Motley Fool Hidden Gems Investing - Four Rules for Using AI

Episode Date: April 5, 2024

Instead of the age of artificial intelligence, investors might be better off thinking of this as the age of co-intelligence. We dig into how you can embrace AI and put it to use. (00:21) Jason Moser and Bill Mann discuss: - Why Disney and Nelson Peltz were both winners in the company’s board fight. - Alphabet’s rumored interest in marketing software provider Hubspot. - Spotify’s price hikes, the strength in Levi’s direct to consumer model, and a true blank check business. (19:11) Wharton Professor Ethan Mollick breaks down his four rules for using AI, and other tips from his new book Co-Intelligence: Living and Working with AI. (34:20) Jason and Bill break down two stocks on their radar: Cognex and WD40. Stocks discussed: DIS, GOOG, GOOGL, HUBS, SPOT, LEVI, DJT, WDFC, CGNX Host: Dylan Lewis Guests: Jason Moser, Bill Mann, Ethan Mollick Engineers: Desiree Jones, Dan Boyd Disclosure: A High-Yield Cash Account is a secondary brokerage account with Public Investing, member FINRA/SIPC. Funds from this account are automatically deposited into partner banks where they earn a variable interest and are eligible for FDIC insurance. Neither Public Investing nor any of its affiliates is a bank. US only. Learn more at public.com/disclosures/high-yield-account Learn more about your ad choices. Visit megaphone.fm/adchoices

We've got another rumored big tech deal and the latest set of price hikes hitting consumers. Motley Fool Money starts now. Everybody needs money. That's why they call it money. From Fool Global Headquarters, this is Motley Fool Money. It's the Motley Fool Money radio show. I'm Dylan Lewis. Joining me in the studio, Motley Fool senior analysts Jason Moser and Bill Mann. Gentlemen, great to have you both here. Hey, Dylan. We've got four rules for using AI, rising prices for music streaming, and of course,

stocks on our radar. We're going to kick off with a little bit of corporate intrigue, though, straight from the pages of the TV show Succession Bill. We have some boardroom drama this week. Disney's board winning approval over activist Nelson Peltz, and they will retain their seats. Bill Peltz and his firm, Tryon Partners, have been a thorn in Disney and Bob Iger's side. It seems like at least this chapter of the drama is finally behind the company. The mouse does not play, does it? No, you can't mess around with the mouse. No, this was a bruising defeat. They only got 31% of the votes after a very expensive, very out-in-the-open, dirty laundry proxy fight. So, I'm not sure that we should feel all that bad

for Nelson Peltz and Tryon Partners, though, because they're up about 40% in the period of time in which they made the investment. So, I guess it depends on what you want. Ultimately, if you invest, you're looking to make money. And so, even though they failed, I think maybe they have gotten Disney to make some changes, and maybe for the better. Yeah, I was going to say, the reporting I saw from The Wall Street Journal said that Pelts had made about $300 million on that $800 million stake. There's some legal fees in there, but I think that's still a pretty decent profit for them to be making. Jason, as we have the board side of this settled, now Disney just needs to get onto the simple

business of fixing its movie studio, fixing its streaming offering, and creating a succession plan for CEO Bob Iger. Simple stuff. I mean, it seems like we've got our success story right here. What do you got next? I mean, you're right. I think this is an important resolution in that it's one more of the sideshows that's kind of come to a conclusion here for this company, right? I mean, they're dealing with all this stuff with DeSantis in Florida, and now they've got Nelson Peltz to deal with. So, I think for Disney, what is better for the company, I guess, is debatable. Would they have been better off with Peltz winning this? We'll never know. But it is important that it gets past all of these sideshows and lets them get down to brass

tacks, really trying to reinvigorate its creative output. Like you said, that's what this company's in the business of doing. It's creative output. I don't think it's arguable that they have really fallen flat over the past several years. Then when you add to that questions regarding succession, what exactly is Iger's plan? It's still all pretty unclear. This resolution, I think, helps them get back down to brass tacks, but they still have a lot of hard work to do, as you noted. With that tough work ahead, I know I was talking with Asit Sharma early in the week. He remains a Disney bull and feels like there's a good outlook for the business. What's your take on it, Jason? Yeah, it absolutely feels like there

