Podcasts about architecturally

Castles speak. Especially in an age when they are no longer necessary. The Act of Union of 1800, which brought Ireland into closer association with Britain, challenged the status of Irish landed proprietors, and not a few responded by building castles. In Gothic: Building Castles in Post-Union Ireland (Four Courts Press, 2026) Dr. Judith Hill explores the projects of two Irish proprietors: the Burys, later Lord and Lady Charleville, who commissioned Francis Johnston, then Ireland's most important architect, to design Charleville Castle; and Lawrence Parsons, later 2nd Earl of Rosse, who reimagined seventeenth-century Parsonstown House as early nineteenth-century Birr Castle.  Architecturally the castles belong to Georgian Gothic, a style that in Britain is overshadowed by later nineteenth-century Gothic and is largely overlooked in Ireland. In this fascinating new book, Dr. Hill investigates Georgian Gothic in its own terms as both a British and Irish phenomenon, demonstrating how antiquarian understanding, associative thinking, awareness of family pedigree and historicised design ideas resulted in a uniquely Irish response to the Gothic revival. Using the ample surviving archives related to both families, she argues that these architecturally original and significant castles eloquently expressed their builders' political and social concerns, making them artefacts of cultural unionism. This interview was conducted by Dr. Miranda Melcher whose book focuses on post-conflict military integration, understanding treaty negotiation and implementation in civil war contexts, with qualitative analysis of the Angolan and Mozambican civil wars. You can find Miranda's interviews on New Books with Miranda Melcher, wherever you get your podcasts.  Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Castles speak. Especially in an age when they are no longer necessary. The Act of Union of 1800, which brought Ireland into closer association with Britain, challenged the status of Irish landed proprietors, and not a few responded by building castles. In Gothic: Building Castles in Post-Union Ireland (Four Courts Press, 2026) Dr. Judith Hill explores the projects of two Irish proprietors: the Burys, later Lord and Lady Charleville, who commissioned Francis Johnston, then Ireland's most important architect, to design Charleville Castle; and Lawrence Parsons, later 2nd Earl of Rosse, who reimagined seventeenth-century Parsonstown House as early nineteenth-century Birr Castle.  Architecturally the castles belong to Georgian Gothic, a style that in Britain is overshadowed by later nineteenth-century Gothic and is largely overlooked in Ireland. In this fascinating new book, Dr. Hill investigates Georgian Gothic in its own terms as both a British and Irish phenomenon, demonstrating how antiquarian understanding, associative thinking, awareness of family pedigree and historicised design ideas resulted in a uniquely Irish response to the Gothic revival. Using the ample surviving archives related to both families, she argues that these architecturally original and significant castles eloquently expressed their builders' political and social concerns, making them artefacts of cultural unionism. This interview was conducted by Dr. Miranda Melcher whose book focuses on post-conflict military integration, understanding treaty negotiation and implementation in civil war contexts, with qualitative analysis of the Angolan and Mozambican civil wars. You can find Miranda's interviews on New Books with Miranda Melcher, wherever you get your podcasts.  Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/architecture

Castles speak. Especially in an age when they are no longer necessary. The Act of Union of 1800, which brought Ireland into closer association with Britain, challenged the status of Irish landed proprietors, and not a few responded by building castles. In Gothic: Building Castles in Post-Union Ireland (Four Courts Press, 2026) Dr. Judith Hill explores the projects of two Irish proprietors: the Burys, later Lord and Lady Charleville, who commissioned Francis Johnston, then Ireland's most important architect, to design Charleville Castle; and Lawrence Parsons, later 2nd Earl of Rosse, who reimagined seventeenth-century Parsonstown House as early nineteenth-century Birr Castle.  Architecturally the castles belong to Georgian Gothic, a style that in Britain is overshadowed by later nineteenth-century Gothic and is largely overlooked in Ireland. In this fascinating new book, Dr. Hill investigates Georgian Gothic in its own terms as both a British and Irish phenomenon, demonstrating how antiquarian understanding, associative thinking, awareness of family pedigree and historicised design ideas resulted in a uniquely Irish response to the Gothic revival. Using the ample surviving archives related to both families, she argues that these architecturally original and significant castles eloquently expressed their builders' political and social concerns, making them artefacts of cultural unionism. This interview was conducted by Dr. Miranda Melcher whose book focuses on post-conflict military integration, understanding treaty negotiation and implementation in civil war contexts, with qualitative analysis of the Angolan and Mozambican civil wars. You can find Miranda's interviews on New Books with Miranda Melcher, wherever you get your podcasts.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Castles speak. Especially in an age when they are no longer necessary. The Act of Union of 1800, which brought Ireland into closer association with Britain, challenged the status of Irish landed proprietors, and not a few responded by building castles. In Gothic: Building Castles in Post-Union Ireland (Four Courts Press, 2026) Dr. Judith Hill explores the projects of two Irish proprietors: the Burys, later Lord and Lady Charleville, who commissioned Francis Johnston, then Ireland's most important architect, to design Charleville Castle; and Lawrence Parsons, later 2nd Earl of Rosse, who reimagined seventeenth-century Parsonstown House as early nineteenth-century Birr Castle.  Architecturally the castles belong to Georgian Gothic, a style that in Britain is overshadowed by later nineteenth-century Gothic and is largely overlooked in Ireland. In this fascinating new book, Dr. Hill investigates Georgian Gothic in its own terms as both a British and Irish phenomenon, demonstrating how antiquarian understanding, associative thinking, awareness of family pedigree and historicised design ideas resulted in a uniquely Irish response to the Gothic revival. Using the ample surviving archives related to both families, she argues that these architecturally original and significant castles eloquently expressed their builders' political and social concerns, making them artefacts of cultural unionism. This interview was conducted by Dr. Miranda Melcher whose book focuses on post-conflict military integration, understanding treaty negotiation and implementation in civil war contexts, with qualitative analysis of the Angolan and Mozambican civil wars. You can find Miranda's interviews on New Books with Miranda Melcher, wherever you get your podcasts.  Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/british-studies

