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<v Speaker 1>You're listening to KFI AM sixty on demand.

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<v Speaker 2>Hey, good afternoon. I'm Chris Merril. This is KFI AM

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<v Speaker 2>sixty and we are on demand anytime in the iHeartRadio app.

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<v Speaker 2>When you're on that app, you can click on that

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<v Speaker 2>talkback button. If you have questions, comments, quipts, quotes, criticisms,

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<v Speaker 2>or compliments about the program, feel free to let us

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<v Speaker 2>know the question. For tonight's talk back. I had a

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<v Speaker 2>story about the former inmates of San Quentin going back

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<v Speaker 2>to play an alumni game on their Field of Dreams,

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<v Speaker 2>which is the baseball field inside the prison, and so

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<v Speaker 2>it's former inmates versus current inmates. Current inmates won big lee. Incidentally,

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<v Speaker 2>what is someplace that you would never go back to visit?

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<v Speaker 2>Because if I got out of Saint Quentin, I would

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<v Speaker 2>never even want to drive by the place, and if

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<v Speaker 2>I did, I go nightmares in there. That's it. I

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<v Speaker 2>just never want to go back. Curious about what where

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<v Speaker 2>it is that you've spent time that you would never

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<v Speaker 2>want to go back to again.

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<v Speaker 3>Good afternoon, Chris listens to hear the other him a, California.

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<v Speaker 3>The one place I would not go back to the

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<v Speaker 3>heating village time share presentation. I thought it was cool.

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<v Speaker 3>I said they were giving away like three days, four nights.

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<v Speaker 3>But it felt like I was a hostage and it

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<v Speaker 3>was very hostile. I do not advise that for anyone.

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<v Speaker 3>The worst the one place a time share presentation. Oh

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<v Speaker 3>my god, thinking about it now is give me exact.

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<v Speaker 2>Yeah, me too. My wife's dragged me to a couple

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<v Speaker 2>of those because she's like, oh, they're gonna pay for

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<v Speaker 2>you know. We had two nights at this dump of

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<v Speaker 2>a hotel in Branson, Missouri. Oh, we did it there.

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<v Speaker 2>And then when we first got married actually was here.

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<v Speaker 2>We sat through one of those timeshare presentations because they

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<v Speaker 2>give us tickets to I think Universal Studios or something.

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<v Speaker 2>We were living in northern Arizona at the time, and

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<v Speaker 2>they said, so we had to sit through that, and

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<v Speaker 2>they said, oh, should only take about two hours. You know,

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<v Speaker 2>when it only takes two hours, You know, when the

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<v Speaker 2>presentation only takes two hours is when you when you

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<v Speaker 2>sign up for a time share right away. In both cases,

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<v Speaker 2>we were stuck there for four hours. We were the

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<v Speaker 2>last to leave. And he's right, you feel like a hostage.

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<v Speaker 2>Oh it's the worst. I'm with you. One hundred percent,

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<v Speaker 2>and finally after the last one, my wife is like, Okay,

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<v Speaker 2>We're never going to do that again. It's not worth it.

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<v Speaker 2>I go, was that worth the two hundred dollars that

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<v Speaker 2>we just save? She goes, no, it was not.

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<v Speaker 4>Hey, Chris, someplace I'd never go back to visit probably

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<v Speaker 4>send you Comic Con that place. I mean, it's it's great,

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<v Speaker 4>but after going for you know, so many years, the

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<v Speaker 4>pandemic stopped me and I think I'm done with that place.

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<v Speaker 2>Too crazy. It is crazy. Yeah, you've been to comic Con, Kayla, No, No,

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<v Speaker 2>it's pretty crazy. When you like, you have to be

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<v Speaker 2>in that mood, the same mood you have to be

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<v Speaker 2>in when you go. I'm going to go deal with

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<v Speaker 2>the crazy amount of people at for instance, Universal Studios,

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<v Speaker 2>which they that we went, which was part of our honeymoon.

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<v Speaker 2>It rained like torrents and it was wonderful. Oh so

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<v Speaker 2>few people there. I mean it was buckets. We're riding

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<v Speaker 2>roller coasters in the rain. It was so great. I

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<v Speaker 2>loved it so much. But Comic Con is it's just

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<v Speaker 2>a madhouse. It's like going to Disney on a popular day.

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<v Speaker 2>It's just it's just a madhouse. And you're standing out,

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<v Speaker 2>you're standing outside and you're in line, and uh, it's hot,

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<v Speaker 2>la beautiful setting. You didn't get a better setting than

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<v Speaker 2>the convention center in San Diego. But yeah, it's a lot.

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<v Speaker 2>You just have to be all in for it. If

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<v Speaker 2>you're not all in for Comic Con, it's no good. Uh,

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<v Speaker 2>all right, did you want to do this other one?

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<v Speaker 2>We had one guy that had thoughts on trans athletes.

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<v Speaker 2>We were talking about the trans athletes earlier. For those

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<v Speaker 2>of you joining us, I just don't like the parents

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<v Speaker 2>are screaming at kids. I don't. I don't care for

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<v Speaker 2>it at all. And then we have people that are

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<v Speaker 2>justifying parents screaming at sixteen year olds. Well they deserved it.

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<v Speaker 2>So what are you gonna do? I mean, yeah, yeah,

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<v Speaker 2>freedom of speech, but you also have freedom to not be,

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<v Speaker 2>you know, an adult acting like a child. Process your emotions.

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<v Speaker 2>Let's uh, let's find the words. Probably not scream at children.

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<v Speaker 2>Drums on again, off oup, hang on, wrong one, hang on.

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<v Speaker 5>If I had a daughter, I would suggest that she

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<v Speaker 5>boycott these competitions where there's transgenders. I mean, it's a

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<v Speaker 5>no win for these young women that can't compete with

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<v Speaker 5>the genetics of a boy. I mean, you can put

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<v Speaker 5>lipstick on the boy, but it's not a girl. So

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<v Speaker 5>just saying it's not gonna work, huh. And this is

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<v Speaker 5>gonna end up tragically down the road.

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<v Speaker 2>I think it is. I'm afraid it is gonna end

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<v Speaker 2>up tragically down the road. And I don't think that's

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<v Speaker 2>because you have trans athletes. I think it's because you

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<v Speaker 2>have people bullying. And as far as it's a no win, well,

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<v Speaker 2>the trans girl that competed did get gold in one

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<v Speaker 2>event and shared that gold with two other girls and

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<v Speaker 2>got silver in the in the long jump event, So

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<v Speaker 2>you can't really say it's a no win when she

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<v Speaker 2>didn't beat them all. So I don't know, man, I wouldn't.

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<v Speaker 2>I wouldn't deprive my daughter of the opportunity to go

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<v Speaker 2>win at the state track and field because of my

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<v Speaker 2>own political leanings. I just wouldn't do it. I wouldn't. Yeah,

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<v Speaker 2>I mean, you do what you want, it's your kid,

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<v Speaker 2>But I wouldn't deprive my kid. How about this? Did

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<v Speaker 2>you happen to see that there was a story. I'm

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<v Speaker 2>shifting gears here. I don't want to talk about it anymore.

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<v Speaker 2>Did you have to see the story about Elon Musk.

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<v Speaker 2>They say that he was doing drugs during the campaign.

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<v Speaker 2>What New York Times with a mind bending article as

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<v Speaker 2>Elon must became one of Donald Trump's closest allies last year,

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<v Speaker 2>leading raucus rallies and donating two hundred and seventy five

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<v Speaker 2>million to help him win the presidency. He was also

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<v Speaker 2>using drugs far more intensely than previously known. According to

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<v Speaker 2>people familiar with his activities, The consumption went well beyond

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<v Speaker 2>occasional use. He told people he was taking so much

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<v Speaker 2>ketamine that it was affecting his bladder, which is a

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<v Speaker 2>known effect of chronic use. He took ecstasy and psychedelic mushrooms,

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<v Speaker 2>and he traveled with a daily medication box that held

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<v Speaker 2>about twenty pills, including ones with the markings of the

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<v Speaker 2>stimulant adderall according to a photo of the box and

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<v Speaker 2>people who have seen it. I don't know about you, guys,

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<v Speaker 2>I am stunned. I'm shocked that the guy who would

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<v Speaker 2>wear a hat on top of the hat and get

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<v Speaker 2>on stage and jump and scream and carry on the

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<v Speaker 2>way that he did would have any history of drug use.

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<v Speaker 2>That seemed like perfectly normal behavior to me. So I

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<v Speaker 2>just that is uh, that is wild that he was

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<v Speaker 2>using a lot of drugs. I assume we're all on drugs.

