(upbeat music) >> In 2009, Cisco made a major announcement in the form of UCS. It was designed to attack the IT labor problem. Cisco recognized that, data center professionals were struggling to be agile and provide the types of infrastructure services that lines of business were demanding for the modern applications of that day. The value proposition was all about, simplifying infrastructure deployment and management and by combining networking compute and storage with virtualization and a management layer, Cisco changed the game for running applications on premises and the era of converged infrastructure was born. Now fast forward a dozen years, and a lot has changed. The cloud has gone mainstream, forcing new requirements on organizations to bridge their on-prem environments to public clouds and manage workloads across clouds. Now to address this challenge, Cisco earlier this month, announced a series of offerings, that meaningfully expands its original vision, to support the more demanding requirements of today's dev sec ops teams. In particular Cisco, with this announcement is enabling customers to deploy a full stack cloud-like operating model that leverages modern platforms such as Kubernetes, new integrations and advanced tooling to bring automation, visibility and better security for both hybrid and multi-cloud environments. Now the underpinning of this solution, is a new UCS architecture called the X series. Cisco claims this new system gives customers a trusted platform for the next decade to support their hybrid and multi-cloud workloads. Gents, great to see you, welcome. >> Hey, thank you. Good to be here. >> Thanks for having a us Dave. I appreciate. >> My pleasure. Looking forward to this. So look, we've seen the X series announcement and it looks to be quite a new approach. What are the critical aspects of the X series that you want people to understand? Maybe James, and you can take that. >> Sure I think that, you know, overall, there is a lot of change coming in the marketplace, right? We're seeing we're looking at and we're seeing from a technology standpoint, a significant amount of change. Look at CPU's and GPU's, the power draw alone is becoming, you know, it basically at the trajectory, it is, it may be untenable for some, you know, of the current configurations that people are consuming, right? So some of these current architectures just can't deal with that, right? Or at least they can't deal with what's coming in the future. We're also seeing the relevance of other types of architectures like maybe arm to start to become something that our customers want to take advantage of, right? Or maybe want to see how that scale fits into their environment on a totally different level. At the same time, the fabrics are really evolving at lightning speed here, right? So we're seeing PCI express, we've gone from gen three to gen four, gen five is coming in the very near future. We're layering on top of that, things like CXL to take that, that fabric to the next level for capabilities and be able to do things that we couldn't do before. To connect things together, we couldn't do before. Beyond that, we probably are just a few years away from even more exciting developments in the fabric space around some of the high performance low latency fabrics that are that are again on the drawing board today just around the corner. Take that and you, you look at the kind of the evolution of the the admin, right? So we're seeing the admin developer emerge. No longer is this just a guy who's sitting in front of a dashboard and managing systems, keeping them up and down, we're now seeing a whole class of developers that are also administrators, right? So all of this together is starting to push us well beyond what human scale really can manage, what human scale can consume. So, there's a lot of change coming and I think that we're taking a look at that and realizing that something like X series has to be able to deal with that change and the challenges that it brings, but also and do so in a simple manner that we can allow automation orchestration and some of these new capabilities to enhance what our customers can do, not to drown them in technology. >> You know, that taught, that's kind of interesting what James was saying about beyond human scale. I mean, I think my little narrative upfront, it was sort of, hey, we recognize as an IT labor problem. We're going to address that. And it really wasn't about massive scale back then, it is now. We really what we've learned from the cloud guys, right? >> Definitely. I mean, people are moving from pets to cattle to now with containers, they're saying that it's mosquitoes, right? Cause they're so ephemeral, they come and go and on a single host, you could have, you know, hundreds if not thousands of containers. And so the application environment has influenced the infrastructure design and really changed the role of the infrastructure operator to one that necessitates automation, necessitates operations at scale, even on prem everyone's trying to operate in that cloud like model and they're trying to bridge, the big challenge I see is, they're trying to bridge their existing environment big monolithic applications they've got on-prem with those data lakes that they built around them over the past decade, but they're also trying to follow their developers as they go out into the public cloud and innovate there. That's really where the nexus of all the application innovation is. So the IT teams who are already strapped for resources it's not like their budgets