Podcasts about ai summit

America celebrates its 250th birthday, Russia and China conduct joint naval drills, dozens are killed in Yemen clashes as tensions mount, the U.N. convenes Global Dialogue on AI Governance, Japan conducts a near-Earth asteroid flyby, Ukraine fails to intercept any ballistic missiles as the latest Russian attacks kill at least 16, the Sara Duterte impeachment trial begins in the Philippines, secret U.K. army files are found dumped in a recycling bin, DOGE officially shuts down, the White House accuses Smithsonian leadership of political activism, and Super Typhoon Bavi makes landfall in the Western Pacific. Sources: Verity.News

Something big is happening in short-term rentals, and most operators haveno idea.In this episode, Mike Sjogren returns to the show with Mike Reilly. And they open with atrend that changes everything.In 2022, most short-term rentals in the US were run by hosts with fewer than 20 units. By 2025, that share had dropped hard. The reason is not that hosts quit. It is that private equity quietly started buying up management companies, because the margins are good and the industry is wide open.Mike breaks down what that means for you, and reveals the project STR Secrets has spent 16 months building to help members cash in on it.In this episode:→ The data behind the great short-term rental consolidation, and why the big money is moving in now→ Freedom Collective: the new vehicle built to help operators sell their management company for a 6 to 8X exit instead of a 3 to 5X→ How 22 members generated over $3 million in new management commissions in about 7 weeks, including one who acquired a company and added 122 doors in a single quarter→ The full AI Summit recap→ Why the most important hire of the next few years is an AI mplementation specialist, and why the CEO's job is to cast the vision, not tinker in the tools until 3am→ Mike's own Q2 numbers from the new AI-powered CRM: 1,000 leads, 68 opportunities, 7 new clients, and $211,000 in new commissions, while taking only 10 percent of the sales calls himselfWhether you have your first property or your fiftieth, this episode will change how you think about where this industry is headed.Ready to scale and exit the right way? Apply to work with us: strsecrets.com/apply

Something big is happening in short-term rentals, and most operators haveno idea.In this episode, Mike Sjogren returns to the show with Mike Reilly. And they open with atrend that changes everything.In 2022, most short-term rentals in the US were run by hosts with fewer than 20 units. By 2025, that share had dropped hard. The reason is not that hosts quit. It is that private equity quietly started buying up management companies, because the margins are good and the industry is wide open.Mike breaks down what that means for you, and reveals the project STR Secrets has spent 16 months building to help members cash in on it.In this episode:→ The data behind the great short-term rental consolidation, and why the big money is moving in now→ Freedom Collective: the new vehicle built to help operators sell their management company for a 6 to 8X exit instead of a 3 to 5X→ How 22 members generated over $3 million in new management commissions in about 7 weeks, including one who acquired a company and added 122 doors in a single quarter→ The full AI Summit recap→ Why the most important hire of the next few years is an AI mplementation specialist, and why the CEO's job is to cast the vision, not tinker in the tools until 3am→ Mike's own Q2 numbers from the new AI-powered CRM: 1,000 leads, 68 opportunities, 7 new clients, and $211,000 in new commissions, while taking only 10 percent of the sales calls himselfWhether you have your first property or your fiftieth, this episode will change how you think about where this industry is headed.Ready to scale and exit the right way? Apply to work with us: strsecrets.com/apply

Fred Gifford, Strategy Lead and Sr. Product Manager at Sony AI, shares how his team is building knowledge graphs from academic literature to predict new biomedical relationships and accelerate drug discovery. He explains why Sony AI publishes so much of its research openly, what he got wrong about AI therapy when writing his novel and why he believes accountability for AI's ethical failures still lags dangerously behind the pace of the technology itself. Key Takeaways:  Why specialized AI tools are losing ground to all-in-one chatbots and what that means for the personal data we hand over What it actually takes to build an ethical dataset from scratch and why most image data used to train AI didn't  His experience of writing about AI therapy years before chatbots became a mental health solution for millions Why Sony AI is choosing to open-source its work  This episode was recorded LIVE at The AI Summit London Guest Bio: Fred Gifford is an AI strategy lead based in London. He has spent the past 5.5 years at Sony AI applying frontier AI research to solve challenges in gastronomy, AI Ethics, and biomedical.  He is also an author under the pen-name Fred Lunzer. His debut novel, Sike, was published by Macmillan / Celadon last year, and focuses on a young couple navigating life with an AI therapist.  ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

Bill Gates, the co-founder of Microsoft and a leading global philanthropist, withdrew from delivering his scheduled keynote address at the India AI Impact Summit in New Delhi just hours before he was set to speak. The Gates Foundation issued a statement saying the decision was made “to ensure the focus remains on the AI Summit's key priorities,” and Ankur Vora, president of the foundation's Africa and India offices, delivered the address in his place. Gates had been initially confirmed and was in India ahead of the event, which was designed to position India as a hub for artificial intelligence development and governance.The sudden cancellation came amid heightened scrutiny over Gates's past interactions with the late financier and convicted sex offender Jeffrey Epstein after recently released U.S. Justice Department documents included emails involving Gates Foundation staff and Epstein. Although Gates denies any impropriety and says he regretted associating with Epstein, the controversy drew significant attention in Indian media and public debate in the lead-up to the summit. Some commentators linked the timing of his withdrawal to that controversy, even as summit organizers and Indian officials did not directly tie the decision to the Epstein files.to c ontact me:bobbycapucci@protonmail.comsource:Bill Gates cancels AI summit keynote address amid scrutiny over Epstein links | CNNBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-epstein-chronicles--5003294/support.

Riccardo Arnaldi, Agentic AI Product Manager at Pandora, shares what it actually looks like to build and scale a brand-facing LLM shopping agent live with millions of customers. He explains why too much autonomy is a liability, how a deterministic routing layer keeps the AI from going off-script, and why traditional QA teams had to rebuild their processes from scratch. He also breaks down a real customer interaction that exposed the gap between automation and appropriate human sensitivity, changing how the team handles frustrated users. Key Takeaways Which metrics Pandora uses to measure success of Gemma, their customer-facing AI agent What breaks when traditional QA processes meet agentic products, and how testing an agent differs from testing software How a brand's voice gets engineered into an AI agent, including exact words it's allowed to use and the persona it borrows What a frustrated customer's outburst revealed about the line between automation and human sensitivity Guest Bio: Riccardo Arnaldi is a product manager with 6+ years' experience building and iterating on digital products through data, experimentation, and AI. Currently, he owns end-to-end development and strategy of LLM-based shopping and customer support agents at Pandora. Previously, he drove X60M+ DKK in incremental revenue by scaling Pandora's website and CRM personalisation programme from the ground up across 7+ markets. An Italian based in Copenhagen, Riccardo is a sports lover and guitar strummer, and is always on the lookout for the next great travel destination (with hype-worthy local foods). ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

