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:
- HPE Discover 2023
- MongoDB Local NYC 2023
- Oracle EU Sovereign Cloud
- Adobe Earnings
- Intel Foundry Disclosures
- Oracle Generative AI Capabilities with Cohere
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.
Daniel Newman: Hey everyone. Welcome back to another episode of the Six Five podcast. It’s episode 173. We’re back on schedule. It’s Friday, baby, and we’ve got tech to talk about with my bestie in crime. No actual crime, by the way, if you’re listening. Mr. Moorhead, how are you doing this morning?
Patrick Moorhead: I’m doing great. I think I rolled in at probably about midnight. Took me about an hour just to chill and kind of get in there. But yeah, on the road the whole week, a robust five hours of sleep, but we are here.
Daniel Newman: Is that good now? Is that considered good, five hours? Is five hours a good-
Patrick Moorhead: No, five hours is absolutely terrible and a person my age, I need about eight to be optimal. But it’s okay, I’m caffeinated up and I’ve got my trusty Red Bull down here at the lower right hand corner if I need it for the end of the day.
Daniel Newman: Now, at your age it’s what? Dinner pretty soon, yeah?
Patrick Moorhead: No, we don’t eat dinner till like 4:00 PM now.
Daniel Newman: Okay, well-
Patrick Moorhead: In our household.
Daniel Newman: I know bedtime, they start to kind of work on the turn down service right around the time that the sun turns from the center of the sky over to the other side, over to the west.
Patrick Moorhead: I’d be pretty late now it’s happened about nine. No, but the sunsets are amazing.
Daniel Newman: And also here they are amazing. And by the way, I just want to say this, this is probably a coming of age moment, but there’s nothing wrong with going to bed before the sun sets on the long summer days. I’m just saying there’s nothing wrong with that. I really do enjoy sleep. I really do.
Patrick Moorhead: It is a little weird to go to sleep when it’s sunny out, but-
Daniel Newman: But it’s like 9:30. It’s like 9:30 and it’s still bright here because it’s awesome. So we got a great week. You and I just came back. We went coast to coast.
Patrick Moorhead: Yes, sir.
Daniel Newman: Because we are gluttons for punishment, we took the flight out Monday, headed out to Vegas, HPE Discover, big event at the Venetian Palazzo, and then we headed east. We jettison across the country on Wednesday, got in late Wednesday night and did MongoDB .local over in New York City. And then we took a late flight from Newark home, but that late flight got later because Newark, well it was Newark, it sucks. When we landed in Newark, we couldn’t get off the plane. When we tried to leave Newark, we couldn’t leave the plane. And the pilots kind of come on and they’re like, “Yep, Newark being Newark, we’re going to be delayed again.”
Okay, so just as a bit of background for our friends, fans, and audience here is, so if you go into New York, the thing to pay attention to is very simple. You can pick the two hour in and out of New York and JFK, kind of same with LaGuardia. And you might get off your plane quicker, but you’re going to spend more time in the car or you can have the benefit of the quicker to the airport experience only to spend more time waiting on your plane in Newark. The only way to actually get in and out of New York quickly is to not go at all, just to be very, very clear. All right, I’m glad we had that talk here. So we’ve got a great show this week. We’re going to be talking about HPE Discover, we’re going to talk MongoDB, we’re going to talk about Oracle a couple times.
They launched Sovereign Cloud that we need to talk about, but they also talk generative AI and we’re just going to go down the list. That’s just going to kind of be a thing until it’s not a thing and then it’s everything. We’re also going to talk about Adobe earnings and then there was a fairly significant disclosure from Intel that we think will be important to talk about. That definitely caused a stir and pullback on some of the recent gains that Intel had seen. Got to do the disclaimer thing. This show is for information entertainment purposes only. And while we will be talking about publicly traded companies, please do not take anything we say as investment advice. I’m so tired of saying that, but-
Patrick Moorhead: Do we even have to say it? I mean, would you actually make a trade based on what we say? If you are, you’re an idiot.
Daniel Newman: I actually think we’re pretty darn smart.
Patrick Moorhead: The market’s just like, like a company does something that you and I think is great and then stock goes down like 10%. I mean-
Daniel Newman: Yeah, but that only happens every other day.
Patrick Moorhead: None of this… I mean, we’re looking at it from a longer term perspective. I can tell you I look at it from a core value proposition standpoint and longevity.
Daniel Newman: Yeah, we’re definitely not looking at it in a super short term. And while we do work very closely with a lot of these tech companies, we know better than spilling the secrets because that wouldn’t be good for our business. But having said that, that’s the flow. That’s the story. And Pat, unlike you, when I host a show, when I’m the primary host of the day, I don’t call my own number first, that’s not my thing. I like to call your number first because you’re the best. So kick us off. Let’s talk HPE Discover 2023.
