Qualcomm Roundtable Interview transcript — SVP of Compute and Gaming talks Snapdragon C, RTX Spark, and the agentic AI future
Qualcomm's Snapdragon C is making a major play for the hottest laptop market in 2026: The ultra budget segment. But competition is stiff, with Apple's MacBook Neo and Intel Wildcat Lake Windows laptops offering strong performance and battery life in affordable packages - even with sky-high global memory prices.
We sat down with Qualcomm's SVP of compute and gaming, Kedar Kondap, and other Qualcomm representatives at Computex 2026 to hear how Snapdragon C fits into its existing product lineup, and how Qualcomm considers itself uniquely positioned to offer a comprehensive ecosystem of agentic AI devices and software.
This transcript has been lightly edited for clarity.
Kedar Kondap, Qualcomm SVP of Compute and Gaming: Our journey was not about solving what has happened in the past 30 years of PC innovation, but solving what's coming next in PCs. A lot of the innovation that has happened, we've obviously proved to the market that we're exceeding performance. We focused on three big metrics all along the way. One was leading with performance and making sure that we have leading performance in all of our silicon. We want to make sure we lead with power. Obviously, that used to be something super critical across the board, even as we start looking at newer generation of devices, and third, as you look at AI as a key metric.
When you think about the keynote today, and what we talked, what I shall talk about, as we enter this agentic world, it is more and more important. Each of these things play a very important role, whether it's performance, whether it's power, or whether it's AI, and the ability to run these intelligently. Right from whether it is a very small device, all the way to the data center. You saw how we're innovating, and the PC is no different. So we launched our X series processors, we extended that to the X Elite, the X Plus, and the X family. We launched the X2 Plus, we launched the X2 Elite, and the X2 Elite Extreme, and we wanted to make sure our intent was very simple: we wanted to make sure that the experiences we offer are available to all the consumers at every price point that we could address. What we introduced yesterday is a new class of platforms, the Snapdragon C. Our intent with that is to address platforms in lower price points that we can go and make sure that we can deliver the same performance pillar, the same battery life pillar, as well as provide AI functionality to all the consumers at price points that were never heard of.
So with that, we wanted to make sure that we have a full stack of products, we are addressing the needs of what consumers want. Consumers want the best performance, the best battery life, and as we enter this world of agentic beta, we want to make sure that across different devices, we're addressing all of these price points. So, we’re excited to be here, and I know there's a little bit of a longer introduction, but I want to make sure you have the perspective of where we come from.
Journalist 1: Thanks, Kadar. Nicole. You were just on stage with Advantech. Can you get us a little background on your announcements and what was said on stage?
Qualcomm Representative: Advantech has been a great partner of ours. I've done more recently the industrial business for Qualcomm, and so, you know, for us to get into this new area, and industrial is actually changing very rapidly. We are starting to see AI enter into the operation, advantage has been here in this space for a number of years, and so we announced a variety of different products to them over the last couple of years. Great to actually be at their keynote. We also announced yesterday [unintelligible] robotics reference design, which is something that is a new area for us. We've been partnered with Advantech for a number of years in this space, but the robotic session design will be a humanoid focus session.
Journalist 2: I'm wondering, Nvidia, a few hours ago, announced they were entering PC market. You guys have had it yourselves for the last two years. How are you thinking about how others come into [unintelligible].
Kedar: Welcome to the family [laughs]. We are, you know, we're excited when you think about the investments that we've made over the last several years, it's a good endorsement to the fact that there is an ecosystem that's growing outside of x86. We invested early on, we invested many years ago, with right from whether it is driving the ecosystem, driving the entire platform story. Whether it is getting the printers to work, whether it's getting the software apps to be compatible, whether it is getting the docs and peripherals to work, whether it's getting more than 2500 games to be compatible with Snapdragon, we led the way in driving that ecosystem, and I think this is positive tailwinds for the entire ecosystem. They'll tell us how we're all taking the ball forward in the trajectory that we started.
