Qualcomm’s CEO on the coming AI phone supercycle

So, Krishna, you run Qualcomm and your technology powers, many Android phones, met a smart glasses, a bunch of coming wearables, and a growing number of cars. And I want to get into all of that. But I want to start with something else, which is you also have a very interesting view of the U.S. and China. Qualcomm has a very strong Snapdragon brand in China. That's something I've actually learned a lot being here at the summit that you guys are having is just the rabid fan base for Snapdragon and China. And I think that gives you a unique window into the into the two markets. And I want to start with how people in China are feeling about AI relative to the United States. The sentiment, when you look at the sentiment and how it pulls on AI around the world, it's very different based on geographies. And maybe could you contrast it to a little bit? If I do a compare and contrast, the broad adoption of AI into the devices and in consumers, I see that happening in China very, very fast. In the United States, I see the development of frontier models in enterprise adoption AI. Those are kind of dominates the conversation. That's the difference in conversation between both. And when you talk to people in China about AI, does it feel like they're imagining maybe a different future than people in America? The sentiment in America when you look at the polling is incredibly negative. Look, every new technology has, it will bring uncertainty, right? So, you know, it's interesting, you know, you, if you go back in time and you see different technology transitions from the concerns. Obviously, what happened in the United States, I give you my perspective is AI has been an important productivity tools for a number of sectors. For example, company like Qualcomm, I was even asked today in a different conversation said, "Well, you guys are doing a lot. You're transforming the company. You're doing a lot of things in parallel. How can you allocate capital to do all of those things in parallel?" And if you actually look, we have been relatively expanding the company with kind of a flat scale of operating expenses. A great part of this is productivity games using AI to the development process. So, so you have clearly those aspects of AI for productivity games and they are obviously concerns about their second impact jobs or companies, you know, going to leverage it on AI and they're not going to need as much manpower. So, in that conversation, it's probably universal. I don't think that's unique to the United States. You do have this conversation about data center. Data center is massive. You look at those massive deployment. You need more, more compute. It's a wall, I think, of the demand for computes. And you obviously have concerns about, "Is this going to increase my electricity bill?" So, those conversations, I think, are natural. The latter, I don't see it in China. I see more of it's like a feature. It's an evolution. The two countries are looking at this a little bit different. I think, for example, China has been really focused on physical AI and everything on the edge. There's a bigger focus on China right now. But I believe in general because of the uncertainty associated with AI, you're going to have a lot of questions. And to be frank, we're in the early days of AI, early, very early. I like to do this metaphor. It's almost like in the early days of the internet, if I could just have to say, "Okay, we already know what's going to happen. Out of Vista is going to win dessert, your map quest is going to win the map, or it's going to win the social media." No, I think we still have a lot of things that needs to happen on AI. And some of those questions will be answered. This episode is brought to you by Mercury, AI native banking that's loved by more than 300,000 entrepreneurs, including me. Visit mercury.com to learn more. Mercury is a fintech, not a bank. Check the show notes for details. This episode is also brought to you by JIRA by Atlassian, where teams and agents get the context, coordination, and control to move work forward. Try it free at JIRA.com. That's J-I-R-A.com. Thanks also to granola, the AI notepad for people in back-to-back meetings. It works everywhere you do and lets you focus on what matters. Try to granola.ai/sources and use the code sources for three months off. Right now in the US, a lot of people are talking about this idea of pacing. Pacing the frontier of AI development. You're seeing things like the hugging face breach, the models becoming more capable, cyber risks increasing. And I'm curious where you stand on this because you, the company and you, you've been in Washington, you're obviously a voice in the policy space in the US on this. When you're seeing this debate, what do you make of it right now? So I'll provide my opinion. Yeah. And I will, two comments. I think first, I'll give you my opinion for free. So it may not be very good. I'm just going to give it for free. Second is it's just an opinion. This is a changing lens caper. It's hard, it's hard to, to be certain about this. But I think the answer is never, it's never on the bookends. The answer is somewhere in the middle, right? So, so first, it's, it's a brand new technology and, and he has a lot of potential. There is a development roadmap and continue to invest in development roadmap. It's going to be important. And the second part of it, it's, it's also important to have guardrails. It's, for example, the yes, there's a lot of comments about what are the risks associated with AI. But let me talk about some of the more practical risks. You know, cyber security, it's, it is, it is a very reasonable risk because everything is digital. I think of a, the reason AI exists is because we as humans digitize