent in there, which is great for sharing too, ‘cause it's not, like, on your laptop and someone's, like, running scary code on there. so yeah, many startups have put those in, and, we expect to see more of them. We also have more agent harnesses already. Cursor, CLI, and Antigravity also.The Modern Data Stack and the Emerging AI StackMatei Zaharia [00:12:34]: Yeah. That's all, beautiful. And I, I feel like the last time this happens, there was the rise of the modern data stack.Matei Zaharia [00:12:42]: I don't know if it's that useful. I'm, I'm curious in your postmortem.Matei Zaharia [00:12:46]: I think most peopleSwyx [00:12:47]: AgreeMatei Zaharia [00:12:47]: will agree that it is finally dead. but maybe this arises to a new modern AI stack that, like, does the same thing.Matei Zaharia [00:12:52]: I don't know.Reynold Xin [00:12:54]: I think the modern data stack was a pretty useful thing, probably even up until this day. I think what, maybe for the audience who don't understand the history, I think the modern data stack is effectively decomposed into you need a layer to ingest the data in, you need a layer to transform your data, and then all of this are run, and then you need a layer to maybe visualize your data. And all of this runs on some data warehouse, or later on, as we're doing data warehouse or lakehouse.Reynold Xin [00:13:21]: I think that concepts are all very powerful and very useful. They enable a lot of workloads. What people eventually run into is a question of unification and consolidation is, hey, do you really need to chop all this into different pieces and work with so many different vendors and platforms in order to get, like, a very simple visualization done, right? So I think, like, over time, everybody started realizing that customers are pushing us. We started, we can realize that, so we started building more and more capabilities and trying to consolidate. And at the end of the day now, customers don't have to worry about having me hook up five different systems in orderMatei Zaharia [00:13:55]: YeahReynold Xin [00:13:55]: produce a chart. But the. I think, honestly, something like this is probably happening, in how many different frameworks do you want to hook up together in order to produce, like do a very simple agent.Matei Zaharia [00:14:06]: Just to be clear, I would say the core of this is this common API on top of all the harnesses. So the API is like, you've got an agent session, and you can send in a message or, like, a file. That's what you can send in, and then you get out, these streams as it's streaming text or as it's doing tool calls. And, or the other thing you can send in is you can, like, tell it to cancel a turn. So that's the API. Now, the thing we did is we could get you that on top of, like, cloud code running in a terminal, Codex, Py, OpenAI SDK, all that stuff. We map them all to that same interface. So that is something that you'd have to maintain yourself if you built your own, like, agent orchestrator, and then whenever cloud changes its API, you gotta, tweak your thing or it's gonna lose some messages. So that's the thing that's valuable to maintain. Then on top of that, like, we built a few apps. I think we built a pretty cool UI and stuff, but that's, And we built a security and control piece, which I'm excited about. But it's that common interface, so we don't. We. That doesn't try to be a stack. And in fact, you could plug in your own UI on top of this, server. That, and that's one of the use cases we care a lot about, ‘cause we want to use this in our own products.Compute, Sandboxes, and Databricks ScaleSwyx [00:15:20]: Yeah. It should be everywhere.Matei Zaharia [00:15:22]: Yeah.Swyx [00:15:22]: I think one of those things that is really interesting to me is, like, well, first of all, I'll, I'll endeavor to do everything and not call it the modern AI stack because like it needs a different name.Matei Zaharia [00:15:32]: Yeah.Swyx [00:15:32]: But like, yes, like, so one of the first people that told me about compute, sandboxing was Nikita from Neon.Swyx [00:15:39]: Because a lot of people think about Neon as like, well, it's serverless Postgres with, like, the separation of compute and storage and, instant branching and all those things. But every database company is also a compute company.Matei Zaharia [00:15:51]: Yeah. Yeah.Swyx [00:15:52]: And so he was showing to me his whole, his sandboxing solution. I don't think he have ever launched it.Matei Zaharia [00:15:57]: So our sandbox solution, the reason we could build it so quickly was because we realized if you just take the actual Lakebase architectureSwyx [00:16:05]: YeahMatei Zaharia [00:16:05]: and remove the database from it, by the coming from NeonSwyx [00:16:08]: Exactly, rightMatei Zaharia [00:16:09]: you have this sandboxSwyx [00:16:09]: Every database company has it already, yeah.Matei Zaharia [00:16:11]: Now, there are some differences. For example, in the one to support this particular workflow, it's important to have local persistence,Swyx [00:16:19]: YeahMatei Zaharia [00:16:19]: because you want your state to persist. Your libraries, you don't have to install your library every time, right?Matei Zaharia [00:16:24]: whereas the Neon architecture, because of the separation of storage from compute, you don't need persistent local disk.Swyx [00:16:30]: Yeah.Matei Zaharia [00:16:30]: So there's some differences.Swyx [00:16:32]: Yeah.Matei Zaharia [00:16:32]: But the, at the end of the day, yeah, it's, Yeah, so this is when you run, like, a coding sandbox. Like, if I use it, yeah, we have the dev env internally at Databricks. There's, like, many, like, tens of gigabytes of data just for, like, all the source code and, like, artifacts and stuff that I built, and I want that to come back next time, so.Matei Zaharia [00:16:51]: Yeah.Matei Zaharia [00:16:51]: But yeah.Matei Zaharia [00:16:52]: Before the show, we was talking about some statistics that might be surprising at the adoption.Matei Zaharia [00:16:56]: It could be internal, it could be external, whatever comes to mind, just to impress people the scale this is happening.Swyx [00:17:02]: So we, on the analytics side, I think we launchedReynold Xin [00:17:06]: Maybe 50 or 60 million virtual machines a day across all three clouds, so we're one of the biggest compute orchestrators out there.Reynold Xin [00:17:13]: Stuff for sure for CPU compute.Swyx [00:17:14]: Yeah.Matei Zaharia [00:17:14]: Yeah.Reynold Xin [00:17:15]: the. And all of this process, I think exabytes of data, I joked about depending on which time zone you are, typically before you have breakfast, Databricks would have processed exabytes of data already on that day. and on Neon, it's pretty interesting, too. It's