The AI Hype Is Real

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On a recent episode of The AI Investor Podcast from 24/7 Wall St. , the team discussed the significant rise of AI's prominence in recent years, with a particular focus on how its current hype compares to past technological booms, like the dot-com bubble.

24/7 Wall St. lead tech analyst, Eric Bleeker, reflected on their long history with AI and companies like Nvidia, emphasizing the importance of understanding the compounding effect in investments, which has been crucial in realizing the potential of AI.

This compounding, particularly in computing power and AI model complexity, has accelerated the development of technologies like generative AI and Transformers, leading to breakthroughs like ChatGPT. Eric notes that while AI has reached a mainstream "iPhone moment" with ChatGPT, there is still uncertainty about whether this surge is a temporary bubble or the beginning of a sustained revolution.

In the video below from the podcast, Eric and his co-host, David Hanson, highlight the importance of being cautious and well-informed when investing in AI, acknowledging both the fear of missing out (FOMO) and the potential risks of overestimating the trend.

Eric and David suggest a balanced investment approach, likening the current AI boom to the dot-com era, where there were both big winners and major losers. They stress the need for ongoing analysis and diversification, as the timing of AI's full impact remains uncertain. The goal of The AI Investor Podcast from 24/7 Wall St. is to provide investors with the tools and context to navigate the volatile landscape of AI investments, ensuring they can capitalize on growth opportunities while being prepared for potential setbacks.

Full transcript below

https://videos.247wallst.com/247wallst.com/2024/08/Clip-1.mp4

David: Obviously, AI is kind of on the tip of every investor's tongue now over the past 18 months or so. But I remember you were talking about it in 2013, 2014. I think you went and visited Nvidia back in 2015 when it was kind of a small cap even. So why now? What has changed? Obviously, the hype cycle compared to those earlier times is much higher now. Is it just hype? A lot of people are looking at this and being like, oh, I mean, you're starting to hear your aunts and uncles at the dinner table might be like, what's this AI thing? So it's certainly reaching that point. And how do you kind of discern, is this just another dot-com bubble? That was only 25 years ago. There's still a lot of scars. And I think people are very hesitant to kind of buy into it. So why now? What has changed from those early days that you were going to visit a smaller NVIDIA? And is it real in your mind, what we're seeing right now?

Eric: Yeah, like you mentioned, I've got a long personal history with NVIDIA. We've done dozens of webinars about it. from our time together at The Motley Fool. NVIDIA was the first stock I ever bought in the mid 2000s. You know, it's just, we have a very long history. Now, David, you know as well as I, the kind of key to investment is the idea of compounding, right? If you did a book on Warren Buffett quotes about compounding, it would probably be about this thick, right? Because compounding, you know, put simply it's, if you get a 10% return for 10 years, that's not 100% returns, it's 159%. And as numbers get bigger, it's more dramatic. So if you have a 20% return, 10 years that's not 200 it's 519 percent so any place that we have significant compounding it's why investing in your returns look so more significant when you do a long time scale is because we always underestimate compounding at scale so just doing a little story here um you know both of our jobs at The Motley Fool involved going out finding the most exciting trends and finding a way to get those two members, like we talked about earlier, with webinars or other ideas where we're able to take the ideas that we're most excited about and get out to people. Around 2020, I think it was late 2020 into early 2021, I had already been covering AI for about a decade at that point. We first started having NVIDIA into the office around, I think, 2009, 2010, when they were first talking about kind of the very first phases of this. And I was looking through ideas around what's going on in artificial intelligence. I know it's a chart that they started producing, that the first breakthrough from the early 2010s, which was called deep learning, that was causing a doubling in the amount of compute. Computing power needed to 8x every two years, I believe it was. But there is a new AI model that was taking off it was causing compute to 275x every two years so you see that and it gets your attention And it seems like something fundamentally new is taking off. And we actually, you know, at the time we did a webinar and we talked about how Elon Musk was poised to harness this for self-driving cars. You know, now you go forward today, right? He's got his AI company and he's building humanoid robots and Tesla. So he's actually doing that. So we're maybe a little early, but we really called what was going on. But what we now know today is what I was observing in this new step change in AI, it's what really led to chat GPT in this breakthrough. And it's an entirely new way of building AI models, which has led to generative AI And that's from something called Transformers. So what Transformers can do is essentially older AI models, it would have to basically analyze everything. If we're looking at sense by sense, Transformers could take up to entire books and understand the context of them. And what this is allowing is AI models that are, again, becoming more complex, we would call it, at a rate that is hard to comprehend. And the clearest way I would have to say it is when the first ChatGP came out in 2018, it had 117 million parameters or ways that you would kind of tune that model. The next one that they're still working on and they're expected to release it in the next year is supposed to have 17.5 trillion. All right. So that's a difference of 150,000. So.