is a tremendous long-term opportunity for the business. You don't want to discount the power of the brand and the presence that this company has globally. That park segment alone is virtually impossible to replicate. Even if you did, that's like, people still want to go to Disney World. They still want to go to Disneyland. I think for them, it's really going to be trying to figure out how to put all of the pieces together in the content side, whether it's studios or streaming. There's a lot of moving parts there. A lot of questions regarding ESPN, still unanswered. Sports, as we know, is a tremendous opportunity there. They're dipping their toe into the sports betting markets there. So, I think there are plenty of opportunities. I think the key is,

they have got to get past Bob Iger, and they have got to get someone in place who knows what they're doing and can steer this company forward. I'm a Disney blerg, I guess I would say. So, obviously, none of the problems that you've spoken about have been solved from this point. They have huge, huge operational issues to deal with, including streaming. It's a big question for them. They have, I guess you would say, have lost in this current iteration of Disney+. So, lots of questions that are upcoming. All right.

Going global, news out this week about a 7.5-magnitude earthquake hitting Taiwan. shock was the strongest to hit the country in 25 years, resulting in over 1,000 injuries and several deaths. And Bill, in addition to the local damage, the tremor also briefly disrupted chip production for Taiwan Semiconductor. This story tends to highlight for me the global dependence on Taiwan when it comes to sophisticated chip manufacturing. Seems like a pretty big deal, right? Yeah, absolutely. Yeah. So, 25 years ago, not that Taiwan Semiconductor didn't exist, but there was an entirely different regime. So this was a potentially worst case scenario. And it really

speaks to a lot of things. And I'll have you know, I got my geology masters on the artist formerly known as Twitter yesterday. So I'm able to talk about this a lot. Armchair expert. I'm an armchair expert. Exactly. I've done it. All of this is to say that in Taiwan, you have to tip your hat to the people and the building standards that they've put into place. Because Taiwan Semiconductor not only was back up and running a day later, and so was all of the companies that it is dependent upon and vice versa, but they've also come out and said that there would be no real hit to their full-year revenue guidance, which is incredible. We also saw some other news in chips this week. Intel, for the first time, breaking

out results of its own chip manufacturing business, their Foundry business. Shares down 10% for the company this week after that first look because we saw $7 billion in operating losses for 2023. Bill, I think we know when it comes to manufacturing, building out factories and foundries, this is an expensive long-term bet. Do you feel like that's something you'd be willing to give Intel some leash on, giving everything we just talked about in terms of regional dependence on Taiwan? Well, Intel has gone from being the dominant player in the chip industry to really also ran. And some of it, you could actually point to the fact that they are trying to design and as well as manufacture, which is somewhat unique in the industry. Companies will do one

or the other. So, $7 billion lost on $19 billion in sales, that is tremendously negative for Intel. They have gotten some government largesse, and they're looking for more. So, they could pay their way through, but it will be on taxpayers' dollars and not necessarily from Cheryl. Real quickly on Intel, the other thing to keep in mind, this is not something that's going to quickly get better. You're talking about these losses. They're guiding for these losses to peak here in 2024, but they're not even really looking to break even until somewhere midway between this current quarter and 2030. 2030, that's a lot of years ahead still. It just speaks to I think the difficulty in really establishing this part of the business, and for investors,

really the difficulty in trying to project exactly what success looks like down the road. All right, before we go to break, so much for antitrust spooking big tech away from acquisitions. Rumors out this week that Google parent Alphabet is interested in the digital marketing business HubSpot. Shares of HubSpot up 8% this week on the news. Jason, are you surprised to see Alphabet sniffing around here? I'm not. I mean, it feels like they're going to test those waters as long as they feel like they're going to be allowed to. Now, it does seem like something that regulators would have a field day with, given when you look at HubSpot from a market cap perspective, a $32 billion market cap. But it's also worth noting, this is

a company that generates about $2 billion in revenue. So, from a revenue perspective, it does seem like it could be reasonable. But that then begs the question, is Google going to pay through the nose just to buy this business? And is it worth it? Because HubSpot today, it's not profitable, no cash flow, you account for that stock-based compensation at least, trading around 15 times sales. I mean, what is Google going to have to pay up to actually get this business? And then furthermore, is it going to be worth it? I mean, given HubSpot's focus on inbound marketing, it seems unique. It seems like something that could be complementary to Google's model. But like Bill and I were talking about before, it really ultimately has become kind of like a