launching, I think, 13 million databasesSwyx [00:17:34]: YeahReynold Xin [00:17:34]: a day now.Swyx [00:17:35]: Yeah, to me that was, like, aReynold Xin [00:17:36]: And that's just likeSwyx [00:17:37]: Like, what do you mean?Matei Zaharia [00:17:38]: Yeah. And that's the point.Reynold Xin [00:17:40]: And a lot of those were thanks to agent- agents and branching experimentationSwyx [00:17:44]: YeahReynold Xin [00:17:44]: because we made it so easy and so quickly, and thanks a lot to Nikita's team, to launch databases. It's, the. So it's changing the way people use databases.Swyx [00:17:54]: Yeah. Okay, we're gonna go into more database talk in a bit, but I wanna make sure we close up anything on Omnigentt. you mentioned, you were excited about the securityOmnigent Security, Contextual Policies, and Spend ControlsSwyx [00:18:03]: control side.Matei Zaharia [00:18:04]: Yeah.Swyx [00:18:04]: a lot of companies are figuring that out right now, as well as the spend side.Matei Zaharia [00:18:08]: Yep.Swyx [00:18:09]: what have you found there?Matei Zaharia [00:18:11]: Yeah, so I spent quite a bit of time talking to internal users, developers, security team, managers, and also lots of customers, and there's a few things. Like, first of all, one thing, that immediately was. became obvious is for security, there's this tension between, like, usability and security. And, the way people do. Like, a lot of coding agents today have very basic things like you can tell me which tool patterns I'll allow or disallow or whatever. It's like yes or no. But that puts you in a very tough spot. So just as an example, like, should my agent be able to read, some confidential documents, or let's say, should it be able to install new packages from npm, which, maybe it's compromised. Yes or no? Like, maybe I wanna allow it. Should my agent be able to publish stuff to the company website? Well, if I'm using it to code on the website, yes. But should it be able to do both, so it can, like grab a confidential document and be prompt injected and leak it? Probably not. So the thing we decided we need is stateful or what we call contextual policies where you keep track of the state of that session. It's not like is it allowed to push to the marketing site or not, but, like, hey, if it did a risky thing, like it installed, a old package from npm, or it read, like, 1,000 confidential docs, then no. Then don't, don't do it. Otherwise, maybe it's okay. That's one example of, like, moving that trade-off so it's both more secure and more useful by having a more powerful engine, essentially. This requires tracking sessions. The other piece that was interesting there is, like, there are these very level events it's doing, and you want some libraries on top that parse them. Like, for example, we have a, MCP server on Google Drive internally. It's got 60 API calls. like, how do I know which of those, like, will share a document with stuff on the internet and which ones won't? It's, it's annoying. So we designed in Omnigentt the policy layer so that it's functions and you can have libraries. Like, someone can make something that maps the level events to high-level ones, and then you write a policy about the high-level things that came out. so and thatSwyx [00:20:25]: This is related to the Panther,Matei Zaharia [00:20:27]: Yeah, Panther is. will help with that. PantherSwyx [00:20:30]: YeahMatei Zaharia [00:20:30]: a similar idea on the event processing side, and it's Python-based versus a weird custom language. this is more, as in realSwyx [00:20:39]: I didn't even know we were good yeah.Matei Zaharia [00:20:41]: Those things are happening, yeah.Swyx [00:20:42]: Yeah.Matei Zaharia [00:20:42]: So yeah, but these are the cool things. I think the contextual or stateful part, and then the way it can be libraries, and that was another reason to make it open source because others will write libraries and, like, we and our customers can use them. And the final thing, because it's stateful, one of the states we track is how much you spent in that session. So I can. I've had, like, I ask an agent to debug something, and it spent $500 because it decided to read a lot of log files and burn a lot of tokens. but I can literally say, “Okay, launch a agent to do this and cap it to spending $5.” Like, ask me for permission if it needs more. And because we're counting that within that session, it'll pop up and tell me, “Okay, you spent five, $5. Do you wanna go on?”Reynold Xin [00:21:27]: So important context here. Matei spent the last five years, a lot of his time was architecting Unity Catalog at DatabricksMatei Zaharia [00:21:34]: YeahReynold Xin [00:21:34]: which is the governance layer for data.Matei Zaharia [00:21:35]: That's right, yeah.Reynold Xin [00:21:36]: And he's combining expertise at that layer together with all the AI governance he knows.Matei Zaharia [00:21:41]: Yeah.Swyx [00:21:41]: DoMatei Zaharia [00:21:41]: But I also spent a lot of time being annoyed by coding agents and getting prompts.Matei Zaharia [00:21:46]: And also as theReynold Xin [00:21:48]: All the aboveMatei Zaharia [00:21:48]: I don't want to end up on the front page as, like, I installed some weird npm package and leakedSwyx [00:21:53]: YeahMatei Zaharia [00:21:53]: all the code, so I'm especially paranoid. But also I have very little time, so I don't want to sit there approving, like, do you want to run a 20-line, bash script, yes or no? so that's why I spend a lot of time figuring out, like, how can I make it as safe as possible and not annoying?Swyx [00:22:10]: Yeah. Is safety and mmm, let's call it security a bigger concern than token maxing or token budgets? which one is, likeMatei Zaharia [00:22:19]: Oh, yeah, they're both there. I don't know. I guess it depends on the type of company you are. So I think, some companies, like, the budget is, limited and, they really care about thatSwyx [00:22:34]: you can be Uber and still be concerned?Matei Zaharia [00:22:36]: Yeah. Oh, yeah, totally. Yeah. If you haveReynold Xin [00:22:38]: for us, securityMatei Zaharia [00:22:39]: YeahReynold Xin [00:22:40]: super paramount.Matei Zaharia [00:22:40]: For us, security is absolutely critical as a, cloud provider. It's, it's the most important thing, and, token maxing, we're not so worried about it yet, but I've seen the Like, for example, I talked to some consulting companies. They have, like, 100,000 employees who are all coding for customers. If those each spend, like, an extra $1,000 a month, that's, that's not fun.Swyx [00:23:04]: YeahMatei Zaharia [00:23:04]: we have, like, only a few thousand engineers.Swyx [00:23:06]: What's the policy in Databricks? Is it just unlimited or what'Matei Zaharia [00:23:08]: It's, it's unlimited, but