In this podcast, Motley Fool analyst Asit Sharma and host Dylan Lewis discuss:
- Where AI developments are showing up in Microsoft‘s financials.
- The concerns over Alphabet‘s ad segment, even as it posts a return to growth.
- How the market is grading big tech companies this earnings season.
Chris Camillo, co-host of Dumb Money Live on YouTube, chats with Motley Fool analyst Sanmeet Deo about how he does on-the-ground research and the bull case for Tesla‘s humanoid robots.
To catch full episodes of all The Motley Fool’s free podcasts, check out our podcast center. To get started investing, check out our quick-start guide to investing in stocks. A full transcript follows the video.
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This video was recorded on January 31, 2024.
Dylan Lewis: Microsoft and Apple show us how the market is grading big tech. Motley Fool Money starts now. I’m Dylan Lewis and I’m joined over the airwaves by Motley Fool Analyst Asit Sharma. Asit, thanks for joining me.
Asit Sharma: Dylan. Thank you as always for having me.
Dylan Lewis: We’ve got a trick or two for improving your investing research and new earnings from Alphabet and Microsoft. That’s where we’re going to start today Asit. We have updates from the newly crowned largest company in the world. Asit, Microsoft reported what looked like an awfully strong quarter. Not a very large market reaction, but strong results from the new king of the mountain top.
Asit Sharma: Well, Dylan, these were cloudy results, to be honest. By cloudy, of course, I mean the cloud was a big part of this picture. As your growth was strong, double digits again. Microsoft’s cloud business is taking share from competitors. When you put all the different cloud parts together, that’s more than half of Microsoft’s revenue this quarter. It helped the company move its top line up 18% year over year. The company is generating quite nice profits off of that. Operating income increased 33% to a cool 27 billion. So what I’m getting out of this is a company that invested early in generative AI and also has kept up its investments in servers in GPU’s in its cloud business, and is executing now and looking like, a much younger company than a business that just threw off $62 billion in revenue over the last three months.
Dylan Lewis: So I mentioned the relatively muted response to the results. I think shares are about flat since the company reported. It is hard to imagine a $3 trillion company growing revenue at 17%. Its leading segment growing 30%. Do you feel like really, these were results that Microsoft had to post in order to back up the valuation that it had grown to recently?
Asit Sharma: I think so Dylan, part of the momentum behind Microsoft has to do with its really huge capital expenditure. It’s got a really big balance sheet and of course, throws off billions in cash flow every quarter. So investors want a payoff from those investments. And the promise has been that our investments in Open AI, our purchases of AMD and NVIDIA, GPUs, and our development of our own silicon as CEO Satya Nadella pointed out. All that is going to equate to us being able to provide businesses with the AI layers that they want and need. It also sort of reassures investors that the demand is out there. It’s not a case of if we build it, they come. It’s a case of we’re building it because they’re coming. Businesses really are trying to get a return on their investments in such things as generative AI, distributed artificial intelligence. Who’s getting the benefit of this? It’s not really the smaller companies that are offering some solutions that may work. It’s the big giants who can on board customers quickly. Whether for Microsoft, it’d be putting in AI applications into Office 365 or providing businesses links to their Cloud via Azure. You name it. They just seem to have a solution in every last part of their business.
Dylan Lewis: So for investors that are trying to follow the AI story with Microsoft Asit we’re not going to have an AI line item. It’s going to be something that shows up in several different segments, several different businesses. It sounds like the Cloud segment, particularly in the intelligent Cloud segment, is really where people need to zero in on for this business.
Asit Sharma: I think so. This is where we see Microsoft providing solutions that it’s developing in conjunction with open AI, which just to remind our listeners was the earliest of the generative AI applications to come to market. But it’s also where you’re starting to see Microsoft experiment with its own solutions. It has something called small language models, which is a growing part in foundational models. Small language models are just what they sound like, they’re smaller, they require less computational power. Satya Nadella talked about this on the call that their models are extremely effective. So this entices business into that intelligent Cloud segment. I think that’s where we can find the most traceable growth to your point. But this is funny, even in places like the gaming and laptop businesses. We’re already seeing the first instances of AI being deployed to machines. This will be something I think we’ll hear more about in the coming quarters from both businesses like Microsoft and manufacturers who play in this ecosystem being able to put AI on the layer of the computing product. So really, it’s hard to identify a part of Microsoft business that isn’t focused on bringing AI to the customer.
