Going ULTRA with RTX Spark and New Surface Devices | Merge Conflict ep. 537

Author: Merge Conflict Podcast · Watch on YouTube

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Original language: English

Original video: Going ULTRA with RTX Spark and New Surface Devices | Merge Conflict ep. 537 · Channel: Merge Conflict Podcast · 56:48 · Watch on YouTube

Topics: AI agents, Cybersecurity and software security, AI infrastructure and hardware, Local and open-source models

Summary

James Montemagno and Frank Krueger discuss Microsoft’s new Surface Laptop Ultra and RTX Spark developer workstation, focusing on their NVIDIA GPUs, ARM processors, unified memory, and premium pricing. They explain Windows ML and its support for tools and model formats such as PyTorch, llama.cpp, and ONNX, then examine Microsoft Execution Containers as a way to isolate AI agents and control their access to files and networks. The hosts also explore running large local models and combining local and cloud models in GitHub Copilot and Windows workflows. They close by comparing the new hardware with Macs, discussing workstation power and setup trade-offs, and noting the Surface Laptop Ultra’s magnetic USB-C charging connector.

Key points

The Surface Laptop Ultra pairs an ARM CPU with a high-core-count NVIDIA GPU and is positioned as a premium device for creators and developers.
Its unified memory is shared by the CPU and GPU, reducing the need to move data between separate memory pools and allowing more system memory to be available for GPU workloads.
Windows ML is described as a runtime for running models across GPUs, NPUs, and CPUs, with support discussed for ONNX, PyTorch, and llama.cpp.
Microsoft Execution Containers provide process or session isolation for AI agents, with controls for file, network, and clipboard access.
The hosts see agent sandboxing as valuable, while noting that permissions, defaults, and developer-tool access can make the experience cumbersome.
Local models can reduce dependence on paid cloud tokens and support long-running or offline tasks, though the hosts caution that they are not generally as capable as leading cloud models.
GitHub Copilot’s discussed local-model features include automatic routing and HydroFusion, which can delegate tasks among available local models and cloud models.
The Surface RTX Spark Dev Box is presented as a single-configuration desktop workstation with 128 GB of unified memory and a removable 2 TB SSD, priced at about $5,600.
The hosts compare Windows’ developing AI features with Apple’s current offerings and discuss the value of integrated, easy-to-use local and hybrid AI experiences.
The Surface Laptop Ultra includes a magnetic USB-C charging connector that the hosts compare to MagSafe.

Chapters

Start	Chapter	Summary
00:00	Opening and Microsoft’s hardware event	The hosts introduce the episode and set up a discussion of Microsoft’s new hardware and AI announcements.
02:38	Surface Laptop Ultra and NVIDIA hardware	Frank describes the Surface Laptop Ultra’s ARM-and-GPU design, display, creator focus, and high price.
05:51	Unified memory and model workloads	James and Frank explain the laptop’s configurations and why shared CPU-GPU memory matters for machine-learning work.
10:48	Creator workflows and Windows ML	They discuss local creative workflows and Windows ML’s role in running models across Windows hardware.
15:03	Model development and deployment	Frank distinguishes development tools such as PyTorch and llama.cpp from stable deployment options such as Windows ML.
18:17	Agent security and execution containers	The conversation turns to safety announcements and Microsoft Execution Containers’ process and session isolation for agents.
24:06	Sandbox controls and practical friction	The hosts weigh the security benefits of isolated agents against permission prompts and the challenges of configuring access.
29:34	Local models in GitHub Copilot	They describe local model options, automatic routing, and delegation between local and cloud models in Copilot.
33:48	Why local AI can feel liberating	Frank explains the appeal of using local models without worrying about cloud token quotas, while acknowledging capability limits.
36:27	Windows AI features and personal workflows	James discusses long-running agent sessions, Windows’ agent-focused direction, and using AI to work with personal and professional information.
41:52	Hybrid AI and Apple comparisons	The hosts consider local and cloud model integration, Apple Intelligence, and the need for simple model experiences.
46:35	Surface RTX Spark Dev Box	James introduces the compact developer workstation, and the hosts review its specifications, price, and physical design.
49:19	Workstation power and setup trade-offs	Frank discusses cooling and power limits, while James considers replacing his Mac mini and changing his desk setup.
55:45	Closing and magnetic USB-C	The hosts wrap up by discussing the laptop’s magnetic USB-C charger and signing off.

Quotes

Unified memory obviously simplifies all that. — 08:32

you want to be deploying with something stable — 17:12

session isolation is cool — 23:00

what they are is liberating. — 35:23

it’s USB-C and it’s MagSafe, but it’s not MagSafe. — 56:17

Concepts and entities

Surface Laptop Ultra, RTX Spark Dev Box, NVIDIA, Windows ML, llama.cpp, PyTorch, ONNX, MXC, memória unificada, GitHub Copilot, Hydrofusion, James Montemagno, Frank Krueger, Microsoft, Apple

Full transcript (original language)

00:00 Welcome back everyone to Merge Conflict your weekly developer podcast talking about all things in the world of software development, AI, and new hardware. I’m one of your co-hosts who works at Microsoft, James Montemagno, and with me, the one and only who used to work at Microsoft, Frank Krueger. How’s it going, buddy? >> Oh, it’s been a while. Do they still call it Microsoft? Is that still the name? Is that trademark registered? Yeah, okay. >> MSFT, still the ticker. Tick tick. >> Hi, James. It’s wonderful to be here on your show. I This is one of my favorite weeks where

00:30 we are going to talk about hardware. Spoilers. I know we like to ease into our topics, like talk about random stuff for 15 minutes, but I feel like we have a lot to cover this week because Microsoft’s in the hardware game, you know, like they put their toes in and then they step out of the water, like, “Ooh, that’s a little cold.” And then they get back in and then they’re like, “Eh, I’ll try it again.” This is one of their “We’re just going to cannonball into the water.” And I don’t know what you want to talk about. What I want to talk about is this big cool laptop they just released, and

01:02 I I just want to dive into that puppy. James, have you heard about this laptop that the little MSFT company has released? >> Well, yeah. >> Little company out of Redmond, Washington. >> I have one sitting in front of me, so yes. Yes, I I I know. >> Okay. Well, aren’t you rich because man, the starting price of this thing is just as big as its beautiful screen. >> Well, >> No, there was a big hardware event, but also a software event and a local like a model event, too. It was kind of a It was like a Windows and hardware event, and to me

01:34 >> Yeah. >> it was also kind of also somewhat a developer event a little bit, too, I want to say. >> I mean, we’re getting all the attention right now, right? Because anytime you say AI, it’s like, “Okay, business people do something with it.” I’m really not sure what business people do. I assume they just chat with it all day or something like that. Maybe it fills all their Excel sheets or something, but I think you and I have the most experience with agents and everything as developers, as I’m sure everyone listening. And we’re kind of the crowd that all the agency stuff is really catered to at the moment. So, I feel

