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Verizon Business Starting Price for LTE Business Internet 25 Mbps Unlimited Data Plan with select Verizon Business smartphone plan savings terms app. Bloomberg Audio Studios Podcasts radio news. Bloomberg Tech is live from coast to coast with Caroline Hyde in New York and Ed Ludlow in San Francisco. This is Bloomberg Tech. Coming up, all eyes on on Nvidia earnings after the closing bell. Investors expecting to learn more about where those billions of dollars on spending are actually going. Plus, Nvidia CEO Jensen Huang and Tesla CEO Elon Musk are speaking right now at the US Saudi Investment Forum. We'll bring you the latest. And Brookfield asset management targets $10 billion of fund commitments for a global infrastructure program in partnership with, you guessed it, Nvidia and Nvidia dictates trade. Right now we are seeing signs of stability in the NASDAQ 100. More broadly, I remind almost $2 trillion been wiped off of this benchmark since the end of October in large part because Nvidia has been down. But all the key MAG7 names have been under pressure. But today, some reprieve in video in the points perspective helping with the NASDAQ 100 crypto. Though still in the eye of the storm, off by 2.8%, the anxiety driving it below $90,000. So still some risk aversion. Okay, Nvidia is up more than 2 1/2% off its session high. It is a stock that's up almost 40% year to date, outperforming double the performance of what we've seen of the Nasdaq in S&P 500. The expectation is revenue growth above 50%, net income growth above 50%. But all that matters is what CEO Jensen Wong tells us about the future. Let's get with Bloomberg's Ian king who leads U.S. semiconductor coverage. I mean, that's what it comes down to. Either they will beat consensus or they won't. But expectations are really high for this quarter, as is the skepticism of what's happening. Bigger picture we're seeing with data center infrastructure give us the things we need to look out for. And what's in your preview of this, this company's earnings? Yeah, I mean the numbers speak for themselves. Right. We're looking for a prediction in the 60 billion range for revenue. And just to give that context, that's 10x where we were three years ago. 10x. Okay. On profit for this year, we're going to be looking at.00 billion of net income. That's more than intel and AMD get in revenue combined. So the numbers have come off the charts that the key here is we all know the numbers are going to be good. We know the forecast is going to be. But the key is, well, do we really believe the basis for those numbers? And that's going to be the key question he's going to face. So in what can his response be? That's more than what he already signaled in gtc, that he has line of sight on half a trillion dollars worth of orders. Not a Blackwell, but Rubin into 2026. How much more can he signal that they will remain integral to inference as well as training. No, you're absolutely right. He's essentially played all his cards in that respect. What's going to happen will be that the investment community are getting their first chance to sort of pull, pull that apart, to ask him about the details, to ask him about the new products, to ask about the margins, to ask about when exactly these sales will kick in. And we haven't, they haven't really had that chance. So that's what they'll dig into today. And his response is how precise he is, will condition the risk, how they feel. There are some real concerns and there are some real questions from video. Some of those will get to pose this evening to gentleman self. There is the idea of depreciation on older chips and circular financing. That's just not going away. Absolutely not. I mean we saw a deal announced with Anthropic yesterday, big commitment to use a lot more of Nvidia's chips. But guess what, Nvidia is putting $10 billion to work in that company over time. So yes, that concern is absolutely not going away and if anything it's going to accelerate until we get a clear outcome. Bloomberg's inking who will be across all those earnings after the bell alongside Ed. We so appreciate it. Meanwhile, look, we know Wall street is eagerly awaiting Nvidia's results for a clearer picture on spending because it impacts the whole rest of the market. Bloomberg's US equities reporter Carmen Reinecke is here to just bring us the context. We know the questions could be asked of Nvidia, but. But what does it signal about the commitment of the magnificent seven of the key hyperscalers and more broadly, the rest of the trade? Yeah, so this is a huge moment for the trade. I think a lot of people are really looking to in video and the stock's reaction to sort of decide the next direction of where the market, the entire market is going to go. You know, Nvidia is the largest weighting in the S&P 500 and the biggest name in AI. And what we also know about Nvidia is that its biggest four clients are some of the other Mag7 members. So we're going to see where their spending is flowing. It's still flowing to Nvidia and how much. When I was reading your, your piece which you co wrote with Ryan for Selica, the data is really interesting. Is me a big part of the Bloomberg tech audience that don't know some of that. So you just talked about waiting. Right. Nvidia is about 8% of the S&P 500. That's a factor you also looked at in videos multiples relative to the index level, the NASDAQ 100, for example. What are the Other key data points that have us on such edge ahead of the earnings report later this evening. Well, you know, as Ian said, I think a lot of people are really looking at the forward guidance. You know, Nvidia is expected to continue to grow revenue even though that growth is expected to slow in the coming years. I think the other thing that people are really looking for is what Jensen's going to say about what they're seeing in the future. Right. Also, as Ian pointed out, the guidance is very important here. And that's, I mean, probably even more important than the numbers that Nvidia actually reports. We want to see the line of sight into revenue growth going forward. There are also still some questions about China, how much revenue can be expected there or not. And so I think the sentiment here, what