Dylan Lewis: AI was certainly a theme in the results we saw from Alphabet as well. We’re going to talk through how that impacted the business. But most eyes, at least on the initial market reaction to the results Asit seem to be on the company’s advertising business. I have to be honest, it feels like Alphabet’s ad business can’t win. It showed a year over year decline for the first time last year. This quarter they’re back to 11% growth markets still not happy.
Asit Sharma: It’s so funny because just pulling all of alphabets, advertising revenue together. You get a number that’s something like 66 billion. Which is what Microsoft did through all of its businesses in revenue. So here’s an advertising business that’s just humongous screw ads, you point out at an 11% rate. What’s the rub here? Well, this is where expectations come in. Investors are concerned that Alphabet is going to lose its edge in advertising as new ways to advertise come into market that are pushed by AI. Microsoft is one company that could take share from Alphabet and all over the landscape. The ability for search to evolve more rapidly and out of Google’s monopolistic hold, it’s real. So investors are looking for any clue that it’s not going to grow as fast as expected. I will note here that the advertising revenue numbers I think they missed by like a fraction Dylan, [laughs]
Dylan Lewis: I mean they warned that. Fair, fairly miss.
Asit Sharma: And the stock is down 6%. Here you have a company. Not quite as profitable as Microsoft, but a big tech player that just can’t seem to win, at least in the near term. Now what could change that? One of the things that took investors by surprise and maybe has contributed to some of the selling, is the fact that Alphabet signaled that it’s cap X. Its capital expenditure is going to ramp up. Noticeably, it was up this quarter. They didn’t give hard numbers, but they’re talking about a significantly bigger spend versus 2023. Sometimes putting out what you’re going to spend on your business is in the art of the telling. Microsoft was out early, way back at the end of 2022. Signaling that AI would be big and they were going to be pouring billions into it. Google has been more circumspect. Gemini model has lagged a little bit behind in development versus Open AI and Microsoft’s offerings and some other large language models. They really only now are projecting that, hey, with AI, yeah, we’re going to pour in those billions too. I think that caught investors a little bit by surprise. But why wouldn’t you want that again with a fortress balance sheet like Microsoft’s and this monster cash flow. As an investor, you want to hear them saying that they’re going to step up their cap X. So you go figure. But of course these are short term moves. The proof will be in the technology that Alphabet is developing and whether they will be able to accelerate that ad revenue a bit later this year and show that really AI is part of their model too. It’s not so much a threat as an enhancement to the advertising business.
Dylan Lewis: I think for a long time we’ve wondered what that next act looks like for Alphabet. It seemed like maybe it would be something that came out of their other bet segment for a while before the AI boom. There’s a lot of market attention there. Now I do want to surface a couple of things that get into some of the other operations that maybe people let go under the radar with this business. Sundar Pachai said the company’s annual subscription revenue reached 15 billion for the trailing 12 months. I was a little surprised by that Asit. I have to be honest, that has been one of those sleepy segments that’s continued to grow and grow and is starting to almost become relevant.
Asit Sharma: Dylan, it’s a business that as you pointed out, is up five times since 2019. This is another reason if you’re an Alphabet shareholder to feel pretty good today because that is recurring revenue and increasingly it’s a part of the business which has always grown quickly. We look at YouTube’s power to generate growth. I think it grew at a 15% rate this quarter year over year. That’s part of that subscription business as well. This is something that Alphabet has excelled at. If you have a company that’s able to hit these big numbers in recurring revenue, that itself becomes fuel for other big bets because you can predict your cash flow and then you can take the excess cash flow, invest it thoughtfully. But let’s now push back against Sundar Pachai’s point on this. The development of AI has lagged a bit at Google. Not in a technical sense, but really in a commercial sense and we so easily forget that for many years, Alphabet was ahead of the curve with investments in its deep mind segment and so many other novel things that they were researching and developing. The issue was just to remind members, or those who might not have heard about this Alphabet was very reluctant to bring their models and work on AI into a consumer facing front because they didn’t feel the technology was ready for prime time and open AI and Microsoft just got the jump and went ahead and put their product out to the world. So there’s a perception that Alphabet is on the back foot with this and this takes the sheen off that subscription service. The joy you might get out of that as a shareholder. Because at the end of the day, it’s still a smaller part of their business. It’s growing very quickly but in terms of being enough recurring revenue to let shareholders sleep easy at night and not worry about the competition from Microsoft and from Meta and from other big tech giants, not quite there yet.