we do. we use our own product to, like, analyze the traces and stuff, and we have a team that'looking to optimize and to see if anyone's doing something weird. And, we had some really cool insights just from analyzing current traces, like whichSwyx [00:23:24]: YeahMatei Zaharia [00:23:25]: models are better at, say, Rust versus like TypeScript or whatever. So yeah, at least in our code base.Swyx [00:23:31]: Yeah. Amazing. Obviously, I have to ask the token question, obviously.Matei Zaharia [00:23:34]: Yeah.Swyx [00:23:34]: I think it'sReynold Xin [00:23:34]: YeahSwyx [00:23:34]: it's a key thing. But yes, security and control above that, and figuring out a sane layer there you can have some autonomy, but, not too much.Matei Zaharia [00:23:43]: Yeah. Yeah, and we wanna make it super easy. As a engineer, you should set a thing. So in Omnigentt, you can ask your agent, “Set a policy on yourself to do this.” So it can likeSwyx [00:23:52]: But if there's something I should be showingMatei Zaharia [00:23:53]: YeahSwyx [00:23:53]: I don't, I don't see it on the GitHub, but,Matei Zaharia [00:23:55]: Oh, yeahSwyx [00:23:56]: there's justMatei Zaharia [00:23:56]: Well, in the docs there's something.Swyx [00:23:57]: Yeah, this is it.Matei Zaharia [00:23:58]: You can look at it later.Swyx [00:23:59]: Okay. Yeah.Matei Zaharia [00:23:59]: Just look in the docsSwyx [00:24:00]: YeahMatei Zaharia [00:24:00]: contextual policies if you wanna see.Swyx [00:24:04]: I just like to point peopleMatei Zaharia [00:24:05]: look at the built-in policies.Swyx [00:24:06]: Yeah.Reynold Xin [00:24:06]: Yeah.Swyx [00:24:06]: If you want to, follow up on this is exactly where to look, right?Reynold Xin [00:24:10]: Yeah.Matei Zaharia [00:24:10]: Yeah. yeah, and the story of these is, like, I just wrote, like, I wrote a doc with like 10 ideas for things before as you were working on them. Well, that was, like, my wish list of things people asked, and I told the team, like, “Hey, can you do like at least five of these for the launch?” And then they just got back with all of them, so.Swyx [00:24:29]: Oh, wow.Matei Zaharia [00:24:29]: so you can come up with more, but them- some of them are just meant to be examples. really you can intercept, like, any event the agent is making, and you can then either block or force it to ask the user or, like, allow, and you can update state to keepSwyx [00:24:45]: YeahMatei Zaharia [00:24:45]: track stuff.Swyx [00:24:46]: Yeah, ‘cause ultimately you're, I think of you as, like, a systems designer.Swyx [00:24:50]: You let people plug in, right? That's the wholeMatei Zaharia [00:24:51]: YeahSwyx [00:24:52]: modus operandi of what you do.Matei Zaharia [00:24:53]: Yeah.Swyx [00:24:54]: It's likeMatei Zaharia [00:24:54]: And we care a lot about also composab- like, can someone else write a library that others use, whichSwyx [00:24:59]: YeahMatei Zaharia [00:24:59]: this is meant to.Reynold Xin [00:25:00]: There's also a batteries included philosophy hereMatei Zaharia [00:25:03]: YesReynold Xin [00:25:03]: probably very similar to how you did Spark, which is you could just start using.Swyx [00:25:06]: Yeah.Matei Zaharia [00:25:06]: Yeah, that's right. It has to be good out of the box at certain things, and then you can build your own things on top that, like, we don't wanna do. But in Spark, if you just wanna like, I don't know, like read a table or do, like, a aggregation, it should be awesome at that out of the box.Building on Omnigent: Contributions, Startups, and AnalyticsSwyx [00:25:23]: Yeah. People wanna catch up on Omnigentt, they should watch your keynote.Swyx [00:25:26]: they should go through the GitHub and the docs. If they wanted to contribute, or they want to build on this ecosystem what would you call out as the most high-leverage places get involved?Matei Zaharia [00:25:36]: Yeah, do get involved in the Discord and in GitHub. Our team is there, is monitoring, and, some of the things people ask for we just built ourselves. Some of them, we're, we're collaborating with them to build it. and also tell us, likeSwyx [00:25:49]: Yeah, they're gonna be veryMatei Zaharia [00:25:49]: how you would like to use it because I think especially for developers, like, everyone wants it to work their own way, and a really good developer tool, like you have to hear the feedback on all the ways and figure out the abstractions and how to let people customize. So we'd love to hear, like, if you think, “Hey, I, I don't want it to work this way,” tell us. We really just wanna get that compatibility layer across agents and then let you do stuff on top.Swyx [00:26:14]: Yeah. is there any, in terms of like the startup side, I'm, I'm a founder.Swyx [00:26:18]: I wantMatei Zaharia [00:26:18]: YeahSwyx [00:26:18]: I see an opportunity, I wanna get in front of you. What's your request for, like, a startup that, like, I wish someoneMatei Zaharia [00:26:23]: Oh, like you wanna integrate with us?Swyx [00:26:24]: someone was working on this.Matei Zaharia [00:26:26]: Oh, for a startup?Swyx [00:26:27]: Yeah.Swyx [00:26:28]: Like, your, you got your own startup. It's doing well.Matei Zaharia [00:26:30]: Yeah.Swyx [00:26:30]: But like, if you weren't working on your own startup, what is, like, obvious that you should You advise many startups too, obviously.Matei Zaharia [00:26:37]: I do think, just as a company with a lot of engineers, like anything that helps me make sense of how people are usingSwyx [00:26:46]: SpendMatei Zaharia [00:26:46]: coding agents and,Swyx [00:26:48]: Yeah. AnalyticsMatei Zaharia [00:26:48]: spend, but also quality or like you should write, you should add this skill, or you should write this thing, or your agents are really horrible at tasks involving this service, so I go spend time. That would be nice. yeah.Swyx [00:27:00]: Yeah. The closest I've found is, this team, GitAI.Matei Zaharia [00:27:03]: Oh, cool. Yeah.Swyx [00:27:04]: They started with, like, we will just do, code and human attribution, but they're building the analytics layer on top of that.Matei Zaharia [00:27:12]: Yeah.Swyx [00:27:12]: I do think, like, there are a bunch of, like, artificial analysis is obviously,Matei Zaharia [00:27:18]: Yeah, they have their benchmarksSwyx [00:27:18]: doing super wellMatei Zaharia [00:27:19]: YeahSwyx [00:27:19]: with their stuff. so there's, there will be people. I think this is like the domain of consultants first, but then peopleMatei Zaharia [00:27:26]: YeahSwyx [00:27:26]: will build software that, let's say, it's kinda like the management planeMatei Zaharia [00:27:29]: YeahSwyx [00:27:30]: for coding agents.Matei Zaharia [00:27:30]: Yeah, I think there'll be a lot of insights there. You have it in other areas.Swyx [00:27:34]: Okay. Well, and