Speaker 1: Bloomberg Audio Studios, podcasts, radio news fourth.
Speaker 2: Quarter revenue has beat estimates. Fourth quarter data center revenue
Speaker 2: coming in at thirty five point six billion dollars thirty
Speaker 2: four point oh nine billion dollars. Fourth quarter revenue that
Speaker 2: top line thirty nine point three billion dollars, exceeding estimates
Speaker 2: of thirty eight point twenty five billion dollars. Now coming
Speaker 2: to that revenue estimate for the first quarter. In Video
Speaker 2: C's first quarter revenue plus or minus two percent, uh,
Speaker 2: the estimate was for forty two point twenty six billion dollars.
Speaker 2: Fourth quarter data center revenue coming in at thirty five
Speaker 2: point six percent, the company saying that it ramped up
Speaker 2: massive scale production of Blackwell AI. In the after hour
Speaker 2: shares hire right now by about three point four percent.
Speaker 3: Yeah, actually in Video saying demand for Blackwell is amazing,
Speaker 3: So that's what we talked about in terms of that transition.
Speaker 3: But again the key metrics, as Tim said, stock is
Speaker 3: up almost four percent here in the aftermarket. The first
Speaker 3: quarter revenue, so looking ahead outlook forty three billion dollars
Speaker 3: plus or minus two percent. The estimate was for forty
Speaker 3: two point three billion, and again fourth quarter data center
Speaker 3: so looking at the quarter that they just wrapped up
Speaker 3: data center revenue. That's the bulk of their business, that's
Speaker 3: those hyperscalers and more. Thirty five point six billion. That
Speaker 3: is a beat. Thirty four point zero nine billion was
Speaker 3: what the street was expecting first quarter, justin gross margin
Speaker 3: again looking forward seventy point five percent to seventy one
Speaker 3: point five percent. Street was looking for a little bit more.
Speaker 3: This is a measure of profitability, and the estimate on
Speaker 3: the street was seventy two point one percent. Again, the
Speaker 3: stock now not up as much, In fact, it's down
Speaker 3: just a hair.
Speaker 2: Yeah, shares climbed as much as four percent after this
Speaker 2: first quarter revenue forecast top estimates. We're getting some more
Speaker 2: commentary too, in Vidia saying that Blackwell is achieving billions
Speaker 2: of dollars in sales in the first quarter. The company
Speaker 2: also saying that it's successfully ramped up Blackwell massive production.
Speaker 2: In Vidia also coming out and saying, as Carol mentioned,
Speaker 2: demand for Blackwell is amazing. We're continuing to get more
Speaker 2: numbers here too. Fourth quarter compute revenue coming in above
Speaker 2: estimates at thirty two point five six billion dollars. Fourth
Speaker 2: quarter networking revenue coming in just shy of estimates a
Speaker 2: three point oh two billion dollars.
Speaker 3: Ye, now the stock is down about one percent here,
Speaker 3: it's bouncing around a lot, not surprising a lot of
Speaker 3: investors in this name. So you're going to see a
Speaker 3: lot of movement as we get tick by tick, headline
Speaker 3: by headline. But again, the key ones right now, it
Speaker 3: has to do with the fourth quarter data center revenue.
Speaker 3: Excuse me, thirty five point six billion. Again, that's above
Speaker 3: what the Street was expecting. Street was looking for thirty
Speaker 3: four point zero nine billion. And again key is the
Speaker 3: revenue outlook forty three point zero billion plus or minus
Speaker 3: two percent. Street was at forty two point three billion.
Speaker 4: And again we.
Speaker 3: Got some context context, if you will, in terms of
Speaker 3: demand for Blackwell being amazing, successfully ramping up the Blackwell
Speaker 3: massive production, Blackwell achieving billions of dollars in sales in
Speaker 3: the first quarter and ramping up the massive scale production
Speaker 3: of Blackwell AI.
Speaker 2: If the company else is saying it to lilivered eleven
Speaker 2: billion dollars of Blackwell architecture revenue in the fourth quarter.
Speaker 3: Joining us right now, Red Brown is here in our
Speaker 3: New York studio, Bloomberg News Earnings reporter Caroline Hyde, co
Speaker 3: host of Bloomberg Technology, also here in studio. You know, Red,
Speaker 3: I want to bring you into this conversation. You keep
Speaker 3: a watch on earnings, just you know, your initial thoughts
Speaker 3: and what we're seeing in the trade because the stock
Speaker 3: is bouncing around a lot.
Speaker 5: Yeah, I mean I do feel like we got to
Speaker 5: like kind of take a cyber relief here because they
Speaker 5: did check off all of the boxes kind of what
Speaker 5: Kun John answer the question marks Kun John has kind
Speaker 5: of touched on there. The outlook is solid, the fourth
Speaker 5: quarter was solid, and there seems to be real kind
Speaker 5: of optimism around the progress with Blackwell. So yeah, I
Speaker 5: think overall this kind of was in line with what
Speaker 5: analysts were expecting, and the markets maybe been a little
Speaker 5: bit down going into this court into this report, but yeah,
Speaker 5: kind of a cyber relief I think for everybody.
Speaker 2: The company did give an up eat forecast. It is
Speaker 2: a sign that the AI build out is strong. Carolin Heid,
Speaker 2: I want to bring you in, co host of Bloomberg
Speaker 2: Technology on Bloomberg TV Weekday at eleven am Wall Street time.
