Podcast appearances and mentions of Linus Torvalds

Nesse episódio trouxemos as notícias e novidades do mundo da programação que nos chamaram atenção dos dias 22/08 a 28/08.

Nesse episódio trouxemos as notícias e novidades do mundo da programação que nos chamaram atenção dos dias 22/08 a 28/08.

Sorg, Katie Dudas, and Dave Podnar are back for another round of geeky tech, gadgets, games, collectibles, and Pittsburgh happenings. The episode opens on a somber note with a tribute to Dolly Parton and the impact of her philanthropy, including her work supporting childhood literacy. Then the crew gets into everything from simulated RC racing and Apple's latest Macs to a life-size Grogu, Linux history, Pokémon fossils, GTA VI leaks, and gaming at Pittsburgh International Airport. Topics discussed include: Remembering Dolly Parton – The crew reflects on Parton's passing, her charitable legacy, her support of literacy programs, and the positive impact she made far beyond entertainment. RC racing meets full-size driving simulators – Sorg discovers first-person RC car racing setups that combine tiny vehicles, onboard cameras, and full simulator rigs. The conversation explores CloudRC, RC aircraft, and whether experiences like this could become the next arcade, mall, or Dave & Buster's attraction. Apple updates the Mac mini and Mac Studio – Dave breaks down Apple's new Mac hardware, including the M6 chip, pricing, local AI performance, and the ability to combine machines over Thunderbolt 5. The crew discusses why local AI processing could become increasingly important for businesses dealing with cloud costs, privacy, and sensitive data. Pokémon Fossils invade Chicago – Chachi reports from the Pokémon Fossil Museum exhibit at Chicago's Field Museum, where fossils inspired by the games are compared with real paleontology. The exhibit even includes Pokémon GO bonuses and limited merchandise. Dungeon Crawler Carl and 3D printing – Katie opens her mysterious box of 3D-printed creations from Chachi's Plastic Fun Time shop, including Dungeon Crawler Carl characters, ornaments, magnets, Pokémon-inspired pieces, the infamous Rock Lobster, and more. Linux turns 35 – Dave traces the unlikely chain of events connecting AT&T antitrust action, UNIX, GNU, Linus Torvalds, and the operating system that became one of the foundations of modern computing. There's even a bonus discussion about Linux running on a Sega 32X. Kingdom Hearts expands – Chachi's Video Game Minute covers a 2027 release window for Kingdom Hearts 4 and a planned animated Kingdom Hearts series for Disney+. Mattel builds its own game studio – Mattel is expanding its internal video game operation with hundreds of developers and new games based on properties including UNO and Hot Wheels. GTA VI leaks and the digital ownership fight – The show looks at reported leaks of Grand Theft Auto VI material tied to protests over digital-only game distribution and the broader debate over whether players actually own their digital purchases. Transformers comes to Minecraft – Sorg and Katie explore the Transformers content available through the Minecraft Marketplace, including G1-inspired characters, story-based gameplay, combat modes, and plenty of temptation for Transformers fans. A nearly life-size Ultimate Grogu – Hasbro Pulse has a roughly 14.6-inch animatronic Grogu featuring movement, sounds, multiple interaction modes, cosplay-friendly settings, and a $599.99 price tag. Nature Calls restroom finder launches – The crowdsourced restroom-finding app discussed on an earlier AwesomeCast is now available, helping users locate bathrooms, water fountains, porta-potties, and other facilities. Gaming at Pittsburgh International Airport – Sorg checks out Gameway, a gaming lounge at Pittsburgh International Airport offering video games, snacks, drinks, and another option for travelers with time before a flight. Disney characters meet NFL teams – Disney and the NFL have teamed up for team-specific character merchandise. The Pittsburgh Steelers get Pete, while other combinations include Captain America with the Patriots, Thor with the Vikings, Darth Vader with the Raiders, and more. The crew also checks in on their recent Pittsburgh Shootout adventures and previews more of what's happening around the Sorgatron Media universe. RC Racing / CloudRC https://www.instagram.com/reels/Db2l4aVjpRO/ https://store.cloudrc.com/ Plastic Fun Time 3D Prints https://plasticfuntime.etsy.com/ Apple Mac mini / Mac Studio Updates https://www.wired.com/story/apple-announces-m6-and-m5-ultra-mac-mini-mac-studio/ 35 Years of Linux https://www.tomshardware.com/software/linux/linux-was-announced-by-linus-torvalds-35-years-ago-today-humble-os-started-with-10-000-lines-of-code-but-has-now-grown-to-40-million-dominates-global-infrastructure Kingdom Hearts Announcements https://thewaltdisneycompany.com/news/games-d23-digital-entertainment/ Mattel Game Studios https://kotaku.com/the-toy-maker-behind-barbie-and-hot-wheels-wants-to-make-its-own-video-games-2000724968 GTA VI Leak Story https://www.tomshardware.com/video-games/hacker-leaks-gta-vi-gameplay-and-map-to-protest-digital-only-release-claims-pre-orders-are-a-legacy-of-physical-game-releases Transformers Minecraft https://www.facebook.com/reel/1056475313409694 Nature Calls Restroom Finder – iOS https://apps.apple.com/us/app/find-toilets-nature-calls-run/id6790583853 Ultimate Grogu https://www.hasbropulse.com/product/star-wars-ultimate-grogu/G44835S00 Pittsburgh Airport Gameway https://www.instagram.com/reel/DcbcVbCBU34/?igsi=MTJweXZ1N2N4cTZ1dg== https://www.facebook.com/reel/1089385550715987 Disney x Pittsburgh Steelers https://www.nflshop.com/pittsburgh-steelers/disney/t-36604861+c-1202616796+z-8-2894738209?ab=%7Bwt-static_graphic%7D%7Bpt-TLP%7D%7Bal-HMB%7D%7Bct-Pittsburgh_Steelers_disney%7D

Sorg, Katie Dudas, and Dave Podnar are back for another round of geeky tech, gadgets, games, collectibles, and Pittsburgh happenings. The episode opens on a somber note with a tribute to Dolly Parton and the impact of her philanthropy, including her work supporting childhood literacy. Then the crew gets into everything from simulated RC racing and Apple's latest Macs to a life-size Grogu, Linux history, Pokémon fossils, GTA VI leaks, and gaming at Pittsburgh International Airport. Topics discussed include: Remembering Dolly Parton – The crew reflects on Parton's passing, her charitable legacy, her support of literacy programs, and the positive impact she made far beyond entertainment. RC racing meets full-size driving simulators – Sorg discovers first-person RC car racing setups that combine tiny vehicles, onboard cameras, and full simulator rigs. The conversation explores CloudRC, RC aircraft, and whether experiences like this could become the next arcade, mall, or Dave & Buster's attraction. Apple updates the Mac mini and Mac Studio – Dave breaks down Apple's new Mac hardware, including the M6 chip, pricing, local AI performance, and the ability to combine machines over Thunderbolt 5. The crew discusses why local AI processing could become increasingly important for businesses dealing with cloud costs, privacy, and sensitive data. Pokémon Fossils invade Chicago – Chachi reports from the Pokémon Fossil Museum exhibit at Chicago's Field Museum, where fossils inspired by the games are compared with real paleontology. The exhibit even includes Pokémon GO bonuses and limited merchandise. Dungeon Crawler Carl and 3D printing – Katie opens her mysterious box of 3D-printed creations from Chachi's Plastic Fun Time shop, including Dungeon Crawler Carl characters, ornaments, magnets, Pokémon-inspired pieces, the infamous Rock Lobster, and more. Linux turns 35 – Dave traces the unlikely chain of events connecting AT&T antitrust action, UNIX, GNU, Linus Torvalds, and the operating system that became one of the foundations of modern computing. There's even a bonus discussion about Linux running on a Sega 32X. Kingdom Hearts expands – Chachi's Video Game Minute covers a 2027 release window for Kingdom Hearts 4 and a planned animated Kingdom Hearts series for Disney+. Mattel builds its own game studio – Mattel is expanding its internal video game operation with hundreds of developers and new games based on properties including UNO and Hot Wheels. GTA VI leaks and the digital ownership fight – The show looks at reported leaks of Grand Theft Auto VI material tied to protests over digital-only game distribution and the broader debate over whether players actually own their digital purchases. Transformers comes to Minecraft – Sorg and Katie explore the Transformers content available through the Minecraft Marketplace, including G1-inspired characters, story-based gameplay, combat modes, and plenty of temptation for Transformers fans. A nearly life-size Ultimate Grogu – Hasbro Pulse has a roughly 14.6-inch animatronic Grogu featuring movement, sounds, multiple interaction modes, cosplay-friendly settings, and a $599.99 price tag. Nature Calls restroom finder launches – The crowdsourced restroom-finding app discussed on an earlier AwesomeCast is now available, helping users locate bathrooms, water fountains, porta-potties, and other facilities. Gaming at Pittsburgh International Airport – Sorg checks out Gameway, a gaming lounge at Pittsburgh International Airport offering video games, snacks, drinks, and another option for travelers with time before a flight. Disney characters meet NFL teams – Disney and the NFL have teamed up for team-specific character merchandise. The Pittsburgh Steelers get Pete, while other combinations include Captain America with the Patriots, Thor with the Vikings, Darth Vader with the Raiders, and more. The crew also checks in on their recent Pittsburgh Shootout adventures and previews more of what's happening around the Sorgatron Media universe. RC Racing / CloudRC https://www.instagram.com/reels/Db2l4aVjpRO/ https://store.cloudrc.com/ Plastic Fun Time 3D Prints https://plasticfuntime.etsy.com/ Apple Mac mini / Mac Studio Updates https://www.wired.com/story/apple-announces-m6-and-m5-ultra-mac-mini-mac-studio/ 35 Years of Linux https://www.tomshardware.com/software/linux/linux-was-announced-by-linus-torvalds-35-years-ago-today-humble-os-started-with-10-000-lines-of-code-but-has-now-grown-to-40-million-dominates-global-infrastructure Kingdom Hearts Announcements https://thewaltdisneycompany.com/news/games-d23-digital-entertainment/ Mattel Game Studios https://kotaku.com/the-toy-maker-behind-barbie-and-hot-wheels-wants-to-make-its-own-video-games-2000724968 GTA VI Leak Story https://www.tomshardware.com/video-games/hacker-leaks-gta-vi-gameplay-and-map-to-protest-digital-only-release-claims-pre-orders-are-a-legacy-of-physical-game-releases Transformers Minecraft https://www.facebook.com/reel/1056475313409694 Nature Calls Restroom Finder – iOS https://apps.apple.com/us/app/find-toilets-nature-calls-run/id6790583853 Ultimate Grogu https://www.hasbropulse.com/product/star-wars-ultimate-grogu/G44835S00 Pittsburgh Airport Gameway https://www.instagram.com/reel/DcbcVbCBU34/?igsi=MTJweXZ1N2N4cTZ1dg== https://www.facebook.com/reel/1089385550715987 Disney x Pittsburgh Steelers https://www.nflshop.com/pittsburgh-steelers/disney/t-36604861+c-1202616796+z-8-2894738209?ab=%7Bwt-static_graphic%7D%7Bpt-TLP%7D%7Bal-HMB%7D%7Bct-Pittsburgh_Steelers_disney%7D