Patrick Moorhead: Yeah, so you and I spent three days there. I rolled in Monday morning and I guess we left Wednesday afternoon. But no, these big tent events for all manufacturers are a time that I think it’s important to soak in the strategy, compare to next year, weigh in on the big announcements they had. Now I want to focus in on two. So HPE was the first to say it was going as a service for all on-prem data centers, server storage and networking. And then they’re adding software based solutions to the HPE GreenLake portfolio on a routine basis. But one thing that I’ve been following pretty closely, and you know I love the hybrid multi-Cloud, is over time the context that the public Cloud is 19 years old. At what point are enterprises going to more seriously consider for each workload having an on-prem as a service or edge as a service as part of its hybrid multi-Cloud strategy?
We already know that between 75 and 90% of all data and investment is still on-prem. But at what point does the hybrid Cloud really kick in? And one of the key players in this is a company called Equinix. And Equinix owns property crate. Basically it’s their data center as a service. So whether you’re HPE, Dell, Citibank, Wells Fargo, if you don’t want to operate a data center with the cooling capabilities, the electrical capabilities, all the real estate and the investment, you go to companies like Equinix and Digital Realty. So the big announcement here was that HPE and Equinix launched private Cloud portfolio at Equinix. So HPE is actually pre-deployment hardware at seven key metro areas around the world in Sydney, Singapore, Frankfurt, Washington, DC, Toronto, and Silicon Valley. I don’t know, does that mean Oakland? I have no idea, but you get the idea.
And if you think about this and why I think this is so provocative, it removes yet one more objection. Now, HPE had always aligned with Equinix, but it was spotty. And essentially what you can do just like you do with an AWS or a GCP or an Azure, if you want to go all in and have quote, unquote, “availability zones” around the world at those seven places that I talked about, you can do this. And here’s the other thing, instead of waiting one, two weeks a month for that hardware to show up, HPE has pre-bought and pre-installed hardware in there for you to go in there. And I was hearing timeframes of a day, which is just so much better. So we’re getting closer to those capabilities of the… Not all of them. You don’t have kind of unlimited scalability like you do at an AWS, but imagine though, Daniel, you add a multi-tenant system and a credit card swiper, you could be a developer and you could sign up for HPE GreenLake, do all of your testing and all of your… I mean, within seconds or minutes.
So pretty excited about this. And this is kind of the long track of the hybrid Cloud and the multi-Cloud coming together. That was announcement one. And the second one, and I won’t go too deep, leave you oxygen in the room was, HP announced an LLM as a service on-prem using its supercomputers. The company really didn’t lean in too much that, hey, this was going on a Cray supercomputer that has this incredible interconnects that connect different clusters because I think they want to have a little flexibility in what they do in the future there. But it seemed to me a very well thought out offering so far for very highly technical customers. And I think we already see HPE ingrained into governments, into three letter acronym security companies, and these are the kind kind of companies that I get the sense of because HP didn’t roll out any customers.
These are the type of customers I think will be most attracted because it’s on Cray. And whenever you’re programming for a specific environment, you have to program to, I think it’s called CDE with Cray, that enables you to bop back and forth between multiple clusters. It’s single tenant by the way. Overall it’s multi-tenant, but what you’re doing is essentially having one, two, 10, 100 different clusters that you can sign up for. I have a lot of questions because there’s a lot of things that weren’t disclosed but don’t know pricing, don’t know the basis of the pricing. Is it by the cluster? Is it by the cluster by GPU? A lot of open-ended questions right now.
I also don’t have a sense of what it takes to program to CDE versus let’s say something from AWS. And I also don’t know when GA is going to be over. This is not a paper launch, it’s also not GA like IBM’s supercomputer training as a service, but it’s a good start. This is something they’re offering that Dell doesn’t offer and I don’t think Lenovo offers it. So it seems like a differentiator to me. It also seems very much in line strategically with what the company wants to do and their continued progress with on-prem IAS.
Daniel Newman: Yeah, I think you hit on a couple things. I mean, one is thematically speaking, I thought the best moment was the moment when Antonio Neri on stage called it hybrid Cloud by accident.
Patrick Moorhead: Yeah.
Daniel Newman: Great quotes. And really talking about how the company was declaratively ahead of the curve on one, landing and hybrid Cloud. Two, the need to build this consumption based service. on-prem because I’ll say it now, I’ll say it again, I’ll continue to reiterate it. The operating model of Cloud is the desire. The actual location of the infrastructure, the desire varies. It varies by company need, but the ability to function and operate that way and HPE does and continues to have a substantial lead in terms of its service distribution. The crawl chart of services for HPE GreenLake is still far ahead of its competition.
I’ve said before, and I’ll say again, I don’t believe that lead will necessarily be sustainable forever. You’ve got very capable, competent competition and you also have the forces of the hyperscale Cloud that sees prem as a massive opportunity, whether it’s Andy Jassy saying 90% of workloads are still on-prem or it’s Antonio Neri saying 70% of enterprise workloads are still on-prem, or it was our guest on the pod yesterday from Citi that suggested that at some point, Cloud workloads will exceed prem workloads.
That period of time in that transition’s going to be long, and we are going to see services that are going to basically bring the two things together. So there was a significant sort of opportunity for HPE to really reiterate and lean into the fact that it’s been on this, it’s been ahead of this, and it continues to be. And I mean, it deepened its AWS partnership, it announced that from the stage.
Patrick Moorhead: Yes.
