On this episode of The Six Five Webcast, hosts Patrick Moorhead and Daniel Newman discuss the tech news stories that made headlines this week. The handpicked topics for this week are:
- AMD Datacenter & AI Event
- Salesforce AI Day NYC
- IBM Quantum Utility Breakthrough
- Oracle Q1 Earnings
- Lenovo AI Disclosures
- Microsoft Activision Deal Blocked in U.S.
For a deeper dive into each topic, please click on the links above. Be sure to subscribe to The Six Five Webcast so you never miss an episode.
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Disclaimer: The Six Five Webcast is for information and entertainment purposes only. Over the course of this webcast, we may talk about companies that are publicly traded and we may even reference that fact and their equity share price, but please do not take anything that we say as a recommendation about what you should do with your investment dollars. We are not investment advisors and we ask that you do not treat us as such.
Transcript:
Pat Moorhead: Hi, this is Pat Moorhead. We are live for another Six Five Podcast. It is Wednesday. It is different. Usually we’re doing this on a Friday, but to Daniel Newman’s credit, we are cranking this out because Dan has to fly back from an undisclosed location on Friday. But the great news is we have so much content and it’s 2:00 PM Central, that we can crank this thing out midweek. Dan, how you doing?
Daniel Newman: Hey, man. Listen, sometimes it just works out and this week I’m in an undisclosed location, although if you look at Twitter, you’ll see that the Futurum Group was the sponsoring research partner of the Digital Enterprise Show in Malaga. I may or may not be overseas somewhere near that location.
And listen, there was so much news that hit so early in this week. I woke up this morning inspired and jet-lagged and I said, “Pat, let’s do this thing today because I’m worried if we wait it won’t get done. And there’s just too many good things to provide our killer commentary on this week.” So good to be here, buddy.
Pat Moorhead: Yeah, so good to be back. I mean there could have been two events, three events I could have gone to, but five weeks on the road, couldn’t do it. Couldn’t do it. But I’m glad we’re here. And by the way, if it’s your first time on the Six Five or listening to the Six Five or watching it, you’ve been living under a rock because we do think we are the preeminent leader in technology analysis. There we go. Did I just say that? I mean, we love our fans, but we do try to bring it. Also, we’re going to talk-
Daniel Newman: It’s not about you.
Pat Moorhead: What’s that?
Daniel Newman: It’s not about you. It’s not about-
Pat Moorhead: No, but sometimes it’s about you. So anyways, we’re going to be talking about publicly traded companies. Don’t take anything we say or infer as investment advice, find a professional. But I’m super excited for the show. Again, midweek and we have six incredible topics that we cover from five to 10 minutes each. We’re going to be talking about the AMD data center and AI launch they had. Daniel attended Salesforce AI Day in New York City. That was one of the events I could have attended but couldn’t. IBM had a recent Quantum breakthrough. In fact today, a few hours ago I think, needs to be shared. Oracle beat beat raise, we’re going to be talking about them. Lenovo made a disclosure this morning as well about how it’s going in AI that we think is worthy of discussion. And finally we’re going to talk about Microsoft’s Activision deal hitting a snag here in the United States.
So I am going to start, I’m going to call my own number. So AMD had a big data center and AI event in San Francisco, which I was not available to attend but was invited. But I copiously took notes and tweeted as Lisa Sue and company were going through all of the announcements. And I got to tell you it was a big one. I mean literally they covered at least eight very meaty topics. They talked about, first of all, you had the data center side where they talked about three flavors of EPYC, Genoa Bergamo, Genoa X and how they were doing in those areas. They also talked about the next generation DPU, Pensando DPU, but particularly investors wanted to know, and quite frankly the entire market is AI crazy, is what is the company doing in hyperscaler data center AI?
And AMD did not disappoint. They made a bunch of announcements. So first of all, they gave an update on the Instinct MI300A that’s targeted at HPC markets. That is essentially a CPU, a GPU with a ton of memory on it, really for HPC markets. It may or may not be computing with Nvidia that has a combination with the GRACE platform. They also brought out the MI300X, which I think was really the star of the show, was what everybody was waiting for. It is for large language model inference, sampling Q3, 192 gigabytes of memory and where most of Nvidia’s cards have 80 gigs of memory, which essentially equates to being able to do more work with less GPUs. Super interested to see though how it competes with Nvidia’s 188 gigabyte H100 NVL solution.
