[00:00:00] Speaker A: I think that we are in a good position right now and we're going to get in a stronger position going forward. Yes, the threats are more sophisticated, but our ability to create intelligent response with systems that used to be quite brittle, I think that's a big step forward.
[00:00:18] Speaker B: This is KVC as a primary target for ransomware campaigns, security and testing and.
[00:00:26] Speaker A: Performance and scalability, risk and compliance.
[00:00:28] Speaker C: We can actually automate that, take that.
[00:00:30] Speaker A: Data and use it.
[00:00:34] Speaker C: Joining me today and back on the show is Tom Gillis, SVP and General Manager, Cisco Security Data Center, Internet and Cloud Infrastructure Group from Cisco. And today we're discussing the future of cybersecurity and the network. So Tom, thanks for joining and lovely to have you back.
[00:00:51] Speaker A: Yeah, Chris, good to be back. Thank you.
[00:00:53] Speaker C: Okay, so I really want to start with I interview you at Cisco Live. So it's kind of a bit more of a follow on, bit more of a deeper dive discussion from our previous interview. But I really want to understand in your mind the need for cybersecurity innovation and why it's important.
[00:01:12] Speaker A: Well, it's a fascinating time we're in, in that the, the toolkits that are available to all of us in the tech industry, broadly, specifically the combination of advanced silicon as well as these AI capabilities. You put those together, wow. We can do amazing things like computers can talk, right. And they can talk in a sensible way. That's amazing. So there's kind of a good news, bad news to that. Which is the good news is we're applying a lot of those techniques to security defenses. But the bad news is the attackers are applying those same techniques to security attacks. And if you read the popular press, there are organized nation states behind a lot of the security stuff that are very ambitious with very broad goals of penetrating major infrastructure and disrupting, you know, their adversaries ecosystem, which means everything from bank accounts to, you know, the water pumps in your cities to transportation to, you know, sort of petrochemicals. All this stuff is, is a target and that is really raising the game in cyber security. So lots of change, lots of activity that creates opportunity.
[00:02:26] Speaker C: So would you say in your experience that from how I see it in media, obviously being the coal face and looking at different vendors like yourself, would you say more vendors in particular innovating more than ever?
[00:02:38] Speaker A: Absolutely. The level of innovation is unprecedented. It's unlike anything we've ever seen. And I'll just say for me, not necessarily as cyber security like, I run a technology engineering team, a very, very large product development team. And every year that team gets maybe 5% more productive. Right? And every year we make some incremental investment based on our growth in the market. And so let's say, you know, maybe we add another 5% of engineering capacity, maybe it's 10%. So total of 15%. We, as leaders and managers, spend a lot of time managing, you know, on this kind of marginal increase in engineering capacity. Now all of a sudden, my team has these AI tools that make us 70 or, you know, but twice as productive, 100% more productive. Like, it's just incredible. So, so, so the ability for us to come up with new ideas, to do new things, it's unlike anything we've been through. So, yes, there's a ton of hype around AI, but I think it's pretty warranted. I mean, it's. It's just an explosive time in almost every domain.
[00:03:47] Speaker C: So then the other side of that is you guys are obviously releasing a lot of new things at the AI and Defense came out last week. But would you say that there are probably vendors sort of, you know, lacking behind in the innovation space and then what. What does that actually mean when we say innovation? Is it new products, is it new services, the way in which we do things? What do you think that means to you when I ask you that question?
[00:04:08] Speaker A: Yeah, so, you know, innovation to me is very clear. There's one definition of it, right, which just means doing something new. And I always get a little annoyed when I hear mature companies be like, oh, you know, there's so much innovation, and they're talking about feature development. That's not innovation. Innovation is new. That's the inno part. Right. Like, we are innovating. And so AI gives us opportunities to innovate in many layers. We can put AI interfaces on top of existing products. So we've already done this with a firewall. We put a natural language interface into it. And so instead of trying to manipulate hundreds of thousands of these very archaic firewall rules, you now can ask kind of common sense questions of like, hey, can Tom access this source code repository? And the firewall will tell you, yeah, he can. But I noticed over here that he also has access to a sales repository that maybe he shouldn't have access to. Right. So that level of interactivity, that's real, like, we're shipping that today. And customers are delighted with that. Now, I think AI also allows us to think about building products fundamentally differently. And kind of picking up on that firewall thread, this is what we did with Cisco's hypershield. So we took what you think of as a traditional firewall. And we said, let's, let's completely reimagine this and do it in a manner that wouldn't even be possible without AI. So this is what I call an AI native product, where it's a product that can only exist if it's leveraging AI. And so everybody's doing this, or they should be. And you know, you asked the question, you know, is, is the whole industry embracing AI? I think by definition, no, Some are going to embrace it more than others. Some are going to focus on the, you know, kind of, let's stick an AI interface on top of our existing product and keep focusing on our existing products. But others, I think will be, have the vision and the courage sometimes to completely reimagine their products in a world of AI Because AI is so transformative. A lot of times things that we've done for 10 or 20 years no longer need to be done, and that can be hard to let go. So I said this earlier, but I really believe it. Change creates winners and losers, and this is a time of unprecedented change, which means I think we're going to see a whole bunch of new winners and a whole bunch of new losers in the industry. You know, that's different than just a few years ago.
