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Intel Arc & Acquiring Granulate, Oracle Heatwave, Micron Earnings, Groq Day, IBM Quantum – The Six Five Webcast

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 six handpicked topics for this week are:

  1. Intel Launches its Arc A-Series
  2. Oracle HeatWave
  3. Intel Acquires Granulate
  4. Micron Earnings Report
  5. Groq Day
  6. IBM Quantum HSBC News

For a deeper diver 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 do not ask that you treat us as such.


Patrick Moorhead: Hi, this is Pat Moorhead with Moor Insights & Strategy and we are back for another Six Five podcast, my favorite day of the week. I’m here with my incredible co-host extraordinaire, looking great in his glasses on a Friday morning, Daniel Newman from Futurum Research. How are you, Daniel?

Daniel Newman: I’m just showing off the hat, man. There’s an event coming up in June. It’s going to be epic, going to be the who’s who, we’ll call it the Davos of tech. It’s going to be on The Six Five, which buddy, I mean, how great is that? We should call it Six Five Summit.

Patrick Moorhead: We should, we should. How about that? No, this is great. So if it’s your first time to The Six Five Podcast, we cover six topics, five minutes each, but we usually talk a little bit more. We do analysis here. We don’t really talk about the news. Sometimes we have to talk about the news to give some context for the analysis, but this is what it’s all about. We’re going to talk about publicly traded companies too. So please don’t say anything, take anything that we say, as investment advice. In fact, just do the exact opposite of what you think we might be inferring. But no, we do have a great show today. We’re going to be talking about Intel, two things going on there. New Intel Arc and them acquiring a company called Granulate. We’re going to be talking about Oracle Heat Wave. We’re going to be talking Micron earnings, GroqDay and an IBM Quantum announcement with HSBC.

So Daniel to jump right in here, Intel Arc GPU launch. So Intel is market leader in what’s called integrated graphics and that’s graphics that are integrated into the SOC in notebooks or desktop. It’s really been AMD and Nvidia who have been pushing discrete graphics forever, but black and white Intel is now in the discrete graphics market. This week it announced Arc 3, 5, and 7 for mobile. That’s not for smartphones mobile, that’s for notebook.

So, I think it’s been since 1998, I’m going to have to go double check, with the i740, they brought out their last discrete, but instead of getting into the nuts and the bolts of the technology, because what I’ve seen is at least for Arc 3, which announces today and then Arc 5 and 7, available early summer of this year, which I believe is a push out of that. I thought they were all coming out here. There’s no other way to look at this other than positive, right? There’s very few black and whites that us analysts can put our hats on, or for that matter even retail investors or people like that. But this is a black and white. One day, Intel isn’t in the discrete graphics market and now it is. I think that’s the thing that should be focused on. And the 3, 5, 7 is exactly what you would expect, different tiers of performance and power draw. Intel is calling Arc 3 enhanced gaming, Arc 5 advanced gaming, not to be confused with enhanced gaming, and then Arc 7 for high performance gaming.

We really don’t have any of the deets on 5 or 7, looks like OEM support is pretty strong. At least the one that we were briefed under NDA, it looks like what I’ll call the leader SKU, is a design from Samsung that was announced at CES 2022, it’s called the Galaxy Book2 Pro.

The final thing that I want to talk about is looking at the future. There are a lot of interesting things you can do when you have access to the CPU and the GPU and you fund most of these notebook designs, which unlike AMD, Intel does more than anybody. There are some interesting things you can do with power. There are some interesting things you can do with actually sharing performance between the IGPU and the discrete Arc GPU. So, you know, I think that’s really what I’m looking at is can Intel do what AMD can’t by integrating the CPU and the GPU?

Daniel Newman: Yeah, first of all, this was a big announcement. We’ve all been waiting on the edge of our seats to see, can Intel come into this space? Can they not only enter it, can they be good at it? Intel’s been under a lot of pressure across the business to grow, to diversify. We heard an investor day. Pat seemed, Pat Gelsinger not Pat Moorhead, although both of you are semi-conductor bulls, seemed very optimistic that the Arc business would be important and meaningful and somewhat a quick trajectory to get into the billions of dollars of revenue for Intel. Of course, gaming is an opportunity. I do think Intel’s always had, on the desktop side, some pretty strong support in specific areas related to GPUs, but sorry, on the PC, on the laptops, it’s been slow, and this is what we’ve been waiting for.