Fresh off raising a monster $15B, Marc Andreessen has lived through multiple computing platform shifts firsthand, from Mosaic and Netscape to cofounding A16z. In this episode, Marc joins swyx and Alessio in a16z's legendary Sand Hill Road office to argue that AI is not just another hype cycle, but the payoff of an “80-year overnight success”: from neural nets and expert systems to transformers, reasoning models, coding, agents, and recursive self-improvement. He lays out why he thinks this moment is different, why AI is finally escaping the old boom-bust pattern, and why the real bottleneck may be less about models than about the messy institutions, incentives, and social systems that struggle to absorb technological change.This episode was a dream come true for us, and many thanks to Erik Torenberg for the assist in setting this up. Full episode on YouTube!We discuss:* Marc's long view on AI: from the 1980s AI boom and expert systems to AlexNet, transformers, and why he sees today's moment as the culmination of decades of compounding technical progress* Why “this time is different”: the jump from LLMs to reasoning, coding, agents, and recursive self-improvement, and why Marc thinks these breakthroughs make AI real in a way prior cycles were not* AI winters vs. “80-year overnight success”: why the field repeatedly swings between utopianism and doom, and why Marc thinks the underlying researchers were mostly right even when the timelines were wrong* Scaling laws, Moore's Law, and what to build: why he believes AI scaling laws will continue, why the outside world is messier than lab purists assume, and how startups can still create durable value on top of rapidly improving models* The dot-com crash and AI infrastructure risk: Marc's comparison between today's AI capex boom and the fiber/data-center overbuild of 2000, plus why he thinks this cycle is different because the buyers are huge cash-rich incumbents and demand is already here* Why old NVIDIA chips may be getting more valuable: the pace of software progress, chronic capacity shortages, and the idea that even current models are “sandbagged” by supply constraints* Open source, edge inference, and the chip bottleneck: why Marc thinks local models, Apple Silicon, privacy, trust, and economics all point toward a major role for edge AI* American vs. Chinese open source AI: DeepSeek as a “gift to the world,” why open models matter not just because they're free but because they teach the world how things work, and how open source strategies may shift as the market consolidates* Why Pi and OpenClaw matter so much: Marc's claim that the combination of LLM + shell + filesystem + markdown + cron loop is one of the biggest software architecture breakthroughs in decades* Agents as the new “Unix”: how agent state living in files allows portability across models and runtimes, and why self-modifying agents that can extend themselves may redefine what software even is* The future of coding and programming languages: why Marc thinks software becomes abundant, why bots may translate freely across languages, and why “programming language” itself may stop being a salient concept* Browsers, protocols, and human readability: lessons from Mosaic and the web, why text protocols and “view source” mattered, and how similar principles may shape AI-native systems* Real-world OpenClaw use: health dashboards, sleep monitoring, smart homes, rewriting firmware on robot dogs, and why the most aggressive users are discovering both the power and danger of agents first* Proof of human vs. proof of bot: why Marc thinks the internet's bot problem is now unsolvable via detection alone, and why biometric + cryptographic proof of human becomes necessaryTimestamps* 00:00 Marc on AI's “80-Year Overnight Success”* 00:01 A Quick Message From swyx* 01:44 Inside a16z With Marc Andreessen* 02:13 The Truth About a16z's AI Pivot* 03:29 Why This AI Boom Is Not Like 2016* 06:33 Marc on AI Winters, Hype Cycles, and What's Different Now* 10:09 Reasoning, Coding, Agents, and the New AI Breakthroughs* 12:13 What Founders Should Build as Models Keep Improving* 16:33 AI Capex, GPU Shortages, and the Dot-Com Crash Analogy* 24:54 Open Source AI, Edge Inference, and Why It Matters* 33:03 Why OpenClaw and PI Could Change Software Forever* 41:37 Agents, the End of Interfaces, and Software for Bots* 46:47 Do Programming Languages Even Have a Future?* 54:19 AI Agents Need Money: Payments, Crypto, and Stablecoins* 56:59 Proof of Human, Internet Bots, and the Drone Problem* 01:06:12 AI, Management, and the Return of Founder-Led Companies* 01:12:23 Why the Real Economy May Resist AI Longer Than Expected* 01:15:53 Closing ThoughtsTranscriptMarc: Something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic. Having said that, I think what's actually happened is an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years where that was controversial. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right?Which is like, it's an overnight success ‘cause it's like bam, you know, chat GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.If I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough.swyx: Before we get into today's episode, I just have a small message for listeners. Thank you. We will not be able to bring you the ai, engineering, science, and entertainment contents that you so clearly want if you didn't choose to also click in and tune into our content.We've been approached by sponsors on an almost daily basis, but fortunately enough of you actually subscribed to us to keep all this sustainable without ads, and we wanna keep it that way. But I just have one favor to ask all of you. The single, most powerful, completely free thing you can do is to click that subscribe button.It's the only thing I'll ever ask of you, and it means absolutely everything to me and my team that works so hard to bring the in space to you each and every week. If you do it, I promise you will never stop working to make the show even better. Now, let's get into it.Alessio: Hey everyone, welcome to the Lidian Space Pockets. This is CIO, founder Kernel Labs, and I'm joined by s Swix, editor of Lidian Space.swyx: Hello. And we're in a 16 Z with a, uh, mark G and welcome.Marc: Yes, yes. A and what, half of 16? Something like that. A one. Exactly,swyx: exactly. Uh, apparently this is the, the final few days in your, your current office.You're moving across the road.Marc: Uh, we're, yeah. We have a, we have some, we have some projects underway, but yeah, this is actually, oh, this is the original. We're in actually the original office. We're in the, we're in the, we're, we're in the whole thing.swyx: It's beautiful. Yeah. Great.Marc: Thank you.swyx: So I have to come out, uh, this is a, you know, I wanted to pick a spicy start in October, 2022.I just made friends with Roone and, uh, I wanted to give him something to sort of be spicy about. And I said, uh. Uh, it'll never not be funny. The A 16 Z was constantly going. The future is where the smart people choose to spend their time and then going deep into crypto and not in ai. And that was in October 22nd, 2022.And Ruen says there was an internal meeting in a 16 Z to reorient around Gen ai. Obviously you have, but was there a meeting? What, what was that?Marc: I mean, I don't, look, I've been doing AI since the late eighties.swyx: Yeah.Marc: So I, I don't know, like all that, as far as I'm concerned, this stuff is all Johnny cum lately.Yeah. You, I mean, look, we've been doing ar entire existence. I mean, we've been doing AI machine learning deep, you know, deeply. We've been doing this stuff way from the beginning. Obviously a AI is just core to computer science. I, I, I actually view them as like quite, uh, quite continuous. Um, you know, Ben and I both have computer science degrees.Um, you know, we, we both, Ben, Ben and I actually both are world enough to remember the actual AI boom in the 1980s. Yeah. There was like a, there was a big AI boom at the time. Um, and there was a, was names like expert systems. Um, and they of like lisp and lisp machines. Uh, I, I coded in lisp. I was coding a lisp in 1989.When that was the, the language of the AI future. Um, yeah. So this is something that we're like completely, you completely comfortable with. I've been doing the whole time and are very enthusiastic aboutswyx: is there a strong, like this time is different because, uh, my closest analog was 20 16 17. It was an AI boom.Mm-hmm. And it petered out very, very quickly. Um, we, it just, it just in terms of investingMarc: sort of, sort of,swyx: yeah. Investment, investment excitement.Marc: Although that's really when the, the, the Nvidia phenomenon really, it was, I would say it was in that period when it was very clear that at, at the time it, the vocabulary was more machine learning, but it, it was very clear at that time that machine learning was hitting some sort of takeoff point.Alessio: Yeah.Marc: Well, and as you guys, you guys have talked about this at length on, on your thing, but, you know, if you really track what happened, I think the real story is, it was, it was the Alex net, uh, basically breakthrough in like 2013. That was the, that was the real knee in the curve. Um, and then it was obviously the transformer breakthrough in 17.Alessio: Yeah.Marc: Um, and then everything that followed. But, but, you know, look, machine learning, you know, there were, you know, look, uh, I mean look, I've been working, you know, I've been working with, uh, one of my, you know, kind of projects working with Facebook since 2004. Um, and on the board since 2007, and of course, you know, they, they started using machine learning very early, um, and, you know, have used it basically, you know, for like 20 years for, you know, content, you know, feed optimization and advertising optimization.And obviously many, you know, financial services. You know, many, many, many companies, many different sectors have been doing this. And so it's like one of these things, it's like, it's not a, it's not a single thing. Like it's, it's like, it's like layers, right? Yeah. Um, and, and the layers arrive at different paces and, but they kind of build up.swyx: Yeah.Marc: Uh, they kind of build up over time and then, and then, yeah. And then look, in retrospect, it was 2017 was kind of the, you know, the key, the key point with the trans transformer and then. And then as you guys know, there was this really weird like four year period where it's like the, the transformer existed and then it was just like,swyx: let's go.Yeah.Marc: Well, but, but it was just, but, but between 2020, but between 2017 and 2021, I mean, that was the era of which like companies like Google had internal chat Botts, but they weren't letting anybody use them.swyx: Yeah.Marc: Right. And then, you know, and then OpenAI developed Chat GT or GPT two, and then they told everybody, this is way too dangerous to deploy.Right. Yeah. You know, we can't possibly let normal people, normal people use this thing. And then you, you guys, I'm sure remember AI Dungeon, um mm-hmm. So the o for, there was like a year where like the only way for a normal person to use GP T three was in, in AI dungeon.Alessio: Yeah.Marc: And so you, you, we would do this, you'd go in there and you'd pretend to play Dungeons and Dragons.In reality, you're just trying to talk to talk to GPT. And so there was this, you know, there was this long, you know, and I, you know, the big, big companies, you know, big companies are cautious and, you know, the big companies were cautious. It, it, by the way, it took open ai. You know, they, they, they talk about this, it took open AI time to actually adjust, you know, kind of re redirect their researchswyx: path.I, I think, uh, let say Rosewood, right? Uh, the, the dinner that founded OpenAI was right there.Marc: Right, right. But that, that dinner would've taken place in 20swyx: 18Marc: 19. The formation of OpenAI Uhhuh as late as 2018.swyx: Uh, uh, sorry. Uh, no, I'm, I'm, I'm, I'm wrong. Probably It should be 20. Yeah. They just celebrated a 10 year anniversary, so it it is 2025.Yeah, so, so 2015?Marc: Yeah. 2015. Yeah. 2015. But then, uh, um, Alec Radford did G PT one in what, probablyswyx: mm-hmm. 17, 18,Marc: yeah. 17, 18. So it, yeah. For, and then, and then they didn't really, and then GPT three was what? 2020? 2020.swyx: 2020.Marc: Because that became copilot immediately. Even open ai, which has been, you know, the leader of, of this thing in the last decade, you know, e even they had to adapt and, and, and lean into the new thing.And so. Um, yeah, I, I think it's just this process of basically sort of wave after wave layer after layer, you know, building on itself. And then you kind of get these catalytic moments where, where the whole thing pops and, and obviously that's what's happening now.swyx: Is it useful to think about will there be any ai, winter?‘cause there's always these patterns. Like, is this, in the summer is something I constantly think about because do I get, do I just like. Just get endlessly hyped and just trust that I will only be early and never wrong or right. Well, are we, will there be a winter?Marc: So there's something about, say the following.There's something about AI that has led to this repeated pattern. Um, and, and, and you guys know this,swyx: it's summer, winter, summer,Marc: winter, summer, winter, summer, winter. And it goes back 80 years. Yeah. 80 years. Uh, so the original neural network paper was 1943. Right. Which is, which is amazing. Uh, that it was, it was far back that long.And then there was you, if you guys have ever talked about this on your show, but there was this, uh, there was a big, uh, there was an a GI conference at Dartmouth University in 1950. 55. 55, yeah. And they got a NSF grant to, uh, for the, all the AI experts at the time to spend the summer together. And they figured if they had 10 weeks together, they could get a GI, uh, at the other end.And they got their, by the way, they got the grant, they got the 10 weeks and then, you know, 1955, you know. No, no. A GI. And like I said, I, I lived through the eighties version of this where there was a big, a big boom and a crash. And so, so there is this thing, and there, there is something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic.Um, and, and it's probably on both sides of like the, the, the boom bus cycle. You, you kind of see that play out. Having said that, I think what's actually happened is like just, and you know, and we now know in retrospect like an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years or that was controversial. And, and we now know that that's the case. And so we, we now, you know, everything we're building on today just sort of derives from the original idea in 1943. And so, so in retrospect, we, we now know that like, these, these guys are right.They, they, you know, they would get the timing wrong and they thought, you know, capabilities would arrive faster, or they were, it could be turned into businesses sooner or whatever, but like, they were fundamentally, the, the scientists who worked on this over the course of decades were fundamentally correct about what they were doing.And, and the, and the payoff from, from, from all their work is happening now. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right? Which is like, it's an overnight success.‘cause it's like bam, you know, chat, GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.Um, and thinking, and look, there were AI researchers who spent their entire lives. They got their PhD. They, they worked for, they've researched for 40 years. They retired in a lot of cases, they passed away and they never actually saw it work.swyx: Yeah. It's all sad.Marc: It is. It is sad. It's sad. Knewswyx: Jeff Hinton was like the last guy.Marc: Yeah. Yeah. Well, there were the guys, uh, was a guy, Alan Newell. I mean, there's tons of John McCarthy. You know, John McCarthy was like one of the inventors in the field. He's one of the guys who organized the Dartmouth Conference and you know, he taught at Stanford for 40 years. Wow. And passed, you know, passed away, I don't know, whatever, 10, 10 years ago or something.Never, never actually go. Got to see it happen. But like, it is amazing in retrospect, like, these guys were incredibly smart and they worked really hard and they were correct. So anyway, so then it's like, okay, you know, say history doesn't repeat, but it rhymes. It's like, okay, does that mean that there's gonna be another, like, you know, basically boom buzz cycle.And I, I will tell you, like, let, like in a sense, like yes, everything goes through cycles and, you know, people get overly enthusiastic and overly depressed and there's, there's a time, there's a timelessness to that. Having said that, there's just no question. Um, so the form, the foremost dangerous words in investing this time are, this time is different.Do you know the 12 most dangerous words investing? No. The four most d foremost dangerous words in investing are this time is different. Yeah. Um, the 12 most dangerous words. And so like, I'll tell you what's different. Like now it's working like, like there's just no, I mean, look, there's just no question.And by the way, I, I'll just give you guys my take. Like L LLMs, like from, from basically the Chad G PT moment through to spring of 25. I think you could still, I think well intention, well, and of. Form skeptics could still say, oh, this is just pattern completion. And oh, these things don't really understand what they're doing.And you know, the hall hallucination rates are way too high. And, you know, this is gonna be great for creative writing and creating, you know, Shakespeare and so sonnets and, you know, as, as rap lyrics or whatever, like, it's gonna be great and all that stuff, but we're not gonna be able to harness this to make this relevant in, you know, coding or in medicine or in law or in, you know, you know, kind of feels that, you know, kind of really, really matter.And I think basically it was the reasoning breakthrough. It, it was oh one and then R one that basically answered that question basically said, oh no, we're gonna be able to actually turn this into something that's gonna work in the real world. And, and then obviously the coding breakthrough over the, over basically the coding breakthrough that kind of catalyzed over the holiday break was kind of the third step in that.Mm-hmm. Where you're just like, alright, if, if, you know, if Linus Tova is saying that the AI coding is no better than he is like. Like, that's, that's never happened before. That's theswyx: benchmark.Marc: Yeah. That's never happened before. And so now we know that it's, it's gonna sweep through coding and, and then, and then we, we know, you know, we know that if it's gonna work in coding, it's gonna work in everything else.Right. It's just then, because that's, that's like, that's like, that's like the hardest in many ways. That's the hardest example. And how everything else is gonna be a, a derivative of that. And then on top of that, we just got the agent breakthrough, you know, with Open Claw, which is fantastic. Which is amazing and incredibly powerful.And then we just got the, the, um, the auto research, uh, you know, the, the self-improvement. You know, we're now into the self-improvement breakthrough. And so the, so the way I think about it is we've had four fundamental breakthroughs in functionality, l OMS reasoning, uh, agents, um, and then, uh, and, and then now RSI, um, and, and they're all actually working.Um, and so I'm, I'm just, as you like, you can tell I'm jumping outta my shoes. Like, like this is, like this is it like this, this is the culmination of 80 years worth of worth of work, and this is the time it's becoming real.Alessio: Yeah.Marc: I, I'm completely convinced.Alessio: I think the anxiety that people feel is like during the transistor era, yet Mors law, and it's like, all right, we understand why these things are getting better.We understand the physics of it. Yeah. With ai, it's. It's so jagged in like the jumps where like, like you said, it's like in three months you have like this huge jump like, and people are like, well this can keep happening. Right? But then it keeps happening,Marc: it'll keep happening.Alessio: And so like how do you think about also timelines of like what's we're building?I think we always have this question with guests, which is like, you know, should you spend time building harness for a model versus like the next model just gonna do it one shot in the lead space. Right. And how does that inform, like how you think about the shape of the technology? You know, you talk about how it's a new computing platform.If you have a computing platform, then like every six months it like drastically changes in what it looks like. It's hard to build companies on top of it.Marc: Yeah. So, so a couple things. So one is like, look, the, the Moore's law was what we now call a scaling law. Like Moore's Law was a scaling law and for your younger viewers, more Moore's Law was every chip chip chips either get twice as powerful or twice as cheap every, every 18 months.And that, and that and that, you know, that it's gotten more complicated in the last few years. But like that, that was like the 50 year trajectory of, of, of the computer industry. And then, and then by the way, and that's what took the mainframe computer from a $25 million current dollar thing into, you know, the phone in your pocket being, you know, a million times more powerful than that.Like that, you know, for, for 500 bucks. And so that, that was a scaling law. And then, and then, and then key to any scaling law, including Moore's Law and the AI scaling laws is, you know, they're not really laws, right? They're, they're, they're, they're predictions, but when they work, they become self-fulfilling predictions because they, they, they, they, they set a benchmark and, and then the entire industry, right?All the smart people in the industry kind of work to make sure that, that, that actually happens. And so they, they kind of motivate the breakthroughs that are required to, to keep that going. And, and in and in chips, that was a 50 year, that was a 50 year run. Right. And it, it was amazing. And it's still happening in, in some areas of, of chips.I think the same thing is happening with the, the core scaling laws. The core scaling laws. In, in, in ai, you know, they're, they're not really laws, but like they, they are basically. There are predictions and then they're motivating catalysts for the research work that is required to be. And, and, and, and by the way, also the investment, uh, dollars, um, uh, you know, required to basically keep, you know, keep the curves going and, and look, it, it is, it's gonna be complicated and it's gonna be variable and they're, you know, there're gonna be walls that are gonna look like they're fast approaching, and then they're gonna be, you know, engineers are gonna get to work and they're gonna figure out a way to punch through the walls.And obviously that's, you know, that's been happening a lot, you know, and then look, there's gonna be times when it looks like the walls have, you know, the, the, the laws have petered out and then they're gonna, they're gonna pick up again and surge and then, and then, and then it, it appears what's happening to the eyes is there's not multiple, you know, multiple scaling laws.Um, there's multiple areas of improvement. And, and I think, you know, I don't know how many more there are already yet to be discovered, but there are probably some more that we don't know about yet. You know, they, like, for example, there's probably some scaling law around, um, world models and robotics that we don't fully understand, you know, kind of acquisition of data at scale in the real world that we don't fully understand yet.So that, that, that one will probably kick in at some point here. There's a bunch of really smart people working on that. Um, and so, yeah, I, I think the expectation is that, that, you know, the, the scaling laws generally are gonna continue. Yeah. The, the pace of improvement will continue to move really fast.Um. To your question on like what to build. So, uh, I'm a complete believer the scaling laws are gonna continue. I'm a complete believer the capabilities are gonna keep getting amazing, um, you know, leaps and bounds. Uh, the part where I kind of part ways a little bit with how, what I would describe as the AI purists, um, you know, which is, which I would characterize as like the people who are.In many ways, the smartest people in the field, but also the people who spend their entire life, like at a lab, um, and have, have, I would say, have very little experience in the outside world. Um, the, the, the nuance I would offer is the outside world of 8 billion people and institutions and governments and companies and economic systems and social systems is really complicated.Um, and, um, and doesn't, you know, it it 8 billion people making collective decisions on planet Earth is not a simple process of like, just like you see this happening now. It's like a bunch of AI CEOs have this thing, which is just like, well, there's just this, they just all have this kind of thing when they talk in public where they're just like, well, there's these, these obvious set of things that so society to do.Alessio: Mm-hmm.Marc: And then they're like, society's not doing any of those things. Right. And it's like, how can society not, you know, what, whatever their theory is, how can society not see x, y, Z? Mm-hmm. And the answer is, well, society is number one. There's no single society, it's like 8 billion people. And they like all have a voice, and they all have a vote, like at the end of the day of how they, they react to change.And then, you know, it just like, it's just human reality is just really complicated and messy. Um, and, and, and so the specific answer to your question is like, as usual, it depends. Um, you know, it, it depends. Look, pe there's no question people are gonna, like, there's no question they're gonna be companies.It's already happening. There are companies that think that they're building value on top of the models and then they're just gonna get blissed by the, by the next model. There's no question that's happening. But I think there's no question also that just the process of adaptation of any technology into the real and into the real messy world of humanity is, is just going to be messy and complicated.It's, it's not going to be simple and straightforward. It's gonna be messy and complicated. And there are gonna be a lot of companies and a lot of products, um, uh, and in, in fact entire industries that are gonna get built to, to, to basically actually help all of this technology actually reach real people.Alessio: The amount of capital going into these companies, I mean, Dario talked about it on the Door Cash podcast and Door Cash was like, why don't you just buy 10 x more GPUs? And he is like, because I'm gonna go bankrupt if the model doesn't exactly hit the, the performance level. How do you think about that?Also as a risk on, you know, you guys are investors, open AI and thinking machines and world apps. It seems like we're leveraging the scaling loss at a pretty high rate, right? Like how comfortable, I guess, do you feel with the downside scenario, like, and say like things Peter out, you think you can kind of like restructure uh, these build outs and uh, you know, capital investments.Marc: Yeah. So should start by saying, so I live through the.com crash, um, and I can tell you stories for hours about the.com crash and it was horrible. No, it was awful. It was, it was, it was apocalyptic by the way. The, a lot of the.com crash was actually at the time, it was actually a telecom crash. It was a bandwidth crash.Like the, the thing that actually crashed, that wiped out all the money with the tele, the telecom companies.swyx: GlobalMarc: crossing. Global, global, yeah.swyx: I'm from Singapore and they, they laid so much cable o over over our oceans.Marc: Actually there was a scaling law in the.com. Era. And it was literally the, the US Commerce Department put out a report in 1996 and they said internet traffic was doubling every quarter.Um, and, and actually in 1995 and 1996, internet traffic actually did double every quarter. And so that became the scaling law. And so what all these telecom entrepreneurs did was they went out and they raised money to build fiber, anticipating that the demand for bandwidth is gonna keep doubling every quarter.Doubling every quarter though is like, you know, grains of chess and the chessboard, like at some point the numbers become extremely large. Right. And, and, and it really, and really what happened was the internet. The internet by the way, continuously kept growing basically since inception. And it's, you know, it's, it's continuously grown.It's never shrunk. And it's grown really fast compared to anything else. Mm-hmm. You know, in, in, in human history. But it wasn't doubling every quarter as of 19 98, 19 99. And so there was this gap in the expectation of what they thought was a scaling law versus reality. And that's actually what caused the.com crash, which was the, it they, they way over companies like global crossing way overbuilt fiber, which is sort of the, and by the way, fiber, telecom equipment, you know, so all the, all the networking gear, you know, and then, and then by the way, the actual physical data centers, like that was the beginning of the, of the, of the data center build and then, and the data center overbuild.And so you had that, but it was, it was literally, I think it was like $2 trillion got wiped out, right? It was like Jesus, it was like a big, it was. And by the way, the other, the other subtlety in it was the internet companies themselves never really had any debt. ‘cause tech, tech companies generally don't run on debt, but the telecom companies run on debt.Physical infrastructure companies run on debt. And so the companies like Global Crossing not just raise a lot of equity, they also raise a lot of debt. So they're highly levered. And so then you just do the thing. It's just like, okay, you have a highly levered thing where you're, you're just over, you're overbuilding capacity.Demand is growing, but not as fast as you hoped. And then boom, bankrupt. Right. And, and then it, and then it's like they say about the hotel industry, which is, it's always the third owner of a hotel that makes money. It has to go bankrupt twice, right? You have to wash out all of the over optimistic exuberance before it gets to actually a stable state.And then it makes money. So by the way, all of those data centers and all of those, all the fiber that they're in use, it's all in use today. Yeah. But 25 years later. But it, it, it took, and actually the elapsed time was, it took 15 years. It took 15 years from 2000 to 2015 to actually fill, fill up all that capacity.The cautionary warning is the, the overbuild can happen. Um, and, and, and, and, you know, you, you get into this thing where basically everybody, everybody who basically has any sort of institutional capital, it's like, wow. It's just, I, I don't know how to invest in these crazy software things. For sure I can put build data centers and for sure I can buy GPUs that I can deploy, you know, compute grids and, and all these things.Um, and so, you know, if you're a pessimist, you could look at this and you could say, wow, this is like really set up to be able to basically replicate, you know, what we went through, what we went through in 2000. Obviously that would be bad. The counter argument, which is the one I I agree with, which is the counter on, on the other side is a couple things.One is the companies that are investing all the, the companies that are investing the money are like the bluest chip of companies. And so back, back, back in the, in the do, like Global Crossing was like a, it was like an entrepreneur. It was like a, a new venture, but like the money that's being deployed now at scale is Microsoft, and, you know, and Amazon and Google, Facebook and Facebook and Nvidia and, you know, these, these, these, and, and now you know, by the way, open ai philanthropic, which are now at like, you know, really serious size, um, you know, as companies with, you know, very serious revenue.These are very large scale companies with like, lots, lots of cash, lots of debt capacity that they've, they've never used. And so th this is institutional in a way that, that really wasn't at the time. And then the other is, at least for now, every dollar that's being put into anything that results in a running GPU is being turned into revenue right away.Like so, and you guys know this, like everybody's starved for capacity, everybody's starved for compute capacity and then, you know, all the associated things, memory and, and, and interconnected and everything else. Um, data center space. And so e every dollar right now that's being put into the ground is turning into revenue.And, and it, and in fact, I actually think there's an interesting thing happening, which is because everybody starve for capacity, the models that we actually have that we can use today are inferior versions of what we would have if not for the supply constraints. That's true. Um, if Right pose a hypothetical universe in which GPUs were 10 times cheaper and 10 times more plentiful mm-hmm.The models would be much better. ‘cause you would just allocate a lot more money to training and you'd just build better models and they would be better. Um, and so we're, we're actually getting the sandbag version of the technology.swyx: Yeah. No. Everything we use is quantized because the, the labs have to keep the, the full versions,Marc: right?swyx: LikeMarc: we're not even getting the good stuff.swyx: Yeah.Marc: But, but getting the good stuff, it's, it's just, even if technical progress stops. Once there's like a much bigger build of like GPU manufacturing capacity and memory, you know, all, all the things that have to happen in the course of the next five or 10 years.Once it happens, even the current technology is gonna get, gonna get much better. And then as you know, like there's just like a million ways to use this stuff. Like there's just like a million use cases for this. Mm-hmm. Like, it, it, you know, this isn't just sending packets across a, a thing, whatever, and hoping that people find something to do with it.This is just like, oh, we apply intelligence into every domain of human activity. And then it works like incredibly well. Yeah. Um. Here's what I know, here's what I know. Um, in the next three or four year, it's like somewhere between three or four years out, basically everything is selling out. So like the, the entire supply chain is, is, is, is sold out or, or, or selling out.And so there, there's no, like, we're just gonna have like chronic supply shortage for, you know, for years to come. Um, there's going to be a response from the market that's gonna result in an enormous, you know, it's happening now. An enormous flood of investment in a new fab capacity and ev you know, every, everything else to be able to do that, at some point the supply chain constraints will unlock, you know, at least to some degree that will be another accelerant to industry growth when that happens.‘cause the products will get better and everything will get cheaper. Um, and so, so I know that's gonna happen. I know that, you know, the deployments, you know, the, the actual use cases are like really compelling. And then, like I said, you know, with reasoning and agents and so forth, like, I know they're just gonna get like much, much better from here.And so I, I, I know the capabilities are like really real and serious. I also know that the technical progress is not going to stop. It. It, it is excel. It is, is accelerating. Like the, the breakthroughs are are tremendous. I mean, even just month over month, the breakthroughs are really dramatic. And so, you know, I think if you were a cynic and there, there are cynics, you can look at 2000, you can find echoes.But I can't even imagine betting it that this is gonna like somehow disappoint and, you know, at least for years to come, I think it would be essentially suicidal to make that bet. Yeah. Um, it was that Michael Burry, uh, uh, that'sswyx: anMarc: interesting guy, huh? We'll pick on a guy. We'll pick, let's pick on one guy.We'll pick. Well ‘cause he did, he he came out with, it was, it was the, heswyx: doesn't mind.Marc: It was the Nvidia short. Right. He came with the Nvidia short. And then if you guys probably talked about this, which is the, the analysis now that like the current models are getting better faster at such a rate that if you are running an Nvidia, if you're running an Nvidia inference chip today, that's three years old, you're making more money on it today than you did three years ago because the pace of improvement of the software is, is faster than the, the, the depreciation cycle, the chip.And then my understanding is Google is running. I don't if they've, I don't know exactly what, uh, these are rumors that I've heard or maybe it's public, but, um, I think Google's running very old TPUs, very profitably. Ference. Yeah. And very profit and very profitably. Yeah. Um, and so, so it actually turns out, as far as I can tell, it's actually the opposite of the Beery thesis is actually.He was actually 180 degrees wrong. It's actually the, the, the, the old Nvidia chips are getting more valuable, which is something that's like literally never happened before. Like it's never been the case that you have an older model chip that becomes more valuable, not less valuable. And that, and again, that's an expression of the just ferocious pace of software progress.Ferocious pace of capability payoff. Yeah. Uh, that you're getting on the other side of this. And so I just, the idea of betting against that, like.swyx: Yeah. Yeah. Well, one ofMarc: my, it seems like an invitation to get your face ripped up.swyx: One of my early hits was like modeling the lifespan of the H 100 and h two hundreds and, and going like, you know, usually they advise like four to seven years and it was, you know, maybe you sort of realistically haircut cut it down to two to three.Yeah. But actually it's going up and not down. Yeah. And, and uh, that's, I mean that's, I think that's the dream. Uh, we are finding utilization and I think utilization solves all problems. Like, you can, you can find use, use cases for even like the poor, like even memory, we're having a shortage. Right. And, and even like the, the shittier versions of, of memory that we do have, we are finding use cases for it.So like That's great.Marc: Yeah.Alessio: How, how important is open source AI and kinda like edge inference in a world in which you have three years of supply crunch. Like, do you think in the, like, you know, if you fast forward like five years, like how do you think about inference, uh, in the data center versus at the edge?Marc: Well, so just to start, yeah. So I think, I think open source is very important for a bunch of reasons. I think edge, edge inference is very important for a bunch of reasons. I, I think just practically speaking, if we're just gonna have fundamental construc, supply crunches for the next, I mean, you, you guys know if you just project forward demand over the next three years, right?Yeah. Relative to supply, one of the, its main predictions you can do is what's gonna, what, what's gonna happen to the cost of, of inference in the core, uh, over the next three years? And like, it may rise dramatically, right? Like, so, so what is, and then is, is, you know, like the, the, the big model competition are subsidizing heavily right now.Right? Right. And so, so what's the, what will be the average person's, you know, per day, per month token cost, you know, three years from now to do all the things that they want to do. And I, I don't know, it's gonna. I mean, I have, you guys probably have friends, I have friends today who are paying a thousand dollars a day for open claw, for claw tokens to run open claw.Right? And so, okay. $30,000 a month. Right? And, and by the way, those, those friends have like a thousand more ideas of the things that they want their claw to do, right? Yeah. And so you, you could imagine there, there's like latent demand of up to, I don't know, five or $10,000 a day of, of, of tokens for a fully deployed, you know, per personal agent.Uh, and obviously consumers can't pay that, right? And so, so, but it gives you a sense of the fu of the fu of the future scope of demand, right? And so, so even, even if there's a 10 x improvement in price performance, that still, you know, goes to a hundred dollars a day, which is still way beyond what people can pay.Mm-hmm. So there's just gonna be like. Ferocious to me, by the way. The agent thing, the other interesting thing is I think the agent thing, so up until now, a lot of the constraints of GGPU constraints, I think the agent thing now also translates into CPU constraints. Mm-hmm. Right?swyx: CPU memory.Marc: Yes. CPU memory, right?And so, like the entire chip ecosystem is just gonna get wait,swyx: wait for network constraints, that that will be the killer.Marc: It's all bottleneck potentially for years. And so, so I, I think that Brad, and, and I think it's actually possible, I mean, generally inference costs are gonna keep coming down, but I think the, let's put it this way, the rate of decline, I think may level out here for a bit because of these supply constraints.And then at some point, maybe the lab stops subsidizing so much and that, that, that again, will be, be an issue. And so there's just gonna be so much more demand for inference than, than can be satisfied. Um, you know, kind of with the centralized model. And then, and then, you know, you guys know this, but like all the, just the dramatic, I mean just the dramatic innovations that have happened in the Apple silicon to be able to do, uh, inferences, it's quite amazing the level of effort being put.Like the open source guys are putting incredible effort into getting, you know, this recurring pattern where the big model will never run on a pc, and then six months later mm-hmm. Oh, it runs in a pc, right? It's like amazing. And there's very smart people working on that. So there's all that. And then look, there's also, you know.There's also like other, there's other motivators. There's other motivators which is just like, okay, how much trust are the big centralized model providers? You know, how much trust are they building in the market versus, you know, how much are, you know, at least for, in certain cases with some people, for certain use cases, people being like, well, I'm not willing to just like, turn everything over.So there, there, there's all the trust issues. Um, by the way, there's also just like straight up price optimization. There's many uses of AI where you don't need Einstein in the cloud. You just need like a, a a, a smart local model. There's also performance issues where you want, you know, you want, you know, you're gonna want your doorknob to have an AI model in it.Right. You know, to be able to, you know, do, um, you know, to be able to do access control. Um, obviously like everything with a chip is gonna have an AI model in it. Mm-hmm. And it, a lot of those are gonna be local. Um, and so, yeah. No, like I think, I think you're gonna have ti and then you're gonna, by the way, also wearable devices, you know, you don't wanna do a complete round trip.You want, you know, you, whatever your smart devices are, you want it to be like super low latency. Yeah.swyx: The question, do we care who makes it? Yeah. One of the biggest news this week was the collapse of AI two, the Allen Institute. Mm-hmm. One of the actual American open source model labs. Yeah. Um, and, uh, I'm not that optimistic on, on American open source.Yeah. Like you, you guys invested in MIS trial and MIS trial's doing extremely well outside of China. That's about it.Marc: Yeah. We'll see. We'll see. I look, I, number one, I do think we care. Uh, I do think we, I do think we care who makes it. Um, I would say this, the, the, the, the previous presidential administration wanted to kill it in the us Oh yeah.They wanted to drown in the bathtub. Um, and so they wanted to kill it. So at least we have a government now that actually like, actually wants it wants it to happen. And youswyx: earned to councilMarc: and Yeah. And the new and the P pcast. Yeah. So the, the, you know, this admin for whatever other political issues people have, which are many, you know, this administration has, I think a very enlightened view and in particular an enlightened view on AI and in particular on open source ai.Uh, and so they're very supportive. Um, my read is the Chi. The Chinese have a very, the various Chinese companies have a very specific reason to do open source, which is, they, they, they don't fundamentally, they don't think they can sell commercial, uh, AI outside of China right now. And or at least specifically not, not in the US for a combination of reasons.And so they, they kind of view, I think, open source AI as a bit of a loss leader against basically domestic, uh, you know, paid, paid services. And then kind of an, you know, kind of an ancillary products. You know, they're, they're very excited about it, by the way. I think it's great. I think it's great that they're doing it.Um, you know, I think Deeps seek was like a gift to the world. Um, I think. The great thing about open source, open source, the, the, the impact of open source is felt two ways. One is you, you get the software for free, but the other is you get to learn how it works, right? And so like the paper, the paper, the paper and, and the code, right?And the code. And so, like, for example, I thought this was amazing. So open comes out with L one and it's an amazing technical breakthrough, and it's just like, absolutely fantastic. But of course they don't explain how it works in detail. And then of course they hide the, they hide the reasoning traces, right?And, and then, and then, and then everybody's like, okay, this is great, but like, who's gonna be able to replicate this? Are other people gonna be able to do this? You know, is their secret sauce in there? And then our one comes out and it's just like, there's the code and there's the paper, and now the whole world knows how to do it.And then, you know, three months later, every other AI model is, is adding reasoning. And so, so you get this kind of double, like even if the Chinese models themselves are not the models that get used, the education that's taken place to the rest of the world, the information diffusion, you know, is incredibly powerful.So that happens and then, I don't know. We'll, we'll see. You know, there are a bunch of American, you know, open source, you know, ai, uh, model companies. I mean, look, there's gonna be tremendous, you know, there already is. There's, you know, there's gonna be tre there's tremendous competition, uh, among the primary model companies.You know, there's, depending on how you count, there's like four or five, you know, big co model companies now that are, you know, kind of neck and neck, uh, in different ways. Um, uh, you know, and, and, and, um, you know, and then obviously Bo Bo both X and then MetAware involved are, you know, both have huge, you know, huge attempts to, you know, kind of, to kind of leapfrog underway.And then you've got, you know, a whole fleet of startups, new companies, including a whole bunch that we're backing, that are, you know, trying to come out with different approaches. And then you've got whatever it is. I don't know how, how many, how many, like main line foundation model companies are there in China at this point?It's probably six. It'sswyx: five Tigers is what they call it. Yeah. Uh, Quinn is in questionable because there's change in leadership,Marc: right?swyx: Yeah.Marc: But that, does that include, that includes like Moonshot,swyx: yes. Can deep seek, uh, uh, ZI, um, Quinn oh one is in there.Marc: Right. And then, um, and by dance and, and then you see,swyx: ance would be like the next tier ance.They weren't as prominent. They weren't, didn't haveMarc: a leading. Yeah. But they, you at least, you know, ance is very inspiring and presumably they have more stuff coming and Tencent probably has more stuff coming and, and so forth. And so, so, so like, look, here, here would be a thing you can anticipate, which is there are not these markets, there are not going to be between the US and China right now, there's like a dozen primary foundation model companies that are like at scale, at, at some level of a critical mass.It's not gonna be a dozen in three years, right? Like, it just because these industries don't bear a dozen, it's, it's gonna be three or you know, there's gonna be three or four big winners or maybe one or two big winners. And so there's gonna be like a whole bunch of those guys that are gonna have to figure out alternate strategies.Um, and I think like open source is one of those strategies. And so I, I think you could see like a whole, i, I, I think the questions like, who's gonna do open source? I think that could change really fast. I, I think that, that, that's a very dynamic thing. I think it's very hard to predict what happens. And, and I think it's very important.swyx: NVIDIA's doing a lot.Marc: Well, I was gonna say. Well, exactly. And then you're got Nvidia and then, and then, you know, just to, again, indu, there's an old thing in business strategy, which is called, uh, commoditize Compliments. Commoditize the compliment. That's right. And so if your Jensen is just kind of obvious, of course, you wanna commoditize the software.Yeah. And he's, and to his enormous credit, he's putting enormous resources behind that. And so maybe it, maybe it's literally Nvidia and I think that would be great.Alessio: Yeah. Uh, narrative violation to European projects, uh, in the, uh, damn.swyx: I'm hosting my, uh, Europe, uh, conference soon. And I got both of them.Alessio: They got us.They got us. MarkMarc: finished. They got us, us. Well, wait a minute. Where was Peter? So where was Steinberger when he did? In AustriaAlessio: was, yeah, yeah, yeah.Marc: He was in what? He was in Vienna. Oh, he was in Vienna. And then where is he now?swyx: Uh, he's moving to sf.Marc: Okay. Okay. Alright. Okay, there we go. And then, yeah, the PI guy, right?The PI guys are European.swyx: Yeah, they're also, they're buddies inAlessio: Australia. Mario's also there. Yeah.Marc: Right. And are they, yeah, they haven't announced yet. Any sort of change changed or have theyAlessio: No, they're, they have a company there.Marc: Okay. Got, okay. Good.Alessio: Good, good,good.Alessio: Um,Marc: yeah, good.swyx: Anyways, I think pie and open cloud very important software things and, and I just wanted you to just go off on what you think.Marc: Yeah. So I think in co the, the combination of the two of them I think is one of the 10 most important softwares. Openswyx: Claw got all the attention, but Right. Talk about pie,Marc: pi pie's, kind of the Yeah. PI's, PI's kind of the architectural breakthrough for those of us who are older. There was this whole thing that was very important in the world of software basically from like 1970 to, I don't know, it still is very important, but like 19, from 1973 to like basically the creation of Linux, which is basically this, this thing used to call like the Unix mindset.Like so, so, ‘cause there were all these different, you know, theories. There are all these different operating systems and mainframes and, and then you know, all these windows and Mac and all these things. And then there was this, but kind of behind it all was this idea of kind of the Unix mindset. And the Unix mindset was this thing where basically you don't have these, like, like in the old days, like, like the operating system that like made the computer industry really work, like in the 1960s mm-hmm.Was this thing called o os 360, which was this big operating system that IBM developed that was supposed to basically run everything. And it was this like giant monolithic architecture in the sky. It was like a, you know, it was like a giant castle. Um, of software. And, and by the way, it worked really well and they were very successful with it.But like, it was this huge castle in the sky, but it was this thing, it was almost unapproachable, which is like, you had to be kind of inside IBM or very close to IBM. And you had to really understand every aspect, how the system worked. And then the, the Unix sky is originally out of at and t and then out out of Berkeley, um, you know, came out and they said, no, let's have a completely different architecture.And the way architecture's gonna work is we're gonna have, we're gonna have a, a prompt and, and a, and a shell. And then, and then we're gonna, all, all the functionality is gonna be in the form of these discreet modules, and then you're gonna be able to chain the modules together. Mm-hmm. Yeah. And so like the, the, the op, it's almost like the operating, operating system itself is gonna be a programming language.Um, and then that led led to the, the, the sort of centrality of the shell. Um, and then that led to sort of, uh, you know, basically chaining together Unix tools. And then that led to the emergence of these, these scripting languages like Pearl, where you, you could basically kind of very easily do this, and then the shells got more sophisticated and then, and then, and then look like, you know, that, that, that number one, that worked and that, that was the world I grew up in.Like I was, I was a Unix guy. You know, sort of from, call it 1988 to, you know, kind of all, all the way through my work and it worked really well. It, it's in the background, um, you know, nor normal people don't need to, didn't need to necessarily know about it, but like, if you were doing like system architecture, application development, you, you, you knew all about it.Um, and then, you know, it's been in the background ever since. And, you know, look, your Mac still has a Unix shell, you know, kind of in there, and your iPhone still has a Unix shell kind of buried in there somewhere. So they're kind of in there. And then, you know, the Windows shell is kind of a, you know, sort of a weird derivative of that.But, um, you know, but look, the inter, the internet runs on Unix, um, and that smartphones, actually, both iOS and Android are Unix derivatives. And so, you know, kind of Unix did end up winning. But, but anyway, and then we just started taking that for granted. And then, and then so, so basically the, the way I think about what happened with Pie and then with Open Claw is basically what those guys figured out is, I always say the, the great breakthroughs are obvious in retrospect, right?Which is the best kind, the best kind. They weren't obvious at the time or somebody else would've done them already. Um, and so there is a, like a real conceptual leap, but then you look at it sort of the backwards looking and you're just like, oh, of course. Mm-hmm. Like the, the, to me those are always the best breakthroughs.Well, actually language models themselves are like that. It's just like, oh, next token completion. Oh, of course.swyx: Yeah. What other objective mattered?Marc: Yeah, exactly. But, but like it, right. But she's even saying it wasn't obvious until somebody actually did it. Right. And so the conceptual breakthrough is real and deep and powerful and, and very important.And so the way I think about pie and olaw is it's basically marrying the, the language model mindset to the un to the Unix, basically shell prompt mindset. And so it's, it's basically this idea that what, what, so what is an agent, right? And as, as, and as you know, like many smart people who have been trying to figure out what an agent is for, for, for decades, and they've had many architectures to build agents and the whole thing.And it turns out what is an agent. So it turns out what we now know is an agent is the following. It's, so it's a language model. And then above that, it's a ba, it's a bash shell. Um, so it's a, it's a Unix shell, and then it's, and then the agent has access, uh, has access to, to the shell. And, you know, hopeful, hopefully in a sandbox, maybe in, maybe in a sandbox.So it's, it's the model. Um, it's the shell. Um, and then it's a fi, it's a file system. Um, and then the state is stored in files. And then, you know, there's the markdown format for the, you know, for, for the files themselves. And then, and then there's basically what in Unix is called Aron job. There's a loop and then there's a heartbeat for the, there's heartbeat and, and the thing basically Wake Wakes up.Wakes up. So it's basically LLM plus shell, plus file system, plus markdown, plus kron. And it turns out that's an agent. And, and, and every part of that, other than the model is something that we already completely know and understand. And in fact, it turns out that like the latent power of the Unix shell is like extraordinary because basically like all, like, there's just like an, there's just enormous latent power in the shell.There's enormous numbers of Unix commands, there's enormous number of command line interfaces into all kinds of things already in the, you know, your entire, I mean your entire, just to start with, your computer runs on a shell. If you're running a Mac or a, or, or a phone, your computer, your computer's running on a shell, uh, already.And so like the full power of your computer is available at the command line level. Um, and then it turns out it's really easy to expose other functions as a command line interface. And so like this whole idea where we need like MCP and these like product mm-hmm. Fancy protocols, whatever, it's like, no, we don't, we just need like a command, command line thing.So that's the architecture. And then it turns out what is your agent? Your agent has a bunch of files starting a file system. And then there's the thing that just like completely blew my mind when I write my head around it as a result of this, which is like, okay. This means your agent is now actually independent of the model that it's running on.Because you can actually swap out a different LLM underneath your agent and your, your agent will change personality somewhat. ‘cause the model is different, but all of the state stored in the files will be retained.swyx: Yeah. Different instruction set, but you just compiledit.Marc: Right, exactly. And it's all right.It's like right. Swapping out a ship and recompiling, but it's, it's still, it's still your agent with all of its memories. Um, and with all of its capabilities. And then by the way, you can also swap out the shell, uh, so you can move it to a different execution environment that is also, is also a b shell, by the way, you can also switch out the file system, right.Uh, and you can, and you can, and you can swap out the, the, the heartbeat for the, the crown framework, the, the loop that the agent framework itself. And so your agent basically is ba basically at the end of the day, it's just. It's just, its files. Um, and then, and then there's of course it a openswyx: call.Marc: Yeah, it's, it's basically, it's, it's just the files.Um, and then by the way, as a consequence of that, the agent and then the agent itself, it turns out a couple important things. So one is it, it's, it, it can migrate itself, right? And so you're, you can instruct your agent, migrate yourself to a different, uh, runtime environment, migrate yourself to a different file system, migrate yourself to a different, you know, swap out the language model.Your agent will do all that stuff for you. And then there's the final thing, which is just amazing, which is the agent is the agent actually has full introspection. It actually, it actually knows about its own files and it could rewrite its own files. Right. Which by the way, is basically no widely deployed software system in history where the, the, the thing that you're using actually has full introspective knowledge of how it itself works and is able to modify itself.Like that, that, I mean, there have been toy systems that have had that, but there, there's never been a widely deployed system that has that capability and then that leads you to the capability. That just like completely blew my mind when I wrap my head around it, which is you can tell the agent to add new functions and features to itself and it can do that.Extend yourself. Yeah. Right? Extend, extend yourself. Like extend yourself. Give yourself a new capability. Right? And so, and so literally it's just like you run into somebody at a party and they're like, oh, I have my open claw, do whatever, connect to my eat, sleep bed, and it gives me better advice and sleep.And you go home at night and you tell your claw, or if they're at the party, by the way, you tell your claw, oh, add this capability to yourself. And your claw will say, oh, okay, no problem. And it'll go out on the internet and it'll figure out whatever it needs and then it'll go out to claw code or whatever.It'll write whatever it needs. And then the next thing you know, it has this new capability. And so you don't even have to, like, you can have it upgrade itself without even having to, without having to do anything other than tell it that you want it to do that. And so anyway, so the, the combination of all this is just, I mean, this is just like a massive, incredible, I mean, it's just incredible.Like if I, if I were, if I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough. Yeah. And again, pe people are gonna look at it and they already get this response. People are gonna look at it and they're gonna say, oh, well, where's the breakthrough?‘cause these, the, all of these components were already known before. Mm-hmm. But, but this is the key, the key to the breakthrough was by using all these components that were known before, you get all of the underlying capability of that's buried in there. And so all, and so for example, computer use all of a sudden just kind of falls, trivi, trivial.Of course it's gonna be able to use your computer. It has full access to the shell. Right. And then, and then you just, you, you give it access to a browser, and then you've got the computer and the browser and, and often away it goes. And, and then you've got all the abilities of the browser also. Um, yeah.And so, and so the capability unlock here is profound. My friends who are, you know, deepest into this, are having their claw do like a, like, literally like a thousand things in their lives. They have new ideas every day. They're just like constantly throwing new challenges at the thing. And by the way, it's early and, you know, these are, you know, these are prototypes and there are, you know, as you guys know, there's security issues.Yeah. And, and so, you know, there's a bunch of stuff to be ironed out, but the, the unlock of capability is just incredible.swyx: Yeah.Marc: And I, I have absolutely no doubt that everybody in the world is gonna, is gonna have at least, you know, an agent like this, if not an entire family of agents. And w

Send us Fan MailWhen analyzing the Top 10 S&OP systems in 2026, it is important to recognize that most S&OP capabilities are not standalone applications but components of broader supply chain planning suites. These suites are particularly common in retail-centric environments, where high SKU counts, omnichannel fulfillment, franchise networks, and volatile demand require structured, macro-level planning coordination. However, the need extends beyond retail. Construction contractors with storefront footprints, franchise-heavy operating models, or expanding eCommerce channels also depend on S&OP frameworks to align demand forecasts, inventory positioning, and supply commitments. In many implementations, S&OP functions as a planning layer within a larger ecosystem that includes demand planning, supply planning, and network optimization. Architecturally, these solutions vary widely: some vendors deliver S&OP as a tightly integrated module inside ERP or supply chain suites, while others position it within analytics-driven “connected planning” platforms that unify finance, HR, and operational planning. Because these approaches differ significantly in scope, specialization, and integration depth, organizations must evaluate them through the lens of their planning maturity, data governance discipline, and enterprise architecture to determine which model will generate the most strategic value.In this episode, our host Sam Gupta discusses the top S&OP systems in 2026. He also discusses several variables that influence the rankings of these S&OP systems. Finally, he shares the pros and cons of each S&OP system.Video: https://www.youtube.com/watch?v=QA4gJulHt3kRead: https://www.elevatiq.com/post/top-sop-systems/Questions for Panelists?