investors take away about their confidence from the report is going to be maybe even more important than the actual numbers. Three most common rein. It's a great story. Thank you very much indeed for bringing us the data as well. And now we bring you the investment perspective. Martin Norton's here with us, chief investment strategist of Empower, which administers more than $1.6 trillion in assets. And that's about the same amount that's been wiped off the NASDAQ 100 since the end of October. Yes. Is there room to the downside here or are you thinking there's some sort of relief rally from any data we get from, from Jensen later? Well, I don't think you can ever count out a relief rally. But what I come back to when we look at the price action that we've seen over the past few weeks is that we have, we have taken some froth off the top, but we're not looking at really attractive valuations at this point. We're still at elevated valuations for a lot of these names. And what's interesting, and Ed alluded to this, you know, the questions that people are raising in the current environment, I don't think they're necessarily going to be conclusions exclusively answered within videos report. Right. The depreciation question, the demand question, you know, extending to the rest of the economy, I think those doubts are, are with us, which would mean potentially more volatility. Well, if Jensen can't tell us how long his GPUs are going to last and what the depreciation of them are, I'm not sure anyone can. But you're so right that that has been, again, an argument about why perhaps the valuations are flush. But you look at Nvidia trading about 30 times future earnings. That's not that elevated. So is it the rest of of the trade that the Palantirs or perhaps some of the energy stocks that have risen to extraordinary degrees? Well I think you raise a good point. It's not that elevated especially if you're focused on that right side of the probability distribution. If you're looking at a full probability distribution and you come to the conclusion that I don't know if I share but some folks are raising hey this isn't as transformative as people have suggested it is. We're not going to see every application take off the way people suggest it would. Then I think there is room for some of these stocks to come down. Now I'm not sure I share that view. I tend to believe that the supercycle is real, that it is going to have a pretty profound impact on the economy. But we have to make room for the full range of outcomes when we price these things. Marta, it's great to have you back on Bloomberg Tech as is quoted in that that well read story on the Bloomberg terminal on bloomberg.com from one investor. This is a quote so goes Nvidia, so goes the market kind of report from, from your desk and your perspective. Is that the situation here? Well I think there's no question that this is a capstone report. It's a macro indicator and it I think has the potential and you see that in pricing around it. Right. This idea that you could have swings up to 7% either way. I think this is the kind of thing that people are really going to key off of. My, my, my question is whether this is going to answer all the AI doubts that that are out there or whether it's just going to arrest them for now. But we're still going to be wrestling with some of these questions going forward. Depreciation is the most common concern or question that I've received for Jensen so far. You know, getting out to people and said what would you ask? There are people that look at the depreciation issue and say how can I model for that impact on the balance sheet of those key customers of Nvidia? But others on, on social media are talking about a different data set set which is utilization. If Those older generation GPUs are running at 100% that's a really good problem to have. Right. This is kind of very specific. But those soft data sets that your team are looking at to work out what on earth's going on. Well you know I think the thing that we're focused most on as we turn our gaze to 2026. Is this question in particular about the capacity build that we expect in 2026 and frankly in 2027. So our view is that, you know, we're going to have these questions to your point about utilization, about depreciation, but our view is that those questions are going to linger as we build out the capacity for AI in 2026 and 2027, because there is so much that you have to put in place to be able to see the demand come through. And so for us as we go through 2026, we're going to be watching, of course, like everybody else, are we seeing that capex is the conviction still there to build out the massive infrastructure that you need for AI? And I think that's the key question that we're wrestling with. It was interesting that you said you don't align yourself with the negativity on actually applications of AI. You do think the super cycle is real. What data set are you looking for that? Because we do have the MIT pilots aren't working. There's always a counter example for every time there's a negative. But Bloomberg Intelligence had some great analysis out showing that actually only 10% of companies at the moment, or people surveyed are saying that they're using generative AI for revenue or for new products. Right. I think there's still an, I mean, first of all, if you take a look at kind of adoption rates for the cycle relative to the Internet and things like that, people are pointing out, the Federal Reserve and others, that you've seen a much faster acceleration of adoption. But to your point, we're still very much early days. And so I think one of the things that we look at is just at the earnings season themselves and looking at what companies are saying. And a lot of the commentary around AI at this point is still very generic. It's not very specific in terms of how AI is actually transforming those businesses. And I think also watching to see how earnings in the broader economy are responding, are you starting to see those cost savings come through, which I think is of course the first leg. And then ultimately you'd also want to see the revenue which we're seeing from the hyperscalers. But I think those, you know, that real world application is really what we're going to be keying off of. And