Capgemini Representative
5:03 ↗
It's a pleasure to deliver this message on the occasion of Qualcomm's investor day to celebrate a partnership that spans 20 years. This long-standing partnership gives us a strong foundation and we are excited to build on it together. Qualcomm and Capgemini can help bring AI from silicon to systems, from innovation to scale deployment and applications. Creating value around AI everywhere—mobile products, auto, IoT, robotics, defense products, and engineering processes. Qualcomm brings expertise in distributed compute, on-device AI, advanced chips, and connectivity including 6G. Capgemini brings agentic products, enterprise platforms, AI native, large-scale product engineering, connectivity software expertise, business transformation, and industry knowledge. Together, we are a complete value chain from chip to system to deployment at scale. This isn't theoretical; we are building on our long-standing relationship. Over the past two decades, we have co-engineered multiple connectivity products, deployed 5G solutions, built V2X connectivity for automotive, and shared experience on Qualcomm's Wi-Fi. This year alone in 2026, we share over 30 client programs. That experience means we can move faster together to new generations of autonomous systems in automotive, defense, and aerospace, and towards advanced industrial solutions to improve efficiency and machine uptime. The opportunity now is to structure collaboration around co-innovation and scalable deployment of reference architectures, and to develop go-to-market models that turn pilots into industrial-scale offerings for telecom, automotive, connected ecosystems, and defense. We are ready and very excited to build the next chapter with Qualcomm.
At Stellantis, we build products and provide services customers truly love and trust. Think about the legendary Jeep Wrangler and Jeep Grand Cherokee, the defining muscle car Charger, or the bestselling minivan Chrysler Pacifica—vehicles that have become icons people connect with every day. Our partnership with Qualcomm has been a key part of our technology journey. What began with connectivity and a digital cockpit now stands to deeper integration across the entire vehicle. Together, we are advancing our vehicles to think and react, making them more intuitive, more responsive, and safer every day. This is how we turn advanced technology into something that truly matters for people behind the wheels. We are proud to partner with Qualcomm to bring these experiences to customers around the world.
I started Figure with one goal: build a general purpose humanoid robot. The world is made for humans, so the robot needs to resemble one too. Nearly half of global GDP is human labor. Figure robots see, listen, and reason. They run on Helix, our own AI model—one neural network connecting what the robot sees to how it moves. We want to ship robots that can go out into the real world, doing everything from logistics to manufacturing and healthcare, to robots that can help day-to-day in every home, hour after hour, fully autonomous. And we're building them at BotQ, our manufacturing facility here in California. A new robot comes off the line roughly once an hour, headed from the factory floor towards our customers. None of this happens alone. Qualcomm has been an incredible partner.
Digital technologies and AI are fundamentally transforming the industries that power the global economy. At Aramco, we believe strategic partnerships are critical to accelerating innovation, and our collaboration with Qualcomm is advancing the technology that helps us deliver energy to the world. Together, through edge AI, we are bringing digital technologies and industrial AI to operational environments, enabling real-time intelligence to enhance decision-making and improving efficiency at our industrial facilities. Our partnership has also delivered the next generation of mission-critical wireless connectivity for industry and distributed intelligence, unlocking more agile, data-driven performance in demanding environments. Beyond technology deployment, we're helping strengthen Saudi Arabia's innovation ecosystem through initiatives like DESAI, design inside Arabia with AI, which supports early stage startups developing industrial solutions. At Aramco, innovation has been at the heart of our success for more than 90 years. Qualcomm is a valued partner in helping us continue this legacy, and we're excited to be building the future together.
At Foxconn Group, we value our long-standing collaboration with Qualcomm Technologies and the momentum behind our shared automotive vision. Next generation infotainment, AI-powered user experiences, and driver assistant systems are becoming key differentiators, accounting for a growing share of vehicle value. Our collaboration supports long-term access to high-performance semiconductors and plays a key role in our next generation software-defined vehicle architecture. By leveraging Snapdragon digital chassis solutions, we can scale our innovation across our future product portfolio and deliver a digital driving experience that continuously evolves for our customers.
Schneider Electric Executive
12:58 ↗
We are entering a new era for energy—the era of intelligence. A unique opportunity to make energy more efficient and more sustainable. To advance energy intelligence to the next level, we are building software-defined products to create autonomous systems with AI-native intelligence. We partner with Qualcomm to make this vision a reality. Our collaboration with Qualcomm has been a true co-innovation journey over a few years and through multiple proofs of concept. We have continuously learned from each other. We are true strategic partners within a broader ecosystem, bringing powerful compute and AI to the edge of our energy management systems to unlock the full potential of hybrid architecture between edge and cloud for our customers. At Schneider Electric, our goal is to advance energy tech thanks to electrification and AI. We strongly believe in the power of tech partnerships. We co-innovate and we need strong technology partners like Qualcomm to move faster and go further.
At Mercedes-Benz, we value partnerships that are built on trust, depth, and a shared ambition to shape what comes next. This reflects what we have built with Qualcomm over many years. Your technologies play a key role in our vehicles today—from high-performance computing to seamless connectivity. And in the evolution of our Mercedes-Benz operating system, MBOS, with Snapdragon digital chassis as part of MBOS, we've unlocked a new level of in-car experience: intuitive infotainment, seamless productivity, and truly immersive moments for our customers. What makes this partnership special is how it continues to grow and how we are working even more closely together. Looking ahead, the future of the automobile will be defined more than ever by software and AI. Together, we're making sure that our customers benefit from a new level of intelligent AI-powered connected experiences in every Mercedes-Benz vehicle. Thank you for the strong partnership and for what we will achieve together.
We are creating something totally new because a wave of innovation is reshaping the world around us. Driven by AI that works for you. It's one of the largest shifts the technology industry has ever seen. And it's the moment Qualcomm was built for. Intelligence is moving everywhere—in autonomous vehicles, personal devices, industrial solutions, robotics, and data centers. To make this all possible, you need high performance and low power, the broadest technology portfolio, and a global ecosystem with global scale. Billions of devices are being reimagined for this new generation of intelligent experiences. That's what makes Qualcomm uniquely positioned for this moment and for what comes next.