Speaker 2: I do want to ask about is there is the
Speaker 2: sigh of relief sort of coming too early? Did we
Speaker 2: get any answers about the impact of deep seek here.
Speaker 4: Well, I think there's flies in the ointment.
Speaker 1: I don't know how much you've talked about them, but I
Speaker 1: think the gross margin is clearly a sign that we're
Speaker 1: having perhaps a slight air pocket that many had talked
Speaker 1: about is where you flip from Hopper to Blackwell. And indeed,
Speaker 1: how much expense is spent on making sure that Blackwell
Speaker 1: is easy to use and get up and running as
Speaker 1: quickly as possible.
Speaker 4: That could be an issue. And you have also got.
Speaker 1: This potential guide of slightly weaker on the revenue for
Speaker 1: the fiscal first quarter plus or minus forty three billion.
Speaker 1: If they come into the low end, that does indeed
Speaker 1: just slightly lose out. But I think we are trying
Speaker 1: to hear ultimately whether that insane demand is now an
Speaker 1: amazing amount of demand and does that basically put off
Speaker 1: any concerns that we had about whether or not more
Speaker 1: can be done with less in the future. And I
Speaker 1: think we'll hear on the call, particularly from Jensen, as
Speaker 1: to ultimately whether inferenced demand is really there for his
Speaker 1: very expensive chick tyrol.
Speaker 2: It is like reading a statement from the Federal Reserve
Speaker 2: insane versus amazing.
Speaker 3: This is what I was going to say ask you,
Speaker 3: is that you know you follow this company so closely,
Speaker 3: and it's how do you read the tea leaves because
Speaker 3: he does tend to be very enthusiastic and maybe changes
Speaker 3: the word and maybe there's a nuance to that change,
Speaker 3: But how do you kind of read through what he says,
Speaker 3: because we know he's going to be a beat.
Speaker 1: I think he's going to be saying, look, trust us
Speaker 1: with this R and D, trust us on a slightly
Speaker 1: lower margin because we have got quote the fastest product
Speaker 1: ramp in our countries.
Speaker 4: His company's history.
Speaker 1: This is a company that suddenly become like Apple and
Speaker 1: giving us a new chip.
Speaker 4: Every year that ever used to happen before.
Speaker 1: There's an extraordinary pace which they're trying to innovate that
Speaker 1: costs money. And indeed, of course you have to be
Speaker 1: patient that sometimes there's going to be a slight friction
Speaker 1: when you come to actually putting these Blackwell supercomputers into
Speaker 1: the mix.
Speaker 2: She shares, we're as high as four percent higher in
Speaker 2: the after hours, now down about four tenths of one percent. Yeah,
Speaker 2: not so much, like though investors are really trying to
Speaker 2: make sense of these numbers. Yeah, it's not going and
Speaker 2: it's not moving in a clear direction.
Speaker 1: I think the clear direction is still always growth, isn't it?
Speaker 1: And the idea that sure and one hundred percent increase
Speaker 1: in revenue that got for their fiscal twenty twenty five,
Speaker 1: which is the one that's just gone, and the one
Speaker 1: prior to that, for two straight years we've had a
Speaker 1: doubling of revenue.
Speaker 4: We're going to have to start to get used.
Speaker 1: To a fifty percent increase in revenue and then a
Speaker 1: twenty three percent growth in revenue. The key question I
Speaker 1: think there is still going to be what about the
Speaker 1: cheap alternatives? What about Trainium too that Amazon has that
Speaker 1: is much cheaper, What about some of these startups that.
Speaker 2: You're seeing, does Tridium too, does that compare with Hopper?
Speaker 2: Does it compare with black?
Speaker 4: Well? About inference much more as well?
Speaker 1: And so this is when they're trying to say, hey,
Speaker 1: you've got your beautiful large language model, come and now
Speaker 1: use it with us, and we will save you so
Speaker 1: much more money about thirty percent.
Speaker 2: So after you've used Nvidia to train it, yes, we
Speaker 2: will process those requests for you exactly.
Speaker 4: And I think that's where you're to start to get
Speaker 4: the edge.
Speaker 1: And in fact, there was an interesting interview done with
Speaker 1: a rival with our CEO of course knows data centers
Speaker 1: and mobiles deeply, and his own design work of course
Speaker 1: helping a lot of those out there, including in Video,
Speaker 1: but he himself saying, look, this is where the opening
Speaker 1: is for competitors.
Speaker 4: It's the inference stage. No one can really compete with the.
Speaker 1: GPU power that in Video has when it comes to
Speaker 1: training these models. But the next layer, when we actually
Speaker 1: get it in and use these incredibly powerful things, that's
Speaker 1: where the edge can come.
Speaker 3: I mean, I don't know. In terms of market expectations,
Speaker 3: not bad.
Speaker 1: Yeah, signaling life kind of everyone was on the money,
Speaker 1: alas did their job well. Jensen's done his job well
Speaker 1: in terms of guiding. But had we got used to
Speaker 1: beaten raises. But look look back to when we were
Speaker 1: sit here together with Meta and Meta's numbers were a
Speaker 1: really late be in miss the forecast, and then Zuck
Speaker 1: gone on and just talked really optimistically and we all
Speaker 1: bought it.
Speaker 2: Yeah that's a good point. Yeah, wait to see what
Speaker 2: happens in the cash session. Wait to hear from Jensen
Speaker 2: a little later. We can only take the moves as
Speaker 2: soon as the numbers come out with a grain of
Speaker 2: solid red brown.