Andy showed running a 40 billion parameter hugging face model on one card and this was super impressive. They also brought out a new platform called the AMD Infinity architecture platform. That’s eight MI300 cards pulled together on one platform with infinity interconnect as its interconnect. So cool stuff. Now let me boil all this text speak down to where I think AMD is an AI. But I want to first caveat that I think the way to look at AI is holistic, going all the way from the smallest IOT endpoint to the hyperscale and everything in between. That is the full capability. Its training, its inference, its CPU, GPU, NPU, FPGA across multiple types of platform. But when we narrow in on this hyperscale AI accelerator market that AMD CEO, Lisa Sue, says will be $150 billion, coming up from $30 billion this year. We have to auger in on that.
And AMD did not disappoint with this MI300X. Now, did I expect AMD to come out with some statement that they were going to put a knockout blow on Nvidia? Absolutely not. You’d have to be a fool to expect that. And some short term investors sold AMD stock based on this. I view this as at the beginning of the AI data center move that AMD is making, not some middle point. Now there’s been a lot of work on high performance computing, but don’t confuse that with AI. Sometimes they cross, but many times they don’t. Now I believe that in the end, I would say within the next six months we will see a major hyperscaler make an announcement with AMD and they will drive some serious volume. Now, is that based on some mistake that Nvidia is making?
Absolutely not. But here’s the thing, these hyperscalers want choice and Nvidia has 95% market share in the hyperscaler data center AI accelerator space. So AMD I think can pick up 10, 20% share over the next four years. But that still means that Nvidia can drive a heck of a lot of volume. And by the way, I also think Intel is in the mix. So again, anybody who thinks this is going to be a winner take all scenario doesn’t understand technology ecosystems or for that matter, business logic. And then by the way, if all that doesn’t work, as we saw with Microsoft in 1998, Google and Amazon in this decade, the global regulatory folks show up on your doorstep. But again, I don’t think that’s going to happen. I think AMD will get 20% of that market by 2027. But AMD first needs a major hyperscaler to show up with big support that leads to big volume and revenue. If not`, all bets are off. Check out my Forbes article will where I auger into 1,200 words of pure joy and analysis on AMD’s event.
Daniel Newman: You’re done?
Pat Moorhead: I’m done.
Daniel Newman: Anything else?
Pat Moorhead: Nope.
Daniel Newman: No one? All right, listen, that’s really good analysis. I’m sitting there and you did hit a lot of the talking points one to one that we’re were on my mind. So I just want to maybe make a few reiterating points about what happened yesterday. First of all, this was a seminal moment because what we just saw was the first company that’s really declaratively showing a competitive roadmap to Nvidia right now in, and yes, I’m talking mostly related to data center GPU and hyperscale AI. And this has to happen. I want to be very clear about that. Technology does not move at a pace that it’s capable of if in fact you have a single sole source competition or lack of competition you could call it. Let’s be very clear, right now when it comes to the AI stack for enterprise, it is a monopoly. There’s really no other way to look at it. You have-
Pat Moorhead: By definition it is a monopoly. Anything over 50% market share in a certain market, then the only question is are you abusing it?
Daniel Newman: Right, and then that’s more or less something that the TomToms on the street are suggesting as the company has gotten bigger, it has had more power in terms of how it bundles its solutions. It’s had more pricing power margins up in the mid-seventies now, the kind of power that Intel perhaps once enjoyed when it had a much more significant market share than it has today. And let’s face it, everybody called that into question and called for potential abuse of that power. And it actually to some extent, limit it. And you see over time one mistake or two mistakes or a few mistakes and suddenly that monopolistic power or just even that market dominance can quickly fade. But let’s even going away from some of the regulatory concerns, AI is not… We are still in the infancy of seeing the applications and the power of AI.
We’re in the earliest days of seeing the number of workloads. For a long time we’ve thought about data centers through the lens of compute data centers for running the traditional workloads applications, ERP, things that we’re thinking about for our business. There’s a whole new data center build out on a global scale that’s going to need to take place for AI. And so you’re going to walk into these Equinix facilities and you’re going to turn right and there’s going to be traditional data center compute and you’re going to turn left and there’s going to be AI data centers with racks and racks and racks or what do you call them? Rock them, rack them, rock them. There’s going to be racks and racks and racks of AI, of compute power for AI workloads and networking for workloads. And that’s going to be the next big boom of opportunity.
So when Pat, you talked about a 20% market share claim, I think they could get 20% without actually taking any revenue share. Meaning Nvidia could continue to grow substantially while AMD ends up with 20% of the market because there is just so much market and the capacity for one vendor to take care of all the business opportunity is unlikely. The other thing is these hyperscalers, you already see that they’re moving dependence away from any of the traditional semiconductor and fabless manufacturers and a lot of them are carrying up with ARM or others to build their own ASICs or chips, whether that’s been Facebook, Meta, whether that’s been Alibaba. So anyways, that’s another big thing that’s going to happen.