Journalist 3: This is for Nichole. She's had remarkable success in automotive and moving into robotics. Is there anything you’ve learned [unintelligible].
Qualcomm Representative: We’re learned a lot from automotive. I think AI at the edge with robotics is a really fascinating space, because you are starting to see this transition where you start to apply AI to start off with an unskilled worker, gradually start to go build up on level of skills, and ultimately start to get to something great. A lot of the underlying capability is similar to what we saw in the early days of automotive, especially the mobility part is quite similar. That will scale very quickly. We will start to see coarse dexterity, so that it's essentially transportation of goods, et cetera. That will happen over the next couple of years, and then the more complex final precision tasks will take more time.
But we are betting across the board, we are betting on models, we are betting on full embodiments. You'll hear more about this tomorrow. We're betting on a variety of different form factors with arms as well. We are also starting to look at what we can do in the end effector space, so we have a lot of technology around precision for the actual and effect of the arms, the actual digits, and what it is. What I like about robotics, which is quite different from the car, is that within the same embodiment, you have to have a lot of different technologies that cooperate, and that is something that we have a lot of capabilities. Lot more to come, but I think super interesting.
Journalist 4: When I was at the keynote from Jensen Huang, I was surprised when he mentioned the RTX Spark platform will support every Windows software ever written, and you suffered from Windows software in running on ARM. So, could you comment on that? And another question, if you could maybe share some more details about Snapdragon C platform, especially the TOPS. I saw a model from Asus, but it was behind in the glass box, and they didn’t have a lot to say of interest in that matter.
[Jensen Huang] mentioned that they will do an announcement tomorrow with Microsoft about the RTX Spark, and he mentioned that every Windows software that has ever been written will run on their platform, and this is not true for your platform, and probably for any Windows on ARM platform right now. So, I'm wondering if you want to comment on that.
Kedar Kondap: I don't want to speculate, but I'll tell you, our partnership with Microsoft has obviously gone several years in the past. We worked with them very closely. We launched the first Copilot class pieces together. We launched the first platforms where Microsoft OS supported it, and supported how these distributed computing work across a different course. So maybe once we start getting more information, we can, but I think I'm sure the engagement of Microsoft is strong enough where we work with them to build this entire ecosystem to make sure that it's compatible with Snapdragon and the architecture, so maybe once we get more information and get more, we can look at it.
The second question on Snapdragon C, so we haven't yet given out the specs for the products, but I'll tell you how I think about Snapdragon C. We wanted to, our OEMs are very anxious to bring this product to market, as is Qualcomm. There is, as we all know, there is a memory supply challenge in the market, and I've heard there's a storage supply that's also challenged, and we wanted to make sure that we have an offering where we can address a lot of price points that we've never addressed before, so think price points below what Snapdragon X has offered in the past. Snapdragon X will give you its relatable, you know, it's great platforms that get 599 today, some of them that hit 500 and above the X plus goes above and X Elite goes above that, so think it's a tier below what we can offer with Snapdragon X, and so our intent with that is to drive the same level of capabilities, obviously scaled to that tier, and what I'll tell you, it's just like the way we've exceeded expectations in launching specs of our products in the X series family of products. You should expect that the C in its class of products will lead its way, but we'll obviously give out specs for you.
Journalist 5: I've got a question regarding [Qualcomm’s] vision on how the tokens in a car, in a PC, in a smartphone and adapts and talk to each other. Cristiano said that we're going to need zillions of tokens, and they're going to be orchestrated. It means different parts going to generate the token, where it's relevant. Okay, like latency, horsepower. How do you gonna orchestrate them with your industry? Are you planning to build a software ledger, SDKs, or building a patented or open system? How do you plan in this vision to open everyone with a heterogeneous chip market, it's going to be difficult to make everyone work.