defensive move on Alphabet's part. Yeah, Bill, when you look at the possibilities here with HubSpot being a part of Alphabet, a lot of search properties here. And as Jason noted, inbound marketing is their specialty. Where do you see this business potentially fitting in? I think this is defensive for Google as much as anything else. They've got two lawsuits out there right now from the Department of Justice for digital advertising in their search engine markets. And there's also a big push in AI to take on a lot of those types of searches. And that could impact their advertising. So this, to me, $2 billion in revenue is a drop in the bucket for Alphabet. So to me, this is solely something that they're doing

to shore up the battlements of the company itself and its core business. All right, coming up after the break, we've got a new trend in how people are buying an American Icon. Stay right here. This is Motley Fool Money. You just found out that your sales team is at risk of missing quota. Don't panic. Just ask Rippling AI. Since it's built on your real-time people and business data, Rippling AI can pull metrics from Rippling and Salesforce into a meeting-ready dashboard showing quota attainment, headcount plan, and monthly revenue to quota by region. In seconds, you'll see exactly what's behind your quota risk and fix it before it's missed. Question answered, action taken, crisis averted. When you have critical business

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the company up 15% on news that it will be raising prices again for subscribers in the United States and other markets, including the U.K., Pakistan, and Australia. Jason, this is the second price hike we have seen from this business in recent history. They raised prices in the United States just last year. Are you surprised at the pace of this? No, I'm not. I tell you, as a Spotify subscriber, I don't even feel those prices. I had to look up actually what I'm paying for Spotify because we have the family plan and it is just integral to all four of our daily lives. Wait, what are you doing? What do you mean? Are you trying to get them to say,

well, let's just keep raising it until Jason Moser complains? Keep it a secret, man. I told Amazon they could double prime and I'd still pay it. But that was like 10 years ago. So, listen, I mean, they're not going to listen to a dummy like me, right? No, I love this. I mean, I think they did something that reminds me of how Disney started their streaming with Disney+. It was this absurdly low price, something like $5.99 or $6.99. It gives them room to just incrementally raise those prices a dollar or two all along the way. For most folks that use Spotify, it's a pretty habitual behavior. You start forgetting about exactly what you're paying. You have to go through

those subscription audits every once in a while to remind yourself. But when you look at the company itself, 602 million monthly active users, 236 million of those are premium subscribers. Now, it is worth noting, they define premium subscribers as users that have completed registration and have activated a payment method. But premium subscribers also include all registered accounts in the family plan and the duo plan. So, it's all to say that 236 million premium subs, that doesn't mean they're getting $1 for every premium sub, but it could be close. You want to pay attention to that ARPU number to understand how much money they're bringing in per user. I think the bigger opportunity for this business longer-term, really, it's in advertising.

It still only makes up about 13% of revenue today. They've got a long way to go there. 602 million monthly active users, that number keeps on growing every quarter. Bill, I thought the approach was pretty interesting here from Spotify, because the company says the increases will help them cover the costs of the audiobook program they launched with their subscriptions. That started out as an entitlement, I think, about six months ago. They are now increasing the prices to maintain that and saying, hey, if you don't want the

audiobooks, you can keep your pricing the same. I think that type of feature pricing functionality is kind of interesting, maybe a little bit of a lens into what we can expect from Spotify in the future. The biggest cost that Spotify has is royalty payments. This audiobook segment is a really big deal for them because the royalty payments are much, much lower on a per minute of usage than they are for songs or anything musical where you're paying for every three minutes of content. $9 billion out of $13.2 billion of their revenues went to royalty payments last year. This restructuring, I think in some ways, is almost more important than the actual raise of prices. They're trying to get their members to go down one path or the other. It really has

to do with what they pay and how much Spotify has to depend on music royalties to make its business. Jason, Levi's earnings this week showing it's never good to bet against denim. Shares of the iconic jean maker up at 12-month highs following the release. And really, it seemed like the focus here and what the market was incredibly excited about was the direct-to-consumer model that they continue to push into. Yeah, it's nice to see such a staid, memorable, reputable brand as Levi's. I'm still a Levi's guy. I'm probably, I mean, I don't have them on today. I have jeans at home, Bill. I have jeans at home.

