Bloomberg Technology Special: Nvidia CEO Jensen Huang | Bloomberg Podcasts

[Music] Bloomberg audio Studios podcasts radio news from the heart of where Innovation money and power Collide in Silicon Valley and Beyond this is Bloomberg technology with Caroline Hyde and Ed L low [Music] live from San Francisco to our TV and radio audiences around the world welcome to a special edition of Bloomberg technology I'm Ed llo in just a few moments Nvidia CEO Jensen hang will join us for a live interview following their latest earnings report the company posting a revenue forecast that beat consensus but fell short of some of the most optimistic estimates stoking concern that the explosive growth is waning let's get right to Bloomberg semiconductor correspondent Ian King who joins me on set let's start with the basics the fiscal third quarter forecast and what we learned through it yeah that forecast was was fine if you compare it to consensus it was there or thereabouts and for most of the companies in the world that will be great and and everybody would be happy but this is NVIDIA this is a company which you know beats pretty much every quarter and by an order of magnitude and it didn't do that and it didn't indicate it would do that and that raised a lot of questions as we heard on the the call there are many story lines I think the demand from the hyperscalers is clearly intact but Blackwell was everything I want to play a sound bite of what Jensen Wong said about Blackwell listen to this the change to the mask is complete uh there were no functional changes necessary and so we're sampling uh functional samples of uh Blackwell Grace Blackwell in a variety of system configurations as we speak the main point here is that there was not a design issue with Blackwell itself as had been reported but based on what Nvidia said this was about the production mechanism um Bloomberg Zan King you did a very good job in the top live blog of explaining a GPU mask could you just try to give a short version of that to our audience yeah the mask is basically the blueprint which basically that is used to burn in the circuit onto the surface of the chip to give it its function right that is a very important step that's the fundamental blueprint and this they were saying we didn't get it wrong but when it came to manufacturing it it didn't produce as many good chips as we wanted so we made some tweaks to that didn't have to redesign it but made some tweaks and that is helping us to get a better yield it's worth noting at this stage the stocks down almost 7% in after hours have been down more at the conclusion of the call I think basically because we didn't learn enough about Blackwell what they said was in the fiscal fourth quarter of fiscal year 25 there will be several billion dollars of sales through Blackwell why does the market want more and what does it want they wanted a a reassurance from nvidia's management and they wanted reassurance in the form of details they wanted you know Jens to put his arm around everybody and say don't worry it'll be fine this is how much I'm going to get they ask consistently were asked questions of how many billions and when will those billions exactly come in and collect credits the CFO and Jensen Wang essentially avoided that question and refused to give that precise reassurance we're showing some of the after hours reaction not just in Nvidia itself but some of its peers both on the chip making side the server equipment providers and I think AMD and arm in particular very noteworthy Bloomberg's Ian King stay with us I want to go out to Chicago and Bloomberg's Ryan velica on our equities team and Ryan that's the broad summary from me about the names moving in after hours there's probably a bigger picture after hours movement in the markets as well start with Nvidia and work outward from there sure well one thing I would say about nvidia's after hours decline is that it does come after a very strong year-to day performance I think it closed up more than 150% this year so even though the re forecast was maybe a little bit shy of some of the most optimistic expectations it did beat expectations and it is you know coming off such a huge game so it's not necessarily surprising to see a little bit of a consolidation now and I think even the decline is a little bit less than the options Market was anticipating so just some context there for looking at the decline but you're right that pretty much uh we are seeing widespread weakness following this report all the mega caps are you know modestly lower we are seeing much more pronounced weakness in other chip makers and Chip design companies and so forth so yeah certainly it does seem like the initial read through here is negative but again it does come after a very strong start to the year we made a big deal about this earnings print for quite a long time I look at something like an Invesco QQ to the ETF that tracks the NASDAQ 100 and I think it's we're down around a percentage point right but in truth Ryan in the Market's reaction was this the macro level event that we thought it was going to be that's a great question I would say that it's kind of close enough in line with expectations even if it is a little bit shy of the most optimistic ones that I don't think this is going to really cause people to really change how they're allocating change their opinions on AI this kind of fundamental secular driver but maybe in the near term we do see a little bit of weakness I mean again some of these stocks have been moving up so much there have been sort of kind of growing calls about their valuation some concerns about that I don't know if this is the kind of absolute blowout that would just you know cause people to continue piling into to the you know the way that they were doing earlier this year there is a lot in the news cycle inclusive of and outside of Nvidia I think one of the names that you note in after hours is super micro it's down significantly um there's an Nvidia relationship to that and then there's the use around that name in and of itself yeah absolutely so we saw yesterday a short report came