Summer rewind: When we say 'the cloud' what we mean is 'the data centre'. Globally, data centres are projected to consume over 1000 terawatt hours in 2026. What does that mean for energy production, distribution, and consumption? Guest Phil Harris, Cerio President and CEO, joins thinkenergy to shed light on something we all rely on but may not fully understand. From efficiency to sustainability, environmental concerns to Cerio's role improving how data centres manage energy. Listen in for the future of cloud computing. Related links  Cerio: https://www.cerio.ai/ Phil Harris on LinkedIn: https://www.linkedin.com/in/paharris/ Trevor Freeman on LinkedIn: https://www.linkedin.com/in/trevor-freeman-p-eng-8b612114  Hydro Ottawa: https://hydroottawa.com/en      To subscribe using Apple Podcasts: https://podcasts.apple.com/us/podcast/thinkenergy/id1465129405 To subscribe using Spotify: https://open.spotify.com/show/7wFz7rdR8Gq3f2WOafjxpl To subscribe on Libsyn: http://thinkenergy.libsyn.com/ --- Subscribe so you don't miss a video: https://www.youtube.com/user/hydroottawalimited  Follow along on Instagram: https://www.instagram.com/hydroottawa  Stay in the know on Facebook: https://www.facebook.com/HydroOttawa  Keep up with the posts on X: https://twitter.com/thinkenergypod  --- Transcript:  [00:00:00] Trevor Freeman: Hi everyone, and welcome to the summer edition of Think Energy. As a reminder, we are in podcast vacation mode, and while our normal day-to-day work continues, we are on a brief pause from our regularly scheduled episodes to recharge, rethink, plan for the fall. But we don't want to leave you without anything to listen to. So, we've pulled some of our favorite insights and episodes from the past year related to the energy transition and where we are. So, welcome to episode two of our summer rewind, the August episode. So, as a reminder, this summer, we're looking at that collision between digital infrastructure and physical infrastructure, how the world of evolving technology is shaping and influencing and changing the way that we interact with energy and, in fact, interact with the energy grid as well. Last month, we looked at my conversation with Lynn Pettis from Overstory and how Overstory and Hydro Ottawa have partnered together to use satellite imagery and AI to protect our grid. In part two of our summer rewind today, or the second episode, we're looking at the world of data centres, and we're hearing lots about data centres as AI grows and takes kind of more of an ever-present role in our day-to-day lives. And I had a conversation with Phil Harris from Cerio. So, we're going to dive back into that episode and look at kind of the staggering energy footprint of AI data centres, of the cloud, etc., and how this boom is really changing how we do data centre design and really forcing a change in how we do data centre design just because of the sheer magnitude of energy required here. And we're going to look at kind of what this means for the future of global power distribution. So, sit back, relax, hopefully somewhere cool in the heat of the summer, and listen to this episode of Summer Rewind with Phil Harris from Cerio. [00:02:18] Podcast Intro: Welcome to Think Energy, a podcast that dives into the fast-changing world of energy through conversations with industry leaders, innovators, and people on the front lines of the energy transition. Join me, Trevor Freeman, as I explore the traditional, unconventional, and up-and-coming facets of the energy industry. If you have any thoughts, feedback, or ideas for topics we should cover, please reach out to us at thinkenergy@hydroottawa.com. [00:02:49] Trevor Freeman: Hi everyone, and welcome back. Data centres have come up a number of times on this show, and for very good reason. They have become a key underpinning technology for so much of our lives. Every time we pull out that phone from our pockets to pull up directions or buy something online, or doom scroll on your social media or news site of choice, every time you use your phone, stream a movie, leverage an AI model, whatever you end up using your phone for. It's funny, as I read this list, I'm sure there's like some university student out there who's thinking, man, what is this old man talking about? We don't use our phones for that. Whatever the kids are doing these days, whatever we're doing these days with our phones, with our computers, our tablets, etc., all of that leverages infrastructure that most of us have never seen, and quite frankly, probably don't really understand. We talk about the cloud like it's this amorphous, nebulous thing. But in reality, we're talking about real hardware in a real building that uses real energy, mainly electricity, a lot of water. And this isn't really new. Like, we've been leveraging centralized data centres for many years now. But what is changing is the scale of the data centres that we're seeing now and the pace of growth in computing power that we need to do the things that we want to do and that our data centres are able to deliver. So, just to throw a few numbers at it, the traditional data centre servers that maybe powered the early days of on-demand online streaming services, for example, they used anywhere from 5 to 15 kilowatts per rack. But modern server racks that are used to power AI searches, for example, can hit anywhere from 60 to 100 kilowatts per rack. This is great from a power output per rack perspective, but it means massive energy needs. And that is showing up in the size of load requests that we're seeing from new data centres. New data centres today are asking for service connections that are orders of magnitude higher than those built even just 5 years ago. Globally, data centres are projected to consume over 1,000 terawatt-hours in 2026. And just a quick kind of refresher from high school or wherever you would have learned this, a terawatt is 1,000 gigawatts, which is 1,000 megawatts. So, 1,000 terawatt-hours, which is roughly equivalent to the annual electricity demand from the country of Japan, an entire country. So, given all of this, there are a lot of incentives to find ways to maximize efficiency and reduce some of that energy demand. And that's where my next guest, Phil Harris, and his company, Cerio, come into play. I'll let Phil get into the details of exactly what Cerio does, but essentially, their goal is to reimagine the data centre to maximize sustainability and reduce energy needs. Phil is Cerio's President and CEO, and has been in the networking and data centre industry for over 35 years, including at well-known companies like Intel and Cisco, to name two. And I'm really excited about this conversation, one, to understand how do we make data centres a little bit more efficient, or maybe a lot more efficient, but also just to really understand, like, what are we talking about when we talk about a data centre? What is actually happening, what is physically inside these buildings? And we'll get into a little bit of that in our conversation. So, Phil, welcome to the show. [00:07:05] Phil Harris: Well, thanks, Trevor. I appreciate it. [00:07:07] Trevor Freeman: So, Phil, obviously, we're here today to talk about your work building sustainable data centres, or trying to make data centres a little bit more sustainable. But before we get into that, you know, you've spent your career, you know, decades of your career at different tech giants, let's call them, Intel, Cisco, to two to mention. You've seen quite a bit of change, no doubt, over your time. Has that change, like does this industry change linearly? Does it grow fairly steady, or is it kind of big jumps? And are we on the cusp of any major shifts? What can you kind of tell us about the future of this sector, data, tech, etc.? [00:07:54] Phil Harris: It's interesting. I think as companies start, and I was at companies like Cisco, for example, when it was a very small company to where it was a very large company, and this should be no surprise to anybody, the bigger the company gets, the harder it is to change. And they really find that the only way they change is when they absolutely have to, not because they want to. And that's a combination of just inertia and shareholders' expectations and a whole bunch of things. So, I would say that the bigger the company is, the harder it is for them to react. And so, I think small, nimble companies tend to do much better when there's a lot of transformational technology and development and changes in the overall ecosystem we live in. I think your, the second part of your question, you know, I look at the current situation as a point in time where a lot of companies will have to make some significant changes simply because we are hitting two new walls: technological walls, commercial walls, geopolitical walls, that are really sort of confining what people can do. So, I think what's about to happen is we're about to see a significant change. And this is not atypical in the industry. If we think about back into the start of what we would think of today as computer science around mainframes that were happening in the '60s, you know, for about a decade and a half, two decades, there was a lot of dominance around a particular way of doing things. And then some new innovational technology came along that rapidly changed that, scaled out, and it went from a very dominant set of players to a much larger number of smaller players who could then provide more innovation and more scale and more choice. And I think we're about to see that transition occurring as well. [00:09:47] Trevor Freeman: So, is this, is there sort of like an analogous time, 10 years ago, 20 years ago, are we on the cusp of like the big, the big change that we've seen before? Like, what would you compare this to, you know, in the last 20, 30 years? [00:10:01] Phil Harris: Yeah, I mean, I think there's been eras of compute. And if we say, I mean, we can find analogies outside of the compute world, but let's just stay in the computer science world. I gave the mainframe example as one, and then we went to what we call client-server, which scaled out rapidly. Telephony, we went from large, big telephone exchanges that started in the government space, went to very large organizations. Now, basically, we've completely scaled out how we make phone calls, to use that now 20th-century terminology. Nobody really makes telephone calls anymore. And we went through this with cloud computing and the internet, where there was a change in the approach to the way we did things that suddenly gave us a scale-out mentality rather than a scale-up mentality. And I think that's what we have to key in on here, is that we can, someone, I was on a panel yesterday where we were talking about scale. And I said, well, to scale or not to scale, that is not the question. It's how do we scale? Do we continue to scale up, which is the current model, or do we start to think about scaling out, which is a more distributed model? So, we go from a small number of big things to a large number of smaller things. And typically in computer science, whatever you want to, storage, compute, memory, telephony, everything we've ever done goes through this arc. [00:11:32] Trevor Freeman: Yeah, it's interesting, and there's, obviously, my brain's going to immediately try and find those similarities between my world that I live in on the energy side of things. And it's the same question. There is no path where we're not expanding the amount of energy we need, we're not going to be using more energy. But there are different ways to do that. And there are different paths we can take: the business-as-usual, the just grow, grow, grow, centralized energy production and large-scale transmission, or there's a combination of like grow those things, but also find alternative methods, more DERs, more sort of like close to consumer energy sources and storage, etc., etc. And people that listen to this podcast know I kind of go on ad nauseam about this. So, lots of similarities there. Another kind of framing or foundational thing that I want to talk through before we really get into the meat of our conversation is helping ground both myself and our listeners in what exactly we're talking about here. So, we all use, whether we know it or not, we use, you know, like cloud computing constantly, whether it's in our calls, how we're using the internet, using AI more frequently now. What is the physical reality behind that? What's actually happening? What is, you know, the term "data centre"? What is a data centre for our listeners here? What does that look like? [00:13:17] Phil Harris: Yeah, let's start there. And that's a great question. We started recognizing that the amount of power and space required for computers in companies and government and all sorts of different applications was getting larger than we could put in a room in a closet near maybe where people were using it. We had to start to create dedicated space, because the power requirements, the cooling requirements, just the noise—you can't hear this, but just in my basement, I have a few different compute systems that my wife continually tells me is keeping the neighbors awake. The reality is the environmental aspect of these things became very difficult. So, we created these purpose-built locations that had then different requirements in terms of access and facilities and power and cooling and staffing. And so, they became a new way of thinking about building compute infrastructure at a building level, not just at the individual computers themselves. So, a data centre is usually a very large room, or building, I should say, that houses large amounts of compute and storage and other networking equipment. There's a whole range of different technologies that go into a data centre that allows us to process information. That's what a data centre is. To give you some analogies, in the US, there's about nearly 6,000 data centres, depending on how you measure a data centre. In Canada, we have about 400. In Europe, there's about 750 that we can identify as standalone data centres. You can probably find more places where computers are outside of people's homes, but that's about the ratio we're looking at. [00:15:10] Trevor Freeman: And we're seeing, I think, and tell me if I'm wrong here, like all this talk about the AI proliferation, data centre proliferation, we're seeing an expansion of these. Is that we're seeing the size of these data centres expand, or we're seeing just more of them popping up? Like, what does it mean when we say we're seeing like data centre growth because of AI? What does that mean? [00:15:36] Phil Harris: Well, it's fascinating because now our worlds collide. Because the way we now think about how to describe a data centre isn't in the square footage or the number of computers. It's in how much power it consumes. And we now measure it in megawatts. It starts in 10 megawatts, or single-digit megawatts for very small data centres, into average-sized data centres in the tens of megawatts, up to now the hundreds and the gigawatts of consumption that you look at these hyperscalers. But I think we have to put this into a sort of a human scale. It helps us to put this in human scale. If I were to go back to ChatGPT, actually about now 15 months ago, ChatGPT-4, if you were to put that data centre footprint into the province of Ontario, for example, where you and I both are right now, it would be the equivalent of a million internal combustion engine cars driving 30 kilometers a day. If you ever drive up the 401, you probably don't want to see another million cars on the 401. But that's the amount of energy that we can think of in terms of a data centre of that scale. [00:17:02] Trevor Freeman: Yeah, and again, putting it in the electrical industry's terms, what we consider as a large load—so, we have a specific designation of a large load request—that is anything 5 megawatts and higher. Up until recently, we would get one or two of those every once in a while. Like, it's pretty rare to get a large load request. We are seeing large load requests coming in at a near constant pace now. Like, the number of large load requests we're getting, and a lot of it is because of this—not all because of data centres or anything like that, but a lot of them are certainly driven by that need for more computing power, more facilities that support that. [00:17:53] Phil Harris: That's right. And at the same time, we're seeing a demand on energy around now home EV charging and other aspects of the general distribution of power. Everything is taking a step function. But if I could just say one thing to your point about 5 or 10 megawatts was a high load, I think we may need to change that scale. It's almost inefficient to build a data centre unless you're somewhere above the 10 megawatt range, because at that point, get somebody else to do it for you. [00:18:23] Trevor Freeman: Ah, interesting. Yeah, and that's where sort of like, almost like renting space in a data centre for a request of that size. Interesting. Something that, you know, I've seen kind of in your writing on your blogs is the idea that traditional data centres are really built for peak capacity, which absolutely mirrors the power industry. We build our electrical grids for peak capacity. And obviously, that leads to a fair amount of inefficiency. So, if you're building just to peak capacity, if you're not at peak capacity, there is an inefficiency happening there. Something that you identified, it's a stat from your research, talks about graphics processing unit usage rates as low as 20% or 25%. So, I'm assuming that means kind of like three-quarters of that hardware is sitting idle or not being used valuably. Tell us a little bit about what Cerio, what you're doing, what your composable architecture specifically is doing to reclaim that wasted power and cooling capacity. [00:19:42] Phil Harris: Yeah, and so it starts off with the premise you correctly raised, is that if we think about the equipment, the physical equipment, and how we put these devices and these components together in a data centre, the same model we've been using today is about 30, 35 years old in terms of individual compute systems where we run applications, software, that has memory and central processing units, those typical things you have in a laptop or you have in every computer. But then we put these accelerators, these GPUs, companies like Nvidia now are the one of the most valuable companies on the planet, if not the most valuable company on the planet, because that's the technology they develop. But we're trying to put these new class of accelerators into an existing compute model, which wasn't designed for this. So, that in itself now starts to fragment the ability to leverage those resources in a data centre. And as you accurately said, you know, it's interesting, if I could geek out on this a little bit for the energy consumer in the room... [00:20:53] Trevor Freeman: Please do. [00:20:54] Phil Harris: ...we think about the notion not only of the megawatts of power going into the data, but we think about what we call power usage efficiency. And that basically says, whatever the power delivered to a data centre, how much of that is applicable to the IT systems in that data centre? A good, well-run, efficient data centre is about 1.2. That means that about 1.2 times the amount of power that's used is delivered. Your home, for example, is about 30 times the amount of power we use is delivered. We are very inefficient from our home use, by the way. But that's another problem to solve another podcast. But in this case, that's all true until we then ask the question, but what's actually being used of that equipment? And that's now in that 25% to 30% range at any point in time. And we refer to that as stranded and idle assets that, for whatever reason, aren't where the application is or aren't applicable to be used for the application at that moment, because they're in some other box. Or it's a time of day when people use equipment. And by the way, equipment like that isn't being used 24/7, but it's drawing power 24/7. So, there's lots of inherent inefficiencies in that model. So, what we do is we provide the ability to dynamically have pools of resources where we can dynamically attach resources to a compute system as required, at the scale you required, and allowing you to be much more efficient in the timing of that and the amount of equipment required to meet your end solution. And by doing that, we can increase the number of accelerators that you apply to a compute system, which inherently means you are much more efficient in those compute systems. Because it's not just the computers, as I said before, there's storage, there's firewalls, there's load balancers, there's networking equipment, all of that can now be much more efficiently used, all of that is drawing power. [00:23:01] Trevor Freeman: So, is the idea then that the equipment not being used or when you're at a lower demand time in terms of computing power, you've got physical equipment idling, sort of in more idle mode, drawing less resources that you can then ramp up? So, the peak amount of equipment's still there, you're just being more efficient with it when it's not being used, and you've developed a way to sort of dynamically pull that in. Is that what I'm hearing? [00:23:28] Phil Harris: Exactly. I'll give you an example. A data centre here in Toronto wanted to have a block of 128 GPUs they could service their customers with. With the current systems they were using previously to deploying our infrastructure, they had to deploy actually 200 GPUs and a very large number of servers to house those GPUs. By deploying Cerio technology, they brought that down to 136 actual GPUs, and they reduced the number of compute platforms by a factor of 4. So, they reduced it by 75%. [00:24:10] Trevor Freeman: Wow, that's fantastic. [00:24:11] Phil Harris: With exactly the same outcomes to their customers, with no contention for resources, no oversubscription of resources, just more efficient use of those resources. [00:24:23] Trevor Freeman: Gotcha. So, still able to meet that peak demand, but not firing up that equipment when it's not needed. [00:24:30] Phil Harris: Well, not just not firing, not having to have as much stranded equipment, because we can use all the equipment all the time. [00:24:38] Trevor Freeman: Gotcha, okay. So, in when I was kind of setting up that last question, I used the term "composable architecture," and I'll admit that I pulled that from your material. Help me understand what that means. So, I've also seen you use "composable infrastructure," sounds a bit abstract. What are we talking about here? What does that actually look like? [00:25:02] Phil Harris: When a consumer or someone who's building a data centre buys their computer equipment, they usually will actually buy the computers, the GPUs, the storage, and other things at the same time. And they will get delivered together, and that box now becomes a unit of compute capacity. But the thing about that is, whether you're able to use that entire capacity, the length in which that's useful, there's a lot of innovation churn right now as new things are coming through very quickly. But that box is now statically built for the rest of its life pretty much. IBM did a study, to take a server out of a rack, these big 6-foot racks or bigger where these servers are housed with lots of wires going into them, power and data and all sorts of things, it's about $1,000 a minute to take one of those servers out of the rack and either change something that's broken, update something. So, they just don't get taken out of the rack, because the average time to take a server out of a rack is about an hour. The math on that's pretty simple. So, if I'm spending $60,000 to upgrade a $20,000 or $30,000 server, I'm just going to leave it there and buy another one. So, that creates more of these stranded assets. So, composability says, let's separate these things into, as I said, pools of resources: compute, accelerators, and other devices, and have a fabric between them that allows us to in real time assemble a compute system that I need—that's the composing part—as I need it, because I can now take the resources anywhere in my data centre if you've got the right fabric, which we've built, that allows you then to real time build that compute system with exactly the same capabilities, exactly the same performance, and without having to change any of your software or the way the servers work. Everything has to be off the shelf to make this work, and that's what we've built. [00:27:03] Trevor Freeman: Gotcha. So, two of the terms—and you'll forgive me, this is sort of a new sector for me—two of the terms that are used as metrics to determine performance are power usage effectiveness, and you've kind of talked about GPU usage. Is the industry moving more towards that GPU usage metric? Is that just something that you guys are kind of leading the curve on, or where are we at on that? [00:27:36] Phil Harris: Oh, no, this is very much the industry way of describing not just efficiency, but requirements. And we use very weird terms for this. Every industry has their weird terminology. [00:27:46] Trevor Freeman: Absolutely, yeah. [00:27:47] Phil Harris: And we're now moving to the, for example, in AI, the number of tokens per second. When you and I put a request or a question into ChatGPT or Copilot or Claude, whatever we use, those words get translated into tokens, actually numbers. Every compute system is just a big calculator at the end of the day. We do massive processing on numbers. How many of those tokens can I put into the system? How long does it take to process those tokens and give me a response? And the tokens per second per watt is now what we're asking. So, how many tokens a second and what power per token is it costing me to process information? And that's the interesting way of thinking about how AI, for example, that's where you started this conversation, will be measured, is the most amount of tokens per second per watt. Now, right now, we're focusing on tokens per second. We're not looking at the last denominator, which is watts. So, that's why these data centres are getting so ridiculously large. And, you know, we even heard it in the State of the Union address in the United States earlier in the week where, you know, there's now the administration pushing cloud vendors and AI vendors to say, "Hey, pretty soon, you're going to be on your own about delivering power because, quite frankly, the way you're going, it's going to become untenable to think about that from a national grid perspective." Now, I think that may be a little bit into the future, but I don't think it's a completely unreasonable sentiment at this point. [00:29:32] Trevor Freeman: Yeah, and I mean, you're talking about, and we talked earlier about the just the scale of energy usage here is reaching a new height, a new level. And if we break it down to the individual racks, you know, these these racks of servers or processors that you've got in your data centre, we're now talking about anywhere from 50 kilowatts to 100 kilowatts of cooling need. And that's the big driver of energy usage, I think, is correct here, is the cooling need per rack multiplied by, of course, big numbers to get those, you know, 5, 10, 20, 30 megawatt data centres we're talking about. When we talk about cooling and we talk about hotspots within a data centre, how does your approach differ from kind of the standard way of doing it? [00:30:32] Phil Harris: That's a great question. And I think we should explain why the cooling part, it's a bit like buying really good, expensive Wagyu steak every day and then having to spend a lot of money on a gym membership to then go and burn off those calories. So, we put all this power into power these compute systems, but then we have to keep them cool. The faster they run, the more powerful they run, the hotter they get, but we need to cool them. So, there's this relationship between the more power we draw, the more cooling we need. And cooling is becoming, as I said, that sort of tradeoff for performance. Now, there's lots of exotic ways of cooling computer systems. We can just blow air across them, we can have liquid like the radiator in your car, or we can literally drop these compute systems into baths of solvents. Ferdinand Porsche, I like to use of other industry analogies. Ferdinand Porsche, the guy who obviously designed the first Porsches and the VW Beetle, realized if I could distribute the heat of the engine block with a horizontal block, I could blow air across it, it was much more efficient than trying to put a radiator to actually cool down the engine block the way that other cars who have the engine in the front. And it's because of surface area. Now, if I've got to put all my GPUs and CPUs and memory close together either in the same box or the same rack, that concentration of heat needs to be addressed with cooling. One of the ways we can address this is not only to be very selective when I compose the GPU, it's the only time it's drawing power, but also, I can spread them out through my data centre by having a fabric that allows me to connect them to the compute systems with the same performance. But now I can distribute my heat generation, that means I can cool more efficiently, just like that Ferdinand Porsche analogy of the Porsche 911. Because now, heat over spread of distance and surface area is a more efficient way, which means that it won't mean that we won't ever get to liquid cooling. I don't think immersion cooling is a good idea for lots of other reasons, but it's a necessity more than an optimization. But we can defer the complexity, the cost of those exotic cooling systems if we're more efficient in the way we use and design our data centres. [00:33:10] Trevor Freeman: And I guess there's a similar description there of if you're concentrating all that heat in a specific physical area within a bigger building, room, whatever you want to call it, that cooling system is having to work to that peak cooling need, so to that hotspot effectively. But it's not working just on that spot, it's working across the whole physical area. If you're spreading that cooling need out across the whole room, one, the peak is a little bit lower, and you're just more effectively using your whole cooling system, is that fair to say? [00:33:48] Phil Harris: That's exactly the right way of looking at this. And think about it from this perspective as well. The reason we have to cool is because if we don't cool sufficiently, those devices become very unreliable and reduce their useful lifespan. Without going into who, because they keep this information confidential, but one large cloud provider in the US, for example, a GPU that normally has a lifespan of at least 3 years is going down to about 9 months right now. And the reason for that reduction in the lifespan of the use of that GPU is because of the heating characteristics within these boxes even with all these cooling mechanisms are becoming now a reduction in the lifespan. So, that means we have to create even, remember I said what it costs to take a system out of a rack? [00:34:44] Trevor Freeman: Yeah. [00:34:45] Phil Harris: That means if we don't have to apply an efficient and effective cooling strategy, our power strategy and cooling strategy, then we start hitting problems very quickly. [00:34:56] Trevor Freeman: Gotcha. Okay. Okay, so there's a mantra that I'll admit I hadn't seen before until kind of reading some of your material. It's, "Friends don't let friends build data centres." And I think it's referring to, you know, this move in there's so many industries that kind of do this cycle of centralization to decentralization. And the sort of data movement went towards that centralization, and you saw these big, massive data centres. But there's kind of a move now back to, let's call it, decentralization or repatriation of data. And so, for various geopolitical reasons, organizations, companies, governments are wanting to pull their data back home and have it kind of be more in their control, living in their own servers. So, how are you or how is Cerio helping companies kind of get back into the data centre business or repatriate their data without kind of, you know, getting into the troubles that led for to that centralization in the first place? [00:36:12] Phil Harris: Yeah, and by the way, I can't take real credit for that quote. Cole Crawford, who was one of the early guys at Facebook before it became Meta, and was one of the leading voices in the Open Compute Platform movement, which was trying to standardize how we do these things, Cole is now the CEO of a company called Vapor IO. And what he was really saying is, it's so complicated and difficult to run data centres, let alone build them, the capital expense. AI isn't just one thing. There's lots of stages in the workflow of AI. We train these big models, you have heard of large language models like ChatGPT or Copilot. But what we use them for, the results of those trained models, is what we call inference. Now, you'll now hear about agentic AI, where we turn those results into actions. Okay, that's the agency part of agentic. Well, the use of AI in the corporate world is now becoming, as you said, both regulated, but from an intellectual property perspective, it's about how I control my data and my information. Because if I put that all into somebody else's large language model, I've basically populated somebody else's large language model with what might be my proprietary information or information that's very sensitive. And it's one of the reasons why you'll hear in the press about Anthropic, for example, trying to put guardrails around the use of their AI, because they're very sensitive to this. Most enterprises, governments, of all sorts, have realized, though, they need to run this in their own data centres, because they need to have control over this information and the use of this information. That's the repatriation you're talking about, moving these workloads now into the organization that previously had said, "Hey, cloud computing can take this problem." We've got to now figure out how enterprises, which are far many more of them in far more diverse locations, can now build their own data centres and get the right power, the right efficiency, the right capabilities at the right cost. [00:38:22] Trevor Freeman: Does that open the door? I mean, earlier you talked about, you know, if we're talking about a 5 megawatt data centre, it's almost not worth it. You know, that's just sort of renting space in someone else's. How does how does that track with an organization that won't have enough data or enough computing power, whatever the metric is, to to warrant a 30 megawatt data centre for their own data, but wants to get that that control, wants to bring it more in house? Is your technology helping those smaller data centres exist? Is that the correlation there? [00:38:58] Phil Harris: We can now move it into, another couple of terms that may be you're listeners may not be familiar with, in the compute world or the data centre world, we talk of brownfield and greenfield. Brownfield is that which is already there, greenfield is something I have to build new. A lot of the brownfield world is the predominant quantity of compute power on the planet is primarily brownfield. The question is, can I take that existing infrastructure and put the capabilities we've been describing in this discussion into those brownfields, so I can reduce the cost of the expansion of that, because I can reuse the compute equipment that's there? I can now add just the discrete GPU technology, for example, into an existing data centre that doesn't then far blow the power budget or the cooling envelope within that environment, but I can still now start taking advantage as I figure out what my larger plans are. And at the same time, how do we have a tier of providers who I'll give you an example. There's a company in again in Canada, ThinkOn, who are building a data centre in in Ottawa. It's going to have its own liquid natural LNG as its source of power for its own power requirements. Why? Because they can have the power they need as they need it in that location, and they can provide that secure infrastructure for both government and private enterprises. And ThinkOn is is certainly in Canada one of those companies that's really seen to be a trusted partner in this. So, it'll be a bit of what can I do myself, how do I have a trusted partner. We think of sovereign AI a lot. That means trust more than anything. And that's becoming the new mechanism of thinking about this. [00:41:01] Trevor Freeman: Thinking about the the environmental impact of of tech and of of data, you know, we've talked about the energy usage here, but there's also the physical aspect to it of, you know, the the pace of improvement in technology means we see obsolescence, or we see kind of technology being outdated fairly quickly. We all, like on the personal level, we all see this with our our cell phones, our smartphones, our our whatever tech we have at home that seems to be out of date fairly soon. I think the the stat or the the saying that's out there is, you know, tech is kind of obsolete or becomes trash within 3 years. Obviously, this is not sustainable. Is this part of the drive of what you're doing? Is it are you looking to sort of extend the life of the physical equipment? You've touched on this a little bit, but maybe expand a little bit on that. [00:42:01] Phil Harris: Yeah, this this goes a little bit back to that brownfield, greenfield discussion. But one way of looking at it, I guess, is um when I put all of these components into one the classic model, the current model, I put my my my central processing unit, my memory, my storage, my GPUs, all in the same box. What is the thing in that box that I want to take advantage of as new innovation happens versus that which is happening over a slower evolutionary cycle? Well, right now, if I put everything in the same compute unit, go back to my cost of taking that box out of the rack, I'm pretty much limited by the slowest innovation curve within that platform now as what I can take advantage of over time. Interestingly, GPUs are innovating currently at a clip of about once a year. Nvidia comes out with a new generation of GPUs once a year. Um but now we're getting more GPUs into the market, we're getting much more diversity, and that diversity means I'll have more options more often. But if my compute system itself is only innovating once every 3 years to your point, then if I don't decouple these things, if I don't have the ability to separate these innovation curves, I'm always stuck with the slowest innovation curve. One of the things we've done at Cerio with the fabric that we've built and the platform we've built is to allow you now to, if you like, dislocate those innovation curves and those options so as new technology comes along, I can apply it to the things that are innovating slower and still get the outcomes I'm looking for. And that will significantly increase the existing lifespan of equipment that's in people's data centres. [00:43:56] Trevor Freeman: So, so looking at a data centre of the future, and not, you know, not far into the future, let's say 5, 10 years from now, are we seeing some of the same technology still exist within that data centre, or is it, you know, everything gets cycled out within Like what's the generation of a data centre, for example? Like how often or how soon will we see it all cycle out? [00:44:20] Phil Harris: I think you there's a there's a there's a technical answer to that, and a financial answer to that. The depreciation models, so that the capital infrastructure can be written off people's books over a 3 to 5-year window, is very typical. So, we see that there's just an a financial inhibition to changing more or faster than that 3 to 5-year window. The technical churn, as I said, is happening much more rapidly in the technologies that are drawing most power, but providing most capability. So, one of the things we're we're looking at is how companies now start leasing infrastructure. Because if they lease the infrastructure, they can now recycle that and bring new technology in faster into their organizations. But to do that, you've got to have the ability to bring new technology in and not be stuck with these static systems that we have today. So, there's a set of financial instruments and now, with work that Cerio is doing, technical capabilities that allow customers to really continue to innovate. So, there's no real, "Hey, it's going to be all churned out in 3 years." I'll continue to innovate over those 3 years, recycling the technology that can stay where it is and bringing new technologies as it becomes available at the right financial model. [00:45:39] Trevor Freeman: I'm curious about what that innovation is. Um so, you talked about Nvidia kind of essentially a new GPU every year, there's a new version every year. What is the innovation? Are they just Is it getting faster and more compute power and therefore it's pulling more energy, and is that just like a perpetual increase, or is it kind of same compute power, less energy? Like, do we ever see, I guess what I'm what I'm getting at with this little bit of a ramble here is, do we ever see that that rate of change in energy usage start to flatten out and come down while we still can grow our computing power, or does energy usage just continue to grow, like are we on a bit of a path with no end right now? [00:46:36] Phil Harris: History taught us a little bit about this. Uh Gordon Moore, who was one of the founders of Intel, actually, we had this term called Moore's Law. And Moore's Law was basically this idea that every 18 months, we'll double the number of transistors on a piece of silicon. Now, for those in the computer science world, we all understand what that means. For the rest of the world, the transistor is the smallest unit of technology within the computer. It's the basic building block of how we build computers, the central processing units, all the GPUs, they all come down to taking literally silicon, and in a foundry, we call them, figuring out how to make as many transistors interconnect with each other in a in a smaller area as possible, or the most amount of transistors we can. So, a bit of a geeky answer to your question, but the way that we look at how each innovation improves is are we increasing the number of transistors, which means we can do more math. Remember, all we're doing is processing numbers. [00:47:45] Trevor Freeman: Per unit, per physical unit, right? [00:47:47] Phil Harris: Per physical unit. [00:47:48] Trevor Freeman: Okay. [00:47:49] Phil Harris: And the way we do that is in these big foundries that process all this silicon into these components, they have what are called process nodes. And the and literally how we etch a transistor, it's called lithography, onto a piece of silicon tells us the power of that piece of silicon. And the more I can etch, so we get into what we call the nanometer scale of what we call a process node. So, every time, if you really look into the spec sheets of Nvidia every generation, they'll talk about how many nanometers their silicon process is based on. Because the smaller I can get that number, the more transistors I can have on the same amount of silicon, the more processing I have, BUT every transistor takes power. So, with more transistors, I require more power, even though in the same physical space, it looks like the same amount of silicon. Therefore, your question was a great one. Do we ever get to zero nanometers? Well, no. We're going to hit a wall here eventually. So then the question is, that's the scale-up model: try and make one thing as big as possible. How about if we make lots of things powerful, but we have more of them? In China, last year, we heard of DeepSeek. DeepSeek was a Chinese government-sponsored effort to try and come up with a much more cost-effective way of doing the equivalent to ChatGPT. They didn't do that with bigger GPUs, they did it with much smaller GPUs, but many more of them. And that comes back to how efficient I am in deploying lots of things together. And that goes back to my earlier point about, we start with scale up, inevitably in the industry, we go to scale out. [00:49:50] Trevor Freeman: And there's Is it fair to say that the power usage per transistor, is that fairly static? Like, is there efficiencies to gain there, or your GPU is going to use more power because you're packing more transistors into it, and once you hit that wall, that's going to be the the power consumption level. Is that right? [00:50:15] Phil Harris: Well, this is the games that the silicon manufacturers like Intel, AMD, Nvidia, they're all trying to figure out how to sort of figure out new and interesting ways of packaging all the silicon in these processing units. And we've got a whole industry and science around the packaging mechanism to make those tiles, and we now think of them as little tiles of processing power. And some will be doing very specific jobs, some will be doing very general jobs. It's now getting to the point where the science around the packaging of these dies or these tiles is as much of the of the of the innovation as the actual tiles and the processing on them. So, it's an extremely complex um um technical problem, uh and we are hitting some walls here, which is why I go back to my earlier point. We're now reaching a point where is it just a technical problem to solve or a technical, operational, and commercial problem we have to think about? And this is that wall that you asked me about right at the beginning of this conversation: are we about to hit a wall? And the answer is yes. [00:51:26] Trevor Freeman: Hmm, interesting. It's I mean, I'm always fascinated by like what are the what are the really smart people in the industry focusing their time on. And it's so that's why we're talking to you, um of you know, you're looking at how do we operationalize this, how do we get the most efficient combination and structure of what we're doing here. There's folks that are looking at how do we pack the most computing power efficiency into these specific units. I guess there's an aspect of how do we cool this in the in the most effective way, like what's how do we um, you know, drive down the cooling power needed. Uh what else is out there in terms of like we have smart people focused on this efficiency? What's the thing that's missing from that that sort of list? [00:52:26] Phil Harris: Well, I think maybe what's going on right now, and if I could just add one more layer of complexity, I'll try and keep it concise. Remember I said we were processing silicon? Well, the earth's got lots of silicon, but we don't have lots of places to process that silicon. The companies that are formed to process silicon into these processing units, we call them foundries. The world's largest is TSMC based in Taiwan, um and then we have Intel, we have Samsung, we have a few others around the world, GlobalFoundries is another one. There is a limit, physical limit, because these foundries are huge and they take decades of development and optimization. So, if we start breaking ground on a new foundry tomorrow, we'll see output in about 5 years. So, we have a constrained supply. So, if I'm a if I'm Jensen at Nvidia or any of the big silicon manufacturers, I'm going to optimize that relatively constrained supply to where I'm going to get the best return on my investment, and that's why this scale-up model is happening. So, given that, we know that we won't have any more foundry capacity of scale for another couple of years at least, then the reality is we've got to think differently about how we're thinking about the processing of that silicon. Do I want just ever bigger processors that become more expensive, more limited in where I can deploy them, and quite frankly, the top 15 consumers in the world of silicon consume about 80% of that silicon, if not more. How do I democratize that? Again, it goes from scale up to a scale-out model where I can use that same processing capacity to produce more silicon. [00:54:20] Trevor Freeman: Fascinating. Um yeah, I just I took us down a little bit of a nerd out path. You had me really interested in that. Um okay, so last question here. We hear this term for a bunch of different reasons um around the world right now. Um we're hearing this term "democratizing" happening a lot, and and I know um and you've talked about democratizing AI. What does that mean? What does that mean to you, or or describe that for us? [00:54:51] Phil Harris: Yeah, I think it really means going right to my last point about if if 15 big, big consumers of silicon are going to consume the vast majority of available supply chain, that makes that a losing proposition for the the rest of the organizations and the rest of the governments and the rest of the individuals on the planet. So, how do we make sure that AI can be built both responsibly from a a sustainability perspective, and I don't mean just ecological side, but that's important here too, but also from the ability to I was on a panel yesterday between the UK government and the Canadian government where we were looking at how do countries around the world have the ability to control their own destiny. There's this whole notion of sovereignty and AI sovereignty right now. That isn't because people want to have closed walls around them, they want to have choice. They don't want to be dictated to by very dominant players where they quite frankly don't have the buying power to compete, you know, the amount of capital going into some of the AI companies, we saw $30 billion going into Anthropic last week, that's actually a small increase in their capitalization relative to the other big AI players on the planet. That's $30 billion. So, we've got to think to ourselves, is that a sustainable model commercially? And the answer is no. So, we've got to have technology, we've got to have the right ability to deliver power, we've got to have the right designs of data centres that can keep them cool in an effective and efficient and responsible way, and we've got to be able to give them enough power to make them viable to make them useful. That's the democratization we all have to be focused on. [00:56:46] Trevor Freeman: And we need every I guess to to round out the point is we need everybody to be able, everybody being, you know, whatever, major industry, countries, whoever, to be able to access that equally so that we don't have to rely on the major players out there in order to do those things you just said. Gotcha. [00:57:04] Phil Harris: That's exactly right. And look, there'll always be a pyramid here. There always has been in technology, there's always still the big players, right? But the question is, have the big players stifled out the ability for smaller players to come up, innovate, provide choice, provide alternative ways of looking at things? And that's what we've got to make sure that we keep the the And there's always reliance on some new technology coming along that enables that. Cerio believes that we've created that next layer in the stack, if you like, of technologies that gives us that opportunity to rethink the innovation curve going forward. [00:57:42] Trevor Freeman: Very fascinating. Phil, thanks for your time. I really appreciate it. This has been super interesting. It's not an area that I often get to spend my time thinking about, so it was great to chat today. As you know, we always kind of round out our interviews with the same series of questions to our guests. So, what's a book that you've read that you think everybody should read? [00:58:05] Phil Harris: Well, I'm not sure I can recommend this for everybody. One of the people who basically along the lines of some of the things I've been talking about today, who've revolutionized the computer world was a gentleman by the name of Linus Torvalds in Helsinki in Finland at the time, he's now based in the States. He realized that there was a dominance around how the operating systems on computers, the things that run the software, was limiting basically innovation, choice, and forcing us down a very closed path. So, he wrote something called Linux, which was a new operating system, so be it on your phone, your TV, your microwave, that's running Linux today. Because there wasn't an operating system that we could then generally deploy that meant there was more developers had the ability to write applications, more hardware vendors could now have software they could run on their on their platforms. He gave the world a new innovation curve, and every time this happens, to my last point, good things happen, very good things happen for the world, for every individual on the planet. And Linus was one of those individuals who saw that need. And so, his book, "Just for Fun," and he's a very quirky guy, as you can probably imagine, is a great book about his philosophical approach to what it takes to change really big problems. And I would encourage all of you just even just read the first few chapters. It's a fascinating view of how an incredibly smart man, smart individual took on probably one of the biggest problems we had in the 20th and 21st century of computing and solved it by recognizing you take a different path. [01:00:03] Trevor Freeman: Yeah, very cool. [01:00:04] Phil Harris: As far as as far as shows, I don't know, I'm one of these guys, I've got two 13-year-old daughters, so my wife and I get to watch TV for a very limited amount of time when we can watch it about the things we want to watch. So, we tend to sort of cram things in. But I am I am a huge Aaron Sorkin fan. So, if I ever need something on a rainy day to go back just to think about how the world could be, I watch The West Wing. It's a show that's imaginative, it's got incredible script writing, it's got incredible character development, but it really talks about how to think about doing the right thing as well. Now, whether you agree with the politics or not, that's a different question, but just the thought that smart thinking solves big problems, again, sort of it's a bit like the Linus Torvalds book, it just speaks to me about sometimes we can solve big problems with individuals or people who just have the right way of thinking about things. [01:01:06] Trevor Freeman: Yeah, I think that's that's the kind of, you know, call it entertainment because it is entertainment, but it's the entertainment that sticks with you and that we we go back to time and again is the ones that we can also like see the the underlying philosophy or or, you know, theory of change that goes into that entertainment. And it's it's fun to watch, it's, you know, either humorous or dramatic or whatever, but there's still that underlying message. And I think, yeah, West Wing is a great example of of that. There's a handful of those other sort of classic shows that are in that line, too. Um, a free round-trip flight anywhere in the world, where would you go? [01:01:46] Phil Harris: This is hard. Um, my wife and I were talking about this the other day, and um I've had I've had the luxury of traveling just about everywhere. I think there's 15 countries on the planet I haven't been to. Wow. But if I ever want to go to one place, it's Bali. And there's two reasons: one, my wife and I went there for our honeymoon and it was the beginning of the most important chapter of my life by far. Um, and and secondly, it's because it has that balance of everything. It's I love to scuba dive, I love the rainforests, the jungle, the architecture, the people, the food. It just brings everything into one package for me. And so, um it just, again, it's those things that sort of speak to you emotionally and also intellectually. It's one of those things that I could always go back to. [01:02:40] Trevor Freeman: Oh, fantastic. Um, who is someone that you admire? [01:02:45] Phil Harris: In history or today? [01:02:47] Trevor Freeman: Ah, you pick, anything. [01:02:48] Phil Harris: That's fascinating. Um, I think historically, it's I'm a Brit, it's hard not to go back to some of my my my forebears or my my country's forebears. Alan Turing, who against all adversity, social, political, technical, came up with an inspirational way of thinking about solving what were deemed to be unsolvable. And again, it was a it's a tragic story, I think we've all if you see, you know, the movie that was made about his life, um, it's a very tragic story, but it's an inspirational story about how again, if you just take a different approach to solving what seems to be an unsolvable problem, you can. You get smart people together, doesn't have to be a big army of people. And I think so Turing is one of those people that always comes back for me, thinking, "Wow, if I could have just some of his courage and some of his imagination and some of his intellect, I'd be a very happy person." [01:04:02] Trevor Freeman: Yeah, and it's almost, I mean, obviously a brilliant man, but it's the willing to think in a different way or willing to approach a problem in a different way that, I mean, there's a long list in history of of major turning points that are as a result of someone thinking in a different way or doing something in a different way, and I think that's a great example of it, so. Just about the entire course of human life in the midpoint of the 20th century changed on that that man's inspiration, that man's imagination. Yeah, and that's that's not an understatement. That's fantastic. Uh, okay, last question. What's something about kind of the energy sector or, you know, your sector that that you're really excited about, or something that you see in the future that you're really excited about? [01:04:47] Phil Harris: Actually, I see it now, to be honest. There are things in the future. Hey, I I I have two 13-year-old kids. I want to have a sustainable ecology and world environment for them to live in and bring their own families up in. And I think about how we can use power more efficiently, but how we can make it It does Look, sustainability is important. I want to see renewable, sustainable energy for the general world as a as a thesis. Right now, it's how we can be much more efficient in the use of power and the right power delivery. And I think, as I said, I gave the ThinkOn example, that's incredibly exciting because now if we can do that at scale, that's an opportunity to do that democratization that I spoke about. So, when I think about the things that are really exciting me about the data centre world, the world I live in, actually that power generation and power availability in a clean, effective, well-managed fashion is exactly what we need right now while the rest of us are solving these transistor problems. [01:05:58] Trevor Freeman: Yeah, it's I mean, our listeners are probably going to roll their eyes because I say this all the time, but one of the things that excites me the most is seeing like we're in a period of change, and and that's a really exciting time to be working in this, and I kind of hear that from you in in your sector as well, and I see it in mine, in the energy sector, of we're we're actually getting to see some of this innovation, some of these like leaps and bounds forward. That's not to say there aren't still problems, that's not to say there aren't steps backwards as well, but it it's very cool to be working on this at a time when we're seeing that change, and and that's kind of what I'm hearing from you as well. [01:06:34] Phil Harris: Indeed. [01:06:35] Trevor Freeman: Awesome. Phil, thanks so much for your time. I really appreciate it. This has been great chatting with you. [01:06:39] Phil Harris: Trevor, the pleasure was all mine. Thank you. [01:06:41] Trevor Freeman: Fantastic. Take care. [01:06:42] Phil Harris: Take care. [01:06:43] Podcast Outro: Thanks for tuning in to another episode of the Think Energy podcast. Don't forget to subscribe wherever you listen to podcasts, and it would be great if you could leave us a review. It really helps to spread the word. As always, we would love to hear from you, whether it's feedback, comments, or an idea for a show or a guest. You can always reach us at thinkenergy@hydroottawa.com.