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<v Speaker 2>I mean, isn't there a point where you see people

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<v Speaker 2>and you go, okay, well there's some drug use going

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<v Speaker 2>on there, and he's admitted to it. Before I'd do

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<v Speaker 2>profen always you can just oh yeah, right, yeah, I know, right, Like, hey,

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<v Speaker 2>here's a fun drug I just started this week, saw Palmetto. Yeah, yep,

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<v Speaker 2>it's supposed to help with prostate function. So I also

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<v Speaker 2>carry around a little pill box with about twenty pills

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<v Speaker 2>a day. Yeah, saw Palmetto. I've got my multi vitamin,

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<v Speaker 2>I've got my blood pressure medication I got Yeah. Yeah,

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<v Speaker 2>I guess I'm like Elon Musk minus the ketamine and

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<v Speaker 2>adderall and the jumping on stage with a chainsaw. Yeah,

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<v Speaker 2>but otherwise exactly the same. The thing with Musk, though,

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<v Speaker 2>is that when he did all that stuff, we didn't

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<v Speaker 2>immediately go what is he on? Because he's an eccentric

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<v Speaker 2>person to start with, you know, so it's like, well,

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<v Speaker 2>Elon Musk is being crazy, but that's what makes him

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<v Speaker 2>a genius, and you go, nam Musk, Elon Musk is

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<v Speaker 2>an eccentric, and he's had some really genius things. Don't

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<v Speaker 2>get me wrong, I don't want to take away from

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<v Speaker 2>anything that he's accomplished. But the behavior that we saw

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<v Speaker 2>was that was a little beyond just eccentric. That was

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<v Speaker 2>just that was drugs. That was straight up drugs. Do

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<v Speaker 2>you buy the black eye?

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<v Speaker 6>Oh?

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<v Speaker 2>That he told his son to hit him. I was

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<v Speaker 2>playing with my son. I told him to punch me,

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<v Speaker 2>and they hit a lot harder than you think. Uh.

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<v Speaker 2>I don't know who tells their kid to punch him.

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<v Speaker 2>That's weird to me. Also, I'm not surprised though that

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<v Speaker 2>if the black eye. It wouldn't surprise me if the

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<v Speaker 2>black eye did come from the kid. And I say

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<v Speaker 2>that because the kid is a bit undisciplined as well.

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<v Speaker 2>He's a four year old who musk brought to the

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<v Speaker 2>Oval office during a press conference and was running around

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<v Speaker 2>and telling the president pretty horrible things during live television.

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<v Speaker 2>You're an e fn idiot. A four year old is

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<v Speaker 2>telling the President of the United States, the commander of

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<v Speaker 2>the free world, you're an fing idiot. So yeah, it

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<v Speaker 2>would not surprise me if the kid has discipline issues

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<v Speaker 2>and would punch dad in the eye. That does not

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<v Speaker 2>surprise me at all. That's what Bratts do. You know,

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<v Speaker 2>they misbehave and if they're not corrected, then they'll continue

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<v Speaker 2>to misbehave. So yeah, that part doesn't surprise me at all.

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<v Speaker 2>So Trump was asked about Elon Musk in this press

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<v Speaker 2>conference this week, because you know, there was the kind

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<v Speaker 2>of the falling out, and then Musk said, Wow, I've

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<v Speaker 2>not really saved the country any money, but I sure

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<v Speaker 2>have saved all of my investors a lot of money.

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<v Speaker 2>They just haven't made squad.

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<v Speaker 7>What started as a political bromance is now wrapping up

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<v Speaker 7>with a little less love. Elon Musk's one hundred and

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<v Speaker 7>thirty days as the head of the Department of Government

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<v Speaker 7>Efficiency came to an end today, well short of his promises,

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<v Speaker 7>and just days after he criticized President Trump's Big Beautiful Bill.

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<v Speaker 7>Trump and Musk sharing the spotlight today at the White

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<v Speaker 7>House as Musk ends his role as a special government employee.

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<v Speaker 2>But while okay, then they get on more stuff blah

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<v Speaker 2>blah blah, and then Trump gave him a gold key

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<v Speaker 2>and then he said it's great, and uh, we're gonna

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<v Speaker 2>save a bunch of money, and YadA YadA, YadA. Does

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<v Speaker 2>this strike you as odd though the times that they've

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<v Speaker 2>had the joint press conferences. In the Oval Office, Trump

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<v Speaker 2>is set at the resolute desk, and Musk has stood by,

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<v Speaker 2>sometimes with this kid crawling all over the president, sometimes

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<v Speaker 2>just nearby, wearing his T shirt because of the respect

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<v Speaker 2>for the office. I know Trump is sitting, and of

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<v Speaker 2>course Musk wearing a baseball capital time. I know that

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<v Speaker 2>Trump is sitting behind the desk, and I think he's saying,

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<v Speaker 2>I'm gonna sit behind the desk and look presidential. But

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<v Speaker 2>there's just something about the tableau of it where Trump is.

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<v Speaker 2>I mean, he likes to lean right, he likes to slouch.

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<v Speaker 2>We've seen that. Everywhere he goes he slouches, and which

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<v Speaker 2>is fine. He can slouch ow you want. I'm slouching

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<v Speaker 2>as we speak. Just seem really odd. All right, Tariff's on,

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<v Speaker 2>Tariff's off, and uh check on traffic. That is next.

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<v Speaker 2>Chris Merril kf I AM six forty live everywhere in

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<v Speaker 2>the iHeartRadio app.

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<v Speaker 1>You're listening to KFI AM six forty on demand.

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<v Speaker 2>KFI AM six forty more stimulating talk. Hey Broll is

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<v Speaker 2>Lucy there in the traffic center.

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<v Speaker 6>Yeah, I'm here.

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<v Speaker 2>Hey, Lucy, heyes, from the show. I'm sorry that you

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<v Speaker 2>had to walk into this circus.

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<v Speaker 6>Oh no, no, no, it's fantastic. You're you're so great.

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<v Speaker 2>Oh you're You're wonderful to say that, but I I

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<v Speaker 2>hate to say the obvious here, Lucy, but you don't

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<v Speaker 2>sound like you don't sound like you're from here. You

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<v Speaker 2>sound like you're from somewhere east, like Vegas or Omaha,

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<v Speaker 2>or maybe Saint.

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<v Speaker 6>Louis or North Carolina. Yeah, yeah, yeah, I know I

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<v Speaker 6>get that a lot. Yeah, from originally from England originally,

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<v Speaker 6>but I have been in this wonderful country for thirty years,

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<v Speaker 6>I think. So I came here on my own. It

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<v Speaker 6>was just on a whim. I grew up watching American shows,

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<v Speaker 6>you know, like I don't know, like The Rockford Files.

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<v Speaker 2>And that Lock.

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<v Speaker 6>And Stopped and I was like, wow, that's really cool.

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<v Speaker 6>So you know, it's like one of those things where

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<v Speaker 6>you know, it was like the soft power of Hollywood.

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<v Speaker 6>So it lured me and the old movies, you know,

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<v Speaker 6>with Kerry Grant and I mean, I know he was

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<v Speaker 6>from my neck of the woods as well, but you know,

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<v Speaker 6>I grew up, so I grew up with the mystique

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<v Speaker 6>of Hollywood, with with America's greatness and with its energy

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<v Speaker 6>and dynamism, and it still has it. So here I am.

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<v Speaker 6>I came to the East Coast and then came over

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<v Speaker 6>to California and did several things on the way.

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<v Speaker 2>How long were you on the East Coast?

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<v Speaker 6>Twelve years?

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<v Speaker 2>Oh? Okay? And then the law. Yeah.

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<v Speaker 6>Well, I lived in Boston and I love Boston still

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<v Speaker 6>and I have so many good friends. But you know,

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<v Speaker 6>the Bostonians are tough. They're a tough bunch. So but

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<v Speaker 6>but you know what, you get them on your side,

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<v Speaker 6>and they're on your side forever. That's not yes.

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<v Speaker 2>So when I was interviewing for my first job in

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<v Speaker 2>California in San Diego, I had a station in Boston

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<v Speaker 2>reach out at the same time, and so then I

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<v Speaker 2>was thinking, in Boston, of course, is a larger radio

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<v Speaker 2>market than San Diego. So I was thinking, well, this

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<v Speaker 2>is a bigger market. But I thought, do I want

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<v Speaker 2>to have the bigger market where everybody hates me, or

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<v Speaker 2>do I want to go to San Diego where the

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<v Speaker 2>weather is amazing and everybody's from somewhere else, you know,

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<v Speaker 2>So I chose San Diego.

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<v Speaker 6>Yeah, and you're right, because every Bostonians hate everybody. They

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<v Speaker 6>hated me at first. Oh yeah, I got death threats.

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<v Speaker 6>I did. Oh you're kidding, No, no I did, I did.

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<v Speaker 6>I mean it didn't help the English Irish issue, you know,

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<v Speaker 6>in the nineties and so, but that was resolved and

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<v Speaker 6>then everybody got used to me. It's like, oh, you're okay, You're.

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<v Speaker 2>Yeah, you just got you got to do your time,

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<v Speaker 2>and then you uh yeah. And then that's what when

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<v Speaker 2>you came to California, What are the hardest names? Because

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<v Speaker 2>you I mean I was listening to your traffic and

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<v Speaker 2>and like you said, you've been here forever, so I

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<v Speaker 2>mean obviously you know all the places. What were the

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<v Speaker 2>hardest ones when you came here and had to learn,

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<v Speaker 2>you know, because every every area has its own unique pronunciation.