02:06 like anytime anyone’s talking AI, it is a little bit of um our club talking, at least for now. It’s taken over the world, for sure, but we’re the ones deepest into this fiasco called AI, SI, whatever it’s called. >> Uh well, there was two devices. One got the most attention, and the second one is the one that I’m also extremely excited about. But, I am excited that you’re excited for Microsoft hardware. I’ve been a huge fan of the Surface line of devices for a long time. They’re beautiful hardware. Frank, I’ll let you

02:38 lead because I know all the things about this device. So, >> I’ll tell you from an outsider’s perspective what I noticed. I noticed Microsoft released and partnered with Nvidia to create a new RTX Spark, whatever the heck that is, Surface Laptop Ultra. The Ultra being very important because there’s a million Surface things out there. Laptop being important. The Ultra meaning it’s fast. They um this is an ARM chip, and you won’t believe how many web pages I had to look

03:08 through to find out what the architecture of the chip actually was. This is an ARM chip, everyone. And it’s an ARM chip bolted to a giant GPU, or it’s a GPU bolted to a small ARM chip. Not really sure which one it is. >> [laughter] >> All crammed inside of a laptop case. And speaking as an Apple dweeb, um this is definitely a big uh competitor to the M5 and the big um big powerful Pro Max that have been coming out lately. This is Microsoft stepping into the ring.

03:40 Nvidia joining them because we need GPUs, and they’re the only ones that can afford RAM these days. So, they’re all getting in there, releasing this big beautiful monster of a machine with a monster price tag. Let me not forget to keep saying that. But, it’s a beautiful machine. Like, you you can’t argue. Um the video they used to introduce it was very Apple-esque. >> [laughter] >> The machine itself, very Apple-esque. It’s a big, beautiful pixel sense uh 200 and let’s just go with 50 um pixels per inch. It’s high res. That’s all that really matters. It’s an HDR monitor.

04:14 And it’s got a ridiculous number of Nvidia cores in it. And as someone who does a lot of ML still, like I train my own models and everything, it’s really cool to have actual Nvidia hardware on um on basic It’s a personal computer, I suppose. I suppose. It’s more of a workstation crammed into a laptop. But, it’s cool to have that Nvidia hardware because as much as I love my Apples, um the the metal the metal ecosystem just

04:47 isn’t nearly as advanced as the CUDA Nvidia ecosystem. Uh the kernels are just a little bit different. Some of them are buggy. A lot of them are much slower than the CUDA world. Right now, my room is 20° warmer than it ought to be because I have my RTX 3090 crushing away on some numbers doing tensor math um using all the flops in the world, tops. I don’t even know what they are anymore. Um that’s all Nvidia hardware. That’s CUDA. That’s my happy place. You can run Python. Any model you download from the

05:21 internet is going to happily run on CUDA hardware very efficiently. And that’s what they stuffed into this laptop case. So, for $2,600, you can get a giant GPU um somehow attached to a monitor and a keyboard and a trackpad all glued into a very fine-looking case. It’s a big price tag, but gosh, it’s a beautiful machine. How can you not be excited about it? You’d have to totally hate tech to not be excited about it. >> No, I mean

05:51 you’re right. It is a is a is a big beautiful machine. Uh and you know, the starting price is yeah, 2700 and goes up to like almost 6,000. Um now I do agree with you like the the real core is actually like the the 32 gig RAM like unified. So, that’s going to get you like basically I don’t know, 30 3,300 or whatever. There’s a there’s a bunch of different tweaks on here. But yes, see I mean you’re right. Like it’s the

06:23 the RTX Spark I’m looking at right here so I can get the text backs. N N1X with um it has either there’s two models for the laptop. One is 5,120 core GPU with an 18 core CPU or a 6,144 core GPU and a 20 core CPU. It’s a lot of cores, Frank. And it has I don’t know if you’ve heard of this thing called unified memory. Can you describe what that means? >> Unified memory. Uh that’s is why it’s an

06:55 arm. I I should have known just from the unified memory that it was arm cuz I don’t know. Intel’s still not doing it for whatever reason. Unified memory means the GPU and the CPU are sharing the same memory bank. Which is a wonderful thing A as programmers because when I’m doing development, I have to um first get my data into system RAM and then it has to be uploaded to the GPU. That’s because I have an Intel system with non-unified memory. It’s a

07:26 pain in the butt because they’re two different speeds, honestly. Like uh DDR4 usually as your CPU RAM. Some people have modern computers DDR6 five six. Um but it’s it’s usually a quite a speed difference between the two. And in the past it was graphics RAM. Graphics RAM was more expensive and faster, the stuff running inside the GPUs. Nowadays, it’s getting a little bit weird. So, you always had this very awkward programming model of you would have to really write pretty sophisticated software to keep feeding data into your

07:59 GPU to keep the GPU hot spinning so that your room increases by 20° whenever you’re in it. That’s very important. But, it’s kind of a pain in the butt because you’re constantly having to synchronize these two basically there’s two different computers in your computer and you’re having to like synchronize the memory through it as programmers. And that was they would try to hide it from you, but like all bad abstractions, it was a leaky abstraction. And if you wanted to get high performance out of training or inference, either side of

08:32 the ML world, you had to get really good at memory transfers. You had to fully understand all the DMA channels and all that. Unified memory obviously simplifies all that. I think it premiered on the Xbox One Xbox, maybe just Xbox. >> [laughter] >> Apple’s been doing it forever. The beautiful thing is we don’t have to do that synchronization as developers. The second beautiful thing is when you increase the RAM of the computer, it’s all just available to the graphics card. I love my RTX 3090, but it only has 24 GB of RAM. The machine has 16 GB of CPU

09:10 RAM. So, technically, I have 40 GB of RAM, but can I use that for training? No, James, I cannot. I am stuck with 24. And just 2 hours ago, my training crashed because I ran out of memory. How apropos. >> [laughter] >> Oh, wow. Jeez. >> Unified is great for two things. A, you get more. B, it simplifies the programming model. That’s why we all like unified memory. It’s important. It’s the future. Some would say the past if an Apple user. >> [laughter] >> Yeah, and I think that’s one thing that Apple’s called out a lot in the the M

09:42 series, the unified memory between the CPU and GPU. And it’s kind of the architecture that is kind of like moving forward. Enables a lot of scenarios. And yeah, so this thing goes anywhere from 24 gigs of LPDDR5X unified memory up to 128. And it also goes up to Uh it says a rem- uh removable. I know that’s the dev box as a removable. Is it >> Is the Surface Laptop one removable? >> I think the laptop had screws for the hard drive also, if I my eyes weren’t I couldn’t tell cuz they had a really smooth um video where they the whole