then the other, big thing is your dream engine.LTAP: Lake Transactional/Analytical ProcessingSwyx [00:27:39]: maybe you wanna tell the story of, LTAP.Reynold Xin [00:27:45]: So, and background with. I'm, I'm gonna make people listen to our Ankur Goyal episode where we talked about SingleStore, HTAPMatei Zaharia [00:27:52]: YeahReynold Xin [00:27:52]: and all that history.Matei Zaharia [00:27:52]: Yeah. The LTAP idea is pretty simple. so if people have heard of the, Ankur's, talk about HTAP, it's effectively the world of databases. Sorry, there's like maybe a lot of context needs to be injected here. The world of databasesSwyx [00:28:06]: I am happy to be the database podcast that I'm forcing people to, like, learn your databases, guys.Swyx [00:28:11]: You cannot vibe code with just markdown files.Reynold Xin [00:28:13]: Yeah.Swyx [00:28:13]: Like,Reynold Xin [00:28:14]: It's one of the most important fundamental systems technologies out there. But the world of database effectively split into roughly two halves. There's what we call OLTP databases, which are transactional, and think of your Postgres, your MySQL, your Oracle databases, and the other side is what we call analytics, and sometime might refer to term OLAP. And the difference is on OLTP, you typically have maybe run some transaction on some event that looks up at one specific row. We update that row, right? It's a very oriented data structure. And on analytics, you're trying to reason on the data. You're trying to compute, “Hey, what's my revenue per store? What's my. How's my website doing every day?” And then you, eventually want to probably end up running anal- machine learning on it to predict, “Hey, how will my maybe sales be going in the future?” they are so very different architecture, and everybody start with OLTP databases. Every app, when you become serious enough, that needs more than markdown files, you need to have a database. You want to lose your data, you want to have some transactional consistency. But once you want to reason on the data, if you only have like- A hundred rows, it's probably okay to run it on your Postgres or your own, your MySQL database. But once you have more data and want to run more complicated analysis, the very analysis might crush your Postgres database. So you start doing, getting data out of the OLTP databaseSwyx [00:29:35]: Replication.Reynold Xin [00:29:36]: Replicate them into the analytic systems and just startSwyx [00:29:39]: Yeah, which for people, Elasticsearch is, like, aReynold Xin [00:29:42]: Yeah. So some of them get into Elasticsearch for, like, blocked analysis. A lot of our customers obviously get into Databricks to run more sophisticated things.Swyx [00:29:51]: Yeah.Reynold Xin [00:29:51]: And there's this term called CDC, whichMatei Zaharia [00:29:54]: Change data captureReynold Xin [00:29:55]: change data capture. and what it does, it reads the binlog of the database, and if you don't understand what binlog is, it's fine. The, but it's a little delta of the data, and it reconstructs based on the delta, the state of the database, on the analytics side. But CDC is, like, a very painful thing. It's how standard in the industry, everybody uses it, but, it ends up being. I think many data engineers ends up being waken up at, like, 3:00 a.m, because there's some pipeline thing.Swyx [00:30:22]: my explanation is, like, Airbyte is like a, became a $5 billion company just doing CDC.Reynold Xin [00:30:27]: Yeah, exactly.Reynold Xin [00:30:28]: CDC is, like, a veryMatei Zaharia [00:30:30]: It's hard.Reynold Xin [00:30:30]: It's one of the most boring but one of the most fundamental operations, like, powering modern society.Matei Zaharia [00:30:37]: huh.Reynold Xin [00:30:37]: But it's so brittle that, we joke that it's, should be called continuous data corruption, because you might change your schema on your OLTP database, and then the CDC pipeline fails to handleSwyx [00:30:48]: YeahReynold Xin [00:30:48]: the schema change.Swyx [00:30:49]: Yeah.Reynold Xin [00:30:49]: And then everything goes out.Swyx [00:30:51]: And there's all sorts of tricks that you can do, like, you add in, like, some versioning or whatever, but yeah.Reynold Xin [00:30:55]: Yeah, but it's a very, in general, very complicated. Like, I think at my keynote, I asked the audience put up their hand if they love their CDC pipeline. Only, like, maybe two people put it up. So if single store, like, about maybe a decade ago, I think the industry had this idea, hey, what if I built a single database that can handle both workloads? Now I don't.Swyx [00:31:12]: Which, like, by the way, every database person ever has ever always dreamed about this.Reynold Xin [00:31:15]: Yes. Yes.Reynold Xin [00:31:16]: This is the holy grail of database engineering is why not build a single system that can do both of this? But it ends up just being a lot of compromises. one, I think one of the first issue is that, hey, each. they say Postgres has a massive ecosystem, right? You want to be using the tools that's built for Postgres. And Spark, for example, had a massive ecosystem. There's a lot of libraries you want to use. If you were to create now a new thing, you don't have a ecosystem. You tend to create a new, smaller proprietary API, and you're lacking both, and it's also very difficult to make it performance-wise to be, comparable on either side. So it ends up being sucking on both. And our whole idea of LTAP, it's obviously a wordplay on the term HTAP, is that we think this is HTAP done right. HTAP wants to build a single engine for both. We think you can get 99% of what you need by unifying the storage, and just have a single storage layer. And once you have the single storage layer, if your Postgres databases are writing data in a column-oriented format, everything analytics can just go read that data directly without any delay, right? There's no pipeline in between, so all the data will immediately be available for reasoning analytics. I think I was telling some customers earlier, hey, when we talked about this is gonna be super useful for agents, I at first didn't really believe in it myself, even though we wrote that positioning.Lakebase, Agents, and Live Operational DataMatei Zaharia [00:32:39]: Yeah.Reynold Xin [00:32:40]: But then last night I was having dinner with a Australian customer, and they told me, “Oh, hey, one of the big issue we have is we have all these logs from our services, and we see SLA dips and want to investigate. But then there's no way for those agents to even understand what's going on in the actual databases themselves. All we see is just, like, product telemetry of the database and the services.” It would make those agents 10 times more powerful if