These AI Stocks Will Make Millionaires By 2029

If you invested $10,000 into Nvidia just four years ago, you'd have over $125,000 today. If you put that money into Palunteer, you'd have close to a4 million right now. That's because these companies had the perfect products for the fastest growing market on the planet. But Nvidia and Palanteer are two of the most well-known companies on Earth. My name is Alex and I spent 8 years as an electrical engineer and AI researcher at MIT. And in this video, I'll show you two smaller stocks set to grow even faster, making them a great way to get rich without getting lucky. Your time is valuable, so let's get right into it. First things first, I'm not here to hold you hostage. This video is all about moving information inside AI data centers at the speed of light. And there are two stocks that I'll use to explain the market. Coherent, ticker symbol CHR, which found a way to make four times more lasers out of every wafer at half the cost. And Lumenum, ticker symbol LIT, which makes lasers to replace copper wires inside data center racks. And of course, I'll share which one of these stocks I think is the best buy right now. I want to make the best use of your time. So, let's start with what these companies have in common, like their markets, their customers, and their risks. When OpenAI released Chat GPT almost four years ago, the biggest bottleneck was compute. How fast new AI models could be trained and how fast they'd respond after being prompted was limited by the number and the speed of the GPUs powering them. But that's not really true today. Each new generation like Nvidia's Hopper, Blackwell, and Reuben GPUs got so much more powerful that they would actually turn through the data faster than anything could feed them. That means these AI chips were sitting idle, waiting for more data so that they could do their job. And that means the bottleneck moved from the chips themselves to the network feeding them. Most data center routers and switches send electrical signals over copper wire, which works well for short distances, but breaks down for large distributed AI data centers. On the flip side, optical networks transmit light through glass fibers, and light can carry much more data over much longer distances with much lower losses along the way. So, copper makes a lot of sense for moving data between chips inside a single rack. But serious AI data centers use optical networks to move data between racks, between buildings, and even across continents using undersea fiber. Optical connections can push 400G, 800G, or even 1.6T of bandwidth per port. G stands for gigabits per second. Your copper internet connection at home is probably 500 megabit or 1 GB internet, which is already fast enough to stream multiple 4K videos at the same time. A 400G optical connection is 400 times faster than that. And 1.6T means 1.6 6 terabs per second or 1,600g. That's the kind of insane bandwidth that massive AI data centers need to feed their GPUs fast enough so they don't sit idle. And just like everything else inside a data center, optical networking is actually an entire stack. Transceivers are the little plug-in modules that sit in switches and server ports. They're called transceivers because they can transmit and receive data. on one end of a fiber optic cable. They read in electrical signals from a chip and convert those signals into light using a tiny laser. Then on the other end, they read in that light and convert it back to electricity. I'm making this video right now because something big is happening with these lasers. The big thing that investors need to understand is that silicon is great for compute but terrible for making light. So unlike most of the chips that we talk about on this channel, laser chips are actually made with indium phosphide or INP instead of silicon. For the last 30 years, INP lasers were mainly used in longhaul telecommunications equipment, signal transmitters, boosters, and switches that carry data over very long distances. So companies like AT&T and Verizon would buy hundreds or thousands of INP lasers whenever they expanded their networks. And since they were such low volume products, the supply chain for them was low volume, too. Using 2-in or maybe even 4-in wafers instead of the big 12-in silicon wafers that the rest of the chip industry uses. But here's the big problem. The AI industry needs hundreds of millions of these lasers today. A 1.6 TB transceiver has eight of these laser chips sending data at 200 Gbits each. And don't forget, each fiber optic cable has two transceivers, one at each end. So that's 16 chips inside a single cable. And most GPUs actually take three cables to connect to the rest of the cluster. One from the GPU's network card to the leaf switch at the top of the rack, one from that switch to the spine switch for that group of racks, and a third one to the core switch that coordinates network traffic for the entire cluster. So that's three cables, six transceivers, and 48 indium phosphide laser chips per GPU. And that's only one part of the network, the one connecting GPUs in different racks over Infiniband or Ethernet. The connections between GPUs inside the same rack are still on copper today. And that network carries around 9 times the bandwidth. So moving it to fiber would mean many more times the lasers and roughly 20 more kowatts of power per rack. All to power the latest AI models. By the way, Claude Fable 5 is so powerful the US government forced Anthropic to keep it offline until just a few weeks ago. But now it's back and knowing how to use it is an advantage that you either have or others have over you. That's where Outskll comes in. 