Podcasts about Iceberg

Iceberg (u/Thomas_Chinchilla) Rape of Nanjing book SciShow Oh-My-God Particle Video Socials: Instagram/Bluesky - @allthingscreepypod | Email - allthingscreepypod@gmail.com | YouTube | Patreon Learn more about your ad choices. Visit megaphone.fm/adchoices

The Titanic was steaming along, making great time on its maiden voyage, when suddenly everything went catastrophically wrong.That sounds a lot like the Wests Tigers in 2026!On the back of one of the club's darkest nights, the Wests Tigers Podcast is here to have our say on what is going wrong with the team and the club.Frankly, being in this position again is not only extremely frustrating but also a sad indictment of some important aspects of this organisation (primarily the people who pull the strings).Joel and Nick deliver a raw assessment of where things are going wrong, and try to reflect the opinions of fellow fans that what we have witnessed in recent times is absolutely unacceptable.Naturally, as we do on every post-game edition, we share a whole bunch of 'One Word' submissions from the Wests Tigers Podcast Forum, and invite you to have your say as well.It's a dark place the club finds itself in at present; we can only hope that the changes so desperately needed to help this organisation and team flourish (at long last) grow from the mess that has been created.Thanks for being there and listening to or watching our pod; it is greatly appreciated.Become a supporter of this podcast: https://www.spreaker.com/podcast/wests-tigers-podcast--6660380/support.

Iceberg lettuce eyed in parasite outbreak; Midwest sees world's worst air quality as wildfire smoke spreads; Trump teleprompter operator betting allegations; and more on tonight's broadcast. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Canadian wildfires are affecting 120 million Americans air quality. Iceberg lettuce sold at Taco Bell has been linked to the explosive diarrhea outbreak. A Mississippi woman was arrested for a DUI in the nude.See omnystudio.com/listener for privacy information.

Un Été au Havre 2026 est lancé ! Pour cette nouvelle édition, la ville se transforme une fois de plus en musée à ciel ouvert.Dans ce reportage, Lilas interviewe Karl et David. Ils nous dévoilent tout sur deux installations marquantes : Iceberg et Les Optimistes.Anecdotes de montage, défis artistiques et intentions créatives : ils se livrent sans détour sur leur démarche et leur vision du Havre.Pour ne rien rater de la saison artistique, rendez-vous sur le site officiel d'Un Été au Havre.

We learned in grad school that working on joint attention and language will lead to speech development. But for the estimated 30% of autistic children who never develop functional, fluent speech, that's not the whole story. Dr. Karen Chenausky, PhD, CCC-SLP, is a speech scientist, SLP, and director of the SPAN Lab at the MGH Institute of Health Professions. She takes us beneath the iceberg to explore the hidden contributors to speech development in autism, including the motor-speech disorder component our field rarely talks about. In this episode, you'll learn: -Challenges that can limit spoken language in autism include joint attention, receptive language, speech perception, sensory differences, fine/gross motor cascades, and motor speech challenges -Minimally speaking vs. minimally verbal vs. pre-verbal: what each term really means, and why we wait until about age 5 to classify a child as 'minimally verbal' -How Dr. Chenausky identifies suspected Childhood Apraxia of Speech (CAS) in minimally speaking children using Iuzzini-Siegel's (2015) criteria, plus the catch-22 when a child doesn't produce enough speech to diagnose speech motor disorders -What to evaluate in a minimally speaking preschooler: the motor component of speech, language comprehension and expression, nonverbal IQ, and gross/fine motor skills -An invaluable assessment tool you may not know SLPs can use: the Vineland Adaptive Behavior Scales for capturing fine and gross motor performance -Auditory-Motor Mapping Training (AMMT), the intonation-based treatment inspired by Melodic Intonation Therapy, and the promising findings on who benefits most (hint: phonemic repertoire and readiness-to-learn skills mattered) -JASPER (Joint Attention, Symbolic Play, Engagement, and Regulation), Connie Kasari's play-based intervention that builds the prerequisite skills for language -A Monday-morning session framework: three-tiered tasks (mastered, on-the-cusp, challenge) that keep the child at a 70-80% success point in their zone of proximal development -Writing pivotal speech goals that expand the phonemic repertoire while diversifying language expression -When to prioritize robust AAC, because every child deserves access to all the ways of communicating -Dr. Chenausky's call to the field to develop more reliable methods to assess nonverbal IQ and receptive language in children with motor praxis and visual processing/visualmotor challenges Research referenced in this episode Chenausky, K., Norton, A., Tager-Flusberg, H., & Schlaug, G. (2018). Behavioral predictors of improved speech output in minimally verbal children with autism. Autism Research, 11(10), 1356-1365. Free link: https://pubmed.ncbi.nlm.nih.gov/30230700/ Chenausky, K., Brignell, A., Morgan, A., & Tager-Flusberg, H. (2019). Motor speech impairment predicts expressive language in minimally verbal, but not low verbal, individuals with autism spectrum disorder. Autism & Developmental Language Impairments, 4. Free link: https://pubmed.ncbi.nlm.nih.gov/35155816/ *To connect with Dr. Chenausky, Google search "Karen Chenausky SPAN Lab"