We welcome back Chad Kenney, VP Product Management, to explore the new definition of "Enterprise-ready" in data infrastructure. We discuss how reliability and uptime are more critical than ever, with downtime costs frequently exceeding $300,000 per hour for a majority of companies according to a recent survey. Kenney notes that while hardware fails less often today, the major causes of downtime—namely security issues and human error—still persist, accounting for a large portion of outages. Our discussion pivots to how Everpure addresses this by simplifying architecture to reduce points of failure by using proprietary data devices instead of traditional SSDs. The new standard for enterprise readiness requires a system built on first principles with a software-centric view of resilience. We then explore how a key differentiator for modern enterprise-ready infrastructure is proactive support, which Everpure has always delivered through extensive telemetry and "fingerprints" that predict issues before they cause an outage. Our predictive technology is so effective that 70% to 75% of support calls are for problems that have not yet occurred. Architecturally, simplicity is critical, including the use of stateless controllers, which eliminates complex manual data management during upgrades, and limited error paths. Furthermore, our software-first mentality abstracts complexity, such as automatic management of RAID groups, to deliver autonomous systems. This frees storage administrators to become strategists and simultaneously reduces the potential for human error, enhancing overall system resiliency. We also dive into cyber resiliency, performance, and the future of data management driven by AI. Everpure builds layered cyber protection through capabilities like SafeMode, native encryption, and partner integrations. This approach prioritizes near-instantaneous recovery from local snapshots, which is faster than recovering from backups. Looking forward, Enterprise-ready means a unified platform (the Enterprise Data Cloud) where diverse workloads, including AI inference processing, can run simultaneously with consistency, enabling "data as a supply chain". This vision is achieved through the API-first and Fusion-enabled platform, ensuring that new feature functionality is immediately available for automation, all while maintaining the simplicity and continuous innovation provided by Evergreen. To learn more, visit: https://www.purestorage.com/platform.html Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts: https://purecommunity.purestorage.com/ 00:00 Intro and Welcome 02:15 Chadd's update on 2026 at Everpure 06:11 Stat of the Episode on Downtime 08:58 Proactive Support 12:32: Component Count Relative to Uptime 17:30: The Meaning Behind 6 9's 23:28 Designing for Cyber Resilience 26:35 Consistent Performance for Tier 1 Apps 29:55 API First and Fusion First

A nouveau-cream wave of ice cream debuts at Coachella, and everyone freaks out. Side Hustle School features a new episode EVERY DAY, featuring detailed case studies of people who earn extra money without quitting their job. This year, the show includes free guided lessons and listener Q&A several days each week. Show notes: SideHustleSchool.com Email: team@sidehustleschool.com Be on the show: SideHustleSchool.com/questions Connect on Instagram: @193countries Visit Chris's main site: ChrisGuillebeau.com Read A Year of Mental Health: yearofmentalhealth.com If you're enjoying the show, please pass it along! It's free and has been published every single day since January 1, 2017. We're also very grateful for your five-star ratings—it shows that people are listening and looking forward to new episodes.

This week on The Hamilton Review Podcast, we are excited to have Peter and Clara Hamilton on the show! In this episode, Peter and Clara are sharing all about the launch of their brand new company, Loam. Loam is architecturally inspired heirloom wood toy blocks, all natural and sustainably sourced and fully made in the USA. You will thoroughly enjoy Peter and Clara's personal story (from Peter's Architectural career, Clara's career in Educational Counseling and balancing their four children with very limited screen time) and how they created Loam. Loam is designed to nurture creativity, imagination,and mindfulness through open-ended, screen-free play. Loam is inspired by the timeless elegance of beautiful materials and craftsmanship. It's a generous gift that connects generations through design, imagination, and tactile joy. Enjoy this inspiring conversation and share it with your friends and family! Peter Hamilton, founder of Loam, was born and raised in Santa Monica, California, studied Creative Writing and Art at Pepperdine University, and has a Master's Degree in Architecture from the University of Oregon. Peter is a licensed architect, and he has owned his own architecture office, Studio Peter Hamilton, for eight years. In his free time, Peter enjoys studying art books, planting trees, and coaching his kids' baseball teams.   Clara Hamilton, wife of Peter and mother of their four children, is a full-time mother and home educator. Clara was raised in Culver City, California, studied Sports Medicine at Pepperdine University and has a Master's Degree in Educational Counseling, and before staying home to care for their children, she served twelve years as a high school teacher, counselor, and administrator in both public and independent schools. In her free time, Clara enjoys reading with her kids, sewing, or spending time outside with her family. How to contact Peter and Clara Hamilton:   Loam Blocks website   Loam Blocks on Instagram   Studio Peter Hamilton   How to contact Dr. Bob: Dr. Bob on YouTube: https://www.youtube.com/channel/UChztMVtPCLJkiXvv7H5tpDQ Dr. Bob on Instagram: https://www.instagram.com/drroberthamilton/ Dr. Bob on Facebook: https://www.facebook.com/bob.hamilton.1656 Dr. Bob's Seven Secrets Of The Newborn website: https://7secretsofthenewborn.com/ Dr. Bob's website: https://roberthamiltonmd.com/ Pacific Ocean Pediatrics: http://www.pacificoceanpediatrics.com/    

This is a free preview of a paid episode. To hear more, visit sub.thursdai.newsHola AI aficionados, it's yet another ThursdAI, and yet another week FULL of AI news, spanning Open Source LLMs, Multimodal video and audio creation and more! Shiptember as they call it does seem to deliver, and it was hard even for me to follow up on all the news, not to mention we had like 3-4 breaking news during the show today! This week was yet another Qwen-mas, with Alibaba absolutely dominating across open source, but also NVIDIA promising to invest up to $100 Billion into OpenAI. So let's dive right in! As a reminder, all the show notes are posted at the end of the article for your convenience. ThursdAI - Because weeks are getting denser, but we're still here, weekly, sending you the top AI content! Don't miss outTable of Contents* Open Source AI* Qwen3-VL Announcement (Qwen3-VL-235B-A22B-Thinking):* Qwen3-Omni-30B-A3B: end-to-end SOTA omni-modal AI unifying text, image, audio, and video* DeepSeek V3.1 Terminus: a surgical bugfix that matters for agents* Evals & Benchmarks: agents, deception, and code at scale* Big Companies, Bigger Bets!* OpenAI: ChatGPT Pulse: Proactive AI news cards for your day* XAI Grok 4 fast - 2M context, 40% fewer thinking tokens, shockingly cheap* Alibaba Qwen-Max and plans for scaling* This Week's Buzz: W&B Fully Connected is coming to London and Tokyo & Another hackathon in SF* Vision & Video: Wan 2.2 Animate, Kling 2.5, and Wan 4.5 preview* Moondream-3 Preview - Interview with co-founders Via & Jay* Wan open sourced Wan 2.2 Animate (aka “Wan Animate”): motion transfer and lip sync* Kling 2.5 Turbo: cinematic motion, cheaper and with audio* Wan 4.5 preview: native multimodality, 1080p 10s, and lip-synced speech* Voice & Audio* ThursdAI - Sep 25, 2025 - TL;DR & Show notesOpen Source AIThis was a Qwen-and-friends week. I joked on stream that I should just count how many times “Alibaba” appears in our show notes. It's a lot.Qwen3-VL Announcement (Qwen3-VL-235B-A22B-Thinking): (X, HF, Blog, Demo)Qwen 3 launched earlier as a text-only family; the vision-enabled variant just arrived, and it's not timid. The “thinking” version is effectively a reasoner with eyes, built on a 235B-parameter backbone with around 22B active (their mixture-of-experts trick). What jumped out is the breadth of evaluation coverage: MMU, video understanding (Video-MME, LVBench), 2D/3D grounding, doc VQA, chart/table reasoning—pages of it. They're showing wins against models like Gemini 2.5 Pro and GPT‑5 on some of those reports, and doc VQA is flirting with “nearly solved” territory in their numbers.Two caveats. First, whenever scores get that high on imperfect benchmarks, you should expect healthy skepticism; known label issues can inflate numbers. Second, the model is big. Incredible for server-side grounding and long-form reasoning with vision (they're talking about scaling context to 1M tokens for two-hour video and long PDFs), but not something you throw on a phone.Still, if your workload smells like “reasoning + grounding + long context,” Qwen 3 VL looks like one of the strongest open-weight choices right now.Qwen3-Omni-30B-A3B: end-to-end SOTA omni-modal AI unifying text, image, audio, and video (HF, GitHub, Qwen Chat, Demo, API)Omni is their end-to-end multimodal chat model that unites text, image, and audio—and crucially, it streams audio responses in real time while thinking separately in the background. Architecturally, it's a 30B MoE with around 3B active parameters at inference, which is the secret to why it feels snappy on consumer GPUs.In practice, that means you can talk to Omni, have it see what you see, and get sub-250 ms replies in nine speaker languages while it quietly plans. It claims to understand 119 languages. When I pushed it in multilingual conversational settings it still code-switched unexpectedly (Chinese suddenly appeared mid-flow), and it occasionally suffered the classic “stuck in thought” behavior we've been seeing in agentic voice modes across labs. But the responsiveness is real, and the footprint is exciting for local speech streaming scenarios. I wouldn't replace a top-tier text reasoner with this for hard problems, yet being able to keep speech native is a real UX upgrade.Qwen Image Edit, Qwen TTS Flash, and Qwen‑GuardQwen's image stack got a handy upgrade with multi-image reference editing for more consistent edits across shots—useful for brand assets and style-tight workflows. TTS Flash (API-only for now) is their fast speech synth line, and Q‑Guard is a new safety/moderation model from the same team. It's notable because Qwen hasn't really played in the moderation-model space before; historically Meta's Llama Guard led that conversation.DeepSeek V3.1 Terminus: a surgical bugfix that matters for agents (X, HF)DeepSeek whale resurfaced to push a small 0.1 update to V3.1 that reads like a “quality and stability” release—but those matter if you're building on top. It fixes a code-switching bug (the “sudden Chinese” syndrome you'll also see in some Qwen variants), improves tool-use and browser execution, and—importantly—makes agentic flows less likely to overthink and stall. On the numbers, Humanities Last Exam jumped from 15 to 21.7, while LiveCodeBench dipped slightly. That's the story here: they traded a few raw points on coding for more stable, less dithery behavior in end-to-end tasks. If you've invested in their tool harness, this may be a net win.Liquid Nanos: small models that extract like they're big (X, HF)Liquid Foundation Models released “Liquid Nanos,” a set of open models from roughly 350M to 2.6B parameters, including “extract” variants that pull structure (JSON/XML/YAML) from messy documents. The pitch is cost-efficiency with surprisingly competitive performance on information extraction tasks versus models 10× their size. If you're doing at-scale doc ingestion on CPUs or small GPUs, these look worth a try.Tiny IBM OCR model that blew up the charts (HF)We also saw a tiny IBM model (about 250M parameters) for image-to-text document parsing trending on Hugging Face. Run in 8-bit, it squeezes into roughly 250 MB, which means Raspberry Pi and “toaster” deployments suddenly get decent OCR/transcription against scanned docs. It's the kind of tiny-but-useful release that tends to quietly power entire products.Meta's 32B Code World Model (CWM) released for agentic code reasoning (X, HF)Nisten got really excited about this one, and once he explained it, I understood why. Meta released a 32B code world model that doesn't just generate code - it understands code the way a compiler does. It's thinking about state, types, and the actual execution context of your entire codebase.This isn't just another coding model - it's a fundamentally different approach that could change how all future coding models are built. Instead of treating code as fancy text completion, it's actually modeling the program from the ground up. If this works out, expect everyone to copy this approach.Quick note, this one was released with a research license only! Evals & Benchmarks: agents, deception, and code at scaleA big theme this week was “move beyond single-turn Q&A and test how these things behave in the wild.” with a bunch of new evals released. I wanted to cover them all in a separate segment. OpenAI's GDP Eval: “economically valuable tasks” as a bar (X, Blog)OpenAI introduced GDP Eval to measure model performance against real-world, economically valuable work. The design is closer to how I think about “AGI as useful work”: 44 occupations across nine sectors, with tasks judged against what an industry professional would produce.Two details stood out. First, OpenAI's own models didn't top the chart in their published screenshot—Anthropic's Claude Opus 4.1 led with roughly a 47.6% win rate against human professionals, while GPT‑5-high clocked in around 38%. Releasing a benchmark where you're not on top earns respect. Second, the tasks are legit. One example was a manufacturing engineer flow where the output required an overall design with an exploded view of components—the kind of deliverable a human would actually make.What I like here isn't the precise percent; it's the direction. If we anchor progress to tasks an economy cares about, we move past “trivia with citations” and toward “did this thing actually help do the work?”GAIA 2 (Meta Super Intelligence Labs + Hugging Face): agents that execute (X, HF)MSL and HF refreshed GAIA, the agent benchmark, with a thousand new human-authored scenarios that test execution, search, ambiguity handling, temporal reasoning, and adaptability—plus a smartphone-like execution environment. GPT‑5-high led across execution and search; Kimi's K2 was tops among open-weight entries. I like that GAIA 2 bakes in time and budget constraints and forces agents to chain steps, not just spew plans. We need more of these.Scale AI's “SWE-Bench Pro” for coding in the large (HF)Scale dropped a stronger coding benchmark focused on multi-file edits, 100+ line changes, and large dependency graphs. On the public set, GPT‑5 (not Codex) and Claude Opus 4.1 took the top two slots; on a commercial set, Opus edged ahead. The broader takeaway: the action has clearly moved to test-time compute, persistent memory, and program-synthesis outer loops to get through larger codebases with fewer invalid edits. This aligns with what we're seeing across ARC‑AGI and SWE‑bench Verified.The “Among Us” deception test (X)One more that's fun but not frivolous: a group benchmarked models on the social deception game Among Us. OpenAI's latest systems reportedly did the best job both lying convincingly and detecting others' lies. This line of work matters because social inference and adversarial reasoning show up in real agent deployments—security, procurement, negotiations, even internal assistant safety.Big Companies, Bigger Bets!Nvidia's $100B pledge to OpenAI for 10GW of computeLet's say that number again: one hundred billion dollars. Nvidia announced plans to invest up to $100B into OpenAI's infrastructure build-out, targeting roughly 10 gigawatts of compute and power. Jensen called it the biggest infrastructure project in history. Pair that with OpenAI's Stargate-related announcements—five new datacenters with Oracle and SoftBank and a flagship site in Abilene, Texas—and you get to wild territory fast.Internal notes circulating say OpenAI started the year around 230MW and could exit 2025 north of 2GW operational, while aiming at 20GW in the near term and a staggering 250GW by 2033. Even if those numbers shift, the directional picture is clear: the GPU supply and power curves are going vertical.Two reactions. First, yes, the “infinite money loop” memes wrote themselves—OpenAI spends on Nvidia GPUs, Nvidia invests in OpenAI, the market adds another $100B to Nvidia's cap for good measure. But second, the underlying demand is real. If we need 1–8 GPUs per “full-time agent” and there are 3+ billion working adults, we are orders of magnitude away from compute saturation. The power story is the real constraint—and that's now being tackled in parallel.OpenAI: ChatGPT Pulse: Proactive AI news cards for your day (X, OpenAI Blog)In a #BreakingNews segment, we got an update from OpenAI, that currently works only for Pro users but will come to everyone soon. Proactive AI, that learns from your chats, email and calendar and will show you a new “feed” of interesting things every morning based on your likes and feedback! Pulse marks OpenAI's first step toward an AI assistant that brings the right info before you ask, tuning itself with every thumbs-up, topic request, or app connection. I've tuned mine for today, we'll see what tomorrow brings! P.S - Huxe is a free app from the creators of NotebookLM (Ryza was on our podcast!) that does a similar thing, so if you don't have pro, check out Huxe, they just launched! XAI Grok 4 fast - 2M context, 40% fewer thinking tokens, shockingly cheap (X, Blog)xAI launched Grok‑4 Fast, and the name fits. Think “top-left” on the speed-to-cost chart: up to 2 million tokens of context, a reported 40% reduction in reasoning token usage, and a price tag that's roughly 1% of some frontier models on common workloads. On LiveCodeBench, Grok‑4 Fast even beat Grok‑4 itself. It's not the most capable brain on earth, but as a high-throughput assistant that can fan out web searches and stitch answers in something close to real time, it's compelling.Alibaba Qwen-Max and plans for scaling (X, Blog, API)Back in the Alibaba camp, they also released their flagship API model, Qwen 3 Max, and showed off their future roadmap. Qwen-max is over 1T parameters, MoE that gets 69.6 on Swe-bench verified and outperforms GPT-5 on LMArena! And their plan is simple: scale. They're planning to go from 1 million to 100 million token context windows and scale their models into the terabytes of parameters. It culminated in a hilarious moment on the show where we all put on sunglasses to salute a slide from their presentation that literally said, “Scaling is all you need.” AGI is coming, and it looks like Alibaba is one of the labs determined to scale their way there. Their release schedule lately (as documented by Swyx from Latent.space) is insane. This Week's Buzz: W&B Fully Connected is coming to London and Tokyo & Another hackathon in SFWeights & Biases (now part of the CoreWeave family) is bringing Fully Connected to London on Nov 4–5, with another event in Tokyo on Oct 31. If you're in Europe or Japan and want two days of dense talks and hands-on conversations with teams actually shipping agents, evals, and production ML, come hang out. Readers got a code on stream; if you need help getting a seat, ping me directly.Links: fullyconnected.comWe are also opening up registrations to our second WeaveHacks hackathon in SF, October 11-12, yours trully will be there, come hack with us on Self Improving agents! Register HEREVision & Video: Wan 2.2 Animate, Kling 2.5, and Wan 4.5 previewThis is the most exciting space in AI week-to-week for me right now. The progress is visible. Literally.Moondream-3 Preview - Interview with co-founders Via & JayWhile I've already reported on Moondream-3 in the last weeks newsletter, this week we got the pleasure of hosting Vik Korrapati and Jay Allen the co-founders of MoonDream to tell us all about it. Tune in for that conversation on the pod starting at 00:33:00Wan open sourced Wan 2.2 Animate (aka “Wan Animate”): motion transfer and lip sync Tongyi's Wan team shipped an open-source release that the community quickly dubbed “Wanimate.” It's a character-swap/motion transfer system: provide a single image for a character and a reference video (your own motion), and it maps your movement onto the character with surprisingly strong hair/cloth dynamics and lip sync. If you've used runway's Act One, you'll recognize the vibe—except this is open, and the fidelity is rising fast.The practical uses are broader than “make me a deepfake.” Think onboarding presenters with perfect backgrounds, branded avatars that reliably say what you need, or precise action blocking without guessing at how an AI will move your subject. You act it; it follows.Kling 2.5 Turbo: cinematic motion, cheaper and with audioKling quietly rolled out a 2.5 Turbo tier that's 30% cheaper and finally brings audio into the loop for more complete clips. Prompts adhere better, physics look more coherent (acrobatics stop breaking bones across frames), and the cinematic look has moved from “YouTube short” to “film-school final.” They seeded access to creators and re-shared the strongest results; the consistency is the headline. (Source X: @StevieMac03)I've chatted with my kiddos today over facetime, and they were building minecraft creepers. I took a screenshot, sent to Nano Banana to make their creepers into actual minecraft ones, and then with Kling, Animated the explosions for them. They LOVED it! Animations were clear, while VEO refused for me to even upload their images, Kling didn't care hahaWan 4.5 preview: native multimodality, 1080p 10s, and lip-synced speechWan also teased a 4.5 preview that unifies understanding and generation across text, image, video, and audio. The eye-catching bit: generate a 1080p, 10-second clip with synced speech from just a script. Or supply your own audio and have it lip-sync the shot. I ran my usual “interview a polar bear dressed like me” test and got one of the better results I've seen from any model. We're not at “dialogue scene” quality, but “talking character shot” is getting… good. The generation of audio (not only text + lipsync) is one of the best ones besides VEO, it's really great to see how strongly this improves, sad that this wasn't open sourced! And apparently it supports “draw text to animate” (Source: X) Voice & AudioSuno V5: we've entered the “I can't tell anymore” eraSuno calls V5 a redefinition of audio quality. I'll be honest, I'm at the edge of my subjective hearing on this. I've caught myself listening to Suno streams instead of Spotify and forgetting anything is synthetic. The vocals feel more human, the mixes cleaner, and the remastering path (including upgrading V4 tracks) is useful. The last 10% to “you fooled a producer” is going to be long, but the distance between V4 and V5 already makes me feel like I should re-cut our ThursdAI opener.MiMI Audio: a small omni-chat demo that hints at the floorWe tried a MiMI Audio demo live—a 7B-ish model with speech in/out. It was responsive but stumbled on singing and natural prosody. I'm leaving it in here because it's a good reminder that the open floor for “real-time voice” is rising quickly even for small models. And the moment you pipe a stronger text brain behind a capable, native speech front-end, the UX leap is immediate.Ok, another DENSE week that finishes up Shiptember, tons of open source, Qwen (Tongyi) shines, and video is getting so so good. This is all converging folks, and honestly, I'm just happy to be along for the ride! This week was also Rosh Hashanah, which is the Jewish new year, and I've shared on the pod that I've found my X post from 3 years ago, using the state of the art AI models of the time. WHAT A DIFFERENCE 3 years make, just take a look, I had to scale down the 4K one from this year just to fit into the pic! Shana Tova to everyone who's reading this, and we'll see you next week

The Government hopes to give a much-needed boost to the building and construction industry with the announcement of $413 million worth of accelerated school infrastructure projects. This follows a raft of school property announcements and the establishment of a new school property agency in July to oversee the planning, building, and maintenance of new school buildings. Hopefully, there will be some opposition input into this new agency, some opposition oversight. Because back in 2019, Jacinda Ardern and Chris Hipkins, surrounded by adoring children, announced funding of $1.2 billion over four years for school property – a new primary school, 200 new classrooms in Auckland amongst them. The new buildings would be needed for the estimated 100,000 extra students who will enter the school system over the next 10 years. So far, so good. At the time, Ms Ardern said there were too many kids getting taught in cold school halls and prefabs, and our plan, she said, will turn that around. It's important we plan ahead for growth, so parents can be confident they can send their child to their local school, and their local school will have enough warm, dry and modern classrooms to learn in, something the previous government failed to do. Then they were voted out in 2023 and in came National, and the next year the Education Ministry put hundreds of projects on hold. Now, why would they do that? Obviously, there are more young people who are going to need classrooms, schools are already overcrowded. There are children being taught in halls and prefabs that are less than ideal. Well, they did that because Labour had absolutely no concept of fiscal control. Their idea of building new classrooms was to go to a groovy young architect and say, "Come up with something fabulous," and they did. Groovy young architects have got amazing ideas and visions, and they can help children reach their full potential and development with the kind of environment that they can create with an unlimited chequebook. So, in came boring, grumpy old National. Hundreds of projects went on hold and $2 billion was saved, they say. The value for money review considered 352 projects at 305 schools with a combined estimated cost of $4.6 billion. It decided 110 projects would go ahead with changes such as removing non-essential aspects of the build or using off-the-shelf rather than bespoke design. If you are going to have an agency that's going to look ahead and plan and build and maintain school buildings, you've all got to be on the same page. Otherwise, what is the point? It makes sense to plan ahead for the future. It makes sense to build new schools where they're needed and to build new classrooms. But not if they're going to be, oh, I don't know, a vision came to me and I just drew something on paper and then it's like, you know, my ancestors are speaking to me and all of a sudden I've got this amazing creation for the cost of a billion dollars. If you could have three schools built for the same amount of money, then that's the way you go. We go for bespoke award-winning design buildings when we are an oil-rich nation who just doesn't know what to do with its money. What will we do? Oh, I know. We'll give gorgeous young architects, brilliant young things, the opportunity to use their talents and create amazing public buildings. This is a good thing if you can afford it, and we cannot. Do school buildings really need to be architecturally designed and award-winning buildings? I would argue right now they don't. They're beautiful and they're clever, but that level of expense is not necessary. It's the same with social housing. We all know Kāinga Ora was given a mandate under the last government to build houses at whatever cost, and away they went. Architecturally designed, beautifully appointed housing communities, which again is all very well and good if you can afford it. But the triumph of ideology over pragmatism saw Kāinga Ora completely blow its budget, leading to debt for generations of taxpayers to pay back. And again, housing projects were stalled while evaluations were made by those with fiscal discipline, who did the sums to see whether Kāinga Ora was giving value for the money spent. And again, this was necessary, but in the meantime, the construction industry who'd been working overtime, all of a sudden were told everything that they were working on or intended to be working on was on hold, while boring, sensible people did the sums. They had to down tools, and what do you do if there's no work? You go where the work is. They can't wait. It's a nightmare. Yes, we do need infrastructure built, but surely not award-winning designer infrastructure built at any cost. And what was the Infrastructure Commission doing while all this, ‘I have a vision' stuff was going on? The Infrastructure Commission, Te Waihanga, was created in 2018. So presumably they saw this vision for Kāinga Ora, they saw the vision for the schools. I mean, why weren't they saying, "Hang on a minute. For that amount of money, we could get three times the value. Put the brakes on. Taihoa. Let's look ahead for 20 years down the track and see what we can get for that money. It's our money that's being wasted and wasted, and it's not being spent wisely. We need schools, we need hospitals, we need roads. These are beyond party politics. The leaders of the parties need to knock their heads together and come up with a plan to give to us, to say, "This is how we'll be spending your money, wisely, prudently, and looking ahead to the years to come." The leaders of the parties need to get together and say to the construction industry, "We can guarantee there will be this work for the next 20 years because this is what we need. It's not that hard. This is what we need for the planned population growth. Here is where we'll be building it. These are the designs, and we've all got certainty for the next 20 years. How bloody hard can it be?" See omnystudio.com/listener for privacy information.

