my name is Ken Flanagan. I'm actually on the product team at Dell Technologies that, formerly known as Precision. Really our performance PC group. So precision has been the brand for the last, nine, 27, 28 years. Now we are introducing a new rebrand and really a simplification of, a lot of subbrands. If you think about Dell as a company. And we ran into this all the time, we talked to people at conferences. We'd be at 3D Experience World, for instance, and we'd ask them what kind of machine you have. And they, you know, you're giving us feedback about the equipment. And a lot of times they didn't know anything more than it was a Dell. So we really are, you know, taking that to heart and simplifying, you know, whether it was precision or maybe you had some latitude. But there's there was a lot of other subbrands there. And what we've done is we've combined all those 11 subbrands into, into this overall stack. Now Alienware still a thing. So if you're gaming, that's not going anywhere. But the overall stack is Dell for consumers, Dell Pro for managed IT environments, and Dell Pro Max and Dell Pro Max is really the workstation class. It's our highest performance, machine. It is the most scalable. It's the most configurable. All the tenants of workstations are going to fall under Dell Pro Max and and a little bit more. Right. So when we talk about, you know, discrete graphics and, you know, the Nvidia RTX Pro line and the, the Ada gen of the RTX cards, that is exclusively going to be Dell Pro Max. So, also importantly, certified solutions are all going to be Dell Pro Max. We don't do ISV certifications for SolidWorks, for instance, on any other platform. They're just not, not built for that. So there is, a lot of words that come with these products, and I, I'm not trying to teach you everything about this, but I do want to position, you know what? All these words and they stack together. What does it actually mean? And it's most significant in, in the mobiles. Right. So in the mobiles you're going to see words like premium and plus or just nothing at all. And so when you see Dell Pro Max that is the traditional 3000 class workstation, entry workstation, kind of the minimum point for ISV certifications. But again, lower power CPU, less scalability, less options on a discrete GPU. And as you move up the stack to the most scalable, obviously you're getting into, what is intended to be somewhat of a desktop replacement if you need to be mobile. We're going to focus a little bit more on the towers. Today. And so the towers are simply called Dell Pro Max. And then whether it's micro slim, T2 and then you still see precision there. So our, our, our bigger systems are more scalable systems. The 58, 60, 7960 and 78, 75, they will still be around. You can still, order the, the Xeon and, and the Threadripper CPUs there, as well as fully configure with the, with the Nvidia RTX professional graphics so that that will continue. But the real sweet spot for SolidWorks users is, is that that T2 tower. And I want to talk about micro and slim a little bit. But just to level set precision will be kind of hanging around, but probably not for the systems that you'll be, purchasing, you know, next year and into the future. So now I also want to say that precision doesn't just fall off a cliff. When we we're in this transition. So there will, definitely be opportunities to, still buy precision machines. And as you see on some future slides, really form factor and a lot of the feature sets are very similar and fall in line with what everyone's been used to with the, you know, 3000, 5007 thousand series of, precision products. So I have this this chart, this is actually part of a document. I put a QR code in the upper right, and it's a two page document that just does a very brief overview of, you know, what is Dell Pro Max used for? Who's using it, what are the use cases around it. And some very basic product guides. So if I'm talking to a SolidWorks user, we generally categorize that as as a creator. Most tools that are modeling tools like SolidWorks are heavily single threaded. So they're we call them low threaded and they're going to value, frequency over, over number. Of course, when you get into number of cores on a CPU, then you're, you're jumping into a different, totally different platform where SolidWorks production design is, is really not going to be the fastest, the fastest, single threaded performing fixed machine is that tower T2. And so that's really the right place. But you can see across here in these columns, these are all kind of generalized workflows between people that are everyday SolidWorks users or people that that maybe don't need the scalability and configurability of a, of a full size tower. And so we call those generally people that are collaborating or even just smaller data sets in the, SolidWorks world. So this is the new naming. We will have more products, will have more configurability. As this all rolls out, I think some of the things that George from Nvidia will cover, even expands on this offering as well when we talk