out today it said it's uh delaying the filing of its 10K uh you know both of those caused us some weakness in the stock I think today it was down more than double digits so you know a lot of reasons to be concerned there in general and it is one of nvidia's biggest customers I think it's the third largest so you this is just a you know another reason for people who might have been kind of souring on super micro to you know maybe be pulling the cell button a little bit Ryan felo with the after hours action out of Chicago thank you let's get the reaction from the cell side with one of the stocks relative Bears da Davidson's Gil Lura had a neutral rating and a street low $90 price Target on shares of Nvidia he joins us now and and Gil I guess does that change your bearish perspective on the stock and your main takeaway from the analyst's call the quarter was a very good quarter their uh ability to continue to grow delivering uh chips at this rate at this scale is fantastic and unprecedented I I don't think there's much of a revenue issue here of a growth issue here I think that little bit of a push back is probably more around the margin situation you had a good conversation with Ian about Blackwell and some of the moving pieces part of what's happening with Blackwell it's a new it's a new product it's got a few hitches along the way that put pressure on Gross margins and then operating margin margins grew more than anticipated so less of the Top Line upside flowed to the bottom line and that's probably where investors are getting a little bit more cautious than they were before because in the last several quarters the huge upside to revenue flowed all the way to the bottom line creating huge upside there to believe in Nvidia right now is to believe 2026 calendar is going to be about 200 billion of Revenue and about four4 and a half to5 of earn earnings that's only possible if they continue to get this type of growth on the top line and more leverage and and the second part of that equation looks a little less certain right now Gil when you said that $200 billion figure Bloomberg Zan King who's covered semiconductors at this company since 1998 sat next to me still for what it's worth gave a little smile I mean it's an astonishing figure I I think there's a lot of emphasis here on Blackwell how did you react to the news of several billion dollar in fiscal forth with Blackwell and the explanation that this was a production issue um impacting the ramp not a sort of core design issue around the product itself so first of all our estimate is far less than 200 billion for 2026 but I said you're a relative be Gill and I got that bit right I think in terms of in terms of Blackwell um what happened to Nvidia is they used to be on a two-year cycle for the data center product and they decided to aggressively move to a one-year cycle and then put a lot of new feature functionality and bundle into the Blackwell platform so that was a very aggressive agenda and it's not that surprising that there's some challenges that they have to encounter if they can still ship in the their fiscal fourth quarter that's a very good sign and by the way their customers don't really care that much their customers are just going to continue to buy the latest and greatest and if that's the h200 they'll just continue to buy h200 they have made that a abundantly clear on their conference calls Microsoft meta Amazon Google Tesla Elon Musk made it abundantly clear they'll buy as much gpus as Nvidia can produce at least this year because they're saying the demand signals are there as long as the demand signals are there they'll buy whatever Nvidia is selling and towards the end of the year a piece of that will be blackw Gil Jensen Wong was at pays and gave a detailed answer that basically summarized Nvidia as a systems vendor the discussion around MV link CPUs everything Beyond GPU how much credit do you assign the company for that the sort of complete systems that they sell uh tremendous amount of credit let's let's start with the beginning when history is is written we'll talk about how uh Jensen Wang and Nvidia created the capabilities that make generative AI possible today in a similar way that Elon Musk is responsible for the electric vehicle and part of the genius wasn't just seeing that this is coming that accelerated computers coming AI capabilities are coming well before anybody else did it's also realizing that in order to create a moat around the chip they need to do a couple of things one is to to own the proprietary software around that Cuda but the other thing is to enhance the bundle as much as possible these gpus work in arrays in in when they work together 10 thousands or sometimes tens of thousands of gpus together when you box those up in a box with multiple gpus CPUs wiring cabling and firmware you make it harder for your competitors to catch up and they've done a remarkable job of that I also wonder about all the rest the story thus far has been about the hyperscalers and meta five names essentially being the core customer of Nvidia we got some detail on low double digit billions sales this year in Sovereign AI do you see evidence that the market is broadening out Beyond just the cloud providers not really it seems like those five are still a substantial amount of the revenue and those five have in their most recent calls said some interesting things one of them is that they consistently said they are over investing so they said they definitely want to invest more we're seeing that in results today but they also use the term overinvestigation if for whatever reason demand for AI capacity goes down for instance because compute doesn't continue to drive uh performance of foundational models you're going to see those same Five actors pull back and say you know maybe we have enough Data Center capacity or maybe what we have in the pipeline is enough and that's the concern for 20125 and 26 is that those very companies could do that Beyond that these are the same companies that are developing their own chips they're at various stages of this but Google's tpus are probably as good