Daniel Newman: It leaned into a VMware partnership, which continues to have a lot to do with the fact that the world is hybrid. So the company wasn’t running away from hybrid by any means and wasn’t running away from workloads being in the public Cloud. So that that’s mostly just validating that we’re right, which is important to me to do at least once per topic, per podcast.
Patrick Moorhead: Per hour.
Daniel Newman: Yeah, I mean, the second thing by the way is-
Patrick Moorhead: Hey, Dan, though. Hey, was that interaction between Matt Wood at AWS and Antonio a little bit awkward when you kind of listened to the words that Matt used, and I hadn’t heard had AWS use this phraseology before, but basically the way that I internalized it was Matt said, “Hey, everything’s going to the public Cloud, and this is just like an intermediary step to help our customers get them there.” And it’s like, I haven’t heard anybody but Andy Jassy use that phraseology, but man, like you’re on HPE’s stage and you’re saying this. I just thought was very provocative. I don’t know if anybody else caught it, but I thought it was a little awkward.
Daniel Newman: I didn’t catch it, but now that you say it, there’s a little bit of room for reflection. I mean, look, that’s the bet. That’s AWS’s bet, but it’s sort of their bet because Outpost, they still know they’re going to have to put their infrastructure, but I think from a control plane standpoint, they’ve always sort of had the approach like, we want to own it all. And so I don’t necessarily see that course changing and I see the partnership as valuable to HPE. Just a quick touch on the LLM thing. It seems early to me, it seems very positive and promising that the company’s going to be able to do this, and it does sort of validate whether it’s been Bluedata, whether it’s been Cray, this company is not new to AI and I think some people want to make the assessment that HPE has just sort of jumped into AI out of nowhere.
I mean, they’ve actually been building architecture and like I said, they’re data services for GreenLake are far ahead of any of the other prem Cloud. It doesn’t even make sense, but the consumption-prem offerings that are out there, and it’s been going down the path of AI, whether that’s been operational AI for ML and AI ops, all the way to the super computing on demand. So I think there’s story there. And then of course they partnered with Luminous, ominous. It’s ominous that they worked with Luminous, but they partnered with a different LLM company, which is kind of interesting too. But a lot of what that LLM focuses in on are things that are important to enterprises. So some of the-
Patrick Moorhead: Have you ever heard of that company before?
Daniel Newman: I was not familiar Pat, but when you look deeper into it, it’s got a rich heritage. It’s been doing this for some time and it is focused a lot on transparency, which is interesting because this enterprise transparency issue is, where was your data? Where were these sort of generative assets constructed from? Where did the… It’s got a lot of that provenance built into the software to function a little bit differently than some of the other open source and popular LLMs.
Patrick Moorhead: I would’ve loved a superfluous Hugging Face announcement alongside a company that I had never heard of before.
Daniel Newman: Well, you got to do something with Hugging Face. I think it’s a requirement right now.
Patrick Moorhead: No, I know, totally. That’s what I mean. Even if it’s a superfluous fly by like, “Hey, and we support Hugging Face models too.”
Daniel Newman: Yeah, so I think we’ve got this one. 17 minutes in one topic. Good for us. That’s pretty much typical Six Five right there. All right. Hey, this host stinks. I am not the world’s best moderator, apparently. All right, so let’s go to topic two, Pat MongoDB.local. This is the one of now what’s going to be 30 of these events. So instead of MongoDB World, the company decided to go glocal. They’re going glocal, they’re going to do 30 events, 19 countries. They’re going to be kind of doing a wave of announcements. Yesterday they did a bunch and I would say it was a big seminal moment for MongoDB in the advancement of its product portfolio. The Six Five was there, we were on the ground. We did what, eight? Eight interviews or eight conversations.
Patrick Moorhead: Eight Conversations, eight videos.
Daniel Newman: And you can find them all, we’ll put some links in the show notes. We talked to company’s head of product, we talked to some of their biggest customers in financial services like Wells Fargo and Citi. We talked to partners like Cisco. We talked to some startups, some cool startups like Ada and One AI. And it was a great day, it was a great day. So what did the company talk about though? Well, their CEO, Dave got on stage and basically focused in on the evolution of the product and the influence that AI is going to have on how the product was developed. Their head of engineering said something interesting in a later session that was designed for the analysts where we talked about when we started developing this product, we’ve kind of asked ourselves, what would we have developed the product to look like if we had developed it for the AI era?
And whether this is just great marketecture or this was actually what they believe they said, we would’ve designed it exactly like we designed it today. Which is an interesting inflection because something that’s been on my mind a lot is how was the database, data pipeline, data fabric needing to change for the AI data center? And we’re hearing different things about storage. And I had a long interaction with the executive team about this. I won’t do it with everybody now, but the fact is, where does software embed into hardware? Where in the stack an operational database like this, where does AI layer on it? What’s the real AI value? Pat, you asked some great questions about this as opposed to just-
Patrick Moorhead: Aw, thanks buddy.