So, the gaming is going to be an area that we’re going to have to watch closely to see if they can enter, if they can compete, if they can be successful, of course, with their relationships and the OEMs. They will get SKUs that will be inclusive of their new Arc TPUs and that will be a great way to get into it. We’ve already seen Samsung, Acer, Dell, Lenovo all are making commitments to play in this space. As they go up the stream with Arc 5 and Arc 7 will those provide more of a strength and competition to the AMD and Nvidia SKUs?

Remember, those companies, it’s not just about the technology, it’s like a religion. So, that’s going to be the real question, is will Intel be able to find religion within that gaming community? Another couple interesting things though, Pat, that is probably worth mentioning is there is an opportunity for growth in this space that isn’t just related to gaming, growth related to data and analytics. In Mike Diamond’s research note from our team, he put it out, he basically talked about the mathematicians, statisticians and how fast that business is growing. 3D sensing technologies for LIDAR, for instance, and how much that is growing.

All of these are going to be key areas for GPUs and their markets where Intel could potentially use its strength to enter, to sell more volume. So, it’s early days Pat, but I think it’s said that the company’s aiming to ship like about four million discrete GPUs in February alone. So, there’s an opportunity to move. It’s going to be competitive. This is one that we’re going to have to come back to and say, “Did the company execute?” I’m more confident than I’ve been in a long time in Intel, under Pat Gelsinger’s leadership, but it’s going to be very, very tough sledding, but I’m optimistic. So, I’ll leave it there.

Patrick Moorhead: No, those were good adders. I think people too quickly forget the new businesses that Intel is getting into. Now, quite frankly, with the supply at the level they’re at, they’re going to sell every one that they can make. It’s key for them to stick their positioning though, in gaming. Daniel, let’s move to the next topic, Oracle HeatWave, first of all, what is HeatWave and what’s new about it?

Daniel Newman: Absolutely. So, let’s start at the high level. This goes back to a decade ago when Sun Microsystems was acquired by Oracle, which was MySQL. Since then, Oracle’s kept MySQL relatively distinct. About 15 months ago, Oracle released what’s called MySQL HeatWave and it’s basically the company’s own optimized implementation of MySQL running on Oracle’s OCI infrastructure. For those of you not familiar, Pat and I have talked a lot about a very bullish sentiment on Oracle cloud. This is MySQL running on Oracle’s public cloud platform.

Basically what happened this week is a third release of HeatWave, scaling up node size, reducing costs for certain workloads, and introducing probably what was most notable here, and that is the in-database machine learning. Our team is currently in the process of research, a brief that is going to come out on this. So, I had the chance to review break it down and here’s what I think is most interesting about this particular iteration of the MySQL launch and moving into ML.

First of all, they’ve added native support for machine learning. It’s full automation, it takes advantage of the autonomous database and technologies that Oracle has been pushing very aggressively. It’s explainable AI, which is becoming an increasingly important topic right now as we’re looking for more transparency. So, all models in HeatWave ML are going to be explainable. They’re differentiated, therefore as well. But also probably what’s going to be most attractive about it, is the improved performance, quality, repeatability of the explanations and of course, some of the scaling. So, you have things like scaling with cluster size, real-time elasticity, more data per node.

So, these were some of the breakdowns that our team identified as key differentiators. As we went through, by the way, Oracle did a bunch of benchmarking. So, I’m going to comment on their benchmarking just a little bit, but I also want to be very clear that commenting put Oracle clearly ahead of competitors, Amazon, Google, and others in this space. Having said that, these are benchmarks that require and could opportunistically be challenged by the other companies Pat, but at this point you’ve got to wonder, because by the way in the second release of HeatWave, there was also some very strong benchmarking that was released and none of the competitors have stepped up and done any benchmarking or done any, say, publicly debated these strong numbers. So, you got to wonder Redshift or if BigQuery felt that they were able to outperform and it was going to be clearly measurable. You’d think they would’ve done those benchmark tests and put those into the market and they haven’t.

As we assessed the conclusions and recommendations, we basically found that across the cloud DB market, that the value was pretty tremendous, the price value for the technology. Had a hard to beat feature set, auto ML, scalability, real-time elasticity, the [inaudible] data per node, and overall the portfolio-wide enhancements that they were able to do. But more so than anything, Pat, it was the price performance that we really walked away from.

