M&A Announcement

Sep 14, 2020

Good morning. My name is Lisa, and I'll be your conference operator today. At this time, I would like to welcome everyone to the NVIDIA to acquire arms conference call. All lines have been placed on mute to prevent any background noise. After the speakers' remarks, session. Thank you. Simona Jankowski, Head of Investor Relations at NVIDIA, you may begin your conference. Thank you. Good morning, everyone, and good afternoon to those in the UK. With me on the call today are Jonathan Huang, President and Chief Executive Officer of NVIDIA Colette Kress, Executive Vice President and Chief Financial Officer of NVIDIA and Simon Seeger, Chief Executive Officer of ARM. I'd like to remind you that our call is being webcast live on NVIDIA's Investor Relations website. The webcast will be available through replay following this call. In addition, you can find a presentation on the proposed transaction on the NVIDIA Investor Relations website. The content of today's call is NVIDIA's property. It can be reproduced or transcribed without our prior written consent. During this call, we may make forward looking statements based on current expectations. These are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a discussion of factors that could affect our results and business, please refer to our most recent Forms 10 ks and 10 Q and the reports that we may file on Form 8 ks with the Securities and Exchange Commission. All our statements are made as of today, September 14, 2020, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. With that, let me turn the call over to Jen Hsun. Thanks, Simona, and thanks, everyone, for joining. I'm delighted to announce that NVIDIA has agreed with SoftBank to acquire 1 of the greatest technology As all of you know, ARM is the world's most popular computing platform. ARM's customers have shipped an astounding 180,000,000,000 chips based on its CPU and its technology is used by 7% of the world's population. ARM chips power everything from cell phones, smartphones to PCs to network infrastructures, supercomputers. We're also we have also used ARM's technology for years, including our SoC for Nintendo Switch console, our self driving car computer, the new Mellanox BlueField Smart NIC and our Jetson Robotics computer. By combining the world's most popular CPU with NVIDIA's AI computing platform, we're creating the leading computing company for the age of AI. Before I get into the deal announcement, let me explain how we see the world and how this transaction fits in with it. Today, the Internet connects billions of people to giant cloud data centers. In the future, trillions of devices will be connected to millions of data centers creating a new Internet of Things that is 1,000 of times bigger than today's Internet of people. From smart retail to manufacturing and service robots, self driving cars to smart streets and cities. Computing will extend from cloud data centers to every corner of the world. The software powering this new Internet will not be written by humans, but by computers learning from data. This is the new wave of computing and it's called AI. The age of AI is driving a tremendous acceleration in the demand for computing precisely at a time that Moore's Law has slowed. This requires a new approach in computing as legacy architectures are not keeping up. Accelerators NVIDIA's accelerated computing platform has risen to the challenge and is leading the path forward and is the backdrop to why this deal is so compelling and complementary for both businesses. There are several exciting growth drivers in our combination. 1st, ARM's vast ecosystem. We can bring NVIDIA's GPU and AI technology to large end markets including mobile and PCs. 2nd, in the data center, NVIDIA will turbocharge ARM's R and D and meet cloud computing customers' demand for a higher velocity Arm CPU Arm Server CPU roadmap. NVIDIA AI would be an excellent support for all data center CPUs, x86 power and ARM. And third, we can accelerate our edge AI and IoT roadmap and growth trajectory for the next wave of computing. The combination will boost our ecosystem of developers who are the cornerstone of our computing platform. ARM expands NVIDIA's developer reach from 2,000,000 to over 15,000,000. The deal will also bring tremendous benefits to customers. We will offer ARM customers access to NVIDIA's AI and GPU IP. We will boost ARM's DAS software ecosystem with NVIDIA's AI and accelerated computing platform. And we will offer cloud data center customers, the broader computer industry, a stronger server CPU roadmap. NVIDIA will maintain ARM's open license model and customer neutrality, serving customers in any industry across the world. We will also retain the name and the strong brand identity of Arm in his home base in Cambridge. Simon and his management team are excited to join NVIDIA. This combination makes financial sense. It is a great deal for both SoftBank and for us. We expect it to be immediately accretive to NVIDIA's non GAAP gross margin and non GAAP EPS on closing. It will also more than double our target addressable market to $250,000,000,000 spanning from computer graphics, smartphones and other devices to data centers, automotive, edge and IoT. I am beyond excited to have joined forces with the talented people of ARM to build this future together. Let me now turn it over to Simon to say a few words. Simon? Thanks, gentlemen, and thanks to everyone for joining. The proposed acquisition is a huge moment for ARM. And for ARM and NVIDIA, it's a new chapter and a new opportunity for us to change the shape of computing over the next 30 years, just as we have in the last 30 years. The next wave of computing is where AI will be the defining technology. The computing platform of the future runs a complex software stack upon an array of processing elements, CPUs, GPUs and DPUs or data processing