10:15 machine explodes, and I couldn’t tell what you’re allowed to explode yourself and what you’re not, but it looks like you could unscrew that hard drive >> It says removable. Says removable solid state drive Gen 5 SSD, the Gen 4 for the 512, the Gen 5 for the 1 TB and 2 TB. Yeah, the resolution of the screen is 3270 by 2180, 262 PPI on it. Um a 3x2 ratio, like all the other Surface devices, HDR, all that stuff that’s on there. But I think in general yeah, it’s a it’s a as you saw like a super gorgeous device. And it’s a really

10:48 high-end device. I think what Pavan was saying was you need device for creators. And that kind of like harkens to what Apple originally had like with the Pro model of devices. And now they saw the obviously the Pro and the Studio models, but then they did uh delineate them with the specific like chips like your Pros and your Max chips that are out there. And you know, by the name of this, the Ultra, you know, that is more than what the like Surface Laptop and the Studio would be. This like they’re saying this is the Ultra, this is the top top to the top end that you

11:22 can get for creators. And they showed a lot of different scenarios, specifically of running a lot of local models. We’ll talk about local models and and training and things. But, a lot of different developer workflows, creator workflows. Um there was one specifically that they showed about an artist that does a lot of um like different um um artwork, you know, kind of like mock-up artwork of space and stuff that you and I you know, gel with that’s kind of very like Firefly-esque. Um Serenity-esque, but

11:55 like that type of that world is the kind of like um you know, illustrations. And he was running it through all of these different models that once he had drawn drew draw the the base of it then he could run it through all these models like locally like five different local models, some cloud models, whole do a whole screen, go through Blender and do all this work all locally. He was like things that used to take me like weeks now take me like a day to do like all on this device like with the power of it and uh it it’s not just these models, but also the

12:26 um they’re talking about super Neumotron and then also the MAI code one flash model, which is 120 gig uh 120 billion parameter model um running locally on these devices and I think that’s like super crazy impressive. Um I’m still running having a hard time running any models on my you know, M4 Pro uh 64 GBs. I I I can do it. It’s just a struggle. That’s all I’m saying. >> I it’s going to be a struggle. I mean, except for MAI, it’s going to be a struggle with everything. Running a

12:58 local model sadly it’s a little more complicated than it needs to be. But, you hit the um nail on the head because you can make the most beautiful machine in the world, but you need to have good software to run it. And that’s kind of what I was saying about the um the uh CUDA Nvidia world. That’s the one nice thing about that world is uh there’s a lot of AI software out there tuned to it, but it’s not just that. It’s video production software is tuned to it. Nvidia not only is a large

13:29 profitable company, but it turns out they’ve taken over a lot of the software ecosystem. So, a lot of your high-end plugins for things take advantage of all these Nvidia chips. Um we shouldn’t forget gaming. This is going to be a monster gaming device, but I don’t know what gamers are going to spend 20 >> They they they showed gears running on it while they were doing all this stuff. >> Yeah, it’s definitely more for the creator crowd. If you’re doing like a lot of CAD, if you’re doing movie production, all that stuff. Things that can take advantage of these ridiculous

14:00 GPUs they’re putting in there. But yeah, building up that software ecosystem is difficult. So, being with Nvidia, they’re lucky. They’re they’re just inheriting a bunch of software that’s just going to work with it. But then they made a bunch of enhancements to Windows also that’s going to take advantage of it. The one that I found kind of interesting was and I you’re going to have to help me here because I could never quite remember its name, but there’s machine learning on Windows. It’s kind of the equivalent of Core ML on the Apple side where you can kind of recompile your models to run nicely on

14:32 Windows and I believe like ONNX models, ONNX models, which is an interchange format, has like native drivers to run officially on Windows. So, it seemed like a big part of this announcement wasn’t just this hardware, but all these software upgrades to Windows specifically for being able to run these more advanced um scenarios more easily cuz you could always do it. Like I’m saying, you could always hit torch up in Python and get these things cranking. But it wasn’t easy. It wasn’t fun. And so, I think and you had that experience

15:03 on Mac. So, getting these things to be easy to run this important. >> Yeah, and that’s what it was specifically. So, the there’s a big blog post on the Windows experience blog, which is um is it to power this. So, Windows ML is a name of it. >> Thank you. >> Is a scalable runtime to play model across GPU, NPU, and CPU. And then they announced uh support for llama.cpp uh giving developers more open source choices and also PyTorch um as well for Windows ML. So, PyTorch and

15:34 also llama.cpp bringing those directly into it um which is pretty rad. So, in general what that looks like they have a diagram on this website is like like your native app or web app, there’s like a custom open source model for ONNX, PyTorch, or GGML goes into Windows ML and then inter- interlaces with the Windows silicon environment whether it’s Intel, Qualcomm, AMD, or Nvidia and then that accesses the GPU, NPU, and the the CPU, too. >> Yeah, and let me kind of break this down as like a practitioner of ML, you’re

16:07 going to use your PyTorches and Nvidia CUDA stuff to develop ML stuff. And it doesn’t even have to be large language models, it could be all sorts of things. It could be the imaging stuff, it could be audio stuff, it could be video stuff. But that’s going to be like your development environment. Uh llama.cpp is very nice for the nerds out there who are building their own harnesses and um development environments and everything that are going to be executing these models because a lot of the open source models out there come in llama.cpp

16:40 native formats, GGML. And so you’re just going to need that file format and something that can execute that file format. That’s why it’s a big deal that llama.cpp comes out. But as app developers, if you actually want to deploy this stuff, you really honestly don’t want to use either of those um because deploying torch in Python is gross and annoying. Uh llama.cpp is just hard to keep up with, it’s it’s a moving target. That’s where the nice Windows ML, it’s nice to have a stable deployment target. And in

17:12 the past it was ONNX, but ONNX has um ONNX is kind of just the file format, so there can be different engines that execute those ONNX models. So, as developers, if you want to add custom ML stuff to your software, you want to be deploying with something stable >> [laughter] >> and platform approved. And that’s where like Windows ML comes into play. So, it’s it’s all those different areas like from development up to nerdy stuff or you’re willing to get your hands a little dirty up to this is the clean polished rosy path forward deploying your things.

17:45 >> And it says here, you know, they’re contributing back to llama.cpp and in partnership with NVIDIA to your point here in the broader community, they’re delivering a bunch of performance improvements to llama.cpp and GUF support in the format through CUDA kernel optimization, internal fusion, improved CPU GPU scheduling, weight repacking, and CUDA graphs. That work also adds Eagle 3, MTP, and D flash 2 speculative decoding, multi GP execution, NVFP4, new model architectures, and back-end samplings.

18:17 All sorts of stuff. I don’t know what any of that means, but sounds cool. >> [laughter] >> I could tell you every single one of those, but all you need to know is that’s the modern stuff invented to make these things fast. We’re just trying to go fast. That’s all we’re trying to do. Um it’s easy to train these things, but making them fast. But it’s funny, that’s not actually how the presentation started. They didn’t start with fast. No. What did they start with? Do you remember? >> Well, we started mostly with I think I think Kayla was the first demo. Was she the first demo or the second demo of the day?