It's nice to see that this is working out for them. What it made me think of immediately was just the other week when we were talking about Nike. We were talking about Nike and how they're making these efforts into the direct-to-consumer. And they kind of took it a little bit too far. right? And so, they saw a little success there in DTC, but it really impacted their wholesale business. And with Levi's, it seems at least like they're not witnessing that yet. Now, Levi's is obviously a much smaller company. I'd say unique compared to Nike. I mean, a little bit more of a focused market. And so, I do understand wanting to focus more on that

direct-to-consumer. And that 48% of the business today versus about 42% from a year ago. So, Clearly, it's something that continues to develop positively for them. We're seeing gross margin expansion of 240 basis points from a year ago. I don't know that it's a business that I have on my list of ones that I want to own, but it is nice to see the business making decisions and being rewarded. Bill, I think a lot of excitement with the Levi's results because now nearly half of the revenue coming from that direct-to-consumer model they have a little more control over. I think the thing that we all have to remember here is, the wholesale side of their business

means relationships with Macy's and Kohl's. And I don't know that either of those businesses are necessarily lighting the world on fire. I feel like you guys are burying the lead a little bit. Because in Beyonce's new album, there is a song called Levi's Jeans, and they were specifically asked whether there's been an uplift in revenues because the beehive is now more aware than ever that Levi's is pretty hip. There are absolutely changes that they're trying to make. They've actually let go 12% of their global workforce. The company is trying very hard to be a lean operation in a way that a lot of the branded companies that we think of haven't necessarily had to be. So, Denim is an incredibly, incredibly competitive business.

But I think that these are, if you'll pardon the pun, legs up. Love it. All right, we're wrapping this week's market news with a look at an unusual market debut. Last week, the Digital World Asset Corp. closed its acquisition of Trump Media and Technology Group, bringing former President Trump's Truth Social public at roughly a $9 billion valuation. Bill, this is a business that has $4 million in revenue in 2023, net losses of $58 million, and the company came public, as I said, at about a $9 billion valuation. Stating the numbers here to have it very simple. This is, in a lot of ways, the end of some of the SPAC activity and the fervor that we had seen for such a long time. It seems like

such a fascinating business. We've seen so many headlines about it. What is your take on this? I'm delighted that you call it a business. $4 million is about the same revenue as the average Shake Shack, and not the company Shake Shack, an individual Shake Shack. So, this business, fundamentals do not matter. And I think that this is probably the end result of the meme stock change that we have seen in the market over the last couple of years, in which companies are valued on vibes. And I, as a fundamentalist, it's not necessarily a game that I really understand what those vibes are, what this company is being valued on. I know it's not on the revenues. It's definitely not on the non-existent profits. It's on something

else. And so, I wonder if people who are investing in this company are really thinking about whether they're holding a business or whether they're holding something that is just meant to be, I hold it because I like it. Yeah. I was going to say, Jason, SPACs are known as blank check businesses. I think this is a blank check business in the purest sense, even post-SPAC, because we are looking at something that is a very simple bet on personality and ties to the former president. Yeah. Well, I love the price to vibe. That's a multiple. We need to incorporate it. And it's big. It's a little bit squishy, but we can get there. At the end of the day,

you've got to look at the fundamentals of the business. It's not to say that they can't succeed, but social media itself is an extremely competitive, very difficult market. I don't really think they have a lot going there, but it's a tough one. Jason Moser, Bill Mann, we're going to see you guys a little bit later in the show. Up next, we've got Wharton Business School Professor Ethan Mollick on his tips for putting AI to use for investors. Stay right here. You're listening to Motley Fool Money. Welcome back to Motley Fool Money. I'm Dylan Lewis. We're firmly in the age of artificial intelligence, or as Wharton professor Ethan Mollick might frame it, co-intelligence. That's

