AI Divergence, Rotation Strength & ROI: What's Next for Mag 7?

for the group will bring in our panel to take a closer look at what that might be. Joining us, Sylvia Jablonski, Chief Executive Officer and CIO over at defiance ETFs, and Stephanie Walter, practice leader, AI stack at Hyper Frame Research. Sylvia, we'll start with you. I mean, how are you looking at the mag seven names, knowing that we've heard from all of them. But Nvidia right now we've seen some rotation away perhaps more recently some rotation back into these names though. So how are you looking at this group. Yeah. Good morning. Well I think that you know we saw some rotation away from them. And as you just said we saw some rotation back. And the reason for that is that the big takeaway from this earnings season so far is that AI demand is certainly not slowing. It's broadening. And the the CapEx continues to to essentially go to that. And what's been really good about this, and it's not necessarily the mag seven that I'm interested in. It would be more like the AI hyperscalers and some of the Mag seven participate in that Amazon alphabet being good examples, companies that are spending, but they're also monetizing on AI, right? So they're seeing accelerated cloud growth. They're building AI infrastructure that's becoming monetizable, and they're just, you know, the earnings that they've provided were a clearing event for the market and investors back in. And Stephanie, we have a great setup here now. Thanks to Sylvia for leading to what you call the divergent seven, which I love. Is there still an argument to be made that we should think of these seven names in the same grouping, because their strategies and their spend are seemingly starting to diverge as as you highlight with your divergent seven. So take us through that name that you like to use and how you're looking at the group. Yeah. I mean, they were originally grouped together because of their market influence, you know, not because they share one business model. Obviously we have Tesla, we have Amazon, we, we have meta, but their, their AI strategies are really diverging significantly. So Microsoft, Amazon, Google, you know, we're talking about the hyperscalers. They monetize cloud infrastructure. Nvidia supplying the underlying platform hardware. Meta is really using AI at least right now, primarily to improve their ads business. And we're sort of waiting to see if they can, if they can create additional revenue streams from from AI and Apple. I mean, they, they have probably the best consumer distribution, but their AI path isn't quite as clear. Tesla is pursuing physical AI through autonomy and robotics, but they're really asking investors to really invest based on their their roadmap, what AI is going to be doing for them in the future. And So you have these companies that are just really starting to use AI and go their own separate ways. And, and they're not, they're not quite acting as a group anymore, for sure. And so then, Sylvia, as you look at, I'm going to call them a group just because the name exists for the mag seven. Who do you view as emerging as the winners here? Yeah. I think again, it would just be what I would almost relabel them as is, is these AI hyperscalers. So they would be going off of this earnings season anyway. Names like Amazon that 37% year over year growth there. You have Microsoft, you have Google. You have even companies like Oracle that with the Google and Open AI partnership, they're companies that are essentially spending on AI. They're becoming, you know, companies that run AI models, cloud data centers. They, they offer, you know, modeling cloud services, support for data centers, things like this to other companies. And what they're doing is they're taking in revenue from this. So what I would do is kind of bifurcate that list. And, you know, not to say that the other other names won't be in that basket, but, you know, I would also broaden that out to, to names like Alibaba and Tencent, for example, that are really better representing the AI hyperscaler trade here. And Stephanie, I want to get your thoughts here too. I mean, the three companies just mentioned there with Amazon, Microsoft and Google, perhaps Google, we should talk about sort of separately here because we saw this spend sort of being justified. But then we have Google as our good counterpoint where we're having the spend really have an impact in pressuring cash flow. Who are you looking at right now, Stephanie, as who's emerging as the leaders or the winners here? And how are you looking at the different reactions we saw to the CapEx spend and how they're affecting the businesses across these big names? Well, I definitely agree that Microsoft and Amazon, they they are emerging as the winners because they're delivering the clearest connection between AI spending and measurable, measurable demand. You know, Microsoft has AI across Azure. They have developer developer tools. They have copilot. AWS is growth was demonstrating that Amazon infrastructure investment is paying off. Google is a little bit different here. Google is interesting. They're really they're making the transition from sort of research led AI into now needing to commercialize it. And so they, they delivered exceptional cloud growth, but the escalating costs of servicing that demand really pressured the cash flow. And so, you know, I like to say investors are asking for the receipts, right? So Amazon and Microsoft give them the receipts. Google is still is still trying to, to figure out how to make money from this huge investment. Really appreciate you both being with us today to take a closer look at these names, especially in advance of hearing from Nvidia at the end of the month. Sylvia Blonsky, Chief Executive Officer and CIO