18:47 >> Even earlier, I think it was safety and security, James. So, it was it was actually, yeah. So, I think Satya said uh safety was actually the very first thing that he mentioned. I’m not really with him. I say throw caution to the wind. Let these things have full disk access to your computer. Give it every login you have. Allow it to use all the memory in your house, you know, just put RAM inside the computer and turn the crank until it has enough RAM. That’s what I think, but who am I to argue with Satya? And what they

19:21 announced was the Windows containers support. I don’t know, was it in like a beta or something because they made a big deal like it sounded like this was almost kind of like an official release or something. So, is that what happened? >> So, it was in preview at Build we announced the Microsoft execution containers MXC and MXC specifically you know, works across Windows, Mac, and Linux. And what it does is it gives basically process and session isolation.

19:52 And obviously on the different operating systems it’s going to use different sort of, you know, container sort of systems that are there. Obviously on Windows because it’s the stack that they own, right? They can go a lot deeper on it. So, on Windows it has like a lot deeper process and session isolation through, you know, actual like MXC locally with like these like one-off process isolated sessions. It also now supports WSL C virtual machines and also Windows 365

20:22 for agents, which is really cool. And I actually was demoing this myself the the day before, so I’m very in tune with it. And actually by demoing it, you know, you I’m actually in love with this more than ever. So, it was actually really cool that it was the first thing because I had I had been And this is just sandboxing people. So, we did heard about sandboxing before and like VS Code and the Copilot app in the CLI. But MXC now actually is rolled out across Code X, Copilot, Open Claw, Replit, LM Studio,

20:54 Open Shell, OnSoth AI, and bunch more that are coming out that are releasing support now that this thing is GA, which is super big because the standardized support kind of gives to us developers it’s actually just an open source library that you can integrate into your application to provide this functionality like everyone else has. And then as users, we get this sort of really um really uh rich features and capabilities. So, you can think of it as you’re able to control disk access and

21:24 network access, um clipboard access, all these other things that you’re able to really get fine-grained control on. Um and you know, what the first thing I did was I’m like, why does why ever would it I want to give, for example, the CLI, VS Code, or the app access to my OneDrive, my work OneDrive. So, you can just say, “Block this folder.” Just like you never need to go to my OneDrive, that’s my business stuff, right? So, you’re there. Now, a lot of these sandboxes are really nice. So, it’ll be like, “Hey, I’m

21:55 trying to access this file. It’s in a sandbox, you know, it’s a shakedown. Am I allowed to?” And you can break out of the sandbox if you need to. There’s always those gates, just like, “Do you approve this thing or not?” Now, auto approval on this thing, it needs this human interaction to do that. And it would like turn it off for that call and then turn it back on and back and forth, which is fascinating. But that’s up to the client, that’s up to the app developer to enable that functionality. Now, the real cool part about it is that most of the apps today are doing process isolation. So, that means for most intense purposes, and that can be that could be like a 5-second boost up to

22:27 like they could have a process that’s running that’s isolated. So, when you boot up Code X, like every session has its own process that is then isolated. But you could make it so you make a request an agent, and as soon as that that turn is done, you kill it, right? You could do that as an option. Normally, even with the CLI or VS Code, it has a process that’s running that’s sitting there for each of the sessions, and those are in isolated process uh there. However, the thing that’s even the cooler than that is session isolation. And

23:00 session isolation is cool and because Open Claw has it integrated today. And what session isolation does is it actually gives a full like user isolation for that application running. So, the Open Claw that is running, the agent that is running in Open Claw has its own basically user account and its own user folder that you can peek into, but it can’t poke out to. Which means every process that is spun up

23:34 in the session of the app, like the entire app, is running as its own separate user account, which is 100% then isolated from you. And that’s like built into this thing. And that is like super crazy cool, actually. I thought that was like really, really neat. Um and I’ve just like really fallen in love with it, funnily enough, because I was demoing it nonstop and I was like, “Oh crap, this is like really cool, you know, in general.” You know, and then then you can have like a wow list and deny list and read only, write only, all these things. The only problem is you really got to set it up. You know,

24:06 that’s the main problem in general. However, what I’m, you know, really thinking is, “Okay, let me have some standard defaults, such as maybe don’t be able to do this stuff in my OneDrive folder or your Dropbox or whatever, you know what I mean?” So, just some like default standards, but you could imagine in the enterprise this is like crazy important. And then they showed a bunch of other Windows features of like really deeply integrating these things where really agents almost really have their own identities on their on your machine, uh which is like so cool. >> Which is right, you know, Unix invented

24:39 this in the ’70s. Yes, user accounts are good and they can be used for other things other than users. That’s a just a good isolation mechanism. So, it’s good to see it actually extending. Honestly, I have a little bit of mixed feelings here because I think with any new security model, there is that time to figure out what should be the defaults and whatnot. You know, still every time I open a session in VS Code, it has to ask me permission to like read something from Microsoft. I’m like, you can you can use the microsoft.com website. It’s fine. It feels like no matter how many times I say allow, a new security model

25:13 gets introduced and that allow is turned off or something like that. So, >> Yeah. >> as a user I get a little bit frustrated with there’s a little bit of theater with our security and there’s a little bit of real security with our security. And I understand those differences, but it can still be frustrating to find that fine line between them. And I totally understand from the enterprise standpoint why they want it, but some of that stuff coming back onto real users, it’s a bit frustrating. >> Yeah. >> talking about Windows Vista, like that we were the first ones to add the annoying pop-up dialogues. Hey, do you

25:45 really want to do this? Do you want to give permission to do this? And it took off quite a few versions to get those dialogues refined and I feel like we’re still just in that annoying stage, but hopefully with MCX coming out and everyone kind of consolidating on it, we’ll have some A, better defaults and B, just I can just say, “Hey, yeah, here here’s a whole set of directories on the computer. Go have fun. I don’t care what you do over there.” >> Exactly. And I do think that this is going to be ever important as these agents are sort of like autonomous agents running on machines separately,

26:17 like you said, you know, it’s like, “Hey, this thing is just running over there.” And it’s I’m not even like I don’t even know what’s going on, right? And you really want it to be its own separate isolated process. Yeah, MXE stuff was really cool. I really like I really dug it. I was super excited about it and just how easy it was. And now that I’ve dug deeper into actually using it a bunch, it’s definitely worth checking out. And there’s like definitely some smart defaults. I think the problem is like if you have sandboxing and then you have like there’s a few things, right? So, for example, there’s there’s like sandboxing to say, “Hey,

26:50 listen, I want you to run all my terminal commands in a sandbox.” That is one thing versus, “Hey, network, dick disk access, things like that.” Cuz the problem we run into as app developers is, “Hey, I need to do a .NET build. Oh, .NET’s not installed in the sandbox.” >> Yeah. >> Right? And you’re like, “Okay, that’s a problem.” Whereas, what I’m talking about is more of permission-based sandboxing for for for accessing locally on your machine. So, I do think when we think sandbox is a pretty loaded term, but what I was at least setting up as my

27:25 defaults for MXC as far as like file and network access, which network access for me is pretty much like, “Yeah, it’s fine.” But, um you could imagine an enterprise, you could just say, “I only want to access like local things. I don’t want you to go out to the internet.” That’d be probably like important for them. But, there’s this. And one of the one of the cool parts is like it also like proxies the access through that. So, for example, I had this demo that was, “Hey, can you go get me a list of like my GitHub issues or whatever?” And it was going to use the GitHub CLI to go do it.