are going up every year, are now taking on a new front out in the cloud while they're still trying to maintain the systems that they've built with on-prem. That's the challenge. >> Yeah that's really the hard part and where some of the innovation here is, is anybody that lives in an old house knows that connecting old to new is very challenging much more challenging than building from scratch. But James I wonder if we'd come back to the to the architecture of the X series and what's really unique about it and what's in it for your customers? >> Yes, absolutely. So we're, when were looking at at kind of redesigning this thing from the ground up, we recognized that, you know from a timing standpoint, we're sitting at a place with the development of future fabrics and some of these other technologies that we finally have the opportunity to hit the timing perfectly to start to do composability right. So we've heard a lot of noise, you know in the market for the last several years about composability and how that's going to be the salvation or change the game here. But at the end of the day, the technology hasn't been there in those offerings, right? So we're sitting at the edge of some of the development of those technologies that are going to allow us to do that. And what we've done with X series, is we've taken a construct that we call the UCS X fabric, which is the ability to consume these technologies today as like a effectively a chassis fabric that can allow us to connect resources together within the chassis and future external to the chassis. But it also allows us to take advantage of the change in fabric that's coming. So as fabrics evolve, as we see new technologies like CXL and the PCI express gen five and beyond, come into play here and eventually physical technologies like Silicon Photonix, those are constructs that are going to allow our customers to do some amazing things and we have the construct to be able to consume those. Our goal here is like, to effectively look out at these disruptive technologies on the horizon and make sure that they're not disrupting our customers that we give our customers the ability to disrupt their competitors and to disrupt their markets, but by consuming those technologies in an easy way. >> You know, you didn't use the term future-proof. And I usually don't like that phrase because a lot of times people go that's future-proof and I'm like, well, what's future proof? Well, it's really fast. Well, okay. And in two years, it's going to be, you know really slow compared to everything else. But what you, what you just laid out is an architecture that's really taking advantage of some of these new capabilities that are driving latency down. So that's so, thank you for that. Now, Todd I get how the X series is going to enable customers you know, today I just mentioned the future but how does it play into Cisco's hybrid cloud vision? >> Well I mean, our customers aren't looking for, you know, point solutions or bolt on layers of software to manage across the hybrid cloud landscape. That's the fundamental challenge and so what we're doing with intersite, if you really think about all the systems that we have in our portfolio, like X series, really it's just extensions of our inner site platform. And there we're bridging the gaps between fundamental infrastructure prem, with all of those services that you need to optimize workloads and infrastructure, both in that on-prem environment but also out in the public cloud and even moving up the stack now into serverless. So we know that customers again are trying to bolt together a cohesive environment that allows them to manage those existing workloads on prem but also support the innovation going on out in the cloud and to do that, you have to have services to manage Kubernetes. You need hooks into modern tool chains like a Hashi corks Terraform, we did that a few months back and we recently brought in something we call our service mesh manager that came out of an acquisition of a Bonzai cloud. So what we're doing is, we're kind of spanning that entire spectrum from physical infrastructure, to the workload and that could be extracted in any number of ways either in containers or containers around VMs or bare metal running applications run on bare metal or just virtual machine applications encapsulation. So, you got all these different modalities that customers are going to run applications in and it's our intent to create a platform here that supports all of them, both on their on-prem environment and also all the resources they're managing out in the cloud. So that's a big deal for us. You know, one thing I want to go back to the X series for a second, something James mentioned, right? Is you know as we see subsystems in computing, start to decompose and break apart, you know, we have intersite as the mechanism to put Humpty Dumpty back together again and that's really, I think composability and district's options bar, but that's okay. But so I'll read it together. And like James said, you know be able to take on whatever fabrics, low latency fabrics, ultra low latency fabrics we need in coming years to sew these systems together, we're kind of breaking a barrier that didn't, that wasn't, you know people have trouble breaking through in the past, right? And that's this idea of true infrastructure as code or true software defined infrastructure. Cause now we're talking about being able to apply policy and automation, to the actual construct of a server. How do you build that thing to the needs of the workload? And