An Interview with Nvidia CEO Jensen Huang About Chip Controls, AI Factories, and Enterprise Pragmatism Monday, May 19, 2025 Listen to Podcast Listen to this post: Good morning, This week’s Stratechery Interview is running early this week, as I had the chance to speak in person with Nvidia CEO Jensen Huang at the conclusion of his Computex 2025 keynote, which occurred this morning in Taiwan. I do plan on touching on some of the topics in this interview later this week, so, in the spirit of sharing my conversations with you — which undergirds this interview series — I wanted to post this as soon as possible. I have spoken to Huang three times previously, in March 2022, September 2022, and March 2023. What was notable about those interviews was the extent to which Huang was trying to make the world understand the potential of GPU computing; now that the potential is being realized, Huang and Nvidia are facing an entirely new set of problems, even as they continue to push computing forward. This interview starts out discussing some of those new challenges that are related to politics in particular: we discuss last week’s deals with Saudi Arabia and the United Arab Emirates, the ban on H20 sales to China, and why the U.S. approach to chip controls risks America’s — and Nvidia’s — long term control. Huang also makes the case for why AI will drive GDP growth in the near future, and maybe even reduce the trade deficit. After that we get into today’s keynote and Huang’s keynote last month at GTC. As I note in this interview, I was surprised at how different they were, perhaps because they had different audiences: Taiwan OEMs and component makers and their enterprise customers today, versus American hyperscalers last month; the key thing to understand about Nvidia is that they want to sell to both. To that end, we discuss why a full-stack Nvidia solution maximizes utility, including how Dynamo improves inference performance, even as Nvidia’s approach to software and systems-building lets them sell you only the parts you want. And — perhaps appropriately given the question — we briefly touch on gaming at the end. As a reminder, all Stratechery content, including interviews, is available as a podcast; click the link at the top of this email to add Stratechery to your podcast player. On to the Interview: An Interview with Nvidia CEO Jensen Huang About Chip Controls, AI Factories, and Enterprise Pragmatism This interview is lightly edited for clarity. Arab AI and the Chip Diffusion Rule Jensen Huang, welcome back to Stratechery Jensen Huang: Great to see you, Ben. It is great to actually meet you in person, our previous talks have been over Zoom, and you’re here in Taiwan. You just announced a new building that’s pretty close to my house, so that’s exciting. When we talked before, I felt like you wanted the world to understand what GPUs could be. It was a pre-ChatGPT when we first started talking and now the world’s entire market rests on a knife’s edge when you announce earnings. Now, I think we’re in a quiet period, I’m not asking about earnings, but how does it feel to be thrust in that position, the center of the world in that regard? JH: Well, you asked me a question that I now have no interesting answer. The answer is I have no feelings about it, but I do do recognize this, that while we’re in the process of reinventing Nvidia, which it is always really central to what we’re doing at the office, we’re trying to reinvent Nvidia so that we could be ahead of the puck so that we could be where the industry will go and we want to solve problems that are hard and contribute to the industry. But very importantly now, not only have we created a computing platform, we reinvented our company, we’re much more of a data center scale company, and we offer technology that is for the very first time wholly integrated to work together, but disintegrated so that the whole ecosystem could work with it. But the thing that I said at the keynote, which is really important is that for the very first time that we’re building computers, not just for the technology industry, we’re building computers for a new industry called AI. Now, AI is partly technology, but it’s also partly labor and it augments labor as we know, and as we go into robotics it’ll be very, very clear. This new technology called AI actually is a new industry wholly, and this whole industry is going to be powered by factories, which is going to need a lot of computers, and people are just coming to terms with the fact that we are about to go into a future where we’re computing, what people call data centers, but they’re really AI factories, is likely to be quite large. I noticed you referenced Satya Nadella on the Microsoft earnings call reported the number of tokens that they processed, I think that was last quarter. Was that your favorite bit of earnings from this quarter? I latched onto it right away too, what a great metric. JH: In fact, the number of tokens that are actually being generated is way, way, way higher than that. That’s just the part that Microsoft was generating for third parties, but their own consumption is much, much higher and doesn’t include OpenAI either, so you could just imagine how much it is. From what I understand, that is a very, very large amount relative to the number that was reported. You’ve been on quite the world tour — you and I know Taiwan is beautiful, I mentioned the new office park — I do have to ask what’s the Middle East like at this time of the year? JH: Hot, but not humid. It’s a dry heat, right? JH: Yeah, it’s dry heat. I sort of really enjoyed it because the buildings were cold and I would walk out and just bask in the sun and I actually felt really great. But the nights are just incredible. The nights are incredible. Eating outside, having a cup of tea outside, it’s real incredible. I’m also of course asking about these AI deals that have been announced with Saudi Arabia and UAE. Why from your perspective is that important and why was it important for you to be there? JH: Well, because they asked me to be there, and we were there to announce two quite ambitious AI infrastructure build outs, one in Saudi Arabia and one in Abu Dhabi, and the leaders of both countries were very out in front recognizing the importance of their nations participating in the AI revolution, recognizing that they have an extraordinary opportunity, they have an abundance of energy and a shortage of labor, and the potential of their countries are limited by the amount of labor that they have, the amount of people that they have. So for the first time, they could transform, if you will, from energy to digital labor and robotics labor, agents, robots. They’re super focused on that and very articulate about it. His Royal Highness in Saudi Arabia was very articulate about it and very passionate about and understand the technology even. And Sheik Tahnoun in Abu Dhabi, very passionate about it, very forward thinking about it, understands very deeply the implications of the technology and the opportunities for them and so I was delighted to be there, we’re partnering with both of them. We helped launch a new company called HUMAIN in Saudi Arabia and their hope is to be on the world stage building these AI factories, hosting international companies, companies like OpenAI who was also there, and so a very big initiative. This is a big shift. Part and parcel of this is a step back from the AI diffusion rules, which I think was pretty harsh on those countries in particular, having a regulated number, has to be controlled by US companies, gated in some respects by what’s built in the US. Nvidia, I think contrary to your previous actions, had come out very strongly against those and from your perspective — there’s a bit where you’ve had to grow up, I feel like. Tae Kim said in his book that Nvidia is like an F1 car built around you, and you’re the driver and is there a bit where you never wanted to think about this government stuff, and so Nvidia never really thought about this government stuff, and then suddenly you’re the most important company of the world and you had to learn about this very, very quickly? JH: Well, it wasn’t that I never wanted to, I never had to. For the vast majority of Nvidia’s life we’ve been dealing with building the technology, building the company, building the industry, competing. Yeah, in an industry that’s pure competition. JH: Every single day, every single moment. Building our supply chain, building our ecosystem. Notice I just described a bunch of things that are gigantic in scale and scope, plenty hard in itself, and all of a sudden the diffusion rule came out, and I think we said it at the time, but I think it’s become apparent to everybody now, it is exactly wrong, it’s exactly wrong for America. If the goal of the diffusion rule is to ensure that America has to lead, the diffusion rule as it was written will exactly cause us to lose our lead. AI is not just the layer of software called a model, AI is a full stack thing, that’s the reason why everybody’s always talking about Nvidia systems and infrastructure and factories and so on and so forth. AI is full stack. If America wants to lead in AI, it has to start by leading full stack at the chip level, at the factory level, infrastructure level, at the model level as well as the application level — AI is all of that. You can’t just say, “Let’s go write a diffusion rule, protect one layer at the expense of everything else”, it’s nonsensical. The idea that we would limit American AI technology right at the time when international competitors have caught up, and we pretty much predicted it. And by international competitors, you mean other models? JH: China’s doing fantastic, 50% of the world’s AI researchers are Chinese and you’re not going to hold them back, you’re not going to stop them from advancing AI. Let’s face it, DeepSeek is deeply excellent work. To give them anything short of that is a lack of confidence so deep that I just can’t even tolerate it. Did we spur that work to be even better by virtue of the restrictions that were placed on them, particularly in terms of memory management and bandwidth? JH: Everybody loves competition. Companies need competition to inspire themselves, nations need that, and there’s no question we spur them. However, I fully expected China to be there every step of the way. Huawei is a formidable company, they’re a world-class technology company. The researchers, the AI scientists in China, they’re world-class. These are not Chinese AI researchers, they’re world-class AI researchers. You walk up and down the aisles of Anthropic or OpenAI or DeepMind, there’s a whole bunch of AI researchers there, and they’re from China. Of course it’s sensible, and they’re