But I said this yesterday Pat and I think I’ll end on this note. Yesterday was a big moment because what the market needs is more than one. The market needs more than one and it also needs an open source player to come in. If you look at right now, the opportunity for an open source means much more of an ecosystem friendly play. So you can bring together the networking, you can bring together the compute, you can bring together the applications and the frameworks, and you give the community a chance to build, you will see a certain share of the market. I think your predictions are probably in the right ballpark and I’ll end there.
Pat Moorhead: I appreciate that. So let’s talk more AI shocking about Salesforce. Dan, you and I have talked about Salesforce AI a ton. What did you learn in New York?
Daniel Newman: Look, I had the chance to get out to New York to hear from Mark Benioff for what I’d say is a very large limited crowd. It was a special opportunity to be out there, but it was a mix of customer, partner, executive and a very small group of analysts. I missed you there buddy.
Pat Moorhead: I missed you too.
Daniel Newman: We got to hear from Gucci and he did create a new word when he talked about how they were using Customer 360 and AI and he said he’s going to Guccify. And I was thinking of you, Mr. Montclair there, if you could Montclarify something for me. And in all serious look, he started off in his first quote was from Mark Benioff was, and I jotted it down, “Maybe it’s the most important technology of any lifetime.” So you hear most important technology of this lifetime, he said of any lifetime. And I think that resounded with me. A couple of things I walked away with that are a little bit more macro. On the macro level things for me is one, is there is a important demarcation going on right now between companies that have long been in AI and understood and supported and invested and those that are in their me too moment, meaning, oh all of a sudden it’s a big deal, we’re going to have an AI story.
Salesforce has had an AI story for a long time. They’ve been focused and investing on a huge level, 210 patents in AI. So they’ve been spending money developing technology more than a decade working in LLMs, going back many years. And you remember hearing about Einstein. I mean, Einstein was announced in 2016. That was when Benioff promised an AI in your boardroom to help you make better decisions. So it’s been part of the ethos for some time. Having said that, I don’t think it’s landed particularly well for Salesforce. I think to some extent the company looks like they’re a little bit more of a follower in terms of how it’s been perceived, coming out with all their GPT products. So the question was really what does it do? Why do you need it at the app layer if you can get it all in Vertex or you can get it all in open AI on Microsoft Azure AI.
And I think what it comes down to is this is a great example of where that data layer comes into play. And they showed a really wonderful example of how proprietary data and open internet data can make the big difference. And Pat, you and I have played around with using a Bard or a ChatGPT to do a press release. Remember we kicked that one around and we were like, “Oh, this is pretty good.” But the problem is it doesn’t have any of that important proprietary data. So they were showing some great examples of how you could write a custom sales letter to a prospected customer where you could give references and you could then give specific examples and timelines. And because you have all the sales cloud, data cloud plus the open LLMs tied together, now instead of just writing that generic release, it could write a very prescriptive specific release, but then on top of it adds all kinds of layers of governance.
So for instance, if you wanted to give references, it would have the ability to redact a name or a company name or a specific example, but still provide and write for you a more genericized letter. And so they were showing a really real world example of how these two worlds are combining in the app layer to start creating better content and work through a sales funnel. So that’s just an example, but I really thought that was powerful to see how really what we’re so impressed by these generic generative creations really are crap. You could never send these things.
Someone even said that to me, Pat, if I send a letter and you want it to look like it’s coming from me, it’ll probably have DN at the end and it would never say like, “Hello Mr. Something.” It would always be like, “Yo, Sir”, or whatever it is it sounds like it’s me. And that’s the other thing with Data Cloud and LLMs that it can do is it can look at the history of all the things you’ve written and all the interactions you have with customers to get a sense of your style, your tone, and start to make things seem more personal. So I thought that was a really powerful example. But let me just tell you what I tweeted that Mark Benioff liked because that was-
Pat Moorhead: It’s not about you Daniel.
Daniel Newman: That was important. That was important that I figured out a way to get that in. But really what resonated with me, and actually I had the chance to talk to the Wall Street Journal about this, was the gen AI and its importance to create trust. Because really right now I think this is where a lot of the confusion exists. So in order for Salesforce or any company to win, there’s three tenets of trust that I’ve identified, and Salesforce really reiterated these, which is something I like, but one is trusting the quality of the output. We keep hearing about hallucinations. Salesforce plus Data Cloud believes they can give you more to trust in the quality of output. Two, trust in safety, bias, transparency. To me that’s somewhat table stakes that you know, IBM, Amazon, Google, Microsoft are all saying they’re doing that, but Salesforce competently is ticked that box.