We also found that the benchmarks demonstrated clear out-performance this current time against Redshift, Snowflake, Synapse, and BigQuery. All of them, according to the data that we were able to review, were both more expensive and none of them had the same level of performance, which we think warrants that the companies that are in review cycles right now probably need to spend some time evaluating what HeatWave is offering.

By the way, very strong. I mean, Oracle’s always been a database company, Pat, but this is one of those things that’s truly showing how they’re taking their infrastructure and their database, the legacy and engineering prowess they’ve had in database for a long time, and putting it together to offer a significant differentiation in market, layering in autonomous database capabilities, competing at scale against major public cloud players and finding something that’s differentiated. So, a very good release, Pat, and pretty impressive numbers.

Patrick Moorhead: Good analysis there, Daniel, by the team. Our analyst, Matt Kimble wrote a note as well, that I’ll put in the show notes and essentially this is, so, HeatWave’s incredible performance has a lot to do with its all-in memory, where other solutions are spooling out back and forth to disk. So architecturally, that gives HeatWave a big advantage on performance, pretty much versus anything that touches a disk. So, that doesn’t surprise me.

Like you said, I didn’t see Oracle HeatWave competitors saying that these benchmarks were wrong either. So, I think they know. This next step, this was the first update in, I think 15 months, added machine learning in the database at no extra cost. So, even though Oracle’s a premium provider, them being able to essentially commoditize a machine learning, is pretty fun. Whether that’s with auto ML, which is key and that doesn’t mean that it’s just magic and you don’t have to do anything, but auto ML makes ML a heck of a lot easier. You don’t have to be necessarily a data science to have it happen.

So, HeatWave ML, not only is it higher performance, because you actually have the machine learning inference in the database, but it’s also basically free. So, once again, on architecture play on something that I think is pretty important. I love the idea of a premium vendor like Oracle commoditizing ML. I know exactly who this is targeted at. It’s 100% targeted at Redshift and how you architect Redshift and get machine learning out of that. So, check out the reports from both of our companies, if you want some of the gory details.

Daniel Newman: Yeah. The details are good. I’m not boomeranging per se here, Pat, but I do love the fact that you did mention the in-memory, because that is such an important differentiator. So, I’m glad you caught that out because I don’t think I mentioned it. So anyhow, good stuff there.

Patrick Moorhead: Listen, this is why we both talk about this, Daniel. If we were just repeat each other, how interesting of a show would that be? It’d be a snoozer.

Daniel Newman: Yeah, companies might like it, but I don’t think that people watching, trying to get the analysis would be all that excited about it.

Patrick Moorhead: Exactly.

Daniel Newman: Want to keep moving?

Patrick Moorhead: Yeah, let’s do that. Yeah. Let’s go to the next topic. And Intel is acquiring a company called Granulate. So, Intel is the unit share and market share leader for servers. I think their market share is around 85% or 80% today. And AMD has the lion’s share of the rest. Then you have folks like IBM Power and IBM Z and of course, Arm in there as well. So, one of the biggest challenges inside of a data center is efficiency. You don’t want to burn too much wattage and all things equal, ceteris paribus, the more power you put into the system, the more performance that you’re going to get.

There have been a lot of ways that CPUs can moderate the amount of power they draw. Some of these are inside of the CPU. It goes all the way back to Intel SpeedStep 20 years ago, to be able to bring voltage in frequency up and down, depending on what you’re doing. But Granulate, sometimes you need additional software to make that happen. So, what Granulate does, is it fine-grain, when it comes to things like microservices that are a lot harder to modulate with power, it allows you to modulate performance and power. Does not require any developer intervention on the operating system or on the application. So, if your application isn’t very good at working directly with the new breed of CPU, or the operating system isn’t, you can use Granulate to do that.

My expectation is that Granulate gets sucked into some lower level firmware or some type of driver that makes it even so auto-magic that even the end enterprise doesn’t have to do anything. I did get a tweet from Dylan Martin who said, “Hey, I have a leaked memo from Intel that says that they’re going to be selling this.” By the way, those can both be true. You can be selling it today, but in the future, it could get sucked into the firmware to make it even easier and enterprises wouldn’t have to load any software.

Daniel Newman: Well, doesn’t that basically address what Intel’s trying to address by effectively making this acquisition moving up, or I guess moving closer to the silicone layer where this optimization automation takes place? I mean, there’s been software for a long time that companies buy and invest in to try to opt. As I said, a lot of it happens like in public law, for instance, it’s in the control plane, you’re trying to optimize workloads, you’re trying to optimize software to make the compute work as efficiently and effectively as possible. You want to boost performance of every core. So, the idea of being able to do this more, quote unquote, what did you say, auto-magically? That really is what this is all about and Intel solving a problem that tends to go out the stack.