units, and that's across networks with applications running simultaneously in the cloud, on the endpoint and at the edge. The hardware and software challenges that must be overcome to deliver this future are vast. Bringing together the technological strengths of ARM and NVIDIA will, I believe, enable us to uniquely address these challenges and put solutions in the hands of innovators who will continue to deliver amazing products built on top of our platforms. As part of NVIDIA, ARM will continue to operate its open licensing model, while maintaining the global customer neutrality that has been foundational to our success, with 180,000,000,000 ships shipped to date by our licensees. There is so much more we can do together as a combined company. As Jensen mentioned, NVIDIA has committed to opening a new global center of AI excellence in Cambridge, which will include an ARM based supercomputer dedicated to AI research and open to researchers in the UK and the rest of the world. This is a big investment in the UK and will attract the world's best to come and work with us and advance the state of AI in industries such as healthcare, robotics and automation. We believe that the combined strengths in both companies will result in even better solutions for our partners, and we are very excited about the possibilities. I truly believe that there is an exciting future ahead for ARM as part of NVIDIA, where together we can create even greater impact. This is an exciting new phase for ARM, and we look forward to writing this next chapter together. Let me turn it over now to Colette, who will give you more details on the proposed transaction. Thanks, Simon. Today, we announced the proposed acquisition of Arnd from SoftBank in a cash and stock transaction valued at $40,000,000,000 We expect the acquisition to close in approximately 18 months, subject to regulatory approvals in various jurisdictions. The transaction has been approved by NVIDIA's, SoftBank's and ARM's Board of Directors. In addition to the strategic rationale Jensen outlined, we believe this is a financially compelling transaction. Upon closing, we expect to be immediately accretive to our non GAAP gross margins and non GAAP earnings per share. ARM has a great business model with very high margin reoccurring revenues. In the trailing 12 months ended March, unaudited pro form a IFRS revenue was 1,800,000,000 dollars with 94% gross margins and adjusted pro form a EBITDA margin of approximately 35%. Note, this does not include the IoT Services Group, which is not part of this transaction. Let me also touch on the transaction structure. NVIDIA will pay as consideration to SoftBank and the Vision Fund an aggregate of 21.5 $1,000,000,000 in common stock and $12,000,000,000 in cash, of which $2,000,000,000 of cash will be paid at the signing and the rest will be paid at closing. Additionally, NVIDIA will pay up to $5,000,000,000 in earn out of cash or stock based on ARM financial performance targets. NVIDIA will also issue $1,500,000,000 in equity to ARM employees for post closing retention. Based on these terms, SoftBank and SoftBank Vision Fund is expected to own in aggregate less than 10% of NVIDIA's stock, depending on the final amount of the earn out in the form of consideration elected by SoftBank, contributing to continuity going forward. NVIDIA intends to finance the cash portion of the transaction with balance sheet cash. Lastly, let me provide an update on our capital allocation strategy. We believe the proposal acquisition of ARM is an outstanding use of cash. We expect to continue to generate a substantial amount of cash in the 18 months that we expect to take for the transaction to close. We currently have $11,000,000,000 in cash and cash equivalents and marketable securities on the balance sheet. And over the last we generated $5,000,000,000 in free cash flow. Our business continues to grow to a robust pace and we are positive on our future. We expect to maintain an investment grade rating following this transaction and plan to continue our dividend. We will now open the call for questions. Operator, please hold for questions. Thank you. Thank you. Our first question comes from the line of Mark Lipacis from Jefferies. Your line is open. Hi, thanks for taking my question and congrats on the announcement. A question for Jen Hsun, I think. Jen Hsun, you've said that dominant compute platforms in the past have been general purpose platforms. And if you look at the data center 5 to 10 years from now, is your view that this is going to be multiple different general purpose compute platforms with a different platform to run parallel processing apps and a different one for serial or is this ultimately a single platform and that runs all the workloads and is that where NVIDIA plus ARM really ends up is that what's really driving core? Thank you. Yes. Thanks for the question. I appreciate that. A computing platform has to be programmable. A computing platform has to allow software developers to continue to advance and come up with creativity and run old software, run new software is architecturally compatible from generation to generation. That's a computing platform. A computing platform of the last generation, we know quite well the CPU ISA that has retained its ISA and its compatibility for generations. Going forward, you're going to see that computers because of the diverse workloads anymore and the type of application it runs like artificial intelligence require acceleration, but the architecture that's the most sensible that the industry is gathering around is a multi processor, multi type of processor, what is otherwise known as heterogeneous type of a computing architecture. The CPU is fantastic at low latency, single threaded, really, really, really predictable latency type of processing. The GPU is really fantastic at high throughput data processing. And the DPU