Speaker 3: I put deep seek in the search and nothing, nothing's
Speaker 3: coming up.
Speaker 2: Let's just say it'll likely be asked about by at
Speaker 2: least one analyst tonight.
Speaker 3: Red round.
Speaker 2: I want to bring you in here on sort of
Speaker 2: the broader market reaction to this. There was this idea
Speaker 2: that given the segiment we've seen in the last five
Speaker 2: six days, uh in the broader market, the cell off
Speaker 2: that we've seen in the megacap tech companies this year
Speaker 2: and in the last few days, this would sort of
Speaker 2: change the tone, does it.
Speaker 5: I mean, it doesn't really seem like the tone has
Speaker 5: changed at all. We're looking at the numbers is flat right,
Speaker 5: kind of across the board, with everybody not really reacting.
Speaker 5: You know, I think a lot of the narrative kind
Speaker 5: of has been said. You know, the spending is still there.
Speaker 5: I think if we read all the analysts reports heading
Speaker 5: into this, that was the one data point that everyone
Speaker 5: was hanging on to that there hasn't been anyone coming
Speaker 5: out and saying, you know, we're going to be adjusting
Speaker 5: our AI spending. They've stuck to you know, those massive
Speaker 5: capex numbers that we saw throughout the quarter, so I think, yeah,
Speaker 5: maybe a little bit of a wait and see still unfortunately,
Speaker 5: you know, for the time being.
Speaker 3: Well, and they did note I'm looking at our live
Speaker 3: blog noted margins are being squeezed by the cost of
Speaker 3: bringing new, more complicated products to market, and it sounds
Speaker 3: like what.
Speaker 2: Well, Carolyn explained that means because you know Kunjohn also
Speaker 2: mentioned this idea of an air pocket or the transition
Speaker 2: from Harper to Blackwell. What exactly happens behind the scenes
Speaker 2: here and why is it so expensive?
Speaker 1: Well, I think you've just ultimately got to make sure
Speaker 1: that it works hardware seamlessly with the software that you've
Speaker 1: got going, and ultimately that becomes more a powerful piece
Speaker 1: of equipment that is able to use your data and
Speaker 1: do what you want with it. I think when it
Speaker 1: came to Hopper, there was that was working beautifully for many,
Speaker 1: but everyone got deeply excited about the fact that there
Speaker 1: was the latest greatest innovation suddenly coming out and sort
Speaker 1: of decided to go long on Blackwell instead. We actually
Speaker 1: saw a repositioning of that by many customers when they realized, oh,
Speaker 1: actually this is going to take work for everyone to
Speaker 1: ensure to pull this in, to get this into my
Speaker 1: data centers, and to ultimately make sure that.
Speaker 4: It's doing what it wants to do with the most efficiency.
Speaker 1: Heating problems for example, just some of the technicalities that
Speaker 1: they hadn't been able to stress test at this rapid
Speaker 1: rate of innovation.
Speaker 3: All right, just to rehash, Nvidier giving a bullish revenue
Speaker 3: forecast for the current quarter, reassuring investors that spending on
Speaker 3: AI computing remains strung. Just reading some of the reporting
Speaker 3: out by our Oni and King, who follows this sector,
Speaker 3: sales will be about forty three billion in the fiscal
Speaker 3: first quarter, which runs through April. Analystaid An estimated about
Speaker 3: forty two point three billion on average, with some projections
Speaker 3: ranging as high as forty eight billion. So there were
Speaker 3: some outliers and some very high expectations. Carolyn, how are
Speaker 3: you thinking about this story? Obviously we want to see
Speaker 3: what more commentary we get on the call the follow through.
Speaker 3: In terms of the trade, like I'm looking at NASDAQ
Speaker 3: one hundred mini futures, they're relatively little change, maybe up
Speaker 3: about one tenth of one percent. S and P five
Speaker 3: hundred mini futures, they are just a hair lower, pretty flat,
Speaker 3: So it's really very calm. It feels like you're in
Speaker 3: the aftermarket.
Speaker 1: And maybe we just sort of braced ourselves because the
Speaker 1: volatility they experienced yesterday, and then say we got used
Speaker 1: to the fact that the market is trying to find
Speaker 1: its direction when it comes to what is the question
Speaker 1: of capacity, then we've got to go back to what
Speaker 1: happened in the beginning of the week, and we're all
Speaker 1: asking questions about TD Cowan's note over the weekend about Microsoft.
Speaker 1: I'm sure that it will be questions put to Jensen
Speaker 1: about ultimately is there a capacity over stretch or underreach
Speaker 1: at the moment, and what about these so called scaling
Speaker 1: rules that he's trying to combat in every feat, whether
Speaker 1: or not it's about the scaling rules of how much
Speaker 1: better llms can become with the amount of data on
Speaker 1: compute you throw at it, but ultimately also the scaling
Speaker 1: rules of China or whether that becomes something you can
Speaker 1: still scale into in any way with an H twenty.
Speaker 2: I'm glad he brought that up because one of the
Speaker 2: questions that kun John mentioned was getting more detail on
Speaker 2: views of more US restrictions, specifically with regard to China.
Speaker 2: Read I know you've been doing some searching within the
Speaker 2: press release. Are you seeing anything in there about China sales,
Speaker 2: about a commentary about China.
