NVIDIA Corporation reported strong fiscal Q1 2025 earnings, surpassing both earnings per share (EPS) and revenue expectations. The company posted an EPS of $0.96, exceeding the forecast of $0.93, and achieved revenue of $44.1 billion against a projected $43.31 billion. Following the announcement, NVIDIA’s stock rose by 4.29% in aftermarket trading, reflecting investor confidence in its growth trajectory.
Key Takeaways
Today, however, the $50,000,000,000 China market is effectively closed to US industry. The h twenty export ban ended our Hopper data center business in China. We cannot reduce Hopper further to comply. As a result, we are taking a multibillion dollar write off on inventory that cannot be sold or repurposed. We are exploring limited ways to compete, but Hopper is no longer an option.
China’s AI moves on with or without US chips. It has to compute to train and deploy advanced models. The question is not whether China will have AI. It already does. The question is whether one of the world’s largest AI markets will run on American platforms.
Shielding Chinese chipmakers from US competition only strengthens them abroad and weakens America’s position. Export restrictions have spurred China’s innovation and scale. The AI race is not just about chips. It’s about which stack the world runs on. As that stack grows to include six g and quantum, US global infrastructure leadership is at stake.
The US has based its policy on the assumption that China cannot make AI chips. That assumption was always questionable, and now it’s clearly wrong. China has enormous manufacturing capability. In the end, the platform that wins the AI developers win AI wins AI. Export controls should strengthen US platforms, not drive half of the world’s AI talent to rivals.
On DeepSeek. DeepSeek and QN from China are among the most among the best open source AI models. Released freely, they’ve gained traction across The US, Europe, and beyond. DeepSeek r one, like ChatGPT, introduced reasoning AI that produces better answers the longer it thinks. Reasoning AI enables step by step problem solving, planning, and tool use, turning models into intelligent agents.
Reasoning is compute intensive, requires hundreds to thousands more thousands of times more tokens per task than previous one shot inference. Reasoning models are driving a step function surge in inference demand. AI scaling laws remain firmly intact, not only for training, but now inference too requires massive scale compute. DeepSeq also underscores the strategic value of open source AI. When popular models are trained and optimized on US platforms, it drives usage, feedback, and continuous improvement, reinforcing American leadership across the stack.
US platforms must must remain the preferred platform for open source AI. That means supporting collaboration with top developers globally, including in China. America wins when models like DeepSeek and QN runs best on American infrastructure. Regarding onshore manufacturing, president Trump has outlined a bold vision to reshore advanced manufacturing, create jobs, and strengthen national security. Future plants will be highly computerized in robotics.
We share this vision. TSMC is building six fabs and two advanced packaging plants in Arizona to make chips for NVIDIA. Process qualification is underway with volume production expected by year end. Spill and Amcor are also investing in Arizona, constructing packaging, assembly, and test facilities. In Houston, we’re partnering with Foxconn to construct a million square foot factory to build AI supercomputers.
Wistron is building a similar plant in Fort Worth, Texas. To encourage and support these investments, we’ve made substantial long term purchase commitments, a deep investment in America’s AI manufacturing future. Our goal from chip to supercomputer built in America within a year. Each g b 200 MB LINK 72 racks contains 1,200,000 components and weighs nearly two tons. No one has produced supercomputers on this scale.
Our partners are doing an extraordinary job. On AI diffusion rule, president Trump rescinded the AI diffusion rule, calling it counterproductive, and proposed a new policy to promote US AI tech with trusted partners. On his Middle East tour, he announced historic investments. I was honored to join him in announcing a 500 megawatt AI infrastructure project in Saudi Arabia and a five gigawatt AI campus in The UAE. President Trump wants US tech to lead.
The deals he announced are wins for America, creating jobs, advancing infrastructure, generating tax revenue, and reducing The US trade deficit. The US will always be NVIDIA’s largest market and home to the largest installed base of our infrastructure. Every nation now sees AI as core to the next industrial revolution, a new industry that produces intelligence and essential infrastructure for every economy. Countries are racing to build national AI platforms to elevate their digital capabilities. At Computex, we announced Taiwan’s First AI factory in partnership with Foxconn and the Taiwan government.