as invidious so in terms of their internal use and selling to customers such as Apple Google's already caught up Amazon's catching up meta and Microsoft are earlier stages but these same companies that are buying every GPU from Nvidia they can will be the ones that'll buy possibly less next year and the year after that I just want to reflect for our TV and radio audience there are people tuned in around the world my understanding is there are watch parties in cities from New York to London for this earnings we've hyped it up for weeks probably this is the most unique earnings print that I've covered in my career what about for you in the semiconductor space why is this so different well so first of all I I tried to participate by wearing Nvidia green today but importantly Nvidia is important because of how much they've added to the cumulative earnings of the S&P 500 and the cumulative performance but I wouldn't necessarily extrapolate their success or sometimes setbacks to the rest of the market because what they do is very specific the data growth and data center construction and and data center um GPU uh F fulfillment into those data centers is a very small set of companies I I'd argue Nvidia is sucking the oxygen for the room from a lot of other techn companies so we celebrate with Nvidia because they've added so much value I wouldn't necessarily read through to the rest of Technology G of Da Davidson the relatively most bearish or perhaps the least bullish name on the street thank you so welcome to this special edition of Bloomberg technology for our TV and radio audience around the world joining me now is Jensen hang CEO of Nvidia straight from the analyst's call and Jensen good evening good afternoon to you I think think the market wanted more on Blackwell they wanted more specifics and I'm trying to go through all of the call and the transcript it seems like a very clearly this was a production issue and not a fundamental design issue with Blackwell but the deployment in the real world what does that look like tangibly and is there a sort of delay in the timeline of that deployment and thus revenue from that product I I I um let's see that just the fact that I was so clear and it wasn't clear enough uh kind of tripped me up there right away and so so let's see we uh we made a mass change to improve the yield functionality of Blackwell is wonderful we're sampling Blackwell all over the world today uh we um uh show people uh giving tours to people uh of the blackwall systems that we have up and running uh you could find pictures of Blackwell systems um all over the web uh we have started volume production uh volume production will ship in Q4 Q4 we will have billions of dollars of Blackwell revenues and um we will ramp from there we will ramp from there the demand for Blackwell far exceeds its supply of course in the beginning uh because the demand is so great uh but we're going to have lots and lots of supply and uh we will be able to ramp uh starting in q four we have billions of dollars of revenues and we will ramp from there into q1 into Q2 and through next year we're going to have a great next year as well Jensen what is the demand for Accelerated Computing beyond the hyperscalers and meta hyperscalers represent about 45% of our total Data Center business we're relatively Diversified today we have hyperscalers uh we have uh internet service providers we have uh Sovereign AIS we have um Industries Enterprises so it's fairly fairly Diversified uh aside outside of hyperscalers is the other 55% now uh the application use across all of that all of that data center uh starts with accelerated Computing accelerated Computing uh does everything of course from uh well the the the models the things that we know about which is generative Ai and that gets most of the attention um but at the core we also do uh database processing pre and postprocessing of of uh of data before you uh use it for generative AI um transcoding scientific simulations computer Graphics of course image processing of course and so there's tons of applications that people use are uh accelerated computing four and one of them is uh generative Ai and so let's see what else can I say I think that's uh that cover jump in Jensen please on on Sovereign AI you and I talked about that before and it was so interesting to hear something behind it that in this fiscal year there will be low double digit I think you said billions of dollars in Sovereign AI sales but to the lay person what does that mean it it means deals with specific governments if so where it's not necessarily sometimes it's uh deals with um a particular a regional service provider that's been funded by the government and oftentimes that's the case in the case of in the case of Japan for example the the Japanese uh government came out and uh offered um uh subsidies of uh couple billion dollars I think uh for several different uh internet companies and Telos to be able to fund their AI infrastructure uh India has a a sovereign AI initiative going and they're uh building their AI infrastructure uh Canada uh the UK France Italy um I'm missing somebody uh Singapore Malaysia uh you know a large number of countries are subsidizing their Regional data centers so that they could become able to uh build out their AI infrastructure they recognize that their country's uh knowledge their country's data Digital Data is also their natural resource not just the land they're sitting on not just the air above them but they they realize now that their their digital knowledge is part of their natural and National resource and they ought to harvest that and process that and transform it into their National digital intelligence and so this is a this is what we call Sovereign AI you could imagine almost every single country in the world uh will EV eventually recognize this and build out their AI infrastructure Jensen you use the word resource and that makes me think about the energy requirements here I think on the call you you talked about how the Next Generation models will have many orders of magnitude greater compute needs but how will the energy needs