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<v Speaker 2>What are some of them that were difficult for you?

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<v Speaker 6>It does koanga, that's crazy, that word cowenga pulva. I mean,

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<v Speaker 6>I've heard all sorts of versions of that. I've heard,

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<v Speaker 6>you know, let's see. You know, I'm just I'm looking

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<v Speaker 6>at my map right now. I mean, just the Spanish

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<v Speaker 6>names in general. I mean I even had a problem

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<v Speaker 6>saying San Diego. It didn't roll off the tongue.

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<v Speaker 2>Did you say it like ron Burgundy, San Diiago.

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<v Speaker 6>Yes, something like, but it was you know, but everyone

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<v Speaker 6>was so kind when I came here, they were so kind.

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<v Speaker 6>They held me and they coached me. He's like, no, no,

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<v Speaker 6>don't say that, don't say that. But then you have

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<v Speaker 6>other words, like people say them differently. No galas no

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<v Speaker 6>galas street on the follow five. So some people say

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<v Speaker 6>nigoles and some people say no galas. I don't know

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<v Speaker 6>which one it is.

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<v Speaker 2>Some of those places can get away with either way, right,

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<v Speaker 2>you can. You can say it either way. Uh, it's

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<v Speaker 2>it's sort of like Colorado, Colorado, you know, or.

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<v Speaker 6>Oh, Nevada or Nevada.

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<v Speaker 2>I was just gonna say that, yeah, because I've got

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<v Speaker 2>the president. Trump said that and then he he was

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<v Speaker 2>there and I've got this audio. This is great, and

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<v Speaker 2>he started started telling people they were saying it wrong.

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<v Speaker 8>Nevada Novada, right, And you know what I said.

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<v Speaker 1>You know what I said.

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<v Speaker 5>I said when I came out here, I said, nobody

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<v Speaker 5>says it the other way.

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<v Speaker 2>It has to be Nevada.

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<v Speaker 9>No, no, if you don't say it correctly.

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<v Speaker 2>And it didn't happen to me, But it happened to

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<v Speaker 2>a friend of mine who was killed. That's true, though

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<v Speaker 2>they actually found his body in Lake Mead when the

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<v Speaker 2>levels went down.

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<v Speaker 6>It doesn't surprise you, and it was it.

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<v Speaker 2>Was funny because they had they found like four bodies

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<v Speaker 2>out there, and three of them were people who actually

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<v Speaker 2>said Nevada instead of Nevadada.

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<v Speaker 6>But here's the thing is a lot of people won't

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<v Speaker 6>allow you to say Nevada. I've had really disapproving looks

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<v Speaker 6>Nevada story or my.

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<v Speaker 2>My father likes to say, uh, Oregon, oh yes, yeah, yeah,

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<v Speaker 2>don't say Oregon.

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<v Speaker 6>Yes, the Oregonians don't like that at all, exactly.

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<v Speaker 2>I've corrected him on that. And who cares, I said,

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<v Speaker 2>people from Oregon care. Yeah. Yeah, So that's funny. Well,

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<v Speaker 2>I'm glad you're in the show, Lucy. This is great.

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<v Speaker 2>It's good to hear from you.

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<v Speaker 6>Oh it's wonderful. I love listening and I'm chuckling away

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<v Speaker 6>and just I just want you to know that.

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<v Speaker 2>Oh you're brilliant. Thank you so much, all right, god

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<v Speaker 2>bless all right, very good. Well, check my schedule and

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<v Speaker 2>see if there's time that Lucy and I get together

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<v Speaker 2>for some bangers and mash Yes, yes, love that all right?

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<v Speaker 2>So I don't know. Let me think here, Kayla, do

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<v Speaker 2>we have I don't want to get into the tariff stuff?

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<v Speaker 2>Do we care about the tariffs right now? You want

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<v Speaker 2>me to just go to break early and then spend

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<v Speaker 2>more time talking about AI. I got a lot of

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<v Speaker 2>stuff on AI this week, so many AI things, So Kilea,

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<v Speaker 2>let's just do that, all right, Let's just go to

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<v Speaker 2>Are you guys cool with that? Can I get a yes?

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<v Speaker 10>No?

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<v Speaker 2>Yes?

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<v Speaker 8>No?

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<v Speaker 2>Right? All right, good, thank you. That's all I needed,

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<v Speaker 2>just one because I have nothing else to say, and

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<v Speaker 2>I don't want to talk about tariffs because they bore me.

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<v Speaker 2>It's AI AI AI AI I I Next Chris Merril

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<v Speaker 2>kf I AM six forty. We're live everywhere in the

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<v Speaker 2>iHeartRadio app.

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<v Speaker 1>You're listening to KFI AM six forty on demand, thy Amy.

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<v Speaker 2>Chris Merril CAFI AM six forty more stimulating talk talkback question. Today,

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<v Speaker 2>we had a story about former inmates at SAM that

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<v Speaker 2>went back to play an alumni baseball game against current inmates,

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<v Speaker 2>and I thought, if I got out of sand Quentin,

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<v Speaker 2>I ain't going back, no way. So what is someplace

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<v Speaker 2>that you would never go back to visit. We've had

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<v Speaker 2>a few on here on One guy said he would

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<v Speaker 2>never go back to Flint, Michigan. I blame him. Another

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<v Speaker 2>dude said he would never go back to a timeshare presentation. Amen,

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<v Speaker 2>A men, my friend, So what is someplace you would

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<v Speaker 2>never go back to visit? If you're on the iHeartRadio app,

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<v Speaker 2>just leak on that talk back and let us know

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<v Speaker 2>what is someplace he would never go back to visit.

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<v Speaker 2>And then obviously why why would you not go back there?

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<v Speaker 2>There was an interesting story that popped this week and

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<v Speaker 2>an interview was done with the the CEO of Anthropic,

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<v Speaker 2>which is one of the AI companies that's out there,

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<v Speaker 2>and he's basically warning a bunch of white collar jobs

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<v Speaker 2>are going to go away. And I was reading and

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<v Speaker 2>he was talking with an Axios reporter. Axios has continue

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<v Speaker 2>to follow up on a lot of these AI stories

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<v Speaker 2>this week. They've really been the forefront of reporting on

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<v Speaker 2>the AI here of late. And they said the US

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<v Speaker 2>government needs AI expertise and dominance to beat China in

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<v Speaker 2>the next big technological and geopolitical shift, but they can't

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<v Speaker 2>pull it off without the help of Microsoft, Google, Open Ai, Nvidia,

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<v Speaker 2>and others. And so we're seeing emerging of Washington and

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<v Speaker 2>Silicon Valley. They say driven by necessity and fierce urgency.

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<v Speaker 2>So much so then that they they use the phrase

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<v Speaker 2>codependent superstructure. The government and these tech companies have formed

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<v Speaker 2>a codependent superstructure in the race to dominate AI, and

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<v Speaker 2>that strikes me as really odd. I know that we

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<v Speaker 2>have government that supports certain businesses, and it doesn't matter

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<v Speaker 2>if you're a Republican or a Democrat. It happens. And

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<v Speaker 2>then when the Democrats do what, the Republicans say that

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<v Speaker 2>we shouldn't be using government to pick and choose winners.

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<v Speaker 2>And then when the Republicans do it, then the Democrats say,

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<v Speaker 2>I can't believe that the Republicans would do this to

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<v Speaker 2>pick and choose winners. And of course there's always winners

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<v Speaker 2>that benefit typically that party, whether that's labor unions or

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<v Speaker 2>whether that's big business and low taxes, blah blah blah. Right,

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<v Speaker 2>We've seen this play out time and time again, but

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<v Speaker 2>we are seeing a lot of subsidies going towards some

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<v Speaker 2>of these companies or you could say investments. Axos points

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<v Speaker 2>out that the White House has cultivated a deeper relationship

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<v Speaker 2>with America's AI giants, championing a five hundred billion dollar

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<v Speaker 2>stargate infrastructure led by Open Ai, Oracle soft Bank, which

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<v Speaker 2>is out of Japan, and MGX from the United Arab Emirates,

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<v Speaker 2>all of these different things to try to give us

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<v Speaker 2>a leg up on the AI race. And yet I

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<v Speaker 2>think to myself, if we had, if we had the

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<v Speaker 2>government that is trying to push forward this the efforts

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<v Speaker 2>in AI in a public private partnership that benefits the

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<v Speaker 2>private sector, how is that different than what China does.

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<v Speaker 2>China is a capitalistic, communistic government, right, I mean it's

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<v Speaker 2>communist capitalism. Communist party does this. They invest and they

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<v Speaker 2>work with the companies and then the companies make money.

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<v Speaker 2>But in this case, the Chinese government gets some of

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<v Speaker 2>the proceeds. That's really the difference is that if the

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<v Speaker 2>company in China that's working with the government, let's say TikTok.

