A New Trend in AI is Emerging: Efficiency

Summary

Motley Fool Money
Episode: "A New Trend in AI is Emerging: Efficiency"
Date: March 26, 2026
Host: Tyler Crowe
Contributors: Matt Frankel, John Quast

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Episode Overview

This episode focuses on two core themes:

1. The impact of recent litigation against big tech—specifically Meta and Alphabet—over social media's role in mental health, and how it might (or might not) signal a "tobacco moment" for these companies.
2. A new emerging trend in artificial intelligence: efficiency. The team explores recent developments from ARM and Google that could change the resource and energy demands of AI—and what that means for investors.

The show closes with a mailbag segment tackling the perennial question: Is it better to dollar-cost average with automatic investments, or should you keep cash for "buying the dip"?

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Key Discussion Points & Insights

1. Big Tech Litigation & the “Tobacco Moment”

(Starts 00:05)

• Headline News: Recent court verdicts found Meta Platforms (Facebook, Instagram) and Alphabet (YouTube) liable in cases linking social media use to mental health struggles, with punitive damages awarded. Meta lost a separate case in New Mexico involving misleading safety claims.

  • "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." — Tyler Crowe (00:15)

• Personal Impact:

  • Neither Matt Frankel nor John Quast are Meta shareholders; John’s household holds Alphabet shares.
  • Both say these verdicts haven't changed their investment thesis as of yet but acknowledge the landscape is shifting.

• Mental Health Context:

  • Social media's link to mental health is no longer controversial.
    • “Social media apps are engineered to maximize user engagement. I don't think that's a controversial take...it is how they generate revenue.” — Matt Frankel (01:53)
  • Matt recommends The Anxious Generation by Jonathan Haidt for deeper exploration.
  • John, speaking as a parent: "People are becoming a lot more cognizant of the dangers of social media right now than they were a few years ago... My kids, I can tell you, won't be on social media until they're at least in their late teens." (03:27)

• Is This the "Tobacco Moment"?

  • The comparison is discussed extensively—will legislative and legal risk erode the business, as with Big Tobacco?... Or, like tobacco, will tech stocks continue to do well despite total societal awareness of harm?
    • "Even after decades of litigation and declining tobacco use in the U.S., tobacco stocks have still been excellent investments over the years." — Tyler Crowe (04:12)
  • BP (post-Deepwater Horizon) and chemical companies (PFAS/"forever chemicals") cited as examples where legal risk truly did hurt long-term shareholder value.
  • $3M in damages is negligible for these firms, but the precedents could snowball.
    • “Facebook has over 3 billion users worldwide. 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?” — John Quast (06:00)
  • The consensus: Too early to tell if this is transformational or not. The cases will be appealed, and the regulatory response is uncertain.

2. AI’s New Inflection: Efficiency Innovations

(Begins 08:48)

• Intro: The conversation shifts from AI's explosive growth and hardware demand to urgent needs for efficiency—energy, memory, and cost.

• Key News Nuggets:

  • ARM’s Move: ARM, known for low-power chips, is pivoting to create its own CPUs under a fabless model. Meta is the first customer (but it isn’t exclusive).
    • “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.” — Matt Frankel (09:24)
  • Google’s Breakthrough: Google announced "TurboQuant," a new way to compress memory for large language models (LLMs), potentially reducing memory requirements by up to 6x.
    • “Google said their recent research showed that a new memory compression method...could potentially reduce the memory requirements of large language models...by a factor of six.” — John Quast (10:13)

• Investor Reaction:

  • Memory chipmakers (Micron, SanDisk) stocks fell; efficiency breakthroughs suggest AI infrastructure may not need as much hardware as previously modeled.
    • "Obviously the knee jerk reaction in the market was for memory companies. Oh, this is bad." — Tyler Crowe (10:46)
  • But efficiency is necessary: physical, power, and supply constraints are making the current trajectory impossible.
    • “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.” — Tyler Crowe (11:04)
  • Power Shortages Impending:
    • "30–50% of data centers in 2026 will be delayed because of power shortfalls...Morgan Stanley projects a 44 GW shortfall through 2028." — Matt Frankel (12:05)
    • Some California centers are built but can’t turn on—grid can't handle it.

• Historical Context & Takeaways:

  • This is the inevitable next step of tech’s evolution—like flat-screen TVs, productivity leaps always follow waves of efficiency improvements.
  • Google’s breakthrough is just for a specific part of memory (“key value cache”), not the entire architecture, so doom for chipmakers is likely exaggerated.
    • "It only optimizes a small part of the memory needs... It's a fraction of a fraction, not a fraction of a whole.” — Matt Frankel (12:50)
  • "Memory stocks like Micron are still up over 300% over the past year, even after the recent pullback." — John Quast (13:10)

• Ultimate Investor Take:

  • Efficiency is an investable theme—look for companies driving energy or compute breakthroughs.
  • "The only way to make all this possible...is we need some breakthroughs in efficiency, in terms of power generation. Something is going to have to happen along the way." — Tyler Crowe (13:47)

3. Mailbag: Automatic Investments vs. Buying the Dip

(Starts 15:21)

• Question:

  • Listener Jay Fung asks whether setting up automated investments is wise, or if "waiting for a dip" makes more sense in the current high market.

• Panelist Approaches:

  • John Quast: Does both: steady auto-investing (dollar-cost averaging, DCA) plus holding some cash to opportunistically buy dips.