is really good at network and serial data movements, security processing. These three types of processors will define the future of computing. It is exactly the reason why we're so excited about this acquisition that with ARM and NVIDIA and Mellanox, we have 3 computing platforms, 1 for networking, 1 for high throughput computing, accelerated computing and AI computing and one for CPUs and single threaded computing. These 3 are incredible platforms with large ecosystems, with industry support broad and wide and together we're going to be able to do great things together. Our next question comes from the line of Toshiya Hari from Goldman Sachs. Your line is open. Good morning and thank you so much for taking the question. Gentlemen, congratulations on the deal. I had a question on how you're thinking about the R and D trajectory at ARM post close and ARM's future prospects in the server CPU space. In terms of R and D, if I recall correctly, I think SoftBank more than doubled ARM's R and D budget post acquisition to accelerate innovation. But what are your plans from an R and D perspective, assuming the deal goes ahead? And in terms of server CPUs, what would you bring to the table that would turbocharge ARM's market share growth? And I ask the latter question because we've seen many companies in the past take a stab at ARM based server CPUs only to, for the most part, be unsuccessful? Thank you. Yes. Toshiya, you and I both know that we've seen the journey of ARM server CPUs over the last several years. And my enthusiasm is at a time when several things have changed. But let me first answer your question. There are 3 ways that we will turbocharge the R and D of our server CPU roadmap. The first is NVIDIA's R and D capacity, our R and D platform is much larger than arms. And just leveraging the capabilities we have, the existing capabilities we have, and recognizing that we have a lot of processor development ourselves even though it's not related related to ARM CPUs, a lot of the tools, a lot of the capabilities that we use to develop very high performance processors could be very easily tapped into. The second is the infrastructure that is required to turn a CPU core into a data center server platform. It includes the SoC, of course, the rest of system logic on the motherboard, the rest of the system including the GPU, the DPU, the system software, all of the algorithms on top, the various system stacks necessary for the various domain applications, whether it's virtualized environments or high performance computing environments or containerized orchestrated type of environments, microservices type of environments. Each one of those stacks is really, really rigorous. And we have the capabilities at NVIDIA within our already within our capabilities to bring all of that to arm. And so for the very first time, we'll be able to create a choice for the data center world that is absolutely world class, that is complete. The fully integrated, the fully developed and optimized stacks and as a result data centers whether it's in the cloud for whatever applications or in the enterprise or at the edge, can take advantage of this fully optimized stack. And then lastly, there are many things that we're developing, both of us that are developing in our future roadmaps that we can now harmonize. And so just the existing engineering we already have in our company, when we put them target The data center the cloud data centers have been waiting for The data center the cloud data centers have been waiting for the ability to pull all of this stuff together, the processors, the chips, the platforms, the software, until now it's not really been possible. And that's one of the reasons why it never succeeded. Building a chip alone is not sufficient anymore. The x86 ecosystem is not just about the chip, but it's about the whole platform solution that has been optimized over time. For us, we've been doing this and this is one of the great strengths of our company. We are a computing platform company that is able to innovate from the chips to the systems, system software all the way to the application stacks on top. And for all of the application the ARM CPUs readily. Now whether we build the the ARM CPUs readily. Now whether we build the ARM CPUs ourselves or not is relevant. We're delighted that Amazon is doing it, that other cloud CSPs have adopted, ARM is building data center CPUs. We're delighted to see Fujitsu use it for supercomputers And we're delighted to see NVIDIA's own BlueField use ARM CPUs to offload the data center operating system onto the SmartNIC. And we're seeing this all over the world. So data center processors of all different types and shapes are going to evolve and with our backing, with our combination, we're going to be able to really accelerate that. Thank you. Thanks, Toshi. Our next question comes from Vivek Arya from Bank of America Securities. Your line is open. Thanks for taking my question and congratulations to all on the announcement. Jensen, my question is on the regulatory and the ecosystem hurdles. So what kind of pushback do you see from regulators, especially in China, given all the trade tensions? And then separately, any pushback from arms customers, several of whom are your competitors today and they have unfettered access to ARM's technology. So what kind of hurdles do you foresee, right, from both that regulatory and ecosystem perspective? And if I could just quickly sneak in one question for Colette, the sense of cost and revenue synergies and any initial reviews would be very helpful. Thank you. The customers after they heard the rumors have reached out to Simon and he's spoken to a lot of customers. And the fact that we're announcing the deal tells you a little something that we believe that the customers are going to be satisfied with our genuine intention to keep the platform open and mutual. We