his philosophy on how humans can best work with AI, and it's the title of his new book out this April. Ethan joined me this week to walk through his four rules for using AI, the different angles that big tech companies are taking in the AI race and how you can use tools like ChatGPT as part of your investing process. What I liked about the book reading through it is it was a great exploration of the space and kind of a foundation, but also in a lot of ways, a very practical user guide for getting up to speed very quickly and kind of going from, all right, I don't know anything to beginner to intermediate. And I think that it's really useful for people in that sense. Knowing how quickly the AI landscape has changed, what was the process like for writing

the book? And was it an accelerated timeline? So, I wrote the book and edited it through the end of December. I wrote it knowing GPT-5 is coming and is not yet, but will be. And all these other tools were coming my way. I did write it pretty quickly. This is my third book. But I couldn't have written it without AI. Actually, there's almost no AI writing in the book. It's not AI writing. There's little AI segments, but they're clearly marked. The interesting thing is AI did all the other stuff that made writing books horrible for me on my behalf. So if I got stuck on a paragraph, sometimes you work on a sentence for a long time, I'm like, give me 30 verses of this sentence that I use as inspiration. There's a lot of work showing

that AI works well as a marketer and as a persona to market too. So I asked it to read my book and various personas to give me feedback on what I was doing and advice. And I asked it to summarize research papers that I turned into part of the paper. So it was very, very helpful in accelerating this process. It's sort of what AI does, the co-intelligence idea. It's an accelerator. I think that that tees up nicely for some of the rules of using AI that you talk about in the book. And I want to run through them because I think there are probably some listeners out there that are avid users of ChatGPT and probably some other folks who maybe aren't as familiar or have never interacted with an LLM before. So how do you structure how people should

be using AI? So I recommend four rules to get started with. And the first rule is invite AI to everything you do. Basically, nobody knows how AI is most useful for your field. Nobody does. I think people are waiting for instructions. I talk to OpenAI all the time. I talk to Microsoft. I talk to Google. There is no instruction manual. Nobody has a book that they haven't shown you yet. There's no consultant who knows anything. Nobody knows anything. So the way to figure out what this does is just to use it a lot and see what it does. And I strongly recommend just trying to use it for everything, sorry, legally and ethically can. Then the second piece of advice is that you should learn to be the human in the loop. So the AI is really good at a lot of things. We could

talk about the studies and results on this, but like it's really good at innovation. It's really good at analysis. It out invents most people. You want to think about what you're actually really good at because whatever you're best at, you're definitely better than the AI. And I think that there's going to be, you know, a real benefit to think about what you want to do and what you want to delegate. The third principle in the book is one where I say, you know, you should treat the AI like a person. And this is kind of considered a sin in the world of AI. You're not supposed to anthropomorphize it. But the fact is, it's trained on human language and human interactions. So it works best when you work with like a human. In fact, one of the mistakes people make is they

assume that software developers are the people who should be using AI, but it's actually not. It's really managers, writers, journalists, teachers often do a much better job using AI because they can take the perspective of it as a person, even though it isn't, and that helps you do great work. And the fourth is, this is the worst AI you're ever going to use. And we are in the early days of this kind of revolution. You detail companies that have outright told their employees don't use AI and said that that is to their detriment.

But I think there's also, it seems, a risk of the company just falling behind in the industry because it's a tool that anyone can use for their jobs. Do you see companies that have particularly good policies when it comes to their workforce and AI? I've seen a wide variety of policies out there, right? I mean, the early day, like the question is about organizational culture and approach. I mean, the most extreme version I know is Ignite Tech, and they're willing to talk about this, where the CEO realized GPT-4 was a big deal last spring and gave everybody in the company, OpenAI, you know, Access, and said to them they have to use AI that month. They should experiment with it. And then he fired everybody who didn't spend at least two hours with AI that

month, but then offered like $10,000 rewards to whoever came with the best prompt at the end of every week, right? Like that's a pretty good indicator of how seriously he took this one way or another. So I think there's a lot of models out there that people are following. I think that might be a little extreme for most organizations, but I think the idea of endorsing its use at the highest levels by high level people using it is pretty important. One of the things that I thought was kind of interesting in the book is you talk about that people are maybe cagey or a little private about AI use and that it's kind of this thing where you're not sure if you should acknowledge that something was generated by AI. Can you elaborate a little bit on that? I thought

