Podcasts about cpu

A Computex 2026 trouxe uma série de anúncios importantes para o mercado de tecnologia, mas poucos chamaram tanta atenção quanto o RTX Spark, a nova plataforma da NVIDIA voltada para computação acelerada por IA em dispositivos locais. Neste episódio do Diocast, discutimos o que exatamente é o RTX Spark, quais problemas ele pretende resolver e como ele se posiciona em um mercado que já conta com soluções como Snapdragon X Elite, Ryzen AI e os novos processadores Intel com aceleração dedicada para inteligência artificial.Mais do que simplesmente lançar um novo chip, a NVIDIA parece estar ampliando sua presença para além das placas de vídeo tradicionais. O RTX Spark combina CPU baseada em arquitetura ARM, GPU com tecnologias derivadas do ecossistema RTX e recursos dedicados para cargas de trabalho envolvendo inteligência artificial. Na prática, isso pode abrir espaço para computadores mais eficientes, capazes de executar modelos de IA localmente, reduzindo a dependência de serviços em nuvem e melhorando aspectos como privacidade, latência e disponibilidade.---https://diolinux.com.br/podcast/lancamento-da-nvidia-rtx-spark.html

US stocks closed sharply higher on Thursday, with the S&P 500 rising 1.8%, the Nasdaq gaining 2.5%, and the Dow Jones climbing 930 points. Investor sentiment improved amid a pullback in oil prices after President Trump cancelled strikes against Iran after earlier threatening "very hard" attacks tonight. He also claimed a deal had been agreed in principle by several allies in the Middle East, including Israel, without elaborating. Further support came from a rally in technology shares as investors positioned themselves ahead of SpaceX's expected IPO tomorrow. Micron and AMD soared 11% and 8%, respectively, while Lam Research added 12.7% and Intel jumped over 10% after being upgraded by BofA on soaring CPU orders. On the other hand, Oracle slipped nearly 9% as investors focused on a cloud revenue miss and rising AI infrastructure costs despite an earnings beat. On the data front, PPI data pointed to accelerating prices in May, consolidating bets that the Fed will raise rates this year.SPI jumps 1436 - Gold up 3% plus...Marcus Today – Daily Market Insights Marcus Today provides clear, practical commentary for self-directed investors – covering markets, portfolios, education, and decision-making without the noise. If you'd like to go further: Start a free 14-day trial of Marcus Today http://bit.ly/mt-trial-podcast Join Marcus Today Use code MTPODCAST for 10% off http://bit.ly/mt-join-podcast-offer MT20 – Managed ETF Portfolio A professionally managed portfolio run by Marcus Padley and the team, using ASX-listed ETFs with active market timing. http://bit.ly/mt20-podcast Principles – How We Think About Investing A short video series on timing, behaviour, and decision-making. No stock tips. http://bit.ly/mt-principles-podcast — Disclaimer This podcast is general information only and does not consider your personal circumstances. It is not personal financial advice. 

Adeniyi Abiodun has been in crypto since 2012, built trading and risk systems at investment banks, and led R&D on Facebook's Project Libra at Meta before co-founding Mysten Labs. So when he says every other L1 has a "skill issue" baked in at architecture time, it's worth listening.David Sencil sits down with Adeniyi at Consensus 2026 to walk through how Sui solved horizontal-scale consensus, why a famous L1 founder said it was impossible, and what comes next — native stablecoins, private payments by default, Walrus storage, and the agentic payment rails Stripe is pricing at a billion TPS.We cover:- Why every other L1 is capped by a single CPU and Moore's Law- The Project Libra story — "way too early" and what survived into Sui- 300ms finality vs Solana's 12 seconds- SuiUSD: $63M in a month and a half, free stablecoin transfers- Protocol-level private stablecoin transactions launching this year- Walrus storage outgrowing Arweave in a year- Why "AI doesn't care about your tribe"Filmed at Consensus 2026.Host: David Sencil

Dans cet épisode crossover Apple Différemment x Tech Café, on revient sur la WWDC 2026 d'Apple et sur la réception de la conférence. Une première impression de déception puis, avec une lecture plus attentive, Apple a finalement présenté plusieurs évolutions concrètes sur ses appareils.  Me soutenir sur Patreon Me retrouver sur YouTube On discute ensemble sur Discord Les annonces phare sur les OS Finies les séquences par OS, on optimise partout et on nettoie les vitres. Les apps se chargent plus vite, la recherche enfin pertinente et à une vitesse décente, recherche des plus beaux sourires de vos photos et vidéos, planificateur de processeur (CPU) optimisé (y compris anciens iPhone), gestion du JavaScript accélérée, switch wifi / connexion cellulaire Contrôle parental : refonte complète On est en 2026 : IA, agents et vibe coding Siri AI, app dédiée, des promesses mais pas partout (la bêta et l'Apple Watch est notre amie) L'édition de photos se met à niveau (vraiment), la génération d'images aussi Vibe coding de raccourcis ou l'aveu de l'échec du nocode Changement des mots de passe par agent IA 5 nouveaux Apple Foundation Models, : plus complexe et complet qu'il n'y paraît Ce qui sera disponible ou pas Mais aussi… Entre politique et annonces ringardes Des annonces sans les citer : un Mac tactile (dessin dans Notes, pull down to refresh, affichage des bordures des fenêtres pour l'accessibilité), l'iPhone pliant, un MacBook Neo avec 12 Go de RAM Compatibilité des OS : M pour le Mac, comme iOS 26 pour l'iPhone et c'est plus critique sur l'Apple Watch (SE 3, 9, ou Ultra 2 minimum), et quelques iPad abandonnés (il faut au moins un processeur A13 ou plus exactement un A12Z (iPad Pro de 2020) Quelques évolutions dans Notes (format markdown, liens entre les sections) Albums vraiment partagés avec autres OS Râle d'agonie ? Des annonces visionOS (fenêtres courbées, centre de contrôle revus, panoramas d'après vos photos, Siri au regard) Adieu Hidden Bar, les services de création de cartes Pas Apple Divorce acté entre les chargeurs et leurs câbles soudés USB-C en Europe Baisse de prix de l'abonnement Google Gemini AI Plus Les prix des forfaits en France vont-ils augmenter ? La voiture électrique sauve des vies (enfin évite des morts) Jeux vidéo La conclusion du Joy-Con Drift en France Participants Avec Mat Fabrice Neuman Une émission présentée par Guillaume Vendé

Earl Gosick, CTO at ESTI Consulting Services Earl Gosick has been attending Dell’s annual event since the EMC World days, and the ESTI Consulting Services co-founder brought to this year’s Dell Technologies World a perspective grounded in 35 years of building deep technical expertise on the Prairies. ESTI, the Saskatoon-based solution provider that won Dell’s Data Centre Solutions Excellence Award for Canada last year, runs a pure-play Dell infrastructure practice with particular depth in storage and data center design. Earl also sits in Dell’s CTO Connect program – a small, invitation-only group of partner technologists with early visibility into Dell’s product roadmap and a real voice in shaping it. His framing for the week: AI is fundamentally a data story, and data stories are storage stories. The push toward on-premises AI infrastructure – from deskside devices up through the newly announced Exascale and Rackscale solutions – is being driven as much by data governance requirements and token economics as by raw performance. Organizations that don’t control their data, Earl argues, can’t truly control their AI outcomes. On cyber resilience, he made a point worth underlining for anyone running managed services: ransomware insurance changes the recovery equation in ways clients don’t always anticipate. When a claim is filed, infrastructure gets frozen for forensic analysis. Recovery speed from a clean, air-gapped golden image – built with technology partners like Index Engines – isn’t a nice-to-have. It’s the whole game. And to close: Saskatchewan and Alberta may be poised to become Canada’s next significant data center hubs. With regulated power, guaranteed energy supply, and a provincial government that has now seen a CoreWeave-scale facility successfully built in the province and is actively pursuing more, Earl sees a real and growing opportunity – and ESTI is already working to support it. Read Full Transcript Robert Dutt: Hello and welcome to In the Channel from ChannelBuzz.ca, bringing news and information to the Canadian IT channel for the last 16 years. I’m Robert Dutt, editor at ChannelBuzz.ca, and your host for the show. We’re continuing our series of conversations from Dell Technologies World in Las Vegas. This week, we’re shifting from the Dell executive perspective to the partner perspective, and today’s guest has been making the trip to this event since the EMC World days. Earl Gosick is co-founder and senior consultant at ESTI Consulting Services, a Saskatoon-based solution provider that just celebrated 35 years in business and took home Dell’s Data Centre Solutions Excellence Award for Canada last year. Earl also sits inside Dell’s CTO Connect program, a small, invitation-only group of partner technologists who get an early look at where Dell’s roadmap is actually heading – and, importantly, a real opportunity to push back on it. Earl’s a storage specialist at his core, and that turned out to be a useful lens at a conference that was fundamentally about AI infrastructure. Because if you pull on that AI thread long enough, it leads you back to data, and data always leads you back to storage. We talked about what the Exascale and Rackscale announcements mean for real customer deployments, why the cyber resilience conversation is as much about recovery speed as backup integrity, and a genuinely interesting thread about why Saskatchewan and the broader Canadian Prairies may be sitting on one of the most underappreciated data centre opportunities in North America right now. Let’s get right into it. My chat with Earl Gosick. Earl, thanks for taking the time. I appreciate it. Earl Gosick: I appreciate you having me here. It’s always nice to talk about what we’re doing with Dell. Robert Dutt: No doubt, and you guys are doing a lot. I understand this is by no means your first DTW rodeo. Earl Gosick: No, I’ve been coming since the EMC World days, and I’ve never – I missed a year through COVID, that was about it. Robert Dutt: Well, I guess we’ll allow you that. So you’ve got this background here, you do the CTO Connect with Dell. What’s different about this year, if anything? What’s the tone or the energy that tells you something about where the industry is at right now, and not necessarily just where Dell would like it to be going? Earl Gosick: I think the driving factor of today is really the supply constraints. You can see what AI is doing and the effect that’s having across the board on every product that has memory or CPU or flash drives in it – which is everything in technology. So that’s really setting the tone. But it also shows how effective AI is as a market driver, and what people think is going to come out of that technology – which is, I think, very important for people to understand. It’s ubiquitous technology that’s going to drive a lot of change in our industry. And we’re seeing a leading edge of that. And if this is the leading edge, there’s some pretty exciting things coming, I suspect, and it’s going to do some pretty important and probably quite wonderful things for our clients. Robert Dutt: We heard from the main stage the idea of encouraging customers to get their hand up early – to get those orders, or even an inkling of where things are going for orders, in as early as possible – and that that will, in effect, Jeff Clarke was suggesting, get folks the best possible results. What’s the guidance you guys are providing your customers around that whole issue, and thinking about availability and pricing of hardware in this current super-fun environment? Earl Gosick: Our position does align with what we’re hearing from Dell when we’re dealing with Dell Technologies, so we try and pass on the messages as transparently as we can, understanding there are supply constraints coming. And we have to deal with those in the only way we have, and that is to figure out what we need. Let’s plan early. Let’s plan the budgets we have for the year, and we can make some estimates about what’s going to be happening six months from now – but they’re estimates, and they’re going to be higher. So it’s probably going to be cheaper for you to have technology that’s sitting on the floor unused for a few months and waste through some support potentially, as opposed to delaying the purchase for three months. So if we know what we’re going to buy, we should operate in a manner that allows us to order those technologies as soon as possible and make sure you’re not waiting for something that delays your business initiatives. Robert Dutt: You guys won the Data Centre Solutions Excellence Award last year for Canada. Take your victory lap. Tell me – what is it you guys are doing in the data centre space that earned that, and what does winning the award tell you about where your practice is focused? Earl Gosick: I hope it helps demonstrate our success. So what ESTI likes to do as a business – our business model is really to build highly competent experts all the way from solution architecture to implementation of those technologies at the customer site. That takes a lot of effort on our behalf, and so it’s nice to get a reward that says we’re doing the right things. Because if you can build a strong rapport with a client who trusts your experts in their field, that creates long-term relationships – which is what both ESTI and Dell are after, and what our clients want. Robert Dutt: You’re a storage specialist at a conference that has been at its core all about AI infrastructure. But at the same time, you go back to when it was – you said – EMC World, all about storage. The more I heard this week, the more it feels like the AI story is really a data story, and data stories are storage stories to at least some degree. How are you seeing that translate in terms of what your customers are actually asking about, or what they’re going to be asking you about? Earl Gosick: It’s significant. You’re right. In order for any type of artificial intelligence to derive a useful data product out the end, it’s built on the data that you have. So customers are coming to the realization that they have to store everything. So it is driving a lot of demand for storage. It’s driving storage in different ways and they just keep everything. Then there’s another product that comes after that, which is cleaning that data – building the data pipelines. When I talk about storage, it’s really about data, and AI is a data-driven product. So it’s doing great things for the storage industry. But the clients understand that they do have to have the data – it has to be there, it has to be available. And then when they build these data products, they have to protect those data products. They’ve got to make sure they’re secure. So it’s driving a lot of initiatives on both sides of the fence that are good for all of us. Robert Dutt: Especially with new or newer customers, or customers who are looking to expand what they’re doing with AI – and acknowledging there’s going to be a range from folks who have had the religion since day one and folks who’ve just been randomly shoving stuff digitally wherever they can. Where do you find those newer customers are at, generally speaking, in terms of sophistication of data management and data governance and all that kind of fun? Earl Gosick: Unfortunately, I’d like to say there’s a median in there. There is not. Everybody is at a different stage in that cycle for them. So you really have to be a little bit cognizant and ask the questions to find out where they’re at before you can really sort of hold their hands and walk them down the road. Many people who started that journey early – you can learn from them. And so they’re going to tell us to start and do something, and you may fail, there may be some things, but you’re going to learn something from that. The second time will be more successful. Then you take that information, you pass it on to the newer people who are trying to get quick value from those investments they’re making on the AI front. So it could be things about how to connect those various data sources because they’re spread everywhere, to how do they build, or select which ones they put their money and their efforts behind. And so you take from the ones that have been doing this for a while, you pass that information on to the ones that are starting on this journey, and you connect the dots. You provide value and make pain go away wherever you can. And customers appreciate that. Robert Dutt: And that sounds like that’s where you’re kind of bridging that gap that exists and trying to bring customers to the level they need to be at to get something out of this. Earl Gosick: Absolutely. Like I said, everybody’s on a journey at a different stage of that journey. And so you have to communicate well to understand where they’re at and what they’re trying to achieve. Once you know that – we don’t always have the answers, but we leverage great partners like Dell who do have somebody that knows the answer. And so building this sort of ecosystem of potential partners to bridge that gap is great. And Dell does that not just from us and the partner community, but their partner community as well, to support all the component pieces that go together to build these pretty highly complex solutions in some cases. Robert Dutt: Of all the announcements, all the stuff that we heard on the main stage and elsewhere this week, what kind of caught your attention – your major aha moment – the thing that’s going to be interesting going back to your business or going back to your customers with new opportunities or the ability to do something better, faster, more? Earl Gosick: So as we talked about, I am a storage guy. So I look at something like Exascale. They’ve been talking about this for a couple of years now in the CTO cycles that I’ve been to. To see that product sort of come to fruition, where you have something and you can just put a personality on that module and build something out – I think that could be very game-changing, especially for AI. They might want to do a lot of things with file storage today, object storage tomorrow. Being able to build up a cluster and put a personality on it that meets the needs of the day – I think that could be quite interesting. That Rackscale solution you saw on the stage with Michael Dell and Jensen the other day – for the larger clients, something like that could be quite interesting. I mean, we’re building these large data centers right now and trying to fill them. Rackscale infrastructure that helps with power and energy and doing a lot of powerful things is going to probably be a game changer for a lot of people. Robert Dutt: One of the things that struck me here is what I want to call the AI agnosticism, as long as you’re doing it on Dell infrastructure – that Dell is talking about here, ranging from, if you’ve got really basic needs, run it locally on your AI PC, moving up a bit there’s the GB10, which is more of a deskside machine, up to the big old box that Jensen signed on stage. How does that map with what you see in terms of customer needs for AI, and what do you think of that kind of approach to structuring both the data center and broader AI processing across the enterprise? Earl Gosick: I think as we touched on earlier, everybody’s on a different stage in that journey. So if you’ve got a guy that’s working at his desk and he’s trying to do some cool things, but he doesn’t have access to a million tokens – that little GB10 you put on the desk beside him and he’s going to do some development, he’s going to learn some wonderful things. Then as you move up the stack in your journey, you’ve got some big clients who are going to do small proof-of-concept type scenarios where they might want a smaller box and then move up that stack. I think it’s important to have a product that covers a diverse range of those people because nobody’s in that one sweet spot – they’re all over the map. Having that full technology set supports wherever they happen to be in their life cycle. Robert Dutt: You touch on tokens, and Jeff Clarke’s presentation was really deep into tokenomics and the kind of the trap there. I’m curious how that maps with what you’ve seen in customers as they’ve started to explore AI. Are they seeing these same challenges, and how are they thinking about it? Earl Gosick: Tokens are the buzzword of the day, but they’re out there for a reason. Everybody has finite resources to put towards the solution they’re trying to build. They may or may not know what that solution is – they’re working towards something, they need tokens to achieve that. What I find interesting is the people who are very early into the game of AI and building solutions around that – it doesn’t take them long before they’re like, “I’m out of tokens. I need to do some stuff.” So it just comes back to the fact that there are only so many resources to solve the needs you have, and you only have so many tokens, and you’ve got to learn to live within what you can get your hands on. And that’s driving the economy, whether it’s at a data center level or at an internal level for any business. Robert Dutt: And does that in turn drive – which I believe is Dell’s thesis here – does that in turn drive the interest in building out infrastructure in-house, so that the relative incremental cost of those additional tokens goes way down because it’s bought and built versus rented? Earl Gosick: Yeah. I think there’s a step along that AI journey where people have potentially outgrown what they can do in the cloud in an economic fashion. We see the supply constraints are driven by CPU and memory usage. If you look at what the cloud hyperscalers offer, when you get into highly intensive memory and CPU, it starts to get very expensive. A lot of storage, a lot of bits and bytes moving back and forth – very expensive. All those things are prevalent in AI. You’re moving a lot of data back and forth, you’re touching a lot of things, you need a lot of memory at times. So once you get to a point where you’re doing useful things with your AI and building generative models, no matter what you do with inferencing, it starts to get really expensive. Then it becomes a time where you can move those things into a data center you control. You can get some economics from it and you can get some sovereignty out of it. A hyperscaler outside of your control can turn things off – they can’t do that when it’s your data center. So you’ve got a lot of control as well as the economics behind how you’re achieving the outcomes you’re looking to achieve. Robert Dutt: I used a word which is actually where I wanted to go next, which is sovereignty. When we’re talking about data center infrastructure and moving bits around and enterprise storage, how is data sovereignty trending among your customers, especially folks who have regulatory concerns and that sort of thing? Earl Gosick: Being a Canadian company, predominantly, we have a larger focus on sovereignty and data sovereignty and sovereign solutions than maybe you’ll see south of the border here. And we find our friends in the European Union are a little bit different – they’re ahead of us even. But it’s a really big concern, especially when you have any type of government agency that you’re dealing with, or anybody that really has intellectual property that they’re looking to protect. They’ve learned that open AI models may expose things – even if it’s just from how they’re creating their algorithms. But if the data gets out there, it’s a concern. They’re protecting their assets as well. These AIs are delivering very useful outcomes for them. They need to make sure they own those outcomes and that they can actually reach them when they need them. So part of data sovereignty is not just the sovereign part of your data, but it’s the actual access to your data. We’re learning things from not just the AI piece but from ransomware – all of a sudden your data goes away. The same thing could happen with a hyperscaler for some people. Sovereign IT solutions are going to be, I think, increasingly important moving forward. Robert Dutt: On that note, you mentioned ransomware, and data resilience and protection is another area I wanted to touch on. We heard the figure that 97% of cyber attacks are now specifically targeting backup infrastructure – because of the old line about, I forget the particular bank robber’s name, but why do you rob the banks? Because that’s where the money is. Why do you go after the backup? Because that’s where all the data is. Does that match with what you’re seeing, and if so, how does that change how you’re designing and recommending data protection for your customers? Earl Gosick: It is absolutely changing people’s realization of how they need to protect their data. This one doesn’t matter if it’s AI or your regular business practices – your data has value, whether it’s to support applications that are running your critical business or you’re building AI products that you need to protect. That has value and you need to access it. What we’re seeing more and more – and we’ve built a really strong practice around this – is building things like cyber vaults and using Dell’s technology partners like Index Engines, where they come in and they can quickly identify threats inside your environment and act on those. Because these guys loiter around for potentially months at a time. They know how to get to your backups. They know they’re not getting paid if you can recover. So they’re going to do everything they can to try and disrupt that. They have AI engines just like ours, but they have a lot of money and they don’t have the constraints about how they use their AI. I mean, these people are criminals, so they act in a method that makes them money. We’re going to be facing even more potential threats in the future, and some of those are going to be AI-driven. We’re going to have to react at AI speeds. There are changes coming, but certainly people are learning to build protection mechanisms that are air-gapped and can respond very quickly to threats. Robert Dutt: When you’re sitting in front of a client who thinks they’re covered – they’ve got a backup solution, they’ve got someone who’s responsible for it – what are the most common gaps that you find between what they think they have and what they actually have? Earl Gosick: I think for many clients, they don’t really understand how disruptive it’s going to be if they run into a ransomware attack. If you’re a client that may have ransomware insurance, for example, and they get hit – you have to tell them, “Do you understand you’re not going to be able to touch any of that infrastructure? Because your insurance company is going to want to do some analysis on that to see how the threat came in.” That infrastructure is dead and gone. You’re starting from scratch. You need a golden image – you need something you know nobody has touched. Protecting the data is only the first piece. Rebuilding from that data, and how fast you can do that – that’s the very critical component. That’s where an air-gapped cyber recovery solution like Dell Cyber Recovery is critical, because you can understand what data to recover and you can recover quickly. Having the data there – that’s the great first step and that’s where you should start. But following that, that is only the first step. Robert Dutt: Your client base is different from a lot of partners I talk to. Given where you sit and who you’re focused on – not necessarily organizations that are under the same kind of pressure or have the same kind of resources to pursue AI – how do you translate and filter what you hear at a conference like this, where a lot is focused towards big enterprise, to a message that makes sense for your customers and scales to their needs and appetites? Earl Gosick: That’s one I think isn’t really that difficult – it’s not as difficult as you would think. Because everybody has the same problems. They run into the same problems. How they build solutions to those problems might change on the scale, but you just have to understand and recognize that everybody’s having the same problems. You can articulate and communicate to them that you’re not the only one that has this. We can resolve this problem at a large scale, but we don’t have to. You came back to it earlier when we talked about the product sets, from small to large – you just pick the right one to meet the solution that these guys have. How you solve that problem of the day doesn’t necessarily change for a really, really large client versus a very, very small client. It’s really just the scale of the end solution and the architecture that’s put together to solve the need. Robert Dutt: From a Titanium partner’s seat, what did the program changes that we saw rolled out – the agentification of the program, some of the incentive shifts – tell you about where Dell sees growth opportunity, and how does it align with where you’re already going or where it might take you? Earl Gosick: I think you can see very easily that Dell is putting a large focus around AI and what it can do for them to streamline their business and be successful. We, like any other company we deal with, are doing the same thing. What they’re doing with their Dell One program, and having a single operation from lead generation down to quoting and pricing and follow-up – it matches what we’re doing on the back end and trying to automate that. Because as long as we can automate that process and reduce the friction in those programs and dealing with Dell, we can spend that time focusing on our clients’ needs. You see Dell, I think, leveraging the same technologies to do that. And if we’re smart business people today, we’re looking to the people around us who are being successful and trying to do what they’re doing in a sense. That’s true for us and our clients. Leveraging AI and seeing how that’s being successful for our partners is driving what we’re all doing – to drive automation and simplification through the processes that are just painful every day that we have to do better at, to support our clients. Robert Dutt: I’m guessing you guys are pretty far down this road already because you’re pretty much a pure-play Dell on the infrastructure side, as far as I understand. But when a company like Dell rolls out these incentives focused on expanding customer footprints – getting a Dell storage customer into Dell PCs or any of the other solution lines – just curious if that moves the needle for you in terms of the incentive, or is it already baked into what you’re doing? Earl Gosick: It’s baked into what we’re doing. In the end of the day, you are trying to build a rapport with a customer based on being a trusted expert. You’re not going to flip your technologies around based on what’s going to get somebody a little bit more money. You’ve got to do the right thing for the customer today and every time you deal with them. The advantage of dealing with Dell is they typically tie their incentives to the product that they are investing in today – that they see the future growing into. So they usually coincide. They understand the pain points of the year, and the incentives usually match the requirements of the day as well. So they’re really good at that. And then they usually have a lot of tools to support that initiative of IT transformation, whatever it is for that time and place in our industry. Robert Dutt: You mentioned earlier you’re on the CTO Connect program – pretty small room, an exclusive group. Tell me about what that relationship looks like on the inside of the room, and the value that an organization like ESTI gets from sitting in there. Earl Gosick: I guess I’ll put it this way. We deal with some technology providers – predominantly Dell. Dell puts us in a room, they tell us what they’re doing for the next year or two, and they ask us if they’re on the right track. That’s telling to me – they care and they listen. They talk about the technologies that we’re going to see upcoming, so it’s helpful for us to talk to our clients about where the industry is headed. But they do sometimes say, “We’re going to do this,” and the room says, “Oh, no, you can’t do that. Our customers love this,” or, “We like this for this reason.” And they say, “Oh, okay.” And we have a dialogue about those things. So I think that’s one of the most important things that comes out of CTO Connect – we hear about industry trends, but they also ask us our opinion on whether they’re on the right track, and then they listen to that opinion. I think that’s telling for any company you deal with – one that engages not only with their clients, but with their technology partners. It’s one of the things I really like about CTO Connect. Robert Dutt: You guys just turned 35 or so, as I understand, as an organization. That’s a long time to be running a consultancy in any market – and markets move, vendors come and go. What’s the philosophy behind building something that durable in a market that changes so fast, and especially in an area of the country that doesn’t necessarily get as much headline attention from vendors as a Toronto or a Vancouver or a Montreal? Earl Gosick: I think it comes back to what I stated earlier around building strong and capable expertise across the board – and that’s building relationships with the clients, building relationships with partners like Dell to solve the solutions of the day. Our clients respect that because they know they can come back to us again and again and we’ll do the right thing together. So that’s really the crux of it. Our business model is a little different in that we support a little bit more of an entrepreneurial aspect to our business. When young, capable people come on board and they build differentiating products, they get a seat at the table – and that’s critical for ESTI and the way we operate. But it’s really about looking at modern technology solutions and being agile to support those ever-changing technologies. It makes our industry exciting. You’re never doing the same thing every day. And as long as you can recognize the fact that you won’t be doing the same thing tomorrow and you just have to find a way to deal with it – that’s how we thrive in our company, and in working with Dell as well. Robert Dutt: All right, so let’s close with asking you to do a little bit of the impossible, given that pace of change. What’s one thing that you’re thinking about today, but maybe not totally all-in on at this point, that you think is going to be shaping the business for ESTI and your customers when we’re sitting here at DTW 2027? Earl Gosick: Well, that’s a really hard question. On the investment side, we do look at some of the technologies today – and as we talked about, AI is big for us. We need to build services that our clients don’t have. So we spend a lot of focus on where they have skills and where they don’t. We’re going to build a lot of expertise around cleaning data, building data pipelines and that kind of stuff, to focus on the needs our clients are asking us to help them solve. So that’s kind of an easy one because everybody sees that going forward. Beyond that – we’re making a strong effort in Saskatchewan and Alberta to build a sort of data center economy to support a lot of these data centers that need to be built. We already have access to power infrastructure to support those things. That’s going to drive a little bit of a change in our operating model just to support our local governments as they try and take advantage of the differentiators we have. That’ll drive some change for ESTI. And then as we expand across the rest of Canada, different geographies have different requirements as well. So lots of change, lots of new people coming on board all the time – interesting but dynamic. Robert Dutt: That will be an interesting thread to pull on. I remember going to an event – God, it must have been 15 years ago now – talking about how Canada really should be a data center powerhouse. When you consider we have power, clean power in relative abundance, we have cold, which turns out to be important – it sounds like maybe there’s an opportunity to realize some of that with what you guys are doing and what governments are starting to look at more seriously. Earl Gosick: They are. Also, right outside my hometown, they just announced a very large data center which is going to house some infrastructure from CoreWeave – and we’re going to see more of that, I think, because that process went very well. I sat in on a conference a couple of weeks ago where it was government and industry getting together to talk about why they were successful, what they bring to the table. Saskatchewan is unique because they have regulated power, energy, and land. They can guarantee, “We will give you power, we can guarantee you’ll get LNG.” Those types of things are very important for anybody trying to build a data center – it’s the critical piece. And with the government having control over all of those, they can guarantee them. That’s where I think Saskatchewan is going to have a real differentiator to support that technology, and the government is well aware of that fact now. They’re going to want to do more of these things. And then our neighbors in both Alberta and Manitoba are sort of on board as well. Certainly Alberta has done a few key data centers to support AI and those are going to continue to happen. We’re sometimes slow to move because it’s government. But once they realize the differentiators they have and what it can do for the market, I think there’ll be some traction there. Robert Dutt: Should be interesting times, and sitting where you’re sitting sounds like a big opportunity. Earl Gosick: Absolutely. I think it’s a big opportunity for all of us – supporting your community around you as well as building a thriving business. Robert Dutt: Earl, I appreciate you taking the time once again. I hope this has been a good DTW for you. Earl Gosick: It’s been a great discussion and a good DTW, so thanks a lot for having me. Robert Dutt: There you have it – Earl Gosick from ESTI Consulting Services. I’d like to thank Earl for his time last week in Las Vegas. Thirty-five years building deep technical expertise from Saskatoon, in a vendor relationship game that tends to reward proximity to the bigger centres – that’s not an accident, and it came through in the conversation. A few things I’ll take away from this one. First, the AI-is-a-storage-story framing. Every AI product ultimately requires data to be collected, governed, moved, and protected. That’s not news to Earl, but it’s a useful reframe for anyone still trying to connect their existing practice to the AI conversation. The hardware gets the headlines. The data work actually gets the contracts. Second, on cyber resilience – the ransomware insurance point Earl raised is worth sitting with. The moment a client files a claim, that infrastructure gets frozen while the insurance company figures out how the breach happened. Your ability to recover doesn’t just depend on whether the backup is intact – it depends on whether you built a clean, air-gapped golden image that nobody has touched. That’s the conversation. And if you’re not having it with your clients, maybe someone else is. And third, keep an eye on Saskatchewan. Regulated power, guaranteed energy supply, and a provincial government that has now seen a CoreWeave-scale data center get successfully built in the province and wants more of them. Earl thinks that’s just the start of something, and I’m inclined to agree. If you’re enjoying the show, please follow or subscribe wherever you listen. We’re on Apple Podcasts, Spotify, YouTube, and most of the usual podcast directories. And if you have a moment to leave a rating or a review, that really does help folks in the channel find the show. Until next time, I’m Robert Dutt for ChannelBuzz.ca, and I’ll see you in the channel.