Daniel Newman: As opposed to just accessing data, meaning making data accessible, the big wins, the big areas, vector search, stream processing, the company made some additional announcements in both of those areas that I thought were really interesting. One of the great examples the company gave with using vector search came down to being able to take different data sets that could be… They did this automotive one where they could take a sound of a vehicle, pair it with a large language model, and then pair it with all of the manuals across an entire portfolio of automobiles to then help a technician, based on just the sound a car makes, auto generate the text that would ultimately give them the workaround to fix a problem with a vehicle. Things like that, that require many different data formats to be simultaneously utilized to both access the data, the schema across structured and unstructured to then create a generative application. And that’s really where MongoDB can be pretty special.
And then of course it made some really good declarations about Atlas, that basically the company has made that full pivot to now Cloud being its leading growth engine, it’s got a multi-Cloud approach, the company is basically saying, we don’t care where. You can put it in Google, you can put it in Microsoft, you can put it in AWS. Clearly developing partnerships with all of them. So the company had some very declarative, some product advancements. I mean, look, the generative AI opportunity of the moment is enterprise search. It’s the ability to take your proprietary data and pair it up with these large language models. And the search feature is interesting because MongoDB is clearly making a run at Elastic and saying, look, we can do it and we can build it right in.
And maybe my last point to keep this moving is, I sense more and more whether it’s stream processing and what they’re doing there and the impact with Kafka or it’s the enterprise search, they’re kind of looking at TAM expansion and growth by just feature crawl, feature creep, feature crawl where they’re saying, look, you used to buy this feature from Confluent and you bought this feature from Elastic, you can just do this all in MongoDB and Atlas and you can just send all the money to us. And that’s going to put pressure on some of these point solutions to either innovate or integrate in order to stay relevant. And of course, MongoDB is doing a little bit more analytics too, which puts pressure on some of your traditional data analytics warehouses. They don’t want to say that they’re a data warehouse, but they’re kind of saying, we can do some of that stuff. So that’s another interesting thing.
Patrick Moorhead: I’m not a data warehouse.
Daniel Newman: It’s not about MongoDB, but maybe it’s about MongoDB, Pat.
Patrick Moorhead: Hey, you say Kafka, I say Kafka. Let me try to fill in-
Daniel Newman: Kafka, Kafka, Kafka, Kafka.
Patrick Moorhead: You say Kafka, I say Kafka. So anyway-
Daniel Newman: Is it right? Is one right?
Patrick Moorhead: I have no clue.
Daniel Newman: Okay.
Patrick Moorhead: Let me ask my son who uses Kafka. So I’m going to hit a little bit of a different incremental angle here. This was all about growth for the company. And I know the company is obviously very customer focused, but I’m going to look at it from a corporate standpoint. And there’s only so many ways you can grow. You can acquire somebody, you can do it organically, you can take somebody else’s share, you can create a new market or you can do something different. So a lot of elements of growth here. So what are some new elements, new things to sell? Even though they make most of their money today on OLTP database, they do have time series, full text search, and analytics, but they added stream processing and vector search. And like you intelligently said, Dan, there are other people in this market who do this.
And Elasticsearch popped up for me and apparently this is not in competition with Confluent on the stream processing side, but in collaboration with. I need to see the architectural diagram before I can say as Confluent did have a booth at the event. The other way you can grow is take market share and one way to do that, add new products or you can go vertical. And what we saw is Atlas for Industries as a big announcement and the first vertical that came out was financial services. We both talked to Citibank and who else? Citibank financial-
Daniel Newman: Wells Fargo.
Patrick Moorhead: Wells Fargo, who had some very nice things to say. And the fine point that they put on it is, hey, when it comes to things like regulatory, we’re special. So it totally made sense. Some of the other things that I appreciated was the simplification story. And we’re seeing this same simplification story in security and we’re seeing it in observability which says, Hey, all these best in breed one-offs are great, but you the enterprise has to integrate this all together. And by the time that you’ve integrated it all together, you’re probably three revisions behind on the best of breed and you’ve potentially created some security holes and you’ve spent a lot of money. And I like the approach here of simplification that says, hey, it’s OLTP, time series, full tech search, analytics stream, or vector search. You have one model and that’s a document model and you have a unified API.
And the final thing is the company’s great. They have a SQL migrator tool that says, hey, if you hate your SQL provider, whether it’s DB2, whether it’s Oracle, come on in, we’ll bring you in. We’ll not only help you migrate your data but will help you migrate your applications. This is called the relational migrator. So whether it’s the application code going from SQL to, can I call MQL or M-Q-L? And schema and data migration, they have you covered. So I just love to see these potential moves that they’re making to steal money from other people. There is market making and that’s where vector search comes in because vector search is very much a big part of the LLM stories that come out. Andreessen Horowitz published a really good schematic on what everything is together. And basically vector search they’re saying is the absolute foundation for all this. Text is important, but vector search when it comes to images, code, music, videos, that stuff really lights it up. So check out our eight videos on the Six Five podcast on LinkedIn, Twitter, Facebook, YouTube, of course.
Daniel Newman: We got it, promo guy. We got it. All right, let’s keep moving.
Patrick Moorhead: I’m proud of what we do, Dan.
Daniel Newman: You should be.
Patrick Moorhead: I don’t want to bury it.
Daniel Newman: I mean, I’m not the world’s best moderator, but I might be the world’s best moderator.