bought the company and we paid, as you know, a very significant price because of the vast network and the vast ecosystem of ARM. We love the business model. And they reach customers that we can't reach. They reach industries we don't reach. NVIDIA sells something along the lines of call it 100,000,000 chips a year. Last year ARM sold in 22,000,000,000 chips. We believe all of those chips in the future are going to include AI computing. We believe all of those chips in the future will be accelerated computing. And we don't have to build all of them. We would love to extend our architecture to all of them. And so the economics of leveraging the core architecture and the core technology MD has already built through the ARM network and ecosystem and this incredible support system they've created over the last 30 years and the reputation for supporting IP that they've created, we're going to be able to take our technology through that. That is incredibly exciting to me. And so that the fact that we would like to offer, number 1, to keep the business model exactly as it was before, open and fair and in fact offer all of ARM's customers even more IP, I think is going to be very exciting. Regulatory, they're focused on pro competition, a condition that can ensure pro competition and pro customers, pro customer choice. We are going to bring customers more choice. We are going to, for the very first time, have a credible plan to turn the ARM CPU core into a full out data center platform. And the data center platform that's for clouds, for high performance computing, for edge, 5 gs edge data centers to enterprise data centers. For the very first time, we can visualize the ability to do that. Frankly, we've been building that out for every CPU, for every X86 CPUs, which are a little different, for power CPU. And last year, we decided we're going to do it for ARM CPUs. We realized what an incredible investment this is going to be. And we realized that this is going to generate a lot of value. And so we this combination really allows us to focus that energy and capture the value and deliver to the market a alternative platform that is going to be very powerful, very capable. And so the regulators love to see pro competitive competitive dynamics in the marketplace. And so we're pro customer, we're pro competition, the regulators should be very supportive of it. And let me see if I can address your question that you had regarding the synergies. When we looked at this business, remember, this is a piece of the overall ARM business as a whole. We have a high growth, high performing group coming on board here to NVIDIA. We have the opportunity to now expand in terms of our R and D across both to really attack a good portion of this opportunity that's in front of us. So at this time, it's a little bit early to talk about any of the synergies. But again, I think we're taking on already a very high growth, well performing group. Thank you. Our next question comes from the line of Aaron Rakers from Wells Fargo. Your line is open. Yes. Thanks for taking the question and also congratulations on the acquisition. I wanted to go a little bit deeper in response to this last question. In your presentation, you highlight offering ARM customers access to NVIDIA's AI and GPU IP. Jensen, I'm just curious of how you see that evolving, how deeply you will go in terms of providing customers with licensable GPU IP? And how do you think about the NVIDIA business model evolving with this acquisition? We're in no mobile devices. NVIDIA builds very few SoCs. We are in very few embedded systems. And the numbers describe it perfectly. ARM sold 22,000,000,000 chips last year, 22,000,000,000 chips. NVIDIA is in the 100,000,000 chips space. The opportunity that the unserved market is nearly all 22,000,000,000 dollars And so that kind of tells you something about the opportunity that we see here. And yet all of those devices, I believe AI is going to define the way that software is going to get written and AI processing will be done in every computer in every device. And those 22,000,000,000 chips are going to be AI computing chips and they're going to do amazing things. And those are all those are all those are all those are all those are all those are all those are all those are all those are all And those are all wonderful platforms that we would like to go and participate in, but we can't build them on. And so the simple way that we're thinking about it is, wouldn't it be great if NVIDIA IP, NVIDIA GPU cores and AI cores were made available through that network and customers could take advantage of it. It's really quite as elegant as that. We can't do this. This idea that it sounds so simple and elegant, but it really is impossible if not for the incredible reach of ARM and the network of support and the reputation and the engineering operations of turning technology into IP reusable blocks, all of that is what we're buying into. This incredibly energy efficient processor combined with the business model combined with the vast ecosystem there. You could imagine some simple math and the there. You could imagine some simple math and the economics could be really exciting. Thank you. And our next question comes from the line of C. J. Muse from Evercore. Your line is open. Yes. Good morning. Good afternoon. Thanks for taking the question. I guess 2 if I could. The first one, Jensen, we've talked in the past about the difficulty of bringing CUDA to the edge for low cost type solutions. So curious, how are you thinking about with the combination of ARM unifying your solution, your Creditor software from the data center to the edge? So that's the first question. Then the second is, I guess, more on the regulatory side with China. You're keeping the IP in the UK, so I think that's a good start. But curious, how you're thinking about their reaction? Would you grant an evergreen