understand, for example, who's placing those orders, what is happening, what exactly are they doing. So now I'm sold on our own message.Swyx [00:33:13]: Yeah.Reynold Xin [00:33:14]: I think it's really. It gets you the almost all of the benefits of the HTAP holy grail, which is, hey, make the data available immediately for reasoning analyticsSwyx [00:33:26]: Yeah, I think,Reynold Xin [00:33:27]: without compromiseSwyx [00:33:28]: in the way that humans are generally intelligent and want to have the ability and access to query anythingReynold Xin [00:33:34]: YeahSwyx [00:33:35]: while they do the work, they also need history and need context.Swyx [00:33:38]: And, like, where else does they get context? That's it's an analytical workload.Reynold Xin [00:33:41]: Exactly.Matei Zaharia [00:33:42]: Yeah. Yeah. And I remember when we had incidents with our databases and engineers said, “Well, I can't just run a giant query on it to see what's going on because that's gonna bring down the database and hoard it even more.” Like, that's the stuff that this gets rid of, because you spin up a whole separate fleet of machines that's doing the analytics. You're not overloading, like, the main databaseReynold Xin [00:34:02]: RightMatei Zaharia [00:34:02]: that's still trying to serve stuff.Reynold Xin [00:34:04]: Yeah.Matei Zaharia [00:34:04]: Yeah.Why LTAP Works Now: Parquet, Postgres, and LakebaseSwyx [00:34:05]: So this has been a dream for a while. what had to get done in order to get to today? Like,Reynold Xin [00:34:11]: Yeah.Swyx [00:34:11]: I feel like, you have announced variants of this several times, but it wasn't as clear as LTAP.Reynold Xin [00:34:18]: Yeah.Swyx [00:34:18]: I think LTAP is like Like, okay, we've got it, guys.Matei Zaharia [00:34:21]: This thing, yeah.Reynold Xin [00:34:21]: I was talking to somebody at Meta, and then he was asking me, “Hey, what's the catch? Why is it possible now?” And I think the reality is we took a lot of time to work on the Lakebase architecture. obviously a lot of it came from the Neon team, which is a separation of storage from compute. And it turned out it was just a tiny little step away going from that to this LTAP idea, which is, hey, we just. in the Neon architecture and in Lakebase architecture, we're writing data in oriented format to the open data lake, but in there we're writing in Postgres pages. Ali and I were spending a lot of time debating, hey, can we just change that to write in column-oriented format? And we're just debating, and one day, one of our engineers who's, like, super smart came in, he's like, “Hey, I just prototyped it. It works.”Swyx [00:35:07]: Wait, it's, prototype what?Reynold Xin [00:35:09]: Prototype, instead of storing the data in the data lake in the oriented formatSwyx [00:35:15]: ColumnReynold Xin [00:35:15]: like Postgres pagesSwyx [00:35:15]: YeahReynold Xin [00:35:16]: write them in Parquet.Swyx [00:35:17]: Yeah.Reynold Xin [00:35:18]: and he just made the observation that, hey, our storage fleet has a lot of extra idle CPUs And we could use those CPUs to do the transcoding from row to column, where row is good for OLTP, but column is good for analytics. so let's do that transcoding at that time. And as a matter of fact, once you transcode the data compresses better. So from those services writing to, for example, S3 or other data lake, like object stores, you can write them faster ‘cause now they are now smaller.Matei Zaharia [00:35:49]: Yeah.Reynold Xin [00:35:49]: So there's no overhead, it's no compromise in performanceMatei Zaharia [00:35:52]: Some CPU overhead.Swyx [00:35:54]: Yeah, because,Matei Zaharia [00:35:55]: YeahSwyx [00:35:55]: we had extra CPUs anyway.Matei Zaharia [00:35:56]: We had that fleet anyway, yeah.Swyx [00:35:57]: so the debate ended. it's one of the classics of, tech, issue of a lot of debate, but then somebody went ahead and just tried to prototype it and it worked.Matei Zaharia [00:36:06]: But, like, something this strategicSwyx [00:36:07]: That's rightMatei Zaharia [00:36:07]: and important to the company, I expect there to be, like, a kickoff thing, like a design doc. Nothing like that.Swyx [00:36:13]: Nothing like that.Swyx [00:36:14]: He just. We were debating in many meetingsMatei Zaharia [00:36:17]: Yeah.Swyx [00:36:17]: and then we're just debating whether it's possible or not from first principle.Matei Zaharia [00:36:20]: YeahSwyx [00:36:20]: and then, somebody just did it.Matei Zaharia [00:36:23]: Yeah, if you set yourself up so people do that'll be great. And that happened a bit with Omnigentt too. I think if I just had a doc on, like, we can make these together, everyone would, would think, “Oh, what about this? What about this?” But then you. if you try it out, it helps. And then if you have real users and they bash it and, like, it's still working, or in this case, if you have the workload, what the workload looks like, you can just test the same pattern then.Databricks' Culture of Fast PrototypingSwyx [00:36:47]: Yeah.Matei Zaharia [00:36:47]: Yeah.Swyx [00:36:47]: Tech aside, which is very cool, this is, like, the most important thing, the culture of innovation, and you don't have to ask my permission, you don't have like, do a whole form- formal process, just do it?Matei Zaharia [00:36:59]: Well, especially these days, I think withSwyx [00:37:01]: YeahMatei Zaharia [00:37:01]: AI, it's easier to buildSwyx [00:37:02]: But so, likeMatei Zaharia [00:37:03]: a prototypeSwyx [00:37:03]: I think you are very I made a lot of suite of, like, large companies and, like, I think that at scale, things slow down, and I'm sure you felt it already, but somehow you have this core of people that, like, are exempt. How? I think we hire and we work with really good people, and that's a very important part of it, and empowering them, but also spending a lot of time, maybe us in the trenches matter a lot also.Matei Zaharia [00:37:28]: Yeah, I think, I think first, people can adapt to being in the larger company, so that helps. And we wanna make sure they know that they can try stuff and settle debates and have a lot of examples of how it was done before, or launch a thing in beta or whatever. and then the other thing I do think as a company, like despite the size, we don't launch that many, like, products. We try to keep it pretty coherent. That's, that was the whole, like, theory of the company, was like instead of having, like, 20 Amazon services you need to set up, like a analytics and machine learning stack, you just have one, and it's, like, the same API, the same semantics across all of them, the same copy of the data. So that requires, like, unification. And then we added one more thing at a time. Like, we added storage with Delta Lake. We