Re-Air Date: 7-14-2026 Original Air Date: 6-7-2024 Banning abortion is wildly unpopular and also one of the primary motivators for the group most strongly supporting the Republican Party and Donald Trump, the Christian Right, which has transformed both the party and politicians into extremists made in their own image, threatening the lives and health of millions and sacrificing democracy in the process. Direct Download Transcript Be part of the show! Leave a voice message, message us on Signal at the handle bestoftheleft.01, or email Jay@BestOfTheLeft.com BestOfTheLeft.com/Support (Members Get Bonus Shows + No Ads!) Use our links to shop Bookshop.org and Libro.fm for a non-evil book and audiobook purchasing experience! Join our Discord community! KEY POINTS KP 1: Abortion and Reproductive Rights - Lectures in History - Air Date 3-16-24 KP 2: Abortion and the erosion of privacy - The Weeds - Air Date 4-10-24 KP 3: Digital surveillance and reproductive rights - Technically Optimistic - Air Date 5-15-24 KP 4: Anti-abortion hardliners want restrictions to go farther. It could cost Republicans - Consider This - Air Date 5-23-24 KP 5: Abortion and Reproductive Rights Part 2 - Lectures in History - Air Date 3-16-24 KP 6: Rakeen Mabud on Greedflation, Rachel K. Jones on Mifepristone - CounterSpin - Air Date 4-5-24 KP 7: Abortion and the erosion of privacy Part 2 - The Weeds - Air Date 4-10-24 KP 8: Digital surveillance and reproductive rights Part 2 - Technically Optimistic - Air Date 5-15-24 (56:09) NOTE FROM THE EDITOR On the abuse produced by abortion restrictions DEEPER DIVES (01:01:35) SECTION A: CRIMINALIZING ABORTION A1: Abortion and Reproductive Rights Part 3 - Lectures in History - Air Date 3-16-24 A2: Digital surveillance and reproductive rights Part 3 - Technically Optimistic - Air Date 5-15-24 A3: Abortion and the erosion of privacy Part 3 - The Weeds - Air Date 4-10-24 (01:20:04) SECTION B: ABORTION EXTREMISM OF THE REPUBLICAN PARTY B1: Texas Republicans Want To Execute Women Who Defy Them - Thom Hartmann Program - Air Date 5-30-24 B2: Why Trumps Abortion Video Needs Some Follow-Up Questions - Brian Lehrer: A Daily Politics Podcast - Air Date 4-9-24 (01:35:45) SECTION C: ABORTION IN THE LEGAL SYSTEM C1: Abortion and Reproductive Rights Part 4 - Lectures in History - Air Date 3-16-24 C2: Abortion and the erosion of privacy Part 4 - The Weeds - Air Date 4-10-24 C3: Why Trumps Abortion Video Needs Some Follow-Up Questions Part 2 - Brian Lehrer: A Daily Politics Podcast - Air Date 4-9-24 (01:52:57) SECTION D: WHAT IS THERE TO DO? D1: Digital surveillance and reproductive rights Part 4 - Technically Optimistic - Air Date 5-15-24 D2: NJ Rep. Mikie Sherrill On Abortion Nationwide, And Campus Protests In Her District - Brian Lehrer: A Daily Politics Podcast - Air Date 5-1-24 D3: Rakeen Mabud on Greedflation, Rachel K. Jones on Mifepristone Part 2 - CounterSpin - Air Date 4-5-24 D4: Digital surveillance and reproductive rights Part 5 - Technically Optimistic - Air Date 5-15-24 MUSIC (Blue Dot Sessions) SHOW IMAGE:  Description: A person dressed in a red cape and white conical bonnet with a red sash over their nose and mouth (referencing the Handmaid's Tale) stands outside the U.S. Supreme Court at dusk holding a cardboard sign with the words "This is NOT fiction." Credit: Photo by Tyler Merbler, Flickr | License: CC BY 2.0 | Changes: Cropped   Produced by Jay! Tomlinson Visit us at BestOfTheLeft.com Listen Anywhere! BestOfTheLeft.com/Listen Follow BotL: Bluesky | Mastodon | Threads | X Like at Facebook.com/BestOfTheLeft Contact me directly at Jay@BestOfTheLeft.com

Sauce shares a story where he called 911, John Bonnes is in studio and talks about the surging Twins at the All Star break, Hawk has some 20 year old audioSee omnystudio.com/listener for privacy information.

Vânia Lima é diretora, produtora, roteirista e executiva, sendo um dos nomes mais influentes da atual geração do audiovisual nordestino. À frente da Têm Dendê Produções, empresa sediada em Salvador, construiu uma trajetória marcada pela realização de séries, documentários e longas-metragens, além da defesa do fortalecimento da produção regional. Ao longo de cerca de 25 anos de carreira, participou da criação de mais de 50 obras e se consolidou como uma das principais articuladoras da indústria audiovisual baiana e brasileira.Entre seus trabalhos mais recentes estão as séries Forrobodó da Paixão, Memórias do Brasil, Iceberg e Cantos do Mar, além do documentário Pontos de Força. Integrante do Conselho Superior de Cinema, da diretoria da BRAVI e fundadora da CONNE, Vânia também atua diretamente na formulação de políticas para o setor, defendendo a descentralização dos investimentos e o fortalecimento das produtoras independentes fora do eixo Rio-São Paulo.Neste episódio do Podcast Papo de Cinema convida…, o editor-chefe do site Robledo Milani recebe Vânia para conversar sobre sua trajetória, os desafios da produção audiovisual brasileira, a força das narrativas nordestinas e os caminhos da indústria nacional. Deixe seu comentário. Compartilhe. Se inscreva no nosso canal no Youtube. Deixe sua avaliação nas plataformas de áudio. O Papo de Cinema é e sempre foi totalmente gratuito, mas depende do seu apoio e envolvimento para continuar operando, como temos feito pelos últimos 15 anos. A sua participação é fundamental e faz toda a diferença do mundo para nós!E lembre-se: o Podcast Papo de Cinema pode ser conferido também no Spotify, Apple Podcasts, Amazon Music, Deezer, e Orelo. 

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The crew of the expedition yacht Iceberg set out to explore one of the world's least-visited corners—and found themselves leading a disaster relief mission instead. Learn more at pmymag.com Subscribe to Power & Motoryacht magazine at pmymag.com/subscribe Subscribe to our FREE newsletter Learn more about your ad choices. Visit megaphone.fm/adchoices

Clarence Ford speaks to Primedia Digital Content Editor Barbara Friedman on Barbs Wire about the latest trending stories. Timestamps: 00:00 Intro 00:12 Logo dispute with Molly Tea 05:16 A viral flipping iceberg in Iceland 09:35 A baby with Bad Bunny rhythm Views and News with Clarence Ford is the mid-morning show on CapeTalk. This three-hour programme shares and reflects a broad array of perspectives, inspirational, passionate, and positive. Host Clarence Ford’s gentle curiosity and dapper demeanour leave listeners feeling motivated and empowered. Known for his love of jazz and golf, Clarence covers a range of themes, including relationships, heritage, and philosophy. Thank you for listening to a podcast from Views and News with Clarence Ford. Listen live on Primedia+ weekdays between 9 am and 12 pm (South African time) on CapeTalk https://buff.ly/NnFM3Nk For more from the show and catch-up podcasts, go to https://buff.ly/erjiQj2 Subscribe to the CapeTalk newsletters https://buff.ly/sbvVZD5 Keep the conversation going online: CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567See omnystudio.com/listener for privacy information.