license to China to get approval? Any thoughts there would be great. Thank you. Yes. One of the things C. J. That we all know is that Moore's Laws come to an end. And there are several things that we know about those 22,000,000,000 chips that are going to get sold and eventually a trillion chips that are going to get sold. The journey to our trillion chips is through AI. And AI is an accelerated computing method of processing. And so in order for us to go from 22,000,000,000 units a year to a lot more than that and having trillions of devices that are around the world that are operating AI software and operating autonomously. That computer architecture, the computing platform has to evolve. The ARM CPU is so energy efficient and the NVIDIA GPU is so energy efficient that we could increase the adoption of accelerated computing and ad computing in those 22,000,000,000 units moving to 100 of billions of units over years just through the course of time. And we can now build very 100 milliwatts and that fits into a very large number of computing devices. And so I think it's a foregone conclusion that computing is going to be accelerated, that computing will most computing platforms will be about AI processing and we're as the world leader in AI computing and ARM the most popular CPU and the largest ecosystem in the world, we should be able to connect these two things together and provide the AI processors and our AI architecture, accelerated computing architecture to all of the ARM partners. And so I'm excited about that part. With respect to China, the important thing to realize is that the ownership, the company ownership of the IP is not the relevant issue. The origin of the IP is the relevant factor in export control. The IP of ARM was originated, created, developed over 3 decades in Cambridge. And so the amount of soft the amount of code, the amount of innovation is measured in thousands of human years. And so the IP will essentially stay in the UK. The headquarters of ARM will be in the UK. We're going to continue to advance the technology in the UK. In Cambridge is a pool, is a company of some of the finest computer scientists in the world. And so, course, we're going to continue to invest there and build there. And so the origin of the technology won't change. And as a result, the fact that ARM now belongs to an American company versus a Japanese company, that doesn't change exports control in any way. Our next question comes from the line of Stacy Rasgon from Bernstein Research. Your line is open. Hi, guys. Thanks for taking my question. I wanted to come back to the customer acceptance of this. I hear what you're saying around keeping the ecosystem neutral. I hear what you're saying about the potential value that customers will have. But at the same time, how does this really work in practice? I mean, it's a practical consideration that you're going to get first look at everything. You're going to control the direction of innovation of the company. You're going to know all of your customers' roadmaps before they do. So how are they really going to get comfortable with this, especially in some of these like high performance computing and server? And I sort of asked this within the envelope of maybe some of your prior efforts to drive an IP licensing business, which to my recollection did not go all that well and was not really accepting all the welcome customers. So just in general, given all of that and how much you're going to own of this ecosystem, how much visibility you'll have into what they're doing, like how are they how are you really going to get them comfortable with this? And do you anticipate any issues? And if there are customer disagreements, would that stand in the way of closing the deal? We would protect the confidentiality information of all of our customers the way we do today and the way that ARM does today. Neither of us really know what the customers are doing with our technology. And so and of course we have we work with every company in the world and so does ARM work with every computer company in the world. We keep all of we keep everybody's confidentiality protected for all of the obvious reasons. I mean we are a computing platform company. NVIDIA sells chips to all of the computer makers. We also license software to them today that runs in their data centers or are doing optimizing compilers or all of our CUDA CUDA DNN, all of the AI optimization libraries are licensed to all of our partners. And then of course, we provide application stacks even on top of that. We work in 3 layers. Our company has evolved far from the chip company years ago. We offer technology, which is at the chip level, but we offer platform technology, which includes a lot of software, a lot of SDKs. And then in some cases, we even offered the entire applications back on top. We open up this 3 layer approach of accessing NVIDIA's platform and the customers decide whether they want to use Layer 1, Layer 2 or Layer 3. If a customer would like to partner with us, for example, one of the telcos who want to partner with us to bring GeForce Now to the market, we partner with them. If somebody would like to only buy our GPU and develop the entire stack themselves for their own cloud gaming service, we're more than happy to do that. And they're willing to use if they would like to use Layer 1 and Layer 2 and then build on top of it themselves for their Layer 3 service or store, we're more than delighted to do that. We do that in gaming. We do that in autonomous vehicles. We do that in robotics. And in the case of ARM, this will just be our layer 1 technology offering, meaning that in the case that a customer would like to have our technology already fixed and hardened in a chip, that's fine. But if they would like to have it be soft and malleable, that's fine too. I think that the business model, the modern business model, this