[00:06:29] Speaker C: Okay, this is interesting. We're at this demarcation between winners and losers. So would you say, based on what you're saying here, Tom, is, you know, if companies are not really embracing AI, whatever their description of it is, so companies who are not doing that at all, is this when they're going to get into the loser category, would you say?
[00:06:46] Speaker A: For the most part, yes. And I think you would be hard pressed to find a company that's like, yeah, no, we're not doing any AI, you know, like, it's so transformative. Any process that you have in business that could be written into an instruction manual or like a, you know, a runbook or a playbook of some sort, AI can do that really well. So even a mundane task like scheduling AI can schedule way better than we used to be able to do with kind of traditional applications.
So really, to me, the, the meaningful question is, to what degree is a company embracing AI? That's really the question. You know, there we will definitely see shades of gray because it's, it's new and it's transformative and it's explosive. But at the same time, there's all kinds of stuff that's not worked out right, so you can't bet everything on it. You have to find the right level of investment, resource focus, vision, executive sponsorship. And, you know, that's going to vary depending on the organization, and it's going to vary widely, I think.
[00:07:46] Speaker C: And going back to the word degree as the operative word, what would you say? Where would that degree be? Would that still be going back to what you said before about AI native in terms of what does that look like in terms of AI and the use of it?
[00:07:59] Speaker A: Yeah, well, so you noted at the beginning of this podcast, my very long and kind of cumbersome title. So my role recently changed in Cisco, where I run not just security, but I run all of our cloud and data center infrastructure. So when we think about a data center, a data center is a very procedural environment. Like there's a thing in a data center called a runbook. And it literally used to be a book that you would write, you know, here's the 500 or a thousand steps to launch a workload. You push this button, do that thing, go to the system, get this number, wait for an IP address, you know, open a ticket, update these firewall rules, update the load balancer. It's a whole series of steps. Some of those steps can be kind of complicated, but it's just a series of steps. You know, I believe that AI can do all that stuff really, really well. So the opportunity, but also the imperative for Cisco is like, you know, jump in with both feet. And we're doing that right. So I have very, very large investments around this. And, and, and I'm not trying to solve every AI problem in the world, but I feel like we can use AI to make our existing products remarkably better. Like totally change the way a customer thinks about how they operate a data center. And that's fun and exciting and interesting.
[00:09:10] Speaker C: So I want to get back on the losers topic just for a moment. What was going to my mind as you were speaking, do you think, okay, just say 12 months, you come back on the show, you talk to me about, you know, the winner, losers sort of landscape. Do you think that the losers or the people that are, you know, underperforming, do you envision that companies like Cisco will just go and buy them, or do you think that they'll just phase out and we just never hear of these organizations ever again?
[00:09:32] Speaker A: I have a very, very strong bias towards this, which is in a world of AI, you have to be willing to blow up your existing products and rebuild them. And because the AI stuff so is so transformative and so I don't want to buy somebody else's legacy product as an I have to go transform, I think there's opportunities to do organic development and because it's kind of like everything needs a rewrite, you know, so might as well just build it yourself rather than trying to buy someone else's, you know, 20 million lines of code and refactor it. That's a bias I had. It's not to say we don't do acquisitions. We sure do. As we're doing these acquisitions, I'm thinking about the larger architecture of the system and how do we make this AI native. How do we make this stuff like really sing, like kind of blow people away with the capabilities that we can deliver with AI. That's my first thought, not an afterthought.