Qualcomm Representative: So I think it will vary by the ecosystem, but yeah, we will certainly build orchestrate the [unintelligible] where it does make sense. I'll give you an example of a car. We had already seen in the car a tremendous amount of content. You don't actually need, you can't even expect in many cases to be running models that all just have to go back to the cloud, just because of networking latency. So we have deployed already earlier this year 30 million parameter models in car. It depends upon what the types of use cases you're trying to run, but then if you think about this in the context of splitting search versus what it is that you're trying to run locally within the vehicle that is happening today. I think this starts to get more and more sophisticated as you start to define what is the use of the model at the edge.
So, with industrial, for example, we are starting to see already VMA is getting deployed in cameras when you have evidence at the edge, where you can annotate at the edge, send it out to cloud as an input, so it's going to depend quite a bit on which the ecosystem that you're trying to run your account. If you look at use cases like polling, if you look at use cases like search, those are probably obviously much more in consumer and enterprise nets, which should have different network orchestration, probably much more controlled by traditional ecosystems. An orchestrator is going to be a fairly standard offering as well.
Kedar Kondap: Aiden. I'm going to add a little bit more context also to what we'll just say, you know, the way you should think about how we think about overall income advantage, it's going to be the context awareness that you get across the various devices, and think of a personal knowledge graph that you build in the examples that he showed, right from whether you're wearing an XR glasses. We are able to connect. You can see what you see, you hear what you hear. You can have context awareness of what the user is doing. It's going to listen to what information you talk to when you're, say, at the doctor's office. You understand exactly when your next appointment is.
The ability for it to abstract all of this information, transfer that knowledge graph agentically into your calendar, into what your daily routine is, be able to take your personal information, whether it's talking about your healthcare routine. The goal that we see is first is to bring all of this orchestration together, and Qualcomm is uniquely positioned, as you can tell, right from whether it's a small physical personal device, whether it's a ring, or whether it's an XR glass, all the way from phones to PCs to automotive to robotics and data centers, we feel like we're in a unique position like one another.
Second, on the question about running stuff on device, now we've always said the world in the last two years. You know, I remember when we launched Snapdragon X Elite. We said with a lot of pride that, oh, we can run 30 billion parameter models. You know, today, fast forward that conversation, we showed 20 30 billion parameter models running on the C Snapdragon X platform. So, models have evolved. I can, what I could do earlier with, you know, accuracy of quantization and stuff, I can do a lot more than I couldn't do in the past. So the industry is evolving, where we're innovating, we're adding more capabilities to each of these devices on-prem, I'll say, or physically on device. At the same time, we know that the token economics, as Krishna showed, everybody in the industry see it?
So, if any of you use, if you have a poster subscription towards AI, you know you run out of tokens very quickly, and there is the fatigue is real, the fatigue on the side of a consumer, the fatigue on the side of the model. You cannot have both of those, the balance doesn't exist today, so the way we see it is one, you can connect all these orchestrations across the devices, same, you can orchestrate on what runs locally on the device, and of course we believe some of it will go in the cloud, and that hybrid orchestration is where we believe the industry is going, so build the knowledge graph across devices, run what you can locally on the device, if not, if the model is large enough, it will go to the cloud, and this whole equation will evolve over time as models start to become smaller, as they start getting quantized accuracies to be better.
What was, like I said, a 30 billion parameter running on a Snapdragon X, I can already run 30 billion parameters models quantized with very good accuracy. So that's how what we mean by this industry and ecosystem is going to change.
Journalist 6: I would like to touch on Snapdragon C again. You expect the platform to be a regional-specific solution, like for emerging markets, for example, and Qualcomm has great experiences in markets like India, for example, where do you expect it to be a global platform? And I'd like to touch on the NPU as well. Previously, every Snapdragon X platform, at least, had an NPU that OEM Certified Assistance for Copilot Plus seems to be the first solution where you sort of loosen your own set of requirements for a Snapdragon compute platform, and what led you to that decision?
Kedar Kondap: So, Nicholas, first I'll answer your first question, which is: it is a global platform. You will see this device launch globally. You know, for us it's there's a large stamp, as you know, in this particular segment. Lot of consumers that use PCs that sit in, I'll say, below the $500 price point. So, we have a large stamp that we can address there. The TAM [Total Addressable Market], as you know, is naturally biased towards emerging markets. So, from that perspective, yes, the focus, you'll see the platforms launch in many of the emerging markets, as well as developed markets. The TAM is much reduced in that, so it's just a function of the definition of where the time sits.