it was just such a unique idea. So I call this the secret cyborg problem, which is that your incentives, like think about the incentives of the average worker in most companies. One, their AI policy is unclear. So am I using it right? Might I get fired for it? No one's ever really told me exactly what to use it for and what might get me in trouble. Like even organizations that are permissive, right? The second thing is once I show people I've written something by AI, will they stop respecting my work as much? Because they think I'm a wizard right now. There's literally this whole thread of Reddit people saying, I'm a wizard at work. What do I do when they find out it's AI use? The third reason is that you might be worried that you get fired, right? Because of

like you're now more productive or even worse you're a scab and all of your co-workers get fired because you've just shown they can do the work or maybe you're just assigned more work which kind of sucks without compensation or you can't launch a competing startup like so there's lots of reasons why employees don't want to share their ai use and like i spoke to someone who literally wrote the policy to ban chat gpt use in a major bank and she wrote it with chat gpt on her phone because like why would she go back to doing something by hand again so when you create those types of policies people just subvert them in their own ways anyways people want to use it's called shadow IT spend, like they'll figure out a way to use it. If your policy doesn't let them

use it, that doesn't stop them from using it. One of the things I wanted to ask about is, you know, you've spent a lot of time looking at the landscape. We see a lot of money pouring into AI. I mean, Amazon just increased their investment in Anthropic, I believe last week to $4 billion. It was a sizable bet for them. How should investors, as we're looking at these big companies making big swings in this space, be trying to get a sense of the success of these bets? Because in some ways, it's so early still, and it's so hard to show meaningful progress. But on the other hand, we're seeing huge dollar signs that are attached to these investments. I mean, so first of all, there's a weird thing that we have to recognize,

which is this idea of AGI, of a computer smarter than a human being that can eventually lead to a super intelligent computer that can do anything. The large AI labs believe in this. They believe they're building AGI. They believe they're building in the next few years. The consensus estimates of AGI and the betting markets are 2031. They're believing this. One thing that I think a lot of analysts get wrong is they don't believe that a lot of these organizations actually believe they're building a human replacement. They do. So a lot of the business decisions of places like open AI do not make sense on a standard analysis. I mean, they could harvest a lot more cash. They're incidentally, I think their run rate's over $2 billion a year in revenue,

but they're not even trying, right? Like they're not making their product user-friendly. It breaks 90% of the time. That's because they're spending every ounce of their energy and compute building the next version of, you know, the next training, the next model, right? Like, so you have to, first of all, believe that these people believe, you don't have to believe it, but you have to believe that they believe that this is possible and that distorts investments, right? And you have to make a decision then also as an investor, do I think this is possible or not? Because if it is, that's a very different hedging strategy than not. Because a lot of what wins or loses in AI depends on how soon we hit a plateau in AI ability and how expensive it is to do that.

There's a scaling law in AI. The more powerful your system is, the larger your AI is, the larger your data set is, the more expensive it is to train, right? So it's about $10 million to train free ChatGPT 3.5 class model now. It's about $100 million to $1 billion to train a GPT-4 class model, right? Maybe $10 billion for a GPT-5 class. There's efficiencies to be gained. No one's really worrying about those yet. So the question is, if GPT-5 or GPT-6 continues to be 10 times better than GPT-4 or whatever the previous version is, then it's going to be a winner-take-all market with just a couple of players who have the money in the computer. Follow where the computer chips are, there's only a couple of companies with the chips, right? And that is, you know, there's four

of them. And there's a really, Anthropic is a pawn, right? Because they can't, they don't have their own computers. They train on whoever, right? OpenAI is enthralled to Microsoft. Google does their own training, right? Meta has its own strategy. So you have to follow where the compute is and you have to make a bet on what you think the future is going to look like. I think it's particularly tough for a lot of people who don't necessarily have that technical expertise to dig into that and follow along. What I find interesting, particularly in the case of a company like Google, is they are kind of put in a position with AI, especially user-facing AI or more generative AI applications, where they have to kind of disrupt their own business