So, we love to say, you can’t run software on air. So, silicone is the one common ingredient, no matter what workload you’re running, you’re running it on something. So as companies’ sprawl of software, as they need to optimize more and more, every workload in their data center, try to get maximize every core, Intel has the opportunity to be a partner to these companies in terms of streamlining and automating that. So, it’s still fairly high level to me, in terms of how the company’s going to monetize this, how they’re going to make it inclusive, how they’re going to, but I do think software optimization is got to be part of the story right now. So, this acquisition gives Intel the opportunity to expand their story and help customers reduce CPU utilization and app latency, which is a big thing that every company’s doing. They’re either buying software to monitor it and in this case, they’re actually looking at ways to implement it where the customer doesn’t have to think about it, just put it in play.

Patrick Moorhead: See, it’s auto-magic, baby.

Daniel Newman: It’s auto-magic, like it should be.

Patrick Moorhead: Yeah, so it’s funny, in the entire press release, it didn’t say if it was using AI or machine learning, or some sort of deep learning, but essentially it learns your applications. So, pretty cool stuff. Daniel, let’s move to the next topic and that is Micron earnings. I think this is the first time Daniel, we’ve talked about Micron earnings on the show.

Daniel Newman: Well, look Pat, there’s nothing more popular right now in the tech press and media than semiconductors. I said, what are you going to run the app on? Air? We also need, you need memory and storage and with every workload and every bit of compute you additionally need more memory and storage. So, it’s been a really interesting opportunity right now to talk about what’s going on there. Then of course, there’s the supply chain, there’s the Ukraine-Russia war. So, semiconductors are even more in focus. With a company like Micron, what was the focus? Well, first of all, high level Pat, and since we don’t just repeat the news, I’m going to be straightforward and just say this, beat on earnings, beat on revenue, strong forward guidance, looked very encouraging. What did the market glom onto after he was able to outpace?

Well, one is where’s growth coming from? Well, for Micron, growth is coming from the data center. That’s the big part of the business that’s been growing. So, I think there’s a lot of worries about what’s going to happen to memory and storage when some of secular trends go cyclical. So, we’ve had secular trends in PC growth and adoption. We’ve had secular trends in smartphones. We had a pile of stimulus pumped into the market that drove people to buy more of these things. Then on top of that, you had schools forced to outfit every kid with a PC. You had workforces forced to give every employee PCs or update to new PCs.

We’ve seen the PC market be incredibly robust. I think both of us would agree Pat, that the PC market will stay robust beyond what most think. Meaning, this isn’t a trend that’s going to reverse and go down 25%. But there is a good chance, Pat, in the next few quarters, the trend will reverse and it will slow a little bit.

So, Micron’s been working hard to shift into areas to be able to support with NAND, things like the 5G trend with mobile devices, data center and the importance of additional storage and memory technologies, they’re seeing 60% growth year over year in this most recent quarter. Also, moving to things like automotive and memory and storage, which is another area that’s very important.

Pat, what did the analysts focus on? Well, this is kind of interesting. Everybody wanted to know about what’s going to happen with neon gas and other raw materials. So, we’re hearing this again. This is the thing now, about half of the world’s neon gas is produced in the Ukraine and it is important for what’s known as lithography, which is basically the way you see these little circuits etched onto the wafers or onto the circuits.

So, most of these companies, Pat, have already dealt with this. They’ve been dealing with this for some time and going through the supply chain resiliency activities over the last couple of years, they’ve been diversifying where they’re getting. Mehrota, I don’t say that out loud very often, Sanjay Mehrota, the CEO of Micron, did say that there is a chance that some of these raw materials could go up in cost if there is a need to acquire them from different sources and if this war was to linger on too long and all this manufacturing stopped, Pat. Also, they shut down China again. They had like cases of COVID and they shut down parts of Shanghai. Very interesting, can’t figure out exactly how that works, but that has also created a little bit of worry that there could be some other supply chain disruptions coming out of China.

Overall on the call, it seemed the company was very confident that it would manage it. It’s diversified its supply chain and that it would be able to handle. There might be some additional costs. Pat, my take on it is that there is some elasticity but in memory and storage, less elasticity than in say, general purpose CPUs, where there tends to be more flexibility on pricing.