Les annonces phare sur les OSFinies les séquences par OS, on optimise partout et on nettoie les vitres. Les apps se chargent plus vite, la recherche enfin pertinente et à une vitesse décente, recherche des plus beaux sourires de vos photos et vidéos, planificateur de processeur (CPU) optimisé (y compris anciens iPhone), gestion du JavaScript accélérée, switch wifi / connexion cellulaireContrôle parental : refonte complèteOn est en 2026 : IA, agents et vibe codingSiri AI, app dédiée, des promesses mais pas partout (la bêta et l'Apple Watch est notre amie)L'édition de photos se met à niveau (vraiment), la génération d'images aussiVibe coding de raccourcis ou l'aveu de l'échec du nocodeChangement des mots de passe par agent IA5 nouveaux Apple Foundation Models, : plus complexe et complet qu'il n'y paraîtCe qui sera disponible ou pasAutres remarques et nouveautés Entre politique et annonces ringardesDes annonces sans les citer : un Mac tactile (dessin dans Notes, pull down to refresh, affichage des bordures des fenêtres pour l'accessibilité), l'iPhone pliant, un MacBook Neo avec 12 Go de RAMCompatibilité des OS : M pour le Mac, comme iOS 26 pour l'iPhone et c'est plus critique sur l'Apple Watch (SE 3, 9, ou Ultra 2 minimum), et quelques iPad abandonnés (il faut au moins un processeur A13 ou plus exactement un A12Z (iPad Pro de 2020)Quelques évolutions dans Notes (format markdown, liens entre les sections)Albums vraiment partagés avec autres OSRâle d'agonie ? Des annonces visionOS (fenêtres courbées, centre de contrôle revus, panoramas d'après vos photos, Siri au regard)En réserveAdieu Hidden Bar, les services de création de cartesDivorce acté entre les chargeurs et leurs câbles soudés USB-C en EuropeBaisse de prix de l'abonnement Google Gemini AI PlusLes prix des forfaits en France vont-ils augmenter ?La voiture électrique sauve des vies (enfin évite des morts)La conclusion du Joy-Con Drift en FranceNos lienshttps://techcafe.fr/https://fabriceneuman.fr/https://profduweb.com

Your iPhone might be running hot and draining fast — and it’s not just you. Dave and Pilot Pete break down the battery chaos introduced by iOS 26.5, which brought overheating, accelerated drain, and even blocked wired charging on iPhone 17 and Air models. The fix that’s working for most people: disable iCloud Keychain first, run Reset All Settings, then carefully re-enable iCloud sync — otherwise you’ll nuke your Wi-Fi passwords across every device. iOS 26.5.1 is out and should help, but until you’ve updated, your electrons deserve better. You’ll also learn why Apple ID passkeys are locked to Apple’s own keychain with no known path to third-party managers like 1Password or Keeper, and why editing a contact on a modern Mac can somehow peg every CPU core — in 2026, no less. From there, Dave and Pete tackle the full listener mailbag: how to rescue missing contact names from Messages, the right way to boot a MacBook with a broken display into clamshell mode so it actually uses the external monitor, and a deep dive on 5K vs. 4K displays where Dave argues your eyes may not care as much as the pixel-per-inch math suggests. You’ll get smart ideas for repurposing a 2015 iPad Pro that can’t run modern apps — including Dave’s Claude Code-built weather dashboard running off a headless iMac as a web interface. A crashing 2021 MacBook Pro turns out to have been felled by a single bad SD card, and the lesson is golden: feed your crash reports to an LLM and let it do the digging. And Don’t Get Caught with outdated OpenAI macOS apps — update ChatGPT, Codex, Atlas, and Codex CLI before June 12th to stay ahead of a code-signing rotation triggered by a compromised open-source library. 00:00:00 Mac Geek Gab 1145 for Monday, June 8th, 2026 June 8th: National Best Friends Day MGG Monthly Giveaway – Win a license to SaneBox Quick Tips 00:00:01 Dan-QT-Multi-select on iPhone with a quick drag 00:04:31 Tim-QT-Have iOS 26.5 Battery Drain? Reset All Settings, but be careful! 00:13:32 Kent-QT-1144-Collapse stacks by clicking the down-facing carat in the menu 00:14:15 Mark-QT-Match Frame Rate on your Apple TV for smoother experiences 00:17:58 What are the differences between refresh rates and frame rates and…why? 00:21:09 KiwiGraham-QT-Apple Account Passkeys vs. Third Party Password Apps Sponsors 00:23:09 SPONSOR: Keeper. Right now, Keeper is offering our listeners 60% off personal and family plans at https://Keepersecurity.com/MGG. This offer is only for podcast listeners! 00:24:50 SPONSOR: Helix Sleep makes premium mattresses and bedding that are customized to fit your personal needs, and conveniently shipped to your door. Go to https://helixsleep.com/MGG for 20% Off Sitewide. 00:26:23 SPONSOR: NordLayer Browser. The business browser built for how modern work actually happens — giving IT the visibility and control to secure SaaS, stop phishing, and prevent data leaks right at the source. Your Questions Answered and Tips Shared! 00:28:09 VaShaun-How can I restore lost Contacts on my Mac? 00:37:36 Si-What to do with an 11-year-old iPad? Claude Code 00:46:40 Michael-Why do we have to pull-to-refresh for updates? 00:50:04 Blake-1144-Damaged displays, external monitors, and MonitorControl 00:55:48 Joe & Michael-CSF-1144–RetinaDesk.com for reviews of 5K and 6K monitors BenQ MA270UP 27” 4K Display Reviews 01:02:50 Hog fan and Cowboy fan-MGG Review–Favorite Tech podcast Don't Get Caught 01:04:14 Father John-DGC-Investigate those crash reports before you replace your Mac 01:09:26 Update your ChatGPT Apps ChatGPT Desktop Codex App Codex CLI Atlas 01:11:06 Andy-DGC-When Troubleshooting, Don’t Get Caught asking the wrong questions or assuming the wrong facts 01:19:36 MGG 1145 Outtro MGG Monthly Giveaway Bandwidth Provided by CacheFly Pilot Pete's Aviation Podcast: So There I Was (for Aviation Enthusiasts) The Debut Film Podcast – Adam's new podcast! Dave's Business Brain (for Entrepreneurs) and Gig Gab (for Working Musicians) Podcasts MGG Merch is Available! Mac Geek Gab iOS app Mac Geek Gab YouTube Page Mac Geek Gab Live Calendar This Week's MGG Premium Contributors MGG Apple Podcasts Reviews feedback@macgeekgab.com 224-888-GEEK Active MGG Sponsors and Coupon Codes List BackBeat Media Podcast Network

Computex happened this week, and there was enough to talk about to devote this week's episode to rounding up the high points, including Nvidia's attempt to dominate the consumer Windows market with RTX Spark, the first RGB mini-LED monitors, 8GB laptops becoming common again, PC hardware production shifting back to DDR4 and old CPU sockets, Intel's entry into the handheld gaming market, the (unsurprising) absence of any news about Zen 6 and Nova Lake, and other stuff! Show notes and links: https://tinyurl.com/techpod-342-computex-26 Support the Pod! Contribute to the Tech Pod Patreon and get access to our booming Discord, a monthly bonus episode, your name in the credits, and other great benefits! You can support the show at: https://patreon.com/techpod

Show 314: The meeting focused on discussing the proper placement of D-Feedback in audio mixing chains, with participants sharing their different approaches and experiences. Bruce, John, and Gregory debated whether to place D-Feedback as the first or last plugin in the chain, with Bruce using it last to clean up audio before applying it, while John and Gregory preferred it first to avoid overworking the AI. The conversation also covered various technical topics including CPU requirements, noise reduction versus feedback elimination, and specific use cases in different venues like stadiums and corporate events. Additionally, the group shared personal stories about past audio engineering experiences, including equipment failures, famous acts they've worked with, and the evolution of audio technology over the years.Stop guessing and start growing. Join Jan Landy and his knowledgeable, affable panel of friends and colleagues for a no-filter discussion on mastering the professional life—with more laughs than a comedy club.Our ZoomCast isn't just a fountain of industry knowledge; it's also an opportunity to laugh. Think of it as therapy, but with more jokes and fewer couches. Stay updated on life and world events, share your thoughts, and enjoy multiple good chuckles along the way. -JOIN US LIVE EVERY WEDNESDAY:- 4:45 PM Pacific (UTC-7) / 7:45 PM EasternHow to Assist:Offer your support by giving us a Like, opinions in the comments on Facebook, LinkedIn, and YouTube and remember to share the show with your industry friends.Creators & Guests Jan Landy - Host D-Feedback, audio signal chain, audio mixing, feedback suppression, live sound engineering, CPU load, noise reduction, gain staging, D-Feedback placement, live sound tips, audio engineering, monitor mixing, foldback setups, professional audio processing

The ASX 200 finished the week on a sour note as the index fell 61 points to 8621 (-0.7%), ending the week down 1.2%. Banks were ugly today after Morgan Stanley downgraded the sector outlook. The Big Bank Basket fell to $266.42 (1.5%), with CBA off 1.7% and WBC sliding 1.2%. Other financials held up better, with MQG unchanged, ASX up 1.5% and ZIP rising 1.7%. Insurers also found some friends again. REITs were better too, with CHC up 1.1% and SGP rising 1.1%. Industrials pushed higher, with WES up 0.4%, while WOW and COL also performed well. Retailers were mixed, with JBH up 1.0% and APE drifting lower. Healthcare stocks were back from the ICU. CSL had its biggest one-day rise since 2022, up 5.8% as the rotation into the sector gathered pace. Even RMD enjoyed a very positive session, gaining 4.3%. PME rose 4.0% and COH added 5.6%.In the tech space, MP1 soared 15.2% after its capital raising, with Citi upgrading its price target by 41%. The All-Tech Index rose 0.7%, with CPU also trading higher.Resources, however, remained in a world of pain as profit-taking continued in BHP and RIO, with FMG down 2.3%. Rare earths and critical minerals stocks also unwound as the AI trade ran out of steam and copper prices fell. LYC dropped 2.9%, MIN fell 5.1% and SFR lost 1.2%. Gold miners drifted lower once again, with NST down 2.5% and NEM off 1.2%. Energy stocks were weaker, with WDS falling 1.3% and STO down 0.6%, while coal stocks slipped and uranium stocks found some nervous support.In corporate news, NHF rose 2.5% on the sale of an insurance business. RSG fell hard following its production report, while AGI rallied 16.8% after two directors resigned.Asian markets mixed. Japan down 1.0%, Hong Kong down 1.0%, and China down 0.7%. South Korea eases back around 1.6%US futures: Dow up 8 and Nasdaq down 280. Oil unchanged. NFP tonight.Marcus Today – Daily Market Insights Marcus Today provides clear, practical commentary for self-directed investors – covering markets, portfolios, education, and decision-making without the noise. If you'd like to go further: Start a free 14-day trial of Marcus Today http://bit.ly/mt-trial-podcast Join Marcus Today Use code MTPODCAST for 10% off http://bit.ly/mt-join-podcast-offer MT20 – Managed ETF Portfolio A professionally managed portfolio run by Marcus Padley and the team, using ASX-listed ETFs with active market timing. http://bit.ly/mt20-podcast Principles – How We Think About Investing A short video series on timing, behaviour, and decision-making. No stock tips. http://bit.ly/mt-principles-podcast — Disclaimer This podcast is general information only and does not consider your personal circumstances. It is not personal financial advice. 

Het is opnieuw een week van de goednieuws-shows bij Big Tech. Onlangs nog Google, volgende week Apple, maar deze week betraden zowel Nvidia als Microsoft het podium. Nvidia-baas Jensen Huang deed dat op GTC Taiwan bij de aftrap van techbeurs Computex. Hij nam zijn ouders mee, praatte over koetjes en kalfjes én kwam met groot nieuws: een gloednieuwe chip. Niet voor datacenters, maar voor in pc's: de RTX Spark, met een combinatie van een CPU én een GPU. Verder praten we met Maurice Schmitz over het enthousiasmeren van de jeugd van tegenwoordig. Want werken in de techsector zien veel jongeren op het event 'Night of the Nerds' misschien wel zitten. Als mede-organisator vertelt hij hoe Eindhoven en Nijmegen hierin het voortouw nemen. Ben van der Burg en Joe van Burik bespreken het allemaal in deze editie van De Grote Tech Show. Vragen, opmerkingen of suggesties? Mail ons! Op: degrotetechshow@bnr.nl De Grote Tech ShowTech verandert onze wereld, in De Grote Tech Show (DGTS) hoor je hoe. Joe van Burik en Ben van der Burg spreken met innovatieleiders en analyseren de techwereld, van AI tot cybersecurity en social media tot quantumcomputers. TechpodcastDe Grote Tech Show (DGTS) is dé techpodcast (en radioshow) voor iedereen die technologie en innovatie echt wil begrijpen. Over AI (of: kunstmatige intelligentie), chips, cloud, cyberveiligheid, social media, quantum en entertainment. Hier hoor je hoe technologie de wereld verandert en wat dat betekent voor bedrijven, investeerders en iedereen in de samenleving. Bij DGTS krijg je de analyses, inzichten en interviews die ertoe doen. Met diepgaande gesprekken en scherpe analyses brengen we de belangrijkste technologische ontwikkelingen in kaart. InnovatiesElke week spreken we kopstukken in de techwereld: ceo's, hoogleraren, ondernemers en investeerders die werken aan de innovaties van morgen. Wat betekenen de nieuwste AI-modellen voor werk en creativiteit? Hoe blijven Europese startups concurreren met het nog altijd machtige Silicon Valley en het ondoorzichtige China? Dit zijn geen oppervlakkige interviews, maar diepgaande gesprekken waarin we de hoofdrolspelers spreken die écht impact maken. De technologische revolutie is in volle gang en beïnvloedt elk aspect van ons leven—van de manier waarop we werken en communiceren tot de geopolitieke machtsverhoudingen. Daarom brengen we niet alleen de technologische kant in beeld, maar ook de economische en maatschappelijke implicaties ervan. Naast de grote innovaties kijken we naar de bedrijven die deze ontwikkelingen vormgeven. Wat is de strategie van big tech-bedrijven zoals Google, Apple, Microsoft en Meta? Hoe verandert de concurrentiestrijd tussen Nvidia, AMD en Intel de chipmarkt? Wat betekenen nieuwe wetten en regels in Europa en de VS voor de toekomst van technologie? AnalysesDaarnaast hoor je bij De Grote Tech Show, exclusief als extra podcast elke week, hoe Joe van Burik en Ben van der Burg de week in tech doornemen. Ze analyseren het laatste nieuws, plaatsen de ontwikkelingen in perspectief en geven scherpe inzichten over wat er écht speelt. Van de doorbraken in AI / kunstmatige intelligentie en de opkomst van nieuwe sociale mediaplatformen tot de impact van geopolitieke spanningen op de halfgeleiderindustrie. Regelmatig schuift een gast uit het netwerk aan om extra expertise te bieden en het debat te verdiepen. Door de combinatie van journalistieke scherpte, technische kennis en een kritische blik ontstaat een programma dat verder gaat dan de headlines en technologie in een bredere context plaatst. AIOf het nu gaat om de risico’s en kansen van AI-technologie of de positie van Europa in de wereldwijde technologische concurrentiestrijd, De Grote Tech Show biedt de achtergrond, de nuance en de inzichten die nodig zijn om deze ontwikkelingen echt te begrijpen. Dit maakt het programma onmisbaar voor professionals in de techsector, beleggers die strategische beslissingen willen nemen en iedereen die wil weten welke innovaties onze toekomst vormgeven. Met de combinatie van exclusieve interviews, deskundige duiding en een kritische kijk op innovatie biedt DGTS een unieke mix van diepgang en actualiteit. Over de makers:Joe van Burik volgt en analyseert de belangrijkste ontwikkelingen in tech, met scherpte, tempo en humor. Je hoort hem dagelijks op BNR Nieuwsradio met het belangrijkste nieuws in de Tech Update en hij presenteert De Grote Tech Show. In het bijzonder volgt Joe al twee decennia de wereld van videogames, waarover hij met bevlogen collega's en gasten praat in de podcast All in the Game. Eerder werkte hij als auto(sport)journalist voor diverse andere media en schreef het boek Formule 1 voor Dummies. Ben van der Burg is techondernemer en voormalig topschaatser. Ben is bezeten door technologie en wordt enthousiast van gadgets, elektrische auto's, goede businessmodellen en de toekomst. Naast De Grote Tech Show is hij ook wekelijks te horen als presentator van De Technoloog. Ook schuift hij regelmatig aan bij Vandaag Inside, Goedemorgen Nederland en andere talkshows, om te praten over het laatste nieuws rond technologie. Rosanne Peters is redacteur van De Grote Tech Show en De Technoloog. Ook is zij te horen in de Tech Update tijdens De Ochtend- en Avondspits. Daniël Mol is redacteur en samensteller van De Grote Tech Show. Hij presenteert zelf bij BNR de Cryptocast en maakt ook De Technoloog. Tevens is hij de vaste vervanger van Ben in De Grote Tech Show; Joe wordt bij afwezigheid vervangen door Iwan Verrips, co-host en eindredacteur van de Ochtendspits met Bas van Werven op BNR Nieuwsradio. See omnystudio.com/listener for privacy information.

Another good month – investors are giddy. Oil – CRITICALLY LOW inventory (Inside Baseball). Fed governor admits inflation is hard to control. A major name says they are reducing stocks – but are they really? Announcing the Winner of the CTP for Salesforce (CRM). PLUS we are now on Spotify and Amazon Music/Podcasts! Click HERE for Show Notes and Links DHUnplugged is now streaming live - with listener chat. Click on link on the right sidebar. Love the Show? Then how about a Donation? PayPal.Donation.Button({ env:'production', hosted_button_id:'JJJHP2GDEJC7J', image: { src:'https://www.paypalobjects.com/en_US/i/btn/btn_donateCC_LG.gif', alt:'Donate with PayPal button', title:'PayPal - The safer, easier way to pay online!', } }).render('#donate-button'); Follow John C. Dvorak on Twitter Follow Andrew Horowitz on Twitter Warm-Up - Another good month - investors are giddy - Oil - CRITICALLY LOW inventory (Inside Baseball) - Fed governor admits inflation is hard to control - A major name says they are reducing stocks - but are they really? - Announcing the Winner of the CTP for Salesforce Markets - Huge reversal in Software stocks - A few names on the move - and moving BIG! - SpaceX IPO - could drain markets - More AI valuations through the roof Pizza Mouth ! Reversal - Software stocks bounced this week on strong results from Snowflake and Okta, which both recorded their best days on record. - The results signal that investors may have been too quick to declare the end of software with the emergence of artificial intelligence. - Even as AI displaces certain tools and job functions, many software companies continue to show growth, assisted by their own AI products. - The iShares Expanded Tech-Software exchange-traded fund rose 8% this week and closed May up 21%, the best monthly performance for the ETF since October 2001. - With this month's rally, the iShares software ETF is only down 3.8% for the year, still badly trailing the Nasdaq, which has gained 18% in 2026. Snowflake - Amazon said Wednesday that its cloud division has landed a $6 billion spending commitment from Snowflake, which includes the use of the company's custom silicon and chips for artificial intelligence. - Snowflake's purchase of services and technology from Amazon Web Services will occur over five years, according to a press release about the agreement. - Snowflake intends to expand its use of Amazon's Graviton general-purpose chips, as well as cloud-based graphics processing units for AI. - Snowflake and Amazon are frenemies - they compete but also partner with each other. - Stock up 36% on this news DELL!!!!!!!!!!!! - Dell Technologies Inc. shares surged due to an outlook for annual sales that far surpassed expectations on demand for servers that power artificial intelligence work. - Revenue in the fiscal year ending in January 2027 will be about $167 billion, including $60 billion from the sale of AI servers, topping analysts' average estimate of $142.1 billion. - The company booked $24.4 billion in AI orders and generated $16.1 billion in AI server sales in the quarter ended May 1, with Chief Operating Officer Jeff Clarke saying “The AI opportunity shows no signs of slowing.” - The shares surged 33% to $420.91 at the close Friday in New York, the biggest single-day increase in the more than seven years since the hardware maker returned to the public markets after a five-year hiatus as a private firm. - Up 150% YTD More Dell - New XPS 13 at $699 targets price-sensitive market - Aims to compete with MacBook Neo, lower-end Windows devices - Launch amid global memory chip crunch to gain market share - WINING OVER JCD: -- 13.4-inch screen (very compact footprint) Options: 2K / 2.5K LCD (120Hz) OLED touchscreen (higher contrast)| - Very thin bezels ? almost edge?to?edge screen - Weighs 2.2 lbs - one of the lightes out there and a rival to Apple's Macbook Neo Infighting - OpenAI may release multi-chip AI software, challenging Nvidia's (NVDA) ecosystem advantage, according to The Information - Oh, and NVDA is now releasing a CPU for PCs that is aggrevating Intel and AMD Kaboom! - Blue Origin's New Glenn rocket exploded in a massive fireball while undergoing a test on a Florida launchpad, dealing a major setback to the company. - The explosion is the latest blow to New Glenn's reputation as a reliable alternative to SpaceX's Falcon 9, and Blue Origin's launch schedule is certain to suffer significant delays. - The incident will also affect Amazon's ambitions to build out its Leo satellite network and may delay Blue Origin's role in NASA's Artemis program, which aims to send humans back to the moon. - As important as it will be for Blue Origin to diagnose the cause of the rocket explosion, it could take many months to repair its launchpad in Florida. Taking Down - Really? - BlackRock Inc. is trimming its bet on stocks across its model-portfolio business as US equities surge to record highs following a strong earnings season. - The firm cut its overweight position in equities from 3% to 1%, triggering billions of dollars of flows between BlackRock's exchange-traded funds. - BlackRock remains confident in equities and will maintain positions that bet on growing corporate profits, artificial intelligence and government spending, but is rotating away from longer-dated US debt in favor of global fixed-income and liquid alternatives. Slight - SpaceX is targeting a valuation of at least $1.8 trillion in its initial public offering, according to people familiar with the matter. - The company is seeking to raise as much as $75 billion, which would make it the biggest IPO of all time, and is expected to start formal marketing of its IPO as soon as June 4. -SpaceX had $18.7 billion in revenue in 2025, and the company's pitch to investors shows its evolution into an AI services and infrastructure giant with a total addressable market of $28.5 trillion. - 3-5% of the shares will be floated (TIGHT) Strategy: keep supply constrained, which: supports price discovery maintains founder control creates early scarcity dynamics - - - SpaceX has reserved 5% of the shares ?in its planned initial public offering for certain employees and individuals selected by its executive officers, exempting them from post-IPO lock-up restrictions AND.. Even more Valuations - AI giant Anthropic is now worth more than OpenAI. - Anthropic announced a $65 billion Series H financing at a $965 billion valuation, a round led by Altimeter Capital, Dragoneer, Greenoaks and Sequoia Capital. - The financing puts its valuation above that of rival AI lab OpenAI. - The valuation has TRIPLED since February Let's GO! - Shares of LG Electronics surged as much as 24% after the company announced a series of automotive innovations built with technology from Alphabet Inc.'s Google. - The company said its new range of solutions is built on Android automotive operating systems. Its system can control multiple displays with different aspect ratios at the same time by using a single-on-chip, which is different from other conventional in-vehicle display systems, LG said. - But 24% on this news? - More reason that the KOSPI is moving higher No One Care - But... - Inflation has been above the 2% target for 5 years now - Minneapolis Federal Reserve President Neel Kashkari said Thursday that bringing down inflation in the U.S. remains his top priority, warning that consumer prices are still “much too high.”| - Speaking to CNBC's Kaori Enjoji at the Bank of Japan-IMES Conference, Kashkari said that the U.S. central bank would continue taking a “balanced approach” to its dual mandate of price stability and full employment. - 5 YEARS! ---- What that tells us is that the Fed is totally unable to do anything about inflation .... Are we the only ones that see that? Inside Baseball - From a colegie that will go un-named. --- Let's just say he is someone who knows what they are talking about and runs BIG money ----- This is what he said to me..... - Apparently, oil execs were opining with POTUS in meetings yesterday that oil inventories are at alarmingly low levels and oil prices could soon skyrocket (I might soften that language a bit but they know the oil biz better than me) if SoH does not open soon. - I ran a few numbers on total oil inventories including and excluding the SPR. - Total supplies are 10th percentile vs history (although that includes a period when the SPR ramped from 0 to 600mln barrels in the 1980's). - Today it is 4th percentile if you start from 1990 when the SPR was basically full. - The 4 week net and % draw the last 3 weeks are the largest draws of all time. - And not surprising the 1 week net and % draw of the SPR are also the 2 largest draws of all time the last 2 weeks. Surprised - No.... --- This is another story similar to what we saw a few months ago - Taiwan prosecutors suspect that three individuals smuggled at least one shipment of Nvidia Corp. AI chips to China after first exporting them to Japan. - The trio was detained for allegedly falsifying documents related to exports of Super Micro Computer Inc. servers containing advanced Nvidia chips, which the US has barred from sale to China without a license. - Taiwan authorities seized about 50 servers for which they accuse the trio of preparing fraudulent export documents, but at least one shipment had already gone through Taiwan customs and made it to Hong Kong. Under/Over? - Tesla will be somehow folder/merged or taken over by SpaceX in an all stock deal - Tesla market cap is $1.6 Trillion so that will be a tough one to take on as SpaceX is about equal in size. ---- If this happens, when ? Mini Retirement - Is this a THING? - A mini retirement is when you take a planned break from working, usually for a few months to a couple of years, instead of waiting until age 65+ to fully retire. - Tim Feerris popularized this... (4 day workweek dude) Step 1: Work & save aggressively 2–10+ years Build a specific “freedom fund” Step 2: Take time off 3 months to 2 years Travel, recharge, pursue interests, or experiment with new ideas Step 3: Return to work Same career… or pivot to something new Then repeat if desired.   Love the Show? Then how about a Donation? Announcing the THE CLOSEST TO THE PIN for SALESFORCE (CRM)   Winners will be getting great stuff like the new "OFFICIAL" DHUnplugged Shirt!     FED AND CRYPTO LIMERICKS   See this week's stock picks HERE Follow John C. Dvorak on Twitter Follow Andrew Horowitz on Twitter

Nvidia announced its new CPU at an event in Taipei and Jon, Rachel, and Matt talked about why potential customers may be interested in buying as well as the potential impacts to primary CPU players such as Intel and AMD. The team also talks about Berkshire Hathaway's homebuilder acquisition before closing with a question regarding passive investing trends. Jon Quast, Matt Frankel, and Rachel Warren discuss: -Nvidia's new Vera CPU -The potential fallout in the CPU markout -Berkshire Hathaway's latest acquisition -Passive investing's impact on the stock market Companies discussed: Nvidia (NVDA), AMD (AMD), Intel (INTC), Qualcomm (QCOM), Berkshire Hathaway (BRK.A)(BRK.B), Taylor Morrison (TMHC) Host: Jon Quast Guests: Matt Frankel, Rachel Warren Engineer: Dan Boyd Disclosure: Advertisements are sponsored content and provided for informational purposes only. The Motley Fool and its affiliates (collectively, “TMF”) do not endorse, recommend, or verify the accuracy or completeness of the statements made within advertisements. TMF is not involved in the offer, sale, or solicitation of any securities advertised herein and makes no representations regarding the suitability, or risks associated with any investment opportunity presented. Investors should conduct their own due diligence and consult with legal, tax, and financial advisors before making any investment decisions. TMF assumes no responsibility for any losses or damages arising from this advertisement.We're committed to transparency: All personal opinions in advertisements from Fools are their own. The product advertised in this episode was loaned to TMF and was returned after a test period or the product advertised in this episode was purchased by TMF. Advertiser has paid for the sponsorship of this episode.Learn more about your ad choices. Visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠megaphone.fm/adchoices Learn more about your ad choices. Visit megaphone.fm/adchoices

NVIDIA puts out a CPU meant for Windows machines, while Dell joins the laptops gunning for the MacBook Neo. And its chips, chips, chips as Computex kicks off.Starring Tom Merritt and Robb Dunewood.Show notes can be found here. Hosted on Acast. See acast.com/privacy for more information.

June is here so guess what? It's officially Hot AI Summer.

The Game Deflators break down new pickups, big gaming news, PS6 backwards compatibility rumors, a Steam Deck price jump, and a retro review of Woody Woodpecker on PS2. Chapters: 00:00 Intro 03:34 Game Pickups and Retro Game Books 06:45 Magic Card Collection and Trading Insights 09:44 Valkyrie Profile Gameplay Experience 12:40 Saros Game Review and Gameplay Mechanics 15:33 Upcoming Game Releases and Personal Gaming Plans 18:51 Microsoft's Exclusive Titles and Banjo Kazooie Nostalgia 35:39 Nostalgia and Character Development in Gaming 37:38 The Future of Xbox Exclusives 40:46 Lenovo's Controversial Handheld Console 47:45 Steam Deck Price Hike and Market Impact 54:43 PlayStation 6 and Backward Compatibility 59:42 Woody Woodpecker Game Review and Nostalgia 01:11:12 Outro John and Ryan return with a fresh round of gaming talk, starting with new pickups from RetroGameBooks.com and a look at what each host has been playing. John is closing in on the finale of Valkyrie Profile, while Ryan celebrates completing Saros and shares thoughts on its final stretch. The conversation shifts to community sentiment as Xbox players voice a growing desire for a revival of Banjo Kazooie. The guys break down why the franchise still resonates and whether Microsoft might finally listen. From there, the episode takes a sharp turn into hardware drama. Lenovo has pulled a handheld device that shipped preloaded with Nintendo and Sega games, raising questions about licensing, oversight, and how something like this makes it to market. The Steam Deck also enters the spotlight after a major price hike that has players debating value, timing, and Valve's long‑term strategy. PlayStation rumors heat up as reports suggest the PS6 could support PS3 titles thanks to a new CPU design. John and Ryan explore what this could mean for backward compatibility and how it might reshape Sony's next generation. To wrap up the show, the Inflation Deflation Challenge features a retro review of Woody Woodpecker: Escape from Buzz Buzzard Park on the PS2. The guys revisit its chaotic platforming, oddball charm, and current market value to decide whether it still holds up.   Find us on TheGameDeflators.com   Twitter - www.twitter.com/GameDeflators Facebook - www.facebook.com/TheGameDeflators Instagram - www.instagram.com/thegamedeflators   The views and opinions expressed on this channel are solely those of the author. The content within these recordings are property of their respective Designers, Writers, Creators, Owners, Organizations, Companies and Producers. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "fair use" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted. Permission for intro and outro music provided by Matthew Huffaker http://www.youtube.com/user/teknoaxe 2_25_18

Nvidia heeft tijdens de eigen goed-nieuwsshow GTC, gehouden rond techbeurs Computex in Taiwan, nieuwe chips aangekondigd die juist voor apparaten van eindgebruikers zelf bedoeld zijn. Het betreft de RTX Spark, voorzien van zowel een CPU als een GPU, om te concurreren met AMD en Intel. Joe van Burik vertelt erover in deze Tech Update. Verder in deze Tech Update: Softbank, bekend van investeringen in OpenAI, gaat tientallen miljarden in AI-datacenters in Frankrijk steken See omnystudio.com/listener for privacy information.