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

NEW Bulletproof All-in AI Summit - 9 August, 2026 Why are humans still doing work that computers can do better? In this episode, Ian sits down with Dr. Peter Boulden and Dr. Craig Spodak to tackle what that question really means for dentistry, AI adoption, and the rapidly changing role of the front desk. The three explore how artificial intelligence is already transforming administrative work, patient communication, scheduling, documentation, and workflow management, and why the biggest mistake a dentist can make is assuming this technology won't reach their practice. Peter makes the case that even dentists who opt out will still feel the impact, because AI agents are already starting to make calls, book appointments, and gather information on behalf of patients. The flood of inbound is coming whether you are ready or not. That is why he frames the real choice as offense or defense: use AI to move your practice forward, or scramble to keep up without it. But the conversation isn't about replacing people. It's about removing repetitive work so team members can focus on the human experiences that matter most. Instead of spending hours on insurance verification, phone calls, and administrative tasks, team members can spend more time creating exceptional patient experiences, building relationships, and strengthening practice culture. The front desk is the highest-turnover, least-trained, most-overwhelmed position in most practices, and it is exactly where AI delivers the fastest relief. Done right, the receptionist does not lose the job. They get promoted out of the parts of it nobody ever wanted. DESCRIPTION The Bulletproof Dental Podcast Episode: 446 HOSTS: Dr. Peter Boulden, Dr. Craig Spodak, and Ian de Jongh In this episode, Peter Boulden, Craig Spodak, and Ian de Jongh explore how artificial intelligence is reshaping dental practices and what practice owners should be doing right now to stay ahead. The conversation covers AI receptionists, agentic AI, workflow automation, SOPs, practice management systems, and the opportunities available to independent dentists willing to embrace emerging technology. They also discuss why AI should be viewed as a tool for amplifying human connection rather than replacing it. Whether you're excited about AI, skeptical of it, or simply unsure where to begin, this episode offers practical insights into how technology is changing the future of dentistry. TAKEAWAYS AI is advancing faster than most dentists realize AI receptionists are becoming increasingly viable Agentic AI can perform tasks rather than simply answer questions SOPs are the foundation of successful AI implementation Practices that embrace AI early may gain significant advantages AI should enhance human connection, not replace it Administrative tasks are among the easiest workflows to automate Front desk teams can focus more on patient experience as repetitive tasks are removed Independent practices can leverage AI to compete at scale Technology is becoming a powerful equalizer in dentistry Resistance to AI will not stop its adoption The future belongs to practices that combine innovation with exceptional patient care. TIME STAMPS 00:00:00 - Construction Meeting Frustrations and AI Resistance 00:01:42 - Why Company Policies Can't Stop Progress 00:03:33 - The Challenge of Large Construction Projects 00:04:46 - Once You See a Better Way, You Can't Go Back 00:05:42 - Self-Driving Cars and the Future of Work 00:08:08 - Using AI to Manage Complex Projects 00:09:21 - The AI Workshop at Bulletproof Summit 00:11:42 - Introducing AI Receptionists in Dentistry 00:13:24 - Why AI Front Desk Solutions Are Growing Fast 00:15:15 - AI Receptionists vs Human Receptionists 00:18:08 - Google, AI Agents, and Autonomous Scheduling 00:20:02 - The Coming Wave of AI-to-AI Communication 00:22:29 - Playing Defense vs Playing Offense With AI 00:23:42 - Why People Are Afraid of AI 00:25:31 - Will AI Replace Front Desk Team Members? 00:28:31 - Let Computers Do Computer Work 00:30:27 - Insurance Verification and Administrative Burden 00:32:19 - Why SOPs Matter More Than AI Tools 00:33:30 - Low-Hanging Fruit for AI in Dental Practices 00:36:13 - How Practices Are Already Using AI Today 00:38:35 - Choosing Technology Based on the Future 00:41:43 - The Great Equalizer for Independent Dentists 00:43:20 - Alliance of Independent Dentists and Industry Change 00:45:18 - Why Independent Practices Can Move Faster 00:47:32 - Lessons From the Bulletproof Mastermind 00:48:11 - Finding Your First AI Breakthrough 00:50:12 - Practical Ways to Start Using AI Today 00:52:33 - Why One AI Win Changes Everything 00:55:57 - The Emotional Cost of Front Desk Work 00:56:27 - Bulletproof Summit AI Workshop Preview 00:58:25 - Final Thoughts on AI Adoption   REFERENCES Bulletproof Summit Alliance of Independent Dentists Claude AI  

This episode is part of our special series on the India AI Impact Summit, examining the conversations, decisions, and debates that are shaping global AI governance. Professor Ravindran addresses early on the perception that the India summit sidelined safety. More than 60% of the summit's events and discussions were focused on safety, trust, and cross-border collaboration. The framing shifted, and deliberately so. When the summit came to the Global South, leading with existential risk, rather than the very real opportunity AI presents to improve healthcare, education, and public services for hundreds of millions of people, would have been the wrong entry point. The two key deliverables from his working group reflect that balance: the Trusted AI Commons, a repository of benchmarks, testing protocols, and best practices designed for AI deployment in resource-constrained settings, and a high-level governance guidance note endorsed by 22 countries, that calls out the issues every national AI policy should address without being prescriptive enough to limit how different countries approach it. On frontier risks, Professor Ravindran notes that the landscape has shifted in ways that would have seemed speculative even a year ago, and that the frameworks being built to manage these risks will need to keep pace with that change. He also reflects on what the growing concentration of the most capable AI models means for countries like India, and why that conversation may need to move from being a company-to-country dialogue to a country-to-country one. His overall view is one of cautious optimism: there will be disruption in the short term, but there will also be a new equilibrium, and the work is to make sure the transition is managed well.Episode Contributors Professor Balaraman Ravindran heads the Department of Data Science and AI at IIT Madras. He is also the Founding Head of the Wadhwani School of Data Science and AI (WSAI), Robert Bosch Centre for Data Science and AI (RBCDSAI), and Centre for Responsible AI (CeRAI) at IIT Madras. He has more than three decades of experience working in reinforcement learning, and his research interest spans responsible AI and deep RL.  Nidhi Singh is an associate fellow at Carnegie India. Her current research interests include data governance, artificial intelligence and emerging technologies. Her work focuses on the implications of information technology law and policy from a Global Majority and Asian perspective. She has previously contributed to the Indian Express, The Secretariat, Medianama and HinduBusiness Line. Every two weeks, Interpreting India brings you diverse voices from India and around the world to explore the critical questions shaping the nation's future. We delve into how technology, the economy, and foreign policy intertwine to influence India's relationship with the global stage.As a Carnegie India production, hosted by Carnegie scholars, Interpreting India, a Carnegie India production, provides insightful perspectives and cutting-edge by tackling the defining questions that chart India's course through the next decade.Stay tuned for thought-provoking discussions, expert insights, and a deeper understanding of India's place in the world.Don't forget to subscribe, share, and leave a review to join the conversation and be part of Interpreting India's journey.

On this week's Good Morning Hospitality, A Skift Podcast: Hotels Edition, Sarah Dandashy and Steve Turk break down why hotel AI is stuck on the wrong side of the ledger and what it will take to flip it. The conversation opens with Mews founder Richard Valtr making the case at Skift's Data and AI Summit that fragmented hotel data is the reason AI keeps cutting costs instead of driving revenue. From there Sarah and Steve dig into what Apple's rebuilt Siri means for how guests will find and interact with travel, Alaska Airlines' bet that Starlink wifi is a better loyalty driver than points for basic economy travelers, and why Delta Air Lines is expanding American Express card benefits without raising fees while every competitor goes the other direction. This episode is presented by ⁠⁠Cloudbeds⁠⁠ & ⁠⁠Bilt⁠⁠. Visit ⁠⁠cloudbeds.com/gmh⁠⁠ to learn more. And for hotels with restaurants and restaurant owners, Bilt Hospitality is finally here. Go to ⁠⁠joinbilt.com/gmh⁠⁠ to learn more. And if you're leaving direct bookings on the table, StayFi turns your wifi into a guest relationship engine. Visit ⁠https://stayfi.com/goodmorninghospitality/⁠ to learn more.

On this week's Good Morning Hospitality, A Skift Podcast: Hotels Edition, Sarah Dandashy and Steve Turk break down why hotel AI is stuck on the wrong side of the ledger and what it will take to flip it. The conversation opens with Mews founder Richard Valtr making the case at Skift's Data and AI Summit that fragmented hotel data is the reason AI keeps cutting costs instead of driving revenue. From there Sarah and Steve dig into what Apple's rebuilt Siri means for how guests will find and interact with travel, Alaska Airlines' bet that Starlink wifi is a better loyalty driver than points for basic economy travelers, and why Delta Air Lines is expanding American Express card benefits without raising fees while every competitor goes the other direction. This episode is presented by ⁠⁠Cloudbeds⁠⁠ & ⁠⁠Bilt⁠⁠. Visit ⁠⁠cloudbeds.com/gmh⁠⁠ to learn more. And for hotels with restaurants and restaurant owners, Bilt Hospitality is finally here. Go to ⁠⁠joinbilt.com/gmh⁠⁠ to learn more. And if you're leaving direct bookings on the table, StayFi turns your wifi into a guest relationship engine. Visit ⁠https://stayfi.com/goodmorninghospitality/⁠ to learn more.

Nicolás Cruz es cofundador de Colombia Tech, la empresa que está construyendo el ecosistema tecnológico colombiano desde adentro: Colombia Tech Week, AI Summit, GovTech, programas de aceleración y misiones a Silicon Valley. En este capítulo de Ser tu propio jefe, le cuenta a Álvaro Rodríguez cómo se llega ahí cuando nadie creía que se podía.Hablamos del papá emprendedor que lo mandó a repartir facturas en bus a los 14 años, del derecho que estudió por rebeldía y abandonó por frustración con la burocracia, de los amigos en Rappi que "querían comer el mundo" mientras él dudaba si subirse, y del salto desde Filo Legal a montar el festival de tecnología más grande del país.Y la parte que más le va a doler al fundador que está buscando plata: por qué hoy los fondos no quieren ver tu PowerPoint, qué números exactos te piden ahora, por qué la tecnología se está volviendo un commodity, y dónde quedó el verdadero foso defensivo. Más una tesis honesta de cómo crecer "rápido a toda m*****, pero cuidando los fundamentales".