Last time we spoke about the invasion of iwo jima. General LeMay's B-29 bombers targeted Japan, inflicting heavy damage on Kobe and Ota's Nakajima factory, though at a cost of lost aircraft. Meanwhile, U.S. forces prepared for the Iwo Jima assault. On February 19, Marines landed amid intense bombardment, facing fierce Japanese resistance. Progress was slow, with heavy casualties. By February 21, they fought to capture Mount Suribachi. Amidst the chaos, kamikaze attacks struck American carriers, causing significant losses and foreshadowing the brutal battles ahead. In the midst of a relentless rain on February 22, Colonel Liversedge led the 28th Marines in a fierce assault on Mount Suribachi, facing determined Japanese resistance. Despite harsh conditions and significant casualties, the Marines pushed forward. On February 23, they reached the summit, raising the American flag to symbolize their hard-fought victory. The Secretary of the Navy, inspired by the moment, declared it would ensure the Marine Corps' legacy for centuries. As battles continued, the Marines faced heavy losses but remained resolute in their mission. This episode is the fall of Manila Welcome to the Pacific War Podcast Week by Week, I am your dutiful host Craig Watson. But, before we start I want to also remind you this podcast is only made possible through the efforts of Kings and Generals over at Youtube. Perhaps you want to learn more about world war two? Kings and Generals have an assortment of episodes on world war two and much more  so go give them a look over on Youtube. So please subscribe to Kings and Generals over at Youtube and to continue helping us produce this content please check out www.patreon.com/kingsandgenerals. If you are still hungry for some more history related content, over on my channel, the Pacific War Channel you can find a few videos all the way from the Opium Wars of the 1800's until the end of the Pacific War in 1945.  As we last observed in Manila, General Griswold's forces had effectively confined the remnants of Admiral Iwabuchi's troops to Intramuros, the South Port Area, and the Philippine Commonwealth Government buildings located at the southeastern edge of the Walled City. Available information led to the conclusion that the Japanese defenses were strongest on the southern and eastern sides of the Walled City and that the Japanese expected attack from these, the most logical directions. Japanese garrisons in the Legislative, Finance, and Agriculture Buildings just across Padre Burgos Street southeast of Intramuros could cover these approaches. The 37th Division could, of course, take the government buildings before launching an assault on Intramuros, but it would be easier to attack the government buildings after Intramuros fell. Conversely, planners deemed it feasible to strike into Intramuros from the west, since Japanese defenses along the west wall, across Bonifacio Street from the Manila Hotel and the South Port Area, appeared weak. But in this case, American troops would first have to clear the South Port Area and then, advancing from the west, would have to attack toward much of their own supporting artillery. The artillery's best positions for close support were on the north and northeast, across the Pasig, and on the east, in the area south from the General Post Office to the City Hall, and much of the artillery ultimately did fire from these areas. About halfway from the northeast to the northwest corner of Intramuros the ancient wall ended, providing direct access into the Walled City at the Government Mint. The only other obstacle on the north was a low sea wall running along the south bank of the Pasig, and Japanese defenses along the north face appeared weak except at the northeast corner. Planners therefore decided that there would be an excellent chance to execute a successful amphibious assault from the north bank of the Pasig against the north-central side of the Walled City.  Given that the Japanese defenses were strongest on the southern and eastern sides of the Walled City, and that the ancient wall ended at the Government Mint between the northeast and northwest corners of Intramuros, it was decided to initiate an amphibious attack from the north bank of the Pasig River targeting the north-central section of the Walled City, executed by the 129th Regiment with close artillery support. However, aware that the Japanese had established a complex tunnel system for rapid troop movement within Intramuros, General Beightler deemed it essential to conduct a secondary assault on Quezon Gate near the northeastern entrance to keep the Japanese forces off balance and to split their attention. Since the Japanese had fortified this area with strong pillboxes just inside the walls, the division concluded that heavy artillery would be required to create an additional breach in the thick wall just south of Quezon Gate, where the 145th Regiment would launch its attack. Furthermore, as the Japanese could target the advancing troops with enfilade fire from the three government buildings to the south, Allied artillery would need to neutralize these buildings during the assault on Intramuros. Lastly, the 1st Cavalry Brigade positioned to the west and southwest of Intramuros would block any potential escape routes for Japanese forces from the Walled City. So far, General MacArthur had severely restricted the employment of air in the metropolitan area. In late January and early February Marine Corps SBDs had bombed or strafed a few pinpointed targets in the North and South Port Areas and had also hit some obvious Japanese gun positions in the open areas of Luneta Park and Burnham Green. One or two strikes may also have taken place against specific targets within Intramuros, but all in all it appears that planes of the Allied Air Forces flew no more than ten or twelve individual sorties against targets within the city after February 3. Before that time both carrier-based and land-based aircraft had presumably limited their strikes to targets within the port areas and to oil storage facilities in Pandacan and Paco Districts. Of course some bombs had gone astray during these strikes and had caused damage within Intramuros, while additional damage within the Walled City had resulted from both American and Japanese artillery fire the first two weeks of the battle for Manila. When approached with General Griswold's plan to carry out an intensive aerial bombardment against the Walled City, MacArthur once again objected: “The use of air on a part of a city occupied by a friendly and allied population is unthinkable. The inaccuracy of this type of bombardment would result beyond question in the death of thousands of innocent civilians. It is not believed moreover that this would appreciably lower our own casualty rate although it would unquestionably hasten the conclusion of the operations. For these reasons I do not approve the use of air bombardment on the Intramuros district.” However, General MacArthur had previously issued orders limiting air operations in the metropolitan area, leading him to reject this proposal. Not wanting to rely solely on infantry for the assault, Griswold and Beightler decided to organize a significant artillery preparation, as they were not explicitly prohibited from using artillery. After several unsuccessful attempts to persuade the Japanese in Intramuros to surrender or release the numerous Filipino civilians they were holding hostage, Griswold initiated the bombardment of Intramuros on February 17, creating several breaches in the east wall. On February 22, Allied artillery began targeting the north wall to breach it and eliminate a Japanese stronghold at the Government Mint, while additional guns took up positions for the final barrage before the infantry assault the following morning. Between 07:30 and 08:30 on February 23, the Americans executed the last preparatory bombardment, effectively damaging the walls of Intramuros and covering much of the interior. Once the supporting fire ceased, the infantry assault commenced, with the 3rd Battalion, 129th Regiment swiftly crossing the Pasig River without opposition and advancing through the Government Mint into Intramuros. Simultaneously, the 2nd Battalion, 145th Regiment climbed over the breach south of Quezon Gate and entered through the gate unopposed, quickly moving southwest toward Letran University. Ten minutes into the assault, Griswold's artillery resumed fire for the next half hour, deploying high explosives, smoke, and white phosphorus across a 100-yard-wide area between the east and west walls. This aimed to seal off the southern third of Intramuros, preventing the Japanese forces there from observing movements to the north or sending reinforcements. The total artillery and mortar fire supporting the assault amounted to 230 tons, equivalent to over 11,650 rounds. By 08:50, the 129th and 145th Regiments connected at Letran University, with the 129th advancing toward Beaterio Street and Fort Santiago against minimal resistance, while the 145th cleared Letran University and secured the first two blocks southwest of Quezon Gate. At 10:45, the 1st Battalion of the 145th Regiment moved through Parian Gate and headed south. As American troops pushed deeper into Intramuros, the Japanese began to recover from the artillery bombardment, offering sporadic resistance from isolated machine-gun and rifle positions. Nonetheless, the 129th successfully cleared the west wall north of Beaterio Street and captured Fort Santiago in the afternoon. However, the 145th had to halt its advance about four blocks southwest of Quezon Gate as the Japanese started releasing nearly 3,000 civilian hostages from San Augustin and Del Monico Churches. Once the civilian evacuation was complete, American tanks and self-propelled artillery targeted Japanese positions within those churches and other strongholds in the southwestern section of Intramuros. Despite the efforts, the troops were unable to reach the south or west walls before nightfall due to fierce resistance. Meanwhile, the 1st Squadron, 12th Cavalry, along with the 2nd Squadron, 5th Cavalry, began clearing the South Port Area, facing relatively light opposition except at one strongpoint. Meanwhile, the 1st Squadron, 5th Cavalry, and elements of the 148th Regiment contained the enemy at the government buildings. On February 24, while the 129th was finishing operations at Fort Santiago, the 145th continued its offensive, successfully cornering the last pockets of resistance in its area into the Aquarium, situated in a bastion at the southwest corner of Intramuros. Although the resistance was fierce in this location, a tunnel linking the bastion to the main wall was unexpectedly left unguarded, allowing Company C to break through into the Aquarium with ease. The final assault commenced in the afternoon, resulting in 115 Japanese casualties as the last organized resistance within Intramuros was overcome. In total, approximately 1,000 Japanese were killed, and 25 were captured during the assault on Intramuros, with the Americans suffering 25 killed and 265 wounded. Concurrently, the cavalrymen completed the clearing of the South Port Area and turned their attention to the government buildings, which would necessitate another intensive preparatory bombardment.  The imposing, columned façade of the Philippine Commonwealth's Legislative Building--the Philippine Capitol--fronted on Padre Burgos Street opposite the southeast corner of Intramuros and lay 150 yards south of the City Hall. About 100 yards south of the Legislative Building was the Bureau of Finance, and another 250 yards to the south-southeast, near the intersection of General Luna and San Luis Streets, lay the main building of the Bureau of Agriculture and Commerce. Architecturally similar to the old Senate and House Office Buildings in Washington DC, the three government structures were modern, earthquake-proof edifices constructed of heavily reinforced concrete. The oblong Legislative Building, with wings four stories high and a central portion rising another two and a half floors, was constructed around two open courtyards. The Finance and Agriculture Buildings, both five-story trapezoids, each featured a central courtyard. The buildings were strong not only by virtue of their construction but because all approaches to them led across wide open ground. Sandbag emplacements and barricades of other types blocked all readily accessible doors and windows, and window-emplaced machine guns covered all approaches. Despite the fact that the Japanese in the three buildings had advantages of position and elevation that permitted them to endanger American and Filipino movements over large areas of Manila, the 14th Corps and the 37th Division at first considered starving the Japanese garrison out. But the two headquarters soon decided this would take too long. Information from prisoners and Filipino hostages who had escaped from the buildings indicated that the Japanese garrisons in the three structures had sufficient strength, ammunition, food, and water to withstand a protracted siege. On February 26, after an hour of final artillery preparation, the 1st Battalion, 148th Regiment entered the ground floor of the Legislative Building from the rear, while the 5th Cavalry attacked the Agriculture Building; however, both units were successfully repelled by the determined defenders. The following day, after a failed attempt to smoke the Japanese out of the Legislative Building, heavy artillery was used to demolish the north and south wings, leaving only the damaged central section, which was subsequently cleared by the infantry. At the same time, the 5th Cavalry cleared out the apartment building and several nearby structures in preparation for another attack on the Agriculture Building, which commenced on February 28 following a three-hour artillery bombardment that caused significant portions of the building to collapse. Facing no initial resistance, the cavalrymen quickly accessed the remnants of the first floor but soon encountered strong opposition from pockets of resistance at the northwest and southeast corners. With support from tanks and armed with small arms, bazookas, and portable flamethrowers, the 5th Cavalry managed to clear the above-ground debris by nightfall, although a few Japanese soldiers remained hidden in basement areas. Ultimately, on March 1, after a failed appeal for surrender, demolitions along with burning gasoline and oil eliminated the last of the Japanese resistance. During this time, artillery, tanks, and tank destroyers relentlessly bombarded the Finance Building from various angles. Eventually, the 1st Battalion of the 148th Regiment would clear the remnants of this building during their final assaults on March 2 and 3. Late on March 3, Griswold joyfully informed Krueger that organized resistance in the Manila area had come to an end. The cost of reclaiming Manila was significant, with over 1,000 Americans killed and 5,500 wounded in the metropolitan area between February 3 and March 3. In contrast, the Japanese suffered approximately 16,000 fatalities in and around Manila. During periods of calm in the fighting, Japanese troops often vented their anger and frustration on the city's civilians, committing acts of violent mutilation, rape, and massacres in schools, hospitals, and convents. This led to the deaths of at least 100,000 Filipino civilians, both from deliberate actions by the Japanese during the Manila massacre and from artillery and aerial bombardments by American and Japanese forces. If you listened to the very first episode of this podcast series, I actually began it with what is known as the Manila massacre. During lulls in the battle for control of Manila, Japanese troops took their anger and frustration out on the civilians in the city. Violent mutilations, rapes, and massacres occurred in schools, hospitals and convents, including San Juan de Dios Hospital, Santa Rosa College, Santo Domingo Church, Manila Cathedral, Paco Church, St. Paul's Convent, and St. Vincent de Paul Church. The Bayview Hotel was used as a designated "rape center". General Yamashita was convicted as a war criminal for the Manila massacre, although Admiral Iwabuchi's marines had committed the atrocities and Yamashita had earlier ordered him to evacuate Manila.  By the end of the Battle of Manila, the public transportation system no longer existed; the water supply and sewage systems needed extensive repairs; the electric power facilities did not function; most of the streets needed repaving; and 39 out of 100 or more large and small bridges had been destroyed, including the 6 over the Pasig River. The University of the Philippines and the Philippine General Hospital were largely irreparable. Lower class residential districts north of the Pasig and upper class apartments south of the river had been destroyed; the Philippine Commonwealth's government's center had been wiped out; the 400-year-old landmark of Intramuros had been nearly razed; severe damage had been inflicted on the economically important installations in the North and South Port Areas; and the industrialized Paco and Pandacan Districts had been badly battered. Many buildings still standing would ultimately have to be torn down as unsafe for occupancy. Millions upon millions of dollars' worth of damage had been done and, as a final shocking note of tragedy, an estimated 100000 Filipino civilians had lost their lives during the battle. However, Manila was officially liberated, marking the end of nearly three years of Japanese military occupation in the Philippines. Following Manila's fall, Krueger aimed to eliminate the Shimbu and Shobu Groups to finalize the liberation of Luzon. Meanwhile, MacArthur deemed it crucial to establish a safe, direct shipping route through the central Philippines to support the creation of large air, naval, and logistical bases on Luzon. Consequently, he instructed the 6th Army to secure southern Luzon and the Bicol Peninsula while also ordering General Eichelberger's 8th Army to seize the islands in the Visayan Passages and the northern part of Samar. To facilitate the southern Philippines Campaign, MacArthur reassigned the 40th and 41st Divisions, the 19th and 34th Regiments of the 24th Division, and the 503rd Parachute Regiment back to the 8th Army. Additionally, he designated the 37th Division to garrison Manila. With the 43rd Division sent south to replace the 40th at Clark Field, Krueger assigned the recently arrived 33rd Division, led by Major-General Percy Clarkson, to take control of the Damortis-Rosario sector. Meanwhile, as the 188th Glider Regiment cleared Ternate Island, Krueger also decided to deploy the 11th Airborne Division and the 158th Regiment to secure the northern shores of the Visayan Passages and open Batangas and Balayan Bays. However, this left only the 1st Cavalry Division and the 112th Cavalry Regiment available for operations against the Shimbu Group, leading Krueger to reluctantly redeploy the 6th Division south to reinforce the 14th Corps, leaving just the 25th, 32nd, and 33rd Divisions under the 1st Corps for operations in northern Luzon. After making these adjustments, Krueger and Griswold began strategizing their offensive eastward against General Yokoyama's Shimbu Group, which had recently received the Noguchi Detachment from the Bicol Peninsula. To ensure the security and recovery of the Manila Bay area, General Patrick's 6th Division was tasked with first capturing Wawa Dam and its pipeline connections, followed by securing Ipo Dam and its related facilities, essential for meeting Manila's water needs. Meanwhile, General Hoffman's 2nd Cavalry Brigade was assigned to secure the Antipolo-Tagig region. Between February 20 and 22, even before the fierce fighting in Manila began to ease, the 7th Cavalry crossed the Marikina River to take control of Taytay and then ventured into the Sierra Madre foothills. The 8th Cavalry followed suit, crossing the river to secure Tagig. On February 23, the 2nd Cavalry Brigade advanced east toward Antipolo, but General Noguchi effectively utilized artillery and conducted small-scale nightly infiltration attacks, successfully harassing and delaying the cavalrymen, who could only measure their progress in feet. Noguchi's effective passive defense meant that by March 4, the 2nd Cavalry Brigade was still a mile and a half from Antipolo, having incurred heavy casualties during this frustrating advance. Among the wounded was General Mudge, who was temporarily replaced by Hoffman as commander of the 1st Cavalry Division. On February 22, the 6th Division also began crossing the Marikina River, with the 20th Regiment fording at Marikina town and the 63rd Regiment crossing at Montalban and San Mateo. Facing no resistance, the 20th Regiment advanced a mile into the steep, grassy hills northeast of Marikina, while the 63rd probed into the high ground east of San Mateo by the evening of February 23. The troops initiated an assault on General Kobayashi's primary defenses at Mounts Pacawagan and Mataba, but made minimal progress before the 1st Regiment arrived from Bataan on February 25. With this new reinforcement, Patrick launched a coordinated attack involving three regiments against Pacawagan and Mataba. However, by March 4, they had only secured a tenuous foothold on the northern crest of Pacawagan, as the efforts of the 1st and 20th Regiments were entirely unsuccessful.   Meanwhile, noticing an uptick in guerrilla activity in the Bontoc and Baguio areas, which indicated a potential major enemy offensive on Baguio, and considering the possibility of an airborne assault in the Cagayan Valley, General Yamashita began reorganizing his forces while preparing the defenses of the triangular redoubt in northern Luzon. He kept most of the 103rd Division stationed in the Aparri and Vigan sectors, assigned the 177th Independent Battalion to secure the naval air base at Tuguegarao, and started organizing eight provisional companies from the remnants of the 2nd Parachute Group at Echague. He tasked the 10th Division with defending the Salacsac-Balete Pass sector to the last man, gathered the remnants of the 2nd Tank Division at Dupax to reform as an understrength infantry division, and relocated the 105th Division to Bagabag, where it would be bolstered by the 10th Regiment. Additionally, he assigned these three divisions to Major-General Konuma Haruo's self-sufficient Bambang Branch, transferred the 19th Division to the Bontoc area to combat the enemy guerrillas, tasked the Hayashi Detachment with holding San Fernando, began moving the worn-out 58th Independent Mixed Brigade north to defend Route 9, and ordered the fatigued 23rd Division to continue containing the enemy in the Rosario-Baguio sector. General Swift's 1st Corps, which had recently lost two divisions, was focusing its main efforts against Baguio. Clarkson's 33rd Division was set to advance north along Route 11, while General Gill's 32nd Division would move northwest through the Ambayabang, Agno, and Arodogat valleys from the south and southeast. Meanwhile, General Mullins' 25th Division planned to launch a holding attack on the Bambang front. However, in mid-February, as Clarkson's forces continued to pressure Japanese troops entrenched along the Hill 600-Hill 1500 ridgeline, they learned that General Sato's withdrawal to the north was already in progress to bolster the San Fernando front. Additionally, the 130th and 136th Regiments successfully cleared the last Japanese forces from the north-central part of the ridgeline by February 22, although they were unable to capture the Hill 600 complex. At the same time, the 32nd and 25th Divisions conducted extensive patrols in their areas, discovering that the Japanese were guarding every approach to the north as various units made contact with Japanese outposts. During this period, the Americans also identified the Baguio-Aritao supply road. Severing this link in the Japanese defensive network would provide the 1st Corps with a significant tactical advantage. Given that the Baguio end of the supply road was more heavily defended and that breaking through to Aritao would threaten the critical Bambang and Bagabag positions, Krueger and Swift decided that the 25th and 32nd Divisions would concentrate their efforts on the Bambang front, while the Baguio front would be maintained in a holding capacity. Volckmann's missions as assigned by 6th Army, which assumed control of USAFIP(NL) on January 13, were to gather intelligence, ambush Japanese patrols, seize or destroy Japanese supplies, disrupt Japanese lines of communication, and block Japanese routes of withdrawal into and exit from the Cagayan Valley. It was not, apparently, initially intended that Volckmann's force would engage in sustained efforts against major Japanese units, and there seems to have been little hope that Volckmann's, or any other guerrilla unit, would ever become effective combat organizations. The most help General MacArthur and Krueger probably expected was in the form of harassing raids, sabotage, and intelligence. But Volckmann--and other guerrilla leaders on Luzon as well--interpreted his missions as broadly as his strength and armament permitted. By the end of February USAFIP(NL) had cleared much of the west coast of Luzon north of San Fernando and also controlled the north coast west of Aparri. Volckmann had rendered Route 11 between Baguio and Tuguegarao and Route 4 from Libtong to Bagabag virtually impassable to the Japanese. Indeed, one of the main reasons that Yamashita moved the 19th Division north had been to regain control over the two vital highways so that supplies could continue moving into the final redoubt. While USAFIP(NL) did not possess sufficient strength to attack major Japanese concentrations or to hold out against large-scale punitive expeditions, it had diverted and pinned down Japanese forces that could undoubtedly have been used to better advantage elsewhere. It would appear that by mid-February USAFIP(NL) had accomplished far more than MacArthur or Krueger had either expected or hoped. Meanwhile, the 121st Regiment secured the highway from Vigan south to Libtong, with Company L capturing Cervantes and pushing the 357th Independent Battalion into the Bessang Pass. Elements of the 121st then shifted their focus to San Fernando, which they attempted to attack unsuccessfully in late February and early March. Following Swift's new strategies, the 33rd Division began patrolling the approaches to Baguio in the last week of February, successfully overrunning the last Japanese positions on Hill 600 and in the Arodogat Valley. Along Route 11, the 71st Regiment executed a successful fighting withdrawal, while American patrols along the coast occupied Agoo and advanced to Pugo with minimal resistance, only to encounter the first sections of the Tuba Trail defended by elements of the 64th Regiment. On the main front, the 25th Division commenced its advance to Puncan on February 21, while the 32nd Division began its push up the Villa Verde Trail toward Santa Fe. The 127th Regiment broke through the trail's outpost line on February 24; the 35th Regiment advanced unopposed along Route 100, reaching Carranglan on February 26; the 161st Regiment targeted high ground overlooking Puncan from the west and successfully secured the trail junction on February 28, diverting the enemy's attention; and the 27th Regiment pushed north along Route 5, facing fierce resistance while clearing the Lumboy area on February 27. On Villa Verde, the 127th Regiment advanced to the Cabalisiaan River crossing by March 1, where they once again defeated the 10th Reconnaissance Regiment. After leaving one battalion to secure the crossing, the 127th continued their advance and encountered the weakened Japanese defenders on March 3. Recognizing the threat to the Salacsac Pass, Konuma promptly sent reinforcements to the 10th Reconnaissance Regiment and ordered General Iwanaka's recently reorganized 2nd Tank Division to prepare for deployment to the Salacsac Pass, taking command of all troops along the Villa Verde Trail. While these reinforcements were en route, the 127th Regiment continued to assault the remaining positions of the 10th Reconnaissance Regiment, ultimately reaching the western entrance of Salacsac Pass on March 5. Meanwhile, to the south, a battalion from the 35th Regiment descended a rugged trail into Puncan from the northeast and secured the heights overlooking the damaged town on March 1. The next day, as patrols entered the deserted Puncan, the rest of the regiment cautiously advanced west along Route 100 from Carranglan, occupying Digdig without resistance on March 3. Over the following two days, organized resistance began to crumble throughout the Lumboy-Puncan area, with Mullins' three regiments successfully connecting at Puncan and Digdig after the encirclement of a 1,250-man enemy force. Concerned about these developments, Konuma quickly decided to bolster the 10th Division with the Takachiho Unit and the majority of the 10th Regiment. Additionally, the 2nd Battalion of the 126th Regiment began its advance up the Ambayabang Valley on February 25, successfully reaching Lawican by March 5. In response to this new threat, Yamashita swiftly directed his reserve 16th Reconnaissance Regiment to secure the upper reaches of the Ambayabang. Finally, to the south, the Americal and 24th Divisions were tasked with initiating operations to secure the Visayan Passages. Consequently, on February 19, the 1st Battalion of the 182nd Regiment landed on Capul Island and launched an assault on Biri Island the next day. After discovering other unoccupied islets near Samar, the battalion established a base at the northwestern tip of Samar, ultimately defeating the last organized resistance in that region by March 1. Meanwhile, elements of the 19th Regiment landed on Verde Island on February 23, managing to secure the island by March 3. The 1st Battalion of the 21st Regiment made an unopposed landing on Lubang Island on February 28, and the 1st Battalion of the 132nd Regiment successfully captured Ticao and Burias Islands on March 3. Additionally, on the morning of February 23, a task force comprising the 1st Battalion of the 188th Glider Regiment, the 1st Battalion of the 511th Parachute Regiment, a Provisional Reconnaissance Platoon from the 11th Airborne Division, several guerrilla groups led by Lieutenant-Colonel Honorio Guerrero, along with supporting artillery, tank destroyers, and amphibious tractors, executed a carefully coordinated rescue of 2,147 internees from an internment camp near Los Baños on Laguna de Bay. The 1st Battalion of the 188th Glider Regiment, commanded by Lieutenant-Colonel Robert Soule, launched a diversionary ground attack from the west, while the majority of the 1st Battalion of the 511th Parachute Regiment crossed Laguna de Bay using amphibious tractors. Company B of the 511th Parachute Regiment parachuted directly into the camp, and the Reconnaissance Platoon along with the guerrillas, who had already infiltrated the area, created chaos throughout the camp. The task force eliminated the Japanese garrison of about 250 guards and managed to escape through enemy-held territory before the Fuji Force could mount a counterattack. The casualties were minimal: only 3 Americans and 2 Filipinos lost their lives, while 2 Americans and 4 Filipinos were injured. However, starting two nights after the raid, the 17th Regiment, along with Kempeitai police and Filipino Ganaps, began terror raids in the surrounding barrios, resulting in the deaths of up to 1,500 Filipino civilians over the next few nights. It was now time to leave the Philippines and return to New Guinea to support the ongoing Australian campaign in Aitape-Wewak. Previously, Brigadier Martin's 19th Brigade had fought its way to Malin and Abau, while Colonel Buttrose's 2/5th Battalion secured Perembil, Asiling, Samisai, and Maharingi. On January 12, Brigadier Moten directed the battalion to initiate a three-pronged offensive toward Luwaite, Bulamita, and Bombisima. The advance was rapid, as patrols encountered only small enemy groups, and all three objectives were successfully captured by the end of January. After the capture of Malin, the 2/8th Battalion and the 2/9th Commando Squadron patrolled the rugged terrain between Nimbum Creek and the upper Danmap for three weeks, facing some resistance on Long Ridge. Due to this pressure, General Aotsu's force received additional reinforcements in the latter half of January before withdrawing to join the defenses of the 20th Division, while General Mano's 41st Division retreated to Balif and Salata. Meanwhile, General Stevens had ordered Brigadier Roy King's 16th Brigade to relieve the 19th at the Danmap, but catastrophic floods hindered the completion of this relief in the south before the month ended. In the north, the 2/1st Battalion took over from the 2/11th Battalion on January 24 and began advancing patrols along Nambut Hill, where they faced significant resistance. Due to these patrols, the Australians launched a company attack on February 4, which the defenders easily repelled. Following a heavy air bombardment, the enemy stronghold was captured on February 7, and another company took McNeil's Creek four days later. Meanwhile, the 2/3rd Battalion initiated an assault on Long Ridge, inflicting considerable casualties on the enemy at Cory's Spur. At this juncture, Stevens decided to sequentially capture But, Dagua, and Wewak, as well as Maprik in the mountains, and to push eastward. The 16th Brigade was the first to advance to Wank Creek and then to the Anumb River. King promptly sent the 2/1st Battalion to secure Nambut Creek while the 2/3rd Battalion moved to the Wolhuk Creek-Una Creek line. By February 18, the 2/1st Battalion had fully secured Nambut Hill, with one company advancing along the coast and pushing the Japanese across the creek the next day. By February 22, the area up to Balam Creek was occupied, and barges had delivered supplies at Wank Creek for four days. The following day, they reached the Anumb River and began patrolling toward Sowom while a sloop bombarded enemy positions along the coast. Finally, on February 28, the 2/2nd Battalion relieved the weary 2/1st Battalion and started preparing for operations against But. Simultaneously, the 2/3rd Battalion successfully established the Wolhuk Creek-Una Creek line and sent patrols northward to connect with both the 2/1st and 2/2nd Battalions. In early February, the 2/5th Battalion launched an attack on Salata, Balif, and Balaga, sending three companies southward. Salata and Bombeta were captured on February 3, followed by Balif three days later, while Balaga remained successfully defended. The 2/6th Cavalry Commando Regiment was tasked with supporting Moten's advance toward Maprik, prompting the 2/10th Commando Squadron to move to Ami. After the Australians secured the Balaga-Numango area on February 13, Buttrose dispatched two companies to capture Barangabandangi and Malahun, which fell by February 17. At this time, the 2/10th Commando Squadron had also advanced northeast of Ami to Walahuta, Kualigem, and Amahaur, resulting in several Japanese casualties. Meanwhile, the 2/7th Commando Squadron conducted patrols deep into the Atob River and the headwaters of the Screw River. The 2/5th Battalion was preparing for relief by the 2/7th Battalion but first needed to fend off a strong counterattack at Malahun on February 23. During the 2/5th's advance, most of the 40th Division withdrew south into a densely populated garden area bordered by the Nanu and Amuk Rivers. This southern flank could not be overlooked as the Australians moved toward Maprik, so Moten sent a company from the 2/6th Battalion to advance through M'Bras, Asanakor, Yubanakuor, and then east to the heavily fortified Sinahau villages, pushing the enemy toward Maprik for destruction. Additionally, a rumor was spread among the locals that the commandos would advance on Maprik via Ami, which successfully prompted the Japanese to reposition most of their forces to the north and northeast. Meanwhile, by early March, the 2/7th Battalion had completed the relief of the 2/5th Battalion and successfully occupied Asanakor on March 7, followed by Inimbi on March 8, Yubanakuor on March 9, and Balangabadabil, Ilahop, and Armimin on March 10. To the north, the 2/2nd Battalion also finished its relief at the Anumb. Additionally, the 2/3rd Machine-Gun Battalion and the 2/9th Commando Squadron took over from the 2/3rd Battalion in the mountainous region. The latter began advancing towards Arohemi on March 4, where they encountered a strong Japanese force that resisted for three days. After a significant airstrike, the Australians managed to clear the area west of the Anumb River by March 9. Simultaneously, the 2/2nd Battalion pushed forward to Simbi Creek, successfully clearing the area and reaching the Ninahau River by March 12. I would like to take this time to remind you all that this podcast is only made possible through the efforts of Kings and Generals over at Youtube. Please go subscribe to Kings and Generals over at Youtube and to continue helping us produce this content please check out www.patreon.com/kingsandgenerals. If you are still hungry after that, give my personal channel a look over at The Pacific War Channel at Youtube, it would mean a lot to me. The battle for Manila is finally over. The capital of the Philippines came at a terrible cost for the Americans, Japanese and innocent Filipino civilians. It would be only a matter of time until the Americans moped up the Philippines and continued onwards to the Japanese home islands.

Baltimore is a city full of neighborhoods with distinct personalities -- from quirky to conventional, from historic to … not so historic. Architecturally speaking, there are absolute gems … as well as diamonds in the rough. Doors Open Baltimore offers a daylong opportunity to explore a few of the city's most interesting buildings. Lauren Bostic Hill, Executive Director for The American Institute of Architects, Baltimore Chapter and Baltimore Architecture foundation and Nakita Reed, board president of the Baltimore Architecture Foundation, offer some highlights. Links: Doors Open Baltimore, Baltimore Heritage.Do you have a question or comment about a show or a story idea to pitch? Contact On the Record at: Senior Supervising Producer, Maureen Harvie she/her/hers mharvie@wypr.org 410-235-1903 Senior Producer, Melissa Gerr she/her/hers mgerr@wypr.org 410-235-1157 Producer Sam Bermas-Dawes he/him/his sbdawes@wypr.org 410-235-1472

rWotD Episode 2627: Penthouse apartment Welcome to Random Wiki of the Day, your journey through Wikipedia’s vast and varied content, one random article at a time.The random article for Saturday, 13 July 2024 is Penthouse apartment.A penthouse is an apartment or unit traditionally on the highest floor of an apartment building, condominium, hotel, or tower. Penthouses are typically differentiated from other apartments by luxury features. The term 'penthouse' originally referred, and sometimes still does refer, to a separate smaller 'house' that was constructed on the roof of an apartment building. Architecturally it refers specifically to a structure on the roof of a building that is set back from its outer walls. These structures do not have to occupy the entire roof deck. Recently, luxury high rise apartment buildings have begun to designate multiple units on the entire top residential floor or multiple higher residential floors including the top floor as penthouse apartments, and outfit them to include ultra-luxury fixtures, finishes, and designs which are different from all other residential floors of the building. These penthouse apartments are not typically set back from the building's outer walls, but are instead flush with the rest of the building and simply differ in size, luxury, and consequently price. High-rise buildings can also have structures known as mechanical penthouses that enclose machinery or equipment such as the drum mechanisms for an elevator.This recording reflects the Wikipedia text as of 00:09 UTC on Saturday, 13 July 2024.For the full current version of the article, see Penthouse apartment on Wikipedia.This podcast uses content from Wikipedia under the Creative Commons Attribution-ShareAlike License.Visit our archives at wikioftheday.com and subscribe to stay updated on new episodes.Follow us on Mastodon at @wikioftheday@masto.ai.Also check out Curmudgeon's Corner, a current events podcast.Until next time, I'm standard Russell.

