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Earlier this month, I gave a formal presentation for institutional investors at the MoneyShow Masters Symposium in Dallas. It was entitled The Next Big Thing to Invest In. 

I described how investors can find publicly-traded opportunities that could return 10 times their initial investment (or more). But finding these opportunities requires thinking differently and breaking from the consensus mentality that the Wall Street herd tends to follows.

I used this same mindset to personally find several of my own biggest winners, which included investing into Netflix in January 2009 (at $4.62/share, split adjusted), into Tesla in August 2013 (through its acquisition of SolarCity, at $38.80 per Tesla-equivalent share), into NVIDIA in March 2017 (at $24.24/share, split adjusted), and even into Bitcoin in 2015 (for $248 per BTC). Each of those is living proof that the strategy has effectively found several 10-baggers in the public markets.

Looking forward, I believe there are three pools that investors should be fishing in to hook the next big opportunities: quantum computing, AI agents, and the space economy.

I’ll describe each of these below, with two investment ideas for each trend.

Quantum Computing

AI is now available everywhere, though it’s not equally distributed.

Some companies are several steps ahead of their competitors when it comes to incorporating AI agents into their operations. They’ve built upon large language model platforms like OpenAI’s GPT or xAI’s Grok to understand questions being asked and to immediately respond with accurate answers.

This allows organizations to scale quickly without necessarily needing to hire a larger workforce. AI chatbots can handle customer service requests and AI marketers can analyze large amounts of information to find insightful patterns. Aside from just cost savings, AI and machine learning can also be used to make a company’s products and technologies stronger and more valuable.

The stock market’s recent volatility has sent investors on a rollercoaster of emotions. Just like in a real theme park, folks have gotten scared, anxious, and even fearful this month.

Yet whatever the market’s mood may be, innovation marches onward. Smart companies are finding ways to use new technologies to become more efficient and more valuable.

The Next Big Thing is out there. Are you prepared to capitalize on it?

7investing offers actionable stock recommendations and Best Buys every month. If you’d like a 7-day free trial of our site, please visit our Subscription Page.

Transcript

Simon Erickson  00:00

Okay, welcome everyone to the next big thing to invest in, which I promise will be one of the most futuristic sessions of the symposium for you this weekend. My name is Simon Erickson. I’m founder and CEO of 7investing also a big fan of blues music and the New Orleans Saints.

 

Simon Erickson  00:16

Quick raise of hands. Please raise your hand if you’ve ever, in your investing lifetime, bought shares, individual shares of Netflix. Cool. Okay, keep them up or raise them if you’ve ever bought shares of Tesla. Fantastic. How about Nvidia and last but not we got a lot of hands on those. How about the last but not least? How about Bitcoin, or any crypto currency? Okay, great. Yeah. So that’s more than I was expecting.

 

Simon Erickson  00:40

The point is that a lot of people will look back on those and say, Oh, of course, it’s just one of its best performers. It’s easy to go back and say, Oh, this was a 40 bag or 100 bag or 3000 bag or whatever you want to say, but it’s a lot harder sometimes to be able to see those in plain sight, even though they are all publicly tradable opportunities for stocks or cryptos, anything else like that.

 

Simon Erickson  01:00

And so the point of this presentation is to go back and from from starting at 2025 where are the best next big things that are in plain sight right now for us to be looking for? Where are the sectors that have those? How do you even spot those in the first place? And what are the actually individual opportunities? And that’s really what allows you to capture the big gains, whether it be from Netflix, whether it be from Tesla, whether it be from Nvidia, whether it be from Bitcoin or anything else, which were all seven investing recommendations and actual holdings at one point. So it’s a whole point of thinking differently. How can we find these opportunities if they’re out there, but we don’t want to be going with her versus doing what conventional wisdom teaches us?

 

