What's Changing with Medicare This Year

0:00Hey, 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? Next question. Do you think AI is a bubble? If yes, how do you time the exit? I do think AI is a bubble. I don't think you could possibly time it. Yeah. Here's why I think it's a bubble. Okay. So we have a senior software engineer. On staff. He's very deep into AI. I mean, he doesn't just do AI for us. He does technology or programming, cashflow, and get all sorts of things. But he's very, like, he builds AI models. Really guy. And he says, hey, Mike, do you want his American models or Chinese models? Why are you asking me this? He goes, well, the Chinese models are like dirt cheap and about just as good. Yeah. Yeah. What? Okay. So we've spent so much money building out data centers and stuff in the

1:04United 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. 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, Americans love American made companies. Yeah. 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. Guess who has more energy infrastructure China. Right. 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 dot com bubble all over again. The problem is we know one knows when that other shoe is going to drop. Let me give you a few examples. So George Soros where the Elychum or Hayden politically is a brilliant investor. I mean, he's the guy that shorted the

2:09British pound in 93 who shorts an entire country's currency. George Soros did it. And he got it right. He shorted the dot com bubble. Lost about 72, no, not 72, 700 million dollars in 1999 dollars. Okay. 700 million. He lost because he was right, but he got the timing wrong. One of the best traders, the one of the goats. Yeah. I mean, he's up there with with Warren Buffett, Ray Daly, like the greats. Someone argue him as one of the greatest. And he shorted it and 700 million was lost. And then he went happened in March. They flipped their position. They say, we can't keep short on this. It's going to keep going up. And they went long. That's buying the market the normal way. And then he lost two billion dollars because it tanked. You can't time this. Julia Robertson tiger or Julian, excuse me, Julian, yeah, Julia Roberts. Julia Robertson tiger

3:16management refused to own tech, completely missed it. And then right when it peaked, finally, got in and it dropped. These are some of the smartest minds on Wall Street and they were getting it wrong. This is why I prefer not to be smart on timing because you can't, but Warren Buffett just sat out in the whole thing. But everyone's different. Yeah. And 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. 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, you still need to be in but I like to have broad diversification. So you don't have to be smart about getting exactly right. And we've already experienced that in our own fund even because when we were managing right when we still manage the money, we we did great. And then we started

4:18noticing 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 when the consensus says this is it's 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. I think we spent way more money on the infrastructure because the cost of running AI models in the future, I think it's going to 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. If we get more efficient, then a lot of these data centers won't be used as much. 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. Okay. But I have no idea if it's this year next year

5:20and five years. Yeah. I'm not going to pretend to know that. Yeah. But I do think maybe it won't be as bad as the dot com crash. AI is everywhere. We're using it. But you know who's not using it? Your past control guy, your electrician, your plumber, right? You know who's not using it? All the small businesses. You know, all they know how to do is open up chat GPT and ask us some questions. They're not really using it. And they accept that you need these data centers and the same the same breath as maybe Morgan Stanley might be using it for research or Citadel or all you some other stuff like pharmaceutical or pharmaceutical companies, the large companies, how they're using it very different. Amazon. Right. Just a different situation. So proceed with caution. And then should we say to we at Kendrick, we're not we're not feeding client data into the AI. Should we say that we're we're your data is safe with Kendrick if you're our clients. Yeah, when we use it for research, market research. Yes. Yes. Right. But yeah, we follow the rules. Yes.

6:22Yeah, you're safe. Okay. So why we have an in house person to make sure we're sick here.