“My life story and career has had a lot of twists and turns. I think just starting super young,I knew I wanted to create something, to build something, to ultimately to start a business and be an entrepreneur. It just took me a long while to figure out what that was and what the thing was that I truly loved and was passionate about. All of the different aspects of my path have influenced and led to what's become Onera and a true passion for building very unique experiential and landscape hotels.” We're in great company with Ben Wolff, Co-Founder and Developer of Onera, a treehouse landscape hotel in the Texas Hill Country. Offering a secluded, luxe, nature escape with nearly a dozen architecturally stunning glamping accommodations, Onera evokes a sense of wonder everywhere you look.  Perfectly positioned just outside of the charming town of Fredericksburg, Ben and his team have curated an assortment of local recommendations and on property experiences, so guests can enjoy a sense of adventure or settle into a serene stay.  In this episode, Ben shares how a series of events sparked an idea in his innate entrepreneurial mind, and how that idea has become a movement that is redefining experiential hospitality through landscape resorts, boutique hotels, and luxury retreats, starting with Onera.  Top Takeaways [1:55] While Ben always had an entrepreneurial mindset, it took a career full of twists and turns, a global pandemic, a wedding day realization and a cross-country roadtrip to set his path towards creating Onera.  [9:00] How Ben found a white space in the nature seeking hospitality market and what led him to fill that gap starting in Texas Hill Country.  [15:20] A few words come to mind when Ben shares what he wants his guests to experience with Onera…Inspired. Enchanted. A Dream. An Oasis. [20:40] Staying at Onera comes with a dip in their signature cedar tubs, a view of deer, wild turkeys and the occasional armadillo, a communal gathering space amidst old oak trees, and curated experiences from dinner with a private chef to an in-room couple's massage. [24:00] Take your pick from this collection of architecturally stunning accommodations - ranging from glamping to a bungalow, a dome to a stilt house, a treehouse to tiny homes - each unique in their design and experience.  [31:15] There's so much to see, sip and savor in and around the charming town of Fredericksburg, from its Hill Country wineries to its German culture and cuisine, from endless fields of wildflowers to shops full of antique finds.  [33:50] A sneak peak into where Ben is taking Onera next, this time with even more focus on sustainability and sunset views. And if that's not keeping him busy enough, Oasi is concepting a tropical fruit tree boutique hotel, what sounds like a delicious stay!   Notable Mentions AirDNA Vacation Rental Data Analytics Amangiri, Utah The Adelphi Hotel, New York Fredericksburg Shops & Restaurants: Wildseed Farms Caliche Coffee  The Peach Basket General Store Frisch Juicerie Otto's German Bistro Hill & Vine  Texas Hill Country Activities: Willow City Loop  Enchanted Rock  Inwood Estates Vineyards Slate Theory Winery City of Wimberley Visit For Yourself Onera Website | Newsletter Instagram: @stayonera X: @uniquestaysguy LinkedIn: Ben-Wolff Stay In Good Company Website

Gareth Russell is a historian and broadcaster, educated at Oxford University and Queen's University, Belfast. He is the author of nine books. He is host of the podcast Single Malt History with Gareth Russell.  Russell divides his time between London and Belfast, Northern Ireland.  In THE PALACE, Russell presents 500 years of the British monarchy, from King Henry VIII to Queen Elizabeth II, through a unique lens--their connections to specific rooms at Hampton Court Palace. Architecturally breathtaking and rich in splendid art and décor, Hampton Court Palace has been the stage of some of the most important events in British history, such as the commissioning of King James's translation of the Bible, the staging of many of Shakespeare's plays, and Queen Elizabeth II's coronation ball.Learn more at: https://www.simonandschuster.com/authors/Gareth-Russell/500660891Follow Gareth at Instagram: @_garethrussell; Twitter: @garethrussell1.

Jonathan, or J. as he's known to friends, is a husband, a father, and the owner of Trailhead Technology Partners, a custom software consulting company with employees all around the world. He is also a Microsoft MVP in .NET and frequently speaks at software meetups and conferences. He doesn't mind too much because he loves sharing what he's learned, and it also gives him an excuse to visit any nearby National Parks, a passion of his, proven by the fact that he's currently made it to 56 of the 63 parks.   J. also has a passion for building community and has served on several non-profit boards over the years as a result. Currently, J. sits on the SoftwareGR board, a non-profit trade organization dedicated to building the software industry in West Michigan. He also runs Beer City Code, a software conference, and has served as president on that board for over a decade. J. loves hiking, reading, photography, and trying to see all the best picture nominees before the Oscars ceremony.   Topics of Discussion: [4:18] J starting his own consulting company, Trailhead. [4:55] The two categories that make up software architecture. [5:54] J's philosophy on when he would rewrite a legacy software system. [10:52] The pros and cons of making small improvements over time. [11:33] What is the strangler fig pattern, and how does that turn into a strategy for a software update? [16:02] Bringing older ASP.NET applications up to .NET7. [19:55] What is a reverse proxy? [22:21] We reference the book Working Effectively with Legacy Code. [25:08] In this process, do both of the applications just get access to everything, or do you have to do something specific? [31:28] Architecturally, does this approach work in modernizing from older or other platform web applications? [34:02] The concept of microfrontends.   Mentioned in this Episodes: Clear Measure Way Architect Forum Software Engineer Forum Programming with Palermo — New Video Podcast! Email us at programming@palermo.net. Clear Measure, Inc. (Sponsor) .NET DevOps for Azure: A Developer's Guide to DevOps Architecture the Right Way, by Jeffrey Palermo — Available on Amazon! Jeffrey Palermo's Twitter — Follow to stay informed about future events! Architect Tips — Video podcast! J. Tower on Twitter J. Tower on LinkedIn YARP Basic YARP Sample Strangler Fig Application   Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

Nathaniel Schutta (or Nate) is a software architect focused on cloud computing and building usable applications. A proponent of polyglot programming, Nate has written multiple books and appeared in various videos. Nate is a seasoned speaker, regularly presenting at conferences worldwide, No Fluff Just Stuff symposia, meetups, universities, and user groups. In addition to his day job, Nate is an adjunct professor at the University of Minnesota where he teaches students to embrace (and evaluate) technical change. Driven to rid the world of bad presentations, Nate co-authored the book Presentation Patterns with Neal Ford and Matthew McCullough. Nate has published Thinking Architecturally and Responsible Microservices both available as free downloads from VMware.   Topics of Discussion: [5:12] How Nate decided he liked development and architecture, and who was Dr. Evil? [7:10] Nate worked at a software company for a brief period and spent a lot of his time building enterprise web apps. [10:13] Is it possible to think and talk about software the same, regardless of language? [14:17] Nate Defines circuit breaker. [15:56] The importance of having good observability and monitoring in place to see what is going on. [22:35] Nate gives some categories of architects and where he thinks it changes in responsibility and scope. [26:14] To quote Ralph Johnson, “Architecture is the important stuff, whatever that is.” While we may have different definitions of “IT,” Nate thinks that it has the decisions that are hard to change later, and the ones we hope we get right in the first place. The “IT” is also what matters to the application at hand. [36:14] Are we currently at another inflection point? [38:03] The current landscape and challenges of inventing things on the fly. [45:22] What can we expect from Nate's new book? [55:54] Engineers often overlook soft skills, and the Dale Carnegie books on leadership are a great place to start.   Mentioned in this Episodes: Clear Measure Way Architect Forum Software Engineer Forum Programming with Palermo — New Video Podcast! Email us programming@palermo.net Clear Measure, Inc. (Sponsor) .NET DevOps for Azure: A Developer's Guide to DevOps Architecture the Right Way, by Jeffrey Palermo — Available on Amazon! Jeffrey Palermo's Twitter — Follow to stay informed about future events! Architect Tips — Video podcast! Azure DevOps Nate Schutta Twitter Nathaniel Schutta Website Thinking Architecturally Fundamentals of Software  Dale Carnegie    Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

Professor James Stevens Curl is the author of the book "Making Dystopia: The Strange Rise and Survival of Architectural Barbarism". He dissects the modernist ideology as a historical phenomenon, which is not independent of the authoritarian social forces that surround it. On the contrary, Stevens Curl demonstrates that modernism became an authoritarian aesthetic ideology from early on, which eventually characterized the whole of Western culture. Where many academics in Western Europe have taken a nihilistic approach to the dystopian urban landscapes that have risen after the Second World War, James Stevens Curl chooses a firm position. As he sees it, modernism is a deeply immoral and a socially destructive project, which should be actively combated. Curl has also written extensively about Victorian architecture. Architecturally, the Victorian era was a rich era, with great building activity and saw the construction of many beautiful churches. In his newest book "English Victorian Churches", Curl explains how the European political currents of the time, British religious policy, and local engagement played a significant role in realizing this rich and beautiful architectural period."

Versailles – the palace, the people, history and legends. The extraordinary story of this mighty castle, built in a swamp on the outskirts of Paris stars a heavyweight cast of royals and played a key role in the destiny of France…As breath-taking today as it was some 400 years ago when King Louis XIV of France, AKA the Sun King (and not for his sunny nature), turned a humble hunting lodge into one of the wonders of the world. Architecturally glorious, gilded and grand, with gardens to match, the palace is full of secrets and its walls have witnessed events that have determined the course of history. We talk about the people who lived here, the history of the palace and the most fascinating facts about Versailles… Follow us: On Twitter On Instagram On Facebook On The Good Life France's website On Paris Chanson's Thanks for listening!

A version of this essay was published by firstpost.com at https://www.firstpost.com/opinion/shadow-warrior-paris-is-burning-why-12837712.htmlI had the disconcerting experience of being on the ground in Paris while the current riots raged. Oddly enough, on my previous visit, in April 2019, I arrived the night the Notre Dame cathedral caught fire, and then was in town during the Yellow Vest riots against fuel taxes. In both cases, my plans were affected: in the current case I stirred out of my hotel room near the Arc de Triomphe with trepidation, worried as I was by TV images of random violence and especially arson.I had been to Paris for several years in a row (until covid) for an annual conference on innovation, so I have a slight familiarity with the city, and it remains one of the most charming cities in the world. Architecturally appealing, with world-class museums (I did my usual homage to the Louvre, the impressionist Musee d'Orsay and the Musee Guimet of Asian art), lovely boulevards, the peerless Eiffel Tower, the unhurried meals in sidewalk cafes: the very picture of the good life.Then there is the dark side of things.The proximate cause of the troubles was the shooting death of a 17 year old youth of Algerian heritage, possibly the result of excessive force by the police. But this is just the spark. As in other countries with restless minority populations (e.g. the US with periodic riots after police shoot yet another black man, as in Los Angeles burning after the death of Rodney King), there are many other resentments that fan the fire. It would be easy to surmise that racism and the reaction thereto are the main factors in action.But I think there is another, possibly preponderant cause: demographic shift. France is getting less white, more black and Arab, and more Muslim. Coupled with an ever-restive leftist streak that has been evident for long (remember the student riots in May 1968 and the always volatile Left Bank?), today we have a left-migrant nexus of sorts that magnifies any issue and takes to the streets.There are large numbers of migrants, including those who came from the colonies and more recently refugees fleeing terror and chaos in Syria, Afghanistan etc. One would think that they would generally be grateful to Europe for taking them in, but radicalization is literally visible on the streets: the older generation is more secular, but their sons and especially their daughters-in-law are more observant, with beards, hijabs and other signs of religiosity. They are influenced by fiery preachers who call for jihad.It is now much easier to marshal ‘flashmobs' via social media. In fact, France has just had to turn off the Internet to prevent further provocation and nastiness. Let us note that this was not trumpeted by Deep State journalists as a sign of autocracy, although that is exactly what they say when India has to turn off the Internet in Kashmir.There were statements made by some of the rioters (I'm not sure if it is just bravado or whether they seriously mean it) that they intend to take over Europe through the power of their numbers, as they are noticeably more fertile than native whites. Eurabia is an inevitable reality, they believe. This, naturally, does not sit well with the locals. They will probably begin to curtail migration, as some Scandinavian countries have begun to do.Perhaps there is also a crisis in governance, which was the opinion of an old friend, whom I met for drinks at the landmark Publicis Drugstore on the Champs Elysees. She was unhappy about the mayor and other politicians whom she blamed for the poor state of general administration. (I just read that a suburban mayor's home was attacked, and his wife injured). Although my friend didn't talk about him, Emmanuel Macron is not universally popular either; even senior citizens appear to be upset with him.She also mentioned that the covid lockdowns had had a hugely disruptive, and lingering, effect, as many people lost their jobs, many moved out of Paris, and have had their prospects diminished. France's place in the world is also diminishing: it is now mostly a purveyor of luxury goods (fittingly, the head of LVMH is now the richest person in the world), and it was roundly humiliated by the US in the AUKUS affair, even though it is still a major arms supplier.Maybe there is a certain angst in the air. Maybe that is the root cause, or at least a root cause.I met a Pondicherry-origin man working in the transit hotel near the airport where I spent my last night in Paris, not wanting to risk riots, arson and barricades on the way from the city to Charles de Gaulle. He was generally negative, warning me about crime ranging from pickpocketing to muggings and especially the riots. He felt that his life as an immigrant (he has been there for many years) has become worse, and he felt he could be targeted by both Arabs and whites based on his Indian looks and the certainty that he was harmless and would not retaliate.I only personally witnessed a boisterous crowd shouting slogans that I couldn't understand, and no violence or arson (thankfully), but there was the constant wail of police sirens in the background, and what sounded like shots in the middle distance. Sadly, the largest library in France was set on fire. Thousands of vehicles were destroyed, and hundreds of houses looted and burned. In the end, I am told residents responded with vigilante squads fending off the unruly mobs.I also spoke to the proverbial taxi driver (a Moroccan-Frenchman), following in the footsteps of famous economists and journalists. He tried to be circumspect, and he didn't seem to be a religious person (there were no accoutrements in his car), but he told me about hard times. He was running an illegal taxi service, and he overcharged me 10 Euros since (he claimed) he didn't have enough change.He spoke about unemployment and discrimination, and how inflation was hurting his living standards. I have in the past found French Arabs not very hostile to Indians (as we don't threaten their livelihoods), and this man wasn't either.The same issue of economic problems was echoed by a Malayali manning a souvenir shop. He had arrived as a student, stayed on for a few years, and now was facing problems in bringing his family over from India. Incidentally, a lot of the souvenir stalls near Sacre Coeur, the Louvre and elsewhere are staffed or owned by Indian-origin people: I met one from Gujarat, another from Mauritius.The number of Indians I saw around Paris has gone up from prior visits: both tourists and residents. There still are far more East Asians (in my hotel there were Koreans and Singaporeans) around. I met a young woman from Kanyakumari who was leading a tour group on the Eiffel Tower. She was optimistic: she was doing her MBA, working part-time, and she has an import-export startup in India that she will be returning to.My chance encounters with these people illustrate the point about European decline. France has a nice little niche in luxury goods, but I suspect their buyers are increasingly from newly-affluent Asia. The departure area at CDG airport Terminal 1 is a veritable secular cathedral, with chandeliers and luxurious seats, surrounded by glitzy and expensive Dior, Chanel, Louis Vuitton, Hermes, Cartier, etc. shops tempting the departing traveler.But decline in the former colonial powers (most evident in Britain, which also shot itself in the foot with Brexit) is a fact. In a way it is poetic justice: Paris is full of evident loot from elsewhere (the Egyptian obelisk from Luxor, the Cambodian sculptures from the Bayon and Angkor Wat) and France clearly was enriched by exploitation of the colonies.But their core industrial strength has vanished (China continues to rape and pillage their IPR), along with their position in the global GDP standings. India has overtaken France and Britain, and will soon overtake Germany. Europe is now less of a factor in the world than it has been since the Middle Ages. Asia is rising again.It's a powerful cocktail: inevitable cyclical decline, memories of imperial grandeur, the determined Islamist assault, and general anti-government feelings going way back to the French Revolution. Surely, the crackdown by some 50,000 police and if necessary, the army, will control the riots, but one day the rioters may win. Predictably, all of Europe is now shifting right-wards: Italy, Finland, Greece, possibly Spain. Hard times beget hard men.1450 words, Jul 3, 2023 This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit rajeevsrinivasan.substack.com

On this week's show, Adam Leventhal posed questions from Hacker News (mostly) to Oxide founders Bryan Cantrill and Steve Tuck. Stick around until the end to hear about the hardest parts of building Oxide--great, surprising answers from both Bryan and Steve.They were also joined by Steve Klabnik.Questions for Steve and Bryan:[@6:38] Q:Congrats to the team, but after hearing about Oxide for literal years since the beginning of the company and repeatedly reading different iterations of their landing page, I still don't know what their product actually is. It's a hypervisor host? Maybe? So I can host VMs on it? And a network switch? So I can....switch stuff? (*)A:Steve: A rack-scale computer; "A product that allows the rest of the market that runs on-premises IT access to cloud computing."Bryan: agrees[@8:46] Q:It's like an on prem AWS for devs. I don't understand the use case but the hardware is cool. (*)I didn't understand the business opportunity of Oxide at all. Didn't make sense to me.However if they're aiming at the companies parachuting out of the cloud back to data centers and on prem then it makes a lot of sense.It's possible that the price comparison is not with comparable computing devices, but simply with the 9 cents per gigabyte egress fee from major clouds. (*)A:Bryan: "Elastic infrastructure is great and shouldn't be cloistered to the public cloud"; Good reasons to run on-prem: compliance, security, risk management, latency, economics; "Once you get to a certain size, it really makes sense to own"Steve: As more things move onto the internet, need for on-prem is going to grow; you should have the freedom to own[@13:31] Q:Somebody help me understand the business value. All the tech is cool but I don't get the business model, it seems deeply impractical. You buy your own servers instead of renting, which is what most people are doing now. They argue there's a case for this, but it seems like a shrinking market. Everything has gone cloud. Even if there are lots of people who want to leave the cloud, all their data is there. That's how they get you -- it costs nothing to bring data in and a lot to transfer it out. So high cost to switch. AWS and others provide tons of other services in their clouds, which if you depend on you'll have to build out on top of Oxide. So even higher cost to switch. Even though you bought your own servers, you still have to run everything inside VMs, which introduce the sort of issues you would hope to avoid by buying your own servers! Why is this? Because they're building everything on Illumos (Solaris) which is for all practical purposes is dead outside Oxide and delivering questionable value here. Based on blogs/twitter/mastodon they have put a lot of effort into perfecting these weird EE side quests, but they're not making real new hardware (no new CPU, no new fabric, etc). I am skeptical any customers will notice or care and would have not noticed had they used off the shelf hardware/power setups. So you have to be this ultra-bizarre customer, somebody who wants their own servers, but doesn't mind VMs, doesn't need to migrate out of the cloud but wants this instead of whatever hardware they manage themselves now, who will buy a rack at a time, who doesn't need any custom hardware, and is willing to put up with whatever off-the-beaten path difficulties are going to occur because of the custom stuff they've done that's AFAICT is very low value for the customer. Who is this? Even the poster child for needing on prem, the CIA is on AWS now.I don't get it, it just seems like a bunch of geeks playing with VC money?(*)A:Bryan: "EE side quests" rant; you can't build robust, elastic infrastructure on commodity hardware at scale; "The minimum viable product is really, really big"; Example: monitoring fan power draw, tweaking reference desgins doesn't cut it Example: eliminating redundant AC power suppliesSteve: "Feels like I'm dealing with my divorced parents" post[@32:24] Q (Chat):It would be nice to see what this thing is like before having to write a big checkSteve: We are striving to have lab infrastructure available for test drives[@32:56] Q (Chat):I want to know about shipping insurance, logistics, who does the install, ...Bryan: "Next week we'll be joined by the operations team" we want to have an indepth conversation about those topics[@34:40] Q:Seems like Oxide is aiming to be the Apple of the enterprise hardware (which isn't too surprising given the background of the people involved - Sun used to be something like that as were other fully-integrated providers, though granted that Sun didn't write Unix from scratch). Almost like coming to a full circle from the days where the hardware and the software was all done in an integrated fashion before Linux turned-up and started to run on your toaster. (*)A:Bryan: We find things to emulate in both Apple and Sun, e.g., integrated hard- and software; AS/400Steve: "It's not hardware and software together for integration sake", it's required to deliver what the customer wants; "You can't control that experience when you only do half the equation"[@42:38] Q:I truly and honestly hope you succeed. I know for certain that the market for on-prem will remain large for certain sectors for the forseeable future. However. The kind of customer who spends this type of money can be conservative. They already have to go with on an unknown vendor, and rely on unknown hardware. Then they end up with a hypervisor virtually no one else in the same market segment uses.Would you say that KVM or ESXi would be an easier or harder sell here?Innovation budget can be a useful concept. And I'm afraid it's being stretched a lot. (*)A:Bryan: We can deliver more value with our own hypervisor; we've had a lot of experience in that domain from Joyent. There are a lot of reasons that VMware et al. are not popular with their own customers; Intel vs. AMDSteve: "We think it's super important that we're very transparent with what we're building"[@56:05] Q:what is the interface I get when I turn this $$$ computer on? What is the zero to first value when I buy this hardware? (*)A:Steve: "You roll the rack in, you have to give it power, and you have give it networking [...] and you are then off on starting the software experience"; Large pool of infrastructure reosources for customers/devs/SREs/... in a day or less; Similar experience to public cloud providers[@01:02:06] Q:One of my concerns when buying a complete solution like an iPhone (or an Oxide rack

The Big Themes:Delivering solutions that create agility for the business: Aviatrix handles the compiling of security enforcement into the fabric of the network. All a customer needs to do is tell Aviatrix the policy of what they want to do, and Avaiatrix puts it into the CI/CD pipeline.Distributed cloud firewalls are the way: In trying to "fix" network security, distributed cloud firewalls offer a great deal of promise. Competing vendors might disagree, but customers will love it, and many already do.Cost savings and better security: With Aviatrix, customers don't have to decide between cost savings or better security; they reap the benefits of both. Architecturally, distributed cloud firewalls are the way, hence customers flocking to Aviatrix. The Big Quote: "As the CEO, and the business, what do they care about? They care about agility. Why are we moving to the cloud, right? That's why we're moving to the cloud. It's not for cost savings, we all know that. Gonna be more expensive than it was on-prem. The reason we're going, is that, right? Speed to the business. How quickly can I deploy applications to my customers, because that's driving my business? This is a business-led transformation. What's great about what we're doing is it simplifies things, right...We decouple all that Bob. Our system is intelligent, we create simplicity, right? Not manage the complexity, such that you actually don't need to think about the network and how the network deploys that network security. Because we own it end-to-end, we figure out the best way to do that."

David is a performance excellence coach focused on teaching, consulting and executive coaching for small to medium sized businesses, including many restaurants. David spent six years as a business/excellence coach for Pal's Excellence Institute. Pal's – or Pal's Suddenly Service – is a drive-through only 31-location restaurant chain located in northeast Tennessee and southwestern Virginia. The restaurant is known for its speed, hospitality, cleanliness and people. Pal's relies heavily on word-of-mouth marketing. That word-of-mouth allows Pal's to spend roughly half as much on marketing as some of its similar competitors. According to David, COVID gave restaurants a second chance to make a first impression. Restaurants that were struggling before the pandemic were struggling after the pandemic, pointing to an internal flaw that contributes to that struggle. Some restaurants used the pandemic as a chance to reset and improve themselves to make a second first impression and win over new customers after the pandemic ended. Quotes “What we see now is a lot of sculptures and spokescharacters have been discontinued. Architecturally speaking, we're getting modern boxes that don't have much life.” (Joseph) “If you look at the new (restaurant) designs, they're all basically the same. You really want to stand out in a sea of sameness.” (David) “How often in life do you get a second chance to make a first impression? If customers are coming back (after the pandemic), we have a chance to win them over and leave all that past behind.” (David) “If people aren't buying it, it's because they don't want it.” (Joseph) “If you think about a restaurant and what it does, it's really a manufacturing operation. You're manufacturing food in real time for a specific order based on your menu.” (David) “Systems are one thing, but activating them tends to be where the rubber meets the road and where most people hit the road.” (Joseph) “Twenty percent of the effort is putting a system in place and 80% of the effort is sustaining it. You have to make it a habit. You have to change in a way that it's harder to go back than it is to go forward.” (David) Transcript 00:00.91 vigorbranding Everyone today I'm joined by my friend David Jones he's the president of a company called the excellence advisory which we'll get into in a little bit. Um, but before we do David why don't you say hello and give a little bit of backstory. 00:11.50 David M_ Jones Well hello joseph and thanks for having me on today I considered a personal and professional honor to be here with you speaking to your audience and I'm actually an engineer by training 25 years in corporate America and then I had the great blessing and ability to work with. Pals through their business excellence institute which I hope we get to talk about and did that for 7 years and ah and today I do teaching consulting and coaching executive coaching for small to medium sized businesses including a lot of restaurants. 00:49.83 vigorbranding That's awesome. Yeah, so pals is um, essentially what prompted our connection on Linkedin. Um, and honestly it's a concept I had never heard of they're they're not here in Georgia or in Central Pennsylvania so I just never come across them. But what really grabbed my attention and prompted our discussion was. Um, pal's sudden service is what it's called has these amazing huge sculptures on their buildings sculptures of their food like hamburgers and drinks and all kinds of things and this just struck me as such an amazing thing. Um. Before we get into why they're doing that can you give us just a little bit of a rundown about what pals is all about. 01:28.79 David M_ Jones Oh absolutely. Yeah, it's so it's a drive through only 31 unit chain in East Tennessee and Southwest Virginia they are known for their speed their hospitality, their service, their cleanliness, their value. And they're people. They're amazing

It took nearly two years, but the Airmount Grave Shelter north of Thomasville near the Wilcox County line has been completely restored. The National Register structure, owned by the Clarke County Historical Society, was crushed by falling trees during Hurricane Zeta in October, 2020. Built in 1853; one-of-a-kind in state The important historic building was built in 1853 and is believed to be the only one of its type in Alabama. Architecturally significant, the unusual, splayed eaves and vaulted or “compass” interior ceiling can be traced to Eastern Seaboard church yards in Delaware and Virginia. “I thought we had gotten...Article Link

Episode Description: On this exciting episode of Duchess, Emma meets the custodian of one of Britain's greatest stately homes: The Marchioness Townshend of Raynham Hall. In this episode, we learn about the fascinating story of how the city of Sydney was named after a Townshend. The Duchess hears how Lord ‘Turnip' Townshend ushered in an agricultural revolution at Raynham, and we are given the full story behind the world's best known ghost photograph! Top Quotes: “You can not dictate the future of a home. All you can do is love it and look after it now.” - Lady Townshend “Traditionally, these houses would have had recitals for every group of people that they had visiting. Music is in the DNA of grand homes.” - The Duchess of Rutland About the Guest and Stately Home: Raynham Hall is a country house located in the glorious countryside of Norfolk. For nearly 400 years it has been the seat of the Townshend family. Born Alison Combs, Lady Townshend is the current custodian of Raynham with her husband Charles Townshend, 8th Marquess Townshend. The couple share four children. Lady Townshend was the editor of The North Norfolk Informer which she co-founded. Work started on Raynham Hall in 1619 commissioned by Sir Roger Townshend and is considered "one of the outstanding country houses of the period.“ Architecturally, Raynham is a neo-classical house and features a particularly striking marble hall - where classical concerts are held. Raynham Hall is the site for perhaps the most famous ghost of all time, taken by photographers for Country Life - the photo of the famous ‘Brown Lady' descending the staircase. About the Host: Emma Rutland, The Duchess of Rutland, did not always stride the halls of stately homes. Born Emma Watkins, the Duchess grew up the daughter of a Quaker farmer, in the Welsh marsh countryside. She trained as an opera singer in the Guildhall School of Music, and worked as a successful interior designer before meeting her future husband David Manners, the 11th Duke of Rutland, at a dinner party. Their marriage in 1992 would transform Emma Watkins into the 11th Duchess of Rutland, thrusting her into the world of aristocracy, and handing her the responsibility of one of the nation's great treasures: Belvoir Castle. While simultaneously running the day to day operations of the castle, and raising five children, The Duchess became fascinated with the history and importance of the other stately homes of the UK. Join The Duchess as she embarks on a wonderful journey through time, to learn more about the incredible homes that have defined Great Britain and, most importantly, meet the other extraordinary women who work tirelessly behind their doors to preserve their history and magic for future generations. Resources: https://raynhamhall.com/ (https://raynhamhall.com/) https://www.belvoircastle.com/ (https://www.belvoircastle.com/) https://www.onefineplay.com/ (https://www.onefineplay.com/) https://www.emmaduchessrutland.com/ (https://www.emmaduchessrutland.com/) https://www.duchessthepodcast.com/ https://www.abercrombiekent.co.uk/about-us/partners/duchess

