Episode 79 | Professor Lake’s Hot Takes for AI Investment Tools

In Episode 79 of “Market News with Rodney Lake,” Professor Lake, director of the GW Investment Institute, shares his “hot takes” on AI’s role in the markets, the use of tools in investment analysis, and how AI serves as a productivity multiplier for the GW Investment Institute. The episode features in-depth analysis of major technology companies including Alphabet, Apple, and Nvidia. He highlights Google’s AI ecosystem and TPUs, Apple’s iPhone 17 upgrade alongside its AI partnership strategy, and Nvidia’s position in chip manufacturing and global competition. Lake emphasizes the need to understand AI’s technological evolution and ecosystem dynamics to make informed investment decisions and prepare for the future of markets and business.

Transcript

Thank you for joining Market News with Rodney Lake. This is a regular program for the GW Investment Institute where we talk about timely market topics. I'm Rodney Lake, the director of the GW Investment Institute. Let's get started.
Welcome back to Market News with Rodney Lake. I'm your host, Rodney Lake. We're coming to you from the George Washington University School of Business. Duquès Hall. Duquès Family Studio. This is a GW Investment Institute podcast. Welcome back to everybody that's listening. And welcome back to all of our viewers on YouTube. Certainly, if you love the show, subscribe.
Tell all your friends. We definitely want to get more people listening, that people that want to connect and listen and learn about stocks, learn about companies, that this is the place for you. As a reminder, this is entertainment and informational purposes only. Disclaimer will also be at the end here. We're going to talk about a lot of companies today.
Some we own, some we don't own, in our portfolios that our students manage. Again, about 11, just over $11 million of student managed funds. That's part of the overall GW endowment, and we're very proud of their performance. Check out the quarterly reports they keep coming out. There will be one coming out soon. Today, what are we going to tackle today on the episode?
So sometimes we do a general market overview. Sometimes you talk about specific companies. Today we're going to add something else, which is we're going to talk about AI specifically. We've talked about that before. But today's episode is going to be effectively my hot takes on all the AI companies and AI in general. So for what it's worth, these are all opinions.
But these are my hot takes. And certainly AI is, you know, the topic this year or just about every day that we all need to think about what's going on, what's going on in the markets. What is AI doing to disrupt ourselves? What is it doing to make your job more efficient or making you more efficient and making you more productive?
Is it going to put you out of a job? There's all of these things that are out there and people are talking about, and I think it's something that you should be focused on, certainly as an investor, as an analyst, as a business person, how do we participate? How do we make sure, that we're positioned really well in the companies that are going to do the best job to take advantage of this?
And that's certainly what we're trying to do with the Investment Institute. And that's we're trying to trying to train our students to do to think about. I think it's super important. I don't think it's going to get less important. If you think about today and you think about, you know, a year from now, three years from now, five years from now, it's hard to sometimes think ten years from now if you know what's happening in the market but one, three and five years out, do you think that I will be more important or less important?
I think it will be more important and possibly way more important. It's accelerating now and it's likely to continue to accelerate. People talk about the singularity. I think that's something to think about. What's going to happen. So for us, let's dial it back. What does it mean for us at the Investment Institute? What does it mean for our classes and our funds?
Well, one of the things obviously on the use of this, and so if you talk about the tools that people are using and then we'll get into the companies, you know, us as analysts. So for our fundamental classes, it's all about and this is financial security analysis for us. Finance 4101 for any of the students. You know, how is this going to benefit us?
Well number one you can use these models and you can use Gemini and ChatGPT and Grok and Claude all of these models. You can use the help you do investment analysis. Of course, our students use tools like FactSet and Bloomberg, but if you have additional tools that you have access to, which almost everybody does and you certainly can use the free version, and some people use the paid version, and sometimes it's very much worth the 20 bucks a month, depending on the platform.
Obviously, that's, not for every single one of them. For the first year, the pro or whatever they have to call it. It can be a very good exchange, a very good price part and a price point and a very high ROI. If you're an analyst taking a sip of my George Washington University School of mug, mug here.
Excuse me. So, will these tools benefit you? Well, I think you have to sit down and use them. But I do think if you're doing investment analysis, and you can use, for example, the GW Investment Institute framework, business, management, price valuation, and balance sheet, and you can use that framework, you know, score 1 to 10, 25% weighted each, come up with a composite score.