about AI development. So just want a level set new brand, you know, precision will still be around. You can capture this QR code if you want a couple. Just a two page, simple overview. All right, so this is a a slide that, the training folks had in there. And I thought it was great because it really does show. Yes. It's very different. The naming seems very different. But when it comes down to it, this is the next generation of, performance PCs, workstations with all the same tenants, that we've had in workstations. And these are the three models that we primarily focus on. And I'm going to start from, I'm looking at the Dell from side left, right, kind of smallest to biggest, so that that smallest one is the Dell Pro Max micro. And the differences in that micro. And we have had lots of customers that have tested the smaller form factor systems. But you are dealing with a lower power Intel Core Ultra processor. So an 85 watt processor, yet you can still put a 4000 class RTX Pro graphics card in there. And that's the small form factor Pro graphics card, but still quite a bit of scalability for the size of it. Those on the smaller side, those can be, installed in a rack, kind of a shelf, system. They can also be installed directly behind the display. They're portable, in a sense. They're actually, I have actually one sitting on my desk here. It they're really powerful. If you are, dealing especially with people that maybe aren't doing the heaviest data sets or dealing with, with, you know, day in and day out where they're really tied to that frequency. This may be an interesting option, especially if you're looking to increase your density in your on prem data center. If you're doing that, that, type of virtualization, we've had a lot of success with, with that real small form factor, but, you know, as you move up the stack, you're going to get a higher power, CPU that next one up is the Dell Pro Max slim. That CPU is going to go up to 125 watt. The memory is more scalable to up to 128GB. And, it does have the same RTX 4000 class small form factor or 75 watt, GPU availability. So, but a little bit more scalability in that, obviously a little bit less portable, a little, you know, obviously not racquetball in the same way either. But the T2 tower, that's really the the bulldog of, you know, most engineering firms that are running, any sort of level of complexity inside of a tool like SolidWorks. It is the fastest single core machine, Intel Ultra K series processors, up to 250 watt, up to a 6000 class, Nvidia RTX GPU. So incredibly powerful. Lots of scalability and, you know, easily the most popular choice for, more complex, more complex data sets. So just to position these, you know, on the left, it's 36, 80 that maps the T2, 34, 60. All these numbers are going away. And hopefully you can kind of see the, the logic in, in changing some of these names. It's, it's a little bit of a word salad. But if you kind of buy into, you know, how would you identify the kind of machine you have? I think this becomes much more, much more descriptive. the tools that you buy today, will be running the AI workloads of today and tomorrow. And so the versatility of the machines and how you configure them is going to matter for what's possible. There is, obviously a lot of attention paid to, GPU based, AI workloads, inferencing and development. But there's other AI going on in the system. And so when you look at the overall system, you're going to consider, all the different parts. So and I say all the different parts because I know everybody probably knows what a CPU is, the right CPU for SolidWorks users and Intel Core Ultra processor. If you're doing something like simulation, if you're doing something like visualization, and that's a heavier workload, you may want to look at the the more core but lower frequency options in the scenery and Threadripper. But the preferred, by far preferred graphics card that goes through the certification process on our systems is the Nvidia, RTX GPUs. The new Nvidia RTX Pro GPUs, and which you may not be aware of, is there's other AI, you know, functionality on these newer machines. The Intel Core Ultra nine actually has a neural processing unit on it. Now. Right now that's that's not widely used outside of things like the background blur and, you know, teams meeting, for instance. And what that is is basically a low power, low latency, neural processing unit sitting right on on the CPU. Obviously not perfect for every AI environment that's why the GPU there, that's, you know, higher power, higher performance, you know, option for any of those AI workloads as well. So any AI happening locally, you need to make sure that you have a system that's configured for that. And by the way, there's lots of reasons that AI happens locally. So that's probably a whole separate webinar. And maybe we'll circle back and talk about those workflows in the context of engineering at a future point. But I wanted to kind of lay out a little bit of education on what's going on in these in these machines that make impact, future AI workloads.