Your second question around NPU, no the platform does have an NPU, we just haven't talked about the sizing, but as you can tell, the silicon economics, we're sizing everything with the capabilities to be able to run use cases synchronously with the price point that we're addressing. So, think of it as you'll still be able to run, get a lot of the capabilities, you'll still be able to run a lot of use cases we talked about, while preserving the performance and battery life goodness that we bring with the Snapdragon product, so you'll see something very similar.
Journalist 7: There's been a lot of good questions on Snapdragon C, but if you're not competing with Neo, what specific product lines of products are you competing kind of in that below $500 price range?
Kedar Kondap: You know, you already heard a couple of our OEM partners talk about devices. I think Asus talked about the device. I want to make sure I don't jump the gun with the excitement that our partners want to launch it, but I think Asus has already announced. We've also addressed the fact that Lenovo, as well as HP, we announced with HP. Just want to give out somebody's information. We've announced with the OEMs, it will sit as I said, you know, Snapdragon X sits at around 599 type products, and it competes, as you know, better than what you can get with Neo and performance insights.
This gets the price points that it would be below 500, obviously. Now, the thing I always have to caveat is the memory and storage prices. I never know what it's going to do to devise price points, but that's how the platform is positioned. Think of it as small core competing products, but you know I'm nervous to say that, because it's going to be so much better than what existed in the market, so that's why I don't want to tell you that it's compete against that, because it's a different class, it's going to be a lot better than what's what you're used to seeing in market,
Journalist 8: Sorry to ambush you with another Nvidia question, as I know you already said you didn't see the announcement. They are going after a market that you guys have historically not went after, I think a few years ago you publicly said this is just not our wheelhouse, so are you guys planning to compete with what Nvidia is doing now, and if so, how?
Kedar: Like I said, I haven't seen this. I don't know what they've announced, but at the end of the day, look, we've come a long way from where we started. We go a couple years back, what we said, Rich, was we have the legacy, we have the technology in even things such as gaming. We come from, as you know, we have a very strong game studio house. We work with all the game engine guys to work with the net engine guys. We work with the studios on the mobile side and other platforms that we work with, but we bring all of the games to Snapdragon. Since we launched Snapdragon X in less than 24 months, we've done a lot of games that work with Snapdragon effectively go from 1300 to more than 2500, 2600. So I think what we've mentioned in the past is not that we couldn't support it, what we've said is we want to carefully not position this as a gaming laptop, right? The gamers who think of launching this as a AAA game-based laptop is not what we want to position.
We don't want to create confusion with what we're addressing, but from a technical perspective, nothing prevents us from addressing a lot of that, because, as you know, even when you think about creators, we've talked about our partnership, and what we've done with Adobe, what we've done with Black Magic, and others. So, we've already showcased that the entire creative industry is something that we support. We sold multiple use cases, so it's the entire ecosystem that already we've been addressing. So, like I said, I'm assuming that their introducing their platforms in market today is tailwinds for what the ecosystem will see as a strong showcase of non-x86 architecture.
Journalist 9: On the question of the Snapdragon C, somebody spoke about the emerging markets. One of the things which has happened in those emerging markets that arise on the tablet usage. So in the past three years, four years post pandemic, you can say that many of the people are buying who are stuck between a rock and a hard place, that you know, laptops are slightly expensive, they have a full use case of the productivity of a laptop, but they wanted a slightly bigger screen, so they are buying with sliders and the keyboard, especially the emerging markets. So, I just want to ask you, is your target that consumer, and do many of those cohorts is parents buying for the kids or education market, private or public, both? And the public market, you know, you know some of the PC loans, they've really done well, and they are restricted that success in the past year or so in education and some of those emerging markets, because the price points are creeping up now. So I just wanted to double click on that. Who is that target consumer in those emerging markets where we expect the volume to come from?