Peter Linneman is an author of the Linneman Letter, the former Professor of Real Estate, Finance, and Public Policy at the Wharton School of Business. Previously listed as one of the top 25 most influential people in commercial Real Estate. In this episode we talked about: Real Estate Finance and Investments Book Valuation of Real Estate assets Inflation in Real Estate Relationship between corporates and interest rates Peter's thoughts on Real Estate Asset Classes Overview of Retail Real Estate Office Market Future of Commercial Real Estate Industry Advice to Real Estate Newcomers Resources and Lessons Learned Useful links: https://www.linnemanassociates.com Books: Factfulness : Ten Reasons We're Wrong About The World - And Why Things Are Better Than You Think by Hans Rosling Rational Optimist by Matt Ridley Youtube: https://www.youtube.com/watch?v=jbkSRLYSojo&t=3s Transcriptions: Jesse (0s): Welcome to the working capital real estate podcast. My name is Jesper galley. And on this show, we discuss all things real estate with investors and experts in a variety of industries that impact real estate. Whether you're looking at your first investment or raising your first fund, join me and let's build that portfolio one square foot at a time. Ladies and gentlemen, my name's Jessica gal, and you're listening to working capital the real estate podcast, a special, special guests today. We just chatted about this. If you don't know him by now, I don't know if you want to know him.   And that is Dr. Peter Lindemann. He's the author of the Lindemann letter, the former professor real estate and finance and public policy at the Wharton school of business. And he was previously listed as one of the top 25, most influential people in commercial real estate. Peter, how you doing?   Peter (49s): I'm doing great. I just got back from Egypt. So my background is a long lasting quality piece of real estate. The Luxor, temple, and luck soar. So good reminder that great real estate lasts like four or 5,000 years.   Jesse (1m 6s): There's a book I'm reading right now and it's on the evolution of skyscrapers and it goes back to the pyramids. It goes back to the, the renderings and the Bible of places that may be existed. Architecturally looks sound, but that is a, it's fantastic to see how we've come from there to where we're at today. And, and, and the drive for humans to build up. Hasn't seemed to wane in any way   Peter (1m 28s): When you see this stuff from three, four or 5,000 years ago. Yo okay. They got it.   Jesse (1m 35s): Yeah. Well, thanks so much for coming on. I, I think this is a real treat for listeners, for anybody watching the video. I'm holding up my real estate and finance and investment book written by the doctor, Peter Lindemann. And I mean, if you're in the real estate industry in any capacity, you will have to have come across this book. I think this, for me, it was second year of the MBA in Toronto and it was just chock full of amazing things. This thing. How long has it been now? When, when was this first published?   Peter (2m 5s): Oh, gee probably 16 years ago or 17 years ago was the first edition it's come to be referred to as the blue Bible. I don't know if that's a good description. It came about very oddly. And then I was teaching my real estate finance investment course for a number of years and I never had a book that I could find that I really liked. So I was teaching my own stuff, but I assigned a book to students because they needed something. So we finally recorded my lectures and after a lot of work and a lot of down additions, that's what came out of it.   Jesse (2m 40s): Yeah. Well, it's great. It's funny. I'd like, you know, you go through a time period where you're like, okay, I got to get rid of these books. Usually the textbooks are the first to go, but I've hung on to this one for a long time, just because I've actually kind of gone back to it. And now that we're at the stage in the career where we're hiring younger individuals, you know, this is something where, you know, they're probably reading in school, but it's definitely something that they can use as a resource.   Peter (3m 4s): Well, and one of the other things nice, is this a nice color? So while it's on your bookshelf, it looks good.   Jesse (3m 10s): Yeah. Yeah. It's not a, it's not that old school. Just topes. Well, you know what? There was a, so we chatted a little bit earlier. You were on a podcast that I recommend a hunter Thompson cashflow connections podcast. And there was something that I was driving in the car, listening to this podcast. And I had to write down because I was just like, you know what? This is it, it was something you said, and it was just an insight. And maybe we could use it kind of as a springboard for this conversation because that conversation did talk a lot about the economics of real estate and where we find ourselves today.   And what you said was demand as loosely described as real GDP growth is up 3% and goods as loosely described by industrial output are down by 1% and services as loosely proxied by employment is 1% short. Demand is up. Supply is down prices. Go up. Can you break that down for us? What we're talking about here?   Peter (4m 7s): Yeah. I mean, I think you broke it down really well. I think this there's very real inflation. The very real inflation started to occur. Let's just do a quick review. 20, 22 years ago, things are shut down. Like a third of the economy is shut. Not just slow shut. And then another third is really slow, but not shut. And then another third is working well, when you shut things, there are ramifications of that.   So for example, two years ago, the price of oil is like five, $10 a barrel. So what do you do with the tar sands? Shut them down. What do you do with the fracking? Shut them down because they aren't even close to break. Even. I'm just taking those as dramatic examples. Then what happens is fortunately the economy I'm talking about the us, but I think the Canadian pretty similar by very late 20 and then through 21 starts growing and it grew faster in its comeback.   Then supply came back. Now that's not surprising when you think about it because things are really awful. Do you expect supply to lead demand? No. Common sense says I wait to see if things are really there before I expand and bring on capacity. So what you've got is real GDP, kind of a crude metric of us demand up 3.2% versus pre COVID not annually.   The two years since COVID began and goods, output is down 1%, as you're saying, and employment is down 1%. And as you said, you don't have to be a genius to figure out supply down 1% from where it was in 2019, demand up three and a half percent prices are up. Now, you're going to have a long discussion of which prices and how much, some more than others. It's that simple.   When will price inflation, moderate, pretty simple. When supply catches up now there's this notion that we have to cool demand. And I asked people, would we be better off if we had no inflation right now? And GDP was also down 1% over those two years, by the way, if real GDP was down 1% and industrial output was down 1% and employment was down 1%. You think we'd have much inflation right now?   No. Would we be better off? Absolutely not. We'd be four and a half percent worse off. So you go, okay. It's a good thing. In fact, no is a good thing. It's a staggeringly amazing thing that after the last two years where we shut down huge plus in the economy, political division, COVID killing millions of people, many more, getting sick absenteeism at work, social unrest, a war now, I mean, name all this stuff that's happening.   And we're three and a half percent or 3.2% larger as an economy than before. That's amazing but left to its own devices. It would have been up about five and a half percent. So demands, not overheated. If, if real GDP was up 10%, then I'd say that's overheated. We can't do that. But we can do five to five and a half percent over a two year period. We've only done three. And at 3.2% under heated, we still need demand to keep driving forward.   We don't want to slow down demand. We want to encourage supply. So if we were going to do policies, the kind of policies we need are, and I'm just giving as an example, I'm not proposing them. Gee, you drill an oil well this year, or you start pumping from a well that isn't pumping. You could write it off in a year, right? You think you get more expiration with that as an incentive, or if you hire somebody net, net, you net, net expand your employment, you get a $4,000 tax credit.   Or if you come back to work after not having work for six, six months, I'm all of these. I'm just making up. As examples, you get a $2,000 tax credit is an individual. You think we'd bring back more late. Do you think we bring back more capacity? And as we did, what would happen to prices they go down. So I don't think this is about demand. It is in some tautological sense. It's about supply has made an amazing recovery from a shutdown, but still legs.   And I don't know how a lot of Terry policy gets us to bring back capacity faster and that's a real activity, so to screen. So that's how I see it. And it has some ramifications for real estate. Your, your construction costs are really going up, right? I mean, that's not an imagination, but on the other hand, so are your rents, so are your property values and you have to take the whole menu.   It's like when you played cards and you got three ACEs and a two and a three, Hey, that's a pretty good hand. You got three ACEs, be happy. Don't don't gripe about gee. I should have forays. Right? All things considered pretty good here.   Jesse (9m 48s): So when it comes to real estate, from the point of view of a couple of variables, there's, there's inflation in the general economy that people just seem to be continuing to worry about time and time. Again, this time it's different as Howard marks will, would, you know, titles each one of his chapters in his latest book. But what I'm curious about is from a real estate perspective, we have the valuation of the real estate asset, and we have those prices in our markets and a lot of other major markets in north America going up. And the concern is that these cap rates get compressed and compressed.   How much lower can these cap rates get compressed? What I'm curious about is it the going to be the valuation that gets out of control or will it be the affordability from a rent perspective that you see as the governing the governor? So to speak on in that dynamic,   Peter (10m 36s): Ultimately it's the fundamentals. And that would go to the mortar. The rent side price is just an outcome, right? Price is a comp bow. You know, the value of a property is the combination of the supply and demand for space, right? Namely income and occupant or retina occupancy and the supply and demand for money to buy income streams, right? And they don't necessarily always align. We're in a period where list supplying demand for space.   Retina occupancy is in quite good shape unless you were in senior housing, unless you're in hospitality, still lagging, unless you're in bad retail, unless you're in office where you don't know if people are coming back to the office. But if you're in apartments and warehouse and good retail, quite good Retin-A occupancy side. Now on the capital side, what's happened is QE one, QE two QE three.   After the financial crisis put unprecedented amounts of money into the system. And you saw coming out in 2014, 15, 16, 17, 18, 19, and that money searching for a home pushed down cap rates. And everybody kept saying, oh, cap rates are going to go up cap rates. But I kept saying, no, the weight of money is going to push it down. Now we've even put in a lot more money. In addition into this system, what do you think happens when that money comes out?   When that money comes out, it's got to find a home. So for example, we have record personal cash holdings. We have record corporate cash holdings. We have record dry private equity capitals. We have direct record, dry uncommitted, money, sovereign wealth and pensions vis-a-vis real estate. And we have record unused bank reserves. What do you think happens when they may still be at record levels, but a little lower record levels?   And the answer is that money's going to find a home and it's going to find it buying cash streams. Some of that is on the stock market. Some of it is real estate. Some of it is gold. And I think cap rates go down now, do they go down every day? No. And people say, well, how much lower they can? Can they go? Things can always go 2% lower. This is one of the things that you remember when you learned about penny stocks. And somebody said, how can you lose? They only cost a penny and you'd go, well, they could go to a half a penny, right?   They could go to a quarter of a penny. So how can the cap rate go lower than 3.7? Well, it can go to 3.6. It can go to 3.5. And the reason is the weight of money. So what do I mean by the weight of money? The example I use scope, the thought experiment. We've done a lot of statistical work on this that I won't go into saying, let them in, let her it's other stuff we've written, but here's the thought experiment. Very simple. Suppose I told you a year from now $4 trillion.   I don't care if it's Canadian or us $4 trillion. In addition to the amount already invested is trying to invest in apartment buildings. Okay. Well, you think will happen to cap rates. They'll go down. By the way, you didn't ask what's the economy like you didn't ask. What are interest rates get in, say, as the yield curve inverted, you simply said, well, that kind of money. It's got to find it. It's going to bid up the values bed down, cap rates.   Now flip that thought experiment. Suppose I told you that a year from now a trillion dollars is exiting apartment buildings. By the way, you could apply this to any property category. And you'd say, wow, that's going to be a problem. A trillion dollars trying to get out is going to crush values. And you go, you didn't know what interest rates were when you made that insight. You didn't know what the economy was. The point is the weight of money and we have put unprecedented amounts of money and it hasn't really come out yet to speak of.   And it will, and it will be asset price inflation, not con goes to the services.   Jesse (15m 5s): So question on that, we've had a economist on the show before of maybe on the one side, closer to the Austrian school, the other side, the modern monetary theory MMT. And for listeners, I would just look up both of those to learn a little bit more. But this idea that when the great financial crisis was happening, there was a number of economists that were saying, you're putting money into the economy, like your example, 4 trillion, 5 trillion that is going to cause inflation, no matter what, however, what was happening was it was sitting on balance sheets of banks. It wasn't getting into the economy.   And I always think about Milton Friedman's. I think it was his Nobel part of it was this velocity of money. You can't just go into the Connie. It actually has to move to create some form of inflation. So, so in this example, could you talk a little bit about when you say the 4 trillion in the market, does that mean on bank's balance sheets? Does that mean it's it's circulating, are those necessary conditions?   Peter (15m 60s): Yeah. At this moment, the same thing happened that I happened after , which is the amount of money going into the banks skyrocketed and the velocity with which they used it. So that in the beginning, there was no notable effect on the economy. It just kept the ship steady, if you will. And then the money started coming out slowly. Well actually slowly, just a little more rapidly than it did before.   And remember the modern banking system is not set up to lend you money to buy a Milky way is set up to have a, an investment firm by the company that makes Milky way, right. It's set up for that. And that's why as 2014 through 19 occurred the money chase assets rather than goods and services. Right? And so I think that's, what's going to happen again by enlarge the money, went into the system to keep it afloat in the way you described it, to make sure there was liquidity.   I think it did it well. And now what will happen over the next few years is it will come out. Will all of it come out? No, the velocity dropped, but as some of it starts coming in, when if I put a ton in beyond whatever you have, even if only a thousand pounds of it come out. So a lot of weight, right? A lot of weight, if I put a hundred tons in even of only a thousand pounds come out, it's still a lot of weight.   It's not much compared to what went into your point about velocity, but it's more than would have otherwise been there. And I think it will chase primarily assets now would include single family homes in that as an asset, right? It's a real ass.   Jesse (17m 55s): Now when it comes to the economy itself, well, you know what, let's back up for a second. I did have somebody from my office. They said, you know, you have to ask, I told them I was having you on. And he said, ask him about the relationship between cap rates and interest rates. Cause we talk a lot about that spread in our industry quite a bit basically. Is it a significant piece of what you guys look at over, over the longterm? How is it tracked? You know, and you mentioned earlier that Lindemann letter, we'll put a link up to that as well, but I'm just curious in the work that you do, how important that relationship is.   If at all,   Peter (18m 29s): If there's a relationship, it would be important. However, having studied it, we can't find a relationship other than that. So I'll give you, for example, in, I think it's the, I can't remember if it's 40 years of 45 years, basically the 10 year treasury yield has fallen by 600 basis points. And the cap rate fell by 300. That's hardly one to one. Then if you look at the micro history of that movement, it's all over the place.   That is to say the spread movements in the spread, basically swamp, the general downward decline, right? That'd be the spreads are all over the place over history. Then go one step further and I'll give another example. We looked at it very sophisticated. Statistically, can't find it. Can't find the correlation. Now, by the way, if you said the interest rate 10 year treasury went from 2.3% today to 14% tomorrow, that would probably have an impact, but that's not likely to happen.   If you said it went from 2.3 to 2.9 or 3.2 or back down to 1.6, by the way we saw it go from 1.6 to 2.3, what happened to cap rates? They went down. If anything, why? Because of the way the money, not the caused the interest rates went up and there was this not interest rates going up causing price, cap rates go down. It's just no relationship. I'll give you the other that captures it. If you look at 2007, cap rates were essentially identical to 2019, okay.   2007, 2019 and 2007, the long and the short rate were above 5%. And in 2019, the short rate, what I'm doing from memory was 2.5 or 2.6. And the long rate was 3.2. How can that be? If it's interest rates that are causing them, that interest rates are 200 basis points higher and you still have the same cap rate that should tell you something, right? And in fact, we've seen periods where there's a flight to quality.   When there's a flight to quality interest rates go down and cap rates go up well so much for the step relationship. It just doesn't exist. At least in the relevant parameters, at least that we can find, or that I've seen. One other thing I'd add about interest rates that I kind of tell friends and clients to call them down. Let's assume let's just assume that a year from now, we're sitting here and the long rates at 3.2% and the short rates at 2.5%.   Okay. A lot of interest rate movement upward. Okay. Is that a disaster? No, that's 2019. That's 2019. Those interest rates I just described we 2019, if we'd have had this conversation in 2019, you would have said, how much longer can these low interest rates last, right? You wouldn't be referring to them as high. I'm sure you had that conversation with people.   Right? So to understand that even a big interest rate movement back is simply to 2019, which by the way, most real estate people said, thank you very much. This is pretty cheap money because it is, we then had a fire sale where the government gave money away. If you were willing to borrow. And the biggest borrower of course, was the U S government biggest borrow in the world during that was the us government. They subsidized you as government and they subsidized borrowers.   Well, if they stopped subsidizing borrowers, that hurts far worse. It helps lenders. It helps savers and it hurts debtors, but it's not like one's more noble than the other, a dollar gain by one or lost by the other washes primarily. So I don't get hung up on that balance. Sheets are pretty sane. And so he just had to have a bit of context. And by the way, telling the us government that their money isn't free is not the worst thing we could do because they're like little children.   If Candy's free, the little children are given candy for free. Right. And he said, whoa, you got to slow down. You got to buy, you got to buy that. Right. Slows them down. That's Congress, if you give them or the system, if you give it free money, guess what they use it like it's free. Yeah.   Jesse (23m 27s): So when it comes to, when it comes to like speaking of washes, when it comes to the other asset classes that we deal with in commercial real estate, retail, industrial multi Rez office space, what we had in our office, which was not dissimilar. I think now we're at 85 locations, 85 major markets. And what we had in our headquarters was during COVID. We almost were revenue was down top-line was down, but it was close. And what happened was we had industrial and multi Raz really were the darlings of the industry.   And they, they kind of made up for retailer, like you said, not, you know, grocery store anchored or really good retail. And on the other side, the office, so office and retail was the drag. Those other two asset classes came up and, you know, picked up the slack. Do you see this trend? Continuing? What are your thoughts on, on the various asset class classes moving forward?   Peter (24m 24s): Okay. Real quick multifamily. In December, 2020, I wrote a piece we're entering the golden era of multifamily investing. And it was because spreads were big capital was available to borrow debt was being given away a because of the subsidy rent unoccupancy are good and going to get a lot better. Well, pro that happened in the last 15 months, it's still has legs, but some of the gold is already been harvested.   All right. So it's not like we're in a bad period for multifamily, but we're in a golden period, but a lot of the gold has already been harvested. Retinol, occupancy look good going forward, demographics. So good fundamental under supply of housing, multi, especially single. And so it has good fundamentals. It can be overbuilt, but then you go to industrial and industrial took me a while to figure out, I think I finally figured it out. Normally you would think if GDP I'm using it as a crude measure of demand, if it grew by two and a half percent, we'd need about two and a half percent more warehouse because two and a half percent of more GDP, two and a half percent more boxes, right.   Just kind of crudely. And that had kind of been a good rule of thumb. We always did more precisely, but as a rule of thumb. And then what happened is we'd see two and a half percent of growth of GDP and 4% growth in warehouse and demand. Didn't say, well, that's odd. Can't last. And then the next year you'd see the same thing, 2016, then the next thing in 70 next thing in 1819, you kept seeing, I finally figured out that if you buy that shirt in a store, it takes one third of the warehouse space that if you buy it online, because an online facility has wider aisles, more staging areas, small box handling, rather than big box handling, lot more loading in and out needed a lot more moving around than let's move a box here or there let's move a pallet.   So online sales use about three times the amount of space. Well that me and this two and a half generates four is about the right math. And given the growth of online, that's going to continue for a number of years. So when does the rent and occupancy balance, when we start building for four and a half percent and demand grows it for four and a half percent, well, that's not going to happen for another couple of years. So the rent unoccupancy fundamentals there look pretty good.   Even as we build more and more the real risks, there are two, one, a lot of online sales don't make money. And a lot of retailers realize that during the pandemic. So are they still going to be so aggressive selling online? And if not, it gets closer to the two and a half generates two and a half. And the other is everyone. Somebody wakes up whole bunch of people wake up at Amazon saying, how do we get it from three times, the amount of footage needed for an online sale to two times.   And if they do that, it changes the math. You then go to retail. I've never wanted to own bad retail. I've always wanted to own good retail. If you own good retail, you're constantly having to reinvent it through its entire history. But if it's a great location and you have a core of good retailers, it's a dynamic business. It's a hard grinded out business. I love the dynamics of great retail. And in fact, online sales have been flat for the last year high, but flat while brick retail is getting record sales and as online gets back to trend, then the trend will continue.   And, but I like good retail. Why would I like bad retail? I mean, it just, and I remember Al Talman long time, kind of one of the gods of the industry, certainly one of the gods of retail, I don't know, 30 years ago, 35 years ago said you can't buy bad retail, cheaply enough to make it work. And that's because even if you get it for almost nothing, your rent cannot be cut low enough to change the price of Cheerios.   And if you can't change the price of Cheerios people, aren't going to shop there. And if they're not going to shop there, you don't have good retail. Right. So good retail. I like the outlook for hotels making a comeback. Weakest part is if you're highly dependent on Chinese tourists, kind of a, what a two-star three-star Chinese tourists. They're not coming back for another couple of years. And if that was your sweet zone was playing to them, that that's going to still be, that's going to be the slowest recovery, but it looks like this summer pending another surge, absent another surge, going to be a great summer and into the fall.   Jesse (29m 47s): So before we get to office, I just, I just had a question, a question on retail. You know, whether it's north America in general, whether it's American or, or a Canadian, I think it's 32, 33 square foot of retail per capita. I think something like that, we're not much better in Canada than the U S obviously the European countries have not built as much. Do you see that there's this conversation or has been over the last two years that, you know, a lot of these potentially multi-family or retail, you know, lower tier areas are going to be re developed repurpose whether it's industrial or whether, you know, whether it's multi rise.   Is that something you do see, you know, developers actually looking at that   Peter (30m 28s): It's the pandemic probably sped it up because it pushed so many retailers that we're going to go out of business, out of business. The thing that kept them from shutting, I mean, we looked at doing some of those deals. The problem is you have one tenant paying $2 a foot. So even though they're only selling $114, they actually make profit in the store at, at $2 a foot rent. And that's because the lease was signed 30 years ago with auctions, right.   I'm being extreme, but you get the point and nobody else wants to be there, but I can't buy it, shut it down and build apartments. Or I can't do anything with it. That happens over time. That will happen over time. So, absolutely. And this notion that we have too much retail reminds me, remember, you're old enough. You remember how you would drive by the old industrial areas of America. And you just see these empty warehouses, these empty 1920s, 1910s, 1940s buildings that works counted as empty industrial, but they weren't empty industrial.   They were just empty space. And if you wanted to call them industrial column industrial, but it's not real. If you got rid of the space in retail, that's irrelevant. It was once retail, but it's irrelevant. Just like that old factory that shut in 1972 was irrelevant as industrial space. The amount of footage we has have goes way down. Now, that's not to say it gets to the right amount, but it goes way down in the same way the old industrial did.   That's what we ought to have. We ought to have. If people are really carefully, they've created a new class obsolete, real estate of any type, right? And then you'd see the retail stock go down. You'd see the industrial stock go down. Although the industrial has kind of run its course, those old old buildings have been dealt with over the last 20 years.   Jesse (32m 38s): So the wild card office space we've seen, we track all the, the major markets we have seen pretty much every U S market has come back from a cell phone data that we have into the major cities. We are a little bit slower just because our government policies have been, they are what they are. We'll not get into a political thing here. But what we have seen is a lot of these markets, a huge increase in the percentage of the office market being subleased space.   Now we're starting to see that trend go the other way, starting to come back down and what I, what we've seen in the markets that we are in here is that really good positioned office space in major cities continue. And it looks like the outcome look as positive, potentially not the same for the suburban area. What are your thoughts on, on the office? Just philosophically first and then maybe some of the data that you're seeing.   Peter (33m 33s): Oh, I totally agree with your view. I think people have a fall. People fell in love with this fantasy that I don't have to be work. I don't have to be at work. I don't have to be answerable. I'm self-motivated to work at home. If you're really honest, you have to be pretty highly, self-motivated pretty disciplined. Have a good work environment and be able to control your schedule pretty effectively. Well, there are people like that. Those are the people who are already working at home. Those are the people who are working from the airport.   Those were the people who were working while they were on the road, et cetera. I've well having said that, I'm always amazed that when I fly back from Europe, which I do quite a bit and I'm in business class. So these are quote, a lot of worker types. And when you're flying from Europe to the United States, it's a Workday, right? It's not night. It's not like when you go the other direction and it's night look around and see what people, these business people, these hard working disciplined people are doing as they fly from Europe to the United States about a third sleep and, and, and all of it, about 10% of the others.   Do nothing, read a book or watch a movie. Well, this is a work day for God's sake. So I'm sitting there working away, working away where Kiawah and I realized most people don't have that discipline. I'm not saying I'm great. I'm just saying they don't have that discipline. The other variant of that, that I like to point out to people is I think Ricky is a brilliant writer comedian. And he created the office in many things. We created the office, both the British and us version. And it was built around the notion that it's really hard to get people to work while they're at the office.   If you think it's really hard working while you got them at the office, what do you think Ricky do? Surveys is show working from home would look like, I mean, let's be honest, right? And people would go back now and give you the last reason. I think people go back and it's self preservation. There's tipping points here. And if nobody's at the office, what's the point of week going to the office, right? I mean, if all I'm going to do is go to the office and sit alone and not interact and be around people.   There's no advantage then is a whole lot of people get there and there's advantages. And then as more than the majority are there, I got to be there because otherwise, I don't know what they're saying about me. And I don't know who's getting the plum assignments so it can flip from if nobody's there. There's absolutely no reason to go there. But basically everybody, when I say everybody, I mean, everybody all at 2019, basically everybody's there like it or not.   I got to be there to protect myself. And self-defense is an amazing instinct of our species. And that's what ultimately is going to bring us back.   Jesse (36m 43s): I had a number of people early in the pandemic. They, you know, they knew, I worked in commercial real estate. We specialize for the most part in an office. And they were like, you know, what are your thoughts on the, on, you know, the pandemic. It turns out, you know, the zoom calls all this, you know, we, you can work from home. And my response was always, if you're in my industry and you don't know that this was a secular trend that was happening happening long before, COVID this idea of agile offices, you know, working for, and we needed kind of a kick in the butt to get the technology where we needed.   I don't think you've been kind of paying attention to the market. I think my outlook is that it's, it's a general positive thing, but you know, I'm a, I'm the perfect candidate as a commercial broker that I sh I should be able to work at home all day. No problem. And I can, but like you said, as motivated as I am being around my team, being accountable to them, physically seeing them being in the space, having just a different idea of my TVs over here, you know, versus my couches over here versus I'm in the office. And I'm in a different mode that it seemed like a insignificant thing at the beginning of COVID I've come to realize it's a, it's a crucial part of how I work.   Peter (37m 49s): So one of the things I say to people I'm old, I'm 71. One of the things I say to people is I'm not sure that this zoom wouldn't be better if you couldn't see me, because I'm not that good looking okay. And that's called a conference call now. Yes, it wasn't encrypted. And yes. So I'm not trying to say technology. Hasn't made it better, easier for you to get a lot of viewers all in, at once and so forth and so on versus a conference call.   But we were doing from 2011 to 2019, we were doing quarterly economic updates for our subscribers. That would have like 500 people on old old-fashioned phone hookup. We didn't have big problems. And I didn't get a lot of people saying, oh, I'm going to commit suicide because I didn't see your lovely face. And let's be honest. You're a good looking guy. I'm not, there are a few people we're looking at, but most of us, it doesn't add to the conversation.   Jesse (38m 57s): Yeah. I'll be happy if I look like that at 71, Peter. So don't sell yourself short. We've got about 10 minutes left here. I want to be a little mindful of your time. But before, before we wrap up, maybe you could kind of provide a little bit of insights, crystal ball for us. You know, what you think the future holds for the commercial real estate industry. And maybe you could kind of couch that with this idea of, you know, people talking about the potential next recession, interest rates going up political unrest.   W what are your thoughts?   Peter (39m 29s): Okay. If we don't have a huge re occurrence of some very bad version of COVID, right? 'cause that's, that's, we shut down to varying degrees. Okay. If we don't have NATO somehow dragged into the Ukrainian situation, which could be very violent and, and really escalate. And we don't have a political reaction like we did in 1971, when Nixon introduced wage and price controls, the U S economy is going to do terrific for the next four or 5, 6, 7 years.   Most of the excesses that existed, not saying all most got white washed out of the system in 20 20, 20, 21, it was kind of a reset, kind of a reboot. We got a new base zero, and I think we get 5, 6, 7 years of runway, unless we do something. We, as a species, do something that really is harmful and COVID would fit that the, the NATO being dragged in militarily and wage and price control.   I saw wage and price controls. When I was just out of college, destroy an economy, I mean, overnight destroy an economy, and it would do it. It could, it would do it again. That's the biggest risk I see to the economy, because I think that's more possible than the COVID being huge or the, or the NATO, but they're all possible short of that. The economy is going to do just fine. And I'll give you my reaction. And I've only started saying this.   I don't know if I set it on hunters, which is a true story, by the way, I'll tell you when I'm lying. True story is I had lunch with a friend about three, four weeks ago. And he said, you know, Peter, I follow you and smart and all this stuff. Great, wonderful. But interest rates going to go up and inflation and the divided Congress and Ukraine. And by the way, he went on to name like six sings.   Each of them, very real. It's not like these out of touch. Each of them is a very real chance that our education system is, is, you know, shambles, you know, and so forth. And he said, therefore, I don't see the U S economy has a future. I don't see how we come back from this one. I just don't see how we grow from it. And I said, Bob was named Bob. I said, Bob, anytime in my life, any intelligent person could have laid out six to seven big challenges that existed at that moment.   And the next word shouldn't be there for it should be. And yet we grew and I'll come back to what we just went through. Imagine in 2019, we had this conversation and we were completely Pressy. And you would have said, Peter, we're going to have COVID, we're going to have a shutdown of a third of the economy. We're going to have riots in our cities. We're going to have Congress, can't get along.   We're going to have a highly contentious election. They're going to be in the Capitol building. What have I missed? Right. Inflation oil prices at a hundred and whatever, a barrel, excuse me. And you would've said therefore, in 2019, if you were completely prescient, you just said, therefore, we can't grow. I'd come back to you and say, Jesse grew three and a half percent. In spite of imagine what we do when we only have a short list of those things.   So I think if I had one message, that's it. And therefore, if you're in the real estate business, you're in the business of satisfying that growth, right? That's what our business is when you come down to it, you're in the business. And so, you know, could there be a bad period, then there's been bad periods. The amazing thing is how short they are and how shallow they are. They don't seem short while they're going on. It's like when you have the flu or COVID, it doesn't seem like short when you got, but when you look back, it's a blip and it doesn't seem that minor.   But when it's done, I had two hip replacements and it was not fun as you're doing it. But, you know, in the big scheme of life, there was nothing particularly same with the economy and its downs.   Jesse (44m 22s): I like that in spite of not therefore. And the reason I was laughing is because I remember two, two and a half years ago being in an office and we were talking, it was right at the pinnacle of coworking and we work. And we just said to the other brokers were like, I don't understand how they can continue to do this. And we said, well, barring, any geopolitical event or global pandemic. I swear to God, somebody said this in the meeting, you know, then, you know, we'll see what happens. And then what happens a year later? And it turns out that, you know, we worked a little bit of a different story, but the office market looks like it's coming back.   Coworking looks like it's going through a shift. But I really liked that in spite of that is a glass half full.   Peter (45m 2s): That would be, if I had one message, I'd hope everybody would take one message. It's not, therefore it's in spite of. And by the way, think about your, I was alive when wage and price controls are going on. Nixon resigned in disgrace. This is the person who had been the speaker of the house a couple of years prior to that is suddenly the president. And by the way, you know, we had just finished Vietnam and, and, and inflation is high and taxes are high.   And we grew over, you know, when you kind of, holy cow, this is a powerful machine. It's an insight of machine. Not as therefore machine. Now, obviously if you get a, therefore, if you get a Venezuela, right. That's, that's when it becomes a, therefore we aren't a Venezuela.   Jesse (45m 55s): Yeah. Well, hopefully we're not, we're not tracking the Boulevard here in Canada or the U S but Peter, in terms of, so I want to wrap up, I want to give listeners a way to reach out. Or if, if anybody wants to connect online before we do, we typically ask our guests a couple of questions, I'm going to make these brief. So if you're okay, I'll send these off to you. They're pretty, they're pretty straight forward.   Peter (46m 18s): Okay, great.   Jesse (46m 19s): For younger individuals getting into our industry, what advice would you give to them?   Peter (46m 24s): Reed, Reed, and then whatever you do read more and then whatever you do read. And the only thing I footnote read to include real podcasts like yours, all right. Real thought podcasts, not just, not just political rant podcast, right? Real podcasts. I try to start every morning while I'm doing a little exercise, listening to a podcast outside of my expertise. And so I would include serious podcast in the read category.   You just want to attain knowledge. You want to attain judgment through others. You want to hear what people who are, they may not be smarter than you, but they've got a different set of experiences. They've got a different set of expertise. They're not necessarily right. Get as much of that as you can, and start building your own tapestry of knowledge and insight, which is all these little stuff. I mean, I really need all of these little threads coming together.   Jesse (47m 26s): So the second ties into the first what's a book. I mean, you, you are the author in our industry. What's a book you would recommend for anybody in our industry or outside in general.   Peter (47m 35s): Well, I mean, it's, self-serving that to a young person, it is self-serving, but I would say my book, real estate, finance and investments, if you were to say, this is also self-serving, but I also believe it in they're going to be dramatic changes in how long people live. So Albert Ratner and Mike Rosen, and I have a book coming out in September called degrade age reboot, and it's going to change. It's going to change. I love to come back as it comes out and talk to you with Dr.   Mike. But when it comes out, it will give you insights on what's going on in modern medicine and what it means for our society. And I give you just a snippet, right? A very tiny little snippet. Imagine genetic engineering could eliminate fat, excess fat. Okay. First of all, medical expenditures would go way down healthcare expenditures. We'd have some number like two to $3 trillion more to spend on other stuff.   What do you want to spend it on? Not to mention that. And I'm just being simple on that one. And there's hundreds of you on that one. Gee, I'd want to short WeightWatchers and go long. And Haagen-Dazs because of anything I eat doesn't cause fat because of the genetic engineering, then bring it on Haagen dies. Right? So, I mean, there's so that now, if you said to me a great book that any there's two books that I would recommend that anybody thoughtful and intelligent, I think should be aware of.   One is called fat fullness, F a C T F U L N ESS, by Hans roster. He's now deceased. That's about three years old. And it's an amazing book that talks about how our images of the world are locked in and not reflective of reality. And the reality is generally much better than we think. And the other along the similar lines, but very different is the rational optimist by Matthew Ridley.   And that's probably about eight, nine years old. But the theme of it is the typical person watching this lives massively better than the king of France, you know, in the 14 hundreds. And you go, wow. You know, I live better than the person who resided in Versailles and he gives much more coaching examples. The other thing I would do, I was a big Hans Rosling fan.   There's an amazing YouTube about four minutes long. And if you put in Han's Rosslyn, F R O S L I N G the world growth explained in four minutes or something like that, it's a four minute video that will leave you feeling good at the end.   Jesse (50m 36s): Yeah. We'll put a link up to that. I think I've seen this one before,   Peter (50m 41s): So, but those would be the two books I would kind of think everybody could read.   Jesse (50m 46s): That's great. Okay. Peter, we're at the end here. Our last quick question, I ask every guest, it's usually more interesting with the, the older guests first car make and model.   Peter (50m 55s): Well, wait, first of all, you asking me, I'm not an old guy. Car was a 19 staff and the American motors corporation, green grim.   Jesse (51m 9s): There's a cottage industry. Now of guys collecting those cars, the gremlins.   Peter (51m 13s): Yeah. Mine fell apart. At some point I got, but I got a good, I don't know, eight years out of it, or seven years out of it, something like that seven years, I guess I got out. So it works.   Jesse (51m 24s): Peter. I really will have to have you back on. I really appreciate the, the conversation today for, for any listeners, aside from the website and the Lindemann letter. Is there any other place that you would kind of point them to online?   Peter (51m 37s): That would be the main place go to Lindemann and associates. You've got links to all the stuff we do there, including our charity, our education charity in Kenya, which is a big part of my wife's denies life. And I take a look at that. It's pretty amazing what these kids do. It's hard. It lifts your spirits and keeps you positive. But yeah, that was just going to lend them and associates you'll you'll find us and feel free to get in touch. Thank you.   Jesse (52m 6s): My guest today has been Peter Lindemann, Peter, thanks for being part of working capital.   Peter (52m 9s): My pleasure.   Jesse (52m 18s): Thank you so much for listening to working capital the real estate podcast. I'm your host, Jesse for galley. If you liked the episode, head on to iTunes and leave us a five star review and share on social media, it really helps us out. If you have any questions, feel free to reach out to me on Instagram, Jesse for galley, F R a G a L E, have a good one. Take care.   ...      