everything. You know, you have all this digital information. Every area has computing power, but this surface area that runs on software is very, very big. So if you have models that can find vulnerability on things and they can hack things and you don't need to be, you know, a cyber warfare specialized team, anybody can get a model and do it. It's a problem. You need to have control. You need to have very serious companies. You need to have the right regulation. You have to have the hard guard bandages. It's no different than on the other major technology like that. So I think that's really the answer. It's not in extremes. It's not like stop it or go full speed. It's do it responsibly. I think there's nothing wrong with that and and have a guard rails. In our little world, we do chips. We do the chips. We do chips to do the matter. I think chips are not little, but that's okay. It is little compared to some of the other big companies. And we do all of this math. We are building in the hardware hooks and controls and knobs for you to store your information security for you to decide whether you want a personal graph to be stored or not. And to be able to have controls, I think that's that's an important thing. All of those companies need to do it with responsibility. You traveled to China with President Trump in May and when you're in those rooms, I'm curious, what do you hear from other world leaders about how they're grappling with AI and the risks? Look, there is obviously there's a lot of semiconductor, the industry that happened to be became a geopolitical industry, I think right now. So you have to be part of those conversations. AI, it's important in every part of this conversation. I think there's a common understanding about how to do those things responsibly. And then the other part, more of the conversations that I'm part of, there's a lot of strong, healthy, commercial in partnerships, kind of relationship between American enterprise and China enterprises. And those relationships, what I have seen then, hopefully I'll see you next week, those relationships actually create a very strong point of stability and come on understanding, I think, between the two countries. And if that's the role that we can continue to play, that's the role we're going to play. Let's talk about the smartphone. So it's really interesting. I mean, the smartphone market is obviously massive. It's one of the most consequential, if not the most consequential computing markets today. At the same time, it's not growing like it once was. I think I saw there's a stat that it's expected to shrink maybe about 14% in terms of overall units ship this year, maybe go down a little more next year. And I'm curious to hear from you, how much of that is the incredible spike in memory costs and component costs for these devices and just sticker shock that consumers have. And the phones are good now and maybe you don't need the next one if the price goes up, you can hang on to the one you've got. And how much of it is something bigger? Okay, there's a lot in that question. Yes, there's a lot. So let's go break that down a little bit. So first I'm going to give you some of the facts. So interesting thing, and maybe people don't realize yet, the smartphone market has yet to recover, yet to recover what the market was before the pandemic. The market is still smaller and now it's artificially smaller, but still smaller than what used to be in 2019, right? So the market has been somewhat still recovering from what the market used to be. And there's a number of factors for that. I think one of it is of course, it's a great thing. Everybody in the world has a smartphone. So it became a mature market. It became kind of a replacement rate. and it's totally normal. Look, I'm probably going to to show my age, but I started working on one G. So I've been through every cycle. And at the end of the cycle, right? You do get a portion that, you know, the market gets to state of maturity, become more of a placement rate market. Having said that, this smartphone is a big market. It's 1.2 billion phones sold every year. Even if you don't want any new feature, you use your phone a lot after two, three, four, five years you're going to buy a new one. However, within that base, there are a couple of things that happen, which has been very telling. The premium and the high tier as the percentage of the total market continue to expand. And it's been like clockwork, ear of ear. Even in a compressed market, the premium tier continue to expand. And the reason is because generation after generation, people are doing more with their phone. I'm sure you still have a laptop. The laptop didn't get replaced by the phone. But there are certain things that you say, oh, I need my laptop for this. This long email is going to write, I'm just going to wait until I get the laptop. I'm going to do it. But now with AI, what we're saying is more and more workloads shift to the phone. So people want better phones. People want phones are more capable. So independent of this transition to an agentic phone, we're starting to see the premium tier increasing. Okay, the next layer, the markets now artificially suppressed because of what happened with memory. Memory prices went up 5x to 6x. So what happened is the premium tier, the high tier has been more resilient. Yes, it's more expensive, but consumers see the value they want to buy the phone. We saw the mid tier, low tier has been way more sensitive. So the market is down 20% this year because of the high memory prices. It's not a demand problem. There's now a pent up demand in the marketplace. The silver lining on this, it's happening at an interesting time when AI smartphones are starting to come. And it could create opportunity for people to want to buy now an