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What's Changing with Medicare This Year · How to Retire on Time

• 0:00
  Mike: Hey, thanks for joining. Here's a question I was recently asked on my show, How to Retire On Time. Take a look. What's the next question?
• 0:06
  David: Next question. Do you think AI is a bubble? If yes, how do you time the exit?
• 0:13
  Mike: I do think AI is a bubble. I don't think you can possibly time it. Yeah. Here's why I think it's a bubble. Okay.
• 0:21
  So we have a senior software engineer on staff. He's very deep into AI. And I mean, he doesn't just do AI for us. He does technology or programming, cash flow, capital, all sorts of things. But but he's very like he builds AI models.
• 0:37
  Brilliant guy. And he says, hey, Mike. Do you wanna use American models or Chinese models? I said, why are you asking me this? He goes, well, the Chinese models are like dirt cheap and about just as good.
• 0:50
  Yeah. What? Okay. So we've spent so much money building out data centers and stuff in The United States when you can go to China and get it for dirt cheap and it make it roughly the same. Now we chose to use American models because for security purposes, for a number of reasons, and that's fine.
• 1:11
  But not every company needs to be that secure. Not every company needs to just keep it American based. Some companies might go to China. And if you think, oh, well, know, Americans love American made companies. Yeah.
• 1:23
  Mhmm. Everything's made in China. And pretty soon AI processing is going to be made in China. And guess who can process a lot more data? China.
• 1:31
  Guess who has more energy infrastructure? China.
• 1:34
  David: Right.
• 1:35
  Mike: So when we realize that we have priced all of these AI stocks, these companies based on a price point that's going away very quickly or could go away very quickly, it's the .com bubble all over again. The problem is we no one knows when that other shoe is gonna drop. Let me give you a few examples. So George Soros, whether you like him or hate him politically is a brilliant investor. Mhmm.
• 2:02
  I mean, he's the guy that shorted the British pound 93. Who shorts an entire country's currency? George Soros did. And he got it right. He shorted the .com bubble.
• 2:16
  Lost about 72 no, not 72. $700,000,000 in 1999 dollars.
• 2:24
  David: Okay.
• 2:24
  Mike: 700,000,000. He lost because he was right, but he got the timing wrong. One of the best traders, the the one of the GOATs. Yeah. I mean, he's up there with with Warren Buffett, Ray Dalio, like the greats.
• 2:40
  Someone argue him as one of the greatest. And he shorted it and 700,000,000 was lost. And then you know what happened? In March, they flipped their position. They say, we can't keep shorting this.
• 2:50
  It's gonna keep going up. And they went long. That's buying the the market the normal way. And then he lost $2,000,000,000 because it tanked. Can't time this.
• 3:03
  Julia Robertson, Tiger, or Julian, excuse me. Julian. Yeah. Julia Roberts. Yeah.
• 3:09
  Robertson, Tiger Management refused to own tech. Completely missed it. And then right when it peaked, finally got in and it dropped. These are these are some of the smartest minds on Wall Street's and they were getting it wrong. This is why I prefer not to be smart on timing because you can't.
• 3:32
  But, you know, Warren Buffett just sat out in the whole thing. But, you know, everyone's different. Yeah. I mean, he got a lot of crap for that, by the way. If you go back to the archives, people were ridiculing him saying he was outdated and stupid and didn't get it.
• 3:48
  He was right. But he went through holy hell for a long time. I would rather have a prepared reaction than a risky prediction. And when it seems like there's a bubble, still need to be in. But I like to have broad diversification.
• 4:01
  So you don't have be smart about getting it exactly right. And we've already experienced that in our own fund even because when we were managing, right, when we're still managing money, did great. And then we started noticing that what was working stopped working and it started to become very slippery. And that's when we pull back and go broad, not to try to get it exactly right, but to still be in. And then to have a mechanism of starting to slow down the risk when the markets tell us.
• 4:28
  When the consensus says this is it. Not when we're predicting it is it. It's one of the hardest things to do. That's why we try to follow systems, not sentiment. I do think it's a bubble.
• 4:39
  I think we spent way more money on the infrastructure because the cost of running AI models in the future, I think it's gonna become more efficient. We've already seen that in the Chinese models in the amount of data it takes to run it. We get more efficient. Mhmm. If we get more efficient, then a lot of these data centers won't be used as much.
• 4:58
  And if they're not used as much, then a lot of those deals don't go through. And if those deals don't go through, then those are deals that go bust. And if they go bust, that creates panic in the market. And if that creates panic in the market, it feeds itself. And if it feeds itself, that's when the bubble pops.
• 5:12
  David: Okay.
• 5:13
  Mike: But I have no idea if it's this year, next year, or in five years. Yeah. But I'm not gonna pretend to know that. Yeah. But I do think maybe it won't be as bad as the .com crash.
• 5:21
  AI is everywhere. We're using it. But you know who's not using it? Your pest control guy. Oh.
• 5:27
  Your electrician. Your plumber. Right. You know who's not using it? All the small businesses.
• 5:32
  All they know how to do is open up ChatGPT and ask it some questions. They're not really using it. And the extent that you need these data centers in the same the same breath as maybe Morgan Stanley might be using it for research or Citadel. Or I'll use some other stuff like Like pharmaceutical or yeah. Pharmaceutical companies.
• 5:52
  The large companies and how they're using it very different. Amazon. Right. Just a different situation. So proceed with caution.
• 6:00
  David: And then should we say too, we at Kedrick, we're not feeding client data into the AI. Should we say that we're, your data is safe with Kedrick if you're our client.
• 6:11
  Mike: Well, and we use it for research, market research.
• 6:13
  David: Yes. Yes.
• 6:14
  Mike: Right. But yeah, we we we follow the rules. Yes. Yeah. You're safe.
• 6:17
  David: Okay.
• 6:18
  Mike: That's why we have an in house person to make sure we're secure.