is just not as odd as it seems. We go to the cloud and we have infrastructure as a service, platform as a service, software as a service. And the platforms make themselves available to you however you would like to be like you to engage it. I think fundamentally NVIDIA is of course going to continue to protect our most important thing, which is our enterprise reputation that we have to be a company that customers and our partners can trust. We are the only AI company in the world that I know of that work with every AI company in the world. And maintaining that trust of openness and fairness and protection of people's privacy and confidentiality, that's something that is pretty sacred to us and we're going to continue to do that. And so we decided that this business model was something that we want to bring to make part of an extension of our company that we think it's great for our business, it's great for economics, that it's great for our strategy, and that it's going to be a pillar for extending our computing platform. If we believe that, as I do, and we make a commitment to keep it open, we will. Got it. Thank you. If I could ask one quick housekeeping question of Colette. You said adjusted EBITDA margins at 35%. SoftBank's own recent presentation suggests EBITDA margins below 15%. Is the differential just the removal of the IT services business? Is it stock comp? Just what's driving that differential? That's correct, Stacy. As we discussed, we are just buying the IPG Group and leaving the IoT data science group on that. So that is the most of the difference between the 2. Got it. Thank you very much guys. Good luck. Thank you. Our next question comes from the line of Harlan Sur from JPMorgan. Maybe to follow-up on that last question, ARM has built its business model around customer neutrality by not competing with its semiconductor customers. Maybe we can take Jensen specific examples. In the areas of embedded with your Jetson platform, automotive with Drive AGX, gaming with your ASIC solutions, networking with BlueField processors, where you guys design your own multi core ARM based processor chips, here you actually will be competing with your customers. So how again do you address ARM's customer neutrality philosophy in these particular areas? By doing just that, keeping staying neutral. Remember, we work with all of the companies that are in the semiconductor industry. We work very closely with Intel. We work very closely with A and D. We selected AMD in our latest generation DGX. And we were delighted by it. We celebrated it. And the 2 engineering teams worked incredibly close together. People say that NVIDIA's primary competitor in AI computing is the TPU. And yet on the first day of the Ampere launch, the only customer that stood there with us was the first customer that launched was Google. And so there's a I think that there's a maturity about the technology industry that it is possible to collaborate largely and in some areas where you compete. We work so closely with all the semiconductor companies. We buy from them. Our systems are only possible because our chips and their chips, we don't build every chip, we don't build voltage regulators, we don't build a lot of repeaters, we don't build a lot of SERDES, a lot of very complicated things that are inside these systems and we don't build them and we rely on core partners to do so. And we are grateful for their partnership. They support us with excellent engineering. And we will do so in return. But mostly the important thing to realize is whatever business model you decide you want to endeavor, you've got to believe in it and you've got to be committed to it. And this business model, we are committed to the open computing business model. NVIDIA is an open computing company. On the one hand, we build systems, but on the other hand, we completely open the insides of it so that people could use our components, whether it's at the platform level, at the system component level, all the way down to the chip level and all the software in between. We make it possible for you to use whatever you decide to use. In the self driving car world, notice on the one hand in our Mercedes business model, we are developing the entire stack, even creating the data center and operating the fleet for as long as we shall live for the 10,000,000, 20,000,000 Mercedes cars that are going to be out there, we're going to operate them, offer services and software to it. Meanwhile, we're selling chips to Tier 1s and OEMs around the world and startups around the world who are building their software stack on top of our chips. And sometimes they many times they offer to the same end customers. We're delighted by that. We're delighted by that. We can't win everything in the world. But the one thing that we believe to be foundational to everything we do is that the more people use our computing platform, the more developers are developing on our computing platform, the more resilient, the more sustainable, the more contribution we can make and the more opportunities it will find for us. That we believe to be foundational. And so I will all day long be more than joyed for somebody to not buy our system, but buy our chip, to not buy our chip, but to license our IP. I'd be more than joyed for that. It's a win for us no matter what. Okay. So I think the business model is something we love very much. I just got to you got to see that math. NVIDIA sells 100,000,000 chips a year. There are 21,900,000,000 chip opportunity for us to go. And we believe they're all going to be accelerated. Moore's Law has ended. We believe AI computing is going to be on all of them. Of course it is. Of course it is. And so considering those facts, the opportunity to use this business model that has taken 3 decades to build, of course, we're going to honor it. Of course, we love it. And of course, we're going to use