Last week, I was in Sweden to launch its first national AI infrastructure. Japan, Korea, India, Canada, France, The UK, Germany, Italy, Spain, and more are now building national AI factories to empower startups, industries, and societies. Sovereign AI is a new growth engine for NVIDIA. Toshiya, back to you. Thank you
Jensen Huang, President and Chief Executive Officer, NVIDIA: In fact, the the the probably the best way to think through it is that AI is several things. You know? Of course, we know that AI is this incredible technology that’s going to transform, every industry, you know, from, of course, the way we do software to to, health care and financial services to, you know, retail to to, I guess, every industry, transportation, manufacturing. And and we’re at the beginning of that. But maybe maybe another way to think about that is is where do we need intelligence?
Where do we need digital intelligence? And and it’s in every country. It’s in every industry. And we know we know because of that, we recognize that AI is also an infrastructure. It’s a it’s a way of developing a techno delivering a technology that requires factories.
And these factories produce tokens, and they, as I mentioned, are important to every single industry in every single country. And so on that basis, we’re really at the very beginning of it because the adoption of this technology is really kind of in its early early stages. Now we’ve reached an extraordinary milestone with AIs that are reasoning, are thinking, what people call inference time scaling. You know, of course, it created a a whole new we’ve entered an era where where inference is going to be a significant part of the compute workload. But any anyhow, you’re it’s gonna be a new infrastructure, and we’re building it out in the cloud.
The United States is is really the the the early starter and, available in US clouds. And this is our largest market, our largest installed base, and we can continue to see that happening. But beyond that, we’re gonna have to we’re gonna see AI go into enterprise, which is on prem because so much of the data is still on prem. Access control is really important. It’s really hard to to move all of every company’s data into the cloud, and so we’re gonna move AI into the enterprise.
And you you saw that we announced a couple of really exciting new products. Our RTX Pro enterprise AI server that runs everything enterprise and AI, our our DGX Spark and DGX Station, which is designed for developers who wanna work on prem. And so enterprise AI is is just taking off. Telcos. Today, a lot of the telco infrastructure will be in the future software defined and built on AI.
And so six g is gonna be built on AI, and that infrastructure needs to be built out. And as I said, it’s very, very early stages. And then, of course, every factory today that makes things will have an AI factory that sits with it. And, the AI factory is going to be drive creating AI and and operating AI for the factory itself, but also to power the products and the things that are made by the factory. So it’s very clear that every car company will have AI factories, and, very soon, there’ll be robotics companies, robot companies, and those companies will be, also building AIs to, drive the robots.
And so we’re at the beginning of all of this build out.
Jensen Huang, President and Chief Executive Officer, NVIDIA: Well, we have more orders today than we did at the at the last time I spoke about orders at GTC. However, we’re also increasing our supply chain and building out our supply chain. They’re doing a fantastic job. We’re building it here onshore in United States, but we’re gonna keep our supply chain, quite busy for several many more years coming. And, with respect to with respect to further announcements, I’m gonna be on the road next week through Europe.
And, it’s it’s, just about every country needs to build out AI infrastructure, and their they’re, team AI factories, being planned. We’re I think I think, in the remarks, Colette mentioned there’s some a a hundred AI factories being built. There’s a whole bunch that haven’t been announced. And I think the important concept here, which makes it makes it, you know, easier to understand, is that like like other technologies that impact literally every single industry, of course, electricity was one, and it became infrastructure. Of course, the information infrastructure, which which we now know as the Internet, affects every single industry, every country, every society.
Intelligence is surely one of those things. I don’t know any company, industry, country who who thinks that intelligence is optional. It’s essential infrastructure. And so we’ve now digitalized intelligence. And and so I I think we’re we’re clearly in the beginning of a of the the build out of this infrastructure, and every every country will have it.