David: And I think it's important to call out, you know, you just said the first GPT, what was the year that that came out? 2018. And I think a lot of, you know, a lot of people remember the launch of chat GPT as like, oh, that's when it started. Right. But what you're saying is this is, you know, there was years of compounding that got us to this point. That's when it became mainstream.

Eric: Exactly. It was in the background until chat GPT-4. which was more recent. I believe that was, when was that? That was December 2022 or 2023. It was recent. October 2022, yeah. Yeah, yeah, right in that zone. End of 2022, yep. So that's the point that that's kind of iPhone moment for AI. And that's what really started moving. So again, this is what we've been seeing. And so you've got a question now that, Is it a bubble? Because kind of like the internet, there's a lot of hype around what networking could do. And then there was a revenue side for it, which you didn't know how long it was going to take. So we've got a couple of sides from that for AI. Facebook this year, Meta, they're supposed to add $16 billion in incremental revenue from their AI efforts. So you're seeing the companies at the forefront, they're already making some pretty serious gains from this. But on the other side, you know, you're seeing a lot of spend because basically every single major tech CEO knows if they fall behind in this, they're maybe done, right? And that's where the arms race is. And there is a question of whether or not that falls off. Now, my personal belief is we're not going to see them come off the gas until we see this level of compounding kind of fall off.

David: Compounding in terms of the, you know, the ability to compute, right? Is that the compounding?

Eric: Correct. And how good these models are getting with more computing and more data. So the point here being, yeah, like we need to have a little bit of humility that we don't know exactly. It could be that AI is the biggest thing and it's going to take 10 years and we're going to have some bumps along the road. It could be within five years, we're saying, okay, this got here faster than anyone ever expected, right? There's still a wide divergence of outcomes. And that's why, again, something like a podcast, where we can come and every couple of weeks talk about the major developments and also talk about if you're investing in it, something that could be life-changing, what are those investments looking like? So again, that's where we're looking. Is this going to be the .com? I think there's definitely going to be aspects of it that it's not going to just be, it can't be as good as it was the past two years, right? If it's just that good, it's into infinity. There's going to be some, you know, zones where things pull back a little bit. Those might be opportunities. There's going to be zones where it's running extremely high and there's going to be zones of extreme growth. You know, we'll talk about some stock ideas today and our goal is to help you, you know, help everyone listening understand where the next zones of growth are coming, because I'm sure everyone's looking at NVIDIA and going, Man, I wish I had known about NVIDIA a few years ago, right? Like where is the next phase of growth? So putting all together, I think AI and its potential is extremely real. I think the companies at the cutting edge are doing a lot with it, but there is also some degree to this of FOMO and companies needing like they need to catch up. And that's what's going to probably create some waves. So if you don't have something like a podcast or some kind of basis for for understanding this market, when those waves hit, they're gonna wash people out and you're not going to enjoy all the upside of the longer term trends. So that's what we're trying to be here for, for investors.

David: Right. Yeah. So giving the giving the context. So when you see the headline, when you see a stock's down 30 percent or see a stock's up 40 percent, we can hopefully give you some context on, well, how does that really impact this overall story? So I want to underline that. But then also just you talked about, you know, this is this is an investor podcast. And I think we want to give a holistic view of many ideas to invest in this trend. This isn't going to be, you know, we're going to talk about Nvidia in just a second, but this isn't going to be buy or sell Nvidia. And that's the only way to play AI. You know, you look back at the dot com, lots of losers, but also lots of big winners. And, you know, probably the right way to play it is to build kind of that basket, that portfolio approach to this, because, again, the timing might be off. You look back at the dot com. I think there were a bunch of online grocery delivery companies that went bankrupt. And everyone's like, oh, it wasn't a bad idea. It was just wrong timing. And now you have DoorDash and Instacart, these other large companies. So there might be some crashes and burns. Some new ones are going to emerge. So that's why giving the context and giving a portfolio of ideas is what you know, we really hope to do.

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