27:59 But, the GitHub CLI is running inside of the sandbox with the sandbox networking, which then blocked it cuz it can’t access GitHub because I turned off network access outside of it on this project. So, it’s kind of interesting in that regard. So, I think there’s this fine line of like, “Okay, what am I what things am I doing versus like I just want to build a project, like just run it on my machine?” Cuz like I have all this stuff on my machine and not in the sandbox, and that’s what kind of is right. Thing versus agent versus like developer build tools. Like those two

28:30 worlds need to kind of like >> Right, but I I feel like we’re we’re the first beta testers of all this agent stuff. All the other other industries, they’re still in the chat world, you know? They’re they’re still doing everything at the chat prompt level. We’re the ones doing the agent and craziness, let it take over my computer stuff. And that line it still is a shaky line. Like just yesterday it couldn’t build my app. And I’m like, why can’t you build that app? They’re like, “Dot net restore is stalling.” I’m like, “Why would Dot net restore stall?” They’re like, “Cuz I don’t have network access.” I’m like, “Oh, okay. Why did it

29:02 take A, why did it take me three Y’s to find out you don’t have network access?” And B, I’m like, “Why don’t you just enable network access?” And it’s like, “Great, I will.” And then the Mac dialog pops up saying, “Hey, do you want to give it network access?” Mac OS 27 changed that dialog box. So it took me a while to figure out how that dialog box works. Finally I granted access and it’s like, “Hey, you have to restart the harness in order to do this.” And I’m like, “But I’m in the middle of a session.” So I’m just >> [gasps] >> Uh, deep breath. >> Goodbye [laughter] cash. >> That’s like this security stuff is a little bit so tricky.

29:34 >> [laughter] >> Well, >> good. We’ll work it out. We’ll figure this stuff out. How hard can it be? >> Well, then the the next thing that they talked about beyond that, right? And also like at the very end we’ll talk about the other hardware that I’m more excited about. So there’s another piece of hardware, but we’ll talk about I’m not talking about every single announcement here as we get into like some deeper Windows stuff, but one of the thing that they really focus on was sort of like local and hybrid AI model usage. And one of the things that Kayla showed off, um, Kayla’s on my team. She also worked on the Windows Terminal team. She’s PM on the Windows Terminal team. Is basically frontier coding models like local on your machine.

30:08 So there’s a few things is like on this machine what they were talking about is like hey taking an AI code one dot one flash um with Nematron models also DeepSeek V4 flash. Like that is a 137 billion parameter um, you know, total 6.8 billion active. Uh, Nvidia’s a 70 billion parameter two-bit, you know, quantization down to 20 gigs on on memory. DeepSeek V4 flash is a 284 billion parameter model. So

30:39 there’s all these things that are going to run locally on the RTX Spark, which is crazy. Obviously, I’d imagine depending on how much RAM you have. You want all the RAM, by the way. And they’re up they’re optimizing tunes to basically run on these machines. Now, of course, you can run those local machines, but you also need great tooling to run things locally. And this is where the brand new local model integration in GitHub Copilot comes in, and there’s two things specifically. One is that Kayla showed off like

31:10 um auto local routing, and specifically that was um turning into efficiency mode, and the model um the the the router can route to a local model on disk automatically. And this efficiency mode has a little like little leaf icon, which is very cute. >> Okay. >> Um but the thing that I think is even more cool is the hydrofusion support, which we did an entire podcast on. And hydrofusion can then decide to delegate out different tasks to different local

31:40 models on disk and make decisions optimizing your token usage across the board. And this thing is coming to like everything basically um out of the box along with all that sandboxing things that happen. And Kayla had a really good demo, which was hey, like I’ve done this repo, and then I’m doing these investigations, and I might be using like a frontier model in the cloud, and then it may decide to then delegate locally, you know, accordingly for that those different tasks and run off sub-sessions. Uh she also showed off

32:13 uh I think she also showed off automations. And actually, this this is actually really genius. Um I was talking to Kayla about her usage of local models on her machine, and she said a lot of what she’s doing is yeah, she does have If she’s like, “Hey, I’m about to do something that is going to take a while, and I don’t actually care about like I mean, time to first token is important, like, you know, and then token like coming back. But if she’s like, “Hey, listen, I know that my local models are never going to run as fast currently as like if I’m running like Luna to go do a thing. However, if I’m like, ’Hey, I’m about to jump in a call and I have a half an

32:45 hour, an hour, whatever it is, or overnight to run long processes, what do I care if it’s running locally on my machine or if it’s running in the cloud, right? Um besides that I’m going to save a bunch of money.’ And then she said she actually has a bunch of automation set up that run every single night at midnight when she her computer is just sitting there with nothing else to do and isn’t crunching via local models to do a bunch of issue triage, bug triage support, like kind of like these workflows automatically that can then

33:16 fire off new sessions or do a bunch of computation. And she’s like, ‘Now that’s all just free for me, right?’ And then she also showed, you know, like what she was showing in the Hydrofusion examples. It may start with a cloud model, local model, go back to cloud It can go back and forth, but it’s going to figure out what it needs to do and what local models you have readily available, which is like super crazy to think about. So, and she I don’t know if she showed it, but what she was really showing is like you now could basically, for all intents and purposes, like just boot up something like this, turn on airplane mode, and go, right? So. >> Yeah.