Syncthing saves the day in an unexpected way, and we dig into what's new in Linux 7.2.Sponsored By:Jupiter Party Annual Membership: Put your support on automatic with our annual plan, and get one month of membership for free!Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love.Support LINUX UnpluggedLinks:Web Boost — Send us a boost via sats or USD

Nesse episódio trouxemos as notícias e novidades do mundo da programação que nos chamaram atenção dos dias 08/08 a 14/08.

Nesse episódio trouxemos as notícias e novidades do mundo da programação que nos chamaram atenção dos dias 08/08 a 14/08.

Seven Linux kernels landed in one day. We sort out which belong in your homelab, and trace Linux's long, occasionally disastrous quest for truly random numbers.Sponsored By:Jupiter Party Annual Membership: Put your support on automatic with our annual plan, and get one month of membership for free!Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love.Support LINUX UnpluggedLinks:Web Boost — Send us a boost via sats or USD

This week, we discuss Bun's move to Rust, OpenAI hunting for revenue, and Stripe's bid for PayPal. Plus, Coté's Dad wisdom. Watch the YouTube Live Recording of Episode 582 Runner-up Titles Turn off my dog Dad Wisdom Amazon subscription and let it fly Dad box Talking about modernization Skin in the game The ivory tower of “Things Actually Work in the Real World” Business fortnight No SegwaysBanking works everywhere else in the world, not America Rundown Rewriting Bun in Rust OpenAI OpenAI's No. 2 Executive to Step Down in Latest Leadership Shake-up OpenAI's Chief Futurist Is Leaving the Company AI Devices Are Coming. Will Your Favorite Apps Be Along for the Ride? OpenAI Executive Kevin Weil Is Leaving the Company OpenAI power consolidates under co-founder Greg Brockman ahead of prospective IPO Barret Zoph is out at OpenAI again after just five months Apple sues OpenAI, accuses ex-employees of stealing trade secrets OpenAI Appears to Be Missing Its Sales Goals by a Vast Margin Stripe, Advent make $53 billion takeover offer for PayPal, sending stock soaring Relevant to your Interests SpaceX, AI Bubble Fears, and The Age of the Trillion-Dollar, Zero-Profit Company Microsoft Frontier Company: AI engineering that amplifies and protects your intelligence Building a CLI for all of Cloudflare California founder fired for ignoring his company's own return-to-office mandate Samsung chip division's single-year profits beat its past 40 years of profits, combined Did a lottery winner become "the company of the future"? Power company hikes data center bills by 30%, cuts residential electricity costs by 1.3% Where AI Works: Slack is the Conversational Interface for Headless AI Salesforce MCP Servers: AI, Data & Analytics for Tableau & Data 360 in Slack IBM and Red Hat launch Lightwell to defend open-source code from AI attacks Infoblox acquires Kentik, adding network observability to its DNS and DDI platform Apple 'Hide My Email' Vulnerability Reveals Peoples' Real Email Addresses House passes bill to make daylight saving time permanent United Airlines' new upsell: Keeping other travelers out of the middle seat Linux creator Linus Torvalds puts foot down on anti-AI comments 1Password now lets Claude sign in to websites without seeing your passwords 1Password and Anthropic Bring Secure Credential Access to Claude forum, an accountable orchestrator for AI agents Google continues its renaming streak by turning NotebookLM to Gemini Notebook 'Pretty revolting': LG's TV are getting huge backlash from users due to installing software What is a micro-retirement? Inside the latest Gen Z trend You paid me, a long-time Linux user, to use Windows 11 exclusively for a month China delivers a one-two punch to America's AI dominance Can Lenovo's World Cup AI Moment Cement Its Enterprise PC Dominance? AI Coding Tools Deliver Speed but Not Business Value Unless Wrapped in Process: China's Moonshot in Talks on Pre-IPO Funds at $50 Billion Value OpenAI and Hugging Face partner to address security incident during model evaluation AI won't fix your broken culture, but you can fix your broken culture Oracle Is Now Down 28% in a Month. Will the 52-Week Low of $132 Hold or Fold? IBM stock craters 23% after issuing second-quarter earnings warning Sheetz is quitting VMware, migrating 11,000 virtual machines Meta in Talks to Lease Computing Power to Anthropic in Potential $10 Billion Deal AWS cloud lead Dave Brown heads to Meta - report - DCD Amazon senior cloud executive departs after 18 years Meta Caps Internal AI Token Spending After Costs Approach Billions in 2026 Meta Compute Launch Sends AI Compute Stocks Tumbling Globally Agentic ransomware for automated database extortion Dark-Moon: Autonomous AI pentesting engine Sponsors Signadot: making sure AI-written code actually works. Nonsense Messi Beats Ronaldo in 2026 World Cup Password Breach Data Rankings United Airlines' new upsell: Keeping other travelers out of the middle seat Yes, you can now order DoorDash from the command line House passes bill to make daylight saving time permanent Listener Feedback Biogen hiring Associate Director, Enterprise Architecture in Triangle, NC Tim releases a font for developers whose close-up vision isn't what it used to be The Java Story | Official Trailer | Full Film Coming July 17th Conferences DevOpsDays Graz, Sept 4-5, 2026 Cloud Foundry Summit, Sept. 21st to 22nd, Heidelberg, Coté speaking. DevOpsDays Rockies, Sept. 22 – 23, 2026, Discount Code: 26DODSWEDEFTALK WeAreDevelopers NA, Sept 23-25, 2026, Discount Code: DEVPOD26 25 Free Tickets DevOpsDays Dallas, Sept 28-29, 2026 DevOpsDays Vilnius, Sep 30 - Oct 1, 2006 DevOpsDays Istanbul, Oct 24th, 2026, Coté keynoting. VMware User Group, Orlando, Oct 20-22, 2026 Cloud Native Denmark, Nov 19th, 2026, Copenhagen, Coté keynoting. SDT News & Community Join our Slack community Email the show: questions@softwaredefinedtalk.com Free stickers: Email your address to stickers@softwaredefinedtalk.com Follow us on social media: Twitter, Threads, Mastodon, LinkedIn, BlueSky Watch us on: Twitch, YouTube, Instagram, TikTok Book offer: Use code SDT for $20 off "Digital WTF" by Coté Sponsor the show Sponsor more podcasts with Failover Media Recommendations Brandon: entogo — Type a keyword. Go anywhere. 28 Years Later, The Bone Temple Matt: Vacation, not micro-retirement Coté: Wolf Hall books.

André David comanda mais um FIAP Decode ao lado de Jéssica Felix para debater a reposta de Linus Torvalds sobre a integração de códigos de IA no Linux, a proposta do novo aplicativo HyperTexting e a aposta de hardware da OpenAI para materializar o ChatGPT. Aperte o play! Decodifique novas conexões - André David: Linkedin e Instagram- Jéssica Felix: Linkedin⁠ Codecon Summit 2026 | 14 e 15 de Agosto   NOTÍCIAS: China diz que itens digitais de jogos podem ser herdados – grandes empresas discordam "Crie o seu próprio Linux": A resposta ácida de Linus Torvalds sobre código de IA  HyperTexting: novo aplicativo promete mudar a forma de navegar na internet  ChatGPT pode ganhar corpo em caixa de som sem tela Novo pixel pode mudar telas e câmeras no futuro  

La gente ha jugado y Kimi ha petado Patrocinador: Indexa es una forma sencilla de invertir cada mes. Ya sea en el SP500, donde están todas las empresas de las que hablamos normalmente (Meta, Amazon, Google, etc) o en Europa, Japón... En Indexa se encargan de gestionar tu cartera, según tu perfil inversor, para que tú te olvides. Si quieres saber más, te dejamos nuestro enlace para ahorrarte las comisiones de Indexa sobre los primeros 15.000 € en el enlace de la descripción o puedes contactar directamente con ellos, y estarán encantados de atenderte. https://indexacapital.com/t/rodqpW?utm_source=monosestocasticos&utm_medium=advertising&utm_campaign=monos-podcast Indexa además tiene una comisión total de apenas del 0,535 de media anual, por lo que es mucho más barata de media que los bancos tradicionales. - Kimi K3, Qwen 3.8 y lo que nos gusta un momento Deepseek - La gente ha jugado y Kimi ha petado - Netflix y Linus Torvalds nos dicen que los anti IA van perdiendo - Mira Murati y Thinking Machine Labs lanzan Inkling - La IA ayuda a los funcionarios a no tener que bajar a la calle monos estocásticos es el pódcast de inteligencia artificial presentado desde Málaga por Antonio Ortiz (@antonello) y Matías S. Zavia (@matiass). Hay un episodio nuevo cada jueves. Puedes unirte gratis a nuestro club social de Telegram y seguirnos en redes sociales: - Telegram https://t.me/monosclub - Twitter https://x.com/monospodcast - LinkedIn https://www.linkedin.com/company/monos-estoc-sticos/ - Instagram https://www.instagram.com/monosestocasticos - TikTok https://www.tiktok.com/@monosestocasticos - Bluesky https://monosestocasticos.bsky.social - Threads https://www.threads.com/@monosestocasticos - Facebook https://www.facebook.com/profile.php?id=61584654541061 Todos los episodios en YouTube: https://www.youtube.com/playlist?list=PL-6s6cUsxTnsY_V0rqQFURaHDYuXD0AXj Más enlaces al pódcast: https://cuonda.com/monos-estocasticos/links

In this episode, Kat Cosgrove (SIG Docs Technical Lead, SIG Release Subproject Lead, and Steering Committee member) and Natali Vlatko (SIG Docs Co-Chair, Steering Committee member for the TODO Group, and Open Source Architect at Cisco) join hosts Kaslin Fields and Abdel Sghiouar to discuss the newly published Kubernetes AI usage policy. We dive into the legal and administrative reasoning behind the policy—including why AI tools cannot legally sign the Contributor License Agreement (CLA) or co-author PRs—and explore how maintainers manage the influx of "AI slop" PRs, spam comments, and restricted AI note-taker bots in community meetings. The discussion highlights the balance between human accountability and AI as an enhancer, while sharing actionable advice on how new contributors can sustainably get involved with SIG Docs, issue wrangling, and the Kubernetes Release Team. Do you have something cool to share? Some questions? Let us know: web: kubernetespodcast.com mail: kubernetespodcast@google.com twitter: @kubernetespod bluesky: @kubernetespodcast.com News of the week Apple Native Container Tool for macOS 1.0: Apple has shipped version 1.0 of its native container tool for macOS. Built in Swift specifically for Apple Silicon, it departs from traditional shared-VM setups like Docker Desktop by isolating every single Linux container inside its own dedicated micro-VM using the native macOS Virtualization framework. Read more on Cloud Native Now. Google OpenRL: Google launched OpenRL, a new open-source project designed to streamline the training and reinforcement learning loops of large language models. The tool brings declarative, Kubernetes-style resource orchestration concepts to the messy process of AI model fine-tuning. Read more on Cloud Native Now. CNCF Welcomes New Members: At KubeCon CloudNativeCon India, the CNCF announced they added 14 new members, end Users, and non-profit organizations, highlighting the continued growth of the Cloud Native Ecosystem. One of the new members is Loveable, who was a recent guest on the show. We highly recommend you go listen to Episode 268 about the Agent Sandbox. Read the full announcement on PR Newswire. Is a Pod the Right Deployment Unit for an AI Agent?: Lin Sun from Solo published a community post on the CNCF blog questioning whether the classic Kubernetes Pod primitive is still the best abstraction for hosting autonomous, long-running AI agents and introducing Agent-substrate, a project attempting to bring a solution to the table. Read more on the CNCF Blog. Links from the interview Kubernetes AI Usage Policy – Read the community's official guidelines and rules for AI-assisted contributions. TODO Group Steering Committee – A Linux Foundation project bringing OSPO professionals and enthusiasts together. Contributor License Agreement (CLA) – Standard agreement required for all human contributors, which AI agents cannot legally sign. Kubernetes SIG Docs – Get involved with the documentation community. SIG Docs Style Guide – Learn the style guidelines for contributing to Kubernetes docs. Kubernetes SIG Release – Details on how to get involved with the release cycle. Links from the post-interview chat Linus Torvalds on AI LinkedIn Post – Torvalds' clarification on using AI as a helper tool rather than writing kernel C++ code. Devoxx– A popular developer conference in Europe Prowbot GitHub Repo – Kubernetes' main CI/CD bot handling PR automation.