Dylan Lewis: Let’s put the results that we’re seeing from Alphabet and Microsoft together a little bit. You’re starting to do that as we were talking about AI. Obviously, when investors are trying to grade the way that these companies are posting their results and the rubric that they’re looking at, AI is a large part of it, and they are zooming in on the cloud segments, in particular, for these businesses. What else are you seeing the market specifically look for in the results from these companies?
Asit Sharma: I think the market is paying attention to that CapEx when you evaluate Microsoft and Alphabet on on afford basis. Like looking out three years from today or five years from today. Part of that story is about the capacity in Megawatt generation from their data centers. This is a metric that some people study to figure out who’s going to be the major players in AI or providing AI cloud services into the future. If you don’t have the capacity, you can’t sell it and guess who is number 1 and number 2 on planet earth in terms of capacity and gigawatts for data it’s Alphabet and Microsoft [laughs]. Part of this story, when you look at these companies, investors want them to keep plowing into their ability to provide silicon, if that’s going to be the next thing. Dylan, if you and I are going to use generative AI applications via the cloud, someone has to be able to provide it at a decent cost, with speed, without latency and in a way that will make it fun for us to use and give us fruitful results, whether it’s a business application or you’re trying to learn a foreign language. Right now, there are a few companies that are actually better positioned than these two to capitalize on that. Just the question is like, how do you reach businesses? How do you reach consumers? Right now, Microsoft is doing a slightly better job of that. But let’s go back to your original point. Wow, that advertising revenue for Alphabet, they just have to protect it. They just have to speed up their AI game a little bit and show that Google search isn’t going away and they’re going to be fine.
Dylan Lewis: We’ll have a firmer sense of the big tech picture when we see results from Amazon and Meta later this week. Until then Asit. Thanks for joining me today.
Asit Sharma: Awesome, till then I really enjoyed it.
Dylan Lewis: Coming up is scanning social media, a part of your investment research. Chris Camillo is a co-host of Dumb Money Live on YouTube and was featured in the book Unknown Market Wizards, Motley Fool Senior Analyst Sanmeet Deo caught up with Camillo to talk about how he does on the ground research and the bull case for Tesla’s humanoid robots [laughs].
Sanmeet Deo: I love Peter Lynch’s book went up on Wall Street. That was one of my first books I read on investing. It was so intuitive to learn like investing with what you know, what you see around you. What are the trends? What are the things that the shoes people are wearing or the drinks people are drinking, or the shops that people are going to, all that stuff. That’s a major investment philosophy here at the Molly Fool. How some of our co founders, David Gardner started investing themselves. He has a quote that says, live a more interesting life and then you’ll be a better investor. That’s a pretty cool way of looking at investing too, and you exemplify that as well. So one of the terms you use quite often is social arbitrage investing, just as you said it already, but so what exactly is that and what are some of the social media platforms that you’re using to follow trends and how can investors get started with it themselves?
Chris Camillo: First of all, to get back to your point on Peter Lynch, I think, he’s so out of sight, out of mind for most of the new generation, they don’t even know who he is or that he was one of the greatest traders who ever lived. But I think the problem is most people just don’t believe that what I do works like that. You could actually pull it off. Most people believe that Wall Street has this huge edge, that the market is rigged, that you can’t possibly beat them by doing this. It just seem too easy and too stupid, and most people just do not believe it. Seven years ago I got on YouTube we have this channel called Dumb Money Live, and Dumb Money dot TV is how you find us there. But we’re on once a week just literally talking about what we do for fun. Just to try to inspire other people to be like, hey, you can literally do this. We literally just talk about what we’re seeing in real life, in our community. We just have a conversation and we try to put the pieces together to connect the dots, the do this. I really do feel that regular people have a really strong edge over Institutional Wall Street. We could talk about that later because I actually got to see behind the curtain of Institutional Wall Street at the data company, I started to mind social data.