Please welcome senior vice president of investor relations Brett Simpson.
Good afternoon everyone and welcome to Qualcomm's 2026 investor day. It's great to be here in New York and see so many familiar faces. Many of you have asked why I joined Qualcomm, and I think we have a really compelling investment case. Today is an opportunity to share why we're so excited about what lies ahead. Thanks to everyone involved from Qualcomm in making this day possible—it's a huge amount of work. I also want to thank the Qualcomm executives here today and the modular executives, Chris and Tim. Now, the agenda: Cristiano will start with a strategic overview, followed by Tony Pialis on data center, then Nakul on automotive and industrial AI, Cristiano again on edge opportunities including 6G, and Akash on financial outlook. We'll have Q&A, then drinks and demos. And I was going to wear my kilt for the Scotland vs. Brazil World Cup match, but I'll be supporting the Tartan Army. Please welcome Qualcomm's president and CEO Cristiano Ammon.
Thank you everyone for joining us. This is an exciting day for Qualcomm. It's been five years since I became CEO, and we've executed our strategy. Today, we start a new chapter. We've built a diversified edge leader across multiple end markets—automotive, IoT, personal AI, compute, industrial networking, and robotics. The next five years have three dimensions: first, building a data center platform with comprehensive solutions; second, becoming a full stack player in physical AI compute at the edge, including mobile devices; and third, transforming from silicon to platform solutions with hardware, software, and developer ecosystem. Qualcomm's advantages include our technology IP, broad relationships across industries, scale in manufacturing—over 1 million leading node wafers annually, 75 tape-outs per year—and execution capabilities. We're present across the entire compute continuum. Now, I'd like to introduce Tony Pialis to discuss our data center business.
Hey everyone, I'm Tony Pialis, general manager of data center for Qualcomm. I joined from Alpha Wave to accelerate value creation. Agentic AI changes compute economics—token counts are skyrocketing, CPU attach rates soaring. Traditional infrastructure won't scale, so a paradigm shift is needed. We've built Dragonfly, our data center infrastructure. Compute has increased over 60,000 times in 30 years, but transformer sizes grow 240 times in two years while memory only doubles, creating a bottleneck. Qualcomm has broken through with our XPU architecture under DRAM stacks, offering SRAM-like performance with HBM density. This eliminates congestion, reduces power, and avoids expensive silicon interposers. We deliver 200x capacity per watt for ultra-low latency workloads and 6x bandwidth per watt for high throughput. HBC earns us the right to win in a $680 billion market. Our AI250 product in 2027 will introduce near-memory compute, followed by AI300 in 2028. We have a full software stack with orchestrators, frameworks, and open tools. Now, I'm excited to introduce Satya Nadella from Microsoft.
Hello everyone. At Microsoft, we've partnered closely with Qualcomm across multiple waves of computing—from PC to mobile and now AI. We share a deep commitment to innovation at the systems level. We're collaborating to reinvent the PC for the AI era with unmetered intelligence at the edge with Windows, and Project Solara for agent-first devices. We're excited about Qualcomm's innovation in data center, especially around high bandwidth compute (HBC), which unlocks significant improvements in cost and performance. We look forward to building the next generation of computing together.
Folks, that was our first surprise. Stay tuned—many more are on the way. HBC targets a $680 billion addressable market, delivering 4-8x performance advantage and TCO benefit. Our AI250 product in mid-2027 will introduce near-memory compute with HBC, followed by AI300 in 2028 with second-generation HBC and scale-up/scale-out networks. We have a full software stack with orchestrators, frameworks, and open tools. We believe in building bridges, not moats. Today, I announce Qualcomm's acquisition of Modular, a world leader in AI software solutions. Please welcome Tim Davis, co-founder and president of Modular.
Thanks, Tony. I'm Tim Davis, co-founder of Modular. We're excited to join Qualcomm to supercharge AI infrastructure. Modular is building AI's unified compute layer—a software layer that enables AI models to run on any hardware, heterogeneous by design. For developers, that means building once, deploying anywhere, lowering costs, and accelerating innovation. Modular is the portable alternative to NVIDIA's software stack, designed for every AI accelerator. Our stack includes Mojo, Max, and Modular Cloud, delivering up to 50% faster AI inference on third-party hardware. We turn heterogeneous data center systems into multi-silicon AI token factories. We're incredibly excited that Qualcomm will help us scale our technology.
Data center customers everywhere, enabling broad hardware independence for the world. Chris Latner, my co-founder at Modell, will share more about our incredible future with Qualcomm later today. Back to you, Tony.
Thank you, Tim. I've been fielding calls all morning from hyperscalers and customers asking how we can begin incorporating Modell's technology. I'm super excited about what we will be doing together.
Now let's talk about CPU technology. Qualcomm has a long lineage in leading in CPUs. They pioneered mobile compute with Snapdragon. We are now winning in both PC and automotive. The company's focus is now transitioning over to data center.
I am excited to introduce Qualcomm's C1000. It is a data center fleet of processors. These processors will run the industry's fastest cores, running greater than 5 gigahertz — more than 30% faster than any of the competition. Coupled to that, we offer more than 250 cores to run the highest throughput workloads. Combine that with Alpha Wave's leading PCIe technology delivering greater than two terabytes of IO bandwidth.
Then add on Qualcomm's memory leadership delivering the highest performance, lowest cost memory solutions employing LPDDR. We have server-class RAS security embedded directly in the hardware. And finally, our CPU is also AI native. That HBC technology that I walked you through for our AI inference engines couples directly as an HBC attach to accelerate AI workloads natively onto the C1000.