The ASX 200 consolidated Friday's gains with a loss of 2 point to 8729. Tech stocks were the star attraction, with REA up 1.5%, WTC up 8.7% and XRO rising 7.6%. The All-Tech Index rose 3.8%. Healthcare remains on the nose, with CSL dropping another 2.5% and RMD pummeled down 7.6%. REITs also slid, with CHC off % and SCG falling %. Banks were mixed, with CBA down 1.0% and WBC up 0.4%, leaving the Big Bank Basket down to $271.87 (-0.6%). Financials were mostly better, with ZIP rallying 5.2% as tech took off. Industrials were a mixed bag. TCL fell 1.8% and LNW dropped 1.0%, while BXB rallied 1.4% and CPU rose 0.9%.In resources, BHP was slightly firmer, RIO rose 1.6% and FMG improved. Gold miners were generally better, with EVN up 2.4% and CMM rallying 1.3%. Lithium stocks were on a charge, with PLS up 4.3% after huge rebalancing volumes last week, LTR up 3.3% and MIN up 1.2%. WDS and STO both made modest gains, as did uranium and coal stocks.In corporate news, LLC lost 5.5% after agreeing to sell the development rights in the Milano Santa Giulia mixed-use project in Milan. SYR soared 16.2% after its offtake dispute with Tesla was resolved, with the electric vehicle maker accepting that the alleged default conditions had been cured. MYX fell 2.9% as it expanded its US commercial footprint. CTT rose 25.5% as it moved to expand its presence in China through the launch of a flagship store on Tmall Global.On the economic front, ANZ-Indeed Australian job ads lifted 1.8%. Asian markets eased. Japan up 0.9%, HK up 0.8% and China down 0.6%. Korea up 4.1%.US futures up slightly, Dow up 49 and Nasdaq up 175. European markets set to open flat. Oil up 2.5%.Marcus Today – Daily Market InsightsMarcus Today provides clear, practical commentary for self-directed investors – covering markets, portfolios, education, and decision-making without the noise.If you'd like to go further:Start a free 14-day trial of Marcus Today http://bit.ly/mt-trial-podcastJoin Marcus Today Use code MTPODCAST for 10% off http://bit.ly/mt-join-podcast-offerMT20 – Managed ETF Portfolio A professionally managed portfolio run by Marcus Padley and the team, using ASX-listed ETFs with active market timing. http://bit.ly/mt20-podcastPrinciples – How We Think About Investing A short video series on timing, behaviour, and decision-making. No stock tips. http://bit.ly/mt-principles-podcast—Disclaimer This podcast is general information only and does not consider your personal circumstances. It is not personal financial advice.

En esta nueva misión de El Emisario Subespacial viajamos hasta Expotaku A Coruña 2026, un evento que sigue creciendo y consolidándose como una cita imprescindible para los amantes del manga, el anime, los videojuegos y la cultura pop. Nuestro corresponsal Zhlain se ha desplazado hasta allí para vivirlo desde dentro y contarnos, con detalle, todo lo que ha dado de sí esta edición. En este episodio nos centramos especialmente en la Zona Indie Dev, un espacio que continúa expandiéndose de manera sorprendente. Zhlain pasó la mayor parte del tiempo probando juegos, conversando con desarrolladores y tomando buena nota de todo el talento que se está moviendo en la escena independiente. Sus impresiones, recomendaciones y descubrimientos forman el núcleo de este contenido. Además, compartimos sensaciones generales del evento, ambiente, organización y aquello que hace que Expotaku A Coruña siga siendo un punto de encuentro tan especial para la comunidad. Cerramos agradeciendo el trabajo de Zhlain y el trato de la organización, y esperamos que disfrutes de este contenido tanto como nosotros al prepararlo. Desde A Link To The Podcast seguimos trabajando para acercarte ferias, presentaciones, entrevistas y reportajes que nos encanta compartir contigo. El Emisario volverá… no sabemos cuándo, pero nuestro corresponsal estará atento a los próximos acontecimientos para contártelos en una futura edición del Emisario Subespacial. LISTADO DE JUEGOS PROBADOS: RaveT Juego destacado: Space Diva (Aventura conversacional) Impresiones: Es el primer juego de este equipo de 4 personas con varios colaboradores. Se trata de una aventura conversacional divertida y muy original. ‍♂️‍➡️ Lanzamiento: El 28 de mayo. Enlace Steam: https://store.steampowered.com/app/3044510/Space_Diva/ ♟️ Alex did it Juego destacado: Chest Cent Impresiones: Un proyecto Solo Dev con un pixel art que es precioso. El juego propone una partida de ajedrez contra una CPU bastante desafiante, pero que se equilibra de forma súper divertida usando cartas de potenciadores. ¡Muy recomendado! Enlace Steam: https://store.steampowered.com/app/4273380/Chesscent/ Juan-Mod Juegos probados: Little Darkness: Terror por capítulos. El primer episodio llegará este mismo año. Shines Over The Board Game: Sensaciones muy chulas que recuerdan a la película Jumanji. The Last Spear: Rollo God of War y explotación de cuevas. Impresiones: Un stand fortísimo que trabaja de la mano con Jandusoft. Traían proyectos potentes como Teared para Nintendo Switch (estilo Ghouls 'n Ghosts), Shines Over para PS5, y proyectos de terror de gran nivel. Web del estudio: https://juan-mod.com/ Liceo la paz Juego destacado: Decay Impresiones: Un frenético deathmatch multijugador en Unreal Engine que promete vicios rápidos. Enlace del evento: https://zonaindie.gamevitation.es/ Soulcraft Games Juego destacado: Lo and Behold Impresiones: Definitivamente uno de los proyectos que hay que seguir de cerca. Podríamos definirlo como un "Hades con furros", donde vas alternando el combate de acción con la reconstrucción y gestión de tu propio pueblo. ‍♂️‍➡️ Lanzamiento: Previsto su Acceso Anticipado para finales de este año. Enlace Steam: https://store.steampowered.com/app/2785640/Lo_and_Behold/ ️ Rioja devs Juego destacado: Pay to Slay Impresiones: Acción directa con un estilo y planteamiento arcade al más puro estilo de Enter de Gungeon. Enlace Steam: https://store.steampowered.com/app/4336490/Pay_To_Slay/ ⚔️ LuceQ Juego destacado: Fraga Impresiones: Un título de estrategia por turnos con mecánicas Rogue-lite que te obligan a pensar muy bien cada movimiento. Enlace Steam: https://store.steampowered.com/app/4541350/Fraga/?beta=0 Don't Know studio Juego destacado: Archangel demon rush Impresiones: Un tower defense combinado con mecánicas rogue-lite. Si te gusta "Orcs Must Die", este te va a encantar. Cuenta con demo jugable en PC. Enlace Steam: https://store.steampowered.com/app/2471750/Archangel_Demon_Rush/ Ninebites Juego destacado: The Sample Impresiones: Un survival de acción con ambientación zombie desarrollado por un talentoso grupo de estudiantes. ¡Mucho mérito! Enlace del evento: https://zonaindie.gamevitation.es/ Monoii Studio Juego destacado: Bottled by bears Impresiones: Charlamos con Matías sobre este divertidísimo y adictivo Clicker en el que unos simpáticos osos producen miel y gestionan su campamento. Pronto llegará su demo a Steam y están adaptándolo para tablets. Enlace Steam: https://store.steampowered.com/app/4390080/Bottled_by_Bears/ ️ Silveil Juego destacado: Nightspyre Impresiones: Roguelite de corte narrativo que destaca de inmediato por una preciosa estética visual en "2D HD" que entra por los ojos. Enlace del evento: https://zonaindie.gamevitation.es/ Axóuxere Games Juegos probados: Colours: Una vuelta de tuerca original al clásico formato Match-3. Trap Ball Adventure: Juego en 3D de habilidad y plataformas lleno de trampas y puzzles. Enlace Google Play Colours: https://play.google.com/store/apps/details?id=axouxere.colours Enlace Steam Trap Ball Adventure: https://store.steampowered.com/app/3727270/Trap_Ball_Adventure/ [02/06/2026 9:29] Zhlain: ️ Conxuro Studio Juegos expuestos: Mr. Boss Rush y Neboa's Hut Juego destacado: O que teña honra: Un relato de María Pita Impresiones: Nos llamó muchísimo la atención este juego de defensa de torres (Tower Defense) ambientado históricamente en la famosa invasión de los ingleses a A Coruña. ¡Propuesta con raíces e historia local! Enlace del evento: https://zonaindie.gamevitation.es/ Ecliptika Collective Juego destacado: Purgatory Hoops Impresiones: Baloncesto arcade en clave de fantasía. Nace como un fantástico proyecto de máster de la Universidad de A Coruña (UDC). Enlace del evento: https://zonaindie.gamevitation.es/ Klayerama Studio Juego destacado: Chaos Of Destiny Remake Impresiones: Un divertidísimo RPG con un look retro súper cuidado (influencia directa de los 8 y 16 bits) que viene cargadísimo de sentido del humor. Enlace Steam: https://store.steampowered.com/app/3230030/Chaos_of_Destiny_Remake/ NEKERAFA Juegos en exposición: Lumina: Prelude y Miña leira (este último, probado). Impresiones: Miña leira es un concepto desternillante: básicamente jugar a "Hundir la flota" pero utilizando verduras en el campo. También organiza la Amorodo Jam: https://itch.io/jam/amorodo-jam-3/entries Enlace itch.io: https://nekerafa.itch.io/minha-leira Game Explorer Spacecrft (Monodo) Juegos probados: Endless Space Scrap: Se nota que hay muchísimo trabajo detrás y una gran mejora desde sus últimas versiones. Enlace Steam: https://store.steampowered.com/app/4054080/Endless_Space_Scrap/ Pet Troll: Un simpático juego ya disponible para dispositivos móviles Android. Enlace Google Play: https://play.google.com/store/apps/details?id=com.pettroll.petstroll Quasar Factory Juego destacado: Master of Cladia Impresiones: Estrategia por turnos y multijugador asimétrico. Durante el evento organizaron torneos con premios para los asistentes, ¡todo un éxito de público! Enlace Steam: https://store.steampowered.com/app/3732690/Master_of_Cladia/ Enlace Google Play: https://play.google.com/store/apps/details?id=com.QuasarFactoryGames.MasterOfCladia&hl=es AKIDNE DEVELOPS Juegos probados: Starry Larry let's Parry: Un juego de combates contra jefes en el que esquivas y devuelves ataques en lugar de atacar directamente. Enlace itch.io: https://akidne-develops.itch.io/starry-larry Tower Clefence: es un tower defense super original donde las torres son instrumentos musicales que se van añadiendo a la banda sonora dinámicamente según colocas las torres en el mapa. Enlace itch.io: https://akidne-develops.itch.io/tower-clefense ️ Notas: El desarrollador es un estudiante de bachillerato autodidacta que ha creado todo el proyecto por su cuenta. El año pasado tenía Chimaelis, un juego mezcla de Pokémon y Dark Souls. Devmo Games Juegos probados: The Pet Squad: Un simulador de mascotas ideal, ahora jugable en tabletas. Enlace https://thepetsquad.devmo.es/ Gato Pompa: Un plataformas súper simpático y con mecánicas originales que nació del desarrollo express en una Game Jam. Enlace itch.io: https://devmo-io.itch.io/gatopompas-tm Widijou Juego destacado: Golpes y Porrazos (Thumps & Blows) Impresiones: El clásico juego de lucha de hombres de palo (stickman) rápido, familiar, gamberro y terriblemente adictivo. No paraba de haber cola en su stand para probarlo. Enlace Steam: https://store.steampowered.com/app/3650210/Golpes_y_Porrazos/ Zeta Works Juego destacado: Chamber exit Impresiones: Escapa de la mazmorra en este frenético juego de plataformas en primera persona donde cada salto te hace ir más rápido. Enlace: https://zetaporfolio.carrd.co/ Dreamscape Games Juego destacado: Bullet Mirage Impresiones: Juego del género Survivors-like con trazos de bullet hell. Enlace del evento: https://zonaindie.gamevitation.es/ [02/06/2026 9:29] Zhlain: OTROS PROYECTOS PRESENTES EN EL EVENTO ✏️ No te pierdas estas otras grandes propuestas que también contaron con espacio de exhibición en la feria: ️ AIKODE (from Naeco): AIKODE es un videojuego de rol de acción (Action RPG) ️ BreixoGameDev: Ghost Node, juego de sigilo y hackeo en tercera persona ️ Deep Ore Games: Knightsworn: Dragon's Knight Legacy, roguelite de construcción de mazos. ️ Nine Bites: Splash on Contact, defiende a lasemilla del fuego con tu cuerpo acuático. ️ ACADEVI (Asociación Canaria de Desarrolladores): Presentando una increíble selección de proyectos creados por la comunidad de Canarias. ️ Mario Ribé: Wong, un plataformas 2D orientado al speedrun. ️ Ninguen: Dimension L, un RPG de estrategia online por turnos. ️ Peseteros: Pis-To-Le-Ro, un juego multijugador local 1vs1 basado en el popular juego. ️ GodOfReDo: un videojuego sobre Godofredo, el mejor cronomago de todos los tiempos. Rapoucado: ️ Entomolography: un videojuego sobre fotografía entomológica. ️ Quenllas: acariciar a diversas especies marinas y aprender sobre ellas. Encuentra todos los detalles y redes de estos creadores en la web oficial: https://zonaindie.gamevitation.es/

Question time again! This month we discuss quite a wide range of topics, such as tracking down printer dots with a USB microscope, the dream of going to SIGGRAPH, the legality of scanning and uploading "lost" old magazines, how to stay objective about new stuff as you get older, steady fan curve strategies for CPU air cooling, how to cope when you find out that cool new open source project was made by AI, renaming files like a pro, and the enduring mystery of ICQ's event sounds. Support the Pod! Contribute to the Tech Pod Patreon and get access to our booming Discord, a monthly bonus episode, your name in the credits, and other great benefits! You can support the show at: https://patreon.com/techpod

Imagine getting stranded on a desert island with a laptop, a DAW, and exactly five plugins before the universe says, “Good luck, audio nerd.” That's the ridiculous challenge Chris & Jody tackle this week on Inside the Recording Studio, and things get surprisingly serious surprisingly fast. Because once you remove the safety blanket of 947 unused plugins, producers suddenly have to admit which tools they actually rely on. In this episode, the guys battle through their top five desert island plugins while trying not to completely destroy the rules they created five minutes earlier. Amp sims? Probably essential. Synths? Hard to live without. Channel strips? Maybe cheating. Creative FX? Absolutely necessary if you don't want your island recordings to sound like sadness and driftwood. Chris & Jody dive into the plugins they trust most for recording, mixing, songwriting, and keeping sessions moving when inspiration hits. Along the way, they drop a ton of recording setup tips for producers trying to simplify their workflow without sacrificing quality. Turns out, having fewer choices can actually make you faster, more creative, and less likely to spend four hours scrolling through presets named “Warm Punchy Master Final FINAL.” The conversation keeps circling back to a painful truth about home studio gear: most of us own way more plugins than we actually need. Instead of chasing every new release, the guys explain why deeply learning a handful of tools often leads to better mixes than endlessly collecting shiny new software. Naturally, the debates get a little heated. One plugin gets defended like it's the last raft leaving the island. Another gets questioned because it technically combines too many features into one package. There's also discussion about workflow speed, CPU efficiency, versatility, and whether a plugin deserves survival status if it only does one thing really well. And because this is Inside the Recording Studio, the episode wanders into wonderfully absurd territory too. There's joking about coconut-powered studios, headphone mixing while hiding from seagulls, and the psychological damage caused by being trapped forever with only stock reverb. Still, underneath the nonsense is a genuinely useful conversation for anyone building a home recording setup. If you've ever wondered how to narrow down your plugin collection, improve your workflow, or choose tools that actually help you finish music, this episode offers practical insight without drowning you in technical jargon. Friday Finds also makes an appearance with more studio goodies worth exploring, because apparently being stranded on a desert island still doesn't stop audio people from wanting more gear. So if you love plugin talk, recording setup tips, home studio gear debates, and watching two engineers argue over imaginary survival conditions, this episode is for you. Subscribe now and join Chris & Jody for more studio wisdom, questionable humor, and audio adventures every week. #HomeStudioGear #RecordingSetupTips #MixingPlugins #MusicProductionTools #AmpSims #ChannelStripPlugins #StudioWorkflow #AudioProduction

Java's use of memory, often chided for being excessive, is actually a strength as it trades more memory use for fewer CPU cycles. Java can only make this tradeoff due to its moving garbage collectors, something more memory efficient platforms often cannot. But what's the point in leaving available memory on the table if using it makes your program run faster? Efficient use of that resource wouldn't be to leave it untapped but to use it to speed up the program. In this "Ask the Architect" episode of the Inside Java Podcast, recorded during JavaOne 2026, Nicolai Parlog talks to Ron Pressler, Java Architect at Oracle.

In this episode, we debrief Telehash #4 and dig into the open-source future of Bitcoin mining. We share behind-the-scenes metrics from HydraPool's six-and-a-half–hour live stress test, including 30.8 zettahashes processed, an average of 1.32 EH/s, a peak of 2.495 EH/s, 2,231 workers, 59 unique users, and an impressively low ~1% server CPU under >2,000 connections. We explain why rejection rates under ~2% matter, how stale and “difficulty too low” shares differ in solo vs pooled mining, and how Stratum “suggest difficulty,” plus our d= and h= password parameters, help right-size starting difficulty—making Telehash inclusive for both exahash renters and single-chip Bitaxe miners. We also touch on leaderboards, loyalty uptime rules, and shout out supporters like Elektron Energy, Compass, Saaz Mining, and Abundant Minds. From hardware to policy, we discuss Bitaxe UX updates (LVGL, Figma-driven UI, external display/knob), DOOMAXE fun, and industry standardization—from firmware and pools to racks, cooling, and power—arguing that open reference designs cut costs and risk for everyone. We cover GridPool's “winners list” approach to decentralized variance smoothing, the Patoshi/extra nonce story, vardiff dynamics, and privacy-conscious VPN mining. We reflect on immersion's decline versus hydro, ASIC roadmap realities and slowing efficiency gains, the supply-chain and security stakes (FCC Wi‑Fi moves, vendor backdoors), and why nonprofit coordination via the 256 Foundation matters for open firmware, dev kits, and reference designs. We close with community invites, next steps for Telehash #5, and a call for ASIC makers and big miners to collaborate on open standards that benefit small and large operators alike.

¿Cierras el libro pero tu cabeza sigue a mil por hora repasando lo que no entendiste? Estás atrapado en un ciclo abierto. Hackeamos el cierre de tu sesión para que el español no te robe el descanso:Acabar vs. Completar: La distinción para vaciar tu CPU mental y eliminar la culpa post-estudio.El "Dump" de 30 segundos: Cómo liberar tu memoria de trabajo para poder desconectar de verdad.Ritual de Aterrizaje: El puente sensorial para pasar del hiperfoco a la paz mental.

Brad's tired of throttling his CPU due to an inadequate heatsink. Will's been spending a lot more time testing PC hardware of late. Between those two things, we thought it was a good time to do a check-in on CPU cooling, and primarily liquid cooling, so we can establish the facts on the ground about modern AIOs and custom loops with an eye toward helping Brad decide what to get. Turns out, there's more to know than ever, and yet it's also never been simpler. We also talk a little about modern air cooling, CPU spikes in Windows, and other stuff! The GamersNexus video on AIO placement: https://www.youtube.com/watch?v=BbGomv195sk Support the Pod! Contribute to the Tech Pod Patreon and get access to our booming Discord, a monthly bonus episode, your name in the credits, and other great benefits! You can support the show at: https://patreon.com/techpod

Today's Post - https://bahnsen.co/3R9QgGV In this Friday Dividend Cafe, David Bahnsen explains why data centers have become a major economic story, tracing their evolution from 1990s CPU-based server facilities to 2010s cloud-driven hyperscale warehouses and today's AI-focused GPU centers that require far more power, cooling, and infrastructure. He argues data center construction and related spending may have accounted for roughly 80% of last year's GDP growth, even as other real estate and industrial activity has been muted, drawing an analogy to the shale/fracking boom. Bahnsen supports data centers and future productivity potential but opposes federal efforts to override local zoning, warns against cronyism, emphasizes the need for a stronger public relations case, and highlights investment implications in adjacent areas like power, water, natural gas, and pipelines. 00:00 Welcome and Setup 00:52 Why Data Centers Matter 01:43 Three Eras of Data Centers 03:51 AI Shift to GPUs 05:42 Data Centers Driving GDP 08:29 Future Productivity Payoff 09:32 What Growth Is Missing 10:12 Fracking Analogy and Backlash 12:15 Localism Versus Federal Override 14:57 PR Playbook Five Points 17:23 Investing Wisely in the Theme 19:35 Wrap Up and Disclosures Links mentioned in this episode: DividendCafe.com TheBahnsenGroup.com

Learn why Activity Monitor is the macOS tool experienced users trust first to diagnose hidden memory drains, runaway CPU usage, and behind-the-scenes energy hogs. Mastering a single built-in tool can put real-time answers and expert-level control right at your fingertips. Quick Access Methods: Spotlight, Finder, and Utilities Folder Five Main Tabs: CPU, Memory, Energy, Disk, and Network Explained Sorting and Identifying Resource-Heavy Processes in CPU Tab Understanding Percent CPU, Multi-Core Macs, and High Usage Scenarios Spotting and Managing Frozen or Runaway Apps via Activity Monitor The Importance of the Kind Column: Rosetta Support and Apple Silicon Transition Using Memory Tab and Pressure Graph to Gauge RAM Health Sorting by Memory to Find Leaky or Misbehaving Apps Energy Tab Insights: Finding Battery-Draining and Power-Hungry Apps Disk Tab: Diagnosing Read/Write Issues and Competing Background Tasks Network Tab: Tracking Data-Heavy Apps and Monitoring for Security Live Dock Icon Graphs for CPU, Network, and Disk Usage How to Force Quit or Inspect Troubled Processes in Activity Monitor Homework: Add Activity Monitor to Dock and Monitor Rosetta Apps Before Support Ends Host: Mikah Sargent Download or subscribe to Hands-On Apple at https://twit.tv/shows/hands-on-apple Want access to the ad-free audio and video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsor: outsystems.com/twit

Learn why Activity Monitor is the macOS tool experienced users trust first to diagnose hidden memory drains, runaway CPU usage, and behind-the-scenes energy hogs. Mastering a single built-in tool can put real-time answers and expert-level control right at your fingertips. Quick Access Methods: Spotlight, Finder, and Utilities Folder Five Main Tabs: CPU, Memory, Energy, Disk, and Network Explained Sorting and Identifying Resource-Heavy Processes in CPU Tab Understanding Percent CPU, Multi-Core Macs, and High Usage Scenarios Spotting and Managing Frozen or Runaway Apps via Activity Monitor The Importance of the Kind Column: Rosetta Support and Apple Silicon Transition Using Memory Tab and Pressure Graph to Gauge RAM Health Sorting by Memory to Find Leaky or Misbehaving Apps Energy Tab Insights: Finding Battery-Draining and Power-Hungry Apps Disk Tab: Diagnosing Read/Write Issues and Competing Background Tasks Network Tab: Tracking Data-Heavy Apps and Monitoring for Security Live Dock Icon Graphs for CPU, Network, and Disk Usage How to Force Quit or Inspect Troubled Processes in Activity Monitor Homework: Add Activity Monitor to Dock and Monitor Rosetta Apps Before Support Ends Host: Mikah Sargent Download or subscribe to Hands-On Apple at https://twit.tv/shows/hands-on-apple Want access to the ad-free audio and video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsor: outsystems.com/twit