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<v Speaker 2>If TikTok makes a bunch of money because of some

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<v Speaker 2>of the investments that the Chinese government has made, then

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<v Speaker 2>the Chinese government says, cool, that was our investment. We

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<v Speaker 2>want something out of it. Right, in the US, the

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<v Speaker 2>government makes an investment and then the company takes off,

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<v Speaker 2>but the government doesn't really recoup that. You have subsidies

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<v Speaker 2>or we give tax breaks, we give we give certain advantages,

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<v Speaker 2>tax abatements, call them right to these companies because the

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<v Speaker 2>companies need to help. We want to, we want to,

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<v Speaker 2>we want to win this battle. And then you go, okay, well,

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<v Speaker 2>what is the government get out of it? And they

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<v Speaker 2>know nothing, but the CEOs will, and then the CEOs go,

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<v Speaker 2>we built that, right, It's been a big political argument.

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<v Speaker 2>You didn't build that. Oh, yes I did. I built

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<v Speaker 2>this from my hands, you know, with my bare hands.

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<v Speaker 2>Like no, literally, the government, the government gave you a

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<v Speaker 2>break so you could build it. Oh, I built this

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<v Speaker 2>from scratch all by myself. I played by the rules.

414
00:22:37.480 --> 00:22:40.359
<v Speaker 2>You did play by the rules. But the rules were

415
00:22:40.400 --> 00:22:43.119
<v Speaker 2>definitely in your favor. Because if I go out there

416
00:22:43.160 --> 00:22:44.960
<v Speaker 2>and I say I want to start a business, I

417
00:22:45.000 --> 00:22:46.480
<v Speaker 2>think the government should give me a tax break. The

418
00:22:46.519 --> 00:22:49.559
<v Speaker 2>government goes, well, how big is your business. The bigger

419
00:22:49.599 --> 00:22:52.599
<v Speaker 2>the business, the more likely you are to have some

420
00:22:52.720 --> 00:22:54.880
<v Speaker 2>help from the government. It's just the way it works.

421
00:22:55.480 --> 00:22:56.960
<v Speaker 2>But what do you owe back to the government. The

422
00:22:57.079 --> 00:22:59.200
<v Speaker 2>smaller your business, the more you're gonna owe the government.

423
00:23:00.319 --> 00:23:02.039
<v Speaker 2>I don't get that tax break because my business is

424
00:23:02.079 --> 00:23:04.319
<v Speaker 2>too small. Small business in the backbone of America. It

425
00:23:04.400 --> 00:23:05.920
<v Speaker 2>pays all of our taxes so that we can give

426
00:23:05.920 --> 00:23:07.680
<v Speaker 2>those taxes to the big companies that really are going

427
00:23:07.759 --> 00:23:10.960
<v Speaker 2>to do great things. Right, that's how our system works.

428
00:23:11.359 --> 00:23:14.119
<v Speaker 2>I find it to be flawed. Not a big fan

429
00:23:14.240 --> 00:23:17.119
<v Speaker 2>of it. I understand how we got here. I'm just

430
00:23:17.200 --> 00:23:20.400
<v Speaker 2>not a big fan of that. And moreover, I'm even

431
00:23:20.480 --> 00:23:22.359
<v Speaker 2>less of a fan of the dishonesty around it. Like, no,

432
00:23:22.440 --> 00:23:24.759
<v Speaker 2>we're not, Yeah you are. Just call it what it is.

433
00:23:25.680 --> 00:23:28.000
<v Speaker 2>You are. So either we're all on a level playing

434
00:23:28.039 --> 00:23:29.640
<v Speaker 2>field and we're all gonna pay the same taxes, or

435
00:23:29.680 --> 00:23:32.039
<v Speaker 2>we're not at a level playing field. Uh, and just

436
00:23:32.079 --> 00:23:35.680
<v Speaker 2>admit it. That's what it is. So what this CEO

437
00:23:35.960 --> 00:23:43.880
<v Speaker 2>of Anthropics said is basically, quit sugarcoating what's coming. Mass

438
00:23:43.960 --> 00:23:48.519
<v Speaker 2>elimination of jobs across technology, finance, law, consulting, and other

439
00:23:48.599 --> 00:23:54.079
<v Speaker 2>white collar professions, especially entry level gigs. Entry level white

440
00:23:54.160 --> 00:23:58.240
<v Speaker 2>collar roll. That's what you need. Entry level white collar

441
00:24:00.079 --> 00:24:02.599
<v Speaker 2>that's a cush job until the cuts come and then

442
00:24:02.640 --> 00:24:05.079
<v Speaker 2>you're the first one out. But let's just call it

443
00:24:06.079 --> 00:24:09.920
<v Speaker 2>lower to middle Management. This is from Anderson Cooper talked

444
00:24:09.960 --> 00:24:12.640
<v Speaker 2>with The Anthropics CEO and CNN Dario.

445
00:24:12.799 --> 00:24:15.839
<v Speaker 11>You've said that AI could wipe out half of all

446
00:24:16.039 --> 00:24:20.160
<v Speaker 11>entry level white collar jobs and spike unemployment to ten

447
00:24:20.400 --> 00:24:21.319
<v Speaker 11>to twenty percent.

448
00:24:21.640 --> 00:24:23.799
<v Speaker 1>How soon might that happen?

449
00:24:24.119 --> 00:24:25.880
<v Speaker 12>Just to back up a little bit, you know, I've

450
00:24:25.920 --> 00:24:29.359
<v Speaker 12>been building AI for over a decade, and I think

451
00:24:29.440 --> 00:24:31.839
<v Speaker 12>maybe the most salient feature of the technology and what

452
00:24:32.000 --> 00:24:35.240
<v Speaker 12>is driving all of this is how fast the technology

453
00:24:35.279 --> 00:24:38.119
<v Speaker 12>is getting better. A couple of years ago, you could

454
00:24:38.160 --> 00:24:40.279
<v Speaker 12>say that AI models were maybe as good as a

455
00:24:40.319 --> 00:24:42.839
<v Speaker 12>smart high school student. I would say that now they're

456
00:24:42.880 --> 00:24:45.400
<v Speaker 12>as good as a smart college student and sort of

457
00:24:45.480 --> 00:24:49.240
<v Speaker 12>reaching past that. I really worry, particularly at the entry

458
00:24:49.319 --> 00:24:53.079
<v Speaker 12>level that the AI models are are, you know, very.

459
00:24:53.039 --> 00:24:55.640
<v Speaker 11>Much at the center of what an entry level human

460
00:24:55.720 --> 00:25:00.599
<v Speaker 11>worker would do. The problem is what is entry level

461
00:25:00.720 --> 00:25:05.039
<v Speaker 11>human worker? Because I can tell you this, I'm not impressed.

462
00:25:05.720 --> 00:25:07.960
<v Speaker 11>I'm not impressed by AI yet. I mean, I'm impressed

463
00:25:07.960 --> 00:25:10.519
<v Speaker 11>by where it's going. I'm impressed by the concept. I'm

464
00:25:10.559 --> 00:25:13.759
<v Speaker 11>impressed by the proof of concept. I'm impressed by some

465
00:25:13.920 --> 00:25:16.559
<v Speaker 11>of the early functionings. I'm not impressed with a lot

466
00:25:16.599 --> 00:25:22.079
<v Speaker 11>of it because hallucinations still run. Wild hallucinations are still

467
00:25:22.119 --> 00:25:28.119
<v Speaker 11>a big issue. Not only that, but in fact, I

468
00:25:28.240 --> 00:25:32.480
<v Speaker 11>was just seeing this today. I googled something today so

469
00:25:32.720 --> 00:25:34.839
<v Speaker 11>mad they just couldn't find it.

470
00:25:34.880 --> 00:25:37.640
<v Speaker 2>I was looking for. My son was talking about free

471
00:25:37.680 --> 00:25:40.559
<v Speaker 2>range chicken. This is just completely random here. My son

472
00:25:40.680 --> 00:25:44.440
<v Speaker 2>was talking about free range chickens versus cage free versus

473
00:25:44.519 --> 00:25:49.680
<v Speaker 2>industrial farm poultry. Because he's buying eggs and he bought

474
00:25:49.680 --> 00:25:54.279
<v Speaker 2>the cheapestakes. And he says, oh, this says that they

475
00:25:54.279 --> 00:25:56.559
<v Speaker 2>are cage free. What does that mean? They have one

476
00:25:56.599 --> 00:25:59.480
<v Speaker 2>foot by two feet instead of they I don't know

477
00:25:59.799 --> 00:26:02.119
<v Speaker 2>this disclosure so that they could roam around the barn.

478
00:26:02.559 --> 00:26:04.839
<v Speaker 2>And he said, there're still not enough room for him, right,

479
00:26:04.880 --> 00:26:08.119
<v Speaker 2>So you just saying this, and I thought, I've seen

480
00:26:08.160 --> 00:26:12.920
<v Speaker 2>the stat before where chickens and cages at these egg farms,

481
00:26:13.319 --> 00:26:18.839
<v Speaker 2>they have like a half foot one half square foot

482
00:26:19.519 --> 00:26:21.519
<v Speaker 2>that's where they live their entire lives. Very small. It's

483
00:26:21.519 --> 00:26:23.200
<v Speaker 2>about the size of an iPad. They live their entire

484
00:26:23.279 --> 00:26:25.039
<v Speaker 2>lives in this area, about the size of an iPad.