M.G. Siegler is the author of Spyglass.org. Siegler joins Big Technology to discuss whether Google is falling behind in AI as OpenAI and Anthropic push ahead with coding agents and super-app ambitions. Tune in to hear why AI agents may reshape the way people use the web, email, apps, and browsers, and why that could put Google in a difficult position. We also cover Apple's upcoming WWDC, the rumored iPhone Fold, Meta's messy subscription strategy, and Anthropic's move toward an IPO. Hit play for a sharp, wide-ranging conversation on the biggest power shifts happening in tech right now. Join Big Technology's AI Summit on June 18: summit.bigtechnology.com --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here's 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Learn more about your ad choices. Visit megaphone.fm/adchoices

Ryan will be showing how to make this and a custom revenue management tool live at the Ai Summit. Grab your spot at the AI Summit: strsecrets.com/aisummit at just $497. Use the coupon : "PODCAST"Every homeowner conversation starts the same way.They want to know what their property can earn.And if you can't answer that question fast, professionally, and with data behind it —someone else will.In this week's training, Mike sits down with STR Secrets coach Ryan Lefebvre to demo the AI-powered comp analysis tool that's helping property managers turn more conversations into signed contracts.Ryan went from 1-2 comp requests a week to 10 a week — from realtors and investors who now send him every new listing because he delivers branded, data-backed reports in minutes, not hours.In this episode:→ The exact tool Ryan built using Claude that generates a full comp report in 2 to 10 minutes (vs. 20-30 minutes manually)→ How to use conservative, base, and optimistic revenue projections to handle any homeowner conversation on the spot→ Why realtors are becoming one of the fastest referral pipelines for new management contracts — and how to tap in→ The AI rabbit hole warning: why building your own tools can quietly kill your business growth→ Mike's financial freedom math: exactly how much you need invested to hit $100K a month in cash flow→ Why arbitrage is a dead end — and what the data on the biggest arbitrage companies actually showsThis is not theory. Ryan runs live comps during the session on real properties submitted by the audience — you'll see exactly how the tool works in real time.Want the comp tool? DM COMP at mike.sjogren and we'll send it straight to you.Ready to install this and a full AI system for your business live?Timestamps:00:00 - Intro & Ryan Lefebvre's background01:42 - From financial crime analyst to AI builder for STR04:22 - How the comp tool works and what it produces06:33 - Live demo: running an Airbnb listing in real time09:26 - Interactive sliders and revenue scenario conversations11:17 - How to handle bad comps and sparse markets13:36 - Live demo: running a property address17:34 - How the tool handles off-market or renovated properties22:38 - Using comp reports to show homeowners the gap between unmanaged and managed26:41 - AI Summit: what's being covered and who's speaking29:04 - Ticket pricing and how to register32:02 - Alex case study: 2 properties to 35 in one year35:29 - The AI rabbit hole warning38:00 - Using AI at any portfolio size41:06 - Mike's financial freedom math ($8M at 15% = $1.2M/year)44:46 - Why arbitrage is a dead model49:27 - Should you replace your channel manager with AI? (No. Here's why)52:45 - Q&A: summit details, recordings, revenue manager AI tool

Ryan will be showing how to make this and a custom revenue management tool live at the Ai Summit. Grab your spot at the AI Summit: strsecrets.com/aisummit at just $497. Use the coupon : "PODCAST"Every homeowner conversation starts the same way.They want to know what their property can earn.And if you can't answer that question fast, professionally, and with data behind it —someone else will.In this week's training, Mike sits down with STR Secrets coach Ryan Lefebvre to demo the AI-powered comp analysis tool that's helping property managers turn more conversations into signed contracts.Ryan went from 1-2 comp requests a week to 10 a week — from realtors and investors who now send him every new listing because he delivers branded, data-backed reports in minutes, not hours.In this episode:→ The exact tool Ryan built using Claude that generates a full comp report in 2 to 10 minutes (vs. 20-30 minutes manually)→ How to use conservative, base, and optimistic revenue projections to handle any homeowner conversation on the spot→ Why realtors are becoming one of the fastest referral pipelines for new management contracts — and how to tap in→ The AI rabbit hole warning: why building your own tools can quietly kill your business growth→ Mike's financial freedom math: exactly how much you need invested to hit $100K a month in cash flow→ Why arbitrage is a dead end — and what the data on the biggest arbitrage companies actually showsThis is not theory. Ryan runs live comps during the session on real properties submitted by the audience — you'll see exactly how the tool works in real time.Want the comp tool? DM COMP at mike.sjogren and we'll send it straight to you.Ready to install this and a full AI system for your business live?Timestamps:00:00 - Intro & Ryan Lefebvre's background01:42 - From financial crime analyst to AI builder for STR04:22 - How the comp tool works and what it produces06:33 - Live demo: running an Airbnb listing in real time09:26 - Interactive sliders and revenue scenario conversations11:17 - How to handle bad comps and sparse markets13:36 - Live demo: running a property address17:34 - How the tool handles off-market or renovated properties22:38 - Using comp reports to show homeowners the gap between unmanaged and managed26:41 - AI Summit: what's being covered and who's speaking29:04 - Ticket pricing and how to register32:02 - Alex case study: 2 properties to 35 in one year35:29 - The AI rabbit hole warning38:00 - Using AI at any portfolio size41:06 - Mike's financial freedom math ($8M at 15% = $1.2M/year)44:46 - Why arbitrage is a dead model49:27 - Should you replace your channel manager with AI? (No. Here's why)52:45 - Q&A: summit details, recordings, revenue manager AI tool

This week I attended the Sana AI Summit in NYC, so I wanted to share the various conversations and new ideas that came from this multi-disciplinary meeting. I hope my summary helps you see some of the bigger issues at play here. Will AI destroy the job market? What is the real economic value so far? What is the difference between AI and humans? How safe is AI in reality? And how can we use AI to really better our lives, careers, and companies? I hope my summary gives you some new ideas to think about as this technology permeates our lives and businesses. (And I recommend Geoffrey Hinton's discussion for a listen.) Speaker Role / affiliation listed Tyler Cowen Economist and author Geoffrey Hinton Computer scientist and “Godfather of AI” Anton Osika Co-Founder, Lovable Lauren Crichton Vice President, Sana Benjamín Labatut Writer Aneel Bhusri Co-founder, CEO and Chair, Workday Jasmine Sun Tech anthropologist Joel Hellermark Founder and CEO, Sana Sara Imari Walker Astrobiologist Ethan Mollick Professor of Entrepreneurship Anu Atluru Essayist and technologist Chapters (00:00:00) - SANAA AI Summit 2017(00:01:23) - A More Human World With AI(00:03:19) - Will AI Hurt the Economy?(00:06:53) - A More Human Workforce(00:08:47) - What is a Human Decision?(00:15:26) - The Ethical Problem of AI(00:18:46) - The cranky writer on AI(00:20:12) - The Future of AI in HR(00:21:58) - A Taste of the AI Summit

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This episode is part of our special series on the India AI Impact Summit, examining the conversations, decisions, and debates that are shaping global AI governance. The working group was designed from the start to be bottom-up rather than top-down. Rather than starting from the positions of countries already leading in AI, the agenda was shaped through consultations, bilateral discussions, and deliberate outreach beyond official channels. The concerns that emerged were consistent: uneven concentration of compute, limited access to quality data, dependence on external platforms, and the risk that much of the global south would not be able to fully participate in or benefit from AI-driven development. The two key outcomes are the Democratic Diffusion of AI Resources charter, a collective commitment to inclusive and equitable AI development adopted in the summit's final declaration, and MAITRI, a collaborative platform designed to connect governments, researchers, and institutions to the essential building blocks of AI without each country having to start from scratch. Saurabh Garg draws a direct line between these initiatives and India's own experience with layered digital public infrastructure, pointing to the principles behind Aadhaar, UPI, and the India AI Mission as exactly what informed the working group's approach. The real work, he makes clear, begins now. Every two weeks, Interpreting India brings you diverse voices from India and around the world to explore the critical questions shaping the nation's future. We delve into how technology, the economy, and foreign policy intertwine to influence India's relationship with the global stage.As a Carnegie India production, hosted by Carnegie scholars, Interpreting India, a Carnegie India production, provides insightful perspectives and cutting-edge by tackling the defining questions that chart India's course through the next decade.Stay tuned for thought-provoking discussions, expert insights, and a deeper understanding of India's place in the world.Don't forget to subscribe, share, and leave a review to join the conversation and be part of Interpreting India's journey.