I think it's going to take time. I think you still need to build that capacity to see the earnings impact, broadly speaking. Matto. So it's great to have you in. Good. Thank you for coming to the Studio Martin Orton, of course, there of Empower. Meanwhile, Nvidia CEO Jensen Huang is already on stage ahead of his earnings publication, of course. Meanwhile, Tesla CEO Elon Musk alongside in DC as part of the US Saudi Investment Forum in Washington dc. Take a listen. And His Royal Highness announced the AI Strategic framework and partnership. Today. We're going big with Elon and Jensen, so thank you for those opportunities. Now they told me I have time for two last questions. So last night at the dinner I got a number of questions because it seems that the schedule leaked and everybody was giving me hints about the last two questions I'm going to do. So the first one was for you, Elon, and there's a big one for you, Jensen, so prepare for that one. AI in space, Is that possible? Yes. If civilization continues, which it probably will, then AI in space is inevitable. You know, I always have to like, preface that, you know, we shouldn't take civilization for granted. We, we need to make sure to take care to ensure that civilization has an upward arc. I mean, any student of history knows that civilization does not always have an upward arc. And in fact, civilizations have life life cycles. So hopefully we are in a strong upward arc. I think we are for now, but we don't want to take that for granted or be complacent. But in order to. The way to think of AI in space is that in order to achieve any meaningful percentage of a Kardashev 2 scale civilization, where you're using even a millionth of the sun's energy, you must have solar powered AI satellites in deep space. So once you realize, like, once you think in terms of a Kardashev 2 scale civilization, which is what percentage of the sun's energy are you turning into useful work? Then it becomes obvious that space is overwhelmingly what matters. Overwhelmingly. The sun only receives roughly 1.2 billionth of the Earth only receives roughly 1,2 billionth of the Sun's energy. So if you want to have something that is, say, a million times more energy than Earth could possibly produce, you must go into space. And so this is where it's kind of handy to have a space company, I guess, sell the book Easier to Cool Chips in Space too. Yes, Easier to cool chips in space, yes. There's definitely no water in space. So you're going to have to do something that doesn't involve water. Just hang out. Well, it's just got to radiate. That's right. So my estimate is that actually that the cost of electricity, like the cost effectiveness of AI in space, will be overwhelmingly better than AI on the ground. So long before you exhaust potential energy sources on Earth. Long before. Meaning, like, I think even perhaps in the four or five year time frame, the lowest cost way to do AI compute will be with solar powered AI satellites. So I'd say not more than five years from now. Wow. And just look at the supercomputers we're building together. Let's say each one of the racks is 2 tons. Out of that, 2 tons is 1.95 of it is probably for cooling, right? Oh, yeah. Just imagine how tiny that little supercomputer is, Right? Each one of these GB300 racks would just be a little tiny thing. And just electricity generation is already becoming a challenge. So if you start doing any kind of scaling for both electricity generation and cooling, you realize, okay, space is incredibly compelling. So let's say you wanted to do, I don't know, 2 or 300 gigawatts per year of AI compute. It's very difficult to do that on earth. So the US average electricity usage, last time I checked was around 460 gigawatts per year average usage. So something like, say if you're doing 300 gigawatts a year, that would be like 2/3 of US electricity production per year. There's no way you're building power plants at that level. And then if you take it up to say, a terawatt per year, impossible. Like you have to do that in space. There just is no way to do a terawatt per year on Earth. And in space, you've got continuous solar. You actually don't need batteries because it's always sunny in space. That's right, exactly. And the solar panels actually become cheaper because you don't need glass or framing and the cooling is just radiative. So that's why I think that's the dream. Yes, that's the dream. So, Jensen, everybody, last night was asking and I'm mindful it's earnings call for you today. So I'm going to say this delicately. Everybody has been asking me to ask you, are we going to have an AI bubble? That's the last question. All right, let's. All right, well, let me just tell you what we see. Okay? So I think it's really important when you look at what's happening around the world and go back to first principles of what's happening in computer science and computing, there are three things that's happening. The first thing is that we all know that Moore's Law has run its course and the ability that the amount of demand for computing versus the amount of computation we can get out of general purpose computing is really challenging. And so the world's been moving to accelerated computing for some time. We've been pushing this now for some over 20 years. Let me give you one statistic. I was just at supercomputing. Six years ago, CPUs were 90% of the world's supercomputers, top 500 supercomputers six years ago. This year less than 15% went from 90% to 10%. And meanwhile accelerated computing went from the other way, 10% to now 90%. Okay, so you're seeing that inflection point, the transition in high performance computing from general purpose computing to accelerated computing. Well, one of the most data intensive, one of the most intensive computation things that the world does in cloud is data processing. Several hundred billion dollars of computation is done on just raw data processing. Had nothing to do with AI, just SQL processing data frames. You know, everybody's names address their sex, their age, where they live, you know, how much money they make. All of that sits into a data frame. And that data frame drives the world today, whether it's a, in banking or whether it's in credit cards or of course e commerce. And everything from ad