so if you talk to an SRE or a developer today and you say infrastructure, they're thinking of Kubernetes cluster, but ultimately we want to push that boundary or that frontier between the world software to find it abstracted as far down in the infrastructure, as we can. And with intersite and X fabric and X series, we're taking it all the way down to the individual drive or CPU or ultimately breaking memory apart and sewing that back together. So it's kind of exciting time for us, cause really, pushing that frontier of what is software defined further and further down into the infrastructure and that just gives people a lot more flexibility in what they build. >> So I want to play something back to you and see if it resonates. Essentially, I look at what you just said is you're building a layer across my on-prem, whatever public cloud across clouds at the conventionally, you know, get to the edge, but let's hold off on that, let's park that for now. But that layer obstructs the underlying technical complexity and allows that infrastructure to be, you said programmable, infrastructure is code essentially. So that's one of my other questions, it's like, how programmable is this infrastructure, you know, today and in the future? But is that idea of an abstraction layer kind of how you're thinking about hybrid and multi-cloud? >> It is in terms of the infrastructure that customers are going to run on prem right in the public cloud the cloud providers are already abstracting that for them. And so what we want to do is bring that same type of public cloud experience to managing infrastructure on prem. So being able to have pools of resources that you allocate out to workloads, shifted as things change. So it's absolutely a cloud-like approach to on-prem infrastructure and you know, one of the things I like to say is, you know, friends don't let friends, build their own private cloud platforms from scratch, right? We're productizing this, we're bringing it as a cohesive system that customers don't need to engineer on their own. They can focus on their operations and James actually, he's a pilot, and one of the things he observed about Intersight a couple of years ago was, this idea of Intersight as a co-pilot and kind of, you know, adding a person to your team almost when you have intersite in your data center, because some very, what feels like rudimentary things are incredibly impactful day-to-day for our customers. So we have recommendation engines. If it, if like, you know, maybe it says some interplay between bios and firmware and operating system and we know that there's an issue there rather than letting customers stumble upon that on their own we're going to flag it, show them the correction, go implement it for them. So that it starts to feel a lot more like what they're accustomed to in a public cloud setting where the system has some intelligence baked in, the system is kind of covering them and watching their back and acting like a co-pilot day-to-day operations. >> Okay, so I get that, you know, the cloud guys will abstract the complexity you guys are focused on prem, but is it, so my question then is multi-cloud across clouds because we have some cloud providers, you know you're partners with Google they do some things with Antho, so I know Microsoft with Ark, but even near-term. Should we think about Cisco as playing that role of my, across cloud, you know, partner if you will? >> Absolutely. You know, cloud agnosticism is core to our approach because we know that, you know if you dial the clock way back to the early odds, right? When cloud first started emerging it was kind of an efficiency play. And you had folks like Nicholas Carr, right? The author that they put out the big switch, kind of envisioning a world where there'd be this ultimate consolidation to maybe one or two or three cloud platforms worldwide. But what we're seeing, you know we had data sovereignty kind of emerge over the past decade but even the past year or two, it's now becoming issues of actual cloud sovereignty. So you have governments in Australia and in India and in Europe actually asserting control over the cloud providers and services that can be used by their public sector organizations and so that's just leading to actually cloud fragmentation. It's not nearly as monolithic of future as we thought it would be. It's a lot of clouds and so as customers want to move around geographically or if they want to go harvest innovation that maybe Google is really good at something like machine vision, or they want to use AWS or Azure for different applications that they're going to go build. We're seeing customers really being put in a place where they're going to deal with multiple cloud providers and the data supports that. So it's definitely our approach especially on the networking technology side to make it very easy for our customers to go out and connect these different clouds and not have to repeat the integration process every time they want to go, you know, start using another public cloud provider. So that's absolutely our strategies to be very agnostic and build everything in mind for customers they're going to be using in multiple providers. >> Thank you for that touch. So James, I want to come back and talk a little bit about sort of your competitive posture here. I mean, you guys, when you made the announcement, I inferred that you were feeling like you were in a pretty good position relative to the competition that you were putting forth, not just you know, core infrastructure in hardware and software but