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!On the product side, everyone is getting Computer - Perplexity, Manus, Cursor, and so on. Meanwhile on the research side, agentic evals like TerminalBench and GDPVal are also assuming computer (Harbor). On both ends, the consolidating LLM OS stack has become a standard toolkit, and Daytona is one of a small set of AI Infra companies that are booming because of it.“The end of localhost” has been Ivan Burazin's obsession for more than a decade.Something that is all too familiar…Long before agents became the default way people talked about software development, Ivan was already chasing the idea that development should not depend on a fragile local machine. CodeAnywhere, one of the first browser-based IDEs, was an early attempt at that future: move the development environment into the cloud, make setup reproducible, and free developers from the endless “works on my machine” tax.The thesis was directionally right, but the market wasn't ready yet.However, agents changed that. They do not care about a laptop, desk setup, or favorite editor. They need a computer they can access through an API: something stateful enough to keep working, fast enough to spin up instantly, flexible enough to resize, isolated enough to be safe, and composable enough to run the messy real-world workflows that real software engineering actually requires.Daytona isn't just selling “sandboxes” in the narrow code-execution sense. It is the latest version of Ivan's original localhost thesis.In this episode, Daytona's CEO joins swyx to explain why AI agents need more than code execution boxes: they need composable computers, stateful sandboxes, instant startup, dynamic resources, and infrastructure that can survive workloads going from zero to 100,000 CPUs.We go deep on the new agent compute market: Daytona's hard pivot from human dev environments to AI sandboxes, the New Year's Eve MVP that customers begged for, why Daytona runs on bare metal with its own scheduler, how one customer runs almost 850,000 sandboxes a day, and why RL/eval workloads went from 0% to roughly 50% of usage in just months. Ivan also explains why agents need Windows and macOS machines, why CLI may matter more than MCP, why Kubernetes is painful for this workload, and why the future AI cloud may look more like Stripe than AWS.We discuss:* How Daytona grew out of CodeAnywhere, Shift, and the “end of localhost” thesis* Why Daytona pivoted from human dev environments to AI sandboxes* Why agents need composable computers instead of disposable code execution boxes* The New Year's Eve MVP that customers chased API keys for* Why Daytona chose bare metal, stateful snapshots, and its own scheduler* How Daytona spins up one sandbox in ~60ms and 50,000 sandboxes in ~75 seconds* Why Daytona's biggest customer runs ~850,000 sandboxes a day* How RL/eval workloads create zero-to-100,000 CPU spikes* Why RL workloads went from 0% to roughly 50% of Daytona usage* Why customers compare Daytona against EKS/GKS and say they're “never going back”* Why every AI agent may need a computer, including Windows and macOS environments* The Apple licensing constraints that make macOS sandboxes hard* Why CLI gives agents more power than MCP* How open source helps agents integrate Daytona* Why agent-generated PRs may break today's CI/CD assumptions* Why AI SaaS companies reselling tokens may face a cold shower* Why the AI cloud may look more like Stripe than AWSIvan Burazin* LinkedIn: https://www.linkedin.com/in/ivanburazin* X: https://x.com/ivanburazinDaytona* Website: https://www.daytona.io* X: https://x.com/daytonaioTimestamps* 00:00:00 Hook* 00:01:12 Introduction* 00:03:15 CodeAnywhere, Shift, and the end of localhost* 00:05:58 What Daytona is: composable computers for AI agents* 00:08:07 The pivot from dev environments to AI sandboxes* 00:10:17 The New Year's Eve MVP and customers begging for API keys* 00:12:56 Bare metal, stateful sandboxes, and Daytona's scheduler* 00:17:28 60ms startup, 50,000 sandboxes, and 850K daily runs* 00:21:53 Spiky RL/eval workloads and the new agent infra problem* 00:28:12 RL workloads, Kubernetes pain, and dynamic resizing* 00:33:31 Why every AI agent needs a computer* 00:38:48 macOS sandboxes and Apple's licensing problem* 00:44:28 Why CLI may matter more than MCP* 00:48:11 Open source, GitHub stars, and agent integration* 00:53:11 Git, CI/CD, and agent collaboration bottlenecks* 00:58:15 Founder life and building a 25-person infra company* 01:02:44 AI SaaS, token resale, and API-first business models* 01:06:10 GPU sandboxes, data centers, and compute growth* 01:09:48 Why the AI cloud may look more like Stripe than AWS* 01:11:26 Closing thoughtsTranscriptIntroduction: Daytona, CodeAnywhere, and the End of LocalhostSwyx [00:00:02]: Okay, we're in the studio with Ivan Burazin, CEO of Daytona. Welcome.Ivan [00:00:07]: Thanks for having me, man.Swyx [00:00:08]: Ivan, you and I go back.Ivan [00:00:10]: Way back.Swyx [00:00:11]: How I don't even know how, you found, did you reach out or, for Shift.Ivan [00:00:17]: I reached out to you. The reason was you - we were just - we were thinking about I was one of the co-founders of CodeAnywhere, the first browser-based IDE, and so we were thinking a long time of, localhost should die. And you had this article.Swyx [00:00:29]: End of localhost.Ivan [00:00:30]: Then I reached out to you because of that, and then we talked, and I was actually at a different job and learning about I was the head of, developer experience, and you were quite well-versed in that, and I actually reached out to you, among other people, how do we go about that? What are the key things and whatnot at this point in time? And you were nice enough to take the call, and I remember I was late on your call with you.Swyx [00:00:51]: I don't remember.Ivan [00:00:52]: I remember because I was with my then I'm thinking of a girlfriend or wife at that point in time, I'm not sure. It's the same person, so that's great, and I was late ‘cause we were, in, Italy on, vacation, and then I was late for something. I felt so bad, and you were so nice to be, good about.Swyx [00:01:10]: The reason I'm nice is because I'm also late to other people, so it's like, who's, who's without sin here, yeah, so I have to, for those who don't know, InfoBip Shift, there's this whole thing that, you did in the past, and, and that was basically one of the inspirations for me starting AI Engineer, which is like, I have to thank you for giving me that push to be like, “Oh, you can, you can build and sell conferences?”Ivan [00:01:34]: I remember you asked you asked me at the beginning to give me advisory shares, and I was so focused on what we were doing, I said no, and I should've took the advisory shares. So I'm sorry, dude. But anyway.Swyx [00:01:43]: We're not, we're not venture backed.Ivan [00:01:44]: No, it doesn't matter.Swyx [00:01:45]: It's Yeah, anyway, so I think what's impressive about you is that CodeAnywhere is the thing that you've been trying to build, and, you kind of put it on hold and then came back after InfoBip. Just give us the story, do you - the story and the origin story, going into Daytona.From CodeAnywhere and Shift to DaytonaIvan [00:02:05]: Sure. Like, really way back, me and my co-founder have been together. I say this, I've said this multiple times, it's like we were married and divorced and married. Some people actually ask me is my co-founder my partner. they thought it literally. It's not literally, but we have done multiple companies together, and to your point, we had this shift where we went from the CodeAnywhere to the conference called Shift, and then back to, Daytona. We originally started stacking servers, doing like virtualization in the early 2000s and, routers and doing basically all these things, at a foundational level, and that was a services company which we sold to focus on what my co-founder actually invented, which was the very first browser-based IDE, right, I say the first. Before us was actually Heroku. They did it for a very short time until they became Heroku. But outside of them, we were the only one, and it was called.Swyx [00:02:55]: There was Cloud9.Ivan [00:02:57]: Cloud9 came out slightly after us. There was Replit, which came out when we stopped doing it, Replit came out, and they have been successful since then, which is great. There was Nitrous.io. There was quite a few that existed at the time, but it was like too early. But the interesting part is that we, at that point in time, because there was no VS Code, there was no Kubernetes, and Docker had just started when we Or I'm not sure if it was even public at that point in time. And so we had to build everything to the whole stack ourselves and that was the key learning that we brought into and that we've been using in Daytona today. So it was super early. There's about 3 million people used CodeAnywhere. It was slightly, it was angel-backed more than venture-backed. We ended up paying everyone back because it didn't have that sort of scale. But, three years ago, we started something similar with Daytona, which is not what we are today, but it was automating dev environments for human engineers, the basically the underlying stack of CodeAnywhere. And then we did a hard pivot last January to sandboxes. And so here we are.Swyx [00:04:01]: Historic pivot, yeah, and, it's one of those things where, I had independently invested in CodeAnywhere, but also in E2B, and then both of you pivoted into the same thing, and I'm like, “F**k.”Ivan [00:04:12]: You invested, you invested in Daytona. You invested in Daytona. But you were the first If we had not got your check, we wouldn't have done it.Swyx [00:04:18]: No way.Ivan [00:04:19]: No, it was like, “We have to get him on board first,” and you were that kicker that we, that got us off the ground.Swyx [00:04:23]: No, because you were putting me on your pitch deck, man. I was like, “Man, this is like a good trip if I don't invest.”Ivan [00:04:29]: That's because it was your quote. It's like we.Swyx [00:04:30]: Yeah. It's the end of localhost.Ivan [00:04:31]: Did a bunch of research about end of localhost and who was interested in that,.Swyx [00:04:34]: No, that's like, I put, I wrote that blog post, and every single company in that field reached out to me, and then every VC who was receiving those pitches then also had to call me and, talk it, talk through it with me.Ivan [00:04:47]: It's finally happening though.Swyx [00:04:48]: It was really super interesting.Ivan [00:04:48]: It's finally happening.Swyx [00:04:49]: It's finally happening.Ivan [00:04:49]: Yeah, it's finally.Swyx [00:04:49]: It's finally happening, with maybe sort of non-human users. Yeah, so what is Daytona today? Let's get like a quick description. I'm wearing the shirt.What Daytona Is Today: Composable Computers for AI AgentsIvan [00:04:58]: You're wearing the shirt. Yes,.Swyx [00:04:59]: It says, I think your branding is very good. Like, it's very consistent. It runs AI code. Like, it cannot be simpler.Ivan [00:05:05]: Exactly, but we're gonna probably have to change that.Swyx [00:05:07]: Oh, s**t.Ivan [00:05:07]: It's also a subset of what we do. Unfortunately, we really love this, Run AI Code is super simple. People interpret it different ways. I think we've given out 5,000, 6,000 of these shirts. People wear them with pride because it doesn't really market about us.Swyx [00:05:21]: Yeah, Daytona's on the back.Ivan [00:05:22]: It markets the back. It markets to the person itself, so I think we did a really good job on that one. But it is also a subset of what we do, because people, when they think about Run AI Code, they just think about these small, let's call it isolates, code execution boxes that, you send some code, you get an output. Whereas what Daytona is today is essentially composable computers for AI agents. It is, the market calls them sandboxes which can be misleading.Swyx [00:05:44]: All these things. All these things on.Ivan [00:05:45]: Yeah, exactly, ‘cause it can be misleading ‘cause people usually think about sandboxes as a demo or a test environment versus a production-grade environment. But what Daytona does, if you think of the laptop that you have in front of you or the computer that's over there, or, my wife is an architect, so she has like a Windows with a 3D graphics card inside to do 3D rendering. Like, as humans, we have different computers or different compositions of computers. And our belief is strongly that agents today and going forward will need all these different compositions of computers to do different types of tasks. And so we offer that basically through an API.Swyx [00:06:19]: Yeah, to give people - I'm trying to sort of front-load all the aha moments or the wow moments so that people can, stay engaged and click like and subscribe. the market is exploding, right? Like, you have been reporting 74% month-on-month growth, and it also, it's just been growing for a while. Like, it's been going like this. And every single - It's not just you guys. It's every single.Ivan [00:06:41]: Everyone, yeah.Swyx [00:06:42]: Sort of, compute provider. I don't know if you agree with me saying compute provider or not.Ivan [00:06:48]: It's fine.Swyx [00:06:48]: Yeah. So like organically PLG-driven growth, but also enterprise is doing super well, I think I wanna rewind to January of last year when you did the pivot. Like, so you obviously called this market early, and you were positioned for it, and you are now one of the market leaders. But what was the insight that made you do the pivot?The Pivot: From Human Dev Environments to Agent SandboxesIvan [00:07:06]: The insight that made us do this pivot is the quarter before that, so end of 2024, when we had - Basically, we did a demo with - I don't I think we discussed this as well, Devin was not public. You actually gave me access to Devin at that time. So Devin.Swyx [00:07:25]: I did?Ivan [00:07:26]: Yeah, you gave me access.Swyx [00:07:26]: I don't think I was supposed.Ivan [00:07:27]: Yeah, exactly.Swyx [00:07:28]: Yeah, I.Ivan [00:07:28]: So it doesn't matter. You.Swyx [00:07:29]: Yeah. I gave like three friends access.Ivan [00:07:31]: Yeah, or it was a call and you showed it to me. It doesn't matter. but OpenDevin was available, which is now called OpenHands. And so we're like, “Oh, this seems to be a thing. This is not public. Let's take our for human automation of dev environments and take, OpenDevin and launch that as a SaaS.” And we did that. Not very many people signed up and used it, but a lot of people reached out that were building agents, and they were like, “Hey, my agent needs a compute sandbox runtime,” whatever you wanna call it. I forgot what it was called at that point. And then we were like, “Oh, amazing. This is a new market. Here is our infrastructure. Here's our product, and go.” And what we found really fast, soon, was that people did not like what we had built. It didn't work. And I remember talking to people at the beginning when we're doing this, the sandbox we're building for agents. People were like, “Oh, why is it different? It's the same thing. We have like EC2, we have VMs, we have all these things.” But we saw that everyone we gave it to, it was like 20, 30 people, they all said, “No.” Like, “This is not what we need. This sort of breaks.” And basically, me and my co-founder not knowing a lot about - ‘cause we're infra people. We're not AI people. So I basically took it upon myself to like watch every single podcast that exists, including all of, all of these and all that, and sort of get up to date, read all the blogs, like get, understand what's going on.Swyx [00:08:45]: Do you wanna shout out who else was useful, just in case people are also looking.Ivan [00:08:49]: Generally we -, I looked at There's a few of podcast, different segments and different types. So there's you guys, No Priors, Bill Gurley's was great while.Swyx [00:09:04]: VG2, yeah.Ivan [00:09:05]: Yeah, while it was around. So there's a few. 20VC is interesting from a different dynamic, and some are different dynamic. But there was, also Red Points.Swyx [00:09:14]: We're not really about the compute market.Ivan [00:09:15]: It was also already - Sorry?Swyx [00:09:16]: You're, you want - You're looking at the agent infra market.Ivan [00:09:19]: I was looking at the agent market and the AI market in general and sort of understanding who are the players, what the perception, and how that goes. And like obviously you complement this with like going to conferences, going to events, going to meetups, reading white papers, like doing all the things that you have to do to understand what's happening. And so when we figured, when we sort of had an idea of what we had to build, literally over the New Year's Eve, literally on New Year's Eve, I half vibe coded the first MVP, first minimal viable product of what Daytona is today. And I went to sleep at like 3:00 AM or something like that. I was doing - I just put my like baby daughter and wife to sleep and, Happy New Year's, and go back to just, doing this. And I sent it to my co-founder, my CTO, and he saw it in the morning. He's like, “This is absolute garbage.” “Do not show this to anybody at all, but the idea is good.” And so he took two weeks, and he rebuilt it.Swyx [00:10:09]: Did it like look like that? Listen, I - It was rough idea.Ivan [00:10:12]: Oh, not even, not even close. Like it was it was way worse. But it was like a very - It was a simplistic view of what it should be. Like, it worked, but it was not ideal. And so he went, we went down the whole, which is his job as CTO, to go, and he came back with this version. We then called all the people that had said like, “This is garbage,” a quarter ago. And we set up these calls, and we gave it to - We just demoed it to everyone. And all the calls went long, every single one. They were 15-minute calls, and they all went to like 25, 30 minutes or whatnot. And everyone said, “We need, we want access.” There was no login, just an API key, ‘cause it was just a beta or an alpha. And they said, “Oh, we want access.” And we're like, “Sure, yeah. Okay, thank you very much.” But after like the next day, if we'd not send it, every single one, like every call that we did, everyone came back, “Where is my API key?” Like everyone wanted it. We're like, “S**t.” Like this is it. Like I've never felt So one, the understanding to your point was like most people thought it was the same infrastructure for humans and agents. We understood a quarter ago it's not. We just didn't know what was the right primitive. And then when we came, and we can talk about what that is, and we gave it to these people, I've never seen, I've never experienced - I've done multiple companies in my life. I've never experienced this, that people literally call you if you do not give them access. Like they want access right now. And so it's like, okay, they don't want this. the thing that they want doesn't seem to exist, or they have not found it, and they really want what we want. And then when we understood that we're onto something, and then when you think about the size of the market, like the market for human engineers and enterprise is a very large market, so think GitLab or whatnot. But the market for every single agent that will exist ever in the future is just like, what is that market? How big is that? And we're like, “We are all in on this.” And so that is where we made sort of the cut between the old product and the new one.Bare Metal, Stateful Sandboxes, and the Lambda + EC2 ModelSwyx [00:12:02]: Yeah. But it wasn't composable at the time?Ivan [00:12:05]: It was very - It was basically just a Linux box that you could change, that you could define number of CPUs, disk, and RAM. Like that is what you could do, but you couldn't have multiple operating systems, you couldn't resize it on the fly, you couldn't add a GPU, you couldn't do like all the things. It was just the, just the first sort of variation of that, yeah.Swyx [00:12:22]: Was it bare metal from the start?Ivan [00:12:24]: It was bare metal from the start. And so the interesting thing that we thought about right away, so our.Swyx [00:12:29]: Which, give people the background, what is the normal path?Ivan [00:12:32]: Yeah, so, basically most providers run this on top of VMs. And also.Swyx [00:12:37]: Firecracker.Ivan [00:12:38]: Yeah, they run on Firecracker and VM. And so we also fire - We can get - We have multiple isolation layers and we can do that. But the common way to do it is that they, one, that the state of the machine, or the hard disk is not part of the sandbox itself. And the other thing is they're not meant to last forever. So most of them are preemptible, like they can There's a time that they can live. And so our thought was when we were going into this is, agents will be like humans in the sense of you don't want your laptop to be shut down until you're done with work. Like, and you want to close the lid and open the lid, it's the same state. So you - Agents would want that, like the pause and come back. They want those two things. But also agents really want speed, right? Can they get it? So when we thought about it's like we need something insanely fast, how to make it fast, how to make it long-running, and stateful. And so those two things, it's like combining a Lambda and an EC2, right? Those two things together. And so we didn't have an idea how others did it, ‘cause we didn't know too that there was a market around this. It was more like, okay, this is what we need, what they need. And we looked at Kubernetes, it wasn't wasn't good enough for that. We looked at Nomad, it didn't enable that. And so our history in rewriting our own scheduler at CodeAnywhere is basically what my CTO came up with. Like, he's like, “Oh, the learnings from there,” and he brought it. And the funny thing is, our third co-founder, when he saw it, he's like, “Dude, what is this? This is like 2008.” Like, we went back in time, and he's like, “Exactly.” And so the reason why Daytona is like super fast, and you see this on benchmarks, is we essentially, we run on bare metal. We have our own scheduler, we use the underlying, disk, CPU, and RAM of the underlying machine, which means your IOPS are insanely fast because there's no, there's no network between an EBS or something like that. But also the snapshot, the point in time, the templates, are also preloaded on the bare metal machines. So when you fire off a sandbox from a template or a snapshot, you're essentially directed to the bare metal machine where that snapshot is based on that NVMe drive, and then it literally just turns on that machine, and it's local. There's no network latency, anything on there. And so that is sort of the specificities that we, when we're thinking from first principles, what a computer would look like for an agent, that is what we came up with, and that's what we created.Benchmarks, 60ms Startup, and 50,000 SandboxesSwyx [00:15:02]: Yeah. I should maybe, I don't know if you endorse this, but there's someone that does compute SDK, you guys do very well on there, with like the TTI, right? I. is this a, is this a is this a relevant benchmark for you guys? I don't know.Ivan [00:15:16]: I don't know, and it changes every day. So today RKL is.Swyx [00:15:18]: I don't know what RKL is. Never heard of it.Ivan [00:15:20]: Yeah. RK, yeah, so it is there.Swyx [00:15:22]: You are, at least a third of the next tier of performance, and then, there's a lot of other better-known names that are very slow to start.Ivan [00:15:31]: Yeah. We've been the number one by far for a long time, and now there's different, there's different definitions also of sandboxes, different isolation patterns, different other things. So RKL runs it literally on the S3, the data, so it's very different, and they spin up a sandbox, spin up a container for that, so it's a different type of thing. So the definition of a sandbox is something that we can all, we all need to get along with. But yeah, we're insanely fast on getting these things, up and running. And so you can see even there that it's a zero point 0.10 to 0.11, so.Swyx [00:16:03]: Close enough. Yeah. what else do you need, right?Ivan [00:16:05]: Yeah. So the benchmarks itself, so, in this, in I don't think the benchmarks equate to market ownership or revenue or anything like that. and I've seen this with multiple benchmarks, not just in sandboxes, but in general benchmarks around.Swyx [00:16:20]: It's table stakes. It's just like.Ivan [00:16:21]: Exactly. But it doesn't hurt.Swyx [00:16:22]: Just roughly check.Ivan [00:16:22]: Like you definitely have to be up there and you have to be competing so that people know that, oh, this is definitely one of the top. Because this is only one dimension of what customers look for. There's other things like how many can you spin up consecutively? There's a feature set, there's support, there's like all different things that people look at, but you definitely have to be there, on the benchmarks.Swyx [00:16:40]: How many people do people spin up consecutively?Ivan [00:16:43]: So we have.Swyx [00:16:43]: Or concurrently, is the Concurrency, right?Ivan [00:16:45]: There's three metrics that we look at. And so one is like time to spin up one, and so our time to spin up one is 60 milliseconds with network latency. So request, spin up, reply, 60, the whole thing, 60 milliseconds. That is one. But if you wanna spin up 50,000 at once, we are now at about 75 seconds. So it takes about 75 seconds to spin up concurrently 50,000. Some others, there's public data around this, like take 2,000 seconds, which is 30 minutes. Like there's different variations of that. And then there is the so it is speed of one, speed of like multiple, and then how many can you consistently have up and running. And so we basically have right now no limit to how much we can add because we basically own our own metal. But the biggest customer of ours does like about 850,000 every single day is sort of where they're, where they're just shy of a million every single day that they're running, we do have a request for half a million concurrent, which is literally half a million CPUs somewhere running. So that's an interesting.Swyx [00:17:44]: They pay by like vCPU seconds.Ivan [00:17:47]: By seconds, yeah.Swyx [00:17:47]: Or whatever. Yeah. Okay, and so and then, and the other thing is, the sleeping and the resuming, ‘cause it's all the stateful resumption of all these things, how, what kind of workload are people putting through this, right? Like how is it Do we measure by gigabytes in memory, gigabytes in storage? I don't In like network attached storage. I, what are the costly ones of, out of all these features?Workload Economics: CPU, RAM, Network, and StorageIvan [00:18:15]: The most expensive thing are CPU.Swyx [00:18:18]: Okay. Yeah, of course.Ivan [00:18:18]: The second one, yeah Then it's RAM, then it's disk. We actually don't charge.Swyx [00:18:22]: Which is snapshotting, right?Ivan [00:18:23]: No, it's actually the, snapshotting's part of it, but basically the size of your hard disk, of your machine. So do you have 10 gigabytes, do you have 20, do you have 50, do you have whatever? And then the transference of that. Right now, currently we don't charge for, network at all at Polychron.Swyx [00:18:37]: Oh, you gotta, yeah, you gotta fix.Ivan [00:18:38]: Yeah. It is very much a it's a larger and larger part of our bill, so we're working around, that part there. Obviously, that is the least, expensive, so the hard disk is the least expensive, so it's basically CPU, RAM, for us network, ‘cause we don't charge the customer, and then hard disk, is how it's split up. But there's also different types of workloads, so we basically split it up into two types of workloads in Daytona. One is what we call background agents or long-running agents. and the other is, basically RLs and evals, which I put sort of together. And so they have very different patterns of usage, and if you look at the usage of a background And I'll just name names of companies, not specifically.Background Agents vs. RL/Evals: Two Usage ShapesSwyx [00:19:21]: Yeah, open, all hands.Ivan [00:19:23]: Yeah. So like a background agent's a Cognition, a Lovable, a like all these things are Harvey. These are all long-running, background agents. And so if you look at their usage patterns, their usage patterns are similar to human, which is like follow the sun. Basically, the usage patterns of that is like noon is probably the highest, and the midnight is the lowest, and then weekends are lower. weekday is higher.Swyx [00:19:42]: Yeah, that's a fun question. How global is it? Is it very US-centric or?Ivan [00:19:46]: The US is a large part, but we have currently, we have Asia, Europe, and the US regions.Swyx [00:19:52]: So it's quite global.Ivan [00:19:53]: Yeah, it's quite global. We have it all over. It's interesting that our I talked to you a bit about this. Our number one city by user.Swyx [00:20:01]: Hmm.Ivan [00:20:02]: Is Singapore.Swyx [00:20:04]: Oh, wow. Amazing.Ivan [00:20:05]: Which is an interesting one, right? Not by revenue, just by just like by individual head count.Swyx [00:20:09]: Really?Ivan [00:20:09]: Just like an interesting thing.Swyx [00:20:10]: Singapore is, Singapore is weirdly high in the adoption charts of AI for the population. It's like an, seven, eight million population. And it's like keeps showing up.Ivan [00:20:20]: No, it's quite interesting. We were quite shocked, and I was like, “Oh, this is interesting.” And also one that's up there.Swyx [00:20:24]: There's a reason I'm doing AI using Singapore. it's because I'm from there.Ivan [00:20:27]: We're there. We're gonna, we're gonna be there as well. and it's interesting that Japan is in the top or like Tokyo's in the top, which is in all the tech cycles it has never been. It has never been, so it's quite interesting that they're.Swyx [00:20:39]: I think the Japanese just love AI. Yeah. It's that, and then it's Brazil. That's it.Ivan [00:20:44]: Brazil has always been in.Swyx [00:20:45]: I think.Ivan [00:20:46]: Even when I look, if you look at like GitHub's data and ask historically with CodeAnywhere, it was always like US, Western Europe, and then you'd have like India, Brazil, China, like that would be there. But like Singapore was not in, specifically Japan was never in sort of that top, that top.Swyx [00:21:01]: Yeah. Weird pockets.Ivan [00:21:01]: Weird. Yeah, so it's very global.Swyx [00:21:02]: Okay, so actually that, but that's helps you to distribute your load through, all time?Ivan [00:21:08]: The interesting thing is like we have those kind of loads, but if you look at the researcher loads, they're quite different. So what they are is like if you give them concurrency of 10,000 or 50,000 or 100,000 CPUs at ARMb, when they fire off a run, it's just 100%. And then it just runs, and then it stops. So it's very, the usage pattern is squares basically, right? And it's also not follow the sun, because people will fire it off at midnight before they go to sleep but then wake up and so it's very unpredictable, so you don't know where that is. So the shapes of the usage are quite different than we have had before. And also what's interesting is when it's sort of a follow the sun, even if you have a high growth company, you can sort of predict your usage patterns and have enough capacity for that, because it's sort of, it grows in a, in a way you can project. When you have companies doing sort of like evals and RL, they're super spiky. So they're gonna come in, it's like, “We're gonna use nothing, then can we have 100,000?” Right? And then go back down. And then 100,000, go back down. So it's very different, right? And.Swyx [00:22:09]: Do you want to lock them into commits so.Ivan [00:22:11]: Yeah, we do.Swyx [00:22:12]: Yeah, okay.Ivan [00:22:12]: We so we have to lock them into some sort of commits to have that capacity, because we have to have, basically we have to have the capacity for peak. Right? And so right now, Daytona's mean utilization is 15%, 1-5.Swyx [00:22:25]: Oh my God.Ivan [00:22:26]: So it's very low.Swyx [00:22:27]: Because it's very spiky.Ivan [00:22:27]: It's very spiky, but we get up to 90%. so we have these things. And so what we're, what we're looking at right now as a company is similar to Cloudflare where you can like geo move things around, but that works really well for basically the background agent where it's follow the sun. But this, it's not. Like it's a very different shape. Obviously with scale you figure these things out, but that's an interesting new problem that we have, as a compute provider in the agent space. And when we were doing the conference recently, and so we talked to like Nikita from Neon and.Swyx [00:22:57]: I should bring it up.Ivan [00:22:58]: Parag from Parallel and whatnot, everyone has the same problem. Whereas the usage is super spiky, and this is something that has not happened before, that you have these types of like it was always, it the amplitudes were not this high, right? So it's quite interesting use case and problem solve.Compute Conference and Spiky Agent InfrastructureSwyx [00:23:12]: Yeah, I don't know if we're gonna bring this up again, but let's just talk about the conference, you had like 1,000 something people at the Warriors game, at the Sorry, where is it? What's.Ivan [00:23:22]: Chase Center.Swyx [00:23:23]: Chase Center.Ivan [00:23:23]: Chase Center.Swyx [00:23:24]: I went. It was, it was very impressive. Obviously, you can, how to throw a conference, what did you learn? you put, you pulled together all these impressive names.Ivan [00:23:33]: What I.Swyx [00:23:34]: What were you looking for?Ivan [00:23:35]: My thesis behind the Compute Conference was let's bring together people that are building infrastructure for AI agents. Because when I think of what we're building, it is the agent is the primary user, what are the ergonomics and usage patterns of agents, and so we can do that. And what I found, this was a theory, it wasn't proven, is that we all have these problems, as I touched onto. And I was, as I was talking on stage, it was like we all have the same underlying infra problems, which is this spiky workloads, unpredictable workloads that we've never had before, in human, compute or human infrastructure. And it's, again, it's the same when I was talking to Parag or when I was talking.Swyx [00:24:20]: Lynn. Nikita.Ivan [00:24:21]: Lynn, Nikita. Lynn especially, I was talking to her the other day as well. Like the It is a very interesting type of problem to solve because I can touch on Cloudflare because there's a lot of like talk about that recently as to how they solve that, which is they have a bunch of geos, and basically, as users work in different places, and depending on your tier, they can move you around the geos. And so that how, that's how they get the higher utilization. But you can sort of predict these, and it's If it's something in You'll rarely get a spike that is 10 orders of magnitude. Like you'll get a like let's say one of your customers has some like an exponential curve. What is that to I'm using Cloudflare as an example. 10%, 20%, whatever it is. I don't, I don't have this data, I'm just assessing. It's surely not 10x, right? It's surely not something there. And so how do you go out and solve this problem? And we're all solving this in different ways. So we have.Swyx [00:25:11]: She also has the same thing.Ivan [00:25:12]: Yeah, I know specifically that like Neon had that issue as well. Like how are we solving these spiky loads and things like that ‘cause we talked about it. And so the interesting thing for me to actually internalize was, yes, everyone that's building for agents first is going through this, and we're all solving similar problems, which is quite.Swyx [00:25:28]: Let me let me double-click on this. Okay. So for example, Neon, I happen to know that they're very sort of S3 oriented, right? so they're just like fully bet on S3. And you get to benefit from S3's distribution and infrastructure. So I would imagine that Neon doesn't have to care, whereas Lynn maybe has to care a bit more because obviously she's doing GPU inference. And, for listeners, we did an episode with her, one and a half years ago. And you have to care. But like, right?Ivan [00:25:54]: Parag cares for sure, and Nikita.Swyx [00:25:58]: And Parag is C of, Parallel.Ivan [00:25:59]: Parallel, yeah.Swyx [00:26:00]: Former CTO of Twitter.Ivan [00:26:01]: Twitter, yeah.Swyx [00:26:02]: They are the search.Ivan [00:26:03]: Yeah, they're search, yeah.Swyx [00:26:03]: I You and I know but the listeners don't know.Ivan [00:26:08]: Yeah, we can put it down in the screen, and so ‘cause we, when we were talking.Swyx [00:26:11]: I'll put it up on the, on the screen.Ivan [00:26:12]: Yeah, right.Swyx [00:26:12]: People can look it up if they need.Ivan [00:26:14]: Look it up. And, yes, but they still have CPU and RAM, allocation that you have to have up and running. And so CPU and RAM, you have to allocate that and have that ready. And so there's basically two ways to do it. One is you either over-provision and you can handle the bursts, or two, you basically have, I don't know if this is a term, just-in-time compute, which is like as your load becomes, as your usage comes in, you can fire off requests for VMs or bare metals at other cloud providers and then get them up and running.Swyx [00:26:43]: This is if you go above 100%, right?Ivan [00:26:45]: Yeah, this is.Swyx [00:26:46]: Like your overflow.Ivan [00:26:46]: If your overflow, like spillage or whatever you do.Swyx [00:26:48]: You probably lose money on it, but it doesn't matter, right?Ivan [00:26:50]: It, not Well, you might, you might not That is a more cost-effective way to do it but it's a slower way to do it. Because basically what you have to do is you have to like queue your requests, spin up these just-in-time compute, get it all ready, provision it, and then get your workload there. And so if the time isn't important that much, that's fine, and you can do that. But if your customer, and especially for, let's say, the RL training runs, the reason why a lot of people come to us is because GPUs are more expensive than CPUs, right? So you want your GPU running at, what, 100% the entire time. And so when you're running runs on CPUs, when the when the CPU cycle is like down and spinning up the next one, you want that to be instantaneous so that your GPU doesn't go down, right? And if you then have to like go out and provision machines, you're essentially telling the GPU that it has to wait, and that's incurring our cost. So there's things that you have to try to solve for there.RL Workloads, Declarative Images, and Kubernetes ReplacementSwyx [00:27:43]: Yeah, let's talk about the different workload, right? You said that, what was it? A few months ago, you had zero RL workload and now it's 50%.Ivan [00:27:52]: It will be this one, 50%, yeah.Swyx [00:27:54]: Let's talk about how different it is, right? Like I imagine, for example, a lot less dynamic code generation of like arbitrary code. Like here, it's probably all the same code. You're just doing parallel runs or something, I don't know.Ivan [00:28:05]: Yeah. So you'll have multiple Depends on the like for each run, you'll have a snapshot. And they, for the most part, they actually do use our declarative image builder, which is like, “Oh, we, the agent wants these dependencies, these env vars.”Swyx [00:28:17]: These ones, yeah.Ivan [00:28:18]: Yeah, the declarative image builder, it.Swyx [00:28:20]: Which is a very modal like thing that they.Ivan [00:28:22]: Yeah. And so we build it on the fly and then we propagate that snapshot, and you can spin up as many sandboxes as you want against that snapshot. And then if you have to do changes, the model can, or like it could be also be automated. It's like, “Oh, now for the next run, we need to install these things or remove these things or whatever to get, a task done,” and then it goes off and runs that. So yes, that is something that it seems that they prefer. The number one reason I found, or should I say, let's take a step back. What we are competing against in that environment is essentially managed Kubernetes. So EKS, GKE, whatever. That is what the vast majority run on. And anyone that has tried Daytona versus GKE, EKS is like, “I'm never going back.” That has always been. There's a few reasons. One is the ergonomics. So if you have, if you're using Kubernetes to spin that up, you have to essentially manage the interface interactions with that. Daytona, although as a compute provider, it's more akin to a Twilio and Stripe from a consumption perspective than it is an AWS. Like you have an API, an SDK, it's quite like easy and seamless to get these things up and running, that's one. The other is the speed to which we spin up, which we mentioned earlier, which is much faster, and the scale to which we can go to. We haven't got into features, but an interesting feature is that it's very hard to OOM, or out of memory, our sandboxes, because we can dynamically on the fly.Swyx [00:29:48]: Resize.Ivan [00:29:49]: Resize, which is like impossible on almost any other thing. There are some technologies that enable you to do that, but it's like a very hard thing. And so we actually saw this when, the Terminal Revenge team is, brought us actually. So thank you, Alex and the team, that brought us into this whole space.Swyx [00:30:05]: It's just very rare that, a framework would just say, “Guys, just use Daytona.”Ivan [00:30:11]: Yeah, I think it says it somewhere. Yeah.Swyx [00:30:13]: Yeah. I was like, “What is this?”Ivan [00:30:15]: There's all, there's multiple there, but they also mention a few other places. and so Daytona specifically-We have, the, just jumping on themes here We, I don't know where it says Data Center.Swyx [00:30:27]: I, there.Ivan [00:30:27]: Doesn't matter.Swyx [00:30:28]: There's a very strong recommendation, which is, very unusual. Which is, it's.Ivan [00:30:33]: We do not pay them for this, just.Swyx [00:30:34]: I know, yeah. They just like you.Ivan [00:30:35]: Yeah, they like us. yeah, and also a thing, so, Data Center has multiple isolation sets underneath. The customer doesn't have to know what they are. But basically we have Docker, which is a container, that's hardened with Sysbox. So it's Docker's, isolation that is a security equivalent to a VM, but it's still a container. And that is the default, and they, especially in these training workloads, really like that as an interface to be able to use just a basic Docker container, and we enable Docker and Docker. Which for these RL runs, if you need to do a Docker compose or Kubernetes, you can spin up a K3S inside of these things, which unlocks a huge amount of workloads that you can do that you cannot do on other providers. So just on that part is much more interesting. And so we went that, through that. We showed them that we could do that, and they enjoyed that quite a bit. They being the general venture people.Swyx [00:31:28]: Those people, yeah.Ivan [00:31:29]: And Harbor people.Swyx [00:31:29]: Harbor people, do are they, are they a company yet?Ivan [00:31:33]: As far, I do not know.Customer Pull, Slack Connect, and the Computer Use BetSwyx [00:31:35]: Okay. All right. Yeah. It's like super obvious that like, there's a lot of excitement and success around these things, okay, so yeah, tell us more, right? Like, this is an exploding workload, Harbor adopted you, which helped speed things along. But what are you learning as this new workload comes online?Ivan [00:31:53]: There's a couple things that we learned, which we chat about in the beginning. We, and this has led our story, as we mentioned, we like talked to a lot of customers along the way, and we add more features and more tool sets as we talk to customers. And it's interesting that And I think it's that the ecosystem is so small and/or the models get smarter, where when we see one user come with a request, we know it goes on a roadmap if like three to five customers come with the same request in that week. It's like very bizarre. It happens so many times, which is.Swyx [00:32:27]: Because they're all friends.Ivan [00:32:28]: Sorry?Swyx [00:32:28]: They all, they're all friends. They're all in the same group chat.Ivan [00:32:30]: Yeah, probably, yeah. ‘Cause and they're like, “Oh, can you do this?” And I'm like, “Okay, this is interesting. We'll put it on a feature request.” And then the next one's like, “Oh, can you do this?” “Okay.” It's all the same, right? It's always the same. And so what we try to do, and I personally try to do, I try to be on as many call, quote-unquote “sales calls” I can. I'm in every Slack channel. We literally have about 1,000 Slack Connect channels, something like that. It's an interesting, there's so many interesting things you find out when you have all the Slack channels. You can also see where people, transfer between companies. You see leave Slack channel, enter Slack channel. It's an interesting thing. Also, just I digress, I feel that Slack Connect is literally LinkedIn what it should be. You have a list.Swyx [00:33:08]: LinkedIn charges you to, use your own connections, but Slack doesn't, right? Slack is like, do it for free. It's more lock-in. It's great.Ivan [00:33:15]: Yeah. It's amazing. Yeah. It's one of the reasons.Swyx [00:33:17]: You're gonna pay Slack for life.Ivan [00:33:18]: Exactly. You're there for life. So that's interesting. And so one of the things, the newer things we were talking about earlier is we made a big bet and put a lot of investment on computer use. that is not seen publicly the light of day. We haven't GA'd that yet, but we have.Swyx [00:33:32]: Is there a thing I can pull up?Ivan [00:33:33]: There is computer use there. It's right up a bit.Swyx [00:33:36]: Oh, yeah. Okay.Ivan [00:33:38]: What we have, what we talked about and what we've seen publicly is there's this theme now about, the human emulator where And Elon from XAI has talked about this publicly, and if you think about the models today, they're actually quite sophisticated and they can do a lot of work, but they still don't have access to all the tools. Like, I'm a strong believer that the most efficient way for an agent to work is essentially headless or through, terminal or whatnot. But if we, if we look at knowledge work in general, there's about 100 million knowledge workers in the US, about a billion in the world, and knowledge workers, and the salaries of them aggregate to 10 trillion in the US 50 trillion worldwide.Swyx [00:34:24]: Wow.Ivan [00:34:25]: Something like that. And if we look at, the five most important sectors of that, so like healthcare and government and financial services and whatnot, that's about 56% of that. So let's say it's about half of that. So in the US it's about 25 trillion, and most of them, most of that work is actually still locked into legacy apps inside of Windows, which is not going anywhere for a very long time. Like, people just won't invest in that. How much of it? our assumption is the following: if, in the RPA market, which is similar market, well, not the same 25% of, these white collar, workers', work is automated. If an agent is more sophisticated, can go through more runs, figure stuff out, let's say it's, 40%, right? And so if you take 40% of that, you get to essentially, $10 trillion a year.Swyx [00:35:17]: That's a TAM.Ivan [00:35:18]: That is a that is a TAM. So that's the TAM of the models, right? That's not our, essentially ours. But you get to that size, and to be able to do that, you essentially have to give agents these computers with the legacy. So computer use, either Mac or Windows or Linux. Linux we also obviously have and others have. But Windows specifically is something very new, and the only option right now is an EC2 with, Windows or on Azure. Both of them take anywhere from three to five minutes to spin up. We've created an actual sandbox, so it's a second instead of milliseconds, but you have, point in time snapshots, you have, forking, you have all the things that you have from a sandbox, but essentially enables you to hopefully unlock all this value. And so that's been our big push and bet, but we've sort of, kept our ear to the ground. What is sort of the next things in the market?RPA Returns: Why Agents Still Need ComputersSwyx [00:36:06]: Yeah, knowledge work, and building, and sort of RPA, the next wave of RPA. I got very excited about RPA kind of during COVID times. The UI path was IPO-ing. And it was, a very hot Isn't it, Eastern European?Ivan [00:36:20]: It is, Romanian.Swyx [00:36:21]: Romanian?Yeah, it might be the only Romanian, big unicorn okay, yeah. This I don't I don't, I don't have like a I think there's, I think there's a stage being set for the resurgence of RPA, ‘cause everyone understands that, yeah, no one wants to deal with these shitty apps and no one's gonna rewrite them. Like, you just have to do, a remote operation and programmatic operation of them.Ivan [00:36:45]: If you wanna unlock it, my own setup was basically the following. So I was doing a board deck recently, last month, whatever, and I'm like, “Okay, let's just, let's just do automated.” So, all our data's in, ClickHouse and PostHog and QuickBooks, where everyone else's is, and I'm basically, connected that all to, my Cloud code, like go off and go Cloud code whatever. Go off and, here's the integrations, go do that. It pulled out the first report, which was great. It connected to Brex and all these things, pulled it, which was great, and then I say, “Okay, now pull out this, and this,” and I kept getting, really well McKinsey-style design reports, but the data said partial data. all the missing data, partial data. Like, it can't access all the things, and I got so frustrated, and so I got, I got, my Mac Mini virtual sandbox with OpenClaw. I gave it its own account in our company, and then I went to all these services and created a read-only account, so literally like an intern in your company. And so I would say, “Now go and do this report,” and it would get the same, or like, “I can't via the MCP or the API or whatever. I can't get all the information.” I'm like, “Go log in.” And it will log into the website, then go in, export the data. It'll export the data and do the thing end to end. So even for things that have today APIs, not all of it is exposed, and I to get value, I get immense value right now, but it has to be a computer usage, unfortunately, and so I spend a bunch of tokens just on that, but I get the job done. And so if even a startup like ours, and using all the hottest tools, still needs a computer agent what hope does, Goldman have to have a headless, right?Swyx [00:38:22]: Yeah, what a - Why isn't Microsoft doing this?Ivan [00:38:27]: I'm pretty sure, Satya had a post yesterday.Swyx [00:38:29]: Oh, okay. I see.Ivan [00:38:29]: Which was like, “Every agent needs a computer.”Swyx [00:38:31]: I see, I see.Ivan [00:38:32]: So they have launched something recently.Swyx [00:38:34]: Yeah, they have Microsoft Power Automate, I'm sure, I'm sure, they're gonna have their version.macOS Sandboxes, Apple Constraints, and the Windows OpportunityIvan [00:38:39]: Version of that, yeah.Swyx [00:38:39]: You're gonna try to do yours, and it - I always know there's always demand for Mac, but I know it's, tricky to host, macOS sandboxes.Ivan [00:38:49]: We will have macOS sandboxes fairly soon. The problem with macOS, OS sandboxes is, I'm deep in this, I don't know how much interesting is.Swyx [00:38:55]: No, it's.Ivan [00:38:56]: MacOS has this problem.Swyx [00:38:57]: It's a licensing thing, right?Ivan [00:38:58]: Licensing thing. So one, you're allowed to run only two parallel VMs per machine, so that's one. Two, you can only license to a different user every 24 hours. So if you come in and theoretically, if I wanna charge you per second and I charge you one second, I have to have it idle for the rest of the day. I can't have anyone else doing that. So the pricing will be different in the sense that I will have to - we would have to charge for 24 hours, and that's not even, that's not even the most difficult thing. But the, thing above that is, from a security perspective, they enable you to do memory snapshot, pause, resume, but only on the same physical drive, physical machine. And so what you can do in, Windows world or Linux world is that I can move in the background, your snapshot from one to the other and manage load, right? Here, if you wanna do that, you essentially have to have your.Swyx [00:39:49]: Yeah, snapshots. Yeah.Ivan [00:39:50]: Your.Swyx [00:39:51]: It's like.Ivan [00:39:51]: Physical machine.Swyx [00:39:52]: You can't break it up.Ivan [00:39:53]: You can't, you can't move things around that, and all of that is, that part is, from a security standpoint, if it is written. Like, I understand the security aspect of that, but it disables you from doing these agentic, like really scalable agentic workloads.Swyx [00:40:08]: You need to do a vibe-coded, clean room implementation on macOS that you can then - That's like Clean OS or something. I don't know.Ivan [00:40:17]: So. We have.Swyx [00:40:18]: ‘cause like Linux was originally like a clean room rewrite of Unix.Ivan [00:40:21]: Okay. Yeah.Swyx [00:40:21]: Or something like that, right? Like same thing to macOS. Someone needs to do it.Ivan [00:40:25]: Someone will do that, and someone will have some long-running agents for a few days to figure this stuff out. But yeah. So definitely we - we're really close to offering something ‘cause people do want it, but the pricing will be different, and the feature set will be sort of stringent.Swyx [00:40:38]: Yeah, nobody's gonna use this. like, the labs, the labs will because they want to automate macOS.Ivan [00:40:42]: They have to do RL. They have to do RL again. But even if you The - So the point is with the RL part, if you, if you do RL on macOS, then the next iteration of the model comes out, it will be able to use these tools significantly. Then you actually need to run those, that somewhere. So you're gonna have to have that, later on. And from, if anyone at Apple is listening, I very much feel that they are shooting themselves in the foot of the scale of the revenue of compute or licensing they could get if they would just enable a concurrency model similar to what you can get on a Windows and a, and Linux.Swyx [00:41:17]: Yeah. Yeah. And I'm sure they've heard this before. They just don't care. Yeah, it's And maybe they will change their mind with the new CEO.Ivan [00:41:24]: Yeah. We'll see.Swyx [00:41:25]: We'll see.Ivan [00:41:25]: High hopes.Swyx [00:41:26]: High hopes.Ivan [00:41:26]: High hopes.Swyx [00:41:27]: Okay. But I, it's very clear the market opportunity is huge in Windows, and you can go for a long time on just Windows, but your customers are gonna want both. and I think, it is interesting to me that, this is the sort of God application of agents, right? Like, I don't It was - How big was OpenClaw for you guys? Like, was it, was there, a significant bump.OpenClaw, Agent Labs, and the B2B2C Sandbox MarketIvan [00:41:54]: Not for us because we.Swyx [00:41:54]: Because you already.Ivan [00:41:55]: We're kind of positioned differently. Whereas although it's completely PLG and we have individual developers that use it, most of the users that use Daytona are sort of a B2B2C. Sort of it's either B2B or B2B2C. So, in the researcher world, it's B2B, so you're selling to, labs and neo labs and things like that. But on the long-running agents, it's mostly, from a scale revenue perspective, it's mostly B2B2C, where you have a app layer agent that uses you at a big scale.Swyx [00:42:26]: Like a Manus. Yeah.Ivan [00:42:28]: Like a Manus Lovable type of thing.Swyx [00:42:31]: Yeah. I think that's the question of, well how, um-Uh, yeah, B2B to C is basically to me what I've been calling an agent lab, which is kind of like you're not in a model lab, but you're making a very good wrapper that is a platform that other people can sign up so they don't have to code those things. Yeah, it sound, it sounds like a much better market than the direct OpenClaw market.Ivan [00:42:56]: I've like - We I've done multiple things. So the CodeAnywhere's part of our career path R in the calendar, was very much an end user developer product. And so that is great. It You can get a lot of developer love, and I feel that we do as a company have a bunch of developer love. But it's a different type, where it's people building these things. Again, it's more akin to a Twilio because you don't really run - As a person, you wouldn't run Twilio. I don't know how many people remember. It was like ask your developer billboard and whatnot. And people really love Twilio, but they only used it inside of like, “Oh, I'm building this app or service for thing.” And so we're very much directly to that. And you also know that I used to work for a competitor for Twilio, so it's kind of ingrained, in my DNA.Swyx [00:43:35]: People don't know InfoBip is that big.Ivan [00:43:38]: Yeah, it's.Swyx [00:43:39]: Because.Ivan [00:43:40]: It's a billion euro.Swyx [00:43:40]: They're all American. They're like, “Whatever's in Europe doesn't matter to me.” But like it's the, it's the same size or bigger? Same size?Ivan [00:43:46]: It's about half the size.Swyx [00:43:47]: Half the size?Ivan [00:43:48]: Yeah, about half the size.Swyx [00:43:48]: It's like, yeah.Ivan [00:43:48]: Still huge. Multiple billions a year. Yes.Swyx [00:43:51]: That's crazy.Ivan [00:43:51]: Exactly, and so that - These are like really interesting and large revenue-generating, very sticky businesses. Whereas when you're selling to the - When your focus is the end developer, it is a very hard sell because they're very price sensitive, very price conscious, very around that. And there's very It's very hard to scale. Your cap is the number of people that are willing to spin up - First of all, wanna spin that up, and then spin up multiple of these. Whereas if you're in the enterprise one, like we know everyone's talking about like how many tokens they're spending, I'm spending. Like a lot of companies today are like, “If this is our company, spend as much as you can.” Like basically that is where we're going. And so if you think about that paradigm, where you're selling to companies that say, “Spend as much as you can to generate, productivity,” versus, “Oh, I'm a single person. I have this much budget, and I'm doing this thing because it's fun or it's helping me out or whatever.” Like it is a different, it's a different go-to-market, I think, strategy.MCP, CLIs, and Sandboxes as the Agent RuntimeSwyx [00:44:50]: Yeah, there's a lot of discussion. I'm just kind of going through like the mental list of things that are in your favor, which is, for example, MCP versus CLI. Like obviously you want CLI. It's been very good for you. I feel like it's maybe a drop in the bucket or maybe it's huge. I'm just checking whether it's like these are big trends.Ivan [00:45:10]: Those things you - work well in our favor, to your point just because every.Swyx [00:45:13]: They're kind of drop in the bucket, right?Ivan [00:45:15]: I think it's like sort of all the things come together. And so there's so many things that impact that. To your point, like OpenClaw wasn't huge for us, but like having the agent SDK, from Anthropic, so or Cloud Claude Code was very interesting. The reason why it was interesting is that a lot of, let's call them app I don't know what to call them, app layer agent companies, essentially they are like, “Oh, I can create this new app, this new agent. All I need, I just use Claude Code, and I throw it into a sandbox, and then I have my interface to the human to that.” And so that enabled so many more companies to actually offer this, and then they would pull on sandbox. So that was, that was interesting. And to your point, like MCP, versus the CLI, the MCP is an interface against an API, whereas the CLI is like you can actually go do things. Like this is it. The difference between integrations and actually running scripts or data or analysis against a thing. So being able to use a CLI very well enables the agent to do more things, and it's because that people will invoke a sandbox, they'll run it in the CLI, and but it'll do anal-analysis on that data and then give you an actual result versus just, pulling data from an API source.Swyx [00:46:29]: Yeah, it's a layer of indirection basically, it's the same thing as agentic search versus RAG, which where you're.Ivan [00:46:34]: Exactly, yeah.Swyx [00:46:34]: Just like you just win whenever people put more agents into their workflow. And so like it doesn't really matter, but I'm just kinda teasing out like what else have people heard about that like it's sort of, “Oh yeah, this is another sandbox use case. Oh yeah, that's another one.” Am I, am I missing any big ones?Ivan [00:46:51]: The thing, the thing that people, which is the computer use stuff, which I think is probably the most interesting one, is, and to your point, we've talked to so many people over the last year. It's like, “Oh, like why do you need a sandbox? Why do you need this? Why this?” And to your point, it's like, “Oh, I need sandbox for this. I need sandbox for that. I need sandbox-” It's like, “Oh, I need it for every single thing.” And so basically what I, what I - and it sounds like a broken record, it's like you use a laptop every single day, right? And you are n of one. It's just you. But now imagine how And by the way, the laptop, the computer PC market, the PC market is about equal to the cloud market in total. So it's about 150, 180 billion a year. Something like that. It's about roughly the three cloud hyperscalers is about equal to like Apple, HP, Lenovo, whatever, It's a little bit less, but it's sort of like that. And now imagine And that's just like, so how big is the addressable market? What, how many people are there in the world now? What's the last data?Swyx [00:47:45]: Let's call it eight billion.Ivan [00:47:46]: Eight billion. And so let's say you can have two computer, like you have one personal and one business, whatever. Like so it's double that, right? and so that's 16 billion, right? How many agents are gonna be running in two years, in 10 years, in 100 years? Like And for every single task, they will need one of these. And so how big is that? That market is essentially quote unquote “infinite”. You will get to the point, and Dylan Patel was at the conference talking about, from SemiAnalysis, that talks usually about GPUs, was also talking about how CPUs will now be a bottleneck because it will be the constraint. You won't be able to grow, or we won't be able to have enough of these because there won't be enough CPUs to basically do.Swyx [00:48:23]: Yeah. Well, I actually had a really good podcast with Doug Oliphant, who, which was his president at SemiAnalysis, where they've basically been like, yeah, it's been a GPU shortage first, but then it's cascaded down to memory and now to CPUs.Ivan [00:48:35]: CPU, yeah.Swyx [00:48:35]: It-What's next? So networking. So, networking actually has been in shortage for a while if you're looking at, just GPU networking. But, yeah, it's really crazy the amount of computer use that's going on, yeah, cool. I, other questions are, just the one very big part is the open sourceness which you didn't have to do, your competitors don't do, like it's not, a lot of people are worried about keeping their projects open source because some competitor can just slot fork it. I don't know if there's any reflections on just being an open source company.Open Source, Trust, and Enterprise ProcurementIvan [00:49:15]: Yeah. There's a bunch. So we the original product that we did was open source.Swyx [00:49:19]: Yeah. CodeAnywhere.Ivan [00:49:20]: So doing that was actually very good for us. There's basically a saying of, What's the saying? Like, companies that are, that are doing really well, measure themselves against, free cashflow, that are kinda okay, it's EBITDA, then, it's, it goes all the way down.Swyx [00:49:36]: The worst is like GitHub stars.Ivan [00:49:37]: GitHub stars. GitHub stars are the worst, yeah. So you go all the way down to GitHub stars. And so our original one was GitHub stars. That's what we talked about, we're at the point we're talking about revenue, so we're we've gone up the stack on that. And so we started.Swyx [00:49:47]: No, profit.Ivan [00:49:48]: Yeah. We haven't, we're, we'll get there. We'll get there. But basically at that point we did stars and GitHub and it was useful, and the original variation that we did, it we split the core into its own repo and it was Apache 2.0, so very, permissive. And then we basically would bundl