recommendation, everything is driven off of that data frame. That data frame costs hundreds of billions of dollars to go compute. And so that's the number one thing end of moore's law. The second thing is generative AI. The most important application of the last 15 years is called Rexis Recommender Systems. How do we know what information to recommend to us in a social feed? How do you know what ad to recommend to somebody, what book to recommend, what movie to recommend? The world is. The Internet is so gigantic without a recommender system that a little tiny phone of us will have no chance of ever seeing the right information. That Rexis is the engine of the Internet today that's going generative AI. It used to be running on CPUs, now it runs on GPUs, which then says the third thing when if you just look at those two applications, many of the Internet companies can build enormous number of GPU supercomputers just doing that. Of course then it creates the third opportunity on top of it, which is agentic AI. This is Grok and this is OpenAI. This is anthropic, this is Gemini. Agentic AI sits on top of that. But don't forget to think about what is happening above. Underneath what everybody sees as AI today, there's a whole movement of computing from general purpose computing to accelerated computing. And that if you just, if you take that into consideration, you'll come to the conclusion that in fact what is left over to fuel that revolutionary agentic AI is not only substantially less than you thought and all of it justified. Well, I was just informed by the team that my boss and your bosses is going to talk next. The honorable President and His Royal Highness the Crown Prince. And hence we ran out of time. But in essence, this is such so much love for you Elon and Jensen, but this in essence is a 92 alliance that shifted from energy to digital to the intelligence age. Powered by pioneers such as Elon and Jensen to serve humanity and create on a net new basis, new economies, new jobs and a better future for humanity. Powered by the Kingdom of Saudi Arabia and the United States. Thank you for a lifetime partnership and friendship. Thank you, Elon. Thank you Jensen. Thank you. That was Elon Musk speaking alongside Nvidia CEO Jensen Huang at the US Saudi Investment Forum in Washington D.C. probably Caroline. The biggest piece of news that came out of it was Elon Musk confirming that XI is going to do a 500 megawatt data center in the Kingdom of Saudi Arabia in partnership with Humane. That's a story that we broke actually back in July. So we had a sense that it was coming. But it's confirmation, confirmation of course all eyes on really the access that Saudi Arabia has to the latest greatest chips and what they're able to continue to export out of the United States to Saudi Arabia to Humane to be able to use on the ground when it comes to Blackwell. And of course we're going to hear so much with your interview later today Ed on details of an AI bubble, the vindication there that we're starting to hear from Jensen as to already the cpu, the GPU necessities when it comes to just our social media desires, let alone what's happening with the genting I yeah we should probably point out the obvious to our audience that Nvidia reports earnings after the closing bell. Jensen Huang is an experienced executive to say the least and he probably thinks to himself what can I or can I not say during the course of this conversation? But a lot of his final answer there was repetition about the idea that as we move from the balance of workloads being inference, having previously been training that is his evidence base for this big build out in AI infrastructure to continue and I think more broadly as well, they were going into the realms of imagination, a realm of imagination that I've heard time and time again, we've heard it from Sundar Pitcher, we've heard it from Jeff Bezos. Now we're hearing from Elon Musk about the idea that actually the energy limitations are far less in space. And this is why suddenly you're hearing a lot of these executives talking about how we might be building, building data centers not on this earth, but in, outside of the world at the moment. This is an interesting sort of way, diversion perhaps of talking about the cost of energy that seems to be going up and to the right here in the United States. Yeah, in space you can put solar panels on satellites and you can use radiation to do cooling. That seemed to be the point that Jensen Wong and Elon Musk were making. As if by magic, in the time that we've been speaking, Bloomberg Senior Tech Executive Editor Tom Giles has appeared on set. I mean, it's a big moment, right? If you have the world's richest man sat alongside, let's be honest, probably the most important person in global technology, you're kind of bracing for news. The news that I saw was confirmation of something we reported that say I doing something in Saudi Arabia. That's right. It's yet again evidence of these, this huge need for data centers and computing capacity, which is what they were talking about from beginning to end. And this is how XI is going to take part in it. This is how Elon Musk and his empire are going to take part in, in ensuring that we have the capacity that we need to fuel all of these services, especially the ones that XI is providing with grok. All of this, Tom, hinges on access to compute and to gpu. How are we unfolding that story as a newsroom at the moment of Humane's access to the latest Nvidia Blackwell architecture and more broadly, how we see the relationship for the demand of data centers to be built out in Saudi Arabia rather than here in the United States. Yeah, Caroline, I was just in Saudi a couple of weeks ago and the thing that I, one of the things that I took away from that was this urgency to find sovereign AI, first of all, all ensure that each region of the world has the computing that it needs. I also saw the urgency of these relationships between US based companies and sovereign wealth funds and in partnership with the Saudi government and other governments throughout that region. And the idea is that there's going to be a lot more partnerships, you're going to see a lot more collaboration. Humane is this company that just came out of nowhere, affected