[00:10:20] Speaker C: Okay, this is interesting. So you said blow people away with the AI capabilities. So in your role, what do you think really blows people's hair back here?
[00:10:29] Speaker A: This isn't like, oh, five years from now. I'm talking about right now, today. Yes, I need to mature it. I need to, you know, sort of prove it out. But like I've got customers that are putting their hands on this. They're like, oh my God, this thing writes its own rules, this thing tests its own rules, it deploys itself, it upgrades itself. So, so that frees those teams up to go do other more high value tasks of which there are many. So this is what I was talking about earlier, remember, like this kind of, this, this notion of abundance. AI is going to create an abundance of intellectual property, like, you know, capacity, an abundance of knowledge worker output, an absolute abundance. And great companies will harness that abundance and put it to great use and others may miss it.
[00:11:14] Speaker C: So the word abundance, I mean, you're right. So there still seems to be people that are rattled by it. Like, oh, but I've been doing this for 27 years and I built every line of code in this.
[00:11:23] Speaker A: Absolutely. 100%. A hundred percent, yes.
[00:11:25] Speaker C: So what happens now?
[00:11:27] Speaker A: Well, this is the point. This is why like, like there will absolutely be winners and losers and everyone's going to pay lift service to it. You'd be crazy not to. I don't think AI is going to be a thing that would be, you know, I'm sure someone says that, but like you'd be hard pressed to find that because it's so obviously powerful. Question is degree, like, you know, like, do you really believe, are you really able to capitalize on, on these new ideas? Are you able to let go of the past and you know, build for tomorrow and how fast and efficiently can you do that, you know, and it's hard to do. I don't wanna trivialize it. That's very hard to do because you can't overreach. Right. You know, if I tried to, you know, let's say I built a machine that could turn water into wine. You go, oh, wow, I read about that, you know, in a book sometime. Well, it turns out that's actually very difficult to do. Or turn lead into gold. Another one difficult to do, so don't try that. But something more, you know, constrained, like, hey, I'm gonna build a firewall that is highly autonomous. Yeah, highly achievable. Very, very interesting. And a first of a series of steps that I think will add up to, you know, an absolute revolution in the IT and infrastructure world.
[00:12:30] Speaker C: So based on what you're saying, do you think this is a point in time where even small little startups could start to maybe not overturn big players, but have a really good opportunity because they are, you know, AI native, they are listening to, you know, people blown away by turning, you know, water into wine. They are thinking like that as opposed to perhaps some other, you know, traditional companies out there that aren't thinking like that. Have you seen this before in terms of opportunities in your time being in the space?
[00:12:58] Speaker A: Yeah, over and over and over again. And I've started three companies and so, you know, market timing is everything. I. My first startup was a content delivery network, a cdn and I was out drinking beers with my buddy and we were sort of recounting it was a marginally successful project, wildly successful at first and then, and then, but not sustained. And I was like, God, you know, so many ideas we had were absolutely right. We were just too early. My buddy, this is overbearing, he's like, dude, we were too early, but we were too early by a decade. And if you're off by a decade, he's just wrong. Even if it's the right idea, like if you're off by a decade, you're wrong. So the point is, market timing is everything. And this AI thing is one of these disruptions that is, that is right upon us now. And some big companies are going to be slow, some big companies are going to go at it too hard and miss. Some big companies are going to be slow and miss it there and it's going to create space for new players. Undoubtedly. Absolutely undoubtedly. I mean, OpenAI is a company that didn't even exist a few years ago and now it's looking like a pillar of the infrastructure. There will be Others.
[00:14:06] Speaker C: So you say there might be big companies who go too hard and miss. What does missing look like in your eyes?
[00:14:12] Speaker A: Oh, it's building one of those machines that can turn lead into gold. Right. You know, you can convince yourself that this is a good idea. You could you run a little prototype where it's like lead that kind of looks like gold, it's yellow. And then you put, you know, $100 million of opex to work for two years and the lead never turns to gold. So, you know, execution is always the hard part in all this stuff. So you've gotta be able to execute and there inevitably will be some that systemically fail to execute. And I think that's gonna really be impactful in this time of great change.
[00:14:47] Speaker C: Okay, so the other thing that I'm curious to know now is, you know, being a practitioner historically in this space and then, you know, doing media stuff now. But one of the things is, you know, even going back a decade, which wasn't the velocity just wasn't there in terms of, you know, AI, innovation, deployment, how do we sort of balance now? We've got to do these things like you said, like, you know, the market's here, it's timing. How do we then balance? Like still staying ahead of the game with security to make sure, like, oh, we're trying to innovate so much, but we now we don't even care about our customers because we're not even protecting them at all. How do you balance that?
