All Eyes on Nvidia Ahead of Earnings

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1:11Bloomberg 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 NVIDIA. Earnings after the closing bell. Now, investors expecting to learn more about where those billions of dollars on AI spending are actually going. Plus, NVIDIA CEO Jensen Huang and Tesla CEO Elon Musk are speaking right now at the U.S. Saudi Investment Forum. We'll bring you the latest. And Brookfield Asset Management targets$10 billion of fund commitments for a global AI infrastructure program in partnership with, you guessed it, NVIDIA. And NVIDIA dictates trade.

1:52Right now, we are seeing signs of stability in the Nasdaq 100 more broadly. I remind you that almost$2 trillion has 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. NVIDIA in the points perspective, helping with the NASDAQ 100. Crypto, though, still in the eye of the storm, we're up by 2.8%, that anxiety driving it below$90 ,000. So still some risk aversion, Ed. OK, NVIDIA is up more than 2.5%, but off its session high, it is a stock that's up almost 40 % year to date.

2:26outperforming double the performance of what we've seen of the Nasdaq 100 and S &P 500. The expectation is revenue growth above 50%, net income growth above 50%. But all that matters is what CEO Jensen Wang tells us about the future. Let's get with Bloomberg's Ian King, who leads our 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 with data center infrastructure. Give us the things we need to look out for and what's in your preview of this company's earnings.

3:03Yeah, 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$100 billion of net income. That's more than Intel and AMD get in revenue combined. So the numbers have come off the charts. The key here is we all know the numbers are going to be good. We know the forecast is going to be good. 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.

3:40So 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 worth of orders, not just 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 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.

4:19And 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 how they feel. There are some real concerns and there are some real questions for NVIDIA. Some of those we'll get to pose this evening to Gentsom himself. 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, a 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.

4:54So 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 AI spending because it impacts the whole rest of the market. Bloomberg's U.S. equities reporter Carmen Reinecke is here to just bring us the context. We know the questions are going to be asked of NVIDIA, but what does it signal about the commitment of the Magnificent Seven, of the key hyperscalers, and more broadly, the rest of the AI trade?

5:29Yeah, so this is a huge moment for the AI trade. I think a lot of people are really looking to NVIDIA 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, if it's still flowing to NVIDIA and how much. When I was reading your piece, which you co-wrote with Ryan Vlaselica, the data is really interesting.

6:06There's going to be a big part of the Bloomberg Tech audience that don't know some of that. So you just talked about weighting, right? NVIDIA is about 8 % of the S &P 500. That's a factor. You also looked at NVIDIA's 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.

6:37I 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.

7:10Really most common, Reineke. 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 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.

7:47But 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, the questions that people are raising in the current environment, I don't think they're necessarily going to be conclusively answered with NVIDIA's report. The depreciation question, the demand question extending to the rest of the economy, I think those doubts 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.

8:28But you look at NVIDIA, trading about 30 times future earnings, that's not that elevated. So is it the rest of the trade, the palanteers 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.

9:04Then I think there's room for some of these stacks to come down. Now, I'm not sure I share that view. I tend to believe that the AI super cycle 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 well-read story on the Bloomberg Terminal and Bloomberg.com from one investor, this is a, quote, so goes NVIDIA, so goes the market kind of report. From your desk and your perspective, is that the situation here? Well, I think there's no question that this is a capstone report.

9:41It'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 question is whether this is going to answer all the AI doubts 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 which is utilization if those older generation gpus are running at 100 that's a really good problem to have.

10:32This is kind of very specific, but are those soft data sets that your team are looking at to work out what on earth is going on? Well, 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 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.

11:13And 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 counterexample 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 product?

11:55Right. I think there's still an, I mean, first of all, if you take a look at kind of adoption rates for the AI 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.

12:28And 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 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. Marta, it's always great to have you in. Thank you for coming into the studio. Marta Norton, of course, there of Empower.

12:59Meanwhile, NVIDIA CEO Jensen Huang is already on stage, ahead of his earnings publication, of course. Meanwhile, Tesla CEO Elon Musk is alongside in D.C. as part of the U.S.-Saudi Investment Forum in Washington, D.C. 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.

13:23Now, 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.

14:02You know, I always have to, like, preface that, you know. We shouldn't take civilization for granted. 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 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 the way to think of AI in space is that in order to achieve any meaningful percentage of a Kardashev two-scale civilization where you're using even a millionth of the sun's energy, you must have solar-powered AI satellites in deep space.

14:51So once you realize, once you think in terms of a Kardashev two-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 one two billionth of, the earth only receives roughly one two 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 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 you just got to radiate that's right so my estimate is that actually the cost of of electricity, like the cost effectiveness of AI in space will be overwhelmingly better than AI on the ground.

16:08So long before you exhaust potential energy sources on Earth, long before, meaning 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 two tons. Out of that two tons, 1.95 of it is probably for cooling. 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.

16:55So if you start doing any kind of scaling for both electricity generation and cooling, you realize, okay, space is incredibly compelling. So, like, let's say you wanted to do, I don't know, 200 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 two-thirds 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.

17:47Like 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've got, 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 me, 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?

18:35That's the last question. All right. 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, 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.

19:07We'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 of 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.

19:49Several hundred billion dollars of computation is done on just raw data processing. It has nothing to do with AI. Just SQL processing, data frames, everybody's name, address, their sex, their age, where they live, how much money they make. All of that sits into a data frame. That data frame drives the world today, whether it's 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.

20:23The 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 I've ever seen 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, if you just look at those two applications, many of the Internet companies can build an enormous number of GPU supercomputers just doing that.

21:13Of 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 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.

22:05But in essence, this is our, 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 our lifetime partnership and friendship. Thank you, Elon. Thank you, Jensen. Thank you.

22:48That was Elon Musk speaking alongside NVIDIA CEO Jensen Huang at the U.S. Saudi Investment Forum in Washington, D.C. Probably, Caroline, the biggest piece of news that came out of it was Elon Musk confirming that XAI 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, too humane to be able to use on the ground when it comes to Blackwell.

23:25And 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 Gentic AI. Yeah, we should probably point out the obvious to our audience that NVIDIA reports earnings after the closing bell. Jensen Wang 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.

24:11And 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 Pichai. We've heard it from Jeff Bezos. Now we're hearing it 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 data centers not on this earth, but 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.

24:44Yeah, 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 Wang 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's right. XAI doing something in Saudi Arabia. That's right.

25:16It's yet again evidence of this huge need for data centers and computing capacity, which is what they were talking about from beginning to end. And this is how XAI is going to take part in it. This is how Elon Musk and his empire are going to take part in ensuring that we have the capacity that we need to fuel all of these services, especially the ones that XAI 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?