The Next Winners of the AI Data Center Boom

**Melvin** (0:00)
With annual revenue growing from 1 billion this year to 24.8 billion next year, and then 71 billion by 2020 So this is a massive, massive scale.

**LGD** (0:09)
What's up, everybody? It's LGD who's set here, and welcome to Milk Road AI, the daily AI show that's always looking for bargains on stocks, even if the bargain might be even bigger next week. Today is July 21st, 2026, recording on July 20th. AI stocks topped a few weeks ago, but does that mean that they're completely cooked? Our lead AI analyst, Melvin, definitely does not think so, and today he's going to explain a very overlooked sector of the trade, photonics, the light that moves the data to the chips and what part of the rack is needed to make that happen. He's also going to share two companies that he likes in the sector and how their revenue is set to take off as the data center build-up winds up for the next leg. If you want to see his moves on these companies and how he's played Neo Clouds, Robotics, and also made huge gains on Micron, Nebius and AMD this year, you got to go Milk Road PRO at the link below. It's just a dollar for a seven-day trial. And a reminder that our podcast today is free. And it wouldn't be possible without our partners at Securitize, the regulated Railsware tokenization, and Bitget Stocks 2 with real liquidity, real dividends. Keep an ear out later in the show for a message from them.
All right, Melvin, what do you got for me today?

**Melvin** (1:11)
Well, thanks for having me back on LG. Last week, we talked about Neo Clouds and people seems to have really enjoyed that show. And I'm back. And today, I want to talk to about a sector that is a bit of a beat down at the moment. And that's Photonics and Optical Networking.
Basically, how data actually moves from these AI data centers between the GPUs.
And I know the second I say Photonics, half of you are going to be like, okay, this sounds crazy. I don't know what that is. But stick with me here. It's actually not that complicated because once you break it down, there's, and once you break it down, it's really easy and there's so much money to be made in this trade still.

**LGD** (1:56)
I don't even know what Photonics is, man, but you said there's money to be made, so I'm all ears.

**Melvin** (2:00)
Exactly. Perfect. Before I tell you what Photonics is, let me give you some context first. If you can just put up that first chart, LG, perfect. The big four hyperscalers, Amazon, Google, Meta, Microsoft, pushed their 2026 CapEx plans, past 700 billion combined, and that's after they all raised guidance, again, following their quarter earnings, their March quarter earnings. To put that in context, if you go back to 2018, these four companies combined were spending something like 30-40 billion a year in total.
By 2024, that number was roughly 261 billion, and this year, as I mentioned, it's already past 700 billion, and it's not slowing anytime soon because last week, Morgan Stanley raises 2027 and 2028 CapEx by 9 and 10 percent, and so now they're essentially calling for $1.23 trillion in CapEx in 2027 and 1.4 trillion in 2028 There's a massive amount of capital that will be directed towards the AI infrastructure buildout. Now, inside that spent, networking like the wiring and the switches connecting all these GPUs together is already eating roughly 15-18 percent of total cluster capital cost. So in a 200,000 GPU cluster today, optical transceivers, which are basically the components that convert electric signals into data, into light, sorry. So data can move between GPUs at extreme speeds, alone are consuming about 17 megawatts and 435 megawatts total power.
That's a real chunk of the build. So reason why I bring all this up is, everybody's been focused on GPUs, the memory trades. We talked about Micron a couple of weeks ago. We talked about NeoClouds last week. But there's this third bottleneck, and they had a bit of a run up, but they have gotten absolutely wrecked, along with some of the semiconductor trades over the last month or so. And I think that's where the real opportunity is. And we're currently going through a massive, massive build out. And the key question is, how do you connect tens of thousands of GPUs together so they can act like one giant brain, instead of just a bunch of chips, you know, sitting next to each other, not talking to each other fast enough? And that's what photonics is. And let me explain that in actually more details, using that image. So easiest way to understand photonics is this. Electronics moves data through copper using electricity, while photonics moves data through glass fiber using light.