Hey channel insiders, I'm Katie Baboso here for partner POV onsite at scale computing platform 2025 in Las Vegas, Nevada. I'm speaking with IT innovators and partners from all over the globe today, including the gentleman joining me now. Please welcome Chris Laffy, senior product strategist, Think Edge at Lenovo. Thank you so much for being here, Chris. Thanks for having me. We also have Craig Tyak, vice president of product management for scale computing.
Welcome. >> Thank you very much. >> Thank you so much. So Chris, we know that Lenovo is a very well- reggarded hardware partner. Craig, obviously Scale Computing, a well- reggarded software vendor, but when we think about the two of you creating marketleading solutions together, why should channel providers want to be a part of that? >> Yeah. Well, well, Scale Computing and Lenovo, we've partnered together for years now to bring solutions to market.
What I'm excited about that we've announced this week is the SE100. It's a perfect example, right? So, Scale Computing brings proven marketleading technology, HCI stack. We we do exactly what we say we do and our customers absolutely love it. Lenovo brings this global reach to the market. They bring, you know, a great brand beside that. Uh, and kind of this joint solution together is really what the channel needs. Now Chris, I know that obviously when we talk about Lenovo and the products that you have, we're not thinking vertical specific, but when you think about going to market with scale computing, are there any use cases that come to mind that really showcase the value of this partnership >> where we're seeing a lot of the the traction and a lot of the momentum that's coming in?
Retail is a a huge opportunity for both of us. You know, Craig mentioned the SE 100. That smaller, faster, lighter mentality in a lighter budget envelope is really what retailers have been asking us for for the last decade, right? And we're able to meet that specific whether it's point of sale or it's loss prevention, selfch checkckout. There are number of employee tracking and management. There's a lot of different things that we can do. Also in manufacturing there's a convergence of IT and OT and some of the distributed nature of the cluster that we can do and putting it right where the the data is being collected right where we need to interact for things like quality assurance, safety, predictive maintenance, these types of things.
K through 12 is another massive space where it's a finite set of workloads but it's very budget conscious and it's you know very tight. So the solution that we're bringing to to market now really reaches into some of those corner spaces that we haven't been able to get into before. And we've seen success in a a lot of these verticals. This is just going to open that aperture up even further for us to step in and basically delight our customers cuz that's really what the bottom line is. >> Well, let's keep talking about your customers.
First of all, when it comes to hypercon converged infrastructure, why does scale computing stand out from other competitors in that space? And then why is that so important to your customers? >> The nature of scale being a relatively light infrastructure and providing a high performance and a light footprint really matches well with the the newer AI chips that are coming to bear because we have performance cores and we have GPU and MPU directly on the chip itself.
So getting to these newer AI workloads and driving these newer AI workloads with agility and a lightweight nature, we don't see that from the other hypercon converge vendors out there. And another thing is is that together we're really leaning into the edge. And one of the things that we see from other hypervisors is they're very protective of their data center business. So they're unwilling to go lighter to get to the edge. not only from you know specifically a budget envelope but it's very protective scale is actually leaning into that market space and together you know we're really innovating and driving a lot of new opportunities new adoptions and new workloads that are necessary for our customers.
So Craig, when we're thinking about scale computing at Lenovo, going to market together, creating solutions, how are you helping your customers and the greater ecosystem of partners harness the power of AI and inevitably plan for the future where AI is going to bring in more innovation? >> Yeah, I think we're right at this precipice right now of adoption of AI in the market. We're seeing really unique use cases around computer vision, machine learning, uh AI in general encompassing all of that and and it's, you know, we talk about having their horizontal platform that it works across industry.
It really is unique to every vertical and how they're bringing that uh that value to market. I think what what we're seeing right now is this this new SE100 we've been talking about is it has all the capability you need for what you're running today with the ability to expand it in the future. not only by adding additional nodes with the concept of our scale out architecture with scale computing, but also just the fact that it's got a GPU sidecar.
We know that these new AI workloads, we know that these machine learning workloads require additional compute beyond that of the CPU. And so, while we can get really efficient and do a lot with what you have today, kind of future proof you for the inevitability of of AI that we see in the market.
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