in order to be where people are using it. I mean, OpenAI made such a humongous splash with ChatGPT, and it seemed like everyone else kind of had to catch up. the implications for Google's business model was pretty clear right away. This is how people interact with information. Do you feel like the incumbents in tech are willing to make those big shifts that will affect their business? I mean, look at Microsoft Dance. It's crazy to watch this organization go all in on generative AI everywhere. Google has been slow off the starting line, but Gemini 1.5 is really impressive. I don't know what their plans are for ad revenue, but they have to move. The game started. What happened when OpenAI

released ChatGPT was that stuff had been kicking around for a while behind closed doors. And the decision to release it kicked off a war. And so again, if you believe that this is the future, then the companies have the purest strategies I've ever seen. Meta's job is to act as a spoiler. It's releasing these open source versions to make sure nobody else wins because they think their applications are the best, right? They already own the social networks. They own the metaverse. This will help them boost that, right? Google is trying to build its own internal product that's better than anyone else to organize information and connect all your Google products together and presumably do ads better. Microsoft just spray painting everything with open AI stuff

right now, you know, and adding AI to everything, right? Amazon is sort of trying to figure out what it wants to be a vendor or not. Like there's a lot of Apple, we have no idea what it's doing. Like this has kicked off a war, and nobody really knows what business model is going to work. I think this is a boom and not a bubble, but there are parts of it that'll be a bubble too, and we don't know the answer to that either. In a practical sense for our audience of investors, you talk about a study where people used AI to look at conference call transcripts and are looking for perceived risk and the volatility that may come from a company based on what's inside the transcripts and the discussions between management and analysts.

What are some other ways you could see an investing audience, especially a beginner investing audience with AI, harnessing tools like ChatGPT? I mean, so there's a whole bunch of different ways of thinking about this. One thing is, I think one of the big misunderstandings I have when I talk to financial folks is that they're used to thinking about it. The definition of AI changed fairly dramatically before and after ChatGPT. Before ChatGPT, it was about how do we build models that analyze lots of data and then give us results?

And by the way, that's absolutely turnover finance. It's very funny when I go to visit a hedge fund or something, they already were disrupted by AI, right? I go visit the trading floor of a multi-billion dollar plus fund, and it's like three people at a cubicle farm at the end of the desk, where it would have been like a wall of people screaming, right? It's a very different, and it's all algorithmical, right? So that's what we used to mean about AI, right?

It was about the algorithms and matching the algorithms and that the big companies could afford to hire the quants and the quants would build the tools and the tools would do the trading, right? And that was a whole angle. And then there was all kinds of analysis being done with proprietary models. GPT-4 and other models like it are pre-trained. That's what the P in GPT stands for. They know a lot of things about the world already, but they also act more like people

than like miracle machines. So I think there's an important thing people who are thinking about AI and finance need to realize, which is the definition of AI has changed dramatically. When we talk about AI prior to the chat GPT, we would talk about AI as a prediction tool for math, right? You could give it a trend line. It would tell you what would happen next. It could predict where you should give it all the data about what people buy or watch on Netflix. It would give you recommendations of what to watch.

And that powerfully changed finance. When you go to a trading floor today, it's three people at a computer. It's not a giant room full of people screaming and yelling. There's just a lot less traders there. where there's quants now who build algorithms and algorithmic trading is a big deal. And the decisions are being made at the speed of light. And that change has already happened in finance. And I think people, when they use a system like ChatGPT, sort of have that model in mind, but that's not how large language models work. Large language models are pre-trained. They're

not magically taking all this data and making decisions. They kind of work like a person. So if you ask a person to pick a stock, that's kind of like asking GPT-4 to pick a stock. It's not actually going to do an amazing job. It'll kind of Google some stuff and look at a spreadsheet and then make something up for you. What it is good at, though, is pieces of that. For example, the AI is very good at doing sentiment analysis, a very hard problem to solve. Are newspaper articles good or bad? That's a hard thing you'd have to hire people to go read them through because machines were never that good at it. The AI can look at 10,000 articles and tell you whether the sentiment change is happening. It can do a good job explaining to