it to continue to extend our platform. It's wonderful for us. Our next question comes from the line of Matt Ramsay from Cowen. Your line is open. Thank you very much. Congrats all around. Actually, I have a question that I wanted to ask from to both Jensen and to Simon from your own perspectives. Obviously, NVIDIA has been an influential member of the ARM partnership. You guys have license for essentially all of ARM's core technology plus an architectural license for V8 and I'm sure V9 as it comes out. So I guess, Simpson, the question that I've been getting folks is why buy the whole company, right? What things are you looking forward to in close collaboration of CPU and in the data center or putting your IP on client and edge devices could you not have accomplished by just being an influential member of the ARM partnership and doing your own architectural license implementation of chips? And I guess, Simon, from the opposite perspective, what things are you now going to be able to do with NVIDIA's influence that you might not have done under the more traditional ARM relationship with partners? Thanks. Yes, really good question, really excellent question. I'm glad you asked it. The why didn't we just kept our license? We were delightful licensees of ARM. As you know, we use ARM in our one of our most important new initiatives and very exciting and something I want to tell you guys a lot more about the BlueField DPU. We use it for the Nintendo Switch. It's going to be the most popular, the most successful game console in the history of game consoles. And so we are enthusiastic ARM licensees. There are three reasons why we that we should buy this company and we should buy it as soon as we can. And the reason for that, number 1 is this. As you know, we would love to take NVIDIA's IP through ARM's network. Unless we were one company, I think the ability for us to do that and to do that with all of our might is very challenging. So I don't take other people's products through my channel. I don't expose my ecosystem to other companies' products. The ecosystem is hard earned. It took 30 years for them to get here. And so we have an opportunity to offer that whole network, that vast ecosystem of partners and customers NVIDIA's IP, number 1. And so you could do some simple math and try to decide the scale of your imagination, but the economics there should be very, very exciting. Number 2, we would like to lean in very hard into the ARM CPU data center platform. There's a fundamental difference between a data center CPU core and a data center CPU chip and a data center CPU platform, a data center computing platform. We last year decided that we would adopt and support the ARM architecture for the full NVIDIA stack and that was a giant commitment. The day we decided to do that, we realized this is going to be for as long as we shall live. And the reason for that is because once you start supporting the ecosystem, you can't back out. And for all the same reasons, when you're a computing platform company and people depend on you, you have to support them for as long as you shall live and we do. And we take that promise very seriously. And so we are about to put the entire mind of our company behind this architecture. From the CPU core to the CPU chips from all of these different customers, all these different partners, Ampere or Marvell or Amazon or Fujitsu or the number of companies out there that are considering building ARM CPUs out of the ARM CPU cores, data center CPU cores is really quite exciting. The investments that Simon and the team have made in the last 4 years, while they were out of the public market has proven to be incredibly valuable. And now we want to lean hard into that and make ARM a 1st class data center platform, a 1st class data center platform from the chips to the GPUs to the DPUs to the software stack to the system stack to all the application stacks on top, we want to make it a full out 1st class data center platform. Well, before we do that, it would be great to own it. We're going to accrue so much value to this architecture in the world of data center before we go and make that gigantic investment and gigantic focus, why don't we own it? And so that's the second reason. 3rd reason, we want to go invent the future of cloud to edge, The future of computing where all these autonomous systems are powered by AI and powered by accelerated computing and all the things that we've been talking about, that future has been invented as we speak. And there are so many great opportunities there. Edge data centers, 5 gs edge data centers, autonomous machines of all sizes and shapes, autonomous factories. We NVIDIA has built a lot of software as you guys have seen Metropolis, Clara, Isaac, Drive, Jarvis, Ariel, all of these platforms are built on top of ARM. All of these platforms are built on top of ARM. And before we go and see the inflection point, wouldn't it be great if we were 1 company? And so the timing is really quite important. I think we've invested so much in all across all of these different areas that we felt that we really, really haven't taken the opportunity to own the company and collaborate deeply as we invent the future, okay? So that's the answer. So from my side, if I can follow-up on that, if I can follow that. The way I look at it is through a couple of different dimensions. Firstly, just picking up on the point about AI. I do truly believe that AI is going to be the defining technology of compute for the future. And we've made great progress on that. We've made great strides in thinking about AI at the edge, AI running on the tiniest microcontrollers and how you enable that, how you do that in an energy efficient way, how you get the software stack going. But we are just to be the starting point on this transition to the world of compute being the world of AI. And we think that by combining