[00:15:20] Speaker A: Would you say it's hard and that there is no one answer to that? That is judgment and that is what management does. Well, that's what defines great management from, you know, sort of good management.
[00:15:32] Speaker C: So do you think there's always going to be this ongoing challenge between. Well, we obviously want to be innovative. We want to have, you know, all these great things that we're doing. But then there's still going to be the security team in the back that are like, oh, well, hey, we need to look at the risk assessments and privacy impact.
[00:15:46] Speaker A: Always. Every single time. Every single time. Right. Like, you know the old saying, the most secure server is the one that's powered off. Right? Like, okay, got it. Right.
So we have to find that balance. And AI is particularly tricky. Here's why. With a traditional application, you know, you have data that lives in a database and you have application logic and then you have what called the presentation layer, the web, the web interface. Okay. So you can put controls in place and sort of understand all that. Now with an AI based application, there's this new layer, right? There's a layer called a model that sits between the data and the application. And the model sucks all the data in. It reads it, and then the data's gone. You can't touch it anymore. It becomes like a. Like a gas that's in the atmosphere. So. So now this model knows a lot of stuff you want to make sure, like, hey, how does it not divulge that information? And I don't know if this translates to where you're from, but I grew up, there was a game we used to call A Hundred Questions. So I've got a secret, and you're going to ask me 100 questions to figure out if you kept my secret. Usually you can guess the secret in, like, 20 questions. So that process happens with AI so the AI models understand sensitive information. Tom's credit card information, Tom's, you know, Social Security number. But if the app that I'm building on top of these models is trying to just administer a firewall, I don't want that firewall talking about Tom's credit card number. But the trick is going to be that if you play 100 questions with that AI model, it might actually inadvertently divulge my credit card number. And so this is why you mentioned earlier that we just launched a product called AI Defense. And AI Defense uses AI to protect AI. So we use AI to ask not 100 questions. We ask a billion questions. And we ask this model over and over and over again, looking to try to trick it, to see if we can get it to inadvertently develop something it shouldn't. So radical new way of, you know, that's not a security control that anyone's familiar with. And that's just one example of how the industry is going to change dramatically in this AI world. Yes, AI introduces whole new classes of threats. Yes, the nature of an application itself changes dramatically, but it's not, you know, these are changes we've got to embrace. Got to.
[00:18:05] Speaker C: So then, I'm curious to know, from your perspective, what do you think rattles people the most about AI?
[00:18:14] Speaker A: There's a couple answers to that question because it's a broad question in a security sense. This idea that attackers are going to use AI to trick me, to fool me in some way, to giving up some sensitive information, that's a very real threat. It is not unreasonable that you could get an email. Hey, Chris, great seeing you on the weekend. I took some pictures of you at the game. I posted them here. Click on this link from someone you know. And you were at the Game. Right. So. So that's. That's sort of scary. I think the larger thing, what we're talking about kind of like shaping the industry stuff, is that this is great fear that, like, AI is going to create this level of change and it's going to wipe out and eliminate jobs. And, you know, that's what I said earlier. A cynic might think that is true, but I'm an optimist and I'm like, are you kidding me? Like, we are going to find ways to do new things in more creative, more valuable ways than ever before. That's why I think it's going to be just an explosive few years where the productivity, the ability to accomplish sophisticated tasks is going to, you know, skyrocket in a manner that, you know, we haven't experienced really ever.
[00:19:20] Speaker C: Yeah, that's interesting. So I want to unpack that a little bit more in terms of explosive few years, which. What you just said. So what do you think that looks like then? Because people often ask me, like, hey, it's great to interview people about what's happening today, but what's happening tomorrow and be beyond that. Anything you can share?
