01:00:06.360 — 01:00:40.240 · Speaker 1
Wall Street, digesting the Federal Reserve decision alongside earnings as well as AI CapEx from tech giants including Alphabet and Microsoft. Now, disruptive technology is rapidly expanding beyond just software and chips into hard physical realities from crucial grid infra, as well as defense satellites to advanced sensors for autonomous machines.
Joining us this morning at the New York Stock Exchange to break down where growth investors should deploy capital Post Fed is Stephen McBride, who is chief analyst at Risk Hedge and author of Disruption Investing. Great to have you here. Thank you so much for joining me.
01:00:40.600 — 01:00:42.440 · Speaker 2
Thank you so much. Great to be here with you.
01:00:42.480 — 01:00:58.320 · Speaker 1
Well, we are digesting a lot of headlines, and we all know that AI is competing for attention this morning. But here we are after the fed. We have about 41 days until the December Fed meeting. So what are the implications as we head into the final weeks of this quarter?
01:00:58.760 — 01:01:54.190 · Speaker 2
Listen, I think with the fed, it's one of those things that it always comes around and investors are always focused on it. I look at the very long term picture, and when you look over the long term, really what drives stock prices is earnings and sales growth. That's what we're seeing big time out of the AI trade right now.
One area where I would tell investors to pay attention with the fed is if they raise rates, then valuations should come down. Why that doesn't concern me at the moment is that you actually look at a lot of the AI winners. They're not trading at crazy valuations. Nvidia's trading at 2527 times earnings. People like to compare it to the.com bubble.
Back then the poster child of the.com Cisco was trading at 100 times earnings. So I think it's very different. And I think I'm a big fan of keeping the main thing the main thing. I think right now the main thing is AI earnings. It's clearly what's been driving the market. And I think it will continue to.
01:01:54.230 — 01:02:13.610 · Speaker 1
Yeah, and I'm glad you mentioned that because this morning we are keeping a close eye on alphabet. Especially given the pullback we've seen in share prices. But you mentioned a good point which is valuation. So when it comes to the AI trade breakdown, how you are looking at the ecosystem and the difference between CPUs and GPUs.
01:02:13.810 — 01:03:11.800 · Speaker 2
Great question. So look what has happened. Is Nvidia obviously the poster child of the AI trade for the first couple of years, AI, the chatbots, ChatGPT, they all ran on GPUs, which is Nvidia's chips. Now we're switching to what they call a gigantic AI. It's if you think about the chatbot era of AI, it's AI that told you to do something.
Hey, here's how to set up the website. Here's the nice present to get for your wife in the agenda AI era. The AI just does the thing for you. And without getting into the nitty gritty, all the agent AI stuff runs on CPUs. So that's why we've seen Intel go up a ton. AMD Nvidia is also making CPUs itself. So I would tell investors we often talk about AI as this big monolithic trade.
There's phases of it. So I would tell investors to pay attention to what's changing. And right now the big thing is a genetic AI.
01:03:12.640 — 01:03:26.280 · Speaker 1
And before we get to genetic AI, I understand you're paying attention to bottlenecks when it comes to the hardware supply chain. So for viewers out there who may not be as familiar, can you tell us about metrology and the winners that you're paying attention to?
01:03:26.320 — 01:04:44.540 · Speaker 2
Yes. Of course. So within the AI supply chain, there's obviously a ton going on. We think about the chips as the infrastructure level, but under that there's a ton of money being spent. And what you find when you dig into the lower levels is each little sector. It's a monopoly and oligopoly. You do just one, two, three companies doing it.
What you mentioned all the chips before they can be put into these AI systems, they have to be processed. They have to be tested to make sure they're not faulty. So what you're seeing in the metrology and other sectors generally the semiconductor capital equipment is you're seeing all these new fabrication plants, the chip fabs being built out.
These fabs cost $2,030 billion. And 70% of that is spent on the machines that make the chips and the testing equipment. So this is one thing where for the first couple of years of AI, yes, the demand was strong, but we had the latent capacity in the system not to have to build a new chip fabs. Now TSMC is building fabs in Arizona and elsewhere.
Intel is getting into the game. Mike runs investing hundreds of billions of dollars. So I think investors will be well placed to dig into the supply chain, the bottom of the of their pyramid, so to speak, right now.
01:04:44.580 — 01:04:55.500 · Speaker 1
Yeah. And Steven, while I have you here, I'm going to try to squeeze in autonomous robots and drones alongside a genetic AI. So how are you looking at the space right now?
01:04:55.780 — 01:05:51.410 · Speaker 2
Fascinating question. It's really an extension of the AI trade. You think of how AI is on your computer, right? Well, actually, there's physical AI. There's AI in the real world. I was just in San Francisco, in LA. I get a Waymo robotaxi everywhere. There's nobody in it. You're seeing the drone stuff or the zipline and other companies do autonomous delivery.
Now, of course there's a defense angle to this as well. So I would just say this is something that's been promised for a decade or 15 years now. The technology has finally gotten to a place that you can deploy it in the real world. So you're at a tipping point, so to speak. Waymo is doing, you know, millions of autonomous miles every week now.
Tesla self-driving is finally working. I know people that own Teslas that don't drive anymore. So I would tell investors, pay attention to this space. It it it plays into the AI infrastructure bill because all that stuff needs chips and everything else too.
01:05:51.450 — 01:05:59.370 · Speaker 1
And finally, before I let you go, I do want to ask you about the difference between value traps versus pullbacks. So how are you looking at what we're seeing.
01:05:59.730 — 01:06:43.910 · Speaker 2
Listen I think AI is clearly the megatrend of the decade. In my mind, there is no future scenario where we don't burn and use so many more AI tokens. Every time Nvidia drops, every time micron drops the big AI winners. I'm buying because I just don't see a scenario in the next four years where demand actually drops.
You go. You use the technology, you talk to people at the at the cutting edge. This is the worst AI will ever be. It's only going to get better from here. More productive, more economically valuable. So I think for the for AI, specifically for the businesses that can compound and generate long term profits here in here, those are the buying opportunities through 2030.
01:06:43.950 — 01:06:51.230 · Speaker 1
Well, Stephen, appreciate her time. There are a lot of moving parts here. So I appreciate you breaking down this very dense topic today. Thank you so much.