you why a product works or not or whether a news article is good or bad. It's much more of a co-intelligence or assistant than it is a sort of magical tool. And I think one of the mistakes I see, especially amateur investors making, is assuming the AI is particularly knowledgeable about investments, and it just isn't, right? It's not going to have a secret insight that you didn't have. Listeners, how are you putting AI to work? We want to hear from you. Shoot us a note at radio at fool.com. Coming up next, Bill Mann and Jason Moser return with a couple stocks on their radar. Stay right here. You're listening to Motley Fool Money. Dylan Lewis. 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 anything based solely on what you hear. I'm Dylan Lewis, joined again by Jason Moser and Bill Mann. We've got stocks on our radar coming in a minute. But first, this week was National Burrito Day. If you missed the official celebration on Thursday, you can catch up this weekend. Jason, I know you are a home cook of burritos. You like making them at the house. Any tips for people as they're putting them together? I like making everything. I think the key is you just got to make sure that you get those burrito tortillas. You got to steam them. You got to get them pliable and flexible. Too many times have I seen people

just skip that step and they're just splitting those skins all over the place. Amateur hour. It's all about the prep. It is. It really is. Bill, what about you? I'm just loving the thought of about a makeup burrito, right? Like, oh, you missed the official day. It's okay. The burritos won't care. Just jump on. You know, I don't know what to make of this, but I went and got a burrito from a place that I don't go very frequently on National Burrito Day, not even realizing that it was National Burrito Day. So, I don't know if I was inceptioned into you having my burrito, but I'm happy to celebrate again this weekend, even though I didn't miss the opportunity. All right, let's get over to stocks on our radar. Our man behind the glass,

Dan Boyd, is going to hit you with a question. Jason, you're up first. What are you looking at this week? Yeah, I've been digging a little bit more into Cognex, ticker CGNX. They are in the business of machine vision. They build hardware and software. They can see and do all sorts of automatable tasks, mainly in manufacturing and distribution. Its largest industry is by revenue. It serves automotive, logistics, and consumer electronics. You've got to love the tailwinds in those. Now, they are pursuing the ultimate opportunity in Industry 4.0, or something also referred to as the industrial Internet of Things. It's just the same thing, really, as the Internet of Things.

Everything's becoming more connected. Everything's talking to each other. The commercial and enterprise opportunity there is massive. I think the interesting thing about this business. They've been at it for over 40 years. The former CEO, the founder of the business, Bob Shillman, founded the company back in 1981. He has a Ph.D. from MIT in computer science and artificial intelligence. This guy was doing AI before it was even cool. So, you've got to like a lot of what they're doing. They are running into some headwinds, I think, just as being concentrated in some of those markets. I think EVs in particular, we're seeing some headwinds there that have impacted the business. I'm trying to get

the bottom of whether we can see that catalyst sort of reignite itself. Dan, a question about Cognex, ticker CGNX. Cognex seems like a galaxy brain play here, but their first vision system was called Data Man, and that's just a funny, in a bad way, name for something. Well, they call their employees Cognoids. Pretty strong culture there at the company. The best annual reports in existence. They did one that was literally a cartoon. It was a comic book. Fantastic. Bill, I appreciate that you're pumping up Jason's radar stock, having to then pitch your own. What are you looking at this week? Look, Ben, I know what I've got here. This is the meme stock of meme stocks. I am interested

in seeing what WD-40 does when they report this next week. They report on Tuesday. day. This stock is trading at a P.E. of nearly 50. It has been on an extraordinary run. WD-40 really doesn't need much in the way of introduction for everyone except for Dylan, who we learned does not have a can of it at his house. It does everything. They make the WD-40 silicone spray. They also make lava soap. That's their business. It's very, very simple. But during COVID, this company caught a bid and has gone like wildfire. They need to back it up with their earnings report. Dan, I'm expecting a comment, not a question here on WD-40. I mean, it's the most useful product in

existence still, and it's kind of a gimme at this point. It's science. At the risk of asking a question I don't need to ask, which one's going on your watch list this week, Dan? I'm going with WD-40, going to nobody's surprise. To nobody's surprise. It's a winner. It's in every household. Bill Mann, Jason Moser, appreciate you guys bringing your radar stocks. Dan, Appreciate you weighing in. That's going to do it for this week's Motley Fool Money radio show. The show is mixed by Dan Boyd. I'm Dylan Lewis. Thanks for listening. We'll see you next time.