Topics covered in this episode: django-orjson Best Django Redis configuration for speed and size Linus Torvalds puts the foot down against Anti-AI Kernel Maintainers Django Steering Council backs the Triptych Project Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Consulting from Six Feet Up Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Michael #1: django-orjson Adam Johnson dropped django-orjson - drop-in replacements for the Django and DRF pieces that touch JSON, swapping stdlib json for orjson, the Rust-based library. Headline numbers: 10x faster serialization, 2x faster deserialization. The interesting question is why this needs to be a package at all. pip install orjson is the easy part. Adam's actual pitch: adopting it "isn't easy, especially when your framework uses json in many different parts." Django scatters JSON across JsonResponse, the test client and test case classes, the json_script template tag, and more. There's no single hook to grab, so you get a library that catches them all. Adam is refreshingly honest about the scale of the win. His words: "While database queries tend to dominate the typical Django application's runtime, the time spent in serialization and deserialization can still be significant." He calls it "a nearly free performance win" - not "this will 10x your app." That's a claim about cost, not magnitude, and it's worth keeping those straight. Worth flagging what the post doesn't cover: caveats. There are none in the article, but orjson has real ones. Django and Flask both render datetimes as RFC 822 HTTP-date (Wed, 15 Jul 2026 12:00:00 GMT); orjson does ISO 8601. It can't do ensure_ascii, it rejects NaN and Infinity (which stdlib happily emits), and it raises on Decimal. If you've got a JS client parsing dates, that's a wire-format change. Who should actually take this? If you're a DRF shop shoveling JSON all day, yes - it's cheap and it's real. If your app mostly renders HTML templates, you're optimizing a slice of runtime that's already near zero. The problem Adam's package solves doesn't exist in Flask or Quart. They already centralize every JSON operation - jsonify, request.get_json(), the test client, the |tojson filter - behind one provider object at app.json. So there's no library to install. It's about ten lines: import orjson from quart.json.provider import JSONProvider # or flask.json.provider class OrjsonProvider(JSONProvider): def dumps(self, obj, **kwargs) -> str: return orjson.dumps(obj).decode() # provider must return str def loads(self, s, **kwargs): return orjson.loads(s) app.json = OrjsonProvider(app) The numbers on talkpython.fm Evaluated it, measured it, and skipped it. The biggest JSON payload we serve is our MCP server returning a cached episode transcript, about 139 KB. Swapping the provider saves 0.119 milliseconds per request. That total response takes 1.1 ms We got 4.1x, not 10x - and the reason is the good lesson. Payload shape decides your speedup. The 10x is for structure-heavy data, lots of small keys where stdlib burns time in Python-level dispatch per item. Our hot payload is one giant transcript string, so the work is escaping and memcpy Calvin #2: Best Django Redis configuration for speed and size Peter Bengtsson revisits a classic: his 2017 "Fastest Redis configuration for Django" benchmark now has a 2026 update posted this week. The 2017 post pitted django-redis serializers (json, ujson, msgpack, pickle) and compressors (zlib, lzma) against each other; conclusion was msgpack + zlib as the sweet spot - avoid the json serializer, it's fat and slow. The 2026 update narrows focus to just compressors: default (no compression), zlib, lzma, and newcomer zstd. New results: lzma compresses best but is slowest; zstd is the fastest compressor on Ubuntu; differences between them are very small. Big takeaway across both: compression buys you a lot of space (2–3.5x smaller) for very little speed cost - worth it for Redis where memory is the constraint. Caveat from the author: results depend heavily on your data - his test stores short strings of numbers, so benchmark your own workload. Michael #3: Linus Torvalds puts the foot down against Anti-AI Kernel Maintainers Write up on Ars. Really good coverage by Maximillian: Time to wake up (for some) Torvalds said that “Linux is not one of those anti-AI projects, and if somebody has issues with that, they can do the open-source thing and fork it. Or just walk away.” I agree with Max, putting your head in the sand and waiting for AI to go away will likely mean you won't be working professionally in software development in the coming years. The statement came amid a lengthy thread arguing about the use of Sashiko, an “agentic Linux kernel code review system” that its creators claim can, in tests, independently find 53.6 percent of the bugs that would end up being fixed by human coders in later commits. “We're not forcing anybody to use [LLM tools], but I will very loudly ignore people who try to argue against other people from using it,” Torvalds said. “Anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time,” Torvalds wrote. Calvin #4: Django Steering Council backs the Triptych Project Django Steering Council issued a Letter of Collaboration backing Carson Gross & Alex Petros's funding bid for the Triptych Project - three proposals to make HTML more expressive natively, in every browser. The three additions: PUT/PATCH/DELETE methods for forms, button actions (buttons that fire HTTP requests without a wrapping form), and partial page replacement. Distills the core ideas from HTMX/Unpoly/Turbo into the HTML standard itself - no JS, no library, nothing to ship or maintain. Current focus is button actions (WHATWG #12330): Logout instead of wrapping a button in a form. Relevant to Django directly - think the admin submit row and disguised delete links; Django 6.0's template partials were already inspired by these patterns. How to help: companies can send non-binding letters of support on letterhead; individuals can read the proposals and weigh in on the WHATWG issues. Extras Calvin: DOOMQL - A playable first-person shooter whose framebuffer is a SQL query. Michael: Granian 2.7.9 fixes WSGI threadpool scheduler starvation/underscaling Welcome Calvin post Joke: Solving all bugs

What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

Linus delivers a blunt verdict on AI in the Linux kernel, Chris finds the remote Linux desktop that finally works, and Brent gives his notes system a serious rebuild.Sponsored By:Jupiter Party Annual Membership: Put your support on automatic with our annual plan, and get one month of membership for free!Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love.Support LINUX UnpluggedLinks:Web Boost — Send us a boost via sats or USD

What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

What happens when China drops open-weight AI models that rival Silicon Valley's best? This episode unpacks how a new wave of international AI releases is shaking up business, policy, and the future of innovation. Linus Torvalds to critics of AI coding in Linux: "Fork it. Or just walk away." Claude on X: "Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. Demand for Fable has been challenging to" China's Moonshot AI Unveils Kimi Model, Threatening America's Lead Alibaba's Qwen Unveils Preview of Flagship AI Model Social media limits are coming for teens across Europe The White House is now deciding who gets access to frontier AI models, not the labs Microsoft chief turns hostile on frontier AI labs, warns companies to guard their IP Meta Is Flooding the Market With Smartglasses. Privacy Advocates Are Up in Arms. Federal employees can download TikTok on government devices, DOJ says Amazon Web Services customers receive bills for up to $1.5tn after global glitch MLB cracks down on using AI via dugout iPads to help shape in-game decisions White House Teleprompter Operator Bet on Trump Speeches, Kalshi Says New York school district is testing lifelike robot teachers Host: Leo Laporte Guests: Harper Reed and Alex Wilhelm Download or subscribe to This Week in Tech at https://twit.tv/shows/this-week-in-tech Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Sponsors: blackhat.com/us-26 and use code TWIT ZipRecruiter.com/twit ethos.com/twit arcticwolf.com/trends threatlocker.com/twit shopify.com/twit

Crime Radar segnala una sparatoria inventata. Linus Torvalds chiude la discussione sull'AI. YouTube e lo scudo di responsabilità nell'UE. AI Slop come I film direct-to-video. La storia d Guybrush Threepwood. Queste e molte altre le notizie tech commentate nella puntata di questa settimana.Dallo studio distribuito di digitalia:Franco Solerio, Francesco Facconi, Massimo De SantoProduttori esecutivi:Simone Podico, Anonimo Bitcoin, Denis Grosso, Mario Cervai, Umberto Marcello, Andrea Giovacchini, Riccardo Famà, Andrea Malesani, Luca Ongaro, Enrico, Daniele Bastianelli, Beconsulting, Fabrizio Reina, Calogero Augusta, Alessio Ferrara, Cristian Pastori, Michele Trabanelli, Donato Gravino, Emanuele Libori, Marco Grechi, Jh4Ckal@Fountain.Fm, Angelo Travaglione, Arzigogolo, Michelangelo Rocchetti, Nicola Grilli, Alessandro Martellotta, Manuel Giannatempo, Claudio Schifanella, Jean Dal Bo, Akagrinta@Fountain.Fm, Giorgio Puglisi, Andrea Guido, Giuliano Arcinotti, Edoardo Volpi Kellerman, Alessandro Grossi, Davide Porta, Silvio Mariuzzo, Davide Tinti, Gabriele Marinelli, Vito Astone, Enrico Carangi, Mario Giammona, Ppogo@Fountain.Fm, Fiorenzo Pilla, Davide Maffoli, Joanpiretz@Fountain.Fm, Cristian De Solda, Tytan, Giacomo Fantozzi, Valerio Galano, Fabio BrunelliSponsor:Squarespace.com - utilizzate il codice coupon "DIGITALIA" per avere il 10% di sconto sul costo del primo acquisto.Links:Introducing the Codex MicroTesla driver in fatal Texas crash pressed accelerator 100%Var e AI hanno una cosa in comuneCrime app using AI generated false report of UA shootingLinux creator Linus Torvalds puts foot down on anti-AI commentsLLM-gen-AI - Software Freedom ConservancySperm donors need limits, says a European fertility groupYouTube may lose EU liability shield for videos on partnered channelsGoogle ordered to open Android and Search to rivals in EuropeChatGPT is back on WhatsApp across the EEA and SwitzerlandUber Announces Acquisition Offer for Delivery HeroStripe e Advent hanno fatto un'offerta congiunta per PayPalDigitalia distillataYour App Could Have Been a Webpage (so I fixed it for you)Hans-Hermann Hoppe - Democrazia: il dio che ha fallitoAI slop movies are the new direct-to-video cash grabsNetflix ha fatto un videogioco per appassionati di film horrorCan Meta make its smart glasses a viable fashion accessory?People With “Pervert Glasses” Are Afraid to Use Them in PublicSamsung will delete your health data if you don't let them use it to train AIGingilli del giorno:BUSY Bar - Productivity Multi-tool Device with an LED pixel screenSolarPunk - uno sguardo diverso e finalmente utopistico sul futuroTaken - Pillola rossa o pillola blu?Supporta Digitalia, diventa produttore esecutivo.

AI is stirring up heated debate in the Linux world, but Linus Torvalds' pragmatic stance may surprise you. Hear why the kernel isn't slamming the door on artificial intelligence and what it means for open source development. Also, Elon Musk claims X will go fully open source, but will this shift redefine trust and innovation on social platforms, or is it just more empty hype? Host: Jonathan Bennett Co-Hosts: Ken McDonald and Rob Campbell Download or subscribe to Untitled Linux Show at https://twit.tv/shows/untitled-linux-show Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsor: blackhat.com/us-26 and use code TWIT

video: https://youtu.be/CVkZvrh7qpw Ubuntu is shipping a kernel that can make certain AMD workloads up to 42 times slower. Linus Torvalds is drawing clearer boundaries around AI-generated code in the kernel. Secure Boot just passed a major certificate expiration deadline. COSMIC Desktop 1.3 brings a polished new Frosted Glass design. And one developer decided to add another place and that's a Sega Genesis from 1994. All of this and more on This Week in Linux. Now let's jump right into Your Source for Linux GNews! Download as MP3 Support the Show Become a Patron = tuxdigital.com/membership Store = tuxdigital.com/store Chapters: 00:00 Intro 00:44 Ubuntu publishes Update that introduces regression for AMD users 03:52 Linus Torvalds talks on AI Code in Linux 07:12 Secure Boot Linux Certificates Expired? 09:27 COSMIC 1.3 with Frosted Glass 11:33 AppManager for AppImages 14:51 FreeBSD Removes All GPL Code 17:16 Rapid Fire Lightning Round 17:40 stillOS 10.2 Released 18:32 Blender 5.2 LTS Released 19:00 Clonezilla Live 3.3.3 Released 19:31 Linux on Sega Genesis and 32X Addon 20:26 Outro Links: Ubuntu publishes Update that introduces regression for AMD users https://discourse.ubuntu.com/t/amdgpu-performance-regression-in-kernel-7-0-0-28-28/85237 Linus Torvalds talks on AI Code in Linux https://lore.kernel.org/linux-media/CAHk-=wi4zC+Ze8e+p3tMv8TtG_80KzsZ1syL9anBtmEh5Z40vg@mail.gmail.com/ https://www.phoronix.com/news/Linux-Is-Not-Anti-AI https://www.gamingonlinux.com/2026/07/linux-creator-linus-torvalds-puts-foot-down-on-anti-ai-comments/ https://itsfoss.com/news/linus-torvalds-on-ai/ Secure Boot Linux Certificates Expired? https://lwn.net/Articles/1079808/ https://almalinux.org/blog/2026-07-14-secure-boot-2023-certificates/ https://linuxiac.com/debian-13-6-released-with-120-security-fixes-and-124-stability-updates/ COSMIC 1.3 with Frosted Glass https://9to5linux.com/cosmic-1-3-desktop-environment-released-with-frosted-glass-effect https://www.phoronix.com/news/COSMIC-Epoch-1.3 AppManager for AppImages https://github.com/kem-a/AppManager https://www.omgubuntu.co.uk/2026/07/appmanager-appimage-installer-linux https://github.com/VHSgunzo/uruntime FreeBSD Removes All GPL Code https://www.phoronix.com/news/FreeBSD-16-Goes-GPL-Free https://fossforce.com/2026/07/freebsd-16-cleans-house-no-gpl-left-in-the-base-system/ https://www.phoronix.com/news/FreeBSD-Intern-AMD-ROCm https://www.phoronix.com/news/FreeBSD-Laptops-June-2026 https://www.phoronix.com/news/FreeBSD-Desktop-Install-NVIDIA stillOS 10.2 Released https://stillhq.io/stillos-gets-gnome-49-a-better-first-boot-and-major-swai-improvements/ Blender 5.2 LTS Released https://www.blender.org/download/releases/5-2/ Clonezilla Live 3.3.3 Released https://clonezilla.org/downloads/stable/release-notes.php Linux on Sega Genesis and 32X Addon https://cakehonolulu.github.io/linux-on-32x/ https://github.com/LinuxMD/linuxmd https://www.tomshardware.com/software/linux/developer-successfully-ports-linux-to-1994-sega-32x-genesis-and-megadrive-expansion-runs-open-source-os-on-paltry-23mhz-processors-and-256kb-of-ram Support the show https://tuxdigital.com/membership https://store.tuxdigital.com/

AI is stirring up heated debate in the Linux world, but Linus Torvalds' pragmatic stance may surprise you. Hear why the kernel isn't slamming the door on artificial intelligence and what it means for open source development. Also, Elon Musk claims X will go fully open source, but will this shift redefine trust and innovation on social platforms, or is it just more empty hype? Host: Jonathan Bennett Co-Hosts: Ken McDonald and Rob Campbell Download or subscribe to Untitled Linux Show at https://twit.tv/shows/untitled-linux-show Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsor: blackhat.com/us-26 and use code TWIT

News sources: https://lmg.gg/L8hqh Timestamps: 0:00 Linus Torvalds welcomes AI coding 1:14 Lenovo's inkjet-printed OLED laptop 2:32 EU forces Google to open Android 4:04 QUICK BITS INTRO 4:13 Ransomware halts Fairlife production 4:44 Samsung foldable specs leak 5:20 Moonshot unveils Kimi K3 5:56 23andMe settles its data breach 6:30 OpenAI sells a $70 basketball 7:04 Credits Learn more about your ad choices. Visit megaphone.fm/adchoices

Nesse episódio trouxemos as notícias e novidades do mundo da programação que nos chamaram atenção dos dias 04/07 a 10/07.

Nesse episódio trouxemos as notícias e novidades do mundo da programação que nos chamaram atenção dos dias 04/07 a 10/07.

Hoje o papo é sobre a nova era do desenvolvimento de software! Neste episódio, conversamos sobre o aumento no volume de código gerado por IA e os desafios de revisar, governar e levar essas mudanças para produção. O papo também passa por novos processos de desenvolvimento, modelos locais e abertos, harnesses, contexto e orquestração de agentes. Vem ver quem participou desse papo: Paulo Silveira, o host que usa a palavra governança Vinny Neves, cohost, dev e professor na Alura Juliano Martins, Head de Plataforma na nullplatform Zarathon “Zara” Viana, Head de Engenharia do QuintoAndar Mauricio Aniche, CTO da Alura  Links:  Newsletter Zara Tips Harness Engineering, por Juliano Martins Stacked Diffs — The Pragmatic Engineer GitHub Stacked PRs Palestra do Linus Torvalds sobre git Stripe Minions — parte 1 Stripe Minions — parte 2 Claude Code OpenAI Codex OpenCode OpenRouter Kimi DeepSeek-V4-Flash Codex CLI Como funciona o loop do Codex DHH fala sobre agentes de código Addy Osmani fala sobre o Gemma 4 12B rodando localmente no Mac Compound Engineering Toda revolução tecnológica começa com quem antecipa o futuro e transforma ideias em soluções de alto impacto. Conheça os cursos da Alura + FIAP Skills & Go: Agentic Engineering, Building AI Products, e AI Data Strategy. Saiba mais sobre o Skills & Go. Vá para o Vale do Silício com Paulo Silveira, Marcell Almeida, Fabrício Carraro e Marcus Mendes na “Imersão IA Sob Controle e Alura no Vale do Silício“! Vagas limitadas, corra para reservar a sua. TechGuide.sh, um mapeamento das principais tecnologias demandadas pelo mercado para diferentes carreiras, com nossas sugestões e opiniões. #7DaysOfCode: Coloque em prática os seus conhecimentos de programação em desafios diários e gratuitos. Acesse https://7daysofcode.io/ Produção e conteúdo: Alura Cursos de Tecnologia – https://www.alura.com.br Edição e sonorização: Rede Gigahertz de Podcasts

This week on AwesomeCast, Sorg is joined by Dave Podnar while Katie is on assignment. The crew digs into practical tech, gaming platforms, open-source operating systems, sports broadcast innovation, retro-inspired phones, and one very funny automated social media mistake involving DoorDash, soccer, and T-Pain. Stories and gadgets discussed: Dave's Awesome Thing of the Week: Shokz OpenRun Pro 2 headphones Dave finally upgrades from cheap running headphones to the Shokz OpenRun Pro 2, praising the open-ear / bone-conduction-style design for running safety, comfort, sweat management, USB-C charging, and situational awareness. Link: https://www.amazon.com/dp/B0D2HKCMBP?maas=maas_adg_api_582366218564361552_static_9_129&ref_=aa_maas&tag=maas&aa_campaignid=lv_IGvrl5TTBxiweexlXK&aa_adgroupid=lv_fdLHIcjvJhpJZvQxFb&aa_creativeid=lv_MMLFRb8MTdZvGlnqFv&gad_campaignid=23921418215&gbraid=0AAAABDw_RJg26Vr6MY-sVAPsmwCxwK4mX&gclid=CjwKCAjw3ejRBhAdEiwADkqPn36qoEfzRElmQ3e9OXSxZdGKjw0DyckEdeqo82D8qqlMdTFDyLXuXhoCVn8QAvD_BwE&th=1 Valve opens the door to SteamOS installs on AMD PCs Sorg talks about Valve allowing SteamOS installs on normal PCs with AMD GPUs, giving PC gamers a way to build their own living-room Steam Machine instead of buying Valve's new box. The conversation also touches on Steam Deck, Linux gaming, Proton, GPU costs, tariffs, and the economics of gaming hardware. Link: https://www.pcgamer.com/hardware/steam-machines/valve-greenlights-steamos-installs-on-normal-pcs-with-amd-gpus-so-you-can-go-make-your-own-steam-machine-if-you-dont-wanna-fork-over-usd1-049/?brid=YWdncwFV2uAIYy2jMECl21FxWfGS Bazzite as an open-source SteamOS-style alternative Sorg brings up Brother Sorg's recommendation of Bazzite, a Linux-based gaming OS with Steam gaming mode and support for launchers like Xbox Game Pass, Battle.net, EA, Epic Games Store, GOG, Rockstar, and Ubisoft Connect. Link: https://bazzite.gg/ Pride Month tech history: Jon “maddog” Hall Dave spotlights Jon “maddog” Hall, a major Linux and Unix figure, sharing stories about Hall's long programming history, his connection to Linus Torvalds, and the importance of recognizing LGBTQ contributors in technology history. Article: https://www.lpi.org/blog/2025/09/10/a-lifetime-in-code-jon-maddog-hall-reflects-at-linuxfest-northwest/ Talk: https://www.youtube.com/watch?v=758QuvXrttM Chachi Says Video Game Minute: GTA 6, Nex Playground, and Ubisoft news Chachi covers three gaming stories: GTA 6 cover art and pre-orders, the Nex Playground motion-based console for kids, and the death of Claude Guillemot, co-founder of Ubisoft. GTA 6: https://www.ign.com/articles/gta-6-cover-artwork-revealed-pre-orders-begin-june-25 Nex Playground: https://www.bbc.com/news/articles/czx50rrz7zro Claude Guillemot: https://apnews.com/article/france-assassins-creed-ubisoft-plane-crash-2df2ea469c3fca0a45c38ae8805a6033 Baja SAE filmed on a “gas station camera” Sorg highlights a low-fi, retro-looking Baja SAE reel from Fairfield University, celebrating the charm of VHS-style and “bad camera” aesthetics in modern social media content. Link: https://www.instagram.com/reels/DZ6BjfCtzo-/ World Cup referee technology, digital twins, sensors, and 3D body scans Sorg discusses advanced soccer officiating tech, including camera sensors, player tracking, digital twins, and automated offside detection that can help reduce blown calls and give officials faster alerts. Link: https://apple.news/ABeSFqwyjRpehEy0x8Nc9nQ Ribbie turns MLB games into pixel-art broadcasts Dave shares Ribbie, a fan-built project that uses real-time Major League Baseball data to recreate live games as a retro 16-bit-style baseball broadcast. The conversation connects it to vibe coding, AI-assisted development, and new ways fans can build creative sports experiences. Link: https://techcrunch.com/2026/06/23/ribbie-turns-real-time-baseball-stats-into-arcade-like-pixel-art-broadcasts/ Commodore phone brings retro branding to a distraction-light flip phone Dave and Sorg look at the Commodore phone, a Sailfish OS-based flip phone designed as a step above a dumbphone, with calls, texting, maps, music apps, Uber/Lyft, classic Commodore games, and limited/no social media access. Link: https://order.commodore.net/callback-audio/?brid=YWdncwHwIXnsUg8Nsyh9q_45Lj2C DoorDash accidentally tags T-Pain in soccer posts The episode wraps with a funny social media fail where DoorDash appears to tag T-Pain instead of soccer player Tim Payne during World Cup-related posts. Sorg and Dave discuss automation, agency workflows, social scheduling, and why T-Pain's response made the whole situation better. Link: https://www.instagram.com/p/DZ56tKCnedX/?brid=YWdncwG5YHkt5InxWn1IZ1Apa3Gc&img_index=2

This week on AwesomeCast, Sorg is joined by Dave Podnar while Katie is on assignment. The crew digs into practical tech, gaming platforms, open-source operating systems, sports broadcast innovation, retro-inspired phones, and one very funny automated social media mistake involving DoorDash, soccer, and T-Pain. Stories and gadgets discussed: Dave's Awesome Thing of the Week: Shokz OpenRun Pro 2 headphones Dave finally upgrades from cheap running headphones to the Shokz OpenRun Pro 2, praising the open-ear / bone-conduction-style design for running safety, comfort, sweat management, USB-C charging, and situational awareness. Link: https://www.amazon.com/dp/B0D2HKCMBP?maas=maas_adg_api_582366218564361552_static_9_129&ref_=aa_maas&tag=maas&aa_campaignid=lv_IGvrl5TTBxiweexlXK&aa_adgroupid=lv_fdLHIcjvJhpJZvQxFb&aa_creativeid=lv_MMLFRb8MTdZvGlnqFv&gad_campaignid=23921418215&gbraid=0AAAABDw_RJg26Vr6MY-sVAPsmwCxwK4mX&gclid=CjwKCAjw3ejRBhAdEiwADkqPn36qoEfzRElmQ3e9OXSxZdGKjw0DyckEdeqo82D8qqlMdTFDyLXuXhoCVn8QAvD_BwE&th=1 Valve opens the door to SteamOS installs on AMD PCs Sorg talks about Valve allowing SteamOS installs on normal PCs with AMD GPUs, giving PC gamers a way to build their own living-room Steam Machine instead of buying Valve's new box. The conversation also touches on Steam Deck, Linux gaming, Proton, GPU costs, tariffs, and the economics of gaming hardware. Link: https://www.pcgamer.com/hardware/steam-machines/valve-greenlights-steamos-installs-on-normal-pcs-with-amd-gpus-so-you-can-go-make-your-own-steam-machine-if-you-dont-wanna-fork-over-usd1-049/?brid=YWdncwFV2uAIYy2jMECl21FxWfGS Bazzite as an open-source SteamOS-style alternative Sorg brings up Brother Sorg's recommendation of Bazzite, a Linux-based gaming OS with Steam gaming mode and support for launchers like Xbox Game Pass, Battle.net, EA, Epic Games Store, GOG, Rockstar, and Ubisoft Connect. Link: https://bazzite.gg/ Pride Month tech history: Jon “maddog” Hall Dave spotlights Jon “maddog” Hall, a major Linux and Unix figure, sharing stories about Hall's long programming history, his connection to Linus Torvalds, and the importance of recognizing LGBTQ contributors in technology history. Article: https://www.lpi.org/blog/2025/09/10/a-lifetime-in-code-jon-maddog-hall-reflects-at-linuxfest-northwest/ Talk: https://www.youtube.com/watch?v=758QuvXrttM Chachi Says Video Game Minute: GTA 6, Nex Playground, and Ubisoft news Chachi covers three gaming stories: GTA 6 cover art and pre-orders, the Nex Playground motion-based console for kids, and the death of Claude Guillemot, co-founder of Ubisoft. GTA 6: https://www.ign.com/articles/gta-6-cover-artwork-revealed-pre-orders-begin-june-25 Nex Playground: https://www.bbc.com/news/articles/czx50rrz7zro Claude Guillemot: https://apnews.com/article/france-assassins-creed-ubisoft-plane-crash-2df2ea469c3fca0a45c38ae8805a6033 Baja SAE filmed on a “gas station camera” Sorg highlights a low-fi, retro-looking Baja SAE reel from Fairfield University, celebrating the charm of VHS-style and “bad camera” aesthetics in modern social media content. Link: https://www.instagram.com/reels/DZ6BjfCtzo-/ World Cup referee technology, digital twins, sensors, and 3D body scans Sorg discusses advanced soccer officiating tech, including camera sensors, player tracking, digital twins, and automated offside detection that can help reduce blown calls and give officials faster alerts. Link: https://apple.news/ABeSFqwyjRpehEy0x8Nc9nQ Ribbie turns MLB games into pixel-art broadcasts Dave shares Ribbie, a fan-built project that uses real-time Major League Baseball data to recreate live games as a retro 16-bit-style baseball broadcast. The conversation connects it to vibe coding, AI-assisted development, and new ways fans can build creative sports experiences. Link: https://techcrunch.com/2026/06/23/ribbie-turns-real-time-baseball-stats-into-arcade-like-pixel-art-broadcasts/ Commodore phone brings retro branding to a distraction-light flip phone Dave and Sorg look at the Commodore phone, a Sailfish OS-based flip phone designed as a step above a dumbphone, with calls, texting, maps, music apps, Uber/Lyft, classic Commodore games, and limited/no social media access. Link: https://order.commodore.net/callback-audio/?brid=YWdncwHwIXnsUg8Nsyh9q_45Lj2C DoorDash accidentally tags T-Pain in soccer posts The episode wraps with a funny social media fail where DoorDash appears to tag T-Pain instead of soccer player Tim Payne during World Cup-related posts. Sorg and Dave discuss automation, agency workflows, social scheduling, and why T-Pain's response made the whole situation better. Link: https://www.instagram.com/p/DZ56tKCnedX/?brid=YWdncwG5YHkt5InxWn1IZ1Apa3Gc&img_index=2

