Thank you. Good to have you back. Thank you so much. Thank you. Thank you. Beautiful. Thank you. Thank you very much. Hello everyone. Very happy to be here at Computex. This is a special time for Qualcomm, a special time for technology, and it's such an honor to be able to speak with you all here at Computex. Thank you so much for being here. As I said, we at Qualcomm are incredibly excited about the future. Is there some Qualcomm folks here in the room? All right. Thank you so much.
Before I start this presentation, this presentation is not about Qualcomm. It's really at the end of the day, I think the evolution of technology is really a combination of companies. No one company is ever responsible for everything. It's really about partnership. So first thing I wanted to say a big thank you to all our Taiwan partners, first all of our suppliers, all of our development partners. A special thank you to TSMC, which has been an incredible partner on this journey. So thank you to our suppliers and our developers, and then also a big thank you to the entire ecosystem and the partnerships, and many of you which are here today. Thank you so much. This is not about Qualcomm. This is all about you and an incredible ecosystem that actually drives everything in technology with wonderful partnership companies that are leaders in technology today. They are leaders because of those partnerships. So thank you very much and thank you all for having me here speaking to you.
Okay, we are incredibly excited because a lot of the things that we have been talking about is really starting to become real and is very easy to see. I have one job today. One job today. And by the way, I won't talk about a data center. So if you came here to hear about our data center projects, I'll tell a little bit. But we'll talk about this at the end of the month. But I have one job today. I want you to understand how AI is going to evolve for all the devices because it's the new form of computing that is touching every single device. And if you walk out of this keynote today understanding what's going to happen to all the devices at the edge and how much we're excited about it, I have done my job. So I'm going to do my best to tell you how this future is going to look like. It's very clear to us. We have conviction what's going to happen and we're going to make it very concrete for you. But it's an incredibly exciting time for all of the computing technology and all the devices that we use every day and the ones we're going to use.
So about two years ago, we talked about how AI will change the human-computer interface and as a consequence will change the architecture of all of our personal computing devices. And that is starting to become a reality in 2026. That's why we call it Qualcomm. 2026 is the year of agents and it's now how AI is really evolving and is going to get to incredible amount of scale. It is evolving from simply answering prompts and working as a tool that augments how we as humans work with our computers into something that can take action on their own. I'm going to give you some examples. I think what you see today on the screen at home, you're going to have agents that is going to basically update everyone on your activity and your schedule. All of the things that you need to do at work will be with you and think about what are the projects that you need to do, what are the tasks that you need to do, it flags the decision and it's going to be working with you. And in your personal life, it will give you information that is relevant to you, all of the updates, state that you need, work with you on a schedule. Everything's going to be prioritized and it's going to be a little different. It's going to feel more autonomous. It's going to feel more personal and it's going to feel like really a companion. And all of this is going to happen proactively across all of your devices.
And for that to be understood, we have to go back to a very basic element of this transition. We have been talking about this, right? Which is the phone today is at the center of your digital life. And I remember when I presented something similar like this when we talked about it at Snapdragon Summit, I actually talked about here at Computex that the phone is the center of a digital life and therefore everything is around the phone. It's how we interact with the phone with the OS and the applications, even the other wearables devices, they are around this phone ecosystem. But now this is different. Those agents become the center of your digital experience. So including the phone and the other devices, they now are around the agent. It's not about an extension of the phone and the digital ecosystem is no longer at the phone itself and the OS and the applications. And what happens, those devices become endpoints for agents. And agents are not trapped, they are not attached to a single ecosystem. And everything that connects you with an agent becomes an endpoint for AI. And that's a very important change. Once you understand that change, you understand how the whole mobile industry is going to change. The things that we take for granted today are going to be different tomorrow. And there's one thing I can tell you coming from Qualcomm. I've been at the company for 30 years. One thing is guaranteed: the mobile industry is not static. It changes all the time.