Join us for the Big Technology AI Summit on June, 18, 2026 at the Commonwealth Club in San Francisco. The lineup: OpenAI President Greg Brockman, Perplexity CEO Aravind Srinivas, Box CEO Aaron Levie, Wired senior correspondant Lauren Goode, and more on the way! Get your tickets here: summit.bigtechnology.com Learn more about your ad choices. Visit megaphone.fm/adchoices

The U.S. House votes to end a record 76-day Homeland Security shutdown, Trump and Putin discuss Iran and Ukraine during a 90-minute phone call, as the Russian president also meets with his Congolese counterpart at the Kremlin, Gov. Landry suspends Louisiana's House primaries, Bernie Sanders hosts a U.S.-China AI safety panel, seven families sue OpenAI over British Columbia's Tumbler Ridge mass shooting, a royal commission releases its preliminary report on Australia's Bondi attack, a new court filing raises questions about the shooting at the White House Correspondents' dinner, the U.S. economy grows 2% in early 2026, and the EU finds that Meta broke child safety rules by not keeping minors of its platforms. Sources: Verity.News

This episode is part of our special series on the India AI Impact Summit, examining the conversations, decisions, and debates that are shaping global AI governance. Raymond draws a distinction early in the conversation that shapes everything that follows: training and inference are not the same thing, and conflating them is leading a lot of countries to make expensive mistakes. Training, he says, is like building the engine. Inference is running the transport system every single day. Most countries do not need to build the engine. What they need is airports, roads, and reliable infrastructure that gets the technology into the hands of people. The global assumption that frontier model training is the only legitimate AI pathway is, in his view, one of the more consequential misreads of the moment. On the ground realities of building in Africa, Raymond is specific about where the bottlenecks actually are. It is not ambition. It is power reliability, cost of connectivity, access to capital, and the kind of financing frameworks that have not yet caught up with what AI infrastructure actually requires. He points to genuinely interesting anomalies, such as Ethiopia's extremely low cost of power sitting alongside very limited terrestrial fiber diversity, as a reminder that building in the Global South is not about replicating Silicon Valley at a discount. It is about finding combinations of constraints that can actually be made to work, and optimising for reliability, cost efficiency, and practical impact rather than scale and prestige. His advice to governments is to start with problems, not hardware. Prestigious projects with no clear use case, over-regulation before a single GPU cluster exists, and attempts to rebuild sovereign versions of large compute clusters are all, in his view, things to ignore. What countries should actually invest in is reliable and clean power, public interest compute access, data governance frameworks, sector specific pilots in health, agriculture, and education, and talent development that works by getting the technology into the hands of people rather than running structured boot camps. For Raymond, the success metric for Africa in five years should not be the size of anyone's model. It should be whether AI has meaningfully improved economic productivity and public service delivery across the continent.Episode Contributors Nidhi Singh is an associate fellow at Carnegie India. Her current research interests include data governance, artificial intelligence and emerging technologies. Her work focuses on the implications of information technology law and policy from a Global Majority and Asian perspective.  Raymond Ononiwu is the founder of Horus Lab, a technology and infrastructure company building Africa's next-generation digital backbone through modular, renewable-powered, AI-ready data centers. An engineer with more than 15 years of experience delivering products across Mixed Reality, Windows Analytics, and Teams Copilot, his work has powered platforms relied on by hundreds of millions globally. Every two weeks, Interpreting India brings you diverse voices from India and around the world to explore the critical questions shaping the nation's future. We delve into how technology, the economy, and foreign policy intertwine to influence India's relationship with the global stage.As a Carnegie India production, hosted by Carnegie scholars, Interpreting India, a Carnegie India production, provides insightful perspectives and cutting-edge by tackling the defining questions that chart India's course through the next decade.Stay tuned for thought-provoking discussions, expert insights, and a deeper understanding of India's place in the world.Don't forget to subscribe, share, and leave a review to join the conversation and be part of Interpreting India's journey.

Ireland welcomes the announcement of European AI Innovation Month, taking place from Dublin 14 October to Brussels 17 November 2026, a Europe-wide programme of events dedicated to accelerating artificial intelligence innovation and deployment across the European Union. As part of Ireland's Presidency of the Council of the European Union in 2026, Ireland will officially launch the month with the International AI Summit on 14 October 2026 at the RDS Dublin. Harnessing AI, Ireland ready for EU Innovation Month Under the theme 'Harnessing AI to Revolutionise Europe's Competitiveness' the International AI Summit will focus on Applied AI and sectoral value creation, highlighting Europe's shift from research to applied AI that delivers tangible impact across industries and public services. It will focus on building AI capacity through world-class infrastructure, computing power, sustainable energy, connectivity, and talent, while showcasing transformative opportunities ranging from generative to agentic AI, frontier models, and quantum convergence, all delivered responsibly to maintain public trust. Participants will include EU Commissioners and Ministers, C-suite leaders from major international and European companies and globally recognised AI experts. Sector-focused sessions will examine how AI is transforming key areas of the economy and society, supported by an Innovation spotlight exhibition space demonstrating cutting-edge AI innovation. Minister for Enterprise, Tourism and Employment, Peter Burke TD, said, "This AI summit is a unique opportunity to showcase Irish and European leadership in applied AI and demonstrate how innovation can drive competitiveness, create value across our economy and benefit society as a whole. Ireland's vibrant AI ecosystem, world-class talent and strategic infrastructure positions Ireland uniquely to lead these discussions and help shape the future of AI in Europe." Minister of State for Trade Promotion, Artificial Intelligence and Digital Transformation, Niamh Smyth said, "We are now 6 months out from the International AI Summit at the RDS, Ireland is proud to host this flagship event in a venue that has championed innovation for centuries, turning ideas into action. Preparations are fully underway for this key commitment of mine, which will bring together Europe's leading minds in technology, business, and government. By collaborating closely with the European Commission and our industry partners, we are ensuring this AI Summit leaves a lasting impact, establishing Ireland as the go-to hub for the next generation of technology while demonstrating how AI can boost European competitiveness and create tangible value for businesses and citizens." Headline speakers will be announced shortly, with further details on speakers and the full programme to follow. An Expression of Interest will also open in the coming weeks for enterprises interested in participating in the Innovation Spotlight Exhibition. See more stories here. More about Irish Tech News Irish Tech News are Ireland's No. 1 Online Tech Publication and often Ireland's No.1 Tech Podcast too. You can find hundreds of fantastic previous episodes and subscribe using whatever platform you like via our Anchor.fm page here: https://anchor.fm/irish-tech-news If you'd like to be featured in an upcoming Podcast email us at Simon@IrishTechNews.ie now to discuss. Irish Tech News have a range of services available to help promote your business. Why not drop us a line at Info@IrishTechNews.ie now to find out more about how we can help you reach our audience. You can also find and follow us on Twitter, LinkedIn, Facebook, Instagram, TikTok and Snapchat.

This episode is part of our special series on the India AI Impact Summit 2026, examining the conversations, perspectives, and debates that are shaping global AI discourse. Tino has been in the room at all four AI summits, and his account of how the conversation has evolved is both candid and grounding. Bletchley Park, he says, was about putting AI on the agenda as a matter of global significance. Seoul was about bringing the private sector formally into that conversation. Paris marked a pivot towards economic opportunity, reflecting a growing recognition, particularly in Europe, that being seen only as a regulator was not a position anyone wanted to hold for long. And New Delhi brought something none of the previous summits had: scale, and a genuinely different set of questions. Half a million people attended, and the conversations happening on the floor of the convention center were about crop yields, public service delivery, and what the technology meant for jobs and families. That, Tino says, is not a dilution of the AI safety agenda. It is a necessary part of building one that the rest of the world can actually be part of. On the criticism that these summits produce declarations that no one enforces and voluntary commitments that companies quietly walk away from, Tino is pragmatic rather than defensive. He points to the eradication of smallpox, the reduction of nuclear weapons, and the Montreal Protocol as reminders that consequential international progress tends to look messy and incremental from the inside. The network of AI safety institutes that now exists across multiple countries, the UN panel on AI, and the fact that frontier labs are taking evaluation and testing seriously at all, are all, in his view, real if incomplete achievements. The harder question, particularly after the U.S. and UK declined to sign the Paris declaration, is whether the summit process can hold its shape as geopolitical competition intensifies and the appetite for multilateral consensus shrinks. For Geneva, Tino hopes the conversation moves inward, towards understanding how AI is actually changing organizations, families, and daily life at the micro level. He is also candid about risks he thinks are still not being taken seriously enough, particularly around loss of control, pointing to early evidence of models that scheme, misrepresent, and in controlled environments show signs of self-preservation. His overall posture is one of cautious optimism: he does not think the technology should slow down, but he does think the work of aligning it with what is genuinely good for people has barely begun. Every two weeks, Interpreting India brings you diverse voices from India and around the world to explore the critical questions shaping the nation's future. We delve into how technology, the economy, and foreign policy intertwine to influence India's relationship with the global stage.As a Carnegie India production, hosted by Carnegie scholars, Interpreting India, a Carnegie India production, provides insightful perspectives and cutting-edge by tackling the defining questions that chart India's course through the next decade.Stay tuned for thought-provoking discussions, expert insights, and a deeper understanding of India's place in the world.Don't forget to subscribe, share, and leave a review to join the conversation and be part of Interpreting India's journey.