Learn why Activity Monitor is the macOS tool experienced users trust first to diagnose hidden memory drains, runaway CPU usage, and behind-the-scenes energy hogs. Mastering a single built-in tool can put real-time answers and expert-level control right at your fingertips. Quick Access Methods: Spotlight, Finder, and Utilities Folder Five Main Tabs: CPU, Memory, Energy, Disk, and Network Explained Sorting and Identifying Resource-Heavy Processes in CPU Tab Understanding Percent CPU, Multi-Core Macs, and High Usage Scenarios Spotting and Managing Frozen or Runaway Apps via Activity Monitor The Importance of the Kind Column: Rosetta Support and Apple Silicon Transition Using Memory Tab and Pressure Graph to Gauge RAM Health Sorting by Memory to Find Leaky or Misbehaving Apps Energy Tab Insights: Finding Battery-Draining and Power-Hungry Apps Disk Tab: Diagnosing Read/Write Issues and Competing Background Tasks Network Tab: Tracking Data-Heavy Apps and Monitoring for Security Live Dock Icon Graphs for CPU, Network, and Disk Usage How to Force Quit or Inspect Troubled Processes in Activity Monitor Homework: Add Activity Monitor to Dock and Monitor Rosetta Apps Before Support Ends Host: Mikah Sargent Download or subscribe to Hands-On Apple at https://twit.tv/shows/hands-on-apple Want access to the ad-free audio and video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsor: outsystems.com/twit

Nvidia just reported Q1 fiscal year 2027. The numbers are extraordinary even by Nvidia's own standards. Free cash flow of $49 billion. A nearly 60% free cash flow margin. Revenue guidance implying over $300 billion for calendar year 2026, with some estimates suggesting $400 billion is possible. Next quarter alone: $91 billion in guided revenue. Vera Rubin is beginning to ship and is expected to generate $20 billion in its first six months.And then Jensen Huang said something on the earnings call that almost nobody covered.Nvidia plans to become the world's largest CPU supplier in 2026.That single claim has profound implications — for Intel, for AMD, for every investor tracking the CPU market, and for the semiconductor supply chain at large. CSI called this out as a remote possibility during their CPU market share update just weeks earlier. Now it is a public commitment from Jensen Huang himself.CSI works through the full picture in this episode. They cover Nvidia's new revenue reporting framework — the shift from a single data center segment to two sub-markets. Hyperscale covers the five major cloud providers: Amazon, Microsoft, Alphabet, Meta, and Oracle. ACIE covers AI clouds, industrial, enterprise, and sovereign data centers. This segmentation matters enormously because 80% of global IT spending is still on legacy systems. The enterprise migration to AI infrastructure is just beginning to happen at scale, and for the first time investors have direct visibility into it through Nvidia's own reporting.They also run the reverse DCF at $223 per share. The result: 20% free cash flow per share growth over five years at a 6% terminal rate gets you to today's price. That is not historically cheap for Nvidia. But it is the lowest bar the company has had to clear in years — and given that EPS grew 214% and FCF per share grew 88% in Q1 alone, clearing that bar looks more feasible than it sounds.CSI's updated position: Nvidia remains their largest personal holding. The updated baseline assumption is 50% stock price growth for 2026, revised upward from 40%. Not a prediction. A framework for thinking about what the business needs to deliver to justify current prices.What we cover:— Nvidia Q1 FY2027: $49B FCF, 60% FCF margin, EPS +214% YoY— Revenue outlook: $300B+ in 2026, $91B guided next quarter— Vera Rubin: $20B in sales expected in first six months— New reporting framework: hyperscale vs. ACIE and why it matters— The enterprise migration — 80% of global IT still on legacy systems— Jensen's CPU claim: Nvidia to be world's largest CPU supplier in 2026— Reverse DCF at $223: 20% FCF/share growth, 6% terminal rate— Why Nvidia has looked "boring" while small caps ran hundreds of percent— Updated CSI baseline: 50% stock price target revised upwardSemi Insider members get access to CSI's full DCF and reverse DCF tools, live Q&A sessions, and analysis like this as it happens. Join at chipstockinvestor.comDisclosure: Nick and Kasey have a position in Nvidia. This content is for general information only and is not individual investment advice. All investing involves risk.chipstockinvestor.com

Learn why Activity Monitor is the macOS tool experienced users trust first to diagnose hidden memory drains, runaway CPU usage, and behind-the-scenes energy hogs. Mastering a single built-in tool can put real-time answers and expert-level control right at your fingertips. Quick Access Methods: Spotlight, Finder, and Utilities Folder Five Main Tabs: CPU, Memory, Energy, Disk, and Network Explained Sorting and Identifying Resource-Heavy Processes in CPU Tab Understanding Percent CPU, Multi-Core Macs, and High Usage Scenarios Spotting and Managing Frozen or Runaway Apps via Activity Monitor The Importance of the Kind Column: Rosetta Support and Apple Silicon Transition Using Memory Tab and Pressure Graph to Gauge RAM Health Sorting by Memory to Find Leaky or Misbehaving Apps Energy Tab Insights: Finding Battery-Draining and Power-Hungry Apps Disk Tab: Diagnosing Read/Write Issues and Competing Background Tasks Network Tab: Tracking Data-Heavy Apps and Monitoring for Security Live Dock Icon Graphs for CPU, Network, and Disk Usage How to Force Quit or Inspect Troubled Processes in Activity Monitor Homework: Add Activity Monitor to Dock and Monitor Rosetta Apps Before Support Ends Host: Mikah Sargent Download or subscribe to Hands-On Apple at https://twit.tv/shows/hands-on-apple Want access to the ad-free audio and video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsor: outsystems.com/twit

Learn why Activity Monitor is the macOS tool experienced users trust first to diagnose hidden memory drains, runaway CPU usage, and behind-the-scenes energy hogs. Mastering a single built-in tool can put real-time answers and expert-level control right at your fingertips. Quick Access Methods: Spotlight, Finder, and Utilities Folder Five Main Tabs: CPU, Memory, Energy, Disk, and Network Explained Sorting and Identifying Resource-Heavy Processes in CPU Tab Understanding Percent CPU, Multi-Core Macs, and High Usage Scenarios Spotting and Managing Frozen or Runaway Apps via Activity Monitor The Importance of the Kind Column: Rosetta Support and Apple Silicon Transition Using Memory Tab and Pressure Graph to Gauge RAM Health Sorting by Memory to Find Leaky or Misbehaving Apps Energy Tab Insights: Finding Battery-Draining and Power-Hungry Apps Disk Tab: Diagnosing Read/Write Issues and Competing Background Tasks Network Tab: Tracking Data-Heavy Apps and Monitoring for Security Live Dock Icon Graphs for CPU, Network, and Disk Usage How to Force Quit or Inspect Troubled Processes in Activity Monitor Homework: Add Activity Monitor to Dock and Monitor Rosetta Apps Before Support Ends Host: Mikah Sargent Download or subscribe to Hands-On Apple at https://twit.tv/shows/hands-on-apple Want access to the ad-free audio and video and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord. Sponsor: outsystems.com/twit