Your favorite open source projects have been busy. We round up the new releases worth knowing about, plus the big kernel changes headed your way soon.Sponsored By:Webroot: Webroot is cloud-based antivirus, engineered to stay out of your way. For a limited time, you can save sixty percent.Jupiter Party Annual Membership: Put your support on automatic with our annual plan, and get one month of membership for free!Managed Nebula: Meet Managed Nebula from Defined Networking. A decentralized VPN built on the open-source Nebula platform that we love.Support LINUX UnpluggedLinks:AppleTalk 1985-2026 Memorial StickerSorry, I only open regular files StickerWebroot — Save sixty percent when you go to webroot.com/unplugged.

video: https://youtu.be/RCmZKZB-Mf8 The Linux News this week was jam packed. Linus Torvalds announced a new release of the Linux kernel. KDE announced a new release of the Plasma desktop. We've got an update on the AUR Malware from last week, it got better and then worse. Commodore revealed their next product, the Commodore Callback a Smart dumb phone. Yea I know. Plus there's some rumbles going on about the Return of Antergos Linux, we'll talk about that All of this and more on This Week in Linux, the weekly news show that keeps you up to date with what's going on in the Linux and Open Source world. Now let's jump right into Your Source for Linux GNews! Download as MP3 Support the Show Become a Patron = tuxdigital.com/membership Store = tuxdigital.com/store Chapters: 00:00 Intro 00:50 Linux 7.1 Released 03:36 KDE Plasma 6.7 Released 08:40 Antergos Linux Returns?! 16:08 AUR Malware Update for Arch Linux Users 19:39 Commodore Callback, a Smart Dumbphone 25:48 Epic Games Launches Lore Version Control System 28:24 DistroWatch Goes Down, Backups Save the Day 29:59 Outro Links: Linux 7.1 Released https://www.omgubuntu.co.uk/2026/06/linux-7-1-kernel-features https://www.phoronix.com/news/Linux-7.1-Released https://9to5linux.com/linux-kernel-7-1-officially-released-heres-whats-new https://www.gamingonlinux.com/2026/06/linux-kernel-7-1-out-now-with-new-ntfs-driver-lots-of-hardware-improvements/ KDE Plasma 6.7 Released https://kde.org/announcements/plasma/6/6.7.0/ https://quantumproductions.info/articles/2026-05/union-spring-2026-update Antergos Linux Returns?! https://github.com/Antergos-NeXT https://9to5linux.com/first-look-at-antergos-next-a-modern-revival-of-antergos-linux-with-kde-plasma https://distrowatch.com/dwres.php?resource=showheadline&story=20201 AUR Malware Update for Arch Linux Users https://lwn.net/Articles/1077619/ https://www.gamingonlinux.com/2026/06/the-security-situation-with-the-arch-linux-aur-got-a-lot-worse/ https://www.phoronix.com/news/Arch-Linux-AUR-More-Malware https://www.phoronix.com/news/Arch-Linux-AUR-More-Than-1500 https://itsfoss.com/news/yay-v13-release/ https://itsfoss.com/news/arch-linux-aur-malware-flood/ https://fossforce.com/2026/06/arch-says-alls-clear-after-aur-malware-incident-affects-1500-packages/ https://fossforce.com/2026/06/aur-registrations-blocked-amid-ongoing-malware-mess/ https://fossforce.com/2026/06/aur-to-arch-houston-weve-got-a-problem-were-under-attack-again/ https://www.phoronix.com/news/Arch-Linux-AUR-Russian-Spam Commodore Callback, a Smart Dumbphone https://commodore.net/callback/ https://itsfoss.com/news/commodore-callback-8020-launch/ https://arstechnica.com/gadgets/2026/06/commodores-newest-gadget-is-a-flip-phone-that-blocks-social-media-and-browsers/ https://www.tomshardware.com/phones/commodore-announces-linux-based-flip-phone-with-no-social-media-no-browser-the-callback-8020-will-be-available-in-five-retro-colorways-starting-at-usd499-runs-99-percent-of-android-apps https://www.wired.com/story/commodore-callback-8020-is-a-digital-detox-phone-that-isnt-dumb/ Epic Games Launches Lore Version Control System https://lore.org/ https://www.phoronix.com/news/Epic-Games-Lore-VCS https://itsfoss.com/news/lore-launched/ https://www.gamingonlinux.com/2026/06/unreal-engine-6-is-all-about-generative-ai-fortnite-and-the-verse/ https://www.theregister.com/devops/2026/06/17/git-good-with-epic-games-new-open-source-vcs-lore/5257978 DistroWatch Goes Down, Backups Save the Day https://distrowatch.com/ https://www.patreon.com/distrowatch/posts/server-outage-161521259 https://mastodon.social/@distrowatch Support the show https://tuxdigital.com/membership https://store.tuxdigital.com/

A version of this essay has been published by Open Magazine at https://openthemagazine.com/world/india-will-collapse-without-digital-sovereignty-and-pax-indica-lessons-from-hormuzBy now it is clear that the Iran War (or West Asia War) has been a disaster to all concerned, including the principals as well as assorted passersby. The massive amounts spent by the US (at last count $25 billion) are at least articulated; the bill for the enormous infrastructural and human suffering inflicted on Gulf states, in the theater of war, must be greater, by definition.The collateral damages suffered by the rest of the world from the cessation of trade through the Straits of Hormuz will presumably run into the trillions of dollars. As one of the worst affected, India, which imports 90% of its hydrocarbons from the Gulf, not to mention other essential items such as urea (for fertilizer), sulfuric acid, helium, etc., is on track to take a massive hit. As an article in The Economic Times said, “India must brace for broad-based economic shock”.Indian exports of up to $50 billion are also affected, especially agricultural products including perishable foodstuffs, but also gems and jewellery, electronics, textiles and garments. Some of this can be diverted via Oman and the UAE's Fujairah port, but much of it passes through the Straits of Hormuz and is potentially blocked and/or stranded at sea.The Hormuz closure is a body blow to India's economy. What can and will India do about it? The Indian State has a habit of rising to the challenge only when there is a crisis, while vegetating otherwise. The 1991 economic crisis is a case in point; the sanctions following “The Buddha is smiling”, and the denial of cryogenic rocket engines and supercomputers are other examples where the nation rallied. So were covid vaccines. Necessity, they say, is the mother of invention.Turning a threat into an opportunityIf I were to be an optimist, I could say that the current crisis is actually an opportunity. In fact, a major opportunity. My reading of the Iran War is that it is President Trump's strategic tit-for-tat against China for denying him rare earths and cutting off soybean purchases. In return Trump decided to deny China access to oil by closing access to Venezuela and Iran. Whether this will work, or whether the G2 condominium (read ‘surrender') will prevail, is unclear.But that is, in a sense, background noise that needs to be managed. India needs to focus on its own issues, of which I see several as critical, and the solution in general is to become Atmanirbhar, self-reliant, and from that, to create an Anti-Fragile nation:* National security/defense* Food security* Energy security* Digital security/narrative control* Trade securityThe first three do not need an explanation: they are obvious. Internal and external security are pre-requisites for any successful society. If India's hard-won food security can be threatened by external threats, then there needs to be some deep introspection. Energy security means diversification, both of hydrocarbon sources, and of types of energy, including renewables, nuclear, biomass, coal-based, and so on.Malign narratives and digital sovereigntyNarrative control is something that the Indian State has failed at so far; it is laughably easy to create hate speech against Indians and India (as has been demonstrated freely by any number of players, starting from the MAGA crowd, to Audrey Truschke to a”Cockroach Janata Party” and some nitwit Norwegian journalist in just the last fortnight) and there are no consequences to the culprits. It's enough to make me pine for Lee Kuan Yew's aggressive legal battles against the media.It's one thing if it were only a problem with foreigners, but with the massive spread of social media, and in particular generativeAI, it is becoming a serious domestic issue. Since India is an avid consumer of social media, and because generativeAI is trained on things like Wikipedia, X, Whatsapp and Google content, biased and motivated material becomes ensconced as The Truth. I have written about narrative warfare and manufacturing consent.This used to be a one-way tsunami of (mis)-information by legacy media, but now there is also the opposite: the wholesale and free vacuuming-up of Indian data (whatever happened to “data is the new oil”?). The “Great Firewall of China” both kept out foreign BIg Tech applications and prevented their plundering Chinese data: is that the way to go?Manufactured narratives are intended for regime change: all the color revolutions today are hatched with massive bot-farms funded by some combination of Deep State, CCP, ISI, Qatar etc. (for example the alleged Gen-Z uprisings that rocked Nepal, drove Sheikh Hasina out of Bangladesh). Thus muzzling malign narratives, and ensuring data security, are imperative.Even Singapore is not immune: it had to block anti-India narratives that likely originated from Chinese sources.A particularly striking example of narrative warfare is the virtual hate speech inducted into Wikipedia by deeply prejudiced anonymous editors. Ashley Rindsberg, who exposed the mighty New York Times' biases in his book The Gray Lady Winked, provides many examples of this.Of note to Indians and Hindus is his recent substack titled “Wikipedia's India War” where he identifies just four editors as having created most of the content condemning the Hindu American Foundation (HAF) in ‘Wikivoice', i.e. the allegedly neutral perspective of Wikipedia. They are, on the contrary, shown to be highly one-sided.As Rindsberg mentions, Wikipedia being central to generativeAI, the damage is baked into the world-view of all AI applications. Truly Orwellian. Says Rindsberg: “four… anonymous accounts can have an enormous impact on what millions of people believe to be the truth.” “Over four years (2021-2025), editors systematically erased HAF's identity as an American civil rights group, transforming its Wikipedia page into a heavily curated dossier of accusations.”Trade, and how the Spice Route was far superior to the Silk RoadFinally, something that is becoming increasingly important: ensuring freedom of trade. This is more than just freedom of navigation, although I find it instructive that Emperor Rajendra Chola sent a huge fleet 1,001 years ago simply to open up the Straits of Malacca. India can make an active attempt to regain primacy in Indian Ocean trade, the whole Pax indica idea.Here is another example of the power of narrative: we have been led to believe that the Silk Road to China was some major highway of commerce between ancient Rome and ancient China, but it was a term coined only in 1877 by the German Ferdinand von Richthofen. There was no highway. A large caravan might take six months, and with 500 camels traversing treacherous deserts and braving bandits, it might carry a maximum of 100 tons. That is puny.In comparison, on the Spice Route, a single stitched ship from Muziris could carry 400 tons of ivory, pepper, silk, tigers and elephants; and the historian Strabo around 1 CE talks about fleets of 250 ships going from Alexandria to India on a six-week monsoon-powered journey. That is 100,000 tons of merchandise. No wonder Pliny the Elder complained that Rome's treasuries were being emptied of gold by India.Simple question: where are hoards of ancient Roman coins found in Asia? Answer: not along the Silk Road. The hoards are in Kerala, Tamil Nadu and Sri Lanka.Today, it is possible for India to aspire to port-led development of trade, especially with the major ports at Trivandrum (Vizhinjam), Maharashtra (Vadhavan), and Great Nicobar (Galathea Bay). The underlying ‘software' of India's millennia-old trade competency was a ‘multi-protocol switch' as I pointed out, and today's India Stack can replicate that. Then there is the need for a blue-water navy: muscle to provide security on the Hormuz to Malacca sea-lanes.So there is a vision. How can India get there? This is where policy matters, as I discussed with policy expert Anuj Gupta. Policy, especially industrial policy, has had a bad reputation in certain circles because it was deemed to violate the virginal purity of classical capitalism. However, in a recent U-turn, even the World Bank admitted that industrial policy may not be all that bad, after all: the success of Japan, the Asian Tigers, and China can't be ignored.That leads to the question of why policy in India has produced mediocre outcomes, what is different now, and where the best use of policy might be.Industrial Policy: What went wrong in the past?There are many problems here. To begin with, the Soviet model, which Nehruvians swore by, was, in hindsight, a dead end. Second, there is the problem of governance: post-Independence bureaucrats have awkwardly borne the legacy of imperial hauteur and the needs of a developing society. Third, until recently, the bare necessities (food, electricity, road access) were not available to many citizens, and GDP growth was not their priority.There is also the culture of jugaad: of clever ways in which you overcome constraints through frugal improvisation and seat-of-the-pants making-do. This is fine for one-off things (e.g. converting a tractor trailer into a makeshift transport vehicle because your truck broke down), but it does not make for efficient and replicable industrial products. As The Economic Times said recently, it is time to junk jugaad. Quality has to become ingrained in people's minds.The issue of governance is significant: the bureaucracy and the judiciary have both under-performed, politicians, as everywhere, have been venal. It is said that China's growth can be attributed to the fact that its babus are engineers, and therefore with engineering ruthlessness move in straight lines. The US' babus are lawyers, and India's are humanities graduates. Well, engineers are not very good at second-order effects (eg. China's lurch from one-child policy to demographic collapse), but a little bit of ruthlessness is probably good.What is going reasonably well?There are a few modest success stories: for example, in electronics manufacturing or assembly. The PLIs (and DLIs) have produced the desired effort, with clusters of excellence where global suppliers have also set up shop (as they did earlier for the automobile industry in, say, Sriperumpudur). The fact that a lot of iPhones in the US are now imported from India is laudable, even though it may be derided as “screwdriver jobs”. That's where one starts the move up the value chain.The current semiconductor policy is a big hope, especially after the landmark agreement by the Dutch firm ASML with Tata Electronics in Dholera, Gujarat. Given that ASML has a near-monopoly position in Deep Ultraviolet Lithography (DUV) this is a major boost to India's chip ambitions. My recent conversation with AMD CTO Suraj Rengarajan went into India's chances to realize its ambitions.A recent announcement from Trivandrum-based fabless startup NetraSemi (a recipient of DLI) of the commercial availability of its edge AI chips is a landmark.Next is the newly announced plan for energy security revolving around both coal gasification and intensive offshore exploration. These fall squarely into the Atmanirbhar category: India simply cannot afford to have its energy held hostage by distant nations. It also needs distinctly Indian innovation.The Samudra Manthan initiative is also showing some promise. At least one out of three deep-water wells in the Andaman Sea (SriVijaya Puram-3) are reported to be showing the availability of natural gas, although it will take 5-10 years for this to be commercially available.What should the future look like for India's Industrial Policies?This of course is the hard question. Here is my personal perspective, and I accept that reasonable people may disagree. I think three areas need to be focused on, and will pay large dividends.* Drones and swarming software* Social media and AI stack* Maritime Trade and Blue-Water NavyI admit that these are not the only worthwhile industrial policies. Another is for copper, which would reverse the catastrophic effects of the closure of the Sterlite plant in Thoothukkudi, as the metal is an increasingly important component in electronics, data centers, etc., and far from being self-sufficient earlier, India now imports 50% of its needs. Another area of interest in quantum computing.There are also failures from which the right lessons need to be learned. The policy for EV batteries has apparently failed: according to Swarajya magazine, India has not been able to escape from near-total dependence on imported Chinese batteries.Drone swarmsI wrote recently that drones may well herald a step-change in warfare. For the moment, though, they are searching for their niche in offensive/defensive warfare. Drone hardware is already a well-trodden path with Chinese and other nations dominating it, although with IdeaForge, Paras, Garuda, IoTechworld Avigation etc., India is also making progress there. And India is indeed buying the hardware, $2 billion-worth, according to the Economic Times.But I believe the real game is in drone swarms. AI-based control software (similar to HiveMind) that would allow an entire swarm to act autonomously, just like a murmuration of starlings, would be the gold standard to aim for. Such a self-managing swarm would be virtually impossible to defend against, and I think India should put in place a PLI to support it, leveraging software capability in the country.Of course, drones are not just for military purposes, but also for commercial uses including things like logistics and agricultural use, such as precision delivery of fertilizer and pesticide to crops (as Garuda demonstrates). An Indian initiative that supports both drone hardware, and especially drone software, would be a potential winner.Digital Sovereignty: Social media and AI stackThere is a raging battle over which part of the AI stack India needs to invest in. As an old Unix hand, I believe the foundational model is not where the differentiation is. In analogy with Linux (the open-source Unix variant that was popularized by Linus Torvalds and an army of volunteers), there is little value in re-writing the operating system, but one can differentiate by building on top of it, or by judiciously choosing certain modules of it.Besides, the cost of building an entirely new foundational model would be astronomical and would consume the entire budget of IndiaAI Mission.Thus, my personal opinion is that the foundational model (especially when, it is believed, there are more or less open-source models available for free, e.g. Llama, DeepSeek) is not where India should expend its precious R&D resources, but on the layers of the stack above it. It is the data that matters, as Larry Ellison apparently suggests too.But there is the interesting counter-example of Sarvam AI which is producing its own sovereign model: multi-lingual and presumably otherwise tuned to Indian needs. The question is whether this can survive when hundreds of billions worth of capital investment are going to the US Big Tech companies and their Chinese rivals. The sad history of Koo, a Twitter rival, comes to mind. So does Arattai, a Whatsapp rival, whose popularity has waned. .A well-thought-through industrial policy on generativeAI is therefore essential. The status quo ante is unsustainable; given the fact that Sarvam has also found it difficult to raise funds in the US, it is worth pondering whether a China-style massive subsidy is the answer. And where should it go, into foundational models or into the layers of the stack above it? The answer is “both”, but with priority to the latter.Here is where I would prioritize investments, in order:* Vertical applications in specific domains: e.g. defense, healthcare, agriculture, governance (particularly in the judiciary and in ease of doing business in the bureaucracy)* Fine-tuning and customization: for the needs of the Indian context, e.g. multi-linguality under Bhashini* Compute infrastructure: GPUs, sovereign and protected indian datasets* Sovereign Small-Language Models such as Sarvam AIAs mentioned above, at the moment India's data is being sucked up for free by US Big Tech. In addition, there is the real danger that Indic Knowledge Systems will be mined and digested, as has happened to yoga, pranayama, etc., which have been given Western analogs and nomenclature, as in Pilates, ‘coherent breathing' etc.These two problems are connected, and both need to be tackled in parallel. Social media is being weaponized against India, and this is magnified by the legacy media in a positive feedback loop. Three examples: one was the rage against Adani based on the dubious research of Hindenburg, which then went under; the second is Bloomberg's reckless accusation about gold reserves being sold by the RBI, which they were forced to retract, but social media and Wikipedia will remember it; the third is the meteoric (media) rise of the Cockroach Janata Party.Trade using major ports, Digital Public Infrastructure and a blue water navyUsing trade for competitive advantage is an age-old tactic. The trade tiffs between the US and China are examples of this: we are witnessing war by other means. Many nations are getting into this act, and India does have some advantages, partly based on geography. Maritime trade is likely to continue to be the key, which makes naval chokepoints the big story, but not the only story to watch out for.The major aspects of maritime trade include infrastructure, the digital “multi-protocol switch”, and security. On the one hand, India is developing not only major container ports, and the road/rail links to get to them, and the industrial goods to ship out through them, but also a serious shipbuilding industry, which was one of India's historical strengths. Then it used to be stitched wooden ships (teak beams lashed together with coconut rope). Now it's modern steel ships.There are the big, efficient new ports, which can now turn ships around with Singapore-like efficiency; the proposed third aircraft carrier group which will make it possible to patrol the Arabian Sea and the Bay of Bengal at the time; the Air-Independent Propulsion diesel submarines and nuclear submarines that can monitor (and if necessary, deny) narrow straits; the sale of supersonic Brahmos cruise missiles to the Philippines, Vietnam and Indonesia (and Cyprus) that create ship-denial zones: all this is muscle.And the final piece, the ‘software' for trade, the “multi-protocol switch”. This last is complicated. Its value is underestimated by many. But this is what enables friction-less transactions between various unrelated parties. The India Stack and the Digital Public Infrastructure can be utilized to provide such a facility. But it is complex enough to need significant study as to what is possible, and how to roll it out.Second-order effectsIn closing, it is worth considering some of what the (unintended) consequences of these proposals may be. Let us note that the G2 has no interest in allowing India to grow and make it a G3. They will do everything in their power to kneecap India, by all means possible.There is also a certain derision for India in some circles. Here is a generic western opinion on why China got rich, and India didn't. Well, the author doesn't consider the second-order effects of the wholesale destruction of Chinese civilization: that is a tradeoff Indians may not prefer for themselves. We all know how China's well-intentioned One Child Policy turned into demographic collapse within a few years. Besides, as The Economist asks, “China is innovative. Its economy is a mess. Which will win out?”This is why I think planning for these second-order effects is important. We tend to ignore them because they seem counterintuitive or unlikely, but Nassim Taleb has sensitized us to how low-probability Black Swan events can have grave consequences.As an example, attempting digital sovereignty may have unwelcome side-effects: Big Tech have the first-mover advantage and network effects and there are increasing returns to scale. They will surely make it hard for a new player to break in. Besides, the large investments in data centers and GCCs that they are making in India would make it very difficult for them to be ejected with a “Great Indian Firewall”.Even taxing their capture of Indian data will be complicated; not to mention that they have demonstrated that they can happily violate copyright laws with no consequence; therefore they will find ways to chew up and spit out Indian Knowledge Systems, and essentially re-colonize India. Digital colonialism is not a threat, it is a reality today, and it is a consequence of the relatively open Indian system.In addition, there is a malign group, the “barbarians within” as Arnold Toynbee once put it, who are ready to sacrifice Indian sovereignty for a pittance.Given all this, it will be very difficult to put in place serious measures to gain digital independence; and the narrative-peddling is likely to gain further momentum: just consider the caste allegations that have haunted BAPS in the US (despite the cases being dismissed by the US DoJ), the Cisco Systems case where, again, the case was dismissed, but the narrative continues, and the persistent efforts in various US states to turn caste into a weapon to bludgeon Indians.Another sensitive issue is that of the multi-protocol switch for trade. While from an Indian point of view, it eases trade and harks back to a Golden Age of Indic maritime commerce, but that will be viewed elsewhere very differently, for instance by the US as an attempt to de-dollarize. The US has jealousy guarded – with very good reasons that we will not go into here – the dollar's reserve currency status.We have also seen what happened to those who attempt to hurt the dollar's primacy: in 1985, the Plaza Accord devalued the dollar, and that was a body blow to Japan's economy, which has not recovered its mojo to this day. Later, Iraq's Saddam Hussein and Libya's Muammar Gaddafi both had ideas about replacing the petro-dollar with, respectively, the Euro and a new pan-African gold-backed currency. We know what happened to them.If the India Stack multi-protocol switch is perceived as an alternative to the US dollar, there may be grave consequences. Therefore, it should be conceived and deployed only as an adjunct to it and to the almighty SWIFT settlement system.ConclusionIndia is at a crossroads now. Even though the Hormuz closure is a serious problem, if it plays its cards right, adversity can be turned into opportunity across a variety of perspectives. The key is Atmanirbhar, self-reliance. If India can now implement a crash program of industrial policy, and at the same time overcome an ingrained Third-World tendency to cut corners, it can finally break free of the years of underperformance, what I called the Nehruvian Penalty in 2004.It is possible, but there are caveats: unforeseen consequences. Hic sunt dracones. Here be dragons. Be afraid. Be very afraid.3700 words, 7 June 2026This is episode 192 of the Shadow Warrior podcast. Here is a companion AI-generated slideshow. (Note that the borders of India are not necessarily depicted correctly here, because it is generated by an AI, notebookLM.google.com) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit rajeevsrinivasan.substack.com/subscribe

Linus Torvalds äussert sich zu KI-generierten Bug Reports für den Linux-Kernel.