Speaker 5: No mention about China. So then Kunjohn is correct that
Speaker 5: we that's definitely going to be a top of mind
Speaker 5: topic for analysts on the call. You know right now
Speaker 5: there's a lot of question marks looming around what they
Speaker 5: can do there. It gets they get around twelve percent
Speaker 5: of their sales over the past few years, most of
Speaker 5: that coming across from game being automotive end data centers.
Speaker 5: So I think there will be questions about, you know,
Speaker 5: what sort of contingencies maybe they have in place if
Speaker 5: any sort of rediction restrictions do come down.
Speaker 3: Well, and Caroline, I mean jensenmong has made his way
Speaker 3: to the way that's read. He said, conversations with President
Speaker 3: Trump about these issues and his concerns.
Speaker 1: Yeah, certainly, and that had been pre premeditated. He'd been
Speaker 1: going to go and see President Trump. We know that
Speaker 1: he'd wanted to. When our own ed Ludlow sat down
Speaker 1: with him previously, he said, I'm ready willing and able
Speaker 1: to go and meet President Trump, and certainly they wanted
Speaker 1: me to go. She because remembers the end of the administration,
Speaker 1: the Biden administration that's suddenly added all these curtailments to
Speaker 1: how much they can place chips in other geographies, not
Speaker 1: just China, because there's this worry that you sell into
Speaker 1: a different nation to Singapore, and actually that's suddenly how
Speaker 1: it's getting dispersed into China as well. So he's got
Speaker 1: a lot to be debating. I do note in I mean,
Speaker 1: I hate to be a cynic when you're looking at
Speaker 1: these press releases, but he really only mentions US companies
Speaker 1: at the beginning of how much that they're working with
Speaker 1: the HWS is the Cisco's the verizons. I mean, it
Speaker 1: really is a focus in on us.
Speaker 3: It's just this week things I think now increasing a
Speaker 3: partnership right with Cisco.
Speaker 1: Exactly to get the networking better again, just get these
Speaker 1: things into people's hands more efficiently.
Speaker 2: We've talked about hop Hopper, We've talked a lot about Blackwell.
Speaker 2: Is it too early for us to be talking about
Speaker 2: Reuben I don't.
Speaker 1: I mean, what in the next innovation, This is the
Speaker 1: next year, this is the next I don't think Jadson
Speaker 1: is ever too early to talk about what he's got
Speaker 1: up next to sleep.
Speaker 2: So that's that's the question. I mean, our investors looking
Speaker 2: for you know, this is this is the This is
Speaker 2: what happens with compute, right, You build something and then
Speaker 2: you build something better, and you build something better. That
Speaker 2: just happens over and over again, and it costs money.
Speaker 2: It costs money. So how important is you know the
Speaker 2: next generation what comes after blackwell apparently code named Rubin.
Speaker 2: How important is that to where we are in the
Speaker 2: timeline of Nvidia.
Speaker 1: I think it's important to show that they are continuing
Speaker 1: to just innovate ahead of any of the competition. That
Speaker 1: the more it's more Lisa Sue who pays attention to
Speaker 1: Ruben and things up like, yeah, how am I managing
Speaker 1: to get any sort of in here in terms of
Speaker 1: owning the data center space when it comes to just
Speaker 1: the ability that Jensen has had to see around corners,
Speaker 1: when it comes to the use and application of his
Speaker 1: GPUs for gaming.
Speaker 4: For crypto and then for generative AI.
Speaker 1: But maybe Lisa Su starts to play the tack of okay,
Speaker 1: but it's me with cheaper price points, and I wonder
Speaker 1: whether the margin starts to creep into that narrative as
Speaker 1: well as maybe yes, it's a deeply expensive piece of
Speaker 1: kit with everyone offering cheaper alternatives.
Speaker 6: What do you do?
Speaker 4: How do you respond?
Speaker 3: All right, folks, we're talking with Caroline Hyde, co host
Speaker 3: of Bloomberg Technology on Bloomberg TV at eleven am Wall
Speaker 3: Street Time. Let's bring into the conversation Mandy Seeing walking
Speaker 3: into our studio Bloomberg Intelligence, Senior Tech Industry Analysis. He
Speaker 3: walked in because we asked him to and we were
Speaker 3: hoping you would. Hey, and video shares have been bouncing around.
Speaker 3: Should any of us who are thinking about the AI industry?
Speaker 3: Is this a dose of optimism?
Speaker 7: It is? But when it comes to Nvidia specific I
Speaker 7: would say, you know, the fact that networking revenue declines
Speaker 7: sequentially for the second quarter in a row again in
Speaker 7: Vidio is very high bar. And you know, given their
Speaker 7: bed and raises, everyone expects them to do, you know,
Speaker 7: well on every line. So networking going down, to me,
Speaker 7: that's a sticking point, along with gross margins going down
Speaker 7: and just the sequential increases that we have seen in
Speaker 7: the past quarters. It looks like it's tapering again. It's
Speaker 7: double digit. But when it comes to the overall growth rate,
Speaker 7: it feels like it's decelerating. And the last data point
Speaker 7: I would offer is the cloud exposure, the hyperscale cloud exposure.
Speaker 7: It was forty five percent before now it's fifty percent Now.
Speaker 7: What it tells you is they kind of we are exposed.