We do a deep dive on one of the coolest cold weather Joes Berg BURG berg. GI Joburg is grateful to 3DJoes.com for all the good looking pics. The amatuerish ones are most likely taken by us! Join this channel to get access to perks: https://www.youtube.com/channel/UC0W3wPhykE4Z6NDF5WgdGew/join Got something to say to GI Joburg? We can be reached at arealsouthafricanhero@gmail.com We have an official Patreon page! Go to https://www.patreon.com/GIJOBURG?fan_landing=true Want some of the most unique GI Joe apparel out there? Check out our official GI JOBURG merch at: https://teespring.com/stores/gi-joburg-the-merch  

Threshold signatures are coming to Bitcoin, but getting them right is harder than it looks. Nadav Kohen of Chaincode Labs walks through his work proving nested MuSig is secure, the road toward FROST-style thresholds, and his upcoming scheme codenamed "Iceberg." He breaks down the famous Alice, Bob, and Carol 2-of-3 example and shows why the obvious approach actually leaks secrets. Grab your copy THE 2036 ISSUE

An examination of the deepest level of the Ancient Mesopotamia iceberg, commonly labeled "Theories and Speculative Ideas." The video reviews each claim against primary sources from Sumer, Akkad, Babylon, and Assyria, including cuneiform tablets, excavation reports, and geological data, to demonstrate how historical method evaluates extraordinary claims.Coverage includes: Ancient Astronauts and the Annunaki: the origin of the theory in Zecharia Sitchin, what the Akkadian term actually means in Mesopotamian religion, and the evidential standards for alien contact claims. Great Flood myths: comparison of the Epic of Gilgamesh, Genesis, and other flood traditions with evidence for Persian Gulf and Black Sea inundations. Gilgamesh's tomb discovered in 2003: the Uruk excavation, the Iraq War interruption, and why no inscription links the tomb to the historical king. Hanging Gardens location: the case for Nineveh and Dur-Sharrukin, Archimedes screw technology by 700 BC, and why Babylon remains plausible. Nimrud Lens and Saturn's rings: what the 3x quartz lens can and cannot do, and the absence of telescopic astronomy in Assyrian records. Annunaki gold-mining slaves: the actual Mesopotamian creation motive of humans as laborers for the gods versus modern reinterpretations. Abraham from Ur: the biblical text, the Amorite migrations circa 2000 BCE, and the northern vs southern Ur debate. Sumerian King List long reigns: hundreds of thousands of years, symbolic numbers, and attempts at dynastic or calendrical readings. Sumerian origins: language isolate status, the Persian Gulf marsh hypothesis, and pre-flood settlement theories. Nibiru and the 12th planet: claims of hidden planets in tablets and the current state of translation work. 4.2 kiloyear event: climate data and its role in the fall of the Akkadian Empire alongside Gutian pressure. Structures beneath Eridu: the E-Abzu temple's 18 rebuild phases and what lies under ziggurat foundations. Linguistic fringe theories: proposed links between Sumerian and Turkic, Hungarian, Elamite, and Dravidian. Meluhha trade network: Indus Valley contacts, Neo-Assyrian memory loss, and claims of an Ethiopia-to-India empire. Nuclear war dark ages: why nuclear events leave unmistakable geological signaturesSumerian copper from Lake Michigan: sourcing from Cyprus and Iran versus New World contact hypotheses. Sacred marriage as genetic experiment: Ishtar priestess rituals and kingship legitimation. Ur III bala system as socialism: command economy, ration payments, and modern ideological projections. King List as doomsday calendar, Nam-Shub virus, 676 BC simulation, and Enki vs Enlil secret societies: modern fiction, numerology, and conspiracy narrativesThe purpose is not to ridicule speculation, but to show what counts as evidence in early Mesopotamian studies, where the limits of knowledge currently lie, and what kind of discovery would be required to reopen closed questions.Keywords: ancient Mesopotamia, Sumerian history, Akkadian Empire, Babylon, Assyria, Annunaki explained, ancient aliens debunked, Sumerian King List, Gilgamesh tomb 2003, Nibiru 12th planet, Hanging Gardens Nineveh, Nimrud lens, flood myth, 4.2 kiloyear event, Mesopotamia iceberg

Grok says: “In this episode of Randumb Thoughts, Darren O'Neill dives deep into Hemingway's Iceberg Theory — the idea that the most powerful storytelling (and truth) lies beneath the surface, with only a small fraction visible above the water. Using that framework, he explores why so many people can look at the exact same information — whether it's a Supreme Court ruling on birthright citizenship, the ambiguous ending of The Bear Season 5, or a viral news story — and come away with completely opposite conclusions. It's not just politics. It's a growing cultural divide where subtext is disappearing and surface-level takes rule. Darren breaks down the 14th Amendment's “subject to the jurisdiction thereof” clause, questions Ketanji Brown Jackson's logic, and highlights the warnings from Justices Thomas and Alito about foreign adversaries creating instant U.S. citizens. He then connects the dots to modern attention spans, social media brain rot, and why so many viewers completely missed the point of The Bear's finale. The conversation shifts to the House passing the Kids Internet Safety Act and why age verification laws are missing the real problem: parents handing devices to 11-year-olds. If you're tired of surface-level noise and want someone willing to go beneath the waterline, this episode of Randumb Thoughts 368 is for you.” Thanks for listening! EXECUTIVE PRODUCERS:WeenieWaWaMark KodraTHANK YOU FOR SUPPORTING THE SHOW! PLEASE SUPPORT RANDUMB THOUGHTS!TRY PROTONMAIL: https://t.co/9i2GPq3gNBTRY INCOGNI: https://incogni.cello.so/KpYfMWSF57i SUBSCRIBE / DONATE: http://randumbthoughts.com/donatePATREON: https://patreon.com/randumbthoughts CHECK OUT MY OTHER SHOWS: PLANET RAGE: https://planetrage.showUNRELENTING: https://unrelenting.showGRUMPY OLD BENS: http://grumpyoldbens.com Thank you for listening to Randumb Thoughts! Please, tell a friend!