This episode covers Mythos uncovering a vulnerability in cURL, a recent Google Threat Intelligence report on a zero-day exploit, and the growing impact of AI on capture-the-flag competitions and bug bounty programs. The hosts also discuss the economics of AI platforms like OpenAI, security research trends, and broader concerns around software vulnerabilities, automation, and defensive tooling.Join us LIVE on Mondays, 4:30pm EST.A weekly Podcast with BHIS and Friends. We discuss notable Infosec, and infosec-adjacent news stories gathered by our community news team.https://www.youtube.com/@BlackHillsInformationSecurityChat with us on Discord! - https://discord.gg/bhis

Jason Howell and Jeff Jarvis break down everything from Google I/O 2026, where the company made its strongest case yet for winning the AI race. Gemini 3.5 Flash and Gemini Spark were unveiled, AI agents are now doing the searching instead of returning links, and Google's reach extended into design, science, YouTube, and shopping. Jason also demos Genie World Models live.Also in this episode: Andrej Karpathy joins Anthropic, Anthropic acquires a major dev tools startup, Amazon Alexa+ can now generate podcast episodes, Elon Musk's latest lawsuit drama, and a growing American rebellion against AI. Speed round includes the OpenAI IPO, xAI's coding agent, Meta's AR glasses, and more.New episodes every Wednesday at aiinside.show Note: Time codes subject to change depending on dynamic ad insertion by the distributor. CHAPTERS: 0:04:31 - Everything announced at Google I/O 2026              - Times: How Google Is Starting to Win the A.I. Race 0:22:42 - A new era for AI Search              - Gemini 3.5: frontier intelligence with action 0:27:53 - Google Launches Gemini Spark: A 24/7 AI Agent That Wants to Make You Ditch OpenClaw 0:44:35 - OpenAI co-founder Andrej Karpathy joins Anthropic 0:46:32 - Anthropic has acquired the dev tools startup used by OpenAI, Google, and Cloudflare 0:55:20 - Amazon's new Alexa+ powered feature can generate podcast episodes 0:57:27 - The Art of War, Elon Musk Edition: How to Lose a Lawsuit and Still Claim Victory 0:59:30 - The American Rebellion Against AI Is Gaining Steam 1:01:46 - NextEra Energy to buy Dominion in deal that unites two key players in race to power AI data centers 1:04:42 - Pope Leo XIV will publish his first encyclical, Magnifica Humanitas, on May 25, with Anthropic co-founder Christopher Olah joining the launch panel at the Vatican 1:06:25 - Linus Torvalds says AI-powered bug hunters have made Linux security mailing list ‘almost entirely unmanageable' 1:08:57 - Meta brings virtual writing to everyone with Meta Ray-Ban Display glasses 1:10:36 - Musk's xAI Unveils First Coding Agent in Bid to Rival Anthropic 1:10:59 - OpenAI is Preparing to File for an IPO Very Soon Hosts: Jason Howell and Jeff Jarvis Download and subscribe to AI Inside in audio and video: https://aiinside.show/  Support the podcast on Patreon for special perks: https://www.patreon.com/aiinsideshow. You'll get ad-free episodes, members-only Discord, T-shirts and stickers you love, and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Learn more about your ad choices. Visit megaphone.fm/adchoices

On this week's show Patrick Gray, Adam Boileau and James Wilson discuss the week's cybersecurity news. They cover: GitHub announced a possible breach CISA leaks important creds, keys in public repo Awful vulnerability in Bitlocker renders it useless without a PIN So. Many. Patches. Polish Government urges officials to ditch Signal for mSzyfr Much, much more This week's show is brought to you by Thinkst Canary. Thinkst's founder, Haroon Meer, is this week's sponsor guest. He joined James Wilson to talk about how doing “the basics” in security isn't trivially easy. This episode is also available on YouTube. Show notes GitHub on X: "We are investigating unauthorized access to GitHub's internal repositories. While we currently have no evidence of impact to customer information stored outside of GitHub's internal repositories (such as our customers' enterprises, organizations, and repositories), we are closely" / X CISA Admin Leaked AWS GovCloud Keys on Github – Krebs on Security Experts Confirm the Fast16 Malware Was Sabotaging Nuclear Weapons Tests, Likely in Iran Iran hackers: Hackers have breached tank readers at gas stations; officials suspect Iran is responsible | CNN Politics War and Data Centers Are Driving Up the Cost of Fiber-Optic Cable Microsoft on pace to break annual vulnerability record as AI-driven patch wave takes hold | The Record from Recorded Future News NCSC's Ollie Whitehouse on surviving the "bugpocalypse" - Risky Business Media Defense at AI speed: Microsoft's new multi-model agentic security system tops leading industry benchmark | Microsoft Security Blog Project Glasswing: what Mythos showed us Linus Torvalds says AI-powered bug hunters have made Linux security mailing list ‘almost entirely unmanageable' First public macOS kernel memory corruption exploit on Apple M5 OpenAI launches Daybreak to combat cyber threats | Cybersecurity Dive Zero-day exploit completely defeats default Windows 11 BitLocker protections - Ars Technica GitHub - Wack0/bitlocker-attacks: A list of public attacks on BitLocker · GitHub Catalin Cimpanu: "The Polish government has advi…" - Mastodon CISA orders all federal agencies to patch exploited bug in Cisco SD-WAN systems by Sunday | The Record from Recorded Future News CVE-2026-20182: Critical authentication bypass in Cisco Catalyst SD-WAN Controller (FIXED) Huawei zero-day attack behind last year's crash of Luxembourg's entire telecoms network | The Record from Recorded Future News Patch bypass allows hackers to exploit prior flaw in SonicWall SSL-VPN | Cybersecurity Dive Microsoft disrupts Fox Tempest malware-signing-as-a-service platform tied to ransomware gangs | The Record from Recorded Future News Streamer Realtime Deepfakes Himself into Mr. Beast, Says He Loves 'Touching Little Boys'

The user-agent string in the HTTP header has been there since the 1990s. The web was built with software navigating it on someone's behalf. For thirty years that someone was a human. That changes now. Matt Biilmann, CEO and co-founder of Netlify, was one of the first to take seriously what it means when the "user" navigating the web is an AI agent. He published the foundational essay on Agent Experience in January 2025, pivoted his entire company around it, and recently shipped netlify.ai as a separate entry point built for agents. We cover the four pillars of Agent Experience, why every product already has an agent experience whether you designed one or not, content negotiation as a way to tell agents to go to a different URL than humans, why SaaS is in real trouble (with a story from inside Netlify about ripping out vendor contracts), how the data-structure assumption that has defined software for fifty years is breaking, and the one thing every website owner should start doing this week.About the GuestMatt Biilmann is the CEO and co-founder of Netlify, the platform that started the Jamstack movement and is leading the shift from developer experience to agent experience. His January 2025 essay on Agent Experience is the foundational text for the discipline. Chapters00:00 Every product has an agent experience (cold open)00:35 The architectural question01:46 Welcome Matt to No Hacks02:15 When AX became a design constraint, not a concept06:44 The January 28 2025 essay and who got it first10:22 Why netlify.ai was built as a separate website12:44 Content negotiation: telling agents to go to a different URL13:54 Qualitative data and the Axis eval framework17:12 Does AX apply to e-commerce and content websites?20:59 The cumulative media argument (TV did not kill radio)25:00 User-agent in HTTP and Al Gore-era agent commerce laws26:33 SaaS business model is dead: build-vs-buy is shifting30:44 The end of structured content as a hard constraint40:25 One thing every website owner should do now43:08 Where to find Matt onlineKey TakeawaysEvery website already has an agent experience. Agent Experience is how AI agents currently interact with your product, whether through computer use, fetching, or working around the barriers you put up. It is not a feature you add. The only question is whether the experience is good or bad.The four pillars: Access, Context, Tools, Orchestration. Matt's framework for thinking about AX systematically. Access answers whether agents can reach your product at all. Context is the prompt-engineering equivalent for agents. Tools are the concrete capabilities you expose. Orchestration covers how agents string those tools together inside your product.Build a separate entry point for agents. netlify.ai is purpose-built for agents while netlify.com remains the human entry point. Content negotiation tells agents to go to one URL, humans see the other. The blessed-path approach beats trying to make one URL serve both.SaaS economics are shifting structurally. The build-vs-buy floor is dropping fast as AI lowers the cost of software. Traditional 90%-margin seat-based SaaS is in real trouble. Dev tool companies have upside because companies need more tools. Everyone else is going to be ripping out vendor contracts and building internally.The data-structure paradigm is breaking. Software engineering has operated on the Linus Torvalds principle that data structures matter more than code. LLMs are not built around data structures. Building software around LLMs means rethinking the assumption that drove fifty years of computer science.Notable Quotes"Every product has an agent experience because all of these agents, whether through computer use or through fetching your website or through working around the barriers you put up from them, have some agent experience right now. It is just a question of is it good or bad.""There is a reason it is called a user agent in the header. It was forward-looking.""We have been ripping out SaaS contracts. Sometimes it is heartbreaking. The rep calls to right-size the contract and the customer reacts with 'let me see if I can build it with an agent.' Then they call back and cancel instead.""The context and the flows and your creativity are probably more important than both the data structures and the code."What To Do NextOpen your website in Claude Code or ChatGPT and ask the agent to complete a real task. Watch where it stalls. That is your AX baseline.Check your traffic logs for AI assistant visitors (ChatGPT-User, Claude-Web, PerplexityBot, GPTBot). The number is rising whether you measure it or not. Cloudflare reports AI assistants are now 5.5% of all internet traffic, up from 3.9% six months ago.Read Matt's January 28 2025 essay on Agent Experience at biilmann.blog as the starting point. Then read the one-year retrospective for the four pillars framework.If you operate a developer tool or any product with a clear automation surface, start a simple eval scenario: take a fresh agent, give it a task, score whether it succeeds. Axis from Netlify will give a proper framework when it ships open source.Resources Mentionednetlify.ai (the agent-built entry point Matt and team shipped recently)netlify.com (the human entry point)Matt's original Agent Experience essay, January 28 2025: biilmann.blogMatt's "AI in the CLI: The Humanoid Robot of the Web" (August 2025)Claude Code (the agent that flipped broad accessibility for CLI coding agents)Connect with Matt BiilmannBlog: biilmann.blogLinkedIn: linkedin.com/in/mathias-biilmann-christensen-a5a3805Twitter/X: @biilmann (x.com/biilmann)Bluesky: bsky.app/profile/did:plc:grjr4il5dredrsuj7nosb4pqMastodon: mastodon.social/@biilmannNetlify: netlify.com and netlify.aiConnect with No HacksWebsite: nohacks.coSubscribe to the newsletter: nohacks.co/subscribeMachine-First Architecture: machinefirstarchitecture.comNo Hacks is a podcast about web performance, technical SEO, and the agentic web. Hosted by Slobodan "Sani" Manic.

EP 292. This week we kick off with a flood of updates: The agency trusted to protect America's critical infrastructure couldn't protect its own credentials.Canada is reopening one of tech's most consequential debates  and this time, your compliance architecture may be in the crosshairs.A researcher's very public falling-out with Microsoft is quietly becoming everyone's security problem.What once took a seasoned red team weeks now takes a small team and a frontier model less than five days.The race to use AI to find flaws faster than attackers is officially underway  and the audit trail question is already lagging behind.AI is flooding the Linux kernel security pipeline with noise, and Linus Torvalds has had enough.Regulators are quietly deploying AI surveillance at a scale that reframes what financial oversight even means.The world's most consequential digital chokepoint just became even more of a geopolitical bargaining chip.Let's go get soaked!Find the full transcript to this podcast here.

Linus Torvalds not into AI bug hunters 7-Eleven hit with ransom demand MENA runs new cybercrime op Get the show notes here: https://cisoseries.com/cybersecurity-news-linus-torvalds-talks-ai-bug-hunters-7-eleven-ransom-demand-menas-new-cybercrime-op/ Thanks to our episode sponsor, ThreatLocker ThreatLocker is extending Zero Trust beyond endpoint control. With their recent release of Zero Trust Network Access and Zero Trust Cloud Access, access isn't based on credentials alone, it requires the right user, the right device, and the right conditions. Because as we've seen in recent large-scale CRM breaches, stolen credentials and misconfigurations can expose massive amounts of data. With ThreatLocker, nothing is exposed, and access is limited to exactly what's needed. Learn more and start your free trial today at ThreatLocker.com/CISO.

Jean-Baptiste Kempf is lead developer of VLC and president of VideoLAN. Kieran Kunhya is a longtime FFmpeg contributor, codec engineer, and the person behind the now-infamous FFmpeg account on X. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep496-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. Transcript: https://lexfridman.com/ffmpeg-transcript CONTACT LEX: Feedback – give feedback to Lex: https://lexfridman.com/survey AMA – submit questions, videos or call-in: https://lexfridman.com/ama Hiring – join our team: https://lexfridman.com/hiring Other – other ways to get in touch: https://lexfridman.com/contact EPISODE LINKS: FFmpeg on X: https://x.com/FFmpeg FFmpeg: https://ffmpeg.org/ VideoLAN (VLC): https://www.videolan.org/ VideoLAN on X: https://x.com/videolan Jean-Baptiste’s Website: https://jbkempf.com/ Jean-Baptiste’s LinkedIn: https://www.linkedin.com/in/jbkempf/ Jean-Baptiste’s GitHub: https://github.com/jbkempf Kieran’s X: https://x.com/kierank_ Kieran’s LinkedIn: https://bit.ly/3OORhmC Kieran’s GitHub: https://github.com/kierank SPONSORS: To support this podcast, check out our sponsors & get discounts: Larridin: Measure AI adoption in your business. Go to https://larridin.com Blitzy: AI agent for large enterprise codebases. Go to https://blitzy.com/lex BetterHelp: Online therapy and counseling. Go to https://betterhelp.com/lex Fin: AI agent for customer service. Go to https://fin.ai/lex LMNT: Zero-sugar electrolyte drink mix. Go to https://drinkLMNT.com/lex Perplexity: AI-powered answer engine. Go to https://perplexity.ai/ OUTLINE: (00:00) – Introduction (03:00) – Sponsors, Comments, and Reflections (10:48) – Weirdest things VLC opens (15:12) – How video playback works (24:33) – Video codecs and containers (35:20) – FFmpeg explained (56:20) – Linus Torvalds (1:00:59) – Turning down millions to keep VLC ad-free (1:15:17) – FFmpeg & Google drama (1:34:31) – FFmpeg developers (1:41:08) – VLC and FFmpeg (1:45:42) – History of FFmpeg (1:48:59) – Reverse engineering codecs (2:02:14) – FFmpeg testing (2:06:21) – Assembly code (handwritten) (2:30:39) – Rust programming language (2:39:55) – FFmpeg and Libav fork (2:48:17) – Open source burnout (2:56:04) – x264 and internet video (3:09:20) – Video compression basics (3:16:17) – CIA and fake VLC (3:26:52) – Ultra low latency streaming (3:44:20) – AV2 codec and video patents (3:54:12) – VLC backdoors (4:04:27) – Video archiving (4:11:04) – Future of FFmpeg and VLC