Speaker 7: And so the fact that you know networking is going down,
Speaker 7: it's a sign that you know, training versus inferencing component
Speaker 7: that seems to be really in question here because networking
Speaker 7: does well. If training is growing, if networking is going down,
Speaker 7: that's a sign that they may be facing some sort
Speaker 7: of challenges or starting to get more questions around the
Speaker 7: scale of training. And I think that's a big question,
Speaker 7: So go.
Speaker 2: Deeper on that with training versus inference. We're talking a
Speaker 2: little bit about it with Caroline context Amazon and what
Speaker 2: Amazon has when it comes to in France. But what
Speaker 2: do we learn in video within Vidia today.
Speaker 7: Look, if you're setting up a giant cluster like Xai
Speaker 7: has with you know, one hundred and two hundred thousand GPUs,
Speaker 7: you need a lot of networking there. But if you
Speaker 7: are setting up a data center with let's say a thousand,
Speaker 7: two thousand GPUs, you don't need as much of Nvidia
Speaker 7: as networking, and that's where you know, training versus inferencing
Speaker 7: really matters, because if you know, companies are leaning towards
Speaker 7: setting up more data centers with fewer chips. I mean
Speaker 7: when I say, if you are still thousands of chips
Speaker 7: but not to the scale of one hundred thousand, then
Speaker 7: networking won't do as well. And that's the whole debate
Speaker 7: about training versus inferencing. So to my mind, you know,
Speaker 7: deep seek and all the recent developments from hyperscalers suggests
Speaker 7: that you may not need giant clusters and that is
Speaker 7: I think going to affect Nvidia going forward. So when
Speaker 7: I look at their guide, when I look at the
Speaker 7: fact that you know, networking declined sequentially, again, it's a
Speaker 7: great print, but to me, the path seems to be
Speaker 7: that it will slow down on the networking side, and
Speaker 7: then you have to ask yourself where will the upside
Speaker 7: come from. Maybe on the call they expand on starlink
Speaker 7: and you know, the sovereigns that is a big pocket.
Speaker 7: If that pans out in terms of training, like setting
Speaker 7: up big clusters that Sam Altman has talked about, you know,
Speaker 7: with projects started, then you will start to see networking
Speaker 7: bounce but for me, there is a clear connection between
Speaker 7: networking and size of cluster and also software. There was
Speaker 7: nothing in the print around software, even though it's you know,
Speaker 7: two billion dollars in revenue when you look at a
Speaker 7: data center, you know, aligne, which with over one hundred
Speaker 7: and fifteen billion dollars two billion is very great small,
Speaker 7: but they didn't mention anything around software. So there's still
Speaker 7: a chip company that depends on you know, companies buying
Speaker 7: their their chips in bulk and also leering and networking.
Speaker 7: So to me that the networking part is critical here.
Speaker 3: You know, one of our on our live blog are
Speaker 3: Carmin Rhinikey saying, you know, bringing kind of salesforce into
Speaker 3: the mix, noting that shares of Salesforce are down more
Speaker 3: than five percent in post market trading after it reported
Speaker 3: we growth outlooks, stoking worry about its new AI product.
Speaker 3: Like you know, you do think about kind of the
Speaker 3: whole infrastructure, the whole community. Caroline, come on in the
Speaker 3: conversation following off mandypin if you've got a question.
Speaker 1: Well, I do think that that's interesting about agent KI
Speaker 1: and this is where salesforce and agent force is in
Speaker 1: the front and center and look, Jensen pays lip service
Speaker 1: to it in the statement saying AI is advancing at
Speaker 1: light speed as a GENTKI and physical AI set the
Speaker 1: stage for the next wave, but he's got to keep
Speaker 1: talking about scaling laws when it comes to training. That
Speaker 1: is going back to a reasoning AI. He's trying to
Speaker 1: find new ways to galvanize us all to be excited.
Speaker 1: But if the agents aren't selling that well as far
Speaker 1: as we thought about.
Speaker 7: Is reasoning really that good for Nvidia? In my mind,
Speaker 7: if the pivot has happened towards more reasoning, huh, that's
Speaker 7: not a positive for Nvidia because when you're doing reasoning,
Speaker 7: you are doing more inference compute. And I mean, based
Speaker 7: on Jensen's past comments, Nvidia has a forty percent share
Speaker 7: in inferencing. Sixty percent is training, right, So how can
Speaker 7: it be better if you're doing more training, you know,
Speaker 7: using that reasoning approach. So those are like very small nuggets,
Speaker 7: but I think in the grand scheme of things they matter.
Speaker 2: You mentioned agentic AGENTIC AI. You got to explain what
Speaker 2: that is for people, especially in the context of what
Speaker 2: you talked about with Panos Pane earlier and what Amazon
Speaker 2: released today, and.
Speaker 1: I think this is how ultimately starts being more helpful
Speaker 1: that a not only will your chatbot basically go away
Speaker 1: and take longer thoughts about things, thoughts quote unquote, you know,
Speaker 1: trying to or personify these these pits of tar and
Speaker 1: it is real, it is real, and person fall in
Speaker 1: love with it. But she if it's ass then is
Speaker 1: going to go off and start actioning stuff for you.
Speaker 1: Not only are they going to tell you the best restaurant,
Speaker 1: they go book it for you. They're going to potentially
Speaker 1: start booking flights, paying for them. Agents can take ultimately
Speaker 1: still relatively basic needs, but run with them and complete
Speaker 1: the task. And that's ultimately where Salesforce and these enterprise
Speaker 1: software companies have started to really see. They're in the
Speaker 1: question for many which has is always being asked is
Speaker 1: how they price for it? And Salesforce sort of stick
Speaker 1: the cell and sells on a limb and started saying, well,
Speaker 1: this is how much going to pay per per user
Speaker 1: or indeed per amount that you actually use.