Ireland welcomes the announcement of European AI Innovation Month, taking place from Dublin 14 October to Brussels 17 November 2026, a Europe-wide programme of events dedicated to accelerating artificial intelligence innovation and deployment across the European Union. As part of Ireland's Presidency of the Council of the European Union in 2026, Ireland will officially launch the month with the International AI Summit on 14 October 2026 at the RDS Dublin. Under the theme 'Harnessing AI to Revolutionise Europe's Competitiveness' the International AI Summit will focus on Applied AI and sectoral value creation, highlighting Europe's shift from research to applied AI that delivers tangible impact across industries and public services. It will focus on building AI capacity through world-class infrastructure, computing power, sustainable energy, connectivity, and talent, while showcasing transformative opportunities ranging from generative to agentic AI, frontier models, and quantum convergence, all delivered responsibly to maintain public trust. Participants will include EU Commissioners and Ministers, C-suite leaders from major international and European companies and globally recognised AI experts. Sector-focused sessions will examine how AI is transforming key areas of the economy and society, supported by an Innovation spotlight exhibition space demonstrating cutting-edge AI innovation. Minister for Enterprise, Tourism and Employment, Peter Burke TD, said, "This AI summit is a unique opportunity to showcase Irish and European leadership in applied AI and demonstrate how innovation can drive competitiveness, create value across our economy and benefit society as a whole. Ireland's vibrant AI ecosystem, world-class talent and strategic infrastructure positions Ireland uniquely to lead these discussions and help shape the future of AI in Europe." Minister of State for Trade Promotion, Artificial Intelligence and Digital Transformation, Niamh Smyth said, "We are now 6 months out from the International AI Summit at the RDS, Ireland is proud to host this flagship event in a venue that has championed innovation for centuries, turning ideas into action. Preparations are fully underway for this key commitment of mine, which will bring together Europe's leading minds in technology, business, and government. By collaborating closely with the European Commission and our industry partners, we are ensuring this AI Summit leaves a lasting impact, establishing Ireland as the go-to hub for the next generation of technology while demonstrating how AI can boost European competitiveness and create tangible value for businesses and citizens." Headline speakers will be announced shortly, with further details on speakers and the full programme to follow. An Expression of Interest will also open in the coming weeks for enterprises interested in participating in the Innovation Spotlight Exhibition. See more stories here. More about Irish Tech News Irish Tech News are Ireland's No. 1 Online Tech Publication and often Ireland's No.1 Tech Podcast too. You can find hundreds of fantastic previous episodes and subscribe using whatever platform you like via our Anchor.fm page here: https://anchor.fm/irish-tech-news If you'd like to be featured in an upcoming Podcast email us at Simon@IrishTechNews.ie now to discuss. Irish Tech News have a range of services available to help promote your business. Why not drop us a line at Info@IrishTechNews.ie now to find out more about how we can help you reach our audience. You can also find and follow us on Twitter, LinkedIn, Facebook, Instagram, TikTok and Snapchat.

Multiple New York Times bestselling author, entrepreneur, and investor Dean Graziosi joins Adam and Dr. Drew in the studio to discuss the future of AI! Adam asks if society should fear a future dominated by artificial intelligence, and Dean explains it's simply humanity's evolution—tools that make daily tasks easier and faster. They discuss how people naturally fear major change and speculate on how deeply AI will integrate into everyone's lives down the road. You can get tickets to Dean and Tony Robbin's AI Summit at www.aisummit555.com.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Fresh off the big GeekWire AI summit this week, Todd and John unpack what they heard from Microsoft EVP Charles Lamanna, OpenAI applications CTO Vijaye Raji, and other speakers at the Agents of Transformation event in Seattle, presented by Accenture. The big thread: the economics of AI, from token budgets becoming a hiring negotiation point to startups running on subsidized credits that may not last. Plus, a startup founder whose engineer burned through $5,000 in AI tokens over a single weekend of vibe coding, OpenAI shutting down Sora amid $15 million-a-day processing costs, and why one panelist says the metrics most companies are tracking are "watermelon metrics" — green (profit) on the outside, red (losses) on the inside. Also: how Todd used a Claude project over several months to prep for the event, John's experience bouncing between Gemini and ChatGPT, and why the simplistic chat era may be over. And in this week's trivia: Sound Transit's light rail starts crossing Lake Washington on a floating bridge — but when did the original I-90 floating bridge open? With GeekWire co-founders John Cook and Todd Bishop. Edited by Curt Milton.See omnystudio.com/listener for privacy information.

Today we're going to talk about simple offers and how they normally beat the heck out of fancy, intricate funnels. Launch Team - https://www.ScrewTheCommute.com/launchteam Please watch this short trailer to the end and leave a comment - https://www.facebook.com/AmericanEntrepreneurFilm/videos/558575401181955 AI Summit - https://www.ScrewTheCommute.com/aisummit AI Hacks - https://www.ScrewTheCommute.com/aihacks Screw The Commute Podcast Show Notes Episode 1096 How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Training Center - https://imtcva.org/ Higher Education Webinar – https://screwthecommute.com/webinars See Tom's Stuff – https://linktr.ee/antionandassociates 00:23 Tom's introduction to Simple Offers 02:37 Making money from simple product sales 05:16 Upselling theory Entrepreneurial Resources Mentioned in This Podcast Higher Education Webinar - https://screwthecommute.com/webinars Screw The Commute - https://screwthecommute.com/ Screw The Commute Podcast App - https://screwthecommute.com/app/ Screw The Commute Podcast Producer - https://screwthecommute.com/larryguerrera/ College Ripoff Quiz - https://imtcva.org/quiz Know a young person for our Youth Episode Series? Send an email to Tom! - orders@antion.com Have a Roku box? Find Tom's Public Speaking Channel there! - https://channelstore.roku.com/details/267358/the-public-speaking-channel How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Retreat and Joint Venture Program - https://greatinternetmarketingtraining.com/ This is the shopping cart system Tom uses! Kartra - https://screwthecommute.com/kartra/ Copywriting901 - https://copywriting901.com/ Become a Great Podcast Guest - https://screwthecommute.com/greatpodcastguest Training - https://screwthecommute.com/training Disabilities Page - https://imtcva.org/disabilities/ Tom's Patreon Page - https://screwthecommute.com/patreon/ Tom on TikTok - https://tiktok.com/@digitalmultimillionaire/ Email Tom: Tom@ScrewTheCommute.com Internet Marketing Training Center - https://imtcva.org/ Related Episodes Questions Into Content - https://screwthecommute.com/1095/ More Entrepreneurial Resources for Home Based Business, Lifestyle Business, Passive Income, Professional Speaking and Online Business I discovered a great new headline / subject line / subheading generator that will actually analyze which headlines and subject lines are best for your market. I negotiated a deal with the developer of this revolutionary and inexpensive software. Oh, and it's good on Mac and PC. Go here: http://jvz1.com/c/41743/183906 The Wordpress Ecourse. Learn how to Make World Class Websites for $20 or less. https://screwthecommute.com/wordpressecourse/

