We Analyzed 6 AI Sectors - Only 3 Look Like HUGE Opportunities

Martin (0:00)

Where the whole stack is heading is that we are gonna see a lot of bigger players eating the small ones. And like, let's say in five to eight years, there might be a couple 10 trillions plus companies who are gonna eat everyone else, and everyone else is really gonna struggle to compete with them.

John Gillen (0:18)

If you are an investor in artificial intelligence, you know that every level of the AI stack has been changing and evolving a lot this year. So where are we on this trade? What do investors need to know about this? And where is value accruing now? Hello and welcome to Milk Road Stocks, the daily market show that has me, John Gillen, filling in for LG today. I promise not to touch any of his stuff or break anything, but I'm gonna be here to host this episode because it's a holiday in Canada, and apparently LG is involved in these things sometimes. I'm John Gillen, today is Tuesday, October 13th. Our lead researcher, Martin, is back for an update on the entire AI stack. We're gonna walk through every level of this and get his thoughts on where the alpha is today. So if that sounds good to you, make sure you like and subscribe, share this episode with somebody who's gonna enjoy it. Martin, how are you today?

Martin (1:00)

Hey John, I'm doing great, thanks.

John Gillen (1:03)

Before we dive into the slides that you've prepared, I thought it would be a good idea to start with just a conversation on why you thought it was important to revisit the whole AI stack now, and why do investors need to be revisiting all of this at this moment in the markets here?

Martin (1:17)

I feel like AI stocks have been stuck lately, and a lot of people are now maybe not interested anymore in AI trade because it feels like the speculational, at least that part of investors is now gone. A lot of has changed fundamentally, and so I wanted to revisit the whole AI stack and see where we are right now, what are the valuations, are those layers making money today, what are the assumptions, and so it defines you what kind of investor you want to be, and it also paints a different risk profile for different layers. So that's what I want to talk about today.

John Gillen (1:58)

I think that's a great topic, and I think before we dive into all of this, I think we're going to start with energy and data centers, but just walk us through really quickly how you see every level of the AI trade here and what these different parts of the stack are.

Martin (2:11)

Yeah. I think this pyramid of six layers, it starts with energy and data centers. This is not something I came up with. That's pretty common approach, how everyone is looking at this AI trade. This is not from my hat.

It starts at the very bottom because we need energy, we need data centers, we need the buildings where people can bring in or companies can bring those GPUs and just plug them and make them connected to the electricity, because then people can use them and sell tokens, use AI and on the other side, there's applications or companies that are trying and using those AI tokens or that intelligence in their own benefits. Either it's about growing their revenues faster or just offering more products or just iterate more quickly or just letting some people go because people are more effective today. So I'm going to walk you through the whole spectrum. So we start from the energy and all the way down to how companies are using this intelligence.

SPEAKER_3 (3:25)

We're going to pause for a second.

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John Gillen (3:44)

Okay, perfect. I'm actually really excited for this because it's been a while since I've done a review of all of this. If you're listening to this episode, I highly recommend you flip over to YouTube for this because just on this slide alone, Martin has a ton of names in every level of this stack laid out. But Martin, let's dive in with energy and start the conversation there.

What are you seeing on the energy layer and what should people know about what's happening here?