AI smartphone. We have seen this market in cycle. So for the past few years, as you said, not a lot of excitement about the phone market. Oh, the phone market is, does not grow. We have, because of this driver of a premium tier expansion, we have been growing, you know, in the Android market, double digit compounded annual growth rate, just some more of the premium tier expansion share gains and more content because people want a better phone. But my prediction is nobody wants to talk about the phone market, everybody's data center, their markets, until the AI super cycle. And then when that happens and 6G happens, I think there will be a lot of conversation about phone. It's important to say phones are not going to go anywhere and it is the largest development platform ever created by mankind. And humans are not going to go travel to a data center, ring the bell and say, give me some AI. You're going to use that to the mobile devices and they're going to have a part in this picture. I want to know what you mean by AI smartphone. But first, you all should use on the screen during the keynote, which is taking the Silicon Valley world, the early adopter world by storm. And then there's also products like Instinct and others and Grockbot and all these things. And I want to stress test what you're saying about workloads moving to the phone because, I mean, these products are browser virtual machines and the cloud, right? Like, news is running a browser in a cloud somewhere. It's not on your phone doing most of the token usage, beaming you back through the answer, right? So if that's the way that these, at least right now, these early agentic personal products are working, does that not make the phone less crucial? I have to be careful not to disclose names, but some AI companies right now, some of the companies that are in front of AI are telling Qualcomm, Qualcomm. By 2028, I need to make sure that I have the ability to run at least 100 billion power meter model into a phone. And I needed to have that thing running kind of all the time. >> So you're saying there's AI companies that are talking about it? >> Well, AI companies are starting to do phones. Look, it's interesting. If I just give you an example of the China phones that we just talked about it, the Dalball phone is a Biden's phone made by Nubia. And there's more coming, there's more coming. But I think there's an understanding. There's an understanding that the phone is pretty important for agents, there's going to be the battle of the agents, which agent you want to do what that's, let's have said before, this is early days on the AI. And there's a lot of clarity now that there are things you have to do on the phone. There are things that you have to do on the phone also supporting other devices. I think it's futile to have a conversation about cloud and edge, because what happened is more and more things are going to do on the cloud. You're going to find more interesting and sophisticated things that you're going to have to do only on the cloud, and you're going to do on the cloud. And there are going to things that you're going to have to do on the device, because you have to do on the device. There's a lot of discussions about cloud and edge, about one competing or replacing the other. That's incorrect. Let me give an example now. Let's say that we pull up our phones, and we're going to say, OK, I have 300 apps, organizing folders. Let's go one by one and say, what is running on the phone, and what's running on the device? It's almost like this doesn't matter. But the moment I put a phone that has a lot of processing power, I've been doing that today. I know, from one chip to the other, there's more processing power. If I put it in an airplane mode, it'd become useless. We put it in our pocket, but we don't use it. And I think that's going to be like that with AI. There's going to things going to happen on the phone, because they have to happen on the phones. The things going to happen on the cloud. And I'll finish by saying, this comment I made about friction. That's important. If you pull up your phone and it takes time for the agent to do certain things for you, then you're going to do it yourself. But certain things, you're going to just get the agent to do it. And the last part is, I talk about in my keynote to the phones very unique to you. So you may have this little app in the corner that does something, maybe open your garage door, or check something. And that app is on your phone. And you need the agent to go over there and then phone and operate that app. So you're going to have a combination. You need to think about those things as one integrated computing system the way the smartphone is today. So you don't want to scribe to a potential world where mues and these personal agents had abstracted away the computing off the device. And most workloads are token usage is happening in these cloud VMs. No, and there's two reasons. I'm going to first give you a reason which is there's the coexistence of the old and the new by definition. And the causes of the old and the new require those systems to be leveraging those both words. It's a remember-- you probably-- I'm going to show my wage. But I remember when everybody talked about the web OS of Palm and all of the applications are going to be cloud basis. And that's just going to be the phone's just going to be a shell. It didn't happen that way, right? I always saw app stores developing. OK. You see now, especially with open-weight models. You see now the growth of on-prem. It's very interesting. If you look at just-- if I got this right, if you look at the Nvidia last earnings, when they talk about-- I think it was in the forward guide. I don't remember. I may get the numbers wrong, but they talk about 40% of the revenue