Put that in there and say, you know, go out. You know, you can use the link. For example, if you don't want to build your own model and say, here's the link for the GW investment Institute from their blog, for their BMPB framework, use that and score this company. So score Nvidia for me. Score Microsoft for me. Score,
You know, Google for me, alphabet is the parent company. Come and you know compare those companies and so put them in a table compare them. Give me some you know attributes and so you can run that analysis now. So it's like having your own analysts. It's like having an assistant. And then you can, you know, iterate on that and you can say, well, you know, deep dive into this one part of the business.
So tell me more about why it's important for, you know, Microsoft, to be growing Azure. And we talked about that in a prior episode that people are concerned it's not growing fast enough. So you can use those models to do that. So on the operational, investment side, when you're doing this work, you know, for us, we're telling our students to use these models.
We're telling them you learn how to use these models better. Obviously always, you know, make sure you know what's your work and don't claim work that's not yours. But at the same time, you know, use these things to leverage your work. Use these things to leverage your research. And I think that's super important. And obviously those companies to now, you know, use that as a little bit of a segue into the companies on the public side.
You're talking about, we'll start with and not Apple, but that's one of our first holdings. We're going to start with Google, as an example. And so clearly people using the iPhone, to maybe run some of the stuff mobile-y. But the models that they're running, Apple doesn't have a model. We'll talk a little bit about that, but starting with Google, very important, a large position for us here at the Investment Institute.
Important. And, you know, using Gemini, as the underlying model that you're using and using their ecosystem is quite good. Colab, for example, on our quant class for coding. So they have their own ecosystem. That can be quite useful. NotebookLM, for example, is quite good at creating presentations, and even podcast. So maybe it'll put me out of business, in the not too distant future already.
We're just hoping to get to the 100th episode before that happens. So hold on NotebookLM. We gotta get to 100 before before you put us out of business. But as an investor, you know, has has that been a good investment? It has. And if you look at over the past year, what's been going on with Google?
Well, look, it was a challenging situation. You had all of this overhang, with the legal situation, and you also had this, you know, idea that they missed the boat, you know, they had fallen behind on the AI space. And again, today's episode is mostly going to be talking about AI here. So they've fallen behind. Now, what has happened?
Over the last, you know, year. Well, the case got resolved. I don't think, most people I don't think, anticipated the sort of, sort of what happened to them being as light as it was, meaning that it was not sort of draconian, for the types of things that they would need to do, like get rid of Chrome, for example.
And so, you know, you had that plus, you know, you had Gemini three come out. And I think that reset everyone's mindset around. Well, it doesn't look like now that ChatGPT is going to run away with this, it looks like Alphabet is producing great models. And if you use that really as a proxy and, you know, other people say this too, not just me, it seems like the best model right now is the model that's currently out.
And that's something to also think about as an investor. So if they all just kind of keep leapfrogging each other, does that, question, does that mean that they're going to just be commoditized? And really then it's about okay, what can you build on top? What's more efficient? What has a better user interface? What works better with your system?
Those, I think are going to be also important because it doesn't look like at least right now, it doesn't look like when the new model comes out, it looks better than the other models, right? So when Gemini three comes out, you know, lots of talk about that. When Claude Sonnet 4.5 comes out, there's a lot of talk about that.
And then ChatGPT, you know, when they release their next model, you know will that be the topic of discussion saying, okay, well that's slightly better than all these other models. And each version doesn't seem to be blowing away the others, and some are better in certain areas. You talk about Claude Code. People are very excited about that and Sonnet 4.5
Codex is a big push from OpenAI and ChatGPT. So but does that mean that okay, that's going to be more and more commoditized? And that's not even including the open weight models like deepseek coming out of China? You know, that was a year ago, approximately now where, you know, people got super concerned about that.
And we'll talk about Nvidia. And so I think that's something to think about and consider as an investor, certainly for your use cases too, like which one should be using, maybe you should be using some of all of them right now, and keeping yourself familiar. As long as obviously the pricing doesn't get out of control right now, it's still, I think, fairly affordable to use all these models.
And I use all of them. However, back to the investment, you know, proposition for this is something that you should be thinking about. So for Amazon, it's different than Alphabet for that because they don't, Amazon doesn't have their own model. Alphabet does. And we'll get to Amazon here in a second. Apple doesn't have it’s own model as we’ve been talking about. Alphabet does.
Google does. And so those are different propositions and different use cases in a different way forward. Now does it mean that, you know only one of those is a good investment that doesn't necessarily mean that that's the case. But things are different in how you think about these companies as a part of your portfolio. I think you should be thinking about that.