Today we're going to talk about turning questions into content and one of the best ways you can do it. Launch Team - https://www.ScrewTheCommute.com/launchteam Please watch this short trailer to the end and leave a comment - https://www.facebook.com/AmericanEntrepreneurFilm/videos/558575401181955 AI Summit - https://www.ScrewTheCommute.com/aisummit AI Hacks - https://www.ScrewTheCommute.com/aihacks Screw The Commute Podcast Show Notes Episode 1095 How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Training Center - https://imtcva.org/ Higher Education Webinar – https://screwthecommute.com/webinars See Tom's Stuff – https://linktr.ee/antionandassociates 00:23 Tom's introduction to Questions Into Content 02:00 Success is giving people what they want 03:17 Have a Frequently Asked Questions on your website 05:24 Private and paid Facebook groups Entrepreneurial Resources Mentioned in This Podcast Higher Education Webinar - https://screwthecommute.com/webinars Screw The Commute - https://screwthecommute.com/ Screw The Commute Podcast App - https://screwthecommute.com/app/ Screw The Commute Podcast Producer - https://screwthecommute.com/larryguerrera/ College Ripoff Quiz - https://imtcva.org/quiz Know a young person for our Youth Episode Series? Send an email to Tom! - orders@antion.com Have a Roku box? Find Tom's Public Speaking Channel there! - https://channelstore.roku.com/details/267358/the-public-speaking-channel How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Retreat and Joint Venture Program - https://greatinternetmarketingtraining.com/ This is the shopping cart system Tom uses! Kartra - https://screwthecommute.com/kartra/ Copywriting901 - https://copywriting901.com/ Become a Great Podcast Guest - https://screwthecommute.com/greatpodcastguest Training - https://screwthecommute.com/training Disabilities Page - https://imtcva.org/disabilities/ Tom's Patreon Page - https://screwthecommute.com/patreon/ Tom on TikTok - https://tiktok.com/@digitalmultimillionaire/ Email Tom: Tom@ScrewTheCommute.com Internet Marketing Training Center - https://imtcva.org/ Related Episodes YouTube Mistakes That Get You Banned - https://screwthecommute.com/1094/ More Entrepreneurial Resources for Home Based Business, Lifestyle Business, Passive Income, Professional Speaking and Online Business I discovered a great new headline / subject line / subheading generator that will actually analyze which headlines and subject lines are best for your market. I negotiated a deal with the developer of this revolutionary and inexpensive software. Oh, and it's good on Mac and PC. Go here: http://jvz1.com/c/41743/183906 The Wordpress Ecourse. Learn how to Make World Class Websites for $20 or less. https://screwthecommute.com/wordpressecourse/

Today I'm going to talk about YouTube mistakes that could get you banned. And some of them are so innocent you wouldn't even think anything of them, but they're against the terms of service. And then I'm also going to give you a bunch of niches that are getting banned like crazy. Launch Team - https://www.ScrewTheCommute.com/launchteam Please watch this short trailer to the end and leave a comment - https://www.facebook.com/AmericanEntrepreneurFilm/videos/558575401181955 AI Summit - https://www.ScrewTheCommute.com/aisummit AI Hacks - https://www.ScrewTheCommute.com/aihacks Screw The Commute Podcast Show Notes Episode 1094 How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Training Center - https://imtcva.org/ Higher Education Webinar – https://screwthecommute.com/webinars See Tom's Stuff – https://linktr.ee/antionandassociates 00:23 Tom's introduction to YouTube Mistakes That Get You Banned 06:47 Hashtag abuse, channel security, dangerous content 10:10 Tag stuffing, trading subscribers, niches that can get you banned 12:35 Celebrity gossip, fake police body cams, compilations, true crime 15:35 Making money online Entrepreneurial Resources Mentioned in This Podcast Higher Education Webinar - https://screwthecommute.com/webinars Screw The Commute - https://screwthecommute.com/ Screw The Commute Podcast App - https://screwthecommute.com/app/ Screw The Commute Podcast Producer - https://screwthecommute.com/larryguerrera/ College Ripoff Quiz - https://imtcva.org/quiz Know a young person for our Youth Episode Series? Send an email to Tom! - orders@antion.com Have a Roku box? Find Tom's Public Speaking Channel there! - https://channelstore.roku.com/details/267358/the-public-speaking-channel How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Retreat and Joint Venture Program - https://greatinternetmarketingtraining.com/ This is the shopping cart system Tom uses! Kartra - https://screwthecommute.com/kartra/ Copywriting901 - https://copywriting901.com/ Become a Great Podcast Guest - https://screwthecommute.com/greatpodcastguest Training - https://screwthecommute.com/training Disabilities Page - https://imtcva.org/disabilities/ Tom's Patreon Page - https://screwthecommute.com/patreon/ Tom on TikTok - https://tiktok.com/@digitalmultimillionaire/ Email Tom: Tom@ScrewTheCommute.com Internet Marketing Training Center - https://imtcva.org/ Related Episodes Five AI Hacks - https://screwthecommute.com/1085/ Five More AI Hacks - https://screwthecommute.com/1088/ Five More AI Hacks - https://screwthecommute.com/1093/ More Entrepreneurial Resources for Home Based Business, Lifestyle Business, Passive Income, Professional Speaking and Online Business I discovered a great new headline / subject line / subheading generator that will actually analyze which headlines and subject lines are best for your market. I negotiated a deal with the developer of this revolutionary and inexpensive software. Oh, and it's good on Mac and PC. Go here: http://jvz1.com/c/41743/183906 The Wordpress Ecourse. Learn how to Make World Class Websites for $20 or less. https://screwthecommute.com/wordpressecourse/

Today, I'm going to give you five more AI hacks that don't take any technical skill. Add this to the last two episodes on AI and you've got 15 hacks you can use now. Launch Team - https://www.ScrewTheCommute.com/launchteam Please watch this short trailer to the end and leave a comment - https://www.facebook.com/AmericanEntrepreneurFilm/videos/558575401181955 AI Summit - https://www.ScrewTheCommute.com/aisummit AI Hacks - https://www.ScrewTheCommute.com/aihacks Suno AI - https://suno.ai Screw The Commute Podcast Show Notes Episode 1093 How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Training Center - https://imtcva.org/ Higher Education Webinar – https://screwthecommute.com/webinars See Tom's Stuff – https://linktr.ee/antionandassociates 00:23 Tom's introduction to Five More AI Hacks 03:16 Screw The Commute song from Suno.AI 06:55 Talking about controversial things with AI 10:40 Watching out for AI hallucinations 11:49 NoteBookLM for document and graphics creation 13:24 Creating headshots Entrepreneurial Resources Mentioned in This Podcast Higher Education Webinar - https://screwthecommute.com/webinars Screw The Commute - https://screwthecommute.com/ Screw The Commute Podcast App - https://screwthecommute.com/app/ Screw The Commute Podcast Producer - https://screwthecommute.com/larryguerrera/ College Ripoff Quiz - https://imtcva.org/quiz Know a young person for our Youth Episode Series? Send an email to Tom! - orders@antion.com Have a Roku box? Find Tom's Public Speaking Channel there! - https://channelstore.roku.com/details/267358/the-public-speaking-channel How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Retreat and Joint Venture Program - https://greatinternetmarketingtraining.com/ This is the shopping cart system Tom uses! Kartra - https://screwthecommute.com/kartra/ Copywriting901 - https://copywriting901.com/ Become a Great Podcast Guest - https://screwthecommute.com/greatpodcastguest Training - https://screwthecommute.com/training Disabilities Page - https://imtcva.org/disabilities/ Tom's Patreon Page - https://screwthecommute.com/patreon/ Tom on TikTok - https://tiktok.com/@digitalmultimillionaire/ Email Tom: Tom@ScrewTheCommute.com Internet Marketing Training Center - https://imtcva.org/ Related Episodes Five AI Hacks - https://screwthecommute.com/1085/ Five More AI Hacks - https://screwthecommute.com/1088/ Authority Shortcuts - https://screwthecommute.com/1092/ More Entrepreneurial Resources for Home Based Business, Lifestyle Business, Passive Income, Professional Speaking and Online Business I discovered a great new headline / subject line / subheading generator that will actually analyze which headlines and subject lines are best for your market. I negotiated a deal with the developer of this revolutionary and inexpensive software. Oh, and it's good on Mac and PC. Go here: http://jvz1.com/c/41743/183906 The Wordpress Ecourse. Learn how to Make World Class Websites for $20 or less. https://screwthecommute.com/wordpressecourse/

In this episode, host Janet Michael talks with Guy Curtis - Director of Marketing, Laurel Ridge Community College, Christine Kriz - Director of Corporate Training, Laurel Ridge Workforce Solutions, and Professor Corinne Hoisington - Professor, Central Virginia Community College; AI educator, international speaker, and author of AI: A Business Perspective, to discuss the Laurel Ridge AI Summit — a half-day event designed to bring practical AI education to workers, business owners, and community members across the Shenandoah Valley. Key Topics Covered Laurel Ridge's year-long participation in the American Association of Colleges and Universities AI initiative How local companies are asking for guidance on AI policies and employee training Why AI isn't as scary as it seems — and why most of us are already using it Real-world AI examples: car inspections, mammogram cancer detection, smart vacuums, autocorrect The three AI-proof job types: Imagination Workers, Skilled Workers, and Emotional Workers How AI is leveling the playing field across every industry Free AI tools beyond ChatGPT — and how to use them responsibly The importance of verifying AI output and keeping humanity in the loop Summit Session Breakdown Time Session 8–9 AM In the Blink of AI – Charting a Course for Virginia's AI-Powered Future 9:15–10:15 AM Navigating the AI Revolution – Adapting Your Career Path for the Future of Work 10:30–11:30 AM Creativity in the Workplace and Classroom – Supercharging Skills with AI Tools Event Details Date: April 1st Time: 8:00 AM – 12:00 PM Location: Corron Community Development Center, Middletown Campus, Laurel Ridge Community College Cost: $225 per person Register: laurelridgeworkforce.com/aisummit Questions: Call 540-868-7021