    • "It really takes the emotion out of the equation and it mathematically forces you to buy more shares when stocks are cheaper." (16:52)

  • Matt Frankel: Leans towards automatic investment. Cites Fidelity study: investing $5,000 every January 1st from 1980-2023 would generate $5.1M, slightly outperforming monthly DCA ($4.8M). "The earlier you get the money in the market working for you, the better." (18:56)

    • “If you time things perfectly, you did about 10% better than if you had just invested everything on January 1st. And if you time things terribly, you did about 18% worse…Is that 10% upside worth the downside risk of trying to wait for that dip? I don't think so.” — Matt Frankel (20:33)

  • Hybrid Solution Advocated: Put 80-90% on schedule, save 10-20% for major dips so you’re not forced to sell good assets when opportunity knocks.

  • Ultimate Wisdom:

    • "The facts don't change. I'd rather be making my financial decisions based on the facts, because the facts don't change. My feelings aren't reliable." — Matt Frankel (18:24)
    • "Missing out by waiting for the dip is often worse than just being invested—even if the market feels expensive." — Summarized from John Quast (17:30)

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Notable Quotes & Memorable Moments

• On Social Media's Addictive Design:

  • "Social media apps are engineered to maximize user engagement. I don't think that's a controversial take...it is how they generate revenue." — Matt Frankel (01:53)

• On the Precedent of Litigation:

  • “Facebook has over 3 billion users worldwide. 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?” — John Quast (06:00)

• On AI Power Constraints:

  • "There's massive power requirements. And you've been yelling, 'Great Scott.' And I've been yelling, 'What the heck is a gigawatt?'" — Matt Frankel, joking about the sheer energy needs (11:38)

• On the Need for Efficiency:

  • "These aren't just like good for the AI infrastructure buildout. They're absolutely necessary to come anywhere close to meeting the goals and targets that we've been talking about." — Tyler Crowe (11:06)

• On Market Timing:

  • "If you time things perfectly, you did about 10% better than if you had just invested everything on January 1st. If you time things terribly, you did about 18% worse..." — Matt Frankel (20:33)

• Favorite Ending:

  • "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.'" — Tyler Crowe (21:57)

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Timestamps for Key Segments

• Big Tech Litigation & "Tobacco Moment": 00:05 – 07:43
• AI Efficiency Innovations: 08:48 – 14:23
• Mailbag: Automatic Investing vs. Buy the Dip: 15:21 – 21:57

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The Motley Fool's Takeaway

• Big Tech faces truly novel, potentially precedent-setting legal risks, but it’s too soon to say whether these are existential for their business models or just another cost of doing business, as with tobacco.
• In AI, the “arms race” is now as much about efficiency as scale. Expect pitches around energy, hardware, and algorithm breakthroughs to proliferate—and remember that most big productivity booms come from unseen efficiency gains, not just raw scale.
• For investors, the discipline of regular investing—while opportunistically using dips—has stood the test of time.

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Transcript

[Matt Frankel]

Foreign.

[Tyler Crowe]

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 full contributors Matt Frankel and John Quast. We 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 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, you know, 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 investing podcast. I think 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 just as you kind of like viewed these verdicts and things like that, has it really changed your view of the company?

[Matt Frankel]

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 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 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.

[John Quast]

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 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 like I said, this doesn't change my opinion. I already kind of had this opinion about these companies.

[Tyler Crowe]

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 laws. 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. 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 perfluoroalkylic substances like pfas or we also call them forever chemicals. You know, the liabilities on those you have, like Dow, Dupont3M, they've tried numerous 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. 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.

[John Quast]

There's a lot to unpack there. I'm not sure if social media is about to have its 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 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 ban 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. 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, but we'll have to wait and see here.

[Matt Frankel]

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.

[Tyler Crowe]

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 weeks.

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[Tyler Crowe]

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 COVID 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 chipmaker ARM or ARM, where they were announcing new AI specific chip designs. So, John, why don't you cover arm? Matt, you can cover the Google announcement after that.

[Matt Frankel]

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. 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 something to watch.

[John Quast]

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, then that might not be the case anymore.

[Tyler Crowe]

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 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.

[Matt Frankel]

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 data centers in 2026 will be delayed because of power shortfalls. According to a report from Siteline 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 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 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.

[John Quast]

Yeah, and I would add to that that, you know, 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 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.

[Tyler Crowe]

Yeah, one is certainly going to help. And again, I'm going to emphasize this as my takeaway. As we watch things like supply chain chains get strained and we talk about these massive numbers, the only way to make this possible, 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 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 after the break, we're going to hit the Mailbag.

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[Tyler Crowe]

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 [e-mail] we'd love to have mailbag segments whenever possible, so send in your questions. Just remember to keep them foolish. That email again is podcastsool.com podcastsool.com 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 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.

[John Quast]

Yeah. So thanks for that, Tyler, and thanks for the question. I do a combination of the two, just like 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 $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 1 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 of. So to directly answer the question, I will never try to talk somebody out of setting up 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 and p gained another 60% before it hit any significant correction at all. So keep things like that in mind.

[Matt Frankel]

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 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 four hundred and seventeen 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 earlier you get the money in the market working for you, the better.

[John Quast]

Yeah. In that study, I'll spare you the mathematics, but it essentially works out to your 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 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 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.

[Matt Frankel]

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. You 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 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 picked the best day of the year for 40 some years. You picked the worst day of the year for 40 some years. So if you time things perfectly, you did about 10% better than if you had 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, 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, little bit of cash, but mostly invested.

[Tyler Crowe]

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 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 and provided for informational purposes only. To see our full advertising disclosure, please check out our show notes. Thanks for producer Bart Shannon for pulling spot duty this week and the rest of the Motley fool team for Matt, John and myself. Thanks for watching, listening and we'll chat again soon.