How are we deploying it? Through three product lines for the C1000. The first is our Agentic CPU leveraging our HBC attach — we deliver industry-best performance. We then deploy it through general-purpose CPUs running virtualized container workloads. And finally, our AI headnode CPUs running and orchestrating all the traffic across disaggregated heterogeneous compute data centers. All of this targeting a $200 billion market, and that number is growing every day.
My next surprise — I'd love to introduce to you Mark Zuckerberg, founder and CEO of Meta, as he introduces how Meta plans to deploy the C1000 into its next generation of data centers.
Hey everyone, great to be here at Investor Day with you. Meta and Qualcomm have been partners for a long time and we're doing some great work together. We first started on the Quest headsets and then we brought Llama to Snapdragon so people could run AI right on their phones. And today Snapdragon is powering our AI glasses too.
Now we're bringing that partnership into our data centers with our latest model Muse Spark. We're delivering AI to billions of people every day across our apps. The data centers, the energy, the compute to run billions of model inferences — that's what makes it all possible. Our goal is to deliver personal super intelligence to everyone in the world. And as our teams work hard to build state-of-the-art models, we need to innovate with how we get the power we need, scale it, and make it accessible to everyone.
So that's why our work with Qualcomm is so critical. They've spent decades figuring out how to get the most performance out of every watt. They're really good at it, and now is the right time to expand this partnership. Today I'm excited to share that we've entered a multi-generational collaboration for Qualcomm to supply CPUs for our data centers and help power our next-generation server fleet. This will help put personal super intelligence into billions of people's hands. There's a lot more to come and I'm looking forward to building together for a long time. Thank you to Cristiano and all the teams at Qualcomm for all the work you do here.
Satya and Mark already in my presentation — and folks, I'm not done yet. Let's move on to the third product line: custom silicon.
We are in custom silicon to target the highest tier of customers where we can deliver the most value-add by bringing our incredible IP portfolio to play. Our wins to date are based on both Alpha Wave legacy wins scaling into production, and most interestingly, in the first six months here I am extremely excited to announce we have won two major hyperscaler deals that will contribute meaningful revenue to Qualcomm starting at the end of this year.
How do we win in custom silicon? We work with our customers. We take their specs and help them build their chips — whether it's front-end RTL design or converting their designs into chiplet-based solutions delivering the most advanced compute and networking solutions in the world. Then using our manufacturing scale and know-how, we optimize their yield and enable them to deploy bespoke solutions en masse to their data centers.
I've been in this space for 30 years. The way you differentiate and win in custom silicon is through your IP portfolio. We have the world's best custom silicon IP portfolio — our own compute, HBC which is a complete game-changer in AI, Alpha Wave's leading electrical and optical services, silicon photonics expertise built over more than 5 years, all coupled with Qualcomm's leading manufacturing and supply chain. Hyperscale customers have been pulling us in, not the other way around.
The final product line is connectivity — the third bottleneck in the industry. We have everything you need to scale from millimeters of connectivity all the way through to tens of kilometers. From die-to-die technology to co-packaged optics, PAM4 electrical and optical services, and coherent light.
We are already in production with our first generation of 800-gig electrical and optical DSPs. By the end of this year, we will be in production with our second generation deploying 224-gig solutions. Looking forward to 2028, we'll bring our third generation based on 448-gig connectivity.
We have developed a transformational infrastructure that is already winning — four product lines, each anchored with multiple customer wins. Up to eight times better tokens per watt per second than traditional GPUs, greater than 200 times memory capacity compared to SRAM solutions, six times memory bandwidth per watt, and CPUs with greater than 2X performance versus competition.
Tokens per watt replaces flops. The race has changed. We are delivering agentic-first, rack-scale platforms that deliver the world's best TCO. I am very proud to announce that within the first six months on the job, we will deliver multiple billions of revenue starting fiscal year '27, meaning this calendar year.
Now I'd like to introduce my colleague Nakul Duggal. But first, I have one last person I want you to hear from — Tamin, the CEO of Humane. He's a visionary in the industry and he has been our first data center customer.
Congratulations to Cristiano and the entire Qualcomm team on this bold milestone. AI is no longer a technology trend. It is becoming the operating system for every industry, every economy, and every society. I believe the next decade belongs to inference — billions of agents, trillions of interactions, continuous intelligence operating across devices, enterprises, and government.
Through our collaboration, Humane and Qualcomm are deploying the next generation AI infrastructure by combining Qualcomm's breakthroughs in semiconductor innovation with Humane's full-stack AI capability — from infrastructure, cloud platform, foundation models, and our AI system.
Success will not be measured by peak performance alone. It will be measured by performance per watt, performance per dollar, performance per outcome. This is where Qualcomm brings something extraordinary — a fundamentally different approach to AI compute that challenges conventional assumptions about power consumption. Years from now, we'll look back on this moment as the beginning of a new era for AI.
Good afternoon, ladies and gentlemen. A very big round of applause for Tony, first of all. Welcome. Dragonfly is here.
I run Qualcomm's automotive, industrial, and robotics businesses. As someone who's been with the company for over 30 years, there has not been a more exciting time to be at Qualcomm. Each of these three businesses is quite different and unique, requiring different strategies. But over the years to diversify Qualcomm, we've built new muscle that strengthens over time.
We see the next several years belonging to physical AI and the massive transformative change that physical AI is going to drive — especially robotics becoming a key catalyst. Physical AI is the next great computing wave. It doesn't run in the cloud. It runs on the edge — in factories, warehouses, retail, hospitality, hospitals — and robots are going to be a very important part of physical AI.
If you look at how physical AI is moving into our lives, you've seen human-facing AI, you've started to see machine-facing AI, and ultimately embodied AI. These three layers are highly interwoven and they compound over time. Human-facing AI has changed our interaction layer — first with chatbots and digital assistants, but now with body cameras and XR glasses. Instrumented AI, machine AI, is about embedding AI into sensors and cameras — making endpoints situationally aware.
The real economic unlock is physical AI and embodied AI — the ability for devices to perceive, reason, and actuate with the goal of completing physical tasks. That evolution is just starting, and we see a massive edge content upgrade cycle ahead.