Speaker 4: But all of this is the return on AI that
Speaker 4: we keep questioning in so many ways.
Speaker 7: I mean, you have to ask yourself, why is Nvidia's
Speaker 7: growth smart going down?
Speaker 6: Right?
Speaker 7: You know, obviously they release a new product that should
Speaker 7: command premium pricing, and look they guided to that. So
Speaker 7: they're saying in the second half you will see gross
Speaker 7: margins rebound, but they're going down for a reason. Either
Speaker 7: they're paying up more for foundry costs to DSMC or
Speaker 7: they're just incanctivizing their customers to buy more. And you know,
Speaker 7: given black Belt did so well in the quarter, there
Speaker 7: could be some you know pricing aspect to it in
Speaker 7: terms of just driving demand and you know, shipping morels.
Speaker 4: Is that because we're getting more competition as well in
Speaker 4: the future.
Speaker 7: I mean CSPs, the four CSPs make fifty percent of
Speaker 7: their revenue hyperscalers, the hyperscalers.
Speaker 3: So all you're talking about your alphabet, you're talking about
Speaker 3: your Microsoft microsycroso.
Speaker 7: Yeah, and Amazon so and it was forty five percent
Speaker 7: last quarter, So that exporture grew, right, I mean, and
Speaker 7: they're shipping more blackwell. So when you connect it to
Speaker 7: clearly there is and these are customers that are buying
Speaker 7: chips in bulk, so they need some pricing, you know.
Speaker 3: To Does that play to the margin that they're getting
Speaker 3: a break?
Speaker 7: I would assume? So, right, Yeah, if you are a
Speaker 7: customer that is paying, you know, twenty billion dollars a
Speaker 7: year or two in Vidia, you want some pricing break
Speaker 7: compared to the other customers, not.
Speaker 3: Just a free basket.
Speaker 1: It was a question that I couldn't answer fully because
Speaker 1: I don't have the depth of knowledge that you do
Speaker 1: Man deep And ultimately, the issue of getting to Blackwell
Speaker 1: and the heating issues that we've seen and the ultimate rollout,
Speaker 1: has that cost them any margin? And does it cost
Speaker 1: them to have top going back and fixing things or
Speaker 1: is it on someone else to keep using ensuring it's working.
Speaker 7: So there were concerns around Blackwell, and look, if you're
Speaker 7: a customer, you would want to wait until they resolve
Speaker 7: all these issues. But in Media moved at a pretty
Speaker 7: fast pace in terms of fixing those issues and actually
Speaker 7: getting eleven billion dollars of revenue in the quarter. So
Speaker 7: the fact that they were to do it so quickly
Speaker 7: shows good execution. But they're shipping a lot of these
Speaker 7: chips to the hyperscalers, who again I feel, have to
Speaker 7: be incentivized to take those bulk shipments, and that could
Speaker 7: have played in terms of the lower margins.
Speaker 2: And we're the concerns about overbuild answered where they put
Speaker 2: to rest.
Speaker 7: I mean they look at all of their suppliers TSMC,
Speaker 7: Micron on the HBM side, all of them are still
Speaker 7: supply constraints, so I can't imagine, you know, there is
Speaker 7: any chance of an overbuild here. There's clearly more demand
Speaker 7: than supply and all the suppliers are continuing to expand capacity.
Speaker 7: So that is the least of my concern here. It's
Speaker 7: more the competition and the lower gross margins and the
Speaker 7: training versus inferencing is the key point that I hope
Speaker 7: he addresses on the call in relation to deep sea.
Speaker 3: I'm just again going to people who maybe are not
Speaker 3: so in it, like you guys are the training versus inferencing,
Speaker 3: Like what do they need to kind of understand. I
Speaker 3: want to go back there because I do feel like
Speaker 3: that's the big factor here.
Speaker 7: Building one million GPU clusters right now, the largest sized
Speaker 7: cluster is a two hundred K cluster that XCAI has built,
Speaker 7: and I think META is also a building, and.
Speaker 2: That's for training or for enfortan training training.
Speaker 7: You build a one million or one hundred thousand chip cluster,
Speaker 7: you're using it for training, You're not doing inferencing because
Speaker 7: inferencing patterns are very volatile, and inferencing is more tied
Speaker 7: to usage. You know, if I am using a chat
Speaker 7: gipt during the day, the traffic will be more, at
Speaker 7: night it will be less. So I'm not going to
Speaker 7: keep the chips under utilized. I want one hundred thousand
Speaker 7: chips to be utilized at maximum capacity. That's why training
Speaker 7: is what is used for, you know, the large GPU clusters.
Speaker 2: But to that point, even to the inference point we learn,
Speaker 2: I think today that deep seek is sort of doing
Speaker 2: surge pricing when it comes to when you're using the
Speaker 2: app because they want people to use it not during
Speaker 2: peak times because that is expensive.
Speaker 7: Yeah, I mean look, and that goes to the under
Speaker 7: supply aspect, right, so the market is still under some
Speaker 7: and that's where wherever you can find capacity, you use it.
Speaker 3: We know, you guys both have to go. Caroline, So
Speaker 3: you're sitting down with Jensen, what do you want to know?