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!This was recorded before Railway suffered a major GCP outage on May 19, despite being a multi-AZ, multi-zone mesh ring, with HA fiber interconnects between their Metal GCP AWS, because workload discoverability was unintentionally still tied to GCP. All has been resolved with a post-mortem.Railway did not start as an AI infrastructure company.It was founded in 2020 years before agents became the default way people thought about deploying software. Jake Cooper, formerly at Bloomberg and Uber, started Railway with a simple obsession: the activation energy to ship something to production should be near zero. Push code, get a URL, iterate. No Docker files, no Kubernetes manifests, no Ansible scripts stacked on Ansible scripts.For years, this was a slow grind. Railway spent its first 18 months hand-acquiring its first 100 users with Jake personally greeting every Discord signup on a second monitor.Today, Railway has raised $124m and is growing very fast. A 35-person team supports 3 million users, adding roughly 100,000 signups a week. Their bare metal data centers have a 3-month payback period vs. renting in the cloud, with 70% margins funding aggressive cloud bursting when needed. The servers they own have actually appreciated in value as RAM prices have climbed basically meaning the value of their hardware now exceeds the capital they've raised.From rebuilding Railway's network overlay over a weekend to moving the vast majority of workloads onto its own bare metal data centers, Jake Cooper is trying to build a new cloud for an agent-native world. In this episode, Railway's founder and “conductor” joins swyx and Alessio to unpack why the next era of software infrastructure is not just “Heroku but newer,” what agents need that humans did not, and why the old deployment loop of Git, PRs, CI/CD, and static cloud resources may be heading for a rewrite.We go deep on Railway's infrastructure stack: own-metal data centers, three-month cloud payback periods, cloud bursting, data center debt, Railpack, Nixpacks, Temporal, feature flags, Central Station, content-addressable filesystems, agent-safe production forks, and why the CLI may become more important than the canvas in an agent world. Jake also shares the founder journey behind Railway, how the company survived losing $500K/month, why it now serves millions of users with only 35 people, and why he believes the pull request is dying.We discuss:* How Railway went from a slow six-year grind to adding 100,000 users a week* How Railway thinks about agents as the next dominant software species* Why agents need version control, observability, compute, storage, and orchestration at 1000x scale* The economics of Railway's own-metal data centers and three-month payback* How Railway uses cloud bursting while scaling its own infrastructure* Why data center debt can be a better tool than venture debt for infra startups* Central Station, Railway's internal system for clustering customer feedback and incidents* Why responsible disclosure and over-communication matter for platforms* Why feature flags, progressive rollouts, and shadow traffic are essential for agents* Temporal's strengths, pain points, and why workflows matter for agents* Railpack, Nixpacks, Nix, and lazy-loaded content-addressable filesystems* Why “cattle, not pets” may change if you can clone the pets* Why Railway is building a new cloud from scratch instead of copying hyperscalers* The solo founder path, focus, writing, and how Jake thinks about company buildingRailway:* Website: https://railway.com/* X: https://x.com/RailwayJake Cooper:* LinkedIn: https://www.linkedin.com/in/thejakecooper/* X: https://x.com/JustJakeTimestamps00:00:00 Introduction: What Is Railway?00:02:07 Jake's Path to Railway00:06:13 Railway's Six-Year Growth Story00:08:52 Rebuilding the Business After the Free Tier00:11:17 Agents as the Next Software Platform00:13:29 Railway's Infrastructure Philosophy00:15:42 Bare Metal, Cloud Economics, and the Compute Crunch00:17:22 Cloud Bursting and Five-Cloud Networking00:20:20 Data Center Debt and Infra Financing00:23:31 Data Centers in Space00:25:24 What Agents Need From Infrastructure00:28:24 CLIs, Canvas, and Agent-Native UX00:35:15 Central Station, Incidents, and Responsible Disclosure00:40:30 Safe Rollouts, SRE Agents, and Production Forks00:45:00 AI SRE, Specs, Code, and Tests00:48:24 Self-Replicating Infrastructure and the New Serverless00:53:18 Heroku, Temporal, and Workflow Engines01:04:07 Railpack, Nixpacks, and Lazy-Loaded Filesystems01:06:01 Coding Agents, Token Spend, and Roadmap Acceleration01:10:56 The Pull Request Is Dying01:12:28 Feature Flags and the Agent-Era SDLC01:16:15 Cattle, Pets, and Cloning Machines01:19:29 Solo Founder Lessons01:24:12 Focus, GPUs, and Building a New Cloud01:28:20 Closing ThoughtsTranscriptAlessio [00:00:00]: Hey, everyone. Welcome to the Latent Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space.Swyx [00:00:10]: Hey, hey, hey. Today we're in the studio with Jake Cooper of Railway.Alessio [00:00:14]: Conductor of Railway.Swyx [00:00:15]: Conductor at Railway. Yeah.Alessio [00:00:16]: Choo-choo.Swyx [00:00:17]: Do you actually have that anywhere, like on your business card?Jake [00:00:20]: We call some of our volunteer moderators conductors. I don't have a business card. We're not that big yet. At some point I will. I got handed a nice business card from the Supermicro folks, and I was like, “Damn, this is pretty official.”Swyx [00:00:30]: Business cards are coming back.Jake [00:00:32]: They're cool. They're hip. The conductor thing is good. We're trying to figure out what we want to call each other internally. Some people think it's super cringe and say, “You don't need a name for people internally.” Some people want to call each other something. We still don't have a really good one.Jake [00:00:55]: We've got New Railcrews, Trainiacs. Nothing has stuck yet.Swyx [00:01:00]: I like Trainiac. Trainiac sounds good. Railwayians. For those who don't know, what is Railway? Let's give people a crisp definition up front.Jake [00:01:09]: Railway is the easiest way to ship anything. You go to the canvas, or you talk with Claude, and you say, “Deploy a Postgres instance, deploy my GitHub repository, run this code,” and you're off to the races.Swyx [00:01:22]: You've got a nice animation on the landing page.Jake [00:01:24]: Thank you. None of my work, by the way. They don't let me touch the design stuff anymore.Jake [00:01:25]: We want to make it trivially easy not just to deploy things, but to evolve applications over time. Most tooling right now stacks entropy on top of entropy: Docker, Kubernetes, Ansible scripts, and all these other things. If we can version all of your software and keep track of all the changes, then we can make it trivial to clone environments, fork into a parallel universe, get copies of production data, get copies of any services, make changes, validate them, and collapse them back in without reproducing everything across a staging environment.The Railway Origin Story: From Uber Systems to a New CloudSwyx [00:02:07]: I was looking at your background: Bloomberg, Uber. Nothing immediately stands out as, “This guy is going to found the next great platform as a service.” What prepared you for Railway?Jake [00:02:21]: It was curiosity to keep going deeper. I started out on front-end stuff, working on Wolfram Mathematica and porting it over. Then I briefly moved to Bloomberg, then toward Uber and distributed systems, taking the Jump Bikes systems and moving them to a distributed system built on top of Cadence, the pre-Temporal Temporal.Swyx [00:02:44]: Which, by the way, I'm happy to talk about, pros and cons.Jake [00:02:48]: Totally.Swyx [00:02:51]: But let's do the Railway story.Jake [00:02:52]: It has been a continual step of wanting an experience. Whether it's walking up to a bike, unlocking it, and having it work frictionlessly, or something else, the depth required to make that happen follows from the experience. A lot of the work I do, and a lot of the team does, is in service of that experience. We fundamentally don't care how deep we have to go. We will swim to the bottom of the swimming pool to get the experience.Jake [00:03:17]: I don't have a physics PhD. I did an EECS degree. It has always been about figuring out the next step: how do we get there? That's what led to starting Railway for that experience and then moving all the way to bare metal data centers. I was adding patches to the kernel this week to get the experience there because I can see how much better it can be.Swyx [00:03:49]: Other patches to the Linux kernel this week?Jake [00:03:51]: Yeah. Not upstream. Our fork.Swyx [00:03:52]: That's a flex. Railpack? No, this is different. This is the OS on top of Railpack?Jake [00:03:57]: No, this is an actual kernel patch. It's always literally: what do we have to do to get that experience? Then figure it out. Anything is figureoutable.Swyx [00:04:10]: Would you send the patch upstream, or does it not fit other use cases?Jake [00:04:13]: Maybe. We have to work out the experience internally. It has to do with the storage layer we're building for some of the agentic stuff. Maybe it'll be useful upstream, but it's deeply useful for us internally.Open Source, Forks, and Non-Deterministic VersioningSwyx [00:04:29]: You mentioned open source before. How do you think about starting from open source, and then coding agents letting you do a lot more from forks of it?Jake [00:04:38]: GitHub's original sin is that it's almost a series of broken pointers. You have this thing, then you clone it, and now you've lost the whole upstream. How do we make it trivial for people to modify really small pieces of it?Jake [00:04:51]: We think of Git in a discrete sense: I've either made a change and merged upstream, or I haven't. What would it look like if it were percentage-based, a little more non-deterministic, or a stream of changes that users traverse as a percentage rolled out in general and then rolled all the way up?Jake [00:05:13]: We have the open-source kickback program and let you deploy templates because we want to make it trivial for people to version these shards over time. It solves a large problem around authentication, authorization, and security. NPM has a way to define, “Don't take any new packages.” The ideal end state is that you roll out progressively to users with the minimum impact zone and continue rolling up. JPMorgan should probably be the last one on the patch line, for all our sakes, because our money and livelihoods are there.Jake [00:05:53]: It's okay if Johnny Vibe Coder gets a broken patch because there's so much entropy in the system that the rubber has to meet the road at some point. You have to test at varying levels.The Long Grind: First Users, Free Tier, and Making the Business WorkSwyx [00:06:13]: I wanted to pull up this glorious chart, which is your usage or number of daily signups?Jake [00:06:22]: Daily signups, I think.Swyx [00:06:24]: You started six years ago. It was a slow grind, and now you're on a rocket ship. You say, “Don't doubt your fight and don't quit.” Maybe pick out certain points that were key inflections for the company.Jake [00:06:40]: At the start, it's about getting your first 100 users, hell or high water. We had a website and a support link. The support link was the Discord channel. I had notifications on with two monitors: the monitor I was working on and the other monitor with Discord. If anybody came in, I was immediately like, “Hey, how's it going?” It was rare, so getting those first 100 users to come back was the start.Jake [00:07:14]: Then you build a consultancy factory because users want all these things. You have to go back to the board and ask, “What is the actual product offering I want to build on top of this?”Jake [00:07:28]: VCs want charts that always go up and to the right, but in reality you don't necessarily want charts that look like that. For us, there have been periods of expansion where we add features to test use cases, and periods of compaction where we ask, “If the experience we have is good, how do we make it significantly better?” Maybe we strip out features that don't fit our ICP anymore.Jake [00:07:57]: The boom from 2022 to 2023 came from the free tier. Everybody under the sun was using it.Swyx [00:08:09]: A lot of Reddit bots and Discord bots.Jake [00:08:12]: And crypto miners. When you build an open product on the internet where anybody can sign up, the internet is a horrible place with so many things. You go through periods of asking, “How do I reach as many people as possible?” Then, “How do I fit the exact use case for the people who really matter and are really excited about this specific thing?”Jake [00:08:39]: Then there was a two-year period of making the actual business work. During the free-tier era, we were losing about half a million dollars a month.Swyx [00:08:59]: On a $20 million bank account.Jake [00:09:02]: On a $20 million bank account with maybe $50,000 a month in revenue. That's a horrible business. I don't know how anybody invested. But you have to go through it and say, “We have an experience people love, but the business has to work.”Jake [00:09:17]: There are two schools of thought. You can run the horrible business all the way up with bad margins, or you can go back and make it work. We've always wanted a super lean team. We're 35 people right now. It's very small.Swyx [00:09:36]: Supporting three million already?Jake [00:09:38]: Yeah. We're adding 100,000 users a week right now, so it's growing fast. We don't want to add headcount for the sake of headcount or throw bodies at problems. We want to build systems. It's hard to build systems during expansion because you're adding things to the system because people are asking for them or things are breaking.Jake [00:10:00]: We had to cut off the free users for a little while, rebuild the business, and make sure it worked. We want to reach as many people as possible because software is important. It's become difficult to create things in the physical world, so it's important to make it easy for people to build in the virtual world and have access to creation. But there are legs to that journey.Jake [00:10:30]: You can see divots in the charts. If you follow between 2025 and 2026, it's either summer or winter. People go on holiday with family.Swyx [00:10:50]: It affects that much?Jake [00:10:51]: Yeah. It's kind of B2C and kind of B2B. People are shipping constantly, then they stop. Our activation curve now shows more people activating on weekdays because we have more business users, so it smooths out over time.Agents as the New Interface to DeploymentSwyx [00:11:17]: Was there a point where you started prioritizing AI development or agent development?Jake [00:11:24]: We've prioritized agentic as a top-of-funnel thing. Over the last six months, we've deeply prioritized agentic as a mechanism to build and deploy things because we believe the curve is so steep and that is how people will build and deploy software.Jake [00:11:42]: It almost fundamentally doesn't matter whether this is dot-com or not because we're all on the internet anyway. If agents are going to deploy a bunch of things and we hit an inference wall at some point, we'll fix those problems. The dominant species over the next 10 years is that we've moved from assembly to C to C++ to JavaScript to words. You're going to need to close that loop.Swyx [00:12:13]: When you say this is dot-com, did you mean buying the domain, or the general case?Jake [00:12:17]: I mean the dot-com era, when companies had a huge run-up because people understood the internet was important. Then they hit bottlenecks, fundamental laws of physics, math didn't work, and everybody came back down to earth. But it didn't matter because the internet became so impactful. If you operate on a long enough time horizon, you should build these things anyway because you can see where it's going.Jake [00:12:45]: That's where I think a lot of agent stuff is. You get to a point where you're running thousands of agents in parallel. What is the inference cost? What is the compute cost? How do you make that efficient? How do you coordinate all this? We have issues coordinating humans; we don't even have good tooling for that. Now we have to figure out how to get agents to coordinate, safely version changes, and know when to raise their hand for someone to intervene. Otherwise it becomes an interrupt factory.Railway's Infrastructure Thesis: Network, Compute, Storage, and MetalSwyx [00:13:19]: Let's go right into the technical side. What are the core infrastructure or architectural beliefs of Railway that allow you to do what you do?Jake [00:13:29]: The primitives matter a lot for us. We need network, compute, storage, and orchestration around it. You need control over a lot of those things. We've talked a lot about how we don't really use Kubernetes because we want higher-order control to place workloads in very specific places.Jake [00:13:48]: The reason is that you have to be very efficient with agents: memory reuse and all these other things, or you're going to massively blow up your cost structure. Being able to rack and stack your own servers and build your own metal unlocks performance and cost. Experiences where you're running 1,000 agents in parallel are not massively cost prohibitive.Jake [00:14:13]: Token use and compute use are blowing up. Over time, those things have to get a lot more efficient. You can get a lot of margin to make those experiences solid by building your own metal. That's all in service of offering a differentiated experience to as many people as humanly possible.Swyx [00:14:51]: You have a data center in Singapore.Jake [00:14:53]: Yeah. We have two in every other region now. In Singapore, we're adding a second one in Q3.Swyx [00:14:58]: What's it like? I've never built a data center. Do you go to Equinix and say, “I want some slots?”Jake [00:15:05]: Yeah. Equinix. You basically go and say, “I want power and I want a cage.” They say, “Great, here's what it's going to be.” You rent the cage for a period of time, fill it with racks and servers, and hook up internet to it. That's all the pieces.Swyx [00:15:36]: Then you handle everything else.Jake [00:15:37]: You handle everything else.Swyx [00:15:39]: What's the math versus clouds doing it for you?Jake [00:15:43]: If we rented in the cloud, our payback period when we go to metal is about three months.Swyx [00:15:50]: Which is crazy.Jake [00:15:51]: It's nuts. That's four years of depreciated hardware. You're going to see a lot of this compute crunch because hyperscalers are buying up a lot of stuff. We're working directly with OEMs, resellers, and people building these machines: Supermicro, Dell, and others.Jake [00:16:11]: Upstream, there's a bunch of supply pressure. When we raised our last round, between deploying capital for servers and now, the amount of money we've raised is less than the amount of money we have in the bank plus the value of the servers because the servers have appreciated as RAM has gone up. It's nuts how valuable hardware has become.Jake [00:16:50]: If you look at hyperscalers, they deployed around $80 billion of capital expenditures this year, and next year will be more. That's a massive infrastructure build-out. You look at that and think it's crazy that they're spending way more than the Manhattan Project. But if every person is going to run dozens or hundreds of agents in parallel, you have no conceptual idea how much compute is required to make that experience happen, even if you're deeply efficient and sharing resources. And that doesn't even count inference.Swyx [00:17:22]: How do you plan the build-out? The growth chart is so vertical. Are you usually at 100% utilization as soon as racks are live? How far ahead are you planning?Jake [00:17:33]: We still maintain cloud presence for bursting. We work with AWS, GCP, and a few other clouds. We can rent, and then the moment we get space or power, we compact those workloads off the cloud. We started on the clouds, then built a system to migrate to our own metal. There's nothing that says you can't continually do that again, and that's exactly what we do. We never want to be compute constrained.Jake [00:18:09]: At the start of the year, we actually became compute constrained because one upstream provider wasn't able to give us quota at the rate we needed, and the hardware was slower. I spent a weekend rebuilding our entire network overlay so we could straddle five clouds: Oracle, AWS, ourselves, GCP, and one other one. We can do more than that now.Jake [00:18:38]: We got into a spot where we were trying to pack instances tight because we couldn't get enough compute. That led to a few reliability issues, which are now past us. I made a tweet pointing out that it's becoming harder and harder to acquire compute at the rate these models need to acquire compute. We got bit by it.Swyx [00:19:15]: How do you think about pricing knowing you might not have your own metal available at all times? Are you pricing assuming you need extra margin if you end up going into the cloud?Jake [00:19:26]: Because we've built out our metal data centers, our margins on metal are around 70%. We can deeply subsidize the cloud business if we want to scale at a reasonable rate. We have a few levers: metal, which makes the margins; cloud burst; debt to buy servers; and venture capital. It's an interesting operational problem: how much cash do we have, how much should we raise, how quickly can we deploy it, and can we scale revenue as quickly as we scale compute?Jake [00:20:05]: If we continue making it trivially easy for people to build and deploy, then the faster we close that loop and the more operationally excellent we are with capital, the faster the business can scale. It's almost a straight linear deployment rate.Financing Infrastructure: Hardware Debt, VC, and Operational LeverageSwyx [00:20:20]: I think infra startups raising debt is a tool people don't utilize enough or know enough about. What can you tell us about that? Is it secured against your CPUs?Jake [00:20:32]: It's secured against our hardware.Swyx [00:20:37]: What rates do you get? Who are the lenders?Jake [00:20:39]: We pay prime plus a spread, and we can refinance any of the debt as rates go down. The terms are pretty good. The unfortunate thing is that Twitter has no nuance, so people say, “Venture debt bad.” But as with all things, there are specific tools and areas where you can be deliberate instead of using one tool as a hammer. Venture capital is not the hammer for everything. You have to explore and figure out what works.Swyx [00:21:12]: VC is usually the most expensive financing you can get.Jake [00:21:15]: Yeah. I also think people think about VC incorrectly from a capital-raising perspective. Most people think, “How do I raise as much money as possible from whoever is probably the best I can get at that time?” That's close to right, but what we've tried to do is figure out what unfair advantage we can buy with that equity.Jake [00:21:34]: It's the most expensive equity you're going to give away at that point in time, assuming the company keeps getting better. How do you use it to work with someone stellar who complements you? In the seed stage, I had never started a company. Ray Tonsing had good advice, and I could text him all the time. He was really fast. Awesome.Jake [00:22:01]: Then with John and Erica at Unusual, they said, “You roughly know what you're doing building a product. We'll mostly leave you alone and be available for advice.” Amazing. Then we got to Series A and the business was an operational tire fire because we didn't know how to scale a business. Work with Erica, and Jordan is over at Redpoint, so bonus.Jake [00:22:28]: Now we've raised from TQ and FPV as we're moving into enterprises. Every step of the way, we've asked: who can we partner with at this specific time to unlock the next section of the journey? I don't know enterprise sales. As an engineer, I can eyeball what features we might need, and we have wonderful people internally who can help. But you want boardroom dynamics where everyone is aligned and asking, “How do we win this?” instead of bickering about strategy.Data Centers in Space and the Physics of ComputeSwyx [00:23:31]: You had a tweet about data centers in space. Why no data centers in space?Jake [00:23:37]: It's not “no data centers in space.” My hot take is that I think it is solvable. I've just never seen anybody solve it.Swyx [00:23:49]: You said, “How are you going to dissipate that much heat in a vacuum?” You're making a physics claim.Jake [00:23:55]: I haven't seen anybody prove how you're going to dissipate that much heat in a vacuum. It doesn't mean it's not possible. It just means nobody has brought it up yet.Swyx [00:24:05]: Astrophage.Jake [00:24:06]: I don't know what that is.Swyx [00:24:07]: The Martian thing. Okay, you're very logical.Jake [00:24:09]: It could work. A lot of people are putting the cart before the horse. They say, “We're going to put data centers in space.” Okay, but how? “We have time to figure it out.” It's like in The Martian where they ask how they're going to intercept something and say, “We'll figure it out.”Swyx [00:24:36]: Making a bet on human invention is weird because you blind trust that it can be solved. But with physics, there are first-principles bounds you can put on it. Maybe not. Maybe you're asking to travel time or break a fundamental thermodynamic law.Jake [00:24:57]: I don't know how VCs do this either. How do you know what's not possible and a grift versus what's possible but sounds completely insane? “We're going to put data centers in space.” Coin flip as to which it is, and I guess you'll know in 10 years. That's one cycle.What Agents Need: Versioning, Observability, and 1,000x ScaleSwyx [00:25:23]: Moving back to agents. The branching, fast spin-up, and orchestration you do feels like pre-work that happened to be exactly what agents want. What do agents want differently than humans?Jake [00:25:37]: They want the ability to version things. It's not that different; it materializes slightly differently. Agents want a way to test changes incrementally. Engineers have feature flags. Is there a reason agents can't use feature flags? I don't think so.Jake [00:25:54]: They want version control. Can we use Git or not Git? That one is up in the air. I think something outside Git will emerge for how we version these things over time. They need observability. You need to query what happened, when it happened, which steps failed, traces, logs, metrics, and all the rest. They need network, compute, and storage. They need to write files, save files, iterate on files, and snapshot file systems.Jake [00:26:25]: A lot of what humans needed is in line with what agents need. Branching and forking are not different; we're just moving 1,000 times quicker. It can look like you need something massively different, but what you need is something massively better than what existed. You need orchestration massively better than Kubernetes. You need networking probably better than Envoy. It goes all the way down the stack.Jake [00:26:55]: If the workload profile doesn't change so much as it gets massively compressed because you need thousands of these things, what assumptions change? etcd is going to melt. You need to replace it with something. You can go all the way down the stack and say, “That part has to change, that part has to change, and that part has to change.”Jake [00:27:19]: The interesting thing about the super-exponential curve is that you have to build systems where you can rip out those parts at any time because a new bottleneck might emerge. You get good at parallel agents, and a different part of the system breaks. So it's similar to what humans needed, but at 1,000x scale.Jake [00:27:55]: How do you do code review in the age of agents?Swyx [00:28:00]: You throw more agents at it.Jake [00:28:01]: You don't. But then who reviews for CVEs and all these other things?Swyx [00:28:07]: More agents.Jake [00:28:08]: And that's how we hit the inference wall. You can continually throw agents at the problem, but I think there's a limit to the number of agents you can throw at a problem.CLI, Agent Handles, and Closing the LoopSwyx [00:28:24]: You already had a CLI before it was cool. How is the shape of what you're exposing changing, if at all?Jake [00:28:28]: CLIs have always been cool. The CLI changes because we think about how to give Claude, Codex, ChatGPT, or any model a handhold.Jake [00:28:50]: A CLI is a single command: deploy, get logs, and so on. Things that were prohibitively annoying to humans are not annoying to agents. They're nice. If I handed you a CLI with 40 arguments and 600 flags, you'd think, “I'm never going to use all of this.” But if you hand it to an agent, it says, “This is excellent. I have so many handles to work with.”Jake [00:29:24]: If you're going to expose things to agents that way, you want as many handles as possible where they can get information, query dynamic information, and close the loop quickly. Most problems right now are about how to close the loop as quickly as possible. Where does the agent get stuck, and how can you remove that?Jake [00:29:49]: Telemetry is important. If you can tell where the agent gets stuck from the CLI and say, “12% of people deviate from the happy path because of this, and now I add this argument and drive it down to 2%,” you massively increase the rate of loop closure.Jake [00:30:03]: That's how we think about not just the CLI, but every point in the dashboard. It's a user journey: I hear about Railway. I get something deployed. I get my first green build or aha moment. I see an endpoint, logs, whatever. Then I iterate. The iteration loop is indefinite. The user wants to deploy a new thing, a Postgres instance, change code, and keep iterating.Jake [00:30:36]: If you focus on the iteration loops and what's blocking them from closing quickly, one thing we say internally is: you never want to be waiting on compute anymore. You always want to be waiting on intelligence. If you're waiting on compute, there's a bottleneck that needs to be destroyed because eventually that bottleneck becomes so large that another workflow emerges to change it.Jake [00:31:04]: We've built a product where you push code, build it, and so on. But I fundamentally believe the push-pull loop is going away. We'll get to a point where you make a small change in production, that change is versioned across your infrastructure, you're working alongside copy-on-write versions of your database and infrastructure, and then you merge it in and it's instantaneously live. That's the holy grail of loops. The push-pull-rebuild thing is a point of friction that we're removing entirely.Canvas as Output: Dashboards, Context Anchors, and HyperstructuresSwyx [00:31:43]: It's incredibly fast. If anyone hasn't tried it, that fast feedback is great. My hot take is that Railway was famous for its canvas, which visualizes your infrastructure and lets you manipulate it visually. But that was for humans. For the next phase of growth, Railway CLI is more important than canvas.Jake [00:32:05]: The canvas is funny because it's a mechanism to show changes over time. You're right that previously we used it a lot as an input. Moving forward, its goal is more like an output. You would go to the canvas, make changes, see them, and watch your infrastructure evolve. Now agents have access to the CLI and can make those changes. So the canvas becomes an output: what information does the human need at this moment to make suitable decisions about control requests? Do I approve this or not?Jake [00:32:57]: It also has to be an anchor for your context, a port in the storm. Think of it like layers in a file system. You start with a project, then drill down into services, then into a function or code, because you want to represent the entire thing not just in your head, but in the canvas. Other people can share that representation, think on the same wavelength, and move quickly.Jake [00:33:33]: A lot of organizations get in trouble as they scale because all the context lives in someone's head. “How does this microservice work?” “I have no idea; go ask this person.” Then you have whole categories of products built around context discovery. A lot of that melts away if you have a solid hierarchy and can infinitely nest services, code, context, and everything else all the way down. That's what lets you build these structures over time.Jake [00:34:18]: It's also what lets us build what I've called hyperstructures: things that are way bigger. You look at the Golden Gate Bridge and ask, “How did we build that?” There's a meme that we lost the technology. To some extent, yes, because the coordination that built those things evolved and changed. We lost some of the art of building structure as we jammed everything into Slack.Swyx [00:34:52]: But you jam everything in Discord.Jake [00:34:53]: Same point. It doesn't matter. It's message passing and interrupts, message passing and interrupts.Swyx [00:35:00]: So you're arguing there should be something better and more structured than Slack?Jake [00:35:04]: Yeah. For sure. I think Slack is awful, and Discord is awful too.Central Station: Context Routing, Support, and Incident ClustersSwyx [00:35:09]: This is the equivalent of my mom test. What have you done that has your solution to this?Jake [00:35:15]: Internally, we've built a tool called Central Station that aggregates all the context from our users. Every piece of feedback, every customer support item, everything gets aggregated into clusters. If an incident is brewing, we can determine how many users are affected and break off a discussion based on that.Jake [00:35:40]: That is more helpful than long-running channels where you're trying to decide which channel to put something in. If you can dynamically aggregate information and dynamically route it to the right person based on context, it works better. We know internally that these four people are close to networking. If we see a networking thing, we can drill it down to those four people. If it's with this part, we can look at the commits. This is no longer a manual process internally.Jake [00:36:13]: If you go to station or help.railway.com, that's why we built it. We wanted to scale with a massive amount of leverage by aggregating feedback.Swyx [00:36:27]: This is built in-house?Jake [00:36:28]: Yep.Swyx [00:36:29]: I remember helping out on this one with Angelo in 2023. You scale a lot with a very small team.Jake [00:36:38]: Yeah. We're about 10 times bigger now.Swyx [00:36:40]: You have your full developer code here? Very cool.Jake [00:36:44]: If you go to railway.com/stats, we expose this as a pub-sub-able thing. It's all real-time metrics. There's a way to get it as JSON somewhere if you care.Jake [00:37:01]: We're big on trying to build everything in public and talk about what we're working on. We've had issues in the past, and we'll say, “Here's how we're fixing these things.” We've gotten compliments and flak for incident reports. We're always trying to make them better and talk with people.Incidents, Disclosure, and Progressive RolloutsSwyx [00:37:20]: You had a big one recently. I liked that it was scoped to 3,000. You presumably used Central Station. Talk through what happened and how you address it internally as a team.Jake [00:37:38]: Internally, this one really sucked. It had to do with an upstream provider that didn't do the behavior it said it documented, which is unfortunate given they wrote the RFC for how the behavior should work. We rolled those things out, and Central Station caught it initially when a couple users said caches weren't invalidating. We turned it off immediately.Jake [00:38:03]: When you roll out to a large user base of three million people, you get a lot of disparate behaviors. We tested in staging and had tests, but we hit an edge case. We've hardened those systems, and now we can make that better. But it was a tough one.Swyx [00:38:39]: I always wonder how private disclosure is supposed to work if people find an issue. Are they supposed to contact you first? When you run a platform, these things will happen. What channels should people pursue to quietly resolve it before it becomes a bigger incident?Jake [00:38:59]: There's responsible disclosure. We err on the side of over-disclosing and letting you know something is wrong versus having your provider gaslight you. We've erred on sharing those things more publicly, even if they impact a small subset of users. That's a decision we've made internally. We have four values. One is honor. The honorable thing is to notify people to the widest degree at which they may have been affected or there was an issue, and then confront it head-on: why did it happen, what can we do better?Swyx [00:39:45]: Not the whole user base. That's because of incremental rollouts and other things?Jake [00:39:50]: Yeah. Progressive rollouts.Swyx [00:39:54]: That should be the norm at all large platforms.Jake [00:39:58]: It should. A variety of companies do this. There's the quote that Meta runs 10,000 different versions of Meta. To our earlier point about agents, they need the same thing. They need shadow traffic and all these other things. We've built so much ceremony around production being sacred that we need to make it trivially easy to test different behaviors in a safe environment. Then you can make mistakes in a safe environment.Safe AI SRE: Customer Agents, Forked Environments, and Production ParityAlessio [00:40:30]: Do you see a world where these things get automatically caught, not necessarily by your agent, but by your customer's agent? The cache invalidation issue seems easy to check if you know to look for it.Jake [00:40:44]: It's hard because to determine it, we almost need to hook into your observability infrastructure. That's why we have the template loop on the platform: so you can roll things out progressively. You can roll out to Johnny Vibe Coder initially, or push a shard that someone consumes at their own leisure. Or you can roll it out over weeks: 0.1% of people, 1% of people, early adopters, then all the way up. That's the non-deterministic version control we talked about earlier.Jake [00:41:30]: I believe that's where most things should go, because most companies end up building staged rollout systems in-house. It's the same thing built again and again at every company. There's a massive opportunity to consolidate developer debt.Alessio [00:41:45]: You should have a free tier. Model providers give free tokens if you let them use the data. You could give free compute if someone is the number-one shard that goes out and lets you plug into their observability.Jake [00:41:55]: We do that. That's why we talked about the impact on 3,000 people. We start with lower-impact people. Larger companies on the platform are last to receive those rollouts so they have a version of the platform that's deeply stable.Alessio [00:42:16]: I have three services, so I'm sure I get the first rollout. You can nuke my thing at any time. There are all these SRE agent companies. Observability people also want agents that fix upstream problems. You have your own agent in the canvas now. How do you see that playing out?Jake [00:42:39]: It's the stacking entropy problem. If you don't have primitives to make iteration in production safe, it becomes difficult. If you're an observability provider saying, “Here's the fix to this error,” assume 80% are good and make sense. But in the last 20% long tail of complex issues, if you let somebody stamp it, you create an opportunity for an incident.Jake [00:43:08]: That's why forked environments are important. People have staging, but it always drifts from production. You need primitives, workflows, and experience built first-party on the platform so you can fork any service at any point in time.Jake [00:43:33]: I think of the canvas as a sheet of transparency paper. The agent is a little guy you push up into the canvas. It should say, “I need to copy that service and that service so I can test these two things.” It gets a read-only copy of production. Anything that's PII gets marked as a transform when we clone the database, create a copy-on-write version, or read from it. Then the agent makes changes and asks, “Does this actually work?” as close to production as possible.Jake [00:44:22]: That's how close you have to be, or you get massive drift. The system becomes unstable. You see this with massive systems built on Docker for local, Kubernetes for production, and a specific thing for something else. That complexity slows developers and becomes unstable at scale, making it hard to iterate. We want to compress that way down and say, “As close to prod as possible is where we want to be.”From AISRE Skeptic to Agent BelieverSwyx [00:45:00]: I was texting Erica for questions, and she says you were originally not a believer in AISRE. Have you come around on it?Jake [00:45:10]: I flipped, but I'm still not a believer in AISRE if you don't have the primitives to make it safe. If you unleash AISRE on production infrastructure without safe primitives for copying volumes and making sure things are fine, it's going to nuke your production database. It's not a matter of if, but when. I'm a big believer in making those loops safe.Jake [00:45:33]: I was a deep AI skeptic until 2023. In 2024, I thought, “Maybe I can roughly make this thing do it.” In 2025, I thought, “Now I can hold this.” Over winter break, everybody came back saying, “It's almost impossible to hold this.”Swyx [00:46:01]: Did you see this on the Claude docs? CloudBot? OpenCloud?Jake [00:46:06]: It's gotten to a point where it's harder to hold it wrong than to hold it right. There's a scene in Avengers where Vision picks up Thor's hammer and says it's terribly well-balanced. It self-balances and works well. I'm a deep believer at this point that this will be the dominant species: assembly, C, C++, JavaScript, words.Swyx [00:46:35]: It feels like a big jump.Jake [00:46:37]: It is. But it's not like you abandon CPU-based discrete logic and move straight to fuzzy logic. You need both. Your skills should call code or applications or some static structure. You can use skills to distill what the procedure should be or how the code should act.Jake [00:47:02]: I'm coming to a thesis: you need three points. You need a clear spec defining the system, the code, and the tests. When you say it out loud, if you've been in engineering long enough, you're like, “Of course. That's an RFC, tests, and code.” But they all matter. Having them together lets them reinforce each other: the spec and tests match, but the code doesn't, so reconcile it. Or the tests and code match but the spec doesn't, so reconcile that. That's the iteration loop.Jake [00:47:41]: That's why you're seeing people talk about software factories, docs, and reconciliation. Some of that is architectural astronomy if you don't implement it, but that loop is where most things will end up.Swyx [00:48:07]: For listeners, we've been talking about this on the pod for three years: the holy trinity of specs and tests. Itamar Friedman from Qodo is the reference if people want to look it up.Self-Modifying Infrastructure and the End of Push-Pull-RebuildSwyx [00:48:18]: One thing I want to mention on the OpenCloud idea is self-modification. I don't know how Railway would support it, but I have my OpenClaw, and I just tell it it has the Railway CLI and can do whatever. In theory, whatever capabilities or new infra it needs, it can call the Railway CLI, provision it, and add it to itself. The agent can modify its own infra.Jake [00:48:45]: It's nuts. I have a loop set up where you put the Railway CLI on top of something that runs on Railway. You're authenticated as whatever the current box is, and you can make any changes to it. Then you call Railway deploy, and it deploys itself.Jake [00:49:04]: It's like: “I need to spin up this instance of this environment. I already exist in this environment. Excellent, I have access to a Postgres instance now.” That's where we want to go with agentic, self-replicating infrastructure. That's your loop: iterate in production. You continue making changes. If it works, merge it upstream. If it doesn't, throw it away.Jake [00:49:37]: How do you make throwaway copies trivial to spin up and super cheap? The era of “I have an AWS instance with four vCPU and 16 gigs of RAM” is going to get destroyed. If you do that for agents, you need a thousand of those machines. It's prohibitively expensive compared with what we've spent a ton of time figuring out: the atomic unit of deploy, whether you call it isolates, sandboxes, or something else. Only pay for what you use, spin up instantaneously, and close the loop as quickly as possible.Jake [00:50:15]: If the system can self-replicate safely and say, “This is my environment, I'm making these changes,” it can come back with, “Does this look good? This is a new state of infrastructure given this prompt. I think I've solved it.” Then you go back and say, “Actually, it looks different.” It does the loop again. Then you say, “Cool. Apply.”Swyx [00:50:38]: That's retroactively obvious, which is the most useful kind. Any other comments on agent deployment on Railway?Jake [00:50:51]: It's getting better every day. I'm on X or Twitter. You can always yell at me about the parts not working as well as they should, because plenty of things should work way better.The New Serverless: Stateful, Long-Running, Pay-for-What-You-Use LinuxSwyx [00:51:04]: At this stage, when people want massively or embarrassingly parallel compute, they usually talk serverless. I feel like there's a new serverless compared to the previous five years of serverless. You're in that new bucket. Do you have comparisons or philosophical differences you want to call out?Jake [00:51:31]: It's somewhere in between. It's the ability to run stateful, long-running workflows or executions.Swyx [00:51:42]: Vercel has Fluid Compute, Cloudflare has some container thing, Google has App Runner and others.Jake [00:51:55]: That's where everything is roughly going, and it's why we've been working on this for six years. We believe users need access to a computer: a box that speaks Linux. They need to deploy what they want. Other systems change the surface area of what you can build. For us, users need a computer and need to deploy anything they truly want. That's why we've focused on the primitives: network, compute, storage. If we give you those and expose them so you can run things indefinitely, that's where we believe it's going.Jake [00:52:43]: Twitter has no nuance, so everyone says “servers” or “serverless.” It's always somewhere in the middle: I want to run it for a long time, but I don't want to provision the resource statically or pay for things I'm not using. That's been our thesis from day one: pay only for what you use, run it indefinitely, and it is full Linux.Swyx [00:53:12]: That's why I like the naming of Fluid. It's fluid. Flexible.Heroku, Focus, and Carrying the Torch Without Becoming the PastSwyx [00:53:18]: Another milestone is the Heroku official deprecation. You're one of the presumptive new Herokus. “New Heroku” has been a category for as long as I've been in developer tooling. It's finally happening. What was that like? Any behind-the-scenes of, “This is the moment”?Jake [00:53:42]: You have people where you're like, “You were running stuff on here? You, as this company?” It's crazy that names you would know are running on it and now coming to us saying, “We want to move a lot of this off.”Swyx [00:54:00]: Any behind-the-scenes on why Salesforce let Heroku stagnate?Jake [00:54:05]: I can only guess. It's hard when it's not your business. Salesforce's business is to build a great CRM. That's their focus. Then you acquire a compute business as an offshoot. A lot of early Meta people talk about focus. Boz has a write-up about how in the early days of Meta they had no money, so they were forced to focus. Then they turned on the money tree and had no reason not to split their focus.Jake [00:54:52]: But that dilutes your product. You get offshoots where you ask, “Is this the focus of the business?” If it's not core, it languishes. A lot of companies get in trouble when they split focus because they're fighting a multi-front war, not just externally but internally for alignment. Where are we going? What are we doing? What is our purpose?Jake [00:55:24]: If you're Salesforce-built and mission-driven, you want to work on Salesforce. Heroku is off to the side. It's not core to the business. Getting resources, budget, focus, and alignment internally becomes hard. It was a matter of time.Swyx [00:56:06]: Kudos for them to call it out instead of leaving it unknown.Jake [00:56:12]: Their release was a little odd. They called it out, but they didn't say they were shutting it down. Behind the scenes, I think they issued messages to people saying they should close accounts and that they were going to deprecate and remove things over time.Jake [00:56:30]: It's crazy because some of my first deployment experiences were on Heroku. You start with dragging things into an FTP server, then you try to get a deploy working, and then it's Heroku. It was the on-ramp for us. But the wheel turns. New things emerge. We're happy to carry the torch for a lot of that. But we don't want to be the new Heroku. We want to be the way people build and deploy software, and ultimately the way people monetize software over time.Swyx [00:57:19]: It's still a big crown to be the new Heroku. There are 50 companies that fought for that.Jake [00:57:23]: Everybody is holding some portion of it. We're happy to support people and companies. The platform works differently. The game loop is similar, but we've been dogmatic about where these things are going: primitives, agents, fan-out. Some things fit; some workflows need to change. We have an approximation of Heroku pipelines with the environment system. It's exciting. We've got a ton of people we can support, and it's growing a lot.Temporal, Workflow Engines, and State MachinesSwyx [00:58:12]: I have one more technical question about Temporal. I've sold my shares. You're a power user and one of our earliest customers. I met you through Temporal. You built on Temporal. You have complaints. This may be the most neutral and informed conversation anyone will hear about Temporal without someone working at the company.Jake [00:58:39]: That's fair. I've used Temporal for almost 10 years because of Cadence at Uber.Swyx [00:58:52]: Give people a sense of what Cadence was at Uber.Jake [00:58:57]: Cadence was the precursor to Temporal. It powers trip actions, rides, when you rent a Jump bike or scooter or car. You're running workflows for a period of time and saying, “This ride will run indefinitely until it finishes.” You attach information: you paused in this zone, so add this charge to the bill. When you end the trip, the workflow is done. That experience was powered by Cadence at the time.Swyx [00:59:34]: I used to say it's like programming the entire user journey top-down as one function.Jake [00:59:39]: It's a powerful idea and important. It's also important for the next phase of the agentic journey. You want an agent to do a specific task, be complete or incomplete on that task, and move on to the next thing. You need a way to manage workflows dynamically.Jake [00:59:59]: Temporal was always great in theory, and great when you got it working the way you wanted in production. But it required you to model the entire journey in your head. If you didn't, you could cause issues where replaying the state of the workflow causes non-determinism.Swyx [01:00:25]: Because it works on deterministic workflow history.Jake [01:00:28]: Exactly. I describe it as a jet engine. If you know how to operate it and run it, it's great. But you can't hand it to people trying to build complicated things if they don't have the whole state in their head.Jake [01:00:48]: We run our whole deployment pipeline on top of it. That's a reasonably complicated workflow: pre-commit hooks, signaling, queuing, and all the rest. We ran into the same thing at Uber. As you express a large workflow, it gets more complicated, with more states in the state machine that you have to map back to the workflow.Swyx [01:01:15]: It's a lot of ifs.Jake [01:01:16]: Exactly. At Uber, we built a system for doing the state machine and testing it. We've started to build some of those things here because it's grown heavily. It's not quite love-hate. When it works well, it works super well. But if someone who doesn't have full context puts something into the system that invalidates state or causes non-determinism, or spins off a ton of activities, you have to keep track of underlying SRE knobs like activity slots. Those should scale with memory, vCPU, and so on. It becomes a bear to scale.Swyx [01:02:10]: You need a capable sysadmin running things behind the scenes. If you moved off, what would you do?Jake [01:02:19]: We'd build our own workflow engine. We have a few internally that we've worked on.Swyx [01:02:27]: This is one of those classes of things you typically wouldn't vibe code, but I'm wondering if you can.Jake [01:02:33]: I still don't think you should vibe code it. You still want to run decent tests to make sure it works.Swyx [01:02:39]: Timo didn't invent that from scratch either. There are libraries you can run. On top of that, it's just a state machine that you have to map out. Ultimately, you define the instructions you want and run them through a state machine.Jake [01:03:00]: It's very doable. Workflow stuff is interesting. Restate is doing neat stuff here.Swyx [01:03:10]: You're tied into JavaScript. Are you a JavaScript maxi?Jake [01:03:13]: Internally, we have TypeScript, Rust, and Go. We don't add more languages. Actually, we have a little C because we write BPF code and hooks. But those are the languages.Swyx [01:03:28]: Is this for sidecars?Jake [01:03:32]: No. It's for the networking stack, volumes, and things like that. We use TypeScript a lot because it powers the dashboard, but we're moving a lot of workflow stuff off the dashboard stack and into the infrastructure stack.Railpack, Nixpacks, and Content-Addressable FilesystemsSwyx [01:04:00]: Cool. Any other technical infrastructure stuff? Railpacks?Jake [01:04:07]: We built an engine for determining dependencies based on source code. It's called Railpack. We built the first version, Nixpacks, on top of Nix, and then we moved.Swyx [01:04:17]: People have been trying to get me to adopt Nix and NixOS for four years. Is it ever going to be a thing?Jake [01:04:23]: I don't know. We're excited about it, but it has pain points. Think of it as a stack of versioned binaries at specific slices in time. If you want version X and version Y, you bloat the package space, which blows up image size and makes real-world workloads difficult.Swyx [01:04:53]: But you content-address it and cache it. In theory, there are optimizations.Jake [01:05:00]: In theory, yes. But with a large enough user base and disparate enough machines, you run into a problem Meta described in the XFAAS paper, their internal serverless system. It becomes difficult at scale unless you break out specific runtimes.Jake [01:05:24]: We didn't want to do that because we wanted to truly allow you to deploy anything. That was our initial thing with Nix. But we've moved toward interesting work around content-addressable file systems that can lazy-load anything from any point and page it into memory.Swyx [01:05:48]: Amazing.Jake [01:05:49]: The future is very bright. It's crazy, and it's going to be nuts.Coding Agent Spend, Roadmaps, and Token ROISwyx [01:05:54]: Founder journey stuff?Alessio [01:05:56]: Your cloud usage: you tweeted you're going to spend $300K this month?Jake [01:06:01]: I think we got to $200K.Alessio [01:06:02]: Coding agents?Jake [01:06:03]: Yeah.Swyx [01:06:04]: Across the company?Alessio [01:06:05]: You only have 35 people, so I'm sure they're not all spending $10K a month. What's the distribution?Jake [01:06:10]: I think I'm at about $25K. We have power users all the way down. We came back from winter break, and I basically said, “If you're writing code by hand, you're doing this wrong.” The tools are good enough now that you can move extremely quickly. There are issues and pain points, but you should be reviewing the code you are writing instead of writing it by hand.Jake [01:06:40]: Architectural patterns matter more now than ever, but you shouldn't spend your time generating code you would write. If you know how to write it, ask the agent to write it and reconcile it until it looks like you would have written it yourself.Jake [01:06:58]: People misconstrue my propensity to push people toward agents as connected to our growth and some reliability bumps. They're not necessarily related. The tools are good enough to move extremely quickly and build things way larger than you could before.Jake [01:07:19]: To the earlier point about cooling data centers in space: I don't know. But with software, you can ask, “How would I build block storage from scratch? How would I do these things?” I have ideas because I have history and have read papers. Let me work them out and build massive test benches with thousands of tests, because those are now free to author. If you're not using AI systems to speed-run your roadmap and reconcile your existing system onto the future, you're missing a large point of what's happening.Alessio [01:08:12]: What's the path to spending $3 million a month? Is it bound by ideas and things customers can absorb?Jake [01:08:19]: For most companies, it's bound by deployment at this point. That's why we've seen a massive boom in users and companies, from Fortune 50s down, asking how to get developers to move faster. You'll probably hit your CFO before any technical limits because they'll look at the eye-watering amount of money spent on tokens. Inference costs have to come down, but we're inference constrained now. There will be price discovery around what makes sense for an org to adopt.Jake [01:09:06]: I think you'll end up with the F1 driver concept. If someone is really adept at these things, it makes sense to put them in a $3 million car. If they're not, it probably doesn't make sense. You'll take a few people and say, “You can drive the F1 car. We need to go in this direction. Figure out if it works and prototype it.”Jake [01:09:33]: We've done some of that and vastly accelerated our roadmap. We thought we'd ship something in a few years; now we can probably ship it in a few months because we validated it and don't have to build it incrementally. We can skip steps and move toward our vision.Alessio [01:09:58]: A lot of people are realizing the roadmap doesn't always have a business impact, so they say tokens are too expensive. But if your roadmap were built to make more money by the time you built it, you'd have token pricing for it, the same way you do with sales. You'd spend a billion dollars on sales if you knew you would get $2 billion of revenue.Jake [01:10:19]: Exactly. A naive way to measure this is the percentage of tokens that end up in production. If you can measure impact because those tokens end up in production, that's awesome. But the burden of proof will rise. Internally, we have a growing number of pull requests that haven't merged. The question becomes: how do you get this into production? It's about how quickly you can build and deploy software, which is exciting because that's our whole thing.The SDLC Shift: Prompt Requests, Feature Flags, and Safe RolloutsSwyx [01:10:56]: The SDLC is changing. One thesis is that the pull request is dying. It's going to be the prompt request. Beyond that, code review is also kind of dying if you have all the other systems in place. What else is changing about the SDLC?Jake [01:11:19]: The AISRE and the tools to make it happen. AISRE is pie-in-the-sky aspirational. What does it take to get an AISRE? What tools do you need to build?Swyx [01:11:32]: You should expose your tooling to customers at some point. The Central Station command center.Jake [01:11:39]: We have it for template maintainers. Template maintainers can deploy and maintain templates, and they get feedback. We're going to expose those things incrementally.Swyx [01:11:51]: Clustering around incidents. Everyone has a version of that, but I don't think anyone has solved it.Jake [01:11:56]: I won't say we've solved it internally, but it's gotten so good that we can see incidents forming pretty quickly. At some point, those will be things either someone else builds or we build. We've always built things purpose-built for us. If it makes sense to make it useful for users, monetize it, or turn that loop into a profit center instead of a cost center, we want to do that.Jake [01:12:28]: Pull request is definitely dying.Swyx [01:12:29]: Do you do first-party feature flagging and incremental rollout stuff?Jake [01:12:34]: We have a feature-flagging engine we built internally and will eventually roll out.Swyx [01:12:38]: I don't see it as a user. How come you didn't give us what you have?Jake [01:12:43]: We have to beta test it. We care a lot about the quality of the things. There's plenty we've used internally that doesn't make it all the way through the journey because it fails. It works for one service but not multiple services. We'd have to build it for multiple services and know that if we released it, we'd rebuild it again and again. Some things are worth that, but many inform the roadmap.Jake [01:13:18]: We don't want to dilute the experience by saying, “This works, but only for this service,” unless it's a core initiative. Over the next few months, we'll roll out things that work for a single service, then multiple services, then multiple services across the environment. You have to be deliberate. Otherwise you create broken disparate experiences and support load because people ask how to use the feature.Jake [01:13:52]: It's the earlier expansion and compaction pattern. You expand the company to get features, then compact and smooth them out so the experience is stellar. You told me in the hallway, “It's gotten so much better.” Internally we're saying, “This part really sucks. We need to make it significantly better.”Swyx [01:14:11]: I can attest to that over the last three years watching you build Railway. For listeners, feature flagging is a huge part of Uber culture. So much so that they have too many feature flags and another thing to remove feature flags. Facebook has Gatekeeper. Agents are going to need this. It's fundamental to incremental rollouts. OpenAI acquired Statsig. GPT-5 is routing and flagging through different models.Jake [01:14:56]: It's super important. If the software development lifecycle is going to change because we're doing things 1,000 times faster and 1,000 times more concurrently, what becomes important at scale?Jake [01:15:16]: Before I started Railway, I built a feature-flagging product and tried to sell it. It was an easier version of LaunchDarkly. I ran into a problem: anyone small enough to adopt your technology doesn't care about feature flags, and anyone large enough to need feature flags needs so much scale that you have to build out all the infrastructure. I scrapped it.Jake [01:15:42]: But what is old is new again. Companies are trying to move quickly, but you can't YOLO a vibe-coded thing straight into production. You need to say, “Here's my blast radius, my impact, and I want to shadow it for these users.” Feature flags. You're going to need the tools larger companies built to maintain their structures. Everything gets compressed by 1,000x so everybody can build those structures quickly.Jake [01:16:07]: That's exactly where we are: compressing the software development lifecycle, then expanding it and adding more new things.Cattle, Pets, and Clonable InfrastructureSwyx [01:16:15]: Another term that comes to mind for newer developers is “cattle, not pets.” People treat production like a pet. It has a name. You baby it and keep it alive. With cattle, you can mass farm, roll out, portion parts out, and kill them.Jake [01:16:37]: I think that might change. You can move toward having pets as long as you have a cloning machine for your pets.Swyx [01:16:52]: Yeah.Jake [01:16:52]: If you can snapshot every single thing at every frame, it doesn't matter if something gets obliterated because you have a snapshot of it. The things we've built right now are designed to block changes from the hermetically sealed DevOps line. You have to write a Dockerfile because you nee