Today we're going to show you how to become an authority in a hurry. In other words, we're going to call this authority shortcuts. Launch Team - https://www.ScrewTheCommute.com/launchteam Please watch this short trailer to the end and leave a comment - https://www.facebook.com/AmericanEntrepreneurFilm/videos/558575401181955 AI Summit - https://www.ScrewTheCommute.com/aisummit Screw The Commute Podcast Show Notes Episode 1092 How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Training Center - https://imtcva.org/ Higher Education Webinar – https://screwthecommute.com/webinars See Tom's Stuff – https://linktr.ee/antionandassociates 00:23 Tom's introduction to Authority Shortcuts 02:13 Borrowing trust to get known 03:04 Podcast guesting, joint ventures, testimonials, media logos 06:20 Partnerships, summits Entrepreneurial Resources Mentioned in This Podcast Higher Education Webinar - https://screwthecommute.com/webinars Screw The Commute - https://screwthecommute.com/ Screw The Commute Podcast App - https://screwthecommute.com/app/ Screw The Commute Podcast Producer - https://screwthecommute.com/larryguerrera/ College Ripoff Quiz - https://imtcva.org/quiz Know a young person for our Youth Episode Series? Send an email to Tom! - orders@antion.com Have a Roku box? Find Tom's Public Speaking Channel there! - https://channelstore.roku.com/details/267358/the-public-speaking-channel How To Automate Your Business - https://screwthecommute.com/automatefree/ Internet Marketing Retreat and Joint Venture Program - https://greatinternetmarketingtraining.com/ This is the shopping cart system Tom uses! Kartra - https://screwthecommute.com/kartra/ Copywriting901 - https://copywriting901.com/ Become a Great Podcast Guest - https://screwthecommute.com/greatpodcastguest Training - https://screwthecommute.com/training Disabilities Page - https://imtcva.org/disabilities/ Tom's Patreon Page - https://screwthecommute.com/patreon/ Tom on TikTok - https://tiktok.com/@digitalmultimillionaire/ Email Tom: Tom@ScrewTheCommute.com Internet Marketing Training Center - https://imtcva.org/ Related Episodes Dangerous Digital Sharecropping - https://screwthecommute.com/1091/ More Entrepreneurial Resources for Home Based Business, Lifestyle Business, Passive Income, Professional Speaking and Online Business I discovered a great new headline / subject line / subheading generator that will actually analyze which headlines and subject lines are best for your market. I negotiated a deal with the developer of this revolutionary and inexpensive software. Oh, and it's good on Mac and PC. Go here: http://jvz1.com/c/41743/183906 The Wordpress Ecourse. Learn how to Make World Class Websites for $20 or less. https://screwthecommute.com/wordpressecourse/

Bill Gates, the co-founder of Microsoft and a leading global philanthropist, withdrew from delivering his scheduled keynote address at the India AI Impact Summit in New Delhi just hours before he was set to speak. The Gates Foundation issued a statement saying the decision was made “to ensure the focus remains on the AI Summit's key priorities,” and Ankur Vora, president of the foundation's Africa and India offices, delivered the address in his place. Gates had been initially confirmed and was in India ahead of the event, which was designed to position India as a hub for artificial intelligence development and governance.The sudden cancellation came amid heightened scrutiny over Gates's past interactions with the late financier and convicted sex offender Jeffrey Epstein after recently released U.S. Justice Department documents included emails involving Gates Foundation staff and Epstein. Although Gates denies any impropriety and says he regretted associating with Epstein, the controversy drew significant attention in Indian media and public debate in the lead-up to the summit. Some commentators linked the timing of his withdrawal to that controversy, even as summit organizers and Indian officials did not directly tie the decision to the Epstein files.to c ontact me:bobbycapucci@protonmail.comsource:Bill Gates cancels AI summit keynote address amid scrutiny over Epstein links | CNN

This week we go “talk show mode” for a special episode where Marlene recaps her trip to the Women + AI 2.0 Summit at Vanderbilt Law, hosted by Cat Moon, and shares why the event felt different from the standard conference grind, more energy, more structure, and yes, a DJ.The summit's core focus sits right on a tension point in the wider AI conversation. There's a persistent narrative that women use AI less than men. Cat Moon's framing, if it's true, it's a problem, and if it's false, it's also a problem, sets the tone for a day built around participation and peer connection. The format uses “spark” cards, mini, midi, and maxi prompts, to push attendees into small conversations, deeper reflection, and a final takeaway.Marlene also highlights sobering research shared during the opening, including an “AI competence penalty” dynamic where identical work is judged differently depending on whether evaluators believe a man or a woman used AI. The discussion lands on why these biases matter inside legal workplaces, and what leaders and peers can do to reduce the social cost of being open about AI usage.Interspersed throughout are short interviews with attendees and speakers. Nicole Morris (Emory) captures the day's purpose, expanding AI knowledge, talking risks, and connecting across roles. Sabra Tomb (University of Dayton School of Law) reframes AI as a leadership amplifier, moving from day-to-day management overload toward strategy and vision. Adele Shen (Vanderbilt) offers a funny but sharp taxonomy of AI “experts,” including “technocratic oracles,” “extinction alarmists,” and “touch grass humanists,” which sparks a candid side conversation about self-promotion, authority vibes, and who becomes “the story” in AI discourse.The episode closes with a look at how education and training can work better. Marlene and Greg lean into peer show-and-tell sessions, leadership modeling, and safe spaces, both governance-safe and learning-safe. A two-person segment from Suffolk Law (Chanal Neves McClain and Dyane O'Leary) adds a teaching twist, integrating AI tools into skills instruction without isolating “AI week” from real lawyering judgment. The final note comes from Stephanie Everett (Lawyerist) on the power of stories, and the reminder that people do not need to internalize the narrative someone else hands them.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | Substack [Special Thanks to ⁠Legal Technology Hub⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠ 

As world leaders and tech bosses gather for India's AI Impact Summit, Danny Fortson and Mark Sellman ask if these global summits are shaping AI or struggling to keep up with it? They also hear from Carina Prunkl, lead author of the new International AI Safety Report, about risks, jobs, autonomy and whether safeguards are keeping pace with technology. Plus, OpenAI snaps up viral agent OpenClaw. Image: Getty Hosted on Acast. See acast.com/privacy for more information.

Bill Gates, the co-founder of Microsoft and a leading global philanthropist, withdrew from delivering his scheduled keynote address at the India AI Impact Summit in New Delhi just hours before he was set to speak. The Gates Foundation issued a statement saying the decision was made “to ensure the focus remains on the AI Summit's key priorities,” and Ankur Vora, president of the foundation's Africa and India offices, delivered the address in his place. Gates had been initially confirmed and was in India ahead of the event, which was designed to position India as a hub for artificial intelligence development and governance.The sudden cancellation came amid heightened scrutiny over Gates's past interactions with the late financier and convicted sex offender Jeffrey Epstein after recently released U.S. Justice Department documents included emails involving Gates Foundation staff and Epstein. Although Gates denies any impropriety and says he regretted associating with Epstein, the controversy drew significant attention in Indian media and public debate in the lead-up to the summit. Some commentators linked the timing of his withdrawal to that controversy, even as summit organizers and Indian officials did not directly tie the decision to the Epstein files.to c ontact me:bobbycapucci@protonmail.comsource:Bill Gates cancels AI summit keynote address amid scrutiny over Epstein links | CNNBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-epstein-chronicles--5003294/support.

Did the gatekeepers at the India AI Summit decide that they needed to be Gateskeepers? Was Bill Gates quietly told that he would not be welcome at a Summit that is already reeling from controversy after controversy? It does look like that. Even before the event, government ‘sources' were quoted as saying there had been a change of plan and that Gates would not be speaking. But the Gates Foundation insisted that he would address the Summit as scheduled.