Patrick Moorhead: I don’t know. All I know is I’m not the world’s best loader. I think I forgot to put the Intel top again.
Daniel Newman: Yeah, I saw that. But I’m not as critical about that kind of stuff.
Patrick Moorhead: Whoopsies, I am.
Daniel Newman: We’re good.
Patrick Moorhead: We’re halfway in. We’re 28 minutes in.
Daniel Newman: I’m the moderator here. Stop it.
Patrick Moorhead: Are you? Well start moderating then.
Daniel Newman: Let’s go. Hey dude, let’s talk about Oracle’s Sovereign Cloud.
Patrick Moorhead: Yeah, so Sovereign Cloud is basically a Cloud that you set up that abides by all the data security. Some countries have, hey, they have to be citizens in that country who manage it. They have to be incorporated in that. And every one of the Cloud players is adopting Sovereign Cloud. Now, sometimes it’s hard to know, hey, they didn’t build a new data center or they didn’t stand up new real estate, what makes it sovereign? Oracle announced their take starting in the EU first, and it’s really straightforward. It’s stood up in multiple countries that are incorporated in those countries. That’s check. It’s abiding by all the EU data sovereignty rules, which by the way also includes that company has to be incorporated in the specific companies in the EUs. But here’s the cool part, there’s no extra added price that goes along with it, and all services are available that are available on the non-Sovereign Cloud.
So again, in pure Oracle fashion, to me, they’ve simplified the message here in a very similar way that they did on-prem Cloud, which was, hey, we’re going to take the same infrastructure that’s in the public Cloud, we’re going to put it on site, that’s Cloud a customer. And you can run the same applications. If you want to be connected to the big Cloud, you can. If you want to be disconnected, you can. And here in this EU Sovereign Cloud, it’s disconnected from the mothership as well. So very simple, very straightforward. Oracle’s on a freaking roll, but this is just another example of them doing simplicity. I saw some really fun and snarky comments from from AWS, Google, and Azure on this. Kind of defensive, which kind of may maybe leads me to believe that there’s something here.
Daniel Newman: Yeah, Oracle’s so popular right now with us that we’re going to talk about them twice on the same show, but we’ll give you a break in between. I mean, look, their growth rate is about three times the size of the other IAS companies right now, which says something. And again, the way every company discloses Cloud revenue is somewhat different so it’s not a straight standup in any case ever anymore, so just know that. So when someone does a 10 best Cloud growth companies and publishes that as some sort of declarative asset, just know it’s mostly marketing gamesmanship. But in all serious, Oracle’s growth has been palpable and impressive. The addition to features like Sovereign Cloud are critical. As regulators drill down on data and data residency and how data is moving from one country to another, the ability to manage that and to enable you to deal with some of the parts of the world that have stricter data requirements is going to be critical.
This is where Cloud hyperscalers really have a bit of an advantage is they can build out these services once and then deliver them at scale to their entire customer data sets. And so for me, this is more of, it is a little bit picks and axes for me. This is kind of like a core feature capability that I would expect, hope, and consider as paramount to Oracle’s continued growth and success, but here they are ticking boxes. They’re ticking boxes, they’re making it easy. And again, remember somewhat, where does Oracle’s huge growth opportunity come from? Well, you have 400,000 people running Oracle’s database and their data sitting. So Oracle in this period of somewhat austerity in business and despite the kind of magnificent seven and the stock prices of Nvidia and Microsoft, most companies are still facing headwinds, business headwinds. And they’re looking at, yes, the Cloud is an operating model, but is there a monetarily advantageous way to get the workloads in the Cloud at a price we can afford?
And if Oracle continues to create more dynamic services and continues to be very aggressive on its pricing, and make no mistake, it is very aggressive on its pricing, it has a chance to continue to take market. And that’s exactly what it’s doing right now. It’s small today, but if it keeps growing at a 3X the rest of the Cloud provider market, it will not be a long time. It does not take a lot of compounding of that growth rate to start to become a real threat. And again, that race for third Cloud is real and at some point over time it adds up and market positions shift. So kudos to Oracle for building out the product services that companies need. And we’ll keep an eye on this one as it goes forward. We’ll be talking more about Oracle in a little bit.
So I’m going to now famously call my own number. It’s been a little while, so the refresher here, but Adobe put out their earnings last week and it got a jolt. You can read the numbers, let’s just say they beat top bottom and raised guidance and they showed really strong numbers, strong ARR, 10% up year over year from same quarter, 13% growth of income. So just all good. But what was so big was it appears that the market is looking at Adobe as one of the winners of the generative AI boom. That’s the reaction that the stock saw, the huge jump in price following its earnings kind of said, hey, we hear your story, we get your story. And here’s a short, when it comes to creative, when it comes to the ability to create, there is not a company that has a more compelling story.
And if you’ve seen the demo of some of the generative creation apps that Adobe has, if you’re listening to this, Pat just blew his mind. But it really is a powerful demonstration and when you see it, you’re just like, who else can do this? You take an image and you circle in a little area and then you type “Pat’s head exploding” and it could literally create Pat’s head exploding. And it’s very, very cool. And I mean, in my opinion it’s very early days, but being kind of declared early as a winner, the company’s getting a lot of things like responsibility right, usage rights correct. And so it’s growing across the board and of course its business is all about recurring. So all this revenue, it comes down to the fact that it’s got recurring services, it’s got pricing power because it’s got limited competition and it is seen as a best of breed in its area.