also all these other components around it that we talked about, observability extending out to the, you know, beyond the four walls of my data center, et cetera. But talk a little bit about why you think this gives you such competitive advantage in the marketplace. >> Well I mean, I think first of all, back to where Todd was going as well, is that, you know if you think about trying to be, to work in this hybrid cloud world, that we're clearly living in, the idea of burrowing features and functions as far down the stack as possible, doesn't make a lot of sense, right? So intersite is a great example. We want to manage and we want to orchestrate across clouds, right? So how are we going to have our management and infrastructure services buried into the chassis, down at the very lowest level, that doesn't make sense. So we elevated our, you know, our operating model to the cloud, right? And that's how we manage across clouds from the cloud. So, building a system and really we've done this from the ground up with X series, building a system that is able to take advantage of all these two technologies. And you mentioned, you know, how being future proof was probably you know, a derogatory term almost and I agree with you completely. I think we're future ready. Like, we're ready to embrace it because we're not trying to say that nothing is going to change beyond what we've already thought of, we're saying, bring it on. We're saying, bring on that change because we're ready for it. We've we can accommodate change. We, we're not saying that the technology we have today is to going to ride us for 10 years, we're saying,, we're ready for the next 10 years of change. Bring it. We can do that in a simple way. That is, you know, I think, you know going to give us the versatility and the simplicity to allow the technology to go beyond human scale without having to you know drown our customers in administrative duties, right? So that co-pilot that Todd mentioned is going to be able to take on a lot more of the work, just like an airplane where you know, the pilot has functionality that he has to absolutely be part of and those are the our developers, right? We want those admin developers to develop, to build things and to do things and not get bogged down in the minutiae that exists. So I think competitively, you know, our architecture top to bottom, you know, all the way up the stack, all the way to the bottom is unique and it is focused on not just the rear view mirror but what's coming in the future. >> So my takeaway there is that, okay, I get it. The new technologies will come along but this architecture is the architecture for the decade. You're not going to have to redo the architecture in a few years. That's really the key point here. Todd, I'll give you last word might just taking some notes here and takeaways that I heard, I heard upfront. Chip diversity really take advantage of all the innovations that are coming out. You're ready for that. You're kind of blurring the lines between blade and rack, giving some optionality there. Scale is a big theme. I mean, the cloud has brought that in and, you know people want to scale, they don't want to be, you know provisioning lawns all day and they won't be able to scale if that's what their job is. Developer friendly, particularly as it relates to infrastructure as code. And you've got a roadmap. So Todd, that's my summary. I'll give you the last word. >> No, it's really good. I mean, you hit it, right. We're thinking about this holistic operating environment that our customers are building for hybrid cloud and we're pre-engineering that environment for them. So our Intersight platform, all of our systems that connect to that, are really built to tackle that hybrid environment from end to end, and with systems like X series, we're giving them a more simple, efficient landing spot for their workloads on prem but crucially it's fully integrated with this hybrid cloud platform so as they have workloads on prem and workloads in the cloud, it's kind of a transparent environment between those two, between those two, two worlds there. So bringing it together so that our customers don't have to build it themselves. >> Excellent. Well, gents thanks so much for coming on theCUBE and sharing the details of this announcement. Congratulations, I know how much work and thought goes into these things, really looking forward to its progress and adoption in the marketplace. Appreciate your time. >> Thank you. >> Thanks for time. >> And thank you for watching this cube conversation. This is Dave Vellante. We'll see you next time. (upbeat music)

>>Live from Orlando, Florida. It's the cube covering Microsoft ignite brought to you by Cohesity. >>Welcome back everyone. You are watching the cube. We are the cube, the ESPN of tech, and we are here at the orange County convention center for Microsoft ignite. I'm your host, Rebecca Knight, sitting alongside of my co host Stu Miniman. We are joined by Dave Cahill. He is the principal PM Bonzai at Microsoft. Thank you so much for coming on the cube. Thanks for having me. It's been a while. Has been by your back. That's right. So you are now, you were the COO of Bonzai. You are now part of Microsoft. There was an acquisition about a year ago. Tell us a little bit about bonsai. It's the AI business system. Got a shout out from Satya on the main stage yesterday. Tell us a little bit about bonsai and then about the transition about now being part of Microsoft. >>Yeah, sure. So the, the big vision for Bonzai from the founders, Mark and Keene