Motley Fool Hidden Gems Investing - A New Trend in AI is Emerging: Efficiency

Starting point is 00:00:00 Efficiency in AI could be just what the doctor ordered. This is Motley Fool Money. Welcome to Motley Fool Money. I'm Tyler Crowe and today I'm joined by longtime Fool contributors, Matt Frankel and John Quast. We've got a really interesting show today. we're going to talk about some stepwise gains in the world of AI, but not in the way we've been talking about it for quite some time. And we're going to hit a mailbag question because

Starting point is 00:00:39 we are already getting them even after announcing that we're going to start taking them at our email address. We'll get into that in a second. But first, probably the biggest Newsday story outside of global war conflicts and things like that was there was some pretty big legislative decisions that happened for big tech, and it wasn't exactly the way they wanted it to go. In a couple of pivotal cases, one of them, Meta Platforms and Alphabet, were found liable for a woman's mental health struggles related to social media addiction, and they had to pay punitive damages. Also, Meta lost a similar case in New Mexico related to misleading statements about safety on their sites. Now, admittedly, this one's kind of a hard one to discuss on an investing podcast. I think

Starting point is 00:01:20 there's a lot of emotions wrapped up in our use of social media and how that affects things. But there is going to be some investing takeaways here. But I wanted to get your guys' thoughts here. Are either of you shareholders in Meta? And as you kind of like viewed these verdicts and things like that, has it really changed your view of the company? So to your first question, Tyler, no, I'm not a Meta shareholder personally. That's not a indictment on the company. I've gone on record that Meta is one of my more favorite companies in the Magnificent Seven. But to your second question, does this change my view of the company? The answer is not yet, but it could potentially. Specifically with the issue of mental health, I think that all the statistics point to

Starting point is 00:02:01 an indisputable conclusion. We do have a mental health epidemic, unlike anything we've ever seen. And I believe two things can be true here. First, social media apps are engineered to maximize user engagement. I don't think that that's a controversial take. It is how they generate revenue. Of course, they want their users on there as much as possible so they can generate ad revenue. The second thing, I mean, I wouldn't blame social media apps entirely for mental health issues, but it does seem to be a contributing factor when it comes to this topic. I think if you're new to this discussion, the book I'd recommend is The Anxious Generation by Jonathan Haidt. It does a great job of laying out the rise of anxiety in Western culture, also potential

Starting point is 00:02:46 remedies, some suggestions by the author. I know this might sound off topic for an investing podcast, but I do believe it is pertinent. The jury verdict here is far from the final conclusion when it comes to Meta. Meta is going to appeal this case, it's going to go higher. But if social media is ultimately deemed harmful, like other harmful things, we could see some substantial reforms from legislators that could have an impact on these cash cows. So I'm not saying that it's the final word, but it is something material to keep an eye on. I'm not a meta shareholder, but we do own shares of Alphabet, which is YouTube's parent company in my household. My wife does in her account. It doesn't really change my opinion on either company. I've already had my kind of opinion formed. I'm a parent of young children. I think all three of us here are parents of young children. So I'm sure we have our own opinions of social media when it comes to how it impacts the mental health of our kids. I feel like people are becoming a lot more cognizant of the dangers of social media right

Starting point is 00:03:42 now than they were a few years ago, which is what the basis of this case was. It was people who use social media and were addicted to it a few years ago. But my kids, I can tell you, won't be on social media until they're at least in their late teens. And one of the reasons is that it's so difficult to say what's safe and what's not. So I guess this doesn't change my opinion. I already kind of had this opinion about these companies. This is a hard topic to discuss. And I want to try to bring like the investment thesis around to this, because one of the comparisons that I've seen with social media outlets and these cases that we saw was this, they're calling it like, for example, Bloomberg called it the tobacco moment, basically, where legislative action starts to chip away at the business because we start to realize the physical, mental harm that these can cause. And it leads to a lot of legislative stuff. But here's the weird part about it, is even after decades of litigation and fines and anti-smoking campaigns and declining tobacco use in the U.S., tobacco stocks have still been excellent investments over the years.

Starting point is 00:04:44 And I want to contrast that a little bit to other companies where punitive legislation have kind of crippled the company. And I think of examples like BP with the Deepwater Horizon spill. Companies that have been making perfluoroalkalite substances like PFAS, or we also call them forever chemicals, you know, the liabilities on those, you have like Dow, DuPont, 3M, they've tried enormous like corporate changes to try to mitigate the liabilities here. And of those, none of the, like over very long periods, none of these companies have really like fared nearly as well when, for example, compared to tobacco as like actual investments.