Simon Erickson  01:39

So kind of there’s three predictors of finding these kinds of stocks. The first is, what I like to say is, think differently. Don’t just show the herd of what the S, p5, 100 or the media is telling you. Try to try to think about the information that’s out there in a different way as an investor, and look for the companies that are also looking for the same information in a different way. This is a graphic back from World War Two, where they were bringing fighter planes and bomber planes back from the theater war in Europe. And they were looking at the information and trying to figure out where the enemy was shooting at them. And they noticed that it was not an equal distribution of the number of bullet holes per square foot on the plane. And if you duck down into a little bit, they took all these planes that they were looking at and returned the theater war. And they said, Okay, if we’re looking at the section of the plane, which is the engine, kind of in the front of the picture, there at the top of the picture, we’re about 1.1 bullet holes per square foot. But it wasn’t even evenly distributed right the fuselage behind that was near like 1.7 we were seeing much, much more fire right in the middle section of the plane, the fuel system that’s out there by the wings, 1.55 bullet holes per square foot. And then the rest of the plane, including the back of the plane, about one the plane, about 1.8 and so the initial wisdom was, oh my gosh, we need to start putting more armor on the plane. In the middle of the plane, clearly, that’s where all the bullet holes are coming. You know, we need to be putting additional armor, which adds cost, which adds weight, it slows the planes down. It was kind of the general consensus at the time. It was Abraham Wald. It was actually one of the statisticians in here. He said, guys, I think we’re looking at this entirely the wrong way. These are the planes that came back. These are the ones that survived but not get shot. Now the enemy is not good enough with an anti aircraft gun to just figure out exactly what part of the plane is going to hit. The ones that we are actually seeing are the ones that have a higher percentage than an shot or the fuel system, we should really be having the armor of the engine, because the engine planes that have shot an engine on the one that are not coming, right? It’s a different way of thinking that actually was useful in this opportunity. Look for companies that are using the same technologies out there today, and think about them in a different way.

 

Simon Erickson  03:41

The second was a couple of MBA professors a couple of decades ago came up with the idea of a blue ocean strategy. And this is a way of thinking about things, where, if you’ve got a lot of competitors, it’s very hard community margin, it’s very hard to do a red ocean fighting it out a lot of competition. You get the price wars. You get into volume wars. It’s just a much more difficult game to play. But if you’re in a blue ocean where you’re doing something completely different than no one else is doing, it’s much easier to try out new things and try new products, try new pricing strategies, capture higher margins. You don’t have the same level of direct competition. So one predictor of finding the next big thing is look for the companies that are competing in blue oceans where there’s not a lot of competition yet. Maybe it’s a new technology we’re just starting to understand. Everybody hasn’t gotten their hands on it yet. Maybe there’s only a limited number of vendors or competitors you’re going up against out there.

 

Simon Erickson  04:28

This is another predictor of finding opportunities in sectors that are not so populated at the time just yet. And they follow both of those projects. Look at the companies that are in the S curve. This is the adoption rate of new technologies or new companies that enter the market. It happens really quickly. It doesn’t go linearly. It follows kind of this S curve, right? If you look at the chart, you look at the telephone and how quickly that went into the percentage of US households, the radio, refrigerator, TVs, computers, internet tends to follow that once the majority catches on, you’ve got kind of the. Of the adopters that catch on to something at first, but then it’s really a couple of years you get to really hit that S curve. And so when we’re looking for these things, don’t just theoretically or philosophically say, Oh yeah, it’s gonna be the next big thing. Look at the companies like growing revenues. Look for the ones that are hitting that S curve. They’re getting adoption really, really quickly, because it’s showing that it’s working. They’re executing very well on bringing it to market.

 

Simon Erickson  05:23

That’s kind of the framework. “Great, Simon, you’ve got three predictors of the next big thing. I would like you to tell me how to make money off of this. And where should we actually be investing our dollars if we’re looking forward rather than backwards?”

 

Simon Erickson  05:34

And so I’ve got three sectors that I think are very interesting right now that follow each of those three predictors. And I’ve kind of chock full of some opportunities for the next big thing and the next big, 10 baggers, 50 baggers, 100 baggers.

 

Simon Erickson  05:46

We do have several of these profiled at 7investing. We make recommendations each and every month. I always like to look forward in what the future is going to give us, first and foremost. And so the three sectors are quantum computing, AI agents, artificial intelligence agents, and this space kind of let’s break each one of those down on a one by one second.

 