So those endpoints for AI, I am going to talk about what is really the surface area. I'm going to remind you of what are the scale of those devices. There are about six billion phones today, two billion personal AI devices, which is the evolution of wearables. And that is exactly a small number when you think about those things as endpoints of agents. Two billion PCs, half a billion connected cars, and people will experience and interact with those agents on these devices. And as I said in the beginning, the role of this conversation today is to help you understand the role of those devices at the edge for this next phase of AI. And we at Qualcomm, we actually told you about those devices running AI before it was popular, but now it's very easy to see. So once you understand the scale, one important message that I want to deliver to you is that today's devices were not designed for those experiences. They're not. It will require a different kind of device when agentic AI becomes the number one AI function in our daily lives, especially for personal computing as we interact with those devices.
All of those devices today, they have been built for actions initiated by the user, not by the agent. And I'm going to break that down for you. The agents are different. They operate all the time. They carry context forward. They will orchestrate multiple tasks reliably and securely. But they are going to do that on their own, not necessarily with human intervention. That alone gives you a glimpse how those devices are going to change and how the architecture of those devices are going to change. And when you think about that, the agent acts on intent. As you have now AI taking a role in the man-machine interface, you understand human intentions. We'll proactively understand the text that it needs to react with the human. We'll take it, we'll break it into several steps, will coordinate across systems, across data sets. Your own data set that lives on the device, the data set that is unique to you on your personal graph, and the data set that is going to be in the cloud. It plans, it executes, you'll verify, you will keep interacting until the task is done. And that by definition changes the hardware with different kind of hardware to be able to do this because it's not just what is initiated by the user, the agent is going to be running on its own. It also changes the operating system and changing the application. And I think that's the incredible opportunity that we have in computing across this entire surface area of devices which are going to be upgraded for this age of AI.
You need to be able to tightly integrate across all the compute domains. You have strict power and latency constraints. I cannot emphasize enough the importance of power. Think about your phone. If it is challenging to make your phone last all day with you operating it, what happens when you and the agent is operating it? That's an incredible engineering challenge from power and latency. Those devices need to be able to support planning, reasoning, coordination across the system. And for that you can start to understand how the compute is going to evolve. You need a very strong and power-efficient CPU for the orchestration of tasks. I think the industry now understands the importance of CPU for orchestration and where the orchestrator is going to run. You need very power-efficient and high compute density of NPU and GPU to be able to run local models.
One other thing that I'm going to do today is to show clearly how AI is going to be distributed across cloud and device. I almost feel that it's going to be so obvious that we're going to start talking about it. We're going to stop talking about cloud and edge because it's all going to be one system. And for that, you're going to need the computing power in those devices to do that on the NPU and then the GPU. You need to have sensor data. Context is super important. Without context, you cannot have the agent to be useful and proactive. All of those things are going to be necessary as we think the next generation of devices for the agent AI and an upgrade is truly coming.
So, and it's not the same thing for every device. It is not. We know this at Qualcomm. In personal devices, that means all-day intelligence, very focused on sensors and context that matter to you. Incredibly power-efficient because you're going to carry it, you are mobile by definition. You're going to carry it with you. And you have high-speed connectivity. In cars and robots, that means sustaining processing power on the most demanding conditions and also independent of connectivity. In the cloud, when you have to, and in the data center, inference will require incredible amount of scale and I'll walk you through it. When we think about the demand for tokens and power efficiency, it's also going to matter there. I'm going to tell you something for companies that have the benefit of working in the mobile industry. The mobile industry for decades, you had a different growth rate of computing power and availability of energy. So you have to come up with solutions that allow you to get all the computing power that you need with the available energy because the battery has to last all day and is limited in its size. That's also going to be true when you think about what's going to happen on the data center. But we'll tell you more about that at the end of the month.
And that in itself is the Qualcomm advantage because we have been working with all of those devices at the edge. All of it, and especially the new Qualcomm that has incredibly diversified. We now have an ability to build systems. There's sub-2 milliwatts from an earbud with micro-power Wi-Fi that connects to an agent for personal AI audio device, all the way to kilowatts what's going to happen in the data center. And I think that is the incredible opportunity that we see for us and for our partners when all of those devices are going to change for this future of agentic AI. And for that you need dedicated computing solutions that scale all the way down to a sub-milliwatt device to a 2,000-kilowatt. And that's an incredible opportunity I think that we have in front of us, leading performance per watt across smartphones, PC, automotive, compute, and robots, and extending that to the data center. I think that's our mission and that is the incredible opportunity.