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So, it turns out that there's a big shortage in indium phospide because demand for lasers suddenly exploded with the AI revolution. Just last month, Lumenum CEO said that the shortage could get even worse than the memory shortage. And we all know what happened to memory stocks over the last 2 years. On top of that, the global market for optical transceivers is expected to grow from $23 billion last year to 112 billion in 2031, which would be a compound annual growth rate of 30%. That's two times faster than the S&P 500 over the last 10 years. So, this is the exact kind of high growth market that I want to be investing in. But, Coherent and Lum also share some serious risks. First, neither of them make their own raw materials. Most of the world's indium phospide supply comes from just three companies. Sumitomo and JX in Japan and AXT, which actually manufactures in Beijing. That's important because indium phospide is on China's export controls list. Second, if hyperscaler spending does slow down, both of these stocks will get hit hard. As I'm about to show you, data centers account for more than 70% of Coherence revenues. Lummentum doesn't report their data center numbers anymore, but their revenues grew by 83% year-over-year, which probably didn't come from telecom companies. Also, Nvidia buys from both of them and owns a piece of them, too. So, if they cut their optical networking budget, both of these companies will feel it right away. That's a huge upside if AI spending keeps growing. But, it's also a lot of exposure to one single market segment. And the third big risk is that indium phosphide shortages and supply constraints mean that both companies have to spend more in order to scale aggressively and they need to do it while demand is hot. So any construction or production delays hurt them twice as bad. Once for losing market share today and again for missing demand down the road. That means today's winners could quickly become tomorrow's losers. And you need to know that going in. All right, let's start with Coherent, ticker symbol CHR. Coherent reported $2 billion in revenue last quarter, which is up 34% year-over-year with gross margins of 38.5%, which is almost 3 points higher than last year. For the full fiscal year, their adjusted earnings came in at $5.61 per share versus $353 the year before. That's 59% earnings growth year-over-year. Threearters of their revenue came from one place. Coherence data center and communication segment generated $5.3 billion of their 7.1 billion in revenues over the last year, while their older industrial laser business actually shrank. That's another strong signal that demand for indium phosphide lasers is now coming mostly from AI. One special thing about Coherent is that they're vertically integrated. They make their own laser chips, package them into optical engines, and build the finished 800G and 1.6 TBTE transceivers that those chips go into. While Lumenum builds and sells components, Coherent does everything starting from the bare wafer. And that wafer might be the secret to their success. Like I said earlier, chips made on indium phosphide used to be very low volume products. So, they were made on 2 to 4in wafers, but Coherent moved their production to 6-in wafers, which lets them make four times more chips at roughly half the cost. But they actually get even more than that for two key reasons. First, there's less wasted space at the edge of the wafer as the wafer gets bigger. More of the wafer gets turned into chips. And second, yields actually tend to go up with total production volume because the process gets refined way more often. Coherent CEO pointed out that their yields are actually higher on their 6-in lines across every single product that they make on them. As a result, Coherent expects to double their indium phosphide output by the end of this year and then double it again by the end of 2027. Nobody else even comes close. Earlier this year, Nvidia invested $2 billion into Coherent, which means they own just under 4% of the company. They also signed a multi-year agreement that includes a multi-billion dollar purchase commitment as well as access to five more of Coherent product lines of co-ackaged optics. And this wasn't some random investment. Nvidia has been in the optical networking game ever since they bought Melanox in 2020, which is how they have the biggest data center networking business in the world today. But Coherence's big advantages in the laser chip market come with some real costs, too. Coherent spent $1.1 billion on capex over the last year versus about $80 million in cash from operations. That means they spent roughly $14 on chip production for every $1 they actually made. Their management team says that investments into data center chip production have an average payback period of about 18 months. So, if they're right, this is pretty much the best investment they could possibly make. But if their schedule slips, it'll be a very expensive mistake. As an investor, I really like