Simon Erickson  06:03

The first is quantum computing. My goodness, this is a two year conversation right here. I think we can actually spend the entire presentation just talking about, why is quantum computing different than classical computing out there? We’ve spent since the 1960s building up these more and more efficient ways of doing computing on binary with classical combinations of processors, and we made them faster and faster and faster. And they had a niche of where they were most useful, right? At first we were kind of doing simple things like mathematical calculations and building programs like Microsoft Excel. There were, there were fairly simplistic in the calculations. And then we started writing rules for software. You know, if you wanted to manage your networks of your company, or you wanted to build a new type of software, something like that, and now they’re getting more and more complex, but we’re trying to use more and more software tools based on the same computing techniques that were built decades ago. But everything in the world is not a zero or a one. We’ve got floating point operations there, which are more of a gradient, right? It’s not just on or off. It’s like, is the color purple? A deep purple, or is it a light purple? You know, is blue have different shades in it. And so we introduced GPUs, graphic processing units. And video made a ton of money for investors, because they would look at things in terms of 1.001 rather than just one or two. There were gradients of things. And then, after we started rendering graphics for video games, we realized who could start recognizing seeing things by the same principle, oh, I’m 99% sure that is a nose and that is a shoulder. So now I can start identifying images and putting those into creating images and creating videos and all the neat things that GPUs have done over the over the last couple of years. But still, Moore’s Law has its limitations, and we’ve known this for decades. There’s only so much you can do with computing that were built upon the classical models that we have had for seven decades now, and so quantum computing uses entirely different type of technology than a classical computer itself does. These are not just the same transistors that we’ve been using for classical computers and integrated circuits. These are now block spheres and new concepts like superposition and things that will make these previously unsolvable problems where you were running things in series from a CPU, where you were running things in parallel from a GPU. Now all of a sudden, you can look at millions of variables all at the same time and calculate them instantaneously, unsolvable problems. I like to give the example of say that we have 1000 marbles at 1000 different locations all across the world. We’re going to drop all from exactly the same height of 1000 feet. We’re going to drop one of them here in Dallas. One of them is going to be in Brazil. One of them is going to be in Australia, one of them is going to be in the Middle East, wherever that might be. Which one of those is going to hit the ground first, you might start thinking, okay, we can probably model something like this, that maybe we could look at what the temperature is. We would look at kind of the wind speeds that are going on out there right now, maybe air pressure. There’s a zillion different variables you could start plugging into some kind of calculation like this, but it would take something like a quantum computer look at all of those at exactly the same time in relation to one another, and immediately tell you the one that’s in Brazil is going to hit the ground first because of A, B, C, D, and 1000 different other variables. And that’s kind of the idea of where these are heading. Or there’s other unsolvable problems. Can we model out drugs so that the drug is hitting exactly the target that the molecules are interacting with one another in the human bodies? Can get exactly where you wanted. It for precision care, for cancer care. Can you do it for discovering new super conductive materials, or any kind of material design out there? Could you do it for logistics, if you wanted to move everybody on an airline across the entire world and make sure that nobody was missing their flight? How can you take all of these variables? That’s how quantum computing is an interesting concept. It’s something we’ve been talking about for a long time, but it’s also very, very difficult to do. But the thing that’s most interesting right now is it’s not just a physics problem or science project problem anymore. You’re actually starting to see some contracts, both from academic institutions and also government sponsors, for things like this, and there’s not a whole lot of opportunities.

 

Simon Erickson  10:00

In the stock market today, but one that is interesting is a company called IonQ. This is the world’s first pure play, publicly traded quantum computing company. Pure play is the most important thing. We’ve seen Microsoft work on this. We’ve seen IBM work on this. We’ve seen Google work on this. They’re very deep pocketed tech companies. But IonQ is specifically saying, I want to build the best and most efficient quantum computer. I’m going to build on ion trapping technology, and without getting into the two bird conversation, this is one of the more stable ways of preserving a cube. It’s not the fastest type of quantum computing, but it is one of the most stable, because they’re very they’re very quantum computers have to be held in a vacuum. They’re very susceptible to interference from other things. This is one of the more stable technologies that’s available out there. And for a while, you know, this is a article I drew from money show back in 2021 where, you know, it just kind of come public. You know, there was a SPAC craze. People were raising lots of money in the summer of 2021 I had two took advantage of taking the opportunity, but they weren’t making any money. They had a million dollars total revenue, just a couple of grants. It was a little bit of a research project, R and D stuff. And we’ve seen even just the almost four years now, since then, the contracts are starting to come in. And it’s not just a yes, we’ll get there when we get there, but businesses and even government sponsored contracts are starting to flow in the door. In fact, $54 million was the prize that they just won on a four year deal with the United States Air Force, who’s wanting to use quantum computing into their own systems and into their own infrastructure. Compare that with their total revenue last year, which was $42 million you’ve basically now got a contract. It’s even more than their total sales he did last year with one single customer. That’s that S curve that we’re talking about. It’s where you start going from. Okay, this is neat science project, million dollars in total revenue, maybe not worth $2 billion valuation, 2000 times sales out there, but you start seeing big contracts like this hit. It’s kind of a sign that people are moving to take action on things rather than just considering it.