485
00:26:25.960 --> 00:26:27.920
<v Speaker 2>And and so I was looking that up. I was

486
00:26:27.960 --> 00:26:34.480
<v Speaker 2>trying to find the exact area, and I kept well,

487
00:26:34.519 --> 00:26:37.480
<v Speaker 2>first of all, I binged it because Cayla, you know big.

488
00:26:38.680 --> 00:26:41.359
<v Speaker 2>And then Bing wasn't giving me the answer I wanted

489
00:26:41.359 --> 00:26:43.640
<v Speaker 2>because I said, how big? I put in the question

490
00:26:43.759 --> 00:26:47.519
<v Speaker 2>something like how large a space do hens have in

491
00:26:47.599 --> 00:26:50.640
<v Speaker 2>an industrial poultry farm? And it said, if you're building

492
00:26:50.680 --> 00:26:52.720
<v Speaker 2>your chicken coop, you should offer this much? And I go,

493
00:26:52.799 --> 00:26:55.039
<v Speaker 2>that's not what I wanted, and it said and then

494
00:26:55.039 --> 00:26:56.799
<v Speaker 2>it gave me a bunch of different instructions on how

495
00:26:56.839 --> 00:26:59.000
<v Speaker 2>to build a chicken coop. So I said, forget this,

496
00:26:59.119 --> 00:27:01.200
<v Speaker 2>and I went over to Google. I, you know, like

497
00:27:01.279 --> 00:27:03.279
<v Speaker 2>what the kids use and uh. And I went over

498
00:27:03.279 --> 00:27:06.960
<v Speaker 2>to Google and Google gave me the same stuff. And

499
00:27:07.160 --> 00:27:09.839
<v Speaker 2>then you know how they all respond now with with

500
00:27:09.960 --> 00:27:13.200
<v Speaker 2>the AI response for Bing, its co pilot for Google

501
00:27:13.279 --> 00:27:17.799
<v Speaker 2>is Gemini. The Gemini response told me the same stuff.

502
00:27:17.839 --> 00:27:21.559
<v Speaker 2>It was wrong, And then it was interesting, it comes

503
00:27:21.640 --> 00:27:26.119
<v Speaker 2>with a disclaimer and it said AI responses may include mistakes.

504
00:27:27.480 --> 00:27:30.160
<v Speaker 2>They had to add a disclaimer. So when you when

505
00:27:30.200 --> 00:27:32.880
<v Speaker 2>you hear uh is it a moodi is how you

506
00:27:32.920 --> 00:27:37.119
<v Speaker 2>say his name m and a a mo dei darrio

507
00:27:37.640 --> 00:27:40.480
<v Speaker 2>is his name? The guy from Anthropic when he says

508
00:27:40.720 --> 00:27:44.519
<v Speaker 2>that they're they're at about entry level job positions. I

509
00:27:44.599 --> 00:27:48.039
<v Speaker 2>think to myself, what are the expectations of a human

510
00:27:48.200 --> 00:27:51.559
<v Speaker 2>entry level job position? Because if the expectation is it's

511
00:27:51.640 --> 00:27:57.160
<v Speaker 2>going to be filled with mistakes, hallucinations and false attributions, yeah,

512
00:27:57.279 --> 00:28:02.000
<v Speaker 2>it's there. But if the expect is that the person

513
00:28:02.079 --> 00:28:05.319
<v Speaker 2>is going to do their job right, then the large

514
00:28:05.400 --> 00:28:08.680
<v Speaker 2>language learning models are not there. They're just not there yet.

515
00:28:09.359 --> 00:28:11.359
<v Speaker 2>And I know I'm only talking about the language learning

516
00:28:11.400 --> 00:28:16.319
<v Speaker 2>models and not the other AI, but it's not there yet,

517
00:28:17.440 --> 00:28:20.039
<v Speaker 2>all right, he continues on, and so it's hard.

518
00:28:19.880 --> 00:28:23.000
<v Speaker 12>To estimate, you know, exactly what the impact would be,

519
00:28:23.119 --> 00:28:26.359
<v Speaker 12>and you know that there's always this question of adaptation,

520
00:28:27.039 --> 00:28:29.920
<v Speaker 12>and you know, these these technology changes have happened before.

521
00:28:30.039 --> 00:28:31.880
<v Speaker 9>But I think what is striking to me about that

522
00:28:32.279 --> 00:28:36.000
<v Speaker 9>this this AI boom is that it's bigger, and it's broader,

523
00:28:36.039 --> 00:28:38.880
<v Speaker 9>and it's moving faster than anything has before, and so

524
00:28:39.319 --> 00:28:42.559
<v Speaker 9>compared to previous technology changes, I'm a little bit more

525
00:28:42.640 --> 00:28:45.319
<v Speaker 9>worried about the labor impact simply because it's happening so

526
00:28:45.599 --> 00:28:48.920
<v Speaker 9>fast that yes, people will adapt, but they they may

527
00:28:48.960 --> 00:28:51.559
<v Speaker 9>not adapt fast enough, and so they're they're you know,

528
00:28:51.599 --> 00:28:53.400
<v Speaker 9>there may be an adjustment period.

529
00:28:53.599 --> 00:28:56.319
<v Speaker 2>Okay, I think that's a very reasonable thing that he says,

530
00:28:57.839 --> 00:29:01.279
<v Speaker 2>and I like that he's he's clear that people will adapt.

531
00:29:01.599 --> 00:29:03.640
<v Speaker 2>And this goes back to the Ludites, right, like, you

532
00:29:03.799 --> 00:29:07.160
<v Speaker 2>can't bring in these automatic weaving machines, how are we

533
00:29:07.240 --> 00:29:09.599
<v Speaker 2>gonna make any money as textile workers. This goes back

534
00:29:09.599 --> 00:29:11.880
<v Speaker 2>to the seventeen hundreds, right, This is where the lud

535
00:29:11.920 --> 00:29:15.599
<v Speaker 2>Eites got their name, people who fear technology. And what

536
00:29:15.680 --> 00:29:19.519
<v Speaker 2>did we learn when they brought in the looms. They

537
00:29:19.599 --> 00:29:21.920
<v Speaker 2>were to make a lot more clothes, a lot faster,

538
00:29:22.920 --> 00:29:26.079
<v Speaker 2>and it brought the price down on clothing. You were

539
00:29:26.079 --> 00:29:28.240
<v Speaker 2>able to crank out supply a lot faster, and then

540
00:29:28.359 --> 00:29:31.519
<v Speaker 2>more people could wear your clothes. They and sales went

541
00:29:31.599 --> 00:29:34.680
<v Speaker 2>up and it actually created more jobs. Right now, AI

542
00:29:34.880 --> 00:29:36.640
<v Speaker 2>is doing the same thing. People that are using it

543
00:29:36.720 --> 00:29:41.079
<v Speaker 2>effectively are enhancing their job. They're becoming more efficient, which

544
00:29:41.119 --> 00:29:42.960
<v Speaker 2>a lot of bosses like, oh, look at how much

545
00:29:43.000 --> 00:29:45.359
<v Speaker 2>more work we can put on them, And people are like, Ah,

546
00:29:45.440 --> 00:29:46.960
<v Speaker 2>you can't make me work harder, how dare you? But

547
00:29:47.039 --> 00:29:49.960
<v Speaker 2>it's the same argument that they had in the seventeen hundreds. Oh,

548
00:29:50.039 --> 00:29:52.119
<v Speaker 2>this technology, now you're gonna want me to do more stuff. Yeah,

549
00:29:52.160 --> 00:29:54.920
<v Speaker 2>but it's gonna be easier to do that stuff. You're

550
00:29:54.920 --> 00:29:57.400
<v Speaker 2>working the same number of hours, you're just getting more done, right,

551
00:29:57.680 --> 00:29:59.759
<v Speaker 2>So that's cool. And anytime that we've had an advancement

552
00:29:59.799 --> 00:30:01.160
<v Speaker 2>in to achnology. I used to hear this in the

553
00:30:01.200 --> 00:30:02.880
<v Speaker 2>eighties all the time. Roll You remember that, Kayla, You

554
00:30:02.920 --> 00:30:06.359
<v Speaker 2>don't because you're you were just a You're a twinkle

555
00:30:06.400 --> 00:30:08.880
<v Speaker 2>in your father's eye in the eighties. But Rowl and

556
00:30:08.920 --> 00:30:10.359
<v Speaker 2>I remember this. You remember back in the eighties, it

557
00:30:10.440 --> 00:30:13.559
<v Speaker 2>was like, robots are going to replace us all. It's

558
00:30:13.640 --> 00:30:15.119
<v Speaker 2>really bad. I grew up in Michigan and so it

559
00:30:15.240 --> 00:30:17.319
<v Speaker 2>was all about the robots. We're going to destroy the

560
00:30:17.359 --> 00:30:21.039
<v Speaker 2>auto industry and uh and they were talking about they're

561
00:30:21.039 --> 00:30:22.599
<v Speaker 2>going to replace all these jobs and all these people

562
00:30:22.599 --> 00:30:23.640
<v Speaker 2>are going to be out of work and it's going

563
00:30:23.680 --> 00:30:27.319
<v Speaker 2>to be terrible. And what we found out is you

564
00:30:27.359 --> 00:30:33.960
<v Speaker 2>could crank out cars faster, more consistent quality, and and

565
00:30:34.680 --> 00:30:37.759
<v Speaker 2>the price of vehicles came down, right, That's what we saw.