Starting point is 00:05:19 Litigation against, you know, company meta is obviously bad and payouts are not like ideal. But if social media is treated similar to tobacco, like in this tobacco moment, couldn't social media still have similar returns as investments in tobacco stocks? I mean, like you said, these are still cash cows. There's a lot to unpack there. I'm not sure if social media is about to have its, you know, tobacco moment. But I will say that the most interesting thing about this, it's not necessarily the fines that were just imposed. I mean, $3 million split between Meta

Starting point is 00:05:51 and Alphabet is nothing for these companies, but it's really the precedents they could set. So the verdict related to safety on social media, that could certainly have some legislative impacts. I mean, for example, there are countries that already banned social media for people under 16 years old. So something like that could happen here potentially. That wouldn't exactly be crippling to these companies. It would have a material impact, but it wouldn't be crippling. The mental health lawsuit, which is the one that was split between Meta and YouTube, is a little more interesting to me. So Facebook has over 3 billion users worldwide.

Starting point is 00:06:26 So would this pave the way for everyone whose life has been harmed by a social media addiction to potentially try to get millions of dollars from these companies? Virtually anyone, I know I could, can make the argument that their lives would have been better or more productive, at least, if it weren't for social media. how much more could I have written over the years if I wasn't on Facebook? Keep in mind that this was an initial decision, as John correctly pointed out, Meta's going to appeal as they should. The final ruling could be a little more consequential. I personally don't think we'll see a wave of successful litigation against these social media giants for mental health lawsuits,

Starting point is 00:07:02 but we'll have to wait and see here. Yeah. I mean, it's an interesting hypothesis to compare tobacco to social media. I would agree with Matt here. I think it's far too early to draw that parallel. This case is going to go up the chain and it remains unseen how things would be regulated if they become regulated at all. So, stand by. Yeah, this is certainly something that's been kind of on the back burner for a long time. We've been thinking about it, but now with these litigation actions, it really starts to bring this into the forefront and something we'll be following in the coming weeks, months, years, we'll see. After the break, we're going to talk about AI and one of the more interesting gains that we've seen in the past couple of weeks.

Starting point is 00:07:44 This isn't a single news story that we want to talk about here with about AI, but it's kind of a kernel from a couple of recent press releases that I want to think about as an essential topic when we think about AI and it's making it happen more efficiently. I'm going to let you guys kind of cover the topics a little bit more with the news stories. But one of them came out from Google talking about some of their ways of running AI models. And the other one came out from chip maker ARM, where they were announcing new AI-specific chip design. So, John, why don't you cover ARM, Matt, and you can cover the Google announcement after that. Okay, so, yeah, ARM. It's always been known for these lower-power CPU designs compared to Intel's x86 architecture. But in the past, it's licensed its technology to companies such as Apple.

Starting point is 00:08:30 The news that we are getting now is that ARM is actually going to make its own CPUs using a Fabless model, so just like NVIDIA or AMD, and Meta is going to be the first customer here for ARM of its custom silicon. I think it's a big deal because it is a pivot for ARM's business model. I would temper the news with a comment that Meta is a customer, but it's not an exclusive agreement. Meta is going to continue to buy products from multiple companies. It's probably more about diversification of the supply chain than anything, but it is

Starting point is 00:09:02 something to watch. Yeah, so on the Google side of things, they said that their recent research showed that a new memory compression method that they call TurboQuant could potentially reduce the memory requirements of large language models, you know, the AI models, by a factor of six. And understandably, shareholders of memory-focused chip makers like Micron and SanDisk were panicking about this. you know, memory efficiency, it's a big focus of AI development recently. And the demands are so high that these memory companies literally can't make chips fast enough. And if Google's right,

Starting point is 00:09:35 that might not be the case anymore. Yeah. And this is what I found kind of interesting when I was, I saw both of these stories come at the same time, because we have been talking about AI deployments and things like that. And obviously the knee jerk reaction in the market was for memory companies. oh this is bad and if arm were to take market share with lower you know power demand chips i could see some of the downstream ai infrastructure companies that have to do all this build out they would say oh yeah they're going to take hits as well and i want to get to how you guys are thinking about this as well but this was kind of like as i started reading the tea leaves between these like two announcements this was kind of my hot take is i think the efficiency gains that we're talking

Starting point is 00:10:16 about here with using less memory, using less power, these aren't just like good for the AI infrastructure build out. They're absolutely necessary to come anywhere close to meeting the goals and targets that we've been talking about. Yeah, Tyler, I feel like you've been playing Doc Brown on this podcast and I've been Marty McFly. Any single time we get an announcement for these data centers, there's massive power requirements and you've been yelling, great Scott. And I've been yelling, what the heck is a gigawatt? You've actually helped me see that they're basically saying that we need all this power and we can't generate that much power. We can't generate at the scale that the hyperscalers are talking about. And there's data to back this up. 30 to 50% of the