In automotive over the next seven years, you will see 500 million vehicles produced with AI cockpits and L2 to L4 autonomy. 50 billion IoT endpoints by 2035. Over a million robots deployed globally. What is today a $300 billion addressable market is going to become over a trillion dollars within the next decade.
Our ambition is simple: we need to own the solution — the silicon, the software, and the stack for physical AI. We will win in automotive, disrupt industrial, and define robotics.
We introduced our first generation of automotive compute products 10 years ago. Today we are one of the largest automotive compute and advanced connectivity players globally. Five generations of compute silicon delivered in 10 years. We've brought the timeline from first silicon to start of production down to 15 months — as fast as consumer product lifecycles.
We now have over 500 million Snapdragon cars on the road, 90 million cockpits powered, and we only entered the cockpit business in 2016. We've launched 450 new car models since 2021 — two new models every week for the last five years. The Snapdragon Digital Chassis is the underpinning of vehicle compute and connectivity globally.
We will exit fiscal year '26 at $6 billion in annualized revenue after delivering 23 consecutive quarters of double-digit year-over-year growth. We have built a $65 billion design pipeline. Our content value from Gen 3 to Gen 5 has uplifted eight times. We are engaged with over 70 automakers and over 100 tier ones and tier twos globally. We are on track to become the largest automotive semiconductor supplier across all pure-play automotive.
We designed Gen 5 for mixed criticality — customers can run cockpit and ADAS applications separately or together. We are running 30 billion parameter models on the cockpit today, commercially. We can run L2 to L4 stacks concurrently. The software-defined vehicle has become an AI-defined vehicle because we can run agents directly on top of SDV with access to vehicle context. A car drives into a parking lot, sees a QR code, scans it, pays for it — that's an agent.
ADAS was a new space for us about three years ago. We are now at 25 OEMs. We have a dozen different stack partners and we're building our own stack as well. We debuted the Snapdragon Ride Pilot stack last year with BMW and are now validated in 60 countries. Stellantis is the latest OEM to deploy the entire Snapdragon Digital Chassis starting SOP28.
We see robo-taxis scaling by the end of this decade. We will build accelerators connecting our SoCs and HBC Gen 2 to provide that same tech to automaker customers. We're also seeing token generators inside the car for federated use cases, and IML use cases for powertrain, drivetrain, and battery management.
This is why we keep winning: full system architecture of a car, global footprint, multi-generational silicon roadmap, deepest and widest software and AI stack in the industry, years of safety expertise, and tremendous supply chain resilience. Automotive is a playbook for diversification, and as AI is upon us, we are very well prepared.
Now let me share what we've done in industrial and embedded. The OT or operational plane in any enterprise has traditionally never needed edge processing — it was all about sending data to the cloud. Now with AI, you have enough information at the edge to process and get to specific outcomes — detecting anomalies, extracting analytics. The OT plane is being rearchitected, creating a once-in-a-generation opportunity.
Over the last 18 months, we built Dragon Wing — a variety of vertical-focused solutions powering AI boxes, connected industrial gateways, edge appliances, industrial PCs, payment terminals, smart home appliances, drones, and body cameras. We focus on three vertical categories — industrial, commercial, and mobility — segmented across 12 verticals.
Vision AI is a major unlock in industrial. We've built an entire video AI stack from camera chips and AI boxes to on-prem appliances to a full video AI service, deploying across retail, smart cities, venues, and more.
We also made three key acquisitions to become more developer-centric: Arduino brought us 33 million developers and a massive global footprint; Edge Impulse enabled model training and tuning at the edge; and Foundries allowed us to manage industrial-grade Linux. We launched Arduino Uno Q and are about to launch Ventuno Q in August — 40 TOPS of AI, octa-core, 12 cameras, full upstream Linux.
Our indirect revenue is up 77% from '24 to '26. Tens of thousands of unique customers, over 200 hardware and tech solutions, more than 35 leading distributors, and 45 global GSIs.
AI is rearchitecting the operational plane, creating an upgrade cycle across billions of endpoints — a massive market opportunity. We have rebuilt our entire product portfolio, developer platform, and vertical go-to-market in 18 months.
Now let me talk about robotics — where embodied AI gets physical. The objective is to perform human tasks: mobility and motion, perception and reasoning, actuating and manipulating in physical space. These are systems that sense, think, and act. This is at least a trillion-dollar opportunity over the next decade requiring a very broad set of technologies that no general-purpose chipmaker has today.
Robotics tasks exist on a continuum of complexity. Starting with inspection — reporting status, visually documenting. Then transportation — moving goods, tools, packages, people. Then interaction with the physical world — pick and place, sorting, assembly. This builds up to multi-robot fleets working in coordination, and finally consumer robotics in the home.
A robot is not one computer — it's three computers working in concert. System two is the reasoning brain — the cerebrum — handling heavy AI workloads requiring deliberative thinking. System one is the action layer that plans motion. System zero is executing motion — the reflex system, millisecond control, the nervous system. This is a heterogeneous compute problem, and we are the only company architecting across all three domains.
The Dragon Wing IQ10 is our central compute SoC — purpose-built robotic silicon that is already commercial. It includes perception IP for visualizing the world across multiple modalities, motion control IP for trajectory and balance, actuation and control IP at the servo motor level, wireless and wired IP for time-sensitive networking, and always-on sensing.
Think about a robot picking a jug of water and pouring it into a paper cup. As it pours, the weight and shape of the cup changes, requiring the robot's hand to sense and adjust grip pressure in real time. That is the complexity of a robot. Three systems are active simultaneously — the brain controller perceiving the embodiment's shape and degrees of freedom, the body controller managing limb movement, and the reflex controller handling real-time motor control at the extremities.
Hand to go to the jar. Knows where the cup is and actually takes that motion on. It coordinates that movement. System zero is actually able to sense the grip pressure, the tactile feedback, the temperature, the moisture, the weight, which allows it to act reflexively across these different systems. We have multiple real-time local loops that run within a system and we have slower loops that are running across systems, and we are building embodiment across all these three different systems.