But social arb is a really important, sometimes I just used the term observational investing because it sounds easier to understand. But almost everything I do now starts on social media. Because all of the world’s conversations or most of them have turned digital. Which is really powerful because you could basically observe the world unfolding in real time now and it’s wild, we’re talking, billions of conversations are happening every day where people are discussing what they are doing where they’re going, what they’re buying, what’s exciting them, what they like, what they don’t like, like, that’s all out there for us to read and interpret and trade off of. There really is nothing closer to a real time data set than what I call contextualized conversational data that sits on social media. So in the past, I used to do a lot of this on Facebook, and then I spent many, many years doing a lot of this on Twitter. Back in the early 2010s, when Twitter was a place where people expressed themselves in that way, I actually started this data intelligence company called Ticker Tags, which I ultimately sold years later to Jeffrey’s bank.
But at ticker tags, we basically had access to the fire hose. In that case, it was really a deca hose, 10% of the fire hose of all tweets. We would basically read the tweets in real time and we had millions of word combinations that represented all the world’s products and brands and anything that would be meaningful to public company and we would measure the volume of conversation around each of those word groupings. Whenever our systems and our algorithms saw a word combination that was important to a company, it could be something as simple as how people speak about one of their products or brands when we saw it accelerating. Or if we saw a big jump year over year in conversation around a topic that was seasonal, then we would surface that for institutional investors, Institutional Wall Street. So we sold this data to hedge funds and to sell side banks. And I spent many years at ticker tags. Basically teaching and educating Wall Street on how to interpret contextualized datasets. It’s amazing to me and I love telling this story to retail investors, individual investors. Because I’m telling you I work with the biggest funds in the world. At the highest levels, I would literally hold their hand and they just refused to do the work.
They thought the dataset was too interpretable. Wall Street really likes data sets that are statistically repetitive and there’s a lot of correlation between, when this happens, this happens in the market, and they could have years of data to prove that they’re actually really risk adverse, and what contextualize data sets, I can show the same thing to 10 people and they’ll have 10 slightly different interpretations of what that means, and there’s actually a lot of leg work to understand that, wait, all these people are talking about the iPhone maybe, 30% more than last year in the 14 days leading up to the first iPhone launch of the year, the new iPhone launch, but are they speaking about it positively, negatively. There’s things that they like, there’s things they don’t like which are more important. You actually have to spend a little bit of time reading a lot of this conversation to extract knowledge from it, and that takes work, and it takes you putting yourself out on a limb and having insight that could be different from someone else’s insight, and Wall Street doesn’t love that.
Also, it’s so new, and scary to them that everyone’s like but Chris, why do you talk about this all the time? Aren’t you afraid other people are going to start doing what you do? I’ve been talking about this now for 14, 15 years, and I have more alpha today than I had 10, 12, 13 years ago. I mean, I think my portfolio was up north of 110% this last year, total portfolio, and so it’s wild that this exists, but people are like, it seems too simple, too easy. It is simple, but it’s also not because it takes a lot of time and mental effort and acuity to connect the dots and to extract knowledge from tens of thousands of conversations. I spend like three hours a night, sometimes four, just reading conversations on social media. By the way, to fully answer your question, I’ve migrated almost exclusively to TikTok now. Most of my insights come off of TikTok comments, if that makes sense. I feel that TikTok comments for the past few years have become the richest data set and it’s completely free and everybody has access to it. I obviously spend a lot of time on other data-sets like Google Trend data. I do purchase data, I purchase web traffic data, I purchase credit card transaction data. I purchase a lot of data as well, and it’s all really good. But the data set that I’m most well known for interpreting are those conversational data-sets that quite honestly anyone in the world has access to. If you’re just willing to spend the time to read a lot of conversation and comments. [laughs]
Sanmeet Deo: I do want to get to your recent Twitter thread on maybe one of the biggest trends you probably are seeing for the future is the Tesla humanoid robots. Tell us a little bit about that thesis.