And then the third is trust in how the data gets used. Salesforce was adamant that when they put their tenets of trust in AI, your data is not our product. Data residency and compliance, customer control and privacy, enterprise scale, built in security, ethical and design and practice. So they’re promising that there is no risk of your data being used for anything other than what you want to specifically use it for. And right now that’s an important message from any company playing in this space. There’s a lot more, but I could keep going forever and I just want to leave a little bit of space for you to weigh in.
Pat Moorhead: No, I appreciate that. So due to a family matter, I wasn’t able to auger in and watch this, but I am, but I have read many of the documents that came out and a lot of the press coverage, I just want to say this upfront. So Salesforce is in a similar position I think that IBM is, even though they’re in different businesses with AI. You had IBM that came out with Watson in 2011 and it really got a lot of fanfare at once, but it really didn’t end up driving anything incrementally for IBM. Same thing with Einstein in 2016. I think we did a podcast on this or it didn’t make sense to me that chatbots were just not smart enough. So I didn’t see how Salesforce, who by the way understands their SaaS swim lanes really well, was going to deliver something that nobody else could deliver and they didn’t.
Einstein did not work well, not necessarily just because of Salesforce, but because overall bots weren’t intelligent, generative AI was here, we were using deep learning and machine learning. But I do believe that when you separate this generative AI into consumer and enterprise, there are different success characteristics primarily because the type of data that you’re looking at is going to be more focused. It’s not world data, it’s not beating somebody on jeopardy, it’s not winning some history award. And I think what we’ve seen recently, lawyers trying to use it in the courtroom where it created cases that came not through a centralized legal service using generative AI and that data set, but world knowledge. It was creative. So when I look at Salesforce’s sales service, marketing, commerce, data, cloud, even visualization with Tableau, MuleSoft automation, the things you can do with Slack. I mean heck, Slack at its core is an intelligent way to communicate through chat and I connect that to ChatGPT and the way that we’re working, there’s a tremendous amount of opportunity here.
And like let’s say Oracle Fusion, like IBM where they’re using narrow data sets, I think real magic is going to happen and I think jobs over time are going to be transformed. There are some jobs that are going to go away. I would call those taskmaster jobs and there will be some that will be added. So I think Salesforce is right where it needs to be and that it’s taking intelligent conversations about it. They’re showing a certain level of maturity and thought leadership and the areas, the SaaS areas that they’re in are right for generative AR. The question is just can they either gain market share, can they increase the basket? Overall the vision of Salesforce is to be able to combine these disparate services into a horizontal platform in not the same way as Google and Microsoft, but in a way that represents that shows the power of the platform.
I’m going to do more research on it and we’ll be putting out a note soon. So let’s move off the prior to AI topics and move into IBM Quantum. So listen, in the history of the Six Five, Daniel, you and I had a very consistent conversation about, hey, things are going to get really interesting when we see business value driven incrementally through Quantum. Now the reality is on any new type of technology it has to go through a certain process, whether that’s 5G that starts with research, whether that’s generative AI that started with research three or four years ago through a seminal Google White paper that came out, the same is true for Quantum. So we’re in this zone of trying to look at what the researchers and scientists are coming up with to give us a better view when there’s going to be incremental commercial volume and you’re going to want to pay attention to this.
Essentially IBM and Berkeley came together, did some serious research and essentially showed that you can show Quantum value without getting to the point where you need perfect qubits. Because the foregone conclusion and why people are like, “Oh this is 10 years away”, is that we need to get the qubits to perfection with fault tolerance. And what IBM and Berkeley showed is that combining error mitigation with over a hundred qubit Quantum computer, you can show value that cannot be done by today’s supercomputer with a CPU and a GPU. I’ve, well not me, my Quantum awesome analyst Paul Smith Goodson has published a Forbes article. I actually did an interview with the Head of Quantum at IBM, Dr. Jay Gambetta when I was over in Paris. So I’ve been sitting on this forever. It’s pretty exciting. Check it out. I think Quantum is going to be here and adding commercial value before most anybody else thinks that. I think this is more evidence of that.
Daniel Newman: So let me ask you Pat, and normally I just come in and opine, but for a long time we have had this thesis that Quantum is cool, but it’s like for 1% of 1% of 1% of the human population that are physicists or some type of deep engineers that can understand just extraordinary technical prowess. And what’s happened is Quantum computing is in lost. Remember Shama Playa Patiyah said it’s uninvestible?