Starting point is 00:10:57 data centers in 2026 will be delayed because of power shortfalls, according to a report from Sightline Climate. Morgan Stanley projects a 44 gigawatt shortfall through 2028. There are already some data centers in california that have been built but not turned on because the grid needs some fortification and this leads to an undeniable conclusion that the current path is unsustainable we need something to change we either need a power generation breakthrough a compute breakthrough or an ai model breakthrough and i think that we're a long ways away from having a true compute or a power generation breakthrough the ai model breakthrough is the easiest path forward and that's what this thing with Google is potentially talking about. We've maybe come up with a more

Starting point is 00:11:40 efficient model. That said, we do need to tap the brakes just a little bit when it comes to the memory requirements. So some memory stocks are selling off because of this. The Google announcement only optimizes a small part of the memory needs, specifically the key value cache. It doesn't reduce the memory needs across the board. It reduces a fraction of a fraction, not a fraction of a whole. The memory imbalance will likely continue, in my opinion. Yeah, and I would add to that, that take this with a grain of salt and zoom out. Memory stocks like Micron are still up over 300% over the past year, even after the recent pullback. And if LLMs evolve like most analysts believe they will, one-sixth of the current memory usage will still be a lot of

Starting point is 00:12:23 memory chips that they need. And it will still keep these companies very busy for the foreseeable future. Every new technology gets more efficient over time, consuming less power, the hardware becomes smaller, et cetera. Think of like, you know, flat screen TVs. This is a natural evolution of AI technology and it's a good thing. Yeah. One is certainly going to help. And again, I'm going to emphasize this as my takeaway, as we watch things like supply chains get strained and we talk about these massive numbers, the only way to make this possible at like John was saying is we need some breakthroughs in terms of efficiency, in terms of power generation, something is going to happen along the way because the numbers that we're talking about are just so hard to wrap

Starting point is 00:13:03 our heads around in terms of the physical supply chain, it's going to be difficult to happen. So I'm very encouraged to see stuff like this because it is going to make it more viable in the shorter term and hopefully clear some of those backlogs that you were just talking about. And coming up for the break, we're going to hit the mailbag. Before we get to our first mailbag question, we want to make you part of the conversation as well. If you have a stock or investing in question for John, Matt, me, or anyone else on the show, you can now email us at podcasts at fool.com. We'd love to have mailbag segments whenever possible. So send in your questions. Just remember to keep them foolish. That email again is podcasts at fool.com, podcasts at fool.com.

Starting point is 00:13:43 And we're going to finish out today. And this is a mailbag question that comes from Jay Fung. I apologize if I mispronounced your name. But the question is, is setting up automatic investments always the best move versus wanting to buy the dip, which is very much in the parlance these days when we're talking about investing for individuals. His email goes on. I know the answer is probably a mix of both. Have automatic investments going and then save a portion to buy the dip. I haven't been able to get myself to pull the trigger yet on automatic investments since the markets have been so high. I'd love your insights. And am I unwise to hold off setting up automatic investments? Now, before we answer this question, we do have to stipulate because this is

Starting point is 00:14:24 a podcast. We can't give personalized advice and none of this should be taken as personalized advice. So Matt, John, as you give your answers, just remember, we're going to think of a hypothetical situation and what you would do personally in this situation. Yeah. So thanks for that, Tyler. And thanks for the question. I do a combination of the two, just like the email said, but I'll build it out a little bit. So I like to build stock positions and ETFs, if that's what you're asking about, automatically over time, as it really takes the emotion out of the equation and it mathematically forces you to buy more shares when stocks are cheaper. So think of it this way. Let's say that I want to invest $5,000 in a certain stock. I might commit to investing

Starting point is 00:15:01 $1,000 on the first day of the next five months instead of all at once. So the way that this works is if I buy $1,000 worth on April 1st, and then the stock falls 20% before May, I'm getting my next round of shares at a nice discount. I'm buying the dip. If it goes up, well, my initial shares will be sitting on a nice gain and I'll be happy in that situation too. So at the same time, I like to maintain a little bit of cash on the sidelines to be opportunistic. So in my example, if a stock that I'm gradually buying falls by 20% with no change in the fundamentals or my investing thesis, I've been known to take some of my extra cash and make my next purchase a little bit larger to take advantage. So to directly answer the question, I will never try to talk somebody out of setting up