566
00:30:38.680 --> 00:30:40.599
<v Speaker 2>The other problems with the auto industry in Michigan are

567
00:30:40.839 --> 00:30:44.960
<v Speaker 2>kind of self imposed. But as far as the industrialization

568
00:30:45.039 --> 00:30:48.640
<v Speaker 2>of the robotics, that wasn't it that made things better?

569
00:30:49.680 --> 00:30:51.680
<v Speaker 2>AI is going to make things better, But as as

570
00:30:51.759 --> 00:30:57.559
<v Speaker 2>he points out, it's happening so quickly that there's going

571
00:30:57.599 --> 00:31:00.240
<v Speaker 2>to be an adjustment period, and as company, they are

572
00:31:00.240 --> 00:31:01.920
<v Speaker 2>looking to save money, especially if we're headed towards some

573
00:31:02.000 --> 00:31:04.119
<v Speaker 2>sort of a recession, which you know, people keep talking

574
00:31:04.119 --> 00:31:06.720
<v Speaker 2>about recession here. Recession there hasn't really played out in

575
00:31:06.759 --> 00:31:09.240
<v Speaker 2>the numbers so far, but we'll see how that goes.

576
00:31:09.279 --> 00:31:12.720
<v Speaker 2>As the summer goes on, then company's gonna be looking

577
00:31:12.759 --> 00:31:14.720
<v Speaker 2>to how can we be more efficient? If I can

578
00:31:14.799 --> 00:31:16.799
<v Speaker 2>bring AI in and I can have my one worker

579
00:31:16.920 --> 00:31:18.960
<v Speaker 2>do twice as much work, then I don't need two workers.

580
00:31:19.000 --> 00:31:20.400
<v Speaker 2>So that's when they say we're gonna be able to

581
00:31:20.519 --> 00:31:23.119
<v Speaker 2>lay people off. Right, We're gonna be able to replace people,

582
00:31:23.839 --> 00:31:28.319
<v Speaker 2>and especially in things like entry level, white collar. So

583
00:31:28.799 --> 00:31:30.559
<v Speaker 2>how many pair of egals does a lawyer need if

584
00:31:30.559 --> 00:31:32.960
<v Speaker 2>AI can do some of that? Well, right now, AI

585
00:31:33.079 --> 00:31:37.000
<v Speaker 2>is hallucinating case law, which is one of the reasons

586
00:31:37.039 --> 00:31:38.640
<v Speaker 2>that people are worried about it. In fact, there was

587
00:31:38.680 --> 00:31:42.039
<v Speaker 2>another poll that came out that says the public is

588
00:31:42.160 --> 00:31:46.000
<v Speaker 2>not so cool on how quickly things are moving. Yeah,

589
00:31:46.200 --> 00:31:49.079
<v Speaker 2>it's great for punching up my resume. It's really neat

590
00:31:49.160 --> 00:31:54.519
<v Speaker 2>for making photos, but maybe it's moving a little too fast.

591
00:31:54.839 --> 00:31:57.119
<v Speaker 2>They might have a point, they might just be scared.

592
00:31:57.839 --> 00:32:00.880
<v Speaker 2>We'll do a little analysis on the sociology of it next.

593
00:32:01.000 --> 00:32:03.240
<v Speaker 2>Chris MERYLI Am six forty were live everywhere in the

594
00:32:03.279 --> 00:32:04.079
<v Speaker 2>iHeartRadio App.

595
00:32:04.160 --> 00:32:07.480
<v Speaker 1>You're listening to KFI AM six forty on demand.

596
00:32:08.240 --> 00:32:11.119
<v Speaker 2>Good evening, my friends, Chris Merril, KFI AM six forty

597
00:32:12.920 --> 00:32:18.039
<v Speaker 2>on demand anytime the iHeart Radio App. All right, our questions,

598
00:32:18.039 --> 00:32:19.559
<v Speaker 2>and I where is one place that you would never

599
00:32:19.680 --> 00:32:22.680
<v Speaker 2>go back? I got a story about former inmates at

600
00:32:22.680 --> 00:32:24.720
<v Speaker 2>San Quentin that went back to play an alumni baseball

601
00:32:24.799 --> 00:32:28.279
<v Speaker 2>game with their field of dreams, and I say, you

602
00:32:28.440 --> 00:32:32.200
<v Speaker 2>never get me back there? No way. If I got out,

603
00:32:32.440 --> 00:32:35.079
<v Speaker 2>I'm not going back. I'm not doing a visit. So

604
00:32:35.160 --> 00:32:36.640
<v Speaker 2>where's someplace you would never go back?

605
00:32:36.839 --> 00:32:42.759
<v Speaker 5>Pigeon Forge, Tennessee, the gateway to Dollywood, and a multitude

606
00:32:42.880 --> 00:32:46.400
<v Speaker 5>of other tourist traps. I've never seen traffic so bad

607
00:32:46.880 --> 00:32:50.720
<v Speaker 5>and so many tourists per square foot. It's horrible and

608
00:32:50.880 --> 00:32:53.200
<v Speaker 5>you can't enjoy it. I don't know what people see

609
00:32:53.240 --> 00:32:57.519
<v Speaker 5>in that place, but it's just absolute congestion beyond anything

610
00:32:57.680 --> 00:33:00.880
<v Speaker 5>LA traffic has ever seen. Wow, hundreds of miles of

611
00:33:01.000 --> 00:33:03.799
<v Speaker 5>driving out of the way. It's not worth it, and

612
00:33:03.920 --> 00:33:05.720
<v Speaker 5>I will never return and avoid it at all.

613
00:33:06.039 --> 00:33:08.200
<v Speaker 2>All right, you guys ever been to Pigeon Forge?

614
00:33:10.000 --> 00:33:10.039
<v Speaker 6>No?

615
00:33:10.319 --> 00:33:11.079
<v Speaker 2>Okay, good talk?

616
00:33:11.440 --> 00:33:11.720
<v Speaker 4>Nope?

617
00:33:12.160 --> 00:33:15.200
<v Speaker 2>No, yeah, all right, so now, uh not a glowing review.

618
00:33:15.440 --> 00:33:18.319
<v Speaker 2>I guess we don't go to Pigeon Forge ever. After

619
00:33:18.440 --> 00:33:21.000
<v Speaker 2>twenty nine years of living in California and Huntington Beach,

620
00:33:21.079 --> 00:33:25.000
<v Speaker 2>I said, I never moved back to Nashville, Tennessee, where

621
00:33:25.000 --> 00:33:28.039
<v Speaker 2>I grew up. Wow, a couple of people for Tennessee today.

622
00:33:28.839 --> 00:33:32.279
<v Speaker 2>A lot of people don't like Tennessee. Right, Well, guess

623
00:33:32.400 --> 00:33:35.400
<v Speaker 2>where I I am. Oh, thank you newsso oh you

624
00:33:35.519 --> 00:33:38.200
<v Speaker 2>made me break a promise. Oh, Gavin Newsom made you big.

625
00:33:39.440 --> 00:33:43.119
<v Speaker 2>Jerry Brown didn't make you break that promise. It took

626
00:33:43.200 --> 00:33:49.160
<v Speaker 2>to Newsom to do it. Okay, Larry, all right, what else?

627
00:33:49.240 --> 00:33:49.960
<v Speaker 6>Good evening.

628
00:33:50.359 --> 00:33:53.480
<v Speaker 2>I would never go back to Catalina Island. That was

629
00:33:53.519 --> 00:33:57.480
<v Speaker 2>the most boringest place I've ever went to. Oh, I

630
00:33:57.599 --> 00:33:59.839
<v Speaker 2>have no desire to ever go back. Wow.

631
00:34:00.119 --> 00:34:00.839
<v Speaker 3>Thank you guys.

632
00:34:00.960 --> 00:34:03.400
<v Speaker 2>Have a great eating. Thanks you too. She's not going

633
00:34:03.440 --> 00:34:05.200
<v Speaker 2>back to Kettlin, not while she wasn't there during the

634
00:34:05.240 --> 00:34:07.519
<v Speaker 2>wine mixer. That's the big one.

635
00:34:08.840 --> 00:34:11.480
<v Speaker 10>All right, Hey, Chris, Hey, I thought it was kind

636
00:34:11.480 --> 00:34:16.119
<v Speaker 10>of weird. I totally agree with everything you're saying today.

637
00:34:17.000 --> 00:34:17.559
<v Speaker 2>That is weird.

638
00:34:17.639 --> 00:34:20.679
<v Speaker 10>I guess the show is still got a lot left,

639
00:34:21.119 --> 00:34:26.320
<v Speaker 10>so we'll see what happens. And look out, Angel Martinez.

640
00:34:26.559 --> 00:34:29.559
<v Speaker 10>Here comes Lucy Heal, Hi Kayla.