didn't used to do any storage. Then we added SQL, we added, machine learning platform stuff. So, but yeah, don't, don't do too many, but do those things well and, that also helps, it helps keep it manageable.Reynold Xin [00:38:33]: Yeah. The other thing we encourage a lot is instead of building, boil the ocean for everything, let's figure out how do we do it incrementally, how do we do it very quickly. Like, many of our productsMatei Zaharia [00:38:43]: YeahReynold Xin [00:38:43]: they're built in the span of weeks, and then we go to, hey. Like, usually my first question to whoever team is building is who's the target customer? Who are you working with? Are you on a first-name basis with them? Are you texting with them? I think having that very tight loop,Matei Zaharia [00:38:59]: Can you bring up another launch that comes to mind when, in this thing? I just want to give examples.Reynold Xin [00:39:04]: Omnigentt itself happened that way.Reynold Xin [00:39:05]: Yeah.Matei Zaharia [00:39:06]: Who's the customer? That's a good oneReynold Xin [00:39:34]: storage layer we did. we had, our largest customer at the time said like, “Okay, I need some. I want something in the cloud ‘cause, I. if the rest of our network is compromised, like this thing needs to be separate to store and query the events.” And then, talked to us, he said, “Okay, this is the rate of events per second. This is, like, the freshness I want. Can you do it?” So that was, like, way larger than any workload we had, and we had our, engineer, working on that, Michael Armbrust, and he worked just to make this work. And once it worked for them, it worked for everyone else. Yeah. This was early in the company, probably like four years in or something.Matei Zaharia [00:40:24]: 20- 2018?Swyx [00:40:26]: Yeah, ‘17, ‘18.Matei Zaharia [00:40:28]: Few companiesSwyx [00:40:28]: Do you have other examples?Matei Zaharia [00:40:30]: there'Swyx [00:40:31]: Maybe you have othersMatei Zaharia [00:40:31]: yeah, Clean Room, which is how you share data in a way without sharingSwyx [00:40:35]: YeahMatei Zaharia [00:40:35]: underlying data, but you allow specific operations. Those were done effectively initially just for two customers. I think the industry has a sense of, hey, maybe if you overfit to, like, one or two customers, it's gonna be really bad for you. But I think the, downside of overfitting is much smaller than the upside itself. And if you try to be too ambitious and boil the ocean, it's a much bigger problem.Swyx [00:40:58]: Yeah. Yeah.Matei Zaharia [00:40:58]: ‘Cause you might end up having no customer.Swyx [00:41:00]: Yeah, that's more, that's the more likely outcome.Matei Zaharia [00:41:02]: Yeah.Tech Companies vs. EnterprisesSwyx [00:41:03]: than you can pivot from there. I do think there is such a thing as a bad customer that sometimes you should fire. Yeah.Matei Zaharia [00:41:08]: They could exist sometimes if you drive. well, one of the challenge I think we probably see, and maybe many AI, so newer generation companies are seeing is, so tech companies are very different from tech companies or traditional enterprises.Swyx [00:41:22]: Yeah.Matei Zaharia [00:41:22]: And, if you optimize everything just for tech companies, you might have various challengesSwyx [00:41:27]: OhMatei Zaharia [00:41:27]: scaling them outside of tech companies.Swyx [00:41:28]: Okay, what likeMatei Zaharia [00:41:30]: YeahSwyx [00:41:30]: what like top three differences that you always think about?Reynold Xin [00:41:33]: Governance is a big oneMatei Zaharia [00:41:34]: I think, yeah, a big one is like, yeah, security, data privacy, governance, all that stuff. So usually if you're building some kinda like B2B or developer tool, like your biggest market is gonna be enterprises, but it's just very different. A company that's existed for like, it's had some form of IT for like 30 years, they have so many legacy systems or they operate in a regulated space. whereas a startup or, even like a, like sorta more recent tech company, all the. everything is new and pristine. So yeah, it's just different, and if you've never worked with enterprises or been in one, you just won't know about it.Reynold Xin [00:42:13]: Yeah.Matei Zaharia [00:42:13]: Yeah.Reynold Xin [00:42:13]: And the procurement process is probably quite different. There's far more stakeholders.Matei Zaharia [00:42:17]: Yeah, that is one. Yeah.Matei Zaharia [00:42:18]: Another piece that's interesting is I think some tech companies, people, will say, “Oh, I can build that myself,” right? I'll just build that myself.Matei Zaharia [00:42:27]: So then you go,Reynold Xin [00:42:28]: I don't think people say that about Databricks, butMatei Zaharia [00:42:31]: yeah, it dependsReynold Xin [00:42:32]: They do.Matei Zaharia [00:42:32]: They do?Matei Zaharia [00:42:32]: Yeah, the. Yeah, and it depends on the teams and things. So, but, on the other hand, like many of the enterprises say, “I don't, I never wanna be in the business of building that.” Like, I don't want my, whatever, I'm a retailer or something, I never wannaReynold Xin [00:42:45]: Yeah, sell clothes,Matei Zaharia [00:42:46]: be down because like some weird like nerd like couldn't get streaming pipelines working.Matei Zaharia [00:42:51]: That is not what I'm doing.Reynold Xin [00:42:53]: Yeah.Reynold Xin [00:42:53]: Yeah. This makes them great customers, to be honest, right?Matei Zaharia [00:42:55]: Yeah. But you have to understand that it's hard without having worked there and stuff, like you may not appreciate.Reynold Xin [00:43:01]: Look, I think they're all great. don't get me wrong, they have different challenges. But the, many of the tech companies, for sure there's a lot, far more DIY.Matei Zaharia [00:43:10]: On the flip side, you have people who are. they're very much experts in their domain, like they're building airplanes, they're, designing medicines, whatever, and they just want to bridge the technology, where like they don't wanna learn, databases or whatever. As cool as we think it is, even as interesting as the average software engineer might think it is to read a little bit, like they just never wanna know. They just say, “I have a, giant like, matrix or whatever with my, clinical data, like how do I, how do I like cluster it or whatever?” So yeah.The Dream Engine and Rewriting the Database StackReynold Xin [00:43:40]: Yeah. That's true. Okay, so and then I wanted to build out the dream engine, vision. where does this all lead? So one of the thing we, realized maybe a couple years back is that every single database engine out there, especially on the analytics side, are a decade old. pretty much everything that have reasonable traction are about a decade old. And they all started targeting