We are also building a full software and application stack complete with support and SDKs for manipulation to write to various types of sensor, and we will ship sample applications: pick and place robotic arms, office scout applications, AMR for navigation, follow me applications. This is open to every developer ecosystem including the Arduino ecosystem that we just enabled.
The other aspect of robotics development is the simulation data and training model flywheel. We are building this environment in house. We are building, as you can see on the left, a simulation platform where before a robot ever touches the real world, you have to be able to train it in a virtual world. It has to be aware of the physics, the sensors, and the rendering as to how that will take place in the real world. This saves you tremendously in terms of the physical involvement of trial and error.
Then we have the data pyramid. That's the fuel for these systems. We combine real world data that Qualcomm has access to, synthetic data that we generate ourselves, and a lot of open source data. And then on the right, we train the foundation model. This is a single model that can take multimodal input like vision, depth, touch, natural language, and it generalizes across use cases. We train these models with simulators, with behavior cloning, and teleoperations, and with reinforcement learning. So the workflow is end to end. We build the hardware, we generate the data, we develop the models, we deploy them into the customer environment.
We announced our IQ10 reference design at Computex in June, and this is purpose-built silicon which is shipping today. We also have IQ9 and IQ8 for simpler embodiment. And we already designed into the Neura robots, which you can see outside in the demo area, with whom we offer a complete reference design that powers the Neura cognitive robot arm as well as the 4N1 humanoid. These robots are trained in the Neura gem with the robotics foundation model, and they run the neurov application platform. This is a full stack silicon solution with a key customer, a key partner in less than six months.
Today we are powering every type of embodiment, and several are shipping already. We have over 100 engagements spanning the entire robotic stack with companies like Neura and Figure. We are working with several drone OEMs, many AI sensor and embodiment partners. With physical AI upon us, IQ10, the robotics reference design, the end-to-end solution stack ensures that customers and partners design with us. We are taking the same approach that has allowed us to scale very quickly in other businesses.
Robotics is already a reality at Qualcomm, and we are very excited to be powering this next generation of physical AI where we believe we are very well positioned.
To conclude, a few takeaways. Automotive, I hope you are all believers, is now a track record. We've had 23 consecutive year-over-year double-digit quarters of growth. We don't expect to let you down anytime soon. $65 billion in design-win pipeline. We have delivered and we are still accelerating. And we are on track to becoming the largest automotive semiconductor player globally.
We are now a category leader in every domain we enter. And that's not easy to do.
Industrial and embedded IoT is now scaling. 18 months in, we have built a product portfolio with Dragon Wing. We've built developer muscle with three acquisitions, four with Modular, and a full vertical stack that goes from silicon to solutions, and robotics is happening now. It's already shipping. Dragon Wing, IQ10, IQ9, and IQ8 are all in production. Partners are integrating them into every embodiment from humanoids to quadrupeds, from cognitive arms to AMRs and drones. Three industries, one IP foundation, one physical AI platform. Thank you very much. And before I turn it over to Cristiano, I would like to play a video from one of our partners, David from Neura. Thank you.
Hello everyone. My name is David Rigger, and I'm founder and CEO of Neurabotics. What we do is we're building robots and enable them to have cognitive abilities to see, hear, feel, and think and react fully autonomously on all kinds of physical tasks like humans do. The benefit of working with Qualcomm together is giving a robot more than just the brain. What I mean by that is today we're seeing physical AI is mainly seen as a vision language action model, but it's actually much more. It's a little bit similar to swimming. You can't learn swimming by just your brain and by vision. So it means you cannot just watch a video and think you're a swimmer. How to learn swim is simply going into the water, trying it out yourself, and then actually training the memory effect of your muscles. Then training also your reflexes and nervous system, how to breathe, how to move your body to actually stay above the water. The task always require more than actually just vision. They need a feel of touch, they need to hear, and combine that all to build the foundation model which can actually do all the physical tasks on this planet. We did build the physical AI platform we call the Reverse. This is a deployment platform where everyone in the world can actually train and contribute to make this one brain actually smarter. What you can expect for all the partnership with Neura and Qualcomm is basically setting a new standard in physical AI, enabling every robot on the planet and every human on the planet to actually train the robots and enable them for all kinds of physical tasks on our platform Neura.
All right. So I got to the last part of the presentation, I think before Akash will come in to walk you through the financials. And I think before I start what I'm going to tell you next, I think this is what's unique about Qualcomm. I know we have a limited amount of time, but there's a lot of new vectors of technology. Hopefully you'll be able to see that it's not only about one solution in the data center, but also when we think about automotive, we're thinking about industrial, which is a whole different industry. In this field of robotics, you need to have the breadth of semiconductors and technology that we have, and I think that's an opportunity with Qualcomm.
With that, I'm going to talk to you about the future of mobile edge devices. I'm going to try to unpack a couple different trends that are going to happen as we think about the role of agents. As I said in the keynote at Computex, the event of agents and orchestrators was a very significant milestone that actually provides clarity on how those devices are going to evolve. And the industry tends to think in binary terms: is all of a sudden everything going to stop and going to go do the other thing? No, but they're going to coexist. But devices are going to have different types of use cases, and that's what I'm going to try to unpack in this presentation.
The first one I want to talk to you about is we all have been used to the mobile, the smartphone at the center of your digital life, and everything is around that smartphone. The OS, the app store, it becomes the control point of the OS and the apps understand the human intentions, and everything is around the smartphone. Even other devices are just an extension of the smartphone. That's not the case anymore. Actually every AI company, every foundational model company now talk to us that devices are the endpoints for agents. That's where the humans are, and the agent is at the center. It's not about the phone at the center anymore. For the agentic experience, once you understand human intentions, the agent is at the center. Devices are just endpoints of the agent.