Starting point is 00:15:44 automatic investments, regardless of whether I think the market is cheap, expensive, whatever. Simply accumulating cash to, quote, buy on a dip, it more often results in missing out on a big gain. So I clearly remember that many people thought the market was ridiculously expensive in 2015 after roughly tripling from the financial crisis lows just six years before and decided to pull some cash out, stay on the sidelines and, quote, wait for the next dip. But then the S&P gained another 60% before it hit any significant correction at all. So keep things like that in mind. Yeah. I want to build on this, Matt. You talked about taking emotions out of it. You know, people, we have feelings. We're emotional beings. We're not going to change that entirely. I think

Starting point is 00:16:25 that's okay. But personally, when it comes to my financial decisions, I don't want to be making that based on my feelings because my feelings aren't reliable. They do change. I'd rather be making my financial decisions based on the facts? Because the facts don't change. And so I want to bring a factual study into this conversation. So Fidelity analyzed some returns, a hypothetical 5,000 annual investment from 1980 to 2023. So basically $200,000 invested over 42, 43 years. If you invested all of that money on January 1st of each of those years, you wound up with 5.1 million. If you invested $417 a month, which is $5,000 a year but broken out monthly, at the start of each month, you had slightly less, $4.8 million. I think that this supports a belief that the

Starting point is 00:17:19 earlier you get the money in the market working for you, the better. Yeah, in that study, I'll spare you the mathematics, but it essentially works out that you're investing for an additional half of a year overall in the $5.1 million case. So that is still a form of averaging into positions like I'm talking about. So it's just wider intervals. You're not trying to buy the dip. I've read that study and the biggest difference was getting your money in sooner. Like I said, for the first year, you'd have $5,000 in the market right away versus, you know, an average of $2,500 in the market at any given point that year. So that makes a big difference over time. And second, I will say it's not always practical for listeners to invest in large lump sums once

Starting point is 00:17:57 a year. For many people putting $500 a month in the market is the earliest that they can invest. So still a very interesting point mathematically. So let's break this down a little bit more from what the study showed. So let's pretend that you were the best trader out there. Somehow you had the $5,000 all up front. As Matt pointed out, that's not always practical, but let's assume you did. You had $5,000 to invest for the year and you could invest it all in a single day. And you picked the very best day of that year, the day that the market was at its lowest

Starting point is 00:18:26 point for the entire year. Somehow you had a crystal ball. You predicted that. And let's just say that there's another person out there who is the worst possible trader possible. They picked the top of the market for a single day of that year and invested all their money on that one. Well, if you were the best, you wound up with 5.6 million. If you were the worst, you still had 4.2 million. So you pick the best day of the year for 40 some years, you pick the worst day of the year for 40 some years. So if you time things perfectly,

Starting point is 00:18:56 you did about 10% better than if you just invested everything on January 1st. And if you time things terribly, you did about 18% worse. So I'd ask myself two questions here. Am I the best? If not, is that 10% upside worth the downside risk of trying to wait for that dip? I don't think so. I think it's better to get invested. However, I think the hybrid approach that you're talking about, Matt, is still a really good idea. So maybe some people would decide, I'm going to invest 80% or 90% of my money on a schedule, and I'm going to set aside 10% to 20% in case the market drops, in case I want to be opportunistic. That way, you do get that money working for you sooner. You're not dramatically, statistically altering your long-term performance,

Starting point is 00:19:41 but you still do have that cash on hand to take advantage of things as things drop. You're not forced to say, oh, should I sell this one to buy that one? You have some cash already on the sidelines ready to go. So maybe it is the best approach, that hybrid, a little bit of cash, but mostly invested. I think the best part of this conversation is I get to use my favorite Charlie Munger quote, which is, I have nothing else to add. And that is actually all the time we have for the show today. Matt, John, thanks for sharing your thoughts. I thought this was a great conversation about when timing the market works and when it doesn't. I'm going to hit the disclosure and then we'll get out of here. As always, people on the program may have interests

Starting point is 00:20:19 in the stocks they talk about, and The Motley Fool may have formal recommendations for or against, so don't buy or sell stocks based solely on what you hear. All personal finance content follows Motley Fool editorial standards is not approved by advertisers. Advertisements are sponsored content

Starting point is 00:20:32 and provided for informational purposes only. To see our full advertising disclosure, please check out our show notes. Thanks for our producer Bart Shannon for pulling spot duty this week and the rest of The Motley Fool team. For Matt, John, and myself, thanks for listening,

Starting point is 00:20:44 and we'll chat again soon. Thank you.

Motley Fool Hidden Gems Investing - A New Trend in AI is Emerging: Efficiency

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