33:48 >> It’s so cool. Uh your your computer will get warm during that process though, I promise. >> [laughter] >> So, you can use it as a heater. You know what it is? It’s it’s liberating. Um maybe you don’t experience this cuz I think you have infinite tokens. But, for those of us with limited tokens, um I’m always worried about like I’m always watching the like how much usage do I have left? Am I over my budget for you know, I I’m always like looking at the date. Oh, it’s the 10th, there’s 30 days in the month, so I should be at 30% and you know, I’m doing this like stupid

34:20 math in my head. But, when you use a local model, and even a stupid one, it’s very liberating because you’re just like, “Oh, I have as much as I want. I can just have this thing chugging and burning whenever I want. There is There’s no little background clock in the back of my head yelling at me, “Hey, don’t do this task because you want to save your tokens for that other task or things like that.” When you have a local model, you’re just like, “I’m going to use it and I’m going to Yeah.” Even the best models out there, I was

34:51 just yelling at Astra and Astra was using up my entire month of credit in like 2 hours when I use it fully. And even then I’m yelling at it because like, “Yeah, that’s an ugly button. You made your button ugly. It should be better than that.” And I find I yell at my dumb models and my local models just as much as I yell at Astra. So, I I would rather um be burning just electricity here in my home and yelling at the model than worrying about token counts that I’m paying for cloud models and all that. So,

35:23 if you haven’t been lucky enough to experience local models, I don’t want to go and say like they’re just as good as the big cloud ones cuz they’re not. They definitely aren’t. But, what they are is liberating. You just have zero guilt. You’re just like, “I’m just going to use this model. Maybe it’s on an airplane. I don’t fly that much anymore, so it’s fine. I don’t care about the airplane scenario.” But, what I care about is just not worrying, not thinking about my quotas and any of that stuff. >> We were sitting there doing these demonstrations and um one of the demoers was booting up one of these models and just like let it rip

35:56 for like 30 minutes and after 30 minutes I had like a full video editor and I was just like, “Cool, here it is.” And there was a The whole thing was in airplane mode. I was like, “Really?” Kind of crazy and like you said very liberating and like, you know, token usage zero. I think you need to It’s a blend, right? You need to use the right model at the right time and then, you know, especially with those like long-running processes. Like I had a session that ran for 100 hours um fully. You know, I you know, was cranking and testing some things out and just going to town, right? And this is like a blend between frontier models, local models, all these other things and

36:27 bopping back and forth between them. And I think like that’s a really unique scenario where I was just like set it and forget it. You know, I’m going to be in San Francisco, just like let it I’m not even I’m not even have this computer. My computer’s at home. What am I doing? I’m not even checking in on it. I’m just like autopilot YOLO. I’ll come back on it. It’s sandbox. It’s good to go. And I think that’s like a very intriguing scenario. I mean, the other thing that they also announced, but actually didn’t like show. I mean, they showed, but they actually have these like AI supercomputer like tower things. Like I don’t know if it’s it’s I don’t

36:59 know if Satya called them like a token factory or something. I forget what he said. Something like that. But basically, there’s these huge like basically servers that, you know, kind of server towers, you know, a DGX stations, um which are these huge stations that they’re talking about running Windows now. And these are apparently using a GB200 Grace Blackwell Ultra chip DGX workstation. It says it can unlock power to run frontier models from Llama 4 Maverick, Kimik K26, DeepSeek 4 4 V4

37:30 Pro, and more than a trillion parameters on these things. Oh my god, that is crazy. >> the professional-grade model runners. Maybe someday I’ll get a 10-year-old one. That would be nice, but I think there was a cute little um after word during the presentation where they were just reminiscing about like the computer industry, and they’re like, “Do you remember when ChatGPT was trained on a DGX 1? Do you remember that DGX 1?” I’m like, “Guys, that was like 3 years ago. It’s not that long ago.” I’m like,

38:03 “I would still kill for that DGX.” >> Yeah. >> And they were acting like it’s all old hardware. They’re like, “Ah, we just have those we we put those out to pasture, shot them, and left them for the carrion.” >> [gasps and laughter] >> I’m like, “Guys, I’ll take your old DGX. Just Satya, Frank will take your old DGX. It’s cool. It’s cool.” >> Yeah. >> [laughter] >> Um well, there’s a few other things in like Windows Windows itself. So, there’s a lot of things around performance, search optimization, making search like the most amazing thing in the entire world. I think they really focus a lot

38:34 on here are the improvements that we’re making to core Windows, how we’re making it sort of an agent-first operating system. And I thought that was really cool how like agents are deeply integrated. And also, I think how they’re evolving Copilot. And specifically around this whole idea that you have this home code and autopilot. And home is really like I am on my machine. I have the context that is my in this case, like I’m in our consumer mode, right? Like I want to write documents. I want to do stuff. And I want to be safe. And I want to not just be, you know, you know, YOLOing it

39:07 out to wherever contacts. But basically, you can you know, Copilot can understand relevant content on the PC, including files, recent activity, local context. And the cool part about accessing these is it can also tap into local actions. So, it can take actions on your behalf. So, it can organize files, diagnose device, troubleshoot issues. It can obviously code. It can carry out workflows. It can basically do anything you want. And I’m thinking of like this kind of like what’s the next gen of like shortcut type of thing actions. But then it also can tap into local models too running on

39:38 your device. So, when it’s accessing these things, it’s able to access the same models that you might be using for coding or these other things to actually do this work. Which is really cool. So, they’re really talking about this hybrid intelligent MXC support built in. And then the idea that you’re going to have these raw long-running personal um agents too. And to your point of like what are people doing, like actually, the thing that I’m doing at work often is, you know, inside of Copilot, like Microsoft Copilot, is I am, for all intents and purposes, having it gather a

40:12 bunch of my work intelligence. Like I do this is a thing that I do. Like I’m planning right now a bunch of our Copilot a GitHub Copilot like advocacy efforts, right? What are we doing for each the rest of each one and then H2. And what I needed to do is I needed to tap into my emails, to my messages, into my files on disk, and into these conversations, and I needed to, you know, tap into other planning docs, co-worse things together, look at latest news on the internet, pull things in, and then take this and then transform it into docs and reviews and these other things and then messages and

40:46 send things and do follow-ups and like and that’s the thing that I’m actually doing at work, which I I wasn’t really doing all that much like 6 to 10 months ago, but I’ve been trying to do a lot more of those processes as these tools gotten better. And I actually find myself doing this too often is like in the Copilot app, what I do end up doing today is like I’m we’re doing a lot of house projects, right? And I’m doing a lot of um like contractor reviews and all these other things. And like right now I’m I’m dragging and dropping files into a thing and doing like I would love to just be able to do a lot of that

41:18 integration into Excel and into these other things like in this workspace. So I’m really excited about how that’s evolving and how these, you know, agent harnesses are running. I’m not sure if I’m there yet. Like I’m not an open claw Hermes like person at this point. Like I I use them in some regard, but I’m starting to I think once you start to see how other people work that I’m interested. Like I’m not really interested in giving meta all my data. Like everyone’s like really excited for a muse. I have zero interest in giving meta all of my data, right? Like I’m not interested in that at all.