extraordinary and so the fact that they do extraordinary work is not surprising to me. The idea of AI diffusion limiting other countries access American technology is a mission expressed exactly wrong, it should be about accelerating the adoption of American technology everywhere before it’s too late. If the goal is for America to lead, then AI diffusion did exactly the opposite of that. I think AI diffusion also misses the big idea about how the AI stack works. The AI stack works like a computing platform, it’s a platform. The larger, the more capable your platform, the larger the install base, more developers run and develop on it. When more developers develop on it, it makes the results, the applications, that run on your computing platform better. As a result, you sell more, and more of your computing platform is adopted, which increases your install base, which increases developers using it to develop AI models, which increases — that positive feedback system can’t be understated for any computing platform, it’s the reason why Nvidia is successful today. The idea that we would have America not compete in the Chinese market, where 50% of the developers are, makes absolutely no sense from a computing infrastructure, computing architectural perspective. We ought to go and give American companies the opportunity to compete in China, offset the trade deficit, generate tax income for the American people, build, hire jobs, create more jobs. Nvidia and China Is it fair to say we’re halfway there? Because we started out with the Gulf deal and the AI diffusion rule and certainly, I think you can see from a nation-state competition perspective, having these countries— JH: These two ideas go hand in hand and what I mean by that is this: if we don’t compete in China, and we allow the Chinese ecosystem to build a rich ecosystem because we’re not there to compete for it, and new platforms are developed and they’re not American at a time when the world is diffusing AI technology, their leadership and their technology will diffuse all around the world. That’s my point, where from your perspective, we’re halfway there. At least we’re not cutting us off in other countries. JH: That’s right. But we should go all the way and let Nvidia back in China. JH: Yeah, but I would argue that, in fact, not going into China is about 90% of the way there. It’s actually not 50/50, it’s 90%. So we got 10% done. JH: Yeah, that’s right. Exactly. For the record, I agree with you. My view is this attempt to limit chip cells and then give them all the chip-making equipment they want is precisely backwards — it’s a lot harder to track chips than it is chip-making equipment anyway. One of the theories that people in Washington DC have put forward is, “The chip-making companies or the semiconductor equipment manufacturing companies, they’ve been in Washington for years, they’re very good at lobbying and Nvidia’s not here, and so they’re behind the eight ball”. Does that ring true to you? Do you just say have a hard time having people in Washington understand this point of view? JH: We had to work really hard in the last several years to build a presence in DC. We have a handful of people, most companies our size have hundreds of people, we have a handful. Our handful of people are amazing, they’re telling our story. They’re helping people explain, understand not just how chips work, but how ecosystems work, and how AI ecosystems work, and what are some of the unintended consequences of the policies. We want America to win. Every company should want their country to win, and every country should want their companies to win, those are not terrible things to feel, those are good things to feel, and it is also good that people love to win. Competition is a good thing, aspiring to be great is a good thing. When some country aspires to be great, we shouldn’t begrudge them. When some company aspires to be great, I don’t begrudge them. It causes us to all rise above and do even better than we could, and so I love watching people who aspire to be great. There’s no question China aspires to be great, good for them! They should expect absolutely nothing less, and for all of the AI researchers and AI scientists that I know around the world, they got to where they are because they all aspire to be great, and they are great. I think the idea that somehow that— To win, you have to put the other one down. JH: That’s right, it makes no sense to me. We ought to go faster. The reason why Nvidia is here today, the reason why we have our position today, we had absolutely zero support from anybody to get here, just let us keep running hard. I think the idea that we would hold other people back, as you mentioned, it just spurs them to be even greater, because these are amazing people. I agree. I find it, as an American, deeply frustrating. I feel we should want to win by out-innovating, by going faster and this idea we’re going to win by pulling up the ladder and cutting people off, and putting bureaucratic red tape on everyone and trying to track everything just seems deeply, frustratingly un-American to me. JH: Yeah. Anyhow, I think the President really sees it, he wants America to win. Well here’s a question on this, because this is the same administration that cut off the H20, a chip that you basically designed to the previous administration’s specs, and suddenly, “It’s not okay”, and now they’re doing this deal. The critics are there, “Oh, this is going to open it up to China, potentially, XYZ”. It does feel like a shift in administration, maybe they’d argue it’s still the same thing. But we’ve also had a lot of shifts between the US and China over the last six weeks, I think is one way to put it. Do you get a sense that maybe there’s been a real realization that this world is so interconnected and related, and what goes on one side happens on the other, and maybe it’s not going to be so easy to peel apart, and there’s going to be a return of pragmatism, and how do we manage this? Are you optimistic in that regard or are you preparing for the worst? JH: The President has a vision of what he wants to achieve, I support the President, I believe in the President, and I think that he’ll create a great outcome for America, and he’ll do it with respect and with an attitude of wanting to compete, but also looking for opportunities to cooperate. I sense that, I see all that. Obviously, I’m not in the White House and I don’t know exactly how they feel, but that’s what I sense. First of all, the ban on H20s, that’s the limit of what we can do to Hopper, and we’ve cut it down to there’s not much left to cut. We’ve written off — I think it’s $5.5 billion — no company in history has ever written off that much inventory, so this additional ban on Nvidia’s H20 is deeply painful. Its costs are enormously costly, not only am I losing $5.5 billion, we wrote off $5.5 billion, we walked away from $15 billion of sales and probably — what is it? — $3 billion worth of taxes. The China market is about $50 billion a year and it’s not $50 million, it’s $50 billion. $50 billion is like Boeing, not the plane, the whole company. To leave that behind so that the profits that go with that, the scale that goes with that, the ecosystem building that goes with that— That’s the real threat to CUDA in the long run— JH: That’s right. China builds an alternative. JH: Exactly. Anybody who thought that one chess move to somehow ban China from H20s would somehow cut off their ability to do AI is deeply uninformed. AI GDP Growth There’s an angle on this in the power stuff that I want to get to in a moment, but this is going to be more fun. Let’s leave aside all the government stuff, we’ll circle back around. A third way to get to my question about financial markets, governments, on today’s keynote you started out by saying, “We’re an infrastructure company, you need five-year roadmaps”. You mentioned in passing that your original TAM estimate when you started Nvidia was $300 million. When did you actually see this coming, “We’re going to be infrastructure?” — again, I go back to our conversations previously, my sense from those is you just wanted people to see this possibility. You saw the possibility of GPU computing, but the scale, has it blown your mind just a little bit? JH: If you watch my keynotes, as you do, almost pretty consistently, things that are happening today, I spoke about five years ago. At the time when I was speaking about it five years ago, the words weren’t as clear and the vocabulary I was using wasn’t as precise, but where we were going is consistent. So basically right now when you talk a lot about robotics at the end of every keynote, which you have been doing, that is our five-year preview that we should really be paying attention to. JH: Yeah. And in fact, I’ve been talking about it for about three years. Yeah, so a couple years from now. JH: It’s a couple years from now, I think it’s going to happen. The thing that is fairly deep and fairly profound for this industry is that for all of the last 60 years we’ve been the IT industry, which is a technology and tool, it’s a technology and tool used by people — for the very first time, we’re going to leave the IT budget, what we sell goes into the IT budget, we’re about to leave the IT budget and into the manufacturing or the OpEx budget. The manufacturing budget is because we’re building robots or because robotic systems are being used to build products and then the OpEx is because of digital workers. The world’s OpEx and CapEx is what? Combined $50 trillion? It’s a giant number. So the IT industry is about a trillion, we’re about to bring, because of AI, all of us into about a $50 trillion industry. Of course my first hope, and I think it will happen this way, although jobs will be changed and some jobs will be lost, a lot of jobs will be created. It is very likely that robotic systems where their agents are physical robots, will likely expand the world’s GDP. The reason for that is we have a shortage of labor, that’s why everybody’s employed. If you go around the United States, unemployment is at all-time lows, and so it’s because we just don’t have enough labor. Restaurants are having a hard time filling staff, many factories are obviously having a very hard time filling staff. I think the idea that you would hire a robot for $100,000 a year, I think people will do that in a heartbeat and the reason for that is because it just increased their ability to generate more revenues, and so I think that that next five, ten years is we’re likely to experience that expansion of GDP and a whole new industry of these token manufacturing systems that people now will understand. What I thought was also interesting about today’s keynote is I prepped for this