Who is really profiting from the small boat crisis? Andrew Gold sits down with investigative journalist Zak Garner-Purkis of Daily Express, who has gone undercover to expose the massive "iceberg" of organized crime operating right under our noses. From delivery app exploitation and suspicious high street barber shops to the terrifying reality of human trafficking and modern slavery—this isn't just about politics; it's a lucrative criminal industry worth more than the drug trade. In this episode, we reveal the three red flags of criminal networks in your neighborhood, the truth about the "shadow GDP," and the shocking failures within the bureaucratic class and the CPS that allow these networks to flourish. Watch to the end to see the three red flags you need to spot on your own high street. SUPPORT MY SPONSORS LINGOPIE: Use my link for a free trial and 55% OFF on the yearly plan: https://learn.lingopie.com/heretics RUMBLE WALLET: Take Control of Your Money and claim $5 in US Stablecoin (USA₮)! Download now at http://wallet.rumble.com/heretics and use the code Heretics5. Chapters 0:00 The "Iceberg" beneath the surface 04:18 Trafficking is more profitable than drugs 08:24 The "Vape Shop" math that doesn't add up 12:56 S* trafficking vs. Labor trafficking 16:44 The Albanian TikTok "Dream" vs. Reality 21:51 The $1,000 "Dingy" debt trap 26:54 The trafficker hiding in the hotel 31:11 Why French police want them to leave 37:08 The "Shadow GDP" draining the UK 41:12 Red Flag #3: It's on your high street right now 45:49 The "Pedo-Asbo" & bureaucratic cover-ups 51:06 The "Vacuum" in the British media 56:12 The truth about begging gangs Hashtags #AndrewGold #SmallBoats #HumanTrafficking #ModernSlavery #OrganizedCrime #InvestigativeJournalism #UKPolitics #BorderForce #SocialIssues #heretics Third-party footage credit Source clip: “Up to 50 migrants launch dinghy from Calais beach unhindered by French police | ITV News” Publisher: ITV News Reporter: Dan Rivers Published: 16 November 2021 Platform: YouTube URL: https://www.youtube.com/watch?v=x879wqdfrqM Use: 3-second excerpt used for commentary/criticism under fair dealing. Copyright: © ITV News / ITV plc. All rights remain with the original copyright holder. Learn more about your ad choices. Visit megaphone.fm/adchoices

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

Double the "E for explicit" in this episode, as I really went for it.  What can I say?  Sometimes there's no substitute for some good old-fashioned vulgarity.  More talk about corruption and abuse by those chosen to protect us from those very things will make a fellow quite cross.  Enjoy the saltiest of episodes.With love on number 101!-T

Mayor Palmer joins to answer some common questions we're getting about fireworks (including why we as a city can't ban them entirely), talks about this week's Towne Days event, and celebrates ribbon cuttings for Monument Park, Wide Hollow trailhead, and Iceberg. Have a question? Leave a comment or email us at communications@herriman.gov and we'll address it in a future edition. 0:00 Start 0:34 Intro 1:24 Towne Days 3:52 Fireworks 10:53 Iceberg is back 11:33 Wide Hollow trailhead 12:52 Monument Park 14:16 World Cup 16:02 Wrapup

► Help us to release the George Connelly documentary: https://www.crowdfunder.co.uk/p/george-connelly-celtic-film

In this episode, David Rubinstein talks with Craig Kerstiens, Snowflake's Director of Software Engineering on Postgres, about the enduring popularity of Postgres, a 30-year-old database technology, due to its reliability and recent innovations like JSON support and vector store databases. He highlighted the challenge of integrating operational (OLTP) and analytical (OLAP) data for AI applications, noting the importance of reducing latency and operational burden. Kerstiens introduced PG Lake, an open-source tool that embeds Iceberg in Postgres, simplifying data movement and querying. He also mentioned Snowflake's mirroring feature and the future of Postgres, emphasizing its continuous improvement and extension ecosystem.

The deeper you go, the darker it gets. Gareth Morgan presents The WWE Conspiracy Iceberg EXPLAINED...ENJOY!Follow us on Twitter:@GMorgan04@WhatCultureWWEFor more awesome content, check out: whatculture.com/wwe Hosted on Acast. See acast.com/privacy for more information.

Dirige y presenta Juan Carlos Baruque Hernández Sumario del programa RAFAEL PÉREZ *Especial historia: La batalla de Okinawa. Nuestra Web: https://mundoinsolitoradio.es Contacta: +34 687 39 80 12 - Solo WhatsApp mundoinsolitoradio@hotmail.com Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

Tosh Wanogho-Maud is the alternate Lola in the West End revival of Kinky Boots.Tosh guest stars as Lola on Monday evenings at the London Coliseum, having previously played the role full-time on the European leg of the show's tour.Prior to joining Kinky Boots, Tosh starred as The Iceberg in the West End production of Titanique (Criterion Theatre). His theatre credits also include David Ruffin in Ain't Too Proud (Prince Edward Theatre), Ben E. King and Rudy Lewis in The Drifters Girl (Garrick Theatre), Jimmy "Thunder" Early in Dreamgirls (Savoy Theatre), Pharaoh in Joseph and the Amazing Technicolor Dreamcoat (Toronto), Little John in Robin Hood (London Palladium), Jud Fry in Oklahoma! in Concert (Theatre Royal Drury Lane), Reverend Hightower in Bat Boy in Concert (London Palladium), Buddy Foster in Side Show in Concert (London Palladium), Joe in Show Boat (Gillian Lynne Theatre), Mutumbo in The Book of Mormon (Prince of Wales Theatre), Young Simba in The Lion King (Lyceum Theatre) and Winston in Whistle Down the Wind (Aldwych Theatre).His screen credits include Man on Phone in Still Up (Apple TV+), Suitor in Bridgerton (Shondaland/Netflix), Husband in Roadkill (BBC One), Police Officer in A Discovery of Witches (Bad Wolf) and Pip in Jingle Jangle (Netflix). Marking his third time In The Frame, in this episode Tosh discusses returning to Kinky Boots and stepping into the heels of Lola in the West End. He talks about how he approaches the role and why it's meaningful to be embracing a different side of his identity onstage. Tosh also shares his thoughts on advocating for yourself in this industry, with lots of other reflections (and plenty of chaos!) popping up along the way.Kinky Boots runs at the London Coliseum until 11th July, with Tosh performing as Lola every Monday.Visit www.kinkybootslondon.com for info and tickets. This podcast is hosted by Andrew Tomlins @AndrewTomlins32 Thanks for listening! Email: andrew@westendframe.co.uk Visit westendframe.co.uk for more info about our podcasts. Hosted on Acast. See acast.com/privacy for more information.