The headlines of the week by The Indian Express

The U.S. Supreme Court delivers the President a major blow, ruling he overstepped his authority by using emergency presidential powers to impose sweeping tariffs last year. Today, he replied angrily at the court decision taking swipes at Justices, the plaintiffs in the case, and Canada, while announcing a new 10 per cent global tariff using a different piece of legislation.Also: Alberta Premier Danielle Smith lays out plans for a referendum on a series of questions. One is mainly focused on immigration. Smith claims Ottawa's immigration policies are jeopardizing her province's finances.And: Canada's hockey men deliver an Olympic semi-final thriller, setting up a potential gold-medal classic with our American rivals.Plus: What today's SCOTUS ruling means for Canada, India's AI Summit, from catching footballs to pushing bobsleds, and more.

Is Bill Gates in hiding over his name being in the Epstein files? Gates cancelled an appearance at a huge AI summit just hours before the event. Of course they're denying questions about Epstein are why... but even Reuters doubts that excuse.Watch the podcast episodes on YouTube and all major podcast hosts including Spotify.CLOWNFISH TV is an independent, opinionated news and commentary podcast that covers Entertainment and Tech from a consumer's point of view. We talk about Gaming, Comics, Anime, TV, Movies, Animation and more. Hosted by Kneon and Geeky Sparkles.Get more news, views and reviews on Clownfish TV News - https://more.clownfishtv.com/On YouTube - https://www.youtube.com/c/ClownfishTVOn Spotify - https://open.spotify.com/show/4Tu83D1NcCmh7K1zHIedvgOn Apple Podcasts - https://podcasts.apple.com/us/podcast/clownfish-tv-audio-edition/id1726838629

Things are getting messy on multiple fronts: Bill Gates canceled at India's AI Summit amid backlash over the Epstein files. Prince Andrew arrested — a reminder that elite immunity is vanishing. The Gates Foundation's tech influence in India raises global censorship concerns. Germany asserts the right to censor Viktor Orbán during Hungary's election, sparking debates about digital sovereignty. Stephen Colbert caught flouting FCC equal-time rules during a senatorial campaign. From elite scandals to global censorship to media hypocrisy, this episode breaks down why accountability is finally catching up with the powerful — and why the law applies to everyone, even TV hosts.

Leanna Byrne looks at the opening of India's AI Impact Summit, where the withdrawal of Microsoft founder Bill Gates has cast a shadow after he cancelled his keynote appearance. His foundation says he stepped back to avoid distracting from the event.France and Germany are at odds over their joint next-generation fighter jet project, raising doubts about its future.And the IMF warns China is relying too heavily on industrial subsidies.

AP's Lisa Dwyer reports that a university in India has been caught passing off a robotic dog as their own invention.

Kapil Gupta, former Enterprise AI Product & Platform Leader at Cigna, shares insights from more than two decades of turning cutting-edge technology into enterprise-ready products. He unpacks the difference between generative AI and agentic AI, and why governance, user choice, and thoughtful design matter just as much as innovation. Learn how enterprises can scale responsibly and why the best technology often feels invisible to the people using it. Key Takeaways:  The tangible difference between generative AI and agent-based workflows Why adoption depends on fitting into existing workflows, rather than forcing behavior change The challenge of legacy systems and disconnected data How companies can innovate quickly without introducing unnecessary risk How pushing back, probing, and questioning AI can unlock more value Why listening to users matters more than building flashy features Guest Bio: Kapil Gupta is an executive product leader specializing in leveraging emerging technologies to solve complex business problems at scale. As a leader of AI product and platform teams at Cigna and previously at industry leaders like Capital One, Deloitte, and IBM, he has turned breakthrough innovations like Generative AI into practical enterprise solutions.  Kapil is driven by a focus on crafting AI-driven product experiences that solve real problems and ensure high adoption, bridging the gap between sophisticated technology and business value. He balances high-level strategic vision with a passion for staying hands-on, often vibe coding prototypes to prove out new concepts. Kapil holds an MS in Computer Science and an MBA from NYU Stern. He shares his work at kapilgupta.me and lives in New York. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte

The Trump administration's July 2025 AI Action Plan calls on National Institute of Standards & Technology to revise its AI Risk Management Framework amid easing federal regulation of the tech. Martin Stanley, principal researcher for AI and cybersecurity at NIST, joined us at the AI Summit on Jan. 9 to discuss new AI control overlays for the Special Publication 800-53 series and the risks they are designed to address. Stanley explained how these overlays build on existing security controls to help agencies better manage AI-specific threats while aligning with broader federal priorities outlined in the AI Action Plan. Stanley also explored where agencies struggle to turn AI risk frameworks into operational reality, from governance structures to implementation at the system level. Looking ahead, he shared how NIST expects AI security guidance to evolve as agencies transition from pilot projects to enterprise deployments and what new or updated standards federal leaders should anticipate next.

Chastity Murphy, former Senior Advisor at the U.S.Treasury and Visiting Research Fellow at the University of Manchester, shares her experiences working on digital money legislation, including the Stable Act. She reflects on the transition from cash to digital payments along with her current research developing offline, anonymous public interest payment systems. Key Takeaways: How early stablecoin legislation shaped our understanding of digital money, privacy, and consumer protection The gap between technologists and policymakers in understanding digital money Real-world risks of surveillance and data visibility in financial transactions The potential for new cryptographic capabilities like selective disclosure and zero-knowledge proofs Practical approaches for creating offline, anonymous, and interoperable digital payment systems that don't sacrifice usability Guest Bio:  Chastity Murphy is a Visiting Research Fellow at the University of Manchester's Law & Technology Initiative, and one of the leading architects of privacy-preserving digital public money. A former Senior Advisor at the U.S. Treasury Department, she helped shape federal policy on central bank digital currency (CBDC) and digital payments, building on her earlier work as the first congressional staffer (under Rep. Rashida Tlaib) to draft stablecoin legislation. Her current research at Manchester's Digital Public Money Infrastructure (DPMI) project explores how cryptography and shield-law protections can make digital money safe for people—not platforms. The work prototypes use cases such as anonymous public-interest payments and privacy-secure disbursement systems for reproductive-health providers, disaster aid, and humanitarian relief. This work focuses on ensuring that the right to transact safely endures across political climates, crises, medical emergencies, and everyday use. ---------------------------------------------------------------------------------------- About this Show: The Brave Technologist is here to shed light on the opportunities and challenges of emerging tech. To make it digestible, less scary, and more approachable for all! Join us as we embark on a mission to demystify artificial intelligence, challenge the status quo, and empower everyday people to embrace the digital revolution. Whether you're a tech enthusiast, a curious mind, or an industry professional, this podcast invites you to join the conversation and explore the future of AI together. The Brave Technologist Podcast is hosted by Luke Mulks, VP Business Operations at Brave Software—makers of the privacy-respecting Brave browser and Search engine, and now powering AI everywhere with the Brave Search API. Music by: Ari Dvorin Produced by: Sam Laliberte  

Cybersecurity and Infrastructure Security Agency CIO Bob Costello joined GovCIO Media & Research at its AI Summit earlier this year to discuss how the agency is deploying agentic AI and tackling cybersecurity workforce challenges. Costello outlined how CISA is integrating AI into operations while prioritizing security, oversight and workforce readiness. Costello also highlighted CISA's partnership with the Office of Personnel Management on the Scholarship for Service CyberCorps program, which aims to strengthen the federal cybersecurity talent pipeline. He said agencies need new approaches to help employees better understand AI's role and build confidence using the technology in day-to-day work. The conversation also touched on how CISA's agentic AI capabilities are accelerating approval timelines and autonomously taking action to mitigate cyber threats.

Key TakeawaysAI's progress: Wiese expresses excitement to return to the event after a year to hear real case studies on how people have embraced AI, especially appreciating the human and change‑management side of this transformational journey. Specifically, she's eager to learn where organizations have tested, scaled, or faced pushback over the past 12 months, noting that adopting AI is an ongoing, iterative process.Curating the agenda: "I think my number one view of all of the submissions was around innovation," notes Wiese, who played a role as a Programming Committee Board member, selecting sessions for the 2026 AI Agent & Copilot Summit agenda. In her process, she looked for examples of where organizations have truly innovated with this technology. "I want honest, too. You know, 'this is what we tried. It didn't work, but we came back at it, here's how'".AI's impact on women in tech: On Thursday, March 19, Wiese will lead a Fireside Chat around her new book, "You're on Mute." The book explores whether AI has actually helped women enter and thrive in the tech industry amid persistent adoption and trust gaps. Through stories from contributors, it examines AI's impact on leveling the playing field and encourages more women to see AI as a path into tech.Event expectations: The real power of conferences and events comes from being together, notes Wiese. With the lineup of speakers, she believes attendees will gain access to candid insights and meaningful peer connections. Visit Cloud Wars for more.