with AI companies and hyperscalers. The other 40, on-prem, NeoCloud, sovereign AI. The moment you believe in on-prem, you accept hybrid AI. Certain things are going to do on-prem, so things are going to do in that cloud. Then the question is, what is the prem? Where does the end-- does the end in your PC? Does it end in your phone? And I think that's the way this is going to go. OK. I see that. I still am struggling to understand what an AI smartphone is. You said that a couple times. You said it this morning. I mean, you could say these phones are already AI phones. They have series kind of good now. Google Gemini is very good. You can have all the chat bots on there. What is an AI smartphone? What is the difference? So the AI smartphone vision became very clear when OpenClaw was launched. And the ability for you to tell an agent, or the ability to text to an agent, and say, here's what I want you to do for me. And that's why I kind of provided the example. You're just going to say, you get a question. You're going to say yes. And then the agent is going to do things for you. It's going to run on that computer. It's going to deal with the planning. It's going to deal with the smart routing about things that are going to be doing locally. It's going to go to your memory, personal memory graph in your context. Your context only exists in the phone. Right. Context does not exist in the cloud. It doesn't exist in the phone. And the sensor data comes from the phone. So it's going to look into those things. It's going to make it relevant to you. I'm going to take action for you. That is very different than the things that you can open your browser and do it yourself. So it's way beyond a browser. I think that's what the AI smartphone is. Now, it's important to explain. We're just at the beginning of this. Early days of AI-- and I love making parallels with the smartphone transition. I'll go there. But early days of AI, you have some of the phone companies talking about. this is the AI. So you'll have the set of features from the smartphone maker, set of features of the OS. So maybe those are the ones that you're gonna use it, but that's not the AI smartphone. Later you saw with orchestrated agents. This is a 3P issue, it's not a first party issue. And there's gonna be different agents, different skills, different things, they're gonna be integrated across different companies. We used the example of some services like payments. The application becomes horizontal and it becomes part of everything. The boundaries of OS and apps no longer matter. And those things, those experience happen across multiple devices. That, that is the fundamental difference. Early days of the phone, I remember that when the Android launch and iOS, the iPhone launch. So you have an incumbent at the time was like Nokia. And you also have like BlackBerry. And they look at the features that came off the smartphone. Let's pick the iPhone as an example. You have iTunes, you have the little music app that you can move the drums and the guitar and things around and play music. You have those, I don't know, 15 apps that come with the OS. Not a lot of things in the app store. So some of the existing companies, BlackBerry and Nokia said, "Okay, we can do those features too." But that wasn't this smartphone. This smartphone was defined by the third-party applications. Nobody know at that time what is going to be invented and what people are going to do. I feel the same way about the AI's smartphone. Once you put the harness and you put the capability, you will see how those things are going to develop and I think that's going to change the phone experience. 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All these devices that are coming. I'm curious to hear the state before we go into the AI wearables the state of VR and AR because Qualcomm has been a player in that industry for a long time and it feels like that industry has struggled to gain real commercial traction although meta is starting to have it with the glasses and Google's coming with their glasses with WarBee Parker etc. I think Apple will come. Everyone's coming now. What do you make of the wearable market as it exists today and is VR or something that you and Qualcomm still believe in? Or are we kind of past that? No, this is good question and because there's a lot of things built into that I will start with VR. It's like a console type market. It's like a gaming market so you should think about that. People thought it might be like I know. People talk about this kind of the future, the metaverse but and I will give you very specifics on those things but if you look the technology developed to the point that you actually have a pretty good experience but it's more like a gaming console experience. A lot of the applications are about gaming not even social it's about gaming because there's not a device that is convenient for you to walk around you know every day. You're just going to put this thing you're going to get fully immersed. Then you got to the middle of the road which is mixed reality right and what you have the combination of augmented reality and C2 but then you get to smart glasses and the thing was not about the visualization technology. You think that is a platform. The inflection point came because of Gen AI. Let's just pick the of those three categories. The one that I believe is the one that is going to be very successful. It's already successful today. I think today the market it is in the 50 to 60 million units shipped. I think we have about 40 different designs across different companies but I think that's going to grow dramatically and let me explain to you what happened and why. First I remember the first smart glasses. The intent was to extend the camera functionality. Take a photo