So many relationships don't end because of a massive, explosive crisis—they fall apart slowly, an inch at a time, through simple, quiet neglect. It's an emotional erosion that happens so gradually you don't even notice the ground shifting beneath your feet until the dam suddenly breaks.In Part 2 of the Faith & Family series, we are tearing down the scripts, expectations, and communication traps that quietly build walls in our homes. Pulling foundational frameworks from the book Forever and Ever, we break down the universal "anatomy of a fight" and explain why couples struggle to connect when one person processes like an "Iceberg" and the other like an "Ocean Wave."Whether you are married, engaged, or single and preparing for the future, this episode is a raw, down-to-earth look at how to move your relationship past a conditional contract and transform it into an unbreakable covenant. It's time to stop keeping score, step out of the daily grind, and learn how to put your actions where your mouth is to protect the person you love.In this message, you'll discover:Why clarity is your absolute best defense against resentment and misunderstanding.The Iceberg vs. Ocean Wave dynamic and how to navigate emotional differences in real time.How differing "value mindsets" (quantity vs. quality) trigger accidental arguments.The three non-negotiable areas of investment that couples neglect when life gets heavy.How to apply the warnings of James and Revelation to breathe fresh life into your first love.—To connect, learn more or donate, visit gravetopchurch.com  Follow us on Instagram, Facebook or TikTok by searching @gravetopchurch

Infinite Beingness is being finite by being you.  Like an iceberg in the ocean, you have a clear and distinct sense of individuality, yet you are made of the same substance you are melting into. Iceberg and sea are like time and timelessness interwoven together. I found timelessness by listening to the clocks ticking in my elementary classrooms. I stopped hearing the teacher as I listened to the silence between the ticks. Looking back, I think I was meditating…     Read Gurudevi's Teachings Article in our Freebies.         #time #timeless #timelessness #eternal #iceberg #meditate #meditation #gurudevi #yogamysticism #spirituality #divine #yoga #swaminirmalananda #blissyoga #svaroopayoga #siddhayoga #muktananda #gurudevinirmalananda 

El Titanic es uno de los naufragios más famosos de la historia. Pero muchos detalles de lo que sucedió exactamente siguen siendo un misterio. Uno de ellos: ¿qué pasó con el iceberg que hundió al Titanic? Resulta que el iceberg estuvo flotando durante un año más después del naufragio. Revelaremos uno de los secretos que rodean al Titanic. Learn more about your ad choices. Visit megaphone.fm/adchoices

We finally told the story the way it was meant to be told.From Saints OGs.From SD cards to studios.From WuN to the world. We broke down the battles, the shows, the clubs, the breakups, the pressure, the distance, the brotherhood.We honored Iceberg — the man, the mind, the verse, the pain, the brilliance. This episode isn't for clicks.It's for the Goons.It's for the era.It's for the generation. It's for Iceberg. RIP Dalitso "Iceberg" Mtambo You live forever in this Wun. TLSDStream the track:Apple: https://music.apple.com/gb/album/is-it-a-moment/6777764168?i=6777764169Spotify:https://open.spotify.com/track/4RAuOX3Y4jyzq9lm51R03n?si=ja7zcGoaTKOxwYQmvvW2AA

Receive the unfiltered memos I send my team as we scale Acquisition.com to $1B+:https://leilahormozi.com/subscribe Don't judge your boss by what you see, because their most important responsibilities are not necessarily visible. In this episode, Leila breaks down the iceberg illusion of leadership and why an employee might be oblivious to 90% of the work that's done by their leader. And entrepreneurs must train their team members to think, decide, and act like owners.In this episode00:00 How empathy for a boss can change career trajectory02:00 The iceberg illusion of leadership04:29 Leadership lessons from Phil Jackson's triangle offense05:56 Delegating decisions vs. delegating tasks08:26 Scheduling absence and training replacements More Value:Get your personalized $100m scaling roadmap: https://www.acquisition.com/roadmap Read the unfiltered memos I send my team as we scale Acquisition.com to $1B+: https://leilahormozi.com/subscribeReceive a curated set of internal memos from the past year at Acquisition.com: https://leilahormozi.com/acq Watch my latest YouTube videos: https://www.youtube.com/@leilahormozi/featuredLearn how to scale your business to millions of dollars in annual revenue: https://www.acquisition.com/ DISCLOSURE Information shared here is for educational purposes only. Individuals and business owners should evaluate their own business strategies, and identify any potential risks. The information shared here is not a guarantee of success. Your results may vary. Copyright © 2026.

By now most organizations have AI strategies (among their other tech strategies). But how do you know when it's time to make a midcourse correction? Better still: How can you predict when, and what kind of corrections you might need? John and Johna discuss, and tell the story of how a university prepared for technology... Read more »

By now most organizations have AI strategies (among their other tech strategies). But how do you know when it's time to make a midcourse correction? Better still: How can you predict when, and what kind of corrections you might need? John and Johna discuss, and tell the story of how a university prepared for technology... Read more »

This episode was edited by author Cody Ray George, links in the details! Welcome to Cryptic Chronicles, where we delve into the shadows of the unknown. Today, we're descending into the depths of the Dark and Disturbing Video Games Iceberg — a chilling exploration of unsettling digital realms where nightmares are brought to life through eerie aesthetics, cryptic narratives, and haunting experiences. From obscure horror titles and cursed game lore to unsettling 4th wall breaks and urban legends, we'll uncover the sinister underbelly of gaming that blurs the line between fiction and unsettling reality. So, ready your mind for a deep dive into the dark, where pixels and paranoia intertwine. Stay tuned — things are about to get unsettling. Follow me on X: https://x.com/CrypticChrncles BUY MERCH! https://httpscrypticchroniclescom.creator-spring.com/ Patreon: https://www.patreon.com/c/crypticchronicles Magic Mind: https://magicmind.com/CRYPTICCR20 Use code: CRYPTICCR20 SOURCES: The Dark and Disturbing Videogames Iceberg YouTube: https://www.youtube.com/watch?v=3gynhyb_aYI Reddit Original Poster: https://www.reddit.com/r/creepygaming/comments/tnzcum/the_definitive_darkcreepyscarydisturbing_video/ Cody Ray George: YouTube- https://www.youtube.com/channel/UCUwokE3_URWJc_5cQY7rm6Q Twitter- http://www.twitter.com/ggghhhost Patreon- https://www.patreon.com/CodyRayGeorge PayPal- https://www.paypal.me/mymusicisawful Instagram- https://www.instagram.com/spirittravelplaza/ LinkTree- https://linktr.ee/codyraygeorge Amazon- https://www.amazon.com/stores/author/B0952D335W