few months ago and really does seem to be wanting to take a play a big role in this data center build out. Tom, before we let you go, there is also this issue of reciprocity. So for example, there's all these projects announced in Saudi and other Gulf states. But the United States government I think is very hopeful that those titans of Middle east finance will also put the equivalent number of dollars into the United States itself. That's right. They want to see, they want to jointly invest in the region. They want to see countries from around the world, particularly this region, oil rich region, also making investments and showing that the US Is a place to invest. You know, this administration wants to send the message that we're open for business and that we're here to build jobs and we're here to bring some sort of manufacturing and technology dominance back to the United States. Bloomberg Senior executive editor Tom Giles, thank you very much. Don't forget to tune in this afternoon. We have an exclusive interview with Nvidia CEO Jensen Huang following the company's earnings. Print that conversation around 6:30pm Eastern time. Okay. Coming up, Pooja Goyal from Carlisle joins us to talk about infrastructure spending from a very different side of the table. Very much looking forward to the this one. It's half time. We'll be right back. This is Bloomberg Tech. For every six Chinese people, there's a Ping an customer. We have accumulated a massive amount of the customer data, not just on the financial side, but end to end across channels thanks to our AI advancements. This is the technology Empowered growth at Ping an podcast. In our latest episode, Ping an is utilizing technology to provide integrated and personalized 24. 7 support for China's rapidly growing elderly population. Now available on Spotify, Apple Podcasts and Ping ads website. Here's a paradox. We buy insurance for peace of mind. Yet the very policies we trust can deliver the biggest financial shocks. Across America, millions of claims are denied every year, not because people did anything wrong, but because policies quietly excluded the things that happened. The psychology of trust tells us we assume the contract is fair. But in insurance, the information gap is massive. The insurer knows every detail of what's coming covered. The policyholder rarely does. That's where my policy advocate comes in. For just 27 cents a day, their platform reads your policies and shows you in plain language where you're vulnerable. They're not selling insurance. They don't do that. It's about transparency, giving ordinary people the same understanding insurance companies have had for decades. Because when you know what's really in your policy, you can plan, protect and avoid surprises before you trust your policy to protect you. Let my policy advocate tell you what it really says. 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Learn more@chase.com business chase for business make more of what's yours the Chase Mobile app is available for select mobile devices. Message and data rates may apply JP Morgan Chase Bank N A Member FDIC Copyright 2025 JP Morgan Chase & Co. Welcome back to Bloomberg Tech. Nvidia is the super bowl moment today. Earnings after the bell. The stock up more than 2% off its session high. It is a stock that's up almost 40% year to date and there are very high expectations. But there is also very high skepticism about what is happening in this infrastructure build out. We'll continue to track it throughout the hour. It is the big one, but one big big move. It's the upside. Is Alphabet, parent company of Google shares trading at a record high on track for their biggest jump since about mid September. Yesterday Gemini 3 was released. An executive saying that this is a big jump in the model's abilities for reasoning and coding. This seems to have been some kind of delayed response in the stock. You know you did see others like Sam Altman of Open Air, even Elon Musk on social media congratulate Google on what they've achieved with Gemini Free. Now that's playing out in the shares. Carrie. It is. And What a cool 140 billion being added in terms of market capitalization. We're up at more than three and a half trillion for Google. Now let's break down though what this so called Gemini leap means. Mandeep Singh is with us, Bloomberg Intelligence Senior Tech Analyst joining us. Is it a big leap? It is. And when you look at some of the benchmarks they showed in the paper around visual reasoning, I mean everyone has been focused on multimodality. This was the true kind of model where you could see multimodality in action in terms of, okay, we can do code. The model can also do image generation and visual reasoning, which is what you see in vemo. I mean when I think about, you know, why they are so successful with Vemo, yes, they have been doing it for the longest, but also some of it is AI that's coming from their models. And I think that was reflected in the paper and look at how far they have come in the past two years from that botch bar loss launch to now Gemini 3 model being a frontier model, so really well executed. And I think it was all on TPU's. That's the other thing. Right, right. When video GPUs used for training, which everyone still relies on Nvidia for training. So that's, that's a big leap. Mandy, this, this is interesting. We were reading your research this morning. I think we're going to bring it up on the screen. So you're basically saying that if this is evidence of the success of the tpu, Google's custom chip that might free up Google Cloud or GCP to take their Nvidia allocation and then put it to work for customers, which is a good thing for their cloud business when it comes to external facing customers. That's right. And so look, Google is still buying Nvidia chips. In fact they are one of the top three customers for Nvidia. And so when I look at, you know, how everyone is using their Nvidia allocation, some of the workloads are training. In fact for Metta, everything is being consumed inside, you know, Meta with the family of apps for training and for inferencing and recommendation systems. In the case of Alphabet, I mean given everything internal is running on TPU's, Google Cloud is where they deploy a lot of the Nvidia allocation, whether