And the purpose of my presentation right now is to tell you how the devices are going to change because of everything that has happened. Let's start talking about the user experience. So those devices have been built for the human as the user. So the workflow is based on the human going to an app and doing things at the human speed. But now the device with the orchestrator and the agents are also going to do other things on behalf of the human. So it's going to operate the device, and we're starting to see that right now. If you ask me where's the epicenter of this start of new agentic use cases, it's actually happening in China right now. And you started to see the agents go to your device and operate the device for you, and it goes to the web once for the agentic experience. That tells you that the device now has two use cases.
It was interesting. I said this before, I'm going to repeat it. When people bought a computer to run OpenClaw and they have the computer running OpenClaw, once you start having that experience with you, not about just the amount of software developers they use, they exist on the world, but the six billion people that have smartphones when they started to use an agentic experience as part of your experience and interaction with the device, you're not going to carry it to computer. It's all going to happen in the same device, and the device is going to have two users because there's two different workflows: there's you and there's agents. So that's one big change.
The other big change is perception and sensing, and that's what is actually changing the device in itself and enabling different endpoints like personal AI devices. So if we have now the computer that interacts with us the way we interact with each other, then you know the context that we are inserted, especially as we think about we communicate with audio, we speak, we listen, we see, and then we are integrated into our surroundings, that context becomes important. So you now have a lot of sensing data that needs to be part of, you know, the processing of those devices, and that is enabling also a different class of device. That's why I told you about what happened to wearables and what happened to augmented reality, mixed reality, and virtual reality. Transition is very important because the reason we've been very focused on glasses is because glasses is close to our senses, close to our eyes, to our mouth, to our ear, and those devices, wearables, was extension of the smartphone. When the smartphone is the center for the agentic experience, they actually an endpoint of an agent, and the stuff that you actually wear becomes very interesting. And especially when you think about glasses, just as a side comment: on Microsoft Build, Satya announced Project Astra, a badge with a camera. It's a new class of devices. We have 40 different designs today with some of the largest AI and model companies in the world thinking about those new form factors. There's one form factor we know is going to get scale, and that's glasses, and the use case is see what I see and hear what I hear. And I'm going to come back to the use case because it's also going to talk about another change that's going to happen on devices at the edge. But now what I would like you to do is new companies are looking at this big change: the devices now are endpoints, the barriers to entry of OS and app store for new experiences no longer the same. You're going to see a lot of excitement. I want to start by showing a video from Amazon.
We're in the middle of a fundamental shift in computing right now. And what's most exciting about this next wave of AI is what it unlocks for people, for their creativity, their curiosity, the things only humans can do. Now, as technology continues to fade into the background, the customer must stay at the center. That shift creates new requirements, not only for the devices already in people's homes, but for entirely new devices built for AI-first experiences. At Amazon, we're building for this future with Alexa, creating experiences that work seamlessly for a customer when they are in the home as well as when they're on the go. Qualcomm is one of our critical partners in expanding both the capabilities and reach of these experiences so AI can seamlessly move with people throughout their daily lives. This relationship is about building what comes next together.
So there's a lot of exciting things coming. And by the way, I'm actually so grateful. I have a relationship with Panos for more than a decade. He's an incredible individual visionary, and I'm actually very grateful for the partnership.
So the other thing is we talk about the orchestrator, and you heard about today, those agents, they generate demand for a lot of tokens. The reason a lot of the hyperscalers just see a wall in front of them of compute demand is because the economics of AI are fundamentally changing: agents and orchestrators.
That's why I said the OpenClaw was an incredible milestone. They're redefining the architecture and economics of AI, not only creating an entry point for Qualcomm into the data center but actually creating a fundamental change in the architecture of compute that touches all the devices on the edge. And this order of magnitude increase, if you look at how we started with conversational to now agents, you see the order of magnitude increase. The projection is 40x the increase in annual token demand between 2026 and 2030.
Now I'm going to show an example for you next, and I'll tell you what you're going to see. When we've been doing a number of those things, and you can try yourself, you can try the different prompts, and you're going to see it changes. Sometimes you get 10%, 20%, 30%, 40%, 50%. I just picked a very simple example for you to see today. We've been showing this, so what you're going to see right now is we got two computers. Those computers have orchestrators; those orchestrators, you give them a prompt, a complex prompt. You ask them to do some research, design a web page, put the results. One we're going to be using is just Claude, using Opus 4.6 100% in the cloud. You see, you know, the thing working. The other one uses smart routing: you use some models, they're locally installed into the machine, and some models in the cloud, and you get those things to work. And what you'll see, you know, at the very end, that you see what hybrid AI really means because you will get to exactly the same outcome that you want. But now when you think about things like mix of experts, when you think about different kinds of models, you can actually see how the architecture of AI is evolving. The reason you saw some foundational model companies saying I am going to give up to do video creation, it's very obvious because you can use your compute capacity to monetize tokens of higher value. And that's what we're starting to see actually. When Microsoft also said at Build that they now create an unmetered intelligence, and people really understand what AI PC is, this is happening everywhere. And the beauty of the devices, like phone, is actually happening on the same device with two different users. And you can see a lot of useless debates I have seen over the years about is this edge or is this cloud. It is actually the wrong conversation to say I have something that I need to do on the cloud, can I do it on the edge, and vice versa. That's the wrong approach. Things are going to be done in the cloud; it's going to be done in the cloud. The growth of the cloud is incredible, but the edge now also becomes a computing that is going to generate tokens. And I think how the industry is naturally going to evolve, and the message here to you is like what happened on the data center inference is actually becoming disaggregated and distributed everywhere. It's just a new form of compute. For example, when you look at the architecture, you're going to have the cloud data center which has hundreds of megawatts to gigawatts. You're going to have regional data centers with tens of megawatts, and on-prem, there's a lot. If you look at results of some of the server companies like Dell, there's a lot of movement for on-prem right now. It's not against the cloud; they're both growing. And you also see as you have more of a hybrid AI, you're going to see more computing happen in PCs and devices at the edge. So inference becomes distributed. Just don't take my word for it; we have an incredible partnership with Google, and I want you to hear from Google about that.