or record a movie posted on Instagram as a story but then Gen AI happened and then you started to do different things. What is this? Translate this. Take me there etc. Who's this person? And you started to see exactly this. The agentic or new AI workloads getting traction. This became a more useful device. And what is interesting about that category if you believe that on what we've been saying for a couple of years AI is the new UI. Then this is a prime real state. Close to your eyes, to your ears and your mouth. Very natural. Humans know how to wear a glass. There are some rules. Like that's the problems we need to solve. The rules is you need to have about 35 grams or less I'm giving you the idea. You need to have 6, 8, 10 battery life and it needs to be a fashion device. That is going to get traction. I actually believe in all of this category of wearables, all of it. The one that I am the biggest bullish and there was will be the biggest category is glasses. Because of see what I see, read what I read in other things. And some interesting use cases. Like for example our research team did something super simple. It's a small model in the glass. You load up your company directory and then you just walk around and say, "Oh who is this person? Oh there's Alex. Here's his sample in number." So there's so many different applications and I think that's the one that developed. Just to finish the answer, watches who play a role, pins, pendants, jewelry, who play a role. So we have a number of different designs with companies. We see everything now. People are experimenting with ear buds with cameras. Jewelry. People can wear jewelry, pendants, badges. The thing we announced with Microsoft. So we'll see. It's early, but it's promising of all of those. I think the biggest one is smart glasses. So let's take the watch out for a second because the watch has other utility, health and fitness and things too. So if you're saying glasses is going to be one, the smartphone is going to obviously continue to be relevant. Would you bet on a third form factor in all these wearables that you guys are seeing? You mentioned there's dozens and big companies are coming with their wearables soon that we haven't seen yet. Do you think there's a third form factor that you're like, oh millions and millions of people will use this? Like a puck that listens to you. you blah, blah, blah, jewelry, whatever. - Yes. And the only difficulty in answer this question is what is deaf form factor? People are experimenting with different things and we'll see it. He feels like an iPod moment. - Mm-hmm. - So I've been thinking about the Walkman too. You know, like in how it was a cultural moment. - Yeah, he feels like that. - Yeah. - Before the Walkman or before the iPod, if I said, well, what everybody carry a device like that? You're saying, I don't know. And then it happens. - So, and it's all about the thing that I said before. Do I trust it and it does have value and it's low friction? If people crack that, I think it's gonna be successful. - Let's talk about data centers because I am still trying to run my head around why is Qualcomm doing data centers? - Why not? - Why not? I guess people need them. Like we need, you know, the world is starved of compute. But what is the opportunity for you guys? I mean, you're a large company, but you're dealing with the hyperscalers. And I guess, delineate the difference of the strategy you have versus an Amazon, a GCP, you know, Microsoft, et cetera. - We have a mobile DNA. We started in mobile. We've been the most concentrated company in mobile. We understand that. We'll continue to do that. And, but there were several steps as we started to diversify the company. We thought that the technology we had could be relevant and disrupt another market. And we started to build computing assets. And we went, started to make the computer bigger. There was a process. You cannot burn any step. You have to go to that process. And we went into PCs and cars. And it's interesting. When you think about car, some of their chips, they run autonomy from both level two plus plus, level three, level four. And we have the silicon running this. This is like a server. It's a server class processor for you to do those things. So we had to develop the capability. So it became a natural thing for us to expand the next step of the company to go to the data center. That's the second part of the answer is, this data center thing is moving at a breakneck speed. And everything that people believe was true, it changed really fast. And I'll give an example. In the very beginning, was all about NVIDIA GPU. And even people want to talk about inferencing, a new harder for inference, the answer was, you train on NVIDIA GPU when you're not doing training, you do inference on NVIDIA GPU. Only NVIDIA GPU. Then inference started against scale. People said, oh, there's different solutions to do inference. There's more efficient. There are more better performance, lower TCO. And if that wasn't true NVIDIA will have nothing to do with GROC. But now you keep going. And you said, the compute demand is very high. I don't have a lot of energy. I need to find a specialized solution. So the inference started to break down and pre-fill in D code. And even the code is breaking down. So we look at this scenario with say, the first pace, memory, technology is going to change, computer technology is going to change, very pace. In our business, it doesn't matter when you enter. If you have something innovative and disruptive, there's room for you. So that's the second tier. So we said, if we can do something unique, we're going to have a market. Let's just go focus on doing something unique. And then get to the layer number three, which is our DNA is building chips, assuming there's