interview before I came and I’m like, “Well, it’s probably going to be a bit of a rehash of GTC”, and I thought it was actually pretty starkly different. Here’s my interpretation, you have to let me know if it’s correct. It felt like GTC was for the hyperscalers and today’s presentation was for enterprise IT, it was like two different markets. JH: Yeah. Do I have that correct in terms of the target? JH: Enterprise IT or agents and robots, and agents for enterprise IT and robots for manufacturing and the reason for that is very clear, this is this the beginning of the ecosystem. You made a beautiful video by the way of the Taiwan ecosystem and that goes into making all the pieces, that was really great. Dynamo and Full-Stack Nvidia Let’s go to the GTC keynote, that was one of my favorite keynotes of yours, I do watch them all and watched them all for years. Some real Professor Jensen energy, as you explain the limitations of data centers, why Nvidia was the answer, and I interpreted that as kind of an anti-ASIC message. You had a combination of, you showed your roadmap, it’s like, “Try to keep up with this”, and then number two, you introduce the Pareto curve of latency versus bandwidth, and because they’re programmable, you can use the same GPUs all over this curve and of course, hyperscalers are the ones that are going make ASICs. Do I have the right understanding of your presentation there? JH: I think the teachings was right, the reasons why I did it wasn’t exactly that. I was simply trying to help people understand how to build a new data center. We’ve been thinking about it and so here’s the challenge. There’s only so much energy in the data center. 100 megawatts is 100 megawatts, 250 megawatts is 250 megawatts and so your fundamental job, if it’s a factory, is to make sure that the overall throughput-per-watt is the highest because that overall throughput in tokens, depending on if it’s cheap, inexpensive tokens, meaning free-to-use tokens or the high quality tokens that somebody might pay actually say, a thousand dollars a month, $10,000 a month. Well you just mentioned a $100,000 AI assistant. JH: Exactly. Would I hire a $100,000/year AI agent? In a heartbeat. And the reason for that is we hire people way more expensive than that all day long and if I can just simply amplify somebody who I’m paying $500,000 a year, that’d be incredible, for a hundred thousand bucks, so of course I would. The quality of tokens that you generate in a factory is quite varied. You need some that are free-to-use, you need some that are high quality and so you’re across that Pareto. You can’t design a chip or a system that is only good at one, because it’ll be underutilized and so now the question is, how do you create a system that simultaneously, at some time, could be used for free token generation, some of it for free tokens, some of it for high quality? If you cause the architecture to be too fragmented, then your ability to move workload back and forth is difficult and so I think when people go through the thinking of it, if you design a system that’s very, very good at high token rate, it naturally has very low overall throughput. If you design something at a very high throughput, it tends to have very low interactivity, it’s tokens-per-second per user is low and so it’s easy to hug the X-axis, it’s easy to hug the Y-axis, it’s hard to fill out that area, and so that’s the invention over all of the combination of what we did with the Blackwell architecture and FP4 and NVLink 72 and the ratio, the balance between HBM memory and its capacity, the balance between the amount of floating-point and the memory capacity and bandwidth and then very importantly, the Dynamo disaggregated streaming serving ecosystem, hardware system. I wanted to ask you about Dynamo, which did not come up today, but I think is super interesting. JH: Super important. Give me the pitch, I think you called it the operating system for data centers. JH: The pitch basically is that the inference workload, the transformer, has different stages of it, and different stages could be used differently depending on the user and depending on the model and depending on the context of that model and so we disaggregated the processing of the large language model into pre-fill, which is the context processing, thinking about what you’re about to ask me. It has to do with my memories of Ben and the type of the deep and conversational podcasts like you like to do, and they tend to have — if I start talking deeply about the industry and the technology, I don’t feel uncomfortable doing so. Right, you’re not doing a sound byte right now for the evening news or something like that. JH: That’s right. I feel like I can lean in and because you’ll understand it, I don’t feel like I’m talking to the wall, and so I feel very comfortable talking about these things. Well, when an AI comes to a chatbot, the chatbot needs to have some of that context and so chatbots have memory, they process context, and they might even have to read a PDF or two, and so that’s called a pre-fill part, that pre-fill part is very floating-point intensive. Then there’s the decode part. The decode part is about now generating the thoughts, it’s about reasoning through what you’re about to say, predicting the next token and so a chain of thought basically generates a lot more tokens, which gets fed back into the context which generates more tokens, and so it’s reasoning through a problem step-by-step, maybe it has to go off and read some stuff. The modern versions of AI, this agentic AI’s, reasoning AI’s, the amount of floating-point, the amount of bandwidth — decode requires a lot of bandwidth — is high in all cases, but it could be higher. It varies. JH: That’s right, it varies depending on things. You don’t need a high floating-point precision in the decode stage. JH: That’s right. So for example, one-shot, and it’s got a strong KV cache already, you don’t need much floating-point. However, the moment you load it with context, you need a lot of floating-point. Dynamo disaggregates all the processing and it disperses it in the data center smartly metering the workload and metering the load on the processors, really complex stuff. Well, and it ties into, if the entire data center is one GPU, you’re talking about a software layer that treats it that way. JH: That’s right, it’s essentially the operating system of an AI factory. When you think about these thinking models, these reasoning models, looking forward — you’re someone, like you said, you have great predictions — do you see these being used mostly in agentic workflows and the downside of them is you’re sitting around and waiting for them, or maybe you’re setting up a bunch of agents that are acting in parallel, so that works out well, or they can actually end up being most important in generating data for training to get better one-shot results which is how people would interact more frequently? JH: I think depending on cost, and my prediction is that it’s likely that reasoning models will just be the baseline, because we’re going to process this so lightning fast. Basically when you turn on Grace Blackwell, it’s 40 times faster, and let’s say the next click is another 40 times faster and the models are getting better. So the idea that between now and five years from now that we could be 100,000 times faster for agentic models, very sensible to me. That’s the history of computing. JH: That’s right. So it just thought about a mountain of things, you just didn’t see it. It’s a fast thinker now, even slow thinking is fast. What was that book? Thinking Fast and Slow, now apply that to AI. I guess it could read the whole thing in a second, so it might defeat the purpose. JH: That’s right. Enterprise AI and Pragmatism To go back, just a quick little touch on politics. Is there a bit where your delivery in talking about this and your performance-per-watt, is that really a US-centric thing in a world where we have a hard time building power and power is the chief constraint? You look at something like these Gulf countries, power more accessible, easier to build for various reasons, and you go to China, guess what? If power is not the chief constraint, you can work through a lot of problems that Nvidia solves for you. Is that a reason GTC is in the US, that’s the message for the US? JH: Oh, I didn’t think of it that way. I think that no matter what happens, your factory will always be a certain size and even though your country has a lot more energy, your data center doesn’t and so I think perf-per-watt is important, always. It’s always important, but the degree of importance may vary. JH: That’s right, yeah. It’s just that if you’re planning for it, on the other hand you say, “Okay, well I have an architecture that has half the performance-per-watt, and so maybe I’ll just get twice as much land, and twice of some much power, and just start building that from the get go”. When you put all that stuff together, though, this is the problem. Remember, even the infrastructure itself and the power delivery let’s say for a gigawatt, let’s just do some simple math. Let me just say $30 billion of it could be shell, power, land, operating it, all that $30 billion. Let’s say the compute and the networking and everything, all in storage, $50 billion, okay? Well, if it turns out that you have to build twice as many, you just multiply your $30 by 2, so it’s $60 billion and so you’re going to have to get some really cheap compute to make up for it. That’s why I always feel that in the world of AI factories, the math would suggest that if an architecture is not as good, sometimes depending on how poor it is, even free is not cheap enough. If it’s your only choice, you’ll make it work. JH: That’s right. Well, let’s contrast that to today. You said a couple of times today, “I love it if you buy everything from me, but I’m happy you buy anything from me”. It was funny before it fully crystallized for me that this feels like the enterprise keynote, which is again my words not yours, there was this sense of pragmatism that I’m like, “He’s sounding like an enterprise CEO right now, they’re very pragmatic”. Of course, if you buy the whole stack, it works better, and it’s kind of interesting where if you’re talking about building a full up AI factory, to use your words, of course using all Nvidia will maximize your returns from it, but there’s a lot of customers out there that are just buying bits and pieces, and those customers, maybe you like them to buy the whole thing, but also if they buy anything from you, they’re probably going to buy it from you forever. So it seems like just strategically, it’s a very useful base to go for. JH: Serving a customer is just smart. If you look at the