it's the latest Blackwell or the latest the prior versions. And that's where you can rent it, you can generate revenues same way as new clouds are doing it. And so from that perspective, I do think that cloud revenue could get a lift just because they have more availability of Nvidia GPUs over there. I really recommend you go read that research if you're a terminal client. If you're not, maybe I'll post it on the social medias later. You just heard Mandeep Singh of Bloomberg Intelligence break it down. Thank you very much. AI infrastructure. Infrastructure spending news keeps Rolling in. Brookfield Asset Management is teaming up with Nvidia, but also Kuwait's wealth fund, targeting $10 billion of commitments for a program to build global infrastructure. The big plan is to acquire up to $100 billion of datacenter energy and other assets. I want to discuss with Pooja Goyal. She's the partner and chief investment officer for Carlyle's infrastructure group. That's just a piece of news, but the structure of it is a really interesting case study for what's happening right now in infrastructure. A financing arm getting commitments for a fund partnering with some of the players in video in the technology case and then saying over a course of time we're going to go out and buy these assets. How do you make a response to that? How do you react to that? Well, first of all, Ed, thank you for having me on your show. And look, from our perspective as infrastructure investors, we have a thesis driven approach to investing in infrastructure assets and a longer term time horizon. And we do believe that AI infrastructure is a significant investment opportunity for us. Now you're at Carlyle. We are developing over 20 gigawatts of data center capacity, primarily hyperscale data center capacity. But we aren't just developing these assets in isolation. We have taken a much more comprehensive view where we are looking across the value chain for air infrastructure and we are making sure that we're developing these assets with that comprehensive lens. So that means absolutely developing data centers, but also addressing one of the most significant bottlenecks when it comes to data center development, which is access to power. Look, you had a little bit of a snapshot where you were watching Elon talk about AI and he was talking about access to energy being the one most significant bottleneck. The way we are developing AI infrastructure is that we are building these large scale energy campuses where we have power generation capacity that's co located next to this data center capacity. That's, that's Copia Power. Am I right? This is actually something that you formed. I was reading about the release back in 2021. It was a new portfolio company that's just building out in terms of a platform nature. These campuses, the scale is extraordinary. What was interesting was back in 2021, it was all about sustainable infrastructure. It was all about renewable power sources. Is that realistic now when we think about the energy necessity? Yeah. I mean, Caroline, you're absolutely, absolutely right. From an energy perspective, you need to take an all of the above approach. So absolutely you need solar and storage, but gas is a very important part of the solution. As well. Look at Copia for example. We think of datacenter development as building large campuses. And a campus is basically like a mini city that has multiple gigawatts of power generation capacity. This includes gas, solar as well as storage. That capacity is connected onto the grid. And located right next to that power generation capacity are hyperscale data centers that are also connected to the grid. So I'm not talking about building islands, I'm talking about building a fully integrated city or a campus, which is a better term for it. And by doing that, you're making sure that data centers are getting access to to power in a more timely manner. Remember, timing is very important here and that power is actually cost effective. Cost and economics matter a lot. But more importantly, it's also more reliable power. Everyone's talking about 5, 9 reliability, which is 99.999%. In order to do that and build long lived infrastructure assets, that reliability is just a very important point. So at Copia, for example, we have a site that we're building in Arizona. It is about two times the size of Manhattan. Once that site is fully built out, you're talking about $30 billion in capital investment between the power generation assets as well as the data center assets. And then Copia has another five campuses in the west behind that. So you want to make sure these campuses are located it close to where there will be demand for compute power. But you also want to make sure it's going to be cost effective, delivered on time and also reliable. I wish we had more time. Absolutely fascinating. The size and the scale. Puja Goyal, come back soon. Tell us how these campuses are evolving. Chief Investment Officer for Carlyle's infrastructure group. We thank you. Let's just turn attention to Nokia now which is also streamlining its business to focus on the networking infrastructure that can connect all of these data centers. Nokia CEO Justin Hotel spoke with us earlier. With AI, the market is going to change dramatically. It's already changing in a data center which is a part of our business. You know, we're building AI factories. Obviously Jensen talks a lot about this. I know Nvidia has earnings later today, but we're connecting data centers to each other and building massive AI factories that's using our optical technology, it's using our IP routing technology. And where's the future head headed? The future is headed to physical AI, robotics, autonomous vehicles, delivery drones, AR VR, you know, glasses, more and more devices. And fundamentally that means our networks need to change to handle that. And that's what we're Planning for and anticipating to seize that opportunity. Can you briefly describe the growth opportunity here and how the profile, the growth profile of your company will change as you make this shift? Yeah, look, I mean today you see, you see the pockets of growth that we have in the fixed infrastructure. And as we see this build for AI native networks going into mobile, we're going