a battery on the other side. That's our DNA. When I look at a data center, does this the amount of compute? Does the availability of energy? Yeah. So we see, oh, we can do something here. And that's kind of where we are. We focus on, can we build energy efficient, high performance CPUs, high performance, energy efficient accelerators? That's our space. And it's just a natural evolution of Qualcomm. So it sounds like designing for the battery was a key insight for why you're doing this. Yeah, look, it's, you know, we have this, we have this conversation all the time about, what are the things that make some companies very unique? For example, Intel was in the data center before Nvidia was, doing CPUs, but Nvidia was doing a lot of parallel processing and, you know, rendering triangles for graphics. Well, that happened. The parallel processing was very important for some of the AI processing that creates an opportunity for them. Right. We feel when you have compute versus energy equation, that creates an opportunity for us. I was the last person to interview Chris Lattner before you acquired his company modular. It's great guy. He's a great guy. And he's a legend. He's invented multiple programming languages, including Swift, and you bought his company modular recently. And for people who don't know what modular was doing, it was essentially a bid to crack the software mode that keeps the AI industry tethered to Nvidia and CUDA, the software layer that Nvidia uses. And he told me, and this was, you know, several months ago, that there's this coming wave of different kinds of chips, which you were just talking about, that, you know, CPUs, all these things, used for AI, and developers need a way to use all of them. And I'm curious how much of that strategy that he had at modular is now the Qualcomm chip and data center strategy. You know, I met Chris in, you know, we're so fortunate to have he and his team in Qualcomm. I'm sure he had options to go to very different companies, if you wanted to. But I think what made modular and Qualcomm a perfect fit is kind of we share, we had, we share the same vision about what is happening with the industry. First of all, a company like Qualcomm, look, when we invented some of the most incredible technology in the world, we licensed for everybody, right? So a company like Qualcomm, we believe that you gain a lot more innovation in scale if the technology is widely deployed, and you have more companies contributing to the innovation. Today, you do have a control point on the software side, and there is an industry need to have an open alternative to run AI, because AI is not going to be unique to the data center. It's going to go everywhere. You talk today about a multitudinal harder in the data center. Think about the multitudinal harder when you put cars and PCs and phones and wearables, all of this. Developers need to target all of this compute to run models big and small, and they need it to have a common platform, and it doesn't exist in AI, what it has been mature in traditional data centers, like Linux as an example, or even if you look at the cloud, think about the Google Kubernetes, or even in our space, when you think about the horizontal phone space, this Android is an open platform. Those things don't exist for AI. So the vision was modular, Chris, and the modular team was thinking, we need to develop this. Developers need this, the industry need this. We're going to develop, it's a modern, it's have higher performance, and runs on any hardware. And I said, okay, let's do this at Qualcomm, and let's offer to everybody. And to the point that we at Qualcomm will celebrate, we will celebrate every single modular deployment on Nvidia, on AMD, on Broadcom, on any other chip, on Intel, because we actually believe the industry will benefit from a standard common open platform. We said we're going to do a patchy 2.0 license, it's going to be open source. What it means to the Qualcomm chip? Once the platform is open, we can't compete on harder. That's where we've done our whole life. That's our mobile business, that's everything that we do. So we're not afraid of the merits of the hardware we can beat to the matter of the harder, that's going to allow harder innovation. If you have a close system, I may have a harder innovation, but nobody will ever be able to use it. So for us, since we're new to the data center, we're entering this space, then we're happy because we'll create an opportunity to compete on the harder. The other part of the equation is the conversation we had before about AI smartphones and PCs and cars. The edge is going to be part of this compute continuum when everything is going to be running AI. And you have the same problem. We need the platform that scales. So we're going to be, like I said, doing everything possible to make sure that every hardware company can use it. Modular is going to be agnostic. Modular is going to be run as a Qualcomm company. And we're just going to be supporting moderner chips and trying to build a great hardware. Let's end on something that I am also trying to figure out, which is 6G. So I've covered multiple Gs. You mentioned 1G earlier in this conversation. 