So that’s really in a nutshell what was exciting. Now the company did grow across all its businesses, digital media, document Cloud, digital experience. And interestingly enough, the company also has the ability to grow significantly in its experience Cloud because it also has really interesting generative data about things like web behavior. So while we’re thinking a lot and early on, our excitement is about seeing this kind of generative graphics, we’re also going to see generative intelligence at a big scale with Adobe because it has so much, if not the most critical in intelligence data set about how people shop and do commerce on the web. So kind of exciting across the board.
I don’t mean to be kind of brief into the point on this earnings, but I mean, top bottom raise, cool generative AI, categorically strong across all areas, still want to hear more about Figma. I’m still calling the deal to close despite the fact that a lot of people think it may or may not. I just don’t think there’s a lot of competitive gating for someone else to build that kind of product and that kind of solution to compete. And so Adobe’s kind of becoming a bit of a wild card to be another rise to a trillion kind of business just because it’s so uniquely positioned.
Patrick Moorhead: Are you calling this one Dan?
Daniel Newman: Not yet, not yet.
Patrick Moorhead: Because I want to remind you about this in three months,
Daniel Newman: I’m not doing it yet, but I’m making an early assessment that I do think this one’s got a real shot.
Patrick Moorhead: I believe that this company is in a major inflection right now. It was a little bit slower to Cloudify than let’s say a Microsoft, but what you’re seeing, if you look at the Cloud ARR numbers, they’re really good and they have a very loyal base of people who quite frankly, they’re not going to move to the Cloud for the sake of the Cloud, they’re going to move to the Cloud if it adds them incremental utility. And that’s exactly what they’re doing. So that’s one inflection. And this second one is this layering on of generative AI. And I don’t care how you want to split it, which says, hey, to get the same level of creativity, I’m going to need less people. Or this is a democratizer of creativity, which means the TAM’s going to grow. So any way, any bet you want to make Adobe wins here, I think.
And if you layer on the increased Cloudification of every one of their applications and use cases, I think it’s pretty darn exciting. The Figma thing, I mean, these companies are not even in the same market and you just have to use Figma and then use something like Photoshop to realize they are not even in the same stratosphere. And one of the biggest arguments, which I know regulators are talking to them about is this notion that you could have just build this yourself. Well guess what? Adobe already tried to build this capability and the company has said publicly it’s been a failure, it hasn’t worked. So just these arguments from these regulators that have zero business experience is a little bit frustrating as opposed to spending time on Apple who squeezes all of its suppliers, some into bankruptcy, doesn’t allow third party app stores to come in, it’s really frustrating to me that bad theory versus actual harm that’s being done. But congrats Adobe, you really knocked it out of the park and it’s great to see the credit that you’re getting for all that hard work.
Daniel Newman: Let’s make a pivot, a bit of a hard pivot and it was a hard pivot. There was an internal foundry business model update and webinar that came out from Intel, didn’t land real well, but I’m not sure that the message was received entirely correctly.
Patrick Moorhead: Are you taking this topic?
Daniel Newman: No, I was just going to tee you up, just hold on.
Patrick Moorhead: Okay, tee it up.
Daniel Newman: Not sure it was received entirely correctly, but Pat, why don’t you weigh in on this one first.
Patrick Moorhead: Well, I was going to say what you said, but then I was going to say after that.
Daniel Newman: You were going to say more though, right? That wasn’t it. I was just-
Patrick Moorhead: No, of course not.
Daniel Newman: I was baiting. Just baiting a little bit up there.
Patrick Moorhead: Yeah. So the company historically had done some updates about its businesses. The first one was for client computing and the second one was for data center and AI. And they were really an end-to-end rotor routing of the business and the business leads got on there. That had been the previous two drill downs. This was intended to be an internal foundry conversation, not to be confused with IFS right that that’s run by Stu Pann, but I think that that was missed and it is very important to understand the internal foundry model at Intel that was represented by not only CFO Dave Zinsner, but also by Jason Grebe, and I hope I said his name correctly. But essentially this was for the financial analysts to update their spreadsheets in a way from margins because it used to be that all of the margins that had to do with manufacturing and process were captured in the business units, but now that’s going to be broken apart where the foundry end of the business will have its P and L and then the product design companies will be able to have their own P and Ls.
And what that shows is say more gives investors a better view of how to view the manufacturing part of the business and then the design products and sell side of the business. And I think that’s very valuable. You can compare it to Nvidia, you can compare it to Intel and you compare it to TSMC and in the future, GlobalFoundries. What it also does, and this is an important thing I’ve spent a lot of time inside a processor company, is the motivations of the business units. When you set up something like this and if you’re running, let’s say you’re Michelle and you’re running the client business, it’s setting you up where you have a much better idea of how profitable your client business can be on whether you do it in the internal foundry or quite frankly, you do it at TSMC or Samsung.