Chris Camillo: Because I feel that this is one of the biggest opportunities of our lifetime as investors. I’m not a Tesla fan boy. I’ve always had a little bit of Tesla on and off. I have some Tesla right now, but I don’t have nearly as much Tesla as I plan on having this next year. I hope, and plan for Tesla to be a huge part of my portfolio the next few years, exclusively because of their optimist humanoid division, which is to me, 10X more exciting than anything else Tesla has going on, whether it be an automotive or even energy. I’m obsessed with this humanoid division at Tesla. I do know that it’s because of automotive, it’s because of the AI division, It’s because of all these other things that Tesla has done that has put them in the pole position to be the leader in humanoids starting in 2027. 2027 is what I’m predicting to be the ChatGPT moment for humanoids. I think Tesla will be in the pole position because of their manufacturing expertise, because of their access to capital markets, and quite honestly be internally whether they admit it or not, I think they’re going like a million miles now with their humanoid division. They’ve released some amazing videos. The Gen 2 optimist is mind blowingly cool considering how uncool it was just a year ago. The rate of improvement is probably one of the most impressive things in the optimist division of Tesla. Elon says will be billions of billions of humanoids, as many as humans, and I do agree with him at some point in the future, but all of my analysis revolves around Tesla having 1.5 million humanoids deployed to commercial and industrial companies by end of 2030, and they’re not selling them, you’re basically leasing them by the hour.
It’s not replacing any human jobs, so this is just basically serving a small percentage of the job shortage in industry right now that is desperate for factory line workers, for warehouse workers, workers to do dangerous jobs, jobs where you’re on your feet, walking five plus miles a day on a factory floor. Working at ports. I mean, the job shortage is stunning. We’re talking hundreds of millions of humans short in these manual labor jobs around the world over the next 10, 15 years, and humanoids are the solution. The amount of revenue that a company that’s able to serve just a small piece of the demand. Because I think we’re going to have a massive demand supply imbalance for many years will be Tesla. They won’t have to sell them, they’ll be able to generate, in my analysis, it’s a little under $100,000 a year per humanoid. Because remember, these humanoids are working around the clock. I had them working 16 hours a day. But you have to really read the Tweet thread to understand everything I’m talking about. But it’s the most interesting thing that’s happening right now that no one’s talking about. To be a social Arb investor, you have to see things at least a little bit earlier than everyone else, and this is my big thesis.
I plan on being a full humanoid expert the next few years. I plan on talking about this a lot. If you want to hear about humanoids, dumbmoney.tv. Come to our live, Dumb Money Live YouTube channel. I’m going to be talking about it. I’m going to be tweeting about it. I’m actually trying to make more humanoid investments outside of Tesla, because I feel like while Tesla will be the leader in the space, everyone is going to be a winner in the space. I think that over the next two or three years, what’s going to happen is a lot of the other automotive manufacturers, OEM’s, are going to get in on this game and going to acquire these private humanoid companies. There was a big announcement this past week that one of the big humanoid early stage companies called Figure AI, doing some really cool stuff at Figure, just did a big partnership with BMW. I wouldn’t put it past BMW if all things go as well as I think they will to try to acquire Figure at some point in the near future. One of my favorites is a company called Apptronik out of Austin. I’m invested in a Apptronik, and there’s a lot of really exciting stuff. I can’t talk about it, but that’s going on in Apptronik. I would have to imagine that in a lot of these companies, Agility Robotics, Sanctuary AI, 1X Tech, I think those are the guys out in Norway, all have really big opportunities in front of them. I do want to say right now the biggest misconception that people have when it comes to humanoids is how about the Boston Dynamics? How can anybody compute? It’s not a commercial humanoid. I don’t even think they’re trying to ever have it be one. It’s a research humanoid. It’s not designed to ever be commercially used, it’s not even a competitor. It’s literally not even a competitor.
Dylan Lewis: As always, people in the program may own stocks mentioned and Motley Fool may have formal recommendations for or against, so don’t buy or sell anything based solely on what you hear. I’m Dylan Lewis. Thanks for listening. We’ll be back tomorrow.