way Nvidia goes to market, we’ve always built things in a fully integrated way because software needs to be integrated with hardware somehow, but we do it with enough discipline that we can then disaggregate the software from the hardware, and you could decide not to use our software, you can choose not to. And if you look at the way we design our systems, we’ve actually disaggregated the systems in a sufficiently disciplined way, that if you wanted to replace some of it, you could. Right now, Grace Blackwell is being integrated, and stood up all over the world in different clouds and they’re all based on our standards, but they’re all a little bit different, and yet we fit into them. That’s I think the real challenge of Nvidia’s business model, and it goes hand-in-hand with wanting to be a computing platform company. The most important thing is that one of Nvidia’s stacks, if it’s our compute stack, that’s great. If our networking stack, which I feel deeply about and as strongly about as my computing stack, if my computing stack gets adopted all in all, terrific. If my networking stack gets adopted, terrific. If both of them gets adopted, incredible. Well, I mean, a lot of people, your NVLink Fusion, you can get just NVLink, you can integrate it with your ASIC with — again, total contrast to what I interpreted the GTC messaging — but again, I can see the view here. I mean, who’s the customer? JH: I still have deep beliefs that Nvidia is building a better system overall, I still believe that. And if I don’t believe that, then obviously we must be doing something wrong, and we’ve got to go get ourselves to believe that, and so I completely believe that Nvidia is the largest scale accelerated computing company in the world, we’re the largest scale AI computing company in the world. Nobody of 36-38,000 people is united to this one job than any place ever and so the idea that a small team of 14 people could do a better job than us would be quite painful to internalize, and so we strive to do better. However, you also believe in scale, and a great way to get scale in everything that you’re selling is to sell it however the customer wants it. JH: That’s right, exactly. That’s exactly right. So I have preferences, but we want to make sure that we’re able to serve every customer however they’d like to be served. Whither Gaming Along these lines, and maybe this is related: I was asking a friend of mine about this interview and he said his son insisted that I ask this question. Some people in gaming feel, you mentioned it today, only 10% of the keynote is about GeForce, but that’s still important to us. Is that a, “It’s still important to us because this all scales and we’re making GPUs?”, or what should I tell my friend’s son about Nvidia and gaming? JH: See, I wish I had said it, RTX PRO wouldn’t be possible without GeForce, Omniverse wouldn’t be possible without GeForce, not one of those pixels that we saw in any of those videos would’ve been possible without GeForce, robots wouldn’t be possible without GeForce, Newton is not possible without GeForce, so GeForce itself, they’re not as deeply part of the GTC event because GTC tends to be about high-performance computing, and enterprise, and AI, and things like that. We have a separate conference for game developers and things like that and so it’s just that when I do GTC, I got a group of people that I always feel a little badly about that their product launch isn’t as central, but it’s just not the right audience, but they also know that GeForce plays such an integral role in everything that we do. I mean, is there a bit that maybe the gamers just don’t fully appreciate the extent to which their GeForce’s are much more than just graphic rendering engines at this point? JH: (laughing) Yeah, right. Exactly. And I said it today, we’re only rendering 1 out of 10 pixels, it’s a shocking number. Suppose I gave you a puzzle, and I gave you 1 out of 10 pieces and the other 10 pieces I’m not even going to give you, you’ve just got to make them up. I got another pitch for you to connect gaming to your other things. You just talked about how you’re disciplined about keeping things separate, and being able to separate it and software managing all that. Kind of sounds like the driver problem on Windows, to be totally honest, that’s just a core skill set that you have. JH: Yeah, it’s just a driver is too low-level, and it’s got too many things, too many registers and the driver abstraction was actually a revolution that Microsoft really played a very large role in. Windows wouldn’t be where Windows is if not for this concept of a driver, and it created an abstraction of an API while underneath the hardware can change fairly significantly. We’re open source, our driver now, and quite frankly, I don’t see that many people contributing to it, and the reason for that is because the moment I come up with another GPU, all the work that they did in the last driver is kind of thrown away, and so without a large body of engineers like Nvidia has, it’s hard to do. But if we optimize every GPU for every driver with its associated driver, then there’s a wonderful isolation layer, an abstraction layer, whether it’s CUDA or DirectX, that people could build on top of. Look, here’s my answer to my friend’s son. I had to ask you about the government stuff, and you gave a good and passionate defense of your view, but you truly got excited and your eyes lit up when I asked about gaming drivers. JH: Oh, is that right? So I think everything’s still good. JH: Oh good. Yeah, I love GeForce actually. There you go, that’s why it’s good to speak in-person. Jensen Huang, thank you very much. This Daily Update Interview is also available as a podcast. To receive it in your podcast player, visit Stratechery. The Daily Update is intended for a single recipient, but occasional forwarding is totally fine! If you would like to order multiple subscriptions for your team with a group discount (minimum 5), please contact me directly. Thanks for being a supporter, and have a great day! Get notified about new Articles Please verify your email address to proceed. ←2025.20: Product Dreams and Marketplace Realities

Netflix began streaming new episodes of the popular British preschool series “Peppa Pig” in the U.S. today — and will offer the “World of Peppa Pig” gaming app within the streamer to go with it. The move is one of Netflix’s splashiest to date when it comes to building out not just its video game offering, but specifically its kids and pre-K titles. “When we think about the overall kids game strategy, there’s taking from what we know from film and television and what they’ve learned with kids, which is about focusing on familiarity and focusing on things that kids already know and love,” Netflix kids gaming chief Lisa Burgess told Variety. “And we’ve also seen hints of that with our games portfolio, too. If you focus on bringing things that are familiar over onto our service, it helps our members to understand what we’re offering. So from from the highest level of what kinds of games do we want to select? We want to go after things that are big IP, beloved IP, a connection to Netflix — and Peppa falls to the top of many of those things, big IP, beloved on our service. And then ‘World of Peppa Pig’ has been a great game for many years. And so when we were thinking about all the opportunities, it was one of the very top ones that we wanted to go after.” Related Stories Per Netflix, the “World of Peppa Pig” app will offer users activities including puzzles, mini-games (spot-the-difference, dress-up games and memory challenges) and coloring books. Popular on Variety Burgess describes the “World of Peppa Pig” games as “very approachable” for a two year old and of interest to kids up to eight year olds, with the “sweet spot” being children ages two to five. “It’s less about the age spectrum and more about how much have they been exposed to games before in the past,” Burgess said. “Overall, the strategy is focusing on things that are familiar, and so that familiarity can be an IP, and not necessarily an IP tied with a game,” Burgess said. “And kids at this age are very IP driven. They want to play with their favorite character like that’s their best friend. And so they want nothing more than to be able to engage with those characters. There are a lot of great kids games that are out there right now, ‘World of Peppa Pig’ was one of them. And so I do think we want to think about our strategy of, what is the value add of us being able to bring some of those other great games onto our service that add value for our members? And then in the other dimension, what about IPs that exist but don’t have great gaming experiences around them for kids? And how do we actually build up good experiences and great gaming experiences for that?” Example: On Monday, Netflix announced it had acquired the streaming rights to powerhouse PBS Kids series “Sesame Street” and would be developing video games for both “Sesame Street” and “Sesame Street Mecha Builders.” “A the high level, it’s all about familiar, big IP,” Burgess said. “Some will be existing games that are already built, and some will be games that we’re building up from the ground up, based on big IP.” To date, Netflix says kids and family viewing represents 15% of its total viewership, and the streamer weeks to make its kids gaming offering “an extension of the safe environment parents already trust” that’s included with that subscription. As Netflix builds out its overall games lineup, it’s also laying the groundwork for keeping a user interested in its offering from pre-K through adulthood by having titles targeted to subscribers in each age demographic. “It’s the million-dollar question: how do you actually facilitate through that journey?” Burgess said. “And with kids, there comes a certain point in time where they no longer want to sit at the kids table. And so you cannot design experiences that are labeled for kids, because they’re not going to want to do that anymore. And so finding that line of, how do you start introducing kids to things that are safe and accessible, but not necessarily just for kids, that are more like for all ages?” Burgess says Netflix is able to use its existing data from kids profiles and family viewing habits to adjust the flow from kids games to more adult games the same way it feeds new content to children as they get older. “For every place possible, we’re going to try and take those learnings and apply them to games,” Burgess said, adding: “but we have a lot that we need to do on the overall journey and discovery experience and it’s something that we’re thinking about as we’re scaling out the portfolio of games for kids, and as that diversity gets bigger.”