6G is coming. I think most people would probably struggle to explain what 5G changed for them. And the carriers were hyping it up like crazy. I mean, this is every G. This is a major hype train that is associated with these coming waves. What practically do you think that 6G is going to unlock? That's not possible today. But because of what you said, I feel compelled to give you the 5G answer first. Because I'm not going to say people are just taking for granted. So I'll tell you the two things from a consumer standpoint that came with 5G. First of all, nobody will have unlimited data rates on a smartphone if it wasn't for 5G. Economically, not viable to do a 4G. That's fair. Not viable. So the fact that people can have unlimited data rates on the phone, it's 5G. So if anything that changed their lives, they have unlimited data rates right now. But that's not the only one. 4G, for example, was the beginning of the smartphone. You get a broadband and the phone became a computer. But at that point in time, you saw the disappearance of CDs. Everybody starts streaming music. You have enough bandwidth to stream music. CDs gone, but not DVDs. But 5G, DVDs are gone because now you have enough ability to stream music. So 5G, the second thing it gives to consumers is high definition video download. That's important for me to tell about 6G. So now let me answer your question. Every even number G is super successful. 2G, super successful. 4G, super successful. So based on that tradition, 6G is going to be super successful. Now, we talk about this, but there's a reason, right? So you have a major disruption in technology and then you get to go fix things, right? So let's go that in memory lane. Phone started with 1G, analog, walk, talkie type phones, though people realize this is incredible. You can carry a phone with you, but there's not enough spectrum for everybody to use it. We needed to bring digital seller and digital seller 2G was about can everybody on earth have a telephone? Super successful. You saw the explosion of mobile, everybody having a telephone, post paid, prepaid. Then 3G, you did some incremental things. You connected to the internet. You started to see the black berries and they remember the windows 3.1s, the black jack and all of those kind of phones. Then 4G was about broadband, big disruption. If I have broadband on the other side of broadband is a computer, it's not a phone. The phone become a computer, change the world. From revolution, you saw what happened. 5G, you fixed some things. Unlimited data rates, high definition video. So now we got to 6G. What is 6G? So 6G has been designed for this future that we just talk about in the beginning of the conversation of AI. So if I give you like a simple consumer feature answer of 6G is high definition video upstream, no matter where you are into the coverage area. Why is that? Think about glasses, see what I see. So 6G will transform all of us into walking cameras on this world. So you have the ability to each and every one of us to upstream all the time, high definition video if you want to. And for see what I see, there's going to be very important context for a lot of us. Or in a privacy conscious way, just be observing constantly. Constant. On your behalf. You annotate every image and then and also when you think of award models and robots, there's a whole bunch of things. I'm just giving you from a feature standpoint. But the big change with 6G is 6G is primarily a data center in physical AI network. So you are now going to look at the radio signals, electric magnetic waves that go from the base station to your phone and you're going to look at that signal and how it performs and what you get back is a physical AI. So another feature of 6G. When the cell tower sends a radio signal to your phone and vice versa, inside that single radio signal and there's billions of connections happen all the time, there is a payload. That's the data they are transferring. And now the signal in itself, I can treat as a radar, like radars that we put in cars for autonomous driving. And now I have billions of those radars. And what I can do with this, I can do a real time mapping of the world. Everything in the network, you know what's happening. For example, in this days become very popular, drone detection. Everything that flies, the entire management of the IARIO economy is going to be driven by 6G networks, they're going to be sensing everything around it. Everything that moves, every car, every pedestrian, every bus, you can track things. Those are massive amount of data and context, you know, for models, especially when you think about physical AI and robots and all that. So, 6G is a very disruptive technology, it changes the nature of the infrastructure and also allow computer to be distributed. So, the 6G infrastructure can also carry tokens. We build the network, they used to be copper and we have a voice, we call each other, then it became megabits and is going to have tokens in the middle of this. That's with 6G. But the easier way to think about it is going to be the technology to enable those new classes of agentic devices and we'll provide real-time sensing data for, you know, AI, hyperscalers, models and everything that it has to do with agentic experiences. And when do people feel this in their everyday lives? Is it one year, 18 months, two years, three years? We're going to do demonstrations at the LA Olympic in 28. Our first silicon, it's, you should be thinking about probably Snapdragon 728 or 29, one of the two, I don't want it to give it a set date, we're going to be showing between prototypes and silicon, 2,029, 30 early deployments and it will get scale, you know, following 2,030. All right, Christiana, thank you so much. Thank you so much. Thank you. Appreciate it. Banking should feel like modern software. Get everything you need in one place. Visit mercury.com to learn more and apply online in minutes. Mercury is a fintech, not a bank, check the show notes for details. Grinola is the best AI notepad I've tried. It works everywhere on a video or phone call in person or an Apple watch. Try it now at Grinola.ai/sources and use the promo code sources at checkout for three months off. Girobiadlasting is where your team and your agents work from the same context. Try it free at gira.com. That's j-i-r-a.com. 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