Hello everyone. I'm Rick Osterloh, senior vice president of platforms and devices at Google, and I'm incredibly excited to talk about our long-standing partnership with Qualcomm.
As the industry shifts towards agentic workflows, we're moving beyond simple responses to offer true digital agents. These are proactive multi-step systems that seamlessly anticipate user needs across your entire ecosystem of devices.
To bring this to life, our teams are focused on bringing a shared full-stack vision. We're combining Google's advanced Gemini models and Android system-level intelligence with Snapdragon silicon. Together, we're innovating side by side to scale on-device AI and Gemini intelligence to the most advanced mobile devices.
With AI, we're redefining next-generation automotive experiences and pushing into new frontiers with wearables like XR glasses and intelligent eyewear. And this innovation is also at the heart of our brand-new Google Books effort to revolutionize the laptop experience.
True agentic workloads require what we call distributed intelligence. By efficiently balancing processing between the cloud and on the device edge, we can deliver seamless experiences that are private, instantaneous, and personalized.
Our deep engineering collaboration with Qualcomm ensures that the broader ecosystem and our OEM partners can scale these innovations rapidly. Gemini intelligence will elevate the Android ecosystem, making it smarter, more proactive, and more helpful than ever before.
Cristiano, congratulations on Investor Day. Thank you for our outstanding partnership, and I'm really excited about our road ahead.
So big thank you. Thank, thank you to Rick for the partnership and the confidence in what we're going to do together. So and I have to pick up the pace now, and I get to my last part of this presentation, which is about 6G.
So we have been designing 6G for this AI era, and I'm going to now show the role of 6G in this conversation we just had, and I'm going to go fast. So I just thought about new classes of devices like glasses. So the goal of the connectivity of 6G is to transform all of us into walking cameras in this world. I need very fast high-definition video. The opposite of what we did with 5G, which is enable streaming and high-definition video. We're going to do that for uplink and across the cell site. So everyone has the ability to stream high-definition video for see what I see. That's very important context for agentic experiences. That's why we're going to the connectivity. I'll go to the details. There's a lot of improvement on the connectivity side.
But that's only one-third of the story. The other part of the story is the computing part. And the computing is going to be required because the 6G infrastructure is no longer dedicated equipment for communications. The network of 6G actually—you need to be thinking about that was a network that was designed for voice. It now transports bits and is going to also generate tokens. And the reason that's important is because the premise of how 6G is going to deal with radio frequency is going to look at radio frequency, physical AI, and you're going to need compute. Look at the architecture; it's kind of the same as the distributed. You're going to have a big data center. You're going to have a regional data center. That's the core of the network. You have to have an edge data center, and you're going to have the cell site and then devices at the edge. And that's why we're also building our data center solution to be scalable, because when you think about 6G becomes one sovereign AI workloads, and some operators will actually be selling token generation machines capacity, like a CSP for AI companies for this distributed compute. And once you have all of this compute, it brings the next part of 6G, which is sensing, because every single RF is going to be treated as a radar, and you use models trained on that RF performance and the RF radio characteristics. You're going to be able to sense everything. Drone detection is on the top of mind. It becomes critical infrastructure. Everything that moves and flies becomes important context for models, and that's part of the perception.
So with that, I'm going to summarize it. What's happening with devices at the edge right now? They're evolving for agentic experiences. They're going to have more than one user, and we're building the next architecture of those devices. You need now a CPU for the orchestrators. The orchestrator is going to operate your device for you. I think everybody now understands the CPU matters, and it's important. You need to have a different architecture on inference because you have to have very high performance, low power inference even when you are not using the device as a human. And that even that high bandwidth compute that we're doing on the data center, we're building a version of that as a co-processor for phones. There's a completely change on the perception and sensor as well as a new modem. And it's not just about the phone; there are different classes of devices, and that is also bringing other people to the space. So I'm going to finish this part of the presentation asking Hark, a new company also founded by Brett, which is going to show you what they're doing.
I founded Hark because today's AI is just not good enough and nobody's taking real advantage of it. It constantly forgets things about you and it runs on devices built a long time ago. So at Hark, we're an AI lab building the world's most advanced personal intelligence. I think the next AI platform is something that truly knows you, that can see, hear, and act in the world with you. And you don't get there by bolting AI onto existing devices. You do it all together: the models, the hardware, and the interface as one product. That's what we're building at Hark, an intelligence that thinks like you and sometimes ahead of you. We're grateful to have excellent partners like Qualcomm who are helping us realize some incredible ideas. We're excited to release the Hark platform this summer and then the next generation of consumer devices after.
The obvious question that everybody's asking: what is the timing? It's hard to predict the timing right now, and I think actually the mobile market is dealing with the uncertainty of the tariff situation, but it's very interesting. We are incredibly encouraged with the design activity, the number of new entrants. Actually, when I talk about China, I am in a situation right now I don't know what the mobile customers are anymore because there's their OEMs, but every single AI foundational model company building agents are also our customers. The surface area is tremendous. There's six billion phones, two billion personal AI, two billion PCs, and 500 million cars. And when you think about this new form factor, I'll just give you an idea how you should think about the glasses. We're just at the beginning of this, just at the beginning. 600 million glasses are shipped annually. There's less than 1% market penetration for smart glasses. But all you need to do, you can actually, we're building a very small reference design that you can build this to any glasses, and you can see, you can have ability to access an agent for audio multimodal or premium display, and you can see the smart earbuds. So that is a great opportunity, and that's what's also going to happen on the mobile devices business of Qualcomm.