News Wuchang: Fallen Feathers Receives Short New Gameplay Trailer, DLSS 4 Support Confirmed PC players can also expect DLSS Frame Generation, Super Resolution and Reflex support when Leenzee's title launches in July. Posted By Ravi Sinha | On 19th, May. 2025 Nvidia recently announced DLSS 4 Multi Frame Generation support for various PC titles, including DOOM: The Dark Ages. Add Leenzee Games’ upcoming hack-and-slash title, Wuchang: Fallen Feathers, to the list. Check out the latest gameplay trailer to see how it looks on a GeForce RTX 5090 at 4K and Max settings while DLSS 4 is enabled. Other notable features available at launch include DLSS Frame Generation, Super Resolution and Reflex. They’re all fairly standard, though the developer has yet to confirm support for upscalers like AMD FSR and Intel XeSS. The system requirements also remain a mystery. Wuchang: Fallen Feathers launches on July 24th for $49.99 on Xbox Series X/S, PS5, and PC, and promises 40 to 60 hours on average to complete. Players can fight the game’s many bosses in any order and unlock different endings. Check out another gameplay trailer here, highlighting some of the threats that protagonist Wuchang goes up against, or head here for more extensive gameplay. Tagged With: Elden Ring: Nightreign Publisher:Bandai Namco Developer:FromSoftware Platforms:PS5, Xbox Series X, PS4, Xbox One, PCView More Borderlands 4 Publisher:2K Developer:Gearbox Entertainment Platforms:PS5, Xbox Series X, PCView More Death Stranding 2: On the Beach Publisher:Sony Developer:Kojima Productions Platforms:PS5View More Amazing Articles You Might Want To Check Out! Wuchang: Fallen Feathers Receives Short New Gameplay Trailer, DLSS 4 Support Confirmed PC players can also expect DLSS Frame Generation, Super Resolution and Reflex support when Leenzee's title lau... Nintendo Will Attend Gamescom 2025 After having skipped last year's Gamescom, Nintendo has now confirmed through social media that it will be att... FBC: Firebreak Trailer Showcases Path Tracing and DLSS 4 Performance on PC Remedy's co-op shooter will support both features when it launches on June 17th for PC (alongside Xbox Series ... Nintendo Switch 2 Will Bring Back Feature That Uses HD Rumble to Find Lost Controllers As long as the Switch 2 can connect to a controller, it can use its HD Rumble to make it vibrate loudly enough... DOOM: The Dark Ages Adds Path Tracing and DLSS Ray Reconstruction in June on PC id Software's acclaimed first-person shooter will also support DLSS Multi Frame Generation on Nvidia's RTX 50 ... Grand Theft Auto 6 – Take-Two Believes Long Gap Between Games is Fine Because of GTA Online Content Strauss Zelnick believes that Rockstar technically puts out Grand Theft Auto Online content equivalent to full... View More

AI is transforming industries worldwide, and its growing impact on digital finance is becoming significant. One of the most intriguing applications of AI lies in the analysis and forecasting of the Bitcoin price in USD – a notoriously volatile metric that traditional financial models struggle to predict. Today, AI is helping decode cryptocurrency’s complexities with speed and precision.From deep learning networks and sentiment analysis to real-time anomaly detection, AI technologies are shaping how investors, institutions and platforms understand and respond to Bitcoin’s dynamic movements.Predicting Bitcoin with deep learningBitcoin has evolved into a global platform operating through numerous nodes around the world. Each node creates further data, like trading volume, volatility and price changes, alongside other trade-related documentation. All this serves as the basis for training deep learning frameworks.Forecasting Bitcoin prices using recurrent neural networks (RNNs) is particularly effective due to the use of Long Short-Term Memory (LSTM) networks. LSTMs excel at capturing long-term dependencies in time series data, making them ideal for handling the complex and dynamic nature of Bitcoin’s real-time price movements. The ability to remember and learn from previously observed patterns allows LSTMs to model the statistical behaviour of Bitcoin prices over time.A recently published study in Forecasting (2024) proposed a hybrid model for predicting Bitcoin prices by incorporating LSTM with attention mechanisms and gradient-specific optimisation. The study boasts an impressive accuracy of 99.84%. Advanced deep learning strategies in financial forecasting, as this study suggests, are superior to those found in traditional models.Using NLP to decode market emotionsNatural Language Processing (NLP) tools help cryptocurrency investors analyse real-time, unstructured data to understand market sentiment and investor behaviour.In 2023, a study posted in arXiv introduced an end-to-end model for forecasting sentiment of tweets together with price prediction. The model employs a BERT-based neural network for sentiment analysis and a GRU for price forecasting. The study claims that by integrating sentiment analysis and deep learning, the cryptocurrency market can be predicted with greater accuracy. The mean absolute percentage error of 3.6% shows the potential in the synergy of both domains.Spotting market anomalies with unsupervised AIUnsupervised learning techniques, like clustering algorithms and autoencoders, are particularly effective at anomaly detection in the cryptocurrency space. Especially in tumultuous markets like Bitcoin, where discerning unpredictable patterns is key, such tools excel at detecting unexpected patterns.Models can flag possible scenarios of flash crashes, price manipulations and other sophisticated activities on the exchange by monitoring real-time market data against historical market data. For instance, if Bitcoin’s price in USD drops sharply while asset dependencies remain constant, AI can detect the outlier and notify human traders or activate protective protocols.Mining blockchain data for AI insightsActive addresses provide one of the most significant advantages of Bitcoin – the transparency of its blockchain. On-chain data enables real-time monitoring of network activity and participant behaviour, like the number of active addresses, hash rate, wallet distributions, and transaction volumes.AI models can analyse such data to identify large-scale trends. For instance, in the previous bull runs, a surge in wallets containing 1-10 BTC (commonly associated with retail investors) was observed. Relatively, declines in miner flows to exchanges can predict supply restrictions.Reinforcement learning models are being taught to predict the impact of on-chain movements on Bitcoin’s market value. A hybrid of blockchain analytics and machine learning is redefining how analysts build predictive models based on clear, accessible public data.The new AI bots break down market bordersArtificial intelligence has increased its foothold in cryptocurrency markets through autonomous trading systems. Unlike older trading bots that had a set checklist to complete, modern bots are highly sophisticated and employ flexible plans based on real-time data.Modern AI bots don’t just follow trends; they consider various factors influencing market prices. AI bots shift from trend-following to mean reversion and take into account price shifts and technical indicators. Some bots can simulate market conditions each second to determine statistically-reasonable points for investment.Ethical and technical problems surrounding AI application on cryptocurrencyImplementing AI in cryptocurrency trading can be risky, although rewarding. Assurance over-fitting remains an issue, as builds driven by historical data are less reliable with remaining black swans or unexpected changes in regulations.Coordinated bot networks pose significant risks to trading volume and market sentiment. For this reason, many platforms have focused on publishing algorithmic audit trading reports for transparency and establishing ethics teams to mitigate any misuse of AI technologies.Explanatory frameworks of AI models, like model transparency and accountability, are particularly important in applications related to finances because of the enormous risks involved and the fragile trust of users.April 2025 updates: Bitcoin and AI integrationIn April 2025, Glassnode reported that addresses holding between 1,000 and 10,000 Bitcoin surged to 2,014, up from 1,944 in early March. The increase in this number of “whales” has been accumulating since April 2024, suggesting that there is confidence returning from major holders.Brief reflection: Bitcoin assessments enter the AI eraAnalysing and predicting the dynamics of Bitcoin and its price in USD through artificial intelligence is a trend that is here for the long run. It will be an essential part of strategy when dealing in cryptocurrency markets. AI provides unprecedented opportunities in financial market analysis through neural networks, mining on the blockchain, business behavioural prediction and creation of risk models.For AI specialists, this might represent the only practical example of having a blend of ultra-high-frequency data, actual working scenarios and comprehensive public systems that encourage collaboration. For the rest of us, we are shown a reality of being surrounded by systems that optimise buying and selling at lightning speeds.(Image source: Unsplash)