Kedar Kondap: So, as you know, we already play in a very strong manner with the Android tablets in all of those ecosystems, we have very strong partnerships across almost all the OEMs that you can think about. We have Samsung, OV, WOSU, Lenovo. We have all of these tablets that have launched. There are specific tablets I've launched that are focused on gaming all the way to productivity, all the way to education. So we have very strong portfolio products launched even in emerging markets with our partners.
With Snapdragon C, I can see a market out there, as you correctly pointed out, education being a very strong segment would address all of that. So, if you saw the press release that we talked about, which Snapdragon C we specifically call out that we will be in the education space. We are doing a bunch of pilot programs with our partners to go and address that. I wouldn't necessarily say that it's going to replace Android tablets, necessarily. I think hard to call whether that ecosystem is going to move away from Android to Windows, but right now they coexist pretty well. Like, there's a good TAM that's available for Android tablets with a stylus, as you correctly pointed out, as well as a TAM with Windows PC, and I think with this particular one, for now we'll be launching the Windows segment.
Journalist 10: Can I talk about we just launched, like Qualcomm with Asus A16? Will you deepen with Taiwan cooperation?
Kedar Kondap: I can't tell you how grateful I am for the partnership with the entire Taiwan ecosystem. The partnership goes obviously deep partnership with the ASUS, and we're grateful for the partnership with ASUS, brings a lot of innovation and market. If you've seen, if you haven't already played around with it, or if you haven't seen it, I encourage you to look at the A16 device with the Snapdragon X2 Elite Extreme product. It's a beautiful, thin, light laptop with significant hours of battery life, so it's a, it's a beautiful laptop, and that's because Asus brings a lot of innovation. You heard yesterday from Acer with the Snapdragon C platform that they're launching, but it goes beyond just the OEM partnership for us here in Taiwan, right?
We work very closely with all the BIOS guys, whether you know all the IBDs, we work with the inside, we work with AI devotees, we work with all the partners there, we work with all of the EC manufacturers, we work with ecosystems, so it's not just one cookware, we work with the camera sensors. So we do a standard ecosystem partnership summit here in Taiwan, the offense is just because innovation is going to happen here, and I think what you hear, even as I speak on Wednesday, is as we talk about what we try to throw the vision of moving to agenting, it's going to need a lot of innovation, that innovation is going to change the way the PCs are going to look, is going to change the edge appliance market, is going to change, because now you're going to be running these hybrid models, running and stuff, and we really believe that Taiwan is the hub for driving innovation, and, like I said, we're very grateful for the partnership that we've had with this ecosystem for the last many years.
Journalist 11: Looking towards the intelligent orchestrator for managing workloads. Do you see a primary device managing the personal AI agents? Would it be a smartphone, a transportable puck, a locally hosted cloud instance, for example?
Qualcomm Representative: I think the orchestrator is actually going to be associated with the user, so it's going to be a personal orchestrator, and the devices will evolve along that orchestrator. I think it depends upon the specific ecosystem that you refer to. So, let me pick an ecosystem that may be different from a personal device that is owned by an Apple or Google system. There are several ecosystems where the personal draft, for example, is specific to the enterprise that would like to own that specific data. It could be within an industrial environment, it could be something that requires the data to be resident within the premise owned by that specific enterprise.
In those environments, it really just comes down to what is the type of data that is being exchanged, whether it is data at the edge, data that is network specific, that is manipulated, that is interacting by the specific data. As you start to think about this in the context of the enterprise, I think, depending upon the type of data that this might be, so if it's a personal device like a camera or my glasses, then it starts to move towards the context within the data, there will be changes in the interaction, so for example, today if you think about enterprise data that is sitting on your laptop, that is part of your email, that is part of your SharePoint. How does that interact with the personal devices that you have? Those are things that, in my mind, are still going to get sorted through, but you're going to start to see the personal graph nature move more and more towards the user itself as a personal device.