By now most organizations have AI strategies (among their other tech strategies). But how do you know when it's time to make a midcourse correction? Better still: How can you predict when, and what kind of corrections you might need? John and Johna discuss, and tell the story of how a university prepared for technology... Read more »

Stuck at the same swimming speed? In this episode, we break down how to smash through your training plateaus by fixing the "bottlenecks" in your technique. Drawing from 19 years of coaching experience, we share the exact step-by-step checklist to optimize your stroke: reducing drag through perfect head and body position, mastering breath control to avoid fatigue, and engaging your lats for a more powerful, effortless pull. Stop just training harder—learn how to swim smarter and finally unlock your next breakthrough. 00:00 Why swimmers plateau and the concept of stroke "bottlenecks." 01:11 The simple formula for speed: Reducing drag vs. increasing propulsion. 01:35 Step 1: Head position, posture, and why you need an "open chest." 03:22 The "Iceberg" rule: Balancing head weight to keep your hips up. 04:05 Posture secrets: How correct body position lets the water support you. 05:08 Step 2: Breath regulation and how improper exhaling causes CO2 buildup. 06:51 Step 3: Catch and pull mechanics (using the catch as a setup, not for power). 08:17 Mastering gradual stroke acceleration instead of pulling too hard early. 08:58 Muscle activation: Engaging your lats and triceps to prevent shoulder injuries. 10:01 Using video analysis to find your bottleneck and build a 3-to-6-month plan.

A pair of tour guides from Greece tell us how the island of Crete offers a natural experience unlike any other. Then travel writer Mark Adams describes his 3,000-mile voyage along the coasts of Alaska to follow what the Harriman Expedition saw in 1899. And a Dutch biologist explains how urban evolution is happening faster than we used to think all over the world. For more information on Travel with Rick Steves - including episode descriptions, program archives and related details - visit www.ricksteves.com.

Ryan Carter is coming to the end of his run as The Iceberg in the West End production of Titaníque at the Criterion Theatre.Ryan is a multi-faceted performer and creative. Prior to his run in Titaníque, Ryan starred as Jagwire in Bat Out Of Hell in the West End and on tour.His other theatre credits include: Motown The Musical (Shaftesbury Theatre), Choir Of Man (Edinburgh Fringe Festival), The Boyfriend (Menier Chocolate Factory) and The World Goes Round (Barn Theatre). Most recently, Ryan played Smokey Robinson and covered Eddie Kendricks in the West End production of Ain't Too Proud (Prince Edward Theatre).As the Creative Producer of RyCa Productions, Ryan produced the acclaimed Refresh concerts, as well as a series of shows at Jack Solomons. Ryan was one of the Creative Directors for Turn Up London and was Creative Director of Digital Projects for The Barn Theatre, where he made the interactive concert The Secret Society of Leading Ladies and worked on Now Or Never by Matthew Harvey. He was the Casting Director for The Wiz at the Hope Mill Theatre and has also worked with Urdang. Ryan also does graphic design and creates and manages social media content for productions within the theatre industry, including the UK premiere of Ride The Cyclone and the reunion concert of Spring Awakening.In this episode, Ryan discusses landing his role in Titaníque and the impact of Bat Out Of Hell. He also delves into his work as a creative, explains why it is important for him to stand up for what he believes in and reflects on his path into theatre.Ryan plays The Iceberg in Titaníque at the Criterion Theatre until 7th June 2026. Follow him on Instagram: @ryanjesse95 This podcast is hosted by Andrew Tomlins @AndrewTomlins32 Thanks for listening! Email: andrew@westendframe.co.uk Visit westendframe.co.uk for more info about our podcasts. Hosted on Acast. See acast.com/privacy for more information.

Are you enjoying this? Are you not? Tell us what to do more of, and what you'd like to hear less of. The Reykjavík Grapevine's Iceland Roundup brings you the top news with a healthy dash of local views. In this episode, Grapevine publisher Jón Trausti Sigurðarson is joined by Heimildin journalist Aðalsteinn Kjartansson, and Grapevine friend and contributor Sindri Eldon to roundup the stories making headlines in recent weeks. On the docket this week are: Ten Since Municipality Elections, But No Majority Coalition Yet Formed In ReykjavíkThe big winner of the Reykjavík municipality elections was The Independence Party. The party's slogan for the city elections was Strax-D or Immediately-D, yet 10 days after the election, with no new coalition in sight, voters may start to wonder what exactly “immediately” actually means.Iceland N-Korean Friendship Association Formed During PsychosisThe founder of the Iceland - North Korean Friendship Association told visir.is she had been in a pshcosis when the association was formed. Mia Marcelina Alexa Guðmundsdóttir founded the association back in 2022 along with a Sunneva Náttsól. According to Mia, she at that point, she supported extreme interpretation of communism. She now says, in a op-ed she published on visir.is, that psychosis had caused her to support extreme, simplified ideology, which she does not support anymore.Icelandair Flights Keep Getting CancelledNumerous Icelandair flights have been cancelled in the past days and weeks because of the airline being unable to get pilots to pilot their plains. While the pilots don't explicitly say why this is, on the face of it it looks to be a part of a debate between the airline and the pilots that work for it, with regards to Icelandair possibly moving parts of their operations abroad, probably to get out of the baggage of paying Icelandic salaries to crews.Do The Icelandic Fisheries Own Everything In Iceland?A new parliamentary report addresses the ownership of Icelandic fisheries in other sectors of the economy. However, the report has been reported for being too limited in its definitions of what is and isn't owned by the fisheries, and one parliamentarian said that the report only caught the “top of the Iceberg” that is that sectors ownership in Icelandic businesses.Nobody Wants A Ferris Wheel In Reykjavík, AgainDuring the past few summers, a ferries wheel has been operated by Reykjavík's harbor, to little enthusiasm by the locals, and what seems like little attendance. The mayor of Reykjavík has suggested that the ferries wheel should be put up yet again, but locals have started a petition to oppose the motion.The Synthetic Windpipe Scandal, Paolo Machiarini and IcelandA tort case filed by against the Icelandic state by the widow of Andemariams Teklesenbet Beyene, who had a synthetic trachea implant in Sweden in a procedure performed by Paolo Macchiarini in 2011, was concluded last week, with the widow winning the caseSupport the show------------------------------------------------------------------------------------------SHOW SUPPORTDonate to the Grapevine here:https://support.grapevine.isYou can also support the Grapevine by shopping in our online store:https://shop.grapevine.is------------------------------------------------------------------------------------------This is a Reykjavík Grapevine podcast.The Reykjavík Grapevine is a free alternative magazine in English published 18 times per year, biweekly during the spring and summer, and monthly during the autumn and winter. The magazine covers everything Iceland-related, with a special focus culture, music, food and travel. The Reykjavík Grapevine's goal is to serve as a trustworthy and reliable source of information for those living in Iceland, visiting Iceland or interested in Iceland. Thanks to our dedicated readership and excellent distribution network, the Reykjavík Grapevine is Iceland's most read English-language publication.You may not agree with what we write or publish, but at least it's not sponsored content.www.grapevine.is