MotoGP racing, the pinnacle of motorbike competition, requires precision and skill–and some scraped elbows and knees.   Image: Ducati/Lenovo Get the Popular Science daily newsletter💡 Breakthroughs, discoveries, and DIY tips sent every weekday. MotoGP is high-speed, high-tech motorcycle racing. The fastest riders in the world compete on specialized, purpose-built motorcycles from companies like Ducati, Honda, Yamaha on the world stage in this series, which is considered the most prestigious in the game. Riders reach incredible speeds on their machines up to 220 miles per hour, and races can go 350 turns with gravity-defying leaning that scrapes elbows and knees. This Grand Prix is for the toughest of the tough on the moto circuit.  Behind the riders and the machinery is a boatload of data and technology; we’re talking massive amounts of data in numbers that make your head spin. As tech company Lenovo puts it, when it comes to MotoGP–a sport in which every millisecond counts–data can mean the difference between a first and last place finish.  Lenovo and Italian motorbike manufacturer Ducati work hand in hand to create a champion racing team with information gathered by 50-plus sensors that track tire rotation, speed, grip, acceleration, and more. Motorcycle racing, at the highest echelon, has evolved way beyond just the machinery or even the skill of the rider. Without the technology, any team would be left in the dust.  The data journey In the past, the only way to evaluate the outer limits of what a motorbike could endure was to disassemble a crashed bike. Today, a multi-pronged approach to data collection takes that process up several notches. Every time a bike enters the pit garage, an in-person team and a crew from the Ducati Lenovo Remote Garage at Ducati’s headquarters in Bologna, Italy analyzes performance.   Via 50 sensors on each bike, Ducati engineers collect tons of data they can parse and assess. Image: Ducati/Lenovo No matter where the team is racing, data streams in from the motorbike sensors. Off-site engineers analyze information from the track, making tiny tweaks to the bike and its operation. That way, every qualifying lap may be reviewed and fine tuned for the best competitive outcomes.  “We debrief after each session, aligning with the rider on the sections and corners in which we think that he can improve his performance,” says David Attisano, the data and performance analysis manager for Ducati Racing. “We review with the rider his maneuvers and what we can expect to improve and how. For example, if the data shows that the rider can brake two meters later than he is, that’s a huge distance in this race.”  For the MotoGP series, Ducati has three different teams with a total of six riders. Each Ducati rider receives the data not just about his own ride but for all the other riders, so they can track what the other five are doing. That’s a giant amount of data. “We can push each other to the limit because we can see what the other riders are doing and comparing, then we can highlight and suggest some changes in their riding style,” Attisano explains.  Through its partnership with technology company Lenovo, Ducati collects and analyzes data to push its bikes to the limit and win races. Image: Lenovo/Ducati Per official MotoGP rules, the sensors can’t transmit the data while the bikes are in motion. As soon as the bike gets to the garage, the engineers download the data. From this point, the data analysis process begins. At this point, the partnership is especially critical as the servers are developed by Lenovo specifically for Ducati. On top of that, there are data signals created with a custom algorithm and simulating based on engineering knowledge about the bikes. The team can even create a detailed “digital twin” of the course that maps each twist and turn, using 200GB of data per circuit. “If the rider tells us that the traction control is not working properly, our electronics engineers can adjust the ECU,” says Attisano. “In our competition, the human factor is very important. We rely on the data and the humans do the last mile to gain the result and to achieve victory.”  Sure, data clearly plays a big part, but human interpretation is still a critical aspect to translate the results. Even those who know nothing of motorcycles can create algorithms or artificial intelligence to offer some hints or tips, but without input from the team, the data has no context. The technology, Attisano emphasizes, is intended to augment the capabilities of human beings, not to replace them.  Italian motorbike manufacturer Ducati makes high-speed, high-tech machines. Image: Ducati/Lenovo “The behavior of the bike is very complicated–it’s very difficult to understand if you have not studied it at university,” he says. “In our experience, the exchange of knowledge between engineers and data scientists is very important.”  Ducati’s data collection on the competitive side feeds into the safety and reliability for all riders, including those who like to take their motorbike for a spin on any given Sunday; not just competitive situations. Every time the bike emerges from the pit at a MotoGP race, the engineers strive to be sure it’s in good form and safe for the rider. Every improvement via the data collected from 50 tiny sensors on each factory-made racing bike leads to a better ride for casual street riders, too.

🎬 It's Monday! Welcome back to another episode of my weekly CGHOW community reply series, where I go through your comments from Discord and YouTube and answer your questions about Unreal Engine, Niagara, and real-time VFX! Whether you're a beginner or an advanced VFX artist, I'm here to help you level up your skills, fix common issues, and give you tips based on your feedback and questions. 👇 Got a question for next week? Drop it in the comments or join the CGHOW Discord! 🔗 Join the CGHOW Community: 👉 Discord: https://discord.gg/CYQSpKwawb 📌 Don't forget to like, comment, and subscribe to support the channel! 📅 New VFX videos uploaded every week! https://linktr.ee/cghow #UnrealEngine #RealtimeVFX

When you finish watching season two of Andor, the natural next move is to dive right into Rogue One: A Star Wars Story, the movie that introduced Diego Luna’s Cassian Andor to the galaxy far, far away. But he’s not actually the lead character in the 2016 film—that distinction goes to Felicity Jones’ Jyn Erso, daughter of reluctant Death Star architect Galen Erso. And while Andor leads right into Rogue One, and the two stories share many of the same characters, Andor creator Tony Gilroy made the call that Jyn wouldn’t be among them. In fact, he never even considered that Jyn would show up in the Andor finale, according to a new interview with Entertainment Weekly. “I tried to sketch some versions along the way of what we would do,” Gilroy explained. “Episode 12 is very unique … we are not trying to hype anything in 12. We always knew it was going to be not a low energy, but a different kind of episode.” Gilroy did briefly consider bringing more Rogue One characters in—Danny Mays’ Tivic the informant, for instance, who’s killed by Andor early in Rogue One, and maybe even Mads Mikkelsen’s Galen Erso—before thinking better of it. “In the end, I realized if people didn’t absolutely have to be there, they shouldn’t,” Gilroy reasoned. “And it would’ve been lame to bring Jyn back as a cameo. That would’ve been really disrespectful in a way. I’d rather honor Rogue and keep it straight.” He’s also well aware that Rogue One fans are now re-evaluating their view of Jyn and Cassian’s relationship. With Andor fleshing out the relationship between Bix (Adria Arjona) and the doomed rebel, including their baby glimpsed at the end of the Disney+ series, it seems highly likely Andor wasn’t falling for Jyn while they plotted to steal the Death Star plans after all. “People who thought that was the love of his life are going to have to reorient their thinking,” Gilroy joked. Want more io9 news? Check out when to expect the latest Marvel, Star Wars, and Star Trek releases, what’s next for the DC Universe on film and TV, and everything you need to know about the future of Doctor Who.