Google veut transformer Android en système de bureau dopé à Gemini, Microsoft tente de rendre Windows 11 plus réactif, OpenAI sort juridiquement gagnant face à Elon Musk mais abîmé publiquement, et l'IA continue de bousculer la cybersécurité, le travail, la musique et les infrastructures.  Me soutenir sur Patreon Me retrouver sur YouTube On discute ensemble sur Discord Presque Google IO Les Google Book, trois livres de bonheur ? Gemini Intelligence prend les commandes pour ta pomme. Toutes les délicieuses nouveautés de Cinnamon bun. Android Auto trace sa route. Windows veut passer le turbo… Sur votre CPU. Glaive et justice Bonne nouvelle pour le procès OpenAI : il est fini. Le partenariat Open AI / Apple finit en compote. Parts des anges : Anthropic brise la chaîne, Cerebras énormément de fric. We love Cox : l'érection d'un nouveau pilier législatif de la tech. Monet for nothing : X part en biais… Comme d'hab. En pratique Et sinon elle fait quoi Mira Murati ? Elle papote. Vous n'êtes pas prêt pour l'IA en entreprise ? Elles non plus. IA et cybersécurité, la MIE et la croûte. Un datacenter dans ta maison qui coûte plus que ta maison. Jeux vidéo Ahoy ! Ubisoft lance une chance au trésor qui va se finir à coup de pelle. Va-t-on arrêter de tuer les jeux en Californie ? Bientôt du FSR4 sur PS5 ?? Participants Une émission préparée par Guillaume Poggiaspalla Présenté par Guillaume Vendé

股價沉寂多時的美國科技公司輝達（Nvidia）最近連續7個交易日收紅，專家表示相對其他半導體公司，輝達現在依然便宜，有機會再漲50%。 文：樂羽嘉 製作團隊：錢玉紘、張雅媛、鄭子鴻 ＊閱讀零時差，點這看全文

What happens when stress, uncertainty, and lack of control start to take over your brain? In this episode, I sit down with renowned behavioral economist Dan Ariely to talk about resilience, learned helplessness, anxiety, and why so many people feel overwhelmed right now. Dan shares how surviving severe burns, years in the hospital, and later facing conspiracy theories and death threats shaped his understanding of stress, resilience, and human behavior. We also dive into why uncertainty at work feels so psychologically destabilizing, how scarcity and anxiety reduce our mental capacity, why humans look for villains during stressful times, and what actually helps us build resilience. Tune in to learn ways to regain agency when life feels chaotic. Check out our sponsors: Shopify - Sign up for a $1 per month trial, just go to shopify.com/anxiousachiever Chime - Head to chime.com/achiever to sign up Quince - Head to quince.com/ACHIEVER for free shipping on your order and 365-day returns Monarch - Use code ACHIEVER at monarch.com to get 50% off your first year Physician's Choice - Use code PCPODCAST10 at physicianschoice.com to get 10% off your entire order In this Episode, You Will Learn 00:00 Why starting something new can help you feel unstuck. 03:45 The mental health benefits of walking with friends. 08:35 Why invisible mental health struggles feel more isolating. 11:00 What workplaces still misunderstand about neurodiversity. 16:15 How physical limitations forced Dan to think more creatively. 19:15 Why uncertainty and unpredictability increase anxiety at work. 22:30 Why does modern life making you less resilient? 24:15 How layoffs and workplace uncertainty create learned helplessness. 29:15 The strategy performers use to stay engaged and motivated. 33:30 Why anxiety consumes your brain's “CPU.” 36:45 Why humans look for villains during stressful times. 38:15 How negative narratives reshape the way you see people. Resources + Links Get a copy of my book - The Anxious Achiever Watch the podcast on YouTube  Find more resources on our website morraam.com Follow Follow me: on LinkedIn @morraaronsmele + Instagram @morraam

Guest is Lucy Sweet, a Staff Software engineer at Uber and the lead for the Kubernetes Node Lifecycle Working Group. Imagine trying to move millions of compute cores and thousands of microservices to a brand new platform. All without dropping a single user request, ride, or delivery. Sounds like an absolute logistical nightmare, right? Well, today we are sitting down with someone who actually lived to tell the tale Lucy. In this episode, we are diving deep into Uber's monumental infrastructure journey: moving away from their in-house system to Kubernetes. We'll be unpacking the reality of running at this scale, why it's always DNS and why building things for fun is worth it. 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 Broadcom announced donating Velero to the CNCF Sandbox Level KubeCon && CloudNativeCon Amsterdam 2026 Transparency report Call for Proposals for KubeCon && CloudNativeCon North America 2026 closes May 31 OpenChoreo v1.0 CNCF Sandbox Links from the interview Lucy on Linkedin Lucy's website [Article] Migrating Uber's Compute Platform to Kubernetes [Lucy Video] Migrating 2 million CPU cores to Kubernetes Up: Portable Microservices Ready for the Cloud Peloton: Uber's Unified Resource Scheduler for Diverse Cluster Workloads Odin: Uber's Stateful Platform Uber Batch platform Apache Mesos Hyrum's Law GKE Blue-Green nodepools Node Lifecycle Working Group Scaling Infrastructure Management with Grail kubegpt.org Osquery Uber Careers  

Sara Awad from Tech Contrarians discusses semi momentum (0:40) Tech correction won't come out of nowhere; it will be forced (4:00) Nvidia earnings (6:30) Marvell and Broadcom (11:30) Micron, Credo, AMD, Intel, Arm, Apple (14:00) Nebius' sweet spot (33:30) Fundamentals over everything (36:50)Show Notes:AMD, Arm gain server CPU share at Intel's expense in Q1: UBSThe Cure For FOMO With Tech ContrariansRead our transcriptsFor full access to analyst ratings, stock and ETF quant scores, and dividend grades, subscribe to Seeking Alpha Premium at seekingalpha.com/subscriptions

Watch On YouTube Hear the full piano sample library on Spotify Download the MainStage template here Carson Bruce welcomes listeners to the Worship Keys podcast, thanks sponsor Aerospace Audio, and highlights their Atmosphere analog drone pedal (v3) with MIDI capabilities and the Aero Pads iOS app. He announces his newly released piano sample library featuring five sampled pianos and 10 patches, with both regular and felt versions, and begins a series on how to build your own sample library. He covers required equipment including a reliable computer and DAW (he tracks in Pro Tools at 96k, 32-bit float), an audio interface (Focusrite Scarlett 18i20 with eight preamps), microphones (his setups range from four to seven mics), headphones, cables, and stands. He emphasizes planning around instrument quality and room acoustics, then shows his upright piano sampling session at Miller Piano Specialists in Franklin, Tennessee on a Ritmüller upright, recording notes by fifths with multiple velocities, organizing playlists, managing CPU issues, and capturing both standard and felt samples, previewing a future episode on editing and cleanup.Aerospace AudioSupport the showThanks for listening! Subscribe here to the podcast, as well as on YouTube and other social media platforms. If you have any questions or suggestions for who you want as a featured guest in the future or a topic you want to hear, email carson@theworshipkeys.com. New episodes release every Wednesday!

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In this episode, Ben Bajarin and Jay Goldberg dive deep into the rapidly shifting landscape of semiconductor supply chains and the unexpected "CPU renaissance" driven by agentic AI. The duo explores the "ultimate constraint" currently bottlenecking the industry, breaks down the latest earnings from ARM and AMD, and analyzes why the "Neo Cloud" players might be facing a massive strategic deficit.Key Discussion Points:The Anhydrous Hydrogen Bromine Crisis: Jay reveals the "ultimate shortage" involving a rare gas essential for EUV lithography and memory production, involving a geopolitical tangle of Japanese refining and Israeli raw materials.+4The Death of the CPU-to-GPU Ratio: Why the industry is moving away from simple hardware ratios and toward rack-level topology and workload-specific modeling.+4ARM & AMD's "Agentic" Surge: Insights into how the need to execute AI-generated code is driving massive demand for high-core-count CPUs, far exceeding previous estimates.+4Optical Networking Timing: A reality check on the "hockey stick" growth for optical interconnects, which is projected to truly inflect around 2028.+1The Neo Cloud Challenge: A critical look at CoreWeave, Nebius, and Iron, focusing on their massive CPU-install-base deficit compared to hyperscalers.+2Breaking News: Late-session discussion on the rumored foundry deal between Intel and Apple.+1

This week on This Week in European Tech, Mads Jensen of SuperSeed, Lomax Ward of Outsized Ventures and Andrew J Scott of 7percent Ventures discuss Arm's AI pivot, Spotify earnings and Anthropic's explosive growth. The conversation also covers the EU's clash with Meta, ASML's semiconductor moat, UK fusion ambitions and SAP's €1 billion acquisition of Prior Labs.Key highlightsWhy AI may be shifting demand back towards CPUsAnthropic's explosive growth, cloud spending and IPO speculationThe debate around AI safety, regulation and national securityASML's semiconductor dominance and China's AI workaroundsWhy energy infrastructure and industrial policy matter for AITimestamps(00:00) Intro and this week's themes(02:00) Arm and Spotify earnings reactions(05:00) Arm's shift from licensing to AI CPUs(09:00) Agentic AI and rising CPU demand(11:00) Anthropic growth, cloud spending and valuation speculation(16:00) Enterprise AI implementation and PE-backed AI services(23:00) AI safety, regulation and national security debates(31:00) The EU's clash with Meta over AI access in WhatsApp(39:00) ASML, semiconductor infrastructure and China's catch-up efforts(46:00) UK fusion ambitions and strategic industrial policy(55:00) SAP acquires Prior Labs for €1 billionSubscribe to EUVC, the home of European tech, for more insights: https://www.eu.vc/subscribe

A inteligência artificial está deixando de ser apenas uma ferramenta de apoio para se tornar uma nova interface entre pessoas e aplicativos. E a BlaBlaCar quer fazer parte dessa transformação. No novo episódio do Podcast Canaltech, conversamos com Nicolas Salvy, CTO da BlaBlaCar sobre a integração da plataforma com o ChatGPT e o impacto que os assistentes de IA podem ter no futuro dos aplicativos. Durante o papo, o executivo explica como a empresa enxerga a evolução dos apps tradicionais para experiências mais conversacionais, em que o usuário pode simplesmente pedir uma viagem, tirar dúvidas ou resolver problemas falando naturalmente com uma IA. A conversa também aborda temas como personalização, suporte automatizado, redução de fricções na jornada do usuário, além dos desafios envolvendo alucinações de IA e confiabilidade das respostas. O episódio ainda mostra como a BlaBlaCar já utiliza inteligência artificial nos bastidores da operação, em áreas como antifraude, moderação de conteúdo, tradução automática e recomendação de viagens. Você também vai conferir: Microsoft quer deixar PCs mais rápidos usando melhor a CPU, ChatGPT começa a exibir anúncios para usuários gratuitos e scassez de RAM faz Apple retirar Macs das lojas Este podcast foi roteirizado e apresentado por Fernanda Santos e contou com reportagens de André Lourenti, João Melo e Lilian Sibila,sob coordenação de Anaísa Catucci. A trilha sonora é de Guilherme Zomer, a edição de Yuri Sousa e a arte da capa é de Erick Teixeira.See omnystudio.com/listener for privacy information.