 

Simon Erickson  12:00

But quantum computing is getting a lot more than just the hardware itself. It’s more than just the quantum computer. It’s actually the whole system. You’ve got to in addition to building a quantum computer, you’ve got to have the software to figure out, how do you define a problem? How do you use this thing, just like the cloud? You know, it’s great. You’ve got all the processors and videos. Got them available for you with Amazon. What’s the interface you’re using to put your problems in there and get them solved. Cyber security, I mean, this is a huge thing for quantum computer. You have a super fast computer, how you gonna protect it? And the intellectual property you have control with this. And so I think this is an interesting company. They are not public, yet. Quantinuum is still a private company that is majority held by Honeywell, but they said that they’re probably going to try to bring the company public by 2026, and 2027 within a year or two. I think this is one that’s probably worth taking a closer look at. They’re getting some some momentum here with DARPA. They’re doing some really neat things. They’re trying to solve the whole system, rather than just the hardware piece.

 

Simon Erickson  12:55

So that’s, that’s Quantum. That’s a really neat one. That’s, it’s always perpetually, five or 10 years out. Every time I would go to the MIT conferences and I’d say, okay, when is quantum gonna hit guys? They’d always say, yeah, it’s five years conveniently, three years later, it’s still five years out. You go two more years, and they said, 10 more years out. You know, it’s one of those things that’s an interesting science experiment. You’re starting to see. What you start seeing companies are making these $40, $50 million contracts. They’ve got some money to work with now, right? It’s not just a philosophical thing. You build the teams, you can actually start putting contracts into place and doing some neat things with them.

 

Simon Erickson  13:26

Artificial intelligence agents is next. I think this is really cool, too. This is a lot of companies that are trying to use AI to reduce your operating costs. Things that used to be done by people are now being done by robotic process automation, whether that might be a customer service chat box, if anyone’s used that in the past, using marketing intelligence, how can we analyze where we’re, where we’re spending our marketing dollars, and use that most efficiently operate operational intelligence? Palantir, I mean, it’s made investors a ton of money from something they built back for the Department of Defense in 2000 or 40,005 and the robotic process automation, having to use AI to do step by step by step, which used to be just a checklist that human beings would be doing. And then the other part of it is, you know, not just the saving cost side, but can you actually use AI to add value to what it is you’re already selling? Can you actually make it more valuable so you can charge more money for you get higher pricing from something like this? And I think that’s the focus I want to I want to focus on the I think the first is going to be pretty standardized. I think that AI is going to be used for a lot of organizations that start understanding this. But there’s only really, in my opinion, a handful of companies that are really doing a good job with AI to make what they’re offering more valuable, and there’s even a smaller subset of publicly traded companies that are doing this really well.

 

Simon Erickson  14:35

The first one, I really like that I think has done this fantastic in the last couple years is The Trade Desk. If you saw my panel last night where we talked about, okay, this is one of my favorite of my favorite companies to invest in, right? It was actually my number one ranked Best Buy with 7investing last month. And so what the trade desk does, programmatic platform on the demand side, to place advertisements into digital channels. Man, that’s a that’s a mouthful, but basically, if you’re an ad agency, you’ll put some ads out there. Um, where do you put them? How do you get them in front of the right person if you want to advertise for the money show master symposium, how can we find the right people that might want to attend this show on the internet, on a podcast, on a streaming television station, wherever it might be. And so the trade desk has for years had the greatest volumes of impressions of digital ads. Every single time you put in an impression anywhere on the internet, you learn from it, and they’re now putting a trillion impressions out there per day, 13 million per second, 13 million more, 13 million every time you analyze that you’re getting smarter about putting the right ad in front of the right person at the right time. And so this amount of data that is now using AI to analyze it’s just extremely valuable for those marketers to optimize their campaign objectives. You’ve got more than 300 different variables. You can categorize in more than 200 different ways, whether that’s conversion rates, whether that’s just kind of the reach that you want to have for an audience, whatever your objective might be, let the trade desk do all of the heavy lifting and provide all of the information for you, and they’ve always stuck by. He or she who has the most data is going to win. You’re going to place the best ad, they’re going to get the best performance objective.

 

Simon Erickson  16:09

And so we’re looking at a company here that not shown on the slide, but in fourth quarter, missed revenue expectations by 2% if something around seven $70 million were kind of expand, I think it was 790 because a 2% 90. There’s a 2% miss on what Wall Street was missing. It’s the first time they’ve missed in 11 years. It hit every single quarterly forecast on revenue and earnings per share for the last 11 years missed. It was the first time in the fourth quarter, and that 2% Miss has now got the stock so like selling off more than 63% since then, outside February. Now, okay, maybe we can make a case it was pretty frothy before. Maybe we can make a case that, you know, while she was a little bit too complacent with with this stock always hitting and it was always a guaranteed thing, it’s also gonna be a tough year for advertising 2025 probably there’s a lot of uncertainty in the world right now. Maybe the volumes of ad spend is coming down. Maybe the pricing of ad spend is going to come down. The trade disk is taking about 20% of any ad that’s that’s placed out there, so it’s a variable revenue model, and they’re probably going to have a little bit of tough here, but 63% on a 2% mess miss. And then a conservative guide is it’s probably sandbagged, as you don’t want to miss for two quarters in a row right now, it seems like a really good time to buy the innovator the industry.