It's been a rough week for Bungie, with the Destiny developer hit by plagiarism accusations for its upcoming extraction shooter, Marathon — here's all we know so farTech11:15, 19 May 2025Marathon's art style has come under fire from a Scottish artistDestiny 2 developer Bungie has been busy in recent weeks, revealing a reveal a series of expansions for its popular shooter, while also unveiling the first gameplay reveal of its Marathon reboot.While the latter has drawn plaudits for its art style, it has now emerged that much of it is built using assets from a Scottish artist, Fern Hook who goes by the moniker 4nt1r34l.‌“The Marathon alpha released recently and its environments are covered with assets lifted from poster designs I made in 2017,” Hook explained on X (formerly Twitter) last week.‌“Bungie is of course not obligated to hire me when making a game that draws overwhelmingly from the same design language I have refined for the last decade, but clearly my work was good enough to pillage for ideas and plaster all over their game without pay or attribution.”Content cannot be displayed without consentBungie has confirmed the accusation is correct, suggesting a departed staff artist was responsible for using Hook's art without her permission.Article continues belowOn Friday's Marathon developer stream, the game's art director Joseph Cross is working to review the in-game assets and remove "inappropriately sourced" designs, while saying that Bungie has reached out to Hook to "do right" by the artist, but no details were given.“It came to our attention that an artist who worked on Marathon in the early stages of pre-production took a number of graphic elements from a graphic designer without permission or acknowledgement, and then placed them on a decal sheet that was then checked in in 2020,” Cross said (thanks, VGC).“The decal sheet included icon and text elements, which ended up in our alpha build. There’s absolutely no excuse for this oversight, and we are working on and are 100% committed to a review process to ensure that instances like this don’t happen again at Bungie.”‌Could Bungie's new game be delayed?A new report from Forbes over the weekend has suggested that morale at Bungie is low, following middling reception to the game's Closed Alpha."Sony and Bungie legal are now sorting through this and there is unlikely to be any much new information as all of this continues to unfold. It is not clear how long an “audit” will take of the assets to remove or find any more plagiarism, as it’s an expansive enough process to have Bungie not even show any footage at all in its recent livestream."‌"Morale is in “free-fall” across all departments, and “the vibes have never been worse.” Everyone has the same concerns about what happens to Bungie as a studio if Marathon bombs, which is something they absolutely cannot afford."Curiously, Forbes reports that there are no talks at the studio about a potential delay from the September release date internally, but this could be happening "privately between higher-up Sony and Bungie leadsership"/Bungie has reportedly needed to pull its plan to release a trailer in June, and the public beta in August may see big changes, too.Article continues belowIt's a concerning shift from the optimism around the game's aesthetic during the recent gameplay reveal.For the latest breaking news and stories from across the globe from the Daily Star, sign up for our newsletters.‌‌‌

For the 110 people working on Anno 117: Pax Romana, the upcoming city-builder from Ubisoft Mainz, every game in the franchise has led to its Winter 2025 release. The Anno series has had some hits and misses — its most recent game, 2019’s 1800, is widely considered one of its best, while future-focused titles 2205 and 2070 had mixed results. But Pax Romana has something for die-hard tactics players, beauty builders, and even newcomers like me: the franchise’s first-ever simultaneous release on PC and console, the reintroduction of land combat, the promise of finally bringing Anno to Rome, and major updates to existing game systems. Recommended Videos Some team members have worked on the series for 10, 15, or 20 years, know exactly what diehard Anno fans want (prettier palettes that take advantage of improved graphics, a greater variety of choice, more robust gameplay systems, and diegetic moments of hilarious catastrophe), and are determined to deliver. I travelled to Rome to be one of the first people in the world to go hands-on with Anno 117: Pax Romana and chat with creative director Manuel Reinher and game director Jan Dungel, emerging from the experience thoroughly jet-lagged and with a newfound appreciation for the series and the genre. Andiamo! A new Anno Anno 117: Pax Romana is the first game in the series since the beloved 1800, which was set during the Industrial Revolution. It’s also the series’ biggest historical leap backwards. The team didn’t want to set the next Anno game during the bloody, war-fueled throes of the Roman Empire, but during the height of a 200-year-long period of peace and prosperity.  “Our fans have asked for this for a very long time,” Reinher tells Digital Trends. “The power of Rome, it’s a very appealing setting, but we struggled because with Rome there’s a certain fantasy that is well-delivered, and delivered so often people have a certain expectation … We found Pax Romana is the playground for us, it ticked all the boxes. It’s almost 200 years of stability in the empire, peak growth … and it’s a good fit because conflict is not the core of the Anno experience.” U In Anno 117, you’ll play as a freshly appointed Roman governor in Latium, a province close to the center of the Empire, tasked with upholding that aforementioned peace and prosperity. Will you govern with an iron fist and hope that fear keeps the peace, or show empathy and kindness and pray to one of your chosen Gods that rival governors don’t step on your exposed toes? And then there’s Albion, the fog-covered Celtic lands where no “civilized” Roman dares tread lest they face the ire of the strange, savage locales. You can go there, as well (though I didn’t get to that during my hands-on), and decide what to do with the land and its people.  Anno 117: Pax Romana hopes to offer players deeper, more meaningful choices than any other game in the franchise. A massive discovery tree, with over 150 “discoveries” divided into three main categories (economy, civic, and military), will help “soften the linearity” players may have felt in previous titles.  Researching improved storage capacities can help you store more product to trade with neighboring provinces, while civic research allows you to explore different religions, or build new public buildings. And you won’t be locked to a certain branch on this discovery tree, you’re free to research paved roads, or learn Latin, or beef up your military presence.  Like any Anno game, 117: Pax Romana is centered around economic simulation with some traditional city builder mechanics and 4X strategy features sprinkled in. But 117 is bringing back a controversial feature players haven’t seen in the franchise in a very long time: land combat. Ub The team is pretty close-lipped about it during our preview, but confirmed Anno 117: Pax Romana will have both land and naval combat, with more depth when it comes to integrating the two, and the promise that only big, powerful cities can have a thriving military. But don’t fret — Anno is not a war sim franchise, and the team considers land combat to be “another choice, another tool.” Diplomacy could be your vibe, rather than wielding steel. Aside from gameplay features, the team wants 117 to be the “most beautiful builder gamer, period.” There’s a new day and night cycle that elicits some big “ooohh” moments, like when the flickering fires of the lucernae come alive as the sun sets, or when burgeoning cities are cut through with gorgeous lavender fields. The added ability to create curved roads allows for more freedom in city layouts, and the team’s attention to detail can be found in every pixel, from the waves breaking around a sailing ship to grain crops shifting softly in the wind. Ubisoft is excited to show people how multicultural ancient Rome was, how it pulled inspiration and even religions from Celtic and Egyptian lands, and how the expansion of the empire led to cultural exchange. “Religious ideas, technologies, resources, they travel from one province to the other,”  Reinher explains.  This ancient melting pot helped stabilize the empire. “People are surprised by that fact … This happened 2,000 years ago. Ideas travelled like this, and it’s a fascinating story that breaks the boundaries of what we all have in our minds when we think about such an economic empire.” Roman onboarding Ubisoft Mainz promises Anno: 117 Pax Romana’s gameplay experience is for both newcomers and old heads alike, thanks to an improved onboarding system. “Anno can be quite complex, but it’s rewarding step-by-step,” Dungel says. “You don’t need to completely understand the universe to enjoy [the games].” To describe sitting down to play an Anno game for the first time while surrounded by the cold stone walls of an ancient Romane estate as “surreal” wouldn’t do it justice. Overwhelmed by the game’s systems and in awe of the Horti Sallustiani (the gardens of Sallust), I worry I won’t be able to create an Empire my ancestors would be proud of. I consider lingering around the craft services table and eat as much olive bread (a staple of the Romane diet) to avoid embarrassing myself. But I have a job to do, and gawking at the marble structure soaring overhead won’t do me any good.  So I sit down, load in, and am immediately tasked with placing my governor’s villa somewhere on this newfound island that’s far enough inland to avoid getting attacked by coastal invaders, but central enough that it can easily connect to warehouses and other important commerce buildings. Ubi An in-game pop-up urges me to ensure that my villa is connected to another important building, but fails to tell me I have to build that second structure. I glance around, helpless, until someone comes over and walks me through it, just for me to immediately get stuck again because I can’t see a missing pixel of road that means the buildings were technically still not connected.  I let out a grunt of frustration. I am jetlagged and my brain is functioning at its lowest possible capacity. I need more olive bread. Soon enough, my Italian ancestors smile upon me. I start to get the hang of things after my little roadblock (teehee). I build a sawmill in the center of a forest to ensure we have a steady supply of wood, and place a collection of houses for my lowest class working folks probably a bit too close to the governor’s house for a man of his stature’s liking (I believe in solidarity across classes in my ancient Rome). I ring the workers’ homes with purple wildflowers, place a tavern and a market close enough to their quarters so that they buff everyone who lives there (which helps you earn more money faster), and send my sole ship out to treaty with a neighboring isle.  “[Building Anno 117] was a little bit challenging, because we have very different audiences,” Dungel admits. “Some people want to collaborate, they are super hardcore, they want to value share and network, but some people are more casual. For the first time, we decided we would try to find a way to please both of these groups, not make it less deep and less complex, but give an option for people who want to go more casual. That’s why you don’t have to deliver all the needs [requirements for every population tier that must be filled in order to progress] … you don’t have to immediately go to another province.” Ub Though I stumble at first, after about 1.5 hours of playtime, I have a tier 3 city sprawling out before my eyes, complete with soap production, ship-building, tunic and sandal makers, tilers, and a temple to worship our chosen goddess, Ceres, who helps boost our farms’ output. There’s a plethora of emergency services, including doctors, Vigiles Urbani (basically Rome’s NYPD), and firefighters, the last of whom successfully snuff out a fire that starts near my sheep pasture. I even have a massive new ship that can carry far more cargo than the one I started with.  But my city is net negative, and losing money fast. I get a loan, then another, then another, and then I start to panic. Despite my efforts, there just aren’t enough people to produce my much-needed products (the pretty lady on a neighboring island really wants tunics), or enough raw material for the people to form into something usable for the empire. I need to build more homes to get more able-bodied workers, but I don’t have enough lumber, and my island is looking more and more like a desert every minute.  Even the Anno experts next to me are struggling with their financials. “I can’t take another loan,” one player bemoans.  Before I can right my ship, the hands-on is over. I had just gotten my negative income out of the triple digits and was in the process of conquering another island that had some crucial resources (olives, mackerel), when we were given a times-up signal. “I was getting the hang of it!” I protest. “I just need more plebeians!” The Ubisoft dev who pulled me from the depths of dirt road despair two hours earlier laughs. He has just seen a new city builder player be born before his eyes. Anno 117: Pax Romana releases later this year for PS5, Xbox Series X/S, and PC.