So, overall though, the company seems to be in good shape, seems to have its supply chain in order. It’s growth and data center has been in impressive. It’s got an outlook of mid team growth for DRAM 30% growth for NAND. I personally believe that their sustainable growth has to come from the strength and data center, but also the growth and adoption in 5G and then their automotive and industrial efforts.

Patrick Moorhead: Wow, you did well here. So, the company beat on the top and beat on the bottom. If you want to compare beats, it was the biggest beat on revenue in over a year, which was really good. The biggest beat on EPS for three quarters, where it goes all the way back to Q3 of ’21 when they beat by 9%, but they beat 8% here. So they’re crushing it. What I wanted to comment on is how strategic the company is and how strategic storage and memory is going to be more even in the future. It’s pretty easy to say, we see this, all these data slides that shows how data’s growing and storage and memory are essentially directly in line with those, more storage than memory, as memory typically goes up in increments. But what we’re going to see, the future of the data center, Micron really is driving that future.

So today in the data center, you can compose the compute and you can compose the storage, but what about the memory? Every time you need a lot more memory, you have to buy more compute. Compute guys love that, but if all you’re looking for is more memory, then you’re basically overpaying for it and you have latency because you have to string your system together through high speed networking.

So, Micron is working on very high speed memory that’s composable, through what’s called an interface called CXL that is really the industry standard. It was pioneered by Intel to be able to have pools of memory. So, imagine having a rack full of memory, just like you have a rack full of storage, and like you have a full of CPU. So, we’re a couple years away, but I’m talking with all of the major CSPs out there and all of the major enterprise compute players, like the HPEs, and the Dells, and the Lenovos, and the Ciscos about really this being the next big change inside the data center.

So, it’s not just commodity stuff folks, it’s technology that’s going to be re-architecting the data centers of the future. So, good stuff. So let’s move into our next topic and that’s GroqDay.

So you’re like, “Wait a second. Are you Groqing? What is Groq?” So, let’s talk about Groq and what it is as a company. So, first off Groq is one of the leaders, if not the leader, in machine learning, right up there with Nvidia. It’s quite smaller than Nvidia, but there are some use cases and some models, particularly low latency inference like NLP, that they just dominate in the industry. Now, I don’t know how they compare to what Nvidia announced last week, but that doesn’t matter because Groq is shipping this technology today.

Well, you and I showed up for their GroqDay event, which I thought was, was cool on, on a couple fronts.

So first off, it just wasn’t about, “Hey, why I’m great as a company and here’s what we’re doing.” They actually had their competitors there. Competitor called Mythic. Now, Mythic operates at a lower power than Groq does and hence lower performance. So are they really competitors? Yeah, they’re competitors, but close enough to where it doesn’t get uncomfortable.

They also had a bunch of cool customers on there as well, which is not different, or not unique, but it was great to see how folks like Google Brain, John Hopkins, [inaudible], differential sciences came in and talked about what they’re doing. More thought leadership than pushing Groq, which I appreciated, but I want to focus on one thing and that was really Jonathan Ross, the founder and CEO of the company, how he kicked it off. You and I, we probably do watch two keynotes a day, we could probably watch more if we wanted to. And what is it typically? It’s typically a monologue talking about the company.

Well, Jonathan actually asked three questions. That was his keynote. And it was, “Hey, is it a winner take all market?” I appreciated this. He was like, “I was wrong. This is not going to be a winner take all market. This is going to be many players who are going to be here.” The second question he asked was, “Hey, how do you hire and retain the best talent in this competitive space, folks like Google, Amazon and Meta?” His answer was interesting in that, “Hey, all we do is machine learning. So essentially, if you want to come in and be part of something that that’s all we’re doing … ”

I was thinking like, “Okay, we don’t do CPUs. We don’t do FPGAs, we don’t do G use for gaming. Come on in, this is all we do.” I thought that was a pretty interesting point. The third question was around is Groq a GPU killer? He was very clear. He is like, “No. We’re going to be in a future world that has CPUs, GPUs, FPGAs and ASICs.” By the way, I like that because that’s the story I tell, I’ll be honest with you.