Pat Moorhead: Uninvestible, yes.
Daniel Newman: And mostly because the word is utility. And I saw Jay Gambetta quoted in the New York Times saying that that’s what this moment is about. This moment is about finding utility. Is that kind of how you see it?
Pat Moorhead: It is. I mean it solved a physics problem using noisy qubits that a supercomputer can’t. And it literally went head-to-head with it. Are we ready to parse this off and have Salesforce and Oracle Fusion use it tomorrow? No, absolutely not. But what it did show is we didn’t need to necessarily overcome having perfect qubits or what’s referred to as fault tolerance. So to me this is an in-between state that most people out there had not considered because right now people are lining up out there, they have either these perfect qubits, like 12, so can’t do much. And then you have these very imperfect qubits that are super noisy and you have thousands, tens of thousands. There was nothing in between. And the approach that IBM had taken, which everybody was like, “Hey, love what you’re doing IBM, the quality and the noisiness of what you have out there.” And what IBM is doing is they are correcting those qubits farther up the path, which I think is something that people hadn’t thought of.
Daniel Newman: And for a long time by the way, there was a lot of criticism of superconducting. A lot of the ion trapping companies just said that they would never get the fault tolerance. I’d been somewhat convinced, but at the same time betting against Google and betting against IBM from a bunch of smaller players, maybe there is a certain amount of experience that we have that would say that those aren’t great bets. But remember Pat, if we say anything far enough into the future, we can be right. You just got to keep pushing.
Pat Moorhead: Exactly. Just don’t put a… And by the way, Daniel, when I was at AMD and Nvidia was working with all of these researchers on AI, it looked like a bunch of BS where GPUs were made to do compute and when I was at AMD, we had ATI. We were working on it as well and it looked like the Kobayashi Maru and then boom, University of Toronto used Nvidia GPUs to do image classification. Is it a cat, is it a dog, is it a human? And then it was like people became believers. We are still waiting for that University of Toronto moment for Quantum. But I don’t think we’re 10 years away, I just don’t. Five years away feels a lot more comfortable for me right now.
Daniel Newman: There’s something that maybe this generative AI boom can be attributed to in terms of making us smarter. And that’s the law of diffusion of innovation is being short-circuited, meaning the diffusion of innovation used to take months to years from the earliest adopters to laggards. And now what we’re really seeing is, would you say that someone that’s just trying ChatGPT for the first time today is probably a laggard at this point?
Pat Moorhead: Yeah.
Daniel Newman: You’re lagging. And what I mean is it’s just not true. When Blackberry came into market, there was a few years by which Blackberry users would’ve been considered your early adopters, not like your leading edge, but just early adopters of smartphones. If you had an Apple iPhone in 07, 08, you were an early adopter of the iPhone. And all I’m saying is it took a few years, Pat. I mean now we’re seeing things down to months, now an enterprise technology like Quantum is going to take longer, but don’t bet on the long tail and some of the predictions that it’s five and 10 years. These breakthroughs are coming faster and faster with less time in between.
It’s also another moment to just… I think the market grossly undervalues IBM’s research, and I know that we’ve said this a lot, but they don’t value the Quantum business at all when you look at the actual price of the stock. And I know that’s not our job, but I always look at that for ground truth, they don’t value the research they do in semiconductors, whether it’s around a nanometer or others. They just haven’t found a way to value it. And so I’m hopeful under Arvind Krishna and I’m hopeful that through whether it’s licensing or through the products they’re able to build and put into market here, that IBM begins to get credit for some of the really critical technology they’ve been able to roll into the market.
Pat Moorhead: IBM’s doing some great stuff and the way that they’re approaching Quantum is as if they’ve been through every major technology turn and they don’t feel like they were getting credit for credits due. So interesting stuff. My gosh, do we really have 1,700 people watching us right now on YouTube?
Daniel Newman: We do. We do.
Pat Moorhead: I think it’s because you’re in Europe, Dan. I think that’s-
Daniel Newman: Oh, what… Maybe we should pod on Wednesdays more often.
Pat Moorhead: No kidding. Exactly.
Daniel Newman: I mean, we did open the whole world to this thing. You should screenshot that by the way. It’s good social…
Pat Moorhead: For proof and evidence. Hey, let’s move to-
Daniel Newman: …Top 10.
Pat Moorhead: What’s that?
Daniel Newman: We could be up there with the all in guys talking to all enterprise tech though. I mean, they get to talk about Trump and things that drive huge crowds. We talk about the hard stuff. This is actually…
Pat Moorhead: I know. By the way, you said Trump and our viewers went from like 1,750 to 1,600.