That’s what this is setting up right now, which is very healthy. I do not think that this is setting up some short term for some short term break off or something like that. But overall, I think the selloff was based on this notion that they wanted an IFS, Stu to come up and talk about a new 18A customer, but that wasn’t what this was set up to do. So I think long-term I would’ve handled it a little bit differently knowing the expectations coming in, but I also know that we’re going to have an IFS update very shortly where that information I think investors were looking for will be more apparent.
Daniel Newman: Yeah, I mean I think that this is one of those situations where the company does so much, it’s easy for things like this to get conflated and I think there was some strong benefits presented, but it just wasn’t the presentation people were looking for. I think what people wanted was Intel to come out and say, Hey, we’ve got some huge fabulous customer that’s going to be using our foundry and we expect some rocket ship revenue. And I think that type of work is in the making. I mean, look, the company’s breaking ground in Israel, in Poland, in Germany and in Ohio, I mean, the investments in its manufacturing capabilities and capacity are material and knowing that the demand for semiconductors is not going to go down anytime soon. Now again, there will be waves, there’s ebbs and flows, but what I mean is, every industry, every business, every technology, and if you believe in this AI trend line, then you better believe that there’s going to be more semiconductors needed.
And you also have to know with all the global macro forces, whether that’s China, Taiwan, whether that’s Ukraine, whether that’s national security, global technology leadership, that Intel is the largest beneficiary of any sort of nationalistic investments that are being made as well as any sort of ally investments across a global scale. And then the supply chain itself and the resiliency. So there’s a definite opportunity for the company to use its internal foundry to do things. It talks about for benchmarking, it talks about cost optimization and it talks about the fact that the company is the second largest foundry. So it’s not TSM gets a lot of credit, but Intel is in the running. So I think that this is one of those situations where the market wants sizzle and what they got was a very practical update about some important business items, agendas, and operating focuses.
Patrick Moorhead: Yeah, they couldn’t just show up on earnings day and their BUs have a super low margin and then it magically… They had to… And this was I think more for the institutional investors than anything else.
Daniel Newman: Absolutely.
Patrick Moorhead: It was just surprising.
Daniel Newman: I mean, being able to show that their operating margin can improve over time, which they had a slide for that and showing… Because that’s been one of the biggest rubs on Intel is the margin has just gotten battered over the last several quarters. And obviously everyone’s looking at that and then you’re looking at the Nvidia margins and you’re looking at all the fabulous companies on TSM margins and then they’re going, well, what’s the future for Intel? Well, the future has to be getting this manufacturing foundry business in order and starting to show that it can actually recapture lost margin that’s been lost and it’s making massive investments to do so, Pat. So look, it probably didn’t land the way it was hoped, but it also was an important disclosure, probably an overreaction from the market because it’s still progress.
But again, I don’t think you can move fast enough. And Intel is always on a shorter leash than other companies right now. So now if Intel wants to tell us about its new big lineup of GPUs training and of course some new partnership to take down InfiniBand and make a real competitive run at Nvidia, I think that would probably get a 10% jolt in a day. But who knows anymore with this market. All right, so one more topic to go. Let’s talk about Oracle. I know, we’re back. We’re back, baby.
Patrick Moorhead: Back, baby.
Daniel Newman: So this is about a week old, Pat, we just didn’t get to it. So one of the companies that’s a lot of investment and focus on enterprise large language models is called Cohere. So we hear a lot about… By the way earlier we talked about Luminous, now we’re talking about Cohere, everything was OpenAI for a while, but what’s happened is then it was open AI and PaLM/Bard, then it was OpenAI, PaLM/Bard, and then Hugging Face. And now we’re kind of going down the list and we’ve got Cohere as a company that HPE tied up with Luminous, Oracle’s tying up with Cohere. And basically what they’re doing is looking to integrate lots of generative AI capabilities into their Fusion Cloud and NetSuite as well as their industry specific apps.
So one of the things that is really interesting here too, Pat, is that we’ve talked to you and I about the holy grail of private data sets, public data sets, and this is where Oracle’s really leaning in. They’re planning to use the Cohere foundational models to point at private data sets, not worrying about public domain data and being able to enable companies to train on smaller sets to be able to create higher confidence results and people that can get key benefits from all that enterprise data into those enterprise apps. So long and short is that what we’re seeing, whether it’s the Google generative AI app builder or you’re seeing Salesforce and their GPT product or Oracle here is you’re seeing that the large software companies are saying, look, yes, every company can become data scientists and build their own training data sets and create algorithms and models if they want to spend a fortune, hire a ton of data scientists, buy hardware that’s not available in the marketplace at all right now, and then try to keep up with a pace that’s unrecognizable right now. Nobody’s seen a pace like this before.
Or you can work with multi-billion dollar high profit companies with deep engineering and data science expertise that are going to build large sets of these AI capabilities right into the applications for you that will address the Pareto 80/20 of your needs. And then maybe you can do a little bit of modification and customization to train for specialty needs, tools, and technologies. This is what that is. If you’re running NetSuite, it’s what are the generative capabilities to build a more sufficient CEO dashboard or CFO dashboard? What are the capabilities to build quote to pay, accounts receivable, generative tools that can take… And again, you’re really going to look at a multi app ecosystem. You’re going to say, how does an email get crafted using the data inside of NetSuite to send something thoughtful to a customer that’s going to help you speed up the collection, but doing so with a very prescriptive interaction as opposed to just an automated email that gets pumped out of your system. Stuff like that.