to see tremendous growth there. It's just not coming in the next few years. We believe it will come over the longer term as the market invests and builds, but it's not going to be in the next couple of years. So really think of our business in a couple of ways. Capturing growth and fixed infrastructure today and then in mobile infrastructure, positioning the business for technology innovation and longer term growth as that market picks up. What industries do you expect to be most dominant? And are there particular industries that you think will be fastest to adopt the AI connectivity that you're hoping to provide? Yeah, I think there's a few things. First of all, you know, there's no question that the core tech industry that we're in today is the engine of growth, right? AI and cloud customers, hyperscalers, cloud providers, and that's of course serving the technologies we have today, LLMs, you know, AI agents. But when we look ahead, I see it being in areas like transport and logistics and manufacturing. Physical AI also an area that we already serve, that we call mission critical enterprises. Think of public safety, rail transport, these are places where AI can add better reliability, better security, better outcomes for people. If you think about public safety, for example, emergency services. And those are areas where I think we'll see fast, you know, we'll see faster AI adoption. But I don't think we can, you know, we can predict the future perfectly. We need to just anticipate what are the use cases and the needs. It may be that, you know, delivery drones, other retail applications also accelerate and those are early users. So for us it's about building the plumbing and the core capability that we need. That was Nokia CEO Justin Hotard. Okay, coming up in earnings reports, investor presentations and company memos, executives have been touting efficiency gains from AI and pointing to the tech for shrinking or flat workforces. We have more on that next car. Meanwhile, we're watching a deal that has sent semrush holding shares skyrocketing 74%. Adobe agreeing to buy the marketing platform. First takeover announcement, of course, since its failed acquisition of Figma. It's an all cash deal, $12 per share. This is Bloomberg Tech. Here's a paradox. We buy insurance for peace of mind. Yet the very policies we trust can deliver the biggest financial shocks across America. Millions of claims are denied every year, not because people did anything wrong, but because policies quietly excluded the things that happened. The psychology of trust tells us we assume the contract is fair. But in insurance, the information gap is massive. The insurer knows every detail of what's covered. The policyholder rarely does. That's where my policy advocate comes in. For just 27 cents a day, their platform reads your policies and shows you in plain language where you're vulnerable. They're not selling insurance. They don't do that. 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They work hard 24 by 7. You don't have to pay them and they don't eat any lunch and they don't have any health care benefits. So they're very affordable and that really complements our workforce. Just a few who've been hearing about AI's impact on the workforce. Increasingly executives have been laying the blame for job cuts at technology's feet. Bloomberg's editor for news, Seth Fiegeman joins us now. And Seth, I'm hearing the term AI Washington. Is it actually that is to blame for these job cuts or is it it's a nice excuse but actually they overheard in Covid and this is a good way of announcing job cuts. You know, I think it's a little bit of both. I mean first off, to step back, we're seeing a real shift in how we talk about this. Even six months ago, a year ago, companies were pretty sheepish about saying I had anything whatsoever to do with cost cutting, headcount reduction because I think no one wanted to be the poster child for massive job displacement, unemployment. Nobody wanted that back. Headline Something has shifted in the last six months and I think it comes down to one, we are in a bit more of a difficult macroeconomic environment where companies1 have more reason to be cutting costs and potentially I improving against that backdrop is going to be a perfect storm for those cost cuts. But two, it's a little bit easier probably for investors to say it's AI than to say we over hire. We're a bloated workforce, we're dealing with outdated technologies. Let's just say AI. I Seth, in terms of a poster child, or maybe a better phrase, a case study, you have Amazon, right? So in June, Andy Jassy signalled or said, you know, that this would happen long term because of AI. But then more recently when Amazon actually did job cuts that was not the messaging. That's right. I think he came out there and said, well, you know, not yet, you know. And I think that the Amazon cuts maybe speak to a different phenomenon that's very tech specific, which is that we're seeing a lot of tech companies do significant cuts and some of that is because of over hiring during the pandemic, to be sure. But also these same tech companies are reallocating substantial resources to compete in the larger air race. And as a result of that, they're trying to trim and be more efficient in other parts of their businesses. So AI is a part of it, but it may not just be because chat bots are taking people's jobs. There is data we can reflect on, on. I think that New York State is the first state that said when you make big layoffs, you've got to say whether it's AI, automation related. We're seeing in the Challenger gray and Christmas numbers, 31,000 jobs were sort of I sacrificed in just October alone. That's right. But again, the challenger stuff is also based on how people, how companies are representing that publicly. To your point though, I think other states are trying to emulate the New York legislation. We would love nothing more than greater transparency on this front because I think there's a lot of fear, there's a lot of misinformation and that will help us really sift back from fiction. Bloomberg. Seth Figman, thank you very much. Let's get to another top story Matter has secured a key legal victory against the Federal Trade Commission. The FTC alleged the company's purchases