Speaker 1: I want to know about For me, I want to
Speaker 1: know about China, and I also want to know about
Speaker 1: this capacity issue that we keep talking about and how
Speaker 1: ultimately at Easy is with the amount that demand he
Speaker 1: still go going all.
Speaker 3: Right, same thing for you, man, Deep, you're sitting down
Speaker 3: with Jensen.
Speaker 7: Hey, right, training, Just tell me your training share right now?
Speaker 7: Is there still sixty forty? Has it changed? And what's
Speaker 7: the outlook?
Speaker 3: All right?
Speaker 4: Guys, you rock.
Speaker 3: Thank you so much. Man Deep seeing Bloomberg Intelligence senior
Speaker 3: tech industry analyst here in studio along with Caroline Hide
Speaker 3: Coast of Bloomberg Technology and Bloomberg TV. Check out Man
Speaker 3: Deep's research. It'll be on the Bloomberg tomorrow. Caroline will
Speaker 3: be all over it on Bloomberg Technology. That comes your
Speaker 3: way at eleven am Wall Street time on Bloomberg TV.
Speaker 2: All right, well, you heard Caroline mention China just now,
Speaker 2: and that's kind of what we want to talk about
Speaker 2: with Michael Shepherd. He's Bloomberg News senior editor for Technology
Speaker 2: and Strategic Industries. He joins us from our wash Rington,
Speaker 2: DC bureau. As Red Brown pointed out to us, Michael
Speaker 2: just a few moments ago, no mention of China in
Speaker 2: the press release. We are waiting for Jensen to take
Speaker 2: questions from analysts about that. What are the concerns around potential.
Speaker 2: I don't want to use the term sanctions, but restrictions
Speaker 2: on what in Nvidia can sell to China.
Speaker 6: Well, that's a better way of putting it, Tim, because
Speaker 6: really what in Vidia has confronted it's not some it
Speaker 6: sanctions or penalties, but limits on the types and quantities
Speaker 6: of chips that can sell to Chinese entities. And of
Speaker 6: course this is in response to the challenge that the
Speaker 6: world's second largest economy poses to the US in advanced technology,
Speaker 6: but especially in this emerging area of artificial intelligence. And
Speaker 6: Donald Trump upon taking office, he made it a national
Speaker 6: priority to preserve dominance and artificial intelligence. But that was
Speaker 6: also a theme during the Biden administration, and some of
Speaker 6: these restrictions that have really been deviled in Vidia at
Speaker 6: times date to the Biden era and President Joe Biden,
Speaker 6: a week before leaving office and handing over the reigns
Speaker 6: of power to Donald Trump, imposed a three tiered system
Speaker 6: of limits on country's access to sensitive chips for AI
Speaker 6: of the likes of which that in Nvidia produces. And
Speaker 6: so we are waiting to see what Jensen Wang will
Speaker 6: have to say about this, what sort of challenge as
Speaker 6: opposed to the business, and what sorts of steps has
Speaker 6: he taken then maybe try to talk Donald Trump out
Speaker 6: of it.
Speaker 3: Has he been so has he been to the White
Speaker 3: House yet.
Speaker 6: And he was one of the last of the big
Speaker 6: tech executives to pay a visit to the White House
Speaker 6: and see Donald Trump. There was no visit by Jensen
Speaker 6: Wang to mar Lago during the transition, and it wasn't
Speaker 6: until January thirty first, that week when deep seek really
Speaker 6: shook the markets, and especially in Vidia. It was a
Speaker 6: Friday that he went in to go meet with the
Speaker 6: President and talk generally about artificial intelligence, of course, but
Speaker 6: you had to imagine that export controls came up. Nvidia
Speaker 6: certainly has railed against them. We saw statements coming from
Speaker 6: their spokespeople, as you know, we heard the Biden folks
Speaker 6: talk more about them. And then as the Trump team
Speaker 6: came in and saw a deep Seek's breakthrough and thought, hey,
Speaker 6: we have to do something ourselves. We may need to
Speaker 6: further tighten these restrictions. Well they weighed in again. But
Speaker 6: Jensen Wong has been quiet about it. So this will
Speaker 6: be a moment for him to say something.
Speaker 2: You know, I think it was Caroline, I can't remember
Speaker 2: exactly who it was on our on our Eric Carrol
Speaker 2: who mentioned that in the press release, the names that
Speaker 2: are mentioned cloud service providers aws Core Weave, Google Cloud Platform,
Speaker 2: Microsoft Aser, Oral Cloud, Oracle Cloud Infrastructure, AWS, Cisco companies,
Speaker 2: all US companies, And I don't know if it's if
Speaker 2: it's a political statement or if it's just a statement
Speaker 2: of the fact that these most prominent companies are based
Speaker 2: in the US. Is there a read into this, Michael,
Speaker 2: that this is a company that's making sure it's touting
Speaker 2: its American connections.
Speaker 6: So many companies, Tim McCarroll, are trying to get on
Speaker 6: the right side of Trump in that sense, and in
Speaker 6: this case, the facts may be conveniently aligned to whatever
Speaker 6: Trump and the new administration may want to hear about
Speaker 6: American companies buying from an American provider, namely in Vidio.