These are the opportunities, and like I said, it is a industry-wide standard, Pat, so Cohere plus Oracle, compared to Salesforce plus OpenAI, compared to what SAP is doing with business, SAP business AI, you’re going to see it from all the platforms and the players. But given what we said earlier, Pat, with Oracle’s recent role, I think that they probably looked to find something very specific. They’re digging in narrowly into that private data set. And I do think it is a compelling offer, especially given the strong growth that we’ve seen across the apps portfolio.
Patrick Moorhead: I don’t know enough about Cohere to intelligently come in, so I can’t figure out if this is a, they were late to the table and they were the last one to dance with. I have no idea because you can partner with OpenAI and then modify the results because OpenAI is the brain. Leveraging OpenAI doesn’t mean that every company that uses it is going to get world data back. OpenAI is the brain and then you customize a level of training above it, very similar to what Microsoft is doing with the layers that they have and then the magic happens. So yeah, again, it’s very hard for me to know what the case is. I think this all comes together if you look at OCI and what OCI brings to the table. And interestingly enough, in this latest round of the friends of Nvidia club, Oracle actually did quite well.
And if you look at the first place that you can get access to many of NVIDIA’s tools, it’s on Oracle Cloud, which if you think about it’s like, wait, they’re the number three, number four, something is really interesting about what Oracle is doing. Now, one thing that is the attractor loop is pricing the way that Oracle does it. Which might sound pretty straightforward, but for the easy stuff, they make less profit and for the harder stuff they make more profit is kind of different, very different from the way that AWS prices stuff. So I’m really look really interested in looking at the top to bottom stack, which is the generative AI services with Cohere plus OCI infrastructure and what does that look like?
Because in the end, you’re not just buying these services with Cohere, you’re pretty much buying everything as a stack. And over time, pricing for these types of services in this full stack will come out. The really good news is that Oracle is a full stack provider. Then you add on top of it the SaaS properties like NetSuite and Fusion, it’s even more important for them to come up with the right solution because they’re going to have to eat their own dog food related to their SaaS apps that’s delivered through a PaaS and an IAS service.
Daniel Newman: Yeah, no, I think you hit on the head, Pat, and I think that’s really where I was trying to go is generative AI is going to be a capability. Some automations were in business applications or capability like some of the business data visibility visualizations that have been created. Now, it’s going to be generative. We’ve already seen things, Pat, over the last few years, attrition scoring that were being created. Now the difference is a generative tool could say, hey, this customer looks highly likely to defect, we’re going to generate an auto email. We’re going to put in all these value added items that we’ve been doing for the customer to remind them of the value. We’re going to hit them up early, we’re going to get ahead. You know what I mean? It’s going to generate some secondary assets to create value, but this is going to be built into the tools.
Companies are not going to have to build a lot of this stuff from scratch. The question now is how much are what people willing to pay for these capabilities on top of what they’re already paying for products, or is this going to be table stakes? And that’s one of the big things a lot of people are keeping eyes on. Is generative AI incremental revenue for a company like Oracle or for Salesforce or is it a expectation within the current customer pricing and more incrementally we’ll see pricing increases like software always does as opposed to truly saying, hey, you want this new AI feature set, it’s going to be a 25% bump to your current cost or, hey, we’re going to bake this in right now because we don’t want you to go to effect over to Microsoft and use their new co-pilot tools. And that’s going to be the question for a while is in the price wars.
So all right I think we did it. I think we did it. We actually got somewhat back on schedule after our 17 minute first topic, but we were starting slow. We got in late. That happens. I think we found our groove as we went on and I think just like every week, what a great conversation. What a great way to start my Friday. I know now we got to do real work. Now we got to do real work, but this is the best part of my week every week. Thanks for making it happen, buddy. Thanks for getting up and getting out of bed. I know we didn’t get home till almost 2:00 AM so thanks for crushing it and thank you audience. Thank you for all of you that tuned in. All 1,218 of you that are watching right now, I can’t say enough about how much we appreciate our community here.
Patrick Moorhead: I appreciate the bot swarm too.
Daniel Newman: All of them, the bot swarm, whatever. I don’t care. Real, whatever. Why are we judging, Pat? It does not matter. We appreciate all you. So there we have it. We covered a ton of ground today. We talked HPE, MongoDB, we talked about Adobe, we talked about Intel, we talked about Oracle twice. We covered a lot of ground, Pat, and it’s always great to be here. So stay with us. Hit that subscribe button. Join us for all our future episodes. Check out all the MongoDB pods that we did this week in New York City. Pat and I are not on the road next week, I believe. It’s going to be a couple of weeks of non-travel for me all the way until I go to London for the F1 race for work, for work. I can’t wait to sleep in my bed for a while. Thank you, everybody.
Patrick Moorhead: Bye, everybody.
Daniel Newman: Thanks for being with us. We’ll see you later.