Is this the end for the hit reality dating show, Married At First Sight? Were the inaugural ‘Enhanced Games' a hit or flop? And what does the end of Stephen Colbert's Late Show tell us about where late-night TV is going? Channel 4 has pulled Married at First Sight UK from streaming in the wake of sexual abuse allegations by former participants. Richard Osman and Marina Hyde unpick what this means for Channel 4, and whether the controversial format is too toxic to save. The Enhanced Games saw elite athletes flock to Las Vegas for a contest where performance-enhancing drugs were encouraged, not banned. Will this herald a new age of sporting entertainment? Stephen Colbert has bid farewell to The Late Show, an institution of America's small screen. But what will happen to late-night TV without it? And what will Colbert do next? The Rest is Entertainment is brought to you by Octopus Energy, Britain's most awarded energy supplier. Lloyds. 250 years on and still backing the nation's aspirations. Join The Rest Is Entertainment Club: Unlock the full experience of the show – with exclusive bonus content, ad-free listening, early access to Q&A episodes, access to our newsletter archive, discounted book prices with our partners at Coles Books, early ticket access to live events, and access to our chat community. Sign up directly at therestisentertainment.com For more Goalhanger Podcasts, head to www.goalhanger.com Video Editor: Joey McCarthy & James Clayden Assistant Producer: Imee Marriott Senior Producer: Joey McCarthy Social Producer: Bex Tyrrell Exec Producer: Sam Psyk & Neil Fearn Filmed at www.westdigitalstudios.com Learn more about your ad choices. Visit podcastchoices.com/adchoices

Entrevista a José Luis del Pozo, especialista en microbiología, sobre el brote de ébola: "Probablemente sea la punta del iceberg"

This week we sit down with Field Solution Architects Anthony Nocentino and Justin Emerson explore an interesting convergence happening in data architecture—the blending of traditionally separate block and file/object storage systems. Likening the experience to a Chocolate Peanut Butter Cup, Anthony (a database expert focused on block storage) and Justin (an expert in unstructured data and file/object storage) discuss how the clear historical distinctions between structured and unstructured data are rapidly blurring. This shift is fueled by modern challenges like high-scale analytics, data governance, and the rise of technologies like Large Language Models (LLMs) and agentic interactions, which no longer care where the data lives. Our conversation dives into the technical tipping point enabled by data virtualization, referencing features like SQL Server 2022's object integration, which allows a database engine to access data stored efficiently on object storage. This capability is far more than an archival play; it helps customers achieve scale-out analytics, improve data governance by maintaining one canonical copy of data across different performance buckets, and simplify tedious operations like SQL backups by bypassing legacy file system complexities. Anthony and Justin highlight how Everpure's platform aligns perfectly with this new reality. Finally, Anthony and Justin discuss the path forward, noting that the technology is underutilized due to organizational silos and an awareness problem. The next big evolution will focus on security and governance for this distributed data via open table formats like Iceberg and catalogs such as Polaris. We close with what currently excites them: Anthony on collaborating with AI (Claude) to create code and speed up outcomes, and Justin on Everpure's core philosophy of simplicity, efficiency, and treating customers like people, particularly in the context of the current economic conditions. To learn more, visit: https://www.everpuredata.com/platform.html Check out the new Everpure digital customer community to join the conversation with peers and Pure experts: https://purecommunity.purestorage.com/ 00:00 Intro and Career Journeys 04:30 Customer Engagement and SKO 09:55 Vacation Recap 13:45 History of Block and Object Storage 16:04 Why Convergence Now? 20:30 Data Virtualization 25:55 Exploring Access Patterns 29:05 What's Holding Back Adoption 36:02 Simplicity for DBAs

In this high-energy kickoff episode, Tyler Kamerman stands before the Clive Emerging Leaders to lay down a foundational blueprint for what it truly means to be an "Intentional Pursuer." Drawing from his own hilarious fifth-grade confessions of "diarrhea of the mouth" to a mid-life career crisis at age 43, Tyler shatters the corporate obsession with the badge of "busyness." He challenges listeners to stop hiding behind overscheduled calendars and instead look backward to their childhood playgrounds to excavate the authentic raw sparks that God uniquely hardwired into their DNA. The episode delivers a massive reality check on what pursuing your calling actually looks like, debunking the myth of the flawless career path through concepts like the 20% "Suck Factor" and the Iceberg of Success. By blending tactical strategies like the 24-Hour Pause with deep theological insights on identity, Tyler reframes passion not as a luxury item for a side hustle, but as the essential, sustainable fuel required for kingdom significance. This is a fierce, witty, and grace-filled charge to stop playing a character, build a trusted community, and confidently step into your own "Send Me" moment. Key Takeaways - Embrace the 20% Suck Factor: Even in your absolute dream job, a portion of the work will simply drain you (like Tyler's spreadsheets!). True passion doesn't eliminate the grind; it gives you the extra willpower and resilience to push through it. - Practice Playground Archaeology: To discover what makes you come alive today, use the 7/10 Rule. Look back at what you naturally loved doing between the ages of 7 and 10 before the world told you your dreams were unrealistic. - Deploy the 24-Hour Pause: Banish the "automatic yes" from your vocabulary to protect your time. Use a script to give yourself a day to evaluate whether an opportunity is a "Heck Yeah" or a "No, Thank You." - Become a "Relevant Surprise": Avoid becoming a replaceable corporate commodity by pairing your professional relevance (your career skills) with a beautiful surprise (your unique, God-given passions).   To connect with Tyler: https://www.tylerkamerman.com/