Coherent's full stack approach to optics. From their costefficient 6-in wafers all the way to their high-speed transceivers. And even though they're spending $14 for every $1 they make, being backed and partly owned by Nvidia lowers the risk of all that spending over the next few years. Talk about a great way to get rich without getting lucky. And that brings me to Lumenum, ticker symbol LI T. And if you feel I've earned it, consider hitting the like button and subscribing to the channel. That really helps me out and it lets me know to make more comparison videos like this. Thanks. Now, let's talk about Lumenum stock. Lumenum reported a billion dollars in revenue last quarter, which was up 109% year-over-year. Adjusted earnings per share came in at $3.23 23 versus just 88 a year ago, which means their earnings are up 267% from last year. And their adjusted gross margins hit 50.4%. You know the shortage is bad when gross margins get this high on components. Lum's main product is an electroabsorption modulated laser or EML. EMLs do two jobs on the same chip. First, it has a laser that runs continuously at a specific wavelength. And second, it has an absorber that sits right next to it. When the absorber turns on, the light from the laser is blocked, which is the same thing as a zero. When the absorber turns off, the laser can get through. That's a one. This absorber can turn on and off more than 100 billion times per second. That's how Lumenum encodes data into its lasers. Lumenum makes several different kinds of lasers besides EMLs. For example, they make ultra high power lasers for silicon photonics that get switched on and off somewhere else entirely. And they also make pump lasers which don't carry data at all. They feed the amplifiers that keep telecom signals strong as they travel across long distances. Lum is effectively sold out of their pump lasers for the foreseeable future. But the biggest opportunity is where all these lasers are about to sit. Today, optical engines live inside a plug at the front of a switch that's connected to a chip by tens of cm of copper. The problem with copper is that the faster you try to move a signal through it, which means the higher the frequency, the more signal you lose along the way for two reasons. First, current stops flowing through the middle of the wire and crowds towards its surface. So, there's less metal actually carrying the signal. That's called the skin effect. And second, some of that signal gets absorbed by the wire's insulation and turns into heat. That's called dialectric loss. And both of these losses can get pretty noticeable, even over just a few inches of copper. But glass doesn't have these problems. It would take 20 m of optical fiber to lose as much signal as just 10 in of copper. And co-ackaged optics actually move the laser right next to the chip. Switching to fiber optics and shortening this electrical path lowers the amount of energy that it takes to move data by over 60%. Nvidia says their co-ackaged optical switches cut network power by 3 and 1/2 times and use four times fewer lasers to do it. That saves around 13 kW of power on a Grace Blackwell rack or about 10% of the rack's entire power budget, which means all that extra power can go back to more compute. That's exactly why Nvidia invested $2 billion in Lumenum on the same day they invested in Coherent and with almost the same terms. Lumenum spent $451 million on factories and equipment last year against $751 million in cash from operations. That means they spent60 for every dollar they actually made compared to Coherence 14 bucks. One thing I should mention is that if you pull up Lumen's numbers, they posted a net loss of $84.65 per share last quarter, but that's due to a one-time non-cash charge of $7.8 billion associated with converting debt to equity. But the business itself generated $279 million in operating income for the quarter. This is why it's important to look into the details instead of just trusting headline numbers. So, if networking really is the next big bottleneck for AI, Lum is one of the only companies in any position to solve it, especially with Nvidia in their corner, too. All right, so which of these two stocks am I actually buying? Personally, I'm still buying both, just like I said last time I covered them. But don't worry, I won't leave you hanging. If I could only pick one, I'd still pick Coherent because they built the world's first production line for 6-in indium phosphide wafers and they're on track to quadruple their capacity by the end of next year. That's exactly what you want to be doing during a shortage. Just remember, they're spending $14 for every dollar they actually generate to do it. That said, I think Lumenum still has a ton of upside. They grew their revenues by 109% year-over-year at over 50% gross margins. And they only spent 60 cents on every dollar to do it. So, at the very least, both of these stocks are worth a spot on every long-term investor's watch list. Let me know in the comments whether you're buying Coherent or Lum. And if you want me to make a deep dive video on either one of them, and if you want to see even more stocks I'm buying to get rich without getting lucky, check out this video next. Either way, thanks for watching and until next time, this is Tickerol U. My name is Alex, reminding you that the best investment you can make is in you.