was how do you build a set of tools? This makes AI more accessible than to just data scientists. How do you open up, ended up to developers and subject matter experts. And so from day one they've been focusing on building this abstraction layer of platform set of tools. They really enables more than just data scientists access to the low-level mechanics of machine learning, of deeper enforcement learning. Um, everything we've been working on really they've been working on for four years prior to the acquisition was, uh, building out that tool chain. And from my side of the world it was where did we figure out where to point that? Where do we, where are we seeing the strongest traction and adoption for the tools? Early days, uh, from a go to market perspective. And so while they worked on the technology, we really found a pocket of interest, uh, in these real world, often industrial systems. Uh, and so inside Bonzai that's a lot of the work we were doing was taking that platform to market. Um, as part of Bonzai. And then, you know, of course post acquisition, we're doing a lot of the same >>thanks so accessible AI. I love the concept, but what does it really mean? So this is so that someone could be a subject matter expert in an industrial company and be able to still program. Can you explain a little bit, give us an example of, of what bonsai was? >>Yeah, sure. And I mean there's a lot of low level mechanics and machine learning, the algorithms, the toolkits, et cetera that are, that are difficult for just anyone to pick up and start programming. And so the idea here is how can you write an obstruction layer above that? And in this case, it takes a foamer for programming language that allows a developer or subject matter expert to break down the concepts of the problem they're trying to solve in, in, in business terms, right? And so if you think about a wind turbine or a drill or um, a baggage optimization system, it's not the data scientists that intimately understands the behaviors of that system and how it works. It's the subject matter expert that can practically stand next to it and understand or hear that it's starting to fail. Or they know the, the way to turn the knobs most optimally to figure out how to program that system. Now if you just took a of data and threw it at infrastructure, eventually it would figure it out the patterns and how to optimize that thing. But you have a subject matter expert inside the four walls of your organization that readily knows how to solve it like that. And so why not empower them with a, a programming language, really a mechanism to outline the core concepts that you want the AI to learn because they've spent their entire career, uh, trying to figure them out. All right, >>so yeah, Dave, yesterday, Satya Nadella talked a bit about the autonomous systems and if I got it right, he said, we're allowing those engineers to really build systems, become the teachers for what's going on there. So help help frame this a little bit as to where this fits into kind of the broader AI discussion that Microsoft's having with companies today. >>Yeah, I think there's, there's a obviously a massive AI portfolio at, at Microsoft and there's lots of different applications and systems and use cases that are fit for more and more intelligence in the form of AI and machine learning. What we've seen is that an opportunity in the real world and the physical domain that requires a different set of tools and techniques than maybe in the logical, you know, our data centric domains. And oftentimes in the press you see a lot of emphasis on supervised and unsupervised learning and very data centric use cases for the logical world, right? For, for databases or CRM systems or things like that. We believe there's this massive opportunity in the physical world. And when you get into the physical world and these vast practically infinite state spaces, you need different sets of tools and from a machine learning perspective, different sets of techniques. And so I think Microsoft looks at the entire portfolio and says, you need the right tool for the job. Um, as opposed to hammer nailing everything. And that's really the autonomous systems piece is really our effort in real world systems. So >>David, you know, when I'm listening to what you're saying there reminds me of some of the discussions we've been having the last five years or so about the industrial internet. A lot of the OT systems here, which really outside the domain of traditional it or though some of the same challenges that your your team's facing. >>Absolutely. So OT, it's interesting you bring that up. Um, oftentimes the teams that have time inside an organization to pick their head up from their day job to look at new emerging technologies aren't in operations. They're not in the business because they're running the business. And so you have to be able to bridge the gap between central technology, central and innovation teams and those that are actually running the business. And I view OT as kind of the, the kind of mortar between those two bricks oftentimes as the one that has to accept this technology and figure out how to deploy it. And that's just not technically that it works, but also kind of commercially and from a safety risk, trust perspective. So OT really has a, a big role in this. And understanding, not that it just solves the problem technically, but it actually can be deployed, um, in ways that fit within corporate security requirements, data privacy requirements, trust, et cetera. Um, it's not, you know, there's