Daniel Newman: Sorry, Obama.
Pat Moorhead: Exactly. Oh, there it go. No, it’s going… No. Hey, let’s get into something we know a lot better than politics and that’s earnings. Oracle beat beat raise. Dan, what the heck’s going on here?
Daniel Newman: First of all, have you seen the run? Okay, we got to do these victory laps from time to time. I think it was one of the first few times I ever went on CNBC, I had a city guy and me and it was like a bull or bear case and basically he was putting the price target at like 60 bucks and just beating up Oracle. No innovation, no disruption, bad business model, customers hate them. And I basically came in there and said, “I think you’re totally missing it.” This was right as Gen 2 Cloud was starting to take shape. You were seeing this run since the acquisitions of NetSuite fusion and this mountain of data the company has at its disposal. And I mean, just what a good quarter. I mean the growth fiscal revenue of 18%, 22 in constant currency. Remember that’s faster growth than Salesforce.
And I’m not saying that to knock Salesforce. I’m saying Salesforce has been a bellwether of software and growth and Oracle has found it’s a bit of its stride now. And Pat, some of the numbers I think that were really interesting and you and I both shared that cool app economy that shows how the company makes money, but outside of that there was some data points that they talked about in their growth. Look, infrastructure growth of 63% for the full year. So OCIs infrastructure right now is growing at about three times the clip of the other cloud providers. Now, they’re not breaking out infrastructure anymore to the degree which we would need to do a full on comparison, but Pat-
Pat Moorhead: I don’t know. No. Are you sure?
Daniel Newman: I don’t think they break out just IAS any more than they need to.
Pat Moorhead: They literally are breaking out IAS now, is Oracle…
Daniel Newman: No, Oracle-
Pat Moorhead: Oh right, right. Sorry, sorry.
Daniel Newman: I can’t compare the Oracle to, what I guess I’m saying is my assertion is at 63 for the year, 77 for Q4. They’re taking share. At this point Oracle is actually has to be taking market share now, albeit it’s a pretty small number at about $1.5 billion. But that is interesting because when you’re growing it three times the market rate, it means some customers, and I have to imagine it’s a combination of the more useful utilities, Gen 2 and also the aggressive pricing. But Oracle still has great margin. So I want to make that pretty clear. The other thing that was really Pat, that was pretty impressive was the 45% growth in their SaaS and cloud application business.
Pat Moorhead: Where did that come from?
Daniel Newman: It does not calculate. Again, are they taking business off of Dynamics and off of Salesforce and off of like SAP? They’re never ones to not tell you on their earnings calls. So they gave some good examples of customer wins that they they’ve taken. But Pat, these are really, really impressive growth numbers. Now that’s the cloud application business. Now I do want to be clear, they split out applications Fusion and NetSuite. So NetSuite’s growing in the mid-twenties, fusion’s in the mid-twenties, then the rest of their cloud application, which is some of their CX and apps and stuff that’s growing at 45%. But still a really impressive growth rate across the board. Company also had a pretty big announcement around some of what it’s doing around gen AI. And so it’s basically going after having low cost. They partnered with Nvidia but low cost GPU clusters.
So they’re going to take the pricing model, the low price model to the market. But this is something I’ve said for a while and it was verified for me. When I went to the Google executive cloud forum and I had customers and I was talking to some of the leaders, the ones that are actually doing the Google’s TPU and they were doing the Nvidia partnerships and I asked the question, I said, “As gen AI is scaling and you’re doing more AI with more customers”, I said, “Do the customers care which silicon they’re running anymore? If it’s all done in Vertex, if it’s all done using your front end?” And basically what they said is that there is a significant shift, they’re very bullish about Nvidia and they understand the value of that relationship. So they were not by any means poo-pooing that, but they basically did say that as more and more customers and startups, unless they’re doing these really large complex training and that customers are more interested in just the efficiency and cost of being able to spin up AI apps like in a gen AI app builder.
So it’s what’s going on there. So you do have to wonder, is there an interesting market opportunity for a pivot for Oracle for those that do have these big training workloads that if they can be the price performance leader in terms of offering the same hardware, will they have a chance to take some additional market? And clearly they’re doing so with traditional cloud workloads Pat, so it was an overall strong performance and of course you have a company that pays a dividend that consistently does buybacks and returns to shareholders. And so no matter what my T-shirt, Pat, of my rush class in college said, “Loved or hated but never ignored.” And I think that that’s really opera bow for Oracle, but the company just keeps executing and you got to give them credit for that.