I’m certain of that. Every industry will use it. That, I’m certain of. And what’s unique about this infrastructure is that it needs factories. You know, it’s a little bit like like the like the energy infrastructure, electricity.
It needs factories. We need factories to produce this intelligence, and the intelligence is getting more sophisticated. We were talking about earlier that we had a huge breakthrough in the last couple of years with reasoning AI, and and now there are agents that reason. And there’s super agents that use a whole bunch of tools, and then there’s clusters of super agents where agents are working with agents, solving problems. And so you could just imagine compared to one shot chatbots and the agents that are now using AI built on these large language models, how much more compute intensive they they really need to be and are.
And so so I I think we’re in the beginning of the build out, and there there should be there should be many, many more announcements in the future.
Jensen Huang, President and Chief Executive Officer, NVIDIA: do this. Thanks. Thanks, Ben. I would say compared to the beginning of the year, compared to GTC time frame, there are four positive surprises. The first positive surprise is the step function demand increase of reasoning AI.
I think it is fairly clear now that AI is going through an exponential growth, and reasoning AI really busted through. Concerns about about hallucination or its ability to to really solve problems. And I think I think a lot of people are are crossing that barrier and realizing how incredible incredibly effective agentic AI is and reasoning AI is. So number one is inference reasoning, alright, and, the the exponential growth there, demand growth. The second one, you you mentioned AI diffusion.
It it’s really terrific to see, that the AI diffusion rule was rescinded. President Trump wants America to win, and and, he also realizes that that, we’re not the only, country in the race, and, he wants he wants, United States to win and recognizes that we have to get the American stack out to the world and have the world build on top of American stacks, instead of alternatives. And so, AI diffusion, hap happened. The res the rescinding of it happened at almost precisely the time that the countries around the world are awakening the importance of AI as an infrastructure, not just as a technology of great curiosity, and great importance, but infrastructure for their industries and startups and society. Just as they had to build out infrastructure for electricity and Internet, you gotta build out infrastructure for AI.
I think that that’s an awakening, and that creates a lot of opportunity. The third is enterprise AI. Agents work, and agents are doing these agents are really quite successful. Much more than generative AI, agentic AI is game changing. You they you know, agents can understand ambiguous and rather rather implicit instructions and able to problem solve and use tools and have memory and and so on.
And and so I think this is enterprise AI is ready ready to take off, and and it’s taken us a few years to build a computing system that that is able to integrate, run run enterprise AI stacks, run enterprise IT stacks, but add AI to it. And this is the, RTX Pro enterprise server that we announced at Computex, just last week. And just about every major IT company has joined us, and I’m super excited about that. And so computing is one stat one part of it. But remember, enterprise IT is really three three pillars.
It’s compute, storage, and networking, and we’ve now put all three of them together for finally, and we’re going to market with that. And then lastly, industrial AI. Remember, one of the implications of of the the the world reordering, if you will, is is, regions onshoring manufacturing and building plants everywhere. In addition to AI factories, of course, there there are new electronics manufacturing, chip manufacturing, being built around the world. And all of these new plants and these new factories are creating exactly the right time when when Omniverse and AI and all the work that we’re doing we’re doing with robotics is is emerging.
And so so this this fourth pillar is is quite important. Every factory will have an AI factory associated with it. And and in order to create these physical AI systems, you really have to train a a vast amount of data. So so back to more data, more training, more AIs to be created, more computers. And so, these four these four drivers are are really kicking into turbocharge.
Jensen Huang, President and Chief Executive Officer, NVIDIA: The the president has a plan. He has a vision, and I trust him. With respect to with respect to our export controls, it’s a it’s a set of limits, and the new set of limits pretty pretty much make it impossible for us to to reduce Hopper any further, you know, for for any productive use. And and so the new limits the new limits, you know, it’s kind of the end of the road for Hopper. We have some we have limited options, and and and so we just the the key is to to understand the limits.