of Instagram and WhatsApp violated antitrust law. A judge didn't agree. Bloomberg's Riley Griffin joins us with the details. I think let's start with the basic legal reasoning that the judge gave. What was the decision based on and what happens? Well, and you have to remember that when the FTC first launched this lawsuit, that was five years ago, that was Trump 1.0. The social media landscape has changed drastically since then. And that was really the reasoning behind his ruling. The FTC had argued that me, we and Snap were its only competitors. And you and I have seen spoken plenty of times about what TikTok is doing to Met as market share. That's what Judge Boseberg said as well. And then Meta gets up and says, see, we have got so much competition, it's fierce out there and continue to tackle it. It's an interesting sort of argument to have to make to your investor base, your employees, that you are under threat in some way. It's such an important point, Caroline, because really this win is also a warning. Looking forward, Meta is going to have to grapple with Judge Boasberg's comments, which are that it is not differentiated from its competitors and that tick tock is eroding its market share. This is probably the most difficult question, but what happens next is that just it now it's all done or there are some changes that matter has to make or there will be more legal challenges down the road. So we've been speaking with analysts. Nobody expects the appeal process to proceed seed, but we're going to wait and see. Really. This means that Metta doesn't have to spin off Instagram or WhatsApp. That was the overhanging threat, but a big win, one that was really priced in. Analysts had expected Matter to to take the w here. Bloomberg's Brady Griffin has been all across the story. Thank you so much. Meanwhile, coming up we're going to get back to the Nvidia earnings. Of course we are. Wall street is awaiting the signals. We await an exclusive conversation with with Jensen Huang. The ED will conduct this is Bloomberg Tech. Turning back to in video. Investors await its results after the closing bell. Kunjan Sabani, Bloomberg Intelligence cialyst wrote at the end of October that Nvidia's partnerships could broaden its revenue and quote with China constrained, expansion into quantum robotics and networking reinforces a long term growth trajectory. Conjurence Barney joins us now here in San Francisco. Whatever happens in the quarter happens. It's all about this kind of long term story. You wrote that note after GTC and DC and you seem to have seen enough to think that long term story is intact. Definitely. I mean it's not going to be over the numbers as you said this quarter but I think given the macro and sentiment backdrop there have been rising concerns or question regarding sustainability of these deals. Be double our customers double ordering or double securing supply and see the final can supply keep up even if the demand is true and can sustain whether it's from the supply chip site from TSMC and packaging or whether supply from the end of data center build up that the customers are trying to build can they execute that fasten? When we heard at GTC from Jensen about the $500 billion half a trillion line of sight how real and tangible are those orders when you look peel into the onion. The timing of that was sort of over six quarters and it did some analysis and that just suggests basically 5 to 10% above consensus. So very very achievable and Very executable target that he laid out. That's one reason why expectations are so high going into today. That single slide behind him on stage, $500 billion. If there are some key questions to pose to Jensen Huang and Nvidia, not just today but on an ongoing basis, what are the they to your mind? Can John, I think we need more clarity around these deals, right? There's deals when it comes to sort of Nvidia securing revenue by these investments. And Sloan, there are questions around depreciation schedule of their GPUs. And again finally there seems to be or at least implies some sort of securing scarcity of GPU securing from multiple different provider, whether it's other merchants, silicon providers or ASIC providers. Can I ask about the depreciation of GPUs? Is Jensen the key person to ask about this? He's obviously understanding exactly how they're using and how they're depreciating within others data centers. Can he give a signal as to whether companies on their own forward looking basis are estimating right, whether it's three, four years, four years, five years? Well definitely from a technology perspective he can definitely give that answer. But there are two input factors here. One is realistically how long can you use this chips which we believe a three to five year period seems fine. But there's also business decisions that the customers are making when they're evaluating the lifetime of this chips, whether will they upgrade to newer chips, will these chips be still valid to use their models which are increasing at unprecedented rate. There are people out there that say the kind of Michael Barry's of this world are wrong because those older generation chips, chips are 100% utilization. Is there a Bloomberg Intelligence House view on that? Well again from a technology perspective we think that useful life we are seeing most of the cases are correct and the chips can be used that long whether from a business perspective, whether from a GPU rental pricing perspective that's valued or not depends on the customer use cases. You've got a busy day. We so appreciate that you've come on to front run. What is our super bowl countrymak intelligence. We thank you. Do not forget to tune in later. You've got to tune in for an exclusive interview with Nvidia CEO Jensen Huang following his earnings. 6:30pm Eastern, 3:30pm Pacific. Who's doing it? You're doing it. Yeah. It's going to be an interesting conversation. There are difficult questions for him. The depreciation factor circular financing which they've already pushed out back up before but let's see what's in the print. Yeah, that does it. From this edition of Bloomberg Tech. Yeah, don't forget to check out the podcast New way to find it online on all the Bloomberg platforms. 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