Pat Moorhead: So I’m going to do a little bit of a victory lap as well. Gen one, I was brutal and I wrote brutal stuff about Gen one OCI because it wasn’t any good. It was overpriced, low performance, the technology was dated. To the company’s credit, Gen two is literally just a miracle. And if you look at when the infrastructure was created, it’s actually the youngest infrastructure architecture out there right now. So when Larry got on the call and he’s talking about generative AI and he’s saying, “Hey, we have the highest performance, lowest cost and the biggest amount of scalability”, most people might do an eye roll and say, “Okay, that’s Larry talking about Larry CTO and founder Larry Ellison and chairman.” But you have to pay attention to what he is saying given the success that they’re having with generative AI. And listen, I’m not confused about scale.
I know that AWS, Azure and GCP have more scale, but AWS started 19 years ago and Gen two I think is two to three years years old. And the business model that they have too is very interesting. Some cloud providers charge more for the basics than they do for the add-ons. And that said, that’s a theory that says, “Hey, if I can entice people with the add-ons and they pull through high-priced basics”, that makes sense. Oracle is pricing their basics low and their add-ons high, which is another way to do pricing. And their business success shows that it’s working again, whether it’s 20 times smaller, 10, I don’t care, this is a long game. You have to have scale and show up and you have to build it and then much bigger things can happen. So kudos to Oracle for the beat Beat Rays and the increased details, that 45% growth on SaaS apps, I have never seen that before.
What have they shown from Fusion and NetSuite has always been ERP. Now they showed ERP for both, but that’s basically a 20%, 20 plus percent. I’ve never seen this 45% and I got to dig in and see where this comes from. So Dan, let’s go into another AI discussion. So far we saw IBM, we saw Dell, we know we’re going to hear more from HPE about AI next week, but Lenovo wants to make sure that everybody knows what they’re up to and what they’re doing in AI. And you might guess given the market share increases of Lenovo’s infrastructure group and their capabilities at the Edge, that they would be doing some serious business in AI. And the good news is they are. So in a release and discussion that we had with Kirk Skaugen and team, Lenovo says that they have revenue to over $2 billion with AI.
And by the way, I really appreciate putting a number on it because it’s so frustrating. Companies that want to be known for AI, they might very well be known for AI and then don’t put any detail around the monetary impact. So Lenovo took their shot here. They also said that they’re going to make another $1 billion investment over three years to accelerate the deployment. And that’s driven by research centers of excellence and other technology investments. But here’s where I want to auger in. They said we have the most comprehensive AI portfolio and as analysts we always need to watch those types of statements. Well, I burrowed in a little bit to that statement and Lenovo sent me some proof points and essentially their measurement of being the most comprehensive is looking at think system servers, think Edge, think Station and think Agile Edge.
The amount of platforms that they have compared to HPE and Dell and I think IBM, and based on Lenovo, the way that they are measuring it, Lenovo does in fact have the most comprehensive AI platform portfolio. So thanks to Lenovo on bringing that out and surfacing that. Thanks for having the courage to actually have a number. We appreciate that and I’m going to look forward to following all the things in AI that you are going to do. I’m particularly interested in how you’re looking at models. What are some proprietary generative AI models that the company can tee up, who the company’s aligning with Companies like Hugging Face as an example, to get a better picture of what the company is doing in the future. But we know that what they’re doing today is making a difference and they put a number on it, $.2 billion
Daniel Newman: Yeah, Pat. Listen, the opportunity around AI has implications for every company, whether you’re a picks and shovels memory and networking and DPU or your applications, but somewhere in the middle the real hardware providers are getting a little bit lost in the shovel. And this is brought, whether it’s been Dell or HPE and now Lenovo, to really need to double down on making sure that their story resonates and lands. And whether we talked to Kirk Skaugen or Flynn Maloy and as they’ve been rolling this out to us, what I’ve really been impressed by is the commitment to the full stack. And instead of seeing yourself as the middle person in this overall opportunity, they’re seeing themselves as the one that does a lot of the customer interfacing. They are the provider of whether that’s the PC and the laptop or the core infrastructure, the GPUs.
I mean, people are buying their compute. They’re not actually going and buying it in most cases from the chip provider. They’re buying AMD from a Lenovo, from some sort of partner. The real way a customer gets their equipment comes through multi source, there’s something called a channel. And the channel is really, really important. Now, the massive investment, the multi-billion dollar investment is worth noting. I thought what they call the innovators program, that was also really, really a valuable thing starting to turnkey these Pat, because you know how I was going on and lamenting about the Google Gen AI app builder, it’s the same thing with infrastructures. How do I spin up that right hardware?