increase and what is the advantage you feel Nvidia has um in in that sense well the most important that we do is increase the performance of and increase the performance and efficiency of our next Generation so Blackwell is many times more performant than Hopper at the same level of power used and so that's Energy Efficiency more performance with the same amount of power or same performance at a lower power and that's number one and uh the second is using uh liquid cooling we support air we support air cooling we support liquid cooling but liquid cooling is a lot more energy efficient and so so the combination of that all of that you're going to get a pretty large uh pretty large step up uh but the important thing to also realize is that AI doesn't really care where it goes to school and so increasingly we're going to see AI be trained somewhere else have that model come back and be used uh near the population or even running on your uh PC or your phone and so we're going to train large models but the goal is not to run the large model models necessarily all the time you can you can surely do that for some of the premium services and the very high value AIS um but it's very likely that these large models would then help to train and teach smaller models and what we'll end up doing is have one large uh you know few large models uh that are able to train a whole bunch of small models and they run everywhere Jensen you explained clearly that demand to build generative AI product on models or even at the GPU level is greater than current Supply in Blackwell's case in particular explain the supply Dynamics to me for your products and whether you see an improvement sequentially quarteron quarter or at some point by the end of fiscal year into next year well the fact that we're growing would suggest that our supply is improving and our supply chain is is quite large one of the largest Supply chains in the world uh we have incredible partners and and they're doing a great job supporting us in our growth as you know we're one of the fastest growing technology companies in history and none of that would have been possible without very strong demand but also very strong Supply uh we're expecting Q3 to have more Supply than Q2 we're expecting Q4 to have more Supply than Q3 and we're expecting q1 to have more Supply than Q4 and so I think our supply our supply condition going into next year will be an will be a large improvement over this last year um with respect to demand uh uh Blackwell is just such a leap and and there's several things that are happening you know just the foundation model makers themselves the size of the foundation models are growing from hundreds of billions of parameters to trillions of parameters uh they're also learning more languages instead of just learning human language they're learning the language of images and sounds and um uh videos and they're even learning the the language of 3D graphics and and whenever they are able to learn these languages they can understand what they see but they can also generate what they're asked to generate and so uh they're learning the language of proteins and chemicals and and physics um you know it could be fluids and it could be uh particle physics and and so they're learning all kinds of different languages or learn the meaning of what we call modalities but basically learn the languages and so so these models are growing in size they're learning from more data and there are more model makers uh than there was a year ago and so the number of model makers have grown substantially because of all these different modalities and so that's just one just the Frontier Model the the foundation model makers themselves have really grown tremendously and then the generative AI Market has really Diversified you know beyond the internet service makers to startups and now Enterprises are jumping in and uh different different countries are jumping in so the demand is really growing Jensen I'm sorry to cut you off I I will lose your time soon um you've also Diversified and when I said to our audience you were coming on I got so many questions probably the most common one is what is NVIDIA we talked about you as a systems vendor but so many points on Invidia GPU cloud and I want to ask finally do you have plans to become literally a cloud compute provider uh no uh our GPU Cloud was designed to be the best version of Nvidia cloud that's built within each Cloud Nvidia dgx cloud is built inside gcp inside Azure inside AWS inside oci and so we buil our clouds within theirs so that we can Implement our best version of our Cloud work with them to uh make that cloud that that infrastructure that AI infrastructure Nvidia infrastructure as performant as great TCO as possible and and so that strategy has worked incredibly well and um of course uh we are large consumers of it because we create a lot of AI ourselves because our chips aren't possible to design without AI our software is not possible to write without Ai and so we use it ourselves tremen you know tremendous amount of it self-driving cars the general robotics work that we're doing the Omniverse work that we're doing so we're using the dgx cloud for ourselves um we also use it for an AI Foundry uh we make AI models for companies that would like to uh have expertise in doing so and so we are AI uh we're an AI we're a Foundry for AI like tsmc is a Foundry for our chips and so so there were three fundamental reasons why we do it uh one is to have the best version of Nvidia inside all the clouds two because we're a large consumer ourselves and third uh because we use it for AI Foundry for to help every other company Jensen Wong CEO of I want to thank you for your time the extended conversation straight off the earnings call thank you uh Nvidia earnings fiscal good to see you to fiscal second quarter done I point out that in after hours the stock is down still almost 7% there'll be a lot of analysis to be done overnight by the sell side by the buy side and we'll bring you the best from Bloomberg's reporters and editors from San Francisco this is Bloomberg technology [Music]