[00:19:35] Speaker A: Yeah, I mean, you know, like, I think I just feel like this is a kid, you know, you'd hear about these predictions of the future. You know, I was a kid, I was like, oh, my God, I'm gonna have a jet pack. And I'm like 7 years old. I'm like, that thing is gonna kick ass. Like, I'm gonna get my jetpack, strap into that thing, and I shoot down a school. It's gonna be amazing. Didn't quite happen, right? Never really got a jetpack. So this isn't jetpacks. Like, like, I'm looking at the components that go into these solutions and, you know, AI is going to allow computers to talk to you and to think. And so everything from the way medicine happens, you know, like right now, AI agents can produce medical diagnoses better than humans. Now, that doesn't replace a doctor. That's just the diagnosis part. That's part of what a doctor does. Doctor does a lot of other things. But if we can have incredibly accurate medical diagnoses at our fingertips, what an impact that's going to have, you know. And think about the, like, kind of robotics applications. We, we have all the, you know, mechanical hardware and the servos and the cameras to build a really cool robot butler. You know, I would love a butler that could do my laundry and get me a beer. The piece that's been missing is the the logical processing to figure out how to, you know, get me a beer and not get me a Diet Coke. And that's suddenly arrived. So I, I think it is really going to be a transformative, transformative few years.
[00:21:03] Speaker C: Do you think there are many people out there that really get AI sort of to like the foundational level? Or do you think like you said before, everyone's just saying, oh, we do AI, we do this. You know, there terms that get, you know, floated around. Whether they do it or not is, is the next question. But do you think that people at the end of the day can hand on their heart, say we thoroughly get AI?
[00:21:23] Speaker A: Well, I think it's a continuum, you know, I think there's some people that would be like, oh yeah, AI is cool and don't even really know what it stands for, you know, and then I think there are folks that, you know, like, someone built this stuff, right? So. And then there's a whole spectrum in between. And, and I think as a leader I feel this way, I know my boss at Cisco feels this way is like, you know, leaders set the tone and leaders need to say like, hey, this, this is not a small thing. Understand the magnitude of the change that's possible and then drive the organization to embrace that change, ride that wave, be on the right side of the problem. Yeah, that's exciting.
[00:21:58] Speaker C: So what tone are you setting, Tom, as a leader?
[00:22:01] Speaker A: Hopefully you infer that. Right. Like things that weren't possible two years ago are suddenly possible. I want to be the company that brings that stuff forward. And there's a double whammy here in that, in the data center, I believe that we can use AI to make infrastructure that actually powers all these AI based applications. So as this AI revolution takes place, I really firmly believe that Cisco can be an engine that drives it.
[00:22:28] Speaker C: So I want to get back to. We spoke before about people talking about a very real fear of them worried about AI and what it can do. So then as you know, you probably heard people talking about cybercriminals are using AI, then we're defending with AI. How do you think we'll ever properly get ahead? We've always sort of been behind, but even if we're not permanently there, what does that sort of conundrum now look like?
[00:22:54] Speaker A: Yeah, this is, this debate goes on a lot. You know, the explosion in AI capabilities is actually going to help the defenders more than the attackers. And the reason for that is like, there's no question AI can make that super scary email that looks just like a real Email from a real person, but people were clicking on the goofy emails anyway, you know, so it doesn't really make the problem that much worse. Whereas on the defense side, you know, having an. A firewall that can write its own rules, that can look at these anomalies and automatically take action, that's net new capability that didn't exist in the industry. So I think it's going to advantage the defender more than the attackers. So I think it's kind of overall good news, but, you know, remains to be seen.
[00:23:41] Speaker C: So that being said, would you then envision that we will stay ahead then in terms of the criminals, or do you think it'll sort of oscillate?
[00:23:49] Speaker A: I think that we are in a good position right now and we're going to get in a stronger position going forward. You know, yes, the attack, the threats are, you know, more sophisticated, but our ability to create intelligent response with systems that used to be quite brittle, I think that's a big step forward.
[00:24:06] Speaker C: What do you mean by brittle?
[00:24:07] Speaker A: Well, you know, a lot of infrastructure, again, pick on our example, firewalls, like, you set a bunch of rules in the firewall and the thing sits there and runs with those rules, so it's hard to update them. You know, you update them very carefully. It takes weeks to update them. So, you know, in a world where you've got these kind of dynamic threats that are coming in and changing all the time, it could be hard for traditional systems to keep track. Or like that application that I talked about, you know, where, where you've got an AI model in it and you're looking only for a credit card number, you're not playing the game of a hundred questions. You're going to miss those types of things. And so with AI powered security controls, now all of a sudden we can see it.
[00:24:44] Speaker C: So I want to flip over now and talk about, you know, security and networking together. Now, I know that you guys are doing a lot of work in this space, but I want to get into your mind about your experience with this. What does this look like? What are your thoughts? And it comes to mind because I think this is really interesting in terms of, you know, the more holistic approach.