Bryan Cantrill is the co-founder and CTO of Oxide Computer Company. We discuss why the biggest cloud providers don't use off the shelf hardware, how scaling data centers at samsung's scale exposed problems with hard drive firmware, how the values of NodeJS are in conflict with robust systems, choosing Rust, and the benefits of Oxide Computer's rack scale approach. This is an extended version of an interview posted on Software Engineering Radio. Related links Oxide Computer Oxide and Friends Illumos Platform as a Reflection of Values RFD 26 bhyve CockroachDB Heterogeneous Computing with Raja Koduri Transcript You can help correct transcripts on GitHub. Intro [00:00:00] Jeremy: Today I am talking to Bryan Cantrill. He's the co-founder and CTO of Oxide computer company, and he was previously the CTO of Joyent and he also co-authored the DTrace Tracing framework while he was at Sun Microsystems. [00:00:14] Jeremy: Bryan, welcome to Software Engineering radio. [00:00:17] Bryan: Uh, awesome. Thanks for having me. It's great to be here. [00:00:20] Jeremy: You're the CTO of a company that makes computers. But I think before we get into that, a lot of people who built software, now that the actual computer is abstracted away, they're using AWS or they're using some kind of cloud service. So I thought we could start by talking about, data centers. [00:00:41] Jeremy: 'cause you were. Previously working at Joyent, and I believe you got bought by Samsung and you've previously talked about how you had to figure out, how do I run things at Samsung's scale. So how, how, how was your experience with that? What, what were the challenges there? Samsung scale and migrating off the cloud [00:01:01] Bryan: Yeah, I mean, so at Joyent, and so Joyent was a cloud computing pioneer. Uh, we competed with the likes of AWS and then later GCP and Azure. Uh, and we, I mean, we were operating at a scale, right? We had a bunch of machines, a bunch of dcs, but ultimately we know we were a VC backed company and, you know, a small company by the standards of, certainly by Samsung standards. [00:01:25] Bryan: And so when, when Samsung bought the company, I mean, the reason by the way that Samsung bought Joyent is Samsung's. Cloud Bill was, uh, let's just say it was extremely large. They were spending an enormous amount of money every year on, on the public cloud. And they realized that in order to secure their fate economically, they had to be running on their own infrastructure. [00:01:51] Bryan: It did not make sense. And there's not, was not really a product that Samsung could go buy that would give them that on-prem cloud. Uh, I mean in that, in that regard, like the state of the market was really no different. And so they went looking for a company, uh, and bought, bought Joyent. And when we were on the inside of Samsung. [00:02:11] Bryan: That we learned about Samsung scale. And Samsung loves to talk about Samsung scale. And I gotta tell you, it is more than just chest thumping. Like Samsung Scale really is, I mean, just the, the sheer, the number of devices, the number of customers, just this absolute size. they really wanted to take us out to, to levels of scale, certainly that we had not seen. [00:02:31] Bryan: The reason for buying Joyent was to be able to stand up on their own infrastructure so that we were gonna go buy, we did go buy a bunch of hardware. Problems with server hardware at scale [00:02:40] Bryan: And I remember just thinking, God, I hope Dell is somehow magically better. I hope the problems that we have seen in the small, we just. You know, I just remember hoping and hope is hope. It was of course, a terrible strategy and it was a terrible strategy here too. Uh, and the we that the problems that we saw at the large were, and when you scale out the problems that you see kind of once or twice, you now see all the time and they become absolutely debilitating. [00:03:12] Bryan: And we saw a whole series of really debilitating problems. I mean, many ways, like comically debilitating, uh, in terms of, of showing just how bad the state-of-the-art. Yes. And we had, I mean, it should be said, we had great software and great software expertise, um, and we were controlling our own system software. [00:03:35] Bryan: But even controlling your own system software, your own host OS, your own control plane, which is what we had at Joyent, ultimately, you're pretty limited. You go, I mean, you got the problems that you can obviously solve, the ones that are in your own software, but the problems that are beneath you, the, the problems that are in the hardware platform, the problems that are in the componentry beneath you become the problems that are in the firmware. IO latency due to hard drive firmware [00:04:00] Bryan: Those problems become unresolvable and they are deeply, deeply frustrating. Um, and we just saw a bunch of 'em again, they were. Comical in retrospect, and I'll give you like a, a couple of concrete examples just to give, give you an idea of what kinda what you're looking at. one of the, our data centers had really pathological IO latency. [00:04:23] Bryan: we had a very, uh, database heavy workload. And this was kind of right at the period where you were still deploying on rotating media on hard drives. So this is like, so. An all flash buy did not make economic sense when we did this in, in 2016. This probably, it'd be interesting to know like when was the, the kind of the last time that that actual hard drives made sense? [00:04:50] Bryan: 'cause I feel this was close to it. So we had a, a bunch of, of a pathological IO problems, but we had one data center in which the outliers were actually quite a bit worse and there was so much going on in that system. It took us a long time to figure out like why. And because when, when you, when you're io when you're seeing worse io I mean you're naturally, you wanna understand like what's the workload doing? [00:05:14] Bryan: You're trying to take a first principles approach. What's the workload doing? So this is a very intensive database workload to support the, the object storage system that we had built called Manta. And that the, the metadata tier was stored and uh, was we were using Postgres for that. And that was just getting absolutely slaughtered. [00:05:34] Bryan: Um, and ultimately very IO bound with these kind of pathological IO latencies. Uh, and as we, you know, trying to like peel away the layers to figure out what was going on. And I finally had this thing. So it's like, okay, we are seeing at the, at the device layer, at the at, at the disc layer, we are seeing pathological outliers in this data center that we're not seeing anywhere else. [00:06:00] Bryan: And that does not make any sense. And the thought occurred to me. I'm like, well, maybe we are. Do we have like different. Different rev of firmware on our HGST drives, HGST. Now part of WD Western Digital were the drives that we had everywhere. And, um, so maybe we had a different, maybe I had a firmware bug. [00:06:20] Bryan: I, this would not be the first time in my life at all that I would have a drive firmware issue. Uh, and I went to go pull the firmware, rev, and I'm like, Toshiba makes hard drives? So we had, I mean. I had no idea that Toshiba even made hard drives, let alone that they were our, they were in our data center. [00:06:38] Bryan: I'm like, what is this? And as it turns out, and this is, you know, part of the, the challenge when you don't have an integrated system, which not to pick on them, but Dell doesn't, and what Dell would routinely put just sub make substitutes, and they make substitutes that they, you know, it's kind of like you're going to like, I don't know, Instacart or whatever, and they're out of the thing that you want. [00:07:03] Bryan: So, you know, you're, someone makes a substitute and like sometimes that's okay, but it's really not okay in a data center. And you really want to develop and validate a, an end-to-end integrated system. And in this case, like Toshiba doesn't, I mean, Toshiba does make hard drives, but they are a, or the data they did, uh, they basically were, uh, not competitive and they were not competitive in part for the reasons that we were discovering. [00:07:29] Bryan: They had really serious firmware issues. So the, these were drives that would just simply stop a, a stop acknowledging any reads from the order of 2,700 milliseconds. Long time, 2.7 seconds. Um. And that was a, it was a drive firmware issue, but it was highlighted like a much deeper issue, which was the simple lack of control that we had over our own destiny. [00:07:53] Bryan: Um, and it's an, it's, it's an example among many where Dell is making a decision. That lowers the cost of what they are providing you marginally, but it is then giving you a system that they shouldn't have any confidence in because it's not one that they've actually designed and they leave it to the customer, the end user, to make these discoveries. [00:08:18] Bryan: And these things happen up and down the stack. And for every, for whether it's, and, and not just to pick on Dell because it's, it's true for HPE, it's true for super micro, uh, it's true for your switch vendors. It's, it's true for storage vendors where the, the, the, the one that is left actually integrating these things and trying to make the the whole thing work is the end user sitting in their data center. AWS / Google are not buying off the shelf hardware but you can't use it [00:08:42] Bryan: There's not a product that they can buy that gives them elastic infrastructure, a cloud in their own DC The, the product that you buy is the public cloud. Like when you go in the public cloud, you don't worry about the stuff because that it's, it's AWS's issue or it's GCP's issue. And they are the ones that get this to ground. [00:09:02] Bryan: And they, and this was kind of, you know, the eye-opening moment. Not a surprise. Uh, they are not Dell customers. They're not HPE customers. They're not super micro customers. They have designed their own machines. And to varying degrees, depending on which one you're looking at. But they've taken the clean sheet of paper and the frustration that we had kind of at Joyent and beginning to wonder and then Samsung and kind of wondering what was next, uh, is that, that what they built was not available for purchase in the data center. [00:09:35] Bryan: You could only rent it in the public cloud. And our big belief is that public cloud computing is a really important revolution in infrastructure. Doesn't feel like a different, a deep thought, but cloud computing is a really important revolution. It shouldn't only be available to rent. You should be able to actually buy it. [00:09:53] Bryan: And there are a bunch of reasons for doing that. Uh, one in the one we we saw at Samsung is economics, which I think is still the dominant reason where it just does not make sense to rent all of your compute in perpetuity. But there are other reasons too. There's security, there's risk management, there's latency. [00:10:07] Bryan: There are a bunch of reasons why one might wanna to own one's own infrastructure. But, uh, that was very much the, the, so the, the genesis for oxide was coming out of this very painful experience and a painful experience that, because, I mean, a long answer to your question about like what was it like to be at Samsung scale? [00:10:27] Bryan: Those are the kinds of things that we, I mean, in our other data centers, we didn't have Toshiba drives. We only had the HDSC drives, but it's only when you get to this larger scale that you begin to see some of these pathologies. But these pathologies then are really debilitating in terms of those who are trying to develop a service on top of them. [00:10:45] Bryan: So it was, it was very educational in, in that regard. And you're very grateful for the experience at Samsung in terms of opening our eyes to the challenge of running at that kind of scale. [00:10:57] Jeremy: Yeah, because I, I think as software engineers, a lot of times we, we treat the hardware as a, as a given where, [00:11:08] Bryan: Yeah. [00:11:08] Bryan: Yeah. There's software in chard drives [00:11:09] Jeremy: It sounds like in, in this case, I mean, maybe the issue is not so much that. Dell or HP as a company doesn't own every single piece that they're providing you, but rather the fact that they're swapping pieces in and out without advertising them, and then when it becomes a problem, they're not necessarily willing to, to deal with the, the consequences of that. [00:11:34] Bryan: They just don't know. I mean, I think they just genuinely don't know. I mean, I think that they, it's not like they're making a deliberate decision to kind of ship garbage. It's just that they are making, I mean, I think it's exactly what you said about like, not thinking about the hardware. It's like, what's a hard drive? [00:11:47] Bryan: Like what's it, I mean, it's a hard drive. It's got the same specs as this other hard drive and Intel. You know, it's a little bit cheaper, so why not? It's like, well, like there's some reasons why not, and one of the reasons why not is like, uh, even a hard drive, whether it's rotating media or, or flash, like that's not just hardware. [00:12:05] Bryan: There's software in there. And that the software's like not the same. I mean, there are components where it's like, there's actually, whether, you know, if, if you're looking at like a resistor or a capacitor or something like this Yeah. If you've got two, two parts that are within the same tolerance. Yeah. [00:12:19] Bryan: Like sure. Maybe, although even the EEs I think would be, would be, uh, objecting that a little bit. But the, the, the more complicated you get, and certainly once you get to the, the, the, the kind of the hardware that we think of like a, a, a microprocessor, a a network interface card, a a, a hard driver, an NVME drive. [00:12:38] Bryan: Those things are super complicated and there's a whole bunch of software inside of those things, the firmware, and that's the stuff that, that you can't, I mean, you say that software engineers don't think about that. It's like you, no one can really think about that because it's proprietary that's kinda welded shut and you've got this abstraction into it. [00:12:55] Bryan: But the, the way that thing operates is very core to how the thing in aggregate will behave. And I think that you, the, the kind of, the, the fundamental difference between Oxide's approach and the approach that you get at a Dell HP Supermicro, wherever, is really thinking holistically in terms of hardware and software together in a system that, that ultimately delivers cloud computing to a user. [00:13:22] Bryan: And there's a lot of software at many, many, many, many different layers. And it's very important to think about, about that software and that hardware holistically as a single system. [00:13:34] Jeremy: And during that time at Joyent, when you experienced some of these issues, was it more of a case of you didn't have enough servers experiencing this? So if it would happen, you might say like, well, this one's not working, so maybe we'll just replace the hardware. What, what was the thought process when you were working at that smaller scale and, and how did these issues affect you? UEFI / Baseboard Management Controller [00:13:58] Bryan: Yeah, at the smaller scale, you, uh, you see fewer of them, right? You just see it's like, okay, we, you know, what you might see is like, that's weird. We kinda saw this in one machine versus seeing it in a hundred or a thousand or 10,000. Um, so you just, you just see them, uh, less frequently as a result, they are less debilitating. [00:14:16] Bryan: Um, I, I think that it's, when you go to that larger scale, those things that become, that were unusual now become routine and they become debilitating. Um, so it, it really is in many regards a function of scale. Uh, and then I think it was also, you know, it was a little bit dispiriting that kind of the substrate we were building on really had not improved. [00:14:39] Bryan: Um, and if you look at, you know, the, if you buy a computer server, buy an x86 server. There is a very low layer of firmware, the BIOS, the basic input output system, the UEFI BIOS, and this is like an abstraction layer that has, has existed since the eighties and hasn't really meaningfully improved. Um, the, the kind of the transition to UEFI happened with, I mean, I, I ironically with Itanium, um, you know, two decades ago. [00:15:08] Bryan: but beyond that, like this low layer, this lowest layer of platform enablement software is really only impeding the operability of the system. Um, you look at the baseboard management controller, which is the kind of the computer within the computer, there is a, uh, there is an element in the machine that needs to handle environmentals, that needs to handle, uh, operate the fans and so on. [00:15:31] Bryan: Uh, and that traditionally has this, the space board management controller, and that architecturally just hasn't improved in the last two decades. And, you know, that's, it's a proprietary piece of silicon. Generally from a company that no one's ever heard of called a Speed, uh, which has to be, is written all on caps, so I guess it needs to be screamed. [00:15:50] Bryan: Um, a speed has a proprietary part that has a, there is a root password infamously there, is there, the root password is encoded effectively in silicon. So, uh, which is just, and for, um, anyone who kind of goes deep into these things, like, oh my God, are you kidding me? Um, when we first started oxide, the wifi password was a fraction of the a speed root password for the bmc. [00:16:16] Bryan: It's kinda like a little, little BMC humor. Um, but those things, it was just dispiriting that, that the, the state-of-the-art was still basically personal computers running in the data center. Um, and that's part of what, what was the motivation for doing something new? [00:16:32] Jeremy: And for the people using these systems, whether it's the baseboard management controller or it's the The BIOS or UF UEFI component, what are the actual problems that people are seeing seen? Security vulnerabilities and poor practices in the BMC [00:16:51] Bryan: Oh man, I, the, you are going to have like some fraction of your listeners, maybe a big fraction where like, yeah, like what are the problems? That's a good question. And then you're gonna have the people that actually deal with these things who are, did like their heads already hit the desk being like, what are the problems? [00:17:06] Bryan: Like what are the non problems? Like what, what works? Actually, that's like a shorter answer. Um, I mean, there are so many problems and a lot of it is just like, I mean, there are problems just architecturally these things are just so, I mean, and you could, they're the problems spread to the horizon, so you can kind of start wherever you want. [00:17:24] Bryan: But I mean, as like, as a really concrete example. Okay, so the, the BMCs that, that the computer within the computer that needs to be on its own network. So you now have like not one network, you got two networks that, and that network, by the way, it, that's the network that you're gonna log into to like reset the machine when it's otherwise unresponsive. [00:17:44] Bryan: So that going into the BMC, you can are, you're able to control the entire machine. Well it's like, alright, so now I've got a second net network that I need to manage. What is running on the BMC? Well, it's running some. Ancient, ancient version of Linux it that you got. It's like, well how do I, how do I patch that? [00:18:02] Bryan: How do I like manage the vulnerabilities with that? Because if someone is able to root your BMC, they control the system. So it's like, this is not you've, and now you've gotta go deal with all of the operational hair around that. How do you upgrade that system updating the BMC? I mean, it's like you've got this like second shadow bad infrastructure that you have to go manage. [00:18:23] Bryan: Generally not open source. There's something called open BMC, um, which, um, you people use to varying degrees, but you're generally stuck with the proprietary BMC, so you're generally stuck with, with iLO from HPE or iDRAC from Dell or, or, uh, the, uh, su super micros, BMC, that H-P-B-M-C, and you are, uh, it is just excruciating pain. [00:18:49] Bryan: Um, and that this is assuming that by the way, that everything is behaving correctly. The, the problem is that these things often don't behave correctly, and then the consequence of them not behaving correctly. It's really dire because it's at that lowest layer of the system. So, I mean, I'll give you a concrete example. [00:19:07] Bryan: a customer of theirs reported to me, so I won't disclose the vendor, but let's just say that a well-known vendor had an issue with their, their temperature sensors were broken. Um, and the thing would always read basically the wrong value. So it was the BMC that had to like, invent its own ki a different kind of thermal control loop. [00:19:28] Bryan: And it would index on the, on the, the, the, the actual inrush current. It would, they would look at that at the current that's going into the CPU to adjust the fan speed. That's a great example of something like that's a, that's an interesting idea. That doesn't work. 'cause that's actually not the temperature. [00:19:45] Bryan: So like that software would crank the fans whenever you had an inrush of current and this customer had a workload that would spike the current and by it, when it would spike the current, the, the, the fans would kick up and then they would slowly degrade over time. Well, this workload was spiking the current faster than the fans would degrade, but not fast enough to actually heat up the part. [00:20:08] Bryan: And ultimately over a very long time, in a very painful investigation, it's customer determined that like my fans are cranked in my data center for no reason. We're blowing cold air. And it's like that, this is on the order of like a hundred watts, a server of, of energy that you shouldn't be spending and like that ultimately what that go comes down to this kind of broken software hardware interface at the lowest layer that has real meaningful consequence, uh, in terms of hundreds of kilowatts, um, across a data center. So this stuff has, has very, very, very real consequence and it's such a shadowy world. Part of the reason that, that your listeners that have dealt with this, that our heads will hit the desk is because it is really aggravating to deal with problems with this layer. [00:21:01] Bryan: You, you feel powerless. You don't control or really see the software that's on them. It's generally proprietary. You are relying on your vendor. Your vendor is telling you that like, boy, I don't know. You're the only customer seeing this. I mean, the number of times I have heard that for, and I, I have pledged that we're, we're not gonna say that at oxide because it's such an unaskable thing to say like, you're the only customer saying this. [00:21:25] Bryan: It's like, it feels like, are you blaming me for my problem? Feels like you're blaming me for my problem? Um, and what you begin to realize is that to a degree, these folks are speaking their own truth because the, the folks that are running at real scale at Hyperscale, those folks aren't Dell, HP super micro customers. [00:21:46] Bryan: They're actually, they've done their own thing. So it's like, yeah, Dell's not seeing that problem, um, because they're not running at the same scale. Um, but when you do run, you only have to run at modest scale before these things just become. Overwhelming in terms of the, the headwind that they present to people that wanna deploy infrastructure. The problem is felt with just a few racks [00:22:05] Jeremy: Yeah, so maybe to help people get some perspective at, at what point do you think that people start noticing or start feeling these problems? Because I imagine that if you're just have a few racks or [00:22:22] Bryan: do you have a couple racks or the, or do you wonder or just wondering because No, no, no. I would think, I think anyone who deploys any number of servers, especially now, especially if your experience is only in the cloud, you're gonna be like, what the hell is this? I mean, just again, just to get this thing working at all. [00:22:39] Bryan: It is so it, it's so hairy and so congealed, right? It's not designed. Um, and it, it, it, it's accreted it and it's so obviously accreted that you are, I mean, nobody who is setting up a rack of servers is gonna think to themselves like, yes, this is the right way to go do it. This all makes sense because it's, it's just not, it, I, it feels like the kit, I mean, kit car's almost too generous because it implies that there's like a set of plans to work to in the end. [00:23:08] Bryan: Uh, I mean, it, it, it's a bag of bolts. It's a bunch of parts that you're putting together. And so even at the smallest scales, that stuff is painful. Just architecturally, it's painful at the small scale then, but at least you can get it working. I think the stuff that then becomes debilitating at larger scale are the things that are, are worse than just like, I can't, like this thing is a mess to get working. [00:23:31] Bryan: It's like the, the, the fan issue that, um, where you are now seeing this over, you know, hundreds of machines or thousands of machines. Um, so I, it is painful at more or less all levels of scale. There's, there is no level at which the, the, the pc, which is really what this is, this is a, the, the personal computer architecture from the 1980s and there is really no level of scale where that's the right unit. Running elastic infrastructure is the hardware but also, hypervisor, distributed database, api, etc [00:23:57] Bryan: I mean, where that's the right thing to go deploy, especially if what you are trying to run. Is elastic infrastructure, a cloud. Because the other thing is like we, we've kinda been talking a lot about that hardware layer. Like hardware is, is just the start. Like you actually gotta go put software on that and actually run that as elastic infrastructure. [00:24:16] Bryan: So you need a hypervisor. Yes. But you need a lot more than that. You, you need to actually, you, you need a distributed database, you need web endpoints. You need, you need a CLI, you need all the stuff that you need to actually go run an actual service of compute or networking or storage. I mean, and for, for compute, even for compute, there's a ton of work to be done. [00:24:39] Bryan: And compute is by far, I would say the simplest of the, of the three. When you look at like networks, network services, storage services, there's a whole bunch of stuff that you need to go build in terms of distributed systems to actually offer that as a cloud. So it, I mean, it is painful at more or less every LE level if you are trying to deploy cloud computing on. What's a control plane? [00:25:00] Jeremy: And for someone who doesn't have experience building or working with this type of infrastructure, when you talk about a control plane, what, what does that do in the context of this system? [00:25:16] Bryan: So control plane is the thing that is, that is everything between your API request and that infrastructure actually being acted upon. So you go say, Hey, I, I want a provision, a vm. Okay, great. We've got a whole bunch of things we're gonna provision with that. We're gonna provision a vm, we're gonna get some storage that's gonna go along with that, that's got a network storage service that's gonna come out of, uh, we've got a virtual network that we're gonna either create or attach to. [00:25:39] Bryan: We've got a, a whole bunch of things we need to go do for that. For all of these things, there are metadata components that need, we need to keep track of this thing that, beyond the actual infrastructure that we create. And then we need to go actually, like act on the actual compute elements, the hostos, what have you, the switches, what have you, and actually go. [00:25:56] Bryan: Create these underlying things and then connect them. And there's of course, the challenge of just getting that working is a big challenge. Um, but getting that working robustly, getting that working is, you know, when you go to provision of vm, um, the, all the, the, the steps that need to happen and what happens if one of those steps fails along the way? [00:26:17] Bryan: What happens if, you know, one thing we're very mindful of is these kind of, you get these long tails of like, why, you know, generally our VM provisioning happened within this time, but we get these long tails where it takes much longer. What's going on? What, where in this process are we, are we actually spending time? [00:26:33] Bryan: Uh, and there's a whole lot of complexity that you need to go deal with that. There's a lot of complexity that you need to go deal with this effectively, this workflow that's gonna go create these things and manage them. Um, we use a, a pattern that we call, that are called sagas, actually is a, is a database pattern from the eighties. [00:26:51] Bryan: Uh, Katie McCaffrey is a, is a database reCrcher who, who, uh, I, I think, uh, reintroduce the idea of, of sagas, um, in the last kind of decade. Um, and this is something that we picked up, um, and I've done a lot of really interesting things with, um, to allow for, to this kind of, these workflows to be, to be managed and done so robustly in a way that you can restart them and so on. [00:27:16] Bryan: Uh, and then you guys, you get this whole distributed system that can do all this. That whole distributed system, that itself needs to be reliable and available. So if you, you know, you need to be able to, what happens if you, if you pull a sled or if a sled fails, how does the system deal with that? [00:27:33] Bryan: How does the system deal with getting an another sled added to the system? Like how do you actually grow this distributed system? And then how do you update it? How do you actually go from one version to the next? And all of that has to happen across an air gap where this is gonna run as part of the computer. [00:27:49] Bryan: So there are, it, it is fractally complicated. There, there is a lot of complexity here in, in software, in the software system and all of that. We kind of, we call the control plane. Um, and it, this is the what exists at AWS at GCP, at Azure. When you are hitting an endpoint that's provisioning an EC2 instance for you. [00:28:10] Bryan: There is an AWS control plane that is, is doing all of this and has, uh, some of these similar aspects and certainly some of these similar challenges. Are vSphere / Proxmox / Hyper-V in the same category? [00:28:20] Jeremy: And for people who have run their own servers with something like say VMware or Hyper V or Proxmox, are those in the same category? [00:28:32] Bryan: Yeah, I mean a little bit. I mean, it kind of like vSphere Yes. Via VMware. No. So it's like you, uh, VMware ESX is, is kind of a key building block upon which you can build something that is a more meaningful distributed system. When it's just like a machine that you're provisioning VMs on, it's like, okay, well that's actually, you as the human might be the control plane. [00:28:52] Bryan: Like, that's, that, that's, that's a much easier problem. Um, but when you've got, you know, tens, hundreds, thousands of machines, you need to do it robustly. You need something to coordinate that activity and you know, you need to pick which sled you land on. You need to be able to move these things. You need to be able to update that whole system. [00:29:06] Bryan: That's when you're getting into a control plane. So, you know, some of these things have kind of edged into a control plane, certainly VMware. Um, now Broadcom, um, has delivered something that's kind of cloudish. Um, I think that for folks that are truly born on the cloud, it, it still feels somewhat, uh, like you're going backwards in time when you, when you look at these kind of on-prem offerings. [00:29:29] Bryan: Um, but, but it, it, it's got these aspects to it for sure. Um, and I think that we're, um, some of these other things when you're just looking at KVM or just looks looking at Proxmox you kind of need to, to connect it to other broader things to turn it into something that really looks like manageable infrastructure. [00:29:47] Bryan: And then many of those projects are really, they're either proprietary projects, uh, proprietary products like vSphere, um, or you are really dealing with open source projects that are. Not necessarily aimed at the same level of scale. Um, you know, you look at a, again, Proxmox or, uh, um, you'll get an OpenStack. [00:30:05] Bryan: Um, and you know, OpenStack is just a lot of things, right? I mean, OpenStack has got so many, the OpenStack was kind of a, a free for all, for every infrastructure vendor. Um, and I, you know, there was a time people were like, don't you, aren't you worried about all these companies together that, you know, are coming together for OpenStack? [00:30:24] Bryan: I'm like, haven't you ever worked for like a company? Like, companies don't get along. By the way, it's like having multiple companies work together on a thing that's bad news, not good news. And I think, you know, one of the things that OpenStack has definitely struggled with, kind of with what, actually the, the, there's so many different kind of vendor elements in there that it's, it's very much not a product, it's a project that you're trying to run. [00:30:47] Bryan: But that's, but that very much is in, I mean, that's, that's similar certainly in spirit. [00:30:53] Jeremy: And so I think this is kind of like you're alluding to earlier, the piece that allows you to allocate, compute, storage, manage networking, gives you that experience of I can go to a web console or I can use an API and I can spin up machines, get them all connected. At the end of the day, the control plane. Is allowing you to do that in hopefully a user-friendly way. [00:31:21] Bryan: That's right. Yep. And in the, I mean, in order to do that in a modern way, it's not just like a user-friendly way. You really need to have a CLI and a web UI and an API. Those all need to be drawn from the same kind of single ground truth. Like you don't wanna have any of those be an afterthought for the other. [00:31:39] Bryan: You wanna have the same way of generating all of those different endpoints and, and entries into the system. Building a control plane now has better tools (Rust, CockroachDB) [00:31:46] Jeremy: And if you take your time at Joyent as an example. What kind of tools existed for that versus how much did you have to build in-house for as far as the hypervisor and managing the compute and all that? [00:32:02] Bryan: Yeah, so we built more or less everything in house. I mean, what you have is, um, and I think, you know, over time we've gotten slightly better tools. Um, I think, and, and maybe it's a little bit easier to talk about the, kind of the tools we started at Oxide because we kind of started with a, with a clean sheet of paper at oxide. [00:32:16] Bryan: We wanted to, knew we wanted to go build a control plane, but we were able to kind of go revisit some of the components. So actually, and maybe I'll, I'll talk about some of those changes. So when we, at, For example, at Joyent, when we were building a cloud at Joyent, there wasn't really a good distributed database. [00:32:34] Bryan: Um, so we were using Postgres as our database for metadata and there were a lot of challenges. And Postgres is not a distributed database. It's running. With a primary secondary architecture, and there's a bunch of issues there, many of which we discovered the hard way. Um, when we were coming to oxide, you have much better options to pick from in terms of distributed databases. [00:32:57] Bryan: You know, we, there was a period that now seems maybe potentially brief in hindsight, but of a really high quality open source distributed databases. So there were really some good ones to, to pick from. Um, we, we built on CockroachDB on CRDB. Um, so that was a really important component. That we had at oxide that we didn't have at Joyent. [00:33:19] Bryan: Um, so we were, I wouldn't say we were rolling our own distributed database, we were just using Postgres and uh, and, and dealing with an enormous amount of pain there in terms of the surround. Um, on top of that, and, and, you know, a, a control plane is much more than a database, obviously. Uh, and you've gotta deal with, uh, there's a whole bunch of software that you need to go, right. [00:33:40] Bryan: Um, to be able to, to transform these kind of API requests into something that is reliable infrastructure, right? And there, there's a lot to that. Uh, especially when networking gets in the mix, when storage gets in the mix, uh, there are a whole bunch of like complicated steps that need to be done, um, at Joyent. [00:33:59] Bryan: Um, we, in part because of the history of the company and like, look. This, this just is not gonna sound good, but it just is what it is and I'm just gonna own it. We did it all in Node, um, at Joyent, which I, I, I know it sounds really right now, just sounds like, well, you, you built it with Tinker Toys. You Okay. [00:34:18] Bryan: Uh, did, did you think it was, you built the skyscraper with Tinker Toys? Uh, it's like, well, okay. We actually, we had greater aspirations for the Tinker Toys once upon a time, and it was better than, you know, than Twisted Python and Event Machine from Ruby, and we weren't gonna do it in Java. All right. [00:34:32] Bryan: So, but let's just say that that experiment, uh, that experiment did ultimately end in a predictable fashion. Um, and, uh, we, we decided that maybe Node was not gonna be the best decision long term. Um, Joyent was the company behind node js. Uh, back in the day, Ryan Dahl worked for Joyent. Uh, and then, uh, then we, we, we. [00:34:53] Bryan: Uh, landed that in a foundation in about, uh, what, 2015, something like that. Um, and began to consider our world beyond, uh, beyond Node. Rust at Oxide [00:35:04] Bryan: A big tool that we had in the arsenal when we started Oxide is Rust. Um, and so indeed the name of the company is, is a tip of the hat to the language that we were pretty sure we were gonna be building a lot of stuff in. [00:35:16] Bryan: Namely Rust. And, uh, rust is, uh, has been huge for us, a very important revolution in programming languages. you know, there, there, there have been different people kind of coming in at different times and I kinda came to Rust in what I, I think is like this big kind of second expansion of rust in 2018 when a lot of technologists were think, uh, sick of Node and also sick of Go. [00:35:43] Bryan: And, uh, also sick of C++. And wondering is there gonna be something that gives me the, the, the performance, of that I get outta C. The, the robustness that I can get out of a C program but is is often difficult to achieve. but can I get that with kind of some, some of the velocity of development, although I hate that term, some of the speed of development that you get out of a more interpreted language. [00:36:08] Bryan: Um, and then by the way, can I actually have types, I think types would be a good idea? Uh, and rust obviously hits the sweet spot of all of that. Um, it has been absolutely huge for us. I mean, we knew when we started the company again, oxide, uh, we were gonna be using rust in, in quite a, quite a. Few places, but we weren't doing it by fiat. [00:36:27] Bryan: Um, we wanted to actually make sure we're making the right decision, um, at, at every different, at every layer. Uh, I think what has been surprising is the sheer number of layers at which we use rust in terms of, we've done our own embedded firmware in rust. We've done, um, in, in the host operating system, which is still largely in C, but very big components are in rust. [00:36:47] Bryan: The hypervisor Propolis is all in rust. Uh, and then of course the control plane, that distributed system on that is all in rust. So that was a very important thing that we very much did not need to build ourselves. We were able to really leverage, uh, a terrific community. Um. We were able to use, uh, and we've done this at Joyent as well, but at Oxide, we've used Illumos as a hostos component, which, uh, our variant is called Helios. [00:37:11] Bryan: Um, we've used, uh, bhyve um, as a, as as that kind of internal hypervisor component. we've made use of a bunch of different open source components to build this thing, um, which has been really, really important for us. Uh, and open source components that didn't exist even like five years prior. [00:37:28] Bryan: That's part of why we felt that 2019 was the right time to start the company. And so we started Oxide. The problems building a control plane in Node [00:37:34] Jeremy: You had mentioned that at Joyent, you had tried to build this in, in Node. What were the, what were the, the issues or the, the challenges that you had doing that? [00:37:46] Bryan: Oh boy. Yeah. again, we, I kind of had higher hopes in 2010, I would say. When we, we set on this, um, the, the, the problem that we had just writ large, um. JavaScript is really designed to allow as many people on earth to write a program as possible, which is good. I mean, I, I, that's a, that's a laudable goal. [00:38:09] Bryan: That is the goal ultimately of such as it is of JavaScript. It's actually hard to know what the goal of JavaScript is, unfortunately, because Brendan Ike never actually wrote a book. so that there is not a canonical, you've got kind of Doug Crockford and other people who've written things on JavaScript, but it's hard to know kind of what the original intent of JavaScript is. [00:38:27] Bryan: The name doesn't even express original intent, right? It was called Live Script, and it was kind of renamed to JavaScript during the Java Frenzy of the late nineties. A name that makes no sense. There is no Java in JavaScript. that is kind of, I think, revealing to kind of the, uh, the unprincipled mess that is JavaScript. [00:38:47] Bryan: It, it, it's very pragmatic at some level, um, and allows anyone to, it makes it very easy to write software. The problem is it's much more difficult to write really rigorous software. So, uh, and this is what I should differentiate JavaScript from TypeScript. This is really what TypeScript is trying to solve. [00:39:07] Bryan: TypeScript is like. How can, I think TypeScript is a, is a great step forward because TypeScript is like, how can we bring some rigor to this? Like, yes, it's great that it's easy to write JavaScript, but that's not, we, we don't wanna do that for Absolutely. I mean that, that's not the only problem we solve. [00:39:23] Bryan: We actually wanna be able to write rigorous software and it's actually okay if it's a little harder to write rigorous software that's actually okay if it gets leads to, to more rigorous artifacts. Um, but in JavaScript, I mean, just a concrete example. You know, there's nothing to prevent you from referencing a property that doesn't actually exist in JavaScript. [00:39:43] Bryan: So if you fat finger a property name, you are relying on something to tell you. By the way, I think you've misspelled this because there is no type definition for this thing. And I don't know that you've got one that's spelled correctly, one that's spelled incorrectly, that's often undefined. And then the, when you actually go, you say you've got this typo that is lurking in your what you want to be rigorous software. [00:40:07] Bryan: And if you don't execute that code, like you won't know that's there. And then you do execute that code. And now you've got a, you've got an undefined object. And now that's either gonna be an exception or it can, again, depends on how that's handled. It can be really difficult to determine the origin of that, of, of that error, of that programming. [00:40:26] Bryan: And that is a programmer error. And one of the big challenges that we had with Node is that programmer errors and operational errors, like, you know, I'm out of disk space as an operational error. Those get conflated and it becomes really hard. And in fact, I think the, the language wanted to make it easier to just kind of, uh, drive on in the event of all errors. [00:40:53] Bryan: And it's like, actually not what you wanna do if you're trying to build a reliable, robust system. So we had. No end of issues. [00:41:01] Bryan: We've got a lot of experience developing rigorous systems, um, again coming out of operating systems development and so on. And we want, we brought some of that rigor, if strangely, to JavaScript. So one of the things that we did is we brought a lot of postmortem, diagnos ability and observability to node. [00:41:18] Bryan: And so if, if one of our node processes. Died in production, we would actually get a core dump from that process, a core dump that we could actually meaningfully process. So we did a bunch of kind of wild stuff. I mean, actually wild stuff where we could actually make sense of the JavaScript objects in a binary core dump. JavaScript values ease of getting started over robustness [00:41:41] Bryan: Um, and things that we thought were really important, and this is the, the rest of the world just looks at this being like, what the hell is this? I mean, it's so out of step with it. The problem is that we were trying to bridge two disconnected cultures of one developing really. Rigorous software and really designing it for production, diagnosability and the other, really designing it to software to run in the browser and for anyone to be able to like, you know, kind of liven up a webpage, right? [00:42:10] Bryan: Is kinda the origin of, of live script and then JavaScript. And we were kind of the only ones sitting at the intersection of that. And you begin when you are the only ones sitting at that kind of intersection. You just are, you're, you're kind of fighting a community all the time. And we just realized that we are, there were so many things that the community wanted to do that we felt are like, no, no, this is gonna make software less diagnosable. It's gonna make it less robust. The NodeJS split and why people left [00:42:36] Bryan: And then you realize like, I'm, we're the only voice in the room because we have got, we have got desires for this language that it doesn't have for itself. And this is when you realize you're in a bad relationship with software. It's time to actually move on. And in fact, actually several years after, we'd already kind of broken up with node. [00:42:55] Bryan: Um, and it was like, it was a bit of an acrimonious breakup. there was a, uh, famous slash infamous fork of node called IoJS Um, and this was viewed because people, the community, thought that Joyent was being what was not being an appropriate steward of node js and was, uh, not allowing more things to come into to, to node. [00:43:19] Bryan: And of course, the reason that we of course, felt that we were being a careful steward and we were actively resisting those things that would cut against its fitness for a production system. But it's some way the community saw it and they, and forked, um, and, and I think the, we knew before the fork that's like, this is not working and we need to get this thing out of our hands. Platform is a reflection of values node summit talk [00:43:43] Bryan: And we're are the wrong hands for this? This needs to be in a foundation. Uh, and so we kind of gone through that breakup, uh, and maybe it was two years after that. That, uh, friend of mine who was um, was running the, uh, the node summit was actually, it's unfortunately now passed away. Charles er, um, but Charles' venture capitalist great guy, and Charles was running Node Summit and came to me in 2017. [00:44:07] Bryan: He is like, I really want you to keynote Node Summit. And I'm like, Charles, I'm not gonna do that. I've got nothing nice to say. Like, this is the, the, you don't want, I'm the last person you wanna keynote. He's like, oh, if you have nothing nice to say, you should definitely keynote. You're like, oh God, okay, here we go. [00:44:22] Bryan: He's like, no, I really want you to talk about, like, you should talk about the Joyent breakup with NodeJS. I'm like, oh man. [00:44:29] Bryan: And that led to a talk that I'm really happy that I gave, 'cause it was a very important talk for me personally. Uh, called Platform is a reflection of values and really looking at the values that we had for Node and the values that Node had for itself. And they didn't line up. [00:44:49] Bryan: And the problem is that the values that Node had for itself and the values that we had for Node are all kind of positives, right? Like there's nobody in the node community who's like, I don't want rigor, I hate rigor. It's just that if they had the choose between rigor and making the language approachable. [00:45:09] Bryan: They would choose approachability every single time. They would never choose rigor. And, you know, that was a, that was a big eye-opener. I do, I would say, if you watch this talk. [00:45:20] Bryan: because I knew that there's, like, the audience was gonna be filled with, with people who, had been a part of the fork in 2014, I think was the, the, the, the fork, the IOJS fork. And I knew that there, there were, there were some, you know, some people that were, um, had been there for the fork and. [00:45:41] Bryan: I said a little bit of a trap for the audience. But the, and the trap, I said, you know what, I, I kind of talked about the values that we had and the aspirations we had for Node, the aspirations that Node had for itself and how they were different. [00:45:53] Bryan: And, you know, and I'm like, look in, in, in hindsight, like a fracture was inevitable. And in 2014 there was finally a fracture. And do people know what happened in 2014? And if you, if you, you could listen to that talk, everyone almost says in unison, like IOJS. I'm like, oh right. IOJS. Right. That's actually not what I was thinking of. [00:46:19] Bryan: And I go to the next slide and is a tweet from a guy named TJ Holloway, Chuck, who was the most prolific contributor to Node. And it was his tweet also in 2014 before the fork, before the IOJS fork explaining that he was leaving Node and that he was going to go. And you, if you turn the volume all the way up, you can hear the audience gasp. [00:46:41] Bryan: And it's just delicious because the community had never really come, had never really confronted why TJ left. Um, there. And I went through a couple folks, Felix, bunch of other folks, early Node folks. That were there in 2010, were leaving in 2014, and they were going to go primarily, and they were going to go because they were sick of the same things that we were sick of. [00:47:09] Bryan: They, they, they had hit the same things that we had hit and they were frustrated. I I really do believe this, that platforms do reflect their own values. And when you are making a software decision, you are selecting value. [00:47:26] Bryan: You should select values that align with the values that you have for that software. That is, those are, that's way more important than other things that people look at. I think people look at, for example, quote unquote community size way too frequently, community size is like. Eh, maybe it can be fine. [00:47:44] Bryan: I've been in very large communities, node. I've been in super small open source communities like AUMs and RAs, a bunch of others. there are strengths and weaknesses to both approaches just as like there's a strength to being in a big city versus a small town. Me personally, I'll take the small community more or less every time because the small community is almost always self-selecting based on values and just for the same reason that I like working at small companies or small teams. [00:48:11] Bryan: There's a lot of value to be had in a small community. It's not to say that large communities are valueless, but again, long answer to your question of kind of where did things go south with Joyent and node. They went south because the, the values that we had and the values the community had didn't line up and that was a very educational experience, as you might imagine. [00:48:33] Jeremy: Yeah. And, and given that you mentioned how, because of those values, some people moved from Node to go, and in the end for much of what oxide is building. You ended up using rust. What, what would you say are the, the values of go and and rust, and how did you end up choosing Rust given that. Go's decisions regarding generics, versioning, compilation speed priority [00:48:56] Bryan: Yeah, I mean, well, so the value for, yeah. And so go, I mean, I understand why people move from Node to Go, go to me was kind of a lateral move. Um, there were a bunch of things that I, uh, go was still garbage collected, um, which I didn't like. Um, go also is very strange in terms of there are these kind of like. [00:49:17] Bryan: These autocratic kind of decisions that are very bizarre. Um, there, I mean, generics is kind of a famous one, right? Where go kind of as a point of principle didn't have generics, even though go itself actually the innards of go did have generics. It's just that you a go user weren't allowed to have them. [00:49:35] Bryan: And you know, it's kind of, there was, there was an old cartoon years and years ago about like when a, when a technologist is telling you that something is technically impossible, that actually means I don't feel like it. Uh, and there was a certain degree of like, generics are technically impossible and go, it's like, Hey, actually there are. [00:49:51] Bryan: And so there was, and I just think that the arguments against generics were kind of disingenuous. Um, and indeed, like they ended up adopting generics and then there's like some super weird stuff around like, they're very anti-assertion, which is like, what, how are you? Why are you, how is someone against assertions, it doesn't even make any sense, but it's like, oh, nope. [00:50:10] Bryan: Okay. There's a whole scree on it. Nope, we're against assertions and the, you know, against versioning. There was another thing like, you know, the Rob Pike has kind of famously been like, you should always just run on the way to commit. And you're like, does that, is that, does that make sense? I mean this, we actually built it. [00:50:26] Bryan: And so there are a bunch of things like that. You're just like, okay, this is just exhausting and. I mean, there's some things about Go that are great and, uh, plenty of other things that I just, I'm not a fan of. Um, I think that the, in the end, like Go cares a lot about like compile time. It's super important for Go Right? [00:50:44] Bryan: Is very quick, compile time. I'm like, okay. But that's like compile time is not like, it's not unimportant, it's doesn't have zero importance. But I've got other things that are like lots more important than that. Um, what I really care about is I want a high performing artifact. I wanted garbage collection outta my life. Don't think garbage collection has good trade offs [00:51:00] Bryan: I, I gotta tell you, I, I like garbage collection to me is an embodiment of this like, larger problem of where do you put cognitive load in the software development process. And what garbage collection is saying to me it is right for plenty of other people and the software that they wanna develop. [00:51:21] Bryan: But for me and the software that I wanna develop, infrastructure software, I don't want garbage collection because I can solve the memory allocation problem. I know when I'm like, done with something or not. I mean, it's like I, whether that's in, in C with, I mean it's actually like, it's really not that hard to not leak memory in, in a C base system. [00:51:44] Bryan: And you can. give yourself a lot of tooling that allows you to diagnose where memory leaks are coming from. So it's like that is a solvable problem. There are other challenges with that, but like, when you are developing a really sophisticated system that has garbage collection is using garbage collection. [00:51:59] Bryan: You spend as much time trying to dork with the garbage collector to convince it to collect the thing that you know is garbage. You are like, I've got this thing. I know it's garbage. Now I need to use these like tips and tricks to get the garbage collector. I mean, it's like, it feels like every Java performance issue goes to like minus xx call and use the other garbage collector, whatever one you're using, use a different one and using a different, a different approach. [00:52:23] Bryan: It's like, so you're, you're in this, to me, it's like you're in the worst of all worlds where. the reason that garbage collection is helpful is because the programmer doesn't have to think at all about this problem. But now you're actually dealing with these long pauses in production. [00:52:38] Bryan: You're dealing with all these other issues where actually you need to think a lot about it. And it's kind of, it, it it's witchcraft. It, it, it's this black box that you can't see into. So it's like, what problem have we solved exactly? And I mean, so the fact that go had garbage collection, it's like, eh, no, I, I do not want, like, and then you get all the other like weird fatwahs and you know, everything else. [00:52:57] Bryan: I'm like, no, thank you. Go is a no thank you for me, I, I get it why people like it or use it, but it's, it's just, that was not gonna be it. Choosing Rust [00:53:04] Bryan: I'm like, I want C. but I, there are things I didn't like about C too. I was looking for something that was gonna give me the deterministic kind of artifact that I got outta C. But I wanted library support and C is tough because there's, it's all convention. you know, there's just a bunch of other things that are just thorny. And I remember thinking vividly in 2018, I'm like, well, it's rust or bust. Ownership model, algebraic types, error handling [00:53:28] Bryan: I'm gonna go into rust. And, uh, I hope I like it because if it's not this, it's gonna like, I'm gonna go back to C I'm like literally trying to figure out what the language is for the back half of my career. Um, and when I, you know, did what a lot of people were doing at that time and people have been doing since of, you know, really getting into rust and really learning it, appreciating the difference in the, the model for sure, the ownership model people talk about. [00:53:54] Bryan: That's also obviously very important. It was the error handling that blew me away. And the idea of like algebraic types, I never really had algebraic types. Um, and the ability to, to have. And for error handling is one of these really, uh, you, you really appreciate these things where it's like, how do you deal with a, with a function that can either succeed and return something or it can fail, and the way c deals with that is bad with these kind of sentinels for errors. [00:54:27] Bryan: And, you know, does negative one mean success? Does negative one mean failure? Does zero mean failure? Some C functions, zero means failure. Traditionally in Unix, zero means success. And like, what if you wanna return a file descriptor, you know, it's like, oh. And then it's like, okay, then it'll be like zero through positive N will be a valid result. [00:54:44] Bryan: Negative numbers will be, and like, was it negative one and I said airo, or is it a negative number that did not, I mean, it's like, and that's all convention, right? People do all, all those different things and it's all convention and it's easy to get wrong, easy to have bugs, can't be statically checked and so on. Um, and then what Go says is like, well, you're gonna have like two return values and then you're gonna have to like, just like constantly check all of these all the time. Um, which is also kind of gross. Um, JavaScript is like, Hey, let's toss an exception. If, if we don't like something, if we see an error, we'll, we'll throw an exception. [00:55:15] Bryan: There are a bunch of reasons I don't like that. Um, and you look, you'll get what Rust does, where it's like, no, no, no. We're gonna have these algebra types, which is to say this thing can be a this thing or that thing, but it, but it has to be one of these. And by the way, you don't get to process this thing until you conditionally match on one of these things. [00:55:35] Bryan: You're gonna have to have a, a pattern match on this thing to determine if it's a this or a that, and if it in, in the result type that you, the result is a generic where it's like, it's gonna be either the thing that you wanna return. It's gonna be an okay that contains the thing you wanna return, or it's gonna be an error that contains your error and it forces your code to deal with that. [00:55:57] Bryan: And what that does is it shifts the cognitive load from the person that is operating this thing in production to the, the actual developer that is in development. And I think that that, that to me is like, I, I love that shift. Um, and that shift to me is really important. Um, and that's what I was missing, that that's what Rust gives you. [00:56:23] Bryan: Rust forces you to think about your code as you write it, but as a result, you have an artifact that is much more supportable, much more sustainable, and much faster. Prefer to frontload cognitive load during development instead of at runtime [00:56:34] Jeremy: Yeah, it sounds like you would rather take the time during the development to think about these issues because whether it's garbage collection or it's error handling at runtime when you're trying to solve a problem, then it's much more difficult than having dealt with it to start with. [00:56:57] Bryan: Yeah, absolutely. I, and I just think that like, why also, like if it's software, if it's, again, if it's infrastructure software, I mean the kinda the question that you, you should have when you're writing software is how long is this software gonna live? How many people are gonna use this software? Uh, and if you are writing an operating system, the answer for this thing that you're gonna write, it's gonna live for a long time. [00:57:18] Bryan: Like, if we just look at plenty of aspects of the system that have been around for a, for decades, it's gonna live for a long time and many, many, many people are gonna use it. Why would we not expect people writing that software to have more cognitive load when they're writing it to give us something that's gonna be a better artifact? [00:57:38] Bryan: Now conversely, you're like, Hey, I kind of don't care about this. And like, I don't know, I'm just like, I wanna see if this whole thing works. I've got, I like, I'm just stringing this together. I don't like, no, the software like will be lucky if it survives until tonight, but then like, who cares? Yeah. Yeah. [00:57:52] Bryan: Gar garbage clock. You know, if you're prototyping something, whatever. And this is why you really do get like, you know, different choices, different technology choices, depending on the way that you wanna solve the problem at hand. And for the software that I wanna write, I do like that cognitive load that is upfront. With LLMs maybe you can get the benefit of the robust artifact with less cognitive load [00:58:10] Bryan: Um, and although I think, I think the thing that is really wild that is the twist that I don't think anyone really saw coming is that in a, in an LLM age. That like the cognitive load upfront almost needs an asterisk on it because so much of that can be assisted by an LLM. And now, I mean, I would like to believe, and maybe this is me being optimistic, that the the, in the LLM age, we will see, I mean, rust is a great fit for the LLMH because the LLM itself can get a lot of feedback about whether the software that's written is correct or not. [00:58:44] Bryan: Much more so than you can for other environments. [00:58:48] Jeremy: Yeah, that is a interesting point in that I think when people first started trying out the LLMs to code, it was really good at these maybe looser languages like Python or JavaScript, and initially wasn't so good at something like Rust. But it sounds like as that improves, if. It can write it then because of the rigor or the memory management or the error handling that the language is forcing you to do, it might actually end up being a better choice for people using LLMs. [00:59:27] Bryan: absolutely. I, it, it gives you more certainty in the artifact that you've delivered. I mean, you know a lot about a Rust program that compiles correctly. I mean, th there are certain classes of errors that you don't have, um, that you actually don't know on a C program or a GO program or a, a JavaScript program. [00:59:46] Bryan: I think that's gonna be really important. I think we are on the cusp. Maybe we've already seen it, this kind of great bifurcation in the software that we writ

