IBM, obviously a tech giant, but it's not in the so-called magnificent seven, right? Yet here it is, hitting a record. So, I guess just high level, give us kind of what's going on here that's been propelling that recent growth.

Yeah, and thank you guys so much for having me. I think with IBM, it really started off as a free cash flow story when we look back about five, six quarters ago going into Q4 when they had the big beat. That was kind of the start of the rally. But you mentioned it not being part of the magnificent seven. I, I think they're really starting to make their name, being able to enable the magnificent seven, right? They've talked about the core pillars being hybrid cloud and gen AI. But a lot about that is being in the infrastructure layer. Really, how do we make all of this work? And they're uniquely positioned to do that by leveraging both infrastructure and consulting with that growing software business that they're starting to get some more recognition for.

And of course, um, when they last reported earnings, the stock actually initially fell because the numbers weren't quite strong enough to meet some lofty expectations. And since then, obviously, we have seen a rebound. When you look forward at what growth is expected, you know, you look at revenue growth, um, in the out years, it's expected it will show kind of low to mid single digit revenue growth, which isn't huge. So is that enough to continue to propel the stock higher?

Yeah, well, maybe touching on the quarter real quick. You know, a lot of times we try to break down these complicated businesses into some of these key metrics. And I think it was Gen AI bookings, free cash flow, and then Red Hat, which is kind of that center of gravity for their software business. And, you know, two of the three were below at least kind of consensus expectations. Free cash flow is the outlier to the positive side. So we look to the future, I think a lot of it, you know, they peg that 5% growth rate. That's kind of what they're looking for. But it's going to be just as much about how they get it than if they get it. So software growth definitely is the number one thing that investors are focused on. You follow that with the Gen AI side of consulting. And then infrastructure obviously going to be much more refresh dependent. So a lot of this valuation and the current sentiment is really coming down to just how does that software business performs?

Um, and to dig into the Gen AI piece of it a little more, obviously on overall AI and sort of machine learning, IBM had Watson and sort of was a pioneer there. Where do they play in that world, not from an infrastructure perspective, but that actual product, right? What's the role that it plays now in terms of the company's growth?

Yeah. Yeah, and I think one thing to always to point out is from a book of business standpoint, we're still at about 80% consulting, right, for Gen AI, which means that they're not only helping people deploy all this, but they're seeing all the trends, seeing all the choke points. And they're really starting to talk a lot more about this idea of client zero, which is about how IBM themselves have saved $3.5 billion in run rate costs at the end of last year by deploying Gen AI. So if you talk about what are they really doing from a product standpoint, their own series of models, the granite models would be what we would call small language model. It's open source. You can move from, um, openshift AI to Watson XAI once you're fully deployed and actually build up your own IP on those smaller models. They're really focused around the enterprise cost efficiency of running those models. And then the other side of that, I know you said not in the infrastructure side, but we got to touch on it a little bit is these things like Watson X governance and Watson X orchestrate. And those two things are really about managing the basically practical, uh, implications of having Gen AI run in your environment. How does the data get accessed, how does it not get access for areas that you don't want it going? And then how do you keep track of all these different models and how they're interacting with each other?

Matt, I also want to ask you about quantum because you wrote about this in your latest note, uh, saying that IBM could be a stealth quantum play. Now, quantum is confusing, right? Because you hear on the one hand that we're sort of years away from it having practical applications, but then you see it, you know, that the some companies like IBM are already making money from it. So help help explain that for our viewers.

Yeah, and I think one of the reasons IBM started talking about is that it is starting to come up so much more with some of these other companies coming up in the space. And it's also coming up more for investors talking to people like me. And so we addressed it, um, at IBM Think. And the way they kind of pointed it out is they have 75 quantum computers, 13 of them are currently running at production. And they feel like this will be a real part of their business by the end of the decade. And I think that by the end of the decade was the part that really surprised a lot of people in the room because like you mentioned, quantum has felt like it's been a story for quite some time, but it's never felt really tangibly real. And I think we're starting to get to the place that the costs are coming down to a point where we can have commercial applications beyond some of these early adopters like biotech.

Um, finally, Matt, I'm curious what you think the biggest risk is or risks, uh, for the stock going forward that might disrupt this trajectory it's been on.

Yeah. Yeah, you know, when you talk about risks from a stock specific perspective, it's kind of when you look at how the stock came up too, right? When you have 62 billion in revenue, it's hard to really get that big of a ship moving fast in one direction in terms of accelerating growth to have numbers go up that way. But the multiple expansion comes around sentiment. And sentiment right now is really improving around those core use cases of Gen AI and that core use case around hybrid cloud. So I, I think if we saw a change in their competitive positioning, particularly as it pertains to Gen AI, where I think people see this as a safer way to play the underlying part and not have to make a bet on who's going to win at the actual large language model level. I think that would be where you could see the most risk from a rerating happening.