641
00:34:30.320 --> 00:34:31.559
<v Speaker 2>Okay, that got creepy fast.

642
00:34:31.840 --> 00:34:36.199
<v Speaker 6>Hi Steve, he loves Hi Kayla. Hey Steve, Hi Kayla, Steve.

643
00:34:39.800 --> 00:34:41.119
<v Speaker 2>You had a little thing with him. You have a

644
00:34:41.119 --> 00:34:44.519
<v Speaker 2>little something going on there, Hi Kayla, Hi Steve. At

645
00:34:44.519 --> 00:34:46.440
<v Speaker 2>the end of the talk backs, he always gives me

646
00:34:46.519 --> 00:34:47.280
<v Speaker 2>a personal message.

647
00:34:47.800 --> 00:34:48.000
<v Speaker 6>Yeah.

648
00:34:48.000 --> 00:34:48.960
<v Speaker 2>Always, always, He's great.

649
00:34:48.960 --> 00:34:49.400
<v Speaker 6>He's a good guy.

650
00:34:49.719 --> 00:34:52.000
<v Speaker 2>Okay, all right. It sounded a little creeper to me,

651
00:34:52.079 --> 00:34:53.119
<v Speaker 2>But if you're cool with it.

652
00:34:53.159 --> 00:34:56.320
<v Speaker 10>Then Hi Kayla, Kayla.

653
00:34:58.719 --> 00:35:03.559
<v Speaker 6>Oh Jesus game that was bring me. That's I'm gonna

654
00:35:03.559 --> 00:35:04.119
<v Speaker 6>have nightmares.

655
00:35:04.119 --> 00:35:08.079
<v Speaker 2>Thank you. Yeah, I don't lan, Hey, it's kind of weird.

656
00:35:08.119 --> 00:35:10.840
<v Speaker 2>I agree with everything you said tonight, So Hi Kla,

657
00:35:11.039 --> 00:35:16.280
<v Speaker 2>thank you. I was talking about the AI here. More

658
00:35:16.320 --> 00:35:18.880
<v Speaker 2>than three quarters of Americans now want companies to create

659
00:35:19.000 --> 00:35:23.800
<v Speaker 2>AI slowly. They say, slow it down. Here to tell

660
00:35:23.880 --> 00:35:28.119
<v Speaker 2>us more about it is the story read by AI outstanding.

661
00:35:27.719 --> 00:35:30.880
<v Speaker 8>Most Americans want AI progress to slow down.

662
00:35:31.320 --> 00:35:36.239
<v Speaker 2>Now that sounds natural, doesn't it. All right, but then

663
00:35:36.239 --> 00:35:38.400
<v Speaker 2>there's kind of a giveaway when it comes to AI,

664
00:35:38.679 --> 00:35:40.840
<v Speaker 2>which is why I think that we are still it's

665
00:35:40.920 --> 00:35:43.159
<v Speaker 2>still not quite ready for prime time. All right, here's

666
00:35:43.159 --> 00:35:45.760
<v Speaker 2>what he said. Let's try this from the beginning.

667
00:35:45.519 --> 00:35:46.039
<v Speaker 1>From the top.

668
00:35:46.320 --> 00:35:50.960
<v Speaker 8>Most Americans want AI progress to slow down, poll finds.

669
00:35:52.559 --> 00:35:55.880
<v Speaker 2>Poll finds. Okay, all right, so we're reading.

670
00:35:55.639 --> 00:35:59.960
<v Speaker 8>This as tech giants race to develop AI. Seventy seven

671
00:36:00.199 --> 00:36:03.800
<v Speaker 8>percent of Americans say they prefer companies take their time

672
00:36:04.079 --> 00:36:08.039
<v Speaker 8>and get it right, even if it delays breakthroughs. According

673
00:36:08.079 --> 00:36:11.480
<v Speaker 8>to the twenty twenty five Axios Harris Poll one hundred,

674
00:36:12.360 --> 00:36:16.360
<v Speaker 8>only twenty three percent support rapid development at the risk

675
00:36:16.440 --> 00:36:21.519
<v Speaker 8>of mistakes. The causes sentiment spans generations from ninety one

676
00:36:21.639 --> 00:36:25.239
<v Speaker 8>percent of boomers to seventy four percent of gen Z.

677
00:36:25.760 --> 00:36:29.719
<v Speaker 2>Wow, even gen Z three quarters say let's let's pump

678
00:36:29.760 --> 00:36:33.239
<v Speaker 2>the brakes. But the concern is that China is going

679
00:36:33.280 --> 00:36:35.599
<v Speaker 2>to get ahead of us. Don't worry is if we're

680
00:36:35.639 --> 00:36:37.800
<v Speaker 2>not ahead of AI, China will get ahead of AI.

681
00:36:38.559 --> 00:36:52.639
<v Speaker 2>And then I then I mean, I mean, then they

682
00:36:52.719 --> 00:36:55.960
<v Speaker 2>would they would, they would, they would be able to

683
00:36:56.000 --> 00:37:02.960
<v Speaker 2>replace their workers first, So I mean you got to win.

684
00:37:04.119 --> 00:37:08.000
<v Speaker 8>Despite pressure from CEOs and investors to lead in a

685
00:37:08.079 --> 00:37:11.440
<v Speaker 8>global AI race, the public remains skeptical.

686
00:37:11.800 --> 00:37:12.039
<v Speaker 2>Yeah.

687
00:37:12.199 --> 00:37:17.800
<v Speaker 8>Many fear job loss, misinformation, and irreversible early design flaws.

688
00:37:18.519 --> 00:37:22.679
<v Speaker 8>The poll suggests Americans have learned from past tech missteps

689
00:37:23.000 --> 00:37:26.119
<v Speaker 8>and want slower, more responsible innovation.

690
00:37:26.599 --> 00:37:30.119
<v Speaker 2>Yeah, and we're also at an exciting period with AI.

691
00:37:30.679 --> 00:37:32.599
<v Speaker 2>Part of the reason that we were that were moving

692
00:37:32.639 --> 00:37:35.199
<v Speaker 2>so quickly is that it's exciting, it's new. We want

693
00:37:35.239 --> 00:37:38.519
<v Speaker 2>to see just how far this can take us, right,

694
00:37:38.719 --> 00:37:42.320
<v Speaker 2>just how how much can we do with AI? It's

695
00:37:42.400 --> 00:37:45.719
<v Speaker 2>kind of exciting for for the kids these days, Like

696
00:37:45.840 --> 00:37:51.840
<v Speaker 2>Kayla Kila. You probably don't remember not having the internet,

697
00:37:52.199 --> 00:37:52.440
<v Speaker 2>do you?

698
00:37:52.920 --> 00:37:54.000
<v Speaker 5>I do you do?

699
00:37:54.400 --> 00:37:54.559
<v Speaker 6>Oh?

700
00:37:54.639 --> 00:37:58.440
<v Speaker 2>Okay, all right, all right, that's fun. Yeah. So then

701
00:37:58.480 --> 00:38:01.000
<v Speaker 2>you also then remember like the days where the web

702
00:38:01.079 --> 00:38:05.360
<v Speaker 2>pages were really rudimentary compared to what we have today, right,

703
00:38:05.440 --> 00:38:08.880
<v Speaker 2>where it was angel fire and what was the other one?

704
00:38:09.039 --> 00:38:12.480
<v Speaker 2>Angel Fire was one of them. There was what was

705
00:38:12.519 --> 00:38:15.400
<v Speaker 2>the other man?

706
00:38:15.800 --> 00:38:16.159
<v Speaker 8>What was it?

707
00:38:17.360 --> 00:38:20.360
<v Speaker 2>Well, Earthlink was a provider, right, I'm just thinking of

708
00:38:20.400 --> 00:38:24.639
<v Speaker 2>the web page designers like geo, geolinks or something an

709
00:38:24.679 --> 00:38:27.000
<v Speaker 2>angel Fire and you could make your own website, right.

710
00:38:27.639 --> 00:38:29.960
<v Speaker 2>My Space made it easy for anybody to make their

711
00:38:29.960 --> 00:38:33.280
<v Speaker 2>own website. And that was you know, that was fifteen

712
00:38:33.360 --> 00:38:35.039
<v Speaker 2>years after we were all sort of getting out of

713
00:38:35.079 --> 00:38:37.079
<v Speaker 2>the Internet in the first place. And if you look

714
00:38:37.119 --> 00:38:41.519
<v Speaker 2>back at MySpace from from the mid to late two thousands,

715
00:38:41.559 --> 00:38:44.760
<v Speaker 2>you see just how rudimentary that looked. So I think

716
00:38:44.800 --> 00:38:47.079
<v Speaker 2>we're at this really exciting time like we were in

717
00:38:47.159 --> 00:38:50.440
<v Speaker 2>the nineties with the explosion of the Internet. We just

718
00:38:50.480 --> 00:38:52.000
<v Speaker 2>want to see how much we can get out of it,

719
00:38:54.440 --> 00:38:57.400
<v Speaker 2>and we're all worried about what if China gets it? Okay,

720
00:38:59.039 --> 00:39:06.360
<v Speaker 2>guess hello, Hello, is there anyone there? Hello? Oh, that's freedom.