And the thing is not everything is going to be done in the hyperscale public cloud, but what if it is, Lenovo provides a lot of hardware to them as well. So Lenovo has the hedge going on there.
Pat Moorhead: Yes.
Daniel Newman: And so they’re partnering with the Edge, they’re partnering with ISVs, they’re investing hundreds of millions of dollars. They’re building software plus hardware solutions. They’re doing a lot of things right. And Pat, this has been reflected and don’t get confused about Lenovo’s, somewhat soft end of year numbers. That was all in the PC business.
Pat Moorhead: That’s right.
Daniel Newman: The ISG business and the servicing business has been really robust.
Pat Moorhead: 50% growth.
Daniel Newman: And I think that they need to get adequate credit for that. So this moment is really more about establishing that there’s a really critical role for companies like Lenovo that are the plumbing, in many ways, of all the requirements to deliver AI at scale. And it was a really positive announcement for the company. So it wasn’t like a, “Hey, we rolled out this new thing.” It was like a, “Hey, we have a story.” And as I alluded to a Salesforce Pat, I’ll allude to here, not a new story. This didn’t start with generative AI. They’ve been doing this for a while now. And so I think it’s appropriate that they raise their hands and say, “We’d like to get credit.”
Pat Moorhead: Good stuff, Dan. And I’ll add that unlike all the other OEMs, Lenovo has a hyperscaler business. So anytime you see the hyperscalers, there could be a chance that Lenovo was part of that. Let’s dive into our last topic. We have four minutes left. Microsoft Activision deal hits another snag, this time in the US and shockingly not just in the UK. What’s going on here, Dan?
Daniel Newman: I mean look, it’s not really any surprise, but it was worth covering that the FTC basically put a temporary request to block this acquisition, setting a hearing. The long and short term is that I think this is partially to Lina Khan, I think it’s partially that it needs more time to spend to really look at this deal. It probably wants to make sure that it gets a voice. A lot of credit was going over to the UK. Right now we’re in this anti-growth environment. Nobody wants to see big companies get bigger and certainly not on the watch of this administration, which really promised to enforce that. Having said that, very little real enforcement has been done. Now, you and I came out, the FTC hasn’t actually made any real comment by the way, on why they’re doing this. But Microsoft doesn’t seem to feel it’s that big of a risk for them.
They came out and said that this is going to give more choice to the gaming market. And Pat, I’m going to stick by what I said. I think there’s enough competition that besides the size of this deal, I can’t really figure out what we’re regulating. And I’m only saying that because between console, subscription services, mobile gaming, PC gaming, there just seems to be enough choice that, again, this is one of those where I just spin my wheels and I bang my head on the desk and go, “But the app store.” Why are we spending so much time on deals like this now? Are there certain titles that are extremely popular within this that could see some pricing power? Yes. But overall, Pat, I think this is another stop and pause moment. I think they will win out the US, I just don’t see it actually being stopped. But I think the optics here are showing that some additional consideration that it didn’t fly through, that some extra thought was given to this thing before ultimately making the decision to approve it.
Pat Moorhead: You sure didn’t want to talk more on this one, Dan?
Daniel Newman: Do you want me to talk more? That was fast.
Pat Moorhead: Seven minutes or so. No, I’m just kidding. No, listen, I’m going to fill in the blanks here. We just have one minute left. A regulatory bodies are seem to be places that innovation dies where they’re just not focused on the right things. I do think that this deal will go through given the right concessions. Microsoft, I’m sure has already given the Sony concession on that. And heck, you don’t make money off the gaming console, you make money off the game. So maybe this is Apple. They want some commitment that people will write directly to their metal API and their crappy notebooks that can’t run games right now because nobody wants to write the metal. But this is going to go through, this is a temporary stop.
But anyways, I think we exhausted all this content in here. Dan, thanks for tuning in. It’s pretty late there in Malaga, I’m sure, but thanks for tuning in, dude, really appreciate that. Hey, I’m going to take us home. I just want to thank everybody for tuning in to the Six Five. We appreciate you and we appreciate everything that you bring to the table. Thanks everybody for tuning in. We appreciate you and appreciate you coming in midweek. We’ll see you in 10 days.
Daniel Newman: 1,0 70 of you. Thanks for watching.
Pat Moorhead: I know, unless we decide to decide to do this on another Wednesday again. But stick in, 9:00 AM Central Time, our normal time, and take care. We’ll talk to you next week. Have a great week.
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