 

Simon Erickson  17:23

And again, this is a company doing $2.4 billion in revenue, growing at 25% they’ve got $12 billion of gross ad spend. That’s a total amount of advertising taking place on this self service platform. And they’re taking, again, about 20% of every dollar spent for themselves as revenue. And it’s a 930, $5 billion total addressable markets, a lot of a trillion dollars spent globally on advertising. And we’re getting more and more efficient about it. And the statistic in true Steve Jobs format show the biggest, most important number in the largest spots, 95% customer retention in every single quarter since this IPO back in 2016 I think this is a fantastic business when you think about the subscription model that they have when you think about the growth that they have ahead of them, and how they’re using AI to make their advantages even stronger, coupled with one of the smartest people in the room at the helm, I think The Trade Desk is a phenomenal investment opportunity.

 

Simon Erickson  18:14

If you look at the next big fan of you and the other company that’s really using AI very intelligently right now is Duolingo. For anyone who’s used this, it’s a fun little app. It’s a mobile app that helps you learn different languages, right? More than 40 languages are available, not even just the obvious ones, like French and Spanish and American or English. It’s Swahili is out there now Valkyrian from Lord of the Rings. You can actually learn that here. Klingon, for anyone who likes Star Trek stories, these are actually available on the platform. But you know, this is a global phenomenon. Language is something that can go, can transcend any borders.

 

Simon Erickson  18:43

Anybody can learn any language out there a massive market to grow into, and they’re growing at kind of an accelerated rate, right? Plus 43% year over year on the number of paying subscribers, you’d have an ad supported tier that’s free if you want to, if you want to have all the ads, get some extra features. You pay a little bit of money. It’s about $84 a year for it. And this is interesting, 8.8% of the monthly active users are now paying subscribers. Now, if we go back just a couple of years, you know, we go back about seven years of time, I was less than 1% of the people that were using this are actually paying and then a couple of years later, right after COVID, is up to 4% we thought we were pretty good at 4% of the people using this for percent of the people using this for pay. Now we’re approaching 9% you can see it’s working that people want to give Duolingo money because they see it’s a really good value out there. And then kind of the bigger picture too, not not just an app that’s kind of fun. They had a cute little green owl for a while. But this is also being used into the education system, not just with American institutions and academic research groups, but as an English test to test for English proficiency, right? It’s not being used for like 5000 institutions across the entire world to test for language proficiency. They had 11, excuse me, 17,000 of those tests in 2019, and more than 700,000 just four. Years later. That’s that that’s that S curve, that’s that hockey stick that you see where it’s really, really catching on quickly out there, and then they’re expanding other things that are outside of language, like math is something that could be transcending all borders in any country out there. Duolingo Max, that’s something we actually have a conversation with AI if you want to try to learn a language, but you’re maybe not so comfortable talking it because you’re not so good at it yet. You guys should talk to an AI person, a different language, and they’ll tell you, Hey, you didn’t say this exactly correct. A little bit less intimidating than the Education Department. There’s Louis fan. He’s from Guatemala. I chat with him a couple of years ago, such a brilliant entrepreneur. I was so excited right out of the gate when the IPO because it’s a really cool company, and now they’ve got 40 and a half million daily active users on Duolingo, which is growing at 50% year over year and has quadrupled basically in just a couple of years here. So this is another one. I think it’s hitting the hockey stick. I think it’s really cool.

 

Simon Erickson  20:49

We got a question in the back, yes?

 

Unknown Speaker 1  20:50

Just curious, are you familiar with Jump speak? They’re similar.

 

Simon Erickson  20:56

We see a lot of competition in this space, right? I mean, Rosetta Stone, if you remember that from here. Remember that from years ago, it’s kind of like when you have the model and use AI, something you need that they do is it kind of adjusts the lesson plans based on how you’re learning. You learn the conjugations of the verbs better than the nouns. Or maybe we can put the easier things up front and then progressive so the delivery model is just as important. I think, yeah, that was my question too. Was like, how they purchased any other language apps? They don’t like to do that. Like to grow it from the from the ground up. He’s a computer scientist by training. He’s kind of the godfather of crowdsourcing. You remember the captcha, the reCAPTCHA, things you know, click on the things that are a street lamp. When you get massive amounts of data that could validate and verify things, the same thing with language, right? If they’ve got 10 million people that are trying to learn Spanish right now, what’s the most effective way to teach it without curing how are we learning the Lord of the Rings language most effectively things like that. You can keep testing back and forth and adjust in real time.