721
00:39:06.880 --> 00:39:13.599
<v Speaker 2>That's the sound of freedom. Oh nobody and then right,

722
00:39:13.960 --> 00:39:16.280
<v Speaker 2>nobody complain when we got rid of that noise, no

723
00:39:16.599 --> 00:39:19.440
<v Speaker 2>at all. And then once uh, you be, you'd be

724
00:39:19.559 --> 00:39:21.599
<v Speaker 2>on the internet, you'd be in your chat room with

725
00:39:21.719 --> 00:39:25.400
<v Speaker 2>your AOL, right, and then Mom would pick up the phone.

726
00:39:25.519 --> 00:39:28.880
<v Speaker 6>Mom, I was using that.

727
00:39:31.000 --> 00:39:34.800
<v Speaker 2>It was the worst. Facts would come in. It's terrible.

728
00:39:35.480 --> 00:39:38.440
<v Speaker 2>So why are we so afraid of AI Because ultimately,

729
00:39:38.559 --> 00:39:41.280
<v Speaker 2>when we say slow down, it's because we're worried about something.

730
00:39:41.400 --> 00:39:41.480
<v Speaker 8>Right.

731
00:39:41.519 --> 00:39:43.440
<v Speaker 2>One of the things that motivate us fear and greed.

732
00:39:43.920 --> 00:39:46.039
<v Speaker 2>And so you've got some people that say, boy, I

733
00:39:46.119 --> 00:39:47.880
<v Speaker 2>want to see how far this can go. I want

734
00:39:47.920 --> 00:39:49.400
<v Speaker 2>to see what AI can do. I just want to

735
00:39:49.440 --> 00:39:52.199
<v Speaker 2>see how prosperous we can be with AI. Right, that's

736
00:39:52.239 --> 00:39:56.000
<v Speaker 2>the greed. But what what what we What causes us

737
00:39:56.039 --> 00:39:58.880
<v Speaker 2>to say, slow it down, let's exercise some caution. Is

738
00:39:58.960 --> 00:40:01.440
<v Speaker 2>the fear side of us? And that's that's a that's

739
00:40:01.480 --> 00:40:05.239
<v Speaker 2>a basic emotion. That is a survival mechanism, the fear,

740
00:40:05.679 --> 00:40:07.960
<v Speaker 2>all right, And we have a lack of understanding when

741
00:40:08.000 --> 00:40:10.760
<v Speaker 2>it comes to AI. We don't know what it's capable of,

742
00:40:10.920 --> 00:40:13.360
<v Speaker 2>good or bad, and the unknown is scary. And most

743
00:40:13.400 --> 00:40:16.039
<v Speaker 2>of us don't understand AI. We don't understand the limitations,

744
00:40:16.039 --> 00:40:18.320
<v Speaker 2>we don't understand the abilities, we don't even understand.

745
00:40:17.920 --> 00:40:18.639
<v Speaker 8>How it works.

746
00:40:19.360 --> 00:40:21.119
<v Speaker 2>And I was reading some more on that today too,

747
00:40:21.239 --> 00:40:24.719
<v Speaker 2>and a lot of it is basically just predictive. Right

748
00:40:25.079 --> 00:40:26.519
<v Speaker 2>in the same way that you might be using a

749
00:40:26.719 --> 00:40:28.239
<v Speaker 2>you might be sending a text it, or you might

750
00:40:28.239 --> 00:40:30.400
<v Speaker 2>be writing an email, and all of a sudden, your

751
00:40:30.920 --> 00:40:33.280
<v Speaker 2>your your Outlook or your Gmail starts to try to

752
00:40:33.320 --> 00:40:36.280
<v Speaker 2>predict what the next word would be. Right, That's kind

753
00:40:36.360 --> 00:40:38.360
<v Speaker 2>of how AI works, but just on a grant, like

754
00:40:38.440 --> 00:40:41.000
<v Speaker 2>what's the most likely answer based on what the next

755
00:40:41.039 --> 00:40:42.599
<v Speaker 2>word would be? And if this is the most likely

756
00:40:42.639 --> 00:40:44.880
<v Speaker 2>next word, what would the next most likely word be?

757
00:40:44.960 --> 00:40:46.320
<v Speaker 2>And that kind of thing, And that's kind of how

758
00:40:46.360 --> 00:40:52.199
<v Speaker 2>AI builds it's it's responses. But we have a lack

759
00:40:52.239 --> 00:40:56.519
<v Speaker 2>of understanding, and that leads us to worry about worst

760
00:40:56.599 --> 00:41:00.360
<v Speaker 2>case scenarios. I mean, it's the same reason that we

761
00:41:00.480 --> 00:41:05.440
<v Speaker 2>don't know. You know, before we had telescopes, we didn't

762
00:41:05.519 --> 00:41:10.119
<v Speaker 2>know what was in the stars, and then we were

763
00:41:10.199 --> 00:41:13.480
<v Speaker 2>worried about what could come and destroy us. We don't

764
00:41:13.639 --> 00:41:16.280
<v Speaker 2>know what is in outer space. We don't know if

765
00:41:16.320 --> 00:41:19.159
<v Speaker 2>there are other life forms, which makes for great Hollywood

766
00:41:19.239 --> 00:41:21.840
<v Speaker 2>movies where you've got the war of the World or

767
00:41:21.920 --> 00:41:25.400
<v Speaker 2>some sort of an alien invasion Independence Day. We worry

768
00:41:25.519 --> 00:41:32.599
<v Speaker 2>because we don't know, and the fear comes from that

769
00:41:32.800 --> 00:41:37.119
<v Speaker 2>blindness that we have. And then we get bad news headlines, right,

770
00:41:37.199 --> 00:41:40.440
<v Speaker 2>we get the headlines about the hallucinations of AI. We

771
00:41:40.519 --> 00:41:43.000
<v Speaker 2>get the headlines about kids using AI to cheat all

772
00:41:43.079 --> 00:41:46.880
<v Speaker 2>over the place. We get warnings from insiders like the

773
00:41:47.000 --> 00:41:50.880
<v Speaker 2>gentleman from Anthropic who says this is going to create

774
00:41:50.880 --> 00:41:53.880
<v Speaker 2>a bunch of layoffs. We're going to see hig unemployment, right,

775
00:41:54.880 --> 00:41:58.119
<v Speaker 2>and we also, let's be honest, we've had bad experiences

776
00:41:58.199 --> 00:42:00.559
<v Speaker 2>with some previous tech. It's like all this am mail

777
00:42:00.599 --> 00:42:02.639
<v Speaker 2>that you've been getting, and I've just been getting some more.

778
00:42:02.679 --> 00:42:04.480
<v Speaker 2>In fact, here I've got a new one how to

779
00:42:04.559 --> 00:42:07.920
<v Speaker 2>spot phishing emails. Now that EI is cleaned, AI excuse me,

780
00:42:07.960 --> 00:42:11.360
<v Speaker 2>has cleaned up the typos, which means AI will be

781
00:42:11.519 --> 00:42:14.679
<v Speaker 2>used by bad actors. And nowadays it doesn't feel like

782
00:42:14.679 --> 00:42:16.719
<v Speaker 2>everybody's trying to take advantage of you, right, They're all

783
00:42:16.719 --> 00:42:19.800
<v Speaker 2>trying to steal your information or your money. We're getting

784
00:42:19.840 --> 00:42:24.440
<v Speaker 2>incessant spam and fraudulent emails, and we see how that

785
00:42:24.599 --> 00:42:28.280
<v Speaker 2>tech is being used for evil, and AI will make

786
00:42:28.360 --> 00:42:31.639
<v Speaker 2>that worse. Bad actors will use AI to try to

787
00:42:31.639 --> 00:42:34.679
<v Speaker 2>take advantage of you, but AI may also help you

788
00:42:34.760 --> 00:42:39.119
<v Speaker 2>identify those threats more quickly. We don't really consider those advantages.

789
00:42:39.199 --> 00:42:43.679
<v Speaker 2>We worry about the dangers. That is normal survival mechanism.

790
00:42:44.599 --> 00:42:46.280
<v Speaker 2>All right, Enough of me sounded like an old man.

791
00:42:48.159 --> 00:42:49.960
<v Speaker 2>Not really, I can't get away from it, but I

792
00:42:49.960 --> 00:42:52.400
<v Speaker 2>will stop talking about old man topics. Like there the

793
00:42:52.480 --> 00:42:55.320
<v Speaker 2>kids these days, and they're fancy electronics you're going to

794
00:42:55.400 --> 00:43:01.760
<v Speaker 2>ruin everything. There's no business like shel business. Every Sunday,

795
00:43:01.880 --> 00:43:04.639
<v Speaker 2>six o'clock at his next Chris Merril KFI AM six

796
00:43:04.679 --> 00:43:06.239
<v Speaker 2>forty were live everywhere the iHeartRadio

797
00:43:06.280 --> 00:43:09.199
<v Speaker 1>App, KFI AM six forty on demand