We believe that the cross-device, as I said earlier, is what will play a super important role. The context awareness from the agent having access to your personal information and bringing that context to information from one device to another, and being able to drive that continuum, is what's going to differentiate more common. We feel we're in a very unique position to be able to go from pocket all the way to the cloud in driving that entire ecosystem.
Journalist 12: I have a question about the economics of the new world you mentioned already, the memory crisis, the skyrocketing memory crisis. I would like to know what impact you expect of the rising memory prices on the development of these agents in future on the consumer side, enterprise side, but also maybe on the other platform side.
Kedar Kondap: I think let's separate out two different things. One is we've all people that have been in this industry long enough to know the sequential nature of what happens with memory. Of course, this time is an anomaly in terms of what we're all seeing. I respect that, but at the same time, we know that eventually the supply chain economics balance out with that, right?
Like, over time, it may not come to the same levels as what we've seen in the past, because this is obviously a super cycle in terms of memory that we've never seen before, largely because of the needs of what AI, what the ecosystem needs. At the same time, though the token economic problem is a real problem, which is you as a consumer you want to be able to use more AI and you want to be able to be more efficient with what you're trying to do, but you're there's only so much in terms of affordability, same thing on the enterprise side, all of what you think about op-ex moving to capex, you have to be able to have that migration happen where you see your op-ex that you invested in and you're going to start moving to capex, or you're going to start getting every employee is going to get multiple models and drive that efficiency that you can get as an enterprise that you want, that migration is going to happen once you move to the other side.
With that migration, the entire equation of economics changes. Why? Because now, if I'm an enterprise, I know that running stuff on device… I'll give you an example, if I can now start running 5070 100 billion parameter models locally on prem, whether the device is a laptop, whether it's a 5 billion parameter model that runs on a phone, or whether it's an edge of line that sits in my desk running a 50-100 billion parameter model, or it's an influencing card that sits in on-prem, I know that the token economics dramatically changed, but I also know that as an enterprise to be able to run trillion parameter models, I'm going to go to the cloud, but I know I need to invest to be able to run on device.
So this balance of equation is what's important, and we feel like this is where we've always said the world is going to go hybrid, we've always said it's not once you're done with training in the cloud, it's going to start moving to the edge with your inferencing, and we feel very good about the position we're in, because that's where we've been investing for the last several years to drive this on device as well as hybrid approach.
Journalist 13: While wireless transition is a very big effort [unintelligible] has put a lot of time in those transitions and a strong focus, you almost single-handed move the industry to the next level, and that Qualcomm changed a lot, now it's more, much more diversified. So, my question is, is Qualcomm from today able to have the same focus on the safety transition in the future, or it may be more help from the industry?
Qualcomm Representative: We are wireless company first, so yes, we have a lot of focus on safety. I think wireless is in the DNA of the company, and wireless is really part and parcel of everything that we do. I mean, if you think about the complexity of building a cell phone, then there is a reason why very few companies are successful with these things. I think the 6G transition, maybe just to speak with 6G, is a very interesting transition, because we believe that the networks are going to actually become very intelligent in 6G, you'll be able to get a sense of creating a virtual digital trend of environments around you. It will bring telcos into the fore in terms of being able to get a much better sense of the physical world. It's a major area of work for us, and these G transitions take a decade, right? So you know that it took a decade for us to be develop 5G.
Journalist 14: Kedar, you answered a couple questions already on the personal graph and that comment about the agent moving closer to the user. I get the point that Qualcomm spans across multiple devices, and that they're, you know, that you're at a unique advantage because of that. But can you take us through how that would be architected? I guess inevitably, if it's spanning across devices, cloud has to be involved in this process, right?
Kedar Kondap: I think Brian, the way you should think about it is, first, we know that the entire ecosystem is fragmented, and we believe that as different hyperscalers, as different model providers, as different OS vendors, as different silicon vendors, all of these need to come together. We were not giving out much information today on what we're doing there, but as you can tell, what we are trying to indicate to the industry is today we have the ability to thread all of these things together, and we're uniquely positioned on how we want to do this over the next several months. We will come out more with respect to how we want to be able to tie these together, but the industry challenge that you highlight, and that's why we feel like we're at the center of driving innovation across this to bring this industry along to try something that's innovative.