 

Unknown Speaker 2  21:54

Yeah, they do one couple of things really well. In my opinion, one is they have this daily streak that almost makes you want to go back because you don’t want to lose your daily streak. And the average number of people with more than 365 days of that streak has gone from 30% to 60% in the last two years. And the way they keep sending you those reminders, if you’re not there, they use AI to send you messages where they know that you will that those messages will make you actually open the app, and they use enormous AI.

 

Simon Erickson  22:28

The daily streak means more advertising viewing, more revenue coming in, more data to learn from all supports, everything of the competitive advantage. So Duolingo, really cool company.

 

Simon Erickson  22:42

Let’s move on. Let’s talk about the space economy next. This is another one I’m really excited about right now, the final frontier, right? This is something that Elon is obsessed with. A lot of other really smart tech entrepreneurs are really interested in right now, right? Exactly, probably learning from Duolingo and then going out of space previously, just affordable for governments, right? These missions were super expensive, so commercial enterprises couldn’t do this. And then today, the thing that’s interesting, speaking about that S curve, is there’s about 12,000 active satellites in orbit as of last month. You know, not, maybe not as many as you might think that there were, but you know, that’s 7000 even just a couple of years ago.

 

Simon Erickson  23:21

And look at this, the FCC is now reviewing 40,000 applications per spectrum, if you want to put a satellite in there, just like yourself, when you got your sliver of spectrum, they used you not interfering with others. There’s four times as many applications outstanding right now as there are total objects from satellite, objects from all countries in outer space. That is, that is a that’s 4x that’s going to be that S curve, you know, you can kind of just see there’s a huge demand for things like this. And what do we want to go in out of space for? You know? What? We even want to put a satellite out there for some of the most common applications are things like Starlink, you know, we want to have space based broadband, high speed internet in all sections of the world. That’s one of the obvious use cases. Imaging. You can now look at anything in the world almost in real time, so you can see patterns on how they’re developing over time.

 

Simon Erickson  24:11

Military. We know that in the Russia invasion of Ukraine, there was space based satellites, and we’re looking at enemy movements and things like this. A lot of defense applications, and then even new satellite applications are coming online. It seems like every year for entrepreneurs to take advantage of. And so I think that as investors, you know this is when you want to look for the top line growth right now. Look for the new bookings, look for these big contract wins, and then look for the companies that want to do consolidation. There’s a lot of money raised by space companies in 2021 remember this, this SPAC craze, or call it the SPAC-e craze, like, just add an E, because that’s where all the money was going. Seemed like everybody raised a ton of money, and then they couldn’t make it valuable enough, or the rockets failed, they couldn’t get out into outer space, and all of a sudden there’s this void where everybody had a lot of money, then nobody had any money. And now we’re in the the recovery period from it, and so it’s going. Be interesting to see who wins the end to end integrated space company race right now, I’ve got two in the space economy that I want to chat about.

 

Simon Erickson  25:09

First is Planet Labs. This is a pretty cool one that’s got small satellites in low Earth orbit that are doing imaging, right so it’s every 90 minutes basically is going around the Earth. They’ve got small satellite got 200 of them out there that are basically just taking images of things and what can we learn about the planet or corporations or countries that we weren’t able to see before? And now, all of a sudden, we are they’re adding 30 or 40 new of these small sets each and every year. And so, like Brazil has hired them right now to use to do this for rainforest before just reforestation. They want to see where there’s changes that are taking risk plumes. You don’t have to look at things in video or images. You actually see ultraviolet or different kinds of things that detect emissions that you are not aware of from a safety perspective of your industrial customer. And it’s kind of neat again, you know you see just last, last fall, they signed a seven year contract with an Asia Pacific customer worth $230 million. It’s a step change, versus $242 million in total revenue for the rest of the year, right? So that’s that’s spread over seven years. Doesn’t happen all at once. We can kind of see there’s something to this. This isn’t just an idea that’s getting played around with out there. Companies are spending a lot of money because they want to go down to space for imaging.