some very specific narrow use cases, and then over time it's become more and more successful. They have grown in their ambition, and then they try to support more and more use cases. But the fastest way to support those use cases tend to be hacked around the abstractions that were initially created, that were not for those use cases.Matei Zaharia [00:44:23]: Yeah.Reynold Xin [00:44:23]: And then, but you can support them more or less okay. And before it, after 10 years of organic evolution that way, it becomes a gigantic pile of s**t.Reynold Xin [00:44:31]: the. And, but that includes Databricks. And very few company or very few systems, I think, have the gut to say, let's go start from scratch. Let's go back to the drawing board and design, knowing everything we know today after a decade of workloads and probably billions in revenue, let's attempt to rewrite it from scratch and make sure it will work and it can support all of these use cases. So we started doing that, but it's a very ambitious project. by the way, you can search on Wikipedia, there's this thing called second system syndrome.Matei Zaharia [00:45:08]: Yeah, I know that. Yes.Reynold Xin [00:45:09]: Or second system effect.Matei Zaharia [00:45:11]: Every developer must know what a second syndrome is.Reynold Xin [00:45:12]: It's you built your first thing and it works out great, and the second one's bound to fail because you become too ambitious.Reynold Xin [00:45:19]: And then you ask so many requirements.Matei Zaharia [00:45:20]: Or like you think everythingReynold Xin [00:45:21]: YeahMatei Zaharia [00:45:21]: and then you're likeReynold Xin [00:45:22]: You justMatei Zaharia [00:45:22]: you're, “I'm gonna design the perfect system this time.”Reynold Xin [00:45:24]: Yeah. And it turned out it's not perfect, and then it start failing and you're too ambitious, never launch, and you get killed. The, and the engineering team that started this, they were brilliant. I think we hired some of the best database engineers, on the planet into Databricks, and they were brilliant. Thank God it's not their second system. Many of them have built more than two in the past.Matei Zaharia [00:45:44]: Ah, nice.Reynold Xin [00:45:45]: But they were still worried about this, hey, building a database engine from scratch, I think the conventional wisdom is gonna take like five years to mature. This would be a very long-term project. It could fail. I think one of the engineers jokingly said, “Hey, maybe we just call it Reynolds Stream Engine.” If we name after a founder, maybe we then may get canceled or killed. But I think they built something pretty remarkable. they went back to. They changed the way the database engines were built from a paradigm point of view. Usually when y

Why did global VCs invest $60M into India's most operationally heavy marketplace problem?The early bet was undoubtedly on the founder, Anjali Sardana.A 23 year old biology graduate from Georgetown University who is today the solo founder of Pronto. The company founded on 2nd April 2024 is at a $200 Million valuation, just a year later and they are growing at god-speed. What began in a single hub in Sector 56, Gurgaon is today 22,000 bookings a day, 5,000+ professionals, and operations across India's biggest cities.But Pronto was never just about convenience. It was built on a belief that India's home services market is broken not just for customers, but even more so for workers. No income stability. No safety net. No formal identity in the system. Not many individual investors write a $20M cheque. Lachy Groom did, alongside General Catalyst and Gladebrook. One year in, Pronto's growth explains the conviction. This episode is the story of the chaos, the urgency and the belief behind one of India's fastest moving startups.00:00 — Trailer01:32 — What is Pronto?03:16 — Hiring the first 30 pros in a single day06:13 — Delivering uniforms in 48 hours08:02 — Hustling to make the first payroll09:23 — The first home office11:28 — Why the customer app is only a nice-to-have17:18 — How pros are trained21:11 — How Gurgaon, Mumbai & Bangalore behave differently29:17 — TAM expands based on ease of access34:58 — Mission is bringing dignity to formal labour42:27 — Pronto's 30-year vision42:48 — How US investors see Indian startups44:37 — How a ₹400 headhunter brought the first hire47:05 — Final round interview for Pronto's chief of staff49:29 — How Anjali hires missionaries54:31 — One thing Anjali would always do as founder58:29 — One thing she's most proud of59:29 — One value Pronto would never compromise on1:01:44 — A company with urgency as core value1:03:55 — What needs to change in India for Pronto to succeed?1:05:18 — How to build a win-win-win business1:07:40 — Why was this problem not solved yet?1:09:02 — If Pronto fails, what would be the reason?1:10:05 — How Anjali spends a day as a solo founder1:15:30 — One lesson learned the hard way-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/neon-fund/X: https://x.com/TheNeonShowwConnect with Nansi on:LinkedIn: https://in.linkedin.com/in/nansi-mishraX: https://x.com/nansi_mishra-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

In episode 121 of The Neon Crew Podcast, Kyle, Mac, and special guest Trevor discuss getting lost in the Backrooms, how we all wish to experience an alien abduction, and identifying just what exactly goes bump in the night.LISTEN TO PODCAST HERE:YouTube: https://www.youtube.com/@theneoncrewpodcast/featured Spotify: https://open.spotify.com/show/3AI17IdYnujCrtSc7M5EKG?si=58d599af20514ae8 Apple Podcasts: https://podcasts.apple.com/us/podcast/the-neon-crew-podcast/id1585795358SOCIAL MEDIA:Facebook: https://www.facebook.com/NeonCrewPodcastYouTube Community: https://www.youtube.com/@theneoncrewpodcast/community Instagram: https://www.instagram.com/neon_crew_podcast/ MERCH: https://www.etsy.com/shop/TheNeonCrewPodcast?ref=shop-header-name&listing_id=1374844203&from_page=listing Music by Gideon HunterGideon's Channel: https://www.youtube.com/@wakerisefall Logo design by Lauren HunterLauren's Instagram: https://www.instagram.com/pineandsun/?fbclid=IwAR1zgGnVTNcnK6lji2A5NhDj-NCmD3f1PLqj1ckjr220HiWvsFJisfy9n8g Films covered on the podcast:https://boxd.it/UKmGq What Goes Bump In The Night: https://open.spotify.com/show/2Z7CX5q7VVoMWHLI3VZfuj?si=f41781f474ff4af2 Timestamps:00:00 | Intro24:02 | Backrooms 1:36:57 | Disclosure Day3:10:08 | Aliens vs. Podcasters (Game)3:23:33 | Kyle's recommendation for episode 122

Send us Fan Mail Pour a drink of your choice and travel back to the 1980s mall scene with us. This episode, we're diving headfirst into Spencer's Gifts—the reigning champion of blacklights, novelty mugs, and teenage rebellion. We talk about the iconic items, the sketchy back room, and why no trip to the mall was complete without it. We want to know what was your favorite purchase from Spencer's Gift Store. https://www.youtube.com/@onedrinkpodcast