The key is to understand the limits and see if we can come up with with, with interesting products that could that could continue to serve the Chinese market. We we don’t have anything at the moment, and, but we’re we’re considering it. We’re thinking about it. Obviously, the limits are are quite stringent at the moment, and, we we have nothing to announce today. And and when the time comes, you know, we’ll we’ll, we’ll, engage the administration and discuss that.
Jensen Huang, President and Chief Executive Officer, NVIDIA: Thank you. This is the start of a powerful new wave of of growth. Grace Blackwell is in full production. We’re off to the races. We now have multiple significant growth engines.
Inference, once the lighter workload is surging with revenue generating AI services. AI is growing faster and will be larger than any platform shifts before, including the Internet, mobile, and cloud. Blackwell is built to power the full AI life cycle from training frontier models to running complex inference and reasoning agents at scale. Training demands continues to rise with breakthroughs in post training and like reinforcement learning and synthetic data generation, but inference is exploding. Reasoning AI agents require orders of magnitude more compute.
The foundations of our next growth platforms are in place and ready to scale. Sovereign AI, nations are investing in AI infrastructure like they once did for electricity and Internet. Enterprise AI AI must be deployable on prem and integrated with existing IT. Our RTX Pro, DGX Spark, and DGX Station enterprise AI systems are ready to modernize the $500,000,000,000 IT infrastructure on prem or in the cloud. Every major IT provider is partnering with us.
Industrial AI from training to digital twin simulation to deployment, NVIDIA Omniverse and Isaac Groot are powering next generation factories and humanoid robotic systems worldwide. The age of AI is here from AI infrastructures, inference at scale, sovereign AI, enterprise AI, and industrial AI. NVIDIA is ready. Join us at GTC Paris. I’ll keynote at Viva Tech on June 11 talking about quantum GPU computing, robotic factories and robots, and celebrate our partnerships building AI factories across the region.
The NVIDIA band will tour France, The UK, Germany, and Belgium. Thank you for joining us, at the earnings call today. See you in Paris.
Key Takeaways
- NVIDIA’s Q1 2025 EPS of $0.96 beat the forecast of $0.93.
- Revenue reached $44.1 billion, surpassing the $43.31 billion forecast.
- Stock surged 4.29% in aftermarket trading, closing at $140.59.
- Data center revenue saw a significant increase of 73% year-on-year.
- The company launched several innovative products, including the Blackwell architecture.
Today, however, the $50,000,000,000 China market is effectively closed to US industry. The h twenty export ban ended our Hopper data center business in China. We cannot reduce Hopper further to comply. As a result, we are taking a multibillion dollar write off on inventory that cannot be sold or repurposed. We are exploring limited ways to compete, but Hopper is no longer an option.
China’s AI moves on with or without US chips. It has to compute to train and deploy advanced models. The question is not whether China will have AI. It already does. The question is whether one of the world’s largest AI markets will run on American platforms.
Shielding Chinese chipmakers from US competition only strengthens them abroad and weakens America’s position. Export restrictions have spurred China’s innovation and scale. The AI race is not just about chips. It’s about which stack the world runs on. As that stack grows to include six g and quantum, US global infrastructure leadership is at stake.
The US has based its policy on the assumption that China cannot make AI chips. That assumption was always questionable, and now it’s clearly wrong. China has enormous manufacturing capability. In the end, the platform that wins the AI developers win AI wins AI. Export controls should strengthen US platforms, not drive half of the world’s AI talent to rivals.
On DeepSeek. DeepSeek and QN from China are among the most among the best open source AI models. Released freely, they’ve gained traction across The US, Europe, and beyond. DeepSeek r one, like ChatGPT, introduced reasoning AI that produces better answers the longer it thinks. Reasoning AI enables step by step problem solving, planning, and tool use, turning models into intelligent agents.