But he did say, “Hey, there are some use cases that GPUs just do better. So hey, we’re not a GPU killer, we have to operate … Not only do we operate in systems with GPUs, but there are actually use cases that we do better at.” He brought out Argon supercomputer benchmarks, showing that it was 50% faster than the A100. So, that was 2,200, A100s versus 16 Groq chips. So, very interesting day, I’ve just started my coverage on the company. Daniel, you’ve been covering them a little bit longer.

Daniel Newman: Yeah, but he did a really good job and these GroqDays are always great to tune in. It’s been a bit of a series for the company. Jonathan’s a very interesting, thoughtful leader. He actually showed up at a Six Five summit last year, and guess what? They’re going to be back this year, so you will have another chance to hear from him at our event. I like that you pointed out the specialty in focus. I think that’s one of the big things here, is when you talk about … We’ve talked about GPUs on this particular pod a few times today. We talked about it, starting with Intel. Well, this is about high performance compute. This is about accelerated computing, low latency. The company really does operate on four tenets. It’s predictability, low latency, velocity, and scalability. So, they really aren’t trying to come into the market and be all things to all people, GPU.

They’re saying, “Hey, for these specific types of workload, where latency is critical, where you want to be able to scale … ” like you mentioned, what was it, 2,200 verse 16, you want to be able to scale at a reasonable amount of chips compute required to do so. They’re working on very specific applications and here’s the thing, is the benchmarks have been incredibly impressive in these specific areas. The company’s new, it’s entering a hyper-competitive market, with some very, very deeply entrenched players that are the known entities in accelerated compute. That’s be a challenge for Groq.

Having said that, the company has seen investment from, I believe, it’s TPG, from Tiger. Major dollars have been poured into this because we all know the magnitude that AI is going to play in our future and the ability for us to take exponential data sets more effectively, get that data to insight in a shorter period of time. That’s really what Groq is doing. I believe in his presentation last year at The Six Five Summit, he said his goal is to bring the cost of compute to zero. Ambitious, right? With no compute, if you’re in the business of compute.

The idea is between architectures, frameworks, software, and what developers are capable of, we can make the compute go further for every single ML application that you would build on Groq. So, the company’s moving in some interesting directions, like the leadership, they’ve recently brought some … you talked about the talent game. They brought some interesting talent onboard. I think they brought the CEO of Xilinks, the founder onto their board of director, but they’ve had a bunch of academics, big Silicon executives with huge experience, come in and want to be part of this story.

Of course, Pat, full disclosure, you and I are both part of this story as investors in the company as well. Always want to put that out there because yes, we are very bullish and optimistic. We put our money where our mouth is, as I like to say it. But you know, Pat, as I listen to the company, I continue to be encouraged. The size of market for AI is going to be massive. I don’t even think we understand how big this market is going to be and companies like Groq have an opportunity. Jonathan said it won’t be winner take all. Couldn’t agree with him more, but they could be a very, very important player in a small set that are going to be winners in this particular space. So Pat, I will leave it there.

Patrick Moorhead: Good stuff, man. Yeah, I’m learning new stuff every day and I’m at the very beginning of my research so far, but I’m glad they’re not trying to do everything for everybody, because that’s just impossible given the diversity in workloads out there, let’s move to our final topic. IBM Quantum news with HSBC. Daniel, what is going on here?

Daniel Newman: Well, in this case, they want to accelerate quantum computing. So, it’s all about accelerating stuff. We are the Six Five accelerator, we’re accelerating a conversation. Yeah, we haven’t talked about, sorry IBM Quantum, in a while. We haven’t talked about Quantum that much in a while. It’s gotten a little quiet after a period of time where there was a lot of announcements. We saw companies like IonQ go public. We saw a Honeywell spin off with CQC to create Quantinuum but what’s happening with quantum? Well, it seems to me that what we’re doing now is we’ve entered an era of bringing quantum to life through real-world applications and partnerships.

So IBM, I think it was yesterday or two days, ago made an announcement alongside HSBC, one of the world’s largest financial institutions, that they’re going to do a multi-year collaboration to basically help HSBC bolster its quantum experience. Essentially what I think is going on Pat, is IBM is working closely, side-by-side with the company, to help them really understand what quantum is capable of and figure out how to implement it as part of their business. So, for a company like IBM, this is going to mean giving access to systems, including … we talked about the Eagle on this show, right? Its Eagle processor and also working closely with the company to do some validation of potential use cases.