Casa Sofia | © Zaickz Moz Casa Sofia, a recent project by AMASA Estudio, addresses the layered complexities of architectural intervention within Mexico City’s Colonia Roma, a neighborhood celebrated for its early 20th-century character but increasingly shaped by speculative pressures and fragmented land use. Just six blocks from Parque México, the house occupies a site caught between cultural significance and economic inertia. Originally built in the 1940s, the building underwent a series of unsympathetic interventions over the decades, most notably its conversion into office space. By the time AMASA Estudio began its work, the house had stood empty for over a decade. Casa Sofia Technical Information Architects1-7: AMASA Estudio Location: Colonia Roma, Mexico City, Mexico Area: 215 m2 | 2,315 Sq. Ft. Completion Year: 2024 Photographs: © Zaickz Moz, © Gerardo Reyes Bustamante The integration of contemporary elements can return life and functionality to the historic constructions of the area. – AMASA Estudio Architects Casa Sofia Photographs © Zaickz Moz © Zaickz Moz © Zaickz Moz © Zaickz Moz © Zaickz Moz © Zaickz Moz © Zaickz Moz © Zaickz Moz © Zaickz Moz © Zaickz Moz © Gerardo Reyes Bustamante © Zaickz Moz © Zaickz Moz Contextual Framework: Urban Fabric, Zoning, and Speculative Vacancy The architects were tasked with renovating and negotiating the tensions between preservation and contemporary inhabitation. Zoning restrictions in the area often preclude new development, inadvertently incentivizing abandonment and deterioration. Within this context, AMASA’s approach reclaims architectural value by demonstrating how adaptive reuse, when carefully considered, can simultaneously address housing shortages and preserve urban identity. Rather than erasing the building’s history, the project adopts a regenerative approach, rethinking the building’s typology and embedding flexibility into the spatial program. In doing so, Casa Sofia becomes a case study of how small-scale interventions can challenge speculative dormancy and reintroduce vibrancy to historic neighborhoods. Architectural Strategy: Inversion, Layering, and Programmatic Flexibility The architectural response centers on spatial inversion and vertical stratification. While the original commission envisioned a straightforward single-family restoration, AMASA Estudio identified the need for a more complex program to ensure viability and relevance. The result is a tripartite configuration: a ground-floor apartment, a flexible garage/commercial unit, and a redefined primary residence beginning on the first floor. This inversion of the conventional domestic hierarchy, placing private spaces on the middle floor and public functions at the top, is more than a pragmatic solution. It reflects a critical rethinking of domestic routines in dense urban contexts. The reallocation of living functions enables three degrees of occupancy: short-term rental, residential use, and commercial potential, each with independent access. At ground level, the vestibule becomes a threshold of coexistence. To the left is a compact yet complete one-bedroom apartment; to the right is a hybrid space adaptable as a garage or storefront; and ahead is the entrance to the main dwelling. The logic of flexibility is woven into every decision, resisting fixed-use zoning and instead proposing an architecture open to evolving modes of urban living. On the second floor, the public realm unfolds in an open-plan configuration that deliberately contrasts the spatial enclosure below. A continuous space integrates living, kitchen, and dining functions, culminating in a terrace that extends the domestic interior outward. This gesture, a horizontal void defined by operable walls, foregrounds the importance of architectural porosity in temperate climates. Light, Circulation, and Spatial Atmosphere Natural light is not merely admitted but orchestrated. A circular skylight punctures the ceiling above the staircase, casting vertical illumination along the building’s spine and subtly guiding the eye upward. It introduces a moment of tectonic tension, where the logic of light meets the logic of circulation. This vertical axis becomes the fulcrum of the spatial experience. The spiral staircase, painted in a distinct green hue, is not hidden but celebrated as an expressive sculptural form. It mediates the transition from compression to expansion, from the seclusion of bedrooms to the openness of the social level. Light enters primarily from above and laterally through folding window panels that open completely to the terrace. The absence of interior partitions on the upper floor allows light to wash uninterrupted across surfaces, emphasizing material textures and the gradient between inside and outside. In contrast, the lower levels, shaded and defined, offer a more intimate atmosphere, underscoring the designers’ sensitivity to light as both a spatial and emotional element. Casa Sofia Restoration Ethos Rather than defaulting to nostalgic restoration, the architects embrace a contemporary material palette rooted in coherence and restraint. The project does not attempt to replicate the past but defines a new architectural narrative grounded in contrast and continuity. The use of a singular green tone for all metalwork, staircases, doors, railings, and furniture introduces a unifying chromatic identity. This bold yet controlled gesture resonates against the subdued gray plaster walls, creating a dynamic interplay between reflection and shadow. The palette is neither flashy nor muted; it is precise, allowing light to animate its surfaces without overwhelming the space. Importantly, the intervention avoids decorative mimicry. Structural upgrades, new spatial logic, and minimalist detailing coexist with the building’s historical shell. This architectural restraint makes the original form legible while enabling new uses to emerge organically. AMASA Estudio’s broader practice often grapples with similar conditions: the friction between permanence and transformation, especially in urban areas burdened by regulatory inertia and socio-economic flux. Casa Sofia embodies this approach, presenting architecture not as a static form but as a series of spatial and material negotiations between past and present, regulation and imagination, economy, and poetics. Casa Sofia Plans Ground Floor | © AMASA Estudio First Floor | © AMASA Estudio Second Floor | © AMASA Estudio Section | © AMASA Estudio Isometric View | © AMASA Estudio Casa Sofia Image Gallery About AMASA Estudio Credits and Additional Notes Lead Architects: Andrea López, Agustín Pereyra Design Team: Cesar Huerta, Gerardo Reyes Client: ECOBIART Inmobiliaria Construction: Erik Cortés Ortega Structural Engineering: Juan Felipe Heredia Installations Engineering: Germán Muñoz Lighting Design: Andrea López, Agustín Pereyra