Reasoning is compute intensive, requires hundreds to thousands more thousands of times more tokens per task than previous one shot inference. Reasoning models are driving a step function surge in inference demand. AI scaling laws remain firmly intact, not only for training, but now inference too requires massive scale compute. DeepSeq also underscores the strategic value of open source AI. When popular models are trained and optimized on US platforms, it drives usage, feedback, and continuous improvement, reinforcing American leadership across the stack.
US platforms must must remain the preferred platform for open source AI. That means supporting collaboration with top developers globally, including in China. America wins when models like DeepSeek and QN runs best on American infrastructure. Regarding onshore manufacturing, president Trump has outlined a bold vision to reshore advanced manufacturing, create jobs, and strengthen national security. Future plants will be highly computerized in robotics.
We share this vision. TSMC is building six fabs and two advanced packaging plants in Arizona to make chips for NVIDIA. Process qualification is underway with volume production expected by year end. Spill and Amcor are also investing in Arizona, constructing packaging, assembly, and test facilities. In Houston, we’re partnering with Foxconn to construct a million square foot factory to build AI supercomputers.
Wistron is building a similar plant in Fort Worth, Texas. To encourage and support these investments, we’ve made substantial long term purchase commitments, a deep investment in America’s AI manufacturing future. Our goal from chip to supercomputer built in America within a year. Each g b 200 MB LINK 72 racks contains 1,200,000 components and weighs nearly two tons. No one has produced supercomputers on this scale.
Our partners are doing an extraordinary job. On AI diffusion rule, president Trump rescinded the AI diffusion rule, calling it counterproductive, and proposed a new policy to promote US AI tech with trusted partners. On his Middle East tour, he announced historic investments. I was honored to join him in announcing a 500 megawatt AI infrastructure project in Saudi Arabia and a five gigawatt AI campus in The UAE. President Trump wants US tech to lead.
The deals he announced are wins for America, creating jobs, advancing infrastructure, generating tax revenue, and reducing The US trade deficit. The US will always be NVIDIA’s largest market and home to the largest installed base of our infrastructure. Every nation now sees AI as core to the next industrial revolution, a new industry that produces intelligence and essential infrastructure for every economy. Countries are racing to build national AI platforms to elevate their digital capabilities. At Computex, we announced Taiwan’s First AI factory in partnership with Foxconn and the Taiwan government.
Last week, I was in Sweden to launch its first national AI infrastructure. Japan, Korea, India, Canada, France, The UK, Germany, Italy, Spain, and more are now building national AI factories to empower startups, industries, and societies. Sovereign AI is a new growth engine for NVIDIA. Toshiya, back to you. Thank you
Jensen Huang, President and Chief Executive Officer, NVIDIA: In fact, the the the probably the best way to think through it is that AI is several things. You know? Of course, we know that AI is this incredible technology that’s going to transform, every industry, you know, from, of course, the way we do software to to, health care and financial services to, you know, retail to to, I guess, every industry, transportation, manufacturing. And and we’re at the beginning of that. But maybe maybe another way to think about that is is where do we need intelligence?
Where do we need digital intelligence? And and it’s in every country. It’s in every industry. And we know we know because of that, we recognize that AI is also an infrastructure. It’s a it’s a way of developing a techno delivering a technology that requires factories.
And these factories produce tokens, and they, as I mentioned, are important to every single industry in every single country. And so on that basis, we’re really at the very beginning of it because the adoption of this technology is really kind of in its early early stages. Now we’ve reached an extraordinary milestone with AIs that are reasoning, are thinking, what people call inference time scaling. You know, of course, it created a a whole new we’ve entered an era where where inference is going to be a significant part of the compute workload. But any anyhow, you’re it’s gonna be a new infrastructure, and we’re building it out in the cloud.
The United States is is really the the the early starter and, available in US clouds. And this is our largest market, our largest installed base, and we can continue to see that happening. But beyond that, we’re gonna have to we’re gonna see AI go into enterprise, which is on prem because so much of the data is still on prem. Access control is really important. It’s really hard to to move all of every company’s data into the cloud, and so we’re gonna move AI into the enterprise.