So hope you saw there's a lot of interesting trends in technology, and as I get to the end of my presentation, and I think you're all eager to see what Akash has in store for you, but I am just going to go talk about this number three pillar that we've been talking in this presentation about the next chapter of Qualcomm: from silicon to platform solutions, and to really building a fully integrated platform for hardware and software, but changing also the company to a developer-first, you know, company mindset. And you saw we're doing this with all the new business we build on the edge, and we're going to be doing this from everything we have on the compute continuum. That's why this acquisition that we made of Modular is so significant for Qualcomm, because it's also builds on the pillars of the Qualcomm advantage, not only the technology but the focus on deep customer partnerships and creation of ecosystem and the scale. We have proved that we can partner across the industry, and it's never the role of one company to innovate, though that creates an incredible opportunity.
Before I bring Chris up here and he's going to talk to you for a few minutes, I am going to say, and I may be a little bit aggressive saying this, but I'm going to say I'm willing to bet that not everyone here will understand what we're trying to do. I think some of you will understand, and this is not a negative comment in any shape or form. It just takes a while to understand how we've been thinking about this. I've been, we've been starting this journey with Modular for more than a year, and it took a lot, I think, for me to convince Chris and team, and he will share his story, but I think we may have an Android moment here, and maybe I'm gonna be as bold to say maybe there's even a Linux moment. I don't know, but we I think we have something good, and I think we have momentum as AI goes everywhere, as compute becomes distributed, as you have every single endpoint become an endpoint for agents doing inference, and you have an industry that wants an open ecosystem, maybe that's what Qualcomm can do supporting everyone. With that, I would like to bring to this stage a legend, Chris Lattner, the founder and CEO of Modular, who will tell you about what we're going to be doing. Chris, please come on stage.
Thank you, Cristiano.
All right. Well, thank you, Cristiano. By way of introduction, I spent my early career building today's software platforms. This includes the compiler technology that runs every phone, no matter from whose vendor is in your pocket, the data centers that span all the hyperscalers, built the Swift programming language at Apple, also built the software stack that powers Google's amazing TPU AI scale platform.
Now I decided to join Qualcomm because I found the team recognizes something. They recognize the opportunity of AI today. They have the ambition to do something big, but also they've made all of the investments already that put them in a perfect position to do something about it. Today feels familiar to me. It feels a lot like back at Apple when it was about to take off. Back then there were a lot of doubters. People did not really understand what was going on. But we had all done the formative work already. And so all we had to do was get people to see it through the products in their lives. So let me walk you through what I see today.
So it turns out that compute has fundamentally changed. You've heard about that a lot today. It's no longer about a single chip. Compute today is a large-scale data center distributed systems problem. We all need to program diverse AI accelerators from multiple different vendors. We need to get the best performance, the best TCO, and we need usability because doing all this is harder than it's ever been before. Now, the world is still struggling to get individual systems to compete with the industry leader. But that's where Modular comes in.
At Modular, we spent the last four and a half years building a novel platform that actually scales. All with the goal from the beginning of unifying the industry and opening a new chapter for accelerated compute. Now, we built this platform to scale across a full spectrum starting from the data center, but then going all the way down to the edge. And so, this is why I'm so excited that Modular is joining Qualcomm. We're bringing together the perfect combination of scalable hardware and scalable software. This is joined with a shared ambition from both teams to make a world that is better for everyone with AI. And I got to tell you a little bit about where we're going.
So now let us remember that everybody wants tokens but they also want amazing economics. Now most people don't really actually want to know how it works. The systems, the software components, all the different pieces that go into this are amazing. And for nerds like me, I love it. It's great. I think I'm in fellow company here, but a lot of people just want a solution. And so together, we're lifting the Qualcomm AI silicon business. Silicon no longer. Now it's about solutions. Full, it-just-works solutions. And an AI solution business is far more valuable.
Now, this end-to-end solution approach starts in the data center. Of course, that's our core focus. But it won't end there. This is the first software platform that was designed from the beginning to unify edge and data center utilizing diverse accelerated compute in all the crazy form factors that are pervasive in our lives.
Now we've been using a lot of operating systems over the course of the last decades. But this platform will grow into a full operating system built natively distributed, natively accelerated, and agentically native by design.
And we are not just building this for us. We're building an open developer platform enabling AI developers, AI researchers, and app developers to innovate like never before.
Together as an industry, we understand that we need to scale incredible amounts of compute. We know that this will require many different organizations to come together to make it possible.
The result of doing this all is an incredible opportunity for everyone: all of our partners, millions of developers, and of course, all the consumers that'll benefit from AI products in our lives.
Now, throughout my career, I've had the privilege to drive open standards. I've built several very large scale open source communities. I've been part of multiple waves of compute. And I feel that today, Qualcomm is really quite well positioned to be the best in the industry to lift the entire world. And as such, we're committed to this being an open platform.
Qualcomm is obviously an incredible hardware company, but today we're going further. We're now a full stack vertical AI solution company. I couldn't be more excited to build together. So, thank you.
Thank you.
Hope you share our enthusiasm about this change in the company, this opportunity changing the industry, what we're going to do together. And we're super happy to have Chris, Tim, and the rest of Modular as part of the Qualcomm family. So I was about to end here, but I thought maybe there's one more thing. Hopefully you are entertained. But we have one more thing, and that's just building on this. We're also very happy to announce a very strategic partnership that we're making with Hugging Face.
And I'll tell you about this partnership.
Qualcomm and Hugging Face started a very unique collaboration because they share exactly the same vision we presented to you today for the data center Dragonfly. Hugging Face will be very focused on demand creation from Qualcomm Dragonfly silicon. Both their inference and storage services will map to all the Qualcomm Dragonfly products. There will be agentic model onboarding combining Hugging Face's 16 million developers and what we're doing with Modular across the whole family of Qualcomm chipsets from Snapdragon to Dragon Wing to Dragonflies. All models are going to be onboarded on Qualcomm technology platforms using an agent that is going to handle the setup, the optimization, deployment with zero manual integration work. And then, just what you heard from Chris, build on an end-to-end agentic AI with distributed intelligence. And that distributed AI framework, when agents can operate seamlessly across the entire compute continuum, leveraging Qualcomm technology as a model, and also cooperating with everyone. And I want you to hear from Clement.