And so quickly, back to Alphabet here. You know. Gemini. Very good. Lots of use cases. Has the ecosystem in Google Workplace. I think it's very important, on the enterprise side, that that's going to be heavily incorporated, as part of a decision for, for businesses to say, well, you know, even if we think ChatGPT next version is, is better or is going to be better, but it works better with Google Docs and Sheets and presentations and Google NotebookLM and all these other things.
So that's really where we're going to go, and that's where we're going to spend our money. And that's super important as an investor to understand that. And so again, not investment advice but Google, if you think about and ask those questions is well positioned there. So if they're models we'll continue to get you know, commoditized. I think that's important to understand.
The other part that also got a lot of publicity, coming out of Google is they build their own TPUs, tensor processing units. And so they're less reliant on Google. Sorry, Google's less reliant on Nvidia for their GPUs. And so that's something important. And they have their own cloud business too. We can obviously spend the whole episode here.
But I think that's important. It positions them well. All right, let's move on here a little bit. Let's talk about Apple. Apple had, you know, good earnings recently. The services business is doing well. And it did well off the earnings. And so I think a lot of people didn't expect the iPhone 17 to do as well as it's done.
You know, it's been a while. You know, the last couple versions, people thought, well, this is the one that's going to do well. And it didn't do well, but this is the one that did. Well, the 17 is doing well. I have a 17 here. I think it's an excellent phone. I think, you know, I upgraded, from a 13, so I was really far back there.
But I think that's the case, too. Also, I think you had a lot of people holding out, not seeing the real big improvements, from one phone to the next to the next series. But now you get 3 or 4 behind, and you're like, well, there does seem to be, you know, some better features, better camera, better storage, better battery.
All these things start to add up and you say, well, I'm going to switch out. So I think that's part of the wave. And that's, you know, part of the wave that I was in, you know, kind of just time to do it, but also the functionality and we'll see how they're going to incorporate AI, They did link up.
We mentioned this on the last episode with Google Now for the AI piece. Now, that's been a big criticism for Apple that they're a laggard here. They have not build their own frontier model. They they're definitely behind. If you use Siri you definitely know it's hard to get Siri to do much of anything. We could test it here but we won't.
So that's something to watch out for. Apple still remains a large position in our portfolio, but I do think at this valuation, and at this market cap, so nearly $4 trillion market cap here in early February, and you're trading, you know, 35 times as a round number for the PE here. And so you're paying up for it.
It is premium, right? It's a premium product. And if you ask people if they're going to switch, still people don't necessarily switch for 10%, 20% increase in the phone. And so that platform, all those billions of users, is important. And I think it's a big moat around the business to use a Buffett term. There is this network effect that they have built, is important and it will continue to be important for the foreseeable future.
How they solve this I do think as an investor, business person, analyst is going to be important. And again, for them, if the models do get commoditized, we're asking that question before maybe that's a net benefit for them because, you know, they didn't build their own. So they then can say, well, our platform, it reigns supreme here. And we're going to use the best model for our customers, and we're going to partner, with the best company to do that.
Right now it looks like, you know, if you remember rewind. They were talking about OpenAI being that platform connection. And you've heard less and less about that. And now you heard the formal announcement recently that they're partnering with Google and Gemini for that. So that should upgrade Siri. We're all waiting for that. Please let us know. Come on Apple, get that out.
Thanks, Tim Cook, for making that happen. All right. Moving on. You know, it would not be an AI episode. So let's get to it next. Without talking about Nvidia. So Nvidia has not done as well as you know, if you rewind last year we had, this big scare from, you know, deep seek and people thought, well, Nvidia is going to be in trouble because this model is way more efficient than, than we thought.
All right. So how is Nvidia doing year to date? So again we're early days here beginning of February in 2026. And it's down 3.32%. All right so let's look at the year over year. All right. Well year over year not bad up 54.62%. Now some of that is because it's off the pullback. But it had a reasonably good year.
And I think a lot of people then said, well you know we're not that concerned about this efficiency for deep seek. It just means actually everybody's going to keep doing more. And maybe we weren't sure about, the type of compute that they were using for it for deep seek when they did those things. And so a little bit less sure about that.
In any case, if even if it was true or 100% true or 100% accurate, well, everyone's just going to keep doing more and buying more things. And so the I think the concern there, you know, dissipated over time. I think that's still kind of out there. If you're using some of these models, if you use deep Sik, the user interface is not the same as, you know, ChatGPT, Grok, Gemini, and Claude.