And you you saw that we announced a couple of really exciting new products. Our RTX Pro enterprise AI server that runs everything enterprise and AI, our our DGX Spark and DGX Station, which is designed for developers who wanna work on prem. And so enterprise AI is is just taking off. Telcos. Today, a lot of the telco infrastructure will be in the future software defined and built on AI.
And so six g is gonna be built on AI, and that infrastructure needs to be built out. And as I said, it’s very, very early stages. And then, of course, every factory today that makes things will have an AI factory that sits with it. And, the AI factory is going to be drive creating AI and and operating AI for the factory itself, but also to power the products and the things that are made by the factory. So it’s very clear that every car company will have AI factories, and, very soon, there’ll be robotics companies, robot companies, and those companies will be, also building AIs to, drive the robots.
And so we’re at the beginning of all of this build out.
Jensen Huang, President and Chief Executive Officer, NVIDIA: Well, we have more orders today than we did at the at the last time I spoke about orders at GTC. However, we’re also increasing our supply chain and building out our supply chain. They’re doing a fantastic job. We’re building it here onshore in United States, but we’re gonna keep our supply chain, quite busy for several many more years coming. And, with respect to with respect to further announcements, I’m gonna be on the road next week through Europe.
And, it’s it’s, just about every country needs to build out AI infrastructure, and their they’re, team AI factories, being planned. We’re I think I think, in the remarks, Colette mentioned there’s some a a hundred AI factories being built. There’s a whole bunch that haven’t been announced. And I think the important concept here, which makes it makes it, you know, easier to understand, is that like like other technologies that impact literally every single industry, of course, electricity was one, and it became infrastructure. Of course, the information infrastructure, which which we now know as the Internet, affects every single industry, every country, every society.
Intelligence is surely one of those things. I don’t know any company, industry, country who who thinks that intelligence is optional. It’s essential infrastructure. And so we’ve now digitalized intelligence. And and so I I think we’re we’re clearly in the beginning of a of the the build out of this infrastructure, and every every country will have it.
I’m certain of that. Every industry will use it. That, I’m certain of. And what’s unique about this infrastructure is that it needs factories. You know, it’s a little bit like like the like the energy infrastructure, electricity.
It needs factories. We need factories to produce this intelligence, and the intelligence is getting more sophisticated. We were talking about earlier that we had a huge breakthrough in the last couple of years with reasoning AI, and and now there are agents that reason. And there’s super agents that use a whole bunch of tools, and then there’s clusters of super agents where agents are working with agents, solving problems. And so you could just imagine compared to one shot chatbots and the agents that are now using AI built on these large language models, how much more compute intensive they they really need to be and are.
And so so I I think we’re in the beginning of the build out, and there there should be there should be many, many more announcements in the future.
Jensen Huang, President and Chief Executive Officer, NVIDIA: do this. Thanks. Thanks, Ben. I would say compared to the beginning of the year, compared to GTC time frame, there are four positive surprises. The first positive surprise is the step function demand increase of reasoning AI.
I think it is fairly clear now that AI is going through an exponential growth, and reasoning AI really busted through. Concerns about about hallucination or its ability to to really solve problems. And I think I think a lot of people are are crossing that barrier and realizing how incredible incredibly effective agentic AI is and reasoning AI is. So number one is inference reasoning, alright, and, the the exponential growth there, demand growth. The second one, you you mentioned AI diffusion.
It it’s really terrific to see, that the AI diffusion rule was rescinded. President Trump wants America to win, and and, he also realizes that that, we’re not the only, country in the race, and, he wants he wants, United States to win and recognizes that we have to get the American stack out to the world and have the world build on top of American stacks, instead of alternatives. And so, AI diffusion, hap happened. The res the rescinding of it happened at almost precisely the time that the countries around the world are awakening the importance of AI as an infrastructure, not just as a technology of great curiosity, and great importance, but infrastructure for their industries and startups and society. Just as they had to build out infrastructure for electricity and Internet, you gotta build out infrastructure for AI.