[00:25:03] Speaker A: Yeah, For a long time there's been a lot of interest in kind of the intersection between security and networking. And, you know, I think that there's two things. One is these AI management tools. The second is advances in silicon itself that are enabling an absolute sort of acceleration of security and networking coming together. So I talked about a product called Swiss, called Hypershield Hypershield is a firewall or really kind of a reimagined version of a firewall that can run in a data center switch. It's not a box, it's not a separate appliance, it's just a feature on a platform. That's one of a number of examples where we think we can make security far more effective than it was when it's separate by integrating it into the network.
[00:25:54] Speaker C: So can I just ask, why was it so separate for so long?
[00:25:57] Speaker A: A lot of reasons. A lot of it was the kind of fundamental building blocks. So a network processor wasn't capable, it wasn't programmable, it wasn't capable of doing advanced functions like a firewall. But as the silicon has progressed, now it's suddenly it is.
[00:26:13] Speaker C: And so then, that being said, and now that things are sort of, you know, working in harmony together, what do you think then? What do you think we can see then as a result of doing this? Obviously it took a while to get to this level, but now we're at this level. With everything else that you said that infused with, you know, AI and everything else that you discussed already with me today, what else can we sort of see on the horizon now?
[00:26:34] Speaker A: Yeah, I think the next wave of computing is clearly going to be much more distributed. So as we dream up these AI applications, robotics, and you know, that robot butler that I was talking about, you have an ability to have these workloads kind of running everywhere, all around us is super, super interesting. But that's going to require security that is infused into the fabric of the network. So we kind of got to have security everywhere. In a world where these devices, you know, are also becoming ubiquitous. Right. In a car, in the infrastructure cells, in a hospital environment, in the factory floor. And the intersection of security networking, I think is, you know, really, really kind of many ways the only way to do that.
[00:27:20] Speaker C: So I like the word infuse. So what do you think businesses that, you know, don't have this fused, infused, you know, security, you know, is part of the fabric of the network. What do you think happens then? Do you think that these companies have a lot more problems than we know and that we hear about? Is this going to be the new way of how businesses have to move in the future?
[00:27:42] Speaker A: Yeah, I think usually what happens is someone makes a mistake, there'll be some sort of high profile disaster where, oh, I've got this AI based system, I wasn't protecting them with a distributed security system. And it led to know some significant consequence that mistakes Usually only happen once and then the whole industry take notes and everyone, you know, needs to embrace this type of solution. And so, you know, that's a cycle that we've seen kind of over and over.
[00:28:11] Speaker C: So what do you think now for 2025 excites you the most? I'll probably see you again in another Cisco event this year, but obviously a few months will pass since I speak to you next. So what do you think really, you know, wakes you up in terms of the industry, what Cisco's doing, what clients are saying, anything you can share?
[00:28:31] Speaker A: I think I've already talked about the significant opportunity that we have to infuse security into the network to make it part of a switch or ladder. I think the larger thing that I'm excited about, what I'm thinking about is this AI revolution, this wave that is already breaking is driving renaissance in the data center and that data centers had become kind of commodity. It wasn't really changing that much. You know, it was, wasn't necessarily exciting and man, it's super exciting again. And I think that for me, I find that personally very, very engaging.
[00:29:08] Speaker C: Okay, so Tom, Cisco celebrates 40 years. Is there any sort of learnings you can share from your perspective as you look? On reflection, I think the big opportunity.
[00:29:18] Speaker A: For Cisco is to focus on things that are naturally improved by integration with the network. And I already talked about how we can really change the way people think about network security by building it from the beginning to work in a different router. The same thing is happening in the data center. All this AI movement is driving really a renaissance in data center construction. And there's a whole bunch of hard problems that have to be solved. And the network all the way from the silicon, the processes to the optics to the systems, the network can be a key component of how we can make the infrastructure to power these AI workloads and continue to drive this revolution that's happening all around us.
[00:29:59] Speaker C: And so Tom, really quickly, any closing comments or final thoughts you'd like to leave our audience with today? As you are episode 300.
[00:30:07] Speaker A: Yeah, thank you for including me on episode 300. 300. I really enjoyed it. Super enjoyed the conversation and yeah, it's going to be an interesting time. I look forward to watching it all play out in the next few months.
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