So maybe they're, you know, people are going to be less likely to use some of those models. So again, market cap 4.39 billion right now for Nvidia. So still doing well. Now some of the things that some of the news around Nvidia, one that's very topical and connected to OpenAI. Another sip out of my GW Investment. Sorry GW
School of Business mug. Some of the news is Nvidia at least this was in the news had talked about this $100 billion investment from Nvidia to OpenAI. Now, Jensen Huang over this, you know, recent time has talked about, well, no, that's not a that's not a given that they're going to get that money. You know, they go step by step.
So people read that, at least in the media, it's being reported that there's less confidence. And he said statements that counter that to, but people are thinking, well, maybe there's just not as much confidence in OpenAI's business model, in OpenAI's path forward, in OpenAI's, you know, competitive position against Google and Amazon and everybody else that's going to try to eat their lunch.
And again, Amazon maybe not direct competitor there, but certainly Google is right now, Anthropic is right now, Grok is right now, and that’s XAI. And so I think that's, interesting, to watch. So what's going to happen here? We'll see. They're also working on opening up China and selling chips. More there.
If you listen to Jensen Wong, that's not in their earnings. That's not in their guidance. And so anything that happens above, there, above here will be upside, for the business. And I think it's important to, to keep watching. And if you're thinking about, you know, who's leading in AI country wise, excuse me, it is the US and it is China.
And you can probably make arguments that one is leading the other, depending on how you're sorting it. Right. They're taking two different approaches. But if you look at the country level and at the company level, but then we can dive into the companies at some point further, and some other episodes to the Chinese ones, that is, we're doing that some of the US companies, and there's plenty of them.
We won't get to all of them today. The approaches so far are different. And so if you look at the US, these are principally close models. And they're principally open weight models in China now. There there's differences in there too. So you know, you're like, oh there's Llama and there's, you know other stuff in China. So it's not it's on all the same.
But again, there seems to be two divergent approaches to how to tackle this technology problem of how to make the models more efficient, how to make the models more powerful, nd all this is is different in both countries. Now, where are the top AI researchers? Where are the top AI models? They're coming out of the US and they're coming out of China.
And so you should be paying attention. Investor, analyst, business person. You should be paying attention to both of these areas and both sets of companies, where you can get information and you have access to information and look at these models, try to use these models if you if you can. And so I encourage you for that. So back to Nvidia.
We'll we'll move on a little bit after that. What's the path forward from here? You know if you think about Nvidia and their business model you know if you think about business, management, price valuation, and balance sheet very quickly. Because this is you know, as Dan Ives, you know, Ives Ives has talked about, he was on the show, godfather of AI Jensen Huang.
It's important to think about them. But as a business this and Jensen Huang says this, this is a pure technology business. They're selling technology to their clients. Excuse me.
They're not necessarily competing with their customers. And some of these other customers, other, you know, companies like Google, for example, would be. Right. So it's a very different situation. And so they're selling the hardware and the compute power, and they're really and Jensen Huang talks about this, a tech company first. And foremost. Excuse me. And that's what they do.
And that's what they provide to customers. And then they're working on the next version. Now other people are getting like the TPUs that are mentioned, their own chips out. And Microsoft, launched Maya 200, talked about it. And I think it's important to watch this and, and see how these chips and their performance. And now I do think it's important to see, you know, the benchmarking, I think right now the TPUs from Google are the only ones that are the internal, chips like the Trainium and the Maya 200s that have independent benchmarking that TPUs do.
And so you got to watch that. You have to see how important that is. But you're also seeing, you know, real data centers being built on trainium chips by Amazon, as an example. And so I do think it's important to watch all of these factors, but it still puts, you know, Nvidia in a good position because right now the demand is super high for all of this.
And they still build the best chips, the Blackwell and the VR rooms that are come out after that. And if they stay ahead on that, you know, maybe that continues to press their network effect. And I think, business person, analyst, investor, you got to think about all of these things and, and really monitor and pay attention.
And I think using these tools, paying attention each day, making sure you're up to speed on what's happening at these companies. And you know, how this company might be moving ahead of this company is very important, but the landscape is changing quickly. There are a bunch of other companies that we can get to, and we'll tackle them in another episode.
But I do think it's important to really pay attention to what's happening in the frontier models. The really on the tech forward, you know, which is Nvidia as an example, we didn't even get the Taiwan Semiconductor whose building up most of these chips on the manufacturing side, the geopolitical risk associated with that. That'll be for another episode.
But these are the hot takes so far on some of these companies. And where we are in the AI game, there'll be more AI to follow. From Market News with Rodney Lake. But that wraps up this episode of Market News with Rodney Lake. Click to subscribe. Thanks for coming back. If you did and if you're new, thanks for being here for the first time.
See you next time. Thank you.