41:52 I am really interested in local models being able to do computation over my stuff, which I think of Apple intelligence, right? Those models that are running local on your device. Like you Apple when the local model trend is there and you know, they’ve been trying to evolve that in the latest devices and the leading opera latest operating systems. And I do like this idea of hybrid. I think this is I don’t know if I don’t I haven’t tried Apple intelligence and and Mac OS 27 yet on my machine, which I have here. Um but

42:22 from my experience of what I saw when I I saw people trying to use Siri was it would ask it a question and then say, “Oh, I can’t do this right here. I’m going to go to the cloud.” That’s almost hybrid, right? Except for you’re doing these actions. In this case, it’s automatic hybrid. It’s going able to be able to do these smart things locally or remotely and configure this for you. Now, I think that the biggest thing that Apple got right that I’ll be interested in this experience is the seamless one-button click turn it on. Like I think that’s really

42:53 important. Like inside of Xcode, inside of um your Mac OS machine inside of your iPhone, you say, “Do I want to use Apple intelligence?” And you say yes, and then that’s all. You don’t have to worry about what model am I using? What am I doing? XYZ. That’s what I would like to see from this experience is like, if you want to go bits and bop and pick your models, go for it. But like we’re going to give you a bunch of defined models that are just really good at doing certain things that you’re going to be doing locally anyways. Like, you know, doing text or doing image stuff or doing like profile processing.

43:28 >> Yeah, absolutely. And I you’re really hitting the nail on the head. And I got to say, I don’t think either operating system’s quite there yet. Because ideally in the future in the same way I can pick which search engine I want to use in my browser, I can just say use Google or whatever, use Bing. Um I would like to be able to under Siri and Apple intelligence or Siri or under Windows ML, just say like “Here’s a model I downloaded from Hugging Face. Use that for everything. That’s the model I want you to use. I want you to

43:58 use it locally. Don’t log it to anything. This is the model.” Um but sadly right now we’re still in the case where um Apple releases one model. It’s the model that comes with the operating system. The the model that comes with macOS 27 iOS 27 is different than the model that came with 26. And I feel like Windows is going to kind of be there right now, too. Plus, Windows is in a really good position because I got to tell you, Apple’s dropped the ball a bit still with Siri. I’ve been using it for a while. I am not amazed. I was arguing

44:29 with it all afternoon where I would keep asking it questions. And I wish it would say the thing like you said of uh it’ll say, “Hey, I’m going to go use ChatGPT or whatever right now.” No, all it kept saying was, uh “I didn’t quite catch that. Do you want to try again?” I’m like, “No, you you obviously got the text. I can see it. You printed the text right there. You got it. You’re just not acting on it.” >> So, for whatever reason. And it doesn’t make any sense to me because I know I use the local model. It’s >> Yeah. >> Like, it can do this stuff. So, I don’t know. There’s there’s Apple’s dropping the ball. I think this is a perfect

45:02 opportunity for I don’t know, Windows to catch up, but Windows to get ahead quite a bit because the demo they had for the start button and search, like they were saying it’s faster than you can type. Now, I know some fast typists out there. So, I’m curious to how just how fast it is, but like >> Yeah. >> the demo looked great. I know it’s easy to make a demo look good, but you know, time will tell when people get this installed on their machines, but I think they have like Apple should have the lead in the same way Google should have the lead in AI. [laughter] All

45:32 these people who should have the lead don’t. Uh so, this is a great opportunity for Microsoft to like really make some inroads. And I know they’ve gotten a lot of flak like Copilot this and that, and the brand is getting a little bit um overwhelmed in trying to put AI into everything, but like the Windows search box is a perfect place to impress people. If you start impressing people on that box, you’re going to get a lot of converts. They’re just going to get used to it. You’re going to set a new bar, a new standard for what your computer should be able to do. And um

46:05 help someday Mac will catch up to them. >> [laughter] >> At least to that demo. >> Well, and I think if the the if users are starting to get used to this aspect, like when you Google or you being or you like search search something into some box and you start to get these AI summaries and you start to follow up with AI, you start to get used to this and you almost want that as the default experience. It’s almost like looking forward, okay, are people are people there now, right? That’s the problem is you try too early or you’re first one of the first there, you know, it’s going to take a lot of revs to get it right and you’re going to maybe make a lot of

46:35 people mad and you’re going to make some people happy and then, you know, maybe you’ll lock it and hopefully so. But let’s talk about the last thing. >> Okay. >> there’s many there’s probably more things that we could cover, but a thing that I am most excited about in this moment is not a laptop. >> Frank Kerrigan. >> Okay. >> Mhm. >> What else is there? >> PlayStation 2. No, it is a brand new It is a brand new uh it’s a It kind of looks like a hybrid between like an Xbox and a PlayStation 2 like slim which is the Surface RTX Spark Dev Box and I’m pretty

47:10 sure they showed this at Build. Um I think I’m pretty sure it was there and if not, well, something was there. But okay. Right? I think it was there. But this for all intents and purposes is very similar to the um Ultra. However, there’s one configuration, you get one you get one, that’s it. >> One price. >> One configuration. And this really is I believe it has a default out of the box um Windows 11 experience for developers. Like it is it is a a special image that is made for developers. I don’t know

47:43 what that means, but they said it uh there for like what it’s supposed to be. I’m pretty sure that’s what it is. But it is a the same 6,144 core GPU, 20 core CPU, the biggest. It is 128 gigs of LPDDR5X unified memory and it is the biggest SSD, the 2 TB, which is removable by the way, in this puppy. And this thing looks just gorgeous. It is a big-ish, not super big, but big-esque, basically, desktop PC and it starts at

48:17 >> 6,000 bucks. >> Five. Yeah, [laughter] five five nine. >> Yep. >> Add US tax to that. >> US dollars. >> I’ve held it. It’s beautiful. It’s fantastic. And yeah, it’s it’s what I want. I think like I know it doesn’t have a screen, Frank, but also our Mac minis don’t have a screen. And I I tweeted after the event that it is official that my Mac mini is officially for sale. So, I am >> Oh, bye, James. >> Yep. >> Traitor. >> I’m done. I’m done.

48:48 >> bigger. It’s bigger though. It’s not mini. I wouldn’t call it mini. It’s It looks like it’s about the size of the laptop. Have you held one? Have you seen it in person? >> Uh I have, yeah. Uh the I have held it in my hand. Uh the question is are the are the technical specifications >> Right. Sure. Sure. Yeah, don’t don’t worry about it. Okay, yeah. They Well, they have it in photographs. They have it next to the laptop and it looks roughly the size of the laptop. It looks like a giant pancake. Um it’s it’s definitely >> [laughter] >> What I appreciate is they’re not ripping off like the Mac Studio design or

49:19 anything. This is a pretty unique design. It looks more like a game console than anything else. Your PlayStation 2 reference is actually pretty pretty spot-on, I would say. My biggest question is where are the fans on this thing? Cuz again, I use my GPU as a heater. I need fans on it to distribute the heat throughout the whole room so that while I’m training neural networks, I can also be heated this winter. That’s a very important feature. So, I’m curious how this thing thermally conducts its thermal. Yeah, I was just cuz um it’s pretty thin. You know, it’s it’s kind of like a two-story. It’s got