"Leviticus" is a 2026 Australian supernatural horror film written and directed by Adrian Chiarella, and stars Joe Bird, Stacy Clausen, Jeremy Blewitt, Ewen Leslie, Davida McKenzie, Nicholas Hope, Zamira Newman, and Mia Wasikowska (who is also an executive producer on the film). It follows two gay teenagers who become tormented by a violent supernatural entity, summoned by their homophobic religious community, that takes the form of the person they desire most – each other. The film premiered in the Midnight section of the 2026 Sundance Film Festival and received positive reviews for its concept, performances, atmosphere, and nuance in crafting a queer horror film with emotional resonance. Chiarella was kind enough to spend some time talking with us about his work and experience making the film, which you can listen to below. Please be sure to check out the film, which will be released in theaters on June 19th from NEON. Thank you, and enjoy! Check out more on NextBestPicture.com Please subscribe on... Apple Podcasts - https://itunes.apple.com/us/podcast/negs-best-film-podcast/id1087678387?mt=2 Spotify - https://open.spotify.com/show/7IMIzpYehTqeUa1d9EC4jT YouTube - https://www.youtube.com/channel/UCWA7KiotcWmHiYYy6wJqwOw And be sure to help support us on Patreon for as little as $1 a month at https://www.patreon.com/NextBestPicture and listen to this podcast ad-free Learn more about your ad choices. Visit megaphone.fm/adchoices

Who is teaching the world's most powerful AI models to think?Turing is one of the largest data partners to OpenAI, Anthropic, Google, Meta, Microsoft, and Nvidia. At a $2.2 billion valuation it has become one of the most important infrastructure layers in the AGI race.Jonathan Siddharth started Turing in 2018 with a thesis that talent matching is a trillion-dollar problem. Turing reached unicorn status in 2021. Then, in 2022, as the foundation model race accelerated, OpenAI approached Turing to provide coding data for ChatGPT.Jonathan recognised that frontier AI labs faced an enormous bottleneck: high-quality training data and human intelligence at scale. Instead of remaining just a talent marketplace, he made a bet that most unicorn CEOs never make. He built a second business on top of the first and leaned back into his AI research roots.Jonathan has a clear view of what needs to happen before we get to super intelligence. The four keys to unlocking AGI: coding, reasoning, tool use, and multimodality. He believes we solve for those four, and AI can do almost anything a human can do in front of a computer. If you are excited about where the AGI race is heading this episode is for you00:00 - Trailer01:06 - What Turing does05:55 - Why OpenAI reached out to Turing8:28 - How GPT-3 became ChatGPT17:54 - How ImageNet breakthrough changed the world21:12 - The largest provider of coding data to AI labs24:34 - Four keys to super intelligence28:45 - Every human will run multiple companies in 10 years32:27 - Can agents have self-improvement loops?34:36 - The future of software engineering36:26 - Agents should create, humans should steer39:46 - Is the line between products and services companies blurring?40:42 - How an agent can handle hiring end-to-end43:36 - Every human can now write software45:22 - Will workflow SaaS disappear?47:46 - No fine-tuning vs fine-tuning camps51:49 - A case study in compute constraints57:06 - Why the world needs so much compute1:01:26 - Where Jonathan would invest today1:03:16 - Where cybersecurity is heading1:08:31 - How the world will look in 10 years-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

Let the heavens shake! It's time for a Count-Pointercount review, as El'Ahrai and John take on "Disclosure Day"! Plus! We draw the curtain on the Hollywood Labor Relations Story Corner...for now. Plus DVD picks, questions, and the rest. Bạn nên lắng nghe! It's not easy having a good time! Even smiling makes my face ache!

In this episode, hosts Dirk Knemeyer and David Heron sit down with Mikey Gilder, the Chief Creative Officer of Avantress Entertainment, known for their hit actual play show Legends of Avantress and the massively successful $9 million+ Kickstarter campaign for Neon Odyssey. The discussion explores the intersection of actual play performance and "crunchy" game design, examining how the rise of shows like Critical Role has fundamentally shifted the way players approach tabletop RPGs. Mikey shares candid insights into the transition from hobbyist to professional publisher, the painful lessons learned while creating The Crooked Moon, and the philosophy of "inverting the pyramid" to provide players with more mechanical "buttons to press" while maintaining narrative freedom. Listeners will find a deep dive into the realities of high-stakes crowdfunding, including how to balance expensive merchandising like plushies and minis with the core integrity of the RPG book.

The Break Room (TUESDAY 6/9/26) 9am Hour 1) This person would like their neighbors to keep their artwork OFF THE APRON! 2) Scariest zoo encounter

Bon jour, and welcome to the show. It's another annual tradition on Time Sensitive where we take you to the French coast of the Mediterranean Sea and recap the world's most prominent and lavish film festival. In fact, this is our eighth Cannes recap on Time Sensitive.The 79th edition of the Cannes Film Festival, which ran from May 12 - 23, 2026, just closed with a controversial Palme d'Or winner, divided critical reception, and an industry increasingly grappling with AI's future.Check us out on...Twitter @TSMoviePodFacebook: Time SensitiveInstagram: @timesensitivepodcastGrab some Merch at TeePublicBig Heads Media  

In this episode of Past Gas, we dive into the explosive rise of the tuner revolution. We explore the wild Motorex scandal that illegally brought the legendary Nissan Skyline GT-R to the US, the neon-lit spectacle of Hot Import Nights, and how a single magazine article birthed The Fast and the Furious. Discover how the World Wide Web and Hollywood mutated grassroots garage builds into a massive global phenomenon.This episode is brought to you by Rocket Money! Let Rocket Money help you reach your financial goals faster. Join at https://www.RocketMoney.com/PastGasAlso thanks to Lumi Gummies for sponsoring this podcast! Go to https://www.LumiGummies.com and use code PASTGAS for 30% off your order.This podcast is also sponsored by BlueChew! Right now, when you buy two months of BlueChew Gold, you get the third for FREE with promo code PASTGAS!And also thanks to Shopify for sponsoring this episode!