Since 2011, when Bobby Bryant watched IBM Watson play and win against the two winningest players in Jeopardy history, he's been obsessed and intrigued by the possibilities when it comes to voice activated intelligent assistants. That same year(2011), APPLE introduced the world to Siri. It was at that moment he envisioned a multi-model and mobile-first experience for consumers on the go for all of their real estate needs. The ability to list, search, and service any home in the country at the edge of your fingertips and/or voice.   Company Overview: Bobby Bryant is the Co-Founder and CEO of Doss.  A Google-backed startup, DOSS is a voice-activated intelligent assistant designed exclusively for the real estate industry. Their objective is to empower people to speak, text, or type any question about any property in the country to get accurate, easy, and instant answers. Architecturally built on an Intelligent User Interface(IUI), DOSS leverages everything that Artificial Intelligence(AI) has to offer to better centralize, democratize, and humanize BIG DATA in a more intuitive and meaningful way   Timestamps: 2:12  Houston – a budding tech hub 3:44  The early days | Military kid, elite athlete 5:10  From school teacher to real estate millionaire 8:30  How losing it all in the real estate collapse led to tech entrepreneurship 11:30  Working with IBM to build an intelligent assistant 13:53  Bobby's approach to building tech as a non-technical founder 16:48  Building the initial team + selling the vision and creating proper incentives 22:49  What is DOSS?  How does it impact the real estate industry? 29.20  Test out DOSS for free at www.askdoss.com 30:44  Bobby's approach to building out an effective marketplace product and business model 36:39  DOSS traction to date + managing server costs and user growth 44:20  What's up next for Doss? + fundraising goals

Mariano Croce is an Argentine entrepreneur who relocated into Queenstown with his young family just before the first COVID lockdown in 2020. He has a background in prefabrication, having co-founded a modular building company in Argentina when he was 24. More than 15 years on, Mariano has created Modulo.nz to provide architecturally designed, high-performance, modular homes built in New Zealand.

This week, Jeffrey Palermo is joined by return guest, Jeremy Likness! Jeremy is an internationally selling author, keynote speaker, and professional coder with a personal mission to empower developers to be their best! He has worked on commercial enterprise software for 25 years and specializes in web technology. Currently, he is also a Sr. Cloud Developer Advocate for Microsoft, but previously held roles at iVision, Wintellect, and AirWatch.   Last year when Jeremy was on the podcast last, they discussed DevOps automation. In this episode, they focus the discussion on working with data on .NET. Jeremy shares about the work that he had been doing on the .NET Data team for the last year, Entity Framework Core, Microsoft Dataverse, GraphQL, and more!   Topics of Discussion: [:38] Be sure to visit AzureDevOps.Show for past episodes and show notes. [:51] About The Azure DevOps Podcast, Clear Measure, the new podcast Architect Tips, and Jeffrey’s offer to speak at virtual user groups. [1:28] About today’s episode with Jeremy Likness. [1:53] Jeffrey welcomes Jeremy back to the podcast! [2:15] Jeremy gives an overview of his role as the Senior Program Manager working on .NET Data and the work that his team does. [5:37] About Microsoft Dataverse and Jeremy and his team have been working with the Azure Storage and Dataverse teams. [8:28] Of the different methods of working with data in C#, what’s the general distribution? Which methods have greater adoption? [11:17] Jeremy and Jeffrey discuss different .NET project types and whether Entity Framework 5.0 the latest stable release. [11:55] Jeremy shares what is most exciting to him with this upcoming .NET release. [13:25] What’s the go-to store on the client-side? [16:04] The new inheritance strategies in EFCore: are they fully implemented and ready? [19:21] Jeremy talks about the focus on speed for EFCore 6. [21:37] A word from Azure DevOps Podcast’s sponsor: Clear Measure. [22:08] Why developers are “forced” to learn object-oriented programming through EFCore’s features. [24:32] How Jeremy goes about testing code that uses Entity Framework. [27:30] Jeremy highlights where to access invaluable EFCore resources. [28:54] Jeremy touches on how the EF code team uses ReSharper. [29:15] What GraphQL is and why it might be useful if you have a .NET application. [32:40] Jeremy highlights another good QL platform: Hot Chocolate by ChilliCream. [34:06] The architecture of GraphQL and whether it is a database engine or a library. [35:33] If you have a .NET app running in App Service and you’ve already got Azure SQL, and you want to get some of your data and use Graph QL, is this a new Azure resource? Architecturally, what would you do to adopt this? [39:18] Jeffrey thanks for Jeremy for joining the podcast!   Mentioned in this Episode: Architect Tips — New video podcast! Azure DevOps Clear Measure (Sponsor) .NET DevOps for Azure: A Developer's Guide to DevOps Architecture the Right Way, by Jeffrey Palermo — Available on Amazon! bit.ly/dotnetdevopsebook — Click here to download the .NET DevOps for Azure ebook! Jeffrey Palermo’s Youtube Jeffrey Palermo’s Twitter — Follow to stay informed about future events! The Azure DevOps Podcast’s Twitter: @AzureDevOpsShow Azure DevOps Podcast Ep. 76: “Jeremy Likness on DevOps Automation” Jeremy Likness’ Blog Jeremy Likness’ Twitter Jeremy Likness’ LinkedIn Jeremy Likness’ GitHub Jeremy’s Email: Jeremy.Likness@Microsoft.com  GraphQL Microsoft Dataverse Microsoft Azure Storage Blazor OData Entity Framework Core .NET MAUI Uno Platform Docs.Microsoft.com/EF Azure Cosmos DB GitHub.com/DOTNET/EFCOREReSharper Hot Chocolate by ChilliCream   Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

Cinco de Mayo (https://en.wikipedia.org/wiki/Cinco_de_Mayo) Things that bring us joy this week: Nomadland (https://letterboxd.com/film/nomadland/) Wooden Boats: In Pursuit of the Perfect Craft at an American Boatyard (https://www.goodreads.com/book/show/164432.Wooden_Boats?from_search=true&from_srp=true&qid=vYPmsRaQDa&rank=1) by Michael Ruhlman Intro/Outro Music: Notice of Eviction by Legally Blind (https://freemusicarchive.org/music/Legally_Blind) Production assistance by Enzo Dreon

Coffee Sessions #34 with Geoff Sims of Atlassian, Machine Learning at Atlassian. //Abstract As one of the world's most visible software companies, Atlassian's vast data and deep product suite pose an interesting MLOps challenge, and we're grateful to Geoff for taking us behind the curtain. //Bio Geoff is a Principal Data Scientist at Atlassian, the software company behind Jira, Confluence & Trello. He works with the product teams and focuses on delivering smarter in-product experiences and recommendations to our millions of active users by using machine learning at scale. Prior to this, he was in the Customer Support & Success division, leveraging a range of NLP techniques to automate and scale the support function. Prior to Atlassian, Geoff has applied data science methodologies across the retail, banking, media, and renewable energy industries. He began his foray into data science as a research astrophysicist, where he studied astronomy from the coldest & driest location on Earth: Antarctica. --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Vishnu on LinkedIn: https://www.linkedin.com/in/vrachakonda/ Connect with Geoff on https://www.linkedin.com/in/geoff-sims-0a37999b/ Timestamps: [00:00] Introduction to Geoff Sims [01:20] Geoff's background [04:00] Evolution of ML Ecosystem in Atlassian [06:50] Figure out by necessity [08:47] Machine Learning not priority number one and disconnected to MLOps [11:53] Atlassian being behind or advanced? [16:38] Serious switch of Atlassian around machine learning [17:47] What data org did it come from? [20:00] Consolidation of the stack [21:21] Tooling - blessing and curse [24:37] Tackling play out [29:38] Staying on the same page [30:48] Priority of needs [31:55] How did it evolve? [35:12] Where is Atlassian now? [40:21] "Architecturally, Tecton is very very similar (to ours), it was just way more mature." [41:17] What unleashed you to do now? [41:36] "The biggest thing is independence from a data science perspective. Less reliance and less dependence on an army of engineers to help deploy features and models." [44:25] Have you bought other tools? [45:43] "At any given time, there's something that's a bottleneck. Look where the bottleneck is, then fix it and move on to the next thing." [48:20] Atlassian bringing a model into production [50:01] "When we undertake whatever the project is, its days or weeks to go to a prototype rather than months or quarters." [53:10] "Conceptually, you're struggling walking towards that place because that's the place you want to be. If that's your problem, that's good. That's the promised land." [54:45] "Using our own tools is paramount because we are customers as well. So we see and feel the pain which helps us identify the problems and understand them."

BCANCC 08 - Lifestyle Commercial Photographer, Creator of Director and Podcaster w/ Jodianne BeckfordJodianne Beckford (goes by Jo) is a Lifestyle Commercial Photographer, Creator of Director Noire Girls Plant who currently resides in Toronto, ON. She gravitates to the contrasting beauty of black and white but also loves incorporating rich colours and tones like gold, mustard yellows, nude tones, and soft mature palettes. Architecturally she loves simple, linear structures and types that clearly, yet beautifully convey meaning. When architecture is muddled with complexity, timeless design is comprised.She is also the creator and podcast host of the famous The E Project Podcast. The “E” Project is a platform that showcases current & aspiring entrepreneurs. She began this project back in 2015 while living in Ottawa. Jodianne soon realized how many amazing creatives were in the Capital and wanted to share their stories in hopes to encourage fellow creatives. She was curious to know who was doing what, how they did it, and why they did it. Today the project has grown to be so much more than she would have imagined. Just a human with a podcast, sharing human stories to inspire the world.Follow Jodianne Beckford on:Instagram - https://www.instagram.com/jodianne.beckford/LinkedIn - https://www.linkedin.com/in/jodianne-beckford-88200554/The E Project - https://podcasts.apple.com/podcast/the-epiphany-project/id1234030062Visit http://jodiannebeckford.com/ or https://www.noiregirlsplant.com Catch the show on:Spreaker - https://www.spreaker.com/show/bcanccWebsite - https://chonillanetwork.com/series/bcancc/And all major podcast directories. Let's connect on:Instagram - https://www.instagram.com/blackcanadiancc/Twitter - https://twitter.com/blackcanadianccTo interact with Jodianne and fellow creatives, join the community by visiting http://bit.ly/BlackCanadianCC. Peace and keep creating, eh!

Show Notes:Jake BrutonAarow BuildingUnbuildit PodcastThe Build Show NetworkJake Bruton is a builder and remodeler in Columbia Missouri. As the owner of Aarow Building for more than a decade Jake brings his education in art to energy efficient, durable, and architecturally significant homes. Growing up in a remodeling and repair business positioned him for success when building because of the vast amount of time fixing, repairing, and replacing the mistakes of previous methods of construction. All of this repair work has driven Jake to educate himself on building science and learn to apply those ideas to his high performance projects. Jake regularly writes for Fine Homebuilding, Journal of Light Construction, Pro Remodeler, and Pro Tradecraft. He is a weekly contributor to Buildshownetwork.com. As a speaker he has presented at JLC Live, Fine Homebuilding Summit, JLC Deck and Remodeling, and EEBA. Jake is currently raising a family of three children with his wife in Columbia Missouri.

This week we finish our conversation about CONSPIRACY THEORIES

Missouri Botanical Garden horticulturist Susie Ratliff has worked at the center's Climatron since 1997. She'll share tidbits about the geodesic dome's iconic history and all the care that goes into its living collection.

There’s a 20-year age gap between the average Realtor and millennial. Even though millennials now make up the majority of real estate transactions, there’s still a huge disconnect between expectation and reality with the agents on the ground.   Millennials think, function and make decisions differently, and Realtors are conflicted by this new dynamic. Instead of paying attention to the habits of these consumers and adapting what we do, many agents make the process of buying and selling increasingly frustrating.    If we want our real estate businesses to have a long-term value proposition, adapting to millennial clients is non-negotiable. What are the key things millennials are looking for in the process of buying and selling a home? Where are Realtors falling short and what can we do about it?    In this episode, I’m joined by Bobby Bryant, CEO and founder of Proptech company DOSS. He shares how his company is meeting the needs of millennials, and what it takes to be relevant as an agent in today’s world.   Three Things You’ll Learn In This Episode    - Why many Realtors can’t crack the millennial marketThe average Realtor is in their 50s, while the average home buyer and seller today is in their early-30s. There’s a huge disconnect between the two and it’s not just in age. Many Realtors don’t have empathy for millennials, which makes it hard to connect with them or provide a service that addresses their concerns.   - The one thing Realtors keep getting wrongOne of the biggest mistakes Realtors make is thinking the real estate interaction and transaction is all about them. It’s important that we stop trying to shift millennials to do real estate the way we want, and start to shift what we do to suit their expectations. This is the only way we remain relevant.    - How to adapt our listings to the expectations of millennialsFind a way to make your listings evergreen and available for viewings 24/7. This doesn’t mean they have to see the home in person. We can leverage tech tools like virtual tours so buyers can take a look at the home whenever they want to.   Guest Bio-    Bobby Bryant is the CEO and founder of DOSS, a Proptech company that's democratizing the real estate industry via a Digital Real Estate Brokerage that's developing a Voice-Activated Intelligent Assistant built into a proprietary real estate search and transactional platform to empower BUYERS, RENTERS, and SELLERS to ask any question about any property in the world to get accurate, easy, and instant answers 24/7.    Architecturally built on an Intelligent-Interface, consumers are able to access everything there is to know about a particular property by speaking, texting, or typing their questions into any Desktop, Smart-Speaker, and Smartphone to search, schedule property tours, digitally submit offers, negotiate price, and much more.  For more information visit https://www.linkedin.com/in/bobby-bryant-53249610 or email bobby@askdoss.com. You can also follow @realbobbybryant on Twitter.  

We sit down with Kelly Swan, one of the finest architects in our market.  If you've ever considered building a dream home or are planning an addition, I know you'll find this interview interesting and informative.  You can find Kelly online at www.architectks.com, email him at getstarted@architectks.com and his mobile 385-265-2663.  

The crew gets feedback on door bevels and heat pump water heaters before taking questions on matching moldings to a house style, converting a seasonal cabin to year round use, and what to do about Sawzall-wielding plumbers.

Matt Mitchell is the lead engineer of the .NET Core Engineering Services Team at Microsoft. Matt joined Microsoft in 2006 after two years as an intern from 2004-05. Right out of the gate he did all C++ Compiler work for about 8 years. Eventually, his work morphed into working on the opensource infrastructure for .NET Core — which is what he’s doing now!   In today’s episode, Jeffrey and Matt are taking a look into DevOps on the .NET Core Engineering Services Team! Matt dissects what Engineering Services is and what they’re responsible for, some of the different system types within .NET Core, an overview of the .NET Core infrastructure and how they go about building and testing, and much more! Tune in to hear all of Matt’s key insights around .NET Core and the Engineering Services Team.   Topics of Discussion: [:39] Be sure to visit AzureDevOps.Show for past episodes and show notes! [:48] Jeffrey gives a few quick announcements. [1:00] About today’s guest, Matt Mitchell! [1:20] Jeffrey welcomes Matt on to the show! [1:26] Matt speaks about his career journey and how he landed his current position at Microsoft. [3:02] Matt dissects what Engineering Services is, how it differs from .NET Framework Engineering Services Team and other teams, and what exactly they’re responsible for. [6:16] How many Git repositories overall make up .NET Core? And how do they organize that? [13:58] Matt explains some of the different system types within .NET Core. [17:11] With having 20 repositories now, does Matt foresee an event where they might have to introduce a 21st repository? And does his team provide guidance on how that would need to be set up if that was needed? [20:05] A word from Azure DevOps Podcast’s sponsor: Clear Measure. [20:30] Jeffrey makes some announcements about upcoming events! [21:09] Matt provides an overview of the .NET Core infrastructure and how they go about building and testing. [26:00] Architecturally, the MS build tasks are the way that individual teams are provided with the tools to call so they don’t have to duplicate that logic in their build scripts. So, for YAML files, is it just template guidance but that logic is duplicated in each repository? [32:20] Matt explains why choosing the right number of repositories is one of the biggest ways to absolve some difficulties. [35:16] Matt provides some examples of content-based systems. [38:19] Matt recommends some resources to check out after listening to this week’s podcast!   Mentioned in this Episode: Azure DevOps Clear Measure (Sponsor) .NET DevOps Bootcamp 2020 — January 16th & 17th in Austin, T.X. .NET DevOps for Azure: A Developer's Guide to DevOps Architecture the Right Way, by Jeffrey Palermo — Pre-order on Amazon here! bit.ly/dotnetdevopsebook — Click here to download the .NET DevOps for Azure ebook! bit.ly/dotnetdevopsbookforcommunity — Visit to get your hands on two free books to give away at conferences or events! Jeffrey Palermo’s Youtube Jeffrey Palermo’s Twitter — Follow to stay informed about future events! “The Evolving Infrastructure of .NET Core,” by Matt Mitchell (on the Microsoft .NET Blog) Announcement of .NET Core Repository Consolidation Timeline for Runtime Repository Microsoft Phoenix Midori Roslyn CompilerBuildXL GitHub Repository   Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

Jodianne Beckford (goes by Jo) is a lifestyle commercial photographer who currently resides in Toronto, ON. She gravitates to the contrasting beauty of black and white, but also loves incorporating rich colours and tones like gold, mustard yellows, nude tones, and soft mature palettes. Architecturally she loves simple, linear structures and types that clearly, yet beautifully conveys meaning. When architecture is muddled with complexity, timeless design is comprised. Not only is she all of these amazing things, but she is my friend and little sister. I love and respect her voice in this culture. She represents both internal strength and the realities of being a misunderstood creative. I hope that her story changes you, challenges your perspectives, and gives you the motivation to share your story. #TheDigitalStoryteller #TorontoFilmLife #StoryOverEverything Subscribe below. Thanks! Follow me on... Instagram: https://www.instagram.com/tristanbarr... Facebook: https://www.facebook.com/TristanBarrocks Twitter: https://twitter.com/tristanbarrocks Send me a message with your questions to me at Hello@TristanBarrocks.ca Website: TristanBarrocks.com

EP30 brings us Masters  Paolo Benedetti and Rick Chafey discussing Architecturally Integrated Water Elements and Complex Swimming Pool Construction.  This episode has been brought to…

Before he became King of England in 1603 James I had never set foot in an English royal palace. What he found when he did was a mixed blessing: he may have liked the grandeur and riches, but he hated the stuffy formality. His answer was to create an entirely new sort of country residence devoted to hunting, reading and relaxation with his male favourites. Architecturally incoherent these places may have been, but James's remarkable forgotten country houses tell us a huge amount about the man and the dawn of the Stuart age.A lecture by Simon Thurley CBE, Visiting Professor of the Built Environment 18 September 2019The transcript and downloadable versions of the lecture are available from the Gresham College website: https://www.gresham.ac.uk/lectures-and-events/the-court-at-playGresham College has been giving free public lectures since 1597. This tradition continues today with all of our five or so public lectures a week being made available for free download from our website. There are currently over 2,000 lectures free to access or download from the website.Website: http://www.gresham.ac.uk Twitter: http://twitter.com/GreshamCollege Facebook: https://www.facebook.com/greshamcollege Instagram: http://www.instagram.com/greshamcollege

For over 47 years, HH Architects has provided Architectural, Interior Design, Strategic Positioning and Master Planning services to clients ranging from churches to municipal entities to schools to corporate buildings. They approach projects from the client’s perspective and by building upon your image and identity, HH Architects strives for creative solutions that meet the Project’s scope, schedule, and budget. Bruce Woody President/CEO, HH Architects, Dallas TX