49:53 a smaller bottom than a and a bigger top. It’s all mushroom-shaped. >> [laughter] >> And it was a little bit confusing like where they’re putting all the fans and everything on it. It’s gorgeous. I I love it. It reminds me of like the old Sun Microsystems boxes. I don’t know if you remember any of those from the early internet days. Okay, no, never mind. Um my biggest complaint cuz I was telling you before we started recording is for roughly the same price, it’s almost costs as much as the same configuration as a laptop, but you’re not getting a screen, you’re not getting

50:24 a keyboard, you’re not getting a touchpad. Uh what you are getting is about 25 more watts of power. I should say that the laptop is 140 watt power supply and this puppy is 165 watt power supply. I still think that that’s a little bit on the low end for my personal taste because my 3090 right now is literally taking up 350 watts of power. So, it’s already running double the amount of power um that this thing can produce. Now, obviously, this is a

50:54 more modern chip. It’s going to do better. It’s a it’s a more efficient chip than my guy. But, you’re still stuck within that power envelope. So, it’s good to know that um with a laptop, you’re in the 140 watt power envelope. With this guy, you’re in the 165 watt power envelope. And these numbers matter. Like, physics matters. You got to shove electricity into these things in order to make them go fast. Um so, it’s it’s pretty cool to have this box out. I don’t know who’s going to buy one.

51:25 Um I I hope that you’re able to make a lot of money on your Mac mini. I’m going to be so sad that you’re not going to be my Mac mini brother anymore. I’m just going to be out here Mac miniing by myself. But, I hope you’re able to get at least 10 grand for your Mac mini so you can buy two of these things. >> I did look I did look and I did see that I should be able to make a few hundred dollars off of >> Will you, really? >> Yes. >> Okay. I don’t know, did you see Did Miguel say he’s going to get the six-pack of these? >> I don’t know. I didn’t I didn’t see. >> [laughter] >> He should. >> A six-pack of these dev workstations, that’s going to be pretty awesome.

51:59 >> Yeah, I’m I’m pretty jazzed. >> I can’t I can’t argue. It’s just a lot of money. >> It’s a lot of money. I’m a I think, you know, for me, obviously, we’ll keep my MacBook Air because I do iOS development. I need a Mac around. Like, you cannot get around it. And the M1 still It’s still a great device. I don’t know, man. It’s still just >> I know that the the rumored like OLED Apple laptops coming out in a couple weeks. Oh, which by the way, a correction for last week. So, the current rumor is they are touchscreen, by the way. So, I don’t know. Did they say whether the new Ultra is a

52:33 touchscreen or not? >> The Ultra is a touchscreen, yeah. >> Yeah, I figured as much cuz Microsoft laptops have >> The the touch sans, yeah, Ultra, whatever it is. >> So, I think I said on the podcast that it wasn’t going to be a touchscreen Mac, and it hasn’t been announced, so this is not official, but the current rumor mill is that it is actually a touchscreen Mac. So, I was like, maybe it is time for me to upgrade, but then I’m like, look at it, my cute little M1. I’m like, you’re such a trooper, little M1. I don’t think I could ever sell you or get rid of you. Like, if I ever drop you down a six-story building or something

53:04 like that accidentally, then maybe I will >> [laughter] >> upgrade, but you’re right. It’s hard to get rid of that thing. It’s been so much value for the buck. >> [laughter] >> Yeah. I’m I’m super jazzed on it. This is my current plan. And, you know, while I I really do like my my my Mac mini, and it’s really great. I I just actually don’t even know if I’ve taken as much advantage of it as I as I should. I mean, no, nor will I know if I will take advantage of the the dev box or not, but we’ll see, at least. And I’m excited to go through

53:36 this journey of where I’m at. So, the the interesting part is just like I went through tons of transitions with Thunderbolt 5 and this and that. Okay, will I go through all this again with all my crazy setup? I will say this though, I’m also reducing My plan is to reduce um my ultra-wide. I’m getting rid of my ultra-wide. >> Okay. >> convinced by John Galloway that this $200 Dell 4K monitor that he got on big day deals was what I should get cuz he said it was good and I said I don’t have Amazon Prime so you’re going to need to buy it

54:07 for me wink free free monitor. Um so he said he said so so it’s it’s coming to the house which is good uh which is nice. And um getting rid of that I want to like redo my setup yet again obviously. But um It just it it’s really tricky like I I don’t I I I’ve never really felt like like um I think when I was building my custom-built tower desktop PCs cuz I was designing what it was. I was

54:39 understanding the ports. I was putting everything in it like it was perfect. I don’t know if I ever had a perfect monitor setup but I do feel when I had two dual screens that like felt correct like a dual screen monitors out of it felt correct for a while. [snorts] Um but I do Yeah, but I do feel like I really want to trim it down. That being said Frank Krueger I could be convinced into an ultra because it has the other monitor right? I would have another monitor that’s there that I could use in accordance with this new 27-in 4K monitor side by side.

55:13 Like I think about it, you know what I mean? I have to get a stand for it. I got to do something. I just think that that dev box would look so sleek just sitting there. We’ll see. Uh I don’t know. Who knows what I’ll do uh in general but that’s where at least where I’m at right now in my mind. But I’m really excited. I feel like you know I’ve always been a Windows person and when the Mac mini came out the size of it the power of it spoke to me and so does this dev box. It really speaks to me as a as a aesthetics developer mini PC that I want.

55:45 And uh I think I’m going to get it. So, we’ll see. >> Oh boy. Well, I know I’m going to send you a bunch of models to try on it cuz I’m going to be curious how fast it is. >> [laughter] >> So, I’m going to make you test a few things. >> uh remote desktop access into your own private account. That’s all I need. >> Make it into a proper workstation server. >> Yeah. >> Oh, we didn’t mention the most important part of the laptop. Before we go, I just have to say don’t call it MagSafe, but they added MagSafe to the laptop. >> [laughter] >> It is though. >> Wild weirdest little USB-C connector

56:17 you’ve ever seen in your life, and no one believes it works, but I’ve seen video online of the people fake tripping over it. It seems to work fine. Um come on, Apple. Catch up. Because it’s pretty cool. It’s it’s a pretty cool design they did there with the USB-C cuz it’s USB-C and it’s MagSafe, but it’s not MagSafe. Copyright trademark Apple. >> it’s the world’s first magnetic USB-C. I have one right here. >> Yeah. >> Boom. There it is. And it’s always working. >> Have you proven it? >> Uh I have tripped over it many times. >> [laughter]

56:48 >> And it does work. Uh it does work. Yes. And it snaps right in. It’s it’s very very nice. So, >> Nice. >> um yeah, it’s it’s absolutely delightful. All right, that’s going to do it people for this week’s Verge Conflict. Go spend all your money on some new Surface devices. I am super stoked. Super good. But, it’s going to do it for this one. So, until next time, I’m James Wang from The >> I now and Don Frank Ruger. Thanks for watching and listening. Peace.