forces, there's just so much more resource and weight that we can put into that and that this gives us an opportunity to take a lead in a way that we couldn't have done on our own. Similarly, when we think about the data center, the data center has been one of the big bets that we've made over the last 4 years under SoftBank's ownership. We just couldn't have done that as a public company, and Matt, you and I have discussed that a number of times over the years. But the increase in R and D that we've done over the last 4 years has enabled us to get to a very different place, and we can now go further. We can now take that to the next level by applying the might of NVIDIA behind it. Now tactically, as we think about NVIDIA's IP portfolio and how we might package that up into products that we can license to the rest of our customer base, that gives us more to go and sell. That's great. And we're going to do that. But it is these kind of big systemic changes that are going on, these big strategic threads where the combination of the 2 companies, I think, puts us in a very unique and really exciting position. Thanks very much to you both. Thanks. And our final question today will come from the line of John Pitzer from Credit Suisse. Your line is open. Yes, good morning. Congratulations, Jensen and Simon. Appreciate you letting me ask the last question. Justin, when you kind of look at the success you've had in the data center, I think one of the key pillars has been your ability to lower the cost of compute for your customer, well summed up in what you always say, the more you buy, the more you save. When you look at the Mellanox acquisition, it's fairly easy to see how that fits into that prism of lowering the cost of computing the data center. I'm just wondering if you could help me understand how I should view the ARM acquisition through that lens? And then as a quick housekeeping for Colette. Colette, the $2,000,000,000 that you are giving to SoftBank at signing, is that effectively a breakup fee that has non recourse? And is that only breakup fee or how do I think about a potential breakup fee here if the regulators don't see the world the way you see it? As you know, ARM is the most energy efficient architecture in the world. It's the most energy efficient computer architecture in the world. And computer energy efficiency in a power limited data center, which is always power limited, whatever size data center you see, there's a limit to the power that it provisions. The more data the more energy efficiency, the greater number of processors you could fit inside. The greater number of processors, of course, you could fit inside, the more throughput or the more customers you could serve. So whether you want to think about it as in dollars per compute or the dollars you can make per compute with your data center, either way, the ARM energy efficiency is extraordinary. That is exactly the reason why Amazon is so excited about Graviton 1 and Graviton 2. You're going to see many others that want to follow suit. And so the energy efficiency of the ARM processors has really, really revealed its amazing cost benefits in the world of data centers. And now with the workload, and this is a very important thing, a very important dynamic. And I think it was Toshiba that mentioned it earlier about the previous history of why ARM CPUs weren't that successful in data centers has fundamentally changed. It used to be that data centers was hyperconverged and the workload was monolithic virtualized, monolithic virtualized in a hyperconverged environment. In that world, used a lot of buzzwords and I'm sorry about that, but in that world, the right architecture is x86. It runs all of the applications in the world. But since then, the world has become disaggregated containerized micro services. That is the way that these data centers are built today. Because of that migration, because of that evolution, applications have been refactored. The applications have been refactored and AI has been infused into it. It is now possible to run on any CPUs. It just has to be very energy efficient, it has to be performant. And most importantly, very importantly, it has to be supported by all of the computing infrastructure around it. The value of the X86 CPU and data centers is not just the core itself, but it's the core, it's the hardware ecosystem. All of the system components that support it, all of the software services that run on top of it, it's all fully optimized. NVIDIA has that stack. We have the networking storage security virtualization stack as a result of Mellanox. We have NVIDIA's AI stack and computing stack, whether it's Kubernetes based or virtualized based or cluster based and multi GPU based, multi node based. No matter what the computing infrastructure environment is, NVIDIA has that stack now. We're going to bring all of it to ARM. We're going to bring all of it to this new ecosystem. And I think our ability to expand the market is going to be greatly enhanced. So let me just quickly answer that last question regarding the breakup fee. The $2,000,000,000 that is paid at signing as essentially a down payment towards the $12,000,000,000 of cash that is owed. Yes, that is all that is a breakup fee. But keep in mind, there's also an ARM license within that as well. So it's not all breakup fee and no, there's no other breakup fees. Perfect. Thanks guys. Very helpful. Thank you, everyone, for today's conference call. You may now disconnect. Okay, you guys. Thank you very much for joining us today. Today's announcement was super exciting. I hope you're as excited as I am. The combining of 2 amazing companies, the most popular CPU in the world with the world's leading AI computing company so that we can create the premier computing company for the age of AI. I look forward to giving you guys updates on an ongoing basis. Thanks for joining us today.