Speaker 6: But of course, so many of Nvidia's chips are made
Speaker 6: in Taiwan by TSMC, so that has to be another
Speaker 6: area of concern for Jensen Wong as he hears Donald
Speaker 6: Trump talk about potential tariffs on semiconductor imports. He hasn't
Speaker 6: imposed him aet he hasn't really announced him yet, but
Speaker 6: it is something that we are watching for in the
Speaker 6: coming weeks, and of course, as it will be delivering
Speaker 6: this address to Congress next Tuesday, evening, and that could
Speaker 6: be a moment where we hear him talk in somewhat
Speaker 6: more detail about this. Remember, the semiconductor supply chain is
Speaker 6: so interconnected globally. You have foundries in Taiwan making chips
Speaker 6: that are designed here in the US, and and so
Speaker 6: all the production and design are happening in a lot
Speaker 6: of different places. So when you see tariffs and export
Speaker 6: controls imposed, you know, the trade flows and the impacts
Speaker 6: really ricochet through the supply chain and all the way through.
Speaker 6: You know, when you get to end use products like
Speaker 6: computers and like cars, you know where we're going beyond
Speaker 6: the data centers that we think of with Nvidio, But
Speaker 6: speaking more broadly on the semiconductor sector, the ripple effect
Speaker 6: through the supply chain will be really strong.
Speaker 4: Michael.
Speaker 3: And you know, certainly something you guys and you are,
Speaker 3: you know, on top of on a regular basis in
Speaker 3: terms of things coming out of the White Houspital. Do
Speaker 3: you wonder about when it comes to ai and what
Speaker 3: President Trump wants to see. Obviously he wants to protect
Speaker 3: the US industry, the US chip industry, but so many
Speaker 3: of these big tech companies here in the United States
Speaker 3: are global players. It's a fine dance, right in terms
Speaker 3: of their top line, their revenue, their growth. Yes, the
Speaker 3: US market obviously important, but global markets are important as well.
Speaker 6: That's a great point, Carol, because when you think about
Speaker 6: one of the best known US chip companies, it also
Speaker 6: happens to be one that is struggling existentially right now,
Speaker 6: and that is Intel. And it has sales overseas, but
Speaker 6: including in China. So any export restrictions, any move that
Speaker 6: could affect its ability to do business in China could
Speaker 6: be bad for Intel and in Vidia as well. You
Speaker 6: know the You know, it's not like Nvidia has no
Speaker 6: business in China, but the most sophisticated chips are or
Speaker 6: off limits. Now the administration is wighing weather to lower
Speaker 6: the threshold on those limits, making even less advanced ships
Speaker 6: made by Nvidia and other makers too off limits for
Speaker 6: Chinese buyers, barring a license of permission from the US
Speaker 6: Commerce Department. So they are thinking about this, and we're
Speaker 6: looking at a series of restrictions too, and these include
Speaker 6: getting Japan and the Netherlands to get companies like Tokyo
Speaker 6: Electron and ASML. These are the businesses that make the
Speaker 6: semiconductor manufacturing equipment, these huge photo lithography machines that are
Speaker 6: really finicky and expensive. What they want is they want
Speaker 6: Japan and the Netherlands to limit maintenance of these machines
Speaker 6: that have already been sold to China. You know, they're
Speaker 6: looking at every which way to contain China in this area.
Speaker 3: Michael, hang on for a second. I just want to
Speaker 3: recap because we are seeing shares of Nvidia up about
Speaker 3: two point two percent now in the postmarket trade, after
Speaker 3: market trade. They've been bouncing around a lot gains and losses,
Speaker 3: but it does look like they're kind of holding at
Speaker 3: this level again, a two point two percent gain. Keep
Speaker 3: in mind, I'm looking at our Ian King his reporting
Speaker 3: and video giving solid quarterly results and a bullish revenue
Speaker 3: forecast for the current period, even if the numbers didn't
Speaker 3: reach the blowout level that some investors were banking on.
Speaker 3: And of course we're waiting for some headlines tim here
Speaker 3: as the call will get underway soon with the C
Speaker 3: suite and Jensen Wong of Nvidia so big.
Speaker 2: I think the big question that I have is how
Speaker 2: much Insight will get And we don't know this yet, Michael,
Speaker 2: but how much Insight will get on the call into
Speaker 2: invidious relationship with China and to what extent restrictions are
Speaker 2: set to affect the company.
Speaker 6: And that is a key question for investors going into
Speaker 6: this because when Deep Seek emerged onto the scene, and
Speaker 6: remember Deep Seek was a trigger for the Trump administration
Speaker 6: to think about tougher restrictions on Nvidia's chips, and it
Speaker 6: was also an existential moment for in Vidia itself. You know,
Speaker 6: Deepseeak was able to produce its chatbot on the cheap,
Speaker 6: undermining this whole idea that hey, we need Manhattan Project
Speaker 6: level CAPEX to be able to produce these breakthroughs in AI,
Speaker 6: and of course to do that you need tons and
Speaker 6: tons of Nvidia accelerators. Deep Seek raise questions about, well,
Speaker 6: maybe we don't need quite so many work quite so much. Nonetheless,
Speaker 6: we've seen the hyperscalers all, you know, reinforce their commitment
Speaker 6: to heavy CAPEX tens and tens of billions of dollars
Speaker 6: in plans for data centers and chip purchases.
Speaker 3: All right, So appreciate being able to get this perspective
Speaker 3: and roll it in. It's such a big part of
Speaker 3: the Nvidia story. Michael Sheppard, thank you, as always, Senior
Speaker 3: editor for Technology and Strategic Industries out there in our
Speaker 3: Bloomberg News Bureau in DC,