Now, in this particular space, financial services, one of them is like anti-money laundering and fraud. This is a huge opportunity right now, when you have the volume of transactions that are going on, you will need additional technology. This is where AI and accelerated workloads are coming into places. This is also where Quantum is coming into place. Really important to note though, Quantum is not a replacement in any way of what they’re doing with IBM, it’s not serving in any way as a replacement to classical computing and what you do with accelerated computing to solve these problems. What’s really going on is, it’s transformative. It’s working in partnership with, or in concert with, to say, “Hey, let’s take the best of what classical of computing can do. And let’s take the best of what quantum computing can do to potentially increase accuracy and more quickly get the insights that are required.”

Pat, as I see it, I believe financial institutions are a massive opportunity for quantum computing. We’ve seen studies in the past from likes of JP Morgan. Now you’re seeing HSBC. We have a decade of fairly significant innovation that’s going to go on in quantum. It’s going to be done in partnership. We’re going to see more simulation, where you’re going to see quantum workloads being deployed in public clouds, or in cloud type of architectures, so that you can take advantage of them in concert like I said, with your classical computing applications. For IBM as a whole, I think the continuous drip of notifying the market, “Hey, we’re winning customers. We’re winning large academic institutions.

We’re winning think tanks, research labs around the world.” To be able to say, “Hey, this technology is valid.” Of course IBM, built on super conducting. You’ve got the likes of Quantinuum and IonQ that are built on ion trapping. There’s still architectural debates going on in the marketplace, but the opportunities in markets and finance and energy, basically everywhere you see AI, in predictions at scale, being done to try to help industries take masses of data, there are parallel applications that quantum can support and bring more value to market as well. This is one example that IBM has. So HSBC, this is cool, but I think overall what’s really cool is what this means in terms of building meaningful, understandable applications for the market.

Patrick Moorhead: Dan, good job here, buddy. I want to add a couple things. So, first of all, if quantum is one of the next big leaps in computing and we all have to ask ourselves, “Hey, what phase are we in now?” There were four phases of AI before it became real. Heck, it took us 25 years to popularize the touchscreen when it came out for a computer. But I can safely say, based on my research, that quantum will be real and quantum will add incremental value over traditional computing. The only question is when. I think over the next three years, we are going to see SaaS services and we are going to see solutions that are going to be better and demonstrate quantum supremacy for algorithms that people actually care about.

I say that is because Google already showed quantum supremacy, but it was on an algorithm that nobody’s really doing anything with. So, we have to look at it like that.

I also want to talk about IBM strategy, which is to be essentially a full stack provider. They have the hardware, they have the developer tools, they have the ecosystem. They have pretty much have everything in place. I mean, they have multiple ways to consume as well. I think the only thing that IBM needs to always be looking at is, are superconductors going to be the technology that are going to take us into the next generation related to not only the number of qubits, the quality of qubits, but also the size of the installations that are required to do this. But right now, that’s the only thing that IBM has to be looking at.

One of the reasons that I think, in addition to some of the benefits of IBM strategy for quantum, that it brings to the table, is trust. If you look at IBM’s roadmap that it put out, I think like six years ago, and what they committed to, they’re actually delivering to promises that they made that long ago. If I do a sweep and I look at what I been told by some of the quantum computers’ makers, they’re slipping schedules all over the place. If they give a roadmap, it might be, I don’t know, two years long, or it’s 10 years long where, where nobody’s going to remember that. So, I think so far, IBM Quantum has engendered trust across its customers because it’s actually delivering what it says it’s going to deliver. So with that Daniel, that is the end of IBM Quantum and the end of this podcast. We talked about Intel, Oracle, Micron, Groq, and of course, IBM. I know you can read that, that’s good, but my bestie, it’s great to be here with you on this Friday.

Daniel Newman: It is and as you know, everybody knows out there, the way this works is we want you to hit that subscribe button, join us on, what? Spotify, apple, YouTube, across social media. Any discrepancies or challenges to the commentary being made on this show should be directly sent towards my friend here @PatrickMoorhead. His Twitter is red hot. You can read it. It’s got way more fun going on than mine does. But if you’re going to pass a few compliments because you really enjoyed our commentary or analysis, danielnewmanUV, that’s where you can find me. I need that kind of support. Monday, send it on Monday because today, I’m feeling good.

Patrick Moorhead: Ultraviolet Dan, UV Dan, baby. I love that. I wish I had something cool like that. But anyways folks, if you like what you heard, hit that subscribe button. Have a great weekend. Not as fluid as we normally are Daniel, but what can we say? We appreciate you and take care.

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.


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