I think that that’s an awakening, and that creates a lot of opportunity. The third is enterprise AI. Agents work, and agents are doing these agents are really quite successful. Much more than generative AI, agentic AI is game changing. You they you know, agents can understand ambiguous and rather rather implicit instructions and able to problem solve and use tools and have memory and and so on.
And and so I think this is enterprise AI is ready ready to take off, and and it’s taken us a few years to build a computing system that that is able to integrate, run run enterprise AI stacks, run enterprise IT stacks, but add AI to it. And this is the, RTX Pro enterprise server that we announced at Computex, just last week. And just about every major IT company has joined us, and I’m super excited about that. And so computing is one stat one part of it. But remember, enterprise IT is really three three pillars.
It’s compute, storage, and networking, and we’ve now put all three of them together for finally, and we’re going to market with that. And then lastly, industrial AI. Remember, one of the implications of of the the the world reordering, if you will, is is, regions onshoring manufacturing and building plants everywhere. In addition to AI factories, of course, there there are new electronics manufacturing, chip manufacturing, being built around the world. And all of these new plants and these new factories are creating exactly the right time when when Omniverse and AI and all the work that we’re doing we’re doing with robotics is is emerging.
And so so this this fourth pillar is is quite important. Every factory will have an AI factory associated with it. And and in order to create these physical AI systems, you really have to train a a vast amount of data. So so back to more data, more training, more AIs to be created, more computers. And so, these four these four drivers are are really kicking into turbocharge.
Jensen Huang, President and Chief Executive Officer, NVIDIA: The the president has a plan. He has a vision, and I trust him. With respect to with respect to our export controls, it’s a it’s a set of limits, and the new set of limits pretty pretty much make it impossible for us to to reduce Hopper any further, you know, for for any productive use. And and so the new limits the new limits, you know, it’s kind of the end of the road for Hopper. We have some we have limited options, and and and so we just the the key is to to understand the limits.
The key is to understand the limits and see if we can come up with with, with interesting products that could that could continue to serve the Chinese market. We we don’t have anything at the moment, and, but we’re we’re considering it. We’re thinking about it. Obviously, the limits are are quite stringent at the moment, and, we we have nothing to announce today. And and when the time comes, you know, we’ll we’ll, we’ll, engage the administration and discuss that.
Jensen Huang, President and Chief Executive Officer, NVIDIA: Thank you. This is the start of a powerful new wave of of growth. Grace Blackwell is in full production. We’re off to the races. We now have multiple significant growth engines.
Inference, once the lighter workload is surging with revenue generating AI services. AI is growing faster and will be larger than any platform shifts before, including the Internet, mobile, and cloud. Blackwell is built to power the full AI life cycle from training frontier models to running complex inference and reasoning agents at scale. Training demands continues to rise with breakthroughs in post training and like reinforcement learning and synthetic data generation, but inference is exploding. Reasoning AI agents require orders of magnitude more compute.
The foundations of our next growth platforms are in place and ready to scale. Sovereign AI, nations are investing in AI infrastructure like they once did for electricity and Internet. Enterprise AI AI must be deployable on prem and integrated with existing IT. Our RTX Pro, DGX Spark, and DGX Station enterprise AI systems are ready to modernize the $500,000,000,000 IT infrastructure on prem or in the cloud. Every major IT provider is partnering with us.
Industrial AI from training to digital twin simulation to deployment, NVIDIA Omniverse and Isaac Groot are powering next generation factories and humanoid robotic systems worldwide. The age of AI is here from AI infrastructures, inference at scale, sovereign AI, enterprise AI, and industrial AI. NVIDIA is ready. Join us at GTC Paris. I’ll keynote at Viva Tech on June 11 talking about quantum GPU computing, robotic factories and robots, and celebrate our partnerships building AI factories across the region.
The NVIDIA band will tour France, The UK, Germany, and Belgium. Thank you for joining us, at the earnings call today. See you in Paris.