This week we're talking about Torvalds vibe coding, the newest Pi AI hat, and what's new with PipeWire and OBS Studio. Then there's some great news in Wine 11 and Hangover 11, Fedora's Games Spin is moving to KDE, and we talk about LetsEncrypt and their new IP certificates. For tips we have csvi for editing comma-separated-values files on the command line, espeak-ng for giving your Linux machine a voice, and the hidden support for Screen Savers in KDE. You can find the show notes at https://bit.ly/4jKwHyV and have a great week! Host: Jonathan Bennett Co-Hosts: Ken McDonald and Rob Campbell Download or subscribe to Untitled Linux Show at https://twit.tv/shows/untitled-linux-show Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

This week we're talking about Torvalds vibe coding, the newest Pi AI hat, and what's new with PipeWire and OBS Studio. Then there's some great news in Wine 11 and Hangover 11, Fedora's Games Spin is moving to KDE, and we talk about LetsEncrypt and their new IP certificates. For tips we have csvi for editing comma-separated-values files on the command line, espeak-ng for giving your Linux machine a voice, and the hidden support for Screen Savers in KDE. You can find the show notes at https://bit.ly/4jKwHyV and have a great week! Host: Jonathan Bennett Co-Hosts: Ken McDonald and Rob Campbell Download or subscribe to Untitled Linux Show at https://twit.tv/shows/untitled-linux-show Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free audio and video feeds, a members-only Discord, and exclusive content. Join today: https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

Rising workplace use of artificial intelligence is outpacing organizational governance, according to data from Microsoft and Gallup. Microsoft reports global AI adoption reached 16.3% in 2025, while Gallup finds nearly half of U.S. workers use AI tools at work at least annually. Despite that usage, only a minority of employees report clear employer guidance on AI ownership and purpose, creating accountability gaps that frequently surface during incidents or audits.Additional data underscores uneven adoption and oversight. Microsoft's AI Economy Institute notes adoption rates in the Global North are nearly double those in the Global South, correlating with earlier infrastructure and policy investment. Within organizations, most AI usage remains occasional rather than daily and is concentrated in knowledge roles, suggesting informal, user-driven deployment rather than standardized programs—conditions that complicate governance for MSP-supported environments.Microsoft's product moves further elevate the governance issue. The company is testing policies allowing IT administrators to uninstall Copilot on managed devices while simultaneously enforcing Windows and Office end-of-life timelines through 2026 and embedding purchasing directly into Copilot workflows. These changes expand administrative control but also place AI more firmly inside operational and economic decision paths that MSPs help manage.Platform announcements from Acronis, Hexnode, and Google extend automation from assistance to execution, while public comments from Nvidia CEO Jensen Huang and Linux creator Linus Torvalds highlight differing views on AI speed versus discipline. For MSPs and IT service providers, the practical takeaway centers on accountability: as AI systems take actions rather than make suggestions, governance, policy definition, and oversight become explicit services rather than implied responsibilities. Four things to know today 00:00 AI Use Expands at Work, but Employees Say Transparency and Ownership Are Missing04:37 Microsoft Lets IT Uninstall Copilot as Windows and Office End-of-Life Deadlines Near07:38 Acronis Launches Archival Storage as Hexnode and Google Advance Platform-Centric Automation11:07 Jensen Huang Warns Against AI Regulation as Linus Torvalds Limits AI's Role in Critical Code This is the Business of Tech.     Supported by:  https://scalepad.com/dave/

Linus Torvalds pushes AI generated code, Jordan Fulghum thinks this is the year of self-hosting, FracturedJson formats for compact / human readability, Scott Werner believes a flood of adequate software is coming, and Sean Goedecke explains why generic software design advice is useless.

Linus Torvalds pushes AI generated code, Jordan Fulghum thinks this is the year of self-hosting, FracturedJson formats for compact / human readability, Scott Werner believes a flood of adequate software is coming, and Sean Goedecke explains why generic software design advice is useless.