Patrick Moorhead and Daniel Newman dig into the week's biggest moves in enterprise AI: Anthropic and OpenAI launching PE-backed enterprise JVs on the same day, Anthropic filling its compute gap with SpaceX's Colossus, Cerebris filing for a $3.5 billion IPO, NVIDIA going deep on co-packaged optics with Corning, and a full IBM Think and ServiceNow recap. Plus, for The Flip, hosts debate whether Anthropic, at $1.2 trillion, is the most important company in enterprise tech. The handpicked topics for this week are: 1. Anthropic and OpenAI Launch PE-Backed Enterprise JVs on the Same Day — Both companies announced private equity joint ventures, with OpenAI backed by Bain, Brookfield, and Advent, and Anthropic partnering with Blackstone, Goldman Sachs, Apollo, and General Atlantic. Daniel's read is that this is fundamentally a distribution play, using private equity portfolio companies as a deployment channel for AI at scale. Pat sees it as the clearest admission yet that enterprise AI cannot be self-implemented at scale without specialized consulting support, and flags that mid-tier systems integrators (SIs) could get cut out of the middle. (The Decode) 2. Anthropic Signs Massive Compute Deal with SpaceX Colossus — Anthropic urgently needed compute and SpaceX had 300 megawatts and 220,000 GPUs sitting at Colossus One in Memphis without enough business to fill them. Pat's take is blunt: this move is pragmatic. Anthropic needs it, xAI has it. Daniel adds that Dario himself said they planned for 10x growth and got 80x, and this deal is the fast backfill that reality demanded. The side note both hosts flag: Anthropic is running on H100s, H200s, and B200s, which puts the whole "Anthropic only runs on Trainium and TPUs" narrative to rest. (The Decode) 3. Cerebris Files for a $3.5 Billion IPO at $26.6 Billion Valuation — This marks their second attempt at an IPO after pulling the first filing. The architecture is genuinely unique, a complete wafer with massive on-chip SRAM and interconnects built directly onto the wafer rather than copper or photonics. Pat calls it the first credible Western alternative for AI inference. Daniel's framing cuts through: you do not have to beat NVIDIA to sell right now. You just need to have availability. The more interesting headline, both hosts agree, is that Sam Altman and Greg Brockman are angel investors, which adds fuel to the ongoing OpenAI lawsuit. (The Decode) 4. NVIDIA and Corning Announce $500 Million Optical Partnership — Three new US factories, co-packaged optics for Vera Rubin, and a supply chain strategy that mirrors what NVIDIA did with Coherent. Pat's context: this is vertical integration through investment rather than acquisition. Daniel's observation is that the pace of movement toward co-packaged optics is accelerating faster than anyone expected, and his "rule of and" applies here too. Copper is not going away. Optics are being added on top because the data volumes moving across these racks are outrunning what copper alone can handle. US manufacturing in North Carolina and Texas is a strategic bonus. (The Decode) 5. IBM Think 2026: Day Zero, Sovereign Core, and the Quantum Plus AI Bet — Pat moderated on stage with CEO Arvind Krishna and calls this IBM's best showing in five years. Arvind opened with the AI divide, the gap between companies still running POCs and companies already in production, and framed where IBM sits as day zero, not because nothing has happened, but because enterprise AI deployment at scale is still so early. Daniel's biggest takeaways: watsonX Orchestrate updates, Sovereign Core going GA with policy at runtime, and the Confluent acquisition potentially being IBM's most important asset since Red Hat, given that 40% of Fortune 500 companies run on it and real-time streaming data is foundational to agentic systems. Both hosts land on quantum plus AI as IBM's next inflection moment. (The Decode) 6. ServiceNow Knowledge 2026: Enterprise SaaS 2.0 is Emerging — Daniel got there on day three of the event and noted the conference was densely packed. His observation: enterprises have not gotten the memo from Wall Street that SaaS is supposedly dead. His emerging thesis is that middleware could make a comeback for AI, with companies needing a layer that lets agents work across any infrastructure, any app, and within the rules of their specific business. Pat agrees and adds that the growth question is about mix, not survival. (The Decode) 7. The Flip: Is Anthropic at $1.2 Trillion the Most Important Company in Enterprise Tech? — Daniel took the affirmative citing that Claude Code is deeply entrenched in developer workflows. Anthropic went from $9 billion to $45 billion ARR in months. Every major hyperscaler is both a customer and an investor. The PE JVs are turning verticals into Anthropic engines. Dario said they planned for 10x and got 80x. Pat's counter: the enterprise trust gap is real after what Anthropic pulled on pricing and performance. Microsoft has 2 billion users across 365, Azure, and Copilot. NVIDIA is the infrastructure Anthropic runs on. And workforce replacement, which is how Anthropic extracts its terminal value, is not arriving as fast as the valuation suggests. In reality, both hosts admit their notes looked almost identical. (The Flip) 8. AMD — Lisa Su guided AI data center growth up from 60% to 80%. With OpEx growing 83%, net income up 95%, free cash flow ripping, and CPUs growing at nearly 40% without price increases, Pat reads this as unit market share gains coming soon. Daniel's framing: AMD is now a two-headed juggernaut with CPUs and GPUs for the data center. And Helios has not even started shipping yet. Both hosts take a victory lap for previously calling this one. (Bulls and Bears) 9. Palantir — Triple beat on revenue, EPS, and forward guidance. Rule of 40 at 145%. Government revenue up 84%, 47 deals over $10 million, and the largest guidance raise in the company's history. Daniel's take: Palantir is redefining the category entirely. It's not a software company in the Salesforce or ServiceNow sense. It's technology, plus ontology, plus people, deployed at the deepest layers inside governments and enterprises. Pat adds that the four deployed FTE model lets them stand up AIP POCs within a week, which is why they are winning business at this pace. (Bulls and Bears) 10. ARM — AGI processor demand doubled from $1 billion to $2 billion within 45 days. Record revenue, strong pipeline, royalty growth at 21% for the full year. The stock ripped after hours, then sold the next day when management confirmed only enough supply for $1 billion of that $2 billion demand. Pat's read: 50% CPU market share with hyperscalers at the core level is the most underdiscussed signal on the call. Daniel adds that the worry about ARM competing with its own customer base in custom silicon has been quietly swept away by the sheer volume of compute demand. (Bulls and Bears) 11. Supermicro — A board member allegedly used a hairdryer to remove labels from GPU boxes being shipped to China. Approximately 20% of their revenue has reportedly been illegally shipped to China. They beat on EPS and Q4 guide but missed Q3 revenue versus consensus. Stock still ripped 18%. Daniel's take: if you are selling picks and shovels during a gold rush and you are this messed up, he cannot imagine owning it with the overhang that is building. (Bulls and Bears) 12. Lattice Semi and Coherent — Lattice revenue up 42%, back into growth, guiding to 50% year-on-year at midpoint. The AMI acquisition at $1.65 billion doubles their serviceable market from $6 billion to $12 billion and puts them inside every AI server on the planet at the BIOS and platform firmware layer. Pat calls the timing right: core financials crushing it, time to make a move. Coherent printed 21% year-on-year growth, 55% EPS growth, margins expanding, debt coming down, entered the S&P 500, and sits at the center of the co-packaged optics trend that is accelerating. Pat's choke point note: Indium phosphide capacity is the constraint. Six-inch fabs are doubling capacity in 2026, a quarter ahead of plan, and competitors are still ramping their transitions. (Bulls and Bears) Want the full breakdown from IBM Think and ServiceNow Knowledge, and check out our on-the-ground coverage linked in the show notes. Be part of our community. Hit that subscribe button and let us know what you want us to cover next week in the comments. Intro Pat on Stage at IBM Think https://x.com/PatrickMoorhead/status/2051381046537601101?s=20 The Decode OpenAI and Anthropic Both Launch PE-Backed Enterprise Services JVs on the Same Day — The Palantir FDE Model Goes Mainstream https://www.bloomberg.com/news/articles/2026-05-04/openai-finalizes-10-billion-joint-venture-with-pe-firms-to-deploy-ai https://techcrunch.com/2026/05/04/anthropic-and-openai-are-both-launching-joint-ventures-for-enterprise-ai-services/ https://www.semafor.com/article/05/04/2026/openai-anthropic-ramp-up-enterprise-push Anthropic and SpaceX Sign Massive Compute Deal — Full 300MW / 220,000 GPU Colossus 1 Memphis Data Center Plus Exploration of Multi-Gigawatt Orbital AI Compute https://www.cnbc.com/2026/05/06/anthropic-spacex-data-center-capacity.html https://www.bloomberg.com/news/articles/2026-05-06/anthropic-inks-computing-deal-with-spacex-to-meet-ai-demand https://www.tomshardware.com/tech-industry/artificial-intelligence/musks-spacex-has-rented-out-access-to-its-supercomputers-220-000-nvidia-gpus-and-300-megawatts-of-ai-compute-power-to-rival-anthropic Cerebras Files for $3.5B IPO at $26.6B Valuation — The First Major AI Chip IPO of 2026 https://www.cnbc.com/2026/05/04/cerebras-ipo-ai-chipmaker.html https://theaiinsider.tech/2026/05/06/cerebras-systems-eyes-3-5b-in-largest-tech-ipo-of-2026-on-strength-of-ai-chip-demand/ https://www.briefs.co/news/ai-chipmaker-cerebras-just-filed-for-a-3-5-billion-ipo/ NVIDIA and Corning Announce Game-Changing Optical Partnership — $500M Investment, 3 New U.S. Factories, and Co-Packaged Optics for Vera Rubin and Beyond https://www.corning.com/worldwide/en/about-us/news-events/news-releases/2026/05/nvidia-and-corning-announce-long-term-partnership-to-strengthen-us-manufacturing-for-ai-infrastructure.html https://www.cnbc.com/2026/05/06/nvidia-corning-optical-factories-nc-texas-ai.html https://www.wsj.com/tech/nvidia-corning-form-partnership-to-expand-fiber-optic-manufacturing-17f525de https://kfgo.com/2026/05/06/corning-partners-with-nvidia-to-expand-us-fiber-optic-output-for-ai-growth/ IBM Think 2026 Boston — Watsonx Orchestrate Next-Gen, Confluent Real-Time Data, IBM Concert, and Sovereign Core Define IBM's Agentic Operating Model https://newsroom.ibm.com/2026-05-05-think-2026-ibm-delivers-the-blueprint-for-the-ai-operating-model-as-the-ai-divide-widens https://www.ibm.com/new/announcements/ibm-announcements-at-think-2026 https://www.instagram.com/reel/DX42DlrglOs/ ServiceNow Knowledge 2026 Las Vegas https://www.servicenow.com/events/knowledge.html https://newsroom.servicenow.com/press-releases/details/2026/Cohesity-and-ServiceNow-Deliver-Real-Time-Recovery-for-Enterprise-AI-Agents/default.aspx https://www.cnbc.com/2025/09/04/nvidia-backed-cohesity-eyes-2026-ipo-with-valuation-rivaling-17-billion-rubrik.html   The Flip: Anthropic at $1.2T Now the Most Important Company in Enterprise Tech — More Important Than NVIDIA, Microsoft, or OpenAI FOR: Dual-hyperscaler compute anchor (Amazon $33B + Google $40B = $73B) is structural — unmatched https://futurumgroup.com/insights/anthropics-gigawatt-scale-tpu-deal-with-broadcom-creates-a-structural-advantage/ Constitutional AI safety positioning wins regulated industries https://www.anthropic.com/news/anthropic-nec-japan-ai-engineering-workforce $900B valuation surpasses OpenAI ($852B) at faster revenue growth and lower burn rate https://techcrunch.com/2026/04/30/anthropic-potential-900b-valuation-round-could-happen-within-two-weeks/   AGAINST: NVIDIA still controls the substrate — every Anthropic dollar of revenue requires NVIDIA inference at some layer https://www.cnbc.com/2026/04/27/nvidia-just-hit-an-all-time-high-why-some-think-a-rally-is-just-getting-started.html Microsoft has the enterprise distribution — 365 + Azure + Copilot reach >2 billion users https://www.marketbeat.com/originals/microsofts-maia-200-the-profit-engine-ai-needs/ $900B valuation is venture marketing — the IPO will reset the number https://www.semafor.com/article/05/04/2026/openai-anthropic-ramp-up-enterprise-push   Bulls & Bears: AMD Q1 2026 — Revenue $10.3B (+38% YoY), MI300X Data Center GPU Demand Drives Stock +20% on the Print https://ir.amd.com/news-events/press-releases/detail/1284/amd-reports-first-quarter-2026-financial-results https://www.cnbc.com/2026/05/05/amd-q1-2026-earnings-report.html https://finance.yahoo.com/markets/stocks/articles/amd-q1-2026-earnings-revenue-203331768.html Palantir Q1 2026 — Revenue +85% YoY, US Commercial +133%, Rule of 40 Score Hits 145%; Largest Guidance Raise in Company History https://investors.palantir.com/files/Palantir%20-%20Q1%202026%20Business%20Update.pdf https://www.reddit.com/r/PLTR/comments/1t3t0me/palantir_reports_q1_2026_us_revenue_growth_of_104/ https://finance.yahoo.com/markets/stocks/articles/palantir-technologies-inc-q1-2026-002218719.html https://semiconalpha.substack.com/p/palantir-q1-2026-rewriting-the-rule Arm Holdings Q4 FY2026 — Record $1.49B Quarter, Full-Year Revenue Crosses $4.92B, $2B AGI CPU Pipeline; Stock +16% After Hours https://finance.yahoo.com/markets/stocks/articles/arm-q4-earnings-call-highlights-225942093.html https://www.stocktitan.net/sec-filings/ARM/6-k-arm-holdings-plc-uk-current-report-foreign-issuer-7e9ca9ac7dda.html https://semiconalpha.substack.com/p/arm-q4-fy2026-record-quarter-2-billion Super Micro Computer Q3 FY2026 — Revenue $10.2B (+123% YoY), Strong Q4 Guide; Stock +18% AH on First Earnings Call Since Co-Founder Indictment Drama https://www.cnbc.com/2026/05/05/super-micro-smci-q3-earnings-report-2026.html https://www.stocktitan.net/sec-filings/SMCI/8-k-super-micro-computer-inc-reports-material-event-e70b2f8b3cb7.html https://www.instagram.com/reel/DX42DlrglOs/ Lattice Semiconductor Q1 2026 — Beat-and-Raise Quarter ($170.9M, +42% YoY) Paired With $1.65B AMI Acquisition That Doubles Lattice's SAM to $12B https://www.stocktitan.net/sec-filings/LSCC/8-k-lattice-semiconductor-corp-reports-material-event-642a862b2bf9.html https://www.ami.com/resources/ami-announces-agreement-to-be-acquired-by-lattice-semiconductor/ https://www.linkedin.com/posts/patmoorhead_lattice-semiconductor-posts-beat-and-raise-activity-7457411226944425984-xA8T Coherent Q3 2026 Earnings https://www.msn.com/en-us/money/companies/coherent-cohr-tops-revenue-expectations-in-q3-as-ai-demand-accelerates-shares-decline/ar-AA22Bz24?ocid=finance-verthp-feeds  

Semiconductor stocks continue to lead the market higher as the AI boom drives massive capital spending, soaring valuations, and relentless momentum in names like Nvidia, AMD, Broadcom, and TSMC. But are investors witnessing the next great technology revolution, or the early stages of another market bubble? Lance Roberts & Michael Lebowitz examine the semiconductor trade from both sides: Explosive AI demand, data center growth, and earnings momentum versus stretched valuations, narrowing market breadth, and growing concentration risk inside the S&P 500 and NASDAQ. Key topics include: 0:00 - INTRO 0:56 - Earnings Revisions are Ratcheting Up 4:32 - The Importance and Use of Technical Indicators 11:05 - Tools for Separating Narratives & Emotions from Market Reality 13:07 - Likes for Lebo Merch 14:10 - Semiconductors, AI, and Bubbles 16:58 - GPU's, CPU's, & LLM's 18:38 - The AMD Story & Supple-Demand Imbalances 24:10 - Portfolio Management Keeps You Out of Trouble 25:05 - Taking Profits is Important 26:45 - Where Will Money Go Next? 29:22 - Dissention in the Fed - Cuts or No Cuts? 32:15 - AI is Disinflationary in Nature 34:06 - The Curb Appeal of the Economy 36:18 - Guessing the Outcome - The K-Shape Continues 38:29 -The Technology Displacement Cycle Hosted by RIA Advisors Chief Investment Strategist, Lance Roberts, CIO, w Portfolio Manager, Michael Lebowitz, CFA Produced by Brent Clanton, Executive Producer ------- Do you enjoy our content? Rate us on Google: https://bit.ly/4b9JtEo ------- Watch Today's Full Video on our YouTube Channel: https://youtube.com/live/X0moIzRXOHg ------- Articles Mentioned in Today's Show: "A Robot Economy: Who Gets Rich, Who Gets Left Behind" https://realinvestmentadvice.com/resources/blog/a-robot-economy-who-gets-rich-who-gets-left-behind/ ------- Watch today's "Before the Bell" feature, "How Markets Ignore the Fear" here: https://youtu.be/1BrnxwNgzeY ------- Watch our previous show, "Q&A Wednesday - What's Your Biggest Concern?" https://youtube.com/live/TFn61TpR-Fc ------- * REGISTER for our next Candid Coffee, Saturday, May 16: "Financial Organization Made Simple:" https://streamyard.com/watch/SA6aj2aMdMhf -------- Download Lance's Latest e-book, "Laws of Money & Wealth:"https://realinvestmentadvice.com/ria-e-guide-library/ -------- SUBSCRIBE to The Real Investment Show here: http://www.youtube.com/c/TheRealInvestmentShow -------- Visit our Site: https://www.realinvestmentadvice.com Contact Us: 1-855-RIA-PLAN -------- Subscribe to SimpleVisor: https://www.simplevisor.com/register-new -------- Connect with us on social: https://twitter.com/RealInvAdvice https://twitter.com/LanceRoberts https://www.facebook.com/RealInvestmentAdvice/ https://www.linkedin.com/in/realinvestmentadvice/ #StockMarket #Investing #SP500 #MarketOutlook #TechnicalAnalysis #Semiconductors #AIStocks #Nvidia #TechnologyStocks

Semiconductor stocks continue to lead the market higher as the AI boom drives massive capital spending, soaring valuations, and relentless momentum in names like Nvidia, AMD, Broadcom, and TSMC. But are investors witnessing the next great technology revolution, or the early stages of another market bubble? Lance Roberts & Michael Lebowitz examine the semiconductor trade from both sides: Explosive AI demand, data center growth, and earnings momentum versus stretched valuations, narrowing market breadth, and growing concentration risk inside the S&P 500 and NASDAQ. Key topics include: 0:00 - INTRO 0:56 - Earnings Revisions are Ratcheting Up 4:32 - The Importance and Use of Technical Indicators 11:05 - Tools for Separating Narratives & Emotions from Market Reality 13:07 - Likes for Lebo Merch 14:10 - Semiconductors, AI, and Bubbles 16:58 - GPU's, CPU's, & LLM's 18:38 - The AMD Story & Supple-Demand Imbalances 24:10 - Portfolio Management Keeps You Out of Trouble 25:05 - Taking Profits is Important 26:45 - Where Will Money Go Next? 29:22 - Dissention in the Fed - Cuts or No Cuts? 32:15 - AI is Disinflationary in Nature 34:06 - The Curb Appeal of the Economy 36:18 - Guessing the Outcome - The K-Shape Continues 38:29 -The Technology Displacement Cycle Hosted by RIA Advisors Chief Investment Strategist, Lance Roberts, CIO, w Portfolio Manager, Michael Lebowitz, CFA Produced by Brent Clanton, Executive Producer ------- Do you enjoy our content? Rate us on Google: https://bit.ly/4b9JtEo ------- Watch Today's Full Video on our YouTube Channel: https://youtube.com/live/X0moIzRXOHg ------- Articles Mentioned in Today's Show: "A Robot Economy: Who Gets Rich, Who Gets Left Behind" https://realinvestmentadvice.com/resources/blog/a-robot-economy-who-gets-rich-who-gets-left-behind/ ------- Watch today's "Before the Bell" feature, "How Markets Ignore the Fear" here: https://youtu.be/1BrnxwNgzeY ------- Watch our previous show, "Q&A Wednesday - What's Your Biggest Concern?" https://youtube.com/live/TFn61TpR-Fc ------- * REGISTER for our next Candid Coffee, Saturday, May 16: "Financial Organization Made Simple:" https://streamyard.com/watch/SA6aj2aMdMhf -------- Download Lance's Latest e-book, "Laws of Money & Wealth:"https://realinvestmentadvice.com/ria-e-guide-library/ -------- SUBSCRIBE to The Real Investment Show here: http://www.youtube.com/c/TheRealInvestmentShow -------- Visit our Site: https://www.realinvestmentadvice.com Contact Us: 1-855-RIA-PLAN -------- Subscribe to SimpleVisor: https://www.simplevisor.com/register-new -------- Connect with us on social: https://twitter.com/RealInvAdvice https://twitter.com/LanceRoberts https://www.facebook.com/RealInvestmentAdvice/ https://www.linkedin.com/in/realinvestmentadvice/ #StockMarket #Investing #SP500 #MarketOutlook #TechnicalAnalysis #Semiconductors #AIStocks #Nvidia #TechnologyStocks

Good overall earnings season – still going strong Economic reports show a mixed picture – but still good enough Semi-annual earnings report option gaining steam Saying goodbye to Spirit Airlines Markets PLUS we are now on Spotify and Amazon Music/Podcasts! Click HERE for Show Notes and Links DHUnplugged is now streaming live - with listener chat. Click on link on the right sidebar. Love the Show? Then how about a Donation? Follow John C. Dvorak on Twitter Follow Andrew Horowitz on Twitter Warm-Up - Good overall earnings season - still going strong - Economic reports show a mixed picture - but still good enough - Semi-annual earnings report option gaining steam - Saying goodbye to Spirit Airlines - EGGS - Breaking News! Markets - Are markets riding tariff refund wave? - Oil shoots up then slips back after Iran tensions rise and fall - New Highs - NAZ100 powering ahead - Huge Capex and OBBBA NEED A NEW CTP - CMG (last time was 2017) Ship Sailing - Seems that under the protection of the USA - a Maersk ship passed through the Strait - But how many can they do a day like this? - Oil down after a huge spike yesterday due to IRAN striking UAE Big Shakeup - US transportation stocks plunged after Amazon announced expanded logistics offerings that will turn it into a major competitor for parcel carriers and air freight companies. - The move is a threat not just to other couriers' grasp on e-commerce, but potentially to more profitable areas such as healthcare, which UPS and FedEx have made a central part of their strategies. - Amazon will offer freight, distribution and fulfillment, and parcel shipping to standalone customers, and its announcement "could be a watershed moment for North American freight transportation companies," according to Morgan Stanley analyst Ravi Shanker. - FedEx Corp. shares fell 9.1% in their worst day in more than a year, while rival United Parcel Service Inc. dropped more than 10%. -- Logistics firms Forward Air Corp. and GXO Logistics Inc. suffered double-digit declines. Old Dominion Freight Line Inc., among other truckers, slid almost 7%. --- FYI - Did you know... last year there was a total of 23.9 BILLION packages shipped in the US. 25% was delivered by Amazon, Fed and UPS delivered a third. Off the Hook - Chump Change - Elon Musk agreed to pay $1.5 million to settle Securities and Exchange Commission allegations that he cheated Twitter shareholders by failing to properly disclose his growing stake in the social media company. - An Elon Musk revocable trust would pay the penalty to end the SEC's lawsuit, which is still subject to court approval, and Musk didn't admit to the regulator's allegations. - The SEC said the deal would be the largest penalty the agency has levied against an entity or individual for allegedly failing to file a beneficial ownership report on time, but Musk's attorney called it a “small fine”. - Musk didn't admit to the regulator's allegations, according to a filing on Monday. This could be something... - Sonos Inc. shares climbed after reporting revenue that jumped 8% and said that it is filing for tariff refunds totaling $40 million. - The company reported second quarter revenue of $282 million, up 8% year over year, and strong growth in international markets. - Sonos is forecasting adjusted earnings before interest, taxes, depreciation, and amortization between $20 million and $48 million for the current quarter - Are markets riding higher also on the tariff refunds? ---- The US government is paying back up to $166 billion in revenue it collected through sweeping global tariffs that were struck down by the Supreme Court in February, with the first payments set to go out on May 11. AND - General Motors raised its 2026 guidance after significantly beating Wall Street's first-quarter earnings expectations following a roughly $500 million benefit from the U.S. Supreme Court decision to terminate and refund certain levies AKA - tariffs. OPEC? - In an unexpected announcement - The United Arab Emirates will exit OPEC on May 1, in a major blow to the cartel that coordinates production among many of the world's largest oil producers, particularly those in the Middle East. - OPEC+ to raise June output quotas by 188,000 bpd - Most members cannot meet targets due to Hormuz closure - Quota increase removes UAE share after it left OPEC+ and OPEC (so just a make-up) - Meanwhile, they cannot meet the iutput as no place to put the oil.... --- This all looks and sounds good but there is no substance. ---- Saudi Arabia produces 10 million barrels a day (Biggest in OPEC). USA produces 13 Million .... Spirit Airlines - Goodbye - shutdown Saturday night at 3PM - The administration had floated a last-ditch bailout that would have given the federal government a controlling stake in the airline, but the proposal stalled amid resistance from key creditors, whose approval would have been required for the deal to go through. - Meanwhile, most ticket holders will get refunds. --- Already Jetblue and others are looking to fill the void by offering more flights from airports that Spirit serviced. -- Takes a low cost alternative off the market and potentially will be a negative for consumers - less competition - WHICH IS EXACTLY WHAT BIDEN ADMINISTRATION DID NOT WANT BY BLOCKING JETBLUE MERGER JC - are you listening?? - Duolingo beats Q1 revenue estimates, driven by 21% growth in paid subscribers - CFO Gillian Munson says investments target long-term user retention - Duolingo aims for 100 million daily active users by 2028 - Guided a bit lower and a strategy shift toward prioritizing user experience and long-term retention over near-term monetization, as it invests in product quality and engagement to build a larger base of paying subscribers. (DUMB?) - Share down 8% CHIPS - Samsung Electronics reported an over eightfold increase in first-quarter operating profits on Thursday, hitting a new record and beating analysts' estimates on the explosive growth of its chip business. -  Revenue: 133.9 trillion Korean won ($89.96 billion) vs. 132.69 trillion won expected - Operating profit: 57.2 trillion won vs. 55.28 trillion won expected - The South Korean technology giant's quarterly profit climbed more than 750% from a year earlier to a fresh record. - The company also posted record revenue, up about 70% year over year. AMD Reports Conf Call: AMD paired strong current-quarter execution with a more ambitious long-term AI and server CPU outlook. The biggest positives were the stronger EPYC trajectory, rising confidence in MI450/Helios demand, and the upgraded server CPU TAM view. - The company now sees the server CPU TAM growing more than 35% annually to over $120 billion by 2030, up from its prior long-term view. - The main caution points were second-half PC and Gaming demand pressure from higher memory and component costs. - Margins 55% - Stock up 15% AH Apple Chips Deal? - Apple Inc. has held exploratory discussions with Intel Corp. and Samsung Electronics Co. about producing main processors for its devices in the US, as a secondary option beyond Taiwan Semiconductor Manufacturing Co. - The discussions with Intel and Samsung are preliminary and have not resulted in any orders, with Apple having concerns about using non-TSMC technology. - Apple is considering additional suppliers due to supply-chain disruptions, including recent shortages driven by the build-out of AI data centers and higher demand for Macs, with CEO Tim Cook saying the company has less flexibility in the supply chain than normal. - Discussions - yet Intel up 14% on the  news (after a 100% run in April) Flashback - 2 weeks - Remember when OpenAi came out with some news that they missed revenue and user growth goals? - Took down tech for a day a couple of weeks ago.... Tech earnings - Overall tech earnings were solid. - Bbig takeaway is that the group (MAG7) are still spending a buttload on expansion into AI etc. Capex $$$$ - Meta was hit on theor outlook (which is why they came back and announced further layoffs) AI Layoffs - Recall - "AI will not take jobs" - More announced this week - Coinbase today - How long until the robots take over? - Recent Announcements AI Job Cuts EGGS - Consumption of eggs is associated with a lower risk of being diagnosed with Alzheimer's Disease for those 65 years and older, according to researchers at Loma Linda University Health - Eating one egg per day for at least five days a week reduces risk of Alzheimer's by up to 27%, researchers found. --- More: Eggs are known to be a source of key nutrients that support brain health. Sabaté said. Eggs provide choline, a precursor to acetylcholine and phosphatidylcholine, both of which are critical for memory and synaptic function, the study stated. Eggs also contain lutein and zeaxanthin—carotenoids that accumulate in brain tissue and are associated with improved cognitive performance and reduced oxidative stress. Eggs also contain key omega-3 fatty acids, and yolks are particularly rich in phospholipids, which constitute nearly 30% of total egg lipids and are essential for neurotransmitter receptor function. LIV Losing Saudi Arabia - LIV Golf will lose its financial backing from Saudi Arabia's Public Investment Fund after the 2026 season, the fund announced Thursday. - "PIF has made the decision to fund LIV Golf only for the remainder of the 2026 season," a representative for the PIF, Saudi Arabia's sovereign wealth fund chaired by Crown Prince Mohammed bin Salman, told ABC News on Thursday. - "The substantial investment required by LIV Golf over a longer term is no longer consistent with the current phase of PIF's investment strategy," the statement continued. "This decision has been made in light of PIF's investment priorities and current macro dynamics. - Looking for Private Equity to step in Cars - The Beijing Auto Show that opened to the public this week is a showcase for how hypercompetition in China has driven new car prices in the world's largest car market to ?a fraction of the level of the next-largest market, the U.S. - In China, there are more than 200 battery-powered models, including hybrids, for sale at less than the equivalent of $25,000, according to DCar, an information and trading platform. - Plenty at the $10k - $12k level Death Squads - Friday, The White house announced plans to add firing squads, electrocution and gas asphyxiation as alternative methods of executing people convicted of the gravest federal crimes - Only THREE federal executions in the last 50 years Weekly Picks Ideas Worst Stocks this Year Worst Stocks   Love the Show? Then how about a Donation? 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