a, there's a, there's a lot of gaps to be bridged there. So I saw this, this, this, like autonomous systems have been projected to grow to more than 800 million in operation by 25. Right? >>That's a big number. So what are you doing within Microsoft to do prepare for that? >>Yeah, so I think I view autonomous systems. It's not a product, it's an endpoint, right? This is like 2000 when VMware came out and said, listen, you're on the journey to the virtual data center. Right? And their customers were in physical data centers trying to go virtual. The journey towards autonomous systems is kind of that we're on that same path. And really it's about providing customers the tools to, but I them along that journey from where they are today to kind of full autonomy, full autonomous systems. And it's a, it's a, it's a maturity, right? You start out, you know, just managing that system, you're maintaining it, then you're, maybe you're, you're optimizing it and you're, then you're controlling it a little bit better, but there's always a human in the loop and then you're at full autonomy. And I think along that path there's lots of different pieces or tools and technologies that we can bring to bear to help them on that journey. Um, technically, commercially. And then also from a safety and trust perspective. And so a lot of the work we're trying to do is build out that tool chain and, and we think Bonzai is a core piece of that actually at the, at the center of what we're trying to do. >>So how, how when you're talking about the human and the aluminum, I'm, I'm imagining a subject matter expert who is working in concert with you developing whatever, whatever tool it is that is going to automate something that they are the subject matter expert, as you said, can fix it like this. Calibrate the buttons and know when a system's about to fail. So how, how trusting are they in terms of, Oh, so this is no longer something I'm going to be doing here. How, how, how do you work with them and, and helping them understand? No, really you can trust this. >>I think it's really about, um, augmenting and scaling the work of the, of the experts and, and oftentimes in every customer engagement we have the subject matter experts are excited because they're literally caudifying their expertise and then figuring out how to scale it. Right? Those experts are frustrated because they are the subject matter expert by definition. They're the problem solver for that problem for everybody in the organization. And so the ability for them to take that expertise in scale, it means more time for them to do what they really want to do, which probably isn't solving problems tactically for everyone. That's not at the expertise level. They are at the executive level. It's about scaling that quality of work so that your expert, you know, your best expert for tuning this turbine can then be scaled across the organization and you're reducing, you know, training costs and other things because you can scale that expertise more effectively. >>Yeah. So Dave, what are some of the big challenges that customers are having? Is it the availability of the expertise and hiring the right people? Uh, you know, we, we've looked at, uh, you know, the, the big data wave, uh, you know, half of those deployments failed for, you know, so many different reasons there. You know, why, why, why, why will this be different? >>Yeah, I mean it's certainly not without challenges. I mean, I think the, one of the things where we run into, you know, data readiness, like I naively thought because we use simulations, we got, we got over the cold start problem that, you know, we don't have data, we'll just use a simulation instead, I think to get around the idea that simulations, there's this idea of a simulation, which is where we train our environment in. And I can kind of go into that in detail, but that's very different than a machine learning ready simulation and having a simulation that runs. It can be parallelized, it can run on Azure that works fast enough to train. These are all impediments to just getting to train these models before you even get to the actual model working in the real world. And so I think the pipeline for training these models is as intense in some cases as you know, data centric training environments. >>Once you get that model trained, it's been about deployment and you have a whole different set of challenges and that's where OT comes into play is starting to figure out, okay, how do we operationalize this model? Is a human in the loop? Is there a a mechanism to to stop the AI and defer to the human right. And we see a maturity model there as well where customers are starting with decision support, which means you know, the AI is not controlling the end system. It is making a recommendation and then a business analyst would then implement that in real time. But walking through what those procedures look like is something that most customers haven't done yet until they're like right at that last step ready to deploy to saying, wait, who's going to watch this? What, what is our safety procedure for deploying a drill, an autonomous drill? It usually doesn't exist in an organization today. >>Yeah, it sounds, it's a little bit different as to, as opposed to, you know, just your regular it operations and you kind of say, here's the five step model. Oh wait, I've always done this. You're, you're attacking some new challenges here. So are they a little bit more likely to move a little bit further and let the autonomy take over? Is that the case? >>Um, I