The last thing I'm going to tell you as we keep moving in the presentation, it is there is excitement about what's happening especially on the PC side with all of those agent AI. So as we go through the presentation, I will come back to this and I will come back to the phones because I believe that what's going to happen on the phone is going to be a very good proxy of what could happen on PC and other devices. But hold that thought. So, I'm going to break this down for you across the different categories of devices and I want to show you how those experiences are evolving. I want to make it less abstract and more concrete for you because this is happening right now. So, I want to start with the devices that are really powered by Snapdragon platforms. You will see agents now being deployed and starting to get scale across phones, PC, and this new category of personal AI devices. I would like you to watch a video. Let's run the video.
So this is incredibly exciting and it's really already happening and you can see the agent isn't tied to the device. It actually moves with the user and is there with the user regardless of the device that you have. So that is one way for you to start to understand this change when the center of the ecosystem, especially mobile, is no longer the smartphone. It's about the agent and the agent is going to be across all of those devices. This is incredible and as I said it is easy to see now why we say that this is the year of agents and adoption is really accelerating and you started to see beginning to run on commercial devices. Orchestrators like OpenClaw and Hare are now running on Snapdragon. Assistants like Claude Desktop are running natively on Snapdragon PCs and you see this thing only accelerating and how the users are going to use more and more in their machines and the machines going to be running on their own doing things. And cloud platforms for example like Perplexity Computer are now building orchestration layers that connect to the device. Google is bringing agentic directly into Android with Gemini Intelligence. Microsoft is doing the same and partners even like Humane are developing full agentic operating systems running on Snapdragon. It's truly incredible.
And I'm going to use now this moment before I keep going with the presentation to tell you about the point I'm going to make about phones because actually an important point to understand. There's six billion phones and how user experience is going to be defined. Those orchestrators are a significant milestone in the transition of AI to agents. And I remember for example when orchestrators like OpenClaw became available, a lot of consumers were buying computers, they're buying Mac Minis and other computers and they run those agents and the computer were doing tasks and you can message to the computer. But this is not unique to those early adopters. This is how computers are going to be utilized by a lot of people. If you have a phone, you don't have the ability to buy a computer, connect it to a battery, put it in a backpack, and carry it with you. You're going to carry one device. And those things are going to happen in the phone. So those devices are going to have two personalities. And I'll come back to this. One personality is you going to operate the device as a human. That's how the device of today has been designed to operate. But the agent is going to operate the device as well. And that's how devices are going to be in the future. And that's going to happen on the same device. And the same device doing both, like a phone, is also going to influence how it's going to happen on PC with laptops. And those personal AI devices are going to get scale because they're very natural for AI glasses for example, as close to your eyes, to your mouth, to your ears. They become very natural. And that is this incredible transition we're going to see in compute.
But it's not just unique to personal computing. This is also happening as we think about the transition that we're going to have to the physical world. The physical world is one of the most exciting areas in our industry right now. Cars, robots, industrial systems are going to be also significant endpoints for agent AI. And in those systems you have other requirements. Latency, safety are measured in milliseconds, in millimeters, every single watt matters. So I want to show you a demo next and I'll walk you through it. For example, how things are going to work in a car. When you think about the car, there will be two layers of intelligence. So in the cockpit, AI will personalize your experience and that is the same thing that we just talked about. The agent is your agent regardless of the device. When you're behind the wheel, you're going to take that experience with you, it's going to interact with the agent. It doesn't matter if you're going to be in the car, on a personal AI device, on a phone, on your PC because the agent is at the center, all the devices around it, including the car. But also, the car has other tasks besides interacting with you. It's interacting with you within the context of the car and on the road. You also have physical AI that is perceiving, it is planning, it is acting using cameras, radar, sensors and maps for your navigation. So that's the interesting thing. You have two different layers of intelligence. You have the interaction with you in the cockpit which is personal to you when you are within the context of the car, but you also have the physical AI that drives the car for you. And this is designed to operate as one integrated system. Watch this video of this in action which will understand how the system works as one.