Special EpisodeGet tickets for the Deep Leaders: One Day Leadership Experience.September 30, 20269am - 3pmRome, GADeep Leaders - Dr. Chris Auger, BCCWhy it's important for leaders to "first look in the mirror"Who is leadership training for?What will attendees experience at the Deep Leaders: One Day Leadership Experience?What are the origins of servant leadership?Dr. Chris Auger, BCC, is a Retired US Navy Seal, the Founder of Deep Water Leadership, Executive and a Leadership & Team Performance ConsultantLinkedIn: Dr. Chris Auger, BCCEmail: chris@deepwaterleadership.comShoutouts and References: Servant LeadershipRobert GreenleafJohn MaxwellDaniel GolemanSimon SinekJesusNews and UpdatesGet tickets for the Deep Leaders: One Day Leadership Experience.September 30, 20269am - 3pmRome, GAWhat does WorkPlay Solutions do?We believe that life's too short for work to suck. We train teams to communicate and leaders to get results - the fun way!  WorkPlay Solutions is an authorized partner of Everything DiSC® and the Five Behaviors®.Website: www.workplaysolutions.comLinkedIn: company/workplaysolFacebook: @workplaysolInstagram: @workplaysolPodcast Info:Host: Mark Suroviec, M.Ed.Music: Music by REDproductions from Pixabay

El Pentágono acaba de hacer algo insólito: publicar online, al alcance de cualquiera, su archivo oficial sobre el fenómeno OVNI. Medio siglo de casos, informes desclasificados, imágenes y testimonios que hasta hace nada dormían en cajones clasificados. La pregunta no es si es un paso histórico —lo es—. La pregunta es otra: ¿estamos viendo una política real de transparencia, o la coreografía perfecta para seguir controlando el relato? En este episodio abrimos el portal, miramos lo que contiene, y sobre todo, lo que no. Porque a veces lo importante no es lo que te muestran. Es lo que deciden no mostrarte. Y además: Mierdificación, con Daniel Arias Aranda. La Capilla Sixtina del Románico (y el grial que nadie esperaba), con Fran Contreras Escucha el episodio completo en la app de iVoox, o descubre todo el catálogo de iVoox Originals

The hit "Titanic" musical parody "Titanique" has made it to Broadway, earning four Tony nominations, including for Best Musical. The show's co-creator Marla Mindelle, individually nominated for her performance as Celine Dion recounting her experience aboard the Titanic, along with Layton Williams, nominated for his performance as the iceberg, discuss "Titanique." Photo by Evan Zimmerman for MurphyMade Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

There's a sneaky new way entrepreneurs are avoiding the work that actually grows a business, and it feels incredibly productive while it's happening.Steph calls it the iceberg idea trap, and AI is the latest and most seductive version of it. In this episode, she makes the case for minimum viable AI: how to use it as the tool it is without letting it become the thing you hide behind.If you've been spending more time building systems than talking to potential clients, this one's going to hit home._____________________Sold Out Group ProgramsJoin the waitlist: https://stephcrowder.com/sogpConnect with StephInstagram: @heystephcrowder

Austin shares his story of failure after failure, and how he learned lessons from each failure which eventually led to success!Time Stamped Show Notes:[0:25] - How to cure the worry over failure[1:23] - Watch out for ‘Iceberg' syndrome[3:00] - Austin's story of success and failure[8:05] - Hindsight is 20/20[9:34] - Failure is a teacher, not an indictmentWant To Level Up Your Job Search?Click here to learn more about 1:1 career coaching to help you land your dream job without applying online.Check out Austin's courses and, as a thank you for listening to the show, use the code PODCAST to get 5% off any digital course:The Interview Preparation System - Austin's proven, all-in-one process for turning your next job interview into a job offer.Value Validation Project Starter Kit - Everything you need to create a job-winning VVP that will blow hiring managers away and set you apart from the competition.No Experience, No Problem - Austin's proven framework for building the skills and experience you need to break into a new industry (even if you have *zero* experience right now).Try Austin's Job Search ToolsResyBuild.io - Build a beautiful, job-winning resume in minutes.ResyMatch.io - Score your resume vs. your target job description and get feedback.ResyBullet.io - Learn how to write attention grabbing resume bullets.Mailscoop.io - Find anyone's professional email in seconds.Connect with Austin for daily job search content:Cultivated CultureLinkedInTwitterThanks for listening!

In this powerful episode of the Secret Life Podcast, host Brianne Davis-Gantt takes listeners on an introspective journey into the depths of anger, unveiling the often-hidden emotions that lie beneath its surface. Drawing from her extensive experience in recovery, Brianne introduces the concept of the "anger iceberg," illustrating how the visible tip of anger often conceals deeper feelings such as fear, sadness, and betrayal.Throughout the episode, Brianne shares practical strategies for navigating these complex emotions. She emphasizes the importance of pausing to recognize anger, identifying triggers, and reflecting on underlying feelings. With a focus on emotional release, Brianne encourages listeners to engage in physical activities, such as hitting a pillow or exercising, to process their anger constructively.Listeners will learn how to communicate their needs calmly, practice self-awareness, and ultimately reclaim their emotional power. Brianne's candid insights and relatable anecdotes empower individuals to confront their anger, transforming it from a defensive mechanism into an opportunity for growth and understanding. This episode is essential for anyone seeking to better understand their emotions and cultivate healthier relationships.