Dan Head (CRO) and Robbie Matthews (Director of Integrations and Onboarding) join me in foggy Londontown to chat about the evolution of marketing, from old world email and DMPs to flexible architecture that is channel agnostic. Learn the nitty gritty of why new school tech is leaving legacy clouds in the dust. Dan also hints at a future of talking toothbrushes and Robbie shares his data dreams.        TRANSCRIPT: [0:00:17] PJ Bruno: Hello again. Welcome back to Braze For Impact, your weekly tech industry discussed digest. This week, we're here in London, in our London office and I'm thrilled to have with me two close friends, Dan Head, Chief Revenue Officer at Braze. Hey Dan.   [0:00:33] Dan Head: Hey PJ. It's good to see you.   [0:00:35] PJ Bruno: And also, Robbie Matthews, Director of Integrations and Onboarding. Robbie, how you doing?   [0:00:40] Robbie Matthews: Good, how are you?   [0:00:41] PJ Bruno: I'm quite well. And I know it's a bit of a canned response, but I got to say, the weather's unbelievable here. I've been getting all this bad intel about bad weather and this is unreal.   [0:00:51] Robbie Matthews: You got a British tan?   [0:00:52] PJ Bruno: Yeah, exactly. I don't know how. I literally got sunburnt yesterday. It's ridiculous.   [0:00:57] Robbie Matthews: It's all lies. Fake news.   [0:00:59] PJ Bruno: Well, you know, coming into Easter weekend, how you guys feeling? Happy Easter, by the way. I don't know if you guys celebrate. Plans for the weekend? Any...   [0:01:08] Robbie Matthews: We tend to celebrate confectionary throughout the year, anyway. So, we can eat chocolate eggs this weekend, too.   [0:01:13] PJ Bruno: I notice in the lobby, there. You guys are loaded up. What we're going to talk about today, really, it's kind of like the evolution of marketing technology and more than that, we want to demystify a lot of the things. Because you hear a lot of snap terminology, a lot of jargon, but let's actually break it down and understand what we're talking about, using the facts. And, before we jump in, I love... you know, Robbie, I know you eat, sleep, and breathe data, or so says your girlfriend.   [0:01:42] Robbie Matthews: I thought you may bring this up.   [0:01:45] PJ Bruno: Yeah, can you just give us that anecdote really quick?   [0:01:49] Robbie Matthews: So, Dan's already smiling at me.   [0:01:53] Dan Head: I'm not familiar with this one.   [0:01:54] Robbie Matthews: So, I was sleeping the other day and I woke up and my girlfriend was just staring at me, like a puzzled face. I was like, "Why are you looking at me whilst I'm sleeping? Firstly, that's a bit weird." And she was like, "Do you realize what you've been talking about for last two minutes?" And I was like, "What you talking about?" She said, "Oh, you've just been sleep talking about, like, piping data into various places and where you should send data to, and this is how you send data." And I was like, "I need to get some better dreams."   [0:02:23] Dan Head: Need to cash in that brace therapy reimbursement.   [0:02:25] Robbie Matthews: Or she needs to find a new boyfriend, is what she needs to do.   [0:02:29] PJ Bruno: Well, that's her journey and that's for her to decide. But, anyway, I'm glad you were able to share that with us, thanks bud.   [0:02:35] Robbie Matthews: Thanks, PJ.   [0:02:36] PJ Bruno: Yeah. So, let's jump right into it. Best place to start, where we came from as far as marketing tech. You know, Dan, you're old. Why don't you tell us...   [0:02:48] Robbie Matthews: Everybody says that.   [0:02:51] PJ Bruno: But you still look so good. We were saying, "Tell me your moisturizer, because I need to get some of that."   [0:02:55] Robbie Matthews: What's a face care regime?   [0:02:56] Dan Head: I'm embalmed.   [0:02:57] PJ Bruno: Yeah. I just let snails crawl over my face every night. It's a beautiful thing. So, how do we move from email to the concept of a stack, or an ecosystem. Do you think you can talk about this a little bit, Dan?   [0:03:10] Dan Head: Yeah. I think it goes back to the perspective that businesses have had on just these technologies from the ground up. Historically, I think companies have looked at providing communications on channels like email as being a utility. You know, you set up a business, I need seats and chairs and desks. I need water coming out the taps and electricity. And I need a way of sending email. And, when the marketers have wanted to have these tools to communicate to their customers, they've asked the IT teams to provide this technology, and the IT teams have gone out and procured that technology. So, over time, a stack of tech debt has built up, if you like. By acquiring these utilities, acquiring technologies for these channels and finding ways to stitch all of that together. Which is, if you like, a ground up, let's just go get the bricks and build the house, sort of thing. But, unfortunately, the world's different now, because every year, CES throws millions of new channels at us, you know? It's connected wind screens, it's connected forks and toothbrushes and all sorts of other crazy stuff. And, businesses just can't keep acquiring channel specific tech anymore. It needs to be data centric, it needs to be customer centric. Because, all of us as individuals have got our preferences about how we want to communicate with brands. And so, now we're moving away from a utility plumbing based approach, to a customer centric data oriented approach. And, that is how, I guess, the modern concept of a vertically integrated stack has been born.   [0:04:55] PJ Bruno: Yeah. And, obviously there's these advances in technology, we're going way more mobile, right? But, there has to be those that are lifting up the torch and kind of pushing us forward. And putting that pressure on legacy, right? You called them the role models, yesterday.   [0:05:12] Dan Head: That's right. Because there are businesses that have been born into this new environment. When you order your on demand taxi, or you order your on demand pizza take-away, whatever, when you're looking for a date, these are technologies and services that haven't existed previously. They've been born into the device. And, you look inside those companies, and the teams and the people and their KPI's and the technology, it's completely different from a legacy enterprise business. And, if those companies don't get customer orientation and data driven communication correct, it's an existential problem for them. They haven't got another business model to fall back on. And so they become, and this is why I see them as role models, they become role models for more classic enterprises. And, that would be my advice to any long standing enterprise, is to go look at those companies and see how they do it. It's a good place to start.   [0:06:10] PJ Bruno: Do you think they're actually, these bigger legacy companies, do you think they're actually interested in completely reworking their tech? Or does it feel like stitch up solutions to stay relevant?   [0:06:23] Dan Head: I think in big companies, big enterprises, I think there are a bunch of political reasons why it makes sense and it's safe to stay with the status quo, you know? If the CEO or CIO says we're going to do this one particular way and we've got our IT standards. And, I work in the CRM team and I know the tech doesn't work, well, I'm only going to have so much appetite to stand up against those folks because at the end of the day, I want to get paid.   [0:06:48] PJ Bruno: Right, right.   [0:06:48] Dan Head: Right? But, I think at some point, and I appreciate the political importance of standards and doing what the bosses say. But at some point, the political importance of customer experience and the political importance of driving outcomes with those customers, I think, is more important than the politics of IT standards, and so on. And businesses eventually figure that out. It's just part of their evolution. And one of the factors that we see, which I think is a good indicator is, where businesses have taken the CMO role and the CTO role and then they've sort of adapted it. And now you see this emergence of the CCO, or the chief customer officer role, where the customer officer has got a greater stake and influence on tech decisions. Because it is literally customer oriented. That tends to be a good indication of that evolution is fairly well progressed.   [0:07:39] PJ Bruno: Yeah. You mentioned customer experience. It's funny that now it all kind of just comes back to that. It's like there's this strength in tech, but really it's ideating towards the customer. And so, my question, I guess, to you is, what is customer experience actually mean now?   [0:07:57] Dan Head: Yeah, just use some examples. We all use these role models, these new technologies, and so on. But, I'm reminded of a quote from Keith Weed, the current, or perhaps former, because he's leaving, CMO of Unilever, he had this expression, "You know, our job as a brand is to get to the future first, and welcome our customers as they arrive." And most enterprises-   [0:08:23] PJ Bruno: That's a great quote.   [0:08:23] Dan Head: Yeah.   [0:08:24] PJ Bruno: That's a strong one.   [0:08:25] Dan Head: I dig that one up a lot. Yeah, I like that one. Most enterprises, I think, are just trying to catch up with the current world. Let alone the future world, so just as an example: If I'm driving down the highway and maybe I would fancy a coffee. And let's say, the folks at Costa Coffee, this business acquired by Coca Cola, they want to send me a notification to say, "You're coming up on a service area and there's a Costa and you can get a deal on a cup of coffee there." Well, I'm driving, there's no point in them sending that to me on my phone. But, as we saw at CES, there are technologies like connected windscreens and there's more connected computing in cars now, anyway. So, there are opportunities for Costa to send that message to me on these new devices. Which would be a more appropriate way to deliver it. But, brands just aren't ready for that. Because brands are channel centric, they're not data centric, they're not customer centric. They're not able to make the most of these technologies as and when they emerge. And, as a result, therefore, they can't be customer oriented.   [0:09:31] PJ Bruno: Right. And since it's all about the customer experience, right, you want to make sure that you're not abusing that use of data, right? So, we live in now, this world, it's a wash of data, right? It's all over the place. It can be collected. So, why is effective and responsible use of data important to what you do?   [0:09:51] Dan Head: Yeah, I mean, of course we've had laws like GDPR and then there's going to be the California Data privacy laws coming in. And the world is realizing that this is... Brand connection with customers is about trust. And that comes through the responsible use of data. So, it's not that there are just new legislative frameworks, which make it law that we have to be responsible. But it's just the basis of good marketing, anyway. And so, the technologies that need to be adopted here, need to enable the marketer to use data effectively, at the right place, at the right time, to seek permission. And to act on that permission and behavior that is being granted and communicated by the customer. It's like a conversation. There have been studies, like the one Forrester released on the brand humanity index about the effect of, and the positive effect of talking to your customers in a human way. And what talking in a human way actually consists of. So, it's not just law and legislation that makes us a necessity, these are the ingredients of delivering positive outcomes.   [0:11:03] PJ Bruno: Right. A human touch is super important. And, now also, more than ever, the stack and the technology is really important. And I remember, you said yesterday, the term you used is, "Architecturally enabling", right? And so, Robbie, you're a little more on the technical side. So, from your perspective, from these role models perspective, even, what are the fundamental engineering building blocks that are architecturally enabling versus those that are somewhat prohimitive.   [0:11:38] Robbie Matthews: Yeah. If we start at looking at these traditional enterprise businesses, and typically they're built on relational databases as a foundation. And then we take an example of what Dan's mentioned of these role models, which are using document based storage as a foundation. We can look at what those are and then how they actually enable what you need to send to customers. So, firstly, just what is a relational database? It's essentially a storage of data that's organized into tables. And each of those tables has a very rigid, defined schema. And what you need to do with that, is be able index it, to be able to say, "Okay, I've got this data in one table, how do I join it to another data in another table." And Dan mentioned tech debt, earlier. And that's a big issue. So, if we take a client like Deliveroo, you can say, "Okay, what sort of data have they got?" They've got their user data, they've got all their purchase data. Maybe have reviews that they've left about you. Favorite restaurants. And that all exists in different tables. And as the landscape becomes more complex, you're going to only increase the amount of data you want about users and the environment they're operating in. And that's going to create tech debt. So, what does that actually mean for a brand, when you come to wanting to send messages and target and talk to your users in a human way? And, really, the first thing is agility. If you've got an ever increasing amount of data that you need to join together when you want to create a segment to target those users. That becomes a much, much harder piece to actually stitch those data tables together, access the data in a quick way and define the messages and the audience that you want to send to your users. So, what do brands actually want to do? They want to use that data. They want to define customer audiences. They want to send individualized messages based on any kind of behavior around a customer, like demographics, location data, contextual data. And as soon as you need to index all those tables, or predict what a customer is going to want to do with your platform, which is the tough thing. We can't predict what customers want to do, that changes every day, as new technologies get introduced. As breaking news happens, you're going to want a segment or an audience that we just can't predict. And as soon as you need to rely on the indexing and the schema to access that data, we lose the ability and the agility to do that, in such a rigid manner, which is what the databases in these relational databases require. So, how, I guess a MongoDB or document based storage actually solves that, is, firstly, it's a schema less database. So, we can define exactly how we want to structure data to support these customer requirements. Using documents, as opposed to a relational schema let's us model very complex objects. And then, due to the structuring of that data, we don't need to make those joins and stitch all the data together in this increasingly complex landscape. So it means customers can make a heap of customized segments, off the cuff, and really give them the agility to create these audiences, send out campaigns as they wish.   [0:14:57] PJ Bruno: And that's all around like free flow of data, right? Because, relational is a lot more stringent. It needs to be set up in a way... I mean, that's kind of what I'm hearing, is...   [0:15:10] Robbie Matthews: I guess there's two parts to that question. There's one is speed in the context of a database. And then, I think when you're talking about free flow of data, that's probably where we want to look at more around ETL processes and Kafka. So, maybe let's touch on the speed in relation to relational and document based storage and then we can come onto Kafka and ETL processes.   [0:15:31] PJ Bruno: Okay.   [0:15:31] Robbie Matthews: So, in speed... As you say, customers just demand customer engagement platforms to run fast. Customers demand it. If you need to send out a break in push, ABC wants you do that as fast a possible. And, really, that's about read and write throughput on your database. So, let's take an example where you have to, like in a relational database, where you need to make a number of individual queries, join different tables, and that could take days to produce the results. Whereas, a no seek with MongoDB style database allows you to run queries in parallel, break up your dataset, run higher number of queries, and get that data back almost instantly. So you get those audiences that you want to target much, much quicker. Yeah, so that's the speed element on the relational database versus MongoDB. The second part of your question about ETL versus Kafka and the streaming is, again, like, "How do I actually access that data, or upload my, data into my data warehouse?" Think previously, Dan mentioned utility. Like they way that brands store data has just changed. Various data from different DB's could be loaded into a master data warehouse, once or twice a day. And that's fine. However, let's take the example of Deliveroo. I don't care to admit how many Deliveroo's I order a day. But, they need to know if I've made two this morning, or one this afternoon. And they don't want that upload of data to happen 24 hours later. And to get told that I actually made three orders in the last day. They want to know about that as soon as it happens, be sent to them as that event takes place.   [0:17:19] PJ Bruno: Right, but you don't want to know that you've ordered three times in one day?   [0:17:21] Robbie Matthews: My waistline doesn't want to know that I've eaten three times in a day, but that's a different story.   [0:17:27] PJ Bruno: It's for another podcast.   [0:17:30] Robbie Matthews: So, ETL versus parallel stream processes. And, what that parallel stream processing does, is essentially sets up a queue of events as and when they happen. Then you can listen to those events, publish those events and then essentially subscribe and act upon those events as and when they happen. So, let's take an example of a train booking company, a UK train ticketing company. Where, if I make a purchase for a journey later today, in the ETL world, that upload may happen tomorrow. In which case, I've already missed my train. I've missed all of the communications around it. It doesn't help. In the Kafka world, as soon as that event purchase takes place, you, as a business can act on that purchase immediately, send information about when the train is, any delays about that train. And make sure that user has a good experience with your brand. But, like I said, in the ETL world, I've probably already missed my train because it left the station 30 minutes late. And then the data was only sent to you as a business, to act on the next day.   [0:18:34] PJ Bruno: Yeah.   [0:18:38] Dan Head: This term, real time, I think is sort of used and abused and misunderstood. Like the examples that Robbie just used about travel, timing, of course it has to be real time. It has to be in the moment, otherwise, you're going to miss your train. You're going to miss your taxi, whatever. And, those examples apply to all other businesses, as well, right? Because again, this interaction between a brand and a customer, in order for that to be human, it has to be current. It has to be up to date, based on information that is relevant right now. So, as an example, let's say, I'm on the train and I'm on the way to work and I'm browsing for some sneakers on my mobile web, on my phone. And I add some things to my cart, but I don't transact and then I get to work. And I nip out for lunch and I actually go an buy those sneakers in store. But, maybe there was an abandoned cart email scheduled for 2:00 PM. And that abandoned cart email is still going to come out at 2:00 PM, it's not going to be cognizant of the fact that I went into the store and I bought those sneakers at lunchtime. So, that is a bad customer experience.   [0:19:52] PJ Bruno: Right.   [0:19:53] Dan Head: Or, just to continue that example, if I'm one of those companies that does sneaker drops, and there's a limited amount of inventory at a particular location. The communications can and should be based on that inventory dropping, you know? Create that exclusivity and that need and that excitement, which is what the sneaker drop is all about. And, I guess what Robbie's talking about is, unless you've got a database structure that can make and broadcast, or make available data in real time elsewhere in your technology ecosystem. Unless that data's being distributed in real time, you can't enable those use cases and you can't satisfy that need for a good, premium customer experience.   [0:20:38] PJ Bruno: And the value of that is just less and less as time goes on, right?   [0:20:42] Dan Head: Yeah, exactly. So, I don't really want to know tomorrow that the sneaker drop inventory has run out, you know?   [0:20:50] PJ Bruno: Just creating the opposite of good experiences?   [0:20:52] Dan Head: Right.   [0:20:53] PJ Bruno: It's just frustration. I'd rather just get nothing, right?   [0:20:55] Dan Head: Right.   [0:20:55] PJ Bruno: I'd rather not even see it. All right, cool. Why don't we do something fun and round up with, I mean, you were talking a little bit, Dan, about toothbrushes that talk to you. I want my toothbrush to talk to me so badly. I have to just talk to myself at the time. But, what's the future hold? What kind of last words do we want to put out about, maybe predictions we might have, or a word to the wise about a good strategy, or just some advice to keep in mind moving forward.   [0:21:29] Dan Head: I think there's two angles, to look at it from a customer's perspective. Speaking about myself, I mean, there are always new devices and new technologies and some of us are going to be quicker on the adoption than others. But, as a population now, we are more tech savvy than ever before. More willing to try technologies more than ever before. We have an expectation of being delighted more than ever before. We're willing to kind of experiment and try stuff. And, from a brand's perspective, how on earth are you going to deal with that? So, brands just need to future proof themselves, they just need to be data centric. They just need to have the engineering horse power. They just need to have the developed muscle groups, the ways of working, the team structures based around what's possible with real time data. And then, whether it's that toothbrush talking to you, or the fork telling me that I'm eating too quickly, you know? Whatever it is, the brand can deal with that. And, I think ultimately, where brands are trying to get to, is there should be this ability to be creative and playful with technology. We shouldn't just be worried about the plumbing, "Oh no, I've gotta send a message on this channel now, rather than that channel because of this new device's come out." If we can use any channels, anywhere at anytime, based on current data, then we can really use that as a creative canvas for just amazing, delightful, surprising marketing. And, that's the kind of thing that we, as a population, kind of enjoy. We don't enjoy stuff that's irrelevant, we don't enjoy stuff that we haven't opted in to. But we are willing to be surprised and we are willing to be engaged if we think the brand is making an effort to do so.   [0:23:22] PJ Bruno: I love it. Robbie, you got anything?   [0:23:25] Robbie Matthews: I think that, I'll bring it back to the architecture, to Dan's point around what brands want to do. You want you customer engagement platform at the point you're ready to use sort of surprise and delight strategies that Dan's talking about in reaching customers. You want your engagement platform to be ready to allow you to do that. And not still be developing itself. And, the way its architected, and the way it's able to meet the marketplace's changes is going to be crucial. So, I mean, WWDC happens, Google IO happens, there's a heap of changes to how you can send messages to users. And your engagement platform has to keep up to date with that. So, how they're architected, how they're able to be flexible to meet the new abilities of these OS's, is crucial. And when you look at, again, going back to the sort of, if you want to make joins, create new tables, that's tough to do. And then you have to look back at your current architecture and work out how you stitch that onto the end. Whereas, we take this example of something like a push carousel, where you send a push and you can swipe through a number of images to that. That came out last year. And just the way we were architecting meant you're able to immediately respond to what is new in the market, and give the brands the ability to go out and use that, as and when they're ready.   [0:24:48] Dan Head: Yeah, and we've talked about food quite a bit here. Maybe it's because it's coming up to lunchtime and it's all on our minds, right? But, an example that just brings all this together for me, I think some of us have seen it, which was recently Burger King ran a campaign where they hijacked McDonald's branches and if you got within 600 yards of McDonald's, you would get a message on your Burger King app saying, "You can now redeem a Whopper for one cent." And it would direct you to the Burger King. And it was this cheeky, creative, just technology embracing campaign that got so much attention, they got to the top of the App Store. I mean, how crazy is that? That a burger app can be higher than Instagram and YouTube on the App Store. It's just-   [0:25:37] PJ Bruno: Well, burgers are future proof, Dan.   [0:25:39] Dan Head: They are. And, particular popular where you're from, huh, PJ? But what a great example of creativity with technology. That campaign wouldn't have been possible unless you had the technology in place that Robbie was talking about. And then, once you've created that surprise and delight, now you've got so many more people that are engaging with your brand, that have downloaded the app. And now you can really start to go and have fun with them.   [0:26:04] PJ Bruno: Totally. Well, Robbie, Dan, thank you guys so much for being here. And thank you all for joining us. Just remember Shift is happening. And Legacy Clouds, in the words of Dan and Robbie, don't miss the train. [0:26:17]

Phil Haack joins the podcast to discuss DevOps at GitHub!   Phil has an interesting and extensive career background. He started out as a Manager of Software Engineering back in 1997. Since then, he’s done a lot — but some of his recent highlights include: being the main Program Manager at Microsoft from 2007-2011 (responsible for ASP.NET MVC and NuGet), and leading the Client Apps team as Director of Engineering at GitHub. Now, most recently, he has founded his own company, Haacked, which he started to mentor software organizations to be the best version of themselves.   In today’s episode, your host, Jeffrey Palermo, and Phil Haack, dive deep into discussing DevOps at GitHub. They talk about his role as Director of Engineering; how GitHub, as a company, grew while Phil worked there; the inner workings of how the GitHub website ran; and details about how various protocols, continuous integration, automated testing, and deployment worked at GitHub.   Topics of Discussion: [:48] About today’s episode with Phil Haack. [1:10] Phil talks about how he became the Program Manager at Microsoft in charge of ASP.NET MVC and NuGet, and what the role entailed. [4:00] The transformation Phil helped lead that continues to affect .NET developers today! [5:35] Phil shares the high points of his career at GitHub. [7:56] How Phil’s role at GitHub developed, and how (and why) GitHub went from “no managers and no meetings” to hiring on managers and starting meetings. [12:10] When did GitHub start to distribute regionally? [13:43] How many leased offices did GitHub crop up while Phil worked there? [15:25] What Phil is currently working on since leaving GitHub! [17:27] About the new book Phil is writing about GitHub. [20:07] Major strategic decisions and key aspects that gave GitHub the ability to put out features at a really fast clip for a really long time (with an incredible quality track record to boot!) [24:18] A word from The Azure DevOps Podcast’s sponsor: Clear Measure. [24:44] Architecturally, is GitHub.com one website or essentially two hundred different web applications that make up all the URLs of the website? [26:50] Was there a standard pipeline structure that GitHub maintained (or a common set of steps), or was it moreso a ship-it-however-you-can protocol per service? [27:50] If Phil had multiple services in the client application, did he have a separate Git repository for each one of those, OR, one Git repository for his team with multiple, independent services? [29:52] Did every continuous integration build have its own Git repository? [32:30] What types and quantity of automated testing did Phil pack into the continuous integration (CI) build? [33:48] Phil highlights some significant things that happened in the CI build step. [34:31] Did Phil find any good frameworks that worked out in the UI space? [35:02] What an automated test can’t tell you and why it’s so crucial to have a really good tester! [36:15] When they did have automated deployment between environments, what tools and methods did Phil use for those deployments? [38:04] For the services they were going to deploy to GitHub servers, how many environments did Phil set up in the deployment pipeline ahead of production? [41:07] The major tools on the deployment side when Phil was working at GitHub. [43:44] What Phil recommends listeners to follow-up on to continue their research!   Mentioned in this Episode: Azure DevOps Clear Measure (Sponsor) Phil Haack (LinkedIn) Haacked MVC Framework GitHub for Dummies, by Sarah Guthals and Phil Haack Hubot Ruby on Rails Scientist.NET Electron ChatOps   Want to Learn More? Visit AzureDevOps.Show for show notes and additional episodes.

Phil Irish makes paintings that are both fierce and beautiful. He is known for cutting paintings into fragments, and installing those pieces to make architecturally scaled collages that engage your senses and your mind. Ontario artist, Phil Irish, has taken some dramatic turns in his creative practice.  Very much a painter, he began to scale up his work to an immersive scale. Creating painterly collages that interact with architecture has opened up new opportunities and collaborations.  These shifts have also involved rethinking business aspects of his work, from venues to funding.  With the ecological and spiritual themes that underlie his work, artist residencies have also been a critical research opportunities - including the Banff Centre and on an arctic icebreaker. Phil Irish holds degrees from York (MFA) and Guelph (BA). His work has been shown at public museums, artist-run-centres, and commercial galleries across Canada, and in touring group exhibitions in the USA.

A nouveau-cream wave of ice cream debuts at Coachella, and everyone freaks out.  Side Hustle School features a new story EVERY DAY of someone who started a hustle without quitting their job. You’ll learn how they got the idea, how they overcame challenges along the way, and what the results are.  Share: #SideHustleSchoolShow notes: SideHustleSchool.comTwitter: @chrisguillebeau Learn more about your ad choices. Visit megaphone.fm/adchoices

Ambrosus is a decentralized IoT network for next-generation supply-chains. The company is building a universally verifiable, community-driven ecosystem to assure the quality, safety, and origins of products using blockchain technology. Ambrosus’ primary focus is on improving supply chains for life-essential products, specifically food and medicine, although the protocol can be applied to almost any complex supply chain. "Architecturally, our eco-system will allow businesses to seamlessly connect with one another, in order to improve supply chain efficiency, transparency, and security."   Founded in 2017 by Angel Versetti and Dr Stefan Meyer, Ambrosus seeks to set the global standard for decentralized supply chain management and provide quality assurance in enterprise IoT ecosystems. With offices in Switzerland, Ireland, and Estonia, Ambrosus boasts partnerships with significant global bodies and associations including the United Nations 10YFP, the Crypto Valley Association, Swiss Food Research, Enterprise Ethereum Alliance and Swiss Coffee Alliance. I chat with Angel Versetti, CEO, and Co-Founder of Ambrosus about his vision and bringing efficiency, transparency, and security to global supply chains.

Show: 23 Show Overview: Brian and Tyler talk with Christian Posta (@christianposta, Chief Architect, Cloud Application Development at Red Hat) about the evolution of SOA and Microservices, Envoy Proxy and Istio Service Mesh, emerging application patterns, and how Kubernetes and Istio are the future of microservices. Show Notes:Istio HomepageEnvoy ProxyIntroduction to Modern Load-Balancing and ProxyingMicroservices: From NetFlix OSS to IstioMicroservic’ing Like a UnicornChristian’s Blog (lots of Microservices stuff)Topic 1 - Welcome to the show. Give us a little bit of your background as a developer and history of working with various development frameworks/languages/concepts.Topic 2 - Let’s start with some basics - as a development paradigm, why are we now seeing technologies like Istio and Envoy? The premise of service mesh “reliably connecting services across the network” sounds eerily similar to what we heard about ESB technology. Can you say some words about why this service mesh concept idea is different? Or is it?Topic 3 - So we’re seeing a need to decouple the application code from the routing-level logic and control. Walk us through the types of things that Istio and Envoy are providing for applications? What are the performance implications of the service mesh? How is this related to API management? Topic 4 - Architecturally, where are you seeing some of the advantages of Istio / Envoy vs. either previous approaches, or some other service-mesh like projects in the market? (e.g. linkerd, Netflix OSS projects) Topic 5 - What are some specific problem examples that people run into that should make them think “maybe I need Istio”?Topic 6 - Where is Istio in its maturity to run in production? Feedback?Email: PodCTL at gmail dot comTwitter: @PodCTL Web: http://podctl.com

Architecturally planned EDD car communities are underway, apparently! Or so, that seems to be the case for Simon in LA, who is racing to buy a fun car for his 3rd garage space before his wife fills it up with stuff. The guys talk about vintage choices for Mark and his golden retriever, and wrap up the hour talking about design for bland cars, eating in cars and does Todd still love his Elise? Thanks to you for listening and watching! Rate & review the podcast, and write to us at everydaydrivertv@gmail.com or www.everydaydriver.com

The second lap of MRelay was Play. What can be learnt from seeing Melbourne as a playground? Recent decades have seen a rise in playful practices in the public spaces, ranging from street art to skateboarding to parkour. From flash mobs to urban gardening. From performative interventions to location-based digital games. In social frameworks how can play be used as a tool to promote inclusion, and improve and increase life opportunities and boost community morale? Architecturally, how can the concept of play trigger us to rethink traditional urban infrastructure and address important social issues and challenges by creating new experience and new situations? How does being playful capture imagination and trigger creativity in public spaces? These were some of the talking points our speakers set out to to explore—namely the intersection between social engagement, interpersonal relations and the environments we inhabit. 'Play' was hosted by Christian Thompson, Australian-born London-based artist. Speakers include Mary Featherston, famed Australian designer; Natalie Thomas, Melbourne-based interdisciplinary artist; Amani Naseem, internationally acclaimed artist, researcher and games culturalist; Linda Sproul, manager of education and community programs for Museum Victoria; Rob McGauran, urban designer and architect; Bruce Gladwin, Australian artist, performance maker and theatre director; and Scott Price, ensemble member of Back to Back theatre.

Aaron and Brian talk to Chip Childers (@chipchilders, VP of Technology @CloudFoundryOrg) about the current status of Cloud Foundry projects, how Microsoft .NET will be integrated, IaaS vs. PaaS, and the CF.org thinking about overall interoperability Interested in the O'Reilly OSCON? Want to register for OSCON now? Use promo code 20CLOUD for 20% off Details to win an OSCON pass coming soon! Check out the OSCON Schedule Free eBook from O'Reilly Media for Cloudcast Listeners! Check out an excerpt from the upcoming Docker Cookbook Topic 1 - From an overall project perspective, what grades would you give Cloud Foundry in terms of stability, core functionality, security, operations, etc? Topic 2 - You were previously involved (directly/indirectly)with CloudStack. As you talk to people in the marketplace, how is it different discussing IaaS vs. PaaS. Topic 3 - How much ability will you have to drive prioritization within sub-projects or new projects? (eg. Security vs. new Languages vs. Interop, etc.) Topic 4 - What’s the CF.org way of thinking about interoperability? Topic 5 - What guidance are you giving the teams in terms of expandability of Cloud Foundry? Architecturally, are there certain places you recommend over other places? Topic 6 - Is there a place for integrating SaaS applications (monitoring, logging, etc.) into Cloud Foundry? Music Credit: Nine Inch Nails (nin.com)

New kid on the block Tarik joins a few regulars this week to thank you for your support at the end of year show! We also talk about bringing in architects and economists to work on games and the latest Kickstarter craze Ouya as well as Oh My Game, Batman and Peter's secret desire to be a dictator.Remember to subscribe in iTunes and please leave a comment or e-mail us letting us know what you think.Download the MP3 directly.Add the Podcast feed to your RSS reader.Subscribe using iTunes.Hosts: Sam Barker, Dominic Aldridge, Peter Holley, Tarik BensariaMusic: http://www.purple-planet.com/

MODERATOR: Michael Wang PANELISTS: Diana Balmori, William O'Brien Jr, David Ruy, Allan Wexler, and Alisha Wormsley. In celebration of the closing of our collaborative exhibition, Architecturally.../works on architecture and space, we invited this distinguished group of architects, designers, professors and artists to discuss the works on view. artist: Ella Ben-Aharon, Edo Ceder, Molly Dilworth, Merav Ezer, Interboro: Tobias Armborst + Daniel D’Oca + Georgeen Theodore, Bess Krietemeyer, Alois Kronschlaeger, Matthias Neumann, Graham Parker, Adi Shniderman, Eirini + Dimitra Tsachrelia in collaboration with Yoichiro Mizuno and Jason Varone Architecturally... is a project by James Hendershot organized and conceived by Matthias Neumann and Alois Kronschlaeger presented by Hendershot Gallery.

Great Global Pagoda (video) www.globalpagoda.org This 16-minute film offers a stunning look at the Global Pagoda being built on the outskirts of Mumbai, India's most populous city. It is a modern wonder of engineering and vision. Architecturally, this building will be by far the largest single-span stone dome in the world, twice as big as the Basilica of St. Peter at the Vatican. Computer-guided stone saws are at work beside craftsmen using timeless chisel and hammer techniques. Download Video (89 MB) Runtime: 19 minutes The Global Pagoda pays tribute to Myanmar for safeguarding the Dhamma by reflecting the outer form of its famous Shwedagon Pagoda. However this pagoda is being built as a hollow structure that will seat 9,000 for meditation, and feature a gallery with educational panels and displays to inform visitors about the matchless contribution of the Buddha to human history. Thus it is intended to serve as a beacon of practice and education for multitudes, for centuries to come. The placement of the keystone by which the dome shall be closed (in which the relics of the Buddha shall be placed) will occur on October 29, 2006. For this function the respected Sangha of various Buddhist countries has been invited. Publisher: Karuna Films Publication Date: July, 2005 There is more information about Vipassana meditation at Dhamma.org, and books and audio resources available for purchase in the Pariyatti bookstore. May all beings be happy!