mean, I think so, and it's, it's certainly lines of business, right? This is not, it is there to kind of manage the transition as needed and kind of watch over for security and privacy concerns. Um, I don't, I don't see the hesitation around the autonomous nature of it from the business users. It's, it's people around the periphery, whether that's security or compliance or safety that is most concerned about that. And organizations I think are still trying to get all of those people in the same room and develop policies around that. And oftentimes for better or worse, we're the, we're the forcing function to get them all in the same room and say, okay, what is this going to look like? But, but I, I see the businesses as really driving for the smarter and smarter and increasingly autonomous systems and excited about those pieces because the, the efficiencies to be gained from, from that are so significant. >>And a lot of these use cases I want to ask you about innovation. So this is, you are part of Bonzai and now you are part of Microsoft, which as big tech companies go is, is a rather mature company. We've had some guests on this week who've said that Microsoft actually feels like a lot like a startup. Yeah. I'm interested to hear the, the approach to innovation, the mindset that your new colleagues have and how you are keeping that, that more startup agile approach and that inclination in this big company. Yeah. So I can certainly speak to our experience with Bonzai. It's been pretty neat. I think as having been acquired a few different times by different companies, the way that Microsoft has landed this technology has actually been quite interesting. And we sit within a team within Microsoft research called business AI and business AI's entire charter is to incubate either required or organically developed technologies to the point that they're ready to graduate and scale across the organization. >>Up until that point in time, they're trying to figure out, you know, almost product market fit, but inside a larger organization, leveraging the tools that you know at their disposal that is the broader Microsoft, whether that's the field of the marketing engine or things like that. And then you seeing bonsai be able to take advantage of things like that. The keynote was Satya and, uh, you know, our access and collaboration with the Microsoft field, but we're still in that incubation mode trying to figure out exactly how the technology goes to market. Um, let be continuing to build out and mature the technology and figure out the right home for it. Um, the right partner for it. If it's a business unit or you know, whatever that may be. Um, and I think in that scenario, we're, we're a bit standalone in that regard while we figure this process out. >>So it's, it's, I think oftentimes you see innovation gets stymied when you, you, you force a premature integration of technologies like this and you almost kind of determine their destiny before even knowing really where they're trying to go. And just letting us breathe a little bit for a pointing for, for a period of time, I think allows a better outcome than if you tried to guess ahead of time. Cause at this early stage, you don't know the answer, right? You're still trying to figure out what is the ideal application, what is the ideal target audience? What is the ideal, um, port part of the portfolio where they should sit? Right? Those, those aren't, I think, guessing those up front, even a year ago when the acquisition closed would have been impossible. So that kind of, I don't know that gestation period is, is I think a key, uh, Dave, take us inside some of the conversations you're having at the show. >>Uh, key takeaways you want people to have of, of your group. Uh, out of Microsoft ignite. >> Yes. Right. I think a lot of the conversations are, you know, this, this big vision that is autonomous systems and that really is an end point. And what you really have to do is distill down, you know, where to get started. And that's not the glamorous kind of use cases are the ones that you see in the press or drones. Um, there are autonomous vehicles, right? It's, you know, things that likely fly or we saw on the Jetsons. But the reality is that like where customers are seeing the strongest business opportunity is, is drills, it's turbines, it's air conditioners, it's a extrusion process for some food that you've probably consumed right while you've been here at the conference. Um, that's, and so really kind of, I think dialing customers into surface level use cases that are a fit for deep reinforcement learning is refreshing because a lot of people come at it saying, well, I don't have an autonomous vehicle and I don't have a drone, so I must not be for you. >>And that couldn't be further from the truth. All you need is a control system. Right? If you have any sort of system run by a PID controller or model predictive control, you can optimize that system further with deeper enforcement learning and bonds as a mechanism for making that significant more accessible to your teams. So I think bringing it way back to like, Hey, I saw this big vision on stage, where do I start? It's just really been a bit of a, you know, a search inside their organization for the types of applications that are good fits >> AI. It's not just for the Jetsons anymore. That's right. Great. I'll take it. Dave Cahill. A pleasure having you on. Thank you so much. Yeah, thank you both. It's good to be back. I'm Rebecca Knight for Stu Miniman. Stay tuned for more of the cubes live coverage.