Journalist 15: I'm going to be one of those guys who brings it back to the ARM thing. I'm just going to read you what Jensen said in his keynote, because I think I'm just going to read it deadpan. “This computer literally runs everything the world has ever created, and it runs agents.” So I don't know if that's true, but I kind of wanted to give it to you, and kind of hear, what are you guys working on in terms of like compatibility, or even emulation, because we've seen a lot of interesting ARM-based emulation coming from like open source places, so is there anything you guys are working on in terms of compatibility that is trying to push things forward?
Qualcomm Representative: I don't know how to use a broad statement like this to give you a full answer, but I'll tell you what we'll do today. There's about the last night track with my team, was we were worried about 50 claws that are available in my team, and from a snap back in perspective, X series perspective, these are run on the device, I think Krishna showed a bunch of these, a bunch of claws that he showed on stage, so you should imagine that we're, we've been leading the industry with driving agentic AI and orchestration on the PC for the last couple years.
So a lot of these models already exist, a lot of these claws run very effectively on Snapdragon, the models are running effectively on Snapdragon, so you should just assume right now that we've shown you the data that we're already dealing with industry with tight innovation.
Journalist 16: Do you see robotics requiring the two layers of intelligence like with autonomous vehicles, or will the user interaction be more integrated with its physical functionality? Essentially, will the robot-human interaction be controlled more on the user side or the robot side?
Qualcomm Representative: I think that is going to predominantly be very similar to what they can do today already. So, language in the primary interface, what the human is talking about. Where it starts to get interesting is when you start to get into responding to a command. So, for example, if the human would like the robot to go do something that kicks off a task for the robot to be able to complete, and that is usually not a question answer conversational type interaction that usually requires the robot to be able to take on a longer horizon task that brings in additional models that bring in additional tasks that are outside of what humans might typically engage in, but the primary interface will remain the same conversation.
Journalist 17: I'll bring it back to Nvidia. I just want to add that from a CPU and NPU perspective, I think, from a GPU perspective the RTX 5070 class, what I have been missing is like what is called Qualcomm’s view from the GPU premium side of the market. Let's say personal computer market, so I need a bit of clarity there, and the second part would be to just focus it towards the developers and the AI community.
Kedar Kondap: Let me tell you, let me address your first question, which is when we look at launching a particular platform in market, whether it's the Snapdragon X Elite, the X Plus or the X. We always look at what the market needs, and we have a way to size where we feel like workloads are best run on a platform. It's the composition of how you could think about silicon. We have a very powerful GPU. We have the IP that we've invested in the high-performance GPUs and CPUs in-house for the last many, many years. We have to make sure that we're addressing a certain price point from X Elite to X2 Elite and X2 Elite Extreme. We size a significant improvement in our GPU performance, largely to address a certain set at the same time. You have to know that where we're shipping products are in certain price points with that target ASP in mind. I don't know what the industry is looking at with newer platforms are getting launched in market.
I haven't seen any of that data yet, but I'll tell you, all the cores that we support are sized to do that. With respect to their second question on developers, we've come a long way today in terms of where you see developers. Like, the entire developer ecosystem is behind what we've done. I talked massive numbers in terms of apps ecosystem, we talked in terms of developers porting apps natively on platforms, natively on Snapdragon, optimized to the NPU, so we have all the tools, everything that we've provided. So I think you should just expect that as we start moving into this new era of agentic…
Brian asked the question of how we're going to bring all these together, you should assume that we're working with the entire ecosystem, because I'll repeat what I said earlier. We are in a very unique position to be able to bring all of that orchestration, so whether it's a wearable, like an earbud or a watch, all the way to whether it's a PC all the way to whether it's a tablet, auto, XR, you name it. We're going to make sure that we're sizing all our platforms and technology to what the industry needs for that particular segment, so it's very segment-based in terms of how we look at the market.
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