 

Simon Erickson  26:23

And then one of my favorite is Rocket Lab. This is one that seven investing kind of put us on the map in a lot of ways, because I was out there banging my fists on the table saying, this is a screaming buy at four and a half dollars a share. It’s worth $23 a share. And the market recovered from that and got us some really nice, good press out there. But if this is a small lift satellite vendor, if you want to put a satellite into space, that’s the size of the vending machine, paid over 300 kilograms right out of a huge satellite, but you couldn’t get out of space before, right? And NASA is not going to watch it for you. Maybe Elon will let you ride share, if he’s happening to be going exactly in the orbital plane you want to. But I wouldn’t count on that happening for a year, a year and a half, and this is so this is kind of democratizing outer space now, right for $70 million now, anybody can go, anybody in this room to go on rocket lab’s website and book to put a satellite in outer space, you gotta make the SEC to approve the first you can actually go out there and just book it yourselves. It’s the democratization of satellite launches that are very personalized, customizable for smaller businesses and even the commercial sector. And so they’re doing about 20 launches a year from their Electron rocket. That’s a smaller lift one, but they’re building a bigger rock. This is kind of the biggest thing is like, where is, where is the company going to be profitable, right? You’re not making a lot of money if you’re only sell the small customers, and you only charge them $7 million in launch, you got to go out for the bigger fish, and people that want to put entire constellations up there for a telecom or for imaging, or for a government or something like that.

 

Simon Erickson  27:52

And so they’re building the Neutron this is going to be the step change for them, which is going to be medium lift, 10,000 kilograms, instead of 300 kilograms. This could bring a whole lot of satellites and place them at exactly the same time. Instead of doing 20 a year, they wanted two or three a year to start out with, going to be $50 million per launch. So that’s the jump. That’s the that’s where the company starts getting profitable. It’s going to get to the pad, they say, by the end of this year, if not early 2026, and I think the opportunity for this one is because a lot of institutions. This is a very, very high risk stock. A lot of people are saying, Hey, I’m not going to get in until big boy gets onto the pad and it shows a successful first launch. Then maybe I’ll jump in. So there’s a lot of money that’s interested in the space economy. This is the second largest commercial provider of launch behind SpaceX, still a very small market capitalization compared to what Elon is doing with SpaceX, but it’s kind of carved out just in a true disruptive fashion. Go out for the smaller, underserved part of the market. First work your way up the market. Build credibility. Don’t have any crashes. You work your way up, and all of a sudden you’ve got now you’re one of five candidates for the for the Department of Defense, NSSL program, which is worth five and a half billion dollars, are down to the top five for inter rocket labs. One of them, they’re kind of really punching above their weight craft class on this one.

 

Simon Erickson  29:12

And then, in addition to launching the satellites, they’re also kind of maintaining the operator. They’re building them. They’ve got a Space Systems Group that we’ll actually design. If you know what you want to do, we don’t know how to build the satellite. You know how to the communications. You don’t know how to do the navigation, the power, all the other things you sound like that. Rocket Lab can now do that too, and they can also handle the operations after they run space too.

 

Simon Erickson  29:35

So there’s the three. I kind of wanted to give plenty of time for questions too, but I really think these are three of the sectors that are not on a lot of radars of institutional funds, and as an individual investor, you have the opportunity to kind of take a swing for the fences in quantum computing and in the early stages of AI, and even in the space economy.

 

Simon Erickson  29:56

It’s fascinating to me. I think the technical interest of this is just. Greatest of financial interest. I really appreciate your time. You know, if you want to check out our website, 7investing, since you came to this presentation, there’s the last 7 official recommendations of our website. We play all over the map. It’s not just growth stocks or emerging technologies, but even popular companies that are much longer so thank you. Let’s open up and ask some questions.

 

Unknown Speaker 3  30:23

I’m curious about the opportunity for a small quantum computing company like IO and Q, or any new others, to compete with a big firm like IBM, who I understand already has some sort of quantum compute But IBM has got all sorts of resources that they don’t have. So how does that competition work in favor of a small company?

 

Simon Erickson  30:52

It’s so early right now that there’s different approaches to how you want to do quantum right? If you’re a company like an IBM or Google, you’re kind of doing the shotgun approach. You’re looking at a whole bunch of stuff, and you’ve got small teams, and you’re going to you’re going to give capital what seems to be working best on the groups that you have, versus IQ, which is saying, Hey, we’re going all in on this approach. If it works, we’ve had a real step ahead of the bigger ones that are much more spread out and diversified, competing internally for capital. If it doesn’t, you’ve got a lot more downside potential too, because it doesn’t work out, you’ve got a much better, deeper pocketed competitor out there, like that. I think that it’s a question of, you know, do you want to be more more specialized and just go all in on one kind of approach, or do you want to have something that’s brought and of course, Microsoft, Google, huge companies, is a very small fraction of their overall buy. I call.

 

Unknown Speaker 4  31:45

I guess the founder of the video, he said, I guess he was kind of pessimistic, so I wasn’t sure what that may be based on what at that particular time, or what is this something maybe to be aware of. Yeah,

 

Simon Erickson  32:00

great question. So the question so the question was invidious CEO, Jason long just had the GTC conference, and I think that the media headliner was like, he says, it’s still 10 to 15 years away, at least, right? And of course, Jenson has a little bit of a bias on this. He’s making the GPUs he didn’t want to get replaced by one chips. But then he kind of came back to and he kind of said, Hey, let me offer the olive branch. Let me have a peace treaty with all these quantum companies. We’re gonna have a forum, we have a panel, we have a quantum day at the conference, where I’m gonna invite all these guys to tell me why I walk. So it’s kind of a little bit of a back and forth. I mean, it’s not going anywhere. There’s no way you’re replacing GPUs with quantum for most applications. But there’s also kind of that super high end of the market the cheapest will never be. And I think that quantum to me, is as much of a consulting project as is a manufacturing challenge. Just like, you know, if you have a really big drug radio with really deep pockets, but they pay a couple billion dollars for a quantum computing project, it would take them bring a new drug to market faster it probably would, you know, or a handful of companies that would be able to handle that. So that’s the market I think quantum is going after. It’s not necessarily going to compete

 

Speaker 3  33:10

exactly rocket I’m thinking SpaceX when they they’ve had several crashes, but they expected and it’s built into their learning curve. What about rocket them? Are they able to throw that one crash, just crash the stock?

 

Simon Erickson  33:30

So it did happen. They did have an anomaly that they looked into last year, which was something, it was a electrical jump in a vacuum, or something that was that happened before the rockets. You never know exactly what’s going to happen. It’s the first time they had any kind of rock explode, and they did a root cause analysis of exactly what happened. They said, Hey, this was not planned. We’re going to be transparent about it. We’re going to go back and we’re going to make sure that we do a full evaluation of what happened. And it’s been about a month on it before they came back out. And then they said, Hey, here’s exactly what we had. We’re going to put this into our protocol going for this was look like where we’re finding the customer, they’re running for this particular actually launches. Have they had what one has exploded. They had a couple of failed launches. The film launch also be successful. That’s where outcome respected, right? This is such a very tough to do everything’s gonna be a couple.

 

Unknown Speaker 5  34:40

I’m kind of watching this privately held company called Firefly aerospace. They’re in the space exploration business, and they’re basically Department of Defense and government kind of serving. And I’m just curious if you have any thoughts on them, they’re pre IPO, and I guess you can get in if you’re accredited, and through some channels. Any thoughts on those guys?

 

Simon Erickson  34:59

Can you tell me a bit about more? What they’re doing, are they? Are they building the satellites? Are they? They’re building.

 

Unknown Speaker 5  35:02

rockets and essentially government halos that don’t want to go on SpaceX because they don’t want to share the same use a lot of due to security concerns. And so they’re sort of a dedicated, currently medium sized rocket that they build, actually, not far from here, near Austin. They launched at the usual science band, yeah, anyway, just wasn’t sure if you knew much about it. But is that a good, kind of early stage, and they’ve had a couple successful launches.

 

Simon Erickson  35:31

I’m not as familiar with that one. I didn’t know there was a documentary called The Space kings, or whatever showed, kind of the astral labs, and it showed the Rocket Lab. And it’s kind of show, you know, everyone is kind of competing with that demand that’s there, right? If you want to, if you want to send 40,000 satellites for space, SpaceX is not going to do all those. They probably just want to send their own anyway. You’ve got a couple others. You got Blue Origin, right? Bezos company that wants to do you got a whole lot like the company, like you just mentioned, Asheville labs, smaller lot providers, but it’s also really hard, like, a lot of, lot of capital expenses, lot operating expenses to build a rocket. One of the reasons that reusable rockets are so interesting right now is because if you actually relight it again, you reusing components, you save on a lot of your costs. I kind of think companies like that in general are going to get acquired because they’ve got something that they’re doing really, really well. They want to fold them into a larger like end to end company, unless they’re just really, really good at doing it all themselves.

